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Ecopath 25 years conference proceedings: Extended abstracts Palomares, M.L. Deng; Morissette, Lyne; Cisneros-Montemayor, Andres; Varkey, Divya; Coll, Marta; Piroddi, Chiara 2009-02-24

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  ISSN 1198-6727  Fisheries Centre Research Reports    2009 Volume 17 Number 3     Ecopath 25 Years Conference Proceedings: Extended Abstracts      Fisheries Centre, University of British Columbia, Canada   Ecopath 25 Years Conference Proceedings: Extended Abstracts     Edited by M.L. Deng Palomares Lyne Morissette Andres Cisneros-Montemayor Divya Varkey Marta Coll Chiara Piroddi                Fisheries Centre Research Reports 17(3) 167 pages © published 2009 by  The Fisheries Centre, University of British Columbia  2202 Main Mall Vancouver, B.C., Canada, V6T 1Z4       ISSN 1198-6727   Fisheries Centre Research Reports 17(3) 2009   ECOPATH 25 YEARS CONFERENCE PROCEEDINGS: EXTENDED ABSTRACTS   edited by  M.L. Deng Palomares Lyne Morissette Andres Cisneros-Montemayor Divya Varkey Marta Coll Chiara Piroddi   CONTENTS    Page  FOREWORD ............................................................................................................................................. 1 WELCOME NOTE ......................................................................................................................................2 THE ORGANIZING COMMITTEE ...................................................................................................................3 ACKNOWLEDGEMENTS ..............................................................................................................................6 ON BEING GREEN..................................................................................................................................... 7 PROGRAM: ORAL PRESENTATIONS ..............................................................................................................8 LIST OF POSTER PRESENTATIONS .............................................................................................................. 12 KEYNOTE SPEAKERS ............................................................................................................................... 14 OPENING SESSION .................................................................................................................................. 16 The origins of Ecopath.................................................................................................................................................... 16 Jeffrey Polovina .......................................................................................................................................................... 16 Ecopath: from the French Frigate Shoals to the Philippines and to UBC ................................................................... 17 Daniel Pauly................................................................................................................................................................ 17 FISHERIES APPLICATIONS: ORAL PRESENTATIONS .......................................................................................20 Foraging arena theory ...................................................................................................................................................20 Carl J. Walters, Villy Christensen, Robert Ahrens ....................................................................................................20 EcoTroph: a new tool in the EwE family....................................................................................................................... 21 Didier Gascuel, Melen Leclerc, Audrey Valls, Sylvie Guénette................................................................................. 21 Exploring fisheries strategies for  ecosystem-based management in the East China Sea.........................................23 Jiang Hong, Cheng He Qin, Francisco Arreguín-Sánchez........................................................................................23   Ecological effect of moonjelly, Aurelia aurita, removal in the Sea of Suo-Nada, Seto Inland Sea, Japan ...............25 Shingo Watari, Hiromu Zenitani, Keisuke Yamamoto, Naoaki Kono......................................................................25 Capturing significant coral reef ecosystem and fishery changes in Bolinao, Philippines (1997-2008) using Ecopath with Ecosim.......................................................................................................................................................27 Rollan C. Geronimo, Porfirio M. Aliño ......................................................................................................................27 Fisheries in Baja California Sur: a trophic-based analysis of management scenarios .............................................29 Andres M. Cisneros-Montemayor, Villy Christensen, Ussif Rashid Sumaila, Francisco Arreguín-Sánchez..........29 Impact of fishing and climate on the Celtic Sea and the Bay of Biscay....................................................................... 31 Sylvie Guénette, Didier Gascuel ................................................................................................................................. 31 FISHERIES APPLICATIONS: POSTER PRESENTATIONS ................................................................................... 33 Recovery scenarios of a highly exploited species, Merluccius merluccius, in the NW Mediterranean Sea ..............33 Giovanni Vargiu, Marta Coll, Isabel Palomera, Sergi Tudela ...................................................................................33 On the transfer payment of the fishery fuel subsidies in China ...................................................................................35 Cheng He Qin, Jiang Hong.........................................................................................................................................35 Vulnerability to fishing of the Central Gulf of California ecosystem...........................................................................37 Francisco Arreguín-Sánchez, Luis A. Salcido-Guevara.............................................................................................37 Effects of local fisheries and ocean productivity on the Northeastern Ionian Sea ecosystem ...................................39 Chiara Piroddi, Giovanni Bearzi, Villy Christensen ..................................................................................................39 Trophodynamic modelling of the eastern shelf and slope of the South East Fishery ................................................. 41 Catherine Bulman, Scott Condie, Neil Klaer, Dianne Furlani, Madeleine Cahill, Simon Goldsworthy, Ian Knuckey....................................................................................................................................................................... 41 The impacts of longline fishery on the pelagic ecosystem in the eastern Taiwan waters......................................... 44 Chien-Pang Chin, Chi-Lu Sun, Kwang-Ming Liu ..................................................................................................... 44 Introducing ecosystem-based management in the Gulf of Thailand.......................................................................... 46 Ratanawalee Poonsawat, Mala Supongpan, Villy Christensen................................................................................ 46 Trophic analysis of Lake Awassa (Ethiopia) using a mass-balanced Ecopath model ...............................................47 Tadesse Fetahi, Seyoum Mengistou...........................................................................................................................47 SPATIAL ANALYSIS: ORAL PRESENTATIONS ................................................................................................ 49 Ecospace: has its time come? ........................................................................................................................................ 49 Steve Mackinson ........................................................................................................................................................ 49 Evaluation of the usefulness of Marine Protected Areas (MPAs) for management of recovery of fish stocks and ecosystems in the North Sea .......................................................................................................................................... 50 Georgi M. Daskalov, Steve Mackinson, Hong Q. Cheng, John K. Pinnegar............................................................ 50 Modelling spatial closures and fishing effort restrictions in Jurien Bay, Western Australia: a case study of the western rock lobster (Panulirus cygnus) fishery ..........................................................................................................52 Hector M. Lozano-Montes, Russ Babcock, Neil R. Loneragan.................................................................................52 A trophic model to simulate the combined effect of artisanal and recreational fisheries on a Mediterranean ecosystem: the Bonifacio Straits Natural Reserve (Corsica, France)..........................................................................55 Camille Albouy, François Le Loc’h, Jean Michel Culioli, David Mouillot ................................................................55 Trophic modeling of a temperate marine ecosystem throughout marine reserve protection in New Zealand .......57 Tyler D. Eddy, Jonathan P.A. Gardner ......................................................................................................................57 Estimating the carrying capacity of monk seals using the French Frigate Shoals Ecopath .....................................59 Frank Parrish, George Antonelis, Evan Howell, Sara Iverson, Charles Littnan, James Parrish, Jeffrey Polovina 59 Exploration of ecological and economic benefits from implementation of marine protected areas in Raja Ampat, Indonesia ........................................................................................................................................................................ 60 Divya Varkey, Cameron Ainsworth, Tony Pitcher.................................................................................................... 60 SPATIAL ANALYSIS: POSTER PRESENTATIONS............................................................................................. 62 Habitat Suitability Model for the Bush Warbler (Cettia diphone) at Jeju Experimental Forests of Korea ..............62 Chan Ryul Park, Kim Eunmi, Chang Wan Kang, Sung Bae Lee ...............................................................................62    ECOSYSTEM COMPARISONS & NETWORK ANALYSIS: ORAL PRESENTATIONS .....................................................64 Comparing indicators of ecosystem change using ecological network analysis........................................................64 Johanna J. Heymans, Maciej T. Tomczak, Thorsten Blenckner Susa Niiranen ......................................................64 Marine mammals – fisheries interactions: how to use Ecopath with Ecosim to capture ecological complexity.....67 Lyne Morissette, Chiara Piroddi ................................................................................................................................67 A simple approach for enhancing ecological networks and energy budgets (namely Ecopath): please, let’s do some PREBAL before we start balancing......................................................................................................................69 Jason S. Link...............................................................................................................................................................69 Impact of offshore windparks on ecosystem structure and flow patterns .................................................................70 Silvia Opitz, Hermann Lenhart, Wilhelm Windhorst ...............................................................................................70 Comparison of trophic structures and key players for two periods in the continental shelf ecosystem of the central pacific of Mexico.............................................................................................................................................................. 72 Víctor Hugo Galván Piña, Francisco Arreguín-Sánchez, Manuel Zetina Rejón, José Trinidad Nieto Navarro .....72 Trophic flow structure of four overfished coastal ecosystems around the Philippines..............................................74 Lualhati Lachica-Aliño, Laura T. David, Matthias Wolff..........................................................................................74 Relationship between biodiversity and ecosystem functioning in Mexican aquatic systems....................................76 J. Ernesto Arias-González, Luis G. Abarca, Javier Alcocer-Durán, José L. Cabrera, Luis E. Calderón-Aguilera, Xavier Chiappa-Carrara, Villy Christensen, Amilcar Cupul-Magaña, Jonathan Franco-López, Horacio Pérez- España, Verónica Morales-Zárate, Fabián A. Rodriguez-Zaragoza, Candy Sansores, Juan J. Schmitter-Soto ..... 77 ECOSYSTEM COMPARISONS & NETWORK ANALYSIS: POSTER PRESENTATIONS .................................................. 79 Metabolism of aquatic ecosystems.................................................................................................................................79 Luis Salcido-Guevara, Francisco Arreguín-Sánchez.................................................................................................79 A fish chain analysis of Northern Gulf cod recovery options:  exploring EwE modeling approaches for policy scenarios .......................................................................................................................................................................... 81 Ahmed Khan ............................................................................................................................................................... 81 Ecosystem structure and functional traits of the Northern Aegean Sea (E. Mediterranean, Greece)......................84 Konstantinos Tsagarakis, Marta Coll, Marianna Giannoulaki, Costas Papakonstantinou, Athanassios Machias, Argyris Kallianiotis .....................................................................................................................................................84 CLIMATE IMPACT EVALUATION: ORAL PRESENTATIONS ................................................................................86 Ecoworld: EwE one link in global systems model ........................................................................................................86 Elizabeth A. Fulton .....................................................................................................................................................86 Experiences in integrating physical-biogeochemical processes into food web dynamics with EwE....................... 88 Simone Libralato, Cosimo Solidoro .......................................................................................................................... 88 Ecological interactions within marine ecosystems determine winners and losers under climate change.............. 90 Christopher J. Brown, Elizabeth A. Fulton, Alistair J. Hobday, Richard Matear, Hugh Possingham, Catherine Bulman, Villy Christensen, Robyn Forrest, Peter Gehrke, Neil Gribble, Shane P. Griffiths, Hector M. Lozano- Montes, Julie Martin, Sarah Metcalf, Thomas A. Okey, Reg Watson, Anthony J. Richardson .............................. 91 Ecological effects of fishing and climate change on the pelagic ecosystem off eastern Australia.............................94 Shane P. Griffiths, Jock W. Young, Matt J. Lansdell, Robert A. Campbell..............................................................94 Ecosystem effects of climate change in the Antarctic Peninsula..................................................................................96 Carie Hoover ...............................................................................................................................................................96 On the use of both unconventional and traditional time series data in constructing dynamic models of a marine ecosystem.........................................................................................................................................................................98 David Preikshot, Richard Beamish, Ruston Sweeting, Chrys-Ellen M. Neville, Krista Lange................................98 Development of an ecosystem model for Galveston Bay: evaluating the influence of freshwater inflows, nutrient inputs and fisheries.........................................................................................................................................................99 Glen Sutton, George Guillen ......................................................................................................................................99 Structure of two high latitude Norwegian fjord ecosystems analysed using Ecopath ............................................ 101 Torstein Pedersen, Einar M. Nilssen, Marianne Nilsen, Lyne Morissette, Anita Maurstad ................................. 101     CLIMATE IMPACT EVALUATION: POSTER PRESENTATIONS............................................................................103 Mechanisms affecting recovery in an upwelling food web: the case of the southern Humboldt ............................103 Sergio Neira, Coleen Moloney, Philippe Cury, Cristia Mullon, Villy Christensen .................................................103 Spatial and temporal trophic dynamics of terrestrial arctic ecosystems .................................................................105 Pierre Legagneux, Gilles Gauthier, Charles J. Krebs ..............................................................................................105 IMPLEMENTING ECOSYSTEM-BASED MANAGEMENT: ORAL PRESENTATIONS................................................... 107 How can EwE assist us in implementing ecosystem-based fisheries management? Drawing from the South African experience......................................................................................................................................................... 107 Lynne J. Shannon, Astrid Jarre, Kate E. Watermeyer ............................................................................................ 107 Ecosystem approach to the mutispecies fishery in the south-austral zone of Chile..................................................109 Sergio Neira, Hugo Arancibia, Steve Mackinson, Mónica Barros ..........................................................................109 Trade-offs between conservation and socio-economic objectives in managing a tropical marine ecosystem ....... 111 William W.L. Cheung, Ussif Rashid Sumaila ........................................................................................................... 111 Supporting ecosystem based management on the west coast of Vancouver Island................................................. 113 Maria Espinosa, Edward Gregr, Villy Christensen, Kai Chan................................................................................. 113 Progress in ranking species importance in whole biological communities using food web models ........................115 Thomas A. Okey, Ferenc Jordán, Simone Libralato, Barbara Bauer.......................................................................115 Using ecological thresholds to inform targets for marine ecosystem-based management......................................117 Jameal F. Samhouri, Phillip S. Levin, Cameron H. Ainsworth................................................................................117 Poaching/preservation: the case of the Meru National Park, Kenya ....................................................................... 118 Maria C. Villanueva, Mark Jenkins, Jacques Moreau............................................................................................. 118 Using Ecopath with Ecosim and local ecological knowledge to examine conflicts between artisanal and indsutrial fisheries in the Red Sea .................................................................................................................................................120 Dawit Tesfamichael ..................................................................................................................................................120 IMPLEMENTING ECOSYSTEM-BASED MANAGEMENT: POSTER PRESENTATIONS................................................ 122 Restoration of Chelonia mydas population in the Caribbean: ecosystem impacts resulting from reduction of seagrass habitat complexity......................................................................................................................................... 122 Colette C. Wabnitz, Karen A. Bjorndal, Alan B. Bolten, Villy Christensen, Daniel Pauly ..................................... 122 Modelling marine food webs in the Mediterranean Sea ............................................................................................124 Marta Coll, Simone Libralato ...................................................................................................................................124 A preliminary model of the San Francisco Estuary ecosystem ................................................................................. 127 Howard Townsend, Marissa Bauer, Larry Brown................................................................................................... 127 ECOPATH WITH ECOSIM AND BEYOND: ORAL PRESENTATIONS .....................................................................128 Use of EwE outputs to investigate attributes of trophic networks of aquatic ecosystems relevant to fisheries management..................................................................................................................................................................128 Francisco Arreguín-Sánchez ....................................................................................................................................128 EwE6: interoperability usage, capabilities, technology, structure and beyond.......................................................130 Sherman Lai, Jeroen Steenbeek, Joe Buszowski.....................................................................................................130 A global map of the relative impact of fishing on the biomass of marine ecosystems from 1950 to 2004 ............. 132 Laura Tremblay-Boyer, Didier Gascuel, Daniel Pauly ............................................................................................ 132 Dynamic linking of Ecosim and the GOTM biogeochemical model using plugins ................................................... 134 Jonathan A. Beecham, Steve Mackinson, John Aldridge........................................................................................ 134 Chesapeake Bay fisheries ecosystem model: computer-generated graphics for creating a gaming experience with ecosystem data and management................................................................................................................................ 136 Villy Christensen, Sherman Lai, Howard Townsend .............................................................................................. 136 MINOE: open source tool to navigate ocean governance in the context of a user-defined ecosystem ................... 137 Julia A Ekstrom ........................................................................................................................................................ 137 Revealing changes in fish community at ecosystem level: use of trophic modelling and topological analysis ..... 139 Manuel Zetina Rejón, José T. Nieto-Navarro, Julia Ramos-Miranda, Francisco Arreguín-Sánchez, Domingo Flores-Hernández ..................................................................................................................................................... 139    Using Ecopath with Ecosim to explore nekton community responses to freshwater input from a Mississippi River diversion in Breton Sound, Louisiana ..........................................................................................................................141 Kim K. de Mutsert, Carl J. Walters, Brian B. M. Roth, James H. Cowan Jr. ..........................................................141 ECOPATH WITH ECOSIM AND BEYOND: POSTER PRESENTATIONS.................................................................. 143 Using true GIS data with Ecospace ............................................................................................................................. 143 Jeroen Steenbeek, Villy Christensen ....................................................................................................................... 143 Production and consumption in Ecopath models: a global overview....................................................................... 145 Chiara Piroddi, Divya Varkey, Lyne Morissette, Villy Christensen........................................................................ 145 Main drivers of marine resources and food-web changes in the Mediterranean Sea ............................................. 148 Marta Coll, Chiara Piroddi, Isabel Palomera, Enrico Arneri, Villy Christensen.................................................... 148 A preliminary model of coastal resources of the Pantagonian marine ecosystem ...................................................151 Sebastián Villasante, Maria do Carme García-Negro, G. Rodríguez Rodríguez, Maria C. Villanueva, Villy Christensen, Ussif Rashid Sumaila...........................................................................................................................151 Exploring novel metrics of ecosystem overfishing using energy budget model outputs ......................................... 153 Jason S. Link, Fabio Pranovi, Marta Coll, Simone Libralato, Villy Christensen, Christopher M. Legault ........... 153 Why Not Ecopath for terrestrial ecosystems?............................................................................................................. 154 Charles J. Krebs, Alice J. Kenney, Gilles Gauthier.................................................................................................. 154 FishBase, SeaLifeBase and database-driven ecosystem modeling............................................................................ 156 M.L. Deng Palomares, Nicolas Bailly, Daniel Pauly................................................................................................ 156 CLOSING SESSION................................................................................................................................. 159 The future of Ecopath ................................................................................................................................................... 159 Villy Christensen....................................................................................................................................................... 159 LOGISTICS............................................................................................................................................161 INDEX OF AUTHORS .............................................................................................................................. 164 ADDENDUM......................................................................................................................................... 166 Elucidation of ecosystem attributes using Ecopath with Ecosim (EwE): application to an oligotrophic lake in Hokkaido, Japan........................................................................................................................................................... 166 Md. Monir Hossain, Takashi Matsuishi, George Arhonditsis ................................................................................ 166 NOTES................................................................................................................................................ 168                 A Research Report from the Fisheries Centre at UBC 167 pages © Fisheries Centre, University of British Columbia, 2009   FISHERIES CENTRE RESEARCH REPORTS ARE ABSTRACTED IN THE FAO AQUATIC SCIENCES AND FISHERIES ABSTRACTS (ASFA) ISSN 1198-6727 Ecopath 25 Years Conference Proceedings: Abstracts FOREWORD I wish to congratulate the organizers of this conference, as it celebrates a momentous event in the history of fisheries science: the emergence of a simple way of representing a marine ecosystem. Many approaches had been developed at the time Ecopath emerged to represent and simulate the interrelationships of prey, predators and fisheries in marine ecosystems, and many have been published since. But none had the simplicity of the approach that Jeffrey Polovina proposed and none of them used data that fisheries and marine scientists readily had available on their desks the way Ecopath does. The first of the abstracts in this report, by Jeff outlines how Ecopath came to be in Hawaii. The second, by Daniel Pauly, outlines how the ‘franchise’ for this approach and software then went from Hawaii to Manila, where he and Villy Christensen further developed the software and assisted in its dissemination. Interestingly, it was in developing countries where, at first, it was most readily picked-up. When Daniel and Villy moved to the Fisheries Centre, in the mid 1990s, the ‘franchise’ moved with them and Carl Walters, by developing Ecosim in Ecopath, put the finishing touch on the Ecopath approach, which was then eagerly adopted by researchers in the Fisheries Centre, and gradually, by a wider circle of colleagues in North America, Europe and elsewhere, even reaching the borders of my discipline, Economics. Ecopath, now 25 years old, really has come of age, to the extent that it was named recently by NOAA as one of the 10 major scientific breakthroughs in the organization’s 200-year history. It is fitting that the Fisheries Centre should host this meeting, both because of its members’ role in the development of Ecopath and because it continues to serve as a hub for its further development.  RASHID SUMAILA DIRECTOR, FISHERIES CENTRE  1 Welcome Note WELCOME NOTE In 1984, Dr. Jeffrey Polovina and his colleagues at the National Marine Fisheries Service, Honolulu Laboratory, developed an innovative marine ecosystem model known as Ecopath. With a name conveying its focus on ecological pathways, Ecopath was the first model to apply a type of statistics called ‘path analysis’ to the field of marine ecology. The model’s simplicity and its ability to accurately identify ecological relationships have revolutionized scientists’ ability worldwide to understand complex marine ecosystems. Now, 25 years later, the Ecopath suite of software is recognized as one of NOAA’s top ten scientific breakthroughs in the last 200 years. The current approach Ecopath and Ecosim (EwE), developed and promoted by Villy Christensen, Carl Walters and Daniel Pauly is used in over 150 countries for a multitude of purposes. EwE has contributed substantially and in tangible ways towards an ecosystem-based management approach of marine resources worldwide. EwE is the first ecosystem-level simulation model to be widely and freely accessible. As of October 2008, there were 5 649 registered users in 164 different countries (www.ecopath.org, 27th October 2008) and well over 200 publications; making EwE an important modelling approach to explore ecosystem related questions in marine science. Further technical and application details on EwE can be found at www.ecopath.org. The Ecopath 25 Years Conference aims to provide an overview of 25 years of progress using this approach in different fields: fisheries management, ecosystem comparisons, spatial analyses, climate impacts, and ecosystem-based management as well as to introduce exciting new features. It is intended to be an international scientific reunion on ecosystem modelling using the software Ecopath and Ecosim (EwE). Futhermore, this event will allow users from the scientific community, education bodies, members of governmental organizations and NGOs to be given an overview on what has been achieved since Ecopath’s inceptions. Key topics of the conference include: expansion of features to the analysis of fishing policies; establishment of marine protected areas (MPAs); study of socioeconomic factors of marine exploitation; and incorporation of climatic drivers in the analysis of marine ecosystems. We wish all participants a fruitful stay in Vancouver and a very exciting week at the Ecopath 25 Years Conference and Workshops!  THE ORGANIZING COMMITTEE ECOPATH 25 YEARS CONFERENCE AND WORKSHOPS  2 Ecopath 25 Years Conference Proceedings: Abstracts THE ORGANIZING COMMITTEE ADVISOR: Villy Christensen Villy Christensen has led the development of the Ecopath approach and software since 1990, when he joined Daniel Pauly at ICLARM in the Philippines on secondment from the Danish International Development Agency. Since the mid-1990s he has worked closely with Carl Walters on what became Ecopath with Ecosim. He is now a faculty at the UBC Fisheries Centre. CHAIR: Chiara Piroddi Chiara Piroddi is a researcher with the Sea Around Us Project at the Fisheries Center, University of British Columbia. Her Master’s thesis used Ecopath with Ecosim to study ecosystem-based approach for two dolphin populations around the island of Kalamos, Ionian Sea, Greece. She is currently working on a global database for mesopelagic fish distributions and Ecopath with Ecosim models for world’s Large Marine Ecosystems. She is also involved in collating basic input parameters from 100 Ecopath models into broad functional groups to reduce parameter specification error for Ecopath models. Though unwillingly at first, Chiara became the natural leader of the organizing committee of the Ecopath 25 Years Conference and Workshops because of her familiarity with the events and the developments related to EwE. Her leadership and unwavering adherence to quality, notably to the food participants will enjoy in the 2 weeks of this event (she is Italian afterall), is what makes this conference a ‘well-oiled’ machine. MEMBERS: Marta Coll Dr Marta Coll Monton is a post-doctoral fellow at Dalhousie University (Halifax, Canada) and Institute of Marine Science (Barcelona, Spain). She is currently working on her Marie Curie project “ECOFUN: Analysis of biodiversity changes on structural and functional properties of marine ecosystems under cumulative human stressors” International Outgoing Fellowships (IOF) Call: FP7-PEOPLE-2007-4-1-IOF. Her interest focuses on understanding how documented changes on marine biodiversity have been translated into changes on ecosystem structure and functioning, and services to humans, and how these changes may impact ecosystems in the future. Thus, her work implies hindcasting changes on coastal ecosystem functioning due to effects of human impacts, and forecasting how these effects could develop in the future. To do so, she mainly applies various ecological modelling tools using historical and fisheries data and combines it with laboratory experiments and field work data analysis. Her PhD work had been mainly based on studying marine ecosystems in the Mediterranean Sea, where she studied the ecosystem impacts of fishing by means of food web modelling and trophodynamic indicators using Ecopath with Ecosim. Carie Hoover Carie Hoover is currently a PhD student at the Fisheries Center, University of British Columbia. She is looking at the effects of climate change on polar ecosystems, with her research focusing on identifying threats to top predators in the Antarctic Peninsula and Hudson Bay ecosystems. She is currently working in association with DFO assessing the status of marine mammals in the Hudson Bay as part of the Global Warming and Arctic Marine Mammals (GWAMM) Project under International Polar Year (IPY) funding. Carie completed her Bachelor of Science degree majoring in Ecology, Evolution, and Marine Biology (EEMB) at the University of California Santa Barbara. After leaving California, Carie moved to Scotland to attend the University of St Andrews where she completed her Masters degree in a biology-mathematics conversion program, with her thesis focusing on predator prey interactions of grey seals, and prey selectivity. 3 The Organizing Committee Sherman Lai Sherman Lai is the Project Coordinator of the Lenfest Ocean Futures Project which plans to bring Ecopath to a whole new level of decision support tools. He is involved in the development of interfaces and in charge of implementing state-of-the-art technologies on collaborative environments, as well as in designing human-computer interaction schemes. Internally he is responsible for project performance, including tracking and meeting development deadlines. Lyne Morissette Dr. Lyne Morissette is a postdoctoral fellow from the “Fonds Québécois de la Recherche sur les Sciences et Technologies” (FQRNT) with Dr Kevin McCann at the University of Guelph. Her current work is focused on the diversity and resilience of ecosystems and the trophic role of predators. Her main interest is to see if genetic diversity is affecting the way prey populations are impacted by predators, and how genetic features of the prey can help maintaining population and community structure through time. Over the years, she gained an expertise on the trophic role of marine mammals in ecosystem, and used Ecopath with Ecosim and other modeling approaches to construct models characterizing ecosystem structure and functions. She is an active member of different research groups with the Department of Fisheries and Oceans of Canada (DFO), the Norwegian College of Fisheries Sciences at University of Tromsø, and the North Atlantic Marine Mammal Commission (NAMMCO). She earned her PhD in Zoology from the University of British Columbia in 2007, and contributed to the Sea Around Us Project completing a database for all Ecopath models available from around the world. She is now on the editorial board of the open-access journal “Diversity”, guest-editing a special issue on “Biodiversity, Conservation and Wildlife Management”. M.L. Deng Palomares Dr. M.L. Deng Palomares is a Senior Research Associate with the Sea Around Us Project at the Fisheries Center, University of British Columbia. She coordinates integration of fish-related data generated by the Sea Around Us Project into FishBase (www.fishbase.org), a very successful information system on fish. This ensures that the fish-related project’s results become immediately available to the public, as well as enabling comprehensive analyses by other project members. Since 2005, she is also Project Coordinator of SeaLifeBase (www.sealifebase.org), a FishBase-like information system on all marine organisms, which links to FishBase and other online biodiversity information systems, e.g., Catalogue of Life and the World Register of Marine Species. Both SeaLifeBase and FishBase are structured to ‘communicate’ with Ecopath with Ecosim for its various data requirements, e.g., trophic levels, diet compositions and growth parameters. Jeroen Steenbeek Jeroen Steenbeek is a corporate trained computer scientist from the Netherlands, and has been a technical consultant with Lenfest Ocean Futures Project since the beginning of the Ecopath with Ecosim 6 (EwE6) project. He is one of the key architects of the structure of EwE6. He is responsible for all-over design and quality assurance of EwE6, and handles database implementation, user interface design and implementation, spatial modeling aspects and model interoperability for EwE6. This fall, Jeroen is going to start his MSc thesis on providing Ecospace with a true spatial data interface. Jeroen built the Ecopath 25 Years website. Divya Varkey Divya Varkey is a PhD student at the Fisheries Center, University of British Columbia. Her research focuses on challenges for ecosystem-based management in Raja Ampat, Indonesia and New Zealand. She has built an ecosystem model for coral reefs in Raja Ampat using the Ecopath and Ecosim modeling approach. She is currently using Ecospace to model ecological changes inside marine protected areas especially looking at how size of the MPA influences the ecology inside the MPA. She is also involved in collating basic input parameters from 100 Ecopath models into broad functional groups to reduce parameter specification error for Ecopath models and the function of ‘mediation’ component in Ecosim to capture third party influences on food web interactions. 4 Ecopath 25 Years Conference Proceedings: Abstracts 5 Colette Wabnitz Colette Wabnitz is currently a PhD student at the Fisheries Center, University of British Columbia. Colette's main interests lie in marine conservation planning. Specifically, her research aims to: improve methods for gathering spatially explicit information on coastal habitats (e.g., coral reefs and seagrass), which includes the use of remote sensing; understand ecological processes that occur within coastal ecosystems using models (e.g. Ecopath with Ecosim); develop appropriate tools for the monitoring and planning of MPAs at multiple scales; and inform marine conservation policy development and assessment. Her PhD project seeks to derive an estimate of seagrass coverage at the scale of the wider Caribbean region and to understand the role of green sea turtles within these ecosystems. She received her BSc in Biology and Environmental Sciences from McGill University, Montreal. For her MSc in Tropical Coastal Management at the University of Newcastle upon Tyne, UK, she looked at the benthic composition and territory size of 5 species of parrotfishes in Belize under the supervision of Dr Peter Mumby. Acknowledgements ACKNOWLEDGEMENTS This conference was made possible through the support of the following sponsors: The Lenfest Foundation (www.lenfestfoundation.org) and the Pew Charitable Trusts (www.pewtrusts.org) contributed to the development of Ecopath with Ecosim. Magic Software Enterprises (www.magicsoftware.com) provided scientific cooperation in EwE’s development. The European Union’s International Cooperation Programme through the ECOST Project coordinated by Pierre Failler supported the conference through travel funds that enabled the participation of a number of developing country scientists. The Sea Around Us (www.seaaroundus.org) Project of the Fisheries Centre made possible the participation of some keynote speakers. The University of British Columbia made possible the participation of all members of the Fisheries Centre and contributed to the sustainable and organic food catering brought to participants of this conference. Abstracts submitted to this conference were reviewed by an international committee comprising of: Francisco Arreguín-Sánchéz, Elizabeth Fulton, Johanna J. Heymans, Steve Mackinson, Jeffrey Polovina, Lynne Shannon and Howard Townsend. We wish to thank Villy Christensen (Opening Session), Howard Townsend (Session I), Rob Ahrens (Session II), Marta Coll (Session III), Catherine Bulman (Session IV), Jason Link (Session V) and Jeffrey Polovina (Session VI and Closing Session) for agreeing to chair the sessions of this conference. Thanks are also due to: Daniel Pauly for his various comments and corrections and to Janice Doyle of the Fisheries Centre for copyediting these conference proceedings; Grace Ong and Marina Campbell of the Sea Around Us Project and Ann Tautz of the Fisheries Centre, who assisted with various administrative issues. Materials used in this conference, e.g., banners, name tags, bags, etc., were made possible with the professional help of Joann Glorioso, the WorldFish Center Philippine Office Events and Conference Coordinator, the SeaLifeBase Team and Mary Ann Bimbao of FIN who facilitated the exchanges between the WorldFish Center and the Sea Around Us Project. The conference flyer was designed by Danny Godfrey and the Ecopath visualization page for the banners by Mike Pan. Finally, the organizers wish to thank students and staff of the Fisheries Centre who volunteered to help out with the various and many tasks involved in making this conference run as smoothly as possible: Pamela Allen, Jonathan Anticamara, Laura Tremblay-Boyer, Eny Buchary, Andrew Dyck, Pramod Ganapathiraju, Joe Hui, Roseti Imo, Ruth Joy, Rajeev Kumar, Lingbo Li, Andrés Cisneros-Montemayor, Grace Pablico, Frankie Robertson, Ashley Strub, Wilf Swartz, Dawit Tesfamichael, Louise Teh, Lydia Teh and Pablo Trujillo.  6 Ecopath 25 Years Conference Proceedings: Abstracts ON BEING GREEN The Ecopath 25 Years Conference Organizing Committee made an attemp to be ‘ecological’ and to employ ‘sustainable’ resources by: (i) providing a website where documents relevant to the Conference, including electronic posters, can be viewed and/or downloaded, thus supporting a ‘paperless’ option; (ii) providing a ‘Notes’ section in these Conference Proceedings instead of separate paper blocks and/or notebooks; (iii) providing coffee mugs instead of paper cups; (iv) using silver and china instead of plastic forks, plastic glasses and paper plates; and (v) providing cheese-cloth bags to carry all Conference materials and other goodies in. Participants are thus requested to use the cloth bags and coffee mugs during the conference and the workshops. Please remember to bring your coffee mugs at coffee breaks or, if necessary, when buying coffee at the nearby cafés. The organizers will not provide paper or plastic coffee cups during these breaks. Participants are also urged to use the Notes section at the end of this Conference Proceedings instead of asking for separate block notes. The organizers will also refrain from providing extra paper during the conference and workshops. Food catering is brought to the Conference through the UBC Alma Mater Society Catering, which practices a strong commitment to sustainability. All coffees are certified organic, shade grown and Fair Trade. Dry goods are from local companies wherever possible and produce is purchased locally when in season. There are options on the AMS menu to include wild salmon and organic meats and produce in meal selections. They try to purchase local seasonal produce. They also work with an organic food broker to ensure best price possible for fruits and vegetables. On a smaller scale, they also support UBC's own organic farm. Their plastic and metal containers and any paper materials used in menu planning are recycled and all of the food waste from their menu preparation is composted, as is a large percentage of their post-consumer food waste. The AMS use non-disposable dishes, glassware and cutlery whenever feasible and their cleaning supplies are environmentally friendly.  7 Program: Oral Presentations PROGRAM: ORAL PRESENTATIONS VENUE All events are hosted at the Aquatic Ecosystems Research Laboratory (AERL) of the University of British Columbia located at 2202 Main Mall, between the newly built Beatty Biodiversity Centre and the Biological Sciences buildings. The registration desk will be located in the AERL Atrium (lobby). All conference sessions will be held in room 120 (east end) of the AERL. Oral presentors are requested to submit their PowerPoint presentations to their respective session Chairs within half a day before their sessions. Poster sessions will be concurrent with coffee and lunch breaks, which will be held in the Atrium. Authors with posters are requested to mount their posters on Monday, 31 August, 0830-1000 following the appropriate sessions which will be displayed on the panels. Please also remain near your posters during coffee and lunch breaks. Note that electronic posters will be printed on letter-sized paper and displayed together in one poster panel. They are also available at http://conference.ecopath.org/electronic-posters. Participants are encouraged to view these electronic posters and discuss with their authors via email. Three desktop computers will be made available to conference participants in AERL room 107/108 (west end). Note that wifi Internet access can be obtained through FatPort. Please inquire at the registration desk for details. SUNDAY, 30-08  1730-2030 Conference Registration MONDAY, 31-08  0830-1000 Conference Registration 0900-0915 Welcome Address, Chair: Villy Christensen DON BROOKS, Associate Vice President Research, University of British Columbia, Professor of Pathology and Laboratory Medicine and Chemistry USSIF RASHID SUMAILA, Director of the Fisheries Centre, Associate Professor, and Director of the Fisheries Economics Research Unit 0915-1015 Opening Session Keynotes, Chair: VILLY CHRISTENSEN 0915-0945 JEFFREY POLOVINA: The origins of Ecopath 0945-1015 DANIEL PAULY: Ecopath: from the French Frigate Shoals to the Philippines and to UBC 1015-1030 Coffee Break and Poster Sessions 1030-1230 Session I: Fisheries Applications, Chair: HOWARD TOWNSEND 1030-1100 Fisheries Applications Keynote CARL WALTERS: Foraging arena theory 1100-1115 DIDIER GASCUEL: EcoTroph: a new tool in the EwE family. 1115-1130 JIANG HONG: Exploring fisheries strategies for ecosystem-based management in the East China Sea. 1130-1145 SHINGO WATARI: Ecological effect of extermination of moonjelly, Aurelia aurita, in the sea of Suo-Nada, Seto Inland Sea, Japan. 8 Ecopath 25 Years Conference Proceedings: Abstracts 1145-1200 ROLAN GERONIMO: Capturing significant coral reef ecosystem and fishery changes in Bolinao, Philippines (1997-2008) using Ecopath with Ecosim. 1200-1215 ANDRES CISNEROS-MONTEMAYOR: Fisheries in Baja California Sur: a trophic-based analysis of management scenarios. 1215-1230 SYLVIE GUÉNETTE: Impact of fishing and climate on the Celtic Sea and the Bay of Biscay. 1230-1330 Lunch and Poster Session 1330-1530 Session II. Spatial Analysis, Chair: ROB AHRENS 1330-1400 Spatial Analysis Keynote STEVE MACKINSON: Ecospace: has its time come? 1400-1415 GEORGI DASKALOV: Evaluation of the usefulness of Marine Protected Areas (MPAs) for management of recovery of fish stocks and ecosystems in the North Sea. 1415-1430 HECTOR M. LOZANO-MONTES: Modelling spatial closures and fishing effort restrictions in Jurien Bay, Western Australia: a case study of the western rock lobster (Panulirus cygnus) fishery. 1430-1445 CAMILLE ALBOUY: Effectiveness of the natural reserve of the Bonifacio Straits (Corsica, France) on the artisanal and recreative fleets.  1445-1500 TYLER D. EDDY: Trophic modeling of a temperate marine ecosystem throughout marine reserve protection in New Zealand. 1500-1515 FRANK PARRISH: Estimating the carrying capacity of monk seals using the French Frigate Shoals Ecopath. 1515-1530 DIVYA VARKEY: Exploration of ecological and economic benefits from implementation of marine protected areas in Raja Ampat, Indonesia. 1530-1600 Coffee Break and Poster Session 1600-1800 Session III. Ecosystem Comp./Network Analysis, Chair: MARTA COLL 1600-1630 Ecosystem Comparisons/Network Analysis Keynote JOHANNA J. HEYMANS: Comparing indicators of ecosystem change using ecological Network Analysis. 1630-1645 LYNE MORISSETTE: Marine mammals – fisheries interactions: how to use Ecopath with Ecosim to capture ecological complexity. 1645-1700 JASON LINK: A simple approach for enhancing ecological networks and energy budgets (namely Ecopath): Please, let’s do some PREBAL before we start balancing. 1700-1715 VÍCTOR HUGO GALVÁN PIÑA: Comparison of trophic structures and key players for two periods in the continental shelf ecosystem of the central pacific of Mexico. 1715-1730 LUALHATI LACHICA-ALIÑO: Trophic flow structure of four overfished coastal ecosystems around the Philippines. 1730-1745 J. ERNESTO ARIAS-GONZÁLEZ: Relationship between biodiversity and ecosystem functioning in Mexican aquatic systems.   1900 Reception   9 Program: Oral Presentations TUESDAY, 01-09  0900-1130 Session IV. Climate Impact Evaluation, Chair: CATHERINE BULMAN 0900-0930 Climate Impact Evaluation Keynote ELIZABETH A. FULTON. Ecoworld: EwE one link in global systems model. 0930-0945 SIMONE LIBRALATO: Experiences in integrating physical-biogeochemical processes into food web dynamics with EwE.  0945-1000 CHRISTOPHER BROWN: Ecological interactions within marine ecosystems determine winners and losers under climate change.  1000-1015 Coffee Break and Poster Session 1015-1030 SHANE GRIFFITHS: Ecological effects of fishing and climate change on the pelagic ecosystem off eastern Australia. 1030-1045 CARIE HOOVER: Ecosystem effects of climate change in the Antarctic Peninsula. 1045-1100 DAVID PREIKSHOT: On the use of both unconventional and traditional time series data in constructing dynamic models of a marine ecosystem.  1100-1115 GLEN SUTTON: Development of an ecosystem model for Galveston Bay: Evaluating the influence of freshwater inflows, nutrient inputs and fisheries. 1115-1130 TORSTEIN PEDERSEN: Structure of two high latitude Norwegian fjord ecosystems analysed using Ecopath. 1130-1230 Lunch and Poster Session 1230-1445 Session V. Implementing EBM, Chair: JASON LINK 1230-1300 Implementing Ecosystem-based Management Keynote LYNNE SHANNON: How can EwE assist us in implementing ecosystem-based fisheries management? Drawing from the South African experience. 1300-1315 SERGIO NEIRA: Ecosystem approach to the mutispecies fishery in the south austral zone of Chile. 1315-1330 WILLIAM CHEUNG: Trade-offs between conservation and socio-economic objectives in managing a tropical marine ecosystem. 1330-1345 MARIA ESPINOSA: Supporting ecosystem based management on the West coast of Vancouver Island.  1345-1400 THOMAS A. OKEY: Progress in ranking species importance in whole biological communities using food web models. 14:00-14:15 JAMEAL SAMHOURI: Using ecological thresholds to inform targets for marine ecosystem-based management. 1415-1430 MARIA C. VILLANUEVA: Preservation: the case of the Meru National Park, Kenya. 1430-1445 DAWIT TESFAMICHAEL: Using Ecopath with Ecosim and local ecological knowledge to examine conflict between artisanal and industrial fisheries in the Red Sea. 1445-1500 Coffee Break and Poster Session           10 Ecopath 25 Years Conference Proceedings: Abstracts 11 1500-1715 Session VI. Ecopath with Ecosim and Beyond, Chair: JEFFREY POLOVINA 1500-1530 Ecopath with Ecosim and Beyond Keynote FRANCISCO ARREGUÍN-SÁNCHEZ. Use of EwE outputs to investigate attributes of trophic networks of aquatic ecosystems relevant to fisheries management. 1530-1545 SHERMAN LAI: EwE6: interoperability usage, capabilities, technology, structure and beyond. 1545-1600 LAURA TREMBLAY-BOYER: A global map of the relative impact of fishing on the biomass of marine ecosystems from 1950 to 2004. 1600-1615 JONATHAN BEECHAM: Dynamic linking of Ecosim and the GOTM biogeochemical model using plugins. 16:15-16:30 HOWARD TOWNSEND: Chesapeake Bay Fisheries Ecosystem Model: Computer- generated graphics for creating a gaming experience with ecosystem data and management.  1630-1645 JULIA EKSTROM: MINOE: open source tool to navigate ocean governance in the context of a user-defined ecosystem. 1645-1700 MANUEL ZETINA REJÓN: Revealing changes in fish community at ecosystem level: using of trophic modelling and topological analysis. 1700-1715 KIM DE MUTSERT: Using Ecopath with Ecosim to explore nekton community responses to freshwater input from a Mississippi River diversion in Breton Sound, Louisiana. 1715-1815 Closing Session 1715-1745 Final Keynote VILLY CHRISTENSEN: The future of Ecopath. 1745-1815 Discussion and election of venue for the next EwE conference.  List of Poster Presentations LIST OF POSTER PRESENTATIONS SESSION I. FISHERIES APPLICATIONS VARGIU, G., COLL, M., PALOMERA, I., TUDELA, S. Recovery scenarios of a highly exploited species, Merluccius merluccius, in the NW Mediterranean Sea using an ecosystem approach. CHENG HE QIN, JIANG HONG. Thinking on the transfer payment of the fishery fuel subsidies in China. ARREGUÍN-SÁNCHEZ, F., SALCIDO-GUEVARA, L.A. Vulnerability to fishing off the Central Gulf of California ecosystem. PIRODDI, C., BEARZI, G., CHRISTENSEN, V. Effects of local fisheries and ocean productivity on the Northeastern Ionian Sea ecosystem. BULMAN, C., CONDIE, S., KLAER, N., FURLANI, D., CAHILL, M., GOLDSWORTHY, S., KNUCKEY, I. Trophodynamic modeling of the Eastern Shelf and Slope of the South East Fishery. CHIN, C.P., SUN, C.L., LIU, K.M. The impacts of longline fishery on the pelagic ecosystem in the eastern Taiwan waters. POONSAWAT, R., SUPONGPAN, M., CHRISTENSEN, V. Introducting ecosystem-based management in the Gulf of Thailand. FETAHI, T., MENGISTOU, S. Trophic analysis of Lake Awassa (Ethiopia) using mass-balance Ecopath model. SESSION II. SPATIAL APPLICATIONS PARK, C.R., KIM, E., KANG, C.W., LEE, S.B. Habitat suitability model for the bush warbler (Cettia diphone) at Jeju Experimental Forests of Korea. SESSION III. ECOSYSTEM COMPARISONS SALCIDO-GUEVARA, L., ARREGUÍN-SÁNCHEZ, F. Metabolism of aquatic ecosystems. KHAN, A. A fish chain analysis of Northern Gulf Cod recovery options using EwE modeling approach. TSAGARAKIS, K., COLL, M., GIANNOULAKI, M., KALLIANIOTIS, A., PAPAKONSTANTINOU, C., MACHIAS, A. Ecosystem structure and functional traits of the N. Aegean Sea (E. Mediterranean, Greece). SESSION IV. CLIMATE IMPACT EVALUATION NEIRA, S., MOLONEY, C., CURY, P., MULLON C., CHRISTENSEN V. Mechanisms affecting recovery in an upwelling food web: the case of the southern Humboldt. LEGAGNEUX, P., GAUTHIER, G., KREBS, C.J. Spatial and temporal trophic dynamics of terrestrial arctic ecosystems SESSION V. IMPLEMENTING ECOSYSTEM-BASED MANAGEMENT WABNITZ, C., BJORNDAL, K.A., BOLTEN, A.B., CHRISTENSEN, V., PAULY, D. Restoration of Chelonia mydas population in the Caribbean: Ecosystem impacts resulting from reduction of seagrass habitat complexity. COLL, M., LIBRALATO, S. Modelling marine food webs in the Mediterranean Sea. TOWNSEND, H., BAUER, M., BROWN, L. A preliminary model of the San Francisco estuary ecosystem. 12 Ecopath 25 Years Conference Proceedings: Abstracts 13 SESSION VI. ECOPATH WITH ECOSIM AND BEYOND STEENBEEK, J., CHRISTENSEN, V. Using true GIS data with Ecospace. PIRODDI, C., VARKEY, D., MORISSETTE, L., CHRISTENSEN, V. Production and consumption in Ecopath models: A global overview. COLL, M., PIRODDI, C., PALOMERA, I., ARNERI, E., CHRISTENSEN, V. Main drivers of marine resources and food-web changes in the Mediterranean Sea. VILLASANTE, S., GARCÍA-NEGRO, M.C., RODRÍGUEZ RODRÍGUEZ, G., VILLANUEVA, M.C., CHRISTENSEN, V., SUMAILA, U.R. A preliminary trophic model of coastal fisheries resources of the Patagonian marine ecosystem LINK, J.S., PRANOVI, F., COLL, M., LIBRALATO, S., CHRISTENSEN, V., LEGAULT, C. Exploring novel metrics of ecosystem overfishing using energy budget model outputs. KREBS, C.J., KENNEY, A.J., GAUTHIER, G. Why not Ecopath for terrestrial ecosystems? PALOMARES, M.L.D., BAILLY, N., PAULY, D. FishBase, SeaLifeBase and database-driven ecosystem modelling. ELECTRONIC POSTERS DUARTE, L.O. Exploring the effects of MPA’s in a tropical marine ecosystem. A multi-species and multi- gear fishing case. MOTTA CARDOSO, A., DE ALMEIDA TUBINO, R., MONTEIRO-NETO, C. Preliminary Ecopath model of Itaipu Lagoon, Niteroi, Rio de Janeiro, Brazil. DE ALMEIDA TUBINO, R., MONTEIRO-NETO, C., EDUARDO MORAES, L., TAVARES PAES, E. Trophic model for an artisanal fishery system in southeastern Brazil. WATERMEYER, K.E., SHANNON, L.J., ROUX, J.P., GRIFFITHS, C.L. Changes in the trophicstructure of the northern Benguela before and after the onset of industrial fishing. WATERMEYER, K.E., SHANNON, L.J., GRIFFITHS, C.L. Changes in the trophicstructure of the southern Benguela before and after the onset of industrial fishing. ADDENDUM Hossain, M.M., Matsuishi, T., Arhonditsis, G. Elucidation of ecosystem attributes using Ecopath with Ecosim (EwE): application to an oligotrophic lake in Hokkaido, Japan.   Keynote speakers KEYNOTE SPEAKERS JEFFREY POLOVINA DrJeffrey Polovina is the Acting Director at the Pacific Islands Fisheries Science Center. His work includes research in biological oceanography in the Central and Western Pacific with focus on population dynamics of high trophic animals. Currently he is involved in developing indicators from satellite remotely sensed oceanographic data to monitor the state of the Pacific Ocean and in describing migration and "oceanic hot spots" used by large pelagic animals including turtles, tunas, opah, and whale sharks by sending out fleets of pelagic animals with electronic tags. In the early 1980s, Dr. Polovina and his colleagues at the National Marine Fisheries Service, Honolulu Laboratory, developed the innovative marine ecosystem model known as Ecopath. Named to convey its focus on ecological pathways, it was the first model to apply a type of statistics called “path analysis” to the field of marine ecology. At the conference Dr. Polovina will describe research context that led to the origin of Ecopath. DANIEL PAULY After many years at the International Center for Living Aquatic Resources Management (ICLARM), in Manila, Philippines, Daniel Pauly became in 1994 Professor at the Fisheries Centre of the University of British Columbia, Vancouver, Canada, of which he was the Director for 5 years (Nov. ’03-Oct. ’08). Since 1999, he is also Principal Investigator of the Sea Around Us Project (see www.seaaroundus.org), funded by the Pew Charitable Trusts, Philadelphia, and devoted to studying, documenting and promoting policies to mitigate the impact of fisheries on the world’s marine ecosystems. The concepts, methods and software which Daniel Pauly (co-)developed, documented in over 500 scientific and general-interest publications, are used throughout the world, not least as a result of his teaching a multitude of courses, and supervising students in four languages on five continents. This applies especially to the Ecopath modeling approach and software (www.ecopath.org) and FishBase, the online encyclopedia of fishes (www.fishbase.org). CARL J. WALTERS Dr Walters is a Professor at the Fisheries Centre whose areas of research include the development of rapid techniques for teaching systems analysis and mathematical modeling to biologists and resource managers. A member of several of NSERC's grant committees since 1970, he has done extensive fisheries advisory work for public agencies and industrial groups. He has also conducted over two dozen three to ten day workshops in the past decade, for the International Canadian Fisheries Service, US Fish and Wildlife Service and the International Institute for Applied Systems Analysis.He is the editor of The Open Fish Journal and has been on the editorial boards of the Journal of Applied Mathematics and Computation, the Northwest Environmental Journal, the Canadian Journal of Fisheries and Aquatic Sciences, and Marine and Coastal Fisheries. Dr. Walters is a Fellow of The Royal Society of Canada. STEVE MACKINSON Dr Steve Mackinson is a scientist at the Centre for Environment, Fisheries and Aquaculture Science. At CEFAS, he has been involved in Ecopath with Ecosim modeling and study of trophic transfer efficiencies in food-webs of North Sea. He has also worked on issues of model complexity and effects of model structure for the Ecopath and Ecosim modeling approach.  Dr Mackinson’s research efforts also extend beyond the strict ecosystem modeling specialty into socio-economic drivers of fisheries management. He has worked on perceptions of the fishing industry and has elucidated measures to bridge gaps between science and stakeholders. JOHANNA J. HEYMANS Dr Johanna J. Heymans is a lecturer with the Ecology department of the Scottish Association for Marine Science. She has worked extensively with Ecopath with Ecosim and Ecological Network Analysis and is very interested in the use of these tools for marine spatial planning as well as ways to combine ecological and social network analysis for ecosystem based management. She is currently working on sustainable management of deep-water fisheries and their impact on marine biodiversity. Previously she worked at the Fisheries Centre on several ecosystem models for the east and west coast of Canada, the decline of Steller sea lions and a historical reconstruction for the Bird’s Head functional seascape in Eastern Indonesia. 14 Ecopath 25 Years Conference Proceedings: Abstracts 15 ELIZABETH FULTON Dr Elizabeth Fulton leads a marine ecosystem modelling team based at CSIRO Marine and Atmospheric Research in Hobart, Tasmania, Australia. She is the developer of the marine ecosystem model ‘Atlantis’ which is used to provide strategic advice to the Australian Fisheries Management Authority concerning the Southern and Eastern Scalefish and Shark Fishery. It has also been applied to 15 marine ecosystems in Australian and United States waters. As well as developing Atlantis, Dr Fulton is a co-developer of the InVitro modelling framework, which allows simultaneous consideration of multiple uses of the marine environment including:  oil and gas, transport, tourism, commercial and recreational fishing. InVitro is being used to evaluate regional marine plans as part of Australia’s Oceans Policy. For her leadership in mathematics and ecosystem modelling, she received the 2007 Science Minister's Prize for Life Scientist of the Year. LYNNE SHANNON Dr Lynne Shannon is a Senior Researcher at the Marine Research Institute, University of Cape Town. She has worked on modeling the Southern Benguela ecosystem and has published several papers on the response of fish populations in the Southern Benguela ecosystem to fisheries and environmental change. In addition, she has published on a wide range of topics that include implications of chlorophyll distribution on pelagic fisheries, regime shifts in the ocean, trophodynamic indicators, viability theory for ecosystem approach and the functioning of marine ecosystems. Her current research involves measures to evaluate the ecological status of world’s fished marine ecosystems. FRANCISCO ARREGUÍN-SÁNCHEZ Dr. Francisco (Paco) Arreguin Sánchez is the Director of the Centro Interdisciplinario de Ciencias Marinas del IPN (Center of Interdisciplinary Marine Sciences of the Polytechnic Institute). He has more than 20 years of experience working in the Gulf of Mexico on fishery-related problems. He has worked on ecosystem models for Senegambian Ecosystem, East China Sea, Gulf of Mexico and Gulf of California. His recent publication explores ecosystem-based harvesting strategies to recover the collapsed pink shrimp. He also participates as a professor in the masters program of "Management of Marine Resources" and in the doctorate program of Marine Sciences, as well as in several research projects. VILLY CHRISTENSEN Dr Villy Christensen is a scientist at the Fisheries Center, University of British Columbia. He works with ecosystem modeling and has a background in fisheries research. His research has since 1990 been centered on understanding impacts of human exploitation on marine ecosystems. He has been central to the development and dissemination of the Ecopath approach and software, a tool for ecosystem modeling.  Ecopath modeling has become the de-facto standard for ecosystem approaches to fisheries management, and is being applied throughout the world. There are more than 350 derived models and publications, and more than 6000 registered users in 150 countries.  Through cooperation with scientists worldwide, he has focused on trophic dynamics of aquatic resources. He has led a large number of training courses and workshops throughout the world, centered on developing ecosystem approaches to fisheries management. His current focus is on communication of science and improving its contribution to the decision-making process. This involves use of advanced gaming technology and visualizations combined with research on the decision-making process. Opening Session – Polovina OPENING SESSION THE ORIGINS OF ECOPATH1 JEFFREY POLOVINA Ecosystem & Oceanography Division, Pacific Islands Fisheries Science Center NOAA Fisheries, 2570 Dole St., Honolulu, Hawaii 96822-2396; jeffrey.polovina@noaa.gov It is truly an honor to present an opening keynote talk at Ecopath 25 Years. It is fantastic to see the tremendous growth in the Ecopath community over the past quarter century and I think some of the newer members might enjoy learning some historical background on the development of Ecopath. In 1975 a decade-long research program was initiated and directed by a consortium of agencies initially composed of the State of Hawaii, National Marine Fisheries Service (NMFS), and US Fish and Wildlife and joined several years later by the University of Hawaii. The objective of the program was to assess the marine resources and ecology of the Northwestern Hawaiian Islands for purposes of protecting unique wildlife and managing potential fishery resources. While much of the research effort was distributed across the 1000 km chain of atolls, banks, and seamounts, the program leaders had the vision to identify one atoll, French Frigate Shoals (FFS), as a site to simultaneously study all the major components of the food web. As the ecosystem study of FFS progressed it was recognized that there was a need to have some quantitative framework to build an ecosystem synthesis. In 1979, I was hired at NMFS and one of my duties was to build an ecosystem model for FFS. I soon learned about the ecosystem modeling work of Dr. Taivo Laevastu at the Alaska Fisheries Science Center, NMFS and initially thought I might use his model for FFS. However I quickly recognized that the complexity of his model required a quantitative understanding of the coral reef ecosystem that we were far from achieving and a simpler model was needed. At FFS, there were over a dozen researchers studying components of the ecosystem ranging from the apex predators such as tiger sharks and monk seals to benthic productivity at the base of the food web and having this team of experts to consult and provide parameter estimates was a key factor in the development of the FFS Ecopath model. In the early 1980s, as I was developing the model, Dr. Daniel Pauly would occasionally visit the Honolulu Laboratory. Once he learned about the model, he recognized its potential in applications to many ecosystems and his enthusiasm for the model provided additional momentum for me to complete the work. In 1984 colleagues and I published a series of 3 papers in Coral Reefs: the first described the Ecopath model and its application to FFS; the second compared the model’s estimate of benthic primary productivity to an independent field estimate as a test of the model; and the third discussed the ecology and management of coral reef ecosystems based on the FFS Ecopath model. Thus in summary, the initial development of Ecopath was a community effort and it is very satisfying to see, a quarter of a century later, that community has grown and is thriving. I’m confident that the outcomes from this gathering will set the stage for Ecopath 50 years!                                                  1 Cite as: Polovina, J., 2009. The origins of Ecopath. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 16. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 16 Ecopath 25 Years Conference Proceedings: Abstracts ECOPATH: FROM THE FRENCH FRIGATE SHOALS TO THE PHILIPPINES AND TO UBC1 DANIEL PAULY The Sea Around Us Project, Fisheries Centre, UBC 2202 Main Mall, Vancouver BC V6T 1Z4, Canada; d.pauly@fisheries.ubc.ca In the early 1980s, the emphasis of most researchers on tropical fisheries, both local and foreign experts, was on applying to exploited fish stocks, and further developing the methods then becoming available for data-sparse situations, length-based stock assessment methods (see, e.g., contributions in Pauly & Morgan, 1987; Roedel & Saila, 1980). It was already becoming clear, however, that single-species approaches were not adequate in the tropics, because the target species, if there even was one, represented an even smaller fraction of the total catch (e.g., of trawlers) than in temperate waters (Pauly, 1979). Hence, applying the then standard yield per recruit (Y/R) models yielded essentially useless solutions (see e.g., Pauly & Martosubroto, 1980). The extension of single-species Y/R to a number of stocks, which for a while became known as ‘multi- species modeling’, while straightforward in principle, and successfully applied to a few fisheries turned out to be too unwieldy to be used routinely (Munro, 1980), despite several attempts at revivals. Also, this approach did not make use of the fact that a large number of fisheries biologists in the tropics, as in temperate areas, were collecting huge amounts of stomach content data with at least the tacit expectation that such data might be useful for some sort of understanding of the role of exploited species within ecosystems (see, e.g., bibliography in Pauly, 1982). I was then based in Manila, the Philippines, and worked at the International Center for Living Aquatic Resources Management, or ICLARM (which despite its unwieldy name was at the time a powerhouse of new ideas), deeply engaged in these research initiatives, including teaching the methodologies they generated (see Venema et al., 1988). This included attempting to organize ecosystem biomass flow estimates into functional groups linked by feeding arrows, a technique I had used earlier (Pauly, 1979, 1982) and taught to others (see, e.g., Yap, 1983). Thus, my mind was ready for Ecopath (Polovina, 1984a, 1984b), whose gradual development I was following through frequent visits to Jeff Polovina in Hawaii. Indeed, I encouraged him to make the code of Ecopath available, so others could follow up on it. He took the advice (Polovina & Ow, 1983; see Polovina, 1993), and I began to apply, use and teach it to other people, notably to visitors and colleagues who came to ICLARM, like Ms. Yap Siaw-Yang earlier, to learn fish stock assessments and, more pertinently, what had turned from multispecies into ecosystem modeling. This led to some additions to Polovina’s Ecopath software, most, however, dealing with the inputs to Ecopath and the interpretation of its outputs. In particular, I realized that Ecopath would be a straightforward way of parameterizing the network approach then launched by Ulanowicz (1986). The first application of this insight was to the Peruvian upwelling system (Pauly, 1987). This work lead to the reprogramming of Ecopath by Ms. Mina Soriano, and the development of ‘Ecopath II’, providing more outputs than the original version. Ecopath II was presented at a workshop in Kuwait, in December 1987. However, the first version of the paper documenting this was destroyed, along with much of the assets of Kuwait Institute of Scientific Research during the subsequent invasion of Kuwait by Iraqi forces; it was included in a book published in the early 1990s (Pauly et al., 1993). The work documented above having established the potential of Ecopath in assembling and harmonizing previously underutilized data, I convinced the then Director-General of ICLARM, Ian Smith, to reserve the                                                  1 Cite as: Pauly, D., 2009. Ecopath: from the French Frigate Shoals to the Philippines and to UBC. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts pp. 17-19. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 17 Opening Session – Pauly position then offered by the Danish international development agency (DANIDA) for a modeler who could take over our Ecopath work. I met young Villy Christensen during a trip to Kiel in 1989, and he was hired. Villy quickly reprogrammed Ecopath II, and released it in the summer of 1990. We could then jointly prepare the extremely successful poster session at ICES in 1990, in which tropical countries were for the first time dominant at an ICES event, and which we documented in a book (Christensen & Pauly, 1993). As well, Villy documented our software, which led to a detailed manual (Christensen & Pauly, 1991), of which numerous updates and translations (in French and Spanish) were subsequently published. Also, he was the lead author of a paper (Christensen & Pauly, 1992), which anchored Ecopath II in the peer-reviewed literature, and which today stands as the third-most cited paper published in the key journal Ecological Modelling. The mid-1990s were a period of consolidation and expansion, where we simultaneously defended the logic of Ecopath – then still much contested – in various fora, and applied it to numerous ecosystem types, often in the context of training courses in many countries on all continents. This is also the time where colleagues in Mexico (F. Arreguin-Sanchez), France (J. Moreau with M.L. Deng Palomares) and others elsewhere began to support the use of the approach and software independently. Also, the trophic levels that were being estimated, and other insights gained through various Ecopath applications, were used in a high profile publication (Pauly & Christensen, 1995). But what contributed most to Ecopath ‘breaking through’ was the development of Ecosim by C.J. Walters, a result of his participating at the Ecopath workshop, documented in Christensen & Pauly (1996), i.e., in the first of many Fisheries Centre Research Reports devoted to Ecopath and related issues. This workshop, held in November 1995, was a result of my transition (September 1994) to the University of British Columbia, and the first in which models were built by a team, whose members were responsible for different functional groups, thus allowing more expertise to be incorporated into the resulting model. Walters (1996), however, saw Ecopath not as an end product, but as the starting point for dynamic simulation, which first included Ecosim (Walters et al., 1997), then later Ecospace (Walters et al., 1998). What happened then is best told by Villy. REFERENCES Christensen, V., Pauly, D. (Editors). 1993. Trophic models of aquatic ecosystems. ICLARM Conference Proceedings No. 26, 390 p. Christensen, V., Pauly, D., 1991. A guide to the ECOPATH II software system. ICLARM Software 6, 71 p. Munro, J.L., 1980. Stock assessment in the tropics: applicability and utility in tropical small-scale fisheries. In: Saila, S.B., Roedel, P.M. (eds.), Stock Assessment for Tropical Small-Scale Workshop, Sept. 19-21 1979, University of Rhode Island, p. 35-47. International Center for Marine Resources Development, Kingston. Pauly, D., 1979. Theory and Management of Tropical Multispecies Stocks: a Review, with Emphasis on the Southeast Asian Demersal Fisheries. ICLARM Studies and Reviews 1, 35 p. Pauly, D., 1982. Notes on tropical multispecies fisheries, with a short bibliography on the food and feeding habits of tropical fish. In: Report of the Regional Training Course on fisheries stock assessment, Samutprakarn, Thailand, 1 Sept. - 9 Oct. 1981, Part II, Vol. 1, , p. 30-35 and 92-98. SCS/GEN/82/41 South China Sea Fisheries Development and Coordinating Program, Manila. 238 p. Pauly, D., 1987. Managing the Peruvian upwelling ecosystem: a synthesis. In: Pauly, D., Tsukayama, I. (eds.), The Peruvian Anchoveta and its Upwelling Ecosystem: Three Decades of Change, p. 325-342. ICLARM Studies and Reviews 15. Pauly, D., Morgan, G.R. (Editors), 1987. Length-based Methods in Fisheries Research. ICLARM Conference Proceedings 13, 468 p. Pauly, D., Martosubroto, P., 1980. The population dynamics of Nemipterus marginatus (Cuv. & Val.) off Western Kalimantan, South China Sea. J. Fish Biol. 17, 263-273. Pauly, D., Christensen, V. (Editors), 1996. Mass-Balance Models of North-Eastern Pacific Ecosystems. Fisheries Centre Research Reports 4(1), 131 p. Pauly, D., Christensen, V., 1995. Primary production required to sustain global fisheries. Nature 374, 255-257. Pauly, D. Soriano-Bartz, M.L., Palomares, M.L.D., 1993. Improved construction, parametrization and interpretation of steady-state ecosystem models. In: Christensen, V., Pauly D. (eds.), Trophic Models of Aquatic Ecosystems, p. 1-13. ICLARM Conference Proceedings No. 26. Polovina, J.J., 1984a. An overview of the Ecopath model. FishBytes (ICLARM) 2(2), 5-7. Polovina, J.J., 1984b. Model of a coral reef ecosystem. I. the ECOPATH model and its application to French Frigate Scool. Coral Reefs 3(1), 1-11. Polovina, J.J., 1993. The First Ecopath. In: Christensen V., Pauly D. (eds.), Trophic Models of Aquatic Ecosystems, p. vii-viii. ICLARM Conference Proceedings No. 26. 18 Ecopath 25 Years Conference Proceedings: Abstracts 19 Polovina, J.J., Ow, M.D., 1983. ECOPATH: A User’s Manual And Program Listing. National Fisheries Sevice, NOAA, Honolulu. Admin. Rep. H-83-23, 46 p. Saila, S.B., Roedel, P.M. (Editors), 1980. Stock Assessment for Tropical Small-Scale Workshop, Sept. 19-21 1979, University of Rhode Island. International Center for Marine Resources Development, Kingston. Ulanowicz, R.E., 1986. Growth and Development: Ecosystem Phenomenology. Springer-Verlag, New York, 203 p. Venema, S., Möller-Christensen, J., Pauly, D. (Editors), 1988. Contributions to Tropical Fisheries Biology: Papers by the Participants of FAO/DANIDA Follow-up Training Courses. FAO Fisheries Report No. 389. 519 p. Walters, C.J., 1986. Suggested improvements for Ecopath modelling. In: Pauly D., Christensen, V. (eds.), Mass-Balance Models of North-Eastern Pacific Ecosystems. p. 82-86. Fisheries Centre Research Reports 4(1). Walters, C., Christensen, V., Pauly, D., 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Rev. Fish Biol. Fish. 7(2), 139-172. Walters, C., Pauly, D., Christensen, V., 1998. 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. Yap, Siaw-Yang, 1983. A holistic, ecosystem approach to investigating multispecies reservoir fisheries. Naga, The ICLARM Quarterly 6(2), 10-11. Fisheries Applications – Walters et al. FISHERIES APPLICATIONS: ORAL PRESENTATIONS FORAGING ARENA THEORY1 CARL J. WALTERS VILLY CHRISTENSEN ROBERT AHRENS Fisheries Centre, University of British Columbia, Vancouver, B.C. V6T1Z4 Canada; c.walters@fisheries.ubc.ca; v.christensen@fisheries.ubc.ca; r.ahrens@fisheries.ubc.ca Foraging arena theory argues that trophic interactions in aquatic ecosystems occur largely in spatially and temporally restricted arenas, such that interaction rates can be severely limited by exchange rates of prey into and out of these arenas. Foraging arenas are created by a wide range of mechanisms, ranging from restrictions of predator distributions in response to predation risk caused by their own predators, to risk- sensitive foraging behaviour by their prey. Foraging arenas partition the prey in each predator-prey interaction in a food web into vulnerable and invulnerable states, with exchange between these states potentially limiting overall trophic flow. Whenever any one species exhibits spatially restricted foraging, two foraging arena structures and vulnerability exchange processes are created: between the species and its predators, and between the species and its prey (since the species no longer occupies the full habitat that its prey may use). Inclusion of vulnerability exchange processes in models for recruitment processes and food web responses to disturbances like harvesting leads to very different predictions about dynamic stability, trophic cascades, and maintenance of ecological diversity than do models based on large-scale mass action (random mixing) interactions between prey and predators. Incorporation of foraging arena vulnerability exchange calculations into Ecosim models has been the main reason for success of Ecosim at representation of dynamic behaviour for many aquatic ecosystems, as judged by ability of Ecosim models to fit historical time series data. Three main challenges for future development of Ecosim are: (1) development of software and protocols for using it to recover estimates of historical, unfished ecosystem states by using a stock reduction analysis approach with historical catch and relative abundance data; (2) representation of changes in trophic interactions due to meso-scale spatial changes in species distribution patterns associated with thermal and hydrodynamic regime shifts caused by climate change; and (3) representation of the highly nonlinear dynamics associated with ecosystem regime shifts and multiple stable states, which can be created by cultivation-depensation effects and other size-dependent interaction patterns.                                                  1 Cite as: Walters, C.J., Christensen, V., Ahrens, R., 2009. Foraging arena theory. In: Palomares, M.L.D., Morissette, L., Cisneros- Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 20. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 20 Ecopath 25 Years Conference Proceedings: Abstracts ECOTROPH: A NEW TOOL IN THE EWE FAMILY1 DIDIER GASCUEL MELEN LECLERC AUDREY VALLS SYLVIE GUÉNETTE Université Européenne de Bretagne, Pole halieutique AGROCAMPUS OUEST UMR Ecologie et Santé des Ecosystèmes, Rennes, France; Didier.Gascuel@agrocampus-ouest.fr EcoTroph is proposed as a plug-in module of EwE version 6, providing a simplified picture of ecosystem functioning. It allows users to represent the distribution of the ecosystem biomass as a function of trophic levels, and to analyse or simulate fishing impact in a very synthetic way (Gascuel et al., 2009). In the EcoTroph approach, the biomass per trophic group and the catch per fishery is represented as a distribution over trophic levels, assuming that the distribution of the biomass (or production, or catch) of a trophic group around its mean trophic level follows a lognormal curve. The Biomass (or production, or catch) Trophic Spectrum is the curve obtained by summing all biomasses across trophic groups. This representation provides a very synthetic overview of an ecosystem and may help users to think at that scale. Thus, trophic ecosystem functioning can be modelled as a continuous flow of biomass surging up the food web, from lower to higher trophic levels, because of predation and ontogenetic processes (Figure 1). 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Trophic level Re lat ive  bi om as s Biomass flow Predation Ontogeny Grazing Primary Production Detritus recycling 1.0 Re lat ive  bi om as s  Figure 1. Diagram of the trophic functioning of an ecosystem, in EcoTroph: theoretical distribution of the biomass by trophic level and trophic transfer processes (from Gascuel et al., 2009). We illustrate the usefulness of such an approach, based on three distinct case studies. The first case study, Guinean ecosystem, is used to illustrate how EcoTroph provides diagnostic tools for assessing the impact of fishing. Based on a previously built Ecopath model, we estimated the biomass and the catch trophic spectrum related to the current state of the ecosystem (i.e., for the year 2004), and we simulated changes in fishing pressure by using multipliers of the fishing mortality values of 0-5 and applied to the whole ecosystem (Gascuel et al., 2008). We show that the current fishing effort led to a 3-fold decrease in biomass of higher trophic levels, compared to the unexploited ecosystem (multiplier of 0; Figure 2, left panel). The decrease in abundance of these high trophic level groups is a consequence of their over-exploitation (Figure 2, right panel) and a significant decrease in the mean trophic level of both the total biomass and the catches. These results confirm and generalize previous single species assessments. Forecasting suggests that higher yields might be obtained by exploiting lower trophic levels, but this would result in a higher impact on the ecosystem and a qualitative degradation of the ecosystem’s health.                                                  1 Cite as: Gascuel, D., Leclerc, M., Valls, A., Guénette, S., 2009. EcoTroph, a new tool in the Ecopath family. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 21-22. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727]. 167 p. 21 Fisheries Applications – Gascuel et al. 22 0.01 0.10 1.00 10.00 100.00 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Trophic level TL Bio ma ss  pe r tr op hic  cl as s ( t/K m2 ) Biomass trophic spectra Increasing fishing efforts 0.0 1.0 2.0 3.0 0.0 1.0 2.0 3.0 4.0 5.0 Fishing effort multiplier Re lat ive  ca tch  in  th e t rop hic  cl as s TL 3.0 TL 3.5 TL 4.0 TL 4.5 TL 5.0 Relative change in catch Figure 2. Simulation of the impact of increasing fishing effort in the Guinean ecosystem. Left panel: simulated catches (relative values) expressed as a function of the multiplier of the current fishing mortality. Right panel: impact on the biomass trophic spectrum (dashed lines represent the ‘current’ situation).  The second case study, the Port-Cros French National park in the Mediterranean Sea, illustrates how EcoTroph may highlight, in a simple way, differences in the ecosystem functioning resulting from the presence of a Marine Protected Area (MPA). In this case study, an Ecopath model was first built using all available information. EcoTroph is used as a tool for the graphical representation of the Ecopath model and to simulate various scenarios, i.e., from a total ban of fishing to the release of all protection currently in force in the MPA. We show that protection leads to a change not only in the biomass trophic spectrum characterizing this ecosystem, but also in the production trophic spectrum and in the functional biodiversity as well. Finally, we used EcoTroph as a tool for comparison of various ecosystems and to conduct a meta-analysis on a global scale. We considered 57 Ecopath models, recently published and referring to contrasting case studies in terms of ecosystem size, latitude, mean depth, productivity, etc. For each model, biomass, production and catch trophic spectra were built. Then, ecosystems were classified in various types of ecosystem functioning according to their spectra characteristics. Various patterns of the exploitation of ecosystems were also defined and their impact on biomass and production trophic spectra was analysed. We conclude that, within the EwE family of models, EcoTroph may be regarded as constituting the ultimate stage in the use of the trophic level metric. In this type of model, calculations are based on each trophic level instead of on species or functional group as used in EwE. The representation, thus provided, constitutes a simplified and useful caricature of the functioning of real ecosystems. REFERENCES Gascuel, D., Boyer-Tremblay, L., Pauly, D., 2009, EcoTroph: a trophic-level based software for assessing the impact of fishing on aquatic ecosystems. Fisheries Centre Research Reports 17(1), Fisheries Centre, University of British Columbia, Vancouver, 82 p. Gascuel D., Guénette S., Pauly D., 2008, The trophic-level based ecosystem modelling approach: theoretical overview and practical uses. ASC-ICES CM 2008 / F:18, Septembre 2008, Halifax (Canada), 16 p.  Ecopath 25 Years Conference Proceedings: Abstracts EXPLORING FISHERIES STRATEGIES FOR  ECOSYSTEM-BASED MANAGEMENT IN THE EAST CHINA SEA1 JIANG HONG CHENG HE QIN State Key Laboratory of Estuarine and Coastal Research, East China Normal University,  North Zhongshan Rd., Shanghai, 200062, China; hongjiang0822@yahoo.com.cn; hqch@sklec.ecnu.edu.cn FRANCISCO ARREGUIN-SANCHEZ  Centro Interdisciplinario de Ciencias Marinas, CICIMAR, del Instituto Politécnico Nacional, Apartado Postal 592, La Paz, 23090, Baja California Sur, Mexico; farregui@ipn.mx The East China Sea (ECS) is a semi-enclosed marginal sea with a wide continental shelf. Large quantities of land-based nutrients and pollutants along with large fresh water inputs mainly from the Changjiang (Yangtze) river system coupled with the ocean current system contribute to a rich fish fauna, with about 700 fish species, and rick offshore fishing grounds exploiting about 20 highly valued species. The wide continental shelf waters of the ECS supported various commercial and recreational fisheries for China, Japan and South Korea. However, heavy fishing pressure exerted on commercial stocks over the last few decades resulted in a significant change in fishery resources, i.e., high value and low volume traditional species are now overfished and marine catches are composed of smaller, younger, lower trophic level and immature fish (Zhang et al., 2007;Chao et al., 2005). There is wide-spread agreement that fisheries need to be managed with consideration of overarching goals, e.g., restoring and maintaining healthy ecosystems and fisheries (FAO 1995, Garcia & Staples 2000), i.e., Ecosystem Based Fishery Management (EBFM) or Ecosystem Approach to Fisheries. This is currently being implemented in many countries’ legislation. EBFM aims to minimize: (i) direct impact on the environment such as caused by destructive gears; and (ii) impact on species composition, abundances, and size (age) structures of populations. Ecosystem models play an important role in the ecosystem approach to fisheries (Araújo et al., 2008), notably In: (i) identifying potential changes in complex systems that cannot be identified with single-species models; (ii) revealing otherwise unknown system properties; (iii) improving knowledge about specific parts of the ecosystem; (iv) “testing” the compatibility of data sets; and (v) serving as a basis for the elaboration and/or exploration of scientific hypothesis about system dynamics and functioning (Araújo et al., 2006; Fulton & Smith, 2004; Walters & Martell, 2004; Christensen & Pauly, 1998; Vasconcellos et al., 1997). The Ecopath with Ecosim (EwE) software (Christensen et al., 2005) is currently the most used and tested ecosystem modelling tool for addressing these issues and in finding a balance between economic and social benefits within the framework of ecosystem conservation in regional fisheries management (Arreguín-Sánchez et al., 2004). The aim of this work is to explore fishery management strategies to optimize current exploitation of fishery resources in the ECS on economic, social and ecological objectives by using a fishing policy optimization routine in a EwE model. The simulations presented here span a period of 11 years based on fleet control, viz.: (i) profits from the fisheries denote the economic achievement; (ii) number of jobs provided by the fisheries that measured with the job/catch value index represents social goals; (iii) the inverse of the P/B ratio by group was used as an ecological criterion of group-species longevity. Both single objectives and combined criteria were tested in the study (Table 1).                                                  1 Cite as: Jiang Hong, Cheng Hu Qin, Arreguín-Sánchez, F., 2009. Exploring fisheries strategies for ecosystem-based management in the East China Sea. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 22-23. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 23 Fisheries Applications – Hong et al. 24 Optimizing for a single objective led to the specialization of fishing fleets. Maximizing for economic achievement decreases the effort of all fishing fleets except that for drift gill net which increased by 33.2 %. The increase in fishing effort of drift gill net and stow net fleets satisfied the requirements for social benefits, i.e., increase in jobs. Optimizing for ecological structure led to a drastic decrease in effort of all fishing fleets except that of drift gill net which had a slight increase of 7.5 % (Table 1). Optimizing for economic and social criteria led to small changes in the ecosystem structure. However, optimizing for ecosystem structure led great decreases in fisheries profits and number of jobs. Combinations of economic-social, economic-ecological, and social-ecological criteria appear as realistic possibilities to improve benefits for fishing activity and ecosystem structure. For all scenarios in general, effort of trawl and shrimp trawl fleets are suggested to decrease, drift gill net to increase, and other fleets decrease in most scenarios presented in Table 1. Finally, an ‘ideal’ mixed policy configuration was found when a compromise was made between economic, social and ecological criteria. Table 1. Optimization of management policies using Ecosim model through open loop simulation for fisheries of the East China Sea for the period of 1990 to 2000. Weighting factors for criteria Outputs after optimization Fleets Econ. Social Ecol. Econ. Social Ecol. Trawl Stow net Drift gill net Purse seine Shrimp trawl Other fleet 1 0 0 1.55 1.04 1.21 0.448 0.683 1.33 0.879 0.269 1.02 0 1 0 1.09 1.47 1.016 0.042 1.97 26.8 0.194 0.398 4.86 0 0 1 0.08 0.06 2.41 0.004 0.008 1.07 0.074 0.002 0.017 1 1 0 1.48 1.31 1.06 0.480 0.982 23.4 0.190 0.241 3.02 1 0 1 1.39 0.87 1.46 0.196 0.878 1.38 0.761 0.057 0.694 0 1 1 1.36 1.25 1.09 0.148 1.70 1.69 1.23 0.319 2.17 1 1 1 1.54 1.16 1.29 0.044 0.900 2.72 0.545 0.271 1.62  ACKNOWLEDGEMENTS This study was made possible with financial support from the Sino-Europe Science and Technology Cooperation Programme, Ministry of Science and Technology, People’s Republic of China (contract no. 0710). REFERENCES Araújo, J.N., Mackinson, S., Stanford, R.J., Hart, P.J.B., 2008. Exploring fisheries strategies for the western English Channel using an ecosystem model. Ecol. Model. 210, 465-477. Araújo, J.N., Mackinson, S., Stanford, R.J., Sims, D.W., Southward, A.J., Hawkins, S.J., Ellis, J.R., Hart, P.J.B., 2006. Modelling food web interactions, variation in plankton production and fisheries on the western English Channel ecosystem. Mar. Ecol. Prog. Ser. 309, 175–187. Arreguín-Sánchez, F., Hernández-Herrera, A., Ramírez-Rodríguez, M., Pérez-España, H., 2004. Optimal management scenarios for the artisanal fisheries in the ecosystem of La Paz Bay, Baja California Sur, Mexico. Ecol. Model., 172, 373-382. Chao, M., Quan, W.M., Li, C.H., et al., 2005. Changes in trophic level of marine catches in the East China Sea region (in Chinese, with English summary). Mar. Sci. 29(9), 51-55. Christensen, V., Pauly, D., 1998. Changes in models of aquatic ecosystems approaching carrying capacity. Ecol. Appl. 8, S104–S109. Christensen, V., Walters, C., Pauly, D., 2005. Ecopath with Ecosim: A User’s Guide. Fisheries Centre, University of British Columbia, Vancouver. Fulton, E.A., Smith, A.D.M., 2004. Lessons learnt from a comparison of three ecosystem models for Port Phillip Bay, Australia. Afr. J. Mar. Sci. 26, 219–243. Vasconcellos, M., Mackinson, S., Sloman, K., Pauly, D., 1997. The stability of trophic mass-balance models of marine ecosystems: a comparative analysis. Ecol. Model. 100, 125–134. Walters, C., Martell, S., 2004. Fisheries Ecology and Management. Princeton University Press, New Jersey. Zhang Q.H., Cheng J.H., Xu H.X, et al., 2007. Fishery Resources and Its Sustainable Use Within the East China Sea Region (in Chinese). Fudan Press, Shanghai, China.  Ecopath 25 Years Conference Proceedings: Abstracts ECOLOGICAL EFFECT OF MOONJELLY, AURELIA AURITA, REMOVAL IN THE SEA OF SUO-NADA, SETO INLAND SEA, JAPAN1 SHINGO WATARI HIROMU ZENITANI KEISUKE YAMAMOTO NAOAKI KONO National Research Institute of Fisheries and Environment of Inland Sea, Fisheries Research Agency, 2-17-5 Maruishi, Hatsukaichi, Hiroshima 739-0452, Japan; swatari@affrc.go.jp; zenitani@affrc.go.jp; soniya@affrc.go.jp; nkono@affrc.go.jp The Seto Inland Sea, west of Japan, is a highly productive semi-enclosed boy of water. The Sea of Suo- Nada is located in the western part of the Seto Inland Sea, with a total area of about 3,100 km2 and an average depth of 23.7 m. Fisheries in this area are important to the local economy, with the annual landings of various fleets (trawl, gill net, set net, and boat seine fisheries) amounting to 12 750 t in 2005. Meanwhile, moonjelly (Aurelia aurita) blooms frequently occur, and have become a problem due to interference with fisheries operations in recent years. A device to cut up moonjelly into pieces was developed to address this problem (Yuichi Fukuda, Oita Prefectural Agriculture, Forestry and Fisheries Research Center, pers. comm.). However, the ecological effect of removing moonjelly from this ecosystem has not been assessed. Thus, we attempted to simulate the effect of this moonjelly removal on the biomass of other trophic groups using Ecopath with Ecosim. The trophic mass-balance model of the sea of Suo-Nada constructed for the period 2001 to 2008 is presented in Figure 1. Species and organic matter of this ecosystem were classified into 23 functional groups, viz.: Spanish mackerel (Scomberomorus niphonius), seaperch (Lateolabrax japonicus), black porgy (Acanthopagrus schlegelii), mullet (Mugil cephalus), anchovy (Engraulis japonicus), mantis shrimp (Oratosquilla oratoria), Japanese tiger prawn (Marsupenaeus japonicus), Japanese blue crab (Portunus trituberculatus), moonjelly, flatfishes, croakers, piscivorous fishes, planktivorous fishes, benthivorous fishes, cephalopods, shrimps, other crustaceans, large-sized benthos (>1.0 g), small-sized benthos (<1.0 g), zooplankton, phytoplankton, seaweeds, and detritus. Groups were created based on the most abundant species, on economic importance, and classification of fisheries statistics. Parameter values, i.e., biomass, production per biomass, consumption per biomass and diet composition, came from published information (e.g., reports of the Fisheries Agency and Fisheries Research Agency of Japan, 2008; Imoto et al., 2007), monthly trawl surveys with species composition and stomach contents (e.g., Kimura et al., 2003), and estimations using empirical relationships available through Ecoempire. We simulated the changes of biomass and catch over a 15-year period by using Ecosim. In this simulation, we evaluated the impact of the removal of moonjelly in the first 5 years with a removal rate (= catch per biomass) of 0.25. Biomass of moonjelly decreased during the removal period, and reached half of its current level at the end of this period (Figure 2). Subsequently, the biomass of monjelly recovered to its level before the removal of moonjelly. An increase of the biomass of anchovy was seen as the biomass of moonjelly decreased. In addition, biomass of Spanish mackerel increased over the same period when the biomass of anchovy increased. Total catch in the 5th year was 9.5 % larger than the current catch level, due to an increased catch of anchovy of the boat seine fishery. However, total catch decreased by 4.0 % in the 10th year and by 3.6 % in the 15th year, respectively. Biomass changes of demersal trophic groups were small, accounting for the constant behaviour of trawl and gill net fisheries, which exploit these groups, and thus, of the limited effect of moonjelly removal on these groups.                                                  1 Cite as: Watari, S., Zenitani, H., Yamamoto, K., Kono, N., 2009. Ecological effect of moonjelly, Aurelia aurita, removal in the Sea of Suo-Nada, Seto Inland Sea, Japan. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 25-26. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 25 Fisheries Applications – Watari et al. 26  Figure 1. Flow chart of trophic interactions in the Sea of Suo-Nada, Seto Inland Sea, western Japan.  0.0 0.5 1.0 1.5 2.0 2.5 Re lativ e b iom ass Spanish mackerel piscivorous fish seaperch flatfish black porgy croaker 0.0 0.5 1.0 1.5 0 5 10 15 Year Japanese tiger prawn shrimp Japanese blue crab other crustaceans large benthos small benthos mullet anchovy planktivorous fish benthivorous fish muntis shrimp cephalopod 0 5 10 15 Year moonjelly zoo plankton phytoplankton seaweed detritus  Figure 2. Dynamic changes in the biomass of trophic groups in the Sea of Suo-Nada, Seto Inland Sea, western Japan.  REFERENCES Fisheries agency and Fisheries research agency of Japan., 2008. Marine fisheries stock assessment and evaluation for Japanese waters (fiscal year 2007/2008). 1517 pp. (in Japanese). Imoto, Y., Kimura, H., Yoshioka, N., Zenitani, H., 2007. Fisheries management of mud dab Pleuronectes yokohamae in Suo-Nada, Seto Inland Sea based on spawning per recruit. Nippon Suisan Gakkaishi. 73, 684-692. (in Japanese). Kimura, H., Matsuno, S., Mimura, K., Wanishi, M., 2003. Report of fisheries resource management promotion project. In: Annual report of Yamaguchi prefectural fisheries research center. 103-137. (in Japanese). Ecopath 25 Years Conference Proceedings: Abstracts CAPTURING SIGNIFICANT CORAL REEF ECOSYSTEM AND FISHERY CHANGES IN BOLINAO, PHILIPPINES (1997-2008) USING ECOPATH WITH ECOSIM1 ROLLAN C. GERONIMO PORFIRIO M. ALIÑO Marine Science Institute, University of the Philippines Velasquez St., Diliman, Quezon City 1101, Philippines; rollan.geronimo@gmail.com; pmalino@upmsi.ph The 200km2 fringing reef of Bolinao in Pangasinan, Philippines (1625’ N and 11956’ E) is an important habitat for the Lingayen Gulf, a major fishing ground in Northern Philippines with an estimated yield of 6 500 t in 2001 (Silvestre & Hilomen, 2004). The extensive reef flat and slope straddles four municipalities and provides livelihood to more than 9,000 subsistence fishers and their dependents (Cruz-Trinidad et al., 2009). The reef has been intensively fished since the early 1980s resulting to significant declines in observed fish biomass based on fishery-independent visual census surveys. While still subjected to intense fishing, the Bolinao reefs were severely hit by the global massive bleaching event in 1998 brought about by an extreme El Niño anomaly. Between June to August 1998, live coral cover on the reef slopes of Bolinao was reduced from 45 % to 17 % (Arceo et al., 2001). Despite this immediate and drastic change in benthic community composition, immediate post-bleaching effects were not apparent on reef fishes or fisheries (Pet-Soede, 2000). In order to assess changes in Bolinao’s coral reefs and gauge the relative impacts of possible causes (e.g., fishing, refuge declines, and increased productivity), we created two Ecopath models of the reef slope system with base years at 1997 (pre-bleaching and relatively less nutrient input) and 2008 (post-bleaching with greater nutrient inputs from proliferation of nearby mariculture structures). Fish benthic functional groups were parameterized from underwater fish visual census and benthic community transects for both years as well as in 1998 and 1999. The 1997 model was then fitted to time-series data and ran until 2008 under various forcing and mediation functions to analyze the ecosystem impacts of benthic changes brought about by mass coral bleaching (i.e., reduced live coral cover, topographic complexity, and increased benthic algal cover) and continued fishing. Results were compared to how the 11-year simulation of the 1997 trophodynamic model captures the 2008 true balanced Ecopath model of the same reef area. Comparison of parameter inputs for 1997 and 2008 reveal increased fish biomass and catches from 1997 to 2008 with majority of the increase attributed to generalist feeding guilds such as detritus, macroalgal (e.g., Scaridae – parrotfishes), and invertebrate feeders (Table 1). This is contrary to studies on effects of bleaching on reef fishes which usually report declines in fish biomass and density following intensive reductions in live coral cover due to bleaching of crown-of-thorns starfish infestation, implying that other factors beyond habitat control affect fish community changes in Bolinao reefs. An 11-year trophodynamic simulation using only fishing as the forcing function (i.e., gradual doubling of fishing effort) captured most of the increase in fish biomass estimated in the 2008 Ecopath model but fishery targeted groups (i.e., invertebrate feeders; piscivores; carnivores; Acanthuridae – surgeonfishes, tangs, unicornfishes; and Siganidae – rabbitfishes) decreased to almost zero indicating that other factors were at play in structuring reef fish communities in Bolinao from 1997 to 2008 (e.g., habitat effects and movement of adults from adjacent reefs). Mediation functions helped explain relative importance of habitat while the remaining difference in biomass estimates from the 11-year Ecosim results and the 2008 parameterized Ecopath model were assumed to be due to adult migration. Fishery policy scenarios are also explored such as varying effort reductions of the different gear types and continued reduction or increase,                                                  1 Cite as: Geronimo, R.C., Aliño, P.M., 2009. Capturing significant coral reef ecosystem and fishery changes in Bolinao, Philippines (1997-2008) using Ecopath with Ecosim. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 27-28. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 27 Fisheries Applications – Geronimo & Aliño 28 due to restoration efforts, of live coral cover and increase (or decrease) in benthic algae for the next 10 years. Incorporating non-trophic benthic interactions (e.g., competition for space) and refining benthic-fish interaction terms can help improve the utility of Ecopath with Ecosim for nearshore, habitat-associated fisheries and move beyond fishery carrying capacities to ecosystem function carrying capacities, a critical step towards ecosystem-based management.  Table 1. Inputs and calculated parameters (in italics) for the 1997 and 2008 trophic model of Bolinao reef slope, Pangasinan, Philippines (16°25’ N and 119°56’ E). Biomass (t·km-2) P/B (yr-1) Q/B (yr-1) EE P/Q Catch (t·km-2·yr-1) + Group name * 1997 2008 1997 2008 1997 2008 1997 2008 1997 2008 1997 2008 Phytoplankton 2.74 3.22 511.00 511.00 - - 0.85 0.42 - - 0.00 0.00 Macroalgae 50.27 83.42 0.96 1.22 - - 0.30 0.30 - - 0.00 0.00 Other algae 8.04 18.68 1.88 4.55 - - 0.95 0.95 - - 0.00 0.00 Corals  105.00 41.42 1.10 1.10 7.30 7.30 0.01 0.11 0.15 0.15 0.00 0.00 Zooplankton 7.97 4.68 80.00 80.00 200.00 200.00 0.60 0.60 0.40 0.40 0.00 0.00 F invert feeder 0.23 1.45 1.26 1.14 10.31 9.90 0.91 0.12 0.12 0.12 0.23 0.03 F carnivore 0.12 0.34 1.82 1.71 13.86 7.97 0.95 0.90 0.13 0.22 0.19 0.48 F corallivore 0.06 0.39 1.73 2.25 15.34 22.74 0.23 0.18 0.11 0.10 0.00 0.00 F detritus feeder 0.11 1.56 1.76 1.76 25.96 26.58 0.22 0.06 0.07 0.07 0.00 0.00 F herbivore – others 0.09 0.80 1.92 1.89 56.17 61.22 0.14 0.28 0.03 0.03 0.00 0.00 F omnivore 0.12 0.59 1.91 1.55 29.78 38.91 0.11 0.18 0.06 0.04 0.00 0.00 F piscivore 0.01 0.14 0.81 0.98 6.19 11.12 0.99 0.51 0.13 0.09 0.00 0.02 F zooplanktivore 0.09 1.62 1.78 1.50 16.13 11.90 0.14 0.07 0.11 0.13 0.00 0.01 Acanthuridae 0.08 0.89 0.93 0.79 20.79 19.11 0.94 0.23 0.05 0.04 0.06 0.00 Scaridae 0.05 0.35 0.93 1.07 17.34 21.53 0.90 0.70 0.05 0.05 0.02 0.10 Siganidae 0.43 0.23 1.61 2.97 24.58 38.69 0.28 0.90 0.07 0.08 0.17 0.46 Sea urchins 0.06 0.68 7.00 7.00 30.42 30.42 0.30 0.30 0.23 0.23 0.00 0.00 Crustaceans 5.71 5.71 11.47 11.47 26.89 26.89 0.04 0.21 0.43 0.43 0.00 0.08 Other sessile benthic inverts 16.54 16.54 6.96 6.96 15.18 15.18 0.52 0.57 0.46 0.46 0.00 0.00 Detritus 1000.00 1000.00 - - - - 0.95 0.46 - - 0.00 0.00 * F = fish functional group + Total catch in 1997 is 0.69 t·km-2·yr-1 and 1.18 t·km-2·yr-1 in 2008  ACKNOWLEDGEMENTS Data used for the models were compiled from different funded projects by the Royal Netherlands Embassy and GEF. Data compilation, synthesis, processing, and simulations were supported through the GEF-Coral Reef Targeted Research (Modeling and Decision Support Working Group) graduate research scholarship granted to R.C. Geronimo. We thank A.J. Uychiaoco, F. Castrence Jr. and H. Arceo for letting us use their data for parameterising these models. REFERENCES Arceo, H.O., Quibilan, M.C., Aliño, P.M., Lim, G., Licuanan, W.Y., 2001. Coral bleaching in Philippine reefs: coincident evidences with mesoscale thermal anomalies. Bull. Mar. Sci. 69, 579-593. Cruz-Trinidad, A., Geronimo, R.C., Aliño, P.M., 2009. Development trajectories and impacts on coral reef use in Lingayen Gulf, Philippines. Ocean Coast. Manage. 52, 173-180. Graham, N.A.J., Wilson, S.K., Jennings, S., Polunin, N.V.C., Robinson, J., Bijoux, J.P., Daw, T.M., 2007. Lag effects in the impacts of mass coral bleaching on coral reef fish, fisheries and ecosystems. Conserv. Biol. 21, 1291-1300. Pratchett, M.S., Munday, P.L., Wilson, S.K., Graham, N.A.J., Cinner, J., Bellwood, D.R., Jones, G.P., Polunin, N.V.C., McClanahan, T.R., 2008. Effects of climate-induced coral bleaching on coral-reef fishes -- ecological and economic consequences. Oceanogr. Mar. Biol. Annu. Rev. 46, 251-296. Silvestre, G.T., Hilomen, V.V., 2004. Status of Lingayen Gulf fisheries – a brief update. In: DA-BFAR, In Turbulent Seas: The Status of Philippine Marine Fisheries. Coastal Resource Management Project, Cebu City, Philippines, pp. 285-291. Pet-Soede, L., 2000. Effects of coral bleaching on the socio-economics of the fishery in Bolinao, Pangasinan, Philippines. November 2000, accessed from pdf.usaid.gov/pdf_docs/PNACN135.pdf. Ecopath 25 Years Conference Proceedings: Abstracts FISHERIES IN BAJA CALIFORNIA SUR: A TROPHIC-BASED ANALYSIS OF MANAGEMENT SCENARIOS1 ANDRES M. CISNEROS-MONTEMAYOR VILLY CHRISTENSEN USSIF RASHID SUMAILA Fisheries Centre, University of British Columbia, 2204 Main Mall, Vancouver, British Columbia, Canada V6T1Z4; a.cisneros@fisheries.ubc.ca; v.christensen@fisheries.ubc.ca; r.sumaila@fisheries.ubc.ca FRANCISCO ARREGUIN-SANCHEZ Centro Interdisciplinario de Ciencias Marinas, CICIMAR, del Instituto Politécnico Nacional, Apartado Postal 592, La Paz, 23090, Baja California Sur, Mexico; farregui@ipn.mx Using published fisheries and ecosystem data for the Baja California Sur (BCS) region in Mexico, we constructed an Ecopath with Ecosim (EwE) version 6 model to represent current ecosystem and fishing dynamics and the outcomes of various fisheries management scenarios. We also used novel applications of the program to evaluate the economic effects of specific fisheries policy measures, particularly those that are attainable and provide overall benefits in a multi-stakeholder setting. During the last 30 years and particularly in the last decade, BCS has embraced the tourism industry, most noticeably in the Los Cabos region, where fishing is one of the main tourist attractions. Meanwhile, the commercial long-liner fleet continues to operate and is widely held to be chiefly responsible for diminishing shark populations. Billfish stocks are also experiencing slight but steady declines, with some allegations that this is mainly due to bycatch in long-lines (The Billfish Foundation, 2008). Conflicts between the sectors were recently worsened by the approval of a shark fishery management law which does not specifically prohibit bycatch of billfish (Diario Oficial de la Federación (DOF), 2007). Social and political groups view this as a direct threat to the economic benefits of the local sport fishing industry (valued by industry to be worth 1.2 billion USD/year in the region; Southwick Associates, Inc., 2008). Amid calls for the complete shutdown of long-lining in the region, government scientists carried out an evaluation of shark bycatch, followed by a mandate setting a bycatch limit for billfish (DOF, 2008). However, no scientific studies have yet been conducted to gauge the impact of fishing fleets on the BCS marine ecosystem. Table 1. Select input parameters for Baja California Sur Ecopath model. Group name Biomass (t·km2) P/B (yr-1) Q/B (yr-1) EE P/Q  Large sharks 0.50 0.250 2.5 0.178 0.100  Coastal sharks 18.30 0.30 2.8 0.107 0.107  Marlin 3.42 0.30 4.0 0.030 0.075  Dorado 30.45 3.0 20 0.085 0.150  Other billfish 5.88 1.40 10.4 0.262 0.135  Skipjack tuna 41.57 1.90 20 0.097 0.095  Flying squid 18.23 5.0 50 0.208 0.100  Small scombrids 243 2.0 10 0.782 0.200  Squid 410 2.5 25 0.850 0.100  Other pelagic fish 1,876 1.5 6.2 0.859 0.242  Zooplankton 3,496 8.3 41.5 0.796 0.200  Phytoplankton 2,903 100 - 0.500 -  Detritus 1.00 - - 0.000 -  We constructed a simplified ecosystem model using modified basic input data from a Central North Pacific EwE model by Kitchell et al. (2002), eliminating or aggregating data for functional groups that were either inapplicable or too specific for the purpose of this work (Table 1).                                                  1 Cite as: Cisneros-Montemayor, A.M., Christensen, V., Sumaila, U.R., 2009. Fisheries in Baja California Sur: a trophic-based analysis of management scenarios. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 29-30. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 29 Fisheries Applications – Cisneros-Montemayor et al. 30 Landings for the main fleets in the region (sport, long-liner, squid and pelagic) were assigned considering that all fisheries currently operate at their MSY, as reported by the Mexican National Fisheries Institute (DOF, 2004). All bycatch and catch-release mortality rates were assigned according to published data for the region and specific groups (INP, 2007; Cramer, 2004; Ditton et al., 1996). Results show that current government-mandated bycatch limits will probably not have a significant positive effect on billfish population levels. In fact, billfish stocks will not recover significantly even if all commercial fishing in the region is banned (although this would effectively recover shark populations). Furthermore, any positive effects would likely be offset by subsequent increases in sport fishing if it is allowed to build up further. Both tourism and commercial fishing are socially and economically important in the BCS region, so it would be unfeasible and undesirable to shut down either activity no matter what the positive environmental effects could be. However, it is possible to explore and find scenarios involving trade-offs between sectors which would have positive ecological effects without high (or perhaps any) socio- economic costs. ACKNOWLEDGEMENTS The first author would like to acknowledge the Mexican Council of Science and Technology for its financial support. REFERENCES Cramer, J., 2004. Life after catch and release. Marine Fisheries Review 66 (1), 27-30 Diario Oficial de la Federación (Federal Gazzete), 2008. Acuerdo mediante el cual se establece el volumen de captura incidental permitido en las operaciones de pesca de tiburón y rayas en aguas de jurisdicción federal de los Estados Unidos Mexicanos ubicadas en el Océano Pacífico. September 12, 2008. Diario Oficial de la Federación (Federal Gazzete), 2007. NORMA Oficial Mexicana NOM-029-PESC-2006, Pesca responsable de tiburones y rayas. Especificaciones para su aprovechamiento. February 14, 2007. http://www.ordenjuridico.gob.mx/Federal/PE/ APF/APC/SAGARPA/Normas/Oficiales /2007/ 14022007(1).pdf Diario Oficial de la Federación (Federal Gazette), 2004. Acuerdo por el que se aprueba la actualización de la Carta Nacional Pesquera y su anexo. Poder Ejecutivo—Secretaria de Medio Ambiente, Recursos Naturales y Pesca, Diario Oficial de la Federación, México, March 15, 2004. Ditton, R.B., Grimes, S.R., Finkelstein, L.D., 1996. A Social and Economic Study of the Recreational Billfish Fishery in the Southern Baja Area of Mexico. The Billfish Foundation. Instituto Nacional de la Pesca, 2007. Estimación de las tasas de captura incidental de la flotas tiburoneras en el Pacífico Mexicano. Dictamen técnico. Kitchell, J.F., Essington, T., Boggs, C.H. Schindler, D.E., Walters, C.J., 2002. The role of sharks and long-line fisheries in a pelagic ecosystem of the Central Pacific. Ecosystems 5, 202-216 Southwick Associates, Inc., Nelson Consulting, Inc. and Firmus Consulting, 2008. The Economic Contributions of Anglers to the Los Cabos Economy. The Billfish Foundation. The Billfish Foundation. http://www.billfish.org/new/newsarticle.asp?ArticleID=66  Ecopath 25 Years Conference Proceedings: Abstracts IMPACT OF FISHING AND CLIMATE ON THE CELTIC SEA AND THE BAY OF BISCAY1 SYLVIE GUENETTE DIDIER GASCUEL Université Européenne de Bretagne, Pole halieutique AGROCAMPUS OUEST, UMR Ecologie et Santé des Ecosystèmes, Rennes, France; sylvie.guenette@agrocampus-ouest.fr; didier.gascuel@agrocampus-ouest.fr The Celtic Sea and the Bay of Biscay have been fished intensively for at least a century. Already sizeable between the two World Wars, the fisheries resumed after 1945 with the support of governmental subventions to modernize the fleets and thus causing an unprecedented increase in fishing capacity in the region. We built a model for the Bay of Biscay and Celtic Sea for 1980, using the Ecopath with Ecosim software (EwE) (Christensen & Walters, 2004). Of the numerous species that are exploited in the ecosystem only a mere dozen were the subject of stock assessment because of their importance for the industrial fleets while most coastal species were never assessed. The model is articulated around 14 industrial species, their prey and predators, for a total of 38 groups.  Cod, hake and Norway lobster were separated in juvenile and adult stanzas to account for species size-structured interactions among themselves and the fisheries. Starting from 1980 we fitted our model to biomass and landing data using time series of fishing mortality used as an index of fishing effort. We also used various climate indices, the North Atlantic Oscillation index (NAO) and sea surface temperature, to modify phytoplankton’s production and obtain better fits. Biomass and catch trophic spectra were built, for the starting and the ending years of the period (i.e., 1980 and 2006) using the ET-Transpose routine (Gascuel et al., 2009) included in the EwE software. Such spectra represent the distribution over trophic levels of the whole ecosystem biomass, or of total catches. Thus, they provide a synthetic overview of the ecosystem state and of the major changes occurring during the period. Finally, the impact of fishing was estimated using the EcoTroph model (Gascuel, 2005; Gascuel & Pauly, 2009). RESULTS Using only fisheries effort, Ecosim predicted the general trend in landing and biomass for several demersal species such as hake, monkfish, while large discrepancies occur for other species such as cod, sole, plaice and whiting. Ecosim could not account for the observed decline in mackerel because the high initial biomass was due to the entry of very large cohorts in the population before 1975, the effect of which were still present in the early 1980s. Thus, fishing alone was not sufficient to have provoked the declined. Forcing the primary production with the NAO index did not improve the fit to time series, although discrepancies in biomass and/or landing trends were corrected in some cases. The scenario that estimated both climate anomalies and vulnerabilities improved the accuracy of the model general predictions and indeed the sum of squares decreased. The NAO index and the anomalies estimated by Ecosim have similar trends although the anomalies are shifted in time, reaching maximum positive values ~3-4 years later than the NAO index. Although total landings remained approximately constant from 1980 to 2006, several changes in the trophic structure are noted. First, the biomass of higher trophic levels decreased while it increased for the                                                  1 Cite as: Guénette, S., Gascuel, D., 2009. Impact of fishing and climate on the Celtic Sea and the Bay of Biscay. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 31-32. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727]. 167 p. 31 Fisheries Applications – Guénette et al. 32 32 lower ones. Biomass ratios 2006/1980 show a decrease of about 30 % for trophic levels higher than 4.0. The same ratio using accessible biomass (i.e., the biomass of exploited groups) suggests that the increase in low trophic levels biomass mainly concerns groups that are not fishable. Fishing mortalities increased for high trophic level groups, suggesting that the fishermen tried to compensate for the decrease in abundance of their traditional stocks. In the same period, landings of the lower trophic levels increased due to increased landings of some lower trophic level species and because the mean trophic level of some groups decreased slightly. Finally, using Ecotroph, we found that the abundance of the total biomass decreased for all trophic levels higher than 3.5 (Figure 1). The rate of decrease exceeds 50 % for trophic levels higher than 4.0. As a consequence, the mean trophic level of the whole ecosystem biomass decreased from 2.42 to 2.35. DISCUSSION The model is still in a preliminary phase, but it was still able to predict biomass and catches of most exploited species, from 1980 to 2006. A notable exception to this is mackerel for which we suspect that the main factors influencing its dynamics may be happening outside the study area. Fisheries explain a large part of the trends for demersal species such as cod, hake, and monkfish, while the effect of indices of productivity were necessary to explain a good part of the trends of all fish and more importantly on whiting, sardine, herring and anchovy. It is clear that not all functional groups depend on the same resources, which would explain why the NAO index applies better on some species and the forcing function estimated by Ecosim on others. For example, the juveniles of flatfish are typically found in estuaries where the main influence on survival is likely to be linked to river flow and other factors that are only partly linked to the strength of the NAO index. 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 Trophic level Bi om as s r ati o B2006/B1980 B*2006/B*1980 B2006/Bunexpl.  Figure 1. Ratios of biomass per trophic class, between the ending year 2006 and thye starting year 1980 or the unexploited situation. B* refers to the accessible biomass, i.e. the biomass of all species or groups currently fished. Even if biomass only slightly decreases and total landings remain more or less constant during the period, some significant changes occurred. The EcoTroph approach especially shows that the increasing fishing mortality induced a decrease in abundance of predator species. Globally, the ecosystem biomass and landings exhibit decreasing trophic levels, indicating a decrease in functional biodiversity of the underlying ecosystem (Pauly et al., 1998). Of course, one should not forget that the fishery does not start in 1980. The flat deterioration of the ecosystem health over the last 25 years, is likely to follow a strong and fast deterioration during the decades after World War II, characterized by an huge increase in the European fishing effort. REFERENCES Christensen, V., Walters, C. J. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modelling, 172:109-139. Gascuel D., 2005 - The trophic-level based model: a theoretical approach of fishing effects on marine ecosystems. Ecological modelling 189, 315-332. Gascuel, D., Boyer-Tremblay, L., Pauly, D., 2009. EcoTroph: a trophic-level based software for assessing the impact of fishing on aquatic ecosystems. Fisheries Centre Research Reports 17(1), University of British Columbia, Vancouver, 83 p. Gascuel D., Pauly D., 2009 - EcoTroph: modelling marine ecosystem functioning and impact of fishing. Ecological Modelling, , in press. Pauly, D., V. Christensen, J. Dalsgaard, R. Froese and F.C. Torres Jr. 1998. Fishing down marine food webs. Science 279: 860-863. Ecopath 25 Years Conference Proceedings: Abstracts FISHERIES APPLICATIONS: POSTER PRESENTATIONS RECOVERY SCENARIOS OF A HIGHLY EXPLOITED SPECIES, MERLUCCIUS MERLUCCIUS, IN THE NW MEDITERRANEAN SEA1 GIOVANNI VARGIU Parco Nazionale dell’Asinara Via Josto, 7. 07046. Porto Torres (SS); vivavargiu@gmail.com MARTA COLL ISABEL PALOMERA Institut de Ciències del Mar, CSIC, Barcelona, Spain; mcoll@icm.csic.es; isabel@icm.csic.es SERGI TUDELA WWF Mediterranean Programme Office Canuda, 37. 08002. Barcelona. Spain; studela@atw-wwf.org The biodiversity in the Mediterranean is threatened by overexploitation of biological resources, direct habitat modification of sea and coastal areas, introduction of exotic species, pollution and climate change (Bianchi & Morri, 2000). In the North-western Mediterranean Sea, highly valued marine resources, e.g., hake Merluccius merluccius, are subjected to intense fishery pressure. Hake is overfished mainly due to: low selectivity of trawling nets (i.e., excessive capture of juveniles); the introduction of modern long lines during the 1970s; and the partial elimination of their spawning refuge (Sardá et al., 2005; Aldebert & Recasens, 1996). A new European Commission Regulation on the Management of Mediterranean Fisheries (CE 1967/2006) was approved in December 2006 on management measures for sustainable exploitation of fishery resources in the Mediterranean Sea. The new regulation enforces a higher selectivity of the current 40 mm diamond mesh codend in trawling. Several experimental case studies demonstrated the positive ecological effects of increasing trawling selectivity (e.g., Bahamon et al., 2006; Guijarro & Massutí, 2006; Sardà et al., 2005), although simulations predict that a drastic reduction of fishing effort in parallel with higher gear selectivity would be necessary for the recovery of highly exploited species such as hake (Coll et al., 2008a). The new regulation also encourages European States to enhance new protected areas for fishing. Here we explored if MPAs contribute an additional ecological value, in contrast with fishing effort reduction, to the recovery of hake in the NW Mediterranean Sea. Our simulations are based on a South Catalan Sea ecosystem model (Coll et al., 2006) calibrated and fitted to catch time series for 1994 to 2003 (Coll et al., 2008b) using Ecosim v. 6 (Christensen & Walters, 2004). The calibrated model was used to derive a new ecosystem model for 2003 (Coll et al., 2008a), which represented initial conditions for the simulations. The baseline simulation was run for 25 years with constant fishing effort. Fishing effort for trawls and longlines was then reduced by 20 %, 30 %, 40 % and 50 % and changes in predicted biomass of adult and juvenile hake were compared to the baseline. The location of an MPA was also tested covering 20 %, 30 %, 40 % and 50 % of the study area.                                                  1 Cite as: Vargiu, G., Coll, M., Palomera, I., Tudela, S., 2009. Recovery scenarios of a highly exploited species, Merluccius merluccius, in the NW Mediterranean Sea. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts pp. 33-34. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 33 Fisheries Applications: Posters – Vargiu et al. 34 Reducing fishing effort increased adult hake biomass, while juvenile hake biomass was reduced (Figure 1, Table 1). This may be due to an increase of cannibalism by adults. The MPA has a positive effect on adult and juvenile hake biomasses, with broader benefits on juveniles. Full recovery of adult hake is obtained only within the protected area (Figure 1). The catch of both juvenile and adult hake generally increases with the MPA, while the catch of juvenile hake decreases when a reduction of fishing effort is simulated, in parallel with a noTable increase of adult hake catch (Table 1). Thus, both management options provide complementary results. When the MPA is implemented, the fishing effort surrounding the protected area substantially increases, with a noTable concentration of fishing effort at 50- 100 m depths (Figure 2b). When fishing effort is reduced, a distributed reduction of both trawl and longline effort is predicted to occur on the area, although the effort is slightly concentrated in the continental shelf (50-100 m depth; Figure 2c). A smaller reduction of total final catch is predicted when MPAs are implemented, likely due to the fact that the total fishable biomass is higher (Table 1). Both management options are predicted to benefit fish communities over invertebrates. In general, results reflect broader benefits of the MPA on the whole community, while the reduction of fishing effort has stronger positive effects on adult hake. ACKNOWLEDGEMENTS We thank the Fisheries Centre for opportunities to learn the EwE approach and continuous advice. REFERENCES Aldebert, Y., Recasens, L., 1996. Comparison of methods for stock assessment of European hake Merluccius merluccius in the Gulf of Lion (Northwestern Mediterranean). Aquat. Living Resourc. 9, 13-22 Bahamon, N., Sardà, F., Suuronen, P., 2006. Improvement of trawl selectivity in the Mediterranean demersal fishery by using a 40 mm square mesh codend. Fish Res. 81, 15- 25. Bianchi, C. N., Morri, C., 2000. Marine biodiversity of the Mediterranean Sea: situation, problems and prospects for future research. Mar. Poll. Bul. 40(5), 367-376. Juvenile hake Adult hake Juvenile hake Adult hake Juvenile hake Adult hake a) Baseline simulation b) 50%MPA c) 50% reduction fishing effort  Figure 1. Biomass of hake in the South Catalan Sea under different management simulations Table 1. Results of various management simulations in the Southern Catalan Sea (scenario MPA or Effort Reduction/baseline). Biomass Juv. hake Biomass adult hake Catch Juv. hake Catch adult hake Total Cf/Ci Binv / Bfish BFf / BFi MPA / Baseline MPA20/BS 1.05 1.29 1.03 1.11 0.95 0.93 1.05 MPA30/BS 1.08 1.46 1.07 1.03 0.92 0.87 1.07 MPA40/BS 1.09 1.67 1.14 0.91 0.88 0.83 1.07 MPA50/BS 1.08 1.9 1.29 0.77 0.84 0.76 1.06 Effort Red /Baseline Eff.R. 20/BS 0.70 1.54 0.56 1.38 0.83 0.91 0.78 Eff.R. 30/BS 0.58 1.8 0.37 1.48 0.74 0.84 0.67 Eff.R. 40/BS 0.48 2.07 0.23 1.50 0.66 0.78 0.58 Eff.R. 50/BS 0.42 2.36 0.15 1.45 0.60 0.72 0.53 C = total catch of exploited species, Binv = biomass of invertebrates, Bfish = biomass of fish, BF = fishable biomass, f = final, i = initial.  a) Baseline simulation b) 50%MPA c) 50% reduction fishing effort Trawl effort Long line effort Trawl effort Long line effort Trawl effort Long line effort Figure 2. Fishing effort distribution in the South Catalan Sea under different management simulations. Christensen, V., Walters C.J., 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172, 109-139. Coll, M., Palomera, I., Tudela, S., Sardà F., 2006. Trophic flows, ecosystem structure and fishing impacts in the South Catalan Sea, Northwestern Mediterranean. J. Mar. Syst. 59, 63-96. Coll, M., Bahamon, N., Sardà, F., Palomera, I., Tudela, S., Suuronen, P., 2008a. Improved trawl selectivity: effects on ecosystems in the South Catalan Sea (NW Mediterranean). Mar. Eco. Prog. Ser. 355, 131-147. Coll, M., Palomera, I., Tudela, S. Dowd, M., 2008b. Food-web dynamics in the South Catalan Sea ecosystem (NW Mediterranean) for 1978-2003. Ecol. Model. 217(1-2), 95-116. Guijarro, B. Massutí, E., 2006. Selectivity of diamond and square-mesh codends in the deepwater crustacean trawl fishery off the Balearic Islands (western Mediterranean). ICES J. Mar. Sci. 63, 52-67. Sardà, F., Bahamón, N., Sardà-Palomera, F., Molí, B., 2005. Commercial testing of a sorting grid to reduce catches of juvenile hake (Merluccius merluccius, L.) in the western Mediterranean demersal trawl fishery. Aquat Liv. Res. 18, 87-91. Ecopath 25 Years Conference Proceedings: Abstracts ON THE TRANSFER PAYMENT OF THE FISHERY FUEL SUBSIDIES IN CHINA1 CHENG HE QIN JIANG HONG State Key Laboratory of Estuarine and Coastal Research East China Normal University, North Zhongshan Rd., Shanghai, 200062, China; hqch@sklec.ecnu.edu.cn; hongjiang0822@yahoo.com.cn Large scale summer fishing closure was implemented in East China Sea (ECS) by the Chinese government in 1995 in response to intensified anthropogenic impacts on the marine ecosystem. The area between 27°N and 35°N was annually closed to trawl and stow net fleets from 1 July to 31 August. Three years later, in 1998, the prohibited fishing area was extended to the South China Sea, the Yellow Sea and Bohai Sea (Yan et al., 2006), the prohibited fishing gears were extended to cover the shrimp trawls and closed seasons were prolonged from 16 June to 15 September. It is now generally recognized that the summer fishing closure led to ecological, economic and social benefits in the last 14 years, and is important for sustainable fisheries development in the ECS (Zhang et al., 2007). The closed season will cover three months and a half in 2009 according to the proclamation of the Ministry of Agriculture, P.R. China. However, subsidy for closed fishing is not established yet in China. In view of this, a subsidy for living expenses of the fishermen during summer fishing closure is considered by the government now. Subsidies to the fishing industry are common worldwide, and it is well accepted that these subsidies contribute to overcapacity in fishing fleets and overexploitation of fisheries resources (Sharp & Sumaila, 2009). Subsidies showed a gradually increasing trend with the expanding of the Chinese fishing industry in recent years. However, the overall quantity of fisheries subsidies is lower in China than in other countries (Chen et al., 2005). At present the primary goal of these subsidies is to control the marine fishing capacity, inhibit the decline of fishery resources and improve the quality of fishers’ lives. Subsidies include a permit buyback policy of fishing vessel, financial support for training, education and for fishers changing to other jobs in coastal areas. China established fuel subsidies in 2006 due to rising oil prices. These have increased since, mainly due to economic and social pressure, i.e., from coastal fishers and fishery operators affected by the constant extension of summer fishing closures. Fuel subsidies are assigned to ship owners according to their fishing license and fuel consumption per unit operation of fishing gears. Trawls, stow nets and high-powered vessels benefit from more subsidies than the lighter gears, e.g, deep water drift nets and fishing tackles. These subsidies contribute to better maintenance of ships and gears, high catches, better jobs and thus discourage fishers from moving out of the fishing industry. These results are contrary to marine fisheries management goals of controlling fishing capacity. Based on the national financial situation and fishery production, fuel subsidies can be decreased in stages and used primarily to subsidize living expenses of fishers during the summer fishing closure in order to reverse negative effects of subsidies on the control of fishing capacity.                                                  1 Cite as: Qin, C.H., Hong, J., 2009. On the transfer payment of the fishery fuel subsidies in China. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 35-36. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727]. 167 p. 35 Fisheries Applications: Posters –Qin & Hong 36 In this study, we estimated the impact of fuel subsidy (scenario 1) and the summer fishing closure subsidy (scenario 2) on fishing fleets and on the ECS ecosystem. Similations were based on the East China Sea Ecopath model of Jiang et al. (2008) starting from a baseline simulation, without subsidy (scenario 0). Differences in two fishery parameters (cost and profit) and three ecosystem parameters (longevity, total system trophic level and Simpson’s BDI) between scenarios 1-2 and scenario 0 were calculated to represent the impact of subsidies on the fishery and on the ECS ecosystem. Table 1. Impact of fuel subsidy (scenario 1) and summer fishing closure subsidy (scenario 2) on the fishery cost and profit.  Changes of cost Changes of profit  Scenario 1 Scenario 2 Scenario 1 Scenario 2 Trawl 2.689 -0.062 -6.390 0.109 Stow net 0.833 -0.060 -3.358 0.113 Drift gill net 0.934 0.000 1.086 -0.003 Purse seine 1.820 -0.058 0.441 -0.020 Shrimp trawl 2.227 -0.058 -6.245 0.309 Fleet6 0.658 -0.058 0.201 -0.022 Total 1.796 -0.060 -4.610 0.158 Results indicate that: (1) scenario 2 will decrease the fishery cost and increase the fishery profit of all fishing gears and the total fishery; (2) scenario 1 will induce a high increase in fisher cost of all gears and a high decrease in fishery profit of the trawl, stow net and shrimp trawl fisheries as well as the total fishery (Table 1). Ecosystem parameter trends, on the other hand, differed in scenarios 1 and 2 (Table 2). The positive impact of summer fishing closure on the ecosystem confirmed by previous studies is emulated here. Furthremore, scenario 2 represents a mature and sTable ecosystem, which when impacted by fuel subsidy, led to an immature and unsTable ecosystem. Without fishing capacity control, fuel subsidy triggered an increase of fishing effort, a negative impact on the fisheries and on the ecosystem and lead to an aggravation of overexploration. On the other hand, summer fishing closure subsidy brought a decrease of fishing effort, a mitigation of overexploration as well as increase in profits. Thus, chanelling payment for fuel subsidy to summer fishing closure subsidy will promote the sustainable use of fishery resources and the health of the ECS ecosystem. Table 2. Impact of fuel subsidy (scenario 1) and summer fishing closure subsidy (scenario 2) on the ecosystem. Ecosystem parameters Absolute values Changes of values (%)  Scenario 0 Scenario 1 Scenario 2 Scenario 1 Scenario 2 Longevity>2 0.4302  0.4472  0.4293  3.9565  -0.2040  Total system Trophic Level 2.5187  2.4829  2.5205  -1.4224  0.0730  Simpson BDI 0.4253  0.4179  0.4258  -1.7299  0.1096  ACKNOWLEDGEMENTS We thank the Sino-Europe Science and Technology Cooperation Programme of the Ministry of Science and Technology of the People’s Republic of China (contract no. 0710) for financial support for this study. And we are grateful for the assistance extended to us by Dr. Villy Christian and Dr. Rashid Sumaila of the Fisheries Centre, University of British Columbia, Canada. REFERENCES Chen, J.N., Mu, Y.T., 2005. Debates on fisheries subsidies and suggetions for improving China’s fisheries subsidies policy (in Chinese with English abstract). J. Zhejiang Ocean Univ. (Nat. Sci.) 24, 130-134. Jiang, H., Cheng, H.Q., Xu, H.G., et al., 2008. Trophic controls of jellyfish blooms and links with fisheries in the East China Sea. Ecol. Mod. 212, 492-503 Sharp, R., Sumaila, U.R., 2009. Quantification of U.S. marine fisheries subsidies. North Am. J. Fish. Manage., 29, 18-32. Yan, L.P., Ling, J.Z., Li, J.S., et al., 2006. Simulative analysis on results of summer close fishing in the East China Sea with Ricker population dynamic pool model. J. Fish. Sci. China., 13, 85-91. Zhang Q.H., Cheng J.H., Xu H.X, et al., 2007. Fishery Resources and its sustainable use within the East China Sea Region (in Chinese). Fudan Press, Shanghai, China.  Ecopath 25 Years Conference Proceedings: Abstracts VULNERABILITY TO FISHING OF THE CENTRAL GULF OF CALIFORNIA ECOSYSTEM1 FRANCISCO ARREGUIN-SANCHEZ LUIS A. SALCIDO-GUEVARA Centro Interdisciplinario de Ciencias Marinas, CICIMAR, del Instituto Politécnico Nacional, Apartado Postal 592, La Paz, 23090, Baja California Sur, Mexico; farregui@ipn.mx; salcidog@gmail.com Vulnerability, defined here as the degree to which ecosystems are likely to experience harm due to a perturbation or stress, has recently become a central focus, particularly relevant, for exploiting aquatic ecosystems. Knowledge of processes related to vulnerability provides key information for management. One way to deal with this is related with the construction and understanding indicators, which, in fact, are expected to express structural functional or organization attributes of ecosystems. The conservation of these attributes in the dynamics of living systems is probably one of the major challenges for management looking for sustainable use of ecosystems. Present state MSY level In this contribution we explore the responses of several ecosystem indicators to a simulated fishing pattern. We selected the Central Gulf of California model (Arreguín-Sánchez et al., 2002), constructed with the Ecopath with Ecosim suite of programs, because this is a very important fishing region in Mexico. The Gulf of California provides about 65 % of the total fish capture of Mexico. We focused on the shrimp fishery, which causes the major perturbation in the ecosystem and also the most important from economic and social points of view. Based on Ecosim (Walters et al., 1997) we simulated effects of a fishing pattern where harvesting rate gradually increased at a rate of 10 % per year from no- fishing until 80 % of the shrimp biomass was extracted, representing severe overfishing. Under this framework we considered target and incidental catches of the shrimp trawl fishing, while other fisheries remain unchanged; this allowed us to assign observed changes due to simulated fishing pattern on the shrimp fishery. We tested 14 different indices namely: mean trophic level of catch, fishery-in-balance, Finn’s cycling, predation cycling, respiration, biomass/production ratio, flows to detritus, resilience (O/C) , Kempton biodiversity (Ainsworth & Pitcher, 2004; Christensen & Pauly, 1992; Ulanowicz, 1986,), interaction strength, trophic replacement, functional impact (Shannon & Cury 2003), supply/demand balance (Bendrichio & Palmeri, 2005; Banavar et al., 1999), loss of primary                                                  1 Cite as: Arreguín-Sánchez, F., Salcido-Guevara, L.A., 2009. Vulnerability to fishing of the Central Gulf of California ecosystem. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 37-38. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p.  Figure 1. Top: changes in the Supply/Demand balance index with changes in fishing pattern of the shrimp trawl fishery, including bycatch. Different states of the shrimp fishery are shown; Present state refers to mid 1990’s, Red point refers to ecosystem shift. Bottom: keyplayers relevant to propagation through the foodweb (dashed line), note they are mostly high trophic levels groups; and those relevant to fragmentation (solid line) of the trophic network; Note they pertain to different trophic levels. Trophic levels are represented by the vertical axes. 4 3 2 1 0.97 0.98 0.99 1.00 1.01 1.02 1.03 0 3 6 9 12 15 18 Mo ba lan c Overfishing and ecosystem changes d rtalidad por pesca dirigida a camarón e o fer ta/ de ma n Supply/ demand balance  Fishing mortality on shrimp 37 Fisheries Applications: Posters – Arreguín-Sánchez & Salcido-Guevara 38 production (Libralato et al., 2006a). In addition, some of them were also associated to keystone species (degree, betweeness, closeness and mixed impacts) and keyplayers (related to fragmentation and propagation of the trophic network) indices (Jordan et al., 2006; Libralato et al., 2006b; Bogartii 2003). Results show a gradual change for all indices with change in fishing pattern, and at high harvesting rates, trends shift abruptly indicating an ecosystem disruption (Figure 1a). All indices show similar behavior independently of the attributes they are expressing, structural, functional or organization. Centrality indices of keystone species represent topological attributes and even when groups with higher ranking are usually different according to the properties they measure, some of them appear continuously such as phytoplankton, zooplankton and sharks, while functional index also select as keystone groups sharks and shrimps, as well as fishing fleets and detritus, when included. Some of these functional groups corresponded to main changes expressed by the interaction strength index. About keyplayers, sharks, serranids, other fishes, zooplankton and detritus are the relevant functional groups concerning the trophic network fragmentation; while marine mammals, seabirds, scianids, scombrids and sharks are the most relevant for the propagation properties of the foodweb (Figure 1b). Shark is a shared functional group for both indices which reveals its importance for the ecosystem. Three high trophic level functional groups, sea mammals, sea birds and scombrids, are also identified as relevant groups by the functional impact index. Results suggest all indices were sensible to changes in the fishing pattern, expressing different properties of the ecosystems; keystone and keyplayers indices identify relevant groups for the ecosystem and can potentially be used to monitor changes in the ecosystem. Results also agree with the concept that high trophic levels are of relevance for ecosystem maintenance. ACKNOWLEDGEMENTS This work was made possible with the support of CONACyT-SAGARPA (12004), Incofish (EC 003739), SPI-IPN (20090932), COFAA and EDI. REFERENCES Ainsworth, C., Pitcher, T.J., 2004. Modifying Kempton’s species diversity index for use with dynamic ecosystem simulation models. In: Pitcher, T.J. (ed.), Back to the Future: Advances in Methodology for Modelling and Evaluating Past Ecosystems as Future Policy Goals, pp. 91–93. Fisheries Centre Research Reports 12(1), 158 pp. Arreguín-Sánchez, F., Arcos, E., Chávez, E. A., 2002. Flows of biomass and structure in an exploited benthic ecosystem in the Gulf of California, Mexico. Ecol. Model. 156, 167-183. Banavar, J.R., Maritan, A., Rinaldo, A., 1999. Size and form in efficient transportation networks. Nature, 399, 130-132. Bendoricchio, G., Palmeri, L., 2005. Quo vadis ecosystem? Ecol. Model. 184, 5-17. Borgatti, S.P., 2003. The key player problem. In: Breiger, R., Carley, K., Pattison, P. (eds), Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pp. 241-252. Committee on Human Factors, National Research Council. Christensen, V., Pauly, D., 1992. ECOPATH II: a software for balancing steady-state ecosystem models and calculating network characteristics. Ecol. Model. 61, 169-185. Jordan, F., Wei-Chung, L., Davis, A.J., 2006. Topological keystone species: measures of positional importance in foodwebs. Oikos 112, 535-546. Libralato, S., Christensen, V., Pauly, D., 2006b. A method for identifying keystone species in food web models. Ecol. Model. 195, 153- 171. Libralato, S., Coll, M., Tudela, S., Palomera, I., Pranovi, F., 2006a. Quantifying effects of fishing on marine trophic webs. Fisheries Centre Working Papers Series 24, 1-48. Shannon, L., Cury, P., 2003. Indicators quantifying small pelagic fish interactions: application using a trophic model of the southern Benguela ecosystem. Ecol. Indicators 3, 305-321 Ulanowicz, R., 1986. Growth and Development: Ecosystems Phenomenology. Springer-Verlag, New York, 203 pp. Walters, C., Christensen, V., Pauly, D., 1997. Structuring dynamic models of exploited ecosystems from trophic mass balance assessments. Rev. Fish Biol. Fish. 7, 139-172 Ecopath 25 Years Conference Proceedings: Abstracts EFFECTS OF LOCAL FISHERIES AND OCEAN PRODUCTIVITY ON THE NORTHEASTERN IONIAN SEA ECOSYSTEM1 CHIARA PIRODDI Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada; c.piroddi@fisheries.ubc.ca GIOVANNI BEARZI Tethys Research Institute, Milano, Italy; g.bearzi@gmail.com VILLY CHRISTENSEN Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada; v.christensen@fisheries.ubc.ca This study describes a marine ecosystem in the northeastern Ionian Sea, western Greece. The study area covers 1021 km2 of sea surface (Figure 1). The bottom includes seagrass meadows (Posidonia oceanica and Cymodocea nodosa), sand, and mud (silt-clay) in areas deeper than 50 m (Zenetos et al., 1997; Haritonidis & Tsekos, 1976). A study conducted by Casotti et al. (2003) shows that this area is extremely oligotrophic. Values of Chlorophyll a, nutrients and particulate organic carbon were among the lowest found in Mediterranean coastal waters (Pitta et al., 1998). Most of the study area is quite shallow, ranging in depth between 100 to 200 m. Commercial fisheries in the study area include bottom trawlers, purse seiners, beach seiners and artisanal boats operating longlines and trammel nets (Bearzi et al., 2008). According to Tsikliras et al. (2007), about 70 species of fish, cephalopods and crustaceans are fished commercially in the area, with a few constituting the main targets: European pilchard (Sardina pilchardus); European anchovy (Engraulis encrasicolus); Mediterranean horse mackerel (Trachurus mediterraneus); Atlantic bonito (Sarda sarda); bogue (Boops boops); picarel (Spicara smaris); European hake (Merluccius merluccius); red mullet (Mullus barbatus) and striped red mullet (Mullus surmuletus).  Figure 1. The northeastern Ionian Sea ecosystem in western Greece covering 1021 km2 of sea surface. An Ecopath with Ecosim model was constructed for the northeastern Ionian Sea for the baseline year of 1964. This year was chosen because catch time series was available from 1964 to 2003. A total of 22 functional groups were considered in the model, including 3 marine mammal species, 1 sea turtle species, 1 sea bird, 8 fishes, 5 invertebrates, and 2 primary producer groups. European hake, European pilchard, round sardinella (Sardinella aurita) and European anchovy as well as the three species of marine mammals were considered separately due to their importance in the food web. For each group, 4 input parameters were estimated: biomass, production per unit of biomass (P/B), consumption per unit of biomass (Q/B) and diet composition.                                                  1 Cite as: Piroddi, C., Bearzi, G., Christensen, V., 2009. Effects of local fisheries and ocean productivity on the Northeastern Ionian Sea ecosystem. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 39-40. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 39 Fisheries Applications: Posters – Piroddi et al. 40 Ecosim was used to run dynamic simulations from the baseline Ecopath model for 1964, incorporating time series estimates (for the period 1964-2006) of biomass, bycatch, catch per unit effort (CPUE) and catches for those functional groups with available information. Time series of effort data (for the period 1964-2003) were then used to force the model. Ecosim scenarios were fitted by adjusting prey vulnerability and/or by searching for nutrient inload anomalies. Ecosim output scenarios were compared to observed time series data to get a goodness of fit (Christensen et al., 2005). The fit that best represented the ‘observed’ data was chosen (Figure 2).  Figure 2. Time series fitting between predicted and estimated functional groups biomass, CPUE and yield from 1964 to 2003 in the northeastern Ionian Sea, western Greece. Ecopath with Ecosim was able to reproduce quite well the biomass trend of important species such as common dolphins, sardines, anchovies, other pelagics and other demersals. The model suggested that the decline observed in various functional groups was a consequence of the intense fishing pressure that occurred in the area until the end of the 1990s. Moreover, Ecosim was able to explain the biomass trajectories of sardines, anchovies, other pelagics and other demersals, only when fishing effort pressure was combined with environmental factors, in particular changes in nutrient concentration. ACKNOWLEDGEMENTS We are particularly grateful to Joan Gonzalvo for providing fisheries data for the study area, and to Daniel Pauly for his advice throughout the study. V. Christensen acknowledges support from the National Science and Engineering Research Council of Canada, and the Sea Around Us Project, funded and initiated by the Pew ChariTable Trusts of Philadelphia. Our thanks also go to the Ionian Dolphin Project team and many other collaborators for contributing to field data collection and data analysis. We are grateful to Dimitrios Moutopoulos, Kostantinos I. Stergiou, Athanassios Tsikliras and Vassiliki Karpouzi for supplying Greek fisheries data and for technical advice during the development of this work. REFERENCES Bearzi, G., Agazzi, S., Gonzalvo, J., Costa, M., Bonizzoni, S., Politi, E., Piroddi, C., Reeves, R.R., 2008. Overfishing and the disappearance of short-beaked common dolphins from western Greece. Endangered Species Res. 5, 1-12. Casotti, R., Landolfi, A., Brunet, C., D'Ortenzio, F., Mangoni, O., Ribera d'Alcalà, M., Denis, M., 2003. Composition and dynamics of the phytoplankton of the Ionian Sea (eastern Mediterranean). J. Geophys. Res. 108 (C9), 8116. Christensen, V., Walters, C.J., Pauly, D., 2005. Ecopath with Ecosim: a User's Guide, November 2005 Edition. Fisheries Centre, University of British Columbia, Vancouver, Canada, 154 pp. Haritonidis, S., Tsekos, I., 1976. Marine algae of the Greek West coasts. Botanica Marina 19, 273–286. Pitta, P., Tsapakis, M., Zivanovic, S., Karakassis, I., 1998. Seasonal variability of water column biogeochemistry in three coastal areas in the Ionian and Aegean Seas. Rap. Comm. int. Mer Méditerranée 35, 284-285. Tsikliras, A.C., Stergiou, K.I., Moutopoulos, D.K., 2007. Reconstruction of Greek marine fisheries landings and comparison of national with the FAO statistics. University of British Columbia, Fisheries Centre Research Reports 15 (2), 163 pp. Zenetos, A., Christianidis, S., Pancucci, M.A., Simboura, N., Tziavos, C., 1997. Oceanological Study of an open coastal area in the Ionian Sea with emphasis on its benthic fauna and some zoogeographical remarks. Oceanologica Acta 20, 437-451.  Ecopath 25 Years Conference Proceedings: Abstracts TROPHODYNAMIC MODELLING OF THE EASTERN SHELF AND SLOPE OF THE SOUTH EAST FISHERY1 CATHERINE BULMAN SCOTT CONDIE NEIL KLAER DIANNE FURLANI MADELEINE CAHILL CSIRO Marine & Atmospheric Research, Castray Esp, Hobart, Tas 7007; Cathy.Bulman@csiro.au; Scott.Condie@csiro.au; Neil.Klaer@csiro.au; Dianne.Furlani@csiro.au; Madeleine.Cahill@csiro.au SIMON GOLDSWORTHY South Australian Research & Development Institute, 2 Hamra Ave, West Beach, SA 5024; goldsworthy.simon@saugov.sa.gov.au IAN KNUCKEY Fishwell, 22 Bridge St, Queenscliff, Vic 3225; fishwell@datafast.net.au In eastern Australia, fisheries have been operating since the early 1900s but the most dramatic changes have occurred much more recently (Tilzey & Rowling, 2001). On the shelf of New South Wales and north- eastern Victoria, steam trawlers and Danish seiners were the main fishing methods used initially and tiger flathead was the main target species but with very little formal management or co-ordinated research. In the late 1960s and early 1970s, diesel-powered otter trawlers enabled the rapid expansion of the fishery into the upper- and mid-slopes, along with more formal management arrangements and research albeit focussed on single species (Klaer, 2001). Now, the emergence of Ecologically Based Fishery Management has inspired the development of a whole ecosystem approach towards management issues (Pitcher, 2001). In the South East Fishery (SEF), increasing seal populations (Goldsworthy et al., 2003), discarding practices in the fishery and environmental variability on fishery production have been some of the issues of concern (Prince & Griffin, 2001). This project investigated their impact in an area of the SEF situated in the south-east corner Australia. We developed Ecopath with Ecosim models to describe the past and present structure and dynamics of the food web of the area, although we present here only the present day model and investigations. The area is in eastern Bass Strait (EBS), between 36° and 39S, and encompasses the shelf and slope from 25 to 700 m, at which point there is a major change in community composition. Bass Strait is the major influence but incursions from the East Australian Current occur seasonally as do wind-driven spring and summer upwellings on the outer shelf and slope. The surface water temperatures average around 13C, but are significantly cooler on the slope in winter and warmer on the shelf in summer. The shelf area consists of soft and hard grounds interspersed with reefy outcrops, and steep canyons can occur on the slope. We used CSIRO scientific data collected during multi-disciplinary surveys of the EBS during 1994-96 (Bax & Williams, 2000) and data from State and Commonwealth commercial fisheries. The 1994-96 study concluded that demersal fisheries were strongly linked to pelagic production. A hydrodynamic model of the average seasonal circulation demonstrated that this production occurs mainly in Bass Strait. Using a circulation model based on satellite altimetry and modelled winds, we computed the historical circulation for the period over which satellite estimates of plankton concentration and primary productivity (PP) were available (1997-2002). PP was estimated from ocean colour/chlorophyll concentration data from 1997                                                  1 Cite as: Bulman, C., Condie, S., Klaer, N., Furlani, D., Cahill, M., Goldsworthy, S., Knuckey, I., 2009. Trophodynamic modelling of the eastern shelf and slope of the South East Fishery. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 41-43. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 41 Fisheries Applications: Posters – Bulman et al. through to 2002 and a PP anomaly time series was derived to force the phytoplankton dynamics in the model. The model consisted of 58 groups covering the shelf and slope but focussed on commercial fishes, particularly, the quota-managed fishes, seals and birds. The scientific surveys identified more than 200 fish species which were allocated into model fish groups. Sharks and rays were the most abundant, followed by species including jack mackerel (Carangidae), barracouta (Gempylidae), whiptails (Macrouridae), cardinal fish (Apogonidae), redfish (Berycidae), cucumberfish (Chlorophthalmidae) and leatherjackets (Monocanthidae), all of which, except barracouta and whiptails, were explicitly modelled. Most of the SEF quota species were also explicitly modelled including mesopelagic fishes, which support both slope and shelf species, and create a transfer of energy from deep to shallow waters. All other fishes were aggregated into shelf, slope or pelagic groups, and further subdivided into three size groups (<30 cm, 30-50 cm and >50 cm standard lengths), and two feeding types (> or < 40 % fish in the diet). The invertebrate communities are highly diverse and show quite high endemism (Bax & Williams, 2000), however, were more aggregated because we knew less about them and our focus was on fishes and seals. Initial biomasses for most model groups were based largely on the 1994-96 CSIRO survey data. Catch and effort statistics were collated and used to construct catch, effort and CPUE time series. An observer monitoring program in the fishery provided information about the commercial and non-commercial bycatch, and was used to estimate the discarded catch not recorded in the fisher’s logbooks. Dietary information was derived primarily from the trophic study of the 1994-96 surveys (Bulman et al., 2001), supplemented by other studies in the SEF (Bulman et al., 2001, 2002; Young et al., 1997; Blaber & Bulman, 1987; Bulman & Blaber, 1986; Young & Blaber, 1986; Coleman & Mobley, 1984). Nine scenarios were devised to investigate the present system:  Reduced levels of primary productivity in the future: decreasing to 80 % and 60 % of current levels;  Growth in seal populations: annual biomass accumulation of 0, 5 or 10 % (=status quo);  Elimination of discarding in the fishery;  Changed rates of fishing effort: decreasing by 25 % or increasing by 25 % from current effort;  Various combinations of these conditions were investigated over a 50 year period: the first 10 years simulated 1994 to 2003 using observed effort time series, and the remaining 40 years was simulated at a constant fishing rate assuming the rate of the last year (2003) of observed data. We found that PP was sufficient to support the modelled ecosystem without the need to rely on importation of organisms such as phytoplankton and zooplankton by ocean currents. However, we predicted that if PP declined, e.g., as a result of warming as climate models predict, fish biomasses would also decline. When seal biomass increased, some commercial species such as sharks, blue-eye trevalla and ocean perch would also increase possibly because seals ate more of their predators even though their own prey declined. When seal biomass was not allowed to increase, predation pressure on prey species decreased allowing their populations to increase. However, gemfish, a seal prey species and a quota species that has been seriously overfished, did not stop declining as expected. Gemfish ate cardinal fish predominantly but so did some of those species released from predation by seals. Competition for cardinal fish increased, their biomass declined and consequently, gemfish continued to decline. Eliminating discarding by retaining all bycatch appeared to have little effect on the fish populations. Nearly all fisheries were predicted to have lower catches in the future, even if the fishing rate increased. Effort has declined over the past 10 years in most fisheries except the Commonwealth trawl fishery where it has risen. This has released fishing pressure on many species allowing some recovery. However this recovery was not necessarily sufficient to result in bigger predicted catches in the future compared to the current catches even if effort was increased. ACKNOWLEDGEMENTS This project was funded by an FRDC grant (No. 2002/028).   42 Ecopath 25 Years Conference Proceedings: Abstracts 43 REFERENCES Bax, N.J., Williams, A. (Eds.), 2000. Habitat and fisheries production in the South East Fishery ecosystem. Final Report to Fisheries Research Development Corporation. Project No. 94/040. 461 pp. Blaber, S.J.M., Bulman, C.M., 1987. Diets of fishes of the upper continental slope of eastern Tasmania: content, calorific, values, dietary overlap and trophic relationships. Mar. Biol. 95, 345–356. Bulman, C.M., Blaber, S.J.M., 1986. The feeding ecology of Macruronus novaezelandiae (Hector 1871) (Teleostei: Merluciidae) in south-east Australia. Aust. J. Mar. Freshw. Res. 37, 621–639. Bulman, C.M., He, X., Koslow, J.A., 2002. Trophic ecology of the mid-slope demersal community off southern Tasmania, Australia. Mar. Freshw. Res. 53, 59–72. Bulman, C.M., Althaus, F., He, X., Bax, N., Williams, A., 2001. Diets and trophic guilds of demersal fishes of the southeastern Australian shelf. Mar. Freshw. Res. 52, 537–548. Coleman, N., Mobley, M., 1984. Diets of commercially exploited fish from Bass Strait and adjacent Victorian waters, southeastern Australia. Aust. J. Mar. Freshw. Res. 35, 549–60. Goldsworthy, S. D., Bulman, C., He, X., Larcombe, J., Littnan, C., 2003. Trophic interactions between marine mammals and Australian fisheries: an ecosystem approach. In: Gales, N., Hindell, M., Kirkwood, K. (Eds), Marine Mammals and Humans: Towards a Sustainable Balance. University of Melbourne Press, Melbourne. Klaer, N.L., 2001. Steam trawl catches from south-eastern Australia from 1918 to 1957: trends in catch rates and species composition. Mar. Freshw. Res. 52, 399–410. Tilzey, R.D.J., Rowling, K.R., 2001. History of Australia’s South East Fishery; a scientist’s perspective. Mar. Freshw. Res. 52, 361-376. Pitcher, T.J., 2001. Fisheries managed to rebuild ecosystems? Reconstructing the past to salvage the future. Ecol. App. 11, 601–617. Prince, J.D., Griffin, D.A., 2001. Spawning dynamics of the eastern gemfish (Rexea solandri) in relation to regional oceanography in south-eastern Australia. Mar. Freshw. Res. 52, 611–622. Young, J.W., Blaber, S.J.M., 1986. Feeding ecology of three species of midwater fishes associated with the continental slope of eastern Tasmania. Mar. Bio. 93, 47–156. Young, J.W., Lamb, T.D., Le, D., Bradford, R.W., Whitelaw, A.W., 1997. Feeding ecology and interannual variations in diet of southern bluefin tuna, Thunnus maccoyii, in relation to coastal and oceanic waters off eastern Tasmania, Australia. Env. Biol. Fish. 50, 275–291.  Fisheries Applications: Posters – Chin et al. THE IMPACTS OF LONGLINE FISHERY ON THE PELAGIC ECOSYSTEM IN THE EASTERN TAIWAN WATERS1 CHIEN-PANG CHIN CHI-LU SUN Institute of Oceanography, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei City 10672, Taiwan; d97241003@ntu.edu.tw; chilu@ntu.edu.tw KWANG-MING LIU Institute of Marine Resource Management, National Taiwan Ocean University, 2 Pei-Ning Road, Keelung 20224, Taiwan; kmliu@mail.ntou.edu.tw Eastern Taiwan waters pelagic ecosystem consists of 17 functional groups (Table 1). Input parameters include biological information, diet compositions and yields of 17 functional groups, which are the main target species of longline-fishery and their preys, are estimated by single specie methods such as VPA, or collected from literatures. The uncertainty of dolphin’s biomass is also considered. Therefore, two different models are constructed in this study: one is run with a set biomass for dolphin, while the other sets dolphin biomass to be calculated. The impacts of the longline-fishery and of fishery management strategies on this marine ecosystem are simulated for a 15-years period with Ecosim. Table 1. Inputs (in parentheses) and outputs of the pelagic ecosystem model 1 in the eastern Taiwan waters. Group name Trophic Level OI Biomass (t·km2) P/B (year-1) Q/B (year-1) EE  Yield (t·km2) Dolphin 4.07 0.157 (3.125×10-4) (0.25) (17.239) 0.448 (3.125×10-5) Blue shark 3.99 0.166 (0.011) (0.3) (2.78) 0.793 (0.001) Lamniformes 4.16 0.144 (0.011) (0.22) (2.2) 0.419 (0.0009) Carcharhiniforms 4.16 0.144 (0.006) (0.23) (2.3) 0.515 (0.0007) Bigeye tuna 3.78 0.154 0.0021 (1.05) (10.5) (0.9) (0.0013) Yellowfin tuna 3.78 0.243 0.0025 (1.71) (11.64) (0.9) (0.0021) Other tunas 3.75 0.177 0.0072 (0.6) (6) (0.9) (0.0022) Swordfish 3.94 0.121 0.0030 (0.33) (3.3) (0.6) (0.0006) Blue marlin 3.99 0.145 0.0012 (0.604) (6.035) (0.6) (0.0005) Other billfishes 3.89 0.133 0.0020 (0.57) (5.7) (0.9) (0.0005) Dolphin fish 3.65 0.082 0.0118 (1.681) (8.48) (0.9) (0.006) Scombrids 3.2 0.508 0.0231 (3.37) (32.57) (0.9) (0.0296) Cephalopod 3.16 0.022 0.0986 (2.5) (25) (0.9) (0.006) Flying fish 2.56 0.309 0.0242 (2) (20) (0.9) (0.0001) Epipelagic fishes 2.6 0.385 4.3160 (2) (10) (0.9) (2.9556) Epipelagic micronekton 2.11 0.111 4.0109 (50) (200) (0.5) - Phytoplankton 1 -- 3.7196 (400) -- (0.5) -  In the eastern Taiwan pelagic ecosystem, sharks (lamniforms and carcharhiniforms) are the top predators, with trophic level of 4.16. The blue shark is the most abundant large shark species and has a lower trophic level than lamniforms and carcharhiniforms. The ecopath results of the two models are similar, even though the biomass of dolphins in model 2 was 10 times than that set for model 1. It is also suggested that dolphins had little effect on other species. Ecosim simulations indicate that lamniforms and carcharhiniforms are overfished. However, the exploitation rate of blue shark appears to be sustainable. Furthermore, various changes in the abundances of many species may occur, due to the removal of large sharks from this marine ecosystem. Biomasses of ‘other billfishes’, ‘other tunas’ and ‘blue marlin’ in model 1 increased by 180 %, 96.8 % and 42.5 %, respectively (Figure 1.). In contrast, ‘cephalopod’ and ‘flying fish’                                                  1 Cite as: Chin, C.P., C., Sun, C.L., Liu, K.M., 2009. The impacts of longline fishery on the pelagic ecosystem in the eastern Taiwan waters. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 44-45. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 44 Ecopath 25 Years Conference Proceedings: Abstracts 45 biomasses decreased by 10.9 % and 20.9 %, respectively (Figure 1.). The keystoness index also suggested that large sharks played an important role in this pelagic ecosystem. A biological reference point of F35% for lamniforms and carcharhiniforms species was proposed. Scombrids and dolphinfishes have the strongest keystone effects, which may be due to the decrease of top-down control by top predators, such as large sharks, tuna and swordfish species, which were heavily removed from this ecosystem by longline vessels. Longline-fishery had positive effects on dolphinfish and marine mammals by removal of both their predators and competitors for preys, though exerts a negative impact on other target species. Therefore, a decrease of longline-fishery efforts may result in a recovery of large sharks, tuna and swordfish species. The ban on dolphin fishery may increase the biomass of dolphins above 50 % of the current biomass (Figure 2.). The effects of increase in dolphin biomass might be due to the other species, besides dolphin fish, whose biomass decreased by 15 % in model 2 (Figure 2.). Variation of biomass (%) -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Fu nct ion al g rou ps Dolphin Blue shark Lamniformes Carcharhiniforms Bigeye tuna Yellowfin tuna Other tunas Swordfish Blue marlin Other billfishes Dolphin fish Scombrids Cephalopod Flying fish Epipelagic fishes Epipelagic micronekton Phytoplankton Scenario 9 Scenario 10  Variation of biomass (%) -1.0 -0.5 0.0 0.5 1.0 Fu nct ion al g rou ps Dolphin Blue shark Lamniformes Carcharhiniforms Bigeye tuna Yellowfin tuna Other tunas Swordfish Blue marlin Other billfishes Dolphin fish Scombrids Cephalopod Flying fish Epipelagic fishes Epipelagic micronekton Phytoplankton Scenario 33 Scenario 34  Figure 1. The variations of biomass in percentage of functional groups included in the the pelagic ecosystem of the Eastern Taiwan water (The removaling large shark from ecosystem). Figure 2. The variations of biomass in percentage of functional groups included in the the pelagic ecosystem of the Eastern Taiwan water (The dolphin fishery is banned).  Spatial Analysis – Poonsawat et al. INTRODUCING ECOSYSTEM-BASED MANAGEMENT IN THE GULF OF THAILAND1 RATANAWALEE POONSAWAT Upper Gulf Fisheries Research and Development Center, Bangpoeng, Praviriyapon Road, Prapradaeng, Samuth Prakarn Province BKK 10120, Thailand; ratvaree@yahoo.com MALA SUPONGPAN Department of Fisheries, Chulabhon Building, 2nd Floor, Kasetsart University Campus, Bangkok 10900, Thailand;  m.supongpan@gmail.com VILLY CHRISTENSEN Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada; v.christensen@fisheries.ubc.ca There is growing interest for ecosystem-based management in the Gulf of Thailand. The Thai sector of the Gulf has been intensively exploited since trawling was introduced in the early 1960s, and the ecological communities in the Gulf have been changed substantially because of high fishing pressure. To evaluate alternative management options we have further developed an ecosystem model of the Gulf in connection with a European Union project aimed at evaluating the societal cost of fishing. Our objective here is to propose and evaluate possible fishery management measures based ecosystem analysis. The model, which was constructed using the Ecopath with Ecosim approach and software, relies on extensive data series collected in the Thai sector of the Gulf. Time series of catch per unit effort of the various fish groups were obtained from research vessel data, while fishing effort of the six fleets in the model (otter board trawl, pair trawl, beam trawl, push net, purse seine and other gear) were obtained from statistical record from the years 1973 to 2004. Outputs from the simulations were used to compare the fishery status and changes during 1973, 2005 and to evaluate the prediction for 2010. The results indicate lower catches, values and profit for all otter board trawler, pair trawler, beam trawler, and push netter from 1973 to 2005 and 2010, while the changes were minimal for the purse seiner and other gears. We conducted optimum policy searches by placing different weights on social, ecological, and economical criteria to evaluate the predicted changes in fishing effort for the six fleets that would be indicated for optimization. We found that if the effort of the otter board trawler was reduced it would benefit the pair trawler, the push netter and other gears, and vice versa. The relative catches of the total multi-species aggregate also decreased except for some pelagic fish groups. The relative biomasses of all groups are currently in a bad situation (values at 0.01-0.4 relative to the baseline). The medium demersal piscivores, juvenile pelagic fish and juvenile carangids are in a better situation. When considering the pressure caused by overexploitation, the excessive number of fishing boats, the lower catch levels, values, profits, the effects on economic, social and ecosystem, the yield and biomass of the fisheries in the Gulf of Thailand, it was concluded that a reduction in effort would be beneficial in the Gulf, and that in order to evaluate tradeoff between fisheries, the management of the fisheries in the Gulf of Thailand need to include an ecosystem-approach. Recommendations were made on a ban of push netter and beam trawler, reduction in effort of otter board trawler and pair trawler on a voluntary bases, introduction of a tenure system for purse seiner apart from bottom trawler and pair trawler that remains active, required registration for other gear, more areas and season closures (or introduction of MPAs), stock enhancement, and promotion of co-management for coastal small-scale fisheries.                                                  1 Cite as: Poonsawat, R., Supongpan, M., Christensen, V., 2009. Introducing ecosystem-based management in the Gulf of Thailand. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 46. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 46 Ecopath 25 Years Conference Proceedings: Abstracts TROPHIC ANALYSIS OF LAKE AWASSA (ETHIOPIA) USING A MASS-BALANCED ECOPATH MODEL1 TADESSE FETAHI SEYOUM MENGISTOU Department of Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia; t_fetahi@yahoo.com Lake Awassa is one of the most-thoroughly studied lakes in Ethiopia. In spite of this, , no attempt has been made to bring the available information together in order to understand the food-web relationship of this lake ecosystem. Perhaps one of the plausible reasons for not pursuing such studies so far in Ethiopia was the lack of comprehensive and easy-to-use models. To fill this gap, literature data were obtained to estimate parameters (see Table 1) to build an Ecopath model (using EwE version 5.0 beta) representing the lake ecosystem for the period November 2003-August 2004. Table 1. Parameters used in the Ecopath with Ecosim model (v. 5.0 beta) of lake Awassa (Ethiopia) for November 2003 to August 2004. Food intake is calculated as Q/B*B and GE, i.e., gross efficiency is calculated as (P/B)/(Q/B) and is usually between 0.1 and 0.3 (see Christensen et al., 2000). Species/group  Trophic level Yield (t·km-2·year-1) Biomass (t·km-2) P/B (year−1) Q/B (year−1) EE Food intake GE Catfish 3.34 5.11a 3.288a 1.4a 4.75b 0.96 15.6 0.295 Juvenile Catfish 3.45  0.358d 0.5b 9.2b 0.916 3.3 0.054 Large Labeobarbus 3.19  1.081d 0.33b 20.38b 0.992 22.0 0.016 Tilapia 2.02 6.97b 3.71b 1.8b 29.53b 1 109.6 0.061 Juvenile Tilapia 2.61  2.4d 1.2b 41.64b 1 99.9 0.029 Aplocheilichtys 3.1  0.714b 3.5b 36.51b 0.999 26.1 0.096 Small Barbus 3.18  1.093d 2.59b 18.51b 0.992 20.2 0.14 Garra sp. 3.06  0.192d 2.68b 17.08b 0.894 3.3 0.157 Zoobenthos 2.09  41.95b 4.3b 21.05b 1 883.0 0.204 Carnivore zooplankton 2.72  2.53c 20c 93.88b 1 237.5 0.213 Herbivore zooplankton 2  1.78c 118.2c 538.86b 1 961.3 0.219 Phytoplankton 1  34.45b 238.5b  0.144   Macrophytes 1  200b 1  0.644   Detritus 1  63.79b   0.104   a: Tekle-Giorgis (2002); b: present study; c: Mengistou (1989); d: guess estimates.  Thirteen functional groups including two ontogenic ones considered in the model resuted to the flow diagram for Lake Awassa illustrated in Figure 1. The producers particularly phytoplankton and detritus are under exploited in this lake ecosystem. Hence, energy transfer from lower trophic levels is low. On the contrary, all consumers have ecotrophic efficiencies (EE) close to 1 indicating that consumers are heavily exploited in the system. Flow from detritus was as important as flow from phytoplankton. Flows from both herbivorous and carnivorous zooplankton to consumers were high. Mixed Trophic Impact (MTI) analyses indicated that phytoplankton and detritus have positive impact on most other groups while zoobenthos has negative impact on some groups. Lake Awassa has low ecological efficiency with a value of 0.00144 for the gross efficiency of the fisheries. The system primary production/respiration (P/R) ratio of Lake Awassa is 5.834 showing that the lake is at developmental stage, with high autotrophy, and some attention should be given to human impacts. This trophic model analysis also enabled us to confirm/refute previous studies and pinpoint critical gaps in the present knowledge about Lake Awassa.                                                  1 Cite as: Fetahi, T., Mengistou, S., 2009. Trophic analysis of Lake Awassa (Ethiopia) using a mass-balanced Ecopath model. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 47-48. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 47 Spatial Analysis – Fetahi & Mengistou 48  Figure 1. Trophic structure and flow diagram of the Lake Awassa ecosystem for the period November 2003 to August 2004. REFERENCES Christensen, V., Walters, C.J., Pauly, D., 2000. Ecopath with Ecosim: A User's Guide. Fisheries Center, Univeristy of British Columbia, Vancouver and ICLARM, Malaysia. Tekle-Giorgis, Y., 1990. Age Determination and Growth Estimation of Immature Oreochromis niloticus Linn. (Pisces: Cichlidae) in Lake Awassa, Ethiopia. MSc Thesis. Univeristy of Waterloo, Canada. 137 p. Mengistou, S., 1989. Species Composition, Dynamics and Production of the Dominant crustacean Zooplankton in Lake Awassa, Ethiopia. PhD Thesis. University of Waterloo, Ontario, Canada. 228 p.  Ecopath 25 Years Conference Proceedings: Abstracts SPATIAL ANALYSIS: ORAL PRESENTATIONS ECOSPACE: HAS ITS TIME COME?1 STEVE MACKINSON CEFAS Lowestoft Laboratory, Pakefield Road, Lowestoft, Suffolk, NR33 0HT, UK, Tel: +44 (0) 1502 524584;steve.mackinson@cefas.co.uk Born in 2000, amidst rapidly growing international political and scientific interest on the use of Marine Protected Areas as fisheries management tools, Ecospace enabled users to probe the what if questions of spatial management. Beattie et al. (2002) developed Ecoseed, which provided the means to investigate trade-offs between the number, size and location of MPAs. Although applications of Ecospace (Walters et al., 1998) are not as prevalent or as well developed as those of Ecosim, with spatial management plans becoming increasingly popular, the issues that need to be addressed are equally pressing. This session showcases applications of Ecospace, seeks to identify the type of problems for which this tool is well suited, and promotes future development on validation and linking with spatial planning tools. REFERENCES Beattie, A., Sumaila, U.R., Christensen, V., Pauly, D., 2002. A model for the bioeconomic evaluation of marine protected area size and placement in the North Sea. Natural Res. Model. 15(4), 413-437. Walters, C., Pauly, D., Christensen, V., 1998. 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.                                                   1 Citeas: Mackinson, S., 2009. Ecospace: has its time come? In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 49. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 49 Spatial Analysis – Daskalov et al. EVALUATION OF THE USEFULNESS OF MARINE PROTECTED AREAS (MPAS) FOR MANAGEMENT OF RECOVERY OF FISH STOCKS AND ECOSYSTEMS IN THE NORTH SEA1 GEORGI M. DASKALOV STEVE MACKINSON CEFAS Lowestoft Laboratory, Pakefield Road, Lowestoft, Suffolk, NR33 0HT, UK, Tel: +44 (0) 1502 524584; georgi.daskalov@cefas.co.uk; steve.mackinson@cefas.co.uk HONG Q. CHENG State Key Laboratory of Estuarine & Coastal Research East China Normal University Zhongshan North 3663 Shanghai, 200062 China; hongjiang0822@yahoo.com.cn JOHN K. PINNEGAR CEFAS Lowestoft Laboratory, Pakefield Road, Lowestoft, Suffolk, NR33 0HT, UK, Tel: +44 (0) 1502 524584; john.pinnegar@cefas.co.uk Marine Protected Areas (MPAs) are increasingly being promoted as an important component of precautionary management both by governments and environmental organisations. Several large MPA’s have been established in the North Sea under the Bergen declaration and under the EU Habitat and Bird directives, many more are planned. In addition ‘boxes’ closed for fishing have been established as a result of the European Commission’s efforts to protect fish stocks under the Common Fishery Policy. By integrating organism dispersal rates, ecosystem interactions and fishing effort dynamics, Ecospace (Christensen et al., 2005), a spatially explicit ecosystem-based modelling tool, allowed us to compare the ecological consequences of different management options, including existing and proposed North Sea MPAs. Ecospace has been designed and is successfully applied to evaluate effects of Marine Protected Areas (MPA) on abundance and distribution of fish and associated fisheries and ecosystem changes (Martell et al., 2005; Walters et al., 1999,). The North Sea Ecospace model was developed on the basis of a detailed mass-balance trophic (Ecopath with Ecosim) model (Mackinson & Daskalov, 2007). Data from the International Bottom Trawl Survey (IBTS) and beam trawl surveys (for benthos) were used for validation of the Ecospace estimates. Data matrices of data per ICES rectangle were created for most of the functional groups (subject to availability of data) for the period 1983-2005. We used modelled MPAs to evaluate the effects of different regimes of fisheries closure and compare existing (‘Sandeel box’, ‘Plaice box’, ‘Cod box’) and planned MPAs. Simulated fisheries closures proved to have significant effect in terms of fishery yield, spatial patterns of fishing effort displacement and impacts on predators, competitors and prey. The effects of an MPA are illustrated by the simulations with the ‘sandeel box’ – an area along the Scottish coast where the sandeel fishery has been banned since 2001. The fisheries closure in our simulations had a significant effect on sandeel biomass, which increased by 10 % (Figure 1).                                                  1 Cite as: Daskalov, G.M., Mackinson, S., Cheng, H.Q., Pinnegar, J.K., 2009. Evaluation of the usefulness of Marine Protected Areas (MPAs) for management of recovery of fish stocks and ecosystems in the North Sea. In: Palomares, M.L.D., Morissette, L., Cisneros- Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 50-51. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 50 Ecopath 25 Years Conference Proceedings: Abstracts 51 In addition, the effects on sandeel also had indirect consequences for predators. Within the ‘sandeel box’ seabird biomass increased, but decreased elsewhere. Within the ‘sandeel box’ many higher trophic level fish predators (especially whiting) also increased in biomass by up to 11 %. Similar effects were found to be associated with the ‘plaice’ and ‘cod boxes’.  Figure 1. Change in biomass density (t/km2) of sandeel after ‘closing’ the fisheries in the ‘sandeel box’ within Ecospace. MPA ‘sandeel box’ is shown on the embedded basemap in right lower corner. Modelling of MPAs in the North Sea highlighted the problem of re-allocation of fishing fleets. In the model, increases in the target species were observed within the MPAs, but catches were higher elsewhere as a result of displaced effort, and this led in some cases to overall stock decrease following the a introduction of an MPA. ACKNOWLEDGEMENTS This work was supported by the EU funded projects Incofish, Reclaim, and Uncover, and UK Defra MF1202 STEEM project. REFERENCES Christensen, V., Walters, C., Pauly, D., 2005. Ecopath with Ecosim: A User’s Guide. Fisheries Centre, University of British Columbia, Vancouver. Mackinson, S., Daskalov, G., 2007. An Ecosystem Model of the North Sea to Support an Ecosystem Approach to Fisheries Management: Description and Parameterisation. Sci. Ser. Tech Rep. Cefas Lowestoft, 142, 196pp. Martell, S.J.D., Essington, T., Lessard, B., Kitchell, J.F., Walters, C.J., Boggs, C.H., 2005. Interactions of productivity, predation risk and fishing effort in the efficacy of marine protected areas for the central Pacific. Can. J. Fish. Aquat. Sci. 62, 1320-1336. Walters, C., Pauly, D., Christensen, V., 1999. Ecospace: predictions of mesoscale spatial patterns in trophic relationships of exploited ecosystems, with empahsis on the impacts of marine protected areas. Ecosystems 2, 539–554. Spatial Analysis – Lozano-Montes et al. MODELLING SPATIAL CLOSURES AND FISHING EFFORT RESTRICTIONS IN JURIEN BAY, WESTERN AUSTRALIA: A CASE STUDY OF THE WESTERN ROCK LOBSTER (PANULIRUS CYGNUS) FISHERY1 HECTOR M. LOZANO-MONTES RUSS BABCOCK CSIRO Marine and Atmospheric Research, Underwood Avenue, Floreat, Western Australia. 6014; hector.lozano-montes@csiro.au; russ.babcock@csiro.au NEIL R. LONERAGAN Centre for Fish and Fisheries Research, School of Biological Sciences and Biotechnology, Murdoch University, South Street, Murdoch Western Australia 6150; N.Loneragan@murdoch.edu.au Temperate Western Australia supports the valuable western rock lobster fishery and the production of fish for commercial and recreational fishers. The western rock lobster fishery has been Australia’s most valuable single species fishery for many years with an average annual catch of about 10 000 tonnes, valued from about 200 to 400 million USD (Department of Fisheries, WA, 2004). The centre of this fishery is located at about 30ºS, near Jurien Bay about 200 km north of Perth. The Jurien Bay Marine Park, declared in August 2003 (CALM, 2005), protects the biological communities in an important section of Western Australia’s central west coast and provides shelter and nursery areas for marine life, including finfish and crustaceans and it is likely to be representative of the marine biodiversity of the central coast of Western Australia (see Wernberg et al., 2006). Despite the lack of any major upwelling zones and the presence of low nutrient marine waters (Caputi et al., 1996), the temperate waters of Western Australia support important commercial and recreational fisheries targeting western rock lobster, West Australian dhufish (Glaucosoma hebraicum), pink snapper (Pagrus auratus), baldchin grouper (Choerodon rubescens) and Roe’s abalone (Haliotis roei) (Department of Fisheries, WA, 2006). This marine park contains different levels of protection with ‘no-take’ sanctuary zones (~4 % of the total area), scientific reference zones (~18 %) that allow fishing for rock lobster and minor fisheries from the shore, and general use zones (~78 %) where all activities are allowed. This means that over 20 % of the park is no longer accessible to fishing for finfish and around 4 % is closed to lobster fishing and all forms of fishing. Understanding the impacts of fishing on the trophic structure of systems has become increasingly important because of the introduction of Ecosystem Based Fisheries Management and the legislative requirements of fisheries to demonstrate that they are not having a negative impact on other species in the environment. Knowledge of trophic linkages and food webs is also critical for developing zoning plans for marine parks and gaining an understanding of the potential effects of no-take or sanctuary zones on trophic flows. The closures to fishing declared as part of the Jurien Bay Marine Park are administered by the Western Australia Department of Environment and Conservation are intended to conserve marine biodiversity and ecosystem function. However, the potential effectiveness of the fishing closures for protecting both fished and unfished species of fish and invertebrates (at scales relevant to fisheries) is very uncertain and has been a source of controversy (e.g., Hilborn et al., 2004; Nardi et al., 2004; Mayfield et al., 2005; Edgar et al., 2007). The aim of this study was to develop a biomass-based dynamic model of Jurien Bay Marine Park to investigate the effectiveness of fishing closure areas on both the western rock lobster fishery and the overall functioning of this system. The Ecopath model comprised 80 functional groups including primary producers, the main species of benthic, demersal and pelagic invertebrates, fishes and non-fish vertebrates and five detritus groups. The Jurien Bay Marine Park map (latitude 31°N-30°N; longitude 114.95°E-                                                  1 Cite as: Lozano-Montes, H.M., Babcock, R., Loneragan, N.R., 2009. Modelling spatial closures and fishing effort restrictions in Jurien Bay, Western Australia: a case study of the western rock lobster (Panulirus cygnus) fishery. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 52-54. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727].165 p. 52 Ecopath 25 Years Conference Proceedings: Abstracts 115.05°E) used for Ecospace simulations (area=823 km2) was drawn on a grid of 60 by 100 cells (each approximately 2.25 km2) with dispersal rates assumed to be of 3, 30 and 300 km yr-1, representing nondispersing, demersal and pelagic groups, respectively. All Ecospace parameters were retained at default setting unless otherwise specified. The Ecospace habitat base map was designed on the detailed marine biological surveys carried by Burt & Anderton (1997) over 60 km of coastline off the central west coast of Western Australia, from Cervantes to Green Head. Using this comprehensive survey, it was possible to include the major habitat types and management zones of the park. The effectiveness of the closure areas were explored using three Ecospace scenarios (with 5, 10, 15 and 20-year simulations each; and 2007 as baseline): (1) sanctuaries zones covering 4 %of the total area; (2) sanctuaries zones increased to 25 % of total area; and (3) No sanctuaries. Our simulations suggest that the introduction of the current management zones with 4 % of sanctuaries produced a modest benefit of ~5 % in the biomass of rock lobster after 20 years. However, rock lobster biomass increased to ~20 % when the sanctuary area covered 25 % of the park, indicating the positive effect of protection provided by this zone. Similar trends were observed for exploited fish species (e.g., pink snapper, dhufish, sharks, among others) were the benefits of increasing the sanctuary areas from 4 % to 25 % produced increments up to 30% in their biomass (Figure 1). On the contrary, a clear decline in the abundance of the main resources of the region was displayed when the closure zones (sanctuaries and scientific reference zones) were removed from the model. After 20 years of open fishing in the park, the biomass of rock lobster declined to 85 % of the 2007 level and the abundance of other target species such as dhufish and pink snapper were reduced to 70% of the baseline abundances (Figure 1). The present simulations indicate that the fishing closures in Jurien Bay Marine Park can lead to increments in the abundance of exploited resources. However, an outcome beneficial to fisheries and overall abundances is not guaranteed. At this stage of the model development, the reliability of the spatial patterns and abundances predicted have to be verified with experts before running further scenarios and evaluate the impact of closures in the fishery and system status. Results from this study improved our understanding of the dynamics and interactions of the components of this marine ecosystem, a key factor in predicting the influence of closed areas within the Park. 0 0.5 1 1.5 Bio ma ss (En d/S tar t) Rock lobster 0 0.5 1 1.5 Bio ma ss  (E nd /St art ) Pink snapper 0 0.5 1 1.5 Bio ma ss  (E nd /St art ) Dhufish 0 0.5 1 1.5 2007 2012 2017 2022 2027 Bio ma ss  (E nd /St art ) 4% Sanctuary 25% Sanctuary No Sanctuaries Sharks  Figure 1. Simulated biomass responses of the main target species in Jurien Bay Marine Park, Western Australia to three MPA simulations. REFERENCES Burt, J.S., Anderton, S.M., 1997. Results of the Biological Survey of the Major Benthic Habitats of Jurien Bay and Surrounding Waters (Cervantes-green Head): 21 April-9 May 1997. Report MRIP/MW/J-07/1997. Marine Conservation branch. Department of Conservation and Land Management. Western Australia. CALM, Department of Conservation and Land Management, 2005. ‘Marine Conservation Reserves in Western Australia- Jurien Bay Marine Park’. Available: http://www.calm.wa.gov.au/national parks/marine/jurien [accessed 19 July 2007]. Caputi, N., Fletcher, W.J., Pearce, A., Chubb, C.F., 1996. Effect of the Leewin Current on the Recruitment of Fish and Invertebrates along the Western Australia Coast. Mar. Freshw. Res. 47, 147-155. Department of Fisheries, 2004. ‘Commercial Fisheries of Western Australia – western rock lobster’. Available http://www.fish.wa.gov.au/docs/cf/RockLobster/index.php?0206 [accessed 12 June 2007]. Department of Fisheries, 2006. Commercial and Recreational Fishing Guide. West coast Region. Government of Western Australia, January 2006. 37p. 53 Spatial Analysis – Lozano-Montes et al. 54 Edgar G.J., Russ, G.R., Babcock, R.C., 2007. Marine protected areas. In: Connell, S.D., Gillanders, B.M. (eds), Marine Ecology, pp 534-565. Oxford University Press. ISBN: 0195553020. Hilborn, R., Stokes, K., Maguire, J.J., Smith, T., Botsford, L.W., Mangel, M., Orensanz, J., Parma, A., Rice, J., Bell, J., Cochrane, K.L., Garcia, S., Hall, S.J., Kirkwood, G.P., Sainsbury, K., Stefansson, G., Walters, C., 2004. When can marine reserves improve fisheries management? Oceans Coast. Manage. 47, 197-205. Mayfield, S., Branch, G.M., Cockcroft, C., 2004. Role and efficacy of marine protected areas for the South African rock lobster, Jasus lalandii. Mar. Freshw. Res. 56, 913-924. Nardi, K., Jones, G.P., Moran, M.J., Cheng, Y.W., 2004. Contrasting effects of marine protected areas on the abundance of two exploted reef fishes at the sub-tropical Houtman Abrolhos Islands, Western Australia. Environ. Cons. 31, 160-168. Wernberg T., Vanderklift, M.A., How, J., Lavery, P.S., 2006. Export of detached macroalgae to seagrass beds from adjacent reefs. Oecologia 147, 692-701 Ecopath 25 Years Conference Proceedings: Abstracts A TROPHIC MODEL TO SIMULATE THE COMBINED EFFECT OF ARTISANAL AND RECREATIONAL FISHERIES ON A MEDITERRANEAN ECOSYSTEM: THE BONIFACIO STRAITS NATURAL RESERVE (CORSICA, FRANCE)1 CAMILLE ALBOUY Université Montpellier II Place Eugéne Bataillon laboratoire ECOLAG UMR 5119 34090, Montpellier, France; albouycamille@gmail.com FRANÇOIS LE LOC’H UMR EME, IRD Avenue Jean Monnet BP 17 Centre de recherche halieuthique méditerranéenne et tropicale 34203, Sète, France; francois.le.loch@ird.fr JEAN MICHEL CULIOLI O.E.F base technique et scientifique de la rondinara BP507 20169, Bonifacio, France; culioli@oec.fr DAVID MOUILLOT Université Montpellier II Place Eugéne Bataillon laboratoire ECOLAG UMR 5119 34090, Montpellier, France; mouillot@University-montp2.fr Human activities have provoked unprecedented threats on coastal marine systems including direct and indirect effects of fishing (Halpern et al., 2008). Indeed, major changes in exploited biological assemblages, and ultimately, biodiversity loss may disrupt ecosystem functioning and then alter the sustainability of goods and services provided by marine ecosystems to humanity (Lotze et al., 2006; Worm et al., 2006). To reduce such impacts of global overexploitation of fish stocks, stakeholders and managers of marine protected areas (MPA) are waiting for scientists to provide tools enabling them to test the effectiveness of environmental control. Assessment methods and predictive models such as EwE can be adapted for investigating the benefits of MPAs on adjacent fisheries. Our study is applied to the Bonifacio Straits Natural Reserve (BSNR, 80 000 ha, Figure 1) created in 1999 in Corsica (France, Mediterranean Sea). The BSNR is characterized by a predominantly rocky substrate which is an archetypal ecosystem known to be one of the most impacted by human activities around the world (Halpern et al., 2008). Several controlled perimeters are defined within the reserve; no-take zones closed to fishing (reserves, cantonments) and strengthened  Figure 1. Map of the Bonifacio straits natural reserve, Corsica, France, Mediterranean Sea. Discontinued line designates the no-take zone; long dashed line the fishing cantonments; dotted line the semi protected areas where spear fishing is forbidden; and white line the reserve’s perimeter.                                                  1 Cite as: Albouy, C., Le Loch, F., Culioli, J.M., Mouillot, D., 2009. A trophic model to simulate the combined effect of artisanal and recreational fisheries on a Mediterranean ecosystem: the Bonifacio Straits Natural Reserve (Corsica, France). In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 55-56. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727]. 167 p. 55 Spatial Analysis – Albouy et al. 56 protected areas (spearfishing prohibited) opened to fishing (Figure 1). The artisanal fleet operating within the perimeter of the reserve is monitored annually since 2000. However, recreational fleets (boat, spear- fishing) still need to be studied. An Ecopath model was created on the entirety of the BSNR, including 32 trophic groups, of which 12 are fish. The majority of the data used to build the model were obtained from the database of BSNR (e.g., fleets, crustacean studies, species list), and of EwE models built previously for Corsica and the Mediterranean. Ecopath indicators of ecosystem maturity show that the BSNR model is in accordance with other Ecopath coastal models (Libralato et al., 2008; Christensen & Pauly, 1993) and with the theory of trophic flows, which suggests realistic features of the model despite uncertainties. An Ecosim model was built to study the combined effects of artisanal and recreational fisheries on a Mediterranean ecosystem within a multi-specific context. Simulations of variations in fishing efforts were conducted during 20 years. The initial value of fishing effort was set to 1 for both fishing types (effort measured in 2000-2001) and varied from 0 to 4 by steps of 0.2 (a total of 440 simulations). We demonstrated that both fishing activities have an additional top down effect on the food web and decreased the biomass of targeted groups such as piscivorous species (Figure 2.). We also found non trivial patterns of biomass variations that emerge for some groups when the two fishing activities produce unexpected trophic cascades. Our trophic approach revealed that some species groups may provide negative signals of biomass decrease (Figure 2.) when MPAs are set or reinforced due to a combined effects of artisanal and recreational fisheries.  Figure 2. Combined effect of changes in fishing effort of recreational and artisanal fleets on three modelled groups of the Bonifacio straits natural reserve, Corsica, France, Mediterranean Sea. Following this analysis an Ecospace model was developed taking into account reserve areas, together with their degrees of protection, the different types of fleets (recreational and professional), fishing zones, and affinities of species to their substrates. Different scenarios, a decrease of the Posidonia oceanica meadow and an increase of non take areas were tested to demonstrate the effectiveness of management measures throughout the food web. REFERENCES Christensen, V., Pauly D., 1993. Flow characteristics of aquatic ecosystems. In: Christensen, V., Pauly, D. (eds.), Trophic Models of Aquatic Ecosystems, p. 339-355. ICLARM Conference Proceedings 26. ICLARM, Manila, Philipines. Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D'Agrosa , C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., Watson, R., 2008. A global map of human impact on marine ecosystems. Science 319(5865), 948-952. Libralato, S., Coll, M., Tudela, S., Palomera, I., Pranovi, F., 2008. Novel index for quantification of ecosystem effects of fishing as removal of secondary production. Marine Ecol. Progr. Ser. 355, 107-129. Lotze, H., Lenihan, H., Bourque, B., Bradbury, R., Cooke, R., Kay, M., Kidwell, S., Kirby, M., Peterson, C., Jackson, J., 2006. Depletion, degradation, and recovery potential of estuaries and coastal seas. Science 312(5781), 1806-1809. Worm, B., Barbier, E., Beaumont, N., Duffy, J., Folke, C., Halpern, B., Jackson, J., Lotze, H., Micheli, F., Palumbi, S., Sala, E., Selkoe, K., Stachowicz, J., Watson, R., 2006. Impacts of biodiversity loss on ocean ecosystem services. Science 314(5800), 787-790. Ecopath 25 Years Conference Proceedings: Abstracts TROPHIC MODELING OF A TEMPERATE MARINE ECOSYSTEM THROUGHOUT MARINE RESERVE PROTECTION IN NEW ZEALAND1 TYLER D. EDDY JONATHAN P.A. GARDNER Centre for Marine Environmental and Economic Research. School of Biological Sciences, Victoria University of Wellington, Coastal Ecology Laboratory, 396 The Esplanade, Island Bay, New Zealand; tyler.eddy@vuw.ac.nz; jonathan.gardner@vuw.ac.nz Marine Reserves (MRs) in New Zealand are being monitored and investigated to determine implications for conservation and management strategies. This research project employs a variety of techniques to answer questions about how MRs impact biological communities and what this means for the management of coastal resources. Underwater research at three central New Zealand MRs (Kapiti MR, Long Island MR and the newly implemented Taputeranga MR; see Figure 1) conducting seasonal size and abundance surveys of reef fish, invertebrates and algae at both protected and unprotected locations is used to determine biomasses of trophic groups. Monitoring data also exists prior to and throughout MR protection, which is used to determine ecosystem response to protection in temperate central New Zealand waters. This monitoring information is used in combination with biological data from the literature to describe trophic linkages within the ecosystem. An ecosystem model that was created for Te Tapuwae o Rongokako MR located midway up the east coast on the North Island, New Zealand has identified that the region is relatively poor in invertebrate biomass when compared to Leigh MR, which lies further north (Pinkerton et al., 2008, Lundquist & Pinkerton 2007). It was determined that the diet of lobsters is composed of a large amount of macroalgae, which has not been observed in other regions of New Zealand. This ecosystem appears to be strongly influenced by lobster abundance, which has been increasing since implementation of the MR.  Figure 1. Map of New Zealand showing marine reserve locations with three study sites shown in red (Kupe/Kevin Smith is now known as Te Taputeranga). Image modified with permission from New Zealand Department of Conservation.                                                    1 Cite as: Eddy, T.D., Gardner, J.P.A., 2009. Trophic modeling of a temperate marine ecosystem throughout marine reserve protection in New Zealand. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 57-58. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 57 Spatial Analysis – Eddy et al. 58 This study is focused in the Cook Strait region located between the North and South Islands, which is characterized by colder waters in comparison to the north and is a highly dynamic area where three ocean currents converge. Temporal data is also used to evaluate ecosystem response to MR protection. This approach allows for an understanding of how MR design and placement, fisheries regulations and coastal resource use affect the dynamics of a biological community. Each of three marine reserves investigated have different designs with respect to boundaries, size and shape. Commercial, recreational and traditional fisheries for reef fish and invertebrate species are important in these regions and we wish to understand how ecosystems respond to MR protection and the impact of factors such as size, placement and design. REFERENCES Lundquist, C.J., Pinkerton, M.H., 2007. Ecosystem Modeling of Te Tapuwae o Rongokaka Marine Reserve. Department of Conservation Science for Conservation Series, Investigation # 3765. Pinkerton, M.H., Lundquist, C.J., Duffy, C.A.J., Freeman D.J., 2008. Trophic modelling of a New Zealand rocky reef ecosystem using simultaneous adjustment of diet, biomass and energetic parameters. J. Exp. Mar. Biol. Ecol. 367, 189-203.  Ecopath 25 Years Conference Proceedings: Abstracts ESTIMATING THE CARRYING CAPACITY OF MONK SEALS USING THE FRENCH FRIGATE SHOALS ECOPATH1 FRANK PARRISH GEORGE ANTONELIS EVAN HOWELL Pacific Island Fisheries Science Center, NOAA Honolulu Hawaii Frank.Parrish@noaa.gov; Bud.Antonelis@noaa.gov; Evan.Howell@noaa.gov SARA IVERSON Department of Biology, Dalhousie University Halifax, Nova Scotia, Canada B3H 4J1; Sara.Iverson@Dal.Ca CHARLES LITTNAN Pacific Island Fisheries Science Center, NOAA Honolulu Hawaii; Charles.Littnan@noaa.gov Jeffrey.Polovina@noaa.gov JAMES PARRISH U.S. Geological Survey, Hawaii Cooperative Fisheries Research Unit 2538, The Mall, University of Hawaii, Honolulu, HI 96822; Parrishj@hawaii.edu JEFFREY POLOVINA Pacific Island Fisheries Science Center, NOAA Honolulu Hawaii; Jeffrey.Polovina@noaa.gov Carrying capacity for the endangered Hawaiian monk seal was estimated using an updated version of the original Ecopath model (Polovina, 1984) developed for the French Frigate Shoals (FFS) ecosystem. The subpopulation of seals at FFS is the largest breeding colony for the species and has declined precipitously over the last two decades. Field data was collected to update model parameters, diet vectors and generate a reference biomass using spatially explicit surveys of demersal fish assemblages. Model boundaries were set using information from seal foraging studies to better represent the central-place foraging behavior of the seals. Because the seals fed across the atoll, neighboring banks, the mesophotic slope, and in portions of the subphotic the trophic components of the model were defined in relation to the ecological subsystem they belonged (e.g., atoll jacks vs. bank jacks). The biomass of monk seals and other top level predators were maximized using Ecopath yielding a total of 47.4 mt·km-2 of monk seals or roughly 356 seals could be produced as the theoretical carrying capacity for the FFS region. This estimate was ~5 % greater than the independent field census data of the FFS monk seal population and is consistent with notions that the FFS seal population is close to or at carrying capacity.                                                   1 Cite as: Parrish, F., Antonelis, G., Howell, E., Iverson, S., Littnan, C., Parrish, J., Polovina, J., 2009. Estimating the carrying capacity of monk seals using the French Frigate Shoals Ecopath. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 59. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 59 Spatial Analysis – Varkey et al. EXPLORATION OF ECOLOGICAL AND ECONOMIC BENEFITS FROM IMPLEMENTATION OF MARINE PROTECTED AREAS IN RAJA AMPAT, INDONESIA1 DIVYA VARKEY Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver BC V6T1Z4 Canada; d.varkey@fisheries.ubc.ca CAMERON AINSWORTH Northwest Fisheries Science Center, 2725 Montlake Avenue East, Seattle, WA 98112 USA; Cameron.Ainsworth@noaa.gov  TONY PITCHER Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver BC V6T1Z4 Canada; t.pitcher@fisheries.ubc.ca The Raja Ampat archipelago extends over 45 000 km2 and consists of more than 600 islands including the ‘four kings’, i.e., Batanta, Misool, Salawati and Waigeo. The area encompasses a variety of marine habitats, including some of the most biodiverse coral reef areas on earth (Donnelly et al., 2003; McKenna et al., 2002). It is estimated that RA possesses over 75 % of the world’s known coral species (Halim & Mous, 2006). A decree by the Bupati (Regent) in 2003 declared Raja Ampat a Maritime Regency, and helped to establish a new network of marine reserves in 2006 covering 4 793 km2 of sea area and 44 % of reef area in Raja Ampat. A total of 7 Marine Protected Areas (MPAs) were declared in Raja Ampat around different Islands (see Figure 1), viz.: Ayau (28 km2), Southwest Waigeo (162 km2), Sayang-Wayag (178 km2), South Waigeo (202 km2), Mayalibit (277 km2), Kofiau (328 km2) and Southeast Misool (943 km2). This study includes analysis based on a Raja Ampat Ecospace model that includes all but 2 of the above mentioned MPAs: (1) the Ayau MPA was excluded because the geographical map of the original Ecopath model for Raja Ampat did not include Ayau; and (2) the   Figure 1. Ecospace map of the Raja Ampat Maritime Regency, West Papua, Indonesia.                                                  1 Cite as: Varkey, D., Ainsworth, C., Pitcher, T., 2009. Exploration of ecological and economic benefits from implementation of marine protected areas in Raja Ampat, Indonesia. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 60-61. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 60 Ecopath 25 Years Conference Proceedings: Abstracts 61 Mayalibit bay MPA was excluded because the bay has very little reef area and therefore was not suitable in a comparison of MPAs for coral reefs. Following discussions with the Fisheries Officer in Raja Ampat and the partner institutions in the project on the motive of the setting up MPAs for the region, spatial EBM research questions of interest were identified, viz.: (1) ecosystem effects of eliminating all commercial fishing in the MPAs; and (2) ecosystem effects of eliminating all destructive fishing in the MPAs. Ecopath and Ecosim parameters inherited from a 2007 Raja Ampat model (see Ainsworth et al., 2007) were used to build a Raja Ampat Ecospace model (see Walters et al., 1998 for a description of Ecospace) of the spatially explicit feeding interactions of this ecosystem’s functional groups. A 2-dimensional grid matrix of spatial habitat cells, with GIS data from the BHS EBM project and oceanographic and biological data from the literature, was used to represent the study area (see Figure 1). Each functional group was allocated to its appropriate habitat(s), i.e., where individuals in the group must find enough food to eat, grow and reproduce, while providing energy to its predators as well as the fisheries. Each cell hosts its own Ecosim simulation and cells are linked through symmetrical biomass fluxes in four directions; the rate of transfer is affected by habitat quality. Optimal and sub-optimal habitats were distinguished using various parameters such as the availability of food, vulnerability to predation and immigration/emigration rate. By delimiting an area as a protected zone, and by defining which gear types are allowed to fish there and when, we explored the effects of MPAs and tested hypotheses regarding ecological function and the effect of fisheries (see also, e.g., Ainsworth, 2006; Pitcher & Buchary, 2002a, 2002b; Salomon et al., 2002; Beattie, 2001; Walters et al.; 1998). The results of these Ecosim simulations were published in Ainsworth et al. (2008). ACKNOWLEDGEMENTS We acknowledge our partners in Indonesia and colleagues at the Fisheries Centre for their support and the continuous advice throughout this study. The study was funded by a grant from the David and Lucille Packard Foundation. REFERENCES Ainsworth, C.H., Varkey, D.A., Pitcher, T.J., 2007. Ecosystem simulation models for the Bird’s Head Seascape, Papua. IN: Pitcher, T.J., Ainsworth C.H., Bailey, M. (eds,) Ecological and Economic Analyses of Marine Ecosystems in the Birds Head Seascape, Papua, Indonesia, pp. 6–172. Fisheries Centre Research Report 15(5). Fisheries Centre, UBC, Vancouver, Canada, 174 p. Ainsworth, C., 2006. Strategic Marine Ecosystem Restoration in Northern British Columbia. Ph.D. Thesis. University of British Columbia, Resource Management and Environmental Studies, 422 p. Beattie, A., 2001. A New Model for Evaluating the Optimal Size, Placement and Configuration of Marine Protected Areas. Unpublished Master’s Thesis. Department of Resource Management and Environmental Science, University of British Columbia, 158 p. Donnelly R., Neville, D., Mous, P., 2003. Report on a Rapid Ecological Assessment of the Raja Ampat Islands, Papua, Eastern Indonesia, held October 30 – November 22, 2002. The Nature Conservancy Southeast Asia Center for Marine Protected Areas, Sanur, Bali Indonesia, 246 p. Halim, A., Mous, P., 2006. Community Perceptions of Marine Protected Area Management in Indonesia. National Oceanic and Atmospheric Administration (NOAA), NA04NOS4630288 [request copies to ahalim@tnc.org]. McKenna, S.A., Boli, P., Allen, G.R., 2002. Condition of coral reefs at the Raja Ampat Islands, Papua Province, Indonesia. Chapter 5. In: McKenna, S.A., Allen, G.R., Suryadi, S. (eds.), A Marine Rapid Assessment of the Raja Ampat Islands, Papua Province, Indonesia. Bulletin of the Rapid Assessment Program, 22. Conservation International, Washington, DC. Pitcher, T.J., Buchary, E.A., 2002a. Ecospace simulations for Hong Kong Waters. In: Pitcher, T. Buchary, E., Trujillo, P. (eds.), Spatial Simulations of Hong Kong's Marine Ecosystem: Forecasting with MPAs and Human-Made Reefs, pp. 30-35. Fisheries Centre Research Reports 10(3). Fisheries Centre, UBC, Vancouver, Canada, 168 p. Pitcher, T.J., Buchary, E.A., 2002b. Ecospace simulations for the People's Republic of China (PRC) inshore waters. In: Pitcher, T., Buchary, E., Trujillo, P. (eds.), Spatial Simulations of Hong Kong's Marine Ecosystem: Forecasting with MPAs and Human-Made Reefs, pp. 36-44. Fisheries Centre Research Reports 10(3). Fisheries Centre, UBC, Vancouver, Canada, 168 p. Salomon, A.K., Waller, N., McIlhagga, C., Yung, R., Walters, C.J., 2002. Modeling the trophic effects of marine protected area zoning policies: A case study. Aquatic Ecol. 36, 85-95. Walters, C. J., Pauly, D., Christensen, V., 1998. Ecospace: prediction of mesoscale spatial patterns in trophic relationships of exploited ecosystems, with emphasis on the impacts of marine protected areas. Ecosystems 2(6), 539-554.  Spatial Analysis: Posters – Park et al. SPATIAL ANALYSIS: POSTER PRESENTATIONS HABITAT SUITABILITY MODEL FOR THE BUSH WARBLER (CETTIA DIPHONE) AT JEJU EXPERIMENTAL FORESTS OF KOREA1 CHAN RYUL PARK Warm-temperate Forest Research Center, Korea Forest Research Institute, Donnaeko St. 20, Seogwipo City, Jejudo; chandrap@chol.com KIM EUNMI CHANG WAN KANG Jeju Wildlife Research Center,Hogeundong 865-2, Seogwipo City, Jejudo; kptta@naver.com; jejubirds@hanmail.net SUNG BAE LEE Warm-temperate Forest Research Center, Korea Forest Research Institute, Donnaeko St. 20, Seogwipo City, Jejudo; imagga2@forest.go.kr Since 2004, the Jeju Experimental Forests (JEFs) of Korea are under sustainable forest management (SFM) fulfilling Forest Stewardship Council requirements. However, there is further need to understand the response of keystone species, like the Bush Warbler (Cettia diphone), White-backed Woodpeckers (Dendrocopos leucotos) and Fairy Pittas (Pitta nympha), to forest practices. Such studies will contribute in building integrated habitat models for these keystone species in Korean JEFs. In order to predict the number of breeding pairs and the location of Bush Warbler nests, quantitative measures of the vertical structure of these forests were obtained with play/back and point count methods (Huff et al., 2000; Bibby et al., 1997). Foliage coverages were recorded at 5 m diameter circular plots in each 50x50 m study areas. The foliage height was classified into six layers (‘A’, above 10 m; ‘B’, 8~10 m; ‘C’, 6~8 m; ‘D’, 4~6 m; ‘E’, 2~4 m and ‘F’,<2 m). Four categories of foliage coverage were recorded in each height layer (0, 0 %; 1, 1~33 %; 2, 34~66 %; 3, 67~100 %; see Park & Lee, 2000). We selected 30 nest and non-nest sites to derive Table 1. CATMOD regression analysis variables based on 30 nest and non-nest points, for the habitat suitability model ofthe Bush Warbler, Cettia diphone, in the Jeju Experimental Forests, Korea. Variable type Variables Category and Class Code Independent Forest type (FT) Coniferous forests CF   Mixed forests with coniferous & broad- leaved forests MCBF   Deciduous broad- leaved forests DBF   Evergreen broad- leaved forests EBF   Mixed Broad- leaved forests MF  Forest height (FH, m) 0 FHA   1~9 FHB   10~12 FHC   13~15 FHD   16~20 FHE  Forest practice (FP) Done within three years FPD   No action FPN  Distance to trail (DT, m) 50~182 DTA   183~375 DTB   376~633 DTC   634> DTD Response  Nest Y   No nest N                                                  1 Cite as: Park, C.R., Eunmi, K., Kang, C.W., Lee, S.B., 2009. Habitat Suitability Model for the Bush Warbler (Cettia diphone) at Jeju Experimental Forests of Korea. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 62-63. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 62 Ecopath 25 Years Conference Proceedings: Abstracts 63 a spatial model for the Bush Warbler. A spatial database was constructed and analyzed, with ArcMap version 9.0 (ESRI), for the effects of FT, FH, FP and DT on the location of nests. We derived independent estimates of the locations of trails and the value of forest height from a 1:5,000-scale forest vegetation map produced by the Korea Forest Research Institute. All variables were similarly transformed into nominal values. A multinomial logistic regression was performed using the PROC CATMOD tools of SAS version 9.1.3 (SAS Institute Inc., 2004). The residual maximum likelihood (REML) method for unbalanced parameters (Robinson, 1987) was employed. Initially all variables were applied to model development, and a 5 % significance level was used as the criterion to accept or reject variables. Breeding density was low in Japanese cedar forests, but the other forests showed no significant difference of breeding density. Coverage ratio of shrub layer below 1.5 m was high at the nest of Bush warblers, and nest height ranged from 0.86 m to 1.11 m. The nest of Bush Warbler was located between 5.9 m to 27.5 m of trails. Among eleven parameters, FHA, FHB, FHC, FPD, DTA, DTB and DTC were used in the final model equation. Habitat suitability for Bush Warbler can be predicted from the function: P=1/(1+exp-(-1.37FHA- 1.18FHB+1.69FHC-1.51FPD—1.20DTA-0.58DTB+1.49DTC)). Habitat suitability of the Bush Warbler was high near trails at low-height forests where forest practices have been conducted for at least three years. In conclusion, the habitat of Bush warbler can be detrimentally affected by forest practice, like thinning and trail construction accompanied with the diminishing of shrub layer. However, development of shrub layer after forest practice can provide the suitable nesting resources for the Bush Warbler. In future, it is need to reveal the effect of spatial configuration of suitable habitat on the breeding success for the Bush Warbler, and to integrate the habitat suitability for forest interior species like White-backed woodpeckers and Fairy Pittas. Table 2. CATMOD regression analysis results for the habitat suitability model of the Bush Warbler, Cettia diphone, in the Jeju Experimental Forests, Korea. Variables DF Chi-square P Forest type (FT) 4 0.34 0.99 Forest height (FH, m) 3 8.86 0.03 Forest practice (FP) 1 8.83 0.00 Distance to trail (DT, m) 3 8.51 0.04 Likelihood ratio 20 61.07 <.0001 ACKNOWLEDGEMENTS This study was carried out with the support of ‘Forest Science & Technology Projects (Project No. 500- 20080086)’ provided by Korea Forest Service. REFERENCES Bibby, C.J., Burgess, N.D., Hill, D.A., 1997. Bird Census Technique. Academic Press limited. London. Huff, M.H., Bettinger, K.A., Ferguson, H.L., Brown, M.J., Altman, B., 2000. A habitat-based point-count protocol for terrestrial Birds, emphasizing Washington and Oregon. USDA Forest Services PNW-GTR-501. Park, C.R., Lee, W.S., 2000. Relationship between species composition and area in breeding birds of urban woods in Seoul, Korea. Landsc. Urban Plan. 51, 29-36. Robinson, D.L., 1987. Estimation and use of variance components. Statistician 36, 3-14. SAS Institute Inc., 2004. SAS OnlineDoc® 9.1.3. Cary, NC: SAS Institute Inc. Ecosystem Comparisons & Network Analysis – Heymans et al. ECOSYSTEM COMPARISONS & NETWORK ANALYSIS: ORAL PRESENTATIONS COMPARING INDICATORS OF ECOSYSTEM CHANGE USING ECOLOGICAL NETWORK ANALYSIS1 JOHANNA J. HEYMANS Scottish Association for Marine Science, Dunstaffnage Marine Laboratory, Oban, PA371QA, UK; Sheila.heymans@sams.ac.uk MACIEJ T. TOMCZAK National Institute of Aquatic Resources, Technical University of Denmark, Jægersborg Allé 1, DK-2920 Charlottenlund, Denmark; mtt@aqua.dtu.dk THORSTEN BLENCKNER SUSA NIIRANEN Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden; thorsten.blenckner@stockholmresilience.su.se; sniir@mbox.su.se Long term changes in ecosystems as diverse as the northern Benguela upwelling system in the South Atlantic, the Chesapeake Bay estuarine system and the Baltic Sea have been studied using food web models in Ecopath with Ecosim. Indices of ecosystem change were calculated using ecological network analysis and decadal regime shifts were estimated for these systems and indices using PCA, STARS and chronological cluster analysis. Results show that in most systems at least 2 regime shifts have occurred over the past 40 years. For instance, in the northern Benguela shifts occurred in 1963 and 1984 while in the Chesapeake shifts occurred in 1971 and 1986. These shifts in physical drivers did not always cause regime shifts in the ecosystems, but ecological regime shifts mostly occurred when anthropogenic stressors such as fishing were analysed in addition to large scale environmental drivers such as SST. Ecopath with Ecosim models fitted to time series and environmental drivers of the northern Benguela upwelling system, the Chesapeake Bay, Baltic Sea and the Central North Pacific were subjected to Network Analysis algorithms to obtain monthly time-step time series of indices such as the total systems throughput (TST), development capacity (C), ascendency (A), overhead (Ø), redundancy (R), overhead on respiration, Finn cycling index (FCI), average path length (APL), proportion of flow to detritus (PFD), fish in balance index (FiB), primary production required for catches (PPRc), trophic level of the catch (TLc) and the total production to biomass ratio (TP/TB). These indices as well as the environmental drivers used to fit the models and estimates of total biomass, catch and respiration were then subjected to sequential regime shift analysis (STARS; Rodionov, 2004) after correcting for autocorrelation using probabilities of 0.05, cutoff lengths of 60 months, Huber parameters of 2, and different AR(1) and subsample sizes and after prewhitening. Principal component analysis (PCA) was then used based on the long-term series of all variables. Sudden changes on the network analysis indices STARS were performed on the first 2 PC score time-series. Finally, chronological clustering (Legendre et al., 1985) of normalized data detected abrupt shifts, in addition to the STARS method.                                                  1 Cite as: Heymans, J.J., Tomczak, M.T., Blenckner, T., Niiranen, S., 2009. Comparing indicators of ecosystem change using ecological network analysis. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 64-66. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 64 Ecopath 25 Years Conference Proceedings: Abstracts The northern Benguela system was forced with sea surface time series anomaly (Heymans et al., 2009) adapted from Sherman et al. (2007). The STARS analysis of this anomaly showed a regime shift in 1984 (Figure 1). The shift in total systems respiration (Figure 2) in 1974 and 1984 are followed by change in throughput, capacity, ascendancy, overhead on respiration and entropy and the 1974 shift is also mirrored by the shift in biomass at that time. The increase of juvenile horse mackerel and modelled jellyfish (Heymans et al., 2009) could possibly explain the increase in respiration in 1974. However, both these 1974 and 1984 shifts could be related to the Benguela Niño that occurs sporadically in this system from as early as 1910, 1934, 1949, 1963, 1974 and 1984 (Shannon & Taunton- Clark, 1988). In addition, the 1963, 1974 and 1984 shifts are all seen in the SST anomaly of Figure 1, while only the 1984 was a proper regime shift according to the analysis. Shifts in the mean for sst anomaly, 1956-2003 Probability = 0.05, cutoff length = 60, Huber parameter = 1 AR(1) = 0.89 (OLS), subsample size = 39 Shift detection: After prewhitening, Plot: Original data 0.85 0.9 0.95 1 1.05 1.1 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01  Figure 1. SHIFTS analysis of SST anomaly (blue) and weighted mean of the regimes using the Huber’s weight function with the parameter 1. Throughput (t/km²/yr) AR(1) = 0.98 (OLS) 45,000 46,000 47,000 48,000 49,000 50,000 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Capacity (t/km²/yr) AR(1) = 0.99 (OLS) 95,000 100,000 105,000 110,000 115,000 120,000 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Ascendency on intneral flow (%) AR(1) = 0.98 (OLS) 19.5 20.0 20.5 21.0 21.5 22.0 22.5 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Redundancy (%) AR(1) = 0.98 (OLS) 36.5 37.0 37.5 38.0 38.5 39.0 39.5 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 FCI (%) AR(1) = 0.97 (OLS) 1.2 1.3 1.4 1.5 1.6 1.7 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Overhead on respiration (%) AR(1) = 0.99 (OLS) 5 6 7 8 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Respiration (t/km²/yr) AR(1) = 0.99 (OLS) 2,500 3,000 3,500 4,000 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Total systems Biomass (t/km²) AR(1) = 0.98 (OLS) 500 600 700 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Total Catch (t/km²/yr) AR(1) = 0.95 (OLS) 0 4 8 12 16 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 PPR for catch AR(1) = 0.96 (OLS) 0 400 800 1,200 1,600 2,000 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Average mutual information AR(1) = 0.96 (OLS) 1.14 1.15 1.16 1.17 1.18 1.19 1.20 1.21 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Entropy AR(1) = 0.99 (OLS) 2 2.1 2.2 2.3 2.4 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 FIB AR(1) = 0.94 (OLS) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 TL catch AR(1) = 0.94 (OLS) 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01 Ascendency (t/km²/yr) AR(1) = 0.97 (OLS) 52,000 54,000 56,000 58,000 60,000 Jan-56 Jan-61 Jan-66 Jan-71 Jan-76 Jan-81 Jan-86 Jan-91 Jan-96 Jan-01  Figure 2. SHIFTS detection in the mean for 15 indices of ecosystem change over time.  65 Ecosystem Comparisons & Network Analysis – Heymans et al. 66 The 1974 and 1984 SST regime shifts was also seen in the throughput, respiration, ascendancy and entropy and overhead on respiration (Figure 2). However, other ecosystem indices show regime shifts in different years. Primary production required for catch (PPRcatch), FIB and TLcatch all showed a regime shift in 1965 when the anchovy, sardine and hake fisheries became big (Heymans et al., 2009). In addition, the PPRcatch shifted again in 1990 and the TLcatch in 1996. The 1990 shift in PPRcatch is related to the reduction in fishing that was instituted by the new Namibian government, while the increase in TLcatch in 1996 is due to the lack of catch of lower trophic species such as anchovy, sardine, seaweed, etc. and an increase in the catch of monkfish, other demersal fish and seals. Regime shift detection in the last 10 years of the analysis should be viewed with caution though, as this is a decadal shift detection algorithm. Thus the change in the biomass, FCI, ascendency on internal flow and redundancy should be viewed with suspicion. However, the marked decline in biomass in the last 10 years seems evident (Figure 2). Northern Benguela 0 1 2 3 Ja n-5 6 Ja n-5 9 Ja n-6 2 Ja n-6 5 Ja n-6 8 Ja n-7 1 Ja n-7 4 Ja n-7 7 Ja n-8 0 Ja n-8 3 Ja n-8 6 Ja n-8 9 Ja n-9 2 Ja n-9 5 Ja n-9 8 Ja n-0 1  Aleutians 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Jan-63 Jan-68 Jan-73 Jan-78 Jan-83 Jan-88 Jan-93 Jan-98 Chesapeake 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Jan-50 Jan-55 Jan-60 Jan-65 Jan-70 Jan-75 Jan-80 Jan-85 Jan-90 Jan-95 Jan-00   Central North Pacific 0 1 2 3 4 5 6 7 Jan-52 Jan-57 Jan-62 Jan-67 Jan-72 Jan-77 Jan-82 Jan-87 Jan-92 Jan-97 Eastern Bering Sea 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Jan-50 Jan-55 Jan-60 Jan-65 Jan-70 Jan-75 Jan-80 Jan-85 Jan-90 Jan-95 Jan-00  Baltic Sea 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Jan-74 Jul-76 Jan-79 Jul-81 Jan-84 Jul-86 Jan-89 Jul-91 Jan-94 Jul-96 Jan-99 Figure 3. Sum of all regime shift indices for the northern Benguela, Aleutian Islands, Chesapeake Bay, Central North Pacific, Eastern Bering Sea and Baltic Sea (preliminary results). The sum of all the regime shift indices shows that the large change in the FIB in 1965 outweighed the changes in most other years (Figure 3). The increase in the catch in the early 1960s caused many of the catch related indices to shift in the mid-1960. The 1974 and 1984 Benguela Niño’s caused shifts around those times. These regime shifts are compared to those in other systems (Figure 3) that are also subjected to environmental drivers and anthropogenic change. REFERENCES Heymans, J.J., Sumaila, U.R. and Christensen, V. (2009) Policy options for the northern Benguela ecosystem using a multispecies, multifleet ecosystem model. Progress in Oceanography in press. Legendre, P., Dallot, S. and Legendre, L. (1985) Succession of Species within a Community: Chronological Clustering, with Applications to Marine and Freshwater Zooplankton. The American Naturalist 125: 257-288. Rodionov, S.N. (2004) A sequential algorithm for testing climate regime shifts. Geophys. Res. Lett. 31. Shannon, L.J. and Taunton-Clark, J. (1988) Interannual and decadal changes in sea surface temperature and relative wind stress in the South-East Atlantic this century. pp. 49-51 in MacDonald, I.A.W. and Crawford, R.J.M., editors. Long-term data series relating to southern African's renewable natural resources. Foundation for Research Development, Pretoria. Sherman, K., Belkin, I., O'Reilly, J. and Hyde, K. (2007) Variability of Large Marine Ecosystems in response to global climate change. ICES CM 2007: 1-46.  Ecopath 25 Years Conference Proceedings: Abstracts MARINE MAMMALS – FISHERIES INTERACTIONS: HOW TO USE ECOPATH WITH ECOSIM TO CAPTURE ECOLOGICAL COMPLEXITY1 LYNE MORISSETTE Institut des Sciences de la Mer de Rimouski (UQAR-ISMER), University of Guelph 310, allée des Ursulines, C.P. 3300 Rimouski (Québec) G5L 3A Canada; lyne.morissette@globetrotter.net CHIARA PIRODDI Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada; c.piroddi@fisheries.ubc.ca Understanding the trophic role of marine mammals in ecosystems is not an easy task. In order to get an adequate overview of the different interactions they can have with the other species of the system (and with fisheries), it is thus important to analyse the whole food web (Bax, 1998). In that sense, an ecosystem modelling approach becomes an interesting tool to address marine mammal issues under different circumstances. For example, ecosystem modeling is considered to be the only reliable method to address the issue of competition between marine mammals and fisheries (IWC, 2004). Within the many types of software available, Ecopath with Ecosim (EwE) is one that is emerging as a reliable and convenient tool for ecosystem modelling. EwE models are generally constructed in a fisheries context, and often deal mainly with commercially important fish species. However, in many cases marine mammal groups are included, making a better representation of all trophic interactions in these ecosystems (Morissette et al., 2006). Studying marine mammals in an ecosystem context, based on modelling, allows to (1) explore the direct interaction between these two top-predators (i.e., fish and marine mammals); and (2) asses the indirect impacts of (and on) other species and species groups in these foodwebs. In that sense, the EwE software provides innovative results. For example, consumption by predators has important influences on the dynamics of both predator and prey populations, and in a complex ecosystem containing many generalists, multi- species interactions may result in counter-intuitive effects on predator and prey population dynamics (Yodzis, 2001). While marine mammals are known to be top-predators in most systems, they also represent a source of beneficial predation for their prey (Figure 1). The EwE approach have been lately used in a wide variety of marine mammal projects, for example, (1) in comparing the methyl mercury exposure from consumption of pilot whale meat and fish in the Faroe Islands (Booth & Zeller, 2005); (2) in explaining the decline of Steller sea lions in Alaska (Guénette et al., 2006); (3) in explaining the decline of short-beaked common dolphins in the Mediterrean Sea (north- eastern Ionian Sea) where food resources and bycatch were detected as reasons of their collapse (Piroddi, 2008); and (4) assessing if whales are a threat to fisheries in tropical breeding areas (Gerber et al., 2009). In this study we assess the different tools available in the EwE software package to address marine mammal issues, i.e., in ecotoxicology, competition with fisheries, bycatch of marine mammals, etc. Out of a sample of 50 EwE models representing marine ecosystems around the world (Morissette, 2007), 88 % included at least one trophic group for marine mammals, and 79% divided marine mammals into categories such as pinnipeds, toothed whales, and baleen whales. From these models, we assess the kind of result generated from EwE tools, their strengths and weaknesses. In particular, we investigate the use of Ecosim (a time dynamic simulation module for policy exploration), Ecotrace (allowing to trace the transfer and bioaccumulation of pollutants through all ecosystem functional groups based on diet transfers and direct uptake from the environment), and Network Analysis tools (e.g., primary production required, PPR,                                                  1 Cite as: Morrissette, L., Piroddi, C., 2009. Marine mammals – fisheries interactions: how to use Ecopath with Ecosim to capture ecological complexity. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 67-68. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 67 Ecosystem Comparisons & Network Analysis – Morissette & Piroddi 68 to sustain marine mammals’ consumption; mixed trophic impacts, MTI, of marine mammals in ecosystems). We present the strengths of using the EwE approach to address the trophic role of marine mammals in ecosystems. The different biases of using this modelling technique to address the issue of competition between marine mammals and fisheries are also discussed.  Figure 1. An example of the mixed trophic impact of harp seals (white) and fisheries (grey) on fish and fleet groups of the Gulf of St. Lawrence, Canada (Morissette et al., 2003). Beneficial predation from harp seals is seen for skates, small demersal fish, shrimps, and large crustaceans.  REFERENCES Bax, N.J., 1998. The significance and prediction of predation in marine fisheries. ICES J. Mar. Sci. 55, 997-1030. Booth, S., Zeller, D., 2005. Mercury, food webs, and marine mammals: Implications of diet and climate change for human health. Environ. Health Perspectives 13, 521-526. Gerber, L., Morissette, L., Kaschner, K., Pauly, D., 2009. Should whales be culled to increase fisheries? Science 323, 880-881. Guénette, S., Heymans, S.J.J., Christensen, V., Trites, A.W., 2006. Ecosystem models show combined effects of fishing, predation, competition, and ocean productivity on Steller sea lions (Eumetopias jubatus) in Alaska. Can. J. Fish. Aquat. Sci. 63, 2495-2517. International Whaling Commission (IWC), 2004. Report of the Modelling Workshop on Cetacean-Fishery Competition. J.Cetacean Res. Manage. 6 (Suppl.), 413–426. Morissette, L., 2007. Complexity, cost and quality of ecosystem models and their impact on resilience: a comparative analysis, with emphasis on marine mammals and the Gulf of St. Lawrence. PhD thesis, University of British Columbia, Vancouver BC, Canada. Morissette, L., Hammill, M.O., Savenkoff, C., 2006. The trophic role of marine mammals in the Northern Gulf of St. Lawrence. Mar. Mammal Sci. 22, 74-103. Piroddi, C., 2008. An ecosystem-based approach to study two dolphin populations around the island of Kalamos, Ionian Sea, Greece. MSc thesis, University of British Columbia, Vancouver, BC, Canada. Yodzis, P., 2001. Must top predators be culled for the sake of fisheries? Trends Ecol. Evol. 16, 78-84. Ecopath 25 Years Conference Proceedings: Abstracts A SIMPLE APPROACH FOR ENHANCING ECOLOGICAL NETWORKS AND ENERGY BUDGETS (NAMELY ECOPATH): PLEASE, LET’S DO SOME PREBAL BEFORE WE START BALANCING1 JASON S. LINK NOAA NMFS NEFSC, 166 Water Street, Woods Hole, MA 02543 USA Jason.Link@noaa.gov The widespread use of Ecopath (EwE) and related energy budget models has been laudable for several reasons, chief of which is providing a tool to present an ecosystem context for improved understanding and management of living marine resources (LMR). Having seen a veritable explosion of these models, it has been recognized that their content and use has spanned a range of quality. Thus, as these models continue to increasingly be used in a LMR context, review panels and other evaluators would benefit from a set of rigorous and standard criteria from which the basis for all EwE and related applications for any given system, i.e., the initial, static energy budget, can be evaluated. To this end, as one suggestion for improving the suite of models in the EwE package specifically and energy budgets in general, here I propose a series of pre-balance (PREBAL) diagnostics. These PREBAL diagnostics can be done in simple spreadsheets before any balancing or tuning is executed. Examples of these PREBAL diagnostics include biomasses, biomass ratios, vital rates, vital rate ratios, total production, and total removals (and slopes thereof) across the taxa and trophic levels in any given energy budget. I assert that there are some general ecological and fishery principles that can be used in conjunction with PREBAL diagnostics to flag issues of model structure and data quality before balancing and dynamic applications are executed. I give examples where these PREBAL metrics have been applied; identifying instances where the model inputs merited re- examination before further modeling steps were executed. I humbly present this PREBAL information as a simple yet general approach that could be easily implemented, might be worth incorporating into these model packages, ultimately resulting in a straightforward way to evaluate (and perhaps identify areas for improving) initial conditions in food web modeling efforts.                                                   1 Cite as: Link, J.S., 2009. A simple approach for enhancing ecological networks and energy budgets (namely Ecopath): please, let’s do some PREBAL before we start balancing. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 69. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 69 Ecosystem Comparisons & Network Analysis – Opitz et al. IMPACT OF OFFSHORE WINDPARKS ON ECOSYSTEM STRUCTURE AND FLOW PATTERNS1 SILVIA OPITZ Leibniz Institute of Marine Sciences University of Kiel Duesternbrooker Weg 20, 24105 Kiel, Germany; sopitz@ifm-geomar.de HERMANN LENHART Institute for Marine Research, Hamburg University Bundesstr. 53, 20146 Hamburg, Germany; hermann.lenhart@zmaw.de WILHELM WINDHORST Ecology Centre University of Kiel Olshausenstr. 40, 24098 Kiel, Germany; wwindhorst@ecology.uni-kiel.de In the scope of the project “Coastal Futures” (see e.g., Burkhard et al., 2009; Lenhart et. al., 2006) four trophic network models for three potential windpark sites (Butendiek, Dan Tysk, Sandbank 24) situated in the German Exclusive Economic Zone (EEZ) of the North Sea were produced based on: i) output data from two ERSEM runs for the area where the potential windpark sites are situated (for a description of the ecological simulation model ERSEM see, e.g., Lenhart et al., 2006; Lenhart, 2001); ii) data from Environmental Impact Analyses for the three sites kindly provided by DHI (German Institute of Hydrography) in Hamburg; and iii) data published in the literature. The trophic network models were produced using the software package Ecopath with Ecosim (EwE), version 4.0. A model per windpark was produced for the so-called Standard Scenario, describing the ecosystem state before construction of a wind-park, and one model for Butendiek for the so-called Scenario B1 (year 2015), i.e., the situation after construction of the windpark. Results show that with distance of windpark from the coast, the biomass per area is declining. However, the food web structures of the different parks do not show remarkable differences. This may be attributed to the fact that the same inputs from ERSEM were used for the three Standard Scenario models and the same diet composition was applied to all windparks and scenarios. Food web structure analysis based on ecosystem indicators showed a mixed pattern for all food web models. Differing values for Sandbank 24 with lowest biomass values per area and with similar structure of food web showed the highest degree of organisation, indicated by an ascendancy value of 37 % of total system capacity. Butendiek showed the highest biomass value per area and the lowest degree of organisation, indicated by an ascendancy value of 28 % of total system capacity. With a trophic level of 4.1, fish-feeding birds and mammals play the role of top predators in the food web at the potential windpark sites. The trophic system at the three windpark sites can sustain a standing stock biomass of mammals of 0.6 to 2.0 mg·cm-2 and of birds of 0.2 to 0.5 mg·cm-2. Mammals consume 6.2 to 29.5 mg·cm-2 of system resources and birds 16.5 to 46.6 mg·cm-2. A hypothesized increase in biomass due to additional substrate available for epibenthic sessile organisms from kolk protection areas of piles after windpark construction had only a negligible impact on total system structure and flow pattern for the three windpark sites when assuming the same concentration on                                                  1 Cite as: Opitz, S., Lenhart, H., Windhorst, W., 2009. Impact of offshore windparks on ecosystem structure and flow patterns. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 70-71. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 70 Ecopath 25 Years Conference Proceedings: Abstracts 71 the kolk protection areas as in the surrounding environment. Based on the assumption that the kolk substrate might offer better settling conditions than the surrounding environment, a stepwise increase of substrate related biomass was simulated to identify the system´s potential for additional biomass production. For the three windparks, an additional biomass on piles of roughly 1 000 times the initial concentration of the three functional groups of sessile organisms was identified as the limit of the system´s carrying capacity. The system´s potential for production of additional biomass of sessile organisms, in particular epifaunal bivalves and macroalgae, not only stimulates an increase of predator populations, e.g., birds and fish, but may have relevance for potential future aquaculture activities in the windparks of organisms low in the food web, e.g., mussels, oysters and algae. A mixed trophic impact analysis showed, in relative quantities, the positive direct and indirect impacts on their predators and negative impacts on their food competitors with an increase in biomass of these groups. Higher trophic level winners of additional biomass from sessile organisms are mammals, omnivorous birds and zoobenthos-feeding fish. A hypothesized increase of biomass concentration of sessile organisms on the kolk protection of piles of up to 1 000 times that of the surrounding environment provides a theoretical potential for increase of biomass of the beneficiaries of 15-20 %. Furthermore, a selection of ecosystem indicators could be extracted from the models with the potential to substantially contribute to the analysis of ecosystem integrity in the investigated areas. REFERENCES Burkhard, B., Lenhart, H., Opitz, S., Garthe, S., Mendel, B., Ahrendt, K., Windhorst, W., 2009. Ecosystem based modelling and indication for integrated coastal zone management in the German North Sea – Case study offshore wind farms. Ecol. Ind. [in press]. Lenhart, H., 2001. Effects of river nutrient load reduction on the eutrophication of the North Sea, simulated with the ecosystem model ERSEM. Senckenbergiana maritima 31(2), 299-311. Lenhart, H., Burkhard, B., Windhorst, W., 2006. Ökologische Auswirkungen erhöhter Schwebstoffgehalte als Folge der Baumaßnahmen von Offshore Windkraftanlagen. EcoSys Suppl. Bd. 46, 90-106.  Ecosystem Comparisons & Network Analysis – Galván-Piña et al. COMPARISON OF TROPHIC STRUCTURES AND KEY PLAYERS FOR TWO PERIODS IN THE CONTINENTAL SHELF ECOSYSTEM OF THE CENTRAL PACIFIC OF MEXICO1 VÍCTOR HUGO GALVÁN PIÑA Departmento de Estudios para el Desarrollo Integrado de la Zona Costera, Centro Universitario de la Costa Sur, Universidad de Guadalajara, V. Gómez Farias 82, San Patricio-Melaque, 48980, Jalisco, Mexico; vhgalpina@gmail.com FRANCISCO ARREGUÍN-SÁNCHEZ MANUEL ZETINA REJÓN JOSÉ TRINIDAD NIETO NAVARRO Centro Interdisciplinario de Ciencias Marinas, CICIMAR, del Instituto Politecnico Nacional, Apartado Postal 592, La Paz, 23000, Baja California Sur, Mexico; farregui@ipn.mx; mjzetina@gmail.com; nietojt@gmail.com The marine region of the southern coasts of Jalisco and Colima includes the fishing area of the shrimp fleet (20- 100 m isobath) and the artisanal fleet (coastline to 40 m isobath). The continental shelf is very narrow where 200 m isobath lies at 7-10 km from the coast. The habitats include insular, coral reef, rocky, soft bottom, seagrass and macrophyte environments which support high productivity and biodiversity in the zone. Presently 500 species of fish and 400 of invertebrates have been reported, of which about 150 are commercially exploited by different artisanal fleets (ca. 1 000 fishers and 500 boats). The highest catch landed in the last decade was 16 000 metric ton, where snappers, sharks and octopus contribute with more than 80 %. Fishers suggest present low catches are associated to the impact of a seasonal shrimp trawl fishing that operates when in transit between larger fishing grounds, by reducing stock abundances as well as through by-catch and habitat degradation. A recent measure includes installation of artificial reefs to avoid both trawling of shrimp fleet and increasing to artisanal fishery production, but not evaluations of effect are avaiable. This study describes aspects of the structure and function of this ecosystem and explores possible changes, which occurred during two periods 1995-1996 and 2007-2008, using ecosystem statistics estimated through Ecopath, e.g., system throughput (TST), consumption (SC), exports (SE), respiration (SR), flows into detritus (SFD), biomass (TB), primary production (TPP), production (TP), ascendancy (A), overhead (O), and capacity of development (C). We also explore possible changes through some indices of ‘keystone species’, sensu Jordan (2006), and ‘keyplayers’, sensu Borgatti (2003). Keystone index gives information on how a group is connected to others, emphasizing topological attributes of the trophic network. Keyplayer identifies the most important groups related to fragmentation of the trophic network and how information is propagated throughout.  Figure 1. Comparison of attributes for the Central Mexican Pacific continental shelf ecosystem for 1995/1996 and 2007/2008. Top panel: summary statistics for the ecosystem; Bottom panel: Ulanowicz information magnitudes, Ascendency (A), Overhead (O) and capacity of Development (D).                                                  1 Cite as: Galván-Piña, V.H., Arreguín-Sánchez, F., Zetina-Rejón, M., Nieto-Navarro, J.T., 2009. Comparison of trophic structures and keyplayers for two periods in the continental shelf ecosystem of the central Pacific of Mexico. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 72-73. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 72 Ecopath 25 Years Conference Proceedings: Abstracts 73 Table 1. Ranking of keystone and keyplayer groups for the Central Mexican Pacific continental shelf ecosystem for 1995/1996 and 2007/2008. Only first five groups are shown. MTL: mean trophic level; 1: ; 2: ; 3: ; 4: ; 5: .  Key players  Keystone groups Fragmentation  Propagation   1995/1996 2007/2008 1995/1997 2007/2009 1995/1997 2007/2009 1 Phytoplankton Phytoplankton Other fishes Zooplankton Marine mammals Puffers 2 Sharks Zooplankton Zooplankton Infauna Seabirds Seabirds 3 Infauna Infauna Shrimps Other fishes Sea turtles Seaturtles 4 Zooplankton Sharks Mollusks Crabs Sharks Sharks 5 Mar. mammals Mar. mammals Brachyurans Large pelagics Billfishes Rays MTL 3.35 2.89 2.74 2.62 3.51 2.97  Comparisons of ecosystem statistics are shown in Figure 1 revealing some changes between periods. In 2007/2008, the system demands more energy (SC/TST) presenting a higher metabolic rate (SR/TST) than in 1995/1996. The first period system showed a lower proportion of useful energy in relation to the metabolic cost (TPP/TR). This condition is also suggested by the quotient of total production to total systems flow, whose value is higher in the second period. These attributes indicate large production coupled with low utilization of this production, i.e., a clear sign that this ecosystem is under the process of maturation (Odum, 1969). The organization of the ecosystem is higher in the recent period as suggested by the A/C ratio (see Ulanowicz, 1986). However, growth potential is slightly lower according to the O/C ratio (also interpreted as index of resilience), i.e., the ecosystem in the first period (1995-1996) exhibits a less mature state than the second period (2007-208). The keystone and keyplayer indices show differences between both periods confirming two different ecosystem stages as shown in the ranking of groups in Table 1. A global comparison of the estimated mean trophic level (MTL) of the first ten groups in the ranking showed, for all cases, a lower MTL for the second period, i.e., assumed to be more impacted than the first period due to maintained/increased fishing. ACKNOWLEGEMENTS The first author wishes to thank the CONACyT. We wish to thank CONACyT-SAGARPA (12004), the National Polytechnic Institute through SIP (20090932), COFAA and EDI. REFERENCES Borgatti, S.P., 2003. The key player problem. In: Breiger, R., Carley, K., Pattison, P. (eds), Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pp. 241-252. Committee on Human Factors, National Research Council. Jordán, F., Liu, W.C. Davis, A.J., 2006. Topological keystone species: measures of positional importance in food webs. Oikos 112, 535-546. Odum, E.P., 1969. The strategy of ecosystem development. Science 104, 262-270. Ulanowicz, R., 1986. Growth and Development: Ecosystems Phenomenology. Springer-Verlag, New York, 203 p. Ecosystem Comparisons & Network Analysis – Lachica-Aliño et al. TROPHIC FLOW STRUCTURE OF FOUR OVERFISHED COASTAL ECOSYSTEMS AROUND THE PHILIPPINES1 LUALHATI LACHICA-ALIÑO LAURA T. DAVID Marine Science Institute, University of the Philippines Diliman, Quezon City; llalino@upmsi.ph; ldavid@upmsi.ph MATTHIAS WOLFF Center for Tropical Marine Ecology (ZMT), University of Bremen, Fahrenheitstrasse 6, D 28359 Bremen, Germany; mwolff@uni-bremen.de Trophic ecosystem models were constructed for four overfished systems situated in embayments in the Philippines (Pauly & Chua, 1988), which experience environmental perturbations through sedimentation and reduced water quality caused by substantial eutrophication and pollution. Their physical structure and trophic functioning vary in several aspects eliciting varying resilience or resistance mechanisms in order to sustain their fisheries (Figure 1). The highly embayed and heavily polluted Manila Bay is characterized by high P/B and P/R ratios and high chl a concentration. Overheads are low due to low cycling and low B/P ratio, suggesting that the system is vulnerable to changes in nutrient or sediment input and has low capacity to withstand environmental perturbations resulting to low fisheries yield. Internal system production is greatly lost to the sediment or converted to algal cysts, i.e., algal blooms, rather than exported out of the system due to low bay flushing as indicated by circulation models.  Figure 1.  Classification diagram from canonical correspondence analysis (CCA) of the experimental trawl surveys conducted in the four fishing grounds. The San Miguel Bay system is smaller than Manila Bay and the shallowest bay of the four systems. It clusters with Manila Bay in terms of water pollution and sedimentation load with low biomass. It efficient transfer of energy and higher cycling index suggest recycling of carbon from detritus and through its predator/ prey interactions within the system thus high fisheries yield. Being shallow, it is well-mixed by wind and tidal influences allowing species to interact substantially (Bundy & Pauly, 2001). Ragay Gulf is the largest and with the deepest embayment area mainly characterized by its physical structure and the input of nutrient from coastal areas. It has unique hydrodynamic processes that interact with an inland sea. Outer high velocity sheer and flushing controls the deep basin with a high percentage of carbon recycled within the linear system. It has a diverse range of coastal habitats and processes with more compartments for carbon to flow within the system, thus having high primary production and                                                  1 Cite as: Lachica-Aliño, L., David, L.T., Wolff, M., 2009. Trophic flow structure of four overfished coastal ecosystems around the Philippines. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 74-75. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 74 Ecopath 25 Years Conference Proceedings: Abstracts 75 standing stock (Lachica-Aliño et al., 2009). The fisheries yield of the system is still relatively low due to inefficient transfer of energy within the trophic levels of the system. Of the four fishing grounds, the San Pedro Bay is the smallest with the highest system overhead. It opens to a larger system, the Leyte Gulf embayment. The bay with high FCI indicating recycling of carbon uptake of detritus is characterized by having high gradient in addition to the high horizontal gradient from north to south that allows the materials to be flushed out of the system towards Leyte Gulf. There is import and export of materials in and out of the system. The management of such overfished ecosystems would benefit from the understanding of the dynamics of their natural environments along with their associated social and ecological systems. This investigation adds to previous studies relating ecosystems’ trophic dynamics and thier vulnerability to human perturbations. Specifically, this study helps explain multidimensional forcing interacting with ecosystem functions at varying scales such as: i) size, depth and shapes that influence attributes leading to functionality effects; ii) the oceanographic processes such as flushing and upwelling affecting system overhead, cycling and type of disturbances; iii) ecosystem trajectories showing non-equilibrium attributes; and iv) opportunities for improving management through reduction of exacerbating stressors and integrated ecosystem management perspectives necessary to meet the impending future changes in a rapidly changing world. ACKNOWLEDGEMENTS This study was assisted by the full support of the Sandwich Program of the Deutscher Akademischer Austausch Dienst e. V. (DAAD) (German Academic Exchange Service) and the PhD Research Scholarship of the Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA). Thanks to the critical comments of Dr. Porfirio M. Aliño of the Marine Science Institute of the University of the Philippines and several other anonymous reviewers. REFERENCES Bundy, A., Pauly, D., 2001. Selective harvesting by small-scale fisheries: ecosystem analysis of San Miguel Bay, Philippines. Fish. Res. 53, 263-281. Lachica-Aliño, L. David, L.T., Wolff, M., Aliño, P.M., Rañola, M.C., 2009. Distributional patterns, habitat overlap and trophic interactions of species caught by trawling in the Ragay Gulf, Philippines. Philipp. Agric. Scientist. 92, 1, [in press]. Pauly, D., Chua, T.E.. 1988. The overfishing of marine resources: socioeconomic background in Southeast Asia. Ambio 17, 3, 200- 206. Ecosystem Comparisons & Network Analysis – Arias-González et al. RELATIONSHIP BETWEEN BIODIVERSITY AND ECOSYSTEM FUNCTIONING IN MEXICAN AQUATIC SYSTEMS1 J. ERNESTO ARIAS-GONZÁLEZ Centro de Investigación y Estudios Avanzados del I.P.N., Unidad Mérida; earias@mda.cinvestav.mx LUIS G. ABARCA Centro de Ecología y Pesquerías, Universidad Veracruzana; luisgaa@gmail.com  JAVIER ALCOCER-DURÁN Universidad Nacional Autónoma de México (UNAM); jalcocer@servidor.unam.mx JOSÉ L. CABRERA Centro de Investigación y Estudios Avanzados del I.P.N., Unidad Mérida; jcabrera@mda.cinvestav.mx LUIS E. CALDERÓN-AGUILERA Centro de investigación Científica y Educación Superior de Ensenada; leca@cicese.mx XAVIER CHIAPPA-CARRARA Universidad Nacional Autónoma de México; chiappa@servidor.unam.mx VILLY CHRISTENSEN Fisheries Centre, University of British Columbia, Vancouver, Canada; v.christensen@fisheries.ubc.ca AMILCAR CUPUL-MAGAÑA Universidad de Guadalajara; amilcar_cupul@yahoo.com.mx JONATHAN FRANCO-LÓPEZ Universidad Nacional Autónoma de México; jfranco@servidor.unam.mx HORACIO PÉREZ-ESPAÑA Centro de Ecología y Pesquerías, Universidad Veracruzana; hespana@gmail.com VERÓNICA MORALES-ZÁRATE Centro de Investigaciones Biológicas del Noroeste; mzarate04@cibnor.mx                                                  1 Cite as: Arias-González, J.E., Abarca, L.G., Alcocer-Durán, J., Cabrera, J.L., Caderón-Aguilera, L.E., Chiappa-Carrara, X., Christensen, V., Cupul-Magaña, A., Franco-López, J., Pérez-España, H. Morales-Zárate, V., Rodriquez-Zaragoza, F.A., Sansores, C., Schmitter-Soto, J.J., 2009. Relationship between biodiversity and ecosystem functioning in Mexican aquatic systems. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 76-78. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198- 6727]. 167 p. 76 Ecopath 25 Years Conference Proceedings: Abstracts FABIÁN A. RODRIGUEZ-ZARAGOZA Universidad de Guadalajara; fabianrz2002@yahoo.com.mx  CANDY SANSORES Universidad del Caribe; csansores@ucaribe.edu.mx JUAN J. SCHMITTER-SOTO Colegio de la Frontera Sur; juan.schmitter-soto@fulbrightmail.org The accelerated loss of biodiversity and change in species composition produced by climate and global change has stimulated vigorous research into how biodiversity influences the properties of ecosystem function (Duffy et al., 2006). There are few empirical or theoretical studies on the consequences of the loss of biodiversity in aquatic ecosystem functioning. Table 1. Initial studied ecosystems located in different regions around Mexico. Ecosystem Characteristics Location Authors Institutions Caribbean coral reefs  Fringing reef associated with mangroves Quintana Roo, Caribbean Sea Arias-González et al. CINVESTAV, UC Chetumal Bay Large bay in northern Belize and eastern Mexico Quintana Roo, Caribbean Sea Schmitter-Soto et al. ECOSUR Campeche Bank coral reefs  Off-shore large insular reefs Yucatan Peninsula Campeche Bank Arias-González et al. CINVESTAV, UC Veracruz Coral Reef System Off-shore small insular reefs Veracruz, Gulf of Mexico Pérez-España et al. UV Alvarado lagoon complex  Is formed by 4 main lagoon systems Veracruz, Gulf of México Franco-López & Abarca UNAM, UV Alchichica lake Crater lake Puebla, Centra area of Mexico Alcocer-Durán & Chiappa UNAM Upper Gulf of California Ocean system Gulf of California Morales-Zárate et al. CIBNOR Pacific Coral Reefs Shallow marginal reef associated with mangroves Pacific Ocean, Mexico  Calderón-Aguilera et al. CICESE, UBCS, UG  We have launched a Mexican national programme to study the relationship between biodiversity and ecosystem functioning in aquatic ecosystems (BEF). This programme emerges from an ecosystem national network initiative founded by CONACYT. The main objectives of BEF are to: 1) evaluate the biodiversity (in terms of species richness and composition), functional characteristics and functional groups of fish species; 2) estimate the structure and properties of different aquatic ecosystems; and 3) evaluate the relationship between biodiversity and ecosystem function. At this initial stage seven aquatic ecosystems representative of Mexico have been included (Table 1). We used fish species as an indicator to study biodiversity and as a main functional group to construct different mass balance models of the food web using Ecopath with Ecosim (v. 6.0). Biodiversity and mass balance models of aquatic food webs are under construction. Here we present the departure of the models constructed from similar criteria used in coral reef ecosystems by Rodriguez-Zaragoza and Arias-González (unpublished data, in preparation) and Arias- González et al. (unpublished data, in preparation). These authors carried out two “natural” experiments from empirical observations in four reefs located in the Caribbean and Campeche Bank. In the Caribbean, three reefs with different ecological features were studied. One reef, Puerto Morelos, is a relatively simple reef with two geomorphic zones, the two other reefs, Yuyum and Mahahual, are more complex reefs composed of four geomorphic zones. Diversity for coral reef fish varied considerably between Puerto Morelos, and Yuyum and Mahahual reefs. Ecosystem indicators for each reef obtained from EwE showed that the reefs with greater biodiversity had the highest total system biomass, throughput, production, flow cycling, number of pathways, path lengths, and more stable and complex food webs (Figure 1). 77 Ecosystem Comparisons & Network Analysis – Arias-González et al. 78 In Campeche Bank, the spatial relationships between distinctive habitats and the interaction between spatial elements, notably biodiversity and flow of energy or materials among the component habitats, were investigated in one of the most complex off-shore coral reefs, i.e., Alacranes Reef. Biodiversity indices were measured and empirical trophic functioning models were constructed for 17 coral reefscapes surveyed by the Alacranes Reef Project. Differences in diversity produce a strong variation in reefscape functioning analyses. Species and functional group richness, composition and abundance of species, and ecological diversity for coral reef fishes varied considerably among reefscapes. Ecosystem functioning indicators for each reefscape obtained from trophic analysis showed that the reefscapes with greater coral structure, habitat complexity and depth had the highest trophic structure and trophic and ecosystem functioning macrodescriptor values. Results suggest that biodiversity enhance reefscape total production. From these pioneering results we would like to test how biodiversity influences ecosystem function in different aquatic ecosystems with distinct evolution development.  Figure 1. Resilience of three coral reefs in the Caribbean under a standard fishing effect. Ma: Mahahual; YX: Yuyum; PMo: Puerto Morelos. ACKNOWLEDGEMENTS This project was founded by CONACYT, CINVESTAV, CIBNOR, CICESE ECOSUR, UC, U de G, UNAM and UV. REFERENCES Arias-González, J.E., González-Gándara, C., Cabrera, J.L., (in preparation). Ecosystem functioning and diversity across reefscapes in Alacranes Reef, Campeche Bank, México. Duffy, J.E., Stachowicz, J.J., 2006. Why diversity is important to oceanography: potential roles of genetic, species, and trophic diversity in pelagic ecosystem processes. Mar. Ecol. Prog. Ser. 311, 179-189. Rodriguez-Zaragoza, F.A., Arias-González, J.E., (in preparation). Biodiversity and ecosystem functioning of three Caribbean coral reefs.  Ecopath 25 Years Conference Proceedings: Abstracts ECOSYSTEM COMPARISONS & NETWORK ANALYSIS: POSTER PRESENTATIONS METABOLISM OF AQUATIC ECOSYSTEMS1 LUIS SALCIDO-GUEVARA FRANCISCO ARREGUÍN-SÁNCHEZ Centro Interdisciplinario de Ciencias Marinas, CICIMAR, del Instituto Politecnico Nacional, Apartado Postal 592, La Paz, 23000, Baja California Sur, Mexico; salcidog@gmail.com; farregui@ipn.mx Species-level studies reveal that basal metabolism can be expressed in body mass as Y=aMb, where a is a constant related to the type of organism, M is body mass and b is the scaling exponent. Rubner (1879) reported that b is equal to 2/3 in a log-log graph in a relationship of body surface expressed as a function of body mass for different animals. Kleiber (1932) obtained a b value of 3/4 using the basal metabolic rate as a function of body mass of several species, including humans. Since then, many studies support the concept of allometric scaling like a power law that varies around 3/4, mainly in living systems, i.e., from microorganisms, such as bacteria, to animals like the elephant (West & Brown, 2005; Garlaschelli et al., 2003; West et al., 1997; Hemmingsen, 1960). The interpretation of this scaling exponent at the ecosystem level has been sought, initially with a physical network, where the shape, size and number of nodes determines the efficiency of energy transport in the ecosystem. However, it may be an indicator of status according to the balance of supply-demand of energy (SDB) (Bendoricchio & Palmeri, 2005), with the assumption that an ecosystem is represented by a network of compartments and flows, and that the potential relationship between fluxes and biomasses has a slope similar to the allometric scaling exponent of the species. This study aims to demonstrate the possible regularity of the allometric scaling value of 3/4 in ecosystems by considering the input-output flows of all compartments as a function of total system biomass (without detritus) with an inter-ecosystem exponent that obeys the 3/4 law of species metabolism. Analysis of 124 EwE models representing different aquatic ecosystems in the world (Figure 1) indicate that most models (95%) had SDB values greater than 0.75 (Figure 2). This suggests an oversupply of resources characteristic of systems that can have a high proportion of supply/demand, a network that is highly indirect (increased flow to detritus), high resilience, among others properties (Bendoricchio & Palmeri, 2005). We obtained the coefficients a=2.3 and b=0.72 (t-student: P=0.28; t0.05=1.66; not significantly different from 0.75) applying ordinary least squares for the relationship between biomass and outflow (Figure 3). This suggests that the ecosistem metabolism, characterized by the sum of outflow of its compartments, is allometrically scaled with biomass. Even with the spatial-temporal differences between ecosystems, scaling analysis reveals a common pattern in their metabolism, keeping the 3/4 law at higher levels of organization. These preliminary results require further analysis to understand the effect of the transfer   Figure 1. Ecopath with Ecosim models of 124 ecosystems in the world: oceanic, continental selves, reefs, islands, coastal lagoons, rivers, lakes and reservoirs.  0 5 10 15 20 25 30 35 0.1 0.5 0.9 1.3 1.7 2.1 2.5 Tr op hic  m od els n=124 ecosystems SDB index  Figure 2. Frequency distribution of the balance of supply-demand of energy index (SDB) for the 122 Ecopath with Ecosim models illustrated in Figure 1.                                                  1 Cite as: Salcido-Guevara, L., Arreguín-Sánchez, F., 2009. Metabolism of aquatic ecosystems. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 79-80 Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 79 Ecosystem Comparisons & Network Analysis: Posters – Salcido-Guevara & Arreguín-Sánchez 80  1 2 3 4 5 6 7 0 1 2 3 4 5 Lo g ( E ou t; t /k m2 /ye ar) Log (Biomass; t/km2) Log(Eout)=2.30+0.72·Log(B) R2=0.65; n=122  Figure 3. Simple linear regression (OLS) of the log-log relationship of biomass and outflow (i.e., Eout, the sum of flow in each model) of the 122 Ecopath with Ecosim models illustrated in Figure 1. Outliers (n=2) were excluded from this analysis. efficiency on SDB, as well as SDB’s response to historical changes or to simulated environment and fishing pressure which contribute to the study of ecological indices. ACKNOWLEDGEMENTS This study was made possible with support from CONACYT, PIFI, CICIMAR, IPN, LAB. OF DYNAMIC AND MANAGEMENT OF AQUATIC ECOSYSTEMS, PROJECT SPI-IPN 20090932 AND INCOFISH (EC- 003739). REFERENCES Bendoricchio, G., Palmeri, L., 2005. Quo vadis ecosystem? Ecol. Model. 184, 5-17. Garlaschelli, D., Caldarelli, G., Pietronero, L., 2003. Universal scaling relations in food webs. Nature 423, 165-168. Hemmingsen, A.M., 1960. Energy metabolism as related to body size and respiratory surfaces, and its evolution. Rep. Steno Mem. Hosp. (Copenhagen) 9, 1-110. Kleiber, M., 1932. Body size and metabolism. Hilgardia 6, 315-353. Rubner, M. 1879. Ueber die Ausnützung einiger Nahrungsmittel im Darmcanale des Menschen. 15, 115. West, G.B., Brown, J.H., 2005. The origin of allometric scaling laws in biology from genomes to ecosystems: towards a quantitative unifying theory of biological structure and organization. J. Exp. Biol., 208, 1575-1592. West, G.B., Brown, J.H., Enquist, B.J., 1997. A general model for the origin of allometric scaling laws in biology. Science 276, 122- 126. Ecopath 25 Years Conference Proceedings: Abstracts A FISH CHAIN ANALYSIS OF NORTHERN GULF COD RECOVERY OPTIONS:  EXPLORING EWE MODELING APPROACHES FOR POLICY SCENARIOS1 AHMED KHAN Department of Geography, Memorial University of Newfoundland, St. Johns, NL. A1B 3X9; ahmedk@mun.ca This paper aims to provide a holistic understanding of recovery options and future scenarios for Northern Gulf cod fisheries through a fish chain modeling approach using Ecopath with Ecosim (EwE). The fish chain is an analytical framework and a governance perspective in understanding fishery systems through the inter-linkages and interactions in the fish production stages from ‘oceans to plate’. Since the Northern Gulf cod stocks collapsed in western Newfoundland in the early 1990s, there has been no significant increase in stock abundance despite two moratoria (1994-1996 and 2003) as shown in Figure 1, with current stocks below limit reference points. This poor recovery status has consequences for livelihoods and fishing communities as they face on-going socio-economic vulnerabilities. Moreover, most fisheries recovery research in Newfoundland has focused largely on natural systems with little research on the social systems such as market drivers, socioeconomics and governance mechanisms. The key research question focuses on how changes in marine ecosystems and socioeconomics pre- and post- collapse affect current recovery prospects for Northern Gulf cod fisheries. The fish chain perspective focuses on three main production stages and their interactions: pre-harvest, harvest and post- harvest as shown in Figure 2. 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 1974 1978 1982 1986 1990 1994 1998 2002 2006 3+ biomass (t) SSB (t) 3+ Biomass (t) SSB (t) Bi om as s ( t) Bi om as s ( t)  Figure 1. Estimated 3 year old plus and spawning stock biomass-SSB. (DFO, 2009). The pre-harvest stage consists of marine ecosystems, fishery resources and stock assessment on key parameters such as biomass, recruitment and growth. The harvest stage includes fish capture and harvesting methods, fishing fleets, fisher demography, catch and dockside value, income and labor mobility, as well as cost and earnings of fishing operations. Finally, the post-harvest stage includes processing activities, packaging and labeling, marketing strategies, distribution channels, employment and demography, return on investment, purchasing and consumption. This final stage also depends on both demand and supply factors, such as consumer taste and preferences, income earnings, technological innovation, market  Figure 2. Schematic representation of the fish chain modeling approach (Thorpe et al., 2005).                                                  1 Cite as: Khan, A., 2009. A fish chain analysis of Northern Gulf Cod recovery options: exploring EwE modeling approaches for policy scenarios. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 81-83. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 81 Ecosystem Comparisons & Network Analysis: Posters – Khan competition, tariffs and trade barriers, and other aspects that may arise from the previous production stages. Externally driven pressures in global fish trade such as socio-political factors or market failure may also affect various stages of the fish chain which may have implications for meeting rebuilding targets. Unlike most seafood value chain approaches that are limited to the harvest and post-harvest stages, the fish chain approach is holistic and encompasses marine ecosystems and governance mechanisms. Moreover, the conceptual and theoretical framework of fish chains (Kooiman et al., 2005) incorporates supply chain organization literature and ecosystem-based management approaches. The three production stages in the fish chain do not operate in isolation. Rather, they are interconnected through formal and informal institutions as well as social networks at varying spatial scales from local to international. Moreover, the approach also focuses on policy instruments along the fish chain that shapes governance outcome ranging from conservation measures, fishing regulations, international agreements, subsidies and taxes, access rights and standards to consumer awareness. These instruments alter human behavior and ecosystem impacts through socio-political arrangements that affect governance outcomes. Preliminary assessments of fisheries ecosystems in the Northern Gulf region, pre- and post-collapse, revealed ecological constraints, market forces and policy gaps for recovery efforts (Khan & Chuenpagdee, 2009; Khan et al., 2009). Ecosystem modeling of the Northern Gulf of St. Lawrence using EwE by Morissette et al. (2009) indicated a major shift in biomass and catch landings for predatory fishes such as cod. There is also a corresponding regime shift to an ecosystem that is currently dominated by forage fishes and invertebrates as well as a decline in the Marine Trophic Index, a measure of biodiversity (Morissette et al., 2009; Savenkoff et al., 2007). Moreover, from the harvest and post-harvest perspectives, there is a shift in target species from collapsed predatory fisheries to shell fisheries with higher landed value and global niche markets (Schrank, 2005). Although the current fishery has higher production value than before, there is an associated socioeconomic concern in terms of distributional and intergenerational equity with loss of livelihoods as shown in Figure 3. Three listing scenarios and associated recovery plans have been proposed following a cost benefit analysis: (i) no direct fishery with some allowable by- catch, (ii) prioritized rebuilding with 50 % by-catch; and, (iii) maximum rebuilding with a zero by-catch (DFO, 2005). Each of these scenarios has policy implications for fish stocks, foregone revenue and coastal livelihoods. In this contribution, I draw upon recent approaches developed by Christensen et al. (2009) to explore fish chain modeling for recovery options. Integrating the harvest and post- harvest stages in the ecosystem model by Morissette et al. (2009) may provide insights in assessing future recovery options. Three scenarios are proposed, partly based upon DFO (2005) socioeconomic listing criteria: i) recovery of large predatory fishes to the 1980 biomass as a rebuilding target (DFO, 2009); ii) high economic rent from the fishery with or without a recovery plan; and iii) high soci0-cultural benefits with distributional quotas for fishing dependent coastal communities. 16000 6500 2420 214 12080 12725 10000 4780 113 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 No. of plant w orkers No. of harvesters Production value ($'00000) Landed value ($'00000) No. of process. plants Pre collapse (1989) Post collapse (2007)  Figure 3. Socioeconomic overview of the Newfoundland fishing industry (GNPFT, 2008). Solid bars: pre-collapse period of 1989; Clear bars: post-collapse period of 2007. The optimal scenarios and the status quo would be explored further under different policy instruments such as complete moratorium and varying amounts of total allowable catch. The expected outputs are useful in identifying opportunities and viable policy options for recovery including institutional arrangements, policy reforms, stewardship mechanism and conservation incentives.  82 Ecopath 25 Years Conference Proceedings: Abstracts 83 ACKNOWLEDGEMENTS Many thanks to Ratana Chuenpagdee for discussions on the fish chain approach, and to Barb Neis for her insights into recovery options through the Community-University Research for Recovery Alliance (CURRA). I also acknowledge financial support from the Social Science and Humanities Research Council of Canada. REFERENCES Christensen, V., Steenbeek, J., Failler, P., 2009. A combined ecosystem and value chain modeling approach for evaluating societal cost and benefit of fishing. Manuscript in preparation for Ecological Economics. DFO. 2005. Socioeconomic Considerations to Inform a Decision Whether or Not to List Three Populations of Atlantic Cod Under SARA. Discussion document. Economic Analysis and Statistics Policy Sector. Fisheries and Oceans, Ottawa. 143 p. DFO, 2009. Assessment of Cod in the Northern Gulf Of St. Lawrence. DFO Can. Sci. Advis. Sec. Sc i. Advis. Rep. 15 p. GNPFT. 2008. Great Northern Peninsular Fisheries Taskforce Forum. Recommendations and Status Report. Nordic Economic Development Corporation and Red Ochre Regional Board Inc. St. Barbe and Parsons Pond. NL. 21 p. Khan, A., Chuenpagdee, R., 2009. What limits Northern Gulf cod recovery in Western Newfoundland? An assessment of fisheries ecosystems pre and post collapse. Paper presented at the International Marine Conservation Congress, Washington DC. May 19- 24th 2009. Khan, A. Chuenpagdee, R., Neis, B., Hooper, R., Sumaila, R. 2009. A fish chain analysis of Northern Gulf Cod fisheries: Pre- and Post-collapse. Paper presented at the 3rd GLOBEC Open Science Meeting. Victoria, BC. June 22-26th 2009. Kooiman, J., Bavinck, M., Jentoft, S., Pullin, R.S.V., (Editors), 2005. Fish for Life: Interactive Governance for Fisheries. MARE Publication Series No. 3, Amsterdam University Press, Amsterdam. 400 p. Morissette, L., Catonguay, M., Savenkoff, C., Swaine, D.P., Bourdages, H., Hammill, M.O., Hanson, J.M., 2009. Contrasting changes between the northern and southern Gulf of St. Lawrence ecosystems associated with the collapse of groundfish stocks. Deep Sea Res. II DOI:10.1016/j.dsr2.2008.11.023. Savenkoff, C., Castonguay, M., Chabot, D., Hammill, M.O., Bourdages, H., Morissette, L., 2007. Changes in the northern Gulf of St. Lawrence ecosystem estimated by inverse modeling: Evidence of a fishery induced regime shift. Estuarine Coast and Shelf Science. 73(4), 711-724. Schrank, W.E., 2005. The Newfoundland fishery: ten years after the moratorium. Marine Policy 29, 407-420. Thorpe, A., Johnson, D., Bavinck, M., 2005. Introduction: The systems to be governed. In: Kooiman, J., Bavinck, M., Jentoft, S., Pullin R.S.V., (eds), Fish for Life: Interactive Governance for Fisheries, pp 41-44. Amsterdam University Press. Amsterdam. Ecosystem Comparisons & Network Analysis: Posters – Tsagarakis et al. ECOSYSTEM STRUCTURE AND FUNCTIONAL TRAITS OF THE NORTHERN AEGEAN SEA (E. MEDITERRANEAN, GREECE)1 KONSTANTINOS TSAGARAKIS Hellenic Center for Marine Research, Former American Base, Gournes, 71003 Heraklion, Greece; Department of Biology, University of Crete, Heraklion, Greece; kontsag@her.hcmr.gr MARTA COLL Institut de Ciències del Mar, CSIC, Barcelona, Spain); mcoll@icm.csic.es MARIANNA GIANNOULAKI COSTAS PAPAKONSTANTINOU ATHANASSIOS MACHIAS Hellenic Center for Marine Research, Former American Base, Gournes, 71003 Heraklion, Greece; marianna@her.hcmr.gr; pap@ath.hcmr.gr; amachias@ath.hcmr.gr ARGYRIS KALLIANIOTIS Fisheries Research Institute, Nea Peramos, Kavala, Greece; akallian@inale.gr Here we summarize some results regarding important structural and functional traits of the North Aegean Sea ecosystem (Eastern Mediterranean). For the first time, an Ecopath model (Christensen & Walters, 2004) was built to describe the North Aegean Sea (24-26°E, 40-41°N; Greece). The study area, despite the fact that it is an oligotrophic region, is one of the most productive areas in the Eastern Mediterranean which is reflected in the high relative fishing catch (30 % of Greek fisheries landings). Thus, the description of the structural and functional characteristics of this area is necessary to place both natural and anthropogenic drivers into an ecosystem context. The ecosystem model was built for the period 2003-2006 and was restricted in the continental shelf (depths of 20-300 m) where most fishing vessels operate. In total, 40 functional groups (FGs) were defined including pelagic and demersal fishes, several benthic invertebrates, dolphins, turtles, seabirds, detritus and discards. Five fleets were included: trawls, purse seines, static nets, longlines and pots. Anchovy and sardine were described as multi-stanza groups, i.e., split into juveniles and adults. The rest of the fish species where integrated into 18 FGs depending on phylogenetic, behavioural and feeding criteria. Biomass data was obtained from surveys and published information concerning the study area. The rest of the parameters required were obtained from the literature or from results of the Hellenic Center for Marine Research (HCMR) projects. Fisheries data was collected with high regional and temporal detail from the HCMR. Species-specific and fleet-specific discards to marketable ratios were used to estimate the amount of discards generated in annual basis. The Pedigree index (i.e., P, a simple index to categorise the overall quality of the model) scored 0.61 implying a reasonable quality of data sources. Mass-balance was achieved after modifying (a) the diet matrix, notably for FGs whose initial input data were not specific for the region; and (b) biomasses, especially for FGs where the sampling method is known to produce underestimations (e.g., benthopelagic fish).                                                   1 Cite as: Tsagarakis, K., Giannoulaki, M., Papakonstantinou, C., Machias, A., Coll, M., Kallianiotis, A., 2009. Ecosystem structure and functional traits of the Northern Aegean Sea (E. Meditterranean, Greece). In: Palomares, M.L.D., Morissette, L., Cisneros- Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 84-85. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 84 Ecopath 25 Years Conference Proceedings: Abstracts 85 Estimated trophic levels of species and/or FGs were within the range of the known trophic levels for each species in the Mediterranean Sea (Stergiou & Karpouzi, 2002). Results of the mixed trophic impact and keystone species index by Libralato et al. (2006) indicate that mesozooplankton was a keystone group in the North Aegean Sea during 2003-2006, while detritus, suprabenthos, phytoplankton and non crustacean benthic invertebrates followed in terms of total effects and keystoneness. Concerning fish, adult anchovy had the higher overall effect and keystoneness. The mean transfer efficiency of the area was higher compared to other Mediterranean areas, in line with higher oligotrophic conditions of the Eastern basin (Table 1). Several statistics and exploitation indicators such as the primary production required to sustain the catch (PPR %), the gross efficiency of the fishery and the mean trophic level of the catch (mTLc) indicated that the North Aegean Sea during 2003-2006 was a highly exploited ecosystem (Table 1). Moreover, the Loss in production index (Lindex, Libralato et al., 2008) suggested that the ecosystem was unlikely to be sustainably fished (probability was moderate-low). The comparison of the indices to the Catalan Sea and Adriatic Sea ecosystems (Coll et al., 2007; Coll et al., 2006; Table 1) though, implies that the Aegean Sea was slightly less exploited, as revealed by the exploitation indices, the lower catches, and the higher mean trophic level of the catch. The North Aegean Sea was in a higher developmental stage according to Odum’s (1969) theory of ecosystem maturity (Christensen, 1995). A further comparison of the different ecosystems could be useful for the exploration of gradients in exploitation patterns and/or ecosystem functioning in the Mediterranean Sea. Table 1. Statistics, flows and indices for the model of N. Aegean Sea and comparison with other Mediterranean modeled areas (S. Catalan: Coll et al., 2006, N. Central Adriatic: Coll et al., 2007). TL = trophic level; PPR = primary production required; PP = primary production; det = detritus; L index = Loss in production index; Psust = probability of being sustainably fished; a = calculated using pp; b = calculated using both pp + det. Index North Aegean Southern Catalan NCentral Adriatic Units Sum of all consumptions 868.83 852.11 1305.04 t·km−2·yr−1 Total system throughput  1703 1657 3844 t·km−2·yr−1 Sum of all production  791 658 1566 t·km−2·yr−1 Total biomass (excluding detritus)  33.04 58.99 130.3 t·km−2 Total transfer efficiency  17.4 12.6 10 % Total catches 2.34 5.36 2.44 t·km−2·yr−1 Mean TL of the catch  3.47 3.12 3.07  Mean TL of the community (excluding TL1) 2.57 2.37 2.13  PPR to sustain the fishery (from pp) 3.45 9.45 6.59 % PPR to sustain the fishery (from pp+det) 6.76 10.6 15 % Gross efficiency of the fishery (catch/net pp) 0.004 0.014 0.002  Finn's cycling index (of total throughput) 24.40 25.19 14.70 % Finn's mean path length  6.26 4.27 3.34  Connectance index  0.29 0.20 0.21  System Omnivory Index  0.175 0.19 0.19  Ascendency 17.64 25.5 27 % L index a 0.026 0.057 0.024  L index b 0.052 0.063 0.055  Psust a 70.54 44.55 71.65 % Psust b 44.71 28.71 38.48 % REFERENCES Christensen, V. 1995. Ecosystem maturity – towards quantification. Ecol. Model. 77, 3-32. Christensen, V., Walters, C.J., 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172, 109–139. Coll, M., Palomera, I., Tudela, S., Sarda, F., 2006. Trophic flows, ecosystem structure and fishing impacts in the South Catalan Sea, Northwestern Mediterranean. J. Mar. Sys. 59, 63- 96. Coll, M., Santojanni, A., Palomera, I., Tudela, S., Arneri, E., 2007. An ecological model of the Northern and Central Adriatic Sea: Analysis of ecosystem structure and fishing impacts. J. Mar. Sys. 67, 119-154. Libralato, S., Christensen, V., Pauly, D., 2006. A method for identifying keystone species in food web models. Ecol. Model. 195, 153- 171. Libralato, S., Coll, M., Tudela, S., Palomera, I., Pranovi, F., 2008. Novel index for quantification of ecosystem effects of fishing as removal of secondary production. Mar. Ecol. Prog. Ser. 355, 107-129. Odum, E.P., 1969. The strategy of ecosystem development. Science 164, 262-270 Stergiou, I.K., Karpouzi, V.S., 2002. Feeding habits and trophic levels of Mediterranean fish. Rev. Fish Biol. Fish. 11, 217-254.  Climate Impact Evaluation – Fulton CLIMATE IMPACT EVALUATION: ORAL PRESENTATIONS ECOWORLD: EWE ONE LINK IN GLOBAL SYSTEMS MODEL1 ELIZABETH A. FULTON CSIRO Marine and Atmospheric Research GPO Box 1538, Hobart, Tasmania 7001, Australia; beth.fulton@csiro.au Climate change is a challenge that is capturing the attention of science, media, politicians and public alike. It has been the focus of some of the greatest acts of collaborative science the world has seen to date (e.g., the IPCC reports and model comparisons). There have been physical models (see the review in Randall et al., 2007), predictions of shifts in species distributions (Ling et al., 2009; Heikkinen et al., 2006) and models of economic impacts (e.g., Hallegatte, 2009). The work on ecosystems has largely been through the use of the output of global climate models as drivers for multispecies or trophic models (Field et al., 2006). While these studies have all produced insights into potential effects of climate change one significant facet that has typically been lacking is feedback. Ecosystems involve links, direct and indirect pathways between their many ecological, physical, chemical and human (social and economic) components. Feedback and change are at the core of ecosystems. While this has always been true (and is one of the major drivers for using ecosystem models to explore fisheries issues), global climate change has made it clear that the non-stationary nature ecosystems, and their dynamics, needs to be addressed explicitly. The bulk of existing “ecological” or “ecosystem” climate models include plankton, typically phytoplankton, and any links to higher trophic levels (if they exist at all) are unidirectional. While these models are useful for understanding the potential distribution of future production and some of the implications for fish groups it is not enough if science is to provide insight into the dynamics of more complex species assemblages or how natural marine resources will need to be managed into the future. One of the most promising ways of bringing feedback to climate projects is through hybrid or coupled models. EwE (Christensen & Walters, 2004) has an extensive track record as a useful (and fast) tool for representing the trophic dynamics of marine foodwebs. The questions it can be used to address are only expanding with the addition of multi-stanza, spatial and economic options. Perhaps the weakest components of EwE have traditionally been its handling of the biogeochemical end of an ecosystem. This is typically not an issue for many of the questions it has been used to address, but it may prove to be a hindrance if environmental forcing (either bottom-up through production or top-down through environmentally related mortality) plays a major role in the key system processes that will shape ecosystems under climate change. An obvious first step then is to couple EwE with biogeochemical (nutrient-phytoplankton) models, and through them global climate models (GCMs), to begin to build truly end-to-end models that have dynamic feedback connections at every step in the chain. By intelligently using each model in the role it plays best and coupling at points that ‘cut-out’ the weakest representations in each model type (e.g., replacing static environmental forcing and production with a link to dynamic production and climate models) the set of coupled models can avoid the biggest limitations of each of the models in isolation. Figure 1. Schematic diagram of the linking of different model types. This chain of coupled models may be extended still further (e.g., Figure 1). First there is the potential to link it to any number of fully developed economic market, trade or network models. EwE already                                                  1 Cite as: Fulton, E.A., 2009. Ecoworld: EwE one link in global systems models. In: Palomares, M.L.D., Morissette, L., Cisneros- Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 86-87. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 86 Ecopath 25 Years Conference Proceedings: Abstracts 87 covers some of these aspects, but like their physical counterparts, global economic models have a long history and it makes sense to explore how their behaviour changes once linked into a truly dynamic framework. However, the future of dynamically coupled ‘world models’ extends beyond these simple chains. Over the last decade, a range of models have been developed that try to span large portions of marine ecosystems (Travers et al., 2007). Each of these modelling platforms has focussed on different aspects, on different processes or scales. Rather than being considered as competitors, these modelling platforms have the potential to be complementary. This opens up a swath of new opportunities, where GCMs or detailed regional hydrodynamic models are used to capture the physical system, biogeochemical models produce sophisticated projections of the patchy nature of primary production, ecosystem models like Atlantis (Fulton et al., 2005) and EwE provide broad scale context, while other (species-level) models follow the life cycle of specific species of interest, or the dynamics of particular industries and their economic connections and governance. This kind of flexibility, playing to the strength of each modelling tool, can prove a significant scientific instrument. A  B  C   Figure 2. Representative maps from three models for the southeast of Australia (A) a downscaled regional nutrient-phytoplankton-zooplankton model, (B) Atlantis and (C) Ecospace. There are significant scientific challenges involved in successfully and seamlessly coupling models with different temporal, spatial, ecological, anthropogenic and process resolutions. Nevertheless early examples already exist (e.g., in the Southeast of Australia, Figure 2) and are being used to give insight into potential ecosystem-level effects of climate change and the implications of these affects for the sustainability of fisheries. ACKNOWLEDGEMENTS The author would like to acknowledge the hard work and patience of Villy Christensen, Sherman Lai, Bec Gorton, Mark Hepburn, Cathy Bulman, Richard Matear and Chris Brown. Without their skills ‘Ecoworld’ would not have gone so smoothly. REFERENCES Christensen, V., Walters, C., 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172, 109–139. Field, J.C., Francis, R.C., Aydin, K., 2006. Top-down modeling and bottom-up dynamics: linking a fisheries-based ecosystem model with climate. Progr. Oceanog. 68, 238-270. Fulton, E.A., Fuller, M., Smith, A.D.M., Punt, A.E., 2005. Ecological Indicators of the Ecosystem Effects of Fishing: Final Report. Australian Fisheries Management Authority Report, R99/1546. 239 p. Hallegatte, S., 2009. Roadmap to Assess the Economic Cost of Climate Change with an Application to Hurricanes in the United States, pp. 361-386. In: Elsner, J.B., Jagger, T.H. (eds), Hurricanes and Climate Change. Springer, New York. Heikkinen, R.K., Luoto, M., Araújo, M.B., Virkkala, R., Thuiller, W., Sykes, M.T., 2006. Methods and uncertainties in bioclimatic envelope modelling under climate change. Progr. Phys. Geogr. 30, 1–27. Ling, S.D., Johnson, C.R., Ridgway, K., Hobday, A.J., Haddon, M., 2009. Climate-driven range extension of a sea urchin: inferring future trends by analysis of recent population dynamics. Global Change Biol. 15, 719-731 Randall, D.A., Wood, R.A., Bony, S., Colman, R., Fichefet, T., Fyfe, J., Kattsov, V., Pitman, A., Shukla, J., Srinivasan, J., Stouffer, R.J., Sumi A., Taylor, K.E., 2007. Climate models and their evaluation. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., Miller, H.L. (eds), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Travers, M., Shin, Y.-J., Jennings, S., Cury, P., 2007. Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems. Progr. Oceanog.75, 751–770. Climate Impact Evaluation – Libralato & Solidoro EXPERIENCES IN INTEGRATING PHYSICAL-BIOGEOCHEMICAL PROCESSES INTO FOOD WEB DYNAMICS WITH EWE1 SIMONE LIBRALATO COSIMO SOLIDORO Department of Oceanography, National Institute of Oceanography and Experimental Geophysics, OGS, Sgonico-Zgonik (Trieste), Italy; slibralato@ogs.trieste.it, csolidoro@ogs.trieste.it The integration of hydrodynamic, biogeochemical, population and community processes represents a key issue for comprehensively accounting for potential cascading effects of natural variations and anthropogenic disturbances on marine ecosystems. Different stressors (e.g., climatic changes, nutrient inputs, exploitation and pollution) impact simultaneously the capability of the ecosystem to maintain itself (and its biodiversity) and to provide goods and services. Climatic changes, for example, might affect nutrient input to coastal areas (Cossarini et al., 2008) producing biogeochemical processes with cascading effects up to commercial species (Loukos et al., 2003). Physical changes might have important implications for exploited species (e.g., modification of the mixed layer depth; see Aydin et al., 2005) or, conversely, fishing might impact on biogeochemical processes with positive feedbacks on commercial species (Pranovi et al., 2003). Such interactions illustrate that in general, stressors might have counterbalance or synergistic effects. Fishing pressure, for example, might exacerbate or might benefit from effects of climatic changes in the marine ecosystem (Stenseth et al., 2002; Walther et al., 2002). Therefore, in order to study potential synergistic/antagonistic effects of different natural/anthropogenic changes in a truly ecosystem approach, dynamic representation of all involved features, from nutrients to top-predators, is required (de Young et al., 2004). The integration of physical, biogeochemical and ecological processes spanning over different trophic levels into an End-to-End approach, however, needs to account for the different pathways that energy, matter and nutrients might have in a food web. Thus, it is fundamental to describe ecological and functional roles of ecosystem components within each trophic level. Moreover, the integration of physical, biogeochemical and food web dynamics entail a good representation of detritus and related feedbacks that might be crucial in driving ecosystem dynamics (Fulton & Smith, 2004). These, together with the identification of appropriate scales for integration/parameterization of the model and the careful definition of main processes linking physical-biogeochemical-community scales, make the End-to-End modelling a non- trivial task (Cury et al., 2008). Ecopath with Ecosim’s flexibility, i.e., having been used in very different contexts, and ability to propose adequate biological resolutions (Christensen & Walters, 2004), makes such integration possible. Moreover, EwE might represent a straightforward tool for implementing the End-to-End approach with an ensemble of models (de Young et al., 2004). In this work, we present our experiences in linking EwE with other physical-biogeochemical models for an End-to-End approach for the Venice lagoon and the Adriatic Sea. The methodological integration is discussed and the conceived End-to-End tool is here used for analysing scenarios of simultaneous climatic and exploitation changes over time. Biogeochemical processes are represented by hydrodynamic- biogeochemical models forced with Regional Climate Model outputs (Giorgi et al., 2004), while fishing effort is included in the EwE food web description. Structural and functional changes of these ecosystems are analysed also through ecological properties and indices such as trophic level and cycling indexes. Scenario analyses were carried out for understanding the role of biological resolution in shaping the observed ecosystem changes.                                                  1 Cite as: Libralato, S., Solidoro, C., 2009. Experiences in integrating physical-biogeochemical processes into food web dynamics with EwE. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 88-89. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 88 Ecopath 25 Years Conference Proceedings: Abstracts 89 Experiences gained in these preliminary coupling experiments might be very useful for future on-line integration. In addition, they might give useful insights on the choice of space and time scales for the integration and the associated aggregation of the necessary input/output parameters. Moreover, these experiments provide evidence of the large number of processes required to correctly link these models. Finally, advantages and limitations of the use of EwE for linking biogeochemical and food web models illustrate the theoretical and technical difficulties encountered in these coupling experiments. REFERENCES Aydin, K.Y., McFarlane, G.A., King, J.R., Megrey, B.A., Myers, K.W., 2005. Linking oceanic coastal production and growth rates of pacific salmon (Oncorhynchus spp.), using models on three scales. Deep-Sea Res. 52, 757-780. Christensen, V., Walter,s C.J., 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172, 109-139. Cossarini, G., Libralato, S., Salon, S., Gao, X., Giorgi, F., Solidoro, C., 2008. Downscaling experiment for the lagoon of Venice. Part II: potential effects of changes in precipitation on biogeochemical properties. Clim. Res. 38, 43-59. Cury, P.M., Shin, Y., Planque, B., Durant, J.M., Fromentin, J-M, Kramer-Schadt, S., Stenseth, N.C., Travers, M., Grimm, V., 2008. Ecosystem oceanography for global change in fisheries. Trends Ecol. Evol. 23, 338-346. de Young, B., Heath, M., Werner, F., Chai, F., Megrey, B., Monfray, P., 2004. Challenges of modelling ocean basin ecosystems. Science 304, 1463-1466. Fulton, E.A., Smith, A.D.M., 2004. Lessons learnt from a comparison of three ecosystem models for Port Phillip Bay, Australia. African J. Mar. Sci. 26, 219-243. Giorgi, F., Bi, X., Pal, J.S., 2004. Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990). Clim. Dyn. 22, 733–756. Loukos, H., Monfray, P., Bopp, L., Lehodey, P., 2003. Potential changes in skipjack tuna (Katsuwonus pelamis) habitat from a global warming scenario: modelling approach and preliminary results. Fish. Ocean. 12 , 474-482. Pranovi, F., Libralato, S., Raicevich, S., Granzotto, A., Pastres, R. and Giovanardi, O., 2003. Mechanical clam dredging in Venice Lagoon: ecosystem effects evaluated with a trophic mass-balance model. Mar. Biol. 143, 393-403. Stenseth, N.C., Mysterud, A., Ottersen, G., Hurrell, J.W., Chan, K-S., Lima, M., 2002. Ecological effects of climate fluctuations. Science 297, 1292-1296. Walther, G-R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T.J.C., Fromenti,n J-M., Hoegh-Guldberg, O., Bairlein, F., 2002. Ecological responses to recent climate change. Nature 416, 389-395. Climate Impact Evaluation – Brown et al. ECOLOGICAL INTERACTIONS WITHIN MARINE ECOSYSTEMS DETERMINE WINNERS AND LOSERS UNDER CLIMATE CHANGE1 CHRISTOPHER J. BROWN School of Biological Sciences, The Ecology Centre, The University of Queensland, St Lucia Queensland, Australia; Climate Adaptation Flagship CSIRO Marine and Atmospheric Research, Cleveland, Queensland, Australia; christo.j.brown@gmail.com ELIZABETH A. FULTON ALISTAIR J. HOBDAY RICHARD MATEAR Climate Adaptation Flagship Climate Adaptation Flagship CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia; Beth.Fulton@csiro.au; alistair.hobday@csiro.au; Richard.Matear@csiro.au HUGH POSSINGHAM School of Biological Sciences, The Ecology Centre, The University of Queensland, St Lucia Queensland, Australia; h.possingham@uq.edu.au CATHERINE BULMAN Climate Adaptation Flagship Climate Adaptation Flagship CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia; Cathy.Bulman@csiro.au VILLY CHRISTENSEN ROBYN FORREST The Sea Around Us Project, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver BC V6T 1Z4 Canada v.christensen@fisheries.ubc.ca; r.forrest@fisheries.ubc.ca PETER GEHRKE Snowy Mountains Engineering Corporation, Spring Hill, Queensland, Australia; peter.gehrke@smec.com.au NEIL GRIBBLE Queensland DPI&F, Sustainable Fisheries, Northern Fisheries Centre, Cairns, Australia; Neil.Gribble@jcu.edu.au                                                   1 Cite as: Brown, C.J., Fulton, E.A., Hobday, A.J., Matear, R., Possingham, H., Bulman, C., Christensen, V., Forrest, R., Gehrke, N., Gribble, N., Griffiths, S., Lozano-Montes, H., Martin, J., Metcalf, S., Okey, T., Watson, R., Richardson, A.J., 2009. Ecological interactions within marine ecosystems determine winners and losers under climate change. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 90-93. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 90 Ecopath 25 Years Conference Proceedings: Abstracts SHANE P. GRIFFITHS Climate Adaptation Flagship CSIRO Marine and Atmospheric Research, Cleveland, Queensland, Australia; shane.griffiths@csiro.au HECTOR M. LOZANO-MONTES CSIRO Marine and Atmospheric Research, Floreat, Western Australia; hector.lozano-montes@csiro.au JULIE MARTIN Department of Regional Development, Primary Industry, Fisheries and Resources, Darwin, Australia; Julie.Martin@nt.gov.au SARAH METCALF Department of Fisheries, Fisheries Research, Hillarys, West Australia, Australia; Sarah.Metcalf@fish.wa.gov.au THOMAS A. OKEY West Coast Vancouver Island Aquatic Management Board, and University of Victoria, School of Environmental Studies, Victoria BC Canada; Thomas.Okey@gmail.com REG WATSON The Sea Around Us Project, Univeristy of British Columbia, Vancouver, Canada; r.watson@fisheries.ubc.ca ANTHONY J. RICHARDSON School of Mathematics and Physics, The University of Queensland, St Lucia Queensland, Australia; Climate Adaptation Flagship CSIRO Marine and Atmospheric Research, Cleveland, Queensland, Australia; Anthony.Richardson@csiro.au Climate change is the most widespread anthropogenic threat that ocean ecosystems face (Halpern et al., 2008). Primary producers will respond rapidly to climate change due to their small size and high population turnover (Hays et al., 2005) and already the distribution and amount of phytoplankton productivity has been altered by climate change (Behrenfeld et al., 2006; Richardson & Schoeman, 2004). Other primary producers, such as seagrass, mangroves and macro-algae will also be strongly affected by climate change. Changes in the amount and type of primary production will have strong flow-on effects throughout the ecosystem (Scheffer et al., 2005). Therefore, the impact of climate change on primary production and its effects throughout marine food webs needs to be understood to ensure robust ecosystem management to preserve biodiversity and support sustainable fishing. Here we investigate the effects of climate-driven primary production change on biodiversity and fisheries across a broad range of marine ecosystems including coastal, deep sea and open ocean environments. Twelve existing Ecopath with Ecosim models of different Australian marine ecosystems were used to investigate flow-on effects of primary production change on community composition, fishery catch and value, and abundance of species with conservation importance. We simulated different trends in the amount of primary productivity in each Ecosim model to explore how primary production change affects marine ecosystems. Additionally, we considered multiple formulations for each Ecosim model to account for ecological uncertainty. These included the effects of habitat dependency and alternative predator-prey interaction strengths. To further illustrate the potential effects of climate-driven production we linked the CSIRO model of global climate change forced by a high greenhouse gas emission scenario to primary production models that force production rate in Ecosim models. Changes in the physical environment affected the production rate in the models of phytoplankton, macro-algae and seagrass, which were then 91 Climate Impact Evaluation – Brown et al. used to force the twelve Ecosim models and predict changes in abundance of organisms, fisheries catch and value and community composition. Initially, an extensive sensitivity analysis was conducted to explore the influence of primary production change in the ecosystems. Primary production change had a large effect on the abundances of all consumer organisms in all ecosystem types. Generally, biomasses increased with increases in primary production and decreased for decreases in primary production. The mean change in biomass of consumer organisms for all Ecosim models and formulations was similar for all levels of primary production change. However, there was considerable variability between the magnitude of responses for different organisms. When predator-prey interaction strengths were estimated using ecological data, there were stronger and more variable predation and competition interactions. Predation and competition reversed the expected responses of some species, for instance some high-value tuna species declined under productivity increases, due to greater abundances of their predators. Relative community composition was not strongly affected by primary production change if all producers responded similarly to climate change. However, changes in the relative productivity of different types of primary producers, such as sea grasses and phytoplankton, could strongly affect relative community composition. For instance, increases in benthic production (seagrass and macro-algae) in coastal models tended to cause increases in the abundance of higher trophic level organisms, whereas increases in phytoplankton production tended to cause the reverse. Comparison of model simulations with and without habitat dependency showed that abundance of habitat dependent organisms was affected, but that overall community composition, fishery catch and fishery value were not affected. However, lack of data on the response of organisms to habitat change and aggregation of life history stages limited our ability to consider habitat associations in the Ecosim models. We then performed a projection of the ecosystem impacts based on the output from the CSIRO climate model under a high emission scenario. Predicted climate change from the climate model generally led to increases in nutrient availability around Australia and greater primary productivity in most regions. Thus, the Ecosim models generally predicted greater fishery catches (Figure 1) and greater abundances of species of conservation interest, such as turtles and sharks under future climate change. However, ecological interactions reversed the expected responses for some populations, resulting in declines in animal populations and reductions in catch value per kilogram in some regions. Changes in community composition were generally small. The predicted magnitude of climate-driven production change will have large effects on marine ecosystems. Increasing awareness of the role ecological interactions play in determining population level responses to ecosystem change has seen greater consideration of ecological interactions for management of ecosystems (Christensen & Walters, 2004, Fulton et al., 2004). Our research demonstrated that ecological interactions will regulate the responses of species to climate change from a diverse range of taxa and ecosystems. However, the predictive ability of our models given projected greenhouse gas emission scenarios was limited by understanding of habitat dependencies and responses of different types of primary producers to climate change. Investigation of a broader range of processes in marine food web models will improve the efficacy of models for predicting effects of climate change on marine ecosystems. The inclusion and improved description of ecological interactions will enable predictive models to become effective tools for the management of biodiversity and fisheries under climate change.  Figure 1. Change in fishery catch (%) over 50 years from linked climate and Ecosim models for Australia Ecosim model regions.    92 Ecopath 25 Years Conference Proceedings: Abstracts 93 REFERENCES Behrenfeld, M.J., O'Malley, R.T., Siegel, D.A., McClain, C.R., Sarmiento, J.L., Feldman, G.C., Milligan, A.J., Falkowski, P.G., Letelier, R.M., Boss, E.S., 2006. Climate-driven trends in contemporary ocean productivity. Nature, 444, 752-755. Christensen, V., Walters, C.J., 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modelling, 172, 109-139. Fulton, E.A., Smith, A.D.M., Johnson, C.R., 2004. Biogeochemical marine ecosystem models I: IGBEM--a model of marine bay ecosystems. Ecological Modelling, 174, 267-307. Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D'Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., Watson, R., 2008. A global map of human impact on marine ecosystems. Science, 319, 948-952. Hays, G.C., Richardson, A.J., Robinson, C., 2005. Climate change and marine plankton. Trends in Ecology & Evolution, 20, 337-344. Richardson, A.J., Schoeman, D.S., 2004. Climate impact on plankton ecosystems in the Northeast Atlantic. Science, 305, 1609-1612. Scheffer, M., Carpenter, S., de Young, B., 2005. Cascading effects of overfishing marine systems. Trends in Ecology & Evolution, 20, 579-581. Climate Impact Evaluation – Griffiths et al. ECOLOGICAL EFFECTS OF FISHING AND CLIMATE CHANGE ON THE PELAGIC ECOSYSTEM OFF EASTERN AUSTRALIA1 SHANE P. GRIFFITHS CSIRO Marine and Atmospheric Research, PO Box 120, Cleveland Qld 4163, Australia;shane.griffiths@csiro.au JOCK W. YOUNG MATT J. LANSDELL ROBERT A. CAMPBELL CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia; jock.young@csiro.au; matt.lansdell@csiro.au; robert.campbell@csiro.au The tropical and subtropical waters off eastern Australia host a highly dynamic pelagic ecosystem that supports one of Australia’s largest and most valuable Commonwealth fisheries, the Eastern Tuna and Billfish Fishery (ETBF). This large multi- species fishery targets apex predators and, therefore, has the potential to disrupt the functionality of the ecosystem if not properly managed.  1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 1E-006 2E-006 3E-006 4E-006 5E-006 6E-006 7E-006 8E-006 Bio ma ss  (t  km -2 ) 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 0.0007 0.0008 0.0009 Bio ma ss  (t  km -2 ) 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 1E-006 2E-006 3E-006 Bi om as s ( t k m- 2 ) Yellowfin tuna (juvenile) catch Yellowfin tuna (adult) catch Bigeye tuna (juvenile) catch 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 0.0007 Bi om as s ( t k m- 2 ) Observed data Ecosim model fit 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05 0.055 0.06 0.065 0.07 Bi om as s ( t k m- 2 ) 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.0005 0.001 0.0015 0.002 0.0025 Bio ma ss  (t km -2 ) Yellowfin tuna (juvenile) biomass Yellowfin tuna (adult) biomass Bigeye tuna (juvenile) biomass 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 1E-005 2E-005 3E-005 4E-005 5E-005 Bi om as s ( t k m- 2 ) 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.0002 0.0004 0.0006 0.0008 0.001 Bi om as s ( t k m- 2 ) Bigeye tuna (adult) catch Albacore catch 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.002 0.004 0.006 0.008 0.01 0.012 Bio ma ss  (t km -2 ) 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year 0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 Bio ma ss  (t  km -2 ) Bigeye tuna (adult) biomass Albacore biomass  Figure 1. Fits of the Eastern Tuna and Billfish Fishery Ecosim model to standardised biomass and catch data for five large pelagic fish species between 1952 and 2006. An Ecopath model was constructed to explore the ecological effects of longlining and climate change from 1998 to 2018. The model reliably reproduced historic time series data of biomass and fishery catch from 1952 to present for commercially-important species (Figure 1), indicating that the model is capable of predicting the future state of the ecosystem after a specific perturbation. A 50 % reduction in ETBF effort resulted in only modest (2-20 %) increases in the biomass of target species and their predators. Doubling the fishing mortality on individual ETBF target species again resulted in small (< 20 %) changes in the biomasses of any functional group. However, climate change scenarios involving a 20 % decrease in micronekton fish biomass and a 50 % increase in squid biomass both resulted in trophic cascades (Figure 2), highlighting their importance as key prey groups in the system.                                                  1 Cite as: Griffiths, S.P., Young, J.W., Lansdell, M.J., Campbell, R.A., 2009. Ecological effects of fishing and climate change on the pelagic ecosystem off eastern Australia. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 94-95. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 94 Ecopath 25 Years Conference Proceedings: Abstracts 95 0.4 0.6 0.8 1 1.2 1.4 Biomass (End / Start) Toothed whales Green sea turtles Leatherback turtles Seabirds Pelagic mackerel sharks Large sharks Hammerhead sharks Blue shark Black marlin Blue marlin Striped marlin Spearfish Swordfish (adult) Swordfish (juvenile) Yellowfin tuna (adult) Yellowfin tuna (juvenile) Bigeye tuna (adult) Bigeye tuna (juvenile) SBT (adult) SBT (juvenile) Albacore Skipjack Medium scombrids and dolphinfish Small scombrids and carangids Lancetfish Large mesopelagic fishes Medium mesopelagic fishes Small mesopelagic fishes Micronekton fishes Epipelagic squids Small mesopelagic squids Medium mesopelagic squids Large mesopelagic squids Sunfish Opah Pelagic triggerfishes/pufferfishes Epipelagic beloniform fishes Small clupeids/engraulids Mesopelagic crustaceans Epipelagic zooplankton Mesopelagic zooplankton Gelatinous zooplankton Primary producers Detritus Decrease in micronekton fish biomass by 20% in 2008  0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5Biomass (End / Start) Toothed whales Green sea turtles Leatherback turtles Seabirds Pelagic mackerel sharks Large sharks Hammerhead sharks Blue shark Black marlin Blue marlin Striped marlin Spearfish Swordfish (adult) Swordfish (juvenile) Yellowfin tuna (adult) Yellowfin tuna (juvenile) Bigeye tuna (adult) Bigeye tuna (juvenile) SBT (adult) SBT (juvenile) Albacore Skipjack Medium scombrids and dolphinfish Small scombrids and carangids Lancetfish Large mesopelagic fishes Medium mesopelagic fishes Small mesopelagic fishes Micronekton fishes Epipelagic squids Small mesopelagic squids Medium mesopelagic squids Large mesopelagic squids Sunfish Opah Pelagic triggerfishes/pufferfishes Epipelagic beloniform fishes Small clupeids/engraulids Mesopelagic crustaceans Epipelagic zooplankton Mesopelagic zooplankton Gelatinous zooplankton Primary producers Detritus Increased squid biomass by 50% in 2008  Figure 2. Predicted relative changes in the biomass of species groups in the ETBF ecosystem after adjusting the biomass of micronekton fishes and squid groups in 2008 to reflect predicted changes due to climate change (see Young et al., 2009). Results show the change in biomasses in 2018 relative to 1998 and after decreasing the biomass of micronekton fishes by 20 % (left) and increasing the biomass of squids by 50 % (right) in 2008.  Our results suggest there may be ecological redundancy among high trophic level predators since they share a diverse suite of prey and collectively only represent < 1 % of the total system biomass. Consequently, the removal of a single apex predator group can be compensated by small changes in the biomass of several competing groups within the same trophic level. However, when the biomass is altered in groups having high biomass and production rates that serve as important prey and predators, more dramatic cascading effects in biomass changes take place throughout the system. We advocate that these species may be contributing to a ‘wasp-waist’ type of control of ETBF ecosystem rather than top-down or bottom-up processes reported to drive other pelagic systems. ACKNOWLEDGEMENTS Several people made an important contribution to the development of the ETBF ecosystem model by providing data or expert advice. Stock assessment and catch data were generously provided by John Hampton, Simon Hoyle and Don Bromhead (SPC); Michael Hinton (IATTC); Dale Kolody and Jeff Dambacher (CSIRO). Villy Christensen (UBC), Hector Lozano-Montes and Cathy Bulman (CSIRO) provided valuable advice on fitting Ecosim models to time-series data. REFERENCES Young, J.W., Lansdell, M.J., Hobday, A.J., Dambacher, J.D., Cooper, S., Griffiths, S.P., Kloser, R., Nichols, P.D. and Revill, A., 2009. Determining Ecological Effects of Longline Fishing in the Eastern Tuna and Billfish Fishery. FRDC Final Report 2004/063. 310 pp.  Climate Impact Evaluation – Hoover ECOSYSTEM EFFECTS OF CLIMATE CHANGE IN THE ANTARCTIC PENINSULA1 CARIE HOOVER University of British Columbia Fisheries Centre, 2202 Main Mall, Vancouver, BC V6T 1Z4 Canada; c.hoover@fisheries.ubc.ca The Antarctic Peninsula is a highly productive system, in which numerous local and migratory top predators are dependent. In addition, the Antarctic Peninsula (Figure 1) is also one of the fastest warming areas in the world, with an average sea surface temperature increase of 2.5˚C over the last 50 years (Marshall et al. 2006; Rogers et al. 2006) causing substantial decreases in sea ice. With the declining sea ice cover come changes to the ecosystem structure. Krill (Euphausia superba) are an important source of food to top predators within this system, and are highly dependent on the sea ice for survival (Atkinson et al. 2004; Loeb et al. 1997). Decreased sea ice has shown to cause a reduction in the amount of krill within the system, and in turn causes increased mortality on juvenile penguins and seals (Brierley & Reid, 1999). It is expected that as temperature increases, years of low sea ice and low krill abundance will increase, causing a strain on the ecosystem. I have built an ecosystem model in order to understand the ecosystem level changes that will occur due to climate change. The model incorporates 59 functional groups to represent all species within the area, the krill fishery which operates in the area, as well as environmental factors such as the amount of sea ice to drive the model through time. One important function group of the model is ice associated algae, which has been included to represent an important source of food for krill and other organisms throughout the winter. Environmental data from the PALMER Long Term Ecological Research dataset has been integrated into the model to drive the phytoplankton groups through time.  Figure 1. FAO statistical areas (FAO, 2001). The Antarctic Peninsual model is based on area 48.1.  Figure 2. Future climate change simulations in the Antarctic Peninsula ecosystem are based on predicted warming trends and green house gas emissions (IPCC, 2007). Previous research focussed on how climate change is likely to impact krill through alterations of sea ice, with speculations on how the remainder of the ecosystem may be altered. By incorporating environmental data such as sea ice extent and open water extent, different primary producer groups can be forced in order to simulate plausible climate scenarios. Using varying levels of climate change as put forth by the IPCC (Figure 2), and linking them to expected sea ice extent (Smith & Stammerjohn, 2001), we can show the potential future ecosystem states. Under these scenarios, the model is run to show what the effects to krill populations would be, and ultimately, how this will affect top predators and ecosystem structure.                                                  1 Cite as: Hoover, C., 2009. Ecosystem effects of climate change in the Antarctic Peninsula. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 96-97. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 96 Ecopath 25 Years Conference Proceedings: Abstracts 97 REFERENCES Atkinson, A., V. Siegel, E. A. Pakhomov, and P. Rothery. 2004. Long-term decline in krill stock and increase in salp within the Southern Ocean Nature 432:100-103. Brierley, A. S., Reid, K., 1999. Kingdom of the krill: the boom and bust cycle of a tiny crustacean holds the key to the health of the Southern Ocean. New Scientist 162, 36-41. FAO, 2001. FAO Major Fishing Areas. Food and Agriculture Organization of the United Nations. IPCC, 2007. Climate Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, UK and New York, USA. Loeb, V., Siegel, V., Holm-Hansen, O., Hewitt, R., Fraser, W., Trivelpiece, W., Trivelpiece, S., 1997. Effects of sea-ice extent and krill or salp dominance on the Antarctic food web. Nature 387, 897-900. Marshall, G.J., Orr, A., van Lipzig, N.P.M., King, J.C., 2006. The impact of a changing southern hemisphere annular mode on Antarctic Peninsula summer temperatures J. Climate 19, 5388-5404. Rogers, A.D., Murphy, E.J., Johnston, N.M., Clarke, A., 2006. Introduction: Antarctic ecology from genes to ecosystems: the impact of climate change and the importance of scale. Phil. Trans. Royal Soc. B 362, 5-9. Smith, R.C., Stammerjohn, S.E., 2001. Variations of surface air temperature and sea-ice extent in the western Antarctic Peninsula. Ann. Glaciology 33, 493-500.  Climate Impact Evaluation – Preikshot et al. ON THE USE OF BOTH UNCONVENTIONAL AND TRADITIONAL TIME SERIES DATA IN CONSTRUCTING DYNAMIC MODELS OF A MARINE ECOSYSTEM1 DAVID PREIKSHOT RICHARD BEAMISH RUSTON SWEETING CHRYS-ELLEN M. NEVILLE KRISTA LANGE Fisheries and Oceans Canada, Pacific Biological Station, 3190 Hammond Bay Road, Nanaimo, British Columbia, Canada, V9T 6N7; d.preikshot@fisheries.ubc.ca; beamishr@pac.dfo-mpo.gc.ca; SweetingR@pac.dfo-mpo.gc.ca; nevillec@pac.dfo-mpo.gc.ca; Krista.Lange@dfo-mpo.gc.ca We constructed an Ecosim model of the Strait of Georgia to examine bottom-up and top-down ecosystem mechanisms related to historic changes in salmonid populations from 1950 to the present. Populations of chinook and coho salmon in the Strait of Georgia declined dramatically between the mid 1990s and early 21st century. There is strong evidence to suggest that processes occurring early in the marine life history of these salmon are causing the decline (Beamish et al., 2008). This Ecosim model is being used to explore potential mechanisms of salmon declines such as predation, competition and production changes. When model predictions of salmon population changes are tuned to stock assessment data, the results suggest that bottom-up forcing is a very likely source of declining salmon populations. Also of interest was the capacity of the model to resolve changes in species with less well understood dynamics like marine birds and hake. Rather than confounding the predictions made by the model, the use of non-conventional time- series for birds and hake suggest that pervasive changes in the Strait of Georgia have also affected species not targeted by fisheries. The model also helps show how bottom-up processes are filtered through an ecosystem and that the effect of such production changes may actually be even more pronounced in species at higher trophic levels like orcas and seals. REFERENCES Beamish, R.J., Sweeting, R.M., Lange, K.L., Neville, C.M., 2008. Changes in the population ecology of hatchery and wild coho salmon in the Strait of Georgia. Trans. Am. Fish. Soc. 137, 503–520.                                                   1 Cite as: Preikshot, D., Beamish, R., Sweeting, R., Neville, C., Lange, K., 2009. On the use of both unconventional and traditional time series data in constructing dynamic models of a marine ecosystem. In: Palomares, M.L.D., Morissette, L., Cisneros- Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 98. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 98 Ecopath 25 Years Conference Proceedings: Abstracts DEVELOPMENT OF AN ECOSYSTEM MODEL FOR GALVESTON BAY: EVALUATING THE INFLUENCE OF FRESHWATER INFLOWS, NUTRIENT INPUTS AND FISHERIES1 GLEN SUTTON Texas Parks and Wildlife Department, 1502 Pine Dr, Dickinson, TX 77539; Glen.Sutton@tpwd.state.tx.us GEORGE GUILLEN University of Houston Clear Lake, Environmental Institute of Houston 2700 Bay Area Blvd, Box 540, Houston, TX 77058; Guillen@uhcl.edu Galveston Bay is the most productive bay along the Texas Coast (Lester & Gonzalez, 2002). The largest commercial and recreational fisheries in terms of landings and numbers have been reported from this bay system. It contains the most productive and extensive oyster, Crassostrea virginica, reefs along the Texas coast and supports numerous recreational and commercial fisheries for finfish and shrimp. Galveston Bay exhibits a typical estuarine salinity gradient with considerable spatial and temporal variability (0.5-30 psu) (Orlando et al., 1993). The primary factor regulating salinity within the bay system is the Trinity River that contributes approximately 55 % of the freshwater inflow. Portions of the bay system have been characterized as being eutrophic (EPA, 2001).  Figure 1. Predicted long and short term effects of reducing fresh water inflow by 10 % each year in the Galveston Bay (Texas) estuarine ecosystem. Management of estuarine fisheries has traditionally relied on single species population modelling, and management. Unfortunately, this approach neglects the complex interactions of various trophic levels and changes in environmental conditions. For example, within Texas estuaries blue crabs, Callinectes sapidus, play a key role in estuarine environments, supplying a critical food source to many inhabitants. While there appears to be a strong relationship between declining blue crab populations and increased effort (Sutton & Wagner, 2007), other alternatives cannot be ruled out. One widely held belief is that reduced fresh water inflow is to blame. The other is increased predation by endemic fish populations. A predictive management tool is needed that can incorporate these often non-linear interactions that are inherent in ecological processes and may materialize as a result of interaction with management actions.                                                  1 Cite as: Sutton, G., Guillen, G., 2009. Development of an ecosystem model for Galveston Bay: evaluating the influence of freshwater inflows, nutrient inputs and fisheries. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 99-100. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 99 Climate impact evaluation – Sutton & Guillen 100 Ecopath with Ecosim (EwE) is one such ecosystem based stock assessment modelling tool that can incorporate complex interactions between fisheries and abiotic factors such as nutrient inputs, freshwater inflows and salinity fluctuations. We attempt to develop a predictive model of estuarine fish and invertebrate populations using an approach that can evaluate the relative impacts of fishing pressure and other environmental fluctuations. We use time series abundance data from TPWD-Coastal fisheries independent fisheries monitoring data to describe trends in the main biomass groups and examine the influence of predation, freshwater inflow and fishing on blue crabs in Galveston Bay, with a view of putting into perspective the degree of influence each will have on reviving stocks. The model predicts both short and long term responses to reduced freshwater inflow. Long term responses are an overall decline in productivity starting at the base of the food chain, while short term responses are less obvious and appear to temporarily benefit top predators. Gulf Menhaden (Brevoortia patronus), Mullet (Mugil cephalus), and eastern oysters closely follow predicted primary productivity trends estimated using a freshwater inflow forcing function. Spotted seatrout (Cynoscion nebulosus) for example prefers a mid to high range salinity and will avoid fresher portions of the bay. Better data fits for this group can be obtained by adjusting its vulnerability index using a salinity time series forcing function, in agreement with predictions made by foraging arena theory. That is, prey species taking refuge in low salinity regions become more available to predation as salinity increases. Long and short term effects on the Galveston Bay food web were predicted by reducing inflow at a rate of 10 % per annum after the time series ends in 2008 (Figure 1). ACKNOWLEDGEMENTS We would like to thank Danielle Crossen who researched and obtained much of the trophic interaction data used in model development. REFERENCES EPA (Environmental Protection Agency), 2001. National Coastal Condition Report. EPA-620/R-01/005. U.S. EPA. Washington, D.C. Lester, J., Gonzalez, L., 2002. The State of the Bay: a Characterization of the Galveston Bay Ecosystem. GBEP T-7, AS-186/02. Galveston Bay Estuary Program, TCEQ. Austin, Texas. Orlando, S.P., Jr., Rozas, L.P., Ward, G.H., Klein, C.J., 1993. Salinity Characteristics of Gulf of Mexico Estuaries. Silver Spring, MD; National Oceanic and Atsmospheric Administration, Office of Ocean Resource Conservation and Assessment. 209 p. Sutton, G.R., Wagner, T., 2007. Stock Assessment of Blue Crab (Callinectes sapidus) in Texas Coastal Waters. Management Data Series No. 249. Texas Parks and Wildlife, Coastal Fisheries Division, Austin, Tx.  Ecopath 25 Years Conference Proceedings: Abstracts STRUCTURE OF TWO HIGH LATITUDE NORWEGIAN FJORD ECOSYSTEMS ANALYSED USING ECOPATH1 TORSTEIN PEDERSEN EINAR M. NILSSEN Department of Aquatic Biossciences, Norwegian College of Fishery Science, University of Tromsø, n-9037, Breivika, Tromsø; torstein@nfh.uit.no; Einar.Nilssen@nfh.uit.no MARIANNE NILSEN Biomiljø, International Research Institute of Stavanger, Mekjarvik, N-4070, Randaberg; Marianne.Nilsen@iris.no LYNE MORISSETTE Institut des sciences de la mer de Rimouski, 310 Allée des Ursulines, C.P. 3300, Rimouski, QC, G5L 3A1, Canada ; lyne.morissette@globetrotter.net ANITA MAURSTAD Tromsø University Museum, University of Tromsø, N-9037, Breivika, Tromsø; Anita.Maurstad@tmu.uit.no At high-latitudes, fjord systems formed during glaciations often show distinct ecosystem properties that differ from oceanic offshore ecosystems. Along the coast of northern Norway, fjords differ with regard to environmental conditions and ecosystem characteristics. In the high-latitude (69-70°N) of the Ullsfjord- Sørfjord system, an ecological program was run from 1989 to 1997. Top-predators, fish, as well as pelagic and benthic invertebrates were intensively sampled and analyzed with regard to trophic interactions and population dynamics. To investigate factors affecting fjord ecosystem structure, an Ecopath model was developed for the lightly exploited cod-dominated Sørfjord ecosystem for the time period 1993-96 (Pedersen et al., 2008). Trophic level estimates from this model has also been compared to trophic level estimates from stable isotope analysis (Nilsen et al., 2008) to evaluate model structure and suggest further improvements. Sørfjord (area 55 km2) is the relatively shallow inner part of the fjord system and is separated from the deeper Ullsfjord by a shallow sill (Figure 1). In this investigation, another Ecopath model covering the same time period was developed for the outer part of the fjord system, Ullsfjord (area 400 km2). Ullsfjord has higher water temperatures, is deeper and have greater fish diversity than Sørfjord. The Ullsfjord model was compared to the Sørfjord model to investigate if energy flow patterns and trophic structure differed between the two systems. We analyzed and compared the trophic interactions and impacts, keystoneness and system properties of the two ecosystems and discussed how differences in water depth and water temperature may affect the coastal ecosystem structure.                                                  1 Cite as: Pedersen, T., Nilssen, E.M., Nilsen, M., Morissette, L., Maurstad, A., 2009. Structure of two high latitude Norwegian fjord ecosystems analysed using Ecopath. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 101-102. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 101 Climate Impact Evaluation – Pedersen et al. 102 0 50 100 150 Cod Haddock Other gadoids Flatfish Shrimp Catch (kg per 30 min haul) Ullsfjord Sørfjord  Large gadoids (Atlantic cod, saithe and haddock) are the main targets for exploitation and are fished by small boats using gill nets, long-lines and hand-lines. Groundfish trawling is prohibited both in Ullsfjord and Sørfjord, but shrimp trawling is allowed in Ullsfjord. In Sørfjord, all commercial trawling is prohibited. During 1993-96, coastal Atlantic cod (Gadus morhua) was the most abundant fish species in terms of biomass, but cod was more important in Sørfjord than in Ullsfjord. Haddock (Melanogrammus aeglefinus), other gadoids and shrimps (deep-water shrimp, Pandalus borealis, and pelagic shrimp Pasiphaea multidentata) were more important in Ullsfjord than in Sørfjord and euphausiids were abundant in both systems (Figure 2). In contrast, benthic invertebrates may be more important in Sørfjord than in Ullsfjord. The abundance of Norwegian coastal cod peaked during 1993-96, but has decreased to low levels in recent years. Thus, both the Ullsfjord and Sørfjord Ecopath models reflect ecosystems where cod was a dominant top-predator.  Figure 1. Overview of the Ullsfjord and Sørfjord system, Norway. A shallow sill separates the two fjords. The two main spawing areas (SA) for coastal cod are indicated by arrows. Bottom trawl haul locations are indicated by bars. Figure 2. Catch per unit effort for various fish and shrimp groups caught by a fine meshed bottom trawl in the Ullsfjord and Sørfjord system, Norway. ACKNOWLEDGEMENTS We acknowledge The Research Council of Norway for financial support (Project no. 190360/S40) and University of Tromsø for support during sampling and analysis. REFERENCES Pedersen, T., Nilsen, M., Nilssen, E.M., Berg, E., Reigstad, M., 2008. Trophic model of a lightly exoploited cod-dominated ecosystem Ecol. Model. 214, 95-111. Nilsen, M., Pedersen, T., Nilssen, E.M., Fredriksen, S., 2008. Trophic studies in a high latitude fjord ecosystem – a comparison of sTable isotope analyses (δ13C and δ15N) and trophic-level estimates from a mass-balance model. Can. J. Fish. Aquat. Sci. 65, 2791-2806.  Ecopath 25 Years Conference Proceedings: Abstracts CLIMATE IMPACT EVALUATION: POSTER PRESENTATIONS MECHANISMS AFFECTING RECOVERY IN AN UPWELLING FOOD WEB: THE CASE OF THE SOUTHERN HUMBOLDT1 SERGIO NEIRA COLEEN MOLONEY Zoology Department and Marine Research Institute, University of Cape Town, Private Bag X3, Rondebosch 7701, South Africa; seneira@udec.cl; coleen.moloney@uct.ac.za PHILIPPE CURY CRISTIA MULLON bUMR EME-212, CRH-Centre de Recherche Halieutique Méditerranéenne et Tropicale, IRD - IFREMER; Université Montpellier II, Sète, France; philippe.cury@ird.fr; cristia.mullon@ird.fr VILLY CHRISTENSEN The Sea Around Us Project, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver BC V6T 1Z4 Canada; v.christensen@fisheries.ubc.ca Although bottom-up forcing and overfishing are known to induce shifts in ecosystem states, system changes and their reversibility under each factor are still poorly understood (Steele, 2004). In this paper, dynamic food web simulations are conducted to evaluate when and why ecological thresholds may be exceeded, and whether bottom-up forcing or fishing is more likely to induce irreversible ecosystem states. Simulations are conducted using a calibrated food web model of the upwelling system off central Chile (33º-39ºS) and the Ecopath with Ecosim software version 5.1 (Christensen et al., 2005). The effects of fishing scenarios are explored by changing fishing mortality according to trophic level. The effects of bottom-up forcing scenarios are explored by changing phytoplankton biomass, as a function of sea temperature, at El Niño Southern Oscillation (ENSO) and decadal scales. Simulations are carried out for 150 years and impacts, system recovery and regime shifts from each scenario are evaluated using trophodynamic indicators and limit reference points for biomass of functional groups as proxies of food web state and ecological thresholds, respectively. Proportionally distributed fishing along trophic levels is the least harmful fishing scenario, resulting in biomass limit reference points rarely being exceeded and high system recovery. Results are summarized in Table 1. Concentrating fishing at higher and lower trophic levels more likely causes reference points to be exceeded and induces ecosystem changes with low-to-medium recovery potential. No limit reference points are exceeded (or regime shift induced) under ENSO scale bottom-up forcing. Decadal scale bottom- up forcing has different effects on the system depending on the sequence in which the high and low phytoplankton biomass periods are simulated. A shift from low phytoplankton biomass towards high phytoplankton biomass does not result in biomass limit reference points being exceeded, whereas the opposite sequence results in a large number of limit reference points being exceeded with medium recovery. The interplay between fishing and decadal scale bottom-up forcing indicates that bottom-up forcing can dampen the effects of fishing, whereas fishing increases the number of limits reference points exceeded and decreases the recovery observed under decadal scale bottom-up forcing. Results suggest that                                                  1 Cite as: Neira, S., Moloney, C., Cury, P., Mullon, C., Christensen, V., 2009. Mechanisms affecting recovery in an upwelling food web: the case of the southern Humboldt. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 103-104. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 103 Climate Impact Evaluation: Posters – Neira et al. 104 fishing (especially unsustainable strategies) is more likely to cause ecological thresholds to be exceeded and to induce regime shifts of low recovery than decadal scale bottom-up forcing. We consider these results of relevance for the management of fisheries in their ecosystem context. Table 1. Number of Biomass limit reference points (BLimit) exceeded and recovery observed under simulated scenarios. Scenario Description Number of BLimit exceeded % Number of recoveries % Fishing 1 Concentrating fishing at higher trophic levels 9 43 5 56 Fishing 2 Concentrating fishing at lower trophic levels 11 52 8 73 Fishing 3 Proportionally distributed fishing across trophic levels 5 24 4 80 Bottom-up 1 Interannual variability (one ENSO per decade) none  none  Bottom-up 2 Interannual variability (two ENSO per decade) none  none  Bottom-up 3 Interannual variability (one ENSO per decade increased intensity) none  none  Bottom-up 4 Decadal variability (low to high phytoplankton biomass) none  none  Bottom-up 5 Decadal variability (high to low phytoplankton biomass) 15 71 11 73 Fishing 1 and Bottom-up 4  8 38 4 50 Fishing 1 and Bottom-up 5  14 67 10 71 Fishing 2 and Bottom-up 4  5 24 2 40 Fishing 2 and Bottom-up 5  13 62 8 62 Fishing 3 and Bottom-up 4  5 24 3 60 Fishing 3 and Bottom-up 5  14 67 6 43  ACKNOWLEDGEMENTS The study was partly supported by the SEAChange programme of the South African Network for Coastal and Oceanic Research, funded by the National Research Foundation and Marine and Coastal Management. We are grateful to Dr. Astrid Jarre, Dr. Lynne Shannon and three anonymous referees for comments on an earlier version of this paper. SN is grateful to Institut de Recherche pur le Développement (France) and to the Marine Biology Research Centre (University of Cape Town, South Africa) for funding provided to complete his PhD studies. VC acknowledges support from NSERC, Canada, and from the Sea Around Us Project, initialized and funded by the Pew Charitable Trusts. REFERENCES Christensen, V., Walters, C.J., Pauly, D., 2005. ECOPATH with ECOSIM: a User’s Guide. Fisheries Centre, University of British Columbia, Vancouver (November 2005 ed., 154 pp). Steel, J., 2004. Regime shifts in the ocean: reconciling observations and theory. Progress in Oceanography 60, 135–141. Ecopath 25 Years Conference Proceedings: Abstracts SPATIAL AND TEMPORAL TROPHIC DYNAMICS OF TERRESTRIAL ARCTIC ECOSYSTEMS1 PIERRE LEGAGNEUX GILLES GAUTHIER Département de Biologie & Centre d’études nordiques, Pavillon Vachon, Université Laval, Québec, QC, Canada, G1V 0A6 pierre.legagneux.1@ulaval.ca; gilles.gauthier@bio.ulaval.ca CHARLES J. KREBS Department of Zoology, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4 ; krebs@zoology.ubc.ca In a global change context, natural wildlife and habitats will suffer from overexploitation or climate change (Visser, 2008; Berteaux et al., 2006; Thomas et al., 2004; Myers & Worm, 2003). A major challenge in ecology and conservation is to forecast the ecological effects of future climate change (Visser, 2008), using the reported effects of recent climate change on ecological processes. Recently, Thomas et al. (2004) predicted that future climate change may cause the extinction of between 15 % and 37 % of species by 2050, based on species-specific climate envelopes. However, these projections were based on habitat loss with extinction risks for polar ecosystems being underestimated (Jenouvrier et al., 2009). Indeed, nowhere else on earth are the effects of global warming more threatening than in the Arctic. All models predict that warming trends will be strongest in the Polar regions as annual temperatures in the Arctic will increase by as much as 3° to 5°C over the course of the 21st century (ACIA, 2004). As climate warms, the distribution and abundance of species will be altered and thus trophic links disrupted. Hence, there is an urgent need to develop programs for conserving biodiversity in response to likely losses of a significant proportion of Arctic species assemblages (Krebs et al., 2003). ArcticWOLVES (Arctic Wildlife Observatories Linking Vulnerable EcoSystems) is an International Polar Year project that is aimed at understanding food webs and ecosystem processes that affect the tundra. The main objectives of this circumpolar project are to: i) determine if the tundra food web is primarily bottom-up or top-down controlled; ii) measure current impact of climate change on wildlife; and iii) predict future impacts on the food web through monitoring and modelling. Throughout the circumpolar world, terrestrial food webs contain relatively few species and are often dominated by the same groups, making them and the systems in which they occur suitable for comparative research (Krebs et al., 2003). While Ecopath has been widely used in fisheries studies (e.g., Gerber et al., 2009), it has been rarely used to describe terrestrial food webs (but see Ruesink et al. 2002; Krebs et al., 2003). Owing to the existence of Ecosim and Ecospace packages included in Ecopath, both temporal and spatial modelling can be conducted. The different sites included in the ArcticWOLVES project (Figure 1) and the long term  Figure 1. Map of the ArcticWOLVES study sites.                                                  1 Cite as: Legagneux, P., Gauthier, G., Krebs, C.J., 2009. Spatial and temporal trophic dynamics of terrestrial arctic ecosystems. In: Palomares, M.L.D., Morissette, L., Cisneros-Montemayor, A., Varkey, D., Coll, M., Piroddi, C. (eds.), Ecopath 25 Years Conference Proceedings: Extended Abstracts, pp. 105-106. Fisheries Centre Research Reports 17(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. 167 p. 105 Climate Impact Evaluation: Posters – Legagneux et al. 106 monitoring on Bylot Island allow us to address several issues on the tundra arctic food web dynamic using Ecopath. For spatial modelling, we used data that were simultaneously collected at seven study sites (Figure 1) on primary production and the abundance and consumption of the major functional groups in 2007 and 2008 using the same protocols. The comparison across sites allows us to depict the functioning of the tundra ecosystem through a gradient of primary production and shed some light on the questions of relative strength of bottom-up vs. top-down effects in structuring arctic communities. For temporal modelling, we used the long term monitoring of most components of the food web (from plants to top predators) on Bylot Island from 1983 to 2008 to investigate temporal variation in the food web and to assess the effect of lemming cycles and grazing by a large snow goose colony on the food web structure (Figure 2). Finally, the temporal model of Bylot Island allows us to investigate and predict the effect of climate change on the food web through the input of long term series on climate (precipitation, NDVI, snow cover etc.) as well as climatic predictions for the next century (Jenouvrier et al., 2009; Thomas et al., 2004).  Figure 2. The Bylot Island food web, based on 15 years of data collection. ACKNOWLEDGEMENTS We are grateful to Marie-Christine Cadieux for her help in managing the data and to all the fieldworkers, students and researchers who collaborated with this project. REFERENCES ACIA, 2004. Impacts of Warming Climate: Arctic Climate Impact Assessment. Cambridge University Press, Cambridge, UK (online: http://www.acia.uaf.edu/). Berteaux, D., Humphries, M.M., Krebs, C.J., Lima, M., McAdams, A.G., Pettorelli, N., Réale, D., Saitoh, T., Tkadlec, E., Weladji, R.B., Stenseth, N.C., 2006. Constraints to projecting the effects of climate change on mammals. Climate Res. 32, 151–158. Gerber, L.R., Morissette, L., Kaschner, K., Pauly, D., 2009. Should whales be culled to increase fishery yield? Science 323(5916), 880- 881. Jenouvrier, S., Caswell, H., Barbraud, C., Holland, M., Stroeved, J., Weimerskirch, H., 2009. Demographic models and IPCC climate projections predict the decline of an emperor penguin population. Proc. Nat. Acad. Sc.i U.S.A. 106, 1844-18487. Krebs, C.J., Danell, K., Angerbjörn, A., Agrell, J., Berteaux, D., Brathen, A., Danell, ö, Erlinge, S., Fedorov, V., Fredga, K., Hjältén, J., Högstedt, G., Jonsdottir, I.S., Kenney, A.J., Kjellén, N., Nordin, T., Roinen, H., Svensson, M., Tannerfeldt, M., Wiklund, C. 2003. Terrestrial trophic dynamics in the Canadian Arctic. Can. J. Zool. 81, 827-843. Myers, R.A., Worm, B. 2003. Rapid worldwide depletion of predatory fish communities. Nature 423, 280-283. Ruesink, J.L., Hodges, K.E., Krebs, C.J. 2002. Mass-balance analyses of boreal forest population cycles: merging demographic and ecosystems approaches. Ecosystems 5, 138-158. Thomas, C.D., Cameron, A., Green, R.E., Bakkenes, M., Beaumont, L.J. Collingham, Y.C., Erasmus, B.F.N., Ferreira de Siqueira, M., Grainger, A., Hannah, L., H