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Fishing impacts on marine ecosystems off Brazil : with emphasis on the northeastern region Freire, Kátia de Meirelles Felizola 2005

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FISHING IMPACTS ON MARINE ECOSYSTEMS OFF BRAZIL, WITH EMPHASIS ON THE NORTHEASTERN REGION by KATIA DE MEIRELLES FELIZOLA FREIRE B. Sc., University of Rio Grande, 1990 M . Sc., University of Rio Grande, 1995  A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Resource Management and Environmental Studies)  THE UNIVERSITY OF BRITISH COLUMBIA September 2005 © Katia de Meirelles Felizola Freire, 2005  Abstract  This study is the first contribution towards the development of ecosystem-based fisheries management in northeastern Brazil, through the exploration of fishing policies based on a trophic model. The following objectives were addressed: 1) analysis of the richness of common names of Brazilian fishes; 2) reconstruction of time series of marine catches; 3) modelling of trophic interactions off northeastern Brazil; and 4) assessment of fishing policies. The analysis of common names indicated a high richness of names per species (average = 6) and the use of the same common name for different species, with a negative impact on the accuracy of catch statistics. The reconstruction of catch time series was based on landings from national yearbooks, and from ICCAT and FAO's databases (1978-2000), allowing for the detection of 'fishing down the food web' in northeastern Brazil. The trophic model estimated a total biomass for this ecosystem of 222 tonnes-km" (excluding detritus), and indicated a low 2  degree of omnivory and the high importance of detritus. Simulations for 2001-2028 indicated that current fishing effort is unsustainable for lobsters and swordfish; however, the model inadequately described the dynamics of swordfish, tunas, and other large pelagics, which have large distribution areas. The simulation of optimum fishing policies led to a diverse fleet when ecosystem health was emphasized. If the main objective was economic or social (or a combination of both and ecosystem health), manual collection of coastal resources, and demersal industrial fisheries could be boosted, while the lobster and longline fisheries should be phased out. A 50% reduction in effort for lobster fisheries would not produce significant changes in lobster biomass; a reduction in effort to the 1978 level (JMSY) would lead to biomass recovery. The instability of institutions responsible for fisheries management in Brazil  has had a deleterious impact on the resources. This negative impact is expected to increase due to the current split of responsibility between two institutions with diverse agendas. An improvement in the collection system of catch statistics is recommended, which would consider a standardized set of common names, as well as gathering information on biological, economic, and social components of this ecosystem and its fisheries.  Table of Contents  Abstract  ii  Table of Contents  iv  List of tables  vii  List of figures  viii  List of appendices  x  Acknowledgements  xi  CHAPTER 1. General introduction  1  1.1. Historical perspective of the worldfisheries  2  1.2. A frameworkfor fisheries management  5  1.3. History offisheriesmanagement in Brazil  11  1.4. Issues on fisheries management in Brazil 1.5. Objectives 1.6. Description of the study area  16 18 19  1.7. Overview of the main marine resources exploited off northeastern Brazil  21  a) Lobsters  23  b) Shrimps  24  c) Tuna and tuna-like fishes  26  d) Southern red snapper  28  e) Crabs  29  f) Turtles  30  g) Whales  31  Summary of the exploitation status of the main resources  31  1.8. Thesis outline 1.9. Bibliography  32 32  CHAPTER 2. Richness of common names of Brazilian marine fishes and its effect on catch statistics 41 2.1. Introduction.  41  2.2. Material and methods  42  2.3. Results  44  a) Richness of common names  44  b) Effect of common names' richness on catch statistics  48  c) The case for standardization of common names  54 iv  2.4. Discussion  58  2.5. Bibliography  62  CHAPTER 3. Analysis of catch datafrommarine fisheries off Brazil  67  3.1. Introduction  67  3.2. Material and methods  71  3.3. Results and discussion  74  a) Commercial fisheries  74  b) Recreational fisheries  90  c) Subsistence fisheries  91  d) Research fisheries  92  e) Ornamental fisheries  93  f) Discards  94  g) Distant water fleets  96  3.4. Conclusions  98  3.5. Bibliography  99  CHAPTER 4. Description of the marine ecosystem off northeastern Brazil using a trophic model 4.1. Introduction  109 109  4.2. Methods  HI  4.2.1. ECOPATH model  111  4.2.2. Habitat area  112  4.2.3. Functional groups  113  4.2.4. Basic input  114  4.2.5. Diet composition  119  4.2.6. Landing data  119  4.2.7. Balancing the model  121  4.2.8. Time-dynamic simulation using Ecosim  123  4.3. Results  127  :  4.4. Discussion  140  4.5. Bibliography  148  CHAPTER 5. Assessing fishing policies for northeastern Brazil  175  5.1. Introduction  175  5.2. Material and Methods  179  5.2.1. Fleet definition and landing data  181  5.2.2. Ex-vessel prices of 'fish' products  181  5.2.3. Fishing costs and profits  181  5.2.4. Optimum fishing policy search  184  5.2.5. Lobster fishery and future fishing policies  187  5.3. Results  J 88  5.4. Discussion  195  5.5. References  204  CHAPTER 6. Concluding remarks  211  List of tables  Table 1.1: Some international or regional fisheries-related agreements  17  Table 1.2: Status of the main fisheries off northeastern Brazil  25  Table 2.1: Common names related to the highest number of species  45  Table 2.2: Common names associated with the ten highest mean annual catches  50  Table 2.3: List of species presenting one unique common name  56  Table 3.1: Structure of the ACCESS database of landing statistics  71  Table 3.2: Sources used to compile landing statistics  71  Table 4.1: Basic input for the 1970s Ecopath with Ecosim model  130  Table 4.2: Diet matrix for the 1970s Ecopath with Ecosim model  131  Table 4.3: System statistics obtained from Ecopath with Ecosim  138  Table 4.4: Relative flows by discrete trophic level  139  Table 5.1: Groups used in the simulations of fishing policies  180  Table 5.2: Price per kilogram of each group  182  Table 5.3: Cost of each fishing fleet  184  Table 5.4: Estimated number of jobs provided by each fishery type  186  Table 5.5: Changes in biomass and catch for spiny lobsters  195  List of figures  Figure 1.1: Framework for fisheries management  7  Figure 1.2: Location of the East Brazil Large Marine Ecosystem  19  Figure 1.3: Framework to the development of the analysis of the impact of fisheries  20  Figure 1.4: Five political regions of Brazil and nine States of the northeastern region  22  Figure 2.1: Flowchart used to split catch amongst all commercial species  46  Figure 2.2: Richness of names of Brazilian marine fishes  47  Figure 2.3: Relationship between no. of names, commercial importance, and habitat  48  Figure 2.4: Mean annual catch of 'bagre' split amongst all species  51  Figure 2.5: Annual catch of 'sardinha verdadeira' split amongst all species  52  Figure 2.6: Link between common and scientific names for 'linguado'  53  Figure 2.7: Catch data split amongst species for 'linguado'  55  Figure 3.1: Decision diagram on the correspondence of common and scientific names  73  Figure 3.2: Landing data for Brazilian marine fisheries  75  Figure 3.3: Comparison amongst landings recorded in ICC AT databases  78  Figure 3.4: Landings of tunas, bonitos and mackerels, swordfish, billfishes, and sharks  79  Figure 3.5: Main species caught by Brazilian marine commercial fisheries  80  Figure 3.6: Groups represented in landings from Brazilian marine commercial fisheries  81  Figure 3.7: States with the highest landings in Brazil  81  Figure 3.8: Landings of the industrial and artisanal marine fisheries  82  Figure 3.9: Landings of the main groups from fisheries in northeastern Brazil  83  Figure 3.10: Mean trophic level of landings for Brazil and northeastern Brazil  85  Figure 3.11: Schematic drawing indicating the overlapping of resources  85  Figure 3.12: Changes in mean trophic level for landings from northeastern Brazil  86  Figure 3.13: Fishing-in-balance index for northeastern Brazil  87  Figure 3.14: Landings originating with fisheries off Ceara and Rio Grande do Norte  89  Figure 3.15: Proportion of other fishes in relation to total landings  90  Figure 4.1: Mixed trophic impact in northeastern Brazil marine ecosystem  133  Figure 4.2: Verification of the model: spiny lobsters and southern red snapper  134  Figure 4.3: Verification of the model: tuna and tuna-like fishes  135  Figure 4.4: Changes in biomass in relation to the Ecopath level  136  Figure 4.5: Variation of the system statistics for East Brazil  136  Figure 5.1: Biomass changes in relation to the original biomass under status quo  188  Figure 5.2: Relative changes in fishing effort for each fleet in four scenarios  190  Figure 5.3: Mean relative change in biomass in four scenarios  191  Figure 5.4: Relative changes in fishing effort under the mandated rebuilding scenario  192  Figure 5.5: Mean relative change in biomass under the mandated rebuilding scenario  193  Figure 5.6: Changes is biomass of spiny lobsters in relation to the 1978 baseline  194  List of appendices  Appendix 1: Glossary of terms used throughout this thesis  221  Appendix 2: List of species included in each functional group  222  Appendix 3: Input parameters for functional groups included in the Ecopath model  232  Appendix 4: Sources used to estimate the diet composition for all species  245  Acknowledgements  I would like to say thank you to all of those who contributed in some way to this final product: General: -  >-  -  My supervisor Daniel Pauly for his supervision during all my years at UBC and for showing me what being a real scientist means; My supervisory committee Les Lavkulich, Villy Christensen, and Art Tautz for all suggestions and comments made to improve this work; All the staff at the Fisheries Centre and the Institute of Resources, Environment and Sustainability for logistic help; Patricia Keen for enthusiastically reviewing this thesis and Steve Martell for reviewing part of the thesis and discussing about the Ecopath model; Ierece Rosa for bringing (or trying to bring) me back to Earth, and for reviewing some chapters of an earlier version of this thesis; Silvio Jablonski and Ana Paula Prates for discussions about fishery politics in Brazil; All local friends who made this task possible through all kinds of support: Joao & Rosangela, Luis & Susana, Renata & Ricardo, Paula & Jose, Marcelo & Daniela, Mario & Faride, Daniela & Ian, Annemarie & Patrick, Patricia, Eny, Elizabeth, Yvette, Lucy, Telmo, Vaso, Brajgeet, and Fabio; All virtual friends: Bery, Silvia Lucato, Ana Carla, Silvia Salas; My parents and other members of my family for all kinds of support; CNPq (National Council for the Scientific and Technological Development) and The Sea Around Us Project for financial support.  Chapter 2: -  Marcelo Vasconcellos and Daniela Kalikoski who initiated, with Deng Palomares, the introduction of Brazilian common names into FishBase; Juarez Rodrigues for helping to encode part of the data used in this chapter; Alfredo Carvalho Filho and A. Costa e Silva for literature; Arthur Tautz for suggesting the analysis of the impact of common names diversity on catch statistics; Aque Atanacio for re-drawing the flowcharts; Carla Vivacqua for giving me some insights on the statistical analyses.  Chapter 3: -  Samuel Bezerra, Geraldo Clelio dos Santos, Iranilde Lima, Sonia Dantas, Adi Maranhao (all from IBAMA-Brasilia), Fabio Hazin, and Paulo Travassos for helping me to obtain data on Brazilian commercial fisheries; Silvia Lucato, Geovanio Oliveira, Carlos Palma, and Luca Garibaldi for clarifying doubts about the national, ICCAT, and FAO databases;  Dirk Zeller for commenting on an earlier version of manuscript that resulted from this chapter; The Sea Around Us Project for providing financial assistance to cover part of the fieldwork costs; Juarez Rodrigues for helping to encode data; Jorge Pablo Castello, Agnaldo Silva Martins, Antonio Olinto, and Everaldo Queiroz for helping to establish the connection between common and scientific names of some Brazilian fishes. Chapters 4 and 5: To Villy Christensen and Daniel Pauly for continuous support during the development of the Ecopath with Ecosim model; Reg Watson and Adrian Kitchingman for helping to calculate areas and other GIS issues; Fred Valdez for helping with the extraction of catch data from the Sea Around Us database; Elizabeth Mohammed, Yvette Rizzo, Eny Buchary, William Cheung, Robert Ahrens, and Steve Martell for discussions about the construction of the model; Victoria Isaac, Kika, Analbery Monteiro, Silvia Lucato, and Gonzalo Velasco for helping with bibliographic support; Silvio Jablonski for allowing the use of length data from the REVIZEE Program/NE Score to estimate mortality rates and make available any required data; Silvia Lucato, Roberto Carvalho, and Rene Scharer for helping with the collection of cost data; Rene Scharer also helped me to keep updated in relation to lobster issues; Dr. Ralf Schwamborn, Dr. Fernando Feitosa, and Dr. Jose Zanon Passavante for providing zoo and phytoplankton data; Rashid Sumaila for providing support onfisherieseconomics; Fabio Freire for helping with MATLAB programming to calculate some of the growth and mortality parameters used in this chapter; All authors who kindly sent me copies of their papers, but whom I cannot name here because of space constraints.  To my husband and my son.  CHAPTER 1. General introduction  Globally, the fishing sector is in crisis as most stocks are fully exploited, overfished or recuperating, with indications that present catches are not sustainable (Watson and Pauly, 2001). The crisis is particularly significant for large predators (Baum et al, 2003; Myers and Worm, 2003). Since 1884, when T. Huxley suggested the inexhaustibility offish marine stocks (Hall, 1999), scientific inquiries have changed from debating the existence of an exploitation limit to defining what the limits are.  Recently, research has centered on the following major issues: uncertainty when defining exploitation limits (Francis and Shotton, 1997); reducing fishing costs and increasing the market value of fishing products (Hilborn et al, 2003); quantifying the relative importance of environmental and/or fishing effects on the collapse of stocks (Steele, 1996); understanding recruitment overfishing (Myers et al, 1999); explicit inclusion of socio-economic vectors (Hall, 1999; Jennings et al, 2001); recognizing the increasing importance of recreational fisheries, whose harvest, in some cases, may exceed that from commercial fisheries (Gentner and Lowther, 2002); considering the need for ecosystem-based approaches (NRC, 1999; Gislason et al, 2000; Murawski, 2000; Pauly and Christensen, 2002); and food security (Choo and Williams, 2003).  1.1. Historical perspective of the world fisheries  The Food and Agriculture Organization of the United Nations (FAO) has been compiling global catch data since 1950. World total catch increased 6% per year from 1950 to 1970, and 2% per year from 1970 to 1990 (FAO, 2000). No increase was observed after 1990 and an annual catch figure of slightly over 85 million tonnes was registered in 2002 for marine waters (www.fao.org; FISHSTAT). This figure would be much higher if discards were considered, estimated at 27 million tonnes per year in 1980-1992 (Alverson et ai, 1994) and 7.3 million in 1992-2003 (Kelleher, 2004), together with illegal, unreported, and unregulated (IUU) catches. Fish landings have likely been declining since 1988, a trend disguised by over-reporting of Chinese catches (Watson and Pauly, 2001). Thus, there is enough evidence to proceed with a "regime shift in fisheries management" (borrowing the terminology from Steele, 1996).  One of the primary reasons for this condition is the race for fish caused by open access to fishing resources. As early as 1968, G. Hardin pointed out the consequences of open access systems, and made suggestions about how to avert the resulting impact by the race for the resource (Hardin, 1968). Factors contributing to the crisis of fisheries include human population growth, increasing consumption rates, stronger disparities in access to resources, prevalence of individualism, materialism and competition, higher speed in the development and adoption of new technologies, and broader and more unpredictable impacts of those technologies (Burger et al., 2001). The need for 'responsible fisheries' is evident. Sissenwine and Mace (2003) attempt to clarify this concept. For them, responsible fisheries have to be sustainable, provide fairly distributed benefits, and not produce unacceptable or irreversible changes to the ecosystem. For a  movement towards responsibility, two key changes must occur. First, the burden of proof should shift such that one must prove that a new fishing activity is not going to cause unacceptable impacts to the ecosystem, rather than the converse, wherein one fishery is, by default, assumed to have no impact (Sissenwine and Mace, 2003). Second, fisheries should be recognized as being embedded in ecosystems and thus their impacts on ecosystems must always be evaluated (Link, 2002). Although there is some conceptual acceptance that ecosystem approaches should be implemented, practical examples are rare. In 1995, FAO presented the Code of Conduct for Responsible Fisheries for effective conservation and management of living aquatic resources, a global and voluntary code to be applied in accordance to the United Nations Convention on the Law of the Sea - UNCLOS (FAO, 1995). This code deals with issues related to the "capture, processing and trade of fish and fishery products, fishing operations, aquaculture, fisheries research, and the integration of fisheries into coastal area management" (FAO, 1995). An important contribution of UNCLOS, in force since 1994, is the concept of Economic Exclusive Zone (EEZ), which establishes that coastal States have the right to exploit, manage, and preserve resources within a limit of two hundred nautical miles from their coastline. This was one step towards the zoning of the oceans and the control of the race for fish, but it has not been sufficient to prevent fishery collapses. The extension of the jurisdiction over marine waters in 1977 was seen as a solution to the fishery crisis of Northern cod off eastern Canada, for example, but this was not sufficient to avoid the fishery collapse of 1992 (Walters and Maguire, 1996). Instead, extension of jurisdiction must be used together with input controls, output controls, and/or technical measures embedded in a sound fishery management policy, with clear objectives, in order to be effective. Several international agreements have been  established and international commissions have been created to deal with the issue of managing migratory stocks. Besides zoning of the oceans and the use of input/output controls, there remains a need to recognize fisheries as embedded in ecosystems. Since the beginning of the 1990s, the research community has directed efforts towards this end, although this issue had been identified much earlier. As early as the mid 1950s, M.B. Schaefer presented an ideal fishery research program with three priority levels of research (Smith, 1994):  •  Level I (high priority) - intensity of fishing, selectivity of the fishing method, yield, size composition by age and sex for both catch and biomass, biomass distribution and its availability to fishery, and rate of population growth;  •  Level II (medium priority) - reproduction, growth, and natural mortality;  •  Level III (low priority) - environmental forces, competition, and predation (Schaefer, 1956).  Although M.B. Schaefer recognized the importance of all three levels to fishery management, he also called attention to the high priority of only the first level, as it was sufficient to evaluate if higher yields would result after reductions in fishing effort. The other levels should be addressed through long-term research. After fifty years of research, level II is already incorporated into fisheries management, but not level III. This is probably the right time to do so, with an additional socio-economic vector. Level III is currently known as EcosystemBased Fishery Management (EBFM). NRC (1999) describes ecosystem based-management (EBM) as "an approach that seriously takes all major ecosystem components and services -  both structural and functional - into account in managing fisheries and one that is committed to understanding larger ecosystem processes for the goal of achieving sustainability in fishery management". Pikitch et al. (2004) describe some of the essentials of this 'new' management system. In addition to EBFM, there is a need to decrease fishing capacity worldwide and to recognize the deleterious effects of subsidies (Munro and Sumaila, 2002). Capacity reductions should be undertaken by both developed and developing countries, although it seems easier in developed countries due to governmental support and because alternatives are available (Jennings et al., 2001). In developing countries, which are responsible for approximately 60% of the total world catch (Jennings et al., 2001), these mechanisms are usually absent. The conflict between small-scale (artisanal and subsistence) and industrial fisheries is particularly serious in these countries due to the high number offishersinvolved in the former. Brazilian fisheries are also in crisis (Dias Neto and Dornelles, 1996), although some argue that there is still potential to increase production (DPA, 1999). This will be discussed in more detail later in this thesis.  1.2. A framework forfisheriesmanagement  The procedures currently used to manage fisheries are widely questioned due to the succession of fishery collapses, and new approaches are being proposed. Whatever new approach for fisheries management is set up, it is likely to be embedded in the classical framework presented in Figure 1.1 and summarized below. A management authority is established within a society, which can be structured between two extremes: as a government authority, where the government decides without consulting with fishers, and as a fishers' authority, where fishers act independently (McCay, 1996). Typically, extremes are not the best choice, and some form  of co-management seems to be a better option. Under co-management, government and fishers work together and this is recognized as a key point for a management system to be successful. This arrangement is expected to be consonant with global and regional initiatives, and is subject to the 'institutional uncertainty' associated with political changes (Francis and Shotton, 1997).  Once a management authority is established, its objectives must be clearly defined. Although this seems to be a trivial issue, unclear and conflicting objectives have been recognized as one important factor behind management failures. The first trade-off a fisheries manager has to face is between short-term and long-term goals and within each of those, which factors should be considered and how. An objective function may be used to facilitate the decision process, but the use of a weight system for each factor is an additional source of controversy (Healey, 1984). Once agreed upon, objectives are then translated into management strategies and finally into management actions, which include input controls, designed to control effort (licences, individual effort quotas, individual effort transferable quotas, vessel restrictions), output controls for controlling removals (total allowable catches, individual quotas, individual transferable quotas), and technical measures (size and sex restrictions, gear restrictions, time and area closures) (Jennings et ai, 2001). Each of these control approaches has strengths and weaknesses, and as such is not expected to perform well on its own. Walters and Martell (2004) and others argue that managing fisheries using methods that depend on estimates of total abundance are too costly and riddled with uncertainty. Instead, direct control of exploitation rates (u-control) using time-area closures and tagging experiments could be more efficient and less costly. However, much research is still required for using tagging for specific fisheries.  SOCIETY  t MANAGEMENT AUTHORITY  MANAGEMENT OBJECTIVES MANAGEMENT STRATEGIES MANAGEMENT ACTIONS FISHERY SCIENCE  • • •  Catch controls Effort controls Technical measures  •  DECISION I  IMPLEMENTATION  FISHERY  ENFORCEMENT • • •  Ecological Social Economic  MONITORING  Yes  Figure 1.1: Framework for fisheries management (based on Jennings et al, 2001).  Identify causes  No  Fishery scientists provide advice towards the establishment of management objectives, strategies, and actions, while decision makers are responsible for choosing which actions should be implemented. However, there is an ongoing debate about the need for a more active participation of scientists in the decision process. Others consider that this movement would undermine the credibility and objectivity of science. Others still consider that being a scientist does not entitle one to express preferences, mainly if the scientist is not going to be directly affected by the outcomes (Walters and Martell, 2004).  Fisheries include ecological, economic, and social components, and all should be considered in decision-making. Since its onset, fisheries management was mainly centred in the ecological component. It was not until the 1950s that the importance of economics in fisheries was formally recognized (Gordon, 1954). The social component was not incorporated until the 1970s (Acheson, 1981). However, the process of properly incorporating these two last components in the traditional ecological framework has been rather slow, partially due to the high degree of complexity involved, mainly after including other interest groups such as those tourism-related and non-governmental organizations - NGOs (Caddy and Cochrane, 2001). The ecological component has been continuously re-assessed, leading to the need for an ecosystem-based approach and the search for ecosystem indicators to detect signs of nonsustainability (Christensen, 2000; Pauly et al, 2000). The other two components have also been continuously assessed leading to, for example, the realization that the most well-designed fisheries management plans would be undermined in the presence of pervasive subsidies (Munro and Sumaila, 2002).  One issue frequently over-looked during the planning of the fisheries management process is the evaluation of short- and long-term results from the proposed actions, a fundamental step within an adaptive management strategy (Walters, 1986). If the objectives are met, the key elements of the strategy should be monitored on a long-term scale; if not, the objectives and actions should be re-evaluated and changed when necessary.  Enforcement is also an essential part of this process, which can be facilitated using comanagement. Costs of enforcement, monitoring and even research should be shared by all parties involved (Sissenwine and Mace, 2003). Each of the steps presented in this general framework is subjected to different degrees of uncertainty (Francis and Shotton, 1997), which should be numerically stated when possible, or otherwise considered qualitatively.  One new component in this framework is the importance of consumers in delineating the future of fishing practices. Consumers and NGOs have played an important role in fisheries that involve unsustainable practices such as dolphin by-catches in tuna fisheries, and turtle and other by-catches in shrimp trawling. This has led to initiatives such as eco-labelling (Deere, 1999; Gardiner and Kuperan Viswanathan, 2004). Users also have an important role when they choose eco-tourism, which is seen as an important mechanism for preserving ecosystem functions (Gossling, 1999).  Fisheries in developing countries present additional challenges, as they are usually multispecies and involve multiple gears. In this case, the use of output controls such as total allowable catches (TAC) based on stock assessment for all individual species would be constrained by the large number of species and the high cost involved. Considering the  importance of artisanal and subsistence fisheries in those areas, it would be also hard to effectively control total catches. Marine protected areas (MPAs) have been increasingly proposed as a tool for fisheries management in developing (as well as in developed) nations. However, Polunin (2002) points out that there is no strong evidence of greater catches in areas near MP As, except when closed areas are large enough in relation to the total fishing ground areas. In order to assess the performance of MP As, clear objectives and success indicators have to be defined. Considering the restricted degree of planning and management of MP As in most tropical areas (Alder, 1996), it is hard to assess their performance.  Another characteristic of developing countries is both high population density and growth, leading to high pressure on fish resources. Marginalization and the resultant Malthusian overfishing are critical issues over and above those previously described (Pauly, 1997). This kind of overfishing is characterized by stagnating overall catches and increasing numbers of fishers, decreasing catch per fisher, evidence of biological, ecological, and economic overfishing, recruitment of young men with no fishing background into the fisheries and the consequent  use  of destructive  practices,  and  women (wives, sisters, daughters)  subsidizing fishermen (Pauly, 1997). Some of the Malthusian overfishing indicators, such as the declining trend in the overall catches, have been observed in Brazil (Dias Neto and Dornelles, 1996), the increasing number of women as fishers in land-based fisheries, targeting mainly molluscs, and the use of explosives and poisonous substances in some States of the northeastern region (Quinamo and Melo, 1997; Alcantara, 2001). In addition, developing regions such as northeastern Brazil have high marine biodiversity, with complex trophic webs, resulting in higher uncertainty in the evaluation of indirect effects of fishing. Finally, the migration of fishing fleets from developed regions (under strict effort control aiming at  decreasing overcapacity) to developing regions is an additional source of concern (Mathew, 2003).  1.3. History of fisheries management in Brazil  Barbosa (1983) and Paiva (2004) present the history of the organization of the fishing sector in Brazil. Portuguese 'discovered' Brazil in 1500. During the 16 century, Portugal regulated all th  fishing rights in Brazilian waters. In 1571, incentives were given to build fishing boats. Small fisheries targeting groupers and anchovies (amongst others) were unable to properly develop due to a State monopoly of salines, which lasted for more than one century.  In 1602, fishers from the Bay of Biscay were permitted to catch whales in Brazilian waters and to build factories to process their oil. This fishery was the only large-scale fishery in Brazil during the colonial period. Because of whaling, the first fishers' associations were established in Bahia State and spread along the Brazilian coast: Rio de Janeiro, Sao Paulo, and Santa Catarina. By the end of the 1880s, whaling began to decline due to the decrease of whale population size, foreign competition in the market, and the use of products other than whale oil for lighting.  Fishery management was handed to local governments ('camaras das vilas') at the end of the 18 century. In 1802, fisheries were recognized as having national importance and more th  incentives were given to their development. Fishing licenses were not required, but the type of fishing boats, gears used, and number of fishers had to be reported. The first gear restrictions were put in place: no trawling was allowed; trawling nets were burnt and fines were applied.  Following the independence of Brazil from Portugal in 1822, the fishing sector was put under the control of the Brazilian Navy. Nets with small mesh size were not allowed and new instructions were given to register all the types of large fishing boats and report on the size of their crew (1824). In 1825 and 1826, these instructions were extended to small fishing boats. However, they were enforced only after 1846, when a Port Authority was created and the legislation was given a national scope. With the national decree No. 876 (1856), the first steps were taken towards the industrialization of the fishing sector. However, this decree was only put in practice after decree no. 8338 (1881), which is considered the first 'Fishing Code'. Several fishers' associations were established and fishers could finally secure some basic rights.  In 1897, after the declaration of the Brazilian Republic, the fishing sector was nationalized, still under jurisdiction of the Brazilian Navy, and all professional fishers were required to register with the Port Authority. In 1912, a decree created a Fishing Authority ('Inspectoria de Pesca'), associated with the Ministry of Agriculture, Industry and Trade. This institution remained active only for three years. In 1915, the Station of Marine Biology was created within the scope of the same Ministry in order to promote research in Brazilian marine waters. This station closed one year later due to the lack of financial support and technical capacity. In 1919/1920, fisheries issues returned to the responsibility of the Brazilian Navy and in 1923, the regulation for the Directorate of Fishing ('Diretoria da Pesca e Saneamento do Literal') was launched. This regulation allowed for better organization of fishers, destruction of illegal fishing gears, and fisheries research. In 1930, the first Fishing School was created in Sao Paulo State, specifically to improve both theoretical and practical knowledge of fishers' children in  terms of the fishing industry. This school was later turned into a research institution, still active today.  From 1933 to 1961, the Division of Fish and Game became responsible for Brazilian fisheries and the Code of Fish and Game of 1934 (reviewed in 1938) was the legal basis for its activities (Anon., 1973). That division was linked to the National Department of Animal Production, a unit of the Ministry of Agriculture. In 1942, an Executive Fishery Commission was created within the same ministry to organize the fishing industry (closed three years later). As part of this attempt, a regulation was implemented in 1950 to oversee the activities of the General Confederation of Brazilian Fishers and other fishers' associations. In 1961, the Council for Fisheries Development (CODEPE) was created and the Division of Fish and Game was transferred to that council. One year later, that division closed and the National Institute for Fishery Development (SUDEPE) was created, which was made part of the Ministry of Agriculture (Anon., 1973). The main goal of SUDEPE was to promote the development of a highly organized fishing sector. The specific objectives of that superintendence were to elaborate the National Plan for Fishery Development, to give technical and financial assistance to fisheries projects, to conduct research, and to promote the application of a Fishing Code. In 1967, decree no. 221 was approved to stimulate the development of fishing industries. Unfortunately, this legal measure also removed rights that fishers had enjoyed in early years. In that same year, SUDEPE and the United Nations established the Brazilian Fisheries Research and Development Program (PDP) and fisheries research finally began to develop in a structured context.  In 1970, the Brazilian 'territorial sea' was extended unilaterally from 12 to 200 nautical miles. As a consequence, a decree related to the rational use and conservation of the renewable resources was approved in 1971 (Anon., 1973). The Institute of Research and Development of the Fishing Sector was created in 1980, which was linked to SUDEPE and responsible for the continuation of the activities developed by the PDP. In 1989, SUDEPE was abolished and replaced by the Brazilian Institute for the Environment and Renewable Natural Resources (IBAMA). This institute deals with issues formerly within the province of the Secretary of Environment (SEMA), the Superintendence of Rubber (SUDHEVEA), the Brazilian Institute for the Development of Forests (IBDF), and SUDEPE. This had a negative impact on the fishing sector since IBAMA, which lacks financial and human resources, is faced with too broad a range of issues. IBAMA has three centres associated with fisheries research and management of marine fisheries resources off northern (CEPENOR), northeastern (CEPENE), and southern (CEPSUL) regions.  In 1982, Brazilian authorities signed the United Nations Convention on the Law of the Sea and ratified it in 1988, committing the country to specific conservation and management standards for living aquatic resources; the Law of the Sea has been enforced since 1994. Since that year, Brazil has been working on a program called Living Resources of the Exclusive Economic Zone (REVIZEE), established to assess the most important exploited stocks and to search for remaining unexploited stocks.  In 1995, an Executive Group for the Fishing Sector was created. This group proposed a National Plan for Fishery and Aquaculture (GESPE, 1998), which never became operational. In the same year, a decree split fisheries responsibility between the Ministry of Environment  (MMA) and the Ministry of Agriculture and Supply (MAA) (Cardoso et al, 1998), with the establishment of the Fishery and Aquaculture Department (DPA) to stimulate fishing production. In 2003, the DP A was closed and a Special Secretary for Aquaculture and Fisheries (SEAP) was created with the same objectives as the DP A, but directly linked to the President of the Republic. IBAMA still retains some influence on the fishing industry and a clear conflict of interests is evident. These changes in the institutions managing the fishing sector do not allow for the establishment of a sound national fishery policy.  New fisheries management schemes have been applied, such as those in the southern (Kalikoski and Satterfield, 2004) and northeastern (Scharer and Scharer, 2004) regions. However, these are localized initiatives attempting to empower small-scale fishers, which are often overlooked at the national scale. Four maritime extractive reserves' were created since 1992 and 13 others have been proposed in order to guarantee the access of local communities to their resources through the exclusion of members from other communities and to promote resource conservation (www.ibama.gov.br/resex/cnpt/). Lima and Dias-Neto (2002), however, mention that the conservation component may not be properly addressed due to lack of clarity in the definition of such objective in the management plans for these reserves. A concern that seems to be shared by Silva (2004), when emphasizing the importance of the partnership between government and local community for the success of these reserves.  1  Extractive reserve is a new conservation category created under the auspices of IB AM A/Brazil in 1989, with the  objective of decentralizing the management of natural resources through the delegation of rights to communities historically associated with the sustainable use of local resources (Silva, 2004).  Brazil is also involved in at least twelve international or regional agreements directly or indirectly related to the management of fishery resources (Table 1.1). Some of these agreements do not have legal power to deal with international conflicts. Others became obsolete due to the lack of political disposition such as CARP AS in 1974 (J .P. Castello, University of Rio Grande/Brazil, pers. comm.). However, much progress was made, for example, after the establishment of the International Whaling Commission (IWC), which led to the ban of whaling practices in Brazil by 1985. Brazil has also implemented some national regulations to be able to follow recommendations set by the International Commission for the Conservation of Atlantic Tunas (ICCAT) for the management of tuna and tuna-like fishes in the Atlantic Ocean (Lima, 2001). The Special Secretary for Aquaculture and Fisheries (SEAP) is currently responsible for negotiating quotas for these migratory species in Brazil and for their implementation.  1.4. Issues on fisheries management in Brazil  The institutional instability described in the previous section has some negative effects in the collection of basic data required for managing Brazilian fisheries. First, there is a lack of continuity in the collection of catch data (Lima and Dias Neto, 2002). Second, effort data are not properly gathered and/or lack continuity (CEPENE, 2000a; Fonteles Filho, undated). Third, there is the chronic problem of attributing catch records to the proper species, a problem longed recognized (Welcomme et al, 1979). Finally, there is no attempt to estimate unreported or illegal catches from Brazilian waters at a national level. This probably reflects a disconnection between the system responsible for data collection and data users.  Table 1.1: Some international or regional fisheries-related agreements in which Brazil is involved (FishBase; www. li shbase .org). Acronym  Name  Coverage  Year Establishment In force Ratified  CARP AS  Regional Fisheries Advisory Commission for the Southwest Atlantic  Fisheries  1961  CBD  Convention on Biological Diversity  Biodiversity  1992  1993  1995  CCAMLR  Commission for the Conservation of Antarctic Marine Living Resources  Environment  1980  1982  -  CITES  Convention on International Trade in Endangered Species of Wild Biodiversity Fauna and Flora  1973  1975  -  COPESCAL  Commission for Inland Fisheries of Latin America  Fisheries  1976  ICCAT  International Commission for the Conservation of Atlantic Tunas  Fisheries  1966  1969  -  INFOPESCA  Center for Marketing Information and Advisory Services for Fishery Fisheries Products in Latin America and the Caribbean  1971  1975  -  Conservation and Management of Straddling and Highly Migratory Fisheries Fish Stocks Agreement  1995  2001  2000  UNCLOS  United Nations Convention on the Law of the Sea  General  1982  1994  1988  WECAFC  Western Central Atlantic Fishery Commission  Fisheries  1973  IWC RAMSAR CONVENTION SHMFSA  International Whaling Commission Convention on Wetlands of International Importance, especially as Waterfowl Habitat  Fisheries Environment  1946  Brazilian fisheries are managed by the federal government and thus, the problems identified above are also observed in northeastern Brazil. This thesis aims to analyze these issues in a context of data requirements towards ecosystem-based fisheries management in northeastern Brazil, and to identify new issues to be addressed. Attempts to quantify the magnitude of the problem would require that data are analyzed at the national level for comparison with alternative existing databases.  1.5. Objectives  The overall goal of this study is to evaluate the fishing impacts on marine ecosystems off Brazil, with emphasis on the northeastern region (East Brazil Large Marine Ecosystem; Fig. 1.2). In order to reach this goal, the following specific objectives were pursued:  I)  to identify the richness of common names of Brazilian fishes and to analyze its effect on fishery statistics;  II) to analyze catches originating from Brazilian marine fisheries and to assess their use as an indicator of ecosystem health; III) to describe the mass and energy fluxes throughout functional groups living in the East Brazil Large Marine Ecosystem that encompasses northeastern Brazil; IV) to assess the impact of current fishing policies and some alternatives.  These objectives were addressed according to the methodological framework presented in Figure 1.3 and discussed in the next chapters.  Figure 1.2: Location of the East Brazil Large Marine Ecosystem (gray) along the Brazilian coast.  1.6. Description of the study area  Brazil (and its fisheries) cannot be analyzed as a single unit because of its size and history. The country is politically divided into five regions, North, Northeast, Center-West, Southeast, and South, reflecting socio-economic differences (Figure 1.4). Goldsmith and Wilson (1991) present a historical perspective for the difference between the South (called Centre-South), where manufacturing was dominant, and the Northeast, which was traditionally responsible for supplying raw materials and cheap labour to the South and for providing a market for its manufactured products. This disparity is also reflected in fishing activities, with a decreasing degree of importance of artisanal fishery from the North (93%) to the South (20%) (Paiva, 1997). Matsuura (1995) proposed the division of the Brazilian coast into North, Northeast, East, Southeast, and South based on bathymetry, oceanographic structure, fauna, flora, and fisheries. This division has been used in the assessment of the resources off the  Artisanal fishery 1  Industrial fishery 1  Common names database (fish)  Reconstruction of marine landing data from commercial fisheries (1978-2000)  OBJECTIVE I (Chapter 2)  • • •  OBJECTIVE II (Chapter 3)  Description of the marine ecosystem off northeastern Brazil - Ecopath model (1970s)  OBJECTIVE III (Chapter 4)  Fishing policy exploration - Ecosim -  OBJECTIVE IV (Chapter 5)  FISHING IMPACTS: Fishing down the food web Changes in biomass Future policy options  Figure 1.3: Framework to the development of the analysis of the impact of fisheries on the marine ecosystem off northeastern Brazil.  Brazilian coast. The Brazilian northeastern region is differentiated from the others by its narrow and irregular continental shelf, deep thermocline, presence of corals, and low primary production.  The study area corresponds to a tropical region located between 1°S and 16°S (Figs. 1.2 and 1.4). The continental shelf off the northeastern Brazil bordering the States of Rio Grande do Norte, Paraiba, Pernambuco, Alagoas, Sergipe, and Bahia is influenced, according to Gulland (1971), by a branch of the South Equatorial Current (SEC) and by the Brazil Current. The latter current is shallow (axis above the 200 m isobath) and represents the western branch of the anticyclonic gyre of the South Atlantic, which moves southwards. The continental shelf off the States of Maranhao, Piaui, Ceara, and Rio Grande do Norte is influenced by the North Brazil Current.  1.7. Overview of the main marine resources exploited off northeastern Brazil  Brazilian marine catches amount to roughly 500,000 tonnes, which correspond to approximately 0.5% of the world capture (FAO, 2001). Although this figure is small (and probably underestimated), it has high social importance, as it involves about seven hundred thousand fishers (CNIO, 1998). Overall, the artisanal fishery, defined as operated inshore by small boats of less than 20 tonnes, is responsible for 60% of total national catches. This value is probably an underestimate due to the absence of a well-structured system of data collection. Northeastern Brazil is responsible for 11.7% of the total Brazilian catches, the smallest contribution amongst all regions (Paiva, 1997).  Figure 1.4: The five political regions of Brazil (North, Northeast, Center-west, Southeast, and South) and the nine States of the northeastern region: MA = Maranhao, PI = Piaui, CE = Ceara, RN = Rio Grande do Norte, PB = Paraiba, PE = Pernambuco, A L = Alagoas, SE = Sergipe, and BA = Bahia. Other states mentioned throughout the thesis are: AP = Amapa and PA = Para (North); ES = Espirito Santo, RJ = Rio de Janeiro, and SP = Sao Paulo (Southeast); and PR = Parana, SC = Santa Catarina, and RS = Rio Grande do Sul (South). Near-surface currents are also presented, based on Johns and Lee (1990).  The annual potential catches off the northeastern shelf estimated by Gulland (1971) were the lowest amongst all the Brazilian regions: 50,000 tonnes for demersal species and 50,000 tonnes for pelagic species (excluding oceanic tuna fishing), i.e., 6% of the potential marine catches for the whole country. Based on other estimates, Paiva (1997) points out that there is still potential to increase catches in this region, although some resources such as lobsters and snappers have already shown signs of decline (Dias Neto and Dornelles, 1996). An overview of the main marine resources exploited in the region is presented below, although several other artisanal multi-species fisheries take place in the region.  a) Lobsters  The artisanal exploitation of Brazilian lobsters began in 1955. Motorboats were introduced by the early 1960s, as the traditional fishery could not supply the demand (Paiva, 1997). Two species represent the majority of the catch, Panulirus argus and Panulirus laevicauda, which are distributed from a depth of 20 m to the shelf break (Farias, 1980). Some catches have been recently reported for a third species, Panulirus echinatus, which is found on rocky bottom off oceanic islands (Paiva, 1997). Most of the lobster catches are exported and those specimens that are smaller than the size required for export are sold in the domestic market (Dias Neto and Dornelles, 1996).  The collection of catch and effort data for lobsters began in 1958 and 1965, respectively (Dias Neto and Dornelles, 1996). Currently, the main sources of catch data are the export figures. Two main sources of bias must be considered relative to these estimates: a) lack of data related to the domestic market, considered low (5%) in relation to the exports by IBAMA/CEPENE (as cited in Lins-Oliveira et al, 1993); and b) the absence of data on catches taken by illegal methods such as diving with compressors (hookah). The Permanent Study Group (GPE) for lobsters analyzes these basic data using single-species approaches. The maximum catch ever registered for Brazilian lobsters was 11,000 tonnes in 1979, although the maximum sustainable yield was estimated at 9,000 tonnes (Dias Neto and Dornelles, 1996). According to these authors, lobster catches have been declining since 1991 and reached 8,000 tonnes in 1994, with an effort 240% higher than f  opt  (i.e., the level of effort that generates maximum  sustainable yield); in 1999, the catch was even lower (6,000 tonnes). Rocha et al. (2001) consider that these stocks are overexploited (Table 1.2).  The first regulatory measures were established in 1961/1962: a) annual closures for 3-4 months; b) minimum tail sizes; c) minimum mesh sizes; d) prohibition of fishing in nursery areas; e) prohibition of the use of trawlers, gillnets, and purse seiners; f) establishment of production quotas; and g) prohibition of capture of mature females (Paiva, 1997). Nowadays, lobsters are caught by traps, gillnets, and diving (with and without compressors, although the use of compressors is prohibited) (Rocha et al. 2001). These regulatory measures continuously change and enforcement is poor, which constitute two major problems in managing Brazilian fisheries (GESPE, 1998).  b) Shrimps  Shrimps were initially caught by artisanal fisheries mainly near Maranhao State, and between Alagoas and Bahia (Farias, 1980). Currently, shrimp fisheries are spread all over the region, mainly operating down to a depth of 20 m (Dias Neto and Dornelles, 1996). The main target species are Xiphopenaeus kroyeri and Litopenaeus schmitti, although Farfantepenaeus subtilis and Farfantepenaeus brasiliensis are also caught in lower proportion (CEPENE, 2000b). By the late 1970s and the early 1980s, the first motorboats were introduced. Single and double otter trawls are the main fishing gears used, although gillnets, traps, and beach seines are also found (Farias, 1980). More than 17,000 tonnes were caught in 1999, associated with a high proportion of by-catch, mainly juveniles of other exploited species (Dias Neto and Dornelles, 1996). Catches are lower than the shrimp production provided by aquaculture: 37,000 tonnes in 2001 (Roubach et al, 2002). This is an industry that has been growing since 1996 with the introduction of Litopenaeus vannamei, but there is some concern about its sustainability due to the destruction of mangroves.  Table 1.2: Status of the main fisheries off northeastern Brazil.  RESOURCE  SCIENTIFIC NAME  REGION  M S Y (t-year" ) 6  1  SOURCE  STATUS  Caribbean spiny lobster  Panulirus argus  N-NE  Smoothtail spiny lobster  Panulirus laevicauda  N-NE  Shrimps  Various  NE  Crabs  Various  N-NE  — —  Southern red snapper  Lutjanus purpureus  N-NE  6,401  Yellowfin tuna  Thunnus albacares  ATL  148,000  Fully exploited  (ICCAT, 2004b)  Albacore  Thunnus alalunga  SATL  26,333-30,915  Fully exploited  (ICCAT, 2004b)  Bigeye tuna  Thunnus obesus  ATL  93,000-114,000  Fully exploited  (ICCAT, 2004b)  Northern bluefin tuna  Thunnusthynnus  WATL  Overexploited  (ICCAT, 2004b)  Swordfish  Xiphias gladius  SATL  — —  Unknown  (ICCAT, 2004b)  Atlantic blue marlin  Makaira nigricans  ATL  1,000-2,400  Overexploited  (ICCAT, 2004b)  Atlantic white marlin  Tetrapturus albidus  ATL  323-1,320  Overexploited  (ICCAT, 2004b)  Atlantic sailfish  Istiophorus albicans  WATL  Unknown  (ICCAT, 2004b)  Unknown  (ICCAT, 2004b)  At equilibrium  (CNIO, 1998)  Oceanic sharks Line fish  1  Prionace glauca Isurus oxyrhynchus Various  2  3  4  5  SATL NE (Abrolhos)  6,706  Overexploited  (Rochaef a/., 2001)  2,744  Overexploited  (Rochaefa/., 2001)  Not overexploited  (CEPENE, 2000b)  Unknown  (CNIO, 1998)  — — 1,445  Overexploited and risk of recruitment (Charuauef a/.,2001) overfishing  1. Line fish are those caught using bottom hand line (groupers and snappers); 2. N = North region and NE = Northeast region; 3. ATL = Atlantic Ocean; 4. SATL = South Atlantic; 5. WATL = Western Atlantic; 6. MSY = Maximum sustainable yield estimated by different methods for each species.  The main control measures in place for shrimp fisheries are: a) time closure; b) mesh size control; c) control of issued licences; and d) prohibition of trawling closer to 3 or 10 nautical miles from the shore (CEPENE, 2000b). These measures vary amongst neighbour States causing local conflicts. The GPE for shrimps points out that there is no need for stronger enforcement as the shrimp stocks do not present any signs of overexploitation (CEPENE, 2000b). However, the by-catch is very high, as pointed out by Dias Neto and Dornelles (1996) and must be considered if an ecosystem-based approach is to be implemented.  c) Tuna and tuna-like fishes  The industrial fishery for tuna and tuna-like fishes began in 1956, through joint ventures with Japanese vessels based in Pernambuco, and ceased in 1964, owing to political and economical reasons (Farias, 1980). Korean vessels started to operate in the region in 1976 (Lessa et al, 2004). By 1983 a national fleet was formed in Pernambuco, but this fleet moved to Rio Grande do Norte after 1994 (Paiva, 1997). In 1993, a fleet was established in Paraiba State. By 2002, 98 longliners were operating from ports located in northeastern Brazil: 61 in Rio Grande do Norte (29 Brazilian vessels and 32 through joint ventures) and 37 in Paraiba (only joint ventures) (Lessa et al, 2004). This represents more than 75% of the total fleet of 129 longliners operating in Brazil (ICCAT, 2004a). Some baitboats (39) and purse seiners (2) also operate off Brazilian ports, but usually fish in southern waters. Since 2000, joint ventures have been established with Spain, Taiwan, United States, Equatorial Guinea, Saint Vincent, Uruguay, and Vanuatu (www.iccat.es), of which some provide flags of convenience.  The main species traditionally caught off northeastern Brazil by the national fleet were yellowfin tuna {Thunnus albacares), swordfish {Xiphias gladius), and sharks. In addition to these species, the catch composition from the leased fleets also included albacore {Thunnus alalunga) and bigeye tuna {Thunnus obesus), a difference attributed to the concentration of effort offshore. Both fleets use surface longline, although the yield obtained by the leased fleet is superior to the national. One serious problem associated with longliners is shark finning, the practice of removing the high valued shark fins and returning the dead shark to the sea. This practice is common within the leased fleet. Although shark finning was officially prohibited in 1998 (Kotas et al., 2001), this activity was not discontinued and was denounced by local fishers in the First Fishing Forum in Paraiba State (August 2001).  Until late 1980s, swordfish catches were low and exported unprocessed (Weidner and Arocha, 1999). After 1996, a fishery targeting swordfish developed, which exported fresh swordfish to the US (Evangelista et al., 1998). Because of the decreasing price in the international market, fishers began to sell this product in national markets (Weidner and Arocha, 1999). Since 1996, swordfish quotas for the South Atlantic have been negotiated with ICCAT after the stock presented the first signs of overexploitation, probably caused by the migration of the fleet from the North Atlantic (Lima, 2001). Brazil is entitled to 16% of the total allowable catch (TAC) of 14,620 tonnes for the South Atlantic, but has been consistently fishing over this limit. Brazil has also increasingly caught southern albacore after 1997. Albacore in the Southern Atlantic is also subject to a TAC system, although no consensus about the quota sharing system has been reached yet (www.iccat.es).  ICCAT (2004) presents revised estimates for the status of all tuna and tuna-like fishes for the Atlantic Ocean. In general, the stocks are fully or over exploited, but for some species such as swordfish and pelagic sharks there is no clear information (Table 1.2). Assessments presented in this ICCAT document are subjected to high level of uncertainty due to the presence of fleets from several countries using different gears that end up issuing, in some cases, contradictory signals about the status of the stocks. Furthermore, increasing efficiency of some gears and unknown IUU (illegal, unregulated, and unreported) catches make assessments even more difficult.  d) Southern red snapper  The Southern red snapper {Lutjanus purpureus) is targeted by both artisanal and industrial fleets, which have a national and international market, respectively (Dias Neto and Dornelles, 1996). The industrial fishery began in early 1960s off Ceara and Rio Grande do Norte coasts (Farias, 1980), but gradually expanded northwards because of the high demand from the international market (Dias Neto and Mesquita, 1988).  This snapper is caught by vertical longline ('pargueira') in oceanic banks, 150 nautical miles off the coast of Ceara and Rio Grande do Norte (depth = 30-140 m) and in the outer continental shelf, 50 nautical miles from the coast (depth = 40-140 m) (Dias Neto and Dornelles, 1996). These authors point out that other species are also caught in this fishery: Lutjanus vivanus, Lutjanus buccanella, Ocyurus chrysurus, Epinephelus spp., and Balistes vetula.  Southern red snapper catches decreased from 1977 to 1990 (Dias Neto and Dornelles, 1996), but partially recovered afterwards because of the effort reduction resulting from decreasing US imports (Paiva, 1997). The first restrictive measures were adopted in the early 1980s: a) no increase in the number of issued licences, and b) minimum capture size. These measures probably helped the stock to recover as well. Assessment estimates indicate a maximum sustainable yield of 4,000-6,000 tonnes (Dias Neto and Dornelles, 1996) or 6,401 tonnes (CNIO, 1998), depending on the source considered. After being overexploited and showing signs of recovery, the status of this stock is still a matter of concern (Table 1.2). In 1999, the catch was approximately 3,360 tonnes, which indicates a declining trend.  e) Crabs  Ucides cordatus is caught by artisanal fisheries in mangroves of northeastern Brazil. Dias Neto and Dornelles (1996) present an overview of this fishery and some of its aspects are summarized below. This fishery usually employs no gears other than fishers' hands ('braceamento'). Small nets ('redinha') were introduced in the early 1990s, and have been considered deleterious to this fishery due to lack of selectivity and impact on mangroves as their roots are used to attach the nets (Botelho et al, 2000). Crab fishers normally exploit oysters and estuarine fish as well, and are marginalized by other segments of the local society (Alves and Nishida, 2003).  Maranhao, Piaui, and Paraiba States are the main producers and Ceara is the main consumer. The internal market absorbs the total production (about 3,000 tonnes). There is no consensus about the present exploitation status of this species (Table 1.2), but there is some concern related to the susceptibility of the mangroves to direct human impacts. Since 1950, these areas  have  been  seriously  degraded  because  of  the  construction  of  harbours  and  petrochemical/chemical industries, saline deposits, the growth of settlements, sewage, increasing land value, tourism, and expansion of agriculture, specially sugar cane and rice (Diegues, 1996). Additionally, the rapid growth of aquaculture since 1996 has raised reasons for concern, although some authors suggest that mangrove areas have not been used (Roubach et al, 2002).  Some conservation measures have been adopted by IBAMA: a) minimum catch size; and b) prohibition of catching females of any size at any time (Dias Neto and Dornelles, 1996). In Paraiba State, regulation no. 01/2003 prohibited the capture of undersized males (5 cm carapace length) and any females during the 'andanca' (reproductive period). Although important, these measures are particularly difficult to enforce in relation to other fisheries because fishers are highly dispersed along mangrove areas.  Other crab species are also caught by local artisanal fisheries: Cardisoma guanhumi, Goniopsis cruentata, and Callinectes spp. No information on the status of these stocks is available.  f) Turtles  Five species of turtles were exploited in Brazil: leatherback (Dermochelys coriacea), hawksbill {Eretmochelys imbricata), olive ridley (Lepidochelys olivacea), loggerhead (Caretta carettd), and green turtle (Chelonia mydas). In 1967, a program to protect turtles was initiated and a complete ban of the turtle fishery was declared in 1986 (Marcovaldi and Marcovaldi, 1999). A national conservation project was established in 1980 (TAMAR Project), which currently  operates in twenty-one bases spread along the coast (Marcovaldi and Marcovaldi, 1999). However, turtles are still caught as by-catch in swordfish and other pelagic longline fisheries (Weidner and Arocha, 1999; Pinedo and Polacheck, 2004) and in gillnet lobster fisheries (Sales and Lima, 2002).  g) Whales  As previously reported, whaling is a very old activity in Brazil, dating back to the 1600s. In the northeastern region, this activity started in Bahia and in 1911, a company was established further north (in Paraiba State), with one, two or three vessels in operation each year. The main whale species caught were minke {Balaenoptera acutorostrata), sperm {Physeter catodon), sei {Balaenoptera borealis), humpback (Megaptera novaeangliae), blue {Balaenoptera musculus), Bryde's {Balaenoptera edeni), and fin {Balaenoptera physalus) (Paiva and Grangeiro, 1970; Singarajah, 1985).  Brazil signed and ratified the International Convention on the Regulation of Whale Fishery in 1950, and since then, its exploitation rates followed the quotas established by the International Whaling Commission (Farias, 1980). From 1981 to 1985, only minke whales could be caught. In 1987, the Brazilian government declared a complete ban of cetacean fisheries (Federal law no. 7643, December 18 , 1987). th  Summary of the exploitation status of the main resources  Most marine resources off northeastern Brazil are fully or overexploited. The status of some resource remains unknown. The national system of fishery statistics is considered poor and more insight would be gained if statistics were corrected for discards, and illegal and  unreported catches were incorporated, including those originating from recreational fisheries. Commercial fisheries are managed using single-species models and there is no initiative to adopt an ecosystem-based management approach.  1.8. Thesis outline  Following this introductory chapter, each specific objective will be presented in a separate chapter containing introduction, methods, results, discussion, conclusion, and bibliography related to each subject. Chapter 2 will address the richness of common names of Brazilian marine fishes and how this richness might affect the national fishery statistics. The analysis of catch data from marine fisheries off Brazil will be addressed in Chapter 3. Chapter 4 will analyze the trophic structure of the East Brazil Large Marine Ecosystem and Chapter 5 will present some of the possible effects of future fishing practices. The last chapter (Chapter 6) will summarize and integrate the thesis and present concluding remarks.  1.9. Bibliography  Acheson, J.M. (1981). Anthropology of fishing. Annual Review of Antropology 10: 275-316. Alcantara, D. (2001). Vida mutilada. Travessia. II: 18-22. Alder, J. (1996). Have tropical marine protected areas worked? An initial analysis of their success. Coastal Management 24: 97-114. Alverson, D.L., M.H. Freeberg, S.A. Murawski and J.G. Pope (1994). A global assessment of fisheries bycatch and discards. FAO Fisheries Technical Paper 339: 1-233. Alves, R.R.N. and A.K. Nishida (2003). Aspectos socioeconomicos e percepcao ambiental dos catadores de caranguejo-uca Ucides cordatus cordatus (L. 1763) (Decapoda, Brachyura) do estuario do Rio Mamanguape, nordeste do Brasil. Interciencia 28(1): 36-43. ANA (2001). Bacias hidrograficas. http://www. ana, gov.br/. Accessed in December 19, 2001.  Anon. (1973). Organizacao dos Pescadores. Revista Nacional da Pesca. X V : 16-17. Barbosa (1983). FEPERJ - Colonia de Pescadores. Boa Pesca. Revista do Gaivotas Clube de Pesca 1(4): 5-7. Baum, J.K., R.A. Myers, D.G. Kehler, B. Worm, S.J. Harley and P.A. Doherty (2003). Collapse and conservation of shark populations in the Northwest Atlantic. Science 299: 389-392. Botelho, E.R.O., M.C.F. Santos and A.C.P. Pontes (2000). Algumas consideracSes sobre o uso da redinha na captura do caranguejo-uca, Ucides cordatus (Linnaeus, 1763) no litoral sul de Pernambuco - Brasil. Boletim Tecnico Cientifico do CEPENE 8(1): 55-71. Burger, J., C. Field, R.B. Norgaard, E. Ostrom and D. Policansky (2001). Common-pool resources and commons institutions. An overview of the applicability of the concept and approach to current environmental problems. In: J. Burger, E. Ostrom, R.B. Norgaard, D. Policansky and B.D. Goldstein. Island Press, Washington, D.C.: 1-15. Caddy, J.F. and K.L. Cochrane (2001). A review of fisheries management past and present and some future perspectives for the third millennium. Ocean & Coastal Management 44(910): 653-682. Cardoso, F.H., M.C.R. Pereira, F.S. Turra and G. Krause (1998). Decreto N° 2.840. http://www.planalto.gov.br/. Accessed in 10 March, 2002. CEPENE (2000a). Boletim estatistico da pesca maritima e estuarina do nordeste do Brasil. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renovaveis, Tamandare: 141 p. CEPENE (2000b). Relatorio da reuniao tecnica sobre o estado da arte da pesquisa e ordenamento da pesca de camaroes peneideos na regiao nordeste do Brasil. Centro de Pesquisa e Extensao Pesqueira do Nordeste - CEPENE, Tamandare, Pernambuco, Brasil: 64 p. Charuau, A., K. Cochrane, D. Die, A. Larez, L.A. Marcano, T. Phillips, S. Soomai, R. Souza, S. Wiggins and M . IJspol (2001). Regional assessment of red snapper, Lutjanus purpureus. FAO/Western Central Atlantic Fishery Commission. Regional reviews and national management reports. Fourth Workshop on the Assessment and Management of  Shrimp and Groundfish Fisheries on the Brazil-Guianas Shelf. Cumana, Venezuela, 2-13 October 2000. FAO Fisheries Report 651. Choo, P.S. and M.J. Williams (2003). Fisheries production in Asia: its role in food security and nutrition. Naga 26(2): 11-16. Christensen, V. (2000). Indicators for marine ecosystems affected by fisheries. Marine & Freshwater Research 51: 447-450. CNIO (1998). O Brasil e o mar no seculo XXI: Relatorio aos tomadores de decisao do pais. Comissao Nacional Iridependente sobre os Oceanos (CNIO), Rio de Janeiro: 408 p. Deere, C. (1999). Eco-labelling and sustainable fisheries. IUCN, Washington DC: 32 p. Dias Neto, J. and L.D.C. Dornelles (1996). Diagnostico da pesca maritima do Brasil. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais, Brasilia: 165 p. Dias Neto, J. and J.X. Mesquita (1988). Potencialidade e explotacao dos recursos pesqueiros do Brasil. Ciencia e Cultura 40(5): 427-441. Diegues, A.C.S. (1996). Ecologia humana e planejamento em areas costeiras. NUPAUB-USP, Sao Paulo, Brazil: 191 p. DP A (1999). Piano estrategico da pesca e aqiiicultura.  www.setorpesqueiro.com.br/  lninjsteriodaagricultura/planoestrategico/index.htm. Accessed in 30 November 2000. Evangelista, J.E.V., J.A. Vasconcelos and G.M. Oliveira (1998). Evolucao da pesca de atuns no nordeste do Brasil. Boletim Tecnico Cientifico do CEPENE 6(1): 77-108. FAO (1995). Code of conduct for responsible fisheries. Food and Agriculture Organization of the United Nations, Rome: 14 p. FAO  (2000).  The  state of world fisheries  and  aquaculture.  http://www.fao.org/  DOCREP/003/X8002E/X8002E00.HTM, Accessed in 14 January 2001. FAO  (2001).  Total  production  (1950-1999).  http://www.fao.org/fi/statist/FISOFT/  FISHPLUS.asp, Accessed in December 12,2001. Farias,  H.R. (1980).  Piano nacional  da pesca  (SUDEPE).  Desenvolvimento da Pesca (SUDEPE), Joao Pessoa, Brazil.  Superintendencia  de  Fonteles Filho, A.A. (undated). Sintese sobre a distribuicao, abundancia, potencial pesqueiro e biologia do pargo, Lutjanus purpureus Poey da Zona Economica Exclusiva do nordeste do Brasil. Avaliacao do Potencial Sustentavel de Recursos Vivos na Zona Economica Exclusiva M M A - REVIZEE. Analise/Refinamento dos dados preteritos sobre propeccao pesqueira, Fortaleza: 17 p. Francis, R.I.C.C. and R. Shotton (1997). "Risk" in fisheries management: a review. Canadian Journal of Fisheries and Aquatic Science 54: 1699-1715. Gardiner, P.R. and K. Kuperan Viswanathan (2004). Ecolabelling and fisheries management. WorldFish Center Studies and Reviews 27: 44 p. Gentner, B. and A. Lowther (2002). Evaluating marine sport fisheries in the USA. In: T.J. Pitcher and C.E. Hollingworth (Eds.). Recreational fisheries: ecological, economic and social evaluation. Blackwell Science Ltd, Oxford: 186-206. GESPE (1998). Piano diretor nacional para pesca e aqiiicultura. Grupo de Trabalho do Piano Diretor do Grupo Executivo do Setor Pesqueiro (GESPE), Brasilia: 151 p. Gislason, H., M . Sinclair, K. Sainsbury and R. O'Boyle (2000). Symposium overview: incorporating ecosystem objectives within fisheries management. ICES Journal of Marine Science 57: 468-475. Goldsmith, W.W. and R. Wilson (1991). Poverty and distorted industrialization in the Brazilian northeast. World Development 19(5): 435-55. Gordon, H.S. (1954). The economic theory of a common-property resource: the fishery. The Journal of Political Economy 62(2): 124-142. Gossling, S. (1999). Ecotourism: a means to safeguard biodiversity and ecosystem functions. Ecological Economics 29(2): 303-320. Gulland, J.A. (1971). The fish resources of the ocean. Fishing News (Books) Ltd., Surrey, England: 255 p. Hall, S.J. (1999). The effects of fishing on marine ecosystems and communities. Blackwell Science, Oxford: 274 p. Hardin, G. (1968). The tragedy of commons. Science 162(3859): 1243-1248.  Healey, M.C. (1984). Multiattribute analysis and the concept of optimum yield. Canadian Journal of Fisheries and Aquatic Science 41: 1393-1406. Hilborn, R., T.A. Branch, B. Ernst, A. Magnusson, C.V. Minte-Vera, M.D. Scheuerell and J.L. Valero (2003). State of the world's fisheries. Annual Review of Environment and Resources 28: 15.1-15.40. ICCAT (2004a). Report for biennial period, 2002-03. Part II (2003) - Vol. 2. English version. International Commission for the Conservation of Atlantic Tunas, Madrid, Spain: 196 p. ICCAT (2004b). Report of the 2004 meeting of the Standing Committee on Research & Statistics (SCRS), Madrid, Spain: 189 p. Jennings, S., M.J. Kaiser and J.D. Reynolds (2001). Marine fisheries ecology. Blackwell Science, Oxford: 417 p. Johns, W.E. and T.N. Lee (1990). The North Brazil Current retroflection: seasonal structure and eddy variability. Journal of Geophysical Research 95(12): 22103-22120. Kalikoski, D.C. and T.T. Satterfield (2004). On crafting a fisheries co-management arrangement in the estuary of Patos Lagoon (Brazil): opportunities and challenges faced through implementation. Marine Policy 28(6): 503-522. Kelleher, K. (2004). Discards in the world's marine fisheries: an update. FAO Fisheries Technical Paper 470: 1-134. Kotas, J.E., S. Santos, V.G. Azevedo, J.H.M. Lima, J. Dias Neto and C. Fernandes Lin (2001). Observations on shark by-catch in the monofilament longline fishery off southern Brazil and the national ban of finning. http://www.wildaid.org/Sharks/GlobalIssues/brazil_ paper.html, Accessed in November 9. Lessa, R.P., J.L. Bezerra Junior and M.F. Nobrega (2004). Dinamica das frotas pesqueiras da regiao nordeste. Analise das principals pescarias. Volume I. Programa de Avaliacao do Potencial Sustentavel dos Recursos Vivos da Zona Economica Exclusiva SCORE-NE, Recife: 138 p. Lima, J.H.M. (2001). Alocacao de quotas de captura no ambito da comissao internacional para a conservacao do atum atlantico - ICCAT. Boletim Tecnico Cientifico do CEPENE 9(1): 227-270.  Lima, J.H.M. and J. Dias Neto (2002). O ordenamento da pesca maritima no Brasil. Boletim Tecnico Cientifico do CEPENE 10(1): 265-330. Link, J.S. (2002). What does ecosystem-based management mean? Fisheries 27(4): 18-21. Lins-Oliveira, J.E., J.A. Vasconcelos and H. Rey (1993). A problematica da pesca de lagostas no Nordeste do Brasil. Boletim Tecnico Cientifico do CEPENE 1(1): 187-210. Marcovaldi, M.A. and G.G. Marcovaldi (1999). Marine turtles of Brazil: the history and structure of Projeto TAMAR-IBAMA. Biological Conservation 91: 35-41. Mathew, S. (2003). Small-scale fisheries perspectives on an ecosystem-based approach to fisheries management. In: M . Sinclair and G. Valdimarsson (Eds.). Responsible fisheries in the marine ecosystem. FAO and CABI Publishing: 47-63. Matsuura, Y . (1995). Os ecossistemas brasileiros e os principals macrovetores  de  desenvolvimento. Subsidios ao planejamento da gestao ambiental. Projeto Cenarios para o Planejamento da Gestao Ambiental (MMA/PNMA). Brasilia, DF, M M A : 39-104. McCay, B.J. (1996). Participation of fishers in fisheries management. In: R.M. Meyer, C. Zhang, M.L. Windsor, B.J. McCay, L.J. Hushak and R.M. Muth. Science Publishers Inc., Lebanon, USA: 60-75. Medeiros, C , I.C. Freitas and M.A. Silva (2000). Relatorio tecnico parcial do REVIZEE Score/NE. Oceanografia Fisica. Universidade Federal de Pernambuco, Recife, Brazil: 37 PMunro, G. and U.R. Sumaila (2002). The impact of subsidies upon fisheries management and sustainability: the case of the North Atlantic. Fish and Fisheries 3: 233-250. Murawski, S.A. (2000). Definitions of overfishing from an ecosystem perspective. ICES Journal of Marine Science 57: 649-658. Myers, R.A., K.G. Bowen and N.J. Barrowman (1999). Maximum reproductive rate offish at low population sizes. Canadian Journal of Fisheries and Aquatic Science 56: 2404-2419. Myers, R.A. and B. Worm (2003). Rapid worldwide depletion of predatory fish communities. Nature 423: 280-283. NRC (1999). Sustaining marine fisheries. National Academy Press, Washington, D.C.: 164 p.  Paiva, M.P. (1997). Recursos pesqueiros estuarinos e marinhos do Brasil. UFC, Fortaleza, Brazil: 278 p. Paiva, M.P. (2004). Aclministracao pesqueira no Brasil. Editora Interciencia, Rio de Janeiro: 177 p. Paiva, M.P. and B.F. Grangeiro (1970). Investigations on the whaling seasons 1964-1967, off northeastern coast of Brazil. Arquivos de Ciencias do Mar 10(2): 111-126. Pauly, D. (1997). Small-scale fisheries in the tropics: marginality, marginalization, and some implications for fisheries management. American Fisheries Society Symposium 20, Betheseda, Maryland. Pauly, D. and V . Christensen (2002). Ecosystem models. In: P.J.B. Hart and J.D. Reynolds (Eds.). Handbook of Fish Biology and Fisheries. Blackwell Publishing, Maiden, Massachusetts, Vol. 2. Fisheries: 211-227. Pauly, D., V. Christensen and C. Walters (2000). Ecopath, Ecosim, and Ecospace as tools for evaluating ecosystem impact of fisheries. ICES Journal of Marine Science 57: 697-706. Pikitch, E.K., C. Santora, E.A. Babcock, A. Bakun, R. Bonfil, D.O. Conover, P. Dayton, P. Doukakis, D. Fluharty, B. Heneman, E.D. Houde, J. Link, P.A. Livingston, M . Mangel, M.K. McAllister, J. Pope and K.J. Sainsbury (2004). Ecosystem-based fishery management. Science 305(5682): 346-347. Pinedo, M.C. and T. Polacheck (2004). Sea turtle by-catch in pelagic longline sets off southern Brazil. Biological Conservation 119(3): 335-339. Polunin, N.V.C. (2002). Marine protected areas, fish and fisheries. In: P.J.B. Hart and J.D. Reynolds. Blackwell Publishing, Maiden, Massachusetts, Vol. 2. Fisheries: 293-318. Quinamo, T. and M.B. Melo (1997). Percepcao ambiental dos Pescadores e pescadeiras do canal de Santa Cruz - PE. Anais do Setimo Congresso Nordestino de Ecologia. Ilheus/Ba: 283-284. Rocha, C.A.S., R.N.L. Conceicao, R.C.A. Carvalho and J.A.N. Aragao (2001). National report on  the  spiny  lobster  fishery  in  Brazil.  Report  on  the  FAO/DAMDA/  CFRAMP/WECAFC Regional Workshops on the Assessment of the Caribbean spiny  lobster (Panulirus argus). Belize City/Belize, 21 April-2 May 1997 and Merida/Mexico, 1-12 June 1998. FAO Fisheries Report No. 619. Roubach, R., E.S. Correia, S. Zaiden, R.C. Martino and R.O. Cavalli (2002). Aquaculture in Brazil. World Aquaculture 34(1): 28-34. Sales, G. and E.H.M.S. Lima (2002). A pesca da lagosta no litoral do nordeste: interacao pesca x conservacao das tartarugas marinhas. IBAMA, Praia do Forte, Brazil: l i p . Schaefer, M.B. (1956). The scientific basis for a conservation program. In: Papers presented at the International Technical Conference on the Conservation of the Living Resources of the Sea, United Nations Publication 1956. II.B.l: 15-55. Scharer, R. and M . Scharer (2004). Artisanal fisheries and community based fisheries management by jangadeiros in northeastern Brazil. 4  th  World Fisheries Congress,  Abstract Volume. May 2-6, 2004. Vancouver/BC, Canada. Silva, P.P. (2004). From common property to co-management: lessons from Brazil's first maritime extractive reserve. Marine Policy 28(5): 1-10. Singarajah, K.V. (1985). A review of Brazilian whaling: aspects of biology, exploitation and utilization, Cochin, India. Sissenwine, M.P. and P.M. Mace (2003). Governance for responsible fisheries: an ecosystem approach. In: M . Sinclair and G. Valdimarsson (Eds.). Responsible fisheries in the marine ecosystem. FAO and CABI Publishing, Rome, Italy and Wallingform, UK: 364391. Smith, T.D. (1994). Scaling fisheries: the science of measuring the effects of fishing, 18551955. Cambridge University Press, Cambridge: 392 p. Spalding, M., C. Ravilious and E.P. Green (2001). World atlas of coral reefs. University of California Press, Berkeley: 424 p. Steele, J.H. (1996). Regime shifts infisheriesmanagement. Fisheries Research 25: 19-23. Tchernia, P. (1980). Descriptive regional oceanography. Pergamon Press, Oxford; New York: 253 p.  Tomczak, M . and J.S. Godfrey (1994). Regional oceanography: an introduction. Pergamon, Oxford, England; New York: 422 p. Walters, C. (1986). Adaptive management of renewable resources. Macmillam Press, New York: 374 p. Walters, C. and J.-J. Maguire (1996). Lessons for stock assessment from the northern cod collapse. Reviews in Fish Biology and Fisheries 6: 125-137. Walters, C.J. and S.J.D. Martell (2004). Fisheries ecology and management. Princeton University Press, Princeton and Oxford: 399 p. Watson, R. and D. Pauly (2001). Systematic distortions in world fisheries catch trends. Nature 414(6863): 534-536. Weidner, D. and F. Arocha (1999). South America: Atlantic, Part A., Section 2 (Segment B). Brazil. In: Latin America, World swordfish fisheries: an analysis of swordfish fisheries, market trends, and trade patterns. Vol. IV. NMFS, Silver Spring, Maryland, Vol. IV: 237-628. Welcomme, R.L., R. Richards and G.S. Neiva (1979). Relatorio da missao sobre peixes ornamentais. PDP Serie Documentos Traduzidos 9: 1-41.  CHAPTER 2. Richness of common names of Brazilian marine fishes and its effect on catch statistics  2.1. Introduction  Fishing impacts are seen not only on target species, but also on non-target species caught as by-catch that is largely discarded. Decreasing trends in the biomass of some species may go unnoticed, as correct species identification may never have been assigned. In addition, the connection between common and scientific names may not be correctly established and different species may be combined in catch statistics, thus undermining stock assessments. This problem, which can remain concealed for a long time, is common in the multi-species fisheries of tropical developing countries.  Overcoming this problem requires an understanding of the connection between common and scientific names. One must be able to comprehend the way names are assigned to living beings. Berlin (1992) presents some principles that govern the naming process of animals and plants: commonness, ease of observation, large size relative to humans, and striking appearance. According to this author, these principles are language universals applying to all cultures. Palomares et al. (1999) corroborated these principles for Philippine fishes. Freire and Pauly (2003), investigating names of Brazilian marine fishes, could confirm only the first three of these principles: commonness, expressed in terms of commercial interest, with 78% of commercial species associated with at least one common name versus 26% of non-commercial species; ease of observation, indicating that 73-75% of easily seen reef-associated and pelagic  species were named; and size, with 79% of the large species receiving names against 50% of the small species. Striking appearance could not be confirmed, at least not using monotypy as a proxy, as suggested by Palomares et al. (1999).  Some scientists consider common names completely unnecessary and suggest they should not be included in scientific publications, reports or legislation. However, common names convey much information about what is known about each organism/species and it is the preferred way for people to refer to them in daily life. Paradoxically, common names can sometimes be more stable than scientific names (Robins et al., 1991). On the other hand, common names are associated with high local and spatial heterogeneity. This creates problems when dealing with catch statistics, especially in tropical and developing regions such as Brazil, where artisanal, multi-species fisheries are very important (Paiva, 1997; Freire, 2003).  The objective of this chapter is to investigate the richness of common names of Brazilian marine fishes, to assess the importance of commercial interest and ease of observation in the richness of common names, and to quantify the effect of the richness of common names on Brazilian catch statistics. The results presented here may contribute, as well, to an understanding of how fisheries induce losses of local biodiversity.  2.2. Material and methods  A database (hereafter referred to as NAMED AT) of 4,156 common names of 725 Brazilian marine fish species was compiled from 30 sources published between 1962 and 2000. It included names that ranged geographically from Para State, in northern Brazil, to Rio Grande do Sul State, in southern Brazil (Barcellos, 1962; Brandao, 1964; Ihering, 1968; Lima, 1969;  Anon., 1976; SUDENE, 1976; Carvalho and Branco, 1977; Figueiredo, 1977; CEPA-MA, 1978; Figueiredo and Menezes, 1978; Lima and Oliveira, 1978; Figueiredo and Menezes, 1980; Menezes and Figueiredo, 1980; Rosa, 1980; Chao et al, 1982; Santos, 1982; Nomura, 1984; Menezes and Figueiredo, 1985; Suzuki, 1986; Godoy, 1987; Martins-Juras et al, 1987; Soares, 1988; Ferreira et al, 1996; Ferreira et al, 1998; Santos et al, 1998; Carvalho-Filho, 1999; Ferreira, 1999; CEPENE, 2000; Figueiredo and Menezes, 2000; Szpilman, 2000). This extended database was constructed based on previous work by Freire and Pauly (2003), which resulted in a large expansion of the list of Portuguese common names of Brazilian marine fishes available in FishBase (www.fishbase.org). The State where the name is used was recorded in the database, when this information was available. The richness of common names was assessed as (1) number of common names per species, and (2) number of species per common name.  The number of common names per species was grouped into classes: 0, 1, 2-5, 6-10, 11-20, 21-30, and >30. Information on local commercial importance was obtained from CEPENE (1997; 1998), Carvalho-Filho (1999), and Szpilman (2000). Habitat type (pelagic, demersal, reef-associated, bathypelagic, bathydemersal, and benthopelagic) was used as a proxy for ease of observation and reflects the definition presented in FishBase (Froese and Pauly, 2000, and www.fishbase.org). See Appendix 1 for the description of each habitat type.  The association amongst number of common names, commercial importance, and habitat type was measured using multiple correspondence analysis - M C A (Greenacre and Blasius, 1994) and was performed using SAS Version 8.2.  Mean catches for the period 1995-2000, obtained in Chapter 3, were used to analyze the effect of the richness of common names in the Brazilian catch database (hereafter referred as CATCHDAT). This period was chosen because of the existence of an electronic catch database and because the catches were relatively stable throughout the period (Freire, 2003). This analysis followed three steps:  1) Identification of common names associated with the ten highest mean annual catches from Brazilian artisanal fisheries (1995-2000); 2) Identification of common names associated with the ten highest mean annual catches from Brazilian industrial fisheries (1995-2000); 3) Selection of ten common names with the highest associated number of species.  The catch recorded for one group by common name (e.g., 'linguado' or 'sardinha') was split equally amongst the species associated with that common name in each State, following the steps defined in Figure 2.1. The definition of industrial and artisanal fisheries is as presented in the Appendix 1.  2.3. Results  a) Richness of common names  Therichnessof common names of Brazilian marine fishes is very high, with an average of six common names per species. Although 208 species have only one common name, there is one extreme case where one species, Macrodon ancylodon, has 37 common names (Fig. 2.2a). In  contrast, there are 1,908 common names that refer to only one species. The worst case here is one common name 'linguado' (flatfish), which is used for 31 different species (Fig. 2.2b). Some of the common names such as 'linguado' and 'cacao' refer to species associated with five different families (Table 2.1). Many others are associated with at least two different families.  Table 2.1: Common names related to the highest number of species for the Brazilian marine realm (representing 25% of all species in the NAMEDAT database), and the respective families associated with each name. COMMON NAME 'Linguado' 'Manjuba' 'Cacao' 'Solha' 'Budiao' 'Sardinha' 'Moreia' 'Baiacu' 'Pescada' 'Voador' Total  # SPECIES 31 24 20 19 18 17 15 13 13 12 182  FAMILIES Achiridae, Bofhidae, Cynoglossidae, Paralichthyidae, Pleuronectidae Atherinidae, Clupeidae, Engraulidae Carcharhinidae, Lamnidae, Sphyrnidae, Squalidae, Triakidae Achiridae, Bothidae, Cynoglossidae, Paralichthyidae Labridae, Scaridae Clupeidae, Engraulidae Chlopsidae, Gobiidae, Muraenidae, Ophichthidae Diodontidae, Ostraciidae, Tetraodontidae Sciaenidae, Sphyraenidae Dactylopteridae, Exocoetidae  The richness of common names was related to the commercial importance of the species and habitat types, with commercial or easily visible species (reef-associated, pelagic, and demersal) receiving between 2 and 30 common names or even more (Figure 2.3). Species of no commercial interest were linked to only one common name, while no common name was associated with benthopelagic, bathypelagic, and bathydemersal species.  Common name Y  Catch = C  State 2  State 1 Catch > 0?  Catch > 0?  > No  Yes = C, V  No  V 5p. 2  v  Commercial?  Commercial?  Yes  No  31  Yes  No  C /2 t  Commercial?  Yes  > No  Yes = C Sp. 3  Commercial?  3L  C,/2  Catch > 0?  > No  Yes = C, Sp. 2  Sp. 1  State n  ±  No  3L  CJ2  2  Sp. 2  Commercial?  Commercial?  No  Yes  C /2  Sp. 1  Yes  No  Yes  C /3  Commercial?  No  ±  Yes C /3  C /3  n  n  n  V  C  spl  = C./2 + C /3 n  C  sp2  = C,/2 + C /2 + C /3 2  n  C /2 2  C 4 sp  C /3 n  Figure 2.1: Flowchart used to split catch (by common name) amongst all possible commercial species. ' C represents catch and 'n' represents the number of coastal States in Brazil (Total =17).  Number of common names per species  0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 Number of species per common name Figure 2.2: Richness of names of Brazilian marine fishes: a) Frequency of scientific species that have one to thirty-seven common names; b) Frequency of common names that correspond to a range of one to thirty-one species.  2  1 CM  E b  o 1 2 3 -2  -1  0  1  2  Dim 1 Figure 2.3: Relationship between number of common names (0, 1, 2-5, 6-10, 11-20, 21-30, >30), commercial importance (no information available, no commercial interest, commercially important), and habitat (demersal, pelagic, reef-associated, bathypelagic, benthopelagic, bathydemersal). Dim 1 and Dim 2 are the two axes obtained with the multiple correspondence analysis, which explain 100% of variation in the data. Dim 1 may be seen as the 'habitat dimension' and Dim 2 as the 'commercial dimension'.  b) Effect of common names' richness on catch statistics  Step I-Artisanal fisheries  The highest catches from Brazilian artisanal fisheries (1995-2000) are associated with the category 'shrimps' and 'other fishes', accounting for mean annual catches of about 39,500 tonnes (Table 2.2). These two broad terms are the first symptom of the low quality of the system responsible for gathering catch statistics in Brazil. In third place is the Atlantic seabob, Xiphopenaeus kroyeri, with a mean annual catch of 11,553 tonnes.  Catfish are in fourth place with a mean annual catch of 10,879 tonnes. These catfishes are recorded under the common name 'bagre', which may refer to ten different species, of which only six are recognized as commercially important: Aspistor quadriscutis, Bagre bagre, Cathorops spixii, Genidens genidens, Hexanematichthys herzbergii, and Hexanematichthys proops (Fig. 2.4). These six species are associated with 59 other common names: 'ariacu', 'ariassu', 'bagre branco', 'bagre cinzento', 'bagre do Natal', 'bagre guribu', 'bagre mandi', 'bagre parare', 'bagre-amarelo', 'bagre-bandeira', 'bagre-bandeirado', 'bagre-crucifixo', 'bagre-curiacu', 'bagre-da-areia', 'bagre-de-areia', 'bagre-de-manta',  'bagre-de-penacho',  'bagre-fidalgo', 'bagre-fita', 'bagre-gonguito', 'bagre-guri', 'bagre-guriacu', 'bagre-guru', 'bagre-leilao',  'bagre-mandim',  'bagre-sari',  'bagre-sari',  'bagre-urutu',  'bagrinho',  'bandeira', 'bandeirado', 'bandim', 'bei9udo', 'cangata', 'conguito', 'guria9u', 'guri-branco', 'gurijuba', 'ieiceca', 'iriceca', 'iriceca', 'irideca', 'irideca', 'iritinga', 'jahu amazonense', 'jandia-uva', 'jau', 'jundia-uva', 'parere', 'peixe fita', 'pira-bandeira', 'sarasara', 'sarassara', 'sargento', 'sari', 'sari-acii', 'sari-assu', 'uriacica amarelo', and 'uritinga'. Note that several names are very similar and these small differences reflect the use of these common names in oral tradition. The total catch for this group was split amongst all possible commercial species (Fig. 2.4). It is worth pointing out that three of those species would not be otherwise associated with any catches: Aspistor quadriscutis, Cathorops spixii, and Genidens genidens. Furthermore, species such as Hexanematichthys proops could be associated with annual catches as high as 3,777 tonnes.  Step II- Industrial fisheries The highest industrial catches are Brazilian sardine, skipjack, croaker, other fishes, and sardine, which together account for about 134,300 tonnes or 42% of total industrial catches  (Table 2.2). With the exception of skipjack, which is clearly linked to Katsuwonus pelamis, all the other four categories reveal the ambiguity in catch statistics from Brazil. 'Sardinha verdadeira' is normally associated with Sardinella brasiliensis, especially in southeastern Brazil, where the bulk of catches originates. However, 'Sardinha verdadeira' is also associated with four other species {Sardinella aurita, Opisthonema oglinum, Cetengraulis edentulus, and Anchovia clupeoides) in different States (Fig. 2.5). On the other hand, S. brasiliensis is also known by 13 other common names: 'biribiri', 'boca-torta', 'charuto', 'escamuda', 'manjuvao', 'maromba', 'sardinha', 'sardinha charuto', 'sardinha-azul', 'sardinha-de-galha', 'sardinha-do-  Table 2.2: Common names associated with the ten highest mean annual catches from Brazilian artisanal and industrial fisheries (1995-2000), based on CATCHDAT.  FISHERY Artisanal  Industrial  PORTUGUESE 'Camarao' 'Outros peixes' 'Camarao sete barbas' 'Bagre' 'Caranguejo' 'Corvina' 'Garajuba' 'Tainha' 'Serra' 'Peixe porco' 'Sardinha verdadeira' 'Bonito listrado' 'Corvina' 'Outros peixes' 'Sardinha' 'Cacao' 'Albacora' 'Camarao' 'Pescada olhuda' 'Sardinha laje'  ENGLISH Shrimp Other fishes Atlantic seabob Catfish Crab Croaker Mullet Total Brazilian sardine Skipjack Croaker Other fishes Sardine Shark Tuna Shrimp Weakfish Herring Total  CATCH (t) 19,959 19,488 11,553 10,879 10,382 9,811 8,878 8,075 6,817 6,366 112,208 65,424 24,276 15,512 19,388 9,699 8,109 7,647 7,563 7,262 6,973 171,852  Commercial  1741  Aspistor quadriscutis 1741  1885  Bagre bagre  1829  1870  >  2929  Bagre (10879 tonnes)  (1)  Cathorops spixii 1829  (15)  Genidens genidens  (15)  Hexanematichthys herzbergii (5)  386  2163 1777  Hexanematichthys proops 3777  Cathorops phrygiatus  (0) -  Genidens planifrons  0)  Hexanematichthys couma  (1) -  (22)  1870 1777  Non-commercial  (4)  Gurijuba Hexanematichthys passany (0) -  1  2000 Uritinga  Figure 2.4: Mean annual catch of 'bagre' (in tonnes) by artisanal fisheries in Brazil (1995-2000), split amongst all possible commercial species. Numbers in parentheses represent other names besides 'bagre' that each species is linked to. The other number in the box represents the total catch for each species, considering all common names they receive.  reino', 'sardinha-legitima', and 'sardinha-maromba'. Amongst all these names, only 'sardinha' is recorded in catch statistics and is associated with 16 other species besides S. brasiliensis.  Here, the catch data for 'sardinha' was split amongst the ten commercial species linked to that name (Fig. 2.5). One of these species (Anchoviella lepidentostole, also known as 'manjuba') presents one of the highest name richness (24). Its catch was split amongst 12 commercial species related to the name 'manjuba' and some of them may be associated with catches as high as 5,200 tonnes.  Commercial  I: 6 5 4 2 4 A: 399  Sardinha verdadeira I: 65424 ; A: 399 1:6101  Sardinella brasiliensis ( 1, 3A :) 1 3  Sardinha  71937  Sardinella aurita  (9)  Non-commercial A: 40  Others  (4)  40  (16)  I: 9 6 9 9 ; A : 3 9 3 8  1:1199,  10  A: 1285.  10  Odontognathus mucronatus ( 0 ) 2484  1199  Opisthonema oglinum ( 3, A3: ) 1 2 8 5  Anchovia clupeoides ( 6 )  Anchoviella lepidentostole ( 0 )  2924  5201  Anchoa spinifer ( 0 ) 450  Cetengraulis edentulus ( 1 2 ) 2924  I: 1 8 2 I: 1 1 9 9 A: 1285  Manjuba  t '  (24) A: 258  I: 4 1 3 9 ; A : 2 9 4 0 A : 3 4 1 „  I: 1 8 2  Anchoa s p p . ( 7 ) 341  A: 258  Lycengraulis grossidens ( 0 ) 228  Figure 2.5: Industrial (I) and artisanal (A) mean annual catch (in tonnes) of 'sardinha verdadeira' in Brazil (1995-2000) split amongst all possible species. Numbers in parentheses represent other names each species can receive in addition to the ones presented or the number of species associated with a common name. The group 'Others' includes Anchoviella guianensis, Brevoortia pectinata, Harengula clupeola, and Pellona harroweri. The group 'Anchoa spp.' includes A. januaria, A.filifera,A. tricolorm, A. lamprotaenia, A. marinii, A. lyolepis, and A. parva.  Step III- 'Linguado', the most diverse common name Even though 'linguado' does not figure as one of the most important species in terms of catch volume at a national scale, it is associated with the highest number of species, both commercial and non-commercial (Fig. 2.6). Only 13 species out of the total have no other common name associated with it besides 'linguado'. The remaining 18 species are interchangeably associated with 31 other common names.  Commercial  Non-commercial  Linguado  Achirus achims AramacS - Bothus ocellatus  <H)-i  Solha redonda  <KM>  r— Bothus robinsi  Aramaca  Cycbpsetta chittendeni -  Achirus lineatus Solha verdadeira  Cyclopsetta fimbriata  Linguado mexicano  Chascanopsetta lugubhs  Linguado remo Rodovalho  Citharichthys arenaceus  Solha dente de velho  — Citharichthys cornutus  Linguado preto — Monolene antillarum -  Catraio  Solha comprida  Citharichthys dinoceros —  Solha-aramaca  Oncoptems darwinii  Lenguado — Paralichthys brasiliensis - Paralichthys isosceles  — I Linguado-aramaca - Paralichthys orbignyana — Paralichthys patagonicus  Citharichthys macrops —  Solha linguada  Citharichthys spilopterus  — Lenguado-de-praia Linguado-de-praia  Linguado-de-areia  r Solha de dente  < >-(>-< i-e-s-  Solha linguado  Linguado dareia  Solha  Paralichthys triocellatus  - Syacium micrurum — Lingua-de-vaca <- Symphurus plagusia  V— Linguado-mulato  <M)-<>-  Tapa Linguado lixa Linguado macho  Etropus crossotus  —  Etropus intermedius  —  Etropus longimanus  —  Monolene sessilicauda  <)-<)!M)  Lingua-de-mulato Lingua-de-mulata  —  Engyophrys senta  Solha urumacara ~  Linguado-da-areia  Syacium papillosum  —  <)-  &  Paralichthys tropicus  —  Trinectes microphthalmus — Trinectes paulistanus  -  Verecundum rasile  -  1  Figure 2.6: Link between common and scientific names for all commercial and non-commercial species that receive the common name 'linguado' (flatfish).  The split of the total catch of 'linguado' amongst all species of commercial interest indicates that catches of some species associated only with that common name could be as high as 308 tonnes, as it is the case for Paralichthys orbignyana (Fig. 2.7 - right side). The same catch value would be associated with Paralichthys brasiliensis (Fig. 2.7 - left side), a species associated with nine other common names.  c) The case for standardization of common names  Only 37 species of Brazilian marine fishes have a unique common name that refers to no other species (Table 2.3). The rest of the species have more than one common name or share the same name with other species. To overcome this confusion, a list needs to be created containing all names linked to each species and indicating the States where they are used. A unique name would then be chosen from that list and declared as the 'official' name. The reasons for each specific choice must be given. The names presented in Table 2.3 could function as a starting point of such a list. Thus, the proposed list should deal first with species having increasingly higher richness of common names, i.e., one should deal first with species with 2 common names, 3, 4, and so on. Emphasis should be given in the first stage to species of commercial importance, which would contribute to an improvement in the statistical recording system of catch statistics. In cases where names are not available, they could be borrowed from the list of Portuguese names assembled by Sanches (1989) or translated from other languages to Portuguese.  Linguado (1604 tonnes) Achirus achirus 46  46  185,  Aramaca  Bothus ocellatus  Aramaca  Cyclopsetta chittendeni  Oncopterus darwinii  187,  Paralichthys brasiliensis  mexicano  Linguado  remo  Rodovalho  -  Linguado-preto  -  Syacium papillosum  Linguado  i—  -  308,  Solha verdadeira  Cyclopsetta fimbriata  Tapa  _4§_  Linguado lixa  Monolene antillarum  Solha  Solha-aramaca  Catraio  Lenguado-de-praia  Lenguado  Paralichthys isosceles  Linguado-de-praia  Linguado-aramaca  Linguado-de-areia  Linguado  46  46  -  Paralichthys orbignyana  dareia  308  Linguado-da-areia Solha de dente 46  Syacium micrurum  —  Symphurus plagusia  167  Lingua-de-mulato Lingua-de-mulata —  — Solha 126.  Paralichthys patagonicus  3—$•  linguado Linguado-mulato  !—  Lingua-de-vaca  —  1  Paralichthys thocellatus  46  Figure 2.7: Catch data (in tonnes) split amongst species that share the same common name ('linguado'), based on an average for the period 1995-2000 (Brazilian marine industrial and artisanal fisheries).  Table 2.3: List of species presenting one unique common name in Brazil, based on NAMEDAT. ENGLISH NAME SPECIES PORTUGUESE NAME Twospot cardinalfish Apogon pseudomaculatus 'Toto' Canthidermis maculatus 'Cangulo machado' Spotted oceanic triggerfish Finetooth shark Carcharhinus isodon 'Cacao dente liso'* Oceanic whitetip shark Carcharhinus longimanus 'Galha branca'* Caribbean reef shark Carcharhinus perezi 'Cacao coralino' 'Cacao noturno'* Night shark Carcharhinus signatus Spotted burrfish 'Baiacu de espinho pintado'* Chilomycterus atringa Peacock cichlid Cichla ocellaris 'Tucunare' 'Congro dentao'* Manytooth conger Conger triporiceps Peruvian pigfish*** Congiopodus peruvianus 'Peixe dragao'* Striped burrfish 'Baiacu de espinho listrado'* Cyclichthys schoepfi Sand stargazer Dactyloscopus tridigitatus 'Mira ceu da areia'* Mulatto conger Enchelycore nigricans 'Moreia negra'* Snappers Etelis oculatus 'Pargo mariquita' Channel scabbardfish Evoxymetopon taeniatus 'Tirante' Brazilian basslet 'Loreto' Gramma brasiliensis Smallmouth grunt Haemulon chrysargyreum 'Cocoroca boquinha'* Spanish grunt Haemulon macrostoma 'Cocoroca espanhola'* Yellowhead wrasse Halichoeres garnoti 'Gudiao amarelo'** Banded cichlid 'Acara preto'* Heros severum Cookiecutter shark Isistius brasiliensis 'Cacao luminoso' Longfin mako 'Anequim preto'* Isurus paucus Lemon shark Negaprion brevirostris 'Cacao limao'* Orange bellowsfish Notopogon fernandezianus 'Beija flor'* Spotted snake eel 'Mucum pintado' Ophichthus ophis None Ophioblennius atlanticus 'Punaru' Lancer dragonet Paradiplogrammus bairdi 'Peixe pau' Yellowfin river pellona Pellona flavipinnis 'Sardinha dourada' Dusky cardinalfish 'Cardeal pintado'* Phaeoptyx pigmentaria Cardinal soldierfish 'Fusquinha' Plectrypops retrospinis Stout beardfish 'Barbudo olhao' Polymixia nobilis Whale shark 'Tubarao baleia' Rhincodon typus Redband parrotfish Sparisoma aurofrenatum 'Budiao manchado'* Beaugregory 'Gregory' Stegastes leucostictus Cocoa damselfish 'Donzela cacau'* Stegastes variabilis Spotfin dragonet 'Mandarim' Synchiropus agassizii Atlantic torpedo 'Torpedo' Torpedo nobiliana *A11 these names had the hyphen removed; The original name was gudiao-amarelo; Obvious common name, if new coinage, given the family name.  Robins et al. (1991) list the criteria used in the standardization process of common names of North American fishes (updated in Nelson et al., 2004). These criteria may be followed, as they have been used for more than 50 years. Preference could be given for simple and descriptive names. Names tied to scientific names, the ones that include the word 'common', and names that honour people or are offensive should be avoided. The spelling available in the most widely used Portuguese dictionary in Brazil - Aurelio (Ferreira, 1999) - would be the best choice amongst the names available. Two additional criteria could be used: no inclusion of hyphens (to avoid different spellings) and the first letter of the common name should be capitalized. According to Joseph S. Nelson (pers. comm., Dept. Biological Sciences, University of Alberta, Canada), the use of names with the first letter in lower case has generated some problems when, for example, adjectives are part of the name.  One example of the process of selection of a unique name, based on criteria similar to those of Robins et al. (1991), is presented for Balistes carolinensis (Grey triggerfish), which is presently connected to 21 common names: 'cangulo' (from an African language and used in 6 States), 'peixe porco' (Latin, 14 States), 'cangulo papo-amarelo' (African, 9), 'capado' (Latin, 9), 'peroa' (Tupi, 9), 'cangulo-da-parede' (African, 1), 'cangulo-de-Fernando' (African, 1), 'peroatinga' (Tupi-guarani, 1), 'acara-fuso' (Tupi), 'acara-moco' (Tupi), 'acaramucu' (Tupi), 'acarapicu' (Tupi), 'acarapucu' (Tupi), 'cangulo-branco' (African), 'cangurro' (African), 'fantasma' (Greek), 'maracuguara' (Tupi-guarani), 'perua' (Tupi), 'piraaca' (Tupi-guarani), 'pira-aca' (Tupi-guarani), and 'pirua' (Tupi). The number of States where the name is used and its contribution to the diversity of languages could be used as initial criterion to choose the official name. In this case, 'cangulo' and 'peixe porco' would be the best candidates as they are used in almost all States. However, these two names are too general, with no descriptive  power at the species level. Moreover, they are associated with six and 11 different species, respectively. 'Capado', 'cangulo papo amarelo', and 'peroa' are the next most frequent names, but they are also associated with Batistes vetula. 'Peroatinga' is recorded in only one State, but it is not used for any other species. 'Peroatinga' originated from Tupi-guarani and would thus contribute to maintaining the diversity of languages amongst the common names, representing a good choice for an official name.  The national official list of common names proposed here would be appropriate whenever species are dealt with in a national context (in scientific publications or reports), in catch statistics, and in legislation.  2.4. Discussion  Two interconnected concepts and their implications have been extensively discussed worldwide: biodiversity and risk of extinction. More recently, the risk of extinction of marine species has been estimated. It appears that both artisanal and industrial fisheries are capable of pushing species towards extinction (Dulvy et al., 2003). As a signatory country to the Convention on Biological Diversity, Brazil is committed to reduce the rate of biodiversity loss by the year 2010 (see www.biodiv.org). Although there is an intense effort towards quantifying biodiversity in Brazilian territory and adjacent waters (MMA, 1998; Baer, 2001; Sabino and Prado, 2003), Brazil is still far from being able to assess how fisheries may be contributing to biodiversity loss.  The lack of accuracy in catch statistics can also have serious implications, as some species may have been caught for years without information being recorded. A series of local  depletions can remain unnoticed, with the process ending with global extinction (Pitcher, 2001). Scarus guacamaia, a parrotfish once distributed throughout the tropical portion of the Brazilian coast, is considered extinct in Brazil (Ferreira et al, 2005). The authors consider that spearfishing probably had an important role in the process of extinction of this species. The national database cannot be used to infer about the influence of fishing on the extinction due to the underestimation of catches that will be addressed in Chapter 3. Additionally, the catch database compiled here (CATCHDAT) indicates that in 1978/1979, two tonnes of 'papagaio' (parrotfish) were caught only in Pernambuco State (no register for other States). 'Papagaio' refers to seven species occurring in Brazil: Bodianus pulchellus, B. rufus, Halichoeres cyanocephalus, Sparisoma chrysopterum, Sparisoma viride, Aetobatus narinari (ray), and the extinct species Scarus guacamaia. As it stands, it is not possible to indicate how much of this total catch was associated with S. guacamaia, if at all. Balistes vetula (queen triggerfish) is considered threatened by the World Conservation Union - IUCN. Aquarium fisheries have caught this species in waters off Ceara State (Monteiro-Neto et al, 2003), but its participation in the total commercial catches in Brazil is not known. This species is locally known as 'peixe gatilho', 'pirua', 'peixe porco', and 'peroa'. The latter two were associated with an annual catch of 8,212 tonnes, but again there is no indication of the share of B. vetula in this total.  Other species may be associated with catches higher than thought. Sardinella brasiliensis catches, for example, were increased by 9% when catches attributed to the category 'sardinha' were split evenly amongst different commercial species (Figure 2.5). This stock is one of the most important in the country and declined severely, with catches dropping from about 228,000 tonnes in 1973 to 32,080 tonnes in 1990 (Dias Neto and Dornelles, 1996). For a stock  with low biomass, and which fisheries managers would like to see recovering, a catch increase of 9% is no small matter.  Catches recorded as 'catfish' could be split in up to six species from five different genera. Some of these species may have annual catches of almost 3,800 tonnes, if catches assigned to other common names are combined. Given that we are dealing with an artisanal fishery, this difference is too high to be neglected. A similar situation occurs for flatfish, although with lower catches (1,604 tonnes). This total may be associated with 14 different species, with catches as high as 308 tonnes for some of these species.  The standardization of common names suggested here could help to avoid this problem and should be achieved through a consultation process including all parties directly or indirectly involved with fish and fisheries: universities, government institutions (such as the Brazilian Institute for Environment and Renewable Natural Resources/IBAMA and the Special Secretary for Aquaculture and Fisheries/SEAP), non-governmental organizations, associations of recreational and commercial fishers, the Brazilian Society of Ichthyology (SBI), the Brazilian Society for the Study of Elasmobranchs (SBEEL), etc. There is no reason to think that an attempt to standardize common names of Brazilian fishes, within a diverse cultural context, would be easy. Besides, the standardization should be seen as a necessary, but not sufficient condition, for a better catch data system.  The understanding of how people name fishes (and life forms in general) would help in the selection process of official names. In this regard, Berlin (1992) and, more generally, Lakoff (1987) present a significant contribution on the principles involved in the naming process and  categorization. More specifically, Begossi and Garavello (1990), Begossi and Figueiredo (1995), Costa-Neto and Marques (2000), Mourao (2000), and Seixas and Begossi (2001) have dealt with categorization of fish in local communities along northern, northeastern, and southeastern Brazil. At a national level, Freire and Pauly (2003) analyzed the naming process for Brazilian marine fishes. However, no attempt was made here to consider the influence of this process in the selection of official names, except for showing the effect of the commercial importance in the richness of common names (also previously recorded by Begossi and Garavello, 1990; Mourao, 2000 in some localities), and the effect of habitat types as representing accessibility. It must be kept in mind that the standardization proposed here is not intended to extinguish local linguistic diversity, but to avoid misinterpretations of national data and their undesirable consequences.  Some of the sources of uncertainty related to this work are: overestimation or (more probably) underestimation of catches, misidentification of species, non-exhaustive list of commercial species, list of common names not properly attributed to one State because of the lack of local fish name lists, and the equal weights used to split catches amongst common names available per State. There will be many ways of dealing with this uncertainty in the future: improving landing data through the incorporation of discards or raising up the available data based on any indication of bias; checking the commercial status of species with local experts; accessing lists of common names used by local authorities; and estimating better weights (with the help of local experts) to split the catch amongst species. As soon as more local data are incorporated in the common names database, an analysis of the impact of the richness of common names can be performed in more detail for each State.  2.5. Bibliography  Anon. (1976). Pesquisas ictiologicas nas aguas do norte do Brasil. Revista Nacional de Pesca XVII(154): 30-32. Baer, A. (2001). Aquatic biodiversity in the national biodiversity strategy and action plans of signatories to the Convention on Biological Diversity. World Fisheries Trust, Victoria, Canada: 140 p. Barcellos, B.N. (1962). Nomes comuns dos peixes da costa do Rio Grande do Sul e seus correspondentes em sistematica. Boletim do Instituto de Ciencias Naturais, Porto Alegre(15): 7-20. Begossi, A. and J.L. Figueiredo (1995). Ethnoichthyology of southern coastal fishermen: cases from Buzios Island and Sepetiba Bay (Brazil). Bulletin of Marine Science 56(2): 710717. Begossi, A. and J.C. Garavello (1990). Notes on the ethnoicthyology of fishermen from the Tocantins River (Brazil). Acta Amazonica 20(unico): 341-351. Berlin, B. (1992). Ethnobiological classification. Principles of categorization of plants and animals in traditional societies. Princeton University Press, Princeton, New Jersey: 335 PBrandao, J.M. (1964). Glossario de nomes dos peixes: sistematico, portugues, ingles. Boletim de Estudos de Pesca 4(6): 1-59. Carvalho, V.A. and R.L. Branco (1977). Relacao de especies marinhas e estuarinas do nordeste brasileiro. P.D.P. Documentos Tecnicos(25): 1-60. Carvalho-Filho, A. (1999). Peixes: costa brasileira. Melro, Sao Paulo: 320 p. CEPA-MA (1978). Piano estadual de desenvolvimento da pesca. Subsidios ao IV Piano Nacional de Desenvolvimento da Pesca 1979/85. Secretaria da Agricultura. Comissao Estadual de Planejamento Agricola (CEPA-MA), Sao Luis, Brazil: 175 p. CEPENE (1997). Estatistica da pesca - 1996. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 120 p.  CEPENE (1998). Estatistica da pesca - 1997. Brasil - Grandes regioes e unidades da federacao. Centre- de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 84 p. CEPENE (2000). Estatistica da pesca - 1999. Brasil - Grandes regioes e unidades da federacao. Centro de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 104 p. Chao, L.N., L.E. Pereira, J.P. Vieira, M.A. Bemvenuti and L.P.R. Cunha (1982). Relacao preliminar dos peixes estuarinos e marinhos da Lagoa dos Patos e regiao costeira adjacente, Rio Grande do Sul, Brasil. Atlantica 5: 67-75. Costa-Neto, E.M. and J.G. Marques (2000). Faunistic resources used as medicines by artisanal fishermen from Siribinha beach, State of Bahia, Brazil. Journal of Ethnobiology 20(1): 93-109. Dias Neto, J. and L.D.C. Dornelles (1996). Diagnostico da pesca maritima do Brasil. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais, Brasilia: 165 p. Dulvy, N.K., Y . Sadovy and J.D. Reynolds (2003). Extinction vulnerability in marine populations. Fish and Fisheries 4(1): 25-64. Ferreira, A.B.d.H. (1999). Dicionario Aurelio Eletronico - Seculo XXI. Rio de Janeiro, Brasil, Lexicon Informatica Ltda. Ferreira, B.P., F.C. Correa and A.N. Ferraz (1998). Relacoes morfometricas em peixes recifais da zona economica exclusiva brasileira, regiao nordeste. Boletim Tecnico Cientifico do CEPENE 6(1): 61-76. Ferreira, C.E.L., J.L. Gasparini, A. Carvalho-Filho and S.R. Floeter (2005). A recently extinct parrotfish species from Brazil. Coral Reefs 24: 128. Ferreira, E.J.G., J. Zuanon and G.M. Santos (1996). A list of commercial fish species from Santarem, State of Para, Brazil. Naga, the ICLARM Quaterly 19(3): 41-44. Figueiredo, J.L. (1977). Manual de peixes marinhos do sudeste do Brasil. I. Introducao. Cacoes, raias e quimeras. Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 104 p.  Figueiredo, J.L. and N.A. Menezes (1978). Manual de peixes marinhos do sudeste do Brasil. II. Teleostei (1). Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 110 PFigueiredo, J.L. and N.A. Menezes (1980). Manual de peixes marinhos do sudeste do Brasil. III. Teleostei (2). Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 90 PFigueiredo, J.L. and N.A. Menezes (2000). Manual de peixes marinhos do sudeste do Brasil. VI. Teleostei (5). Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 116 PFreire, K.M.F. (2003). A database of landing data on Brazilian marine fisheries from 1980 to 2000. Fisheries Centre Research Reports 11(6): 181-189. Freire, K.M.F. and D. Pauly (2003). What's in there? Common names of Brazilian marine fishes. Fisheries Centre Research Reports 11(1): 439-444. Froese, R. and D. Pauly (2000). FishBase 2000: concepts, design and data sources. ICLARM, Los Banos, Laguna, Philipinnes: 344 p. Godoy, M.P. (1987). Peixes do estado de Santa Catarina. Editora da UFSC, Florianopolis, Brazil: 571 p. Greenacre, M.J. and J. Blasius (1994). Correspondence analysis in the social sciences: recent developments and applications. Academic Press, London; San Diego, CA: 370 p. Ihering, R.v. (1968). Dicionario dos animais do Brasil. Editora Universidade de Brasilia, Brasilia: 790 p. Lakoff, G. (1987). Women, fire, and dangerous things: what categories reveal about the mind. University of Chicago Press, Chicago: 614 p. Lima, H.H. (1969). Primeira contribuicao ao conhecimento dos nomes vulgares de peixes marinhos do nordeste brasileiro. Boletim de Ciencias do Mar 21: 1-20. Lima, H.H. and A.M.E. Oliveira (1978). Segunda contribuicao ao conhecimento dos nomes vulgares de peixes marinhos do nordeste brasileiro. Boletim de Ciencias do Mar 29: 126.  Martins-Juras, L.A.G., A.A. Juras and N.A. Menezes (1987). Relacao preliminar dos peixes da Ilha de Sao Luis, Maranhao, Brasil. Revista Brasileira de Zoologia 4(2): 105-113. Menezes, N.A. and J.L. Figueiredo (1980). Manual de peixes marinhos do sudeste do Brasil. IV- Teleostei (3). Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 96 PMenezes, N.A. and J.L. Figueiredo (1985). Manual de peixes marinhos do sudeste do Brasil. V- Teleostei (4). Museu de Zoologia, Universidade de Sao Paulo, Sao Paulo, Brazil: 105 PM M A (1998). First national report for the convention on biological diversity - Brazil. Ministerio do Meio Ambiente, Brasilia: 270 p. Monteiro-Neto, C , F.E.A. Cunha, M.C. Nottingham, M.E. Araujo, I.L. Rosa and G.M.L. Barros (2003). Analysis of the marine ornamental fish trade at Ceara State, northeast Brazil. Biodiversity and Conservation 12: 1287-1295. Mourao, J.S. (2000). Classificacao e ecologia de peixes estuarinos por Pescadores do estuario do rio Mamanguape - PB. Programa de Pos-Graduacao em Ecologia e Recursos Naturais, Universidade Federal de Sao Carlos, Sao Carlos, Brazil. PhD Thesis: 156 p. Nelson, J.S., E.J. Crossman, H. Espinosa-Perez, L.T. Findley, C.R. Gilbert, R.N. Lea and J.D. Williams (2004). Common and scientific names of fishes from the United States, Canada, and Mexico. American Fisheries Society, Special Publication 29, Bethesda, Maryland: 386 p. Nomura, H. (1984). Nomes cientificos dos peixes e seus correspondentes nomes vulgares. In: H. Nomura (Ed.). Dicionario dos peixes do Brasil. Editerra, Brasilia, Brasil: 27-63. Paiva, M.P. (1997). Recursos pesqueiros estuarinos e marinhos do Brasil. UFC, Fortaleza, Brazil: 278 p. Palomares, M.L.D., C.V. Garilao and D. Pauly (1999). On the biological information content of common names: a quantitative case study of Philippine fishes, Proceedings of the 5  th  Indo-Pacific Fish Conference, Societe Francaise d'Ichtyologie & Institut de Recherche pour le Developpement: 861-866.  Pitcher, T. (2001). Fisheries managed to rebuild ecosystems? Reconstructing the past to salvage the future. Ecological Applications 11(2): 601-617. Robins, C.R., R.M. Bailey, C.E. Bond, J.R. Brooker, E.A. Lachner, R.N. Lea and W.B. Scott (1991). Common and scientific names of fishes from the United States and Canada. American Fisheries Society, Special publication 20: 183 p. Rosa, R.S. (1980). Lista sistematica de peixes marinhos da Paraiba. Revista Nordestina de Biologia 3(2): 205-226. Sabino, J. and P.I. Prado (2003). Avaliacao do estado do conhecimento da diversidade biologica do Brasil. Vertebrados. Versao preliminar. Diretoria de Conservacao da Biodiversidade, Brasilia: 123 p. Sanches, J.G. (1989). Nomenclatura portuguesa de organismos aquaticos. Proposta para normalizacao estatistica. Instituto Nacional de Investigacao das Pescas, N°14, Lisboa: 322 p. Santos, E. (1982). Nossos peixes marinhos (Vida e costume dos peixes do Brasil). Editora Itatiaia Limitada, Belo Horizonte, Brasil: 265 p. Santos, M.C.F., A.E.T.S. Freitas and M.M. Silva (1998). Composicao da ictiofauna acompanhante da pesca de camarao em Tamandare/PE e Pontal do Peba/AL. Boletim Tecnico Cientifico do CEPENE 6( 1): 47-60. Seixas, C.S. and A. Begossi (2001). Ethnozoology of fishing communities from Ilha Grande (Atlantic Forest coast, Brazil). Journal of Ethnobiology 21(1): 107-135. Soares, L.H. (1988). Catalogo dos peixes do litoral do Estado do Rio Grande do Norte. Boletim do Departamento de Oceanografia e Limnologia do Centro de Biociencias da Universidade Federal do Rio Grande do Norte 7: 1-39. SUDENE (1976). Pesquisas dos recursos pesqueiros da plataforma continental maranhense. Serie Estudos de Pesca 6: 1-67. Suzuki, C.R. (1986). Guia de peixes do litoral brasileiro. Edicoes Maritimas, Rio de Janeiro, Brazil: 394 p. Szpilman, M . (2000). Peixes marinhos do Brasil: Guia pratico de identificacao. Instituto Ecologico Aqualung, Rio de Janeiro: 288 p.  CHAPTER 3. Analysis of catch data from marine fisheries off Brazil  3.1. Introduction  Fishery management aims to maintain fished stocks at sustainable levels, despite the lack of consensus on what 'sustainability' means. The stock size and species composition found in fished areas at the present have certainly been altered by decades or even centuries of fishing pressure (Jackson et al., 2001). To better understand these changes, it is necessary to have at least some indirect indicators, such as time series of catch and effort data, for those cases where no direct information on stock abundance is available. However, one should be aware that an abundance trend based on catch and effort data may issue conflicting signs about the stock state when there is, for example, a range collapse in its distribution area (Walters and Martell, 2004).  The time series of these indicators should be long enough to help us understand issues such as the "shifting baseline syndrome", directly associated with the way in which successive cohorts of scientists perceive the health of a stock based on increasingly depleted stocks (Pauly, 1995). If we do not accept and understand the effects and implications of this phenomenon, we will continue attempting to preserve current stock levels, which may not be a sustainable solution. Instead, we may want to rebuild stocks and ecosystems (Pitcher, 2001). Jackson et al. (2001) point out that short time series also fail to detect some long-term environmental shifts and their  impact on stocks, which consequently influence our misperception of the depletion process of most fishing stocks worldwide.  Detailed, long series of catch and effort data are lacking or not easily available in many countries, including Brazil, with the exception of landing data at the national level available from the Food and Agriculture Organization (FAO) and from the International Commission for the Conservation of Atlantic Tunas (ICCAT) for tuna and tuna-like fishes. Aragao (1997) presents an overview of the evolution of data collection systems related to the Brazilian fishing sector and this overview will help to understand why such a detailed database does not exist. Before 1967, the Production Statistical Service (SEP) of the Ministry of Agriculture was responsible for assembling landing data collected by the IBGE (Brazilian Institute of Statistics and Geography), State institutions, and the Ministry of Finance. In 1967, SUDEPE created the Statistical Advisory Board, which proposed a new plan for data collection. However, it was never implemented. In 1968, the PDP Program (SUDEPE/FAO) began collecting landing data in the southernmost region and later extended its activities to other regions. In the early 1970s, PDP and SUDENE (Superintendence for the Development of the Northeastern Region) collaborated to collect data from the northeastern region. When PDP became the sole responsibility of SUDEPE, in 1980, the system of data collection began to deteriorate. During this period IBGE continued to collect data, but their quality was considered low.  One year after the demise of SUDEPE and the establishment of IBAMA, the latter developed a system of data collection that began in Ceara (ESTATPESCA), northeastern Brazil. This system was gradually extended to other States of the northeastern region, but was not able to encompass all its States. Some States did not collect any data during this transitional period  due to the lack of human and financial resources. At present, data collection is highly heterogeneous, being performed by IBAMA, State institutions, and/or universities. IBAMA remains responsible for gathering data from all these institutions and presents them in the form of national bulletins ('Estatistica da Pesca'). One of IBAMA's branches, CEPENE is responsible for gathering data for northeastern Brazil and publishes them as regional bulletins. Only the 2001 CEPENE Bulletin is available online. With the recent political changes, the future of data collection from the fishing sector is unclear.  Some argue that the importance of the artisanal fishery in Brazil is one of the factors leading to poor data collection (Paiva, 1997). Others attribute this difficulty to problems in communication and organizational structure (see e.g. Marcilio and Lisanti, 1973). For the fishing sector, this is magnified by the lack of institutional interest in an activity with low contribution (0.25%) to the gross domestic product (FAO, 2002b), by the shortage of financial and specialized human resources, and probably by unstable institutional arrangements.  A complete assessment of the state of marine resources requires that all extractions are properly documented. Recreational fisheries, for example, are associated with expenditures of US$ 5-38 billion worldwide (Cowx, 2002), but there is no precise estimate of global catches as many countries do not have the mandate to record their catches. Recreational catches may be higher than those from commercial fisheries in some areas (Gentner and Lowther, 2002) and differentially affect stocks at risk (Coleman et al., 2004). Ornamental fisheries are also a growing industry with a worldwide export value of about US$ 350 million (Hardy, 2003). Most of the marine ornamental fishes are caught in the wild as opposed to the freshwater species, which are bred in captivity (Andrews, 1990), putting an additional pressure on marine  resources. H. Bleher (cited in Andrews, 1990) estimates that 150 million fishes are traded in the ornamental market each year. Catches from subsistence fisheries are often high in developing countries and at the same time harder to obtain due to the highly dispersed fishing grounds and landing sites. Research is also responsible for some extraction, which normally is not incorporated in national databases of total catches probably due to the low figures in relation to other fisheries. There is also a growing concern with the magnitude of catches from illegal, unreported and unregulated fishing (IUU) and its impact on the sustainability of fish stocks (FAO, 2002c). This indicates that the most basic data required to access the health of stocks, i.e. total catches, are underestimated in many countries.  The goal of the present chapter was to analyze the catch data available for marine Brazilian fisheries and to assess the possibility of its use to indicate the state of the stocks. The following specific objectives were addressed:  1) to compile and to document annual landing data originatingfromBrazilian marine fisheries per State and per fishery type for the period 1978-2000; 2) to compare the database compiled in (1) with other existing databases at a national scale; 3) to assess the occurrence of 'fishing down the food web' in Brazil; 4) to identify some sources of underestimation in order to lead to further improvement of the database compiled here.  3.2. Material and methods  Annual landing data from Brazilian commercial marine fisheries were compiled and encoded in Microsoft Access for the period 1978-2000 by State, by fishery type (artisanal and industrial), and by species or group of species (Tables 3.1 and 3.2).  Table 3.1: Structure of the ACCESS database of landing statistics originatingfromBrazilian marine fisheries. DESCRIPTION  VARIABLE 1. Year  1978-2000  2. State  Amapa, Para, Maranhao, Piaui, Ceara, Rio Grande do Norte, Paraiba, Pernambuco, Alagoas, Sergipe, Bahia, Espirito Santo, Rio de Janeiro, Sao Paulo, Parana, Santa Catarina, and Rio Grande do Sul  3. Fishery  Artisanal or Industrial  4. Species  By common name  5. Landings  Tonnes  6. Source  All sources are listed in Table 3.2  Table 3.2: Sources used to compile landing statisticsfromBrazilian marine fisheries. PERIOD  FREQUENCY  SOURCES  FORMAT  1978-1979  Annual  Paper  (SUDEPE, 1980; 1981)  1980  Annual  Paper  (B3GE, 1980)  1981-1989  Semi-annual  Paper  (IBGE, 1981; 1982a; b; 1983a; b; 1984a; b; 1985a; b; 1986a; b; 1987a; b; 1988a; b; 1989a; b)  1990-1997  Annual  Paper  (CEPENE, 1995a; b; c; d; e; 1997a; b; 1998)  1998  Annual  Electronic  IBAMA (G.C. dos Santos, pers. comm.)  1999  Annual  Paper  (CEPENE, 2000b)  2000  Annual  Electronic  IBAMA (S. Bezerra, pers. comm.)  After encoding the database (called CATCHDAT hereafter), the correspondence between the common names presented in the original source and the scientific name was established, using the decision diagram illustrated in Figure 3.1. The general database of common and scientific names (I in Fig. 3.1) was created only for this study and includes molluscs, crustaceans, fishes, turtles, and whales. The database of fish names (II in Fig. 3.1) includes 4,172 common names associated with 725 species of marine and estuarine species, and represents an extension of the database presented in Freire and Pauly (2003) and discussed in Chapter 2. After applying the process illustrated in Figure 3.1, seven species remained unknown: 'ubaroba' and 'miracu' (Rio de Janeiro State), 'papa fina' and 'papuda' (Bahia), 'sagra' (Parana), and 'tapa pomba' (Santa Catarina).  The database compiled here was compared with the FAO database (www.fao.org; FISHSTAT) and with ICCAT databases TASK I, TASK II, and CATDIS (www.iccat.es), all of them available online. TASK I includes all catches of tunas, tuna-like fishes, and sharks, by gear, region, and flag (no effort data); TASK II presents catch (both number and weight) and effort data for the main species and includes spatial information (latitude and longitude); and CATDIS raises landings originating from TASK II to total landings and also includes spatial information (latitude and longitude; no effort).  The mean trophic level (TL) of the catches was estimated based on the information on the diet of each species, as compiled in Chapter 4 and complemented with data from FishBase (www.fishbase.org) and Opitz (1996):  Original reports with common names r Initial landing database Construction of a small database (I) of common names based on CEPENE (1997a,b; 1998; 1999a,b,c,d,e,f,g,h) Was the common name of the landing database present in (I)? N Check the large database (II) of common names of both commercial and non-commercial species  Scientific name in (I) used  Was the common namefromthe landing database present in (II)? N Consultation of online sources and local experts  Is that species considered of commercial interest? (Based on Carvalho-Filho, 1999; Szpilman, 2000) N  Scientific name not considered  Scientific name in (IT) used in the landing database  FINAL LANDING DATABASE Figure 3.1: Decision diagram on the correspondence between common and scientific names for commercial species to obtain the final landing database. The database of common names (IT) is available in FishBase (www.fishbase.org).  TL, = \ + Y '  DC -TL 'J  Z _ i  u  J  i  7=1  m  m  ;=i  i=i  where DC,y represents the diet composition of predator /, j is the prey, Y,* are landings of species i in year k, and m is the number of species or group of species caught in year k (Pauly et al, 2001). Note that categories such as 'outros peixes', 'caico' and 'mistura', all representing unidentified fishes, were not included in this analysis due to the impossibility of assigning them a precise trophic level. A Fishing-in-Balance (FiB) index (Pauly et al, 2000) was calculated in order to assess if changes in the mean trophic level were compensated by changes in catches: FIB = \og(Y • (1 / TE) >) - log(7 • (1 / TE) °) TL  k  k  TL  0  where k refers to year, 0 = baseline year (1978), Y = catch, TL = mean trophic level in the catch, and TE = transfer efficiency between trophic levels = 0.1 (based on Pauly and Christensen, 1995).  3.3. Results and discussion  a) Commercial fisheries  Comparing databases Total landings obtained from the database compiled in this chapter represent the sum of data related to the seventeen States that record marine landings from artisanal and industrial fisheries in Brazil and were similar to data available from the FAO database for the period  1980-1988 (Fig. 3.2). The latter showed a peak of 756,000 tonnes landed in 1985 and a decline after that year, reaching a total of 567,687 tonnes in 2000. This pattern follows the declining trend of global catches discussed in Pauly et al. (2002). The database compiled in this chapter is also able to detect this declining trend, even though there was an increased discrepancy between the landings from these two sources after 1988. This discrepancy is partially associated with higher landings of large pelagics (tuna, swordfish, billfishes) recorded by FAO after revising catches for this group in collaboration with ICCAT; the national bulletins used in the compilation of the landings database compiled here contain underestimates of catches from longline fisheries. Most of the discrepancy is explained by catches of 'marine fishes nei' (nei = not elsewhere identified), as FAO has included, since 1995, 100,000 tonnes of estimated subsistence and recreational catches under this category (FAO, 2002a). However, neither the basis for such estimate nor the reasons for differences in previous years (1989-1994) are stated.  800 -i  0 -I 1977  1  1  1  1982  1987  1992  r— 1997  Figure 3.2: Landing data for Brazilian marine fisheries from this database and from FAO database FISHSTAT (www.fao.org) for 1978-2000.  The database presented here has some advantages in relation to the FAO database: the breakdown per State, allowing for the allocation of landings to the three Brazilian large marine ecosystems (North, East, and South), the distinction between landings originating from industrial and artisanal fisheries, and more detailed information per species. Some problems were detected in the linkage between landings recorded in the FAO database and landings recorded using Portuguese common names in national bulletins compiled here. Landings for 1995 were analyzed in detail and indicate that most differences are related to the loss of detailed information, but in some cases, catches are attributed to the wrong species. Some of these differences are highlighted as follows:  •  'agulha' (halfbeak) landings were attributed only to ballyhoo halfbeak (Hemiramphus brasiliensis), when in fact more species are caught; 'agulha branca' landings were not included;  •  Atlantic bonito landings are lower than those presented in national bulletins;  •  'Lagosta' (lobster) catches were attributed to Caribbean spiny lobster (Panulirus argus), when in fact only 80% is expected to be P. argus and 20% would be P. laevicauda (Smoothtail spiny lobster) (Dias Neto and Dornelles, 1996). More recently a third species has been caught around oceanic islands, Panulirus echinatus, but catch rates are very low (Lins-Oliveira and Vasconcelos, 2004).  •  'barbigao', 'chubinho', 'sarnambi', and 'vieira' were combined with 'outros moluscos' (other molluscs) in the category 'marine molluscs', thus eliminating information on actual species caught;  •  landings for Patagonian grenadier (Macruronus magellanicus) were included, even though this species is not recorded for Brazil (www.fishbase.org);  •  landings for Scyllaridae were not recorded;  •  'caconete' and 'machote' landings were not included in shark landings;  •  'betara', 'batera', 'goete', 'Maria Luiza', 'tortinha' and 'pescadinha' were not included in croakers or drums (Sciaenidae), which implies accuracy loss; the same loss was observed for groupers, snappers, and clupeoids.  The comparison with ICCAT database is restricted to tuna and tuna-like fishes and requires an analysis of the three subsets made available through the ICCAT webpage (TASK I, TASK II, and CATDIS). Landings originating from all vessels that carry Brazilian flag (national and leased) and recorded in TASK I are the highest and close to those recorded in CATDIS (Fig. 3.3). However, TASK II only contains 22 to 69% of the landings recorded in TASK I and its use poses problems when catch and effort data are required in a spatial scale. ICCAT data provided in TASK I was chosen to be compared with FAO and my database due to the highest degree of coverage. With the exception of swordfish, the database compiled in this chapter presents the highest landing values for all large pelagics covered by ICCAT for most of the years (Fig. 3.4). FAO landing values were corrected based on ICCAT databases and thus are equivalent, except for 2000, when ICCAT landings are slightly higher, and for sharks, as ICCAT coverage is rather poor and landings from national sources were used instead by FAO. The pitfall of this approach is that landings originating from artisanalfisheriesare not included in the FAO database, and leads to an underestimation of catches of tunas, bonitos, mackerels, and billfishes (Fig. 3.4). Considering that several of these stocks are either fully or over exploited, there is reason for concern if this is an approach used for many other countries.  60 50 40 §> 30 .5  T3  § 20 10 0 1977  1982  1987  1992  1997  Figure 3.3: Comparison amongst landings recorded in three databases compiled by ICCAT for vessels using Brazilian flags (national and leased) for 1978-2000 (Source: www.iccat.es).  Landing trends The decline in overall Brazilian landings is accounted for mainly by the massive decline in landings of sardine {Sardinella brasiliensis), from 300,000 in 1988 to less than 50,000 tonnes in 1990 (Figs. 3.5). Fishes represent the highest landings, followed by crustaceans, molluscs, and mammals (Fig. 3.6). Note that whaling was completely banned in 1985, although a ban on successive species had occurred since 1981. Minke whales, Balaenoptera acutorostrata, continued to be exploited until 1985 (Singarajah, 1997). Turtles were a minor component of the total landings: 60 tonnes in 1980 (not shown). A gradual process to ban turtle fisheries also occurred in Brazil from 1967 onwards, until the complete ban of 1986 (Marcovaldi and Marcovaldi, 1999). However, contrary to the whales, some turtles were still caught in 1987-88 and are recorded in this database (< 5 tonnes). After that year, there were no landing data for turtles, although they are still caught as by-catch in swordfish and other pelagic longline fisheries (Weidner and Arocha, 1999), in lobster gillnets (Sales and Lima, 2002), and for self consumption.  1977  1982  1987  1992  1977  1982  1987  1992  1997  1997  Figure 3.4: Landings of tunas, bonitos and mackerels, swordfish, billfishes, and sharks originating from all vessels carrying Brazilian flags for 1978-2000 recorded in TASK I database (www.iccat.es), my database (total, industrial, and artisanal), and in FISHSTAT (www.fao.org).  The majority of Brazilian marine landings come from Rio de Janeiro, Santa Catarina, and Sao Paulo, although landings from Para have increased in 2000 (Fig. 3.7). The drastic decline in landings from Rio de Janeiro is mainly associated with the decline in sardine fisheries. The first three States are located in the southeastern and southeast regions, where most of the landings originate (Fig. 3.8). The decline in landings from the industrial sector is evident in both regions, although it is also noted in the artisanal sector. This reflects the typical development of the fishing sector, where the introduction of a new fishery (in this case, the industrial fishery) leads to an initial increase in landings and then to oscillations and collapse (Pauly, 1997).  1978  1982  1986  1990  1994  1998  Figure 3.5: Main species caught by Brazilian marine commercial fisheries (1978-2000).  a)  800  600 Fishes  1 400 "S -J  200  Crustaceans ^~^> • • • • j  1978  1982  1986  1990  i  i  1994  i  1998  16 12 a .S T3 C -J  8 4 0  _i  1978  1982  1986  i  i  1990  i  i  1994  i_  1998  Figure 3.6: Groups represented in landings from Brazilian marine commercial fisheries (1978-2000): a) Fishes and crustaceans; b) Molluscs and mammals.  Figure 3.7: States with the highest landings in Brazil (industrial and artisanal fisheries combined).  Southeast Industrial + Artisanal  South  600 500 400  | 300 .5 200  Industrial + Artisanal  300  1  200 100 0 1978 1982 1986 1990 1994 1998 Northeast  600  |  1978 1982 1986 1990 1994 1998  500  500  400  400  | 300  300  J 200  Industrial + Artisanal  100 0  200 100  Artisanal _i  i  i  North  600  i  i  i  i  i  i  i_  0  1978 1982 1986 1990 1994 1998  1  I  I  I  I  I  I  I  I  I  I  1978 1982 1986 1990 1994 1998  Figure 3.8: Landings of the industrial and artisanal marine fisheries off the southeastern, southern, northeastern, and northern regions of Brazil (1978-2000).  Landings from the northeastern and northern regions combined accounted for about 200,000 tonnes, with most landings originating with artisanal fisheries (Fig. 3.8). In this case, the introduction of a limited industrial fishery seems to have had little impact on the artisanal sector, as they both remained stable for the last 20 years. When this study is extended to include the period 1950-1979, a better analysis may be performed as most of the industrial fleet began to operate in the 1960s, although a new expansion occurred in the mid 1990s. Additionally, the analysis of individual fisheries would allow for a better understanding of the impact of industrial over artisanal fisheries.  The main group of species landed in northeastern Brazil were marine shrimps, other marine fishes, tunas, catfishes, drums and croakers, and lobsters (descending order of landings for 2000) (Fig. 3.9). Shrimps were responsible for the highest landings during the whole period, with the exception of the first year when drums and croakers dominated the catches. The proportion of other marine fishes increased in the last six years, reflecting a rather poor system of data collection or reporting. Although the database compiled here is not the best resource for analyzing tuna landings, it is able to indicate increasing landings for this group in the late 1990s. Lobster landings oscillated during the whole period with a decline of 42% in the last six years. Shrimps dominated the landings from artisanal fisheries and lobsters, southern red snapper, and shrimps dominated those from industrial fisheries, with a strong decline in landings of these three groups in the latter years.  1977  1982  1987  1992  1997  Figure 3.9: Landings of the main groups of species originating from marine commercial fisheries in northeastern Brazil (1978-2000; artisanal and industrial).  Fishing down the food web The mean trophic level of all Brazilian landings originating from marine waters presents a trend upwards for the period 1978-2000 (Fig. 3.10a). A similar trend was observed by Vasconcellos and Gasalla (2001) when analyzing data from Brazilian fisheries provided by FAO. In order to assess the impact of fishing in local habitats, landings of large pelagic species were eliminated, as these species are largely migratory and affected by changes in other habitats, for example, the whole Atlantic for yellowfin and bigeye tunas. Landings from artisanal and neritic industrial fisheries were combined as they are targeting the same stocks (Fig. 3.11). A slight decreasing trend in the mean trophic level of these landings was observed after 1984 (Fig. 3.10a). However, this analysis combines landings from large marine ecosystems (LMEs) as diverse as North, East, and South Brazil.  Landings originating only from northeastern Brazil (East Brazil LME) showed a stable mean trophic level for the whole period. However, there was a downward trend when large pelagics were excluded (Fig. 3.10b). The downward trend in mean trophic level was even clearer when the analysis of landings was performed at a finer spatial scale. Fishing down the food web was detected in landings originating from five out of the seven States for which landing data was properly collected using the ESTATPESCA program (Fig. 3.12). About 0.16 trophic levels were lost every ten years in those States, with the exception of Paraiba State, which recorded a lower rate. The decreasing trend in mean trophic level was not compensated by increasing catches for most States (Fig. 13.3), which would have justified a deliberate choice of moving down the food web, towards the more productive, lower components of the trophic web. The FiB index in fact declined indicating that these ecosystems had already been impacted during  a)  3.8  2.8  1  1977 b) 3.8  1  1982  1  1  •—  1987  1992  1997  1987  1992  1997  r  3.6 -  2.8 1977  1982  Figure 3.10: Mean trophic level of landings for Brazil (a) and northeastern Brazil (b) for the period 1978-2000. Both total landings and landings excluding large pelagic species are presented.  Deep-sea  Figure 3.11: Schematic drawing indicating the overlapping of resources targeted by artisanal and industrial fisheries on shelves (neritic), and the oceanic fisheries further offshore.  1977  1982  1987  1992  1997  Figure 3.12: Changes in mean trophic level for landings from northeastern Brazil in 1978-2000. PI = Piaui, CE = Ceara, RN = Rio Grande do Norte, PB = Paraiba, PE = Pernambuco, AL = Alagoas, and SE = Sergipe. Maranhao and Bahia States are not shown due to the lack of a proper system of data collection.  .1.6 I 1977 b)  0.4  1  1  1  1982  1987  1992  1982  1987  1—  1997  r  -0.8 1977  1992  1997  Figure 3.13: Fishing-in-balance (FiB) index for northeastern Brazil during 1978-2000. CE = Ceara, RN = Rio Grande do Norte, and PB = Paraiba; b) PI = Piaui, AL = Alagoas, SE = Sergipe, and PE = Pernambuco.  this period (1978-2000). The use of longer time series would clarify this hypothesis. Overall, decline rates of mean trophic level of landings in northeastern Brazilwere greater than those observed in Gulf of Thailand, Canada, and India (Christensen, 1998; Pauly et al, 2001; Bhathal, 2004).  Ceara and Rio Grande do Norte States present a stable mean trophic level throughout the period (Fig. 3.12). It seems that these areas have been affected by the high mobility of the industrial fleet from Ceara, which operates mainly in the coast of other states (CEPENE, 2000a). Thus, landings originating from other States would mask any trends in the local ecosystem. Moreover, it is worth pointing out that there is a high degree of correspondence between catches originating from both artisanal and industrial fisheries in Ceara and Rio Grande do Norte States (Fig. 3.14). This indicates that both fleets are fishing the same stocks or possibly there are flaws in the data collection system leading to the extrapolation of data from one state to the other.  There is also a possibility that overaggregation of categories such as 'outros peixes', 'caico', and 'mistura', all representing other fishes, may be affecting this analysis, as they reach high proportions (0.3-15% of total catch), particularly in the beginning and in the end of the period studied (Fig. 3.15). The breakdown of these groups into species is required, based on data from neighbour States and from anterior/posterior years, to elucidate this issue. However, there is evidence that taxonomic detail only exacerbates the downward trend observed based on overaggregated landing data (Pauly and Palomares, 2001).  Figure 3.14: Landings originating with marine fisheries off Ceara and Rio Grande do Norte: a) artisanal and b) industrial (1978-2000).  1978  1982  1986  1990  1994  1998  Figure 3.15: Proportion of other fishes in relation to total landings in Brazil and northeastern Brazil.  b) Recreational fisheries  Although FAO has added an estimate of 100,000 tonnes to Brazilian landing data provided by local agencies in order to account for catches originating from recreational and subsistence fisheries (FAO, 2002a), neither the basis for such estimate nor the proportion of each component was recorded. A l l catches were added as 'marine fishes nei' (not elsewhere identified) and as such were not incorporated in the database compiled here.  Freire (2005) indicates that preliminary estimates of catches from recreational fisheries off northeastern Brazil are very low (about 1,150 tonnes in 2001). Eighty-six species or group of species are caught by anglers and the main ones are: catfish (Ariidae), threadfins (Polydactylus spp.), rays (unidentified), jacks (Caranx spp.), pompanos (Trachinotus spp.), southern  kingcroaker (Menticirrhus americanus), puffers (unidentified), snooks (Centropomus spp.), king mackerel (Scomberomorus cavalla), sharks (unidentified), weakfish (Cynoscion spp.), banded croacker (Paralonchurus brasiliensis), tarpon (Megalops atlanticus), jenny mojarra (Eucinostomus gula), dolphinfish (Coryphaena hyppurus), mutton snapper (Lutjanus analis), serra mackerel {Scomberomorus serra), groupers (Epinephelus spp.), yellowtail snapper  (Ocyurus chrysurus), sailfish (Istiophorus albicans), tunas (Thunnus atlanticus, T. obesus and T. alalunga), and barracuda (Sphyraena barracuda). However, catches were not separated into species and would have to be included in the category 'marine fishes nei'. There is no estimate for other regions in Brazil, with the exception of an indication that about 33 tonnes-year" were 1  caught in oceanic tournaments promoted by the Rio de Janeiro Yatch Club in 1969-1992 (Paiva and Pires-Junior, 1983; Arfelli et al, 1994) and an extra four tonnes caught off Espirito Santo State in 1990 (Arfelli et al, 1994). Preliminary analysis of shore-based fishing tournaments off northeastern Brazil indicates that total catches amounted to an average of three tonnes-year" in 1995-1999 (Freire, in press). 1  None of the estimates presented above were added to the database compiled here as the series are either too short or do not contain enough detail in terms of species composition. This does not imply that this activity is not important at a national scale, but rather indicates that the available data up to now do not allow for the proper assessment of this activity.  c) Subsistence fisheries  As previously noted, FAO has added 100,000 tonnes to catches provided by Brazilian fisheries agencies to account for recreational and subsistence fisheries, but does not give any ratio between them. Some local sources indicate that 15-30% of the catches originating from  artisanal fisheries off northeastern Brazil in the 1970s (Piaui, Ceara, and Rio Grande do Norte States) were probably not accounted for, but subsistence fisheries were not mentioned (SUDENE/UFRN, 1975; SUDEPE/PDP, 1978; 1979). Artisanal fisheries also include a subsistence component as some fishers keep some fish for consumption or for paying the transport of fishes from the boat to landing sites (pers. obs.), which are not accounted in local statistics. Diegues (1996) and Glaser (2003) indicate that mangroves areas are particularly exploited for subsistence purposes.  d) Research fisheries  Catches originating from research vessels are not usually included in national databases. Several large-scale research programs were performed along the Brazilian Exclusive Economic Zone (EEZ) to assess the potential of exploitation of some species and later on to assess the state of some exploited stocks. In southern Brazil, projects such as PDP, AREPE, and ECOPEL were developed in order to study the anchovy-centered pelagic ecosystem off southern Brazil in 1976-1977, 1980-1982, and 1987-1991 (Castello, no year). Fishing hauls were involved in all these projects, but total catch was not incorporated in the national database. ECOSAR was a similar large-scale project designed to study the sardine-based pelagic system off southeastern Brazil and the resulting catches were not incorporated either (Rossi-Wongtschowski et al, 1996). In the same region, a project to analyze tuna fisheries using live-bait was developed in 1980-1991. This project alone produced a total catch of 495 tonnes, with Katsuwonus pelamis representing 94% of this total (Avila da Silva and Vaz dos Santos, undated).  In northeastern Brazil, several projects were developed by SUDENE (Institute for the Development of Northeastern Brazil) and SUDEPE during the 1960s and 1980s, and ECOTUNA Project (Ecology of Tuna and Tuna-like fishes) was set up during the 1990s (Hazin et al, 1999), followed by REVIZEE (Assessment of the Living Resources off the Brazilian Exclusive Economic Zone - EEZ), which in fact encompassed the whole Brazilian EEZ.  Although total catches resulting from research activities are low in relation to commercial catches, it would be interesting to quantify its magnitude in relation to unreported catches from other sectors such as recreational fisheries. Catch data may be recovered through an extensive literature review of reports produced by the projects listed here and by many others not listed.  e) Ornamental fisheries  Brazilian ornamental fisheries began on a commercial scale in Brazil by 1959 (Denis, 1985), but were mainly based on freshwater species with an average of about 10.6 million fishes exported annually in 1970-1976 (Welcomme et al, 1979). Marine species have been targeted more recently. IBAMA is responsible for controlling ornamental fisheries, but the control is performed only through a system of forms for trade permits. However, monitoring of this activity is rather poor, with coverage restricted to only some coastal states (Monteiro-Neto et al, 2003). Moreover, underreporting is a common practice aiming at lowering taxes and avoiding quotas. A total of 143 species and about 60-80 thousand individuals of marine ornamental fishes were traded by Ceara State alone in 2000 (Monteiro-Neto et al, 2003). This is the only record of trade of marine ornamental species found for Brazil.  f) Discards  Global estimates of by-catch and discards were found to be very high, accounting for 27 million tonnes per year in 1980-1992 (Alverson et al, 1994) and somewhat lower in 19922003 (7.3 million, according to Kelleher, 2004). There is no estimate of by-catch and discards at a national level in Brazil. Some discarding practices will be highlighted, but there is little attempt to quantify the effect of such practices, with the exception of localized estimates:  •  Finning: common practice amongst leased longliners targeting tuna and tuna-like fishes off northeastern Brazil (Lessa et al, 2004) - not quantified;  •  Longline: Cramer (2003) indicates that in 2001 about 15.3, 2.0 and 0.1 tonnes of undersized swordfish, billfishes, and pelagic sharks, respectively, were discarded dead by US pelagic longliners targeting tuna and swordfish in ICCAT areas 93 and 96, which include Brazilian waters. No other document was found addressing discards other than finning practices in this region by national or leased vessels.  •  Shrimp trawling: by-catch and discard rates vary amongst States due to differences in target species and location of fishing grounds in relation to the coast. In southern Brazil, 812 tonnes of juveniles of drums and croakers, flatfishes, and rays were discarded in 1992-1993 by beam trawlers, with an average of 0.3 kg of fish discarded per kilogram of shrimp landed (Haimovici and Mendonca, 1996). Shrimp trawlers in this region discard not only fishes, but also squids such as Loligo sanpaulensis (Perez and Pezzuto, 1998). In northeastern Brazil, discard rates of 2.5:1 kg of fishes and crabs were recorded for Piaui State. Moreover, large-scale trawlers targeting Penaeus subtilis in Bahia State discard Xiphopenaeus kroyeri, a shrimp species targeted by artisanal  fishers (CEPENE, 2000c). By-catch rates of 3.2:1 were observed in Paraiba State (Nunes and Rosa, 1998), although no indication about discard rates was given. Other bottom trawling: estimates of discards by fish trawlers are available mainly for southern Brazil, where these fisheries are very important. Haimovici and Habiaga (1982) found a discard proportion of 0.26 for pair-trawlers and pointed out that beside juveniles of the commercial species, other potential commercial species such as Trichiurus lepturus and Prionotus punctatus are discarded due to poor storage methods. A total of 5,641 tonnes of juveniles of drums and croakers, flatfishes, and rays were discarded in 1992-1993 by beam trawlers, with an average of 1.1 kg of fish discarded per kilogram of fish landed (Haimovici and Mendonca, 1996).  More  recently, Vasconcellos et al. (in press) estimated that 9,740 and 4,000 tonnes of croakers and drums were discarded in the late 1970s and 1990s, respectively. Overall, discards by trawlers can reach 17-25 thousand tonnes in this region (Haimovici, 1998). Lobsters: Ivo et al. (1996) indicate that 54 species of fishes and crustaceans are caught by trap and gillnet lobster fisheries in Ceara State, even though no discard rate was mentioned; FAO/WECAFC (2001) indicates that 10% of the lobster fleet continues fishing during the closed season in Ceara State. Lobster diving (with compressor hookah) and gillnets are illegal (IBAMA, 1994) and their catches are likely to be underestimated in national databases. Turtles: caught as by-catch in swordfish and other pelagic longline fisheries (Weidner and Arocha, 1999; Pinedo and Polacheck, 2004). There is also some indication that 60 turtles were caught per month by shrimp trawlers in Alagoas State and 100-130 per year in Sergipe State (both in northeastern Brazil) (IBAMA, 1994). There is also  evidence of increasing number of turtles entangled in gillnets targeting lobsters in Ceara and Bahia States (Sales and Lima, 2002). •  Mammals: even though there was a ban of whaling activities in Brazil and no marine mammal is currently allowed to be killed in Brazilian waters, incidental catch has been a serious problem. Monteiro-Neto et al. (2000) indicate that in Ceara State alone an average of 7-13 Sotalia fluviatilis and Steno bredanensis were caught annually in 19921998 (with a maximum of 31 in 1996). Sotalia fluviatilis (tucuxi) was also caught by gillnets in Alagoas State. In Rio Grande do Sul State (southern Brazil), the franciscana Pontoporia blainvillei is caught by bottom gillnets targeting sciaenids, which killed 919 fransciscanas in 1976-1987 (Pinedo, 1994). However, the list of marine mammals incidently caught in fisheries activities is much longer and includes bottlenose, Atlantic spotted, striped, spinner and common dolphins, and the long-finned pilot, false killer, killer, and minke whales (Siciliano, 1994).  g) Distant water fleets  US and other distant water fleets fished illegally for shrimp in Brazilian waters during the 1980s (Weidner and Hall, 1993), almost leading to the collapse of shrimp stocks off Amapa State (Chimanovitch, 2001). In the 1990s, vessels from Japan, Korea, Spain, and Taiwan frequently called Brazilian ports in the northeastern region for services and it is suspected that such vessels were targeting tuna in Brazilian waters (Weidner and Hall, 1993). Saint Peter and Saint Paul Archipelago is particularly vulnerable due to its distance from mainland (Chimanovitch, 2001). Currently, there is no estimate of catches by distant water fleets, but they probably represent an annual loss of US$ 500 million for Brazil (Chimanovitch, 2001).  The database compiled here presents trends for landing data from marine commercial fisheries off Brazil as recorded in national reports, but it has several flaws inherited from the original sources. For the period between 1990 and 1994, for example, the entries were calculated based on the mean of landings for the period 1986-1989 and corrected only for those species that were dealt with in the context of study groups (CEPENE, 1997a). Catch data for shrimps and sardines from Sao Paulo are probably underestimates (Gasalla and Tomas, 1997). And finally, catches from other fishing activities, i.e, the abovementioned (a-f), are not incorporated in the national database.  This study will be extended to include, in a first phase, data from the period 1970-1977. For those cases where landing data are available from sources other than the national sources, they will be incorporated in the present database, together with the original information. Furthermore, this database will be gradually corrected for discards and other unreported catches, including those from recreational and ornamental fisheries, two sectors that have been growing in the last few years. In addition, the breakdown of the categories 'outros peixes', 'caico', and 'mistura', all of which representing unidentified fishes, will be performed based on the catch composition of different years and on that from neighbouring States. In a second phase, the database will be expanded to include the period 1950-1969. This phase will be more problematic as some sources available present landing data combined in broad categories such as 'fish', 'crustaceans', 'mammals', and do not distinguish between catch from marine and freshwaters.  The objective here was to assemble basic data needed for assessments, which are scattered in documents that are usually not readily available. Several researchers have likely already  undergone the process of data collection and encoding, and others would have to repeat this process, if data are not made easily available in an electronic version. This is also an opportunity to collaborate to create a more complete national database as soon as more accurate data from specific study groups are incorporated.  All potential users should be aware that the State associated with a given landing record does not imply that this landing came from waters along the coast of that State due to the high mobility of some large motorized boats. Additionally, the correspondence between common and scientific names remains incomplete. Landing data compiled in this chapter was used in the simulations run in chapters 4 and 5 for northeastern Brazil, in conjunction with ICCAT data for tuna and billfishes. This was possible only owing to the breakdown of catches by State and posterior grouping for the nine States included in this region.  3.4. Conclusions  Brazilian landings data compiled in this chapter indicate a decreasing trend in landings after the mid 80s, mainly associated with the collapse of sardine fisheries off southeastern Brazil. This database fails in recording tuna and tuna-like fish catches (with the exception of sharks) originating from industrial fisheries and have to be corrected using ICCAT database. However, ICCAT data cannot completely substitute landings from this database, as Brazil has not been reporting catches from artisanal fisheries to this commission. Moreover, several other sources of catches such as recreational, subsistence, research, ornamental, and distant-water fleet fisheries, and discards are not accounted for, resulting in underestimated catches. The use of Brazilian landings available from FAO implies a loss in taxonomic detail as many species are  grouped in taxonomic levels higher than recorded in national bulletins and, in some cases, landings are attributed to the erroneous species.  Even though catches are underestimated, fishing down the food web is observed in Brazilian ecosystems, particularly when a finer spatial scale is used. East Brazil Large Marine Ecosystem has seen an average loss of 0.016 trophic levels per year since 1978, based on information from landings. However, problems with the underestimation of catches, correspondence between common and scientific names, and overaggregation of categories such as 'other fishes' remain to be resolved.  3.5. Bibliography  Alverson, D.L., M.H. Freeberg, S.A. Murawski and J.G. Pope (1994). A global assessment of fisheries bycatch and discards. FAO Fisheries Technical Paper 339: 1-233. Andrews, C. (1990). The ornamental fish trade and fish conservation. Journal of Fish Biology 37(Suppl. A): 53-59. Aragao, J.A.N. (1997). Analise da consistencia estatistica do programa de coleta de dados de desembarque de pescado - ESTATPESCA, executado pelo lbama no nordeste do Brasil, Universidade Federal do Ceara, Fortaleza, Brazil. Master Thesis: 193 p. Arfelli, C.A., A.F. Amorim and R. Graca-Lopes (1994). Billfish sport fishery off Brazilian coast. Collective Volume of Scientific Papers, ICCAT XLI: 214-217. Avila da Silva, A.O. and A . M . Vaz dos Santos (undated). Analise das capturas de atuns e afins baseadas na pesca pelo metodo de vara e isca-viva realizada pelo NPq Malacostraca de 1980 a 1991. Analise/Refinamento dos dados preteritos sobre prospeccao pesqueira. Avaliacao do potencial sustentavel de recursos vivos na Zona Economica Exclusiva M M A - REVIZEE. Anexo 2, Vol.31(l): 19 p.  Bhathal, B. (2004). Historical reconstruction of Indian marine fisheries catches, 1950-2000, as basis for testing the 'Marine Trophic Index'. Department of Zoology, University of British Columbia, Vancouver. Master Thesis: 130 p. Castello, J.P. (no year). A anchoita Engraulis anchoita (Engraulididae: Teleosteii) no sul do Brasil. Analise/Refinamento dos dados preteritos sobre prospeccao pesqueira. Avaliacao do potencial sustentavel de recursos vivos na Zona Economica Exclusiva M M A REVIZEE. Anexo 2, Vol.31(3): 61 p. CEPENE (1995a). Estatistica da pesca - 1990. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 89 p. CEPENE (1995b). Estatistica da pesca - 1991. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 90 p. CEPENE (1995c). Estatistica da pesca - 1992. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/EBAMA, Tamandare, Pernambuco: 90 p. CEPENE (1995d). Estatistica da pesca - 1993. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 89 p. CEPENE (1995e). Estatistica da pesca - 1994. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 89 p. CEPENE (1997a). Estatistica da pesca - 1995. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 110 p. CEPENE (1997b). Estatistica da pesca - 1996. Brasil - Grandes regioes e unidades da federacao. Centra de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 120 p.  CEPENE (1998). Estatistica da pesca - 1997. Brasil - Grandes regioes e unidades da federacao. Centro de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA,  Tamandare,  Pernambuco: 84 p. CEPENE (2000a). Boletim estatistico da pesca maritima e estuarina do nordeste do Brasil 1999. Centro de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare: 150 p. CEPENE (2000b). Estatistica da pesca - 1999. Brasil - Grandes regioes e unidades da federacao. Centro de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare, Pernambuco: 104 p. CEPENE (2000c). Relatorio da reuniao tecnica sobre o estado da arte da pesquisa e ordenamento da pesca de camaroes peneideos na regiao nordeste do Brasil. Centro de Pesquisa e Extensao Pesqueira do Nordeste - CEPENE, Tamandare, Pernambuco, Brasil: 64 p. Chimanovitch, M . (2001). Zona maritima. Isto e Online 1633 (17/01/2001): www.terra.com. br/istoe/1633/brasil/1633 zona maritima.htm. Christensen, V. (1998). Fishery-induced changes in a marine ecosystem: insight from models of the Gulf of Thailand. Journal of Fish Biology 53 (Supplement A): 128-142. Coleman, F.C., W.F. Figueira, J.S. Ueland and L.B. Crowder (2004). The impact of United States recreational fisheries on marine fish populations. Science 305(5692): 1958-1960. Cowx, I.G. (2002). Recreational fishing. In: P.J.B. Hart and J.D. Reynolds (Eds.). Handbook of fish biology and fisheries. Volume 2. Fisheries. Blackwell Publishing, Maiden, MA, 2: 367-390. Cramer, J. (2003). Pelagic longline by-catch. Collective Volume of Scientific Papers ICCAT 55(4): 1576-1586. Denis, I.R.M. (1985). Exportacao brasileira de peixes ornamentais. Serie Documentos Tecnicos do Instituto de Pesquisa e Desenvolvimento Pesqueira - PDP 32: 119-162. Dias Neto, J. and L.D.C. Dornelles (1996). Diagnostic*) da pesca maritima do Brasil. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais, Brasilia: 165 p. Diegues, A.C.S. (1996). Ecologia humana e planejamento em areas costeiras. NUPAUB-USP, Sao Paulo, Brazil: 191 p.  FAO (2002a). FAO yearbook. Fishery statistics. Catches and landings. 2000. Food and Agriculture Organization of the United Nations, Rome: 617 p. FAO (2002b). Fishery country profile. The Federative Republic of Brazil, www.fao.org/ fi/fcp/fcp.asp, Accessed in 10 March, 2002. FAO (2002c). Implementation of the international plan of action to prevent, deter and eliminate illegal, unreported and unregulated fishing. FAO Technical Guidelines for Responsible Fisheries. FAO, Rome: 122 p. FAO/WECAFC (2001). Workshop on management of the Caribbean spiny lobster (Panulirus argus) fisheries in the area of the Western Central Atlantic Fishery Comission. Merida, Mexico, 4 - 8 September 2000. FAO Fisheries Report No. 643. FAO, Rome. 66 p. Freire, K.M.F. (2005). Recreational fisheries of northeastern Brazil: inferences from data provided by anglers. In: G.H. Kruse, V.F. Gallucci, D.E. Hay, R.I. Perry, R.M. Peterman, T.C. Shirley, P.D. Spencer, B. Wilson and D. Woodby (Eds.). Fisheries assessment and management in data-limited situations. Alaska Sea Grant College Program, University of Alaska Fairbanks. Freire, K.M.F. (in press). Unregulated catches from recreational fisheries off northeastern Brazil. Fisheries Centre Research Reports. Freire, K.M.F. and D. Pauly (2003). What's in there? Common names of Brazilian marine fishes. Fisheries Centre Research Reports 11(1): 439-444. Gasalla, M.A. and A.R.G. Tomas (1997). Evaluation of the status of fisheries data collection and stock assessment problems in Sao Paulo, southeastern Brazil. In: F. Funk, T J . Quinn-II, J. Heifetz, J.N. Ianelli, J.E. Powers, J.F. Schweigert, P.J. Sullivan and C.-I. Zhang (Eds.). International Symposium on Fishery Stock Assessment Models for the 21  st  Century. University of Alaska Sea Grant College, Anchorage, Alaska: 41-60. Gentner, B. and A. Lowther (2002). Evaluating marine sport fisheries in the USA. In: T.J. Pitcher and C.E. Hollingworth (Eds.). Recreational fisheries: ecological, economic and social evaluation. Blackwell Science Ltd, Oxford: 186-206.  Glaser, M . (2003). Interrelations between mangrove ecosystem, local economy and social sustainability in Caete Estuary, North Brazil. Wetlands Ecology and Management 11: 265-272. Haimovici, M . (1998). Present state and perspectives for the southern Brazil shelf demersal fisheries. Fisheries Management and Ecology 5: 277-289. Haimovici, M . and R.P. Habiaga (1982). Rejeicao a bordo na pesca de arrasto de fundo no litoral do Rio Grande do Sul num cruzeiro de primavera. Documentos Tecnicos de Oceanografia 2: 1-15. Haimovici, M . and J.T. Mendonca (1996). Descartes da fauna acompanhante na pesca de arrasto de tangones dirigida a linguados e camaroes na plataforma continental do sul do Brasil. Atlantica 18: 161-177. Hardy, R. (2003). Introduction to the special issue on 'Ornamental fish'. Aquaculture Research 34(11): 903-903. Hazin, F.H.V., S. Hamilton and T. Vaske Junior (1999). Necton: grandes peixes pelagicos. Avaliacao e acoes prioritarias para a conservacao da biodiversidade da zona costeira e marinha. http://www.bdt.fat.org.br/workshop/costa/pelagicos/, Accessed in February 2, 2005. IBAMA (1994). Lagosta, caranguejo-uca e camarao do nordeste. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renovaveis, Brasilia: 190 p. IBGE (1980). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 1(1): 171. IBGE (1981). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 2(1): 167. IBGE (1982a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 3(2): 174. IBGE (1982b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 3(1): 171. IBGE (1983a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 4(2): 162.  EBGE (1983b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 4(1): 185. EBGE (1984a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 5(1): 159. IBGE (1984b). Brasil - Grandes regi5es - Unidades da Federacao. Estatistica da Pesca 5(2): 160. IBGE (1985a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 6(2). IBGE (1985b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 6(1). IBGE (1986a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 7(2): 182. IBGE (1986b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 7(1): 180. IBGE (1987a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 8(2): 184. IBGE (1987b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 8(1): 182. IBGE (1988a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 9(1): 187. IBGE (1988b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 9(2): 186. IBGE (1989a). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 10(1): 1-70. IBGE (1989b). Brasil - Grandes regioes - Unidades da Federacao. Estatistica da Pesca 10(2): 1-58. Ivo, C.T.C., M.E. Santiago and C. Monteiro-Neto (1996). Fauna acompanhante na pesca das lagostas Panulirus argus (Latreille) e Panulirus laevicauda (Latreille), no estado do Ceara, Brasil. Arquivos de Ciencias do Mar 30(1-2): 41-47.  Jackson, J.B.C., M.X. Kirby, W.H. Berger, K.A. Bjorndal, L.W. Botsford, B.J. Bourque, R.H. Bradbury, R. Cooke, J. Erlandson, J.A. Estes, T.P. Hughes, S. Kidwell, C.B. Lange, H.S. Lenihan, J.M. Pandolfi, C.H. Peterson, R.S. Stenek, M.J. Tegner and R.R. Warner (2001). Historical overfishing and recent collapse of coastal ecosystems. Science 293: 629-638. Kelleher, K. (2004). Discards in the world's marine fisheries: an update. FAO Fisheries Technical Paper 470: 1 -134. Lessa, R.P., M.F. Nobrega and J.L. Bezerra Junior (2004). Dinamica de populacoes e avaliacao de estoques dos recursos pesqueiros da regiao nordeste. Volume II. DIMAR, Departamento de Pesca - Universidade Federal Rural de Pernambuco, Recife-Brazil: 245 PLins-Oliveira, J.E. and J.A. Vasconcelos (2004). Pesca de lagostas no nordeste do Brasil. In: R.P. Lessa, M.F. Nobrega and J.L. Bezerra Junior (Eds.). Dinamica de populacoes e avaliacao de estoques dos recursos pesqueiros da regiao nordeste. REVIZEE - Score NE. UFRPE, Dimar, Recife: 237-245. Marcilio, M.L. and M.L. Lisanti (1973). Problemes de l'histoire quantitative du Bresil: metrologie et demographic Colloques Internationaux du Centre National de la Recherche Scientifique(543): 29-37. Marcovaldi, M.A. and G.G. Marcovaldi (1999). Marine turtles of Brazil: the history and structure of Projeto TAMAR-IBAMA. Biological Conservation 91: 35-41. Monteiro-Neto, C , T.T. Alves-Junior, F.J.C. Avila, A.A. Campos, A.F. Costa, C.P.N. Silva and M.A.A. Furtado-Neto (2000). Impact of fisheries on the tucuxi (Sotalia fluviatilis) and rough-toothed dolphin (Steno bredanensis) populations off Ceara state, northeastern Brazil. Aquatic Mammals 26(1): 49-56. Monteiro-Neto, C , F.E.A. Cunha, M.C. Nottingham, M.E. Araujo, I.L. Rosa and G.M.L. Barros (2003). Analysis of the marine ornamental fish trade at Ceara State, northeast Brazil. Biodiversity and Conservation 12: 1287-1295. Nunes, C.R.R. and R.S. Rosa (1998). Composicao e distribuicao da ictiofauna acompanhante em arrastos de camarao na costa da Paraiba, Brasil. Trabalhos Oceanograficos da Universidade Federal de Pernambuco 26(2): 67-83.  Opitz, S. (1996). Trophic interactions in Caribbean coral reefs. ICLARM Tech. Rep. 43: 341 PPaiva, M.P. (1997). Recursos pesqueiros estuarinos e marinhos do Brasil. UFC, Fortaleza, Brazil: 278 p. Paiva, M.P. and O.C. Pires-Junior (1983). Temporadas de pesca esportiva e oceanica, ao largo do estado do Rio de Janeiro. Boletim de Ciencias Marinhas 38: 1-12. Pauly, D. (1995). Anecdotes and the shifting baseline syndrome of fisheries. Trends in Ecology and Evolution 10(10): 430. Pauly, D. (1997). Small-scale fisheries in the tropics: marginality, marginalization, and some implications for fisheries management. American Fisheries Society Symposium 20, Bethesda, Maryland.  -v  Pauly, D. and V. Christensen (1995). Primary production required to sustain global fisheries. Nature 374: 255-257. Pauly, D., V. Christensen, S. Guenette, T.J. Pitcher, U.R. Sumaila, C.J. Walters, R. Watson and D. Zeller (2002). Towards sustainability in world fisheries. Nature 418: 689-695. Pauly, D., V. Christensen and C. Walters (2000). Ecopath, Ecosim, and Ecospace as tools for evaluating ecosystem impact of fisheries. ICES Journal of Marine Science 57: 697-706. Pauly, D., M.L. Palomares, R. Froese, P. Sa-a, M . Vakily, D. Preikshot and S. Wallace (2001). Fishing down Canadian aquatic food webs. Canadian Journal of Fisheries and Aquatic Science 58: 51-62. Pauly, D. and M.L.D. Palomares (2001). Fishing down marine food webs: an update. In: L. Bendell-Young  and  P.  Gallaugher.  Kluwer  Academic  Publishers,  Norwell,  Massachusetts: 47-56. Perez, J.A.A. and P.R. Pezzuto (1998). Valuable shellfish species in the by-catch of shrimp fishery in southern Brazil: spatial and temporal patterns. Journal of Shellfish Research 17(1): 303-309. Pinedo, M.C. (1994). Review of small cetacean fishery interactions in southern Brazil with special reference to the franciscana, Pontoporia blainvillei. In: W.F. Perrin, G.P.  Donovan and J. Barlow (Eds.). Gillnets and cetaceans. Report of the International Whaling Commission, Special Issue 15. The Red House, Cambridge: 251-259. Pinedo, M.C. and T. Polacheck (2004). Sea turtle by-catch in pelagic longline sets off southern Brazil. Biological Conservation 119(3): 335-339. Pitcher, T. (2001). Fisheries managed to rebuild ecosystems? Reconstructing the past to salvage the future. Ecological Applications 11(2): 601-617. Rossi-Wongtschowski, C.L.D.B., M.C. Cergole and S.A. Saccardo (1996). Relatorio do projeto prospeccao e avaliacao de biomassa por metodos hidroacusticos do estoque da sardinha e da anchoita na regiao sudeste do Brasil - ECOS AR U e III. Sales, G. and E.H.M.S. Lima (2002). A pesca da lagosta no litoral do nordeste: interacao pesca x conservacao das tartarugas marinhas. IBAMA, Praia do Forte, Brazil: l i p . Siciliano, S. (1994). Review of small cetaceans and fishery interactions in coastal waters of Brazil. In: W.F. Perrin, G.P. Donovan and J. Barlow (Eds.). Gillnets and Cetaceans. Report of the International Whaling Commission, Special Issue 15. The Red House, Cambridge: 241-250. Singarajah, K.V. (1997). Whales and whaling. In: K.V. Singarajah (Eds.). Fundamentals of marine biology with particular emphasis on the tropical realm. Minerva Press, London: 276-304. SUDENE/UFRN (1975). Boletim informativo da producao pesqueira do estado do Rio Grande do Norte - 1974. N° 6. Universidade Federal do Rio Grande do Norte, Natal: 76 p. SUDEPE (1980). Estatistica da pesca. Producao - 1978. Ministerio da Agricultura, Brasilia: 84 PSUDEPE (1981). Estatistica da pesca. Producao - 1979. Superintendencia do Desenvolvimento da pesca, Brasilia: 141 p. SUDEPE/PDP (1978). Sumarizacao dos dados coletados no estado sobre: controle de desembarque realizado na pesca industrial e artesanal. Periodo Janeiro-Junho/1977. Series Documentos Informe Semestral do Estado do Piaui 2: 1-16.  SUDEPE/PDP (1979). Sumarizacao dos dados coletados no estado sobre: controle de desembarque realizado na pesca industrial e artesanal. Periodo julho - dezembro/1978. Serie Documentos Informe Semestral do Estado do Ceara(5): 1-29. Vasconcellos, M . and M.A. Gasalla (2001). Fisheries catches and the carrying capacity of marine ecosystems in southern Brazil. Fisheries Research 50: 279-295. Vasconcellos, M., D. Kalikoski, M . Haimovici and T. Pitcher (in press). Estimating unreported catches of the main demersal species from fisheries discards in southern Brazil. Fisheries Centre Research Reports. Walters, C.J. and S.J.D. Martell (2004). Fisheries ecology and management. Princeton University Press, Princeton and Oxford: 399 p. Weidner, D. and F. Arocha (1999). South America: Atlantic, Part A., Section 2 (Segment B). Brazil. In: Latin America, World swordfish fisheries: an analysis of swordfish fisheries, market trends, and trade patterns. Vol. IV. NMFS, Silver Spring, Maryland, Vol. IV: 237-628. Weidner, D.M. and D.L. Hall (1993). Latin America. World fishing fleets: an analysis of distant-water fleet operations, past-present-future.  Office of International Fisheries,  NMFS, NOAA, U.S. Department of Commerce, Maryland: 513 p. Welcomme, R.L., R. Richards and G.S. Neiva (1979). Relatorio da missao sobre peixes ornamentais. PDP Serie Documentos Traduzidos 9: 1-41.  CHAPTER 4. Description of the marine ecosystem off northeastern Brazil using a trophic model  4.1. Introduction  Models are representations of complex systems that attempt to depict their main components and the interrelations amongst these components. These representations, which can be physical, verbal, graphical or mathematical, reflect the interest of the modeller, if only because of their partial character (Haddon, 2001). In this study, the interest is the effect of fisheries on the marine ecosystem off northeastern Brazil, i.e., on its major functional groups, here defined as groups of species that share similar population parameters, diet composition, distribution area, and behaviour.  Modelling requires that the ecosystem to be studied is properly defined. This is a difficult task, particularly in the marine realm, due to the absence of fixed boundaries. Longhurst (1998) proposed a hierarchical classification for the oceans, where the most general levels are the biomes (coastal, westerly winds, trade wind, and polar), subdivided in fifty-seven provinces based on physical forcing and the response of phytoplankton to this forcing. One of these provinces is the Guianas Coastal Province (a part of the Atlantic Coastal Biome), which extends from Trinidad to Cape de Sao Roque (Rio Grande do Norte State). However, this province encompasses two sub-regions that are influenced by the Amazon River in a completely different fashion, and hence the division provided by Matsuura (1995) and presented in Chapter 1 is more realistic.  Matsuura (1995) proposed the division of the Brazilian coast into five sub-regions (north, northeast, east, southeast, and south) based on bathymetry, oceanographic structure, fauna, flora, and major fisheries. The north sub-region is characterized by high primary production due to the discharge of the Amazon River, and has a sandy or muddy bottom and a rich benthic community. Bottom trawling is the most important fishery. In contrast, the northeast subregion, the object of this study, is characterized by rocky substrates and low primary production due to the influence of the warm North Brazil and Brazil currents. This sub-region corresponds to the East Brazil Large Marine Ecosystem (Sherman et al, 2002) and it is distinguished from other large marine ecosystems (LMEs) by criteria such as bathymetry, hydrography, and productivity. LMEs have been proposed as a conceptual framework for ocean management and their use should facilitate the comparison of the results obtained here with the ones obtained in multi-country projects to recover marine biomass that have been developing worldwide (Sherman and Duda, 2001).  Many models have been built to describe marine ecosystems around the world (see e.g. contributions in Christensen and Pauly, 1993). In Brazil, Vasconcellos (2000) and Vasconcellos and Gasalla (2001) modelled the Brazilian southeast and south sub-regions, which are characterized by wide continental shelf and sandy or muddy bottoms that allowed for the development of an important bottom trawl fishery for drums and croakers. In the pelagic realm, sardines are dominant in the southeast (and they used to support the major Brazilian fishery), while anchovies are very abundant in the south, although not yet exploited (Castello and Castello, 2003). Gasalla and Rossi-Wongtschowski (2004) developed a model for southeastern Brazil where the effects of changes in fishing patterns were assessed. Two other areas in Brazil were also modelled in terms of trophic interactions: one to the north of the  area modelled in this thesis (Wolff et al, 2000) and one to the south (Telles, 1998). The present study will allow for the comparison between the East Brazil Large Marine Ecosystem and the other previously modelled regions.  The objective of this chapter is to describe the East Brazil Large Marine Ecosystem (off northeastern Brazil) and the main trophic interactions between the functional groups occurring in this ecosystem. This model will be the basis for the exploration of fishing policies for the main resources exploited that will be presented in Chapter 5.  4.2. Methods  4.2.1. ECOPATH model  A model was constructed for the East Brazil Large Marine Ecosystem for the 1970s using Ecopath with Ecosim (EwE version 5.1; www.ecopath.org), a computer package based on an early version of Ecopath (Polovina, 1984). The Ecopath module represents a mass-balance model based on two master equations (Christensen et al, 2004; Christensen and Walters, 2004):  (1)  Pi=Y,+  E  > + i BA  + i MO  B  i  +  M 2  i  • t B  where: P, = total production rate for each functional group /; P, = B,-(P,/B,); Y, = catch rate of/; E, = net migration rate for group / (emigration minus immigration); B A = bioaccumulation rate of /; M0, = non-predation mortality rate for / = P,-(1-EE,)/B,; B, = biomass of group /; EE, = ecotrophic efficiency (proportion of the production used in the system); M2, = total predation  rate for i =  -DC^; Q, = consumption by predator j = B/(Q/B/); and DC/, = diet 7=1  composition = fraction of the diet of predator j that is made up of prey i, and  (2)  Q, = P, + R, + UF,  where: Q, = consumption by functional group /; R, = respiration by /; and UF, = food of i that remains unassimilated.  Values of B„ P,/B„ Q,/B„ EE,, and DC/, for each functional group were provided to the model, allowing equations (1) and (2) to be solved (Christensen et al, 2004). These data were gathered from scientific papers, reports, theses, and unpublished sources related to this ecosystem and similar ecosystems, as well as from FishBase, a global database on fishes (Froese and Pauly, 2002, see also www.fishbase.org). Catch data were obtained from Chapter 3. Details about the source of each data type are provided below.  4.2.2. Habitat area  The total area modelled here (Large Marine Ecosystem 16 - East Brazil) encompasses 1,074,984 km and corresponds to the Exclusive Economic Zone (EEZ) off northeastern 2  Brazil. The shelf is usually narrow, reaching down to 20 km, but can reach up to 220 km at the Abrolhos Bank, the southernmost region included in the study area (Ekau and Knoppers, 1999). A total of 1,200 km of coral reefs are found in the region (Spalding et al, 2001). Creed 2  (2003) estimates that Brazil has a seagrass coverage of 200 km , 70-80% of which located in 2  northeastern Brazil (Joel Creed, pers. comm.; Laboratory of Benthic Marine Ecology, Rio de Janeiro, Brazil). The habitat area (fraction) for each group was estimated based on information available in the literature. For those groups for which no information was available, a 'guesstimate' was calculated based on the extension of the habitat (e.g., coral, mangrove, seagrass) they are associated with.  4.2.3. Functional groups  Forty-one functional groups were used to describe the marine ecosystem off northeastern Brazil, including marine mammals, fishes, crustaceans, molluscs, other invertebrates, zoo- and phytoplankton, benthic producers, and detritus (Table 4.1). Details of the species included in each group are presented in Appendix 2. More groups could have been used, but this would have led to data requirements that would be hard to meet due to unavailability of data.  The functional groups were chosen based on the distribution area of each species, their maximum body size, trophic level, and consumption rates, in combination with information provided from previous models built for similar habitats. This division was intended to encompass all exploited groups in such a way that allowed for the analysis of the effect of fisheries on the biomass of the stocks. Groups were kept generic to include all catches that are recorded by common name and incorporate various species. Finally, one group (dolphinfish) was split into stanzas (juveniles and adults) in order to properly represent the complex trophic ontogeny of this group (Christensen et al., 2004).  4.2.4. Basic input  The basic input data were: Biomass (B), Production/Biomass (P/B), Consumption/Biomass (Q/B), and/or Ecotrophic Efficiency (EE). The values used for each species to calculate an average for each functional group in the 1970s model are presented in Appendix 3. A l l biomass values were expressed in wet weight density (tonnes-km" ), using habitat area as reference, and all rates were put on an annual basis. For each functional group, only one of those parameters could be missing and was estimated by the model. Usually, the model estimates ecotrophic efficiency, as it cannot be empirically calculated. However, as biomass estimates were not readily available for several groups, they were estimated by the model, after ecotrophic efficiency values obtained from similar ecosystems were used as input. Details of calculations of basic input for each group are presented below:  Biomass (B) Estimates of biomass for northeastern Brazil are absent in most cases and thus they were mostly estimated by the model or obtained from models of similar regions. The biomass of manatees was estimated based on a total population of 400 individuals (Medeiros et al, 2000) and an individual mean weight of 400 kg (Edwards, 2000). In the absence of other information and considering that these species have been protected since 1967, the estimate of total population for 1978 was considered the same as estimated by Medeiros et al. (2000), even though other factors beside hunting may have affected the population such as accidental catch, and agricultural and industrial pollution (Borobia and Lodi, 1992).  For baleen whales and toothed cetaceans, estimates of biomass for the East Brazil LME were obtained from updated estimates by Kristin Kaschner (pers. comm., Fisheries Centre, UBC,  Vancouver, Canada), based on Kaschner et al. (2001). These estimates are based on a model predicting global distributions of marine mammals and as such are likely to be only gross estimates of local abundance. Moreover, these estimates represent annual means while seasonal abundance may vary as observed for humpback whales (Kinas and Bethlem, 1998; Zerbini et al, 2004), the only species for which abundance has been estimated in local studies.  Total biomass for tunas and tuna-like fishes were obtained from ICCAT assessments for each specific stock. As recommended by ICCAT, the hypothesis of one single stock was considered for yellowfin and bigeye tunas and two stocks for albacore (northern and southern). Biomass estimates were divided by the total distribution area of the species following the latitude limits defined in Collette and Nauen (1983): between 40°N and 35°S for yellowfin tuna, 40°N-40°S for bigeye tuna, and 5°N-45°S for albacore. For the first two tuna species, total biomass was available in ICCAT documents. For albacore, total biomass was calculated using a conversion factor (CFi) based on an estimate of spawning biomass (ICCAT, 2004b), considering an ageat-maturity of 5 years and 8 years of longevity: (3)  CF^C^S.-W./j^S.-W.) a=j  (4)  a=\  TB = SSBICF  X  where: S = survival, a = age,y = age-at-maturity, k = longevity, TB = total biomass, and SSB spawning biomass. For all three tuna species, biomass per area were estimated to the East Brazil LME using mean catches for the period between 1995 and 2000 as a correction factor (CF ): 2  (5)  CF = (Catch ME-Area TOTAL)/(Catch TOTAL" Area LME) 2  L  Mean catches for 1995-2000 were used in the correction factor instead of catches for 1978 as tuna fisheries developed in Brazil in the last few years and thus, earlier catches would not be considered an adequate index of local abundance (Walters, 2003). CPUE-based indexes were not used, as the coverage of the TASK II-ICCAT database containing effort data for East Brazil was rather limited, as discussed in the previous chapter.  The resulting biomass of this group in the East Brasil LME (BLME) was calculated as follows:  (6)  B  L M E  = TBCF  2  The same procedure described above was applied to the southern stock of swordfish, which is distributed between 15°N and 45°S. The total biomass was estimated based on the spawning biomass (ICCAT, 2004b), considering an age-at-maturity and maximum age of 5 and 15 years, respectively. For other large pelagics, biomass was estimated using the same procedure, considering one single Atlantic stock of white and blue marlins. Two stocks of sailfish are recognized by ICCAT, but the absence of biomass for the western stock precluded the consideration of such division. The resulting biomass for other large pelagics is likely to be underestimated, as biomass data for other pelagic species such as Acanthocybium solandri and Scomberomorus spp. are not available.  For spotted goatfish, the value of biomass available in Opitz (1996) seems to be overestimated when compared to Southern red snapper, a species that has been sustaining an intense industrial fishery off northeastern Brazil since the 1960s. Thus, a biomass of 1/10 the original value was used. For squids, an arbitrary ratio of 1/100 of the average value of the biomass  estimated by Vasconcellos (2002) for the Southern Atlantic in the 1950s and 1990s was used. The rationale behind this ratio is that local squid annual catches are very low (< 1 tonne) when compared with, e.g., southern/southeastern Brazil (about 1,200 tonnes; based on the database compiled in Chapter 3) and with the entire southern Atlantic Ocean (85,000 tonnes in 1978; www.fao.org). Lower catches were used as an indicator of low local biomass due to the lack of local information of biomass.  The biomass of detritus was calculated by the equation:  (6)  logioD = -2.41 + 0.054 logioPP + 0.863 logi E 0  where: D = detritus standing stock (gCm~), PP = primary production (gCm~ -year"), and E = euphotic depth (m) (Pauly et al, 1993). Primary production was obtained by multiplying B by P/B from the basic input in Ecopath and dividing by a factor of 16.7 in order to convert carbon weight to wet weight (Opitz, 1996).  The biomass values for all other functional groups are as in the original sources cited in Appendix 3. For groups with no estimate of biomass available, an estimate of ecotrophic efficiency for similar groups from similar areas was used, and biomass was estimated by EwE using the mass balance constrained by equations (1) and (2) mentioned above.  Production/Biomass (P/B) The values and references used to calculate P/B for each group are presented in Appendix 3. For exploited fish groups, the instantaneous rate of total mortality (Z) was used as an estimate of P/B (Allen, 1971), where Z is the sum of natural (M) and fishing (F) mortality rates. Groups 117  such as tunas and other large pelagics, for which biomass estimates where available for each species, had a Z value estimated using biomass as a weighting factor. As much as possible, estimates were obtained from local studies. Some estimates were calculated using lengthfrequency distributions from the REVIZEE Program-Score NE (Assessment of the Living Resources of the Brazilian Economic Exclusive Zone - Northeastern Score), converted to agefrequency using growth parameters obtained from local studies or from FishBase (www.fishbase.org).  For most of the species there was no historical trend of total mortality rates. In these cases, when only more recent estimates were available (as for example in Lessa et al., 2004), the trend available for similar species was used to estimate mortality rates in 1978. Thus, for reef fishes, the trend available for the southern red snapper was used, while for dolphinfish, trends from other large pelagics were used. For shrimps, the trend for Farfantepenaeus subtilis (Ehrhardt et al., 1999) was assumed for the group as a whole. For the remaining species, estimates were used as presented in the original source.  Consumption/Biomass (Q/B) Studies related to annual consumption of food by the groups included in the model built here are lacking in northeastern Brazil. The exceptions are those presented in Wiedemeyer (1997), whose study is restricted to estuarine areas. For almost all groups, Q/B was obtained from similar models for same or similar species, including the models constructed for northern and southeastern Brazil, or from FishBase. Most of these estimates are based on an equation that predicts consumption in relation to mortality, growth parameters, temperature, and caudal morphometries (Palomares and Pauly, 1998). P/Q values resulting from this estimates are  expected to be between 0.1 and 0.3, a limit considered physiologically realistic for most groups (Christensen et al, 2004). Q/B was changed when necessary in order to produce P/Q values within this range.  4.2.5. Diet composition  The diet matrix for each functional group was obtained as the percentage of each group in terms of total wet weight (or volume) in the diet of the predator, based on the sources presented in Appendix 4. However, some sources presented only frequency of occurrence or numerical importance of various food items and these data required translation into an appropriate format, based on information available for other areas and some indication of the individual prey weights. In the absence of any other information besides frequency of occurrence, all items were assumed to contribute equally to the diet of the predator.  The mixed trophic impact - MTI (sensu Leontief, 1951) was estimated using diet information. MTI allows for the assessment of the impact of changes of biomass of each group on other groups included in the model (Christensen et al, 2004). The resulting impacts are relative and may be compared amongst groups.  4.2.6. Landing data  Landing data used in the model were mostly obtained from the data compiled in Chapter 3 CATCHDAT for 1978 (see sources therein), with the exception of landings of tuna and tunalike fishes (Thunnus alalunga, Thunnus albacares, Thunnus obesus, Istiophorus albicans, Katsuwonus pelamis, Makaira nigricans, Tetrapturus albidus, and Xiphias gladius) originating from industrial fisheries, which were retrieved from the CATDIS-ICCAT database due to its  completeness. CATCHDAT provides landing data for all whales combined, not allowing for the split between the two groups considered in this model (baleen whales and toothed cetaceans). Thus, the landings were split according to the number of minke (baleen) and sperm whales (toothed) caught in 1978 (Singarajah, 1985), considering their mean individual weight (Trites and Pauly, 1998).  Landing data for 1978 were used as representing the 1970s as this is the earliest year for which landing data is separately recorded by fishery type in national sources (industrial and artisanal). Moreover, no complete list of species caught is available for the period between 1960 and 1977; landings were recorded only for those species that made up to 75-80% of total landings in each State. For earlier years, no species detail is provided and landings are recorded by very broad categories (fishes, crustaceans, molluscs, whales, and turtles). A l l values were expressed in tonnes-km" , considering the total study area as basis and not only the fishing ground area.  In order to establish the correspondence between common name and the group used in the model, the database compiled in Chapter 2 was used. Catches recorded by broad categories such as 'outros peixes', 'mistura', 'caico', and 'outras especies' were not included. They all represent unidentified species, which together accounted for about 6% of the total landings.  Catch data included in the model are restricted to landings and no estimate of discards or catches from other fishing activities such as recreational, subsistence, research, and illegal was added due to the absence of quantitative studies in the region, mainly through large areas  and related to the period being modelled (1970s). As such, landings represent an underestimation of the total extractions from the East Brazil LME.  4.2.7. Balancing the model  The procedure of connecting such diverse data into one single framework such as Ecopath with Ecosim is expected to show some incompatibilities, which are indicated by ecotrophic efficiencies greater than one (i.e., mortality is higher than production). Thus, some changes were incorporated in the original data from the sources presented in Appendices 3 and 4 in order to obtain an initial version of a balanced flux of biomass between functional groups and to make the data more appropriate to northeastern Brazil. Main changes were incorporated in the diet matrix, as this is one of the most uncertain input data in the model. In some cases, changes in the diet composition did not suffice and extra changes were required, which are described below. The following was based on ecotrophic efficiency largest to smallest:  a) In order to decrease the high ecotrophic efficiency of 'large carnivorous reef fishes', the proportion of this item in the diet of 'southern red snapper' was decreased by 80% (from 0.15 to 0.03); this was a plausible change as there was no indication of weight (or volume) of each prey item in the original source used. Adittionally, the proportion of cannibalism was reduced by 50% (from 0.04 to 0.02). These changes did not suffice and P/B was increased by 100% (from 0.18 to 0.37), as data presented in Lessa et al. (2004) for this group are probably underestimated considering the commercial fishery for this group; b) A 50% reduction of the proportion of 'bathypelagic fishes' in the diet of 'benthopelagic fishes' and 'squids' was needed (from 0.019 to 0.008 and from  0.284 to 0.114, respectively); the consumption by biomass for this group had to be decreased to 1/3 of its original value (from 9.5 to 3.2), with a resulting estimate compatible with other models; c) The proportion of 'seagrass' in the diet of 'needlefishes' was decreased by 50% (from 0.068 to 0.034); the same change was applied to the diet of 'omnivorous reef fishes' (from 0.023 to 0.011). The consumption of 'needlefishes' was reduced by 50%, resulting in a value similar to the estimate used by Mohammed (2003) for Grenada and the Grenadines, and to the estimate for 'small pelagics'. The estimate of seagrass production available for Pernambuco State was not able to support the grazing impact of all consumers in the larger area. This was accommodated by increasing the biomass of this group by 100% (from 100 to 200 tonnes-km" ); d) A 50% reduction of the proportion of zooplankton in the diet of shrimps and other molluscs was applied (from 0.336 to 0.168 and from 0.156 to 0.078, respectively); most of the original sources of diet data were from southern Brazil where zooplankton production is much higher than in the study area. The estimate of biomass from a local study in northeastern Brazil (9.62 tonnes-km" ; Schwamborn, 1997) seems to be too low. Thus, the original estimate was taken out and an ecotrophic efficiency of 0.95 was entered, leaving the biomass to be estimated by the model; e) P/B for microfauna was increased by 10% (from 280 to 308 year" ); 1  f) Phytoplankton biomass was increased by 30% (from 9.29 to 12.08), resulting in an estimate consistent with other models for the tropical western Atlantic; g) The biomass value for squids, corresponding to 1/100 of the value provided by Vasconcellos (2002) for the South Atlantic (0.0042 tonnes-km" ), seemed to be too 2  low for the study area. Thus, this value was set to be estimated by the model, given an ecotrophic efficiency of 0.9 available from the same source.  The resulting model is expected to be able to reproduce observed trends in the time series of abundance, natural, fishing or total mortality, or catches available for any of the groups included in the model. In order to check for this correspondence, the Ecosim module of EwE was used and will be described in the next section.  4.2.8. Time-dynamic simulation using Ecosim  The Ecosim module allows for time-dynamic simulation of changes in biomass for each functional group based on the following equation (Walters et al, 1997; Christensen et al, 2004): (7)  ^ = g, at  " j  +  h ~(MO,. + F + e,)• B t  t  j  where: dB,/dt = change in biomass of group /; g, = net growth efficiency; Q/, = consumption of group j by group i; n = number of functional groups; Qy = consumption of group i by group j; I, = immigration of group i; MO, = non-predation natural mortality rate of group /; F, = fishing mortality rate of group i; e, = emigration of group i; and B, = biomass of group /.  One of the pillars of Ecosim is the 'foraging arena theory', which states that prey are not always available to predators, but they interchange between vulnerable and unvulnerable pools based on the trade-off between the risks of being eaten or starving (Walters and Juanes, 1993; Christensen et al, 2004). The rate at which prey move from one pool to another is called vulnerability. This assumes high values if the ecosystem is dominated by a top-down control  and low values if a bottom-up control is dominant (Christensen et al, 2004). Thus, the amount of a prey / consumed by predator j (Q,y) depends on the vulnerability (v,y) and is defined by:  J  2v a . y+  y Bj  where ay = effective search rate of predator j feeding on prey i; B, = prey biomass; and B = y  predator biomass.  Vulnerabilities (v,y) cannot be directly estimated, so they were evaluated by changing the default values (2) in order to fit the predicted Ecosim simulations to the observed time series of relative or absolute biomass, using times series of fishing mortality or fishing effort to drive changes in biomass for those groups for which data were available. The sum of the squares between the observed and the predicted time series was used to decide which vulnerability value produced the best fit (Christensen et al, 2004).  All available time series were simultaneously incorporated into the model through the use of a comma-delimited file (CSV). However, changes in the vulnerability settings were made in one group at a time, beginning with those groups better rooted in local data: spiny lobsters, southern red snapper, baleen whales, and toothed cetaceans. These were followed by tuna and tuna-like fishes for which ICCAT time series were used as a proxy for local data. All time series used are as follows:  a) Spiny lobsters Catch per unit of effort (CPUE) of spiny lobsters (Panulirus argus and P. laevicauda) was used as an estimate of abundance as no direct estimate was available. These data were  obtained from Ivo and Pereira (1996) for 1978-1994 and complemented by an estimate for 2000 available in Castro e Silva (2003). A linear trend for CPUE between 1994 and 2000 was assumed in order to estimate missing values of CPUE (1995-1999). The resulting series was then used to back-calculate the effort in trap-days required to produce the spiny lobster catches compiled in Chapter 3. This effort series was used as a driving function for this group in Ecosim and, as such, had to be complete (Christensen et al, 2004). CPUE trend was converted into biomass trend using the biomass estimated by the model as the starting point. b) Southern red snapper Similarly to spiny lobsters, CPUE of L. purpureus was used as a proxy for the trend in biomass changes, based on Paiva (1997) for the period 1978-1992. No estimate of CPUE was found for later years, with the exception of an indication that it has been in average 3 kg-hookday" (Fonteles Filho, undated). This was used for 1993-2000 and the effort required to obtain 1  the catch data for this species compiled in Chapter 3 was estimated. The resulting effort series was used to drive changes in biomass of L. purpureus in the EwE simulations. c) Whales Times series of catch data (in weight) for baleen whales (minke whale) and toothed cetaceans (sperm whale) were obtained from catches in number presented by Singarajah (1997), using a mean individual weight of 6.6 and 18.5 tonnes, respectively (Trites and Pauly, 1998). The resulting values were adjusted to the total catch recorded in the national fishery statistical bulletins and compiled in Chapter 3. Fishing effort was considered constant until 1980 for toothed cetaceans and until 1985 for baleen whales, as only one vessel was involved in whaling in this area (Rabay, 1985). For the remaining years, fishing effort was considered zero due to the ban of whaling activities in Brazilian waters.  d) Tunas Trends in biomass for the whole Atlantic Ocean were used for yellowfin and bigeye tunas, based on the hypothesis of one stock for the whole Atlantic (ICCAT, 2004b; 2005a). Fishing mortality (F) trends for both species were obtained from ICCAT (2004b). For albacore, the trend in biomass available for the Southern Atlantic (south to 5°N) was used, based on the hypothesis of two stocks (ICCAT, 2004a). No time series of fishing mortality was found for this species. The trends in biomass and fishing mortality were translated into absolute values for the study area using Ecopath values as starting points. An average for all species for which information was available was considered as representative of the whole group. e) Swordfish For swordfish, a time series of  B/BMSY  (MSY = maximum sustainable yield) was  obtained from ICCAT (2003) for the Southern Atlantic stock. This trend was translated into absolute biomass using the biomass at the Ecopath level as the starting point. A time series of fishing mortality for this stock was obtained from the same source and was used to drive changes in biomass for this group in EwE. f) Sharks ICCAT (2005b) presents very preliminary information about the abundance of sharks based on the ratio of shark to tuna catches. These estimates are available only for blue shark Prionace glauca, which corresponds to about 60% of the sharks caught by longliners in Brazilian waters (ICCAT, 2005b), and for shortfin mako (Isurus oxyrinchus). An average trend in biomass was obtained using the biomass estimated by Ecopath for 1978 and the trend in  CPUE available for blue shark and of absolute biomass for shortfin mako for the Southern Atlantic. g) Other large pelagics A trend in  B/BMSY  was used for blue marlin (Makaira nigricans) and white marlin  (Tetrapturus albidus), assuming the existence of one single Atlantic stock for both species (ICCAT, 2004b). For skipjack, a series of absolute biomass for the whole Atlantic was obtained from ICCAT (1999). Sailfish (Istiophorus albicans) and longbill spearfish (Tetrapturus pfluegeri) have been historically caught and assessed together. Although this has changed in the last years, the assessment for Western Atlantic is still based on this composite. A trend in CPUE was used for the composite (ICCAT, 2004b) and combined with the trend for other species, using the biomass defined in the Ecopath model as the starting point to obtain a time series of biomass. Trends in  F/FMSY  were obtained for blue marlin, white marlin, and  sailfish/spearfish from ICCAT (2004b). For skipjack, a series of fishing mortality was available in ICCAT (1999). These trends were combined for the whole group and expressed based on the value of fishing mortality estimated for 1978 at the Ecopath level. The resulting trend was used to drive changes in biomass for 'other large pelagics'.  After the adjustments of vulnerabilities were made, changes in biomass for the period 19782000 were assessed for some groups using Ecopath with Ecosim.  4.3. Results  The basic input matrix obtained in the balanced trophic model of the 1970s for the marine ecosystem off northeastern Brazil is presented in Table 4.1. Forty-one functional groups were  assumed to describe the main trophic relationships, with a total biomass (excluding detritus) of 222 tonnes'km" estimated for this ecosystem.  The diet matrix for the northeastern Brazil marine ecosystem obtained in this study for the 1970s model is presented in Table 4.2. The mixed trophic impact (MTI) analysis allows a better understanding of the impact of one group over the others. Most of the impacts are quite modest, probably due to the highly reticulated diet matrix. However, seagrass and macroalgae exert a strong positive impact on manatee and herbivorous reef fishes, respectively (Fig. 4.1). A high negative impact of omnivorous reef fishes is observed over spiny lobsters. Sharks have a negative impact, as a predator, over swordfish.  A model is considered a reasonable representation of one system if it is able to reproduce with some degree of confidence some observed patterns. The model was not able to reproduce the observed changes in biomass available for spiny lobsters, southern red snapper, and tuna and tuna-like fishes, unless adjustments in the vulnerability were made from the default (2.0). Thus, for spiny lobsters and southern red snapper, the vulnerabilities that resulted in the best fit were 1.2 and 1.3, respectively (Fig. 4.2). For swordfish and other large pelagics, low values (1.3 and 1, respectively) produced the best fit as well (Fig. 4.3). For tunas, a vulnerability of 8 was able to produce a good fit between the ICCAT series of biomass and the value predicted by the model. For sharks, changes in vulnerability did not result in much difference in the predicted values; the model was still able to capture some of the decline of sharks observed in the Atlantic, but not at the level indicated by ICCAT (2005b). No changes in the original basic input were incorporated at this stage.  After the vulnerabilities adjustments were made, the final changes in biomass for many of the groups could be assessed. The largest changes were observed for spiny lobsters and swordfish (Fig. 4.4), which declined to 12 and 14% of the biomass in the beginning of the period (1978), respectively. Tunas, other large pelagics, and sharks presented intermediate decline rates of biomass, reaching 52%, 72%, and 85% of the original biomass, respectively. A slight increase in biomass was observed for toothed cetaceans, large carnivorous reef fishes, and dolphinfish (1.7 to 6.9%). Southern red snapper (L. purpureus) presented a decline in biomass until 1996 and seemed to recover to levels above the observed in the Ecopath level. For the remaining species, changes in biomass (positive or negative) were very low and are not shown.  EwE provides a series of system statistics that allow for the comparison amongst different ecosystems and details about the equations used to obtain each estimate are available in Christensen et al. (2004, available at www.ecopath.org). In order to compare these statistics, an analysis of the sensitivity of the system statistics provided by EwE to the aggregation of the 41 functional groups included in the model was performed after aggregating the original groups into 31 and 21 groups. This procedure indicated that all the statistics provided remained within the range between +20 and -20% of the original value, with the exception of the connectance index, the throughput cycled (excluding detritus), and the predatory cycling index (Fig. 4.5). Thus, these statistics should not be used in the comparison of the characteristics of the ecosystem studied here with other ecosystems in Brazil or in other tropical shelves.  Table 4.1: Basic input for the 1970s Ecopath with Ecosim model for the marine ecosystem off northeastern Brazil. B = biomass in the habitat area (wet weight); P/B = production/biomass; Q/B = consumption/biomass; and EE = ecotrophic efficiency*. B P/B Q/B Catches EE (tonneskm") (year ) (tonneskm" (year') 0.00 0 0.0002 0.06 27.38 1. Manatee 0.30 0.003130 0.3852 4.62 0.03 2. Baleen whales 0.000307 0.50 0.1427 10.85 0.08 3. Toothed cetaceans 0 (0.38) 0.0150 80.00 5.40 4. Seabirds 0.000006 0.50 0.1630 22.00 0.15 5. Sea turtles 0.003420 0.99 0.0350 0.82 8.00 6. Tunas 0.005786 0.72 0.0257 0.64 9.60 7. Other large pelagics (0.43) 0.000872 20.44 0.0005 4.36 8. Dolphinfish 0 (0.31) 0.0013 59.21 13.08 9. Dolphinfish juveniles 0.99 0.000190 0.0090 0.29 4.00 10. Swordfish 0.004471 0.60 (0.0324) 0.27 4.00 11. Sharks 0.41 0.001871 (0.1013) 0.50 3.50 12. Rays 0.99 0.004061 (0.6045) 4.41 12.45 13. Small pelagics 0.99 0.000656 (0.1150) 18.95 5.42 14. Needlefishes 0.005490 (0.90) 0.0143 5.30 0.73 15. Southern red snapper 0.81 0.015600 6.34 0.37 16. Large carnivorous reef fishes (0.2338) 9.22 0.86 0.002100 (0.9726) 1.57 17. Small carnivorous reef fishes 0.39 0.000052 (1.1164) 0.55 23.13 18. Herbivorous reef fishes 0.005680 0.95 (1.1400) 0.44 10.57 19. Omnivorous reef fishes 0.95 0.041052 (1.3468) 10.27 1.93 20. Demersal fishes 0.008000 0.86 (0.7631) 1.03 22.60 21. Mullets (0.24) 0.000045 10.80 0.0500 0.82 22. Spotted goatfish 3.18 0.80 0.000768 (0.0746) 0.78 23. Benthopelagic fishes 1.1710 5.44 (0.71) 0 1.90 24. Bathypelagic fishes 0.99 0.007960 7.40 (0.0138) 1.28 25. Spiny lobsters 0.90 0 (0.6111) 0.35 7.40 26. Other lobsters 0.012430 0.99 (3.9006) 2.73 13.45 27. Shrimps 10.82 0.99 0.005300 (1.5077) 5.23 28. Crabs 0.90 0 (0.1767) 6.40 36.50 29. Squids 0.85 0.000005 (0.1510) 6.76 1.90 30. Octopus 0.95 0.001580 (2.5310) 18.87 3.30 31. Other molluscs 0.000003 0.95 50.77 (1.5906) 19.58 32. Other crustaceans 0.91 0 6.74 (6.9979) 2.34 33. Other invertebrates 0.95 0 26.04 165.00 (2.1656) 34. Zooplankton 0.98 0 (0.0631) 1.09 4.23 35. Corals (0.09) 0 560.00 5.9890 308.00 36. Microfauna NA (0.08) 0 12.0860 157.04 37. Phytoplankton NA (0.09) 0 98.4060 13.25 38. Macroalgae NA (0.004) 0 77.7620 66.46 39. Mangroves NA (0.09) 0 0.0520 100.00 40. Seagrasses NA** NA (0.33) 0 201.9130 41. Detritus Values in parentheses were estimated by Ecopath with Ecosim. **NA = not applicable. Group name  2  1  Table 4.2: Diet matrix for the 1970s Ecopath with Ecosim model for the marine ecosystem off northeastern Brazil" 10  Prey / Predator  12  13  14  15  16  17  18  1. Manatee 2. Baleen whales 3. Toothed cetaceans  0.0035  0.0018  4. Seabirds  0.0177  0.0250 0.0082  5. Sea turtles 6. Tunas  0.0086  7. Other large pelagics  0.0126  0.0251  0.0264  0.1702  0.0264  0.0351  0.0019  8. Dolphinfish 0.0029  9. Dolphinfish juv.  0.0105  0.1783 0.0194  10. Swordfish 11. Sharks  0.0107  0.0084  12. Rays 0.2500  13. Small pelagics  0.0834  0.4568  0.0976  14. Needlefishes  0.1626  0.3247  0.2273  0.0334  0.0059  0.0041  15. Southern red snapper  0.0034  0.0001  0.0001  16. Large carnivorous reef fishes  0.0310  0.0009  0.0009  17. Small carnivorous reef fishes  0.0247  0.1089  0.3023  0.3023  18. Herbivorous reef fishes  0.0019  0.0012  0.0003  19. Omnivorous reef fishes  0.0377  0.1245 0.0003  0.0720  20. Demersal fishes  0.2890  0.1331  0.0163  0.0153  0.0835  0.1239  0.0302  0.3944  0.0114  0.0030  0.1030  0.1235  0.1158  0.0158  0.0003  0.0003  0.0402  0.0071  0.0535  0.0535  0.2989  0.0553  0.0014  0.0003  0.0003  0.0734  0.3537  0.0295  0.0193  0.0986  0.1915  0.0942  0.0404  0.0188  0.0267  0.0188  0.0986  0.0392 0.0295  0.0300  0.0845  0.0069 0.2978  0.0063  0.3547  0.0659  0.0659  0.0051 0.0002  0.0046  0.0605  0.3602  0.0376  0.0001  0.0002  0.0092  0.0038  0.0680  0.0103  0.1081  0.0457  0.2012  0.1353  0.0859  0.0074  0.0457  0.2563  0.1349 0.0009  0.0002  25. Spiny lobsters 0.0034  26. Other lobsters 0.0043  27. Shrimps 28. Crabs 0.0060  29. Squids  0.4790  30. Octopus  0.0043  31. Other molluscs  0.0300  0.0001  0.0014  0.2209  0.0739  0.0192 0.0048  0.0043  0.0135 0.6420  34. Zooplankton  0.2969  0.2200  0.1057  0.4539  0.1129  0.0022  0.0003  0.0001  0.0001  0.0001  0.0209  0.1443  0.0968  0.1552  0.0281  0.2809  0.1272  0.0766  0.0005  0.0101  0.0032  0.0126  0.0186  0.0022  0.0022  0.0022  0.0567  0.0018  0.0101  0.0323  0.0003  0.0003  0.0002  0.0406  0.0229  0.0003  0.0118  0.0118  0.0002  0.0328  0.0057  32. Other crustaceans 33. Other invertebrates  0.0649  0.0015  0.0001  24. Bathypelagic fishes  0.0649  0.0010  0.0003  22. Spotted goatfish 23. Benthopelagic fishes  0.0100  0.1972  0.0000  21. Mullets  0.0877  0.0060  0.0004  0.0002  0.0510  0.1433  0.0374  0.0055  0.1923  0.0016  0.0617  0.1432  0.0143  0.0306  0.0643  0.0077  0.0350  0.0283  0.1195  0.0030  0.0732  0.0001  0.0348  0.3935  0.6100  0.0026  0.1373  0.0118  35. Corals 36. Microfauna  0.2077  37. Phytoplankton 38. Macroalgae  0.0436  39. Mangroves  0.1465  40. Sea grasses  0.7964  41. Detritus  0.0436  0.1569 0.0302 0.1095  0.0028  0.0003  0.0173 0.0342  0.0199  1.0000  Table 4.2: Diet matrix for the 1970s Ecopath with Ecosim model for the marine ecosystem off northeastern Brazil* (continued). Prey/Predator  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  1. Manatee 2. Baleen whales 3. Toothed cetaceans 4. Seabirds 5. Sea turtles 6. Tunas 7. Other large pelagics 8. Dolphinfish 9. Dolphinfish juv. 10. Swordfish 11. Sharks 12. Rays 13. Small pelagics  0.0004  0.0016  0.0929  0.0954  0.0465  14. Needlefishes 15. Southernredsnapper 16. Large carnivorous reef fishes  0.0001  17. Small carnivorous reef fishes  0.0071  18. Herbivorous reef fishes  0.0002  19. Omnivorous reef fishes  0.0019  20. Demersal fishes  0.0599  21. Mullets  0.0314  0.0002 0.0003 0.0440 0.0500  0.0218 0.0443  0.0003  0.0164  0.0446  0.0392  0.0228  0.0011  0.0147  0.1271  0.0106  0.1612  0.0730  0.0123  0.0110  22. Spotted goatfish 23. Benthopelagic fishes  0.0443  24. Bathypelagic fishes  0.0076  0.0564  0.0255  25. Spiny lobsters  0.0008  26. Other lobsters  0.0008  27. Shrimps  0.0405  0.2587  0.2250  0.2210  28. Crabs  0.2336  0.0718  0.3110  0.0036  29. Squids  0.0004  30. Octopus  0.0045  31. Other molluscs  0.1749  0.0084  0.0024  0.0770  0.0412  0.0309  32. Other crustaceans  0.2791  0.1729  0.0050  0.1530  0.3046  0.0839  33. Other invertebrates  0.0849  0.2021  0.0024  0.1900  0.0887  0.0371  34. Zooplankton  0.0074  0.1567  0.0050  0.0607  0.6429  0.0001 0.0422  0.0003  0.2049 0.0003  0.2930 0.1075  0.5000 0.5000  0.0021  0.0090  0.3689  0.0726  0.0398  0.0905  0.1682  0.0054  0.1113 0.1856  0.0615 0.5975  0.0008  0.0087  0.0032  0.1144  0.0172  0.0113  0.0159  0.0251  0.0779  0.0273  0.0438  0.0001  0.0003  0.1182  0.0188  0.0018  0.1985  0.0010  0.1930  0.0009  0.5020  0.0407  0.1050  0.1179  0.0752  0.0001 0.0470  0.1022  0.0710  0.0006  0.1961  0.0054  37. Phytoplankton 38. Macroalgae  0.4785 0.0051  35. Corals 36. Microfauna  0.0141 0.1934  0.0500  0.1625  0.0696  0.4000  0.5875  0.0339  0.3300  0.3086  0.1429  0.0134  0.000069  0.000001  0.00004  0.5344  0.6889  0.0045  0.2624  39. Mangroves 40. Seagrasses  0.0114  41. Detritus  0.0137  0.0134 0.0361  0.6685  0.0013 0.3499  0.2026  0.1204  0.2200  0.2500  0.9821  * Functional groups 37-40 and 41 do not require predator column as they refer to primary producers and to the product of the degradation of all groups included in the model respectively.  IMPACTED GROUP  e |  g,  -a,  I 8 §> 1 I -s 8 I I M »i l l 1 s s i 1 j .i g g g J I | e  ffl  H  «  «5  H  Manatee ~ ™ ^ — — " ~ " ™ ~ — — — Baleen whales L U Toothed cetaceans ' ' Seabirds Sea turtles Tunas — — — — — _ Other large pelagics ~~ Dolphinfish 1—i Dolphinfish juv. , Swordfish ^——————— Sharks i i a — m Rays Small pelagics Needlefishes Southern red snapper Large carnivorous reeffishes• Small carnivorous reeffishes• Herbivorous reef fishes Omnivorous ummvorous reef reei nsnes fishes Demersal fishes Mullets Spotted goat fish Benthopelagic fishes Bathypelagic fishes Spiny lobsters Other lobsters Shrimp Crabs Squids Octopus Other molluscs Other crustaceans Other invertebrates Zooplankton Corals Microfauna Phytoplankton Macroalgae Mangroves 1  :  £j O ^ ^ Q ^ *-  1  i  i  |  |  Detritus  Figure 4.1: Mixed trophic impact in northeastern Brazil marine ecosystem for the 1970s. The impact in each group is positive when placed above the line and negative when below.  a) 0.016  r  0.000 1977 1  J  1980  1  1983  — 1986 1  1  1989  1  1  1992  1  1995  1  1998 2001  Figure 4.2: Verification of the model: observed time series (dots) of biomass for spiny lobsters (a) and southern red snapper (b) off northeastern Brazil and estimated valuesfromEcopath with Ecosim under four values of vulnerability V (lines) for the periodfrom1978 to 2000. The thicker line is associated with the vulnerability value used in the final version of the model.  0.000 1977  1980  1983  1986  1989  1992  1995  1998  2001  Figure 4.3: Verification of the model: observed time series of biomass (dots) and estimated values (lines)fromEcopath with Ecosim under different settings of vulnerability (v) for swordfish (a), other large pelagics (b), sharks (c), and tunas (d) off northeastern Brazil in 1978-2000.  Figure 4.4: Changes in biomass in relation to the Ecopath level (1.0) for some groups included in the 1970s model of the marine ecosystem off northeastern Brazil (1978-2000). The remaining groups did not show any significant changes. 0.4 to  3  s 60 St M  M3,=0.01  i  0.0  ^ , = 0.03  i  -0.4  (/) -0.8 op CO  -1.2  >>  00  -1.6  s  -2.0 31 groups  21 groups  Figure 4.5: Variation of the system statistics (SyS) for the East Brazil Large Marine Ecosystem obtained with Ecopath with Ecosim models using 31 and 21 groups (SySi  ess  groups)  in relation to the  original 41 groups model (SyS i). Open circles correspond to the connectance index, open squares to 4  the throughput cycled (excluding detritus), and open triangles to the predatory cycling index. M i and 3  M i indicate the mean absolute variation of the system statistics using 31 and 21 groups in relation to 2  the baseline (41 groups).  Northeastern Brazil marine ecosystem, as represented in this model, presents a total system throughput of 23,042 t-km^-year" (Table 4.3). This value is equal to the sum of all flows in 1  this system, including consumption, export, respiration, and flow to detritus, and indicates the size of the system in terms of flows (Ulanowicz, 1986). Of this total, 18% represents consumption by predators, 30% is exported, 6% is lost via respiration, and a very high proportion flows into the detritus group (46%). Total primary production is 8,375 t-km" -year"', 2  with 22% originatingfromphytoplankton and the remainingfrommangroves, macroalgae, and seagrass. Only 3.4% of this production is consumed and the rest goes into the detritus. The primary production of this system exceeded the respiration (P/R=1.5) and the total biomass (P/B=15.4) of all functional groups included in the model.  In terms of catches, they added up to 0.13 t-km" -year"' (Table 4.3), with demersal fishes 2  accounting for 33%, reef fishes for 17%, shrimps for 10%, spiny lobsters for 6%, and tuna and tuna-like fishes for 5% of this total. The mean trophic level of the catch was 3.4, and the primary production required was 1.3%. The gross efficiency of catches in this area, defined as the ratio of catch to primary productivity (Christensen et al., 2004) was 0.00002.  The trophic aggregation analysis indicated the existence of ten discrete trophic levels {sensu Lindeman, 1942). The ninth trophic level encompasses only dolphinfish, swordfish, and sharks (Table 4.4). Microfauna and herbivorous reef fishes are the only functional groups besides primary producers that operate at one single trophic level. All the other groups operate through a range of two to seven trophic levels, but concentrate at levels II to IV. The mean transfer efficiency between trophic levels (geometric mean weighted by flows for trophic levels II-IV) was estimated at 11.4%. Transfer from level I to II was low (6.4%), increasing to a maximum  Table 4.3: System statistics obtained from Ecopath with Ecosim for the 1970s model of East Brazil Large Marine Ecosystem (off northeastern Brazil), for other models of marine ecosystems off Brazil, and for models representing shelf ecosystems in tropical areas. Brazil Shelf This study Mangrove Coral reef Shelf Northeast North Northeast Southeast South 5584 43394 9098 23042 10559 Total system throughput 13119 2274 10364 3555 4178 Sum of all production 2988 1670 3134 9150 8375 Calculated total net primary production 16 18 16.7 12.1 6 Phytoplankton biomass 1670 1080 1920 2988 1900 Phytoplankton production 28.9 10.5 9 2.2 1.5 Zooplankton biomass 584 150 1156 945 57 Zooplankton production 1.2 3.3 0.6 0.9 6.6 Total primary production/total respiration 37.2 0.2 5.6 20.5 37.6 Total primary production/total biomass 0.04 0.02 1.24 0.01 0.01 Total biomass/total throughput 13132 1640 146 45 222.5 Total biomass (excluding detritus) 0.28 0.26 0.21 0.11 0.16 Omnivory Index 0.37 0.62 0.45 0.68 0.31 Prop, totalfluxoriginatingfromdetritus 10.4 12.6 6 11.4 9.3 Mean transfer efficiency between TL NA 1.67 0.99 268.30 0.13 Total catches NA 2.6 3.7 3.4 2.1 Mean trophic level of the catch NA 5.6 5.9 0.2 86000 Gross efficiency (catch- 10/net pp.) NA 22.0 30.7 2.5 Primary production required (catches) 1.3 7 97000 28661 1074984 220 Study area 22 25 13 41 19 Number of groups Statistic/Ecosystem  4  1  2  Other shelves Units  3  SE US Yucatan Venezuela SWGOM Grenada 5  7  6  14518 2049 5420 692 4336 454 5.6 7.9 1865 356 36.5 1.7 475 30 1.7 0.8 9.2 7.0 0.03 0.03 65 470 0.22 0.28 NP 0.43 NP 17.6 0.79 0.09 4.1 3.0 1.8 1.8 NP 53.6 174300 100000 42 21  8  9  7621 3699 3290 45 3150 8.2 328 1.8 27.0 0.02 122 0.32 0.27 6.6 5.20 2.8 16.0  7713 5029 4668 45.5 4687 5.7 124 4.1 44.4 0.01 105 0.36 0.53 9.2 0.31 3.5 0.7  14332 3755 3115 36.2 2534 2.5 100 1.0 24.3 0.01 128 0.26 NP NP 0.08 4.3 0.3  7.9 30000 16  6.7 65000 19  NP % 25957 km 51 groups  t-km"-year"' t-km^-year" t-km"-year" t-km" t-km"-year"' t-km" year" dimensionless dimensionless dimensionless t-km" dimensionless dimensionless 2  1  2  1  2  2  2  1  2  %  t-km"-year"' dimensionless dimensionless 2  2  1. From Wolff et al. (2000); 2. From Telles (1998); 3. From Gasalla and Rossi-Wongtschowski (2004); 4. From Vasconcellos and Gasalla (2001); 5. Southeastern United States, from Okey and Pugliese (2001); 6. From Arreguin-Sanchez et al. (1993); 7. From Mendoza (1993); 8. Southwestern Gulf of Mexico, from Manickchand-Heileman et al. (1998); 9. Grenada and the Grenadines, from Mohammed (2003). Note that some statistics were not provided in the original source and were obtained after re-entering the data, wherever the completeness of the basic input allowed. NA = not applicable and NP = not provided.  Table 4.4: Relativeflowsby discrete trophic level for the marine ecosystem off northeastern Brazil in the 1970s model. Flows through the trophic level X are too low to be shown. TL represents the fractional trophic level sensu Odum and Heald (1975). GroupYTfophic level  TL  I  Manatee Baleen whales Toothed cetaceans Seabirds Sea turtles Tunas Other large pelagics Dolphinfish Dolphinfish juv. Swordfish Sharks Rays Small pelagics Needlefishes Southern red snapper Large carnivorous reef fishes Small carnivorous reef fishes Herbivorous reef fishes Omnivorous reef fishes Demersal fishes Mullets Spotted goatfish Benthopelagic fishes Bathypelagic fishes Spiny lobsters Other lobsters Shrimps Crabs Squids Octopus Other molluscs Other crustaceans Other invertebrates Zooplankton Corals Microfauna Phytoplankton Macroalgae Mangroves Seagrasses Detritus  2.02 3.72 4.45 3.45 3.15 4.31 4.50 4.58 4.42 4.56 4.65 3.88 3.05 3.43 4.21 4.01 3.68 2.00 3.33 3.36 2.04 3.50 3.58 3.58 3.30 3.25 2.73 2.61 3.64 3.58 2.35 2.17 2,16 2.47 2.83 2.00 1.00 1.00 1.00 1.00 1.00  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1  II  III  0.9865 0.0119 0 0.4475 0 0.0759 0.1095 0.5045 0.1899 0.5298 0 0.1564 0 0.0588 0 0.1057 0 0.1078 0 0.0304 0 0.0990 0.0003 0.3950 0.2796 0.4710 0.0515 0.5465 0 0.2073 0 0.3323 0 0.5683 1 0 0.0722 0.6346 0.0819 0.6040 0.9664 0.0297 0 0.6389 0 0.5958 0 0.5693 0.1156 0.5953 0 0.7924 0.4209 0.4450 0.6124 0.2423 0 0.5097 0 0.6663 0.7038 0.2610 0.8431 0:1440 0.8810 0.0992 0.5789 0.4211 0.2500 0.6816 1 0 0 0 0 0 0 0 0 0 0 0  IV 0.0013 0.4517 0.5299 0.2694 0.2579 0.5007 0.5434 0.4383 0.5206 0.5524 0.4055 0.4164 0.2313 0.3620 0.4979 0.4466 0.3267 0 0.2180 0.2594 0.0037 0.2644 0.3032 0.3895 0.2068 0.1801 0.1285 0.1150 0.4115 0.2503 0.0348 0.0127 0.0196 0 0.0684 0 0 0 0 0 0  V  VI  0.0003 0 0.0906 0.0090 0.3330 0.0561 0.0990 0.0164 0.0192 0.0030 0.2991 0.0381 0.3358 0.0548 0.3326 0.1048 0.3065 0.0583 0.3348 0.0719 0.3445 0.1301 0.1596 0.0265 0.0153 0.0027 0.0376 0.0022 0.2528 0.0369 0.1781 0.0390 0.0937 0.0104 0 0 0.0631 0.0113 0.0508 0.0038 0.0002 0 0.0826 0.0132 0.0929 0.0075 0.0370 0.0036 0.0677 0.0140 0.0272 0.0002 0.0055 0.0001 0.0291 0.0012 0.0724 0.0058 0.0714 0.0114 0.0003 0 0.0002 0 0.0002 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0  VII 0 0.0011 0.0048 0.0012 0.0002 0.0052 0.0066 0.0169 0.0063 0.0096 0.0188 0.0021 0.0001 0.0003 0.0047 0.0037 0.0008 0 0.0006 0.0001 0 0.0009 0.0006 0.0006 0.0006 0 0 0 0.0005 0.0006 0 0 0 0 0 0 0 0 0 0 0  VIII  IX  0 0 0 0.0001 0.0003 0 0 0 0 0 0 0.0005 0.0006 0 0.0016 0.0001 0 0.0005 0.0009 0.0001 0.0020 0.0002 0.0001 0 0 0 0 0 0 0.0003 0.0002 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0001 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0  from level III to IV (16.6%) and decreasing thereafter to 4.3% at level IX. The estimated omnivory index, calculated as the average omnivory index of all predators weighted by the logarithm of each predator's food intake (Christensen et al, 2004), was 0.21.  4.4. Discussion  This study represents the first attempt to model the trophic components of the whole marine ecosystem off northeastern Brazil. Two previous studies dealt with a small reef area off Bahia State (Telles, 1998, using EwE) and a mangrove area off Pernambuco State (Wiedemeyer, 1997, not using EwE) (Table 4.3). As a first attempt, this required a considerable effort to gather information for an area that is much less studied than the southeastern and southern regions for which trophic models have already been constructed using EwE (Rocha et al, 1998; Vasconcellos, 2000; Gasalla and Rossi-Wongtschowski, 2004).  The characteristics of the ecosystem modelled in this study will be discussed here and at the same time compared with other models constructed for Brazilian marine ecosystems and for tropical continental shelves along the western Atlantic (see Table 4.3). The models presented for comparison were chosen due to the use of similar methodology, but all of them refer to more recent periods. Telles (1998) found much higher biomass for most of the functional groups in the Abrolhos region (southernmost part of my study area). However, Telles modelled a very small (7 km ) reef area, which has been protected since 1983, and which 2  therefore is expected to harbour a higher biomass per unit of area. Wiedemeyer (1997) restricted the analysis to a small mangrove subsystem embedded in an estuarine system (35 km ) and dealt only with the benthic food web. Wolff (2000) also analyzed a small mangrove 2  area (220 km ) to the north of the area studied in this thesis and found extremely high total 2  system biomass per unit of area, mainly of mangrove vegetation. Part of the results of all these models were used in the model of northeastern Brazil constructed here, and may be seen as representing different subsystems embedded in a larger ecosystem. Thus, most of the comparisons below will be restricted to shelves areas both in Brazil and other countries.  The total system throughput (23,042 t-km" -year" ) indicates that this system is similar in size 2  1  to the Southeastern United States and Grenada and Grenadines in terms of amount of flows. The total primary production off the northeastern coast of Brazil was the highest amongst the shelves cited here. However, we must consider that some of these models were built to analyze specific subsystems such as the one for south Brazil, which aimed to assess the pelagic subsystem and did not include coastal systems. Thus, they did not include all primary production generated by benthic producers in these areas. The biomass originating from phytoplankton off northeastern Brazil (12.1 t-km" ) was lower than in Venezuela, 2  Southwestern Gulf of Mexico, and Grenada and Grenadines (36-46 t-km" ), but higher than 2  southeastern United States and Yucatan.  Vasconcellos and Gasalla (2001) and Gasalla and Rossi-Wongtschowski (2004) worked with large shelf ecosystems in southern and southeastern Brazil. The phytoplankton biomass in those areas was higher than in the marine ecosystem off northeastern Brazil (Table 4.3), as also reported by Matsuura (1995). However, the P/B ratio for phytoplankton may be slightly overestimated in the northeastern region (157 year" ), as it results in a production level that 1  surpasses the value for southern Brazil, a system dominated by Engraulis anchoita. That value is also very close to the P/B for southeastern Brazil (166 year" ), an area associated with 1  upwelling processes and highly influenced by small pelagics (in this case, Sardinella brasiliensis).  One important system statistic of an ecosystem is the omnivory index, which measures the degree to which a system exhibits weblike characteristics, i.e., how the interactions are spread amongst trophic levels. Pauly et al. (1993) suggested the use of this index as an alternative to the connectance index, which is highly affected by the number of functional groups included in the model. The omnivory index was 0.21, very similar to all other shelf systems considered (Table 4.3), which indicates that the functional groups are specialized, consuming food items over a few trophic levels. If we consider that the omnivory index is correlated with maturity in the same fashion as the connectance index (Odum, 1969), then one would say that northeastern Brazil would be on the immature side of the maturity spectrum. This hypothesis is supported by the high ratio of system primary production to respiration (6.6), but not by the high ratio between system primary production and biomass (37.6). The latter is one of the highest amongst the shelf systems presented in Table 4.3, and is very similar to the ratio observed in southern Brazil.  Detritus seems to have an important role in the marine ecosystem off northeastern Brazil considering that only about 3% of the total primary production is consumed and the remaining flows to the detritus, and 62% of the total flow in this system originates from detritus. Pace et al. (1984) points out that failure to properly consider different components of the zooplankton may lead to an overestimation of the detritus originating from phytoplankton. However, this is not expected to produce a large effect on this model as most of the primary production originates from benthic producers. Of all inflows to detritus, about 29% is derived from  recycling, the highest percentage amongst the shelves analyzed here. The understanding of the recycling capacity of a system is important, as it is closely related to its ability to recover from perturbations (Vasconcellos et al, 1997).  Petersen and Curtis (1980) suggest that an efficient system of recycling between phyto- and zooplankton would decrease the amount of nutrients available to benthic communities in tropical areas, which would be characterized by important pelagic fisheries in detriment of demersal fisheries and short food chains. The system analyzed here indicated that the biomass of demersal fishes was high and did support high catches (probably underestimated due to the non-inclusion of discards). This would reveal the importance of coastal vegetation and the detritus resulting from its decay to support a benthic community.  Total extractions (catches) from the marine ecosystem off northeastern Brazil were 0.13 tkm" , a level very similar to southeastern US, Yucatan, and Grenada and the Grenadines. The mean trophic level (TL) of the landings was 3.4, which was higher than the model representing the northern mangrove area (2.1) where mangroves were by far the most exploited resource, followed by mangrove crabs (Ucides cordatus). In southeastern Brazil, where sardine is the main fish resource (Paiva, 1997), Gasalla and Rossi-Wongtschowski (2004) found a mean trophic level of catches of 2.6. As these authors constructed a model for 1998-1999, after the collapse of sardine fisheries in that region, the difference between the mean trophic of catches originating from northeastern and southeastern Brazil is expected to be higher in the late 1970s, when catches of sardine (TL = 2.8) were about 7 times higher than in 1999 (according to the database compiled in Chapter 3). In southern Brazil, the mean trophic level of catches was higher (3.7) than in northeastern Brazil. Even though sardines dominate fisheries in  southern Brazil, demersal fishes such as drums, croakers, and hakes (TL = 3.5 to 4.1) are also heavily targeted, leading to an increased trophic level. The mean trophic level of landings in the Caribbean was higher than in northeastern Brazil, as a result of the greater importance of tuna fisheries in the Caribbean and the deficient coverage of inshore fisheries for lobsters and reef species (Mohammed, 2003).  The gross efficiency of the fisheries (catch divided by net primary production) in northeastern Brazil (0.00002) was the lowest amongst the systems compiled in Table 4.3 and also lower than the weighted global average of 0.0002 (Christensen et al, 2004). It is reasonable to assume that the low gross efficiency was related to the underexploitated state of most of the resources in the 1970s. The value of primary production required (PPR) for catches originating from northeastern Brazil was very low (1.3%) compared to the values estimated by Pauly and Christensen (1995) for global catches (8%), for tropical shelves (16.1-48.8%), and for the shelf models compiled in Table 4.3. Primary production required (primary production required to sustain catches-100/observed primary production) is seen as an indication of the ecological footprint of human activities and would imply that catches in northeastern Brazil were having a very low impact on the marine ecosystem. However, one has to consider that only landings were included in the model, not considering any discards. Additionally, landings recorded in very broad categories such as 'outros peixes', 'outras especies', 'caico', and 'mistura' (all representing other species) were not incorporated in the model. Finally, estimates of primary production estimate for mangroves from Wiedemeyer (1997) may be overestimated. Thus PPR, as calculated here, underestimates the overall impact of fisheries on this ecosystem.  The mean transfer efficiency between trophic levels of 11.4% was very close to the mean calculated by Pauly and Christensen (1995) over 48 trophic models (10%), with the highest value observed between trophic levels III and IV (16.6%). Pace et al. (1984) consider that trophic efficiency is highly variable and the use of a standard value of 10% may be misleading. Note that the values of transfer efficiency for the models presented in Table 4.3 oscillate between 6.6 and 17.6%, within the range indicated by Pauly and Christensen (1995), and in fact bracket their mean value of 10%.  All the comparisons of system statistics may be affected by the definition of the system and its functional groups, and by the origin of the input data. More insight would be gained if a model for the current time is built for the same system and the system statistics for both periods are compared. However, because of the scarcity of basic data for northeastern Brazil, both models (early and current period) may be based on the same data and systems statistics would not differ much (see, e.g., Araujo et al, 2005, available online at www.cefas.co.uk/news.asp). The original setting of the 1970s model is limited as biomass estimates for most groups were not available due to the lack of biomass surveys for this region. Biomass was estimated by the model using ecotrophic efficiency from models of similar areas. Mortality rates for some groups were also borrowed from similar areas and may not reflect the actual fishing pressure occurring off northeastern Brazil.  Several papers dealing with the diet of species in northeastern Brazil present only the frequency of occurrence or numerical frequency of prey in the gut of their predators (Alves and Fernandes, 1973; Rodrigues, 1974; Vasconcelos Filho, 1979; Vasconcelos Filho et al, 1984; Cunha and Furtado, 1985; Macedo Costa et al, 1987; Vasconcelos Filho and  Cavalcanti, 1993). Gasalla and Soares (2001) reviewed the evolution of diet studies in Brazil and pointed out the 1990s as a benchmark in terms of the studies of trophic relationships in Brazilian ecosystems. However, these authors did not mention changes in the nature of the basic data of diet composition provided by these studies. For northeastern Brazil, for example, several past diet studies cannot be properly incorporated in food webs studies owing to the absence of proportion in weight (or volume) of prey items. Thus, results from other regions had to be considered instead. Moreover, there is the persistent problem of combining several species into one single functional group, a procedure that can mask important linkages in terms of predation or competition (Paine, 1988).  Even though these constraints limit the interpretation of the results presented here, the model is still able to capture some of the generalities of the system and some inconsistencies in the data. Thus, the biomass of 0.5 tonnes-km" estimated for southern red snapper (in the habitat area), 2  based on the information available in Ivo (1982), seemed to be overestimated and was replaced by a value estimated by the EwE model (0.01 tonneskm" ). On the other hand, the biomass of 2  phytoplankton calculated based on Medeiros et al. (1999) was probably underestimated and an estimate 30% higher was considered more realistic (12 tonnes-km ). Additionally, the model 2  indicated a high sensitivity to the vulnerability of swordfish to sharks and of bathypelagic fishes and omnivorous reef fishes to swordfish. Thus, it is worth to invest more in understanding the dynamics of the swordfish stock in Brazilian waters, especially if we consider Brazil's position at ICCAT that its swordfish fishing quotas in the Atlantic should be increased (Evangelista et al, 1998).  The model presented here was able to closely reproduce the biomass trends for all species for which times series were available. However, there are several other groups that did not show any changes in biomass levels during the simulated period. These trends have to be looked at with reservation as some reef species, e.g., have shown signs of overexploitation (Lutjanus analis, L. jocu, and Ocyurus chrysurus) or have been exploited at their maximum level (Lutjanus vivanus and L. synagris) (Lessa et al., 2004). Another important issue to be addressed in future developments of the model is the effect of changes on the basis of this trophic web. Even though Creed (2003) indicates that there is little information about changes in seagrass biomass for South America (Brazil included), in the Abrolhos region (south of the studied area), a national marine park, 0.5% of seagrass area is lost per year due to anchor damage. A total of 40% of Brazilian seagrass beds are considered threatened (Creed, 2003). Another extraction not accounted for in catch statistics is the extraction of macroalgae. According to Oliveira (2000), macroalgae (Gracilaria cornea, G. caudate, and Hypnea musciformis) have been exploited since the 1960s along the area between Ceara and Paraiba States, with Gracilaria spp. showing signs of overexploitation.  Mangroves have also shown ominous symptoms, with their cover area shrinking from 25,000 km in 1983 to 13,400 km in 1997 (Valiela et al, 2001). In northern Brazil, mangroves are 2  2  extracted for house construction, fishing traps, and as firewood (Wolff et al, 2000) and similar uses are likely to occur in northeastern Brazil (see, e.g., Botelho et al, 2000). Additionally, mangroves are destroyed by the pollution caused by chemical and petro-chemical industries, infrastructure development, and agriculture (Diegues, 1996). These practices are likely to affect other benthic primary producers as well. More recently, there is some indication of the destruction of mangrove areas for the establishment of shrimp ponds (WRM, 2004), even  though some consider that the 83% annual increase in shrimp production of northeastern Brazil complies with 'sustainability principles' and no conversion of mangrove areas is currently observed (Roubach et al, 2002).  This chapter allowed for the description of the flows amongst trophic components in the marine ecosystem off northeastern Brazil and some of its general features. Indices generally used as indicators of maturity of ecosystems did not allow for conclusive answers about the maturity of the East Brazil Large Marine Ecosystem. On the other hand, results indicated that recycling is an important feature of this ecosystem, which is characterized by low phytoplankton-originated primary production supplemented by high production from coastal vegetation. There was some indication that omnivory in shelves (at least tropical shelves) may be lower than in other ecosystems. Some inconsistencies in isolated estimates of biomass were found, as well as gaps in basic information required to better understand this system, even for commercial species. Catch rates were low in comparison with other shelf systems in Brazil and along other tropical shelves in the western Atlantic, which serves many times as driving force for initiatives by the federal government towards policies aiming at increasing catches from Brazilian waters. The results presented here serve as basis for the exploration of future fishing policies for the marine ecosystem off northeastern Brazil within a multi-species and ecosystem approach.  4.5. Bibliography  Abarca-Arenas, L.G. and E. Valero-Pacheco (1993). Toward a trophic model of Tamiahua, a coastal lagoon in Mexico. In: V. Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conf. Proc. 26: 181-185.  Ainsworth, C , B. Ferriss, E. Leblond and S. Guenette (2001). The Bay of Biscay, France: 1998 and 1970 models. Fisheries Centre Research Reports 9(4): 271-313. Albertoni, E.F., C. Palma-Silva and F.A. Esteves (2003). Natural diet of three species of shrimp in a tropical coastal lagoon. Brazilian Archives of Biology and Technology 46(3): 395-403. Albuquerque, C. and G.G. Marcovaldi (1982). Occurrence and distribution of the populations of Trichechus manatus Linnaeus (Sirenia, Trichechidae) from the Brazilian coast. Atlantica 5(2): 2-3. Allen, K.R. (1971). Relation between production and biomass. Journal of the Fisheries Research Board of Canada 28: 1573-1581. Aluigi, M.G. and M.T. Spedicato (1994). Alimentazione di Scaeurgus unicirrhus (Orbigny, 1840) (Cephalopoda, Octopoda). Biologia Marina Mediterranea 1(1): 287-288. Alves, M.I.M. and G.L. Fernandes (1973). Sobre a alimentacao e mecanismo alimentar da biquara, Haemulon plumieri Lacepede (Pisces, Pomadasyidae). Arquivos de Ciencias do Mar 13(1): 1-7. Amaral, A.C.Z., E.H.M. Amaral, F.P.P. Leite and N.M. Gianuca (2000). Diagnostico sobre praias arenosas. Avaliacao e acoes prioritarias para a conservacao da biodiversidade da zona costeira e marinha. Base de Dados Tropical, http://www.bdt.fat.org.br/workshop/ costa/praias/, July 22, 2004. Araujo, J.N., S. Mackinson, R.R. Ellis and P.J.B. Hart (2005). An Ecopath model of the western English Channel ecosystem with an exploration of its dynamic properties. Centre for Environment, Fisheries and Aquaculture Science, Lowestoft: 45 p. Arceo-Carranza, D., J. Franco-Lopez, G.L. Waggy and R. Chavez-Lopez (2004). Trophic comparison of two species of needlefish (Belonidae) in the Alvarado lagoonal system, Veracruz, Mexico. Gulf and Caribbean Research 16: 81-88. Arendt, M.D., J.E. Olney and J.A. Lucy (2001). Stomach content analysis of cobia, Rachycentron canadum, from lower Chesapeake Bay. Fishery Bulletin 99: 665-670. Arias-Gonzalez, J.E., B. Delesalle, B. Salvat and R. Galzin (1997). Trophic functioning of the Tiahura reef sector, Moorea Island, French Polynesia. Coral Reefs 16(4): 231-246.  Arkhipkin, A.I., V.V. Laptikhovsky, C M . Nigmatullin, A.V. Bespyatykh and S.A. Murzov (1998). Growth, reproduction and feeding of the tropical squid Omithoteuthis antillarum (Cephalopoda, Ommastrephidae) from the central-east Atlantic. Scientia Marina 62(3): 273-288. Arocha, F. and L.J. Urosa (1991). Some biological studies of Loligo plei and occurrence of Loligo plealii (Cephalopoda, Myopsida) in northeastern Venezuela. Acta Cientifica Venezolana 42(3): 145-152. Arreguin-Sanchez, F., J.C. Seijo and E. Valero-Pacheco (1993a). An application of ECOPATH II to the north continental shelf ecosystem of Yucatan, Mexico. In: V. Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conference Proceedings 26: 269-278. Arreguin-Sanchez, F., E. Valero-Pacheco and E.A. Chavez (1993b). A trophic box model of the coastal fish communities of the southwestern Gulf of Mexico. In: V. Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conference Proceedings 26: 197-205. Arruda, E.P., O. Domaneschi and A.C.Z. Amaral (2003). Mollusc feeding guilds on sandy beaches in Sao Paulo State, Brazil. Marine Biology 143: 691-701. Azevedo-Araujo, S. and A.L. Vasconcelos Filho (1979). Aspectos gerais sobre a alimentacao do tibiro, Oligoplites palometa, Cuvier, 1831 (Pisces - Carangidae), no canal de Santa Cruz - Pernambuco. Revista Nordestina de Biologia 2(1/2): 119-126. Baird, R.C., T.L. Hopkins and D.F. Wilson (1975). Diet and feeding chronology of Diaphus taaningi (Myctophidae) in the Cariaco Trench. Copeia 2: 356-365. Beerkircher, L., M . Shivji and E. Cortes (2003). A Monte Carlo demographic analysis of the silky shark {Carcharhinus falciformis): implications of gear selectivity. Fishery Bulletin 101: 168-174. Berkeley, S.A. and E.D. Houde (1978). Biology of two exploited species of halfbeaks, Hemiramphus brasiliensis and H. balao from southeast Florida. Bulletin of Marine Science 28(4): 624-644.  Bjorndal, K.A. (1997). Foraging ecology and nutrition of sea turtles. In: P.L. Lutz and J.A. Musick (Eds.). Marine science series. CRC Press, Boca Raton, Florida: 199-231. Blanchard, J.L., J.K. Pinnegar and S. Mackinson (2002). Exploring marine mammal-fishery interactions using 'Ecopath with Ecosim': modelling the Barents Sea ecosystem. Science Series Technical Report, CEFAS, Lowestof 117:1 -52. Borobia, M . and L. Lodi (1992). Recent observations and records of the West Indian manatee Trichechus manatus in northeastern Brazil. Biological Conservation 59(1): 37-43. Botelho, E.R.O., M.C.F. Santos and A.C.P. Pontes (2000). Algumas consideracoes sobre o uso da redinha na captura do caranguejo-uca, Ucides cordatus (Linnaeus, 1763) no litoral sul de Pernambuco - Brasil. Boletim Tecnico Cientifico do CEPENE 8(1): 55-71. Bowman, R.E., C.E. Stillwell, W.L. Michaels and M.D. Grosslein (2000). Food of northwest Atlantic fishes and two common species of squid. NOAA Technical Memorandum NMFS-NE-155. Northeast Fisheries Science Center, Woods Hole, Massachusetts: 137 p. Braga, F.M.S. and M.A.A.S. Braga (1987). Estudo do habito alimentar de Prionotus punctatus (Bloch,1797) (Teleostei, Triglidae), na regiao da ilha Anchieta, estado de Sao Paulo, Brasil. Revista Brasileira de Biologia 47(1/2): 31-36. Branco, J.O., M.J. Lunardon-Branco, J.R. Verani, R. Schveitzer, F.X. Souto and W.G. Vale (2002). Natural diet of Callinectes ornatus Ordway, 1863 (Decapoda, Portunidae) in the Itapocoroy Inlet, Penha, SC, Brazil. Brazilian Archives of Biology and Technology 45(1): 35-40. Branco, J.O. and H.C. Moritz Junior (2001). Natural feeding of Xiphopenaeus kroyeri (Heller) (Crustacea, Decapoda) in the Armacao do Itapocoroy, Penha, Santa Catarina. Revista Brasileira de Zoologia 18(1): 53-61. Branco, J.O. and J.R. Verani (1997). Dinamica da alimentacao natural de Callinectes danae Smith (Decapoda, Portunidae) da Lagoa de Conceicao, Florianopolis, Santa Catarina, Brasil. Revista Brasileira de Zoologia 14: 1003-1018. Brewster-Geisz, K.K. and T.J. Miller (2000). Management of the sandbar shark, Carcharhinus plumbeus: implications of a stage-based model. Fishery Bulletin 98: 236-249.  Brogim, R.A. and P.C. Lana (1997). Espectro alimentar de Aratus pisonii, Chasmagnathus granulata e Sesarma rectum (Decapoda, Grapsidae) em um manguezal da Baia de Paranagua, Parana. Iheringia Serie Zoologia 83: 35-43. Bugoni, L. and C M . Vooren (2004). Feeding ecology of the Common Tern Sterna hirundo in a wintering area in southern Brazil. Ibis 146(3): 438-453. Burton, M.L. (2001). Age, growth, and mortality of gray snapper, Lutjanus griseus, from the east coast of Florida. Fishery Bulletin 99: 254-265. Calixto-Albarran, I. and J.-L. Osorno (2000). The diet of the magnificent frigatebird during chick rearing. The Condor 102: 569-576. Camara, J.J.C., M.C. Cergole, E.C. Campos and G. Narbieri (2001). Estrutura populacional, crescimento, mortalidade e taxa de explotacao do estoque de manjuba, Anchoviella lepidentostole (Pisces, Engraulidae), do rio Ribeira do Iguape, sudeste do estado de Sao Paulo, Brasil, durante o periodo de 1993 a 1996. Boletim do Instituto de Pesca 27(2): 219-230. Campos, C.E.C. and J.E. Lins-Oliveira (2001). Caracterizacao biometrica e meristica do saramunete, Pseudupeneus maculatus Osteichthyes: Mullidae), em Ponta de Pedras, Pernambuco. Boletim do Instituto de Pesca 27(2): 185-189. Castello, L. and J.P. Castello (2003). Anchovy stocks (Engraulis anchoita) and larval growth in the SW Atlantic. Fisheries Research 59(3): 409-421. Castillo-Rivera, M., A. Kobelkowsky and A.M. Chavez (2000). Feeding biology of the flatfish Citharichthys spilopterus (Bothidae) in a tropical estuary of Mexico. Journal of Applied Ichthyology 16: 73-78. Castro, C.B. (2000). Recifes de Coral. Avaliacao e acoes prioritarias para a conservacao da biodiversidade da zona costeira e marinha. Base de Dados Tropical, http://www.bdt.fat. org.br/workshop/costa/recifes/. Castro e Silva, S.M.M., A.C.P. Pontes and C.A.S. Rocha (2003). Report on the spiny lobster fishery in Brazil. In: Report of the second workshop on the management of Caribbean spiny lobster fisheries in the WECAFC area. Havana, Cuba, 30 September - 4 October, 2002. FAO Fisheries Report No. 715: 56-67.  CEPENE (2000). Relatorio da reuniao tecnica sobre o estado da arte da pesquisa e ordenamento da pesca de camaroes peneideos na regiao nordeste do Brasil. Centra de Pesquisa e Extensao Pesqueira do Nordeste - CEPENE, Tamandare, Pernambuco, Brasil: 64 p. Chaves, P.T.C. and M.C. Robert (2001). Nota complementar sobre os habitos de Gerres melanopterus (Teleostei, Gerreidae) na Baia de Guaratuba, Parana, Brasil (25°52',S 48°39'W). Revista Brasileira de Zoologia 18(1): 255-259. Chaves, P.T.C. and A. Serenato (1998). Diversidade de dietas na assembleia de linguados (Teleostei, Pleuronectiformes) do manguezal da Baia de Guaratuba, Parana, Brasil. Revista Brasileira de Oceanografia 46(1): 61-68. Chaves, P.T.C. and S.C. Umbria (2003). Changes in the diet composition of transitory fishes in coastal systems, estuary and continental shelf. Brazilian Archives of Biology and Technology 46(1): 41-46. Chaves, P.T.C. and A.L. Vendel (1998). Feeding habits of Stellifer rastrifer (Perciformes, Sciaenidae) at Guaratuba mangrove, Parana, Brasil. Brazilian Archives of Biology and Technology 41(4): 423-428. Christensen, V. and D. Pauly (1993). Trophic models of aquatic ecosystems. ICLARM Conf. Proc. 26: 390 p. Christensen, V. and C.J. Walters (2004). Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modelling 172(2-4): 109-139. Christensen, V., C. Walters and D. Pauly (2004). Ecopath with Ecosim: a user's guide. Fisheries Centre, University of British Columbia, Vancouver: 154 p. Colinas-Sanchez, F. and P. Briones-Fourzan (1990). Feeding of the spiny lobsters Panilurus guttatus and P. argus (Latreille 1804) in the Mexican Caribbean. Anales del Instituto de Ciencias del Mar y Limnologia 17(1): 89-106. Collette, B.B. and C.E. Nauen (1983). FAO species catalogue. Vol.2. Scombrids of the world. An annotated and illustrated catalogue of tunas, mackerels, bonitos and related species known to date. FAO Fisheries Synopsis 2(125): 1-137.  Cortes, E. and G.R. Parsons (1996). Comparative demography of two populations of the bonnethead shark {Sphyrna tiburo). Canadian Journal of Fisheries and Aquatic Science 53: 709-718. Cox, S.P., T.E. Essington, J.F. Kitchell, S.J.D. Martell, C.J. Walters, C. Boggs and I. Kaplan (2002). Reconstructing ecosystem dynamics in the central Pacific Ocean, 1952-1998. II. A preliminary assessment of the tropical impacts of fishing and effects on tuna dynamics. Canadian Journal of Fisheries and Aquatic Science 59(11): 1736-1747. Crabtree, R.E., C. Stevens, D. Snodgrass and F.J. Stengard (1998). Feeding habits of bonefish, Albula wipes, from the waters of the Florida Keys. Fishery Bulletin 96: 754-766. Creed, J.C. (2003). The seagrasses of South America: Brazil, Argentina and Chile. In: E.P. Green and F.T. Short (Eds.). World atlas of seagrasses. Prepared by the UNEP World Conservation Monitoring Centre. University of California Press, Berkeley, USA: 243250. Cunha, M.C.C. and E. Furtado (1985). Aspectos da alimentacao da mariquita, Holocentrus ascensionis, no estado do Ceara. Boletim de Ciencias do Mar(40): 1-8. DeLancey, L.B. (1989). Trophic relationship in the surf zone during the summer at Folly Beach, South Carolina. Journal of Coastal Research 5(3): 477-488. Dias, T.L.P., I.L. Rosa and B.M. Feitoza (2001). Food resource and habitat sharing by the three western South Atlantic surgeonfishes (Teleostei: Acanthuridae: Acanthurus) off Paraiba Coast, North-eastern Brazil. Aqua Journal of Ichthyology and Aquatic Biology 5(1): 1-10. Diegues, A.C.S. (1996). Ecologia humana e planejamento em areas costeiras. NUPAUB-USP, Sao Paulo, Brazil: 191 p. Dragovich, A. and J.A. Kelly Jr. (1964). Ecological observations of macro-invertebrates in Tampa Bay, Florida 1961-1962. Bulletin of Marine Science of Gulf Caribbean 14: 74102. Dualiby, D.O. (1988). Ecologia trofica de Mugil curema, M. incilis y M. liza (Pisces: Mugilidae) en la Cienaga Grande de Santa Marta, Caribe Colombiano. I. Analisis  cualitativo y cuantitativo. Annates del Instituto de Investigaciones Marinas de Punta de Betin 18: 113-126. Duarte, L.O. and C.B. Garcia (1999a). Diet of the lane snapper, Lutjanus synagris (Lutjanidae), in the Gulf of Salamanca, Colombia. Caribbean Journal of Science 35(1/2): 54-63. Duarte, L.O. and C.B. Garcia (1999b). Diet of the mutton snapper Lutjanus analis (Cuvier) from the Gulf of Salamanca, Colombia, Caribbean Sea. Bulletin of Marine Science 65(2): 453-465. Duka, L.A. (1986). Feeding of Ceratoscopelus warmingii (Myctophidae) in the tropical Atlantic. Journal of Ichthyology 26(5): 89-95. Duque-Nivia, G., A. Acero, A. Santos-Martinez and E.R. Rubio (1996). Food habits of the species of the genus Oligoplites (Carangidae) from the Cienaga Grande de Santa MartaColombian Caribbean. Cybium 20(3): 251-260. Edwards, H. (2000). Trichechus manatus. Animal Diversity Web. http://anirnaldiversity. ummz.umich.edu/site/accounts/information/Trichechus manatus.html, July  15 , 2004. th  Ehrhardt, N.M. (2001). Comparative regional stock assessment analysis of the shrimp resources from northern Brazil to Venezuela. Regional reviews and national management reports. Fourth Workshop on the Assessment and Management of Shrimp and Groundfish Fisheries on the Brazil-Guianas Shelf. Cumana, Venezuela, 2-13 October 2000. FAO Fisheries Report 651: 1-14. Ehrhardt, N.M., J.A.N. Aragao and K.C.A. Silva (1999). Stock assessment of the industrial pink shrimp (Penaeus subtilis) fishery in northern Brazil. FAO Fisheries Report 600: 99111. Ekau, W. and B. Knoppers (1999). An introduction to the pelagic system of the North-East and East Brazilian shelf. Archive of Fishery and Marine Research 47(2/3): 113-132. Eskinazi-Leca, E. (1969). Dados sobre o comportamento alimentar de Mytella falcata D'Orbigny, 1846 (Mollusca - Mytillidae). Boletim de Estudos de Pesca 9(3): 9-16. Evangelista, J.E.V., J.A. Vasconcelos and G.M. Oliveira (1998). Evolucao da pesca de atuns no nordeste do Brasil. Boletim Tecnico Cientifico do CEPENE 6(1): 77-108.  Fernandes, L.M.B. (1971). Sobre a alimentacao da lagosta Panulirus argus (Latr.) 1804. II estagios pos-puerulus e adulto. Serie Estudos de Pesca 1: 1-6. Ferreira, M . M . (1968). Sobre a alimentacao da aruana, Chelonia mydas Linnaeus, ao longo da costa do Estado do Ceara. Arquivos da Estacao de Biologia Marinha da Universidade do Ceara 8(1): 83-86. Fonteles Filho, A.A. (undated). Sintese sobre a distribuicao, abundancia, potencial pesqueiro e biologia do pargo, Lutjanus purpureus Poey da Zona Economica Exclusiva do nordeste do Brasil. Avaliacao do Potencial Sustentavel de Recursos Vivos na Zona Economica Exclusiva M M A - REVIZEE. Analise/Refinamento dos dados preterites sobre prospeccao pesqueira, Fortaleza: 17 p. Fonteles-Filho, A.A. (1988). Sinopse de informacoes sobre a cavala, Scomberomorus cavalla (Cuvier) e a serra, Scomberomorus brasiliensis Collette, Russo & Zavala-Camim (Pisces: Scombridae), no Estado do Ceara, Brasil. Arquivos de Ciencias do Mar 27: 21-48. Fonteles-Filho, A.A. and F.T.P. Ferreira (1987). Distribuicao geografica da captura do pargo, Lutjanus purpureus Poey, e sua relacao com fatores oceanograficos nas regiooes Norte e Nordeste do Brasil. Boletim de Ciencias do Mar 45: 1-23. Ford, J.K.B., G.M. Ellis, L.G. Barrett-Lennard, A. B.Morton, R.S. Palm and K.C. Balcomb III (1998). Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal British Columbia and adjacent waters. Canadian Journal of Zoology 76: 1456-1471. Froese, R. and D. Pauly (2002). FishBase. http://www.fishbase.org, January 15, 2004. Furtado-Ogawa, E. (1970). Alimentacao da sardinha-bandeira, Opisthonema oglinum (Le Sueur), no estado do Ceara. Arquivos de Ciencias do Mar 10(2): 201-202. Furtado-Ogawa, E. (1977). Notas bioecologicas sobre Pachygrapsus transversus (Gibbes, 1850) no estado do Ceara (Crustacea: Brachyura). Arquivos de Ciencias do Mar 17(2): 107-113. Garcia, C.B. and L.O. Duarte (2002). Consumption to biomass (Q/B) ratio and estimates of Q/B-predictor parameters for Caribbean fishes. Naga, the ICLARM Quaterly 25(2): 1931.  Gasalla, M . A. and C.L.D.B. Rossi-Wongtschowski (2004). Contribution of ecosystem analysis to investigating the effects of changes in fishing strategies in the South Brazil Bight coastal ecosystem. Ecological Modelling 172(2-4): 283-306. Gasalla, M.A. and L.S.H. Soares (2001). Comentarios sobre os estudos troficos de peixes marinhos no processo historico da ciencia pesqueira e modelagem ecologica. Boletim do Instituto de Pesca 27(2): 247-263. Gianninni, R. and A . M . Paiva Filho (1990). Aspectos bioecologicos de Stellifer rastrifer (Perciformes: Sciaenida) na Baia de Santos, SP. Boletim do Instituto de Oceanografia, Sao Paulo 38(1): 57-67. Gilliam, D. and K . M . Sullivan (1993). Diet and feeding habits of the southern stingray Dasyatis americana in the central Bahamas. Bulletin of Marine Science 52(3): 10071013. Gomes Azevedo, H. (1980). Estudo ecologico da regiao de Itamaraca, Brasil. XI. Regime alimentar da ostra Crassostrea rhizophorae, 1828 (Pelecypoda, Filobranchia, Ostreidae). Trabalhos Oceanograficos da Universidade Federal de Pernambuco 15: 343-356. Gonzalez-Sanson, G. and L.S. Alvarez-Lajonchere (1978). Alimentation natural deMugil liza, M. curema, M. trichodon and M. hospes (Pisces, Mugilidae) en las lagunas costeras de Tunas de Zaza. Investigaciones Marinas 41: 1-40. Green, E.P. and F.T. Short (2003). World atlas of seagrasses. Prepared by the UNEP World Conservation Monitoring Centre. University of California Press, Berkeley, USA: 298 p. Guedes, E.A.C. and A.N. Moura (1996). Estudo da biomassa e composicao mineral de "algas arribadas" em praias do litoral norte de Alagoas. Boletim de Estudos de Ciencias do Mar 9: 19-30. Haddon, M . (2001). Modelling and quantitative methods in fisheries. Chapman & Hall/CRC, Boca Raton, Florida: 406 p. Harrigan, P., J.C. Zieman and S.A. Macko (1989). The base nutritional support for the gray snapper (Lutjanus griseus): an evaluation based on a combined stomach content and stable isotope analysis. Bulletin of Marine Science 44(1): 65-77.  Harris, R., P. Wiebe, J. Lenz, H.R. Skjoldal and M . Huntley (2000). ICES zooplankton methodology manual. Academic Press, San Diego: 684 p. Hersh, S.L., D.K. Odell and E.D. Asper (1990). Bottlenose dolphin mortality patterns in the Indian/Banana river system in Florida. In: S. Leatherwood and R.R. Reeves (Eds.). The bottlenose dolphin. Academic Press, Inc., San Diego: 155-164. Hirst, A.G. and R.S. Lampitt (1998). Towards a global model of in situ weight-specific growth in marine planktonic copepods. Marine Biology 132(2): 247-257. Hopkins, T.L. and R.C. Baird (1973). Diet of the hatchetfish Sternoptyx diaphana. Marine Biology 23: 34-46. Hopkins, T.L. and R.C. Baird (1985). Feeding ecology of four hatchetfishes (Sternoptychidae) in the eastern Gulf of Mexico. Bulletin of Marine Science 36(2): 260-277. Huizar, A.R.R. and X.C. Carrara (2000). Habitos alimentarios de Diodon histrix y Diodon holocdnthus (Pisces: Diodontidae) en las costas de Jalisco y Colima, Mexico. Boletin del Centro de Investigaciones Biologicas 34(2): 181-210. IBAMA (1994). Lagosta, caranguejo-uca e camarao do nordeste. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renovaveis, Brasilia: 190 p. ICCAT (1999). Report of the ICCAT SCRS skipjack stock assessment session. Collective Volume of Scientific Papers ICCAT SCRS/99/21: 1-52. ICCAT (2001a). Report of the 2001 Billfish Species Group session: 76 p. ICCAT (2001b). Report of the fourth ICCAT billfish workshop. Collective Volume of Scientific Papers ICCAT 53: 1-130. ICCAT (2003a). Report of the 2002 Atlantic swordfish stock assessment session. Collective Volume of Scientific Papers ICCAT 55(4): 1289-1415. ICCAT (2003b). Report of the 2002 ICCAT bigeye tuna stock assessment meeting. Collective Volume of Scientific Papers ICCAT 55(5): 1728-1842. ICCAT (2003c). Report of the 2002 ICCAT white marlin stock assessment meeting. Collective Volume of Scientific Papers ICCAT 55(2): 350-452.  ICCAT (2004a). 2003 ICCAT albacore stock assessment session. Collective Volume of Scientific Papers ICCAT 56(4): 1223-1311. ICCAT (2004b). 2003 ICCAT Atlantic yellowfin tuna stock assessment session. Collective Volume of Scientific Papers ICCAT 56(2): 443-527. ICCAT (2004c). Report of the 2004 meeting of the Standing Committee on Research & Statistics (SCRS), Madrid, Spain: 189 p. ICCAT (2005a). Report of the 2004 ICCAT bigeye tuna stock assessment session. Collective Volume of Scientific Papers ICCAT 57(2): 3-38. ICCAT (2005b). Report of the 2004 inter-sessional meeting of the ICCAT sub-committee on by-catches: shark stock assessment. Collective Volume of Scientific Papers ICCAT 58 (3): 799-890. Isaac, V.J., J. Dias Neto and F.G. Damasceno (1992). Biologia, dinamica e administrafao pesqueira do camarao rosa, Penaeus subtilis, da costa norte do Brasil: 144 p. Isaac, V.J. and U.S. Moura (1998). Taxa de consumo alimentar de tres populacoes de peixes do estuario do rio Caete, Braganca-PA, no litoral norte do Brasil. Boletim do Museu Paraense Emilio Goeldi, Serie Zoologia 14(1): 57-75. Ivo, C.T.C. and A.J. Hanson (1982). Aspectos da biologia e dinamica populacional do pargo Lutjanus purpureus Poey, no Norte e Nordeste do Brasil. Arquivos de Ciencias do Mar 22(1/2): 1-41. Ivo, C.T.C. and J.A. Pereira (1996). Sinopse das principals observacoes sobre as lagostas Panulirus argus (Latreille) e Panulirus laevicauda (Latreille), capturadas em aguas costeiras do Brasil, entre os estados do Amapa e do Espirito Santo. Boletim Tecnico Cientifico do CEPENE 4(1): 7-94. Ivo, C.T.C. and M.J.B. Sousa (1988). Sinopse de informacoes sobre o pargo, Lutjanus purpureus Poey (Pisces: Lutjanidae), no Norte e Nordeste do Brasil. Arquivos de Ciencias do Mar 27: 57-67. Kaschner, K., R. Watson, V. Christensen, A.W. Trites and D. Pauly (2001). Modeling and mapping trophic overlap between marine mammals and commercial fisheries in the North Atlantic. Fisheries Centre Research Reports 9(3): 35-45.  Kasuya, T. (1976). Reconsideration of life history parameters of the spotted and striped dolphins based on cemental layers. Scientific Reports of the Whales Research Institute Tokyo 28: 73-106. Kinas, P.G. and C.B.P. Bethlem (1998). Empirical Bayes abundance estimation of a closed population using mark-recapture data, with application to humpback whales, Megaptera novaeangliae, in Abrolhos, Brazil. Annual Report. International Whaling Commission 48: 447-452. Kinzer, J. and K. Schulz (1985). Vertical distribution and feeding patterns of midwater fish in the central equatorial Atlantic. I. Myctophidae. Marine Biology 85(3): 313-322. Kinzer, J. and K. Schulz (1988). Vertical distribution and feeding patterns of midwater fish in the central equatorial Atlantic. II. Sternoptychidae. Marine Biology 99(2): 261-269. Kitchell, J.F., T.E. Essington, C.H. Boggs, D.E. Schindler and C.J. Walters (2002). The role of sharks and longline fisheries in a pelagic ecosystem of the Central Pacific. Ecosystems 5: 202-216. Koch, V. and M . Wolff (2002). Energy budget and ecological role of mangrove epibenthos in the Caete estuary, North Brazil. Marine Ecology Progress Series 228: 119-130. Kulka, D.W., M.R. Simpson and T.D. Inkpen (2003). Distribution and biology of Blue hake (Antimora rostrata Gunther 1878) in the Northwest Atlantic with comparison to adjacent areas. Northwestern Atlantic Fisheries Science 31: 299-318. Langtimm, C.A., T.J. O'shea, R. Pradel and C.A. Beck (1998). Estimates of annual survival probabilities for adult Florida manatees (Trichechus manatus latirostris). Ecology 79(3): 981-997. Lau, C.J. (1988). Dietary comparison of two slow-moving crustacean (Decapoda: Scyllaridae) predators by a modified index of relative importance. In: J.H. Choat, D. Barnes, M.A. Borowitzka, J.C. Coll, P.J. Davies, P. Flood, B.G. Hatcher and D. Hopley (Eds.). Proceedings of the Sixth International Coral Reef Symposium, Townville, Australia, 812 August 1988. Volume 2: Contributed papers: 95-100. Laughlin, R.A. (1982). Feeding habits of the blue crab, Callinectes sapidus Rathbun, in the Apalachicola estuary, Florida. Bulletin of Marine Science 32: 807-822.  Leao, S.M.A.N., R.K.P. Kikuchi and V. Testa (2003). Corals and coral reefs of Brazil. In: J. Cortes (Ed.). Latin American coral reefs. Elsevier, Amsterdam and Boston: 9-52. Leontief, W.W. (1951). The structure of American economy, 1919-1939; an empirical application of equilibrium analysis. Oxford University Press, New York: 264 p. Lessa, R. and F.M. Santana (1998). Age determination and growth of the smalltail shark, Carcharhinus porosus, from northern Brazil. Marine and Freshwater Research 49: 705711. Lessa, R.P., M.F. Nobrega and J.L. Bezerra Junior (2004). Dinamica de populacoes e avaliacao de estoques dos recursos pesqueiros da regiao nordeste. Volume II. DIMAR, Departamento de Pesca - Universidade Federal Rural de Pernambuco, Recife-Brazil: 245 PLindeman, R.L. (1942). The trophic-dynamic aspect of ecology. Ecology 23(4): 399-417. Lins-Oliveira, J.E., J.A. Vasconcelos and H. Rey (1993). A problematica da pesca de lagostas no Nordeste do Brasil. Boletim Tecnico Cientifico do CEPENE 1(1): 187-210. Lipinski, M.R. and T.B. Linkowski (1988). Food of the squid Ommastrephes bartramii (Lesueur, 1821) from the Southwest Atlantic Ocean. South African Journal of Marine Science 6: 43-46. Longhurst, A. (1998). Ecological geography of the sea. Academic Press, San Diego, California: 398 p. Lorenzo, J.M. and J.G. Pajuelo (1999). Biology of a deep benthopelagic fish, roudi escolar Yromethichthys prometheus (Gempylidae), off the Canary Islands. Fishery Bulletin 97: 92-99. Macedo Costa, T.L., A.L. Vasconcelos Filho and E.M.B. Galiza-Viana (1987). Aspectos gerais sobre a alimentacao do cangulo, Balistes vetula Linnaeus, 1758 (Pisces Balistidae) no estado de Pernambuco - Brasil. Revista Brasileira de Zoologia 4(2): 71-88. Macpherson, E. (1979). Relations trophiques des poisons dans la Mediterranee occidentale. Rapport du Comm. Int. Expl. Sci. Mer Medit. 25/26: 4958.  Magalhaes, K.M., E. Eskinazi-Leca and A.M.Moura Junior (1997). Morfometria e biomassa da fanerogama marinha Halodule wrightii Ascherson no litoral norte de Pernambuco. Trabalhos Oceanograficos da Universidade Federal de Pernambuco 25: 83-92. Magnusson, J.V. (2001). Distribution and some other biological parameters of two morid species Lepidion eques (Gunther, 1887) and Antimora rostrata (Gunther, 1878) in Icelandic waters. Fisheries Research 51 (2-3): 267-281. Magro, M., M.C. Cergole and C.L.B. Rossi-Wongtschowski (2000). Sintese de conhecimento dos principals recursos pesqueiros costeiros potencialmente explotaveis na costa sudestesul do Brasil: peixes. M MA - Ministerio do Meio Ambiente, dos Recursos Hidricos e da Amazonia Legal, CIRM - Comissao Interministerial para os Recursos do Mar, Brasilia: 109 p. Maida, M . and B.P. Ferreira (1997). Coral reefs of Brazil: an overview. Proceedings of the 8  th  International Coral Reef Symposium 1: 263-274. Mancera, E. and J. Mendo (1996). Population dynamics of the oyster Crassostrea rhizophorae from the Cienaga Grande de Santa Marta, Colombia. Fisheries Research 26(1-2): 139148. Manickchand-Heileman, S.C., J. Mendoza-Hill, A.L. Kong and F. Arocha (2004). A trophic model for exploring possible ecosystem impacts of fishing in the Gulf of Paria, between Venezuela and Trinidad. Ecological Modelling 172(2-4): 307-322. Manickchand-Heileman, S.C., L.A. Soto and E. Escobar (1998). A preliminary trophic model of the continental shelf, south-western Gulf of Mexico. Estuarine, Coastal and Shelf Science 46: 885-899. Manickchand-Heileman, S.C. and D.A.T. Phillip (2000). Age and growth of the yellowedge grouper, Epinephelus flavolimbatus, and the yellowmouth grouper, Mycteroperca interstitialis, off Trinidad and Tobago. Fishery Bulletin 98(2): 290-298. Mansilla Mufioz, A.O. and S.M.B. Pereira (1997). Caracterizacao quali-quantitativa das comunidades de macroalgas nas formacoes recifais da praia do Cupe - Pernambuco (Brasil). Trabalhos Oceanograficos da Universidade Federal de Pernambuco 25: 93-109.  Mantelatto, F.L., R.A. Christofoletti and P.B. Camargo (2002). A food source analysis for the swimming crab Callinectes ornatus (Portunidae) in Ubatuba Bay (Brazil), using carbon isotopes. Nauplius 10(1): 61-66. Mantelatto, F.L.M. and R.A. Christofoletti (2001). Natural feeding activity of the crab Callinectes ornatus (Portunidae) in Ubatuba Bay (Sao Paulo, Brazil): influence of season, sex, size and molt stage. Marine Biology 138: 585-594. Marcovaldi, M.A. and G.G. Marcovaldi (1999). Marine turtles of Brazil: the history and structure of Projeto TAMAR-IBAMA. Biological Conservation 91: 35-41. Marquez, R. (1975). Observation on the mortality and growth of the mullet (Mugil cephalus) in the Tamiahua Lagoon, Mexico. Aquaculture 5(1): 109. Martinez, C. (2004). Food and niche overlap of the Scarlet Ibis and the Yellow-crowned Night Heron in a tropical mangrove swamp. Waterbirds 27(1): 1-8. Matsuura, Y . (1995). Os ecossistemas brasileiros e os principals macrovetores de desenvolvimento. Subsidios ao planejamento da gestao ambiental. Projeto Cenarios para o Planejamento da Gestao Ambiental (MMA/PNMA). Brasilia, DF, M M A : 39-104. Medeiros, C , B. Kjerfve, M . Araiijo and S.N. Leitao (2000). The Itamaraca estuarine ecosystem, Brazil. In: U . Seeliger and B. Kjerfve (Eds.). Coastal marine ecosystems of Latin America. Ecological Studies, Vol. 144. Springer, Berlin: 71-81. Medeiros, C , S.J. Macedo, F.A.N. Feitosa and M.L. Koening (1999). Hydrography and phytoplankton biomass and abundance of North-East Brazilian waters. Archive of Fishery and Marine Research 47(2/3): 133-151. Mel'nikov, Y.S. (1981). Size-age composition and growth pattern of Allocyttus verrucosus (Oreosomatidae). Journal of Ichthyology 21(2): 178-184. Mendoza, J.J. (1993). A preliminary biomass budget for the northeastern Venezuela shelf ecosystem. In: V . Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conference Proceedings 26: 285-297. Menezes, M.F. (1985). Biologia pesqueira do cangulo, Balistes vetula Linnaeus: reproducao e crescimento. Arquivos de Ciencias do Mar 24: 53-59. Meylan, A. (1988). Spongivory in hawksbill turtles: a diet of glass. Science 239: 393-395.  Mignucci-Giannoni, A.A. and C.A. Beck (1998). The diet of the manatee (Trichechus manatus) in Puerto Rico. Marine Mammal Science 14(2): 394-397. Mohammed, E. (2003). A generic marine ecosystem model for the Southeastern Caribbean in the late 1999s: application to Grenada and the Grenadines. Fisheries Centre Research Reports 11(6): 191-225. Monteiro, N.U. and L.M. Barroso (1963). Estudo sobre o ciclo sexual e o regime alimentar do pargo. Boletim de Estudos de Pesca 3(11-12): 13-20. Montenegro Silva, B.C., N.G. Bernal Gonzalez and A. Martinez Guerrero (1986). Estudio del contenido estomacal de la tortuga marina Lepidochelys olivacea en la costa de Oaxaca, Mexico. Anales del Instituto de Ciencias del Mar y Limnologia, Universidad Nacional Autonoma de Mexico, Mexico City 13(2): 121-132. Moriniere, E.C., B.J.A. Pollux, I. Nagelkerken and G.V. der Velde (2003). Diet shifts of Caribbean grunts (Haemulidae) and snappers (Lutjanidae) and the relation with nurseryto-coral reef migrations. Estuarine, Coastal and Shelf Science 57: 1079-1089. Morris, R.D. and J.W. Chardine (1992). The breeding biology and aspects of the feeding ecology of brown noddies Anous stolidus nesting near Culebra, Puerto Rico, 1985-1989. Journal of Zoology 226: 65-79. Motta, P.J., K.B. Clifton, P. Hernandez, B.T. Eggold, S.D. Giordano and R. Wilcox (1995). Feeding relationships among nine species of seagrass fishes of Tampa Bay, Florida. Bulletin of Marine Science 56(1): 185-200. Muto, E.Y., L.S.H. Soares and R. Goitein (2001). Food resource utilization of the skates Rioraja agassizii (Mtiller & Henle, 1841) and Psammobatis extenta (Garman, 1913) on the continental shelf off Ubatuba, south-eastern Brazil. Revista Brasileira de Biologia 61(2): 217-238. Nielsen, J.G. (1999). A review of the genus Neobythites (Pisces, Ophidiidae) in the Atlantic, with three new species. Bulletin of Marine Science 64(2): 335-372. Nigmatullin, C M . and N.M. Toporova (1982). Food spectrum of the short-finned squid Sthenoteuthis pteropus (Steenstrup, 1855) in the tropical Atlantic epipelagial [Pishchevoj spektr kylorukogo kal'mara (Sthenoteuthis pteropus (Steenstrup, 1855) v ehpipelagiali  tropicheskoj atlantiki]. Feeding and food relationships of the atlantic fishes and invertebrates [Pitanie i pishchevye otnosheniya ryb i bespozvonochnykh Atlanticheskogo Okeana]: 3-8. Odum, E.P. (1969). The strategy of ecosystem development. Science 164(3877): 262-270. Odum, W.E. and E.J. Heald (1975). The detritus-based food web of an estuarine mangrove community. In: L.E. Cronin (Ed.). Estuarine research. Academic Press, New York: 265286. Okey, T.A. (2002). Simulating extreme fishing policies in Prince William Sound, Alaska: a preliminary evaluation of an ecosystem-based policy analysis. Fisheries Centre Research Reports 10(2): 94-108. Okey, T.A. and R. Pugliese (2001). A preliminary Ecopath model of the Atlantic continental shelf adjacent to the southeastern United States. Fisheries Centre Research Reports 9(4): 167-181. Oliveira, E.C., P.A. Horta, C.E. Amancio and C.L.S. Anna (2000). Algas e angiospermas marinhas benticas do litoral brasileiro. Avaliacao e acoes prioritarias para a conservacao da biodiversidade da zona costeira e marinha. Base de Dados Tropical, http://www.bdt. fat.org.br/workshop/costa/algas, Accessed in August 13 2004. th  Oliveira Filho, E.C. (1983). The Brazilian seagrasses. Aquatic Botany 16: 251-267. Opitz, S. (1996). Trophic interactions in Caribbean coral reefs. ICLARM Technical Report 43: 341 p. Oxenford, H.A. and W. Hunte (1999). Feeding habits of the dolphinfish (Coryphaena hippurus) in the eastern Caribbean. Scientia Marina 63(3-4): 303-315. Pace, M.L., J.E. Glasser and L.R. Pomeroy (1984). A simulation analysis of continental shelf food webs. Marine Biology 82: 47-63. Paine, R.T. (1988). Road maps of interactions or grist for theoretical development? Ecology 69(6): 1648-1654. Paiva, M.P. (1997). Recursos pesqueiros estuarinos e marinhos do Brasil. UFC, Fortaleza, Brazil: 278 p.  Palomares, M.L.D. and D. Pauly (1998). Predicting food consumption of fish populations as functions of mortality, food type, morphometries, temperature and salinity. Marine and Freshwater Research 49: 447-453. Paludo, D. and A. Langguth (2002). Use of space and temporal distribution of Trichechus manatus manatus Linnaeus in the region of Sagi, Rio Grande do Norte State, Brazil (Sirenia, Trichechidae). Revista Brasileira de Zoologia 19(1): 205-215. Paula, A.F., M.A.O. Figueiredo and J.C. Creed (2003). Structure of the macroalgal community associated with the seagrass Halodule wrightii Ascherson in the Abrolhos Marine National Park, Brazil. Botanica Marina 46(5): 413-424. Pauly, D. and V. Christensen (1995). Primary production required to sustain global fisheries. Nature 374: 255-257. Pauly, D., M.L. Soriano-Bartz and M.L.D. Palomares (1993). improved construction, parametrization and interpretation of steady-state ecosystem models. In: V . Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conference Proceedings 26: 1-13. Pauly, D., V. Christensen and C. Walters (2000). Ecopath, Ecosim, and Ecospace as tools for evaluating ecosystem impact of fisheries. ICES Journal of Marine Science 57: 697-706. Pauly, D., A.W. Trites, E. Capuli and V. Christensen (1998). Diet composition and trophic levels of marine mammals. ICES Journal of Marine Science 55: 467-481. Pereira-Barros, J.B. and E.P. Santos (1971). Sobre a estimacao da taxa de mortalidade na populacao do molusco Mytella falcata (Orbigny) 1846, da Lagoa Mundau - Alagoas. CARPAS, Mar del Plata, Argentina: 10 p. Perez, J.A. A. and M . Haimovici (1995). Descriptive ecology of two South American eledonids (Cephalopoda: Octopodidae). Bulletin of Marine Science 56(3): 752-766. Petersen, G.H. and M.A. Curtis (1980). Differences in energy flow through major components of subarctic, temperate and tropical marine shelf ecosystems. Dana 1: 53-64. Petracco, M., V.G. Veloso and R.S. Cardoso (2003). Population dynamics and secondary production of Emerita brasiliensis (Crustacea: Hippidae) at Prainha Beach, Brazil. Marine Ecology 24(3): 231-245.  Plotkin, P.T., M.K. Wicksten and A.F. Amos (1993). Feeding ecology of the loggerhead sea turtle Caretta caretta in the Northwestern Gulf of Mexico. Marine Biology 115: 1-5. Polovina, J.J. (1984). Model of a coral reef ecosystem. I. The ECOPATH Model and its application to French frigate shoals. Coral Reefs 3: 1-11. Portsev, P.I. (1980). The feeding of the cutlassfish, Trichiurus lepturus (Trichiuridae), off the west coast of India. Journal of Ichthyology 20(5): 60-65. Prince, P.A. (1980). The food and feeding ecology of Grey-headed albatross Diomedea chrysostoma and Black-browed albatross D. melanophris. Ibis 122: 476-488. Prince, P.A. and R.A. Morgan (1987). Diet and feeding ecology of Procellariiformes. In: J.P. Croxall (Ed.) Seabirds: feeding ecology and role in marine ecosystems. Cambridge University Press, Cambridge; New York: 135-171. Rabay, G.C. (1985). Baleias. Fatos e mitos. Joao Pessoa, Brazil: 34 p. Randall, J.E. (1967). Food habits of reef fishes of the West Indies. Studies in Tropical Oceanography 5: 665-847. Rezende, S.M. and B.P. Ferreira (2004). Age, growth and mortality of dog snapper Lutjanus jocu (Bloch & Schneider, 1801) in the northeast coast of Brazil. Brazilian Journal of Oceanography 52(2): 107-121. Rocha, G.R.A., M.A. Gasalla, C.L.D. Rossi-Wongtschowski, L.S.H. Soares, A.M.S. PiresVanin, E.Y. Muto, M.C. Cergole, E. Aidar, H.S.L. Mesquita, S.M.F. Gianesella-Galvao, L.A. Vega-Perez and A. Jarre-Teichmann (1998). Quantitative model of trophic interactions in the Ubatuba shelf system (Southeastern Brazil). Naga 21(4): 25-32. Rocha, G.R.A., C.L.D.B. Rossi-Wongtschowski, A.M.S. Pires-Vanin and A. Jarre-Teichmann (2003). Seasonal budgets of organic matter in the Ubatuba shelf system, SE Brazil. I. Planktonic and benthic components. Oceanologica Acta 26: 487-495. Rodrigues, M.M. (1974). Alimentacao do ariaco, Lutjanus synagris Linnaeus, do estado do Ceara (Brasil). Arquivos de Ciencias do Mar 14(1): 61-62. Rosas, F.C.W., E.L.A. Monteiro-Filho, J. Marigo, R.A. Santos, A.L.V. Andrade, M . Rautenberg, M.R. Oliveira and M.O. Bordignon (2002). The striped dolphin, Stenella  coeruleoalba (Cetacea: Delphinidae), on the coast of Sao Paulo State, southastern Brazil. Aquatic Mammals 28(1): 60-66. Roubach, R., E.S. Correia, S. Zaiden, R.C. Martino and R.O. Cavalli (2002). Aquaculture in Brazil. World Aquaculture 34(1): 28-34. Roux, O. and F. Conand (2000). Feeding habits of the bigeye scad, Selar crumenophthalmus (Carangidae), in la Reunion Island waters (south-western Indian Ocean). Cybium 24(2): 173-179. Sadovy, Y . and A . - M . Eklund (1999). Synopsis of biological data on the Nassau grouper, Epinephelus striatus (Bloch, 1792), and the Jewfish, E. itajara (Lichtenstein, 1822). NOAA, US Department of Commerce, Seattle, Washington: 65 p. Santos, M.C.O., S. Rosso, R.A. Santos, S.H.B. Lucato and M . Bassoi (2002). insights on small cetacean feeding habits in southeastern Brazil. Aquatic Mammals 28(1): 38-45. Schaeffer-Novelli, Y., G. Cintron-Molero, R.R. Adaime and T.M. Camargo (1990). Variability of mangrove ecosystems along the Brazilian coast. Estuaries 13(2): 204-218. Schiller, D. and C.B. Garcia (2000). Observations on the diet of Balistes vetula (Pisces: Balistidae) in the Gulf of Salamanca, Colombian Caribbean. Boletin de Investigaciones Marinas y Costeras 29: 35-40. Schwamborn, R. (1997). Influence of mangroves on community structure and nutrition of zooplankton in northeast Brazil. ZMT Contribution no. 4, Center for Tropical Marine Ecology, Bremen, Germany: 77 p. Sergipense, S., E.P. Caramaschi and I. Sazima (1999). Morfologia e habitos alimentares de duas especies de Engraulidae (Teleostei, Clupeiformes) na Baia de Sepetiba, Rio de Janeiro. Revista Brasileira de Oceanografia 47(2): 173-188. Sherman, K., P. Celone, K. Ohlets, P. August, C. Damon, L. Juda, J. Sutinen and J. Poggie (2002). Large Marine Ecosystems of the World, http://www.edc.uri.edu/ lme/Text/eastbrazil.htm, January 16,2002. Sherman, K. and A . M . Duda (2001). Toward ecosystem-based recovery of marine biomass yield. Ambio 30(3): 167-168.  Sierra, L.M., R. Claro and O.A. Popova (1994). Alimentacion y relaciones troficas. In: R. Claro (Ed.). Ecologia de los peces marinos de Cuba. Instituto de Oceanologia Academia de Ciencias de Cuba and Centro de Investigaciones de Quintana Roo, Mexico: 263-284. Silva, C.M.L. and Z.S. Almeida (2001). Alimentacao de Rhizoprionodon porosus (Elasmobranchii: Carcharhinidae) da costa do Maranhao, Brasil. Boletim do Instituto de Pesca 27(2): 205-211. Silva Junior, M.G. (2004). Crescimento e mortalidade de algumas especies de peixes do estuario do rio Caete, Braganca, PA. Programa de Pos-Graduacao em Biologia Ambiental, Universidade Federal do Para, Belem: 101 p. Singarajah, K.V. (1985). A review of Brazilian whaling: aspects of biology, exploitation and utilization, Cochin, India. Singarajah, K.V. (1997). Whales and whaling. In: K.V. Singarajah (Ed.). Fundamentals of marine biology with particular emphasis on the tropical realm. Minerva Press, London: 276-304. Smith, C D . (2003). Diet of Octopus vulgaris in False Bay, South Africa. Marine Biology 143: 1127-1133. Soares, L.S.H. (2003). Food consumption of fish in a sub-tropical SW Atlantic ecosystem off Brazil: comparison of four sciaenid species. Oceanologica Acta 26: 503-509. Soares, L.S.H., A. Jarre-Teichmann and C.L.D.B. Rossi-Wongtschowski (1998). Field estimates of food consumption of the searobin Prionotus punctatus (13loch, 1797) on the continental shelf off Ubatuba, southeastern Brazil. Revista Brasileira de Oceanografia 46(1): 45-60. Soares, L.S.H. and A.E.A.M. Vazzoler (2001a). Diel changes in food and feeding activity of sciaenid fishes from the south-western Atlantic, Brazil. Revista Brasileira de Biologia 61(2): 197-216. Spalding, M . , C. Ravilious and E.P. Green (2001). World atlas of coral reefs. University of California Press, Berkeley: 424 p.  Stillwell, C.E. and N.E. Kohler (1982). Food, feeding habits and estimates of daily ration of the shortfin mako (Isurus oxyrinchus) in the northwest Atlantic. Canadian Journal of Fisheries and Aquatic Science 39 (3): 407-414. Stillwell, C.E. and N.E. Kohler (1993). Food habits of the sandbar shark Carcharhinus plumbeus off the U.S. northeast coast, with estimates of daily ration. Fishery Bulletin 91(1): 138-150. Stoner, A.W. and R.J. Zimmerman (1998). Food pathways associated with penaeid shrimps in a mangrove-fringed estuary. Fishery Bulletin 86(3): 543-551. Tabash, F.A. and L . M . Sierra (1996). Assessment of Lutjanus vivanus and Lutjanus buccanella in the north Caribbean coast of Costa Rica. Naga 19(4): 48-51. Tararam, A.S., Y. Wakabara and M.B. Equi (1993). Habitos alimentares de onze especies da megafauna bentica da plataforma continental de Ubatuba, SP. Publicacao Especial do Instituto de Oceanografia, Sao Paulo 10: 159-167. Tata, A. and A. Prieto (1991). Production secundaria en una poblacion del bivalvo tropical Tivela mactroides (Veneridae) en el Oriente de Venezuela. Caribbean Journal of Science 21:28-34. Teixeira, R.L. (1994). Abundance, reproductive period, and feeding habits of eleotrid fishes in estuarine habitats of north-east Brazil. Journal of Fish Biology 45: 749-761. Teixeira, R.L. and M . Haimovici (1989). Distribuicao, reproducao e habitos alimentares de Prionotus punctatus e P. nudigula (Pisces: Triglidae) no litoral do Rio Grande do Sul, Brasil. Atlantica 11(1): 13-45. Telles, M.D. (1998). Modelo trofodinamico dos recifes em franja do Parque Nacional Marinho dos Abrolhos - Bahia. Departamento de Oceanografia, Fundacao Universidade do Rio Grande, Rio Grande, Brazil. Master Thesis: 150 p. Trites, A. and D. Pauly (1998). Estimating mean body masses of marine mammals from maximum body lengths. Canadian Journal of Zoology 76(5): 886-896. Tsarin, S.A. (1994). Age, growth and some production characteristics of Ceratoscopelus warmingii (Myctophidae) in the tropical zone of the Indian Ocean. Voprosy ikhtiologii (Moscow) 34(2): 234-242.  Tsipoura, N . and J. Burger (1999). Shorebird diet during spring migration stopover on. The Condor 101:635-644. Ulanowicz, R.E. (1986). Growth and development: ecosystems phenomenology. SpringerVerlag, New York: 203 p. Valiela, I., J.L. Browen and J.K. York (2001). Mangrove forests: one of the world's threatened major tropical environments. Bioscience 51(10): 807-815. Vasconcellos, M . (2000). Ecosystem impacts of fishing forage fishes: an analysis of harvest strategies for the Brazilian sardine, University of British Columbia, Vancouver, Canada. PhD Thesis: 188 p. Vasconcellos, M . (2002). Mass-balance models of oceanic ecosystems of the Atlantic. Fisheries Centre, UBC, Vancouver: 76 p. Vasconcellos, M . and M.A. Gasalla (2001). Fisheries catches and the carrying capacity of marine ecosystems in southern Brazil. Fisheries Research 50: 279-295. Vasconcellos, M . , S. Mackinson, K. Sloman and D. Pauly (1997). The stability of trophic mass-balance models of marine ecosystems: a comparative analysis. Ecological Modelling 100: 125-134. Vasconcelos Filho, A.L. (1979). Estudo ecologico da regiao de Itamaraca - Pernambuco Brasil. IV. Alimentacao da sardinha bandeira, Opisthonema oglinum (Le Sueur, 1817), no Canal de Santa Cruz. Trabalhos Oceanograficos da Universidade Federal de Pernambuco 14: 105-116. Vasconcelos Filho, A.L. and E.F. Cavalcanti (1993). Primeiras informacoes sobre a alimentacao de Gobionellus oceanicus (Pallas, 1770), (Pisces - Gobiidae), na Ilha de Itamaraca - PE. Trabalhos Oceanograficos da Universidade Federal de Pernambuco 22: 157-180. Vasconcelos Filho, A.L., D.S. Guedes, E.M.B. Galiza and S. Azevedo-Araujo (1984). Estudo ecologico da regiao de Itamaraca - Pernambuco - Brasil. XXVII. Habitos alimentares de alguns peixes estuarinos. Trabalhos Oceanograficos da Universidade Federal de Pernambuco 18: 231-260.  Vaske-Junior, T. (2000). Relacoes troficas dos grandes peixes pelagicos da regiao equatorial sudoeste do Oceano Atlantico. Departamento de Oceanografia, Fundacao Universidade do Rio Grande, Rio Grande, Brazil. PhD Thesis: 144 p. Vega-Cendejas, M.E., F. Arreguin-Sanchez and M . Hernandez (1993). Trophic fluxes on the Campeche Bank, Mexico. In: V. Christensen and D. Pauly (Eds.). Trophic models of aquatic ecosystems. ICLARM Conference Proceedings 26: 206-213. Vega-Cendejas, M.E., M . Hernandez and F. Arreguin-Sanchez (1994). Trophic interrelations in a beach seine fishery from northwestern coast of the Yucatan peninsula, Mexico. Journal of Fish Biology 44: 647-659. Vendel, A.L. and P.T.C. Chaves (1998). Alimentacao de Bairdiella ronchus (Cuvier) (Perciformes, Sciaenidae) na Baia de Guaratuba, Parana, Brasil. Revista Brasileira de Zoologia 15(2): 297-305. Vianna, M . and J.R. Verani (2002). Biologia populacional de Orthopristis ruber (Teleostei, Haemulidae) especie acompanhante da pesca de arrasto do camarao-rosa, no sudeste brasileiro. Atlantica 23(1): 27-36. Viegas, O. (1982). Growth and productivity of Tagelus plebeius (Solecurtidae, Bivalvia) from the Calunga Channel, Maceio, Alagoas, Brazil. Atlantica 5(2): 124-125. Villasmil, L., J. Mendoza and O.J.M. Ferrer (1997). Crecimiento y mortalidad del cangrejo azul Callinectes sapidus Rathbun, 1896, del Lago de Maracaibo. Ciencia 5(1): 7-15. Villela, M.J., P.A.S. Costa and J.L. Valentin (1997). Crescimento e mortalidade de juvenis do camarao rosa (Penaeus brasiliensis Latreille, 1817) na Lagoa de Araruama, Rio de Janeiro. Revista Brasileira de Biologia 57(3): 487-499. Walters, C. (2003). Folly and fantasy in the analysis of spatial catch rate data. Canadian Journal of Fisheries and Aquatic Science 60: 1433-1436. Walters, C.J. and F. Juanes (1993). Recruitment limitation as a consequence of natural selection for use of restricted feeding habitats and predation risk taking by juvenile fishes. Canadian Journal of Fisheries and Aquatic Science 50: 2058-2070.  Walters, C , V. Christensen and D. Pauly (1997). Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7(2): 139-172. Wiedemeyer, W. (1997). Analysis of the benthic food web of a mangrove ecosystem at northeastern Brazil. IfM, Kiel University, Germany. PhD Thesis: 155 p. Wolcott, T.G. (1978). Ecological role of ghost crabs, Ocypode quadrata (Fabricius) on an ocean beach: scavengers or predators. Journal of Experimental Marine Biology and Ecology 31(1): 67-82. Wolff, M., V. Koch and V. Isaac (2000). A trophic flow model of the Caete Mangrove Estuary (North Brazil) with considerations for the sustainable use of its resources. Estuarine, Coastal and Shelf Science 50: 789-803. WRM (2004). Brazil: mangrove ecosystems turned into shrimp aquaculture ponds. World Rainforest Movement's bulletin 84: http://www.wrm.org.uv/bulletin/84/Brazil.html, Accessed in May 15, 2005. Wyanski, D.M., D.B. White and C.A. Barans (2000). Growth, population age structure, and aspects of the reproductive biology of snowy grouper, Epinephelus niveatus, off North Carolina and South Carolina. Fishery Bulletin 98: 199-218. Yoneda, N.T. (2000). Plancton. Avaliacao e acoes prioritarias para a conservacao da biodiversidade da zona costeira e marinha. Base de Dados Tropical, http://www.bdt.fat. org.br/workshop/costa/plancton/anexo, Accessed in August 12, 2004. Young, R.F. and H.E. Winn (2003). Activity patterns, diet, and shelter site use for two species of moray eels, Gymnothorax moringa and Gymnothorax vicinus, in Belize. Copeia 3(1): 44-55. Zahorcsak, P., R.A.M. Silvano and I. Sazima (2000). Feeding biology of a guild of benthivorous fishes in a sandy shore on south-eastern Brazilian coast. Revista Brasileira de Biologia 60(3): 511-518. Zembal, R. and J.M. Fancher (1988). Foraging behavior and foods of the light-footed clapper rail. The Condor 90: 959-962.  Zerbini, A.N., A. Andriolo, J.M. Rocha, P.C. Simoes-Lopes, S. Siciliano, J.L.Pizzomo, J.M. Waite and G.R. Van Blaricom (2004). Winter distribution and abundance of humpback whales (Megaptera novaeangliae) off northeastern Brazil. Journal of Cetacean Research and Management 6( 1): 101 -107. Zetina-Rejon, M.J., F. Arreguin-Sanchez and E.A. Chavez (2003). Trophic structure and flows of energy in the Huizache-Caimanero lagoon complex on the Pacific coast of Mexico. Estuarine, Coastal and Shelf Science 57(5-6): 803-815.  CHAPTER 5. Assessingfishingpolicies for northeastern Brazil  5.1. Introduction  There is a growing interest in ecosystem-based fisheries management (EBFM) in the last few years resulting from a better understanding of the incompatibility of getting maximum sustainable yield from a number of target stocks (a common management goal) that are trophically linked. There is also an increased concern with the effect of fisheries on the habitats and on non-target species, mainly those long-lived and with low reproductive rates such as cetaceans, seabirds, sea turtles, and sharks (see, e.g., Hall et al, 2000). The importance of ecosystem considerations was recognized as early as the mid-1950s, even though a low priority was assigned to them (Schaefer, 1956). As an example, Holt (1978) advocated that moving from managing yellowfin tuna fisheries from maximum sustainable yield (MSY) to maximum economic yield (MEY) would benefit dolphins incidentally caught by purse seiners.  Although EBFM is not a new idea from the theoretical point of view, there is much to be learned about how to make it operational and ultimately how to measure its success. Link (2002b) suggests that one can expand on the few approaches already available in Fishery Management Plans that consider ecosystem effects of fishing in conjunction with the traditional single species approaches. The same author lists several issues to be ranked by priority in specific ecosystems as a starting point, which are related to the geography of the system, abiotic factors, key species, species interactions, aggregate and system level  properties, and fisheries (Link, 2002a). The analysis of each of these issues requires the establishment of an open dialogue amongst all stakeholders involved in ecosystem-related activities in order to decide on goals, objectives, strategies, indicators of performance at the ecosystem level (both traditional and innovative), monitoring system, and feedback mechanisms.  High complexity of ecosystems often leads to responses to management measures that are not always foreseen in single species management plans. In attempts to protect stocks from the direct impact of fisheries, technical measures such as the use of nets with larger mesh sizes are one of the most traditional measures recommended since the establishment of fisheries science in the late 1800s. In a search for a better understanding of the trophic links between species in an ecosystem, it was found that larger meshes may decrease the impact on non-target species that act as competitors of target species, and thus have a deleterious effect on the latter. This is one of the reasons that led the Organization for Economic Co-operation and Development to consider this measure inefficient unless used in conjunction with another management measures (OECD, 1997). Along these lines, Walters and Kitchell (2001) postulated a phenomenon of 'cultivation/depensation': high fishing pressure leads to low population abundance; after a reduction in fishing effort, the population may be unable to recover due to the predation release of some prey of the target species that act as competitors (or predators) of juveniles of the target species. Testing for this effect is possible using multi-species models, and the results have profound policy implications.  Another current issue related to trophic relationships within ecosystems is the proposal of resuming whaling activities as a way of improving the state of fisheries worldwide. The  rationale behind this proposal is the increasing consumption by marine mammals of species targeted by commercial fisheries as a result of increasing abundance of mammals. A cull has even been proposed for a few marine mammals that are perceived as important competitors of fisheries (Yodzis, 2001). Besides the ethics involved in culling, the effects of such measures in highly complex environments are not direct and guaranteed, as culling can result in increasing abundance of competitors or predators of other target species. Additionally, Kaschner and Pauly (2004) found that the trophic and spatial overlap between fisheries and mammal consumption is lower than usually assumed and restricted to specific areas. Thus, culling of marine mammals would have only minimal effects on global catches.  Fisheries are not only about 'fishes' and their competitors and/or predators. Fisheries are supposed to generate profit and employ people. With a growing world population, particularly in developing countries, and increasing demand for fish protein (Delgado et al, 2003), there is a need to consider different ecological, economic, and social goals under a much higher pressure than earlier. One way this can be accommodated is through multi-objective functions that include these three dimensions of fisheries to identify an 'optimum' use of a natural resource (see, e.g., Healey, 1984).  Fisheries management schemes around the world have evolved to a very high degree of complexity in order to try to optimize gains obtained from fishing activities, which in most cases require a decrease in fishing capacity. Some developing countries such as Brazil are still striving to boost their fisheries through programs to increase fishing capacity. The Special Secretary of Aquaculture and Fisheries (SEAP) launched the 'Profrota Pesqueira' in 2004, a program aiming to increase and modernize the Brazilian fishing fleet (Anon., 2004). The  objective of this program is to give incentives to build, buy, or adapt a total of 370 vessels for oceanic fisheries targeting tuna and tuna-like fishes, and to build another 150 medium and large vessels to catch laulao catfish (Brachyplatystoma vaillanti), southern red snapper {Lutjanus purpureus), and southern brown shrimp (Farfantepenaeus subtilis) off northern and northeastern Brazil. Simultaneously, the Brazilian government has put in place a national campaign to increase the per capita consumption of seafood in Brazil to above the current 7 kg-year" . Both these programs require a heavy system of subsidies, which Brazil considers 1  essential to the development of fisheries in developing countries. They should be therefore included in a 'green box' of allowed subsidies, as part of a special treatment by the World Trade Organization (WTO) towards developing countries aiming at the development of their fisheries (Anon., 2005).  In northeastern Brazil, fisheries targeting tunas and tuna-like fishes, lobsters, southern red snapper, shrimps, and demersal fishes are very important as a result of their bulk catch or the revenue generated by their exports. Many of the stocks in this region are considered overexploited. Lobster is one of the most valuable resources in northeastern Brazil due to its very high price in the international market. Catches are mainly exported to the US, where 21% of the spiny lobster commercialized originates from Brazil (Cascorbi, 2004). Swordfish, shrimps, and southern red snapper catches are also, at least partially, exported.  In this chapter, the effect of current fishing practices over these stocks will be analyzed in the light of the information available for each fishing sector. Also, the degree in which the current information allows for increasing fishing effort as proposed by national plans will be assessed.  Some scenarios for future fishing policies will be investigated, with emphasis on the lobster fishery for which long time series of catch and effort are available.  5.2. Material and Methods  The Ecopath model constructed in Chapter 4 for the marine ecosystem off northeastern Brazil was used as the basis for the simulations of fishing policies presented in this chapter. Some additional fisheries-related data were required and are presented in the following subsections. Temporal changes in biomass were assessed through the Ecosim module included in the Ecopath with Ecosim (EwE) software, version 5.1 (Walters et al, 1997; Christensen et al, 2004):  (1)  dB " " - r = 8i!,Qji-ILQiJ at  j  + /  - -W0,+F,  +e,)-B,  j  where: dB,/dt = change in biomass of group /; g, = net growth efficiency; Qj, = consumption of group j by group /; n = number of functional groups; Qjy = consumption of group i by group j; I,- = immigration of group i; MO, = non-predation natural mortality rate of group i; F,- = fishing mortality rate of group /; e, = emigration of group i; and B, = biomass of group i.  All simulations were performed for a fifty years period through changes in fishing effort for each fleet or fishing mortality for each exploited species (according to data availability) amongst the 41 groups included in the model (Table 5.1; see also Chapter 4). During the simulations, fishing effort and mortality were allowed to change only for the 2001-2028 period.  Table 5.1: Groups used in the simulations of fishing policies and their respective trophic level and biomass in the total area of the East Brazil Large Marine Ecosystem (After Chapter 4). Group name 1. Manatee 2. Baleen whales 3. Toothed cetaceans 4. Seabirds 5. Sea turtles 6. Tunas 7. Other large pelagics 8. Dolphinfish 9. Dolphinfish juveniles 10. Swordfish 11. Sharks 12. Rays 13. Small pelagics 14. Needlefishes 15. Southern red snapper 16. Large carnivorous reef fishes 17. Small carnivorous reef fishes 18. Herbivorous reef fishes 19. Omnivorous reef fishes 20. Demersal fishes 21. Mullets 22. Spotted goatfish 23. Benthopelagic fishes 24. Bathypelagic fishes 25. Spiny lobsters 26. Other lobsters 27. Shrimps 28. Crabs 29. Squids 30. Octopus 31. Other molluscs 32. Other crustaceans 33. Other invertebrates 34. Zooplankton 35. Corals 36. Microfauna 37. Phytoplankton 38. Macroalgae 39. Mangroves 40. Seagrasses 41. Detritus  Trophic level 2.02 3.72 4.45 3.45 3.15 4.31 4.50 4.58 4.42 4.56 4.65 3.88 3.05 3.43 4.21 4.01 3.68 2.00 3.33 3.36 2.04 3.50 3.58 3.58 3.30 3.25 2.73 2.61 3.64 3.58 2.35 2.17 2.16 2.47 2.83 2.00 1.00 1.00 1.00 1.00 1.00  Biomass (tkm ) 0.000004 0.385200 0.142700 0.015000 0.163000 0.035000 0.025700 0.000500 0.001280 0.009400 0.032400 0.101300 0.604500 0.115000 0.014300 0.233800 0.972600 1.116400 1.140000 1.346800 0.763100 0.050500 0.074600 1.170600 0.013800 0.611100 3.900600 1.507700 0.176700 0.151000 2.531000 1.590600 6.997900 2.165600 0.063100 5.989000 12.085900 98.405500 77.761600 0.052000 201.912800 2  5.2.1. Fleet definition and landing data  The fishing fleet operating in northeastern Brazil was divided into twelve groups: large pelagic artisanal, small pelagic artisanal, manual collection, demersal artisanal, longline, reef, lobster, demersal industrial, turtle, whaling toothed, whaling baleen, and snapper. This division was chosen to represent some of the basic dynamics of the fleet operating off northeastern Brazil under the limitation of data availability for several more specific fisheries. Landing data compiled in Chapter 3 were used here after being divided amongst the twelve fleet types based on the knowledge about the dynamics of each species and fleet/gear. As in Chapter 4, catches recorded by any broad category indicating 'other fishes' and originating from subsistence, recreational, ornamental, and research fisheries were not considered here.  5.2.2. Ex-vessel prices of 'fish' products  Ex-vessel prices of 'fish' products (at dockside) were obtained from SUDEPE (1980) (Table 5.2). No distinction was made for price of products originating from artisanal and industrial fisheries, as prices are estimated by the ratio of total value to total catch (after combining both fisheries) in the original sources. Non-market value was not considered in this analysis.  5.2.3. Fishing costs and profits  Fishing costs (fixed and variable) and profits were obtained from local studies for those fleets for which data were available. Thus, data for crab capture were considered as representative of manual collection fisheries (Glaser and Diele, 2004). For demersal artisanal and lobsters fisheries, data were obtained from Carvalho et al. (1996; 2000). No local data was found for the other fleet types. For large pelagic artisanal and industrial demersal fisheries, the  Group name / Fleet  LPelArt  Baleen whales Toothed cetaceans Sea turtles Tunas Other large pelagics Dolphinfish Swordfish Sharks Rays Small pelagics Needlefishes Southern red snapper Large carnivorous reef fishes Small carnivorous reef fishes Herbivorous reef fishes Omnivorous reef fishes Demersal fishes Mullets Spotted goatfish Benthopelagic fishes Spiny lobsters Shrimps Crabs Octopus Other molluscs Other crustaceans  _ — _ 20.3 22.4 26.8 10.9 — — _ — — — _ — _ 14.2 _ — —  SPelArt _  Manual _  — _ 12.7 16.9 _ — — — _ — _ — _ —  DemArt _  Longline  _  —  _  —  _  _  11.05 — _ _  — — — _ — _ — _ 11.7 25.9 29.3  _ _  — — — _ 16.1 24.8 _ — _ 25.0 _ _ _ 35.0  Lobster  _  — _ 20.3 22.4 26.8 21.4 10-.9 12.7  _  — _  Reef — _ _ _ _ _ -  _ — _ _ _ _ _  _  _ — — — — _ _ _ _ 14.2 _ _ _ _ _ _ _ —  _ _ _ — _ 21.6— 16.9 — 19.9— 179 _ _ _ _ _ _ 22.4 _ _ _ 116.4 _ _ _  Demlnd  Turtle  _ — _ _ _ _ _  _ — .8 _ _ _ _  —  _  — — _ _ 16.1 _ _ — 25.0 _ _ _ ~  4.6 _ _ _ _  10  11.0 _ _  _ _ _  j^jj^f  •  _ — — — _ _ — _ _ — _ _ _ ~  _ — — — _  — — _ —  ^leerf 4^ — _ _ _ _ _ _ — — — _ _ — _ _ — _  S n a  PP  e r  — — _ 22.4 _ _ _ 23.4 21.6 16.9 _ 179 16.1 _ _ —  _  _ _  _ ~  1. Price in cruzeiros (Cr$), the Brazilian currency in 1978 (US$ 1 = Cr$ 17.98 in 1978; www.bcb.gov.br); 2. In this thesis, for convenience, the names of the fleets are derived either from their size ("small scale pelagic artisanal"), their gear ("longline") or their target organisms ("lobsters"); and 3. Dashes indicate no catch. Source: SUDEPE (1980).  information available in Arreguin-Sanchez (2002) was used as an indication of potential costs and benefits for these fleets. For small pelagic artisanal fisheries, estimates provided by Trinidad et al. (1993) were used. Pedrosa and Carvalho (2000) analyzed the cost of longline fisheries harbored in Rio Grande do Norte State. However, it was not possible to incorporate their results in this model due to the lack of a revenue value for comparison. Similarly, results from Mattos and Hazin (1997) for shark longline could not be used due to limitations imposed by the use of research vessels (as also pointed out by these authors). Costs and benefits from longline fisheries were then obtained for a combination of foreign fisheries targeting tuna and swordfish (O'Malley and Pooley, 2003).  Burke and Maidens (2004) provide an estimate of cost of reef fisheries in relation to gross revenue, but do not mention the relation between variable and fixed costs; this partition was based in Arreguin-Sanchez (2002). For turtle fisheries, the estimate for crab fisheries was used considering that individuals are collected by the beach, when laying eggs during the reproduction season, and are sold or consumed locally. Even though southern red snapper is considered an important target of fisheries in northeastern Brazil, no local data on the economics of this fishery was found. It was assumed that the breakdown of costs and benefits are similar to the lobster fisheries, as both fisheries target the external market (export), use traps (although not exclusively), and the stocks are considered overexploited.  Finally, for whaling activities, data from Conrad and Bjorndal (1993) were used, complemented with information on number of whaling vessels available in Statistics Norway (2005), correcting costs for the time spent in whaling activities in opposition to other fishing activities (38-41%). However, these authors did not provide any ratio between fixed and  variable costs and thus, an average value of the fixed cost for all industrial fleets (longline, demersal, and lobster) was used. Details of the breakdown of fishing costs and profits are presented in Table 5.3. Table 5.3: Cost of each fishing fleet operating off northeastern Brazil for the simulation performed based on the 1970s Ecopath model. Fleet  Abbreviation  1. Large pelagic artisanal 2. Small pelagic artisanal 3. Manual collection 4. Demersal artisanal 5. Longline 6. Reef 7. Lobster 8. Demersal industrial 9. Turtle 10. Whaling toothed 11. Whaling baleen 12. Snapper  LPelArt SPelArt Manual DemArt Longline Reef Lobster Demlnd Turtle Toothed Baleen Snapper  Fixed cost (%) 2.0 0.6 0.0 8.3 18.6 2.9 7.3 4.5 0.0 10.0 10.0 7.3  Variable cost (%) 33.0 80.0 32.9 75.0 73.0 47.1 92.5 45.5 32.9 70.0 70.0 92.5  Profit (%) 65.0 19.4 67.2 16.7 8.4 50.0 0.2 50.0 67.2 20.0 20.0 0.2  5.2.4. Optimum fishing policy search  The first simulation was run considering the maintenance of the 2000 level of fishing effort or mortality for all exploited fishing groups. Secondly, an optimum fishing policy for all fleets operating off northeastern Brazil was assessed based on economic, social, and ecological criteria using the 'fishing policy search' routine available in Ecosim. The optimum policy search was based on a non-linear search procedure for maximizing the following multicriterion function: (2)  Max  oulpul  =w f f NPV w f NJ w f B J l d j  1=1 > i  ij+  2 d  j=\  j+ 1=1  i d  i  P  where NPV# = net present value of the catches of functional group i by fleet j; I = number of fleets = 12; k = number of exploited groups = 26; NJ = number of jobs generated by unit of y  monetary value of catches; B, = biomass; (P/B), = production over biomass ratio, obtained from the basic input of Ecopath; and wi, w and w are weights (see below). A nonlinear 2  3  optimization method known as Fletch was used in this search (Fletcher, 1970). Changes in fishing effort and mortality were applied to the levels observed in 2001 and onwards for all fleets used in the model, except for turtle fisheries and whaling (toothed and baleen), as they were banned during the 1980s.  The economic criterion was assessed through the net present value (NPV) of the resources exploited in the future, partially based on the opportunity cost of the capital. NPV was calculated as follows:  NPv = Yy,w  t  t=o  where: T = simulation period (2000-2028); V = net benefit in year t = gross revenue minus t  cost; W = weight used to discount the benefit (V ) = d ; d = l/(l+r); and r = conventional l  t  t  discount rate. In order to consider future generations, an intergenerational discount factor (df ) g  was added to the simulations, through changes in the weight W (Sumaila and Walters, 2005): t  d d'~ t W=d'+^l  f  G  where df = intergenerational discount factor in year t and is equal to l/(l+rf ); % = g  g  intergenerational discount rate and it was assumed equal to r; and G = generation time (assumed equal to 20 years). Discount rates (r and r ) of 10% were used as Sathaye et al. fg  (cited in Van Vliet et al, 2003) considers that 8-12% is the usual rate for developing countries.  Gross revenue was calculated as the product between catch and price per kilogram for each functional group. Catch was obtained for 1978 as shown in section 5.2.1 and price was obtained from SUDEPE (1980) (Table 5.2).  The social criterion was defined through the number of jobs provided per catch value for each fleet. The estimated number of jobs provided by fishery type in northeastern Brazil is presented in Table 5.4.  Table 5.4: Estimated number of jobs provided by each fishery type in northeastern Brazil. No. jobs per Fishery  R$ 10,000 of  Sources  catch* 1. Large pelagic artisanal 2. Small pelagic artisanal 3. Manual collection 4. Demersal artisanal 5. Longline 6. Reef 7. Lobster 8. Demersal industrial  1.9 7.6 7.1 0.8 0.1 1.4 3.2 7.4  9. Turtle  3.4  2.1 10. Whaling toothed 0.4 11. Whaling baleen 12. Snapper 0.6 * In 'reais' = Brazilian currency from 1994  CEPENE (2000a), Database in Chapter 2 CEPENE (2000a), Database in Chapter 2 Costa-Neto and Lima (2000), Alves and Nishida (2003) CEPENE (2000a), CEPENE (2000b) Evangelista et al. (1998), Database in Chapter 2 CEPENE (2000a), Database in Chapter 2 Castro e Silva et al. (2003), CEPENE (2000a) CEPENE (2000a), CEPENE (2000b) Based on manual collection, considering the price/kg for turtle SUDEPE (1979), Singarajah (1985), Rabay (1985) SUDEPE (1979), Singarajah (1985), Rabay (1985) Based on lobsters, considering the price/kg for snapper on; US$ 1 = R$ 2.47 (May 2005).  The ecological criterion intended to maximize the biomass of long-lived animals, i.e., the biomass of each functional group was weighted by the inverse of its production/biomass ratio. The rationale behind this approach is that the presence of long-lived organisms with low P/B ratios is associated with the maturity of an ecosystem (Christensen et al, 2004).  The partial effect of each criterion was assessed through four scenarios depending on the management objectives assumed for the study area:  (a) Economic: maximization of the economic rent (net benefit = revenue-cost); wi was set to 1; w and W 3 were set to zero; 2  (b) Social: maximization of number of jobs; w was set to 1; wi and W 3 were set to 2  zero; (c) Ecological: maximization of ecological benefits; W 3 was set to 1; wi and w  2  were set to zero. (d) Compromise: in this scenario, all three components (economic, social, and ecological) were considered equally important and wi, w , and w were set to 1. 2  3  (e) Mandated rebuilding: in this scenario, wi and w were equal to 1; w was set to 2  3  5 and the model was forced towards a policy aiming to increase the biomass of sharks. The mandated relative biomass of sharks was set to 1, indicating that the biomass of this group should maintain the value estimated for the year of the base model (1978).  5.2.5. Lobster fishery and future fishing policies  A simulation was run in Ecosim for 50 years (1978-2028) in order to analyze the effect of changes in the effort employed by lobster fisheries in relation to the 2000 effort level under four scenarios: (a) same constant effort level as observed in 2000 (status quo); (b) decrease of 50% in effort over the first year and constant thereafter (1/2 effort); (c) ban of lobster fisheries; (d) recovery plan (to the 1978 biomass level). For all other fleets, effort was considered constant at 2000 levels for the period 2000-2028.  5.3. Results  The simulation of the performance of the main functional groups in the marine ecosystem off northeastern Brazil under the current fishing regime indicates that spiny lobsters will be extirpated from the system in a short time (Fig. 5.1). Biomass of swordfish would also decrease to unsustainable levels in a short time. Groups such as sharks and other large pelagics will continue to decline slightly with their biomass stabilizing at 81% and 69% of the 1978 level, respectively. Decreasing biomass of sharks may lead to a slight increase in tunas' biomass due to the decreasing predation pressure. An increase in biomass would be expected for baleen whales. Southern red snapper biomass would stabilize at the 2000 level.  2.0  r  1.6 -  1978  1988  1998  2008  2018  2028  Figure 5.1: Biomass of functional groups that showed variation in relation to the original biomass (1978) for northeastern Brazil during the simulations for 50 years. Fishing rates for 2000-2028 were set at levels observed in 2000.  The simulations for the optimum configuration of the fleet of northeastern Brazil as a whole indicated that very similar configurations would result when trying to maximize rent, number of jobs, and the compromise (rent, jobs, and biomass of less productive groups, all equally weighted). In all three cases, the effort of manual collection for crabs and other molluscs could be increased to more than 100 times the current level (Fig. 5.2). The effort of demersal industrial fisheries could also be largely increased, although to an extent less than the effort of manual collectors. One important difference amongst these three scenarios is that small pelagic artisanal fisheries are recommended to increase in order to produce jobs under the social and compromise scenarios, but not from the economic point of view. In terms of maximizing number of jobs per catch value and profit, fisheries such as lobsters and reef fisheries would have to be shut down. In order to maximize the ecological structure of the system, five fisheries could maintain their current fishing pressure: small pelagic artisanal, manual collection, artisanal and industrial demersal, and reef fisheries (Fig. 5.2). Longline and lobster fisheries would have to be practically shut down. On the other hand, large pelagic artisanal and snapper fisheries could increase the fishing pressure to 6 and 2 times the 2000 level, respectively.  The recommended configuration of the fleet would result in changes in biomass very similar amongst the four scenarios. Particularly, one can note that the biomass of swordfish, tunas, and spiny lobsters would increase in all scenarios, with higher rates in the ecological scenario (Fig. 5.3). Most of the remaining groups would have their biomass constant during the simulated period or slightly decreased. Note that lesser groups in the ecological scenario reach lower biomass than in 2000.  a)  180 160 140 120 h 100 80 60 40 20 0  b) 180 160 140 120 100 80 60 40 20 0  c)  6 r 5 -  fg  4 3 2 1 0  d)  180 160  C  I  1 4 0  120  g IOO  2,  80 60 40 20 0 LPelArt  SPelArt  Manual  DemArt Longline  Reef  Lobster  Demlnd Snapper  Figure 5.2: Relative changes in fishing effort (f2028/f2ooo)for each fleet included in the 1978 model for northeastern Brazil after a simulation from 2000 to 2028 under four scenarios: a) economic, b) social, c) ecological, and d) compromise ( n ^ = 10). Columns represent means and whiskers are means plus one standard deviation. Note the different scale used in the vertical axis for the ecological scenario (c). The horizontal dotted line in (c) indicates the 2000 effort level (not shown for the other scenarios).  a)  60  r  50 40 30 20 10 0  -10 b)  L  60 50 40 30 20 10 0  -10  c)  L  60 50 40 30 20 10 0  -10 d)  60 50 40 30 20 10 0  -10  t5 ,2 ^ M  S « 4* ^ju  c 3  O.J3  9-„ _ .|  — Sue  «©Q  •A o  3§  Figure 5.3: Mean relative change (B d/B2ooo - 1) in biomass for all functional groups (trophic level > 2; en  arranged in decreasing order) obtained by simulations for the period 2000-2028 under four optimization scenarios: a) economic, b) social, c) ecological, and d) compromise ( n ^ = 10). Compromise indicates that an equal weight was given to the components a-c.  All scenarios discussed seem to be somewhat masked by the interaction between sharks and swordfish/tunas. In order to increase the biomass of tunas and swordfish (two groups with a high trophic level and high market value), sharks (which prey on tunas and swordfish) had to be fished out. As this is an unacceptable scenario due to Brazil's commitments towards the International Plan of Action for Sharks, a fifth scenario was run where a recovery of shark biomass was aimed for. The results of this scenario, which considers economic, social, and mandated rebuilding as equally important and attributes a higher weight in the multi-criterion function to the ecological component, are similar to the compromise scenario. However, fishing effort of large pelagic artisanal and longline fisheries should be decreased even further in order to protect sharks (Fig. 5.4). Lobster fisheries are expected to be turned off as well due to its low profitability. As in most of the other scenarios, manual collection effort could be increased in order to maximize profitability and number of jobs generated by this fishing sector.  I 1  180 160 140 120 100 80 60 40 20 0 LPelArt SPelArt Manual DemArt Longline  Reef  Lobster Demlnd Snapper  Figure 5.4: Relative changes in fishing effort (f2028/f2ooo)in relation to 2000 for each fleet included in the 1978 model for northeastern Brazil after a simulation for 2001-2028 under the mandated rebuilding scenario aiming at the recovery of shark populations (n^ = 10). Columns represent means and whiskers are means plus one standard deviation.  In terms of biomass, the mandated rebuilding scenario would lead to an increase of 21% in the biomass of sharks (Fig. 5.5). On the other hand, it would be expected a decrease of 52% in the biomass of tunas, 62% for southern red snapper, 38% for demersal fishes, 20% for small pelagics, and 29% for mullets. Swordfish would benefit from such a fleet configuration, probably due to a combination of the release from the competition imposed by tunas and from the fishing pressure by longliners. A strong increase in biomass of lobsters also resulted from this configuration due to the closure of non-profitable lobster fisheries.  • U °  °  °~tr  Figure 5.5: Mean relative change in biomass for all functional groups with trophic level (TL) equals or higher than 2 (arranged in decreasing order), obtained by the simulation for 2001-2028 under the mandated rebuilding scenario (n™^ = 10). This scenario aims to recover shark biomass to the 1978 level and considers an equal weight for the economic, social, and mandated rebuilding component (1). A weight of 5 was attributed to the ecological component.  A closer look at lobster fisheries indicates that a reduction of 50% in effort would avoid the looming collapse of the spiny lobsters' stocks and would lead to a slight increase in biomass (Fig. 5.6). These stocks would reach the same level of biomass as observed in 1978 only if the fishing effort were reduced to the 1978 level. A complete ban of lobster fisheries would result in a biomass 22% higher than the recovery scenario (Fig. 5.6 and Table 5.5). The more realistic recovery plan would lead to a very high gain in biomass (more than 9 times higher than the 2000 level) and to gains in catch (92%).  Recovery  1/2 effort Status quo 1978  1988  1998  2008  2018  2028  Figure 5.6: Changes is biomass of spiny lobsters in relation to the 1978 baseline after four policy strategies: maintenance of current fishing effort (status quo); reduction of effort to 50% of the 2000 effort level (1/2 effort); effort required to reach the 1978 biomass level (recovery); and banning of lobster fisheries (ban).  Table 5.5: Changes in biomass and catch for spiny lobsters caught by lobster fisheries in northeastern Brazil estimated in relation to 1978 and 2000 baselines (Year ) resulting from changes in effort storl  representing four scenarios (status quo, decreasing fishing pressure by 50% in relation to 2000 level, recovery of biomass to the 1978 level, and ban of lobster fisheries). Year tart s  Year  end  Biomass  Catch  Effort  Observed  1978  2000  0.10  0.47  4.80  Status quo < 50% effort Recovery Ban  1978 1978 1978 1978  2028 2028 2028 2028  0.00 0.41 1.00 1.22  0.00 1.01 0.96 0.00  4.80 2.40 0.96 0.00  Status quo < 50% effort Recovery Ban  2000 2000 2000 2000  2028 2028 2028 2028  0.00 3.99 9.66 11.83  0.00 2.01 1.92 0.00  1.00 0.50 0.20 0.00  5.4. Discussion  The results of the simulations presented here indicate that the current levels of fishing pressure would lead to even further decline and eventual collapse of important local stocks such as lobsters and swordfish. As these stocks are mainly caught to supply international markets, these collapses would represent an important loss in terms of acquisition of foreign currency through exports. For other target groups such as sharks, and other large pelagics, biomass would continue declining slightly for the first years and would stabilize after that.  Avoiding the collapse of main fisheries requires that some decisions are made about the perceived 'value' of different components of an ecosystem and the benefits expected from its natural resources. As simulated here using a defined set of values (reflected in the weights used in the multi-criterion function), the ecological scenario resulted in a more diverse fleet  configuration in relation to the other scenarios. Curiously, an increase in fishing effort of the artisanal large pelagic fishery is recommended in this scenario. This probably results from the high catches of sharks by this fishery in relation to the industrial sector (longliners). Sharks prey on groups that have a high B/P ratio, which served as a criterion to define the ecological structure of the system. Thus, the increasing effort for the artisanal pelagic fishery represents an attempt to decrease the biomass of sharks to obtain higher biomass of such groups. However, this scenario is not realistic as the low proportion of sharks recorded by longliners results from an artifact due to the non-inclusion of shark discards resulting from finning practices (Lessa et al, 2004). Some effort should be put into determining the magnitude of these discards or hope for their complete ban after international initiatives such as the recent position of the International Commission for the Conservation of Atlantic Tuna (ICCAT) favorable to ban finning practices (Ocean Conservancy, 2004).  The compromise scenario suggested a fleet configuration equal to the social scenario and very close to the economic scenario. This reveals the importance of the way the multi-criterion function is defined and the weights attributed to each component included in the function. Zetina-Rejon et al. (2004) and others had already mentioned the similarity of the economic and social scenarios when fisheries that result in higher rent are the same that produce more jobs, in this case, manual collection fisheries targeting crabs and molluscs. Promoting manual collection does not seem plausible in terms of fishing policy, due to its essential subsistence feature, but these results indicate that there is potential for growth from a social and economic perspective. However, the biological limits of the target stocks have to be respected and are likely to be affected by pollution in coastal areas caused by urban and industry development and by destruction of mangrove areas (Leao and Dominguez, 2000; Marques et al, 2004).  Additionally, the introduction of a new gear for collecting crabs ('redinha') has resulted in a three-fold increase in catchability, raising concern for the eventual overexploitation of these resources (Ivo and Vasconcelos, 2000).  One factor that affects the simulation of future economic gains of alternative fishing policies is the discount rate. A rate of 10% was used in the simulations run in this chapter, which reflects the high discount of future benefits in developing countries. The use of high values usually leads to the degradation of natural resources (Field and Olewiler, 2002). This opinion is shared by Costanza et al. (1997), who indicate that rates higher than 5% result in unsustainable practices. In fact, some simulations for the extraction of wild palmito in Brazil compiled by Orlande et al. (1996) indicated that rates in excess of 8% favored total extraction. All scenarios simulated here, but the ecological one, did suggest a very high increase in the most profitable fisheries. It is recommended that the effect of lower and higher discount rates be assessed in determining the trade-offs amongst different fishing sectors in northeastern Brazil.  All simulations presented here assumed no change to the ban of manatee, turtles, and whales fisheries, but did not explicitly consider the non-market value of these groups. This value was partially recognized through the use of the inverse of the P/B ratio in the definition of the desired ecosystem structure in the ecological and compromise scenarios. In the mandated rebuilding scenario, this value was set up even higher by the use of a weight of 5 for the ecological component (and 1 for all others). Ultimately, the decision on the relative weight of each component included in the multi-criterion function is to be reached through an agreement amongst all stakeholders involved in a direct or indirect way with the allocation of natural resources (Healey, 1984), within a framework of integrated coastal management that up to  now has been considered deficient in northeastern Brazil and, in fact, in the whole country (Marques et al., 2004).  The results generated by the simulations indicate that the biomass of several groups would be at lower levels by 2028 than in the 1970s, if current fishing pressure is maintained. Some of them would even collapse in a short time. The bulk of the increase in the fishing fleet proposed by the Brazilian government is directed towards increasing the fleet targeting tuna and tunalike fishes. The model used as the basis for the simulations run in this chapter are not able to correctly duplicate the dynamics of these groups due to their highly migratory behavior. Thus, much of the response of the stock biomass to the fishing pressure within the East Brazil Large Marine Ecosystem (off northeastern Brazil) will depend on the fishing effort applied along the whole distribution area of the respective stocks. If the increase in the oceanic fleet size is coupled with negotiations of Brazil within ICCAT to increase its quotas, the scenario would be more positive as the total effort exerted over the stock is not expected to increase. If not, further decline of these stocks, beyond the documented by Myers and Worm (2003) and by ICCAT (2004b; 2004a; 2005), is expected.  For snappers and shrimps, the incompleteness of information evidenced through this simulation exercise indicates that increases in effort proposed by the 'Profrota Pesqueira' program have not been a result of a complete analysis of these fisheries. No cost-benefit analysis was found for snapper fisheries and the times series of catch and effort are not complete enough to allow for an analysis of CPUE trends (even with all its limitations). Additionally, the interchangeability between vessels targeting snappers and lobsters may pose additional fishing pressure on lobster stocks. The number of licenses allowed for shrimp  trawlers in northern Brazil (for which catch and effort data are available) decreased from 250 to 185 in 1997 [Negreiros-Aragao and Silva, 2000]. The proposal to build new vessels for this fishery counteracts previous attempts to control fishing effort; old vessels may remain in this sector or be re-directed to other fisheries increasing the fishing pressure. Detailed information about the status of shrimp stocks in northeastern Brazil are lacking.  The lobster fishery is one of the most well studied fisheries in Brazil. In 2004, lobster exports yielded US$ 75 million, indicating the importance of this fishery for the local economy. The simulations indicated that this stock is expected to collapse within a few years if current fishing pressure is maintained. The biomass level of spiny lobsters would recover to the level observed in 1978 only if there were a significant decrease in fishing effort to the 1978 level. The resulting fishing effort is equivalent to the effort that would produce the maximum sustainable yield of 8,962 tonnes of spiny lobsters (Ivo and Pereira, 1996), a value well above the 6,500 tonnes officially recorded for 2000 (according to the database compiled in Chapter 3). Fishing effort in 2000 was 3.7 times higher than the 1978 level and 37.4 times higher than in 1965 when the first data were collected for lobster fisheries, indicating a strong decline in catch rates. This decline was the main reason that led to the rejection of the application of the lobster fishery in Prainha do Canto Verde (Ceara State) for certification by the Marine Stewardship Council (Chaffee, 2001; Scharer, 2001).  One factor not captured in these simulations was the dynamics of industrial and artisanal lobster fisheries due to the absence of effort data for each component. Castro e Silva et al. (2003) comment on the transference of boat ownership from large companies targeting lobsters to artisanal fishers, through special arrangements. Indeed the database presented in Chapter 3  was able to capture this transference through a change in the bulk of catches originating with industrial fisheries up to 1995 and with artisanal fisheries since then. It is also well known that effort was displaced to the coast of other States where the lobster fishery was not fully developed (IBAMA, 1994), and this could mask even more severe local depletions.  The analysis of the dynamics of lobster fisheries as presented here is also limited due to inclusion of one single fleet called 'lobster fisheries'. However, this sector is far from homogeneous as three basic gears are used in northeastern Brazil: traps, diving, and gillnets ('cacoeira'), each one with its own dynamics. Traps were introduced since the establishment of this fishery as an industrial activity in the late 1950s and the latter two were introduced in the 1970s after the decline in the CPUE obtained by lobster traps. Traps maintained legal status since its introduction, but gillnets and diving oscillated between the legal and illegal status in the last decade or so. Gillnets are responsible for the destruction of the substrate and in some cases led to the removal of up to 200 kg of substrate/net-day in Ceara State (Paiva et al. 1973, cited in Ivo and Pereira, 1996). Removal of substrate was also documented in Rio Grande do Norte State: 2.2 kg/100 m net-day (Vasconcelos and Lins-Oliveira, 1996). In relation to the size caught, Ivo and Ribeiro Neto (1996) did not find any statistical difference between the mean size of lobsters caught by gillnets and traps in Ceara State. In early 2005, a movement towards banning the use of gillnets had apparently succeeded after three years of negotiations. However, this regulation was withdrawn some days later due to the pressure of the industrial sector (www.ibama.gov.br; Rene Scharer, pers. comm., Instituto Terramar, Fortaleza, Brazil).  Diving is responsible for the capture of immature lobsters when practiced in waters shallower than 20 m (Lins-Oliveira et al, 1997). In addition to the negative impact on the biological  component of this fishery, there is a strong social component of this fishery that has to be considered: number of deaths and disability caused by physiologically inappropriate diving profiles. It is estimated that 90% of all lobster divers in Rio Grande do Norte State have suffered at least one diving accident (Procuradoria Regional do Trabalho - RN, 2005). Considering that lobsters have a market price about 3.3 higher than the second most valuable seafood resource, and as such are considered 'sea gold', the gains with diving activities are perceived as higher than the losses, and are worth the risk. This perception is emphasized by higher rents obtained by divers (and gillnets) in relation to trap fisheries (Carvalho et al., 1996). The diving sector of lobster fisheries poses an additional challenge in terms of maximizing the objective function. Although this sector produces higher rent than the trap fisheries, and generates high number of jobs, there is a high risk associated with this activity that is not accounted for in the Ecosim simulations. A penalization system for such risky fisheries would allow simulations to become more realistic, as was done for the New England herring fishery (Healey, 1984).  Thus, future developments of this model require the incorporation of the three gear types involved in lobster fisheries. This was not possible in this version of the model due to the lack of effort data for gillnet and diving sectors. Additionally, the recording system of Brazilian fisheries precluded the split of total lobsters catches amongst these three gear types. The incorporation of the dynamics of each lobster fishery will be a hard task due to the illegal nature of diving activities in northeastern Brazil since 1978 (Vasconcelos and Lins-Oliveira, 1996). The analysis of trade-offs for lobster fisheries in relation to another fisheries occurring in this region also requires a better understanding of relative importance of artisanal and industrial lobster fisheries. Finally, the spatial dynamics of the fleet should be incorporated,  possibly through the use of Ecospace, a module available in EwE that allows for spatial simulation (Walters et al, 1999).  All the simulations presented here inherited the high degree of uncertainty associated with the input data used in the Ecopath model built in the previous chapter. This uncertainty, associated with the lack of information on the social and economic aspects for most of the local fisheries, leads to a high degree of uncertainty in the results of the simulations. The scenarios simulated in this chapter did not consider differences in ex-vessel prices between artisanal and industrial fisheries, as national fisheries statistics only provide combined prices. Additionally, the results are valid only for a scenario of constant price for each fished group. Negreiros Aragao (2005) points out that the price for Brazilian spiny lobsters, e.g., has increased in the last years. This increase in price can precipitate the collapse of this stock due to the attraction of additional fishing effort.  The underestimation of catches, as discussed in the previous two chapters, also leads to somewhat unrealistic scenarios. For example, dolphinfish catches are much higher than officially recorded; a sampling program run in northeastern Brazil was able to sample much more dolphinfish than was recorded in statistical bulletins (Rosangela Lessa, pers. comm., Universidade Federal Rural de Pernambuco, Recife/Brazil). Shrimps are mainly exploited by artisanal fishers (84% on average, according to the database compiled in Chapter 3) and the statistics collection system may be failing to cover it all. The same problem is expected for crabs and other molluscs, which are mainly caught by artisanal fishers in remote areas. Finally, the non-inclusion of by-catch discards in this preliminary version of the model contributes to low exploitation rates. Discarding of by-catch is common practice in northeastern Brazil, but  not usually quantified. Ivo (1996) points out that 47 fish and 9 crustacean species are caught as by-catch in lobster fisheries, and most of them (if not all) are discarded. In some States, the ratio of fish by-catch to shrimp catches in trawling fisheries reaches 5:1, with 50% of the bycatch being discarded (CEPENE, 2000b). In others States, discards from the industrial shrimp fleet include shrimp species caught by artisanal shrimp fisheries, a factor not considered by the model as presently defined.  The simulations presented here will also probably benefit from splitting tuna and swordfish groups into juveniles and adults, with predation by sharks heavily concentrated on juveniles. Fishing pressure on these groups would be somewhat shared by juveniles and adults: for swordfish, slightly higher proportion of juveniles is caught by longliners in this area (Lessa et al, 2004); for yellowfin tuna the composition is reversed, with slightly higher proportion of adults in the catches (Lessa and Duarte-Neto, 2004); for the other two tuna species (bigeye and albacore), no local data was found. Another change recommended is to split the sharks group into two: coastal and pelagic. This would avoid the existence of a 'super shark' group that prey upon both the pelagic and demersal components of the system and thus has an impact on the system higher than expected. This task will be possible only if some effort is spent towards obtaining more detail in the identification of sharks' landings. Fisheries statistics in Brazil record 80-100% of sharks' landings (about 18,000 tonnes for 1978-2000, based on the database compiled in Chapter 3) as 'cacao' or 'caconete' (unidentified sharks).  Even though Ecosim has showed its usefulness for the exploration of fishing policies in other areas (Christensen and Walters, 2004), its application to areas such as northeastern Brazil will depend on more effort to improve the basic trophic model of the region and the collection of  basic social and economic data for many of its fisheries. This is not a challenge for an ecosystem-based fisheries management approach only, but reveals the weakness of the current single-species based fisheries management and that many fishery-related decisions are rather based on guesses and on the belief that the large extension of the Brazilian marine waters would always support a production higher than what is biologically feasible.  5.5. References  Alves, R.R.N. and A.K. Nishida (2003). Aspectos socioeconomicos e percepcao ambiental dos catadores de caranguejo-uca Ucides cordatus cordatus (L. 1763) (Decapoda, Brachyura) do estuario do Rio Mamanguape, nordeste do Brasil. Interciencia 28(1): 36-43. Anon. (2004). Federal Law no. 10849. www.planalto.gov.br/ccivil_03/Ato2004-2006/2004/ Lei/L10.849a.htm, Accessed in May 29 , 2005. th  Anon. (2005). Contribution to the discussion on the framework for disciplines on fisheries subsidies. Paper from Brazil. TN/RL/W/176. http://docsonline.wto.org, Accessed in May 18 , 2005. th  Arreguin-Sanchez, F. (2002). Impact of harvesting strategies on fisheries and community structure on the continental shelf of the Campeche Sound, southern Gulf of Mexico. Fisheries Centre Research Reports 10(2): 127-134. Burke, L. and J. Maidens (2004). Reefs at risk in the Caribbean. World Resouces Institute, Washington, DC: 80 p. Carvalho, R.C.A., C.R.C. Ferreira, J.A. Vasconcelos, M.Y.S. Oliveira and L.M.A. Campos (1996). Custos e rentabilidade de embarcacoes envolvidas na pesca da lagosta no nordeste do Brasil, 1995. Boletim Tecnico Cientifico do CEPENE 4(1): 233-262. Carvalho, R.C.A., M.Y.S. Oliveira, L.M.A. Campos, S.W. Freitas and E.C.S. Silva (2000). Analise de custo e rentabilidade da captura e beneficiamento de camarao, estados de Pernambuco e Alagoas, nordeste do Brasil, 1997-1998. Boletim Tecnico Cientifico do CEPENE 8(1): 279-296.  Cascorbi, A. (2004). Seafood report: Caribbean spiny lobster Panulirus argus. Seafood watch, 61 p. Castro e Silva, S.M.M., A.C.P. Pontes and C.A.S. Rocha (2003). Report on the spiny lobster fishery in Brazil. In: Report of the second workshop on the management of Caribbean spiny lobster fisheries in the WECAFC area. Havana, Cuba, 30 September - 4 October, 2002. FAO Fisheries Report no. 715: 56-67. CEPENE (2000a). Boletim estatistico da pesca maritima e estuarina do nordeste do Brasil 1999. Centro de Pesquisa e Extensao Pesqueira do Nordeste/IBAMA, Tamandare: 150 p. CEPENE (2000b). Relatorio da reuniao tecnica sobre o estado da arte da pesquisa e ordenamento da pesca de camaroes peneideos na regiao nordeste do Brasil. Centro de Pesquisa e Extensao Pesqueira do Nordeste - CEPENE, Tamandare, Pernambuco, Brasil: 64 p. Chaffee, C. (2001). Lobbying for lobsters. SAMUDRA Report 29: 30-36. Christensen, V., C. Walters and D. Pauly (2004). Ecopath with Ecosim: a user's guide. Fisheries Centre, University of British Columbia, Vancouver: 154 p. Christensen, V. and C.J. Walters (2004). Trade-offs in ecosystem-scale optimization of fisheries management policies. Bulletin of Marine Science 74(3): 549-562. Conrad, J. and T. Bjorndal (1993). On the resumption of commercial whaling: the case of the minke whale in the northeast Atlantic. Arctic 46(2): 164-171. Costa-Neto, E.M. and K.L.G. Lima (2000). Contribuicao ao estudo da interacao entre Pescadores  e  caranguejos  (Crustacea,  Decapoda,  Brachyura):  consideracoes  etnobiologicas em uma comunidade pesqueira do estado da Bahia, Brasil. Actualidades Biologicas 22(73): 195-202. Costanza, R., J. Cumberland, H. Daly, R. Goodland and R. Nogaard (1997). An introduction to ecological economics. St. Lucie Press, Boca Raton, Florida: 275 p. Delgado, C.L., N . Wada, M.W. Rosegrant, S. Meijer and M . Ahmed (2003). Fish to 2020: supply and demand in changing global markets. International Food Policy Research Institute/WorldFish Center, Washington, D.C./Penang: 226 p.  Evangelista, J.E.V., J.A. Vasconcelos and G.M. Oliveira (1998). Evolucao da pesca de atuns no nordeste do Brasil. Boletim Tecnico Cientifico do CEPENE 6(1): 77-108. Field, B.C. and N.D. Olewiler (2002). Environmental economics. McGraw-Hill Ryerson, Toronto: 498 p. Fletcher, R. (1970). A new approach to variable metric algorithms. The Computer Journal 13(3): 317-322. Glaser, M . and K. Diele (2004). Asymmetric outcomes: assessing central aspects of the biological, economic and social sustainability of a mangrove crab fishery, Ucides cordatus (Ocypodidae), in North Brazil. Ecological Economics 49: 361-373. Hall, M.A., D. Alverson and K.I. Metuzals (2000). By-catch: problems and solutions. Marine Pollution Bulletin 41(1-6): 204-219. Healey, M.C. (1984). Multiattribute analysis and the concept of optimum yield. Canadian Journal of Fisheries and Aquatic Science 41: 1393-1406. Holt, S.J. (1978). Some implications of maximum sustainable net yield as a management objective for whaling. Report of the International Whaling Commission 28: 191-193. IBAMA (1994). Lagosta, caranguejo-uca e camarao do nordeste. Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renovaveis, Brasilia: 190 p. ICCAT (2004a). 2003 ICCAT albacore stock assessment session. Collective Volume of Scientific Papers ICCAT 56(4): 1223-1311. ICCAT (2004b). 2003 ICCAT Atlantic yellowfin tuna stock assessment session. Collective Volume of Scientific Papers ICCAT 56(2): 443-527. ICCAT (2005). Report of the 2004 ICCAT bigeye tuna stock assessment session. Collective Volume of Scientific Papers ICCAT 57 (2): 3-38. Ivo, C.T.C. (1996). Biologia, pesca e dinamica populacional das lagostas Panulirus argus Latreille e Panulirus laevicauda Latreille (Crustacea: Palinuridae), capturadas ao longo da plataforma continental do Brasil, entre os estados do Amapa e do Espirito Santo. Departamento de Hidrobiologia, Universidade Federal de Sao Carlos, Sao Carlos. PhD Thesis: 277 p.  Ivo, C.T.C. and J.A. Pereira (1996). Sinopse das principals observacoes sobre as lagostas Panulirus argus (Latreille) e Panulirus laevicauda (Latreille), capturadas em aguas costeiras do Brasil, entre os estados do Amapa e do Espirito Santo. Boletim Tecnico Cientifico do CEPENE 4(1): 7-94. Ivo, C.T.C. and J. Ribeiro Neto (1996). Estudo comparativo sobre a pesca de lagostas com covo e rede de espera no estado do Ceara. Boletim Tecnico Cientifico do CEPENE 4(1): 95-134. Ivo, C.T.C. and E.M.S. Vasconcellos (2000). Potencial reprodutivo do caranguejo-uca, Ucides cordatus cordatus (Linnaeus, 1763), capturado na regiao estuarina do rio Curimatau (Canguaretama, Rio Grande do Norte, Brasil). Boletim Tecnico Cientifico do CEPENE 8(1): 45-53. Kaschner, K. and D. Pauly (2004). Competition between marine mammals andfisheries.Food for thought. The Human Society of the United States, Washington, DC: 28 p. Leao, Z.M.A.N. and J.M.L. Dominguez (2000). Tropical coast of Brazil. Marine Pollution Bulletin 41(1-6): 112-122. Lessa, R. and P. Duarte-Neto (2004). Age and growth of yellowfin-tuna {Thunnus albacares) in the western equatorial Atlantic, using dorsal fin spines. Fisheries Research 69: 157170. Lessa, R.P., M.F. Nobrega and J.L. Bezerra Junior (2004). Dinamica de populacoes e avaliacao de estoques dos recursos pesqueiros da regiao nordeste. Volume II. DEVIAR, Departamento de Pesca - Universidade Federal Rural de Pernambuco, Recife-Brazil: 245 PLink, J.S. (2002a). Ecological considerations in fisheries management: when does it matter? Fisheries 27(4): 10-17. Link, J.S. (2002b). What does ecosystem-based management mean? Fisheries 27(4): 18-21. Lins-Oliveira, J.E., J.A. Vasconcelos, K.M.F. Freire, K.M.F. Cunha, V.M.C. Henriques and F.A.M. Freire (1997). Aspectos legais da captura de lagostas no nordeste do Brasil. VII COLACMAR. Congresso Latino-americano sobre Ciencias do Mar. Volume II. 22 a 26 September, 1997, Santos, Brazil.  Marques, M., M.F. Costa, M.I.O. Mayorga and P.R.C. Pinheiro (2004). Water environments: anthropogenic pressures and ecosystem changes in the Atlantic drainage basins of Brazil. Ambio 33(1-2): 68-77. Mattos, S.M.G. and F.H.V. Hazin (1997). Analise da viabilidade economica da pesca de tubaraes no litoral do estado de Pernambuco. Boletim Tecnico Cientifico do CEPENE 5(1): 89-114. Myers, R.A. and B. Worm (2003). Rapid worldwide depletion of predatory fish communities. Nature 423: 280-283. Negreiros Aragao, J.A. (2005). Liberacao da pesca da lagosta com rede cacoeira - uma decisao preocupante. Digest 119. Negreiros-Aragao, J.A. and K.C.A. Silva (2000). Northern Brazil shrimp fisheries. FAO Fisheries Reports 628: 37-44. O'Malley, J.M. and S.G. Pooley (2003). Economic and operational characteristics of the Hawaii-based longline fleet in 2000. Joint Institute for Marine and Atmospheric Research, Honolulu: 31 p. Ocean Conservancy (2004). First international ban on shark finning adopted, www. oceanconservancv.org. Accessed in May 18 , 2005. th  OECD (1997). Towards sustainable fisheries. Economics aspects of the management of living marine resources. Organization for Economic Co-operation and Development, Paris: 268 POrlande, T., J. Laarman and J. Mortimer (1996). Palmito sustainability and economics in Brazil's Atlantic coastal forest. Forest Ecology and Management 80(1-3): 257-265. Pauly, D., V. Christensen and C. Walters (2000). Ecopath, Ecosim, and Ecospace as tools for evaluating ecosystem impact of fisheries. ICES Journal of Marine Science 57: 697-706. Pedrosa, B.M.J, and R.C.A. Carvalho (2000). Analise de viabilidade economica da pesca de atuns e afins no nordeste brasileiro. Anais do XXXVIII Congresso Brasileira de Economia e Sociologia Rural, Rio de Janeiro, 2000. Universidade Federal do Ceara, Fortaleza, Brazil: 1-15 p.  Procuradoria Regional do Trabalho - RN (2005). Acidentes do trabalho. http://www.prt21.gov. br/inform2/, Accessed in May 18 , 2005. th  Rabay, G.C. (1985). Baleias. Fatos e mitos. Joao Pessoa, Brazil: 34 p. Schaefer, M.B. (1956). The scientific basis for a conservation program. In: Papers presented at the International Technical Conference on the Conservation of the Living Resources of the Sea, United Nations Publication 1956. n.B.l: 15-55. Scharer, R. (2001). A small start. An experiment in Prainha do Canto Verde tests the MSC's principles and criteria for community-based certification of a fishery. SAMUDRA Report 29(August): 26-29. Singarajah, K.V. (1985). A review of Brazilian whaling: aspects of biology, exploitation and utilization, Cochin, India. Statistics Norway (2005). Fishery Statistics 2002-2003. Statistics Norway, Oslo, Kongsvinger: 106 p. SUDEPE (1979). Anuario do registro geral da pesca - 1978. Ministerio da Agriculture, Brasilia: 407 p. SUDEPE (1980). Estatistica da pesca. Producao - 1978. Ministerio da Agriculture, Brasilia: 84 PSumaila, U.R. and C. Walters (2005). Intergenerational discounting: a new intuitive approach. Ecological Economics 52: 135-142. Trinidad, A.C., R.S. Pomeroy, P.V. Corpuz and M . Agiiero (1993). Bioeconomics of the Philippine small pelagics fisheries. ICLARM Technical Reports 38: 1-73. Van Vliet, O.P.R., A.P.C. Faaij and C. Dieperink (2003). Forestry projects under the clean development mechanism? Modelling of the uncertainties in carbon mitigation and related costs of plantation forestry projects. Climate change 61: 123-156. Vasconcelos, J.A. and J.E. Lins-Oliveira (1996). Estudo comparative sobre a pesca de lagostas com rede-de-espera e mergulho no estado do Rio Grande do Norte. Boletim Tecnico Cientifico do CEPENE 4(1): 135-172.  Walters, C. and J.F. Kitchell (2001). Cultivation/depensation effects on juvenile survival and recruitment: implications for the theory of fishing. Canadian Journal of Fisheries and Aquatic Science 58: 39-50. Walters, C , D. Pauly and V. Christensen (1999). Ecospace: prediction of mesoscale spatial patterns in trophic relationships of exploited ecosystems, with emphasis on the impacts of marine protected areas. Ecosystems 2: 539-554. Yodzis, P. (2001). Must top predators be culled for the sake of fisheries? Trends in Ecology & Evolution 16(2): 78-84. Zetina-Rejon, M.J., F. Arreguin-Sanchez and E.A. Chavez (2004). Exploration of harvesting strategies for the management of a Mexican coastal lagoon fishery. Ecological Modelling 172(2-4): 361-372.  CHAPTER 6. Concluding remarks  The successive collapses of fisheries worldwide have led to a re-assessment of past and current practices of fisheries management and to a search for new directions. Collapses have been observed in areas where very detailed information is available, as well as in areas with limited data. These collapses have important ecological, economic, social, and cultural implications. Normally they imply a displacement of fishing effort from traditionally exploited species to previously unexploited resources and/or to new fishing grounds. However, with a continuous history of successive depletions and with few unfished places to go, managers are facing the hard task of deciding whether to continue with current exploitation levels, to preserve remaining stocks or, in some cases, to attempt to recover some of these stocks and ecosystem functions lost to intensive exploitation. Some developed countries have a social system in place that allows for provision of some benefits (e.g., unemployment insurance) to those depending on fisheries in case of resource collapse. Conversely, many (if not all) developing countries lack such a system and a more precautionary approach should be in place.  Brazil faced a severe decline of sardine stocks in the southeastern region in the early 1990s, and has also seen some of its main stocks in the northeastern region decline. This thesis aims to contribute to the management of marine fisheries resources off northeastern Brazil, a region that has been much less studied, and which is characterized by a large number of people depending on this activity to make a living through subsistence and artisanal fisheries: 47% of all fishers officially recorded in Brazil in 2004 (According to the Special Secretary of  Aquaculture and Fisheries: www.planalto.gov.br/seap/). The overall goal of this study was to evaluate the fishing impacts on the East Brazil Large Marine Ecosystem. In order to reach this goal, the following specific objectives were pursued: (a) identification of the richness of common names of Brazilian fishes and its effect on fishery statistics; (b) analysis of catches originating from Brazilian marine fisheries and assessment of their use as an indicator of ecosystem health; (c) description of the biomass and energy fluxes for the functional groups occurring in the East Brazil Large Marine Ecosystem, encompassing northeastern Brazil; and (d) assessment of the impact of current fishing policies and some alternatives.  Chapter 1 presented an overview of the state of world fisheries, of major fisheries in northeastern Brazil, and of the evolution of the Brazilian fisheries management system through time. This overview was essential to set the stage for all analyses presented in the following chapters. This chapter also showed how unstable the institutional framework has been since the onset of organized fishing in Brazil, leading to a poor system of collection of fisheries statistics and related undesirable consequences. A brief description of the ecosystem off northeastern Brazil was given, i.e., of a tropical environment with low productivity, but which is (unrealistically) expected to provide high catch levels.  Chapter 2 documented the high richness of common names of Brazilian fishes and was essential to the analyses presented in the following chapters. Each species present an average of six common names, but this ranged up to 37 names. Conversely, some common names may be used for up to 31 different species, creating a very intricate naming system. Not surprisingly, this system affects the quality of fishery statistics, as data are recorded by common names that may be associated with unrelated species. One of the analyses presented  in this chapter indicated that higher diversity of names is associated with commercial species. There is also a difference between names used by the commercial and the recreational fishing sectors. With increasing interest in recreational fisheries in Brazil, and specifically in northeastern Brazil, managers should be able to combine catch data and related information from both sectors in order to make better decisions. A standardization of common names is proposed here, based on previous experience in North America. This standardization is not intended to eliminate cultural diversity, reflected in a wide variety of names, but to allow improvements in the collection system for catch statistics and to allow for better communication amongst members of the fishing sector.  Chapter 3 presented how fisheries statistics spread throughout documents were compiled through a database to be made widely available. This database was presented on a per State basis, which allows for addressing area-specific questions on the development of fisheries. More specifically, the compiled database allowed for the use of time series of catch statistics in the EwE model constructed for northeastern Brazil and the exploration of future fishing policy options. This was previously not possible, as the only comprehensive electronic database available to date was FAO's, which presents catch data at a national level. The results presented here indicated that fishery statistics presented in national databases are failing to capture the landings of tuna and tuna-like fishes originating with industrial fisheries. On the other hand, FAO statistics are using ICCAT catches to correct the database officially provided by Brazil. However, this approach will result in an underestimation of tuna and tuna-like fishes due to the omission of catches originating from artisanal fisheries. Additionally, FAO has also misallocated catches attributed to some species and overaggregated catches for others. Several  additional sources of underestimation of total extractions from Brazilian waters were indicated, and will be later incorporated into the database presented here.  The preparation of this chapter faced the challenge of dealing with a high diversity of common names of fishes, as all national documents used in this compilation report landing data via common names. The task of combining all the information into a single database required a detailed analysis of common names, which was previously addressed. This chapter indicated that the 'fishing down the food web' trend observed in many other parts of the world is also occurring in Brazil. However, the trend is more visible when the analysis is performed at the level of States. This indicates that even low quality fisheries statistics can be useful to detect fishing impacts on the ecosystem, such as the gradual elimination of predators of higher trophic levels.  Chapter 4 described the trophic interactions of the marine ecosystem off northeastern Brazil and some of its main features. Forty-one groups were used to describe this system, including marine mammals, sea turtles, seabirds, fishes, cephalopods, crustaceans, corals, other invertebrates, zoo- and phytoplankton, and a complex of other primary producers (macroalgae, mangroves, and seagrasses), which created a set of subsystems with a total biomass of 222 tonneskm" (excluding detritus). Catches were low, a result of several sources of 2  underestimation discussed in the previous chapter, but mainly due to the low productivity in this region. System statistics indicated that detritus is an important component of this system. The degree of omnivory was low, as in other tropical shelves along the western Atlantic.  Chapter 5 indicated that in order to move towards ecosystem-based fisheries management and to be able to deal with trade-offs amongst fishery sectors in northeastern Brazil, much basic information is still missing. Preliminary results indicated that current fishing practices are unsustainable for lobsters and swordfish stocks, which are likely to collapse in a few years. Biomass of other groups, such as other large pelagics and sharks, will decline even further. Policies emphasizing ecosystem health would lead to a more diverse fleet configuration, but may require that longline and lobster fisheries are practically shut down. Economic, social, and compromise (equal weight for economic, social, and ecological components) scenarios indicated that fishing effort for manual collection and industrial demersal fisheries could be increased. A l l scenarios would lead to an increase in biomass of swordfish, tunas, and spiny lobsters. However, these results appear to be masked by the dynamics of sharks and tunas/swordfish. The biomass of spiny lobsters would reach 1978 levels if there were a massive decrease in fishing effort, down to a value equivalent to fvisY- However, attention was called for the heterogeneity of lobster fisheries due to the existence of three sectors (traps, gillnets, and diving), each one with its own dynamics. Effort should be made towards collection of data for each of these sectors.  The general conclusion of the thesis is that fishing has negatively impacted the marine ecosystem off northeastern Brazil as evidenced by the 'fishing down the food web' phenomenon, with decreasing abundance of predators of higher trophic levels. This phenomenon is more visible, however, when the available data are analysed at the State level. Some stocks such as lobsters and swordfish had their biomass decreased to very low values in relation to the late 1970s, and will crash in a few years if rebuilding policies are not put in place.  A better analysis of the impact of fisheries on the local ecosystem is difficult due to the poor system of collection of fishery statistics that fails to keep continuous records, probably associated with the high instability of Brazilian management institutions. Besides, the system, which fails to record even basic information such as catches per fleet type, has not done much towards estimating by-catch discards, and has recorded catches using common names whose linkage to the scientific names are poorly defined. Biological, economic, and social information available for this area are still far from allowing for an ecosystem-based approach for fisheries management, considering trade-offs amongst multi-objectives. The attempt to quantify the impact of fishing in this ecosystem in the absence of basic data leads one to argue about the factual basis for the current program of the Brazilian government towards increasing and modernizing its fleet. If there are data supporting such decisions, its origin is not known. This makes for a lack of transparency in decision-making. Finally, the current situation of two institutions responsible for managing Brazilian fisheries (SEAP and IBAMA) is expected to make the state of fish resources in Brazilian waters even worse.  Study limitations and general recommendations: The analyses presented in this thesis were based on catch statistics that are inherently weak, which may have affected the results obtained. The use of categories such as 'outros peixes', 'mistura' and 'caico', all representing 'other' or 'miscellaneous' fishes, should be avoided in national fishery statistics or at least reduced to the minimum level possible. These categories may be including species that are major prey for some of the exploited fisheries resources and thus the analysis of the impact of fisheries on the ecosystem would be improved. Additionally, institutions reporting catch statistics would benefit from a standardized set of common names 216  of exploited species, to be selected by all stakeholders involved in fishery-related activities. As this standardization is expected to be obtained through a long, elaborate process, these institutions should provide, for now, at least a list of species associated to each name per State and not for the whole of Brazil, as is currently the case. The impact of this richness of names was quantitatively assessed by equally splitting catches amongst all species of commercial interest linked to a given name. This analysis should be tested in the field, in at least some States. The database of common names should be continuously extended in order to improve the coverage of names on a per State basis and to include names commonly used before 1962. This extension is essential to deal with catch statistics from earlier periods (1950-1961).  The electronic database of landing data produced here will be incorporated into the database of the Sea Around Us Project (www.seaaroundus.org), which has been working on mapping global catches to assess the impact of fisheries on a larger scale. It also will be made available to the general public in Brazil through IBAMA, SEAP or a Brazilian Fisheries Society (still to be created). The database is expected to be extended backwards to 1950, as foreign fleets started to operate in this area by the mid 1950s. This will allow for better assessment of the impact of these fleets on local ecosystems. Quantification of discards and other sources of underestimation of catches would contribute to make this database more realistic. Particularly, data on finning activities, although recognizably difficult to obtain due to the illegal nature of this activity, are particularly crucial to assess the impact of current policies devoted to expanding tuna and swordfish fisheries.  After the catch database is extended to the 1950s, the spatial mapping of the catches by State would allow for a better understanding of the expansion of fishing grounds through time. One  limitation of this analysis would be the fact that fishing boats of some States extend their operational area after a local depletion, but may still sell their catch in the port where they were originally registered. The only way to overcome this problem would be through explicit reporting of fishing grounds, which is currently done only by longliners.  Collection and analysis of catch data is very important, but not sufficient to draw inferences on the performance of fisheries and the health of ecosystems. The current system only records the number of boats legally registered in each State, but does not present information on fishing days, number of fishers, number of fishing traps, or number of hooks for most fleets. With the exception of data collected by study groups associated with the main resources in the area, there is no recognition that effort data should be provided together with catch data for better assessment of fisheries. In some cases, these study groups present effort by some specific gears used to catch a given resource, but fail to address the problem of other gears that may also impact the resource in question. Alternatively, the local government could move towards obtaining estimates of fishing mortality through tagging programs.  The trophic mass-balance model constructed here using Ecopath with Ecosim is very preliminary and has inherited several of its flaws from the original data sources. The absence of biomass surveys led to the use of data from other areas or to their estimation by the model. Mortality rates were, in many cases, also inferred from other systems or estimated based on length-frequency distributions. Local studies of diet composition mainly described diets in terms offrequencyof occurrence or numericalfrequencyand data from other regions in Brazil or for the same species in other tropical areas were used as indicators of the impact of each group. It is recommended that local diet composition data be generated, at least for the main  resource species, including Lutjanus purpureus, Panulirus argus, and P. laevicauda, as well as key species of crabs, shrimps, and molluscs. Data on predation on Lutjanus purpureus are also required, as no information was found on potential predators. This, together with an incomplete series of CPUE data, precluded explorations of policies specifically for snapper fisheries.  More functional groups (particularly tunas and swordfish) should be split into juveniles and adults, as was done for dolphinfish in the current version of the Ecopath with Ecosim model. This will allow for a better understanding of the impact of the development of longline fisheries. Recreational catch data were not incorporated in the model due to the lack of data on a per species basis. Considering the possible effect of recreational fisheries on juveniles of exploited fishes and/or on prey items of those fishes, the use of split groups for some of the other fish groups would allow for testing the effect of increasing effort by anglers.  The improvement of the basic model through the inclusion of additional local data or gathering the information available in the grey literature, theses, or reports not easily available is paramount to portrait more realistically local trophic interactions and the impact of fisheries in this region. A new version of the model will then be submitted to local experts for an in-depth evaluation. The improved version should be the result of an interdisciplinary team involving scientists with expertise on the different functional groups included in the model, as well as fisheries economists and social scientists.  Fishing policy exploration was limited by the manner in which catches were split amongst the fleets, by the absence of price data specific to the industrial and artisanal fleets, by the lack of  data on costs for several fleets (or lack of consistency in the available data), and by the crudeness of the estimation of number of jobs generated by each fleet. This attempt to assemble all local information into a single framework to analyze the ecological structure of this system and fishing impacts showed several information gaps. It also demonstrated that if northeastern Brazil is going to move towards ecosystem-based fisheries management strategy, an extra effort should be made to collect the essential information required for improved trophic models to be used as the platform to explore future directions for local fisheries. Even if all of these information gaps are filled, the management of Brazilian fisheries would still be negatively affected by the unstable institutional structure. This is particularly worrisome if we consider the split of responsibility between two institutions working in a non-collaborative arrangement.  Appendix 1: Glossary of terms used throughout this thesis.  1. Artisanal fisheries: includes manual collection, paddling/sailing boats, and usually motorboats < 12-15 m and < 20 RGT (Registered Gross Tonnage), although limits may differ amongst States; 2. Bathydemersal - near the bottom below 200 m; 3. Bathypelagic - from 200 m to the bottom, thus including the mesopelagic, bathypelagic, and abyssopelagic zones; 4. Benthopelagic - in zones about 100 m off the bottom at all depths below the edge of the continental shelf; 5. Commercial fisheries: include both artisanal and industrial fisheries, but excludes subsistence and recreational fisheries; 6. Demersal - on or near the bottom and feeding on benthic organisms; 7. Industrial fisheries: originated from boats usually > 12-15 m and > 20 RGT, although limits may differ amongst States; 8. Landing data: refers to live weight in tonnes of the taxa caught (molluscs, crustaceans, fishes, turtles, mammals), without discards or other unreported catches; 9. Pelagic - at the sea surface or mid water, from 0 to 200 m depth; . 10. Reef-associated - on or near coral reefs.  Functional group  Species  Sources  Comments  1. West Indian manatee  Trichechus manatus  (Albuquerque and Marcovaldi, 1982) OccursfromAmapa to Sergipe States (Paludo and Langguth, 2002) and disappeared from the south of its distribution range (Espirito Santo and Bahia States). Currently T. manatus is considered endangered.  2. Baleen whales  minke (Balaenoptera acutorostrata), sei (Singarajah, (B. 1997) borealis), blue (B. musculus), Bryde's (B. edeni), fin (B. physalus), humpback (Megaptera novaeangliae), southern right (Eubalaena australis), and southern minke (B. bonaerensis).  With the exception of the last two species, all were commercially exploited until early 1980s.  3. Toothed cetaceans  Globicephala macrorhynchus, Hyperoodon (Singarajah, 1997) planifrons, Kogia breviceps, K. simus, Orcinus orca, Peponocephala electra, Physeter macrocephalus, Pseudorca crassidens, Sotaliafluviatilis,Stenella attenuata, S. clymene, S. coeruleoalba, S. frontalis, S. longirostris, Steno bredanensis, Tursiops truncatus, and Ziphius cavirostris.  Seventeen out of the 30 species of toothed cetaceans reported in Brazil are found in the northeastern region; only the sperm whale (Physeter macrocephalus) was commercially exploited.  4. Seabirds  Aramides mangle, Arenaria interpres, Vooren and Brusque (1999) Buteogallus aequinoctialis, Butorides striates, Charadrius collaris, Fregata magnificens, Nyctanassa violacea, Phalacrocorax olivaceus, Puffinus gravis, and Rallus longirostris.  Ninety-three out of the 148 seabird species recorded for Brazil are found in northeastern region; the most important in terms of distribution range and common occurrence are listed here.  5. Sea turtles  Chelonia mydas, Caretta caretta, (Marcovaldi and Marcovaldi, 1999) Dermochelys coriacea, Eretmochelys imbricata, and Lepidochelys olivacea.  All these species were commercially exploited until 1986.  Functional group  Species  Sources  Comments Only includes large tunas.  6. Tunas  www.fishbase.org Thunnus alalunga, T. albacares, and T. obesus.  7. Other large pelagics  www.fishbase.org Acanthocybium solandri, Auxis rochei, A. thazard, Euthynnus alletteratus, Istiophorus albicans, Katsuwonus pelamis, Makaira nigricans, Mola mola, Ranzania laevis, Sarda sarda, Scomber colias, S. japonicus, Scomberomorus cavala, S. regalis, S. serra, Sphyraena barracuda, S. guachancho, Tetrapturus albidus, and T. pfluegeri.  8. Dolphinfish  Coryphaena hippurus  www. fishbase.org  9. Dolphinfish juveniles  Coryphaena hippurus  www.fishbase.org  10. Swordfish  Xiphias gladius  www.fishbase.org  11. Sharks  www.fishbase.org Alopias vulpinus, Carcharhinus acronotus, C. falciformis, C. galapagensis, C. leucas, C. limbatus, C. longimanus, C. obscurus, C. perezi, C. plumbeus, C. porosus, C. signatus, Carcharias taurus, Euprotomicrus bispinatus, Galeocerdo cuvier, Isogomphodon oxyrhynchus, Isurus oxyrinchus, Mustelus canis, M. higmani, Negaprion brevirostris, Prionace glauca, Rhizoprionodon lalandii, R. porosus, Scyliorhinus haeckelii, Sphyrna lewini, S. media, S. mokarran, S. tiburo, S. tudes, and S. zygaena.  Incomplete list.  12. Rays  Aetobatus narinari, Atlantoraja castelnaui,  Incomplete list.  www.fishbase.org  Functional group  Species  Sources  Comments  Dasyatis americana, D. centroura, D. guttata, D. marianae, D. say, Gymnura altavela, G. micrura, Manta birostris, Narcine brasiliensis, Pteroplatytrygon violacea, Rhinobatos percellens, Rhinoptera bonasus, Torpedo nobiliana, and Zapteryx brevirostris. 13. Small pelagics  www.fishbase.org Anchoa cubana, A.filifera,A. hepsetus, A. januaria, A. lyolepis, A. pectoralis, A. spinifer, A. tricolor, Anchoviella brevirostris, A. cayennensis, A. lepidentostole, Cetengraulis edentulus, Cheilopogon cyanopterus, Chloroscombrus chrysurus, Exocoetus volitans, Hirundichthys qffinis, H. speculiger, Lycengraulis grossidens, and Sardinella aurita.  14. Needlefishes  www.fishbase.org Hemiramphus balao, H. brasiliensis, Hyporhamphus unifasciatus, H. robertii, and Oxyporhamphus micropterus similis.  15. Southern red snapper  Lutjanus purpureus  (Fonteles-Filho and Ferreira, 1987)  16. Large carnivorous reef Epinephelusflavolimbatus,E. guttatus,www.fishbase.org E. fishes itajara, E. niveatus, E. striatus, Gymnoihorax moringa, Lutjanus buccanella, L. griseus, L. jocu, L. vivanus, Mycteroperca bonaci, and Rachycentrum canadum.  Incomplete list.  Functional group  Species  Sources  Aulostomus maculatus, Bodianus www.fishbase.org rufus, Dactylopterus volitans, Fistularia petimba, F. tabacaria, Halichoeres bivittatus, Holocentrus adscensionis, H. rufus, Hippocampus erectus, Lutjanus apodus, Myripristis jacobus, and Selar crumenophthalmus. w wA. w. fishbase. org 18. Herbivorous reef fishes Acanthurus bahianus, A. chirurgus, coeruleus, Cantherhines pullus, Halichoeres bivittatus, H. cyanocephalus, H. maculipinna, H. poeyi, Kiphosus incisor, Scarus guacamaia, S. trispinosus, S. zelindae, Sparisoma amplum, S. atomarium, S. axillare, S. jrondosum, and S. radians.  17. Small carnivorous reef fishes  quadricornis, Albula www.fishbase.org 19. Omnivorous reef fishes Acanthostracion vulpes, Archosargus rhomboidalis, Batistes vetula, Cantherhines macrocerus, C. pullus, Chilomycterus schoepfii, Diodon hystrix, Epinephelus morio, Eucinostomus argenteus, E. gula, Haemulon plumieri, Lutjanus analis, L. synagris, Monacanthus ciliatus, and Ocyurus chrysurus. 20. Demersal fishes  Amphichthys rubigenis, Antigonia capros, www.fishbase.org Bairdiella ronchus, Bothus ocellatus, B. robinsi, Centropomus parallelus, Conodon nobilis, Corniger spinosus, Cynoscion acoupa, C. jamaicensis, C. leiarchus, C. virescens, Diapterus auratus, D. rhombeus, Diplectrum radiali, Eucinostomus havana, E. jonesii, E. melanopterus, Eugerres  Comments Incomplete list.  Incomplete list.  Incomplete list.  At least 186 species are included in this group. Some of them are listed here.  Functional group  Species  Sources  Comments  brasilianus, E. plumieri, Isopisthus parvipinnis, Larimus brevipes, Macrodon ancylodon, Menticirrhus littoralis, Micropogonias fiirnieri, Ophioscion punctatissimus, Orthopristis rubber, Paralonchurus brasiliensis, Prionotus punctatus, P. roseus, Stellifer rastrifer, and Umbrina coroides 21. Mullets  Mugil curema, M. curvidens, M. gyrans, www.M. fishbase.org hospes, M. incilis, M. liza, M. platanus, and M. trichodon.  22. Spotted goatfish  Pseudupeneus maculatus  23. Benthopelagic fishes  Acanthistius brasilianus, Bryx dunckeri, www.fishbase.org Caelorinchus marinii, Caranx lugubris, Centropomus ensiferus, C. pectinatus, Etmopterus gracilispinis, Lobotes surinamensis, Neobythites gilli, N. ocellatus, Nezumia aequalis, Oligoplites palometa, O. saliens, Peprilus alepidotus, P. paru, Promethichthys prometheus, Ribeiroclinus eigenmanni, Rivulus marmoratus, Ruvettus pretiosus, Scombrolabrax heterolepis, Selene setapinnis, Seriola fasciata, S. zonata, Serranus auriga, Stromateus brasiliensis, Thyrsitops lepidopoides, Trachinotus carolinus, T. marginatus, Trichiurus lepturus, and Zenopsis conchifera.  47 species are included in this group. Some are listed here.  24. Bathypelagic fishes  Some of these species are: Alepisaurus  A total of 113 species are recorded for  (Campos and Oliveira, 2001)  www.fishbase.org  Functional group  Species  Sources  Comments  ferox, Allocyttus verrucosus, Antimora rostrata, Ceratoscopelus warmingii, Chauliodus sloani, Diaphus fragilis, D. metopoclampus, D. perspicillatus, D. taaningi, Gempylus serpens, Howella brodiei, Lampanyctus nobilis, Lampris guttatus, Lepidocybium flavobrunneum, Lobianchia dofleini, Malacosteus niger, Melanonus zugmayeri, Melanostomias bartonbeani, Myctophum nitidulum, Nessorhamphus ingolfianus, Notolychnus valdiviae, Photonectes braueri, Sternoptyx diaphana, S. pseudobscura, Stomias affinis, and Yarrella blackfordi.  this area. Some are listed here.  25. Spiny lobsters  Panulirus argus, P. laevicauda, and P. (Lins-Oliveira ef al, 1993) echinatus.  All of these lobster species are commercially important. P. argus is associated with the highest catches.  26. Other lobsters  Parribacus antarticus, Scyllarides brasiliensis, and Nephropidae.  27. Shrimps  Farfantepenaeus brasiliensis, F. subtilis, (KAMA, 1994) Litopenaeus schmitti, and Xiphopenaeus kroyeri.  All are commercially exploited.  28. Crabs  (Amarale/a/., 2000) Aratus pisonii, Arenaeus cribarius, Callinectes bocourti, C. danae, C.(Castro, 2000) exasperatus, C. larvatus, C. ornatus, C. sapidus, Cardisoma guanhumi, Goniopsis cruentata, Ocypode quadrata, Uca leptodactyla, U. maracoani, U. rapax, U. yhayeri, and Ucides cordatus.  At least 170 species of crabs are included in this group. Some are listed here.  Functional group  Species  Sources  Comments  29. Squids  Bathyteuthis abyssicola, Histioteuthis www.cephbase.org bonnellii, Loligo plei, Lolliguncula brevis, Ommastrephes bartramii, Onychoteuthis banksii, Ornithoteuthis antillarum, Sthenoteuthis pteropus, and Thysanoteuthis rhombus.  30. Octopus  Benthoctopus januarii, Eledone massyae, Octopus defilippi, O.filosus,O. macropus, O. vulgaris, Ocythoe tuberculata, Pteroctopus tetracirrhus, and Scaeurgus unicirrhus.  31. Other molluscs  Anomalocardia brasiliana, Crassostrea (Amaral etal, 2000) rhizophorae, Lucina pectinata, Mytella (Castro, 2000) charruana, M. falcata, Tagelus plebeius, and Tivela mactroides.  According to these authors, there are 155 species for sand beaches and reef areas around Abrolhos, respectively, but no comprehensive list of molluscs was found for northeastern Brazil; this group is here mainly represented by species of commercial interest.  32. Other crustaceans  Albunea paretii, Blepharipoda doelloi, (Amaral etal, 2000) Calianassa grandimana, C. guassutinga, C. jamaicense, Callichirus major, Cloridopsis dubia, Dulichiella spinosa, Emerita portoricensis, Ericthonius brasiliensis, Excirolana braziliensis, Gammaropsis atlantica, Hippa testudinaria, Lepidopa distincta, L. richmondi, L. venusta, Leucothoe dissimilis, L. spinicarpa, Maera hirondelei, M. quadrimana, Orchestia gammarella, O. montagui, and O. platensis.  This group encompasses all crustacean species not cited above, which belong to the following groups: Benthic Copepoda, Gammaridae, Isopoda, Ostracoda, Stomatopoda, Tanaidacea and Thalassinidea. Some of the species are listed here.  www.cephbase.org  Functional group  Species  Sources  Comments  33. Other invertebrates  Astropecten riensis, Astrophyton (Amaral era/., 2000) muricatum, Callispongia pergamentacea, (Castro, 2000) Capitella capitata, Chiridota rotifera, Cucumaria pulcherrima, Diamphiodia riisei, Diopatra tridentate, Dysidea janiae, Echinaster echinophorus, Echinometra lucunter, Encope emarginata, Eurithoe complanata, Holothuria grisea, Hyatella cavernosa, Laeonereis acuta, Lumbrineris limicola, Lytechinus variegates, Mellita quinquiosperforata, Micropholis atra, Naineris laevigata, Narcissia trigonaria, Nereis indica, Ophidiaster guildingii, Ophionereis squamulosa, Spongia bresiliana, Stylocidaris affinis, Thyone brasiliensis, Tripneustes ventricosus, and Tropiometra carinata.  This group includes ascidians, chitons, non-annelid worms, polychaets, sea cucumbers, sea stars/brittle stars, sea urchins, and sponges; a comprehensive list of invertebrates was not found for this region, except for the partial lists provided by these authors for reef and sandy substrates; some species are listed here.  34. Zooplankton  (Siphonophorae, (Yoneda, 2000) Coelenterata Scyphomedusa), Hydromedusae, Ctenophora, Turbellaria, Rotifera, Pteropoda, Copepoda (Calanoidea, Cyclopoidea, Harpacticoida, Poecilostomatoida), Cladocera, Mysidaceae, Amphipoda Hyperidea, Euphausiacea, Chaetognatha, Appendicularia, and Thaliacea.  See source for species occurrence.  35. Corals  (Maida and Ferreira, 1997) Agaricia agaricites, A.fragilis,Astrangia (LeaoF.et al, 2003) brasiliensis, A. rathburi, Favia gravida, leptophylla, Madracis decactis, Meandrina braziliensis, Montastrea cavernosa,  Low diversity and high degree of endemism.  Functional group  Species  Sources  Comments  Mussismilia braziliensis, M. harti, M. hispida, Phylangia americana, Porites astreoides, P. branneri, Scolymia wellsi, Siderastrea stellata, and Stephanocoenia michelini (scleractinian), Millepora alcicornis, M. brasiliensis, M. nitida, and Stylaster roseus (hydrocorals), and Neopongodes atlantica (soft corals). 36. Microfauna  Forarninifera, pelagic and benthic bacteria, and ciliates.  (Telles, 1998)  37. Phytoplankton  Chlorophyta, Cryptophyceae, (Yoneda, 2000) Chrysophyceae, Diatomophyceae, Dinophyceae, Dictyochophyceae, Prasinophyceae, Euglenophyceae, Prymnesiophyceae, Raphidophyceae, and Xantophyceae.  See source for species occurrence.  38. Macroalgae  Bryopsis pennata, Bryothamnion (Oliveira era/., 2000) triquetrum, Caulerpa cupressoides, C. mexicana, C. prolifera, C. racemosa, C. sertularioides, Centroceras clavulatum, Chamaedoris peniculum, Cladophora vagabunda, Cladophoropsis membranacea, Codium isthmocladum, Dictyopteris justii, D. plagiogramma, Dictyota menstrualis, Digenea simplex, Enteromorpha lingulata, Gelidiella acerosa, Gelidium americanum, G. coarctatum, G. crinale, Hypnea musciformis, H. spinella, Laurencia papillosa, Lobophora variegate, Neomeris annulata, Pterocladiella bartlettii, P.  A total of 404 species (including Chlorophyta, Phaeophyta, and Rhodophyta) are listed for this region; species with broader distribution area are listed here.  Functional group  Species  Sources  Comments  caerulescens, Stypopodium zonale, Ulva fasciata, U. lactuca, Valonia aegagropila, and Ventricaria ventricosa. 39. Mangroves  Avicennia germinans, A. schaueriana, (Schaeffer-Novelliefa/., 1990) Conocarpus erecta, Laguncularia racemosa, and Rhizophora mangle.  —  40. Seagrasses  Ruppia maritime, Halodule emarginata, (Oliveira H. Filho, 1983) wrightii, Halophila baillonii, and H.(Green and Short, 2003) decipiens.  —  41. Detritus  —  —  —  Group 1. Manatee 2. Baleen whales  Species  B (tkrn ) 2  Trichechus manatus0.00015 Balaenoptera acutorostrata Balaenoptera borealis  Source/Area (Medeiros etal, 2000) Northeastern Brazil  P/B (year ) 1  0.065 0.035  —  Source/Area (Langtimmef al, 1998) Florida (Blanchard a/., 2002) Barents Sea  —  Globicephala macrorhynchus  27.375 5.950  5.060  Balaenoptera physalus Balaenoptera musculus Megaptera novaeangliae  3. Toothed cetaceans  1  5.070  Balaenoptera edeni  Various species  Q/B (year")  0.020  (Blanchard etal, 2002) Barents Sea  3.850 3.430  0.020  (Blanchardetal, 2002) Barents Sea  4.380  —  —  —  —  12.154 12.970  Kogia simus  14.508  Orcinus orca  Stenella attenuata  (Edwards, 2000) Global (Kaschner et al, 2001) Global (Kaschner et al, 2001) Global (Kaschner et al, 2001) Global (Kaschner etal, 2001) Global (Kaschner et al, 2001) Global (Kaschner et al, 2001) Global  (Kaschner etal, 2001) Global 0.02510 Kaschner (pers. com.) LME 16  Kogia breviceps  Physeter macrocephalus Pseudorca crassidens  Source/Area  0.050  (Okey, 2002) Alaska  8.600 6.902  —  —  11.810 0.078  (Kasuya, 1976) Pacific Ocean  (Kaschner etal, 2001) Global (Kaschner etal, 2001) Global (Kaschner etal, 2001) Global (Kaschner et al, 2001) Global (Kaschner etal, 2001) Global (Kaschner et al, 2001) Global  Group  Species Stenella coeruleoalba  B (t-km )  Source/Area  P/B (year )  —  —  0.126  —  0.080  —  —  —  8.600  —  —  —  2  Tursiops truncatus Ziphius cavirostris  —  Various species  0.00520  4. Seabirds  Unidentified species  0.01500  5. Sea turtles  Unidentified species  0.16300  6. Tunas  Thunnus alalunga Thunnus albacares Thunnus obesus  7. Other large pelagics  0.01830 0.00710 0.00960  0.00314 Istiophorus albicans Makaira nigricans 0.00147  (Kaschner e/a/., 2001) Global Kaschner (pers. com.) LME 16 (Opitz, 1996) Caribbean (Telles, 1998) Northeastern Brazil (ICCAT, 2004b) Southern Atlantic (ICCAT, 2004b) Atlantic Ocean (ICCAT, 2003b) Atlantic Ocean (ICCAT, 2001a) Western Atlantic (ICCAT, 2001b) Atlantic Ocean  1  5.400 0.150 0.660 0.969 0.680 0.271 0.139  Source/Area (Kasuya, 1976) Pacific Ocean (Hershe/a/., 1990) Florida, US  (Opitz, 1996) Caribbean (Telles, 1998) Northeastern Brazil (ICCAT, 2004b) Atlantic Ocean (ICCAT, 2004a) Atlantic Ocean (ICCAT, 2005) Southern/Southeastern Brazil (ICCAT, 2001a) Western Atlantic (ICCAT, 2001b) Atlantic Ocean  Q/B (year")  Source/Area  —  —  —  —  1  80.000 22.000 9.600 15.530 17.160 5.000 4.000  Scomberomorus cavala  0.55000  (Arreguin-Sanchez et al, 1993)/Gulf of Mexico  0.640  (Fonteles-Filho, 1988) Northeastern Brazil  8.900  Scomberomorus serra  0.67000  (Arreguin-Sanchez et al., 1993)/GulfofMexico  0.882  (Fonteles-Filho, 1988) Northeastern Brazil  10.200  (ICCAT, 2004b) (ICCAT, 2003c)  0.152  (ICCAT, 2004b) (ICCAT, 2003c)  Tetrapturus albidus0.00168  (Kaschner et al, 2001) Global  — (Opitz, 1996) Caribbean (Telles, 1998) Northeastern Brazil (Vasconcellos, 2002) South Atlantic (Vasconcellos, 2002) South Atlantic (Vasconcellos, 2002) South Atlantic (Cox etal, 2002) Central Pacific (Coxetal., 2002) Central Pacific (Arreguin-Sanchez et al., 1993) Gulf of Mexico (Arreguin-Sanchez et al., 1993) Gulf of Mexico  5.000 (Cox et al., 2002)  Group  Species  9. Dolphinfish juveniles  Tetrapturus pfluegeri Coryphaena hippurus Coryphaena hippurus  10. Swordfish  Xiphias gladius  11. Sharks  Carcharhinus acronotus Carcharhinus falciformis Carcharhinus leucas Carcharhinus limbatus Carcharhinus longimanus  8. Dolphinfish  B (Man ) 2  Source/Area  Atlantic Ocean (Cox et al, 2002) 0.00081 Central Pacific (Mohammed, 2003) 0.00500 Caribbean Ecopath with Ecosim 0.00170 software  —  —  —  P/B (year )  Source/Area  0.440  Atlantic Ocean (Cox etal, 2002) Central Pacific (Lessa et al., 2004) Northeastern Brazil  1  4.362 13.085  3x adult mortality  0.220  (ICCAT, 2003a) Southern Atlantic  0.329  (Beerkircher et al, 2003) Southeastern US  0.460  (Lessa et al, 2004) Northeastern Brazil  —  Carcharhinus perezi  —  —  —  Carcharhinus plumbeus  —  —  0.300  Carcharhinus porosus Carcharhinus signatus Galeocerdo cuvier  0.219  —  0.370  — (Brewster-Geisz and Miller, 2000) United States Based on Lessa and Santana (1998) Northeastern Brazil (Lessaetal, 2004) Northeastern Brazil  Q/B (year ) 1  Source/Area  5.000 (Coxetal, 2002) 8.470  (Mohammed, 2003) Caribbean  24.406 Ecopath with Ecosim software (Vasconcellos, 2002) South Atlantic (Opitz, 1996) 6.410 Caribbean (Opitz, 1996) 4.870 Caribbean (Opitz, 1996) 4.225 Caribbean (Opitz, 1996) 6.090 Caribbean (Opitz, 1996) 4.870 Caribbean 4.000  6.280  (Opitz, 1996) Caribbean  3.100  (Stillwell and Kohler, 1993) Eastern United States  4.270  (Opitz, 1996) Caribbean  Group  Species  B (t-km-)  Source/Area  — — — —  — — — —  Isurus oxyrhynchus Negaprion brevirostris Prionace glauca Rhizoprionodon porosus Sphyrna lewini Sphyrna tiburo 12. Rays 13. Small pelagics  Unidentified species Anchoa spinifer Anchoviella lepidentostole Chloroscombrus chrysurus Hirundichthys affinis Opisthonema oglinum Sardinella aurita  14. Needlefishes  15. Southern red snapper  Hemirhamphus brasiliensis Hyporhamphus unifasciatus  2  — — —  — — —  P/B (year )  Source/Area  — —  — —  -1  0.650  — 0.534 0.500  —  Lutjanus purpureus 0.50000  — (Cortes and Parsons, 1996) Florida (Manickchand-Heileman et al. ,2004)Afenezuela-Trinidad  —  — — — — (Ivo and Hanson, 1982) Northeastern Brazil  10.000 4.500 2.750  6.640 2.410 3.170 13.100 0.904  4.740 6.520 4.900 16.000  Source/Area (Stillwell and Kohler, 1982) Northwest Atlantic (Opitz, 1996) Caribbean (Cox etal, 2002) Pacific (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Manickchand-Heileman et al, 2004)Afenezuela-Trinidad (Isaac and Moura, 1998) Northern Brazil  (Camara et al, 2001) Southeastern Brazil  — 13.030  — — — —  1  11.480  4.135  —  (Lessa etal, 2004) Northeastern Brazil  Q/B (year )  (Lessa etal, 2004) Northeastern Brazil (Lessa et al, 2004) Northeastern Brazil (Mendoza, 1993) Venezuela (Lessa etal, 2004) Northeastern Brazil (Lessa et al, 2004) Northeastern Brazil (Ivo and Sousa, 1988) Northeastern Brazil  14.100  (Garcia and Duarte, 2002) Colombia  13.700  (Vega-Cendejas etal., 1993) Eastern Mexico  — 37.900  —  — (Garcia and Duarte, 2002) Colombia  —  Based on Palomares and Pauly 5.300 (1998) Global  Group 16. Large carnivorous reef fishes  Species  B (tkm' ) 2  Epinephelus flavolimbatus  P/B (year )  Source/Area  0.307  (Manickchand-Heileman and Phillip, 2000) Trinidad and Tobago  1  Epinephelus guttatus Epinephelus itajara  Epinephelus striatus  —  0.850 0.418  —  0.550  Lutjanus buccanella  1.190  Lutjanus grisfius  0.640  Lutjanus jocu  0.134  Lutjanus vivanus  1.260  Mycteroperca . bonaci Aulostomus maculatus Bodianus rufus Halichoeres bivittatus Halichoeres maculipinna  Q/B (year')  4.800  Epinephelus niveatus  17. Small carnivorous reef fishes  Source/Area  (Sadovy and Eklund, 1999) Western Atlantic (Wyanskie/a/., 2000) North & South Carolina, US (Sadovy and Eklund, 1999) Cuba (Tabash and Sierra, 1996) Western Costa Rica  6.400 8.800 3.900 12.600  Source/Area  (Opitz, 1996) Caribbean (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Opitz, 1996) Caribbean (Garcia and Duarte, 2002) Colombia  (Burton, 2001) Eastern Florida (Rezende and Ferreira, 2004) Northeastern Brazil (Tabash and Sierra, 1996) Western Costa Rica  (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) 7.100 Colombia (Opitz, 1996) 2.600 Caribbean 4.500  8.100  (Opitz, 1996) Caribbean  (Opitz, 1996) Caribbean (Opitz, 1996) 8.900 Caribbean (Opitz, 1996) 13.800 Caribbean 5.900  Group  18. Herbivorous reef fishes  Species  B (tkrn )  Source/Area  P/B (year )  Source/Area  Halichoeres poeyi  —  —  —  —  1  Acanthurus bahianus Acanthurus chirurgus Acanthurus coeruleus  Q/B (year") 1  34.500 24.800 24.500 —  13.600  Scarus coeruleus  —  19.300  Scarus guacamaia  —  12.000  Scarus taeniopterus Sparisoma aurofrenatum Sparisoma chrysopterum  —  20.900 29.600 22.900 34.000  —  Sparisoma rubripinne Archosargus rhomboidalis Balistes vetula  20.800  Based on Menezes (1985) Northeastern Brazil  Epinephelus morio Haemulon aurolineatum  j  1  5  0  (Lessa et al, 2004) Northeastern Brazil  (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean  (Opitz, 1996) Caribbean (Garcia and Duarte, 2002) 7.700 Colombia (Opitz, 1996) 5.100 Caribbean (Opitz, 1996) 12.950 Caribbean  25.500 0.763  Source/Area  (Opitz, 1996) 9.400 Caribbean  Scarus coelestinus  Sparisoma radians  19. Omnivorous reef fishes  2  Group  B (Man )  Source/Area  Haemulon plumieri  —  —  Lutjanus analis  —  —  0.763  Lutjanus synagris  —  —  0.270  Species  -2  P/B (year ) 1  Source/Area  — (Lessaefa/.,2004) Northeastern Brazil (Lessae/a/., 2004) Northeastern Brazil  Monacanthus ciliatus Ocyurus chrysurus 20. Demersal fishes  —  —  0.470  10.600 4.500 6.700  2.810  (Silva Junior, 2004) Northern Brazil (Silva Junior, 2004) Northern Brazil (Silva Junior, 2004) Northern Brazil  —  —  —  —  —  1.450  Bagre bagre  —  —  0.895  Bothus ocellatus  —  —  —  —  Cathorops spixii  —  —  —  —  Conodon nobilis  —  —  —  —  2.002 3.640  (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Caribbean (Opitz, 1996) Caribbean (Opitz, 1996) Caribbean  7.900  —  Cynoscion jamaicensis Cynoscion microlepidotus  Source/Area  (Lessaefa/.,2004) Northeastern Brazil  Aspredo aspredo  (Magroe/a/.,2000) Southeastern Brazil (Silva Junior, 2004) Northern Brazil  —  —  —  —  Diapterus rhombeus —  —  —  —  —  —  —  —  Eugerres plumieri  1  11.800  Aspredinichthys jilamentosus  Diapterus auratus  Q/B (year )  (Opitz, 1996) Caribbean (Isaac and Moura, 1998) 12.000 Northern Brazil (Garcia and Duarte, 2002) 6.100 Colombia (Garcia and Duarte, 2002) 7.700 Colombia  10.200  (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) 11.400 Colombia (Garcia and Duarte, 2002) 10.200 Colombia 11.800  Group  B (Hem )  Source/Area  P/B (year )  Isopisthus parvipinnis  —  —  1.070  Larimus brevipes  —  —  —  —  —  1.808  Species  Macrodon ancylodon Menticirrhus americanus Menticirrhus littoralis Micropogonias fiirnieri  21. Mullets  22. Spotted goatfish 23. Benthopelagic fishes  2  1  (Soares, 2003) Southeastern Brazil — (Magro et al., 2000) Southeastern Brazil  Q/B (year ) 1  —  —  —  —  1.100  Orthopristis ruber  —  —  2.460  Paralonchurus brasiliensis  —  —  1.100  Prionotus punctatus —  —  1.244  Stellifer rastrifer  —  —  3.590  Umbrina coroides  —  —  —  Mugil cephalus  —  —  1.054  Mugil curema  —  —  1.000  (Opitz, 1996) Caribbean  0.819  0.50500  — (Soares, 2003) Southeastern Brazil (Vianna and Verani, 2002) Southeastern Brazil (Soares, 2003) Southeastern Brazil (Magro et al., 2000) Southeastern Brazil (Gianninni and Paiva Filho, 1990) / Southeastern Brazil — (Marquez, 1975) Tamiahua Lagoon, Mexico (Abarca-Arenas and ValeroPacheco, 1993) Tamiahua Lagoon, Mexico (Lessaeia/., 2004) Northeastern Brazil  Caranx lugubris  —  —  —  —  Centropomus ensiferus  —  —  0.930  (Zetina-Rejon et al., 2003) Pacific coast of Mexico  Source/Area  (Soares, 2003) Southern Brazil 10.840 (Soares, 2003) Southern Brazil  30.650  — 9.100  —  Pseudupeneus maculatus  Source/Area  6.700 11.100 11.600 8.320 17.000 12.500 7.800  — (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Soares, 2003) Southern Brazil (Opitz, 1996) Caribbean (Soares, 2003) Southern Brazil (Soares et al., 1998) Southern Brazil (Isaac and Moura, 1998) Northern Brazil (Garcia and Duarte, 2002) Colombia  — 22.600  — (Garcia and Duarte, 2002) Colombia  (Opitz, 1996) Caribbean (Opitz, 1996) 9.600 Caribbean  10.800  —  —  Group  Species  B (tkrn- )  Source/Area  P/B (year )  Source/Area  Promethichthys prometheus  —  —  0.490  (Lorenzo and Pajuelo, 1999) Canary Islands  2  1  Syacium micrurum  —  —  Trachinotus carolinus  —  —  —  —  Allocyttus verrucosus Antimora rostrata  —  —  0.300 0.466  —  —  0.228 0.650  Arctozenus risso  Based on REVIZEE, unpublished data (Kitchell etal, 2002) Central Pacific (Mel'nikov, 1981) South Africa (Magnusson, 2001) (Kulka etal, 2003) North Atlantic (Ainsworth et al, 2001) Bay of Biscay  Chauliodus sloani Ceratoscopelus warmingii Unidentified species 25. Spiny lobsters  Panulirus argus  4.700 2.29192 —  7.800 7.700  0.928  Trichiurus lepturus Alepisaurus ferox  1  13.400  Selene setapinnis  24. Bathypelagic fishes  Q/B (year )  9.200 2.900  —  Source/Area  (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Garcia and Duarte, 2002) Colombia (Kitchell etal, 2002) Central Pacific  —  (Ainsworthetal, 2001) Bay of Biscay, France (Ainsworth et al, 2001) 6.297 Bay of Biscay, France 7.128  (Tsarin, 1994) Equatorial Indian Ocean  (Vasconcellos, 2002) South Atlantic 1.230  —  Panulirus laevicauda  1.770  26. Other lobsters  Unidentified species  —  —  27. Shrimps  Farfantepenaeus  ~  ~  0.350 3  2  6  1  (Ivo and Pereira, 1996) Northeastern Brazil (Ivo and Pereira, 1996) Northeastern Brazil Based on the natural mortality for spiny lobsters (Villelaetal, 1997)  (Opitz, 1996) Caribbean (Opitz, 1996) 0.740 Caribbean (Opitz, 1996) 0.740 Caribbean 0.740  Group  Species  B (t-kin ) 2  Source/Area  P/B (year ) 1  brasiliensis  28. Crabs  Source/Area Southeastern Brazil (Ehrhardt, 2001) (Isaac etal, 1992) Northern/Northeastern Brazil (CEPENE, 2000) Northeastern Brazil  Q/B (year")  Source/Area  —  —  —  —  1  Farfantepenaeus subtilis  —  —  1.913  Xiphopenaeus kroyeri  —  —  3.024  Unidentified species  —  —  —  —  26.900  Aratus pisonii  —  —  —  —  13.110  Callinectes danae  —  —  —  —  12.300  Callinectes sapidus  —  —  9.450  Eurytium limosum  —  —  1.650  Goniopsis cruentata  —  —  —  Pachygrapsus gracilis  —  —  4.660 9.990  Uca cumulanta Uca maracoani  —  —  4.941  Uca rapax  —  —  4.530  Uca thayeri  —  —  —  Uca vocator  —  —  6.480  Ucides cordatus  —  —  0.160  (Villasmilera/., 1997) Venezuela (Koch and Wolff, 2002) Northern Brazil  — (Koch and Wolff, 2002) Northern Brazil (Koch and Wolff, 2002) Northern Brazil (Koch and Wolff, 2002) Northern Brazil (Koch and Wolff, 2002) Northern Brazil  — (Koch and Wolff, 2002) Northern Brazil (Koch and Wolff, 2002) Northern Brazil  22.000 22.000 9.590  95.000 32.160 95.000 78.270 95.000 14.000  (Opitz, 1996) Caribbean (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wolffera/.,2000) Northern Brazil (Wolffefa/.,2000) Northern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wolff etal, 2000) Northern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wolff etal, 2000) Northern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wolff etal, 2000) Northern Brazil (Wolffetal, 2000) Northern Brazil  Species  B (tkm )  29. Squids  Unidentified species  0.42068  30. Octopus  Unidentified species  —  31. Other molluscs  Crassostrea rhizophorae  Group  2  Source/Area (Vasconcellos, 2002) South Atlantic  —  4.600 1.900  Macoma bathica  —  —  1.500  Mytella falcata  —  —  2.768  Unidentified species  33. Other invertebrates  1  5.160  (Viegas, 1982) Tagelus plebeius 30.80000 Northeastern Brazil (Tata and Prieto, 1991) Tivela mactroides 96.70000 Venezuela  32. Other crustaceans  P/B (year")  —  —  1.75000 (Arias-Gonzalez et al, 1997)/French Polynesia (Petraccoef a/.,2003) Emerita brasiliensis 14.00000 Southeastern Brazil (Rocha a/., 2003) 0.17500 Isopoda Southeastern Brazil (Rocha et al, 2003) 0.02500 Ostracoda Southeastern Brazil (Rocha et al, 2003) Stomatopoda 0.01500 Southeastern Brazil (Rocha et al, 2003) 0.07500 Tanaidacea Southeastern Brazil Caribbean Ascidians 35.00000 (Opitz, 1996) Benthic Copepoda  1.227 2.200  Source/Area (Vasconcellos, 2002) South Atlantic (Opitz, 1996) Caribbean (Mancera and Mendo, 1996) Colombia Burke and Mann (1974, in Tata and Prieto, 1991) Canada (Pereira-Barros and Santos, 1971 )/Northeastern Brazil (Viegas, 1982) Northeastern Brazil (Tata and Prieto, 1991) Venezuela  —  —  32.545  (Arias-Gonzalez et al, 1997) French Polynesia (Petraccoe<a/.,2003) Southeastern Brazil (Rocha et al, 2003) Southeastern Brazil  7.500 13.750  — 23.680 20.430 2.300  — (Arias-Gonzalez et al, 1997) French Polynesia (Arias-Gonzalez et al, 1997) French Polynesia (Opitz, 1996) Caribbean  Q/B (year") 1  Source/Area  (Vasconcellos, 2002) South Atlantic (Opitz, 1996) 6.760 Caribbean  36.500  —  —  —  —  —  —  —  —  18.871  (Opitz, 1996) Caribbean  203.070 (Arias-Gonzalez et al, 1997) French Polynesia  —  —  219.920  (Arias-Gonzalez et al, 1997) French Polynesia  —  —  (Arias-Gonzalez et al, 1997) French Polynesia (Arias-Gonzalez et al, 1997) 100.930 French Polynesia (Opitz, 1996) 29.000 Caribbean 85.270  Group  Species Asteroidea Chitons  B (t-kni ) 2  0.02000 18.00000  Crinoidea  0.50500  Echinoidea  0.03000  Holothuroidea  0.00500  Ophiuroidea  15.08500  Polychaeta (detritivorous)  9.52500  Polychaeta  6.99000  Sponges  30.50000  Unidentified species  12.40000  35. Corals  Unidentified species  51.85600  36. Microfauna  Unidentified species  37. Phytoplankton  Unidentified species  34. Zooplankton  38. Macroalgae Unidentified species  Source/Area (Rocha etal., 2003) Southeastern Brazil (Opitz, 1996) Caribbean (Rocha et al, 2003) Southeastern Brazil (Rocha etal, 2003) Southeastern Brazil (Rocha etal, 2003) Southeastern Brazil (Rocha etal, 2003) Southeastern Brazil (Rocha etal, 2003) Southeastern Brazil (Rochaetal, 2003) Southeastern Brazil Caribbean (Opitz, 1996) (Schwamborn, 1997) Northeastern Brazil  (Telles, 1998) Northeastern Brazil (Telles, 1998) 5.98900 Northeastern Brazil (Medeiros et al, 1999) 3.67000 Northeastern Brazil (Paula et al, 2003) (Mansilla-Mufloz and Pereira, 1997) 1930.807 (Guedes and Moura, 1996) Northeastern Brazil  P/B (year ) 1  Source/Area  Q/B (year") 1  Source/Area  (Rocha etal, 2003) (Opitz, 1996) 3.240 Southeastern Brazil Caribbean (Opitz, 1996) (Opitz, 1996) 0.260 7.200 Caribbean Caribbean (Rocha etal, 2003) 0.450 — — Southeastern Brazil (Rocha etal, 2003) (Rochaetal, 2003) 0.600 14.154 Southeastern Brazil Southeastern Brazil (Rocha et al, 2003) (Opitz, 1996) 6.250 3.360 Southeastern Brazil Caribbean (Rocha et al, 2003) 1.350 — — Southeastern Brazil (Rocha et al, 2003) (Rocha etal, 2003) 6.335 33.361 Southeastern Brazil Southeastern Brazil (Rocha etal, 2003) 3.600 — — Southeastern Brazil (Opitz, 1996) (Opitz, 1996) 4.020 1.700 Caribbean Caribbean (Hirst and Lampitt, 1998) (Opitz, 1996) 26.044 (Harris et al, 2000) 165.000 Caribbean R. Schwamborn, pers. comm. (Telles, 1998) (Telles, 1998) 1.090 8.460 Northeastern Brazil Northeastern Brazil (Telles, 1998) (Telles, 1998) 280.000 1786.00 Northeastern Brazil Northeastern Brazil (Ekau and Knoppers, 1999) NA 496.630 NA Northeastern Brazil 0.550  13.250  (Opitz, 1996) Caribbean  NA  NA  Group 39. Mangroves  Species Avicennia sp.  B (t-krn ) 2  47107.50  Conocarpus erecta 4054.10 Laguncularia racemosa  16045.10  Rhizophora mangle80910.70 40. Seagrasses Halodule wrightii 41. Detritus —  57.10 119.38 366.28 201.91  Source/Area (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) (Paulaetal., 2003) (Magalhaes etal, 1997) Northeastern Brazil (Paulyef al, 1993) (Medeiros etal, 1999) Northeastern Brazil  P/B (year ) 1  68.000 49.296 39.502 71.771 31.561  —  Source/Area (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil (Wiedemeyer, 1997) Northeastern Brazil  —  Q/B (year")  Source/Area  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  1  GROUP  SPECIES  SOURCE  1. Manatee  Trichechus manatus  2. Baleen whales  Balaenoptera acutorostrata (Pauly etal, 1998)  Global  Balaenoptera borealis  (Pauly etal, 1998)  Global  Balaenoptera edeni  (Pauly et al, 1998)  Global  Balaenoptera musculus  (Pauly etal, 1998)  Global  Balaenoptera physalus  (Pauly et al, 1998)  Global  (Pauly et al, 1998) Megaptera novaeangliae Globicephala macrorhynchus(Pauly al, 1998) Kogia breviceps (Pauly etal, 1998)  Global Global Global  3. Toothed cetaceans  (Mignucci-Giannoni and Beck, 1998)  AREA Puerto Rico  Kogia simus  (Pauly et al, 1998)  Orcinus orca Peponocephala electro  (Pauly et al, 1998) (Ford etal, 1998) (Pauly et al, 1998)  Physeter catodon  (Pauly etal, 1998)  Global  Sotalia fluviatilis  (Pauly et al, 1998) (Santos et al, 2002)  Global Southeastern Brazil  Stenella attenuata  (Pauly etal, 1998)  Global  Stenella clymene  (Pauly etal, 1998)  Global  Stenella coeruleoalba  (Pauly etal, 1998) (Rosas et al, 2002)  Global Southeastern Brazil  Stenella frontalis  (Pauly etal, 1998)  Global  Stenella longirostris  (Pauly etal, 1998)  Global  Global Global British Columbia Global  GROUP  4. Seabirds  AREA  Steno bredanensis  (Paulye/a/., 1998)  Global  Tursiops truncatus  (Paulyera/., 1998) (Santos etal, 2002)  Global Southeastern Brazil  Ziphius cavirostris  (Paulyera/., 1998)  Global  Anous stolidus  (Morris and Chardine, 1992)  Puerto Rico  Arenaria interpres  (Tsipoura and Burger, 1999)  Eastern United States  Calidris alba  (Tsipoura and Burger, 1999)  Eastern United States  Calidris canutus  (Tsipoura and Burger, 1999)  Eastern United States  Calidris pusilla  (Tsipoura and Burger, 1999)  Eastern United States  Charadrius semipalmatus  Eastern United States  Eudocimus ruber  (Tsipoura and Burger, 1999) (Prince and Morgan, 1987) (Prince, 1980) (Martinez, 2004)  Northern/Northeastern Brazil  Fregata magnificens  (Calixto-Albarran and Osorno, 2000)  Western Mexico  Nyctanassa violacea  (Martinez, 2004)  Northern/Northeastern Brazil  Pachyptila desolata  (Prince and Morgan, 1987)  South Georgia  Rallus longirostris  (Zembal and Fancher, 1988)  Western United States  Sterna hirundo  (Bugoni and Vooren, 2004)  Southern Brazil  Caretta caretta  (Plotkin et al, 1993)  Gulf of Mexico  Chelonia mydas  (Ferreira, 1968)  Northeastern Brazil  Diomedea melanophrys  5. Sea turtles  SOURCE  SPECIES  South Georgia  GROUP  SOURCE  SPECIES  AREA  Dermochelys coriacea  (Bjorndal, 1997)  Global  Eretmochelys imbricata  Thunnus alalunga  (Meylan, 1988) (Montenegro Silva etal, 1986) (Bjorndal, 1997) (Vaske-Junior, 2000)  Caribbean Western Mexico Global Northeastern Brazil  Thunnus albacares  (Vaske-Junior, 2000)  Northeastern Brazil  Thunnus obesus  (Vaske-Junior, 2000)  Northeastern Brazil  Acanthocybium solandri  (Vaske-Junior, 2000)  Northeastern Brazil  Istiophorus albicans  (Vaske-Junior, 2000)  Northeastern Brazil  Makaira nigricans  (Vaske-Junior, 2000)  Northeastern Brazil  Sphyraena barracuda  (Vaske-Junior, 2000)  Northeastern Brazil  Tetrapturus albidus  (Vaske-Junior, 2000)  Northeastern Brazil  Tetrapturus pfluegeri  (Vaske-Junior, 2000)  Northeastern Brazil  8. Dolphinfish  Coryphaena hippurus  (Vaske-Junior, 2000)  Northeastern Brazil  9. DolpWnfish juveniles  Coryphaena hippurus  (Vaske-Junior, 2000) (Oxenford and Hunte, 1999)  Northeastern Brazil Eastern Caribbean  10. Swordfish  Xiphias gladius  (Vaske-Junior, 2000)  Northeastern Brazil  11. Sharks  Carcharhinus falciformis  (Vaske-Junior, 2000)  Northeastern Brazil  Carcharhinus longimanus  (Vaske-Junior, 2000)  Northeastern Brazil  Carcharhinus signatus  (Vaske-Junior, 2000)  Northeastern Brazil  Prionace glauca  (Vaske-Junior, 2000)  Northeastern Brazil  Lepidochelys olivacea 6. Tunas  7. Other large pelagics  GROUP  12. Rays  13. Small pelagics  14. Needlefishes  15. Southern red snapper  SPECIES  SOURCE  AREA  Rhizoprionodon porosus  (Silva and Almeida, 2001)  Northeastern Brazil  Sphyrna lewini  (Vaske-Junior, 2000)  Northeastern Brazil  Dasyatis americana  (Gilliam and Sullivan, 1993)  Bahamas  Dasyatis centroura  (Bowman et a!., 2000)  Northeastern US  Dasyatis say  (Bowman etal., 2000)  Northeastern US  Myliobatis freminvillii  (Bowman etal, 2000)  Northeastern US  Pteroplatytrygon violacea  (Vaske-Junior, 2000)  Northeastern Brazil  Rhinoptera bonasus  (Bowman etal, 2000)  Northeastern US  Rioraja agassizii  (Muto era/., 2001)  Southeastern Brazil  Torpedo nobiliana  (Bowman et al, 2000)  Northeastern US  Anchoa hepsetus  (DeLancey, 1989)  South Carolina, US  Anchoa januaria  (Sergipense etal., 1999)  Southeastern Brazil  Cetengraulis edentulus  (Sergipense etal, 1999)  Southeastern Brazil  Chloroscombrus chrysurus (Chaves and Umbria, 2003) (Vega-Cendejas et al, 1994) Opisthonema oglinum (Furtado-Ogawa, 1970) (Vasconcelos Filho, 1979)  Southeastern Brazil Yucatan Peninsula, Mexico Northeastern Brazil Northeastern Brazil  Hemiramphus balao  (Berkeley and Houde, 1978)  Southeast Florida  Hemiramphus brasiliensis  (Berkeley and Houde, 1978)  Southeast Florida  Strongylura marina  (Arceo-Carranza et al, 2004)  Eastern Mexico  Lutjanus purpureus  (Monteiro and Barroso, 1963)  Northeastern Brazil  GROUP 16. Large carnivorous reef fishes  17. Small carnivorous reef fishes  SPECIES  AREA  Epinephelus guttatus  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Epinephelus itajara  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Gymnothorax moringa  (Young and Winn, 2003)  Belize  Lutjanus griseus  (Harrigane/a/., 1989)  Florida, US  Lutjanus jocu  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Mycteroperca bonaci  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Rachycentron canadum  (Arendt etal., 2001)  Chesapeake Bay, US  Aulostomus maculatus  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Bodianus rufus  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  (Sierra et al, 1994)/FishBase  Cuba  (Moriniere etal, 2003)  Netherlands Antilles  Selar crumenophthalmus  (Roux and Conand, 2000)  Southwestern Indian Ocean  Acanthurus chirurgus  (Dias etal, 2001)  Northeastern Brazil  Acanthurus bahianus  (Dias  a/., 2001)  Northeastern Brazil  Acanthurus coeruleus  (Dias etal, 2001)  Northeastern Brazil  Kiphosus incisor  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Scarus guacamaia  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Sparisoma radians  (Randall, 1967)/FishBase  Puerto Rico/US Virgin Islands  Halichoeres bivittatus maculipinna Lutjanus apodus 18. Herbivorous reef fishes  SOURCE  GROUP 19. Omnivorous reef fishes  20. Demersal fishes  SOURCE  SPECIES  AREA  (Vega-Cendejas et al, 1994) Acanthostracion quadricornis  Yucatan Peninsula, Mexico  Albula vulpes  (Crabtreeera/., 1998)  South Florida, US  Archosargus rhomboidalis  (Vega-Cendejas etal, 1994)  Yucatan Peninsula, Mexico  Balistes vetula  (Schiller and Garcia, 2000)  Colombian Caribbean  Chilomycterus schoepfii  (Mottae/a/., 1995)  Florida, US  Diodon holocanthus  (Huizar and Carrara, 2000)  Western Mexico  Diodon hystrix  (Huizar and Carrara, 2000)  Western Mexico  Eucinostomus argenteus  (Vega-Cendejas et al, 1994)  Yucatan Peninsula, Mexico  Eucinostomus guia  (Vega-Cendejas et al, 1994)  Yucatan Peninsula, Mexico  Haemulon plumieri  (Vega-Cendejas et al, 1994)  Yucatan Peninsula, Mexico  Lutjanus analis  (Duarte and Garcia, 1999b)  Colombian Caribbean  Lutjanus synagris  (Duarte and Garcia, 1999a) (Rodrigues, 1974)  Colombian Caribbean Northeastern Brazil  Bairdella ronchus  (Vendel and Chaves, 1998)  Southern Brazil  Citharichthys spilopterus  (Castillo-Rivera etal, 2000)  Gulf of Mexico  Dormitator maculatus  (Teixeira, 1994)  Northeastern Brazil  Eleotris pisonis  (Teixeira, 1994)  Northeastern Brazil  Etropus crossotus  (Chaves and Serenato, 1998)  Southern Brazil  Eucinostomus melanopterus(Chaves and Robert, 2001) Isopisthus parvipinnis  (Soares and Vazzoler, 2001b)  Southern Brazil Southeastern Brazil  GROUP  SOURCE  SPECIES Larimus breviceps  (Soares and Vazzoler, 2001b)  Southeastern Brazil  Menticirrhus littoralis  (DeLancey, 1989)  South Carolina  Micropogonias furnieri  (Soares and Vazzoler, 2001b)  Southeastern Brazil  Ophioscion punctatissimus (Zahorcsakefa/., 2000)  Southeastern Brazil  Orthopristis ruber  Southeastern Brazil  (Zahorcsakefa/,,2000)  Paralonchurus brasiliensis (Soares and Vazzoler, 2001a)  21. Mullets  AREA  Southeastern Brazil  Prionotus punctatus  (Braga and Braga, 1987) (Teixeira and Haimovici, 1989)  Southeastern Brazil Southern Brazil  Stellifer rastrifer  (Chaves and Vendel, 1998)  Southern Brazil  Symphurus tessellatus  (Chaves and Serenato, 1998)  Southern Brazil  Umbrina coroides  (Zahorcsak et al, 2000)  Southeastern Brazil  Mugil curema  (Dualiby, 1988) (Gonzalez-Sanson and Alvarez-Lajonchere, 1978)/FishBase (Dualiby, 1988)  Colombian Caribbean  (Dualiby, 1988) (Gonzalez-Sanson and Alvarez-Lajonchere, 1978)/FishBase  Colombian Caribbean  Mugil curvidens Mugil incilis Mugil liza Mugil trichodon  Cuba Colombian Caribbean  Cuba  22. Goatfish  Pseudupeneus maculatus  (Randall, 1967)/FishBase  West Indies  23. Benthopelagic fishes  Centropomus ensiferus  (Sierra et al, 1994)  Cuba  Hymenocephalus italicus  (Macpherson, 1979)  Western Mediterranean Sea  Neobythites gilli  (Nielsen, 1999)  Atlantic  GROUP  SPECIES  SOURCE  AREA  Nezumia aequalis  (Macpherson, 1979)  Oligoplites palometa  Colombian Caribbean (Duque-Niviae/a/., 1996) (Azevedo-Araujo and Vasconcelos Filho, 1979) Northeastern Brazil  Trachinotus carolinus  (DeLancey, 1989)  South Carolina, US  Trichiuruslepturus  (Bowmanetal, 2000) (Portsev, 1980)  Northwestern Atlantic Western India  Alepisaurus ferox  (Vaske-Junior, 2000)  Northeastern Brazil  Argyropelecus aculeatus  (Hopkins and Baird, 1985)  Gulf of Mexico  Argyropelecus affinis  (Kinzer and Schulz, 1988)  Central Equatorial Atlantic  Argyropelecus sladeni  (Kinzer and Schulz, 1988)  Central Equatorial Atlantic  Ceratoscopelus warmingii  (Kinzer and Schulz, 1985) (Duka, 1986)  Central Equatorial Atlantic Tropical Atlantic  (Kinzer and Schulz, 1985)  Central Equatorial Atlantic  Diaphus taaningi  (Baird era/., 1975)  Venezuela  Gempylus serpens  (Vaske-Junior, 2000)  Northeastern Brazil  Notolychnus valdiviae  (Kinzer and Schulz, 1985)  Central Equatorial Atlantic  Sternoptyx diaphana  (Hopkins and Baird, 1985) (Hopkins and Baird, 1973)  Gulf of Mexico Atlantic and Pacific oceans  Sternoptyx pseudobscura  (Hopkins and Baird, 1985)  Gulf of Mexico  25. Spiny lobsters  Panulirus argus  (Colinas-Sanchez and Briones-Fourzan, 1990) Qu intana Roo, Mexico (Fernandes, 1971) Northeastern Brazil  26. Other lobsters  Parribacus antarticus  (Lau, 1988)  24. Bathypelagic fishes  • Diaphus dumerilii  Western Mediterranean Sea  Indo-Pacific  GROUP 27. Shrimps  28. Crabs  29. Squids  30. Octopus  SPECIES  SOURCE  AREA  Farfantepenaeus brasiliensis(Albertonietal, 2003)  Southeastern Brazil  Farfantepenaeus subtilis  (Stoner and Zimmerman, 1998)  Western Puerto Rico  Litopenaeus schmitti  (Tararamera/., 1993)  Southeastern Brazil  Xiphopenaeus kroyeri  (Branco and Moritz Junior, 2001)  Southern Brazil  Aratus pisonii  (Brogim and Lana, 1997)  Southern Brazil  Callinectes danae  (Branco and Verani, 1997)  Southern Brazil  Callinectes ornatus  (Branco et al, 2002) (Mantelatto and Christofoletti, 2001) (Mantelatto et al, 2002)  Southern Brazil Southeastern Brazil Southeastern Brazil  Callinectes salpidus  (Laughlin, 1982)  Florida, US  Ocypode quadrata  (Wolcott, 1978)  North Carolina, US  Pachygrapsus transversus  (Furtado-Ogawa, 1977)  Northeastern Brazil  Ucides cordatus  (Wolff et al, 2000, based on Rademaker, 1998)  Northern Brazil  Loligo plei  (Arocha and Urosa, 1991)  Venezuela  Lollingula brevis  (Dragovich and Kelly Jr., 1964)  Florida, US  Ommastrephes bartramii  (Lipinski and Linkowski, 1988)  Argentina and Uruguay  Ornithoteuthis antillarum  (Arkhipkinefa/., 1998)  Central-east Atlantic  Sthenoteuthis pteropus  (Nigmatullin and Toporova, 1982)  Atlantic  Octopus vulgaris  (Smith, 2003)  South Africa  31. Other molluscs  32. Other crustaceans 33. Other invertebrates  AREA  Eledone massyae  (Perez and Haimovici, 1995)  Southern Brazil  Scaeurgus unicirrhus  (Aluigi and Spedicato, 1994)  Mediterranean Sea  Crassostrea rhizophorae  (Gomes Azevedo, 1980)  Northeastern Brazil  Macoma constricta  (Arrudaetal., 2003)  Southeastern Brazil  Mytella falcata  (Eskinazi-Leca, 1969)  Northeastern Brazil  Olivella minuta  (Arruda et al, 2003)  Southeastern Brazil  Tagelus pleibeus  (Arruda et al, 2003)  Southeastern Brazil  Amphipoda/Isopoda/Tanaidacea  (Opitz, 1996)  Caribbean  Echinodermata  (Telles, 1998) (Tararame/a/., 1993)  Northeastern Brazil Southeastern Brazil  (Telles, 1998)  Northeastern Brazil  (Telles, 1998)  Northeastern Brazil  Various  (Telles, 1998) (Vasconcellos, 2002) (Mohammed, 2003)  Northeastern Brazil South Atlantic Southern Caribbean  Various  (Telles, 1998)  Northeastern Brazil  Porifera Polychaeta/Ascidia/Briozoa/ Sipunculida 34. Zooplankton  35. Corals  SOURCE  SPECIES  GROUP  (Mohammed, 2003) 36. Microfauna Various * Groups 37 to 40 are not included as they are primary producers and group 41 is a detritus group.  Southern Caribbean  

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