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An analysis of the management and economics of salmon aquaculture Liu, Yajie 2008

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AN ANALYSIS OF THE MANAGEMENT AND ECONOMICS OF SALMON AQUACULTURE  by  YAJIE LIU   B.Sc. Shanghai Fisheries University, 1990 M.Sc. University of Troms?, 2000      A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in  THE FACULTY OF GRADUATE STUDIES  (Resource Management and Environmental Studies)    THE UNIVERSITY OF BRITISH COLUMBIA  January 2008        Yajie Liu, 2008   ii  Abstract  Salmon aquaculture can be a potential solution to bridge the gap between declining capture fisheries and increasing seafood demand. However, the environmental impacts it creates have generated criticism. The overall objectives of this dissertation are to examine the economic consequences of environmental issues associated with salmon aquaculture, and  to  explore  policy  implications  and  recommendations  for  reducing  environmental impacts. These objectives are addressed in five main analyses.          The growth of salmon aquaculture is analyzed based on farmed salmon production in the  four  leading  producing  countries  and  the  sector  as  a  whole.  Analyses  indicate  that salmon aquaculture is unlikely to continue to grow at its current pace. A joint production function approach is used to estimate pollution abatement costs for  the  salmon  aquaculture  industry.  Results  reveal  that  pollution  abatement  costs  vary among observations and models. On average, pollution abatement cost is estimated at 3.5% in terms of total farmed salmon production, and 6.5% in terms of total revenue of farmed salmon.  The ecological and economic impacts of sea lice from salmon farms on wild salmon population  and  fisheries  are  also  studied.  Analyses  suggest  that  these  effects  are  minor when the sea lice induced mortality  rate is below 20%,  while they  can  be severe if the mortality is greater than 30%. Sea lice have greater ecological and economic impacts on pink salmon than on chum salmon. These effects are greater under a fixed exploitation rate than under a target escapement policy. The  economic  performance  of  open  netcage  and  sea-bag  production  systems  for salmon  aquaculture  is  compared.  Netcage  systems  appear  to  be  more  economically profitable than sea-bag systems when environmental costs are either not or only partially included. Sea-bag systems can be financially profitable only when the salmon they produce can achieve a price premium. Finally,  policy  implications  are  explored  and  recommendations  are  made  for sustaining  salmon  aquaculture  in  a  holistic  manner  based  on  the  results  from  previous chapters.  Technologies,  economic-based  instruments  and  more  stringent  environmental policies can be employed to reduce environmental impacts. However, there is no single solution  to  solve  these  environmental  impacts,  and  a  combination  of  policy  options  is needed.    iii  Table of Contents  Abstract................................................................................................................................ ii Table of Contents ............................................................................................................... iii List of Tables ........................................................................................................................v List of Figures..................................................................................................................... vi Co-Authorship Statement.................................................................................................. ix Chapter 1 General Introduction and Review of Salmon Aquaculture ...........................1 1.1 General Introduction and Thesis overview..............................................................1 1.2 Review of Salmon Aquaculture ................................................................................3 1.2.1 Introduction...........................................................................................................3 1.2.2 Overview of Salmon Aquaculture.........................................................................5 1.2.3 Salmon Aquaculture and its Effects......................................................................8 1.2.4 Salmon Aquaculture Practice in Leading Producing Countries or Regions .......17 1.2.5 Economics of Environmental Problems..............................................................24 1.3 References.................................................................................................................31 Chapter 2 Growth of Salmon Aquaculture .....................................................................39 2.1 Introduction..............................................................................................................39 2.2 Global Salmon Aquaculture Production................................................................40 2.3 Analyses of Growth in Salmon Aquaculture.........................................................41 2.4 Discussions and Conclusions...................................................................................44 2.5 References.................................................................................................................47 Chapter 3 Estimating Pollution Abatement Costs of Salmon Aquaculture .................49 3.1 Introduction..............................................................................................................49 3.2 Theoretical Framework...........................................................................................52 3.2.1 Environmental Production Function ...................................................................55 3.2.2 Directional Distance Output Function ................................................................57 3.2.3 Pollution Abatement Costs..................................................................................58 3.2.4 Directional Vector...............................................................................................60 3.3 The Data....................................................................................................................61 3.4 Results and Discussions ...........................................................................................63 3.5 Sensitivity Analysis ..................................................................................................66 3.6 Conclusions...............................................................................................................68 3.7 References.................................................................................................................72 Chapter 4 Potential Impacts of Sea Lice from Farmed Salmon on Wild Salmon Fisheries ..............................................................................................................................75 4.1 Introduction..............................................................................................................75 4.2 British Columbia Wild Salmon Fisheries ..............................................................77 4.3 Methodology .............................................................................................................80 4.3.1 Age-structured Model .........................................................................................80 4.3.2 Catch Function ....................................................................................................82 4.3.3 Cost Function ......................................................................................................83 4.3.4 Profit Function ....................................................................................................83 4.3.5 Potential Ecological and Economic Effects of Sea lice ......................................85 4.4 The Data....................................................................................................................85 4.4.1 Ecological Parameters.........................................................................................86 4.4.2 Economic Parameters..........................................................................................89   iv  4.4 Results .......................................................................................................................91 4.4.1 Chum Salmon......................................................................................................91 4.4.2 Pink Salmon ........................................................................................................93 4.5 Sensitivity Analysis ..................................................................................................95 4.5.1 The Effects of Combined Factors .......................................................................96 4.5.2 Mortality Rate Induced by Sea Lice from Salmon Farm ....................................98 4.5.3 Productivity and Capacity Parameter................................................................102 4.5.4 Costs and Price..................................................................................................103 4.6 Discussions and Conclusions.................................................................................104 4.7 References...............................................................................................................108 Chapter 5 Economic Analysis of Netcage Versus Sea-bag Production Systems for Salmon Aquaculture in British Columbia .....................................................................113 5.1 Introduction............................................................................................................113 5.2 Materials and Methods..........................................................................................114 5.2.1 Salmon Aquaculture Systems ...........................................................................114 5.2.2 Production Capacity..........................................................................................116 5.2.3 Economic Analysis............................................................................................117 5.3 Results .....................................................................................................................127 5.4 Sensitivity Analysis ................................................................................................130 5.4.1 Discount Rate....................................................................................................131 5.4.2 Feed Costs.........................................................................................................132 5.4.3 Environmental Costs.........................................................................................133 5.4.4 Market Price......................................................................................................134 5.4.5 Feed Conversion Ratio and Survival Rate ........................................................135 5.4.6 Growth Cycle ....................................................................................................135 5.4.7 A Combination of Input Factors .......................................................................136 5.5 Discussions and Conclusions.................................................................................137 5.6 References...............................................................................................................139 Chapter 6 Conclusions, Policy Implications and Recommendations..........................142 6.1 Summary.................................................................................................................142 6.2 Current Environmental Management Strategies and Policies ..........................143 6.3 Key Findings, Policy Implications and Recommendations................................146 6.3.1 The Growth of Salmon Aquaculture.................................................................146 6.3.2 Pollution Abatement Cost .................................................................................147 6.3.3 Impacts of Sea Lice on Wild Salmon Populations and Fisheries......................149 6.3.4 Open Netcage vs Sea-bag Production Systems.................................................150 6.4 Conclusions.............................................................................................................152 6.5 References...............................................................................................................154 Appendix 4.1. Location of Salmon Farms in Broughton Archipelago Area ..........156 Appendix 4.2. Calculation of the Population Capacity.............................................157 Appendix 4.3.  Ricker Population-recruitment Model with Stochastic Variable ..158      v  List of Tables Table 1.1.Problems and negative impacts associated with salmon aquaculture ................................................9 Table 3.1. Summary Statistics for the Norwegian Salmon Aquaculture, 1985 - 2005.....................................62 Table 3.2. Average pollution abatement costs associated with the two production models.............................63 Table 4.1a. Parameter values for chum salmon. ..............................................................................................87 Table 4.1b. Parameter values for chum salmon. ..............................................................................................88 Table 4.2a. Parameter values for pink salmon. ................................................................................................89 Table 4.2b. Parameter values for pink salmon.................................................................................................89 Table 4.3. Recruitment, harvest, escapement and total discounted profit for chum salmon............................91 Table 4.4. Recruitment, harvest, escapement and the total discounted profit for pink salmon........................94 Table 5.1. Estimated capital investment costs and annual depreciation for netcage systems. .......................119 Table 5.2. Estimated capital investment costs and annual depreciation for sea-bag systems. .......................120 Table 5.3. Enterprise budget over a single production cycle of netcage and sea-bag production systems. ...123 Table 5.4. Estimated Feed cost based on the quantity used and price............................................................124 Table 5.5. Estimated smolt cost based on quantity used and price ................................................................124 Table 5.6. Estimated labour cost based on the numbers of employee assumed and their weekly wages.......124 Table 5.7. Projected 20-year cash flows in thousand Canadian dollars for netcage production systems.......128 Table 5.8. Projected 20-year cash flows in thousand Canadian dollars for sea-bag production systems.......129 Table 5.9. Financial performance of netcage and sea-bag systems................................................................130 Table 5.10. Net present values under different values of input factors for sea-bag systems..........................136                     vi  List of Figures Figure 1.1. Farmed salmon production by major producing country and species..............................................7 Figure 1.2. Nominal prices of farmed and wild salmon in British Columbia and the United States. ..............16 Figure 1.3. Production and value of farmed and wild salmon in BC. ..............................................................19 Figure 1.4. Farmed and wild salmon production in Norway............................................................................20 Figure 1.5. Production and production costs of Norwegian farmed salmon. ...................................................21 Figure 1.6. Wild and farmed salmon and wild sea trout production in the UK. ..............................................23 Figure 1.7. External costs and market effects. .................................................................................................26 Figure 2.1. Farmed salmon production by major producing country...............................................................41 Figure 2.2. 5-year moving average of year-on-year growth rate of farmed salmon production. .....................43 Figure 2.3. 5-year moving average of year-on-year growth rate of production of ?all finfish aquaculture? ....43 Figure 2.4. 5-year moving average of year-on-year growth rate of catch of ?all capture finfish species?........44 Figure 2.5. Changes in production, cost and price of Norwegian farmed salmon. ..........................................46 Figure 3.1. Nitrogen and phosphorus from Norwegian salmon aquaculture industry and other sources.........50 Figure 3.2. Environmental output sets. S1: regulated technology; S2: unregulated technology......................54 Figure 3.3. Illustration of environmental production and output distance functions........................................59 Figure 3.4. Pollution abatement costs for two production models...................................................................64 Figure 3.5. Production loss due to technical inefficiency ................................................................................66 Figure 3.6. Estimated pollution abatement cost for various mapping rules.. ...................................................67 Figure 3.7. Pollution abatement costs under different mapping rules for inputs and outputs. .........................68 Figure 4.1. The study area (dark oval), including Kingcome and Bond to Knight Inlet..................................79 Figure 4.2. Ecological and economic impacts of sea lice on chum salmon .....................................................93 Figure 4.3. Ecological and economic impacts of pink salmon under two management strategies...................95 Figure 4.5. Recruitment changes under three scenarios for pink salmon under two management policies. ....98 Figure 4.6. Recruitments and discounted profits for chum salmon under a fixed exploitation rate policy......99 Figure 4.7. Recruitments and discounted profits for chum salmon under a target escapement policy. .........100 Figure 4.8. Recruitments and discounted profits for pink salmon under a fixed exploitation rate policy......101 Figure 4.9. Recruitments and discounted profits for pink salmon under a target escapement policy. ...........102 Figure 5.1. Nominal costs of some input factors for salmon aquaculture in British Columbia . ...................121 Figure 5.2. Nominal production cost and price of salmon aquaculture in British Columbia. ........................125 Figure 5.3. Net present values for netcage systems at different discount rates .............................................132 Figure 5.4. Net present values for netcage systems when feed costs increase and decrease..........................133 Figure 5.5. Net present values for netcage systems under different environmental costs..............................134    vii  Acknowledgements  It has been a long, great and challenging journey for me. Along the way, I have been accompanied and supported by many people who made this dissertation possible. Now I have the opportunity to express my sincere gratitude to them.  First  of  all,  I  would  like  to  express  my  deepest  and  most  sincere  gratitude  to  Dr. Rashid  Sumaila,  my  thesis  supervisor,  for  introducing  me  to  the  wonderful  world  of resource  and  environmental  economics.  I  would  have  never  started  and  finished  this dissertation without his enthusiasm, inspiration, mentoring, encouragement and support. I am so grateful for his believing in me and what I am doing, and I am so thankful for his invaluable guidance and advice. His cheerful enthusiasm and ever-friendly nature and his motto  ?KEEP  PUSHING?  have  kept  me  in  a  good  fighting  spirit  to  accomplish  my dissertation. I could not have imagined having a better mentor than Rashid for my PhD.  I  would  like  to  thank  my  committee  members,  Dr.  Ratana  Chuenpagdee  from  the Department  of  Geography  and  Social  Studies  at  the  Memorial  University  of Newfoundland, Dr. Sumeet Gulati, Food and Resource Economics and Forest Resources Management of the University of British Columbia, Dr. John Volpe from the School of Environmental  Studies  at  the  University  of  Victoria,  Dr.  Les  Lavkulich,  Resource Management and Environmental studies of the University of British Columbia. They all have played important roles and guided me at different stages of my work. Thank you all for your great effort, advice and support. It has been a great experience for me to work with you all.  I would like to thank all faculty and research associates at the Fisheries Centre for sharing information, guidance and thoughtful discussions. Especially, I would like to thank Dr. Daniel Pauly for providing my first job at the Fisheries Centre; I have benefited a lot from his global approaches to fisheries issues.    During my work, I have been helped by many people from academia, government, industry, communities and NGOs. Thank you all very much for your generosity and help. I owe  a  special  thanks  to  Dr.  Andy  Rosenberg  of  the  University  of  New  Hampshire  for helping me secure WWF funding; Robert Ahrens for helping me with salmon population dynamic models; Drs. William Cheung and Cameron Ainsworth for helping with Visual   viii  Basic programming; Dr. Carl Pasurka from the US Environmental Protection Agency with GAMS,  and  Ms.  Svein Erik  Stave  from  Statistics  Norway  for  providing  me  Norwegian salmon aquaculture data. My thanks also go to Vasiliki Karpouzi, Dale Marsden, Meagan Bailey and Janice Doyle for partially proof-reading parts of my thesis.   I am also very grateful to Janice Doyle and Ann Tautz at the Fisheries Centre and Lisa Belanger at the Resource Management and Environmental Studies for assisting and keeping  me  on  track  with  all  the  logistics  of  my  study  and  work.  I  also  give  a  special thanks to Gerry O?Doherty and Rosalie Casison for keeping my computer working. I would like to thank all my fellow graduates and colleagues at the Fisheries Centre for providing me a stimulating and  fun environment in which to learn  and grow.  It has been wonderful to get to know you and work with some of you. You all have made my journey  very  educational,  enjoyable  and  memorable.  I  have  made  some  good  friends through the  years,  I can?t name them all. Thank  you all for helping me get through the difficult  times  I  have  encountered,  and  for  all  the  emotional  support,  friendship, comraderie,  entertainment,  company  and  caring  you  provided  to  me.  I  could  have  not achieved it without you all. Especially, I am so thankful to Dr. Maria (Deng) Palomares for providing me safe shelter during the most difficult days of this journey. I am also very thankful to my sport-mates, Carie, Robyn, Jordon, Fang, Jeff, Theresa and Peter for keeping me physical fit and ready for the fight.  I owe a big debt to my Chinese friends who provide an environment where I really feel like home. Thank you all for the great support. Last  but  not  least,  I  wish  to  thank  my  entire  family  back  in  China,  my  parents, brothers,  sisters-in-law,  nephews  and  nieces  for  their  unconditional  love,  patience  and moral support. I know no matter what happens, I will always have a safe place to go to.  Financial  support  from  WWF,  Environment  Canada,  Pacific  Biologist  Foundation, Canada?s Research Network in Aquaculture (AquaNet), Canada is greatly appreciated.  I dedicate this dissertation to my grandma who passed away during the first year of my PhD study.    ix  Co-Authorship Statement   A version of chapter 2, ?can farmed salmon production keep growing?, is in press in the journal  Marine  Policy.  U.  Rashid  Sumaila,  my  supervisor,  is  coauthor  on  the  paper. Chapter 5, ?economic analysis of Netcage versus sea-bag production systems for salmon aquaculture  in  British  Columbia?,  has  been  published  in  the  journal  Aquaculture Economics and Management. U. Rashid Sumaila, my supervisor, is coauthor on the paper. A version of chapter 3, ?estimating pollution abatement costs of salmon aquaculture?, will be submitted to the journal Land Economics, with U. Rashid Sumaila and Sumeet Gulati, one  of  my  committee  members,  as  coauthors.  A  version  of  chapter  4,  ?the  potential ecological and economic impacts of sea lice from salmon farms on wild salmon fisheries?, will be submitted to the journal Canadian Journal of Fisheries and Aquatic Science, with U.  Rashid  Sumaila  and  John  Volpe,  one  of  my  committee  members,  as  coauthors.  A version of Chapter 6, ?salmon aquaculture and the environment: economic perspectives for policy development?, is in preparation, with U. Rashid Sumaila and Ratana Chuenpagdee, one of my committee members, as coauthors. The first author for each Chapter which has been  published,  or  is  in  press  or  will  be  submitted  for  publication  has  been  the  core contributor in terms of identifying, designing and performing of the research, conducting data analyses and preparing manuscripts. The coauthors all have been helping to prepare manuscripts.          1  Chapter 1 General Introduction and Review of Salmon Aquaculture   1.1 General Introduction and Thesis overview  Aquaculture has provided employment and income opportunities for coastal communities as  well  as  foreign  income  to  the  producing  countries,  and  affordable  seafood  for consumers. It has also been seen by many as a strong potential contributor to bridge the gap between dwindling capture fisheries and increasing seafood demand. With advanced technologies  and  globalization,  aquaculture  has  become  the  fastest-growing  food-producing  sector  in  the  world.  However,  the  rapid  expansion  and  development  of aquaculture have  created environmental problems, in particular, the industrial culture of carnivorous species, such as salmon.   Environmental problems that can be brought about by salmon aquaculture include disease and  parasite  transfer  and  spreading,  escapees,  waste  discharges,  introduction  of  exotic species (e.g., Atlantic salmon into the Pacific Ocean), uses of chemicals and drugs, and consumption  of  fishmeal  and  fish  oil.  The  resources  or  sectors  that  can  potentially  be affected consist of wild and recreational fisheries, marine mammals, recreational activities, and upland properties, archaeological resources and navigation. These effects have made salmon aquaculture one of the most controversial forms of aquaculture in the world.  While the negative environmental impacts associated with salmon aquaculture have been widely acknowledged, economic analysis of these impacts is rarely conducted. Thus, this dissertation  aims  to  examine  the  economic  consequences  of  environmental  impacts associated  with  salmon  aquaculture.  Based  on  the  results  of  the  economic  analyses,  I explore policy implications and recommendations for reducing environmental impacts and sustaining  salmon  aquaculture  in  a  holistic  manner.  Different  environmental  problems addressed to achieve this objective are organized into six chapters as described below.     2  In Chapter 1, I present an overview of salmon aquaculture. Environmental and economic impacts associated with salmon aquaculture are reviewed. I follow this with a review of aquaculture  practice  in  the  four  leading  producing  countries  of  the  world.  Then,  the theoretical  foundation  of  environmental  problems  from  an  economic  perspective  ? externality ? is presented. Finally, some existing methods and techniques for measuring environmental costs are introduced based on the literature review.   Salmon aquaculture has expanded rapidly in the last two decades. It is believed that salmon aquaculture will continue to increase to meet growing seafood demand since wild capture fisheries has stagnated. In Chapter 2, a question is posed: can farmed salmon production keep  growing?  To  answer  this  question,  the  5-year  moving  average  rates  of  growth  in salmon  aquaculture  production  over  time  were  analyzed  for  four  of  the  world?s  leading salmon aquaculture countries, and globally.   Pollution  discharged  from  salmon  farms  has  intensified  due  to  the  rapid  expansion  of salmon  aquaculture.  In  some  coastal  areas,  salmon  aquaculture  has  become  the  largest source  of  certain  types  of  pollution  (e.g.,  nitrogen  and  phosphorus)  compared  to agriculture,  sewage  and  industry.  In  Chapter  3,  I  introduce  an  innovative  production function  approach  to  address  pollution  problems  associated  with  salmon  aquaculture.  A joint production approach was developed to model the good outputs (salmon products) and bad  outputs  (pollution)  from  salmon  aquaculture  simultaneously.  Two  environmental production technologies were proposed, namely, regulated and unregulated technologies. Two  production  functions  with  different  mapping  rules  were  specified  in  the  analysis. Empirical  application  was  based  on  time  series  data  from  the  Norwegian  salmon aquaculture industry. Pollution abatement costs are estimated using this approach.  Sea lice problems associated with salmon aquaculture have been at the centre of debate over the environmental impacts of salmon aquaculture worldwide. It is believed that sea lice from salmon farms pose a high risk to the declining wild salmonids. In Chapter 4, I examine the potential ecological and economic impacts of sea lice problem on wild salmon fisheries. Salmon population dynamics and bioeconomic models are developed. Pink and   3  chum salmon in the Broughton Archipelago, British Columbia, are used as case studies. Two management strategies are applied: fixed exploitation rate and target escapement. I also explore how the combined factors affected wild salmon populations and fisheries.  Conventional netcage technology for salmon aquaculture has been criticized because it is believed  to  be  the  key  reason  for  generating  environmental  problems  from  salmon aquaculture.  One  way  to  prevent  or  minimize  these  problems  is  to  use  enclosed containment production systems, such as sea-bags. In Chapter 5, I compare the economic performance  of  netcage  and  sea-bag  production  systems  with  and  without  incorporating environmental  costs  into  production  decision  making.  Capital  budget  and  investment appraisal methods are applied.   Based on the results of the analyses (Chap. 2 - 5) conducted earlier, it can be concluded that  salmon  aquaculture  is  unlikely  to  continue  to  grow  at  the  current  pace,  and  does potentially impose costs on the environment and natural resources, such as wild salmon. Without  government  intervention  and  economic  incentives,  the  salmon  aquaculture industry  may  not  incorporate  these  environmental  costs  into  their  production  decision making.  Thus,  in  Chapter  6,  policy  implications  and  recommendations  are  explored  for reducing  environmental  costs.  Different  options,  such  as  technological  approaches, institutional  measures,  environmental  regulations  and  economic  instruments  (e.g., pollution taxes and subsidies) are proposed as potential solutions.    1.2 Review of Salmon Aquaculture 1.2.1 Introduction Aquaculture  is  ?the  farming  of  aquatic  organisms,  including  fish,  mollusks,  crustaceans and aquatic plants? (FAO 2000). Aquaculture is different from capture fisheries because it involves  some  form  of  intervention  during  the  organism?s  rearing  process  from  larvae stage to adulthood. An important feature of aquaculture is that it is an activity owned by an   4  entity (e.g., an individual or a company) unlike capture fisheries resources (FAO 2000). Aquaculture per se is not a new activity, and has been practiced for centuries in ancient Asia and the Mediterranean. The real evolution of aquaculture development started in the 1970s due to technological advancements and growing world seafood demand (Subasinghe 2005).  Since  then,  aquaculture,  in  particular  industrialized  aquaculture,  has  dramatically expanded, and it has now become the fastest-growing food-producing industry in the world economy (Hishamunda and Ridler 2002; FAO 2007).   Aquaculture  is  highly  diverse,  and  comprises  a  wide  range  of  species,  systems  and production practices. Worldwide, over 200 species occupying different levels of the food web  have  been  commercially  cultivated  (Subasinghe  2005).  Based  on  the  biological characteristics of cultured species and the physical features of location, different systems and  technologies  are  required  for  each  cultured  species  within  various  environments, extending  from  freshwater,  brackish  water  to  seawater,  even  flooded  fields  and  rice paddies. Cultured species can be retained in a variety of facilities, such as ponds, pens, tanks,  raceways,  rafts  and  cages.  Additionally,  aquaculture  practice  can  be  operated  at different  scales  depending  on  the  levels  of  inputs  used  and  outputs  produced.  Hence, aquaculture is often broken down into small-, medium- and large-scale operations (Barg and Phillips 1997).   It is estimated that aquaculture production has increased by an annual average growth rate of  8.8%  since  1970,  and  it  currently  contributes  one-third  of  the  world?s  total  seafood supply (FAO 2007). In 2005, about 91% of world aquaculture production came from Asia and the Pacific region, with China contributing 70% of the total production (FAO 2007). Even though there are concerns with the accuracy of Chinese figures, undoubtedly China is the biggest contributor to world aquaculture production. A major portion of the world?s production  comes  from  freshwater  fish  species  (i.e.,  cyprinids),  seaweed  and  mollusks (e.g.,  oyster  and  mussel).  Capital-intensive  and  profit-driven  aquaculture  practices  have been  rapidly  growing,  but,  aquaculture  is  still  dominated  by  small-scale  producers  in developing  countries  (Garcia  and  Grainger  2005;  FAO  2007).  FAO  predicts  that   5  aquaculture  will continue its rapid expansion in order to meet  growing seafood demand around the world (FAO 2007).   Aquaculture is well known for providing cheap protein sources and alleviating poverty in remote  and  poor  rural  coastal  communities  around  the  world.  Aquaculture  also  creates employment and income opportunities as well as foreign earnings. Since capture fisheries have reached their upper ceiling (e.g., Watson and Pauly 2001), aquaculture has been seen by many to have a strong potential to bridge the gap between the dwindling supply from capture fisheries and increasing seafood demand (e.g., Tidwell and Alan 2001; Garcia and Grainger 2005; FAO 2007).   Despite the fact that aquaculture provides many benefits to the producers and society as a whole, some forms of aquaculture are under scrutiny and criticism because they generate negative economic and environmental impacts on the environment  and natural resources. These  impacts  vary  considerably  in  terms  of  species  cultured,  production  system  used, scale of operation, severity and magnitude of problems within aquaculture itself and other resource users. Among all the aquaculture practices, intensive aquaculture of carnivorous species  (e.g.,  salmon  and  shrimp)  is  the  most  controversial  practice  because  it  can potentially create severe environmental problems.   1.2.2 Overview of Salmon Aquaculture Salmon aquaculture first started as a way to enhance and  restore declining wild salmon stocks  in  Japan,  Canada  and  the  US  (Thorpe  1980).  In  the  late  1960s  and  early  1970s, aquaculturists in Norway and Scotland started growing salmon in open floating cages close to  seashores  for  delivering  fresh  salmon  to  the  local  markets  (Willoughby  1999). Breakthroughs  with  respect  to  biological  and  technological  bottlenecks,  such  as  smolt rearing and formulation of dry feed, have dramatically advanced salmon aquaculture. The technology for commercial-scale salmon aquaculture was first successfully established in Norway and Scotland. This technology was introduced to Canada in the late 1970s and to Chile  in  the  1980s.  Since  then,  salmon  aquaculture  has  experienced  exponential  growth   6  worldwide, and farmed salmon production has increased from around 500 tonnes in 1970 to  over  1.3  million  tonnes  in  2005,  according  to  FAO  statistics  (FISHSTAT).  World farmed salmon production has exceeded wild salmon production since 1998 (FAO 2007).   Farmed salmon production is concentrated in a few regions and countries, namely, Norway, Chile,  the  UK  and  Canada.  In  total,  these  countries  are  the  source  of  over  85%  of  the world?s total production and value of farmed salmon. Norway is the number one producer, followed by Chile, the UK and Canada. The most remarkable increase has taken place in Chile. It is believed that Chile will soon replace Norway as the number one farmed salmon producer in the world if it continues to develop at the current rate. Farmed salmon species include  Atlantic,  chum,  chinook,  coho  and  sockeye  salmon.  Atlantic  salmon  is  the dominant  species  with  over  95%  of  the  total  world  farmed  salmon  production.  Atlantic salmon is native to the Atlantic Ocean and chum, chinook, coho and sockeye are native to the Pacific Ocean. However, Atlantic salmon has been introduced into the Pacific Ocean due  to  its  strong  resistance  to  environmental  conditions  and  its  fast  growth.  Figure  1.1 shows farmed salmon production by major salmon farming regions and species.       7  0.00.20.40.60.81.01.21.41984 1987 1990 1993 1996 1999 2002 2005YearProduction (million tonnes)NorwayChileUK+IrelandOthersCanada  0.00.20.40.60.81.01.21.41984 1987 1990 1993 1996 1999 2002 2005YearProduction (million tonnes)AtlanticCohoChinook Figure 1.1. Farmed salmon production by major producing country and species.  Salmon  aquaculture  has  experienced  remarkable  growth  as  a  result  of  expanding  new cultured locations, improved productivity, enhanced husbandry practices and management, and growing global markets (Bj?rndal et al. 2002 & 2003; Asche and Khatun 2006). In the meantime,  salmon  aquaculture  has  undergone  a  number  of  structural  and  technical changes, and it has expanded, intensified and diversified. Salmon aquaculture was initially devised  for  improving  the  livelihoods  of  the  coastal  communities  that  depended  upon salmon by increasing employment and income. In the beginning, salmon farms were small family businesses with the farms scattered along the sheltered inlets, and products targeted local markets (Willoughby 1999; Hjelt 2000). Today, salmon aquaculture has become  a vertically-integrated industry with the farms concentrated in the coastal areas, and products   8  are mainly exported; it has become a market and a profit-driven enterprise (Bj?rndal et. al. 2003;  Asche  and  Khatum  2006).  It  is  estimated  that  70%  ~  80%  of  farmed  salmon production is delivered by a dozen multinational companies (Naylor et al. 2003).   1.2.3 Salmon Aquaculture and its Effects There are two types of effects associated with salmon aquaculture: i) environmental effects, and ii) market effects, both of which are described below.  1.2.3.1 Salmon Aquaculture and Environmental Effects  Potential  negative  environmental  problems  associated  with  salmon  aquaculture  mainly include: 1) disease and parasite transfer and spreading, 2) escapees, 3) waste discharges, 4) introduction  of  exotic  species  (e.g.,  Atlantic  salmon  into  the  Pacific  Ocean),  5)  uses  of chemicals  and  drugs,  and  6)  consumption  of  fishmeal  and  fish  oil.  The  resources  and activities that can be potentially affected by these problems include wild salmon and other wild fish stocks, marine mammals, recreational activities, upland properties, archaeological resources  and  navigation  (Table  1.1).  These  environmental  problems  and  their  impacts have been widely acknowledged in a number of articles in the literature (e.g., Naylor et al. 2000  &  2003;  Kautsky  et  al.  2001;  Pauly  et  al.  2002;  Morton  et  al.  2004;  Morton  and Routledge 2005; Krko?ek et al. 2005 & 2006; Naylor and Burke 2005), and detailed in Table 1.1.           9  Table 1.1.Problems and negative impacts associated with salmon aquaculture  Problem  Potential effects  Affected resources (major) Disease and parasites  Transfer of diseases and parasites.   Wild fish and shellfish fisheries; First Nations?ubsistence fisheries.  Escapees    Inter-breeding with wild salmon; Competition for food and space;  Transferring diseases and parasites.  Wild salmon; Pelagic fish fisheries; Other marine resources.  Waste discharges   Environment; Habitat destruction.  Shellfish and benthic communities; Biodiversity.  Use of chemicals and drugs  Environment; Risks to human health.  Bottom fish and shellfish fisheries; Human health.   Use of fishmeal and fish oil Pressure on wild pelagic fisheries; Net loss. Wild pelagic fisheries.  Introduction of exotic species   Inter-breeding with wild salmon; Competition for food and space;  Transferring diseases and parasites.  Wild salmon populations and fisheries.   Attracted to aquaculture sites Killing.  Marine mammals, birds.    Fish Feed Problems Salmon is a carnivorous fish species, which requires high-protein feed to grow. Fishmeal and fish oil are primary animal protein sources in fish feed. Fishmeal and fish oil are made of small, bony and oily pelagic wild-caught fish as well as byproducts from fish processing plants,  and  bycatch  from  trawl  fisheries  (New  and  Wijkstr?m  2002).  These  pelagic fisheries are generally not suitable for human consumption or not economically viable to be processed for human food (Hardy and Tacon 2002; Tacon et al. 2006). It is estimated that  producing  1  kg  of  salmon  requires  2.8  ?  4.2  kg  of  wild  capture  fish  as  source  of protein (Tuominen and Esmark 2003). Hence, some argue that salmon aquaculture is not a net contributor to seafood supply because it consumes a great amount of marine capture fishery resources as inputs (Naylor et al. 2000; Delgado et al. 2003).   About one-third of total landed wild capture fish is destined for reduction fisheries as feed sources  for  aquaculture,  poultry  and  other  farmed  animals  (FAO  2007).  The  world   10  fishmeal and fish oil production have remained relatively stable, with 6 ~ 7 million tonnes of fishmeal and slightly over 1 million tonnes of fish oil (Tacon et al. 2006). Currently, about  50%  of  global  fishmeal  and  80%  of  global  fish  oil  production  are  consumed  by aquaculture, and the rest are consumed by poultry and other farmed land animals (Tacon et al. 2006). However, the demand for fishmeal and fish oil by the aquaculture sector will continue to increase if the intensive culture of carnivorous species continues to expand. Chile is a good example of this development. The country used to be the second biggest producing and exporting country of fishmeal and fish oil in the world. Today, Chile is a big consumer and importer of fishmeal and fish oil because of the remarkable growth of salmon  aquaculture  in  the  country.  Increasing  demand  for  fishmeal  and  fish  oil  for aquaculture  has  the  potential  to  create  pressure  on  marine  capture  fisheries  (Folke  and Kautsky 1992; Pauly et al. 2002; Garcia and Grainger 2005). The availability and cost of feed may serve as critical constraints to aquaculture expansion in the near future (Garcia and Grainger 2005).  There  are  a  few  studies  dealing  with  the  interaction  between  aquaculture  and  capture fisheries  in  relation  to  fishmeal  and  fish  oil  issues  (e.g.,  Hannesson  2003;  Asche  and Tveret?s 2004). Asche and Tveret?s (2004) pointed out that aquaculture would not pose a threat to wild fisheries if a sufficient management regime was to be set up, and substitutes for  fishmeal  developed.  Hannesson  (2003)  concluded  that  aquaculture  could  drive  these pelagic fish stocks to overexploitation if the management regimes are not efficient. Hence, the growing aquaculture sector poses a potential threat to wild reduction fisheries if these fisheries are poorly managed and regulated.  Escaped Fish Farmed  salmon  can  escape  from  netcages  due  to  storms,  marine  mammal  attacks,  and human error. There are three biological and ecological concerns associated with escaped farmed salmon. First, they may establish in the wild, and compete with wild salmon for food,  habitat  and  spawning  grounds  (Carr  et  al.  1997;  Volpe  et  al.  2001).  This  may potentially disturb already-stressed wild stocks. Second, escaped fish may spread diseases   11  and parasites, such as sea lice, to the wild stocks (Naylor et al. 2000 & 2003). This poses another potential risk to wild fish stocks, especially wild salmon stocks. A third concern is that escaped fish may hybridize with wild salmonids, which may deteriorate wild salmon genetic gene pools (e.g., Youngson and Verspoor 1998; McGinnity et al. 2003). Atlantic salmon has been introduced to the Pacific due to its high growth rate and strong resistance to the environmental conditions. This introduction may intensify potential environmental risks to the indigenous species, such as sockeye, chinook, chum and coho salmon (Sumaila et al. 2005).   Pollution Pollution  from  salmon  aquaculture  arises  from  uneaten  feed,  fish  faeces,  dead  fish, chemical residuals and fouling compounds. These wastes are usually discharged directly into the surrounding environment without treatment. The waste discharges are disposed of in solid and soluble forms into the marine environment. These solid and soluble wastes result in three types of pollutants in the marine environment, i.e., those containing organic matter,  nutrients  and  chemotherapeutic  contaminants  (Haya  et  al.  2001;  Brooks  and Mahnken 2003). The levels and composition of wastes vary, depending on a number of factors,  such  as  feed  composition,  fish  density,  health  of  fish,  feeding  strategy,  feeding method and feed conversion ratios (Ackefors and White 2002; Brooks and Mahnken 2003).   Solute  wastes  dissolve  into  the  water  body  as  phosphorus  and  nitrogen,  which  become inputs for marine plants. Small or modest additions of nutrients in nutrient-poor areas can increase biodiversity and productivity. However, a long-term accumulation of nutrients can cause eutrophication in low flushed areas or nutrient rich areas (Folke et al. 1994 & 1997). Eutrophication may result in harmful algae bloom and severe reductions in water quality. Fish  can  be  poisoned  and  killed  (Black  et  al.  1997;  Troell  et  al.  1997).  Hence,  the ecological  impacts  of  nutrients  can  be  measured  by  the  changes  in  water  quality, phytoplankton  production,  and  the  losses  of  fish  and  shellfish  stocks  (Milewski  2001; Pillay 1992).    12  The organic or solid wastes can be dispersed without reaching high concentrations in areas with strong currents or tides. However, they can sink and may pile up on the seabed when they  cannot  be  disseminated  by  the  environment  (Carroll  et  al.  2003).  The  build-up  of organic wastes in the seabed sediment can create dead zones, which can result in negative biological and chemical structured changes (Janowicz and Ross 2001). The abundance of benthic organisms and communities may decline with increasing organic load (Brooks and Mahnken 2003; Brooks 2001). Further, the contaminated sediments may pose a potential risk to habitats or spawning grounds of traditional fish and invertebrate, such as herring, lobster, sea urchin and clam fisheries (Janowicz and Ross 2001; Pohle et al. 2001; Wildish et al. 2001). And they may result in reductions in productivity of fish and invertebrates (SAR 1997). For instance, in the Broughton Archipelago, British Columbia, some shellfish fishers complain that their clam beds have become black and smelly because of salmon farms nearby.    Another  concern  is  chemotherapeutic  pollution.  Salmon  farmers  use  chemicals  and medicines to treat and prevent disease and parasites. These drugs and chemicals include antibiotics, pesticides, disinfectants, fungicides, ivermectin, and anaesthetics (Davies and Rodger 2000; Haya et al. 2001; Zitko 2001; Burridge 2003). Some drugs and chemicals are  discharged  into  the  environment  with  the  wastes  (Davies  and  Rodger  2000).  The accumulated residuals of chemicals and drugs in the sediments may have toxic effects on the benthic organisms (Haya et al. 2001; Davies et al. 2001). Some studies demonstrated that  toxicity  may  reduce  the  biomass  of  bacteria  and  alter  species  composition  and abundances of microbial communities (Collier and Pinn 1998; Davies et al. 1998; Haya et al. 2001). Most research on these issues has been conducted in laboratories and focuses on targeted species such as shrimp and lobster (Burridge 2003). For instance, ivermectin used in the treatment of sea lice infections has been shown to be lethal to shrimp and lobster in laboratory experiments (Haya et al. 2001). Farmed salmon and some organisms or bacteria can  gradually develop antibiotic resistance if they  are treated or ?bathed? with the same drugs for long periods. This can lead to increased uses of some drugs and chemicals with the attendant problems.      13  Disease and Parasite Problems Disease is a primary threat to the continued growth in salmon aquaculture because it can cause major economic losses to the sector (Asche et al. 1999; Hjelt 2000; Arthur et al. 2002). Salmon are usually raised in highly-dense netcage systems, leading to high stress levels,  which  is  uncommon  in  their  natural  environment.  This  makes  farmed  fish  more vulnerable to diseases and parasites. If one fish gets a contagious disease in a farm, the disease may be transferred or spread to the whole farm, even to neighbouring farms if they are  close  enough  to  each  other.  Diseases  and  parasites,  such  as  furunculosis,  bacterial kidney  disease,  infectious  hematopoietic  necrosis  virus  and  sea  lice,  have  progressively evolved along with the expansion of salmon aquaculture (Hjelt 2000).   The economic impacts of disease can be substantial. The direct and immediate economic impacts  of  disease  are  suffered  by  aquaculture  farms  themselves  (Mustafa  et  al.  2001; Subasinghe et al. 2001; Menzies et al. 2002). The effects of disease on aquaculture can be measured  through  reduction  in  growth,  low  market  prices,  and  increasing  mortality  rate (McVicar 1997 & 2004; Mustafa et al. 2001; Tully and Nolan 2002). If a disease causes severe reduction in output, the dynamics of supply and demand may change, resulting in high  demand  relative  to  supply,  and,  therefore,  high  market  price  will  emerge.  It  may, however, also cause lower market prices if people get concerned about seafood safety and human health, which may lead to declining demand (Israngkura and Sae-Hae 2002). The net effect of disease on demand and price will depend on which of these two factors is greater.   Besides  the  impacts  on  aquaculture  itself,  disease  can  also  impose  impacts  on  wild fisheries.  Most  diseases  are  infective  and  epidemic,  thus,  they  can  be  spread  and transferred to the environment and other biotic resources. For instance, sea lice problems from  salmon  farms  have  been  at  the  centre  of  the  debate  over  declining  wild  salmon fisheries  (e.g.,  Krko?ek  et  al.  2005  &  2006;  Brooks  and  Stucchi  2006).  Sea  lice  are common  parasites  for  both  farmed  and  wild  salmon,  but  a  high  level  of  sea  lice  from salmon farms may amplify pathogen concentrations within the farm and increase infection   14  risk to proximate wild salmon populations through escaped fish and the water. A number of studies have demonstrated that such high concentrations of sea lice have contributed to the  decline  of  some  wild  salmonid  stocks  in  different  jurisdictions,  such  as  in  Norway (Finstad et al. 2000; Bjorn and Finstad 2002), Scotland (Gargan et al. 2002) and the west coast of Canada (Morton et al. 2004; Krko?ek et al. 2005 & 2006).   Another concern regarding disease and parasite problems is the use of chemicals and drugs. The  residuals  of  some  drugs  and  chemicals  in  the  fish  body  may  pose  a  health  risk  to humans.  For  instance,  Hites  et  al.  (2004)  in  their  controversial  study  indicated  that  the concentration of organic contaminants (PCBs) was significantly higher in farmed salmon than in the wild. Nevertheless, the development of vaccines has greatly reduced the use of antibiotics (Asche et al. 1999; Bj?rndal et al. 2002; Tveret?s 2002), and hence reduced the potential risks from this source.  Tremendous efforts have been put into reducing disease problems both in terms of research and  funding.  However,  some  impacts  may  be  catastrophic.  For  instance,  Gyrodactylus salaries, a freshwater parasite in salmonids, has spread to 41 rivers and 36 hatcheries in Norway since it was first introduced in 1975 from Sweden through transportation (Johnsen and Jensen 1992; Johnsen 2006). The only way to eradicate this parasite once it strikes is to kill all the fish in the infected rivers and hatcheries by treating with rotenone (a pesticide) treatment. After treatment, the rivers and hatcheries may not be used for  years, and the wild salmon stocks in such contaminated rivers may go extinct (Johnsen 2006). In addition, parasite  treatment  using  rotenone  is  not  always  successful.  Therefore,  a  new  attempt  is being  made  in  one  Norwegian  river,  where  acid  aluminium  is  being  used.  One  such treatment  would  cost  around  NOK  1.2  million 1 .  For  the  larger  rivers,  there  is  no appropriate way to treat the parasite because the water body is so large and the whole river system is so complicated. Since its beginning, approximately NOK 250 million has been used  for  the  treatment  program  (NASCO  2006).  So  far,  due  to  disease  and  escapement                                                  1  NOKCAD 5.51 ?    15  problems among 453 wild salmon populations, 50 of them have already become extinct and another 135 are threatened or vulnerable, while the rest remain healthy (Porter 2005).   1.2.3.2 Salmon Aquaculture and Economical Effects  In addition to environmental problems, salmon aquaculture also creates potential market effects  through  declining  prices  of  both  farmed  and  wild  salmon  sectors.  Salmon aquaculture provides to the market products that are similar to the wild counterpart; thus, market  competition  intensifies  with  increasing  supplies  from  salmon  aquaculture.  This results in declines in profits for wild salmon fisheries (Naylor et al. 2003; Knapp 2005; Knapp et al. 2007). Alaska is affected the most because it lands the largest wild salmon catch  in  the  world.  Salmon  aquaculture  is  banned  in  Alaska.  Currently,  total  ex-vessel values of the Alaskan wild salmon fisheries are just one quarter of what they used to be only a decade ago. In this case, the price of salmon fishing permits has fallen by 75 ? 90% (Naylor et al. 2003; Knapp et al. 2007). Fishers who bought their fishing boats and permits during the high-price years of the late 1980s and early 1990s can no longer afford to stay in the fisheries and pay off their debts (Naylor et al. 2003). The BC wild salmon fisheries have  also  been  hard  hit  by  the  salmon  aquaculture  industry,  but  the  overall  economic impacts  are  not  as  great  as  in  Alaska  since  the  BC  wild  salmon  fisheries  are  relatively smaller.  Since the late 1980s, the prices of both farmed and wild salmon have declined. Fresh wild salmon  products  are  only  available  for  a  specific  period  of  the  year  during  the  fishing season. Salmon aquaculture, on the other hand can supply stable and predictable volumes of salmon products with consistent quality year-round. On average, farmed salmon achieve a  higher  market  price  than  wild  salmon  (Figure  1.2).  However,  wild  salmon  may  have some  market  advantages  over  farmed  salmon  simply  because  it  is  ?wild?.  Hence,  some consumers  may  be  willing  to  pay  a  higher  price  for  wild  salmon  products,  making  it command  a  price  premium.  Figure  1.2  shows  the  nominal  prices  of  farmed  and  wild salmon in BC and USA. It should be noted that the reported prices for farmed salmon are   16  those for Atlantic salmon, while wild salmon prices in USA and Canada are the average prices of all wild salmon species except pink salmon.  British Columbia, Canada-1.02.03.04.05.06.07.01986 1989 1992 1995 1998 2001 2004YearSalmon price (CAD$/kg)Wild Farmed  United States of America0.02.04.06.08.010.012.01984 1987 1990 1993 1996 1999 2002 2005YearSalmon price (US$/kg) WildFarmed Figure 1.2. Nominal prices of farmed and wild salmon in British Columbia and the United States.    The salmon aquaculture industry has also suffered profit losses from declining prices.  For instance, based on the Norwegian salmon aquaculture data, the profit margin has declined gradually, with dramatic declines in 2002 and 2003. Some salmon farms even made zero profits.  Salmon  farms,  especially  small  farms,  that  incur  high  production  costs  may  not stay in business. This has led to a reduction in Norwegian production of farmed salmon in recent years.    17  In addition, fishmeal and fish oil used by salmon aquaculture are primarily derived from pelagic fishes, such as anchovies, sardines, mackerel, herring. These fishes are low-value species,  and  in  general  not  economically  profitable  to  process  for  human  consumption. However,  these  fish  may  be  important  protein  sources  for  some  people  in  developing countries.  For  instance,  some  of  these  species  are  considered  as  food  fish  to  provide protein sources in the Philippines, Indonesia and China. Hence, the use of pelagic fishes for fishmeal and fish oil may create potential food security issues (Pauly et al. 2005).   In  sum,  salmon  aquaculture  does  produce  environmental  and  economic  impacts  on  the surrounding environment and natural resources. Some negative impacts are local in scope, for example, organic pollution, habitat destruction and loss of biodiversity; some may be regional, for instance, disease transfers and degradation of wild stocks via escapees; a few are  even  global,  such  as  the  use  of  fishmeal  and  fish  oil  and  declining  prices  of  wild salmon  fisheries  products  through  international  trade.  These  effects  have  made  salmon aquaculture  one  of  the  most  controversial  aquaculture  industries  in  the  world.  In  this dissertation,  I  focus  on  environmental  and  economic  effects  associated  with  salmon aquaculture with an emphasis on pollution and disease and parasite problems.    1.2.4 Salmon Aquaculture Practice in Leading Producing Countries or Regions 1.2.4.1 British Columbia, Canada   Canada is the fourth-largest salmon farming country in the world after Norway, Chile and the UK, with BC contributing two-thirds of total Canadian production. Salmon aquaculture began in BC in the early 1970s along the Sunshine Coast, as family-run small businesses concentrating on native salmon species, such as chinook and coho (Volpe 2001). In order to boost the economy of coastal communities from the declining fishing and forest sectors, Atlantic salmon was introduced to BC waters in the early 1980s. BC has the advantage of exporting its farmed salmon to the US, with cheap transportation cost and short transport time.  The  US,  as  one  of  the  biggest  international  markets  for  farmed  salmon,  has   18  experienced  increasing  demand  for  farmed  salmon  products  over  the  years.  As  a  result, salmon  aquaculture  in  BC  has  boomed.  Like  producers  in  other  jurisdictions,  salmon aquaculture in BC has moved from localized small businesses to multinational enterprises. For instance, around 100 small businesses two decades ago were replaced by half a dozen large  multinational  and  corporate  producers  in  recent  years  (Cox  2004).  These multinational operations are also vertically integrated, i.e., they engage in hatchery, grow-out, processing, and marketing of salmon.   Over the  years, farmed  salmon production  and farmgate values increased exponentially. Today,  salmon  aquaculture  has  become  a  vital  part  of  the  local  economy,  and  farmed salmon production accounts for 15% of total BC agricultural production in terms of weight (MAFF 2004). While creating employment and income for local communities, the industry is  becoming  the  biggest  agricultural  food  exporter,  earning  millions  of  valuable  export dollars (MAFF 2004). Currently, there are 23 companies who own 131 tenures occupying 2,400  hectares.  Most  of  BC  farm  sites  are  concentrated  in  three  areas:  the  Broughton Archipelago, Johnstone Strait and Clayoquot, and Barkley Sounds. Around 80% of tenures are actually active (MAFF 2004).  The dramatic  expansion has led to public concerns and debates over environmental and economic  impacts  brought  about  by  salmon  aquaculture.  For  instance,  wild  and  farmed salmon have experienced changes over time. Figure 2.3 shows the quantity and value of farmed and wild salmon in BC from 1986 to 2005. Wild salmon production and landed value have declined while farmed salmon production and farmgate value have increased over  time.  The  decline  in  wild  salmon  production  and  value  may  be  at  least  partially attributed to the rise of salmon aquaculture due to falling prices and environmental impacts (e.g., disease and parasite).   19  0204060801001201986 1989 1992 1995 1998 2001 2004YearSalmon production (?000t)wild salmon farmed salmon -501001502002503003501986 1989 1992 1995 1998 2001 2004YearNominal values (million CAD$)wild salmon farmed salmon Figure 1.3. Production and value of farmed and wild salmon in BC.  In response to these debates, the BC Provincial Government placed a moratorium on new salmon farm tenures in 1995, and the Salmon Aquaculture Review (SAR) was constituted to  examine  aquaculture  practices,  and  to  investigate  environmental  problems  associated with  salmon  aquaculture.  In  1997,  SAR  was  completed,  and  49  recommendations  were made. SAR concluded that ?salmon farming in British Columbia, as presently practiced and  at  current  production  levels,  presents  a  low  overall  risk  to  the  environment?  (SAR 1997). In the following five years, a number of environmental monitoring programs were implemented.  In  2002,  the  moratorium  was  lifted,  and  new  tenures  have  since  been approved and issued.     20  1.2.4.2 Norway  Norway  is  the  world  leader  in  salmon  aquaculture.  It  is  also  a  pioneer  in  technological innovation and development of new markets for farmed salmon products (Aarset 1998). It has  been  the  number  one  salmon  producer  in  the  world  since  the  beginning  of  salmon development. Salmon aquaculture in Norway started as a government-supported activity to rebuild  the  livelihoods  of  rural  fishing  communities  facing  depressed  economies  due  to declining  wild  fisheries  (Hjelt  2000;  S?nvisen  2003).  Hence,  most  farms  are  located  in rural areas and small municipalities. The major markets for Norwegian farmed salmon are the EU, the US and Japan.  0.00.40.81.21.62.01980 1983 1986 1989 1992 1995 1998 2001 2004Year-100200300400500600Wild salmon production (?000t)Farmed salmon production (?000t)Farmed Figure 1.4. Farmed and wild salmon production in Norway.   Today, salmon aquaculture has become an important industry in Norway. It has not only generated employment for coastal communities, but it has also generated foreign income for  the  country.  Farmed  salmon  production  has  increased  exponentially  since  the  early 1980s (Fig. 1.4). Recently, slumping market prices have led to declines in the growth rate of salmon production.  In contrast, wild salmon production is small compared to farmed salmon. It accounts for less than 1% of the total farmed salmon production, according to Norway Statistics (2006). Wild salmon fisheries include sea and river fishing. They are not a large commercial fishing industry, but mostly consist of recreational activities.       21  Salmon  aquaculture  in  Norway  is  a  highly-capitalized,  highly  technological  and  less labour-intensive  practice  than  in  other  countries,  because  labour  in  Norway  is  very expensive.  The  productivity  has  improved  over  time.  Production  cost  per  tonne  has declined over time (Fig. 1.5), while total production costs have increased. However, the declines in feed, smolt and labour costs have slowed down in recent years.  0369121518211985 1988 1991 1994 1997 2000 2003-100200300400500600SmoltLaborFeed ProductionProduction (?000t)Production costs (NOK/kg) Figure 1.5. Production and production costs of Norwegian farmed salmon.                                                                                                                                                                                                                                                                                                                                                               In Norway, pollution, genetic impact, biodiversity and disease are the main problems faced by  the  salmon  aquaculture  industry  and  society  at  large  (Hjelt  2000).  With  the environmental  problems  associated  with  salmon  aquaculture  increasing  over  time,  the policy  for  salmon  aquaculture  has  shifted  from  developing  regional  economies  and expanding farmed salmon production to environmental protection from disease and other environmental  problems  (S?nvisen  2003).  Norway  has  relatively  strict  regulations  and policies on salmon aquaculture, such as limited entry, constraints in farm sizes and fish density,  feed  quota,  and  control  on  location  and  ownership  (Bj?rndal  1990  &  2002; S?nvisen  2003).  In  fact,  these  regulations  have  created  economic  incentives  for  salmon producers  to  internalize  some  of  the  external  costs  of  aquaculture  into  their  production decision-making (Asche et al. 1999; Bj?rndal et al. 2002; Tveret?s 2002). However, due to limited  availability  of  suitable  space  and  stringent  aquaculture  policy,  Norwegian producers have moved their investments to countries such as Canada, the US and Chile.       22  1.2.4.3 Chile  Chile  is  the  world?s  fastest-growing  salmon  aquaculture  producer.  Its  production  is growing  at  an  exponential  rate.  The  salmon  aquaculture  sector  is  Chile?s  fourth-largest exporter. Most of Chile?s production is exported to Japan and the US, while small amounts go to Latin American and EU markets (Bj?rndal and Aarland 1999; Bj?rndal 2002). It is believed  that  Chile  will  soon  become  the  world?s  largest  farmed  salmon  producer  and exporter if it continues expanding at its current rate. Besides being endowed with a long coast  line  and  good  environmental  conditions,  Chile  also  has  the  advantage  of  having abundant cheap labour. In addition, it is the world?s second-biggest fishmeal and fish oil producer  after  Peru.  Hence,  it  has  reliable  and  cheap  feed  available.  Chile  uses  more labour-intensive  production  technology  and  has  the  lowest  production  costs  among salmon-producing countries (Barton 1997; Bj?rndal & Aarland 1999; Bj?rndal 2002).   Most of Chilean salmon aquaculture production is concentrated on the Puerto Montt region, southern Chile (i.e., Region X), which is currently operating almost at full capacity. Thus, further expansion can only occur in the Los Lagos region, further south (i.e., Regions XI and XII) (Buschmann et al. 2006). However, the infrastructure in these regions is so poor that it may become the limiting factor for further expansion (Bj?rndal 2002). In addition, Chilean salmon aquaculture still depends, to a great degree, on imported eggs; hence, egg supply  could  be  another  obstacle  for  further  expansion  (Bj?rndal  2002).  Salmon  is  not native  to  Chilean  waters,  so  there  is  no  ecological  competition  and  genetic  interaction between  wild  and  farmed  salmon.  However,  escapes  and  pollution  problems  still  exist, which  can  affect  other  species  and  resource  users  in  the  surrounding  environment (Buschmann  et  al.  2006).  In  Chile,  low  wages  and  workplace  safety  problems  are  the biggest challenges (Barrett et al. 2002). Chile is also reported to have fewer environmental regulations  and  enforcement  capacities  compared  to  Norway,  the  UK  and  Canada (Bj?rndal 2002).     23  1.2.4.4 The UK  Salmon  aquaculture  in  the  UK  is  concentrated  in  Scotland.  Commercial  salmon aquaculture  in  Scotland  started  in  the  1960s.  It  has  similar  development  trends  as  in Norway. The major market for farmed salmon in the UK is the EU countries. Due to a limited coastline, suitable sites for salmon farms are almost fully occupied (Porter 2005). Increases in farmed Atlantic salmon production have correlated with marked declines in wild  salmon  and  sea  trout  populations  (Fig.  1.6).  However,  wild  salmon  and  sea  trout production  are  currently  insignificant  compared  to  farmed  salmon.  They  are  mostly exploited by recreational fishers. The most controversial issue in Scotland is the negative impacts of sea lice from salmon farms on wild sea trout stocks. It is widely argued that the high level of infestation of sea lice and escapees associated with salmon aquaculture have contributed to the decline of wild salmon and sea trout populations in Scotland (Gargan et al. 2002).   0.00.20.40.60.81.01.21.41.61.81984 1987 1990 1993 1996 1999 2002 2005Year-20406080100120140160180Sea troutWildFarmedWild production (?000t)Farmed salmon production (?000t) Figure 1.6. Wild and farmed salmon and wild sea trout production in the UK.       Overall,  these  different  salmon-producing  countries  have  a  lot  in  common.  All  of  their production has increased exponentially over the last two decades. These producers use the same production technology, and compete in the same global market. In addition, they face similar  challenges  and  problems,  such  as  high  production  costs,  low  market  prices  and   24  controversies  over  environmental  problems.  However,  they  have  different  institutional structures,  practices  and  management  strategies.  Salmon  aquaculture  growth  has  slowed down in Norway, Scotland and BC, as a result of environmental concerns and low market prices,  while  its  growth  has  continued  to  increase  in  Chile.  Further,  the  rigorous regulations in Norway have pushed salmon aquaculture producers out of Norway to places where there is less regulation and more potential for profit-making, such as, Chile, which offers  low  labour  costs  and  has  good  feed  sources,  less  regulation,  good  environmental conditions and governmental support.    Salmon aquaculture producers have faced different environmental problems. Disease and escapement  problems  are  more  serious  and  controversial  in  Norway,  the  UK  and  BC, because they are commonly believed to be the cause of declines of wild salmonids stocks. On  the  other  hand,  the  focus  of  arguments  in  Chile  is  on  contamination  of  the  marine environment, low wages and unsafe working conditions in the sector. Even though disease and escapement problems have also taken place in Chile, they are not as controversial as in Scotland and BC, because Chile does not have wild salmon fisheries.    1.2.5 Economics of Environmental Problems  While  the  environmental  impacts  associated  with  salmon  aquaculture  have  been  widely acknowledged, economic analysis is needed to  foster  a sustainable aquaculture practice. Economics,  in  particular  environmental  economics,  has  emerged  as  a  policy-supporting tool to quantify the environmental impacts associated with aquaculture (e.g., Folke et al. 1994; Barbier 2000; Sathirathai and Barbier 2001; Barbier 2003). In the literature, a small number  of  studies  have  addressed  environmental  problems  associated  with  shrimp aquaculture (e.g., Babier 2000; Sathirathai and Barbier 2001; Barbier 2003). In the case of salmon  aquaculture,  there  are  huge  gaps  between  environmental  impacts  and  their associated economic consequences.     25  1.2.5.1 Externality   When an action or economic activity of a party or an agent impacts on people other than themselves, and the impact is not taken into account by the party causing it, an externality is said to exist. In other words, externalities are effects of an action or economic activity that are borne by a third party, not by the agent undertaking that action or activity (Field and Olewiler 2002). Furthermore, these effects are not reflected in the prices of products or services. Externalities can be positive or negative. If externalities are negative, the third party  (e.g.,  an  individual  or  firm)  has  to  bear  costs,  known  as  external  costs,  while  if externalities  are  positive,  the  third  party  enjoys  external  benefits.  Externalities  are categorized  in  a  number  of  ways:  producer-on-producer  externalities,  producer-on-consumer  externality,  consumer-on-consumer  externality  and  consumer-on-producer externality (Field and Olewiler 2002).   In an economically-efficient operation, marginal costs should equal marginal benefits, then the level of output and market prices of inputs and outputs are said to be socially optimal, and net social benefits are maximized. All the costs and benefits should be included. When external costs or benefits exist, the private calculation of costs and benefits differs from society?s valuation. Thus, private optimal actions are inefficient from the perspective of the society,  and  net  social  benefits  will  not  be  maximized.  This  results  in  market  failure because market prices and levels of output are not socially optimal, as they do not reflect external  costs  and  benefits.  Hereafter,  I  will  focus  on  producer-on-producer  externality, which means I will emphasize external costs.  One  can  describe  external  costs  using  demand  and  supply  curves.  The  demand  curve expresses the marginal willingness to pay (WTP) for a product by consumers, while the supply curve represents the marginal cost of supplying a given product to the market. Thus, the  demand  curve  captures  the  marginal  benefits,  and  the  supply  curve  captures  the marginal costs from an activity. Without externalities, the private benefits and costs should theoretically equal the social benefits and costs at the margin. If external costs exist, the total social costs  are equal to the private  costs  plus external costs.  I  describe them in a graph. In Figure 1.7, the marginal benefits, marginal private cost, and marginal social cost   26  curves are denoted as DD, MPC and MSC, respectively. The intersection points A and A* give the market equilibrium  where the quantity produced and consumed is efficient at the market price, and hence,  net social benefits are maximized ( Field and Olewiler 2002).         Figure 1.7. External costs and market effects.   In  Figure  1.7,  at  point  A,  without  incorporating  external  costs,  the  producer  maximizes profits  by  producing  the  quantity  (Qp)  at  the  price  Pp.  The  quantity  (Qp)  is  the  socially optimal level, and price (Pp) reflects real costs of production. The private marginal benefit and cost are the same as social marginal benefit and cost. At point A*, when external costs are  present,  the  private  marginal  cost  curve  (MPC)  shifts  upward  to  become  the  social marginal cost curve (MSC). The social cost equals the sum of private cost and external cost. The market equilibrium is shifted from A to A*. In the new market equilibrium, the socially  optimal  quantity  (Qs)  is  produced  at  the  price  (Ps).  The  socially  optimal  output level (Qs) is lower than the private equilibrium output level (Qp), while the socially optimal price (Ps) is higher than the private equilibrium price (Pp) because society has to bear the external  costs,  which  private  producers  do  not  take  into  account  without  government intervention. In other words, the price (Pp) for a private producer does not reflect the real costs of production, and market failure occurs. If an economic incentive is implemented (such as an emission tax or effluent discharge fee), the private producer will internalize the external cost in his decision making, and the social optimum ought to be achieved at the market  price  (Ps).  However,  in  most  cases,  producers  do  not  take  into  account  these external  costs  because  of  poor  understanding  of  externalities  and  inadequate  policy instruments (Field and Olewiler 2002).  A* Ps B Pp  A MSC MPC Qs  Qp  Quantity DD Price/Cost ($)   27  1.2.5.2 Salmon Aquaculture and Externality  The  environmental  impacts  associated  with  salmon  aquaculture  represent  negative externalities from the production process, and these externalities are the costs incurred by the  affected  resource  users,  such  as  commercial  and  recreational  fishers.  For  salmon aquaculture  producers,  they  are  external  costs,  which  are  not  incorporated  into  their production  decision-making  without  the  relevant  policy  being  in  place.  For  instance, disease  can  cause  economic  losses  to  both  salmon  aquaculture  producers  and  the  wild salmon fishers. Aquaculture producers will internalize the costs resulting from reduction in revenues and increase in their production costs if they are known; the costs to wild salmon fisheries will not be internalized by salmon farmers without government intervention or economic  incentives.  In  the  case  of  pollution,  the  external  costs  may  include  potential impacts on benthic communities, seaweed, shellfish and wild fish fisheries.    Salmon aquaculture is a commercial activity, and its primary objective is to maximize its profits from aquaculture operation by maximizing revenue and/or minimizing production costs. If a salmon aquaculture operation continuously makes negative profit, the operation will have to fold. Therefore, salmon aquaculture producers will not take into account these external  costs  without  government  intervention.  However,  some  environmental  impacts may have  feedbacks on  the productivity of salmon production, in which case producers will  internalize  these  environmental  impacts  into  their  production  process  (Asche  et  al. 1999; Bj?rndal et al. 2002; Tveret?s 2002). For instance, Asche et al. (1999) and Bj?rndal et al. (2002) pointed out that environmental impacts were, to a large extent, internalized into the decision-making in the Norwegian salmon aquaculture.   1.2.5.3 Methods for Measuring Environmental Costs  While  externalities  are  acknowledged,  how  to  calculate  them  is  a  big  challenge.  The economic evaluation of environmental costs ?involves putting prices or social values on physical  environmental  changes?  (Angelsen  and  Sumaila  1996).  Environmental economists  have  developed  a  variety  of  methods  or  techniques  to  assess  these   28  environmental values. Broadly speaking, these valuation methods can be categorized into three  types.  The  first  type  refers  to  direct  market  valuation  methods,  which  attempt  to quantify environmental costs based on physical changes and observed market prices; it is relatively  straightforward.  For  instance,  the  costs  due  to  the  loss  of  fish  and  shellfish catches can be estimated based on the reduction in the amount of fish or shellfish catch resulting from diseases and/or pollution and the market prices of these fish and shellfish.   The second type is revealed preference methods, which use indirect or surrogate market prices  to  estimate  environmental  costs.  They  include  the  travel  cost  method,  hedonic pricing and surrogate market pricing. The travel cost method is used to estimate the values of  recreational  amenities.  Hedonic  pricing  is  used  to  estimate  the  use  values  of environmental  amenities,  for  instance  through  their  effects  on  upland  property  values. Surrogate  market  pricing  is  used  to  estimate  costs,  e.g.,  replacement/restoration  costs, compliance  cost,  abatement/prevention  costs.  Abatement  cost  methods  apply  different technologies  for  reducing  environmental  impacts,  while  compliance  costs  methods implement  environmental  regulations  or  policies  to  force  producers  to  mitigate environmental  impacts.  Abatement  and  compliance  costs  can  be  the  same  if  applying  a technology is mandated by environmental regulation.  The third method allows people to state, choose or rank their preferences or options based on a hypothetical market. It is commonly called ?stated preference? techniques. The most widely-used method is the contingent valuation method, which is a survey-based technique. It  has  been  extensively  used  for  estimating  non-market  values  of  resources  and environmental  service.  In  a  contingent  survey,  a  variety  of  questions  will  be  designed based  on  a  hypothetic  market.  Then,  people  will  be  asked  to  state  their  preference  by answering  questions  about  hypothetic  choices.  The  questions  can  include  how  much people  are  willing  to  pay  for  improving  specific  environmental  quality  or  service,  or willing to accept in compensation for giving up specific environmental service or enduring a welfare loss from deteriorated water quality or damages caused by salmon aquaculture.     29  These three types of valuation methods have been widely described in the literature (e.g., Muir et al. 1999; Barbier 1994 and 2000; Boardman et al. 2001; Field and Olewiler 2002). Some of these methods have been used for estimating the external costs associated with aquaculture.  For  instance,  Folke  et  al.  (1994)  used  a  ?modified?  contingent  valuation method  to  estimate  the  cost  of  reducing  eutrophication  from  salmon  aquaculture  in  the Baltic  Sea.  Smearman  et  al.  (1997)  conducted  a  contingent  valuation  survey  by  asking people?s  willingness-to-pay  for  improving  water  quality  that  was  degraded  by  trout farming  in  West  Virginia.  The  cost  of  the  damage  from  the  waste  was  estimated  to  be about  25%  of  the  production  costs,  whereas  applying  a  filtration  technology  to  prevent waste  discharges  would  cost  farmers  about  6%  of  the  production  cost.  Sathirathai  and Barbier  (2001)  applied  a  direct  market  valuation  method  and  bioeconomic  models  to estimate the external costs generated by mangrove destruction and water pollution from shrimp  farming  in  Thailand.  They  concluded  that  shrimp  farming  would  not  be economically  viable  if  external  costs  were  incorporated.  Babier  (2003)  developed  a bioeconomic  model  to  estimate  the  welfare  losses  in  coastal  fisheries  due  to  mangrove deforestation resulting from shrimp farming in Thailand.   Nevertheless, some environmental costs can be measured in monetary terms, while some are difficult to quantify  because they are not traded on the market, such as biodiversity losses due to pollution. In some cases, ecological or environmental impacts are not fully understood and large gaps exist in our knowledge of actual and long-term impacts on the environment  and  resources.  Some  environmental  costs  are  difficult  to  quantify  because they may result from different sources, and the measured using different methods. Thus, alternatively, abatement costs and compliance costs can be used as environmental costs. Both abatement and compliance costs are relatively easy to estimate and less controversial than directly estimating environmental costs. For instance, implementing new technologies (e.g., Buschmann et al. 2001; Chopin et al. 2001; EPA 2002; Troell et al. 2003) and best management practices (e.g., Ackefors and White 2002; Boyd 2003; Neori et al. 2004) have been seen as feasible and achievable means to mitigate and prevent environmental impacts associated with salmon aquaculture.   30  However,  different  methods  or  techniques  have  different  advantages  and  disadvantages. There is no ?perfect? method or technique. Many environmental economists have put great efforts into measuring environmental costs imposed by different sectors. In the following chapters,  I  will  apply  different  valuation  methods/techniques  to  deal  with  pollution  and disease problems associated with salmon aquaculture.                                       31  1.3 References Ackefors, H. and P. White, 2002. A framework for developing best environmental practices for aquaculture. World Aquaculture 33(2): 54-59.   Angelsen, A. and U.R. 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Targeted environmental monitoring for the effects of medicines used to treat sea-lice infestation on farmed fish. ICES Journal of Marine Science 58(2): 477-85.  Delgado, C.L., N. Wada, M.W. Rosegrant, S. Meijer, and M. Ahmed, 2003. Fish to 2020: Supply and Demand in Changing Global Markets. International Food Policy Research Institute and WorldFish Centre. 232p.  EPA, 2002. Development Document for Proposed Effluent Limitations Guidelines and Standards for the Concentrated Aquatic Animal Production Industry Point Source Category. Engineering & Analysis Division Office of Science and Technology, Environmental Protection Agency, United States, Washington, DC. 571p.  FAO, 2000. FAO Yearbook of Fishery Statistics: Aquaculture Production. FAO Fisheries Series, 86/2. Rome, Italy.  FAO, 2007. The State of World Fisheries and Aquaculture 2006. Fisheries and Aquaculture Department, Food and Agriculture Organization of the United Nations, Rome, Italy. 180p.  Field, B. and N. Olewiler, 2002. 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ICES Journal of Marine Science 58(2): 486-91.                             39  Chapter 2 Growth of Salmon Aquaculture2    2.1 Introduction There is ample evidence that the world?s capture fisheries catches have reached their upper ceiling (e.g., Watson and Pauly 2001). Studies have demonstrated that the catches of some species,  especially  top  predators,  have  dramatically  declined  recently  (e.g.,  Pauly  et  al. 2002;  Meyer  and  Worm  2003).  Increasingly,  aquaculture  has  been  seen  by  many  as  a solution  to  bridge  the  gap  between  the  dwindling  capture  fisheries  catch  and  increasing seafood demand (e.g., Tidwell and Alan 2001; Garcia and Grainger 2005).   It is estimated that aquaculture production has been growing annually at an average rate of 8.8% since 1970. Turning to farmed salmon, its production has increased from around 500 tonnes in 1970 to over 1.3 million tonnes in 2005. Salmon aquaculture has been increasing at  an  average  rate  of  24.6%  since  1980  to  present  (FAO,  FISHSTAT).  World  farmed salmon  production  first  exceeded  wild  salmon  production  in  1998.  Over  the  years, aquaculture?s  contribution  to  the  world?s  seafood  supply  has  increased.  Currently, aquaculture contributes about one-third of the world?s total seafood supply (FAO 2007). These numbers have fuelled optimism, leading the Food and Agricultural Organization of the United Nations (FAO) to predict that aquaculture will continue its rapid expansion in order  to  meet  growing  population  and  seafood  demand  around  the  world  in  the  future (FAO 2007).   Given  this  overwhelming  growth  in  farmed  salmon  production,  it  has  been  hard  to pullback and to investigate the question: can farmed salmon production keep growing at recent  rates?  To  answer  this  question,  it  is  not  enough  to  look  at  the  total  growth  in production or even the average growth rate over time but rather it is necessary to look at                                                  2 A version of this chapter is currently in press. Liu, Y. and Sumaila, U.R. (2008) Can Farmed Salmon Production Keep Growing? Marine Policy.   40  the  year-on-year  growth  of  farmed  salmon  production  to  determine  whether  the  annual incremental  growth  rate  of  production  is  increasing,  decreasing  or  remaining  stable. Further,  we  also  analyzed  the  growth  in  all  finfish  aquaculture  and  all  finfish  capture fisheries to compare them with the growth in farmed salmon.  Many  reasons  have  been  advanced  in  the  literature  that  suggest  that  aquaculture,  in particular intensive aquaculture of carnivorous species such as shrimp and salmon, cannot continue  to  grow  at  its current  pace  (Pauly  et  al.  2002;  Naylor  et  al.  2003;  Naylor  and Burke 2005; Tacon et al. 2006). The current contribution distinguishes itself by analysing the data. First, we present the growth of salmon aquaculture production over time. Then, based on FAO, time series production data in the leading producing countries and for the sector as a whole are used to compute the 5-year moving average rate of growth3 in salmon aquaculture  production.  Based  on  the  grow  rates  calculated,  a  regression  line  is  drawn starting at the peak point4. Similarly, I also calculate the 5-year moving average rates of growth  in  all  finfish  aquaculture  and  capture  fisheries  and  draw  their  regression  lines, respectively.  2.2 Global Salmon Aquaculture Production Salmon  aquaculture  has  experienced  remarkable  growth  as  a  result  of  expanding  new cultured locations, improved productivity, enhanced husbandry practices and management, and  growing  global  markets  (Bjorndal  2002;  Bjorndal  et  al.  2003;  Asche  and  Khatum 2006).  In  the  meantime,  salmon  aquaculture  has  undergone  a  number  of  structural  and technical changes, and it has expanded, intensified and diversified during the course of the last  two  decades.  Figure  2.1  shows  salmon  aquaculture  production  by  the  four  major salmon fishing countries over time. It can be seen from this figure that there has indeed been remarkable growth.                                                    3 The moving average growth rate is a better measure than the normal growth rate because it can help to reveal the ?hidden? trend in an evolving dataset, and also filters some of the noise in the dataset. 4 Farmed salmon production in fact increases in an increasing rate initially, then increases in a declining rate, and begins to decrease. One could have fitted a traditional S-curve covering the whole period of the time series. However, these S-curves will not help me to achieve my goal.   41  0.00.20.40.60.81.01.21.41984 1987 1990 1993 1996 1999 2002 2005YearProduction (million tonnes)NorwayChileUKCanadaOthers Figure 2.1. Farmed salmon production by major producing country. Data source: FAO FISHSTAT (http://www.fao.org/fi/website/FIRetrieveAction.do?dom=topic&fid=14795).    2.3 Analyses of Growth in Salmon Aquaculture The results are presented in Figure 2.2. The figures show, unequivocally, that in all four countries, and for the world as a whole, the year-on-year growth rate of salmon production quickly reaches a peak and then begins sliding down towards zero. The analysis reveals a decline of 1.2 percent per year in global farmed salmon production since it peaked in 1966 (Figure  2.2e).  From  Figure  2.2a,  it  can  be  seen  that  growth  rate  in  farmed  salmon production  in  Norway  peaked  in  1971  at  a  rate  of  100%.  The  growth  rate  has  been declining at 2.5% per year since it peaked. In the case of the UK, the growth rate peaked in 1979 at about 89%, and since then, the country has witnessed a decline of 3% per year in the rate of growth of farmed salmon production. Canada?s rate of growth of farmed salmon production peaked in 1977 at about 440%. Since the peak year, the growth rate has been declining at a rate of 10.9% per year. Chile?s rate of farmed salmon growth in production peaked in 1986, at a growth rate of about 157%, with a decline of 6.2% per year since the peak year.     42  One can conclude from this result that the ability of salmon aquaculture to keep growing at its current pace5 is doubtful. Analysis of production data for all farmed finfish, both marine and freshwater, shows a decline of 0.34% per year in the growth rate from the peak year. These  results  have  implications  for  global  fisheries  policy  because  they  mean  that  the world may not be able to rely on aquaculture to supply fish protein for human consumption as assumed by some. 3ay = -2.4516x + 78.457R2 = 0.82140204060801001966 1971 1976 1981 1986 1991 1996 2001YearGrowth rate (%) 3by = -2.9731x + 68.638R2 = 0.9062(10)10305070901970 1975 1980 1985 1990 1995 2000 2005YearGrowth rate (%) 3cy = -10.931x + 252.07R2 = 0.7307(10)40901401902402903403904401977 1981 1985 1989 1993 1997 2001 2005YearGrowth rate (%) 3dy = -6.2084x + 100.47R2 = 0.75350204060801001201401601977 1981 1985 1989 1993 1997 2001 2005YearGrowth rate (%)                                                  5 The current pace refers to the widely average annual growth rate of 8.8% estimated by FAO based on aquaculture data from 1970 to present. 2a  2b 2c  2d   43  3ey = -1.2072x + 54.404R2 = 0.72590204060801966 1971 1976 1981 1986 1991 1996 2001YearGrowth rate (%) Figure 2.2. 5-year moving average of year-on-year growth rate of farmed salmon production in Norway (2a), the UK (2b) Canada (2c), Chile (2d), and globally (2e).    A  relevant  question  to  ask  at  this  juncture  is,  whether  the  decline  reported  above  is happening only in the case of farmed salmon. If the answer is yes then it can be argued that the finding will not have a huge policy implication. To address this question, an analysis of production data for ?all finfish aquaculture? was carried out. The results from this analysis are presented in Figure 2.3. y = -0.3424x + 13.308R2 = 0.538503691215181966 1973 1980 1987 1994 2001YearGrowth rate (%) Figure 2.3. 5-year moving average of year-on-year growth rate of production of ?all finfish aquaculture?.    2e   44  It  is  shown  in  the  figure  that  for  the  period  from  1966  to  2005,  the  rate  of  growth  in production of all finfish aquaculture, i.e., marine, diadromous and freshwater, peaked in 1984, and has since been declining at the rate of 0.34% per year.  Finally, the paper investigated whether what is demonstrated for aquaculture is also true for capture fisheries. An analysis of catch data for ?all capture finfish? was conducted, the results of which are reported in Figure 2.4. This figure shows that the trend in the growth rate  of  catch  of  capture  fish  is  similar  to  the  trend  in  the  growth  rate  of  production  of farmed  fish, implying that when it  comes to trends in growth rates of production/catch, there is no difference between capture and farmed fish.  y = -0.1385x + 5.6484R2 = 0.5247(1)01234567891952 1960 1968 1976 1984 1992 2000YearGrowth rate (%)  Figure 2.4. 5-year moving average of year-on-year growth rate of catch of ?all capture finfish species?.     2.4 Discussions and Conclusions  It  has  been  demonstrated  in  Chapter  3  that  farmed  salmon  production  has  witnessed  a significant increase in the last three to four decades. More importantly, a simple analysis of production data for the major salmon aquaculture countries, and the world, shows that the optimistic view that aquaculture will continue its rapid expansion in order to meet growing y = -0.1385x + 5.6484 R2 =0.5247   45  population and seafood demand around the world is not supported by production data for salmon farming and for ?all finfish aquaculture?6.   The declining growth rate in the production of farmed salmon and all finfish aquaculture is an indication that the expectation that fish from aquaculture will continue increasing into the future at recent rates, thereby providing a solution to the declining catch from global capture fisheries, is not likely to come to fruition. The declining growth rate may indicate that the productivity of salmon aquaculture is beginning to decline. This decline may be attributed  to  changes  in  market  conditions,  e.g.,  falling  prices,  demand,  new  markets (Tveter?s and Heshmati 2002; Asche and Khahun 2006), the scarcity of inputs and their costs, e.g., feed (Tacon et al. 2006), scarcity of suitable space (Bj?rndal 2002; S?nvisen 2003)  and  environmental  concerns  resulting  in  stricter  regulations,  and  increasing consumer awareness about food safety and quality of farmed productions (Whitmash and Wattage 2006). These are some of the reasons why salmon aquaculture cannot continue to increase at recent growth rates forever.   The  substantial  increase  in  farmed  salmon  production  is  accompanied  by  a  decrease  in market prices for farmed salmon products. In the meantime, production costs have steadily declined as a result of technological innovations and productivity growth (Bj?rndal et al. 2002; Asche and Khatun 2006). Salmon aquaculture is driven by profit-making. Hence, the more profitable salmon aquaculture is, the more expansion takes place, everything being equal.  Initially,  due  to  high  market  prices,  salmon  producers  received  higher  returns  on investment  and  greater  incentive  to  expand.  The  rapid  expansion  has  led  to  greater competition, lower market prices, and increasing environmental problems.                                                   6 There is no doubt that aquaculture is playing an important role for providing seafood for consumers. In some countries or regions, a significant amount of seafood consumed is from aquaculture. Even with a 1-2% annual growth rate, total production from aquaculture will be significant. However, this growth rate may not meet the needs of the world?s growing population if the demand for seafood keeps growing at a higher rate (>1-2%) than aquaculture.     46  01020304050607080901985 1988 1991 1994 1997 2000 2003Years0100200300400500600700PriceProduction costProductionPrice and cost (NOK/t)Production (?000 t) Figure 2.5. Changes in production, cost and price of Norwegian farmed salmon.  As Norway has the most data available, information on Norwegian salmon aquaculture are used  to  demonstrate  these  relationships.  Figure  2.5  shows  changes  in  price,  cost  and production for the Norwegian salmon aquaculture industry from 1985 to 2005 (on average, 1CAD$ = 5.5NOK). As may be seen from the figure, price and production costs have been declining,  while  production  has  been  increasing  over  time.  In  some  years,  price  and production  cost  were  almost  equal,  implying  profits  were  low.  As  long  as  salmon aquaculture is still profitable, its growth will continue. Farmed salmon products used to be luxury  seafood  available  in  restaurants  for  the  elite,  but  today  they  have  become  more affordable seafood available in most seafood markets (Forster 2002; Knapp et al. 2007). This is one benefit of salmon aquaculture ? it leads to increasing consumer surplus.   The  result  of  this  simple  study  has  far-reaching  policy  implications  ?  it  means  that  the convenient  assumption  by  some  that  because  of  aquaculture,  the  world  need  not  worry about the pending demise of capture fisheries may be unfounded.           47  2.5 References Asche, F. and F. Khatum, 2006. Aquaculture: Issues and Opportunities for Sustainable Production and Trade. Issue Paper No. 5. International Centre for Trade and Sustainable Development, Geneva, Switzerland. 63p.  Bj?rndal, T., R. Tveter?s and F. Asche, 2002. The development of salmon and trout aquaculture. 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European Environment 16: 108-121.                                           49  Chapter 3 Estimating Pollution Abatement Costs of Salmon Aquaculture: A Joint Production Approach7   3.1 Introduction  Pollution  is  one  of  the  environmental  concerns  associated  with  salmon  aquaculture. Pollution involves uneaten feed, faeces and organic matter from salmon farms entering the marine environment. These are directly discharged into the marine environment because there are no solid and effective barriers between netcages and the surrounding environment. Pollution  may  potentially  have  negative  impacts  on  sediments  and  water  columns,  on benthic communities and on some fishery resources (e.g., Milewski 2001; Levings et al. 2002; Brooks and Mahnken 2003; Naylor et al. 2003). For instance, pollution in the form of  nitrogen  and  phosphorus  may  increase  the  risk  of  eutrophication,  and  alter  species composition and phytoplankton density in the water column (NRE 2006). Pollution in the form of organic matter may change sediment chemistry, resulting in changes in sediment flora and fauna in affected areas (e.g., Mazzola et al. 2000; McGhie et al. 2000; Pohle et al. 2001).   Some impacts are measurable near-field changes in sediments and water variables that are sensitive to organic matter and nutrient additions, while some are far-field effects which are  difficult  to  observe  and  measure,  such  as  eutrophication  and  effects  on  food  webs (Hargrave  2003).  There  is  an  extensive  literature  that  documents  these  ecological  and environmental  impacts,  especially  in  Europe,  North  America    and  Chile,  where  most farmed salmon are produced (e.g., Tlusty et al. 2000; Pohle et al. 2001; Levings et al. 2002; Brooks et al. 2003; Naylor et al. 2003). These negative impacts may be considered small at a large scale, but they can be very significant locally,  especially in areas where salmon farms are concentrated.                                                   7 A version of this chapter will be submitted for publication. Liu, Y., Gulati, S. and Sumaila, U.R. The Pollution Abatement Costs of Salmon Aquaculture.   50   In  the  case  of  the  Norwegian  salmon  aquaculture  industry,  pollution  from  fish  farms together with discharge from households, industry, and agriculture have posed a potentially serious  risk  in  coastal  waters  and  fjords  (NRE  2006).  Fig.  3.1  shows  that  nitrogen  and phosphorus from aquaculture have increased rapidly over the last two decades, and their contributions to the overall nitrogen and phosphorus production have become larger over time. Today, Norwegian aquaculture is the largest source of phosphorus, and the second largest  source  of  nitrogen  in  the  coastal  areas  of  the  country  (NRE  2006).  Although pollution has not increased at the same rate as the rapid growth of aquaculture production, it is still increasing.  -51015202530351985 1992 1995 1998 2001 2004YearsAquacultureAgricultureSewageIndustryNotrogen inputs(?000 t) -1234561985 1992 1995 1998 2001 2004YearsAquacultureAgricultureSewageIndustryPhosphorus inputs(?000 t) Figure 3.1. Nitrogen and phosphorus from Norwegian salmon aquaculture industry and other sources into the marine environment. (Data source: NRE 2006).    51  Recognizing  the  impacts  of  pollution  on  the  environment  and  natural  resources,  salmon producers should bear the environmental costs of pollution according to the Polluter-Pays-Principle. The environmental costs can be determined either by the cost of damage caused by pollution to the environment and resource users, or by measuring abatement/prevention cost directly imposed on the production process. In most cases, the environmental costs estimated  from  these  two  approaches  are  not  the  same,  especially  in  the  case  of  weak environmental policies. However, due to the difficulty of directly estimating damage costs, this  study  focuses  on  pollution  abatement  cost,  which  is  assumed  to  be  a  proxy  for environmental cost.  A production process, such as salmon aquaculture, produces desirable or ?good? outputs (salmon)  while  simultaneously  generating  undesirable  or  ?bad?  outputs  (e.g.,  pollution). Bad outputs are the by-products of good outputs (i.e., good outputs cannot be produced without producing some bad outputs). Good outputs are generally marketable, while bad outputs are commonly unmarketable. In conventional production theory, the productivity and  efficiency  of  a  firm  or  an  industry  are  generally  measured  based  on  good  outputs. However, joint production approaches and models have been recognized and developed to incorporate bad outputs along with good outputs for measuring efficiency and productivity (e.g., F?re et al. 1989; Chung et al. 1997; Chambers et al. 1998; F?re et al. 2005 & 2007). The  joint  production  approaches  have  several  advantages  compared  to  conventional production  approaches.  First,  they  can  automatically  capture  two  or  more  outputs, including multiple good and bad outputs. Second, the model does not require information on pollution abatement technology and its associated costs. Third, the model only requires quantitative data on inputs and outputs; no specific price data are needed (F?re et al.1989; Pasurka 2001; F?re et al. 2003).   In this study, production technology that constructs the joint production of good and bad outputs  is  specified  based  on  the  assumptions  of  strong  and  weak  disposability  for  bad output. Strong disposability assumes that disposing bad outputs is free of charge, and it is viewed  as  unregulated  technology.  On  the  contrary,  weak  disposability  assumes  that   52  disposing bad outputs is not free of charge, and it is viewed as regulated technology, which implies  that  producers  face  environmental  regulations  that  limit  their  discarding  of  bad outputs, and have to engage in pollution abatement activities (F?re et  al. 1989). Hence, abating  pollution  becomes  a  costly  activity,  and  producers  have  to  internalize  pollution abatement cost into their production process.   The  rest  of  the  chapter  is  organized  as  follows.  Section  2  presents  the  theoretical framework; Section 3 provides the data and describes an empirical application based on Norwegian  salmon  aquaculture;  Section  4  reports  the  results;  in  Section  5  sensitivity analysis  is  conducted  for  some  key  parameters;  Section  6  presents  conclusions  by summarizing the results, limitations of the study and suggestions for further research.  3.2 Theoretical Framework Let us assume a production process that employs a vector of inputs  n+  to yield a set of good outputs denoted by a vector m+ , and bad outputs denoted by a vector j+ . The technology (T) for the production process is represented by: T = [(x, y, z): x can produce (y, z)] The technology illustrates all technically feasible relationships between inputs and outputs. For a given input vector x, the output set P(x) represents all feasible output vectors (y, z), that is: ] The production possibility set P(x) illustrates the trade-offs between good and bad outputs along  the  production  possibility  frontier.  Inputs  and  good  outputs  are  assumed  to  be strongly disposable whereas bad outputs are weakly disposable. In other words, inputs and good outputs are assumed to be freely disposable, while bad outputs are disposed at a cost. Thus, the production possibility set P(x) is also an environmental output set (F?re et al. 2005  &  2007).  The  environmental  production  possibility  set  P(x)  has  the  following properties:   53  i.  P(x) is convex and compact,  n+  and satisfies the condition of no free lunch. That is  ) ; ii.  Strong disposability of good output and of inputs: If  ) , then for  y , ) , and for  x ,  ) ; iii.  Null-jointness: If  )  and 0, then  0 ; iv.  Weak disposability in  good and bad outputs:  If  ) , and  1, then ). The first and second properties are standard assumptions in production theory (Shephard 1970). The first assumption implies that inactivity results in no outputs (i.e., no free lunch), and finite inputs produce finite outputs. The second assumption is strong disposability for good outputs and inputs implying that it is possible to freely dispose them (F?re et al. 1989, 2005  &  2007).  The  third  assumption  is  null-jointness  between  good  and  bad  outputs implying that if no bad outputs are produced, then good outputs will not be produced as well. The fourth assumption is weakly disposability of outputs implying that both good and bad outputs can be reduced. It is costly to reduce bad outputs because good outputs have to be reduced simultaneously in order to ensure that a new output vector  )  is feasible (F?re et al. 1989, 2005 & 2007). The third and fourth assumptions are of special interest to this study. However, the last two assumptions can not hold with the second assumption at the same time. The reason why they cannot hold will be explained in Figure 3.2.  The  environmental  output  set  is  illustrated  in  Figure  3.2.  The  production  possibility frontier  P(x)  is  constructed  from  observations  given  input  level  x.  The  points  A  and  B represent the combinations of good and bad outputs given a set of input (x). Since non-parametric  linear  programming  methods  are  used  to  measure  production  efficiency,  the production  possibility  frontier  P(x)  is  piecewise  linear.  The  environmental  output  set  is bounded by the piecewise linear segments OABC.        54            Figure 3.2. Environmental output sets. S1: regulated technology; S2: unregulated technology. (modified from Fare et al. 2005)  The output set OABC satisfies assumptions (i ? iv). However, if bad output is assumed to be as strongly disposable as good output, assumption iii, i.e., the null-jointness, is violated (F?re et al. 2005). In other words, the assumption of strong disposability for bad output abuses the physical relationship between good outputs and bad outputs. This assumption is plausible because it indicates that producers will not pay the cost of disposing bad outputs in the absence of regulations. Instead, there is a real possibility of breaking the physical relationship between good and bad outputs (F?re et al. 2005; Picazo-Tadeo et al. 2005). When  environmental  regulations  are  imposed  on  firms  or  farms,  disposing  bad  outputs becomes  a  costly  activity  (F?re  et  al.  1989).  Hence,  if  bad  outputs  are  free  disposal,  it means that they are unregulated by the society. The positively-sloped portion (Figure 3.2 S1)  implies  that  increasing  good  output  production  is  accompanied  by  increasing  bad output  production.  The  vertical  line  segment  (Figure  3.2  S1,  S2)  can  occur  when  bad outputs  are  strongly  disposable.  In  the  case  of  salmon  aquaculture,  pollution  increases when salmon production grows, everything being equal.   Based  on  these  assumptions  about  inputs  and  outputs,  a  joint  production  approach  is developed to model both good and bad outputs.  It is assumed that producers attempt to maximize good outputs and minimize bad outputs if there is an environmental regulation implemented. I specify two production models with different mapping rules for outputs, C Y (good output) O B AZ (bad output) Pw(x) zo F(xo,zo)  f S1: Regulated technology O B AZ (bad output) C Ps(x) Y (good output) S2: Unregulated technology   55  known as (i) environmental production functions (EPF); and (ii) directional distance output functions  (DDOF).  These  two  models  serve  as  the  functional  representation  of environmental  production  technology.  EPF  is  constructed  for  solely  maximizing  good output  and  keeping  bad  outputs  constant  in  a  directional  vector  (e.g.,  F?re  et  al.  2007). DDOF is formed for expanding good outputs and contracting bad outputs in a directional vector (e.g., Chung et al. 1997; Picazo-Tadeo et al. 2005; F?re et al. 2005 & 2007). Both models  are  additive,  and  their  expansion  and/or  contraction  take  place  in  a  directional vector. EPF is a special case of DDOF.   3.2.1 Environmental Production Function Like traditional production functions, given the vectors of inputs and bad outputs  ) , an environmental production possibility frontier is defined as  )  and constructed based on observations. I assume that )  is the bounded line segments OABC in Figure 4.2. S1.  The  maximum  amount  of  good  outputs  can  be  produced  based  on  the  production possibility frontier ) . Given a set of inputs and bad outputs )00 z , the maximum feasible production of good outputs is defined as )00 z . Because good outputs can be freely  disposed,  y  is  feasible  if ) .  Then,  the  environmental  production  set  is defined as )}. Hence, an environmental production function is ?a complete  characterization  of  the  single  output  environmental  technology?  (Fare  et  al. 2007).   There are parametric and non-parametric methods of specifying production models. The parametric method specifies a mathematical equation for a production model, for example, a quadratic function for directional distance function (e.g., Fare et al. 2005; Vardanyan and Noh 2006). The non-parametric method uses data envelopment analysis (DEA) technique to measure the efficiency performance of producers. DEA uses linear programming (LP) techniques that first identify the theoretically best producers based on observed data (e.g., inputs and outputs). Then, a production possibility frontier is constructed as a piecewise linear  envelope  of  all  observed  outputs  and  inputs.  The  producers  on  the  frontier  are   56  assumed  to  operate  efficiently.  Producers  who  are  not  on  the  frontier  are  regarded  as inefficient.  The  production  level  due  to  inefficiency  is  calculated  by  comparing  the performance  of  each  producer  to  the  best  producer.  Non-parametric  methods  have advantages  over  parametric  methods  because  they  can  incorporate  several  inputs  and outputs without generating different estimates. It should be noted that parametric methods (e.g., translog vs quadratic models) may produce different estimates. Further, they can be performed with limited datasets, and they also avoid the biases brought about by different parametric models (Fare et al. 1989). Therefore, in this study, a non-parametric method is adopted.   Assuming there are a sample of k = 1?K producers employing a vector of inputs  kn , n = 1?N to obtain a vector of good output  km , m =1?M, and a vector of bad outputs  kj , j = 1?J,  q is  the  maximum  output  that  producers  intend  to  increase.  The  environmental production function on the production technology T is then defined by  )]                                      (3.1) Let g denote a directional vector,  )y  for good outputs. Where  my R+ , and  0m . EPF on the production technology T is defined by  )]yy ??qb                             (3.2) The objective function of EPF is to maximize good output by increasing quantity q  in the directional vector gy given inputs and bad outputs. When bad outputs are unregulated, the objective function for observation  ?is written as: ?max);,,( kyk gzyxFu q=                                         (3.3.1) Subject to                                  ?1knNnkn xx ?=a                                                                        (i)                                                                 ??1kmmykMmkm ygy +?=q                                                          (ii)                                                  ?1kjJjkj zz ?=a                                                                       (iii) Where  0kjmn z ,  k are  the  intensity  variables,  which  are  weights  assigned  to each observation when constructing the production frontier. These intensity variables map   57  out the efficient frontier. Observations on the frontier are considered efficient, while those not on the frontier are considered inefficient. Since  k  is nonnegative, constant returns to scale is imposed.  When bad outputs are regulated, the objective function for observation  ?is written as                                                 ???? max kykkk g q                                             (3.3.2)                                                                              Subject to                                  ?1knNnkn xx ?=a                                                                        (i)                                                                 ??1kmmykMmkm ygy +?=q                                                          (ii)                                                  ?1kjJjkj zz ==a                                                                       (iii) Where  qkjmn z  and  k are defined above. The right hand side of the constraints of LP  problems  represents  the  actual  amounts  of  inputs  or  outputs  employed  or  produced, while the left hand side of the constraints represents the amount of inputs or outputs used or produced by the most efficient or best producers. It should be noted that the signs of the constraints  for  bad  outputs  in  two  equations  are  different.  In  the  3rd  constraint  equation above (Eqs. iii-1 and iii-2), the equality sign means that bad outputs are weakly disposable under regulated technology, i.e., the observed amount of bad outputs equals the amount of bad outputs produced by the most efficient producers, while the inequality sign means bad outputs are strongly disposable under unregulated technology, i.e., the observed amount of bad outputs equals or is less than the amount of bad outputs produced by the most efficient producers.  3.2.2 Directional Distance Output Function Directional distance output function (DDOF) has the quality that it can allow the expansion of good output and contraction of bad output at the same time. Let g denote a directional vector,  )zy g , for good and bad outputs. Where  my R+ ,  jz R+ , and  0+ jm . DDOF on the production technology T is then defined by  )]zyzy ??bb          (3.4)   58  where  b  is the maximum attainable expansion of good output along the +gy direction, and largest feasible contraction of bad output along the -gz direction vector. Applying the same principles  for  strong  and  weak  disposability  for  bad  outputs  as  in  EPF,  DDOF  under unregulated and regulated production technologies are written as:  The objective function under unregulated technology is:          ???? max kzykkk g b?                             (3.5.1) Subject to                                    ?1knNnkn xx ?=a                                                                      (i)                                                     mykkmMmkm gyy?1b =                                                      (ii)                                                     jzkkjJjkj gzz?1b =                                                      (iii)  The objective function under regulated technology is:           ???? max kzykkk g b?                               (3.5.2) Subject to                                    ?1knNnkn xx ?=a                                                                      (i)                                                      mykkmMmkm gyy?1b =                                                     (ii)                                                      jzkkjJjkj gzz?1b =                                                     (iii)  where, 0kjmn z ,  k , the input and output constraints are defined as in the case of environmental production function.  3.2.3 Pollution Abatement Costs  When bad outputs are not regulated, their disposal is free of charge for producers, and all inputs are used for producing good outputs. When environmental regulations are imposed, disposing bad outputs (pollution) becomes a costly activity because producers have to take away resources from producing good outputs to reduce/abate bad outputs. In other words, the inputs that are used to produce good outputs have to be diverted for cleaning/abating   59  bad outputs. The reduction in bad output production comes at the cost in the form of a reduction  in  good  output  production.  Hence,  the  cost  of  environmental  regulation  is described  as  pollution  abatement  cost  (PAC),  which  is  the  lost  good  output  related  to pollution abatement activity to producers. Pollution abatement cost is also the opportunity cost  of  the  regulation  (F?re  et  al.  2005  &  2007).  It  is  seen  from  the  private  producer?s perspective, and measured by the difference of the forgone good outputs under unregulated and  regulated  technologies.  Therefore,  pollution  abatement  costs  under  two  production functions are expressed as follows: (i)  environmental production function:              )?????? ykkkykkk g                                             (3.6.1) (ii)  directional distance output function:              )?????? zykkkzykkk g                             (3.6.2) Where )??? ykkk g , )??? ykkk g , )??? zykkk g and)??? zykkk g  are defined earlier.   It  should  be  noted  that  these  production  models  are  usually  used  to  measure  technical inefficiency  of  producers.  Given  input  vectors,  technical  inefficiency  measures  are determined  by  the  ratio  of  actual  good  output  to  maximum  potential  good  output.  If observed data points lie on the frontier, producers are defined to be  efficient, otherwise they are inefficient. The magnitude of technical inefficiency measures the distance between observed data points and the production possibility frontier.   Figure 3.3. Illustration of environmental production and output distance functions. Y2  B O D C (gy, -gz) a b1 P(x) b2    a2  Z (bad output) a1 A Y1 Y (good output)   60  Figure  3.3  illustrates  an  environmental  production  function  and  a  directional  distance output  function.  Points  A,  B  and  C  are  on  the  frontier  P(x)  and  are  efficient.  Point  a operates inside the frontier and is inefficient. Any point on or inside P(x) can be expanded and/or contracted in both  ) . For instance, in the case of the environmental production function, keeping bad output unchanged, the producer operating at point a can expand its good  output  from  a  to  a1  with  regulated  technology  or  from  a  to  a2  with  unregulated technology.  Under  the  directional  distance  output  function  model,  the  producer  can increase its good output and decrease bad output by moving from a to b1 with regulated technology or from a to b2 with unregulated technology.  Thus,  pollution  abatement  costs  can  be  determined  by  the  difference  between  the maximum good output  production associated with unregulated and regulated production technologies, or they can be determined on the loss of good output production related to technical inefficiency (F?re et al. 2007). As can be seen in Figure 3.3, if the environmental production  function  model  is  used,  the  lost  output  due  to  inefficiency  is  the  distance between  a  and  a1  under  regulated  technology  and  between  a  and  a2  under  unregulated technology; the PAC is the distance between a1 and a2. If the directional distance output production function is used, the lost output due to inefficiency is the distance between a and b1 under regulated technology and between a and b2 under unregulated technology; the pollution  abatement  cost  is  the  vertical  distance  between  b1  and  b2,  i.e.,  the  distance between  Y1  and  Y2.  Since  farmed  salmon  are  sold  in  the  market,  the  potential  revenue losses are calculated using average  yearly market prices and potential output production losses.  Therefore,  pollution  abatement  costs  also  can  be  determined  by  the  potential revenue losses.  3.2.4 Directional Vector  Before conducting the programming, I need to specify the directional vector g(gy) and g(gy, gz)  for  the  EPF  and  DDOF  models,  respectively.  I  choose  the  directional  vector )zy g for  the  EPF  model,  and )zy g for  the  DDOF  model. The reason for choosing the unity directional vectors ( 1y  and 1z ) is that the unity   61  directional vectors indicate the ?shortest? distance when ?optimizing over the direction? to reach  the  production  frontier  (F?re  and  Grosskopf  2000).  In  other  words,  the  estimates from  the  two  models  give  the  maximum  unit  expansion  in  good  output  production  and simultaneous unit contraction in bad output production. I test the effects of using different directional  vectors  on  the  pollution  abatement  costs  in  sensitivity  analysis.  Linear programming  is  used  to  solve  the  maximization  problem  for  each  functional  form.  The computer software General Algebraic Modeling System (GAMS) is used to perform the calculation. GAMS is a  high-level modeling system for mathematical programming  and optimization (GAMS8). The optimal solutions are achieved for unregulated and regulated production technologies for two production models based on explicitly differentiating the assumptions on the constraints regarding inputs and outputs, in particular, the constraints due to bad outputs.   3.3 The Data Since  Norway  has  widely-available  ecological  and  economic  data  related  to  salmon aquaculture, I use the Norwegian salmon aquaculture industry as my empirical application of  the  joint  production  models  proposed  herein.  Norway  is  the  pioneer  in  salmon aquaculture  development  and  production.  The  country  has  been  the  number  one  farmed salmon producer in the world since the beginning of salmon farming. However, due to the lack of farm-level data, I consider salmon aquaculture as a whole and use the data collected at an aggregated industry level on an annual basis.   In this analysis salmon aquaculture operation needs four inputs (feed, smolt, labour and capital) to produce one good output (salmon production) and two bad outputs (nitrogen and phosphorus). The quantities of salmon production and inputs are extracted from Statistics Norway  and  the  Fisheries  Directorate  Norway  (www.ssb.no),  whereas  the  quantities  of nitrogen  and  phosphorus  were  estimated  by  the  Norwegian  Institute for  Water  Research (NIVA 2005) and compiled by Natural Resource and Environment Norway (NRE 2006). Several  methods  are  used  to  quantify  nitrogen  and  phosphorus  from  aquaculture.  The                                                  8 More information about GAMS can be found at http://www.gams.com/   62  production parameters, such as production, feed used, nitrogen and phosphorus contents in feed  and  farmed  salmon,  treatment  yield,  wastewater  volume,  nitrogen  and  phosphorus concentration of samples and number of sampling periods are used for these calculations, and  the  detailed  information  can  be  found  in  OSPAR  (2004).  The  data  set  ranges  from 1986 to 2005, and is summarized in Table 3.1. Since both the environmental production function  and  directional  distance  output  function  are  additive  models,  the  measurement unit and magnitude of inputs and outputs may affect the results (Picazo-Tadeo et al. 2005; F?re et al. 2007). To avoid these problems, I scale all inputs and outputs into fractions by dividing these by their respective maximum values in the samples of inputs and outputs. In other  words,  the  values  of  all  the  inputs  and  outputs  are  normalized  between  0  and  1. However, I also run the models without normalizing the data, and it turns out the results from both analyses are the same.  Table 3.1. Summary Statistics for the Norwegian Salmon Aquaculture, 1985 - 2005.      Units  Minimum  Mean  Maximum Good output  Production  tonnes in thousands  44.9  286.1  582.2 Phosphorus  tonnes in thousands  0.7  3.1  6.1 Nitrogen  tonnes in thousands  2.5  13.7  27.3 Feed  tonnes in thousands  87.3  357.4  727.6 Labor  man-hours in millions  3.0  3.9  4.9 Smolt  numbers in millions  27.3  96.0  160.2 Input Capital  NOKs in millions  402.7  1,723.8  2,147.3  The lost good output associated with technical inefficiency is estimated for the EPF and DDOF  models  using  the  same  data  set.  The  pollution  abatement  costs  are  simply  the difference  between  the  lost  good  outputs  resulting  from  technical  inefficiency  for unregulated and regulated production technologies. By multiplying by the price of good output, i.e. farmgate price, the losses of good outputs in terms of revenue are calculated. Hence, the pollution abatement costs are expressed in both lost production and revenue of the good output.    63  3.4 Results and Discussions Table 3.2 shows the results. On average, pollution abatement costs expressed in terms of lost  production  and  revenue  are  about  10.3  thousand  tonnes  and  472  million  NOKs, respectively,  over  the  20  years.  These  comprise  3.5%  and  6.5%  of  total  farmed  salmon production  and  revenue,  respectively.  On  average,  the  PACs  estimated,  based  on  the DDOF  and  EPF  models,  are  about  12.1  and  8.2  thousand  tonnes,  which  corresponds  to about 4.2%, and 2.9% of total salmon production, respectively. In terms of revenue, the costs are around 544 and 400 million NOKs, which work out to about 7.5% and 5.5% of total revenues, respectively. Out of a total of 20 observations, 8 in the DDOF model, and 10  in  the  EPF  model  do  not  incur  pollution  abatement  costs.  Considering  that  salmon producers make very low profit margins currently, these PAC estimates are quite large. If these  PAC  estimates  are  internalized  into  producers?  production  processes,  the  profit margins may disappear.   Table 3.2. Average pollution abatement costs associated with the two production models.  Production  Revenue Model  000 t  % of total  million NOK  % of total # of years with PAC=0 Environmental production function  8.16  2.85  400  5.53  10 Directional distance output function  12.09  4.23  544  7.52  8  Average  10.13  3.54  472  6.53  9  Without environmental regulations, farmed salmon could be increased by 3.5% in terms of tonnes of salmon production and 6.5% in terms of revenues. However, such increases in good  output  production  will  be  accompanied  by  simultaneous  increases  in  bad  output production.  This  implies  that  these  pollution  abatement  costs  reflect  trade-offs  between good and bad outputs (Table 3.2).   It should be noted that pollution abatement costs show a wide variation depending on years (or  producers)  and  production  models  (Figure  3.4).  Over  the  years,  PAC  has  shown  a decreasing trend. This is because salmon aquaculture operation is getting more efficient due  to  the  improvement  of  feed  formulation  and  feeding  technology,  and  husbandry   64  management (Bj?rndal et al. 2002). However, in some years PAC increased unexpectedly. For  instance,  in  1989,  1994  and  2002,  PACs  were  much  higher  than  their  respective adjacent  years  (Fig.  3.4).  These  sudden  increases  in  PACs  may  be  caused  by  different factors,  such  as  investment  in  production,  market  conditions,  regulatory  changes,  or biophysical  shocks  (e.g.,  disease  outbreak  and  accidents).  Tveret?s  (1999)  and  Tveret?s and Heshmati (2002) indicated that these factors might result in technical changes from year to year. For instance, in 1989, Furunculosis, a bacterial disease, became endemic in Norway,  hitting  the  salmon  aquaculture  industry  hard,  with  189  salmon  farms  and  wild salmon populations in 18 rivers affected (Johnsen and Jensen 1994).  PAC1051015202530354045501986 1989 1992 1995 1998 2001 2004YearsDPACEPACAveragePollution abatement cost (?000 tonnes) PAC20.00.51.01.52.02.51986 1989 1992 1995 1998 2001 2004YearsDPACEPACAveragePollution abatement cost (?million NOKs) Figure 3.4. Pollution abatement costs for two production models. PAC1: PAC is expressed in terms of lost production; PAC2: PAC is expressed in terms of lost revenue. EPAC: Environmental production function; DPAC: Directional distance output function.   65  Between  DDOF  and  EPF  models,  the  former  estimates  higher  pollution  abatement  cost than the latter. This is because different mapping rules for bad outputs are applied in these two  models.  DDOF  increases  good  output  and  decreases  bad  outputs  in  a  directional vector; EPF only increases good output and keeps bad outputs unchanged. In the DDOF model, some inputs have to be diverted to reduce bad outputs, while all inputs are used to increase good outputs in the EPF model.   Since  pollution  abatement  costs  are  estimated  based  on  technical  inefficiency,  I  herein show the production losses under unregulated and regulated technologies for two models due  to  technical  inefficiency.  Under  unregulated  technology,  the  levels  of  production losses  for  the  two  models  are  very  close.  Under  regulated  technology,  the  level  of production  losses  is  very  low  in  the  DDOF  model,  while  it  is  much  higher  in  the  EPF model. This result is consistent with the belief that salmon aquaculture operations attempt to  increase  their  production  and  decrease  pollution  (Figure  3.5).  This  implies  that producers who must increase good output and decrease bad output can be regarded as more technically efficient.              66  (a): unregulated technology01020304050601 4 7 10 13 16 19Producers (in ascending order of inefficiency)EPFDDOFProduction loss (?000t)  (b): regulated technology051015201 4 7 10 13 16 19Producers (in ascending order of inefficiency)EPFDDOFProduction loss (?000t) Figure 3.5. Production loss due to technical inefficiency. (a): unregulated technology; and (b): regulated technology. EPF: environmental production function; DDOF: directional distance output function.  3.5 Sensitivity Analysis As  the  mapping  rules  for  directional  vectors  have  impacts  on  the  estimated  pollution abatement cost (e.g., Vardanyan and Noh 2006), a variety of mapping rules are applied for the two directional models ? EPF and DDOF. First, it is assumed that the directional vector for bad outputs remains constant set equal to 1, and the directional vector for good output is  assumed  to  gradually  increase  from  a  scale  of  1  to  10.  The  results  show  that  the estimated  PACs  fall  with  increasing  directional  vector  for  good  output.  This  is  to  be expected  because  more  inputs  have  to  be  diverted  to  producing  good  outputs.  The magnitude of the decline gets smaller as the directional vector for good output gets bigger. This is the case in both models.   67  Directional distance output function010203040501986 1989 1992 1995 1998 2001 2004Years(gy,gz)=(1,1)(gy,gz)=(2,1)(gy,gz)=(5,1)(gy,gz)=(10,1)Pollution abatement cost (?000t)  Environmental production function0102030401986 1989 1992 1995 1998 2001 2004Years(gy,gz)=(1,1)(gy,gz)=(2,1)(gy,gz)=(5,1)(gy,gz)=(10,1)Pollution abatement cost (?000t) Figure 3.6. Estimated pollution abatement cost for various mapping rules. The figure on the top is directional distance output function; the figure on the bottom is environmental production function.  Second, it is assumed that regulations have no effects on input factors. Within a production process,  assuming  inputs  are  all  used  to  produce  good  output  when  bad  outputs  are unregulated, some inputs have to be allocated for pollution abatement activity when bad output is regulated. However, in some cases, inputs do change depending on the resource, economy  and  time.  For  instance,  the  use  of  feed  has  gradually  reduced  with  the improvement of feed formulation and feeding technology. Thus, I test the effect on PAC under an assumption of expanding good output and reducing input uses. Here, I use the DDOF to illustrate these effects on PACs. Two scenarios are performed: i) increasing good output while reducing inputs and bad outputs simultaneously g(-gx,+gy,-gz) = (-1,1,-1); and   68  ii)  increasing  good  output  while  reducing  inputs  and  keeping  bad  outputs  constant  g(-gx,+gy, -gz) = (-1,1,0). The results are compared with the base scenario g(+gy,-gz) = (1,-1).  010203040501 4 7 10 13 16 19Salmon farms (in ascending order of PAC)(+gy,-gz)(-gx,+gy,-gz)(-gx,+gy)Pollution abatement cost (?000t) Figure 3.7. Pollution abatement costs under different mapping rules for inputs and outputs.    In  Fig.  3.7,  it  is  found  that  PACs  decline  when  inputs  are  reduced.  This  indicates  that directly reducing inputs may be more resource efficient than directly reducing bad outputs because  pollution  is  reduced  at  source  in  the  former  case.  This  result  may  provide producers and policy makers a useful insight for formulating environmental regulations. As  in  the  case  of  salmon  aquaculture,  it  is  difficult  to  mitigate  pollution  once  it  is discharged into the  environment. This is because pollution is directly dispersed into the open ocean, given current open netcage technology. Since feed is the key input factor in contributing waste discharges, controlling feed input may be the most efficient means to regulate pollution discharges for salmon aquaculture. For instant, a feed quota program has been established in Norway since 1995. The aim of the program is to control production through controlling feed (Hjelt 2000).  3.6 Conclusions In this study, I develop a joint production function to model both good and bad outputs from salmon aquaculture industry. This allows me to calculate pollution abatement costs from  a  production  process  and  from  a  private  producer?s  perspective.  Two  production models,  environmental  production  function  and  directional  distance  output  function  are applied.  Good  and  bad  outputs  are  treated  in  an  asymmetrical  way  in  the  models.   69  Environmental production function only maximizes good outputs and keeps bad outputs constant.  Both  models  are  appropriate  in  the  case  of  salmon  aquaculture  because  some producers  are compelled to reduce bad output (pollution) such as producers in Norway, while  some  are  not  such  as  producers  in  Chile.  Directional  distance  output  function expands good outputs and contracts bad outputs. The analyses are conducted based on the assumptions  of  strong  and  weak  disposability  for  bad  outputs.  Thus,  unregulated  and regulated  production  technologies  are  specified.  The  analyses  are  carried  out  on  the Norwegian  salmon  aquaculture  industry.  One  good  output  (salmon),  two  bad  outputs (nitrogen and phosphorus), and four inputs (feed, smolt, labor and capital) are included in the analyses. The data are aggregated at the industry level, and range for a period of 20 years from 1986 to 2005. I choose a non-parametric approach to solve the maximization problem that this analysis entails. Pollution abatement costs are calculated by determining the difference between the foregone good outputs using two technologies.   Although  pollution  abatement  cost  is  estimated  based  on  a  production  process  from  a producer?s  perspective,  it  can  be  viewed  as  the  costs  of  pollution  damage  on  the environment and resource users. Some may argue that the damage costs estimated in this approach  may  be  underestimated.  The  producers  who  fail  to  implement  environmental regulations in their production decision making should be penalized. The level of penalty can  be  set  based  on  the  estimates  of  pollution  abatement  costs.  Further,  pollution abatement costs can be used as reference points to set pollution taxes that can be imposed on producers or consumers. To the best of my knowledge, this study is the first attempt to use a joint production function approach, especially directional distance output function to estimate pollution abatement costs for aquaculture, in general, and salmon aquaculture, in particular,  although  a  joint  production  model  has  been  applied  earlier  to  estimate productivity and technical efficiency for shrimp farming in Mexico (Martinez-Cordero and Leung 2004).   The estimated pollution abatement costs are closely dependent on the model forms used. Environmental  production  function  and  directional  distance  output  function  are  all  joint production  models,  but  they  have  different  mapping  rules.  Joint  production  models,   70  especially  directional  distance  output  function  model,  have  gained  growing  interest  and become  the  most  favorite  model  because  of  its  flexibility  of  mapping  rules  and  clear connection  to  traditional  production  functions  (e.g.,  Chung  et  al.  1997; Chambers  et  al. 1998; Pasurka 2001; F?re et al. 2005 & 2007; Verdanyan and Noh 2006). The directional distance output function model has been used to estimate shadow prices (e.g., F?re et al. 2006), productivities (e.g., Chung et al. 1997), and pollution abatement costs (e.g., F?re et al. 2007; Pasurka 2001; Verdanyan and Noh 2006). Further, joint production models can be used to test the economic effects of different environmental policies on different sectors (e.g., Br?nnlund et al. 1995). For instance, if the government sets a pollution level as a reduction target, we can use joint production models to test how much production, revenue or profit producers have to give up in order to meet the target. In this study, the directional distance output function is more appropriate because it fits better the goal of producers and policy makers: increasing good output and reducing bad outputs.  It should be noted that this joint production approach provides a framework to measure pollution abatement costs through technical inefficiency across farms and years. This study explores these costs for different years due to data constraints at the farm level. Ideally, a cross-sectional panel data of salmon farms is more appropriate than using a time series of data aggregated from all the salmon farms. However, in the case of salmon aquaculture, it is impossible to get such a cross-sectional panel data. Pollution abatement costs based on a time series data may be underestimated like demonstrated in Pasurka (2001). Due to data limitation,  I  have  assumed  no  technical  changes  over  20  years,  which  is  clearly  strong assumption.  However,  I  believe  that  technical  changes  have  been  incorporated  into production process, such as input and output factors.  Overall,  the  Norwegian  salmon  aquaculture  industry  is  getting  more  efficient  over  the years, in particular during the last several years, although technical efficiency and pollution abatement costs  greatly  differ among  years. Clearly, some  years are more efficient than others, and vice versa. This comparative difference provides a basis for future study about why some years are generally more efficient than others. In addition, these differences may reveal  a  pattern  of  variation  by  various  factors,  such  as  production  techniques,  farm   71  characteristics, environmental regulations, market conditions, and biophysical shocks (e.g., disease outbreaks).   I assume that salmon aquaculture operates under certain forms of regulatory constraints. This  means  that  salmon  producers  in  Norway  have  engaged  in  pollution  abatement activity.  This  assumption  is  appropriate  because  in  fact  there  are  some  regulatory frameworks proposed and implemented for salmon aquaculture industry. It is particularly true  for  the  Norwegian  salmon  aquaculture.  For  instance,  Norway  has  implemented  a number of regulations, such as limitations on production level, farm size, and fish density, and  feed  quota  (Hjelt  2000;  Maroni  2000).  Feed  is  the  key  factor  that  contributes  to pollution. Feed formulation and feeding technology have been greatly improved over the years. For instance, feed conversion ratio, a measure of a fish?s efficiency in converting feed into increased body weight, has been greatly reduced from around 4.0 in the 1980s to about 1.2 at present (Asche et al. 1999; Bj?rndal et al. 2002; Tveret?s 2002). Moreover, feeding technology has improved from hand feeding to automatic feeders (Bj?rndal et al. 2002).   Given current production technology and environmental regulations, if pollution is to be reduced, salmon production has to be reduced simultaneously. In particular, salmon farms which  are  clustered  in  some  areas  have  to  be  closed  down  partially  or  fully.  This  has already happened in the North Sea. The North Sea Agreement declares that the pollution level in the North Sea has to be reduced to the level in 1985 for all production sectors and households  in  all  the  countries  bordering  the  North  Sea.  In  order  to  meet  the  target, Norwegian fish farming facilities have been prohibited in the North Sea region since 1997 (NRE 2006).       72  3.7 References Asche, F., A. Guttormsen and R. Tveter?s, 1999. Environmental problems, productivity and innovations in Norwegian salmon aquaculture. Aquaculture Economics and Management 3(1): 19-29. Bj?rndal, T., R. Tveter?s and F. Asche, 2002. The development of salmon and trout aquaculture. In Paquotte, P., Mariojouls. C. and J. Young (Eds): Seafood Market Studies for the Introduction of New Aquaculture Products. Cahiers Options M?diterran?ennes 59: 101-115. Brooks, K.M., A.R. Stierns, C.V.W. Mahnken and D.B. Blackburn, 2003. Chemical and biological remediation of the benthos near Atlantic salmon farms. Aquaculture 219(1-4): 355-77.  Brooks, K.M. and C.V.W. Mahnken, 2003. Interactions of Atlantic salmon in the Pacific Northwest environment II. Organic wastes. Fisheries Research 62(3): 255-93.  Br?nnlund, R, R. F?re and S. Grosslope, 1995. Environmental regulation and profitability: an application to Swedish pulp and paper mills. Environmental and Resource Economics 6: 23-36. Chambers, R.G., Y. Chung and R. F?re, 1998. Profit, directional distance functions and Nerlovian efficiency. Journal of Optimization Theory and Applications 98(2): 351-364. Chung, Y.H., R. F?re and S. Grosskopf, 1997. Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management 51(3): 229-240. F?re, R., S. Grosskopf and W. Weber, 2006. Shadow prices and pollution costs in U.S. agriculture. Ecological Economics 56: 89-103. F?re, R., S. Grosskopf, C.A.K. Lovell and C. Pasurka, 1989 Multilateral productivity comparisons when some outputs are undesirable. Review of Economics and Statistics 71: 90-98.  F?re, R. and S. Grosskopf, 2000. Theory and application of directional distance functions. Journal of Productivity Analysis 13(2): 93-103.  F?re, R., S. Grosskopf, D.W. Noh and W. Weber, 2005. Characteristics of a pollution technology: theory and practice. Journal of Econometrics 126: 469-492.  F?re, R., S. Grosskopf and C. Pasurka, 2003. Estimating Pollution abatement Costs: A Comparison of ?Stated? and ?Revealed? Approaches. http://ssrn.com/abstract=358700 F?re, R., S. Grosskopf, and C.A. Jr. Pasurka, 2007. Environmental production functions and environmental directional distance functions. Energy 32: 1055-1066. Hargrave, B.T., 2003. Far-Field Environmental Effects of Marine Finfish Aquaculture. A Scientific Review of the Potential Environmental Effects of Aquaculture in Aquatic Ecosystems. Canadian Technical Report Fisheries Aquatic Science 1, Fisheries and Oceans Canada, 3-11.  Hjelt, K.A., 2000. The Norwegian regulation system and the history of the Norwegian salmon farming industry. In Liao, C.I and C. Kwei (Eds): Cage Aquaculture in Asia: Proceedings of the First International Symposium on Cage Aquaculture in Asia. Asian Fisheries Society, Quezon City, Philippines.1-17p.   73  Johnsen, B.O. and A.J. Jensen 1994. The spread of furunculosis in salmonids in Norwegian rivers. Journal of Fish Biology 45:47-55.  Levings, C.D., J.M. Helfield, D.J. Stucchi and T.F. Sutherland, 2002. A Perspective on the Use of Performance Based Standards to Assist in Fish Habitat Management on the Seafloor near Salmon Net Pen Operations in British Columbia. Department of Fisheries and Ocean, Vancouver, Canada, 59p.  Maroni, K., 2000. Monitoring and regulation of marine aquaculture in Norway. Journal of Applied Ichthyology 16: 192-195.  Martinez-Cordero, F.J. and P.S. Leung, 2004. Sustainable aquaculture and producer performance: measurement of environmentally adjusted productivity and efficiency of a sample of shrimp farms in Mexico. Aquaculture 241: 249-268.  Mazzola, A., S. Mirto, T. La Rosa, M. Fabiano and R. Danovaro, 2000. Fish-farming effects on benthic community structure in coastal sediments: analysis of meiofaunal recovery. ICES Journal of Marine Science 57(5): 1454-61.  McGhie, T.K., C.M. Crawford, I.M. Mitchell and D. O?rien, 2000. The degradation of fish-cage waste in sediments during fallowing. Aquaculture 187(3-4): 351-66.  Milewski, I., 2001. Impacts of salmon aquaculture on the coastal environment: a review. In M. F. Tlusty, D.A. Bengston, H.O. Halvorson, S.D. Oktay, J.B. Pearce and J.R.B. Rheault (Eds), Marine Aquaculture and the Environment: A Meeting for Stakeholders in the Northeast. Falmouth, Massachusetts, Cape Cod Press, 35p.  NRE, 2006. Natural Resource and the Environment, Statistics Norway. http://www.ssb.no/english/subjects/01/. Access Feb., 2007. Naylor, R.L., J. Eagle and W.L. Smith, 2003. Salmon aquaculture in the Pacific Northwest - a global industry. Environment 45(8): 19-39.  Pasurka, C.A., 2001. Technical change and measuring pollution abatement costs: an activity analysis framework. Environmental Resource Economics 18(1): 61?85. Picazo-Tadeo, A.J., E. Reig-Martinez and F. Hernandez-Sancho, 2005. Directional distance functions and environmental regulation. Resource and Energy Economics 27: 131-142.  Pohle, G., B. Frost and R. Findlay, 2001. Assessment of regional benthic impact of salmon mariculture within the Letang Inlet, Bay of Fundy. ICES Journal of Marine Science 58(2): 417-26.  Shephard, R.W., 1970. Theory of Cost and Production Functions. Princeton University Press, Princeton, NJ, 308p. Tlusty, M.F., K. Snook, V.A. Pepper and M.R. Anderson, 2000. The Potential for soluble and transport loss of particulate aquaculture wastes. Aquaculture Research 31(10): 745-55.  Tveter?s, R. and A. Heshmati 2002. Patterns of productivity growth in the Norwegian salmon farming industry. International Review of Economics and Business 50(3): 367-394.    74  Tveter?s, S. 2002. Norwegian salmon aquaculture and sustainability: the relationship between environmental quality and industry growth. Marine Resource Economics 17: 117-128.  Vardanyan, M. and D.W. Noh, 2006. Approximating pollution abatement costs via alternative specifications of a multi-output production technology: a case of the US electric utility industry. Journal of Environmental Management 80: 177-190.                                            75  Chapter 4 Potential Impacts of Sea Lice from Farmed Salmon on Wild Salmon Fisheries9  4.1 Introduction The  dramatic  declines  in  pink  salmon  populations  around  the  Broughton  Archipelago, British  Columbia  (BC),  in  2002  triggered  a  debate  over  the  possible  effect  of  sea  lice (Lepeophtheirus salmonis and Caligus clemensi) originating from salmon farms on wild salmon  populations.  Since  then,  a  number  of  studies  have  been  conducted  in  both laboratory  and  field  environments  to  explore  the  connections  between  farm-derived  sea lice and wild salmon populations in BC (Morton et al. 2004; Brooks 2005; Krko?ek et al. 2005 & 2006; Beamish et al. 2006). Some argue that salmon farms intensify the level of sea lice in surrounding waters, which leads to serious infection of wild juvenile pink and chum  salmon,  possibly  resulting  in  increased  mortality  and  declines  in  wild  salmon populations (e.g., Morton et al. 2004; Morton and Routledge 2005; Krko?ek et al. 2005 & 2006). Others claim that factors other than sea lice (e.g., ocean conditions) may play more important  roles  in  the  decline  of  wild  salmon  populations  because  these  populations fluctuate widely on their own from year to year, and that sea lice are natural parasites (e.g., Noakes et al. 2000; Brooks 2005; Brooks and Stucchi 2006).  Farmed  salmon  are  typically  reared  in  open  netcages  with  no  solid  barriers  to  separate farmed salmon from the surrounding environment. It should be noted that in most cases the parasites  that  are  found  within  salmon  farms  do  not  orginate  there;  rather,  the  farms amplify those that originate in the wild (Bakke and Harris 1998; Beamish et al. 2005). Sea lice, including L. salmonis and C. clemensi, are naturally occurring parasites in the coastal marine  waters  of  BC  (Margolis  and  Arthur  1979;  McDonald  and  Margolis  1995). Returning  wild  adult  salmon  such  as  pink,  chum,  and  sockeye  can  carry  high  levels  of adult  sea  lice  (Beamish  et  al.  2005),  which  may  lead  to  initial  infection  of  a  farm population. The extreme density of salmon within the netcages ensures completion of the                                                  9 A version of this chapter will be submitted for publication. Liu, Y., Volpe, J. and Sumaila, U.R. The Potential Ecological and Economic Impacts of Sea lice from Salmon Farms on Wild Salmon Fisheries.   76  lice  cycle,  leading  quickly  to  amplified  pathogen  concentrations  within  the  farm  and increased infection risk to nearby wild salmon populations (Noakes et al. 2002; Morton et al. 2004; Krko?ek et al. 2005 & 2006).  Several studies have attempted to examine the links between sea lice from salmon farms and the declines in wild salmonid populations at both local and regional scales. In Norway, high levels of sea lice infection are known to have profound negative effects on sea trout (Salmon trutta), Arctic char (Salvelinus alpinus), and Atlantic salmon (Salmo salar) smolt populations  in  Norwegian  fjords  (Finstad  et  al.  2000;  Bjorn  and  Finstad  2002).  The collapse  of  sea  trout  populations  along  the  coast  of  Scotland  was  caused  by  heavy infestation of sea lice (Butler 2002; Gargan et al. 2002). On the west coast of Canada, sea lice  production  within  a  farm  has  been  observed  to  reach  four  orders  of  magnitude (~30,000x) higher than ambient levels, triggering infection rates of wild juvenile salmon that  is  73  times  higher  than  ambient  levels  near  the  farm  and  a  greater  than  normal infection level up to 30 kilometers away (Krko?ek et al. 2005). This increased infection pressure has been shown to induce 9 - 95% mortality in exposed pink and chum salmon populations (Krko?ek et al. 2006).   Clearly,  these  studies  demonstrate  that  without  appropriate  management  and  treatments, salmon farms can harbour higher densities of sea lice than wild salmon populations. If the farms are sited close to fish migratory routes, there is a higher chance for migratory wild fish to get infected. This is especially so for migratory juveniles because they are more vulnerable to the parasites than adult fish (Morton et al. 2004; Beamish et al. 2005). Thus, sea  lice  from  salmon  farms  pose  a  potential  risk  to  some  wild  salmonid  populations, although the extent of the risk varies, and the ultimate impacts of sea lice on wild salmon are  yet  to  be  fully  determined.  However,  the  literature  on  European  and  BC  salmon farming demonstrate that there is a close connection between the levels of sea lice derived from salmon farm and wild salmon populations. The objective of this chapter is to examine whether sea lice from salmon farms have ecological and economic effects on wild salmon populations and fisheries, and if they do, to what extent. To address this objective, I first examine  how  increases  in  juvenile  mortality  caused  by  sea  lice  may  affect  salmon   77  population levels, then explore how such effects impact the performance of the commercial fishing sector.   4.2 British Columbia Wild Salmon Fisheries Pink and chum salmon are anadromous and semelparous species. That is, they reproduce and spend their early life in freshwater and their adult life in seawater, and spawn only once. Upon emergence from the gravel in spring or early summer, pink and chum salmon fry immediately migrate toward the sea, and spend about 1.5, and 2.5 - 4.5 years at sea, respectively. Then, mature adult salmon return to their spawning grounds to spawn in late summer and fall (Groot and Margolis 1991). Pink salmon have a simpler life cycle with a fixed two-year life span; thus, all pink salmon are mature at age two, and return as either odd- or even-year populations, which are genetically distinct (Heard 1991). Chum salmon mature at ages two to seven  years with most maturing between ages three to five  years (Salo 1991). Wild salmon may interact with salmon farms during their migration periods. Sea  lice  impact  is  measured  in  terms  of  number  of  lice  per  unit  body  weight,  so  wild salmon are at the greatest risk during the juvenile out-migration stage. For this reason, I restrict  my  examination  to  the  possible  effects  of  salmon  farm-derived  sea  lice  on  wild juvenile salmon.  Both  pink  and  chum  salmon  in  the  Broughton  Archipelago  have  experienced  wide variations in rates of return in recent years, with the numbers of returning salmon typically being below the historical average. However, the returning pink salmon population in 2002 declined remarkably, and little improvement has been made since then (DFO 2006). Pink and chum salmon are caught by the First Nations, recreational and commercial sectors. A fixed exploitation rate of about 20% for chum salmon has been implemented since 2002 (DFO  2006).  This  policy  aims  to  ensure  sufficient  escapement  levels  while  providing relatively stable fishing opportunities. This exploitation rate covers all user groups, and of this 20%, a fixed exploitation rate of 15% is allocated to the commercial sector and the remaining 5% is allocated to First Nations and recreational fishing. For pink salmon, there   78  have been very limited opportunities for commercial fisheries in the last few years because of low returns (DFO 2006).   The top management priority for salmon fisheries in BC is to conserve salmon populations and their habitat to avoid overexploitation (DFO 2005). Two management policies have commonly been implemented in BC wild salmon fisheries. One is a fixed exploitation rate, and the other is a target escapement. For an overexploited population, a target escapement policy  is  more  desirable  from  an  ecological  perspective  because  it  will  allow  the populations to rebuild relatively quickly, and such a management policy will result in the largest  possible  average  long-term  catch  (Walters  and  Korman  1999).  During  recovery, fishers  have  to  reduce  or  stop  fishing  entirely  for  some  period  of  time.  Overexploited populations recover more slowly under a fixed exploitation rate policy, because it always allows some catch, which is less variable from year to year (Walters and Korman 1999). Here,  I  study  the  exploitation  of  pink  and  chum  salmon  under  these  two  management policies.  The  objective  is  to  test  whether  the  ecological  and  economic  effects  of  farm-derived sea lice on wild salmon is significantly different when the fisheries are managed under a fixed exploitation rate versus target escapement policies.  Given  the  complex  population  structure  of  salmon  and  the  complexity  of  the  fisheries, management is very challenging. Both salmon fisheries consist of a number of different stocks; fishers employ multiple fishing gears (seine, gillnet, troll); and fish are harvested by different users (commercial, recreational and First Nations). In addition, the fisheries are  managed  under  different  management  goals,  i.e.,  conservation  and  maximization  of socioeconomic benefits. Due to lack of data for each individual stock of pink and chum salmon,  I  assume  that  pink  and  chum  salmon  fisheries  are  each  managed  as  a  single population.  Also,  the  catch  is  assumed  to  be  only  for  commercial  use.  Analyses  are repeated for each of the two management policies.  Study Area ? Broughton Archipelago This study focuses on the Broughton Archipelago, which includes a group of islands north of Johnstone Strait and off the northeast coast of Vancouver Island. My focus is on the   79  Kingcome, Bond and Knight Inlets (within DFO?s management area 12; see Figure 4.1). The reason for choosing this area is that the effects of farm-derived sea lice on wild salmon populations are known to be greatest here and, as a result, more data are available in the region (Morton et al. 2004; Brooks 2005; Morton and Routledge 2005; Krko?ek et al. 2005 & 2006; Brooks and Stucchi 2006).            Figure 4.1. The study area (dark oval), including Kingcome and Bond to Knight Inlet. (Source: Ryall et al. 1999, P53).  Twenty  nine  licensed  salmon  farms  were  located  in  this  area  in  2007,  owned  by  three companies: 19 by Marine Harvest Canada Inc.; 9 by Mainstream Canada; and 1 by Grieg Seafood BC. The locations of these farms are shown in Appendix 4.1. According to the British Columbia Ministry of Agriculture, Food and Fisheries (MAFF10), these farms are not  all  operational  in  any  one  year  since  sites  need  to  be  fallowed  between  production cycles. On average, about 14 - 16 salmon farms are in operation at any one time with 10 - 14 farms fallow from March to June during juvenile salmon migration period. The farmed salmon production level in this area has remained relatively stable even though the total farmed salmon production in BC has seen steady increases in recent years (MAFF5).                                                   10 http://www.agf.gov.bc.ca/fisheries/bcsalmon_aqua.htm.   80  4.3 Methodology I construct an age-structured model to capture wild salmon population dynamics with fry production modelled following a Ricker relationship (Ricker 1954). I then introduce to this a sea lice induced mortality rate. This dynamic model tracks salmon population abundance as a function of ecological parameters. To extend this ecological model to a bioeconomic one, economic components associated with fishing are added. This process is conducted under two different scenarios: i) without sea lice induced mortality; and ii) with sea lice induced  mortality  applied  to  the  fry  production  model.  The  ecological  effects  of  farm-derived sea lice are determined by the difference between the outcomes under these two scenarios, and are expressed in terms of changes in recruitment and catch of pink and chum salmon in the fishery. The economic effects are determined by the difference between the outcomes of these two scenarios in terms of the potential discounted profits to pink and chum salmon fisheries. I then compute and compare discounted profits using conventional and intergenerational discounting methods. The analyses are carried out for a time horizon of 30 years.  In addition to the deterministic population dynamic models, I also apply a Ricker stock-recruitment model with a stochastic variable to explore the effects of sea lice versus the combined  effects  of  all  factors  (including  sea  lice).  It  is  assumed  that  the  stochastic variable  captures  the  combined  effects  of  all  environmental  factors  and  human interventions that may affect wild salmon populations.    4.3.1 Age-structured Model   A  commonly-applied  population  assessment  method  for  Pacific  salmon  is  the  ?run reconstruction?  model,  which  uses  spatial  and  temporal  catch  and  escapement  data  to estimate salmon run sizes at different times throughout the adult reproductive migration stage.  Age-structured  models  that  do  not  rely  on  the  spatial-temporal  structure  of  catch statistics are commonly used in salmon population assessment (e.g., Kope 1987; Savereide and Quinn II 2004). However, farmed-derived sea lice have the greatest impact on wild salmon  at  the  juvenile  out-migration  stage.  Of  interest  here  though  is  how  lice-induced   81  juvenile  mortality  may  affect  salmon  populations  at  the  adult  stage,  requiring  an  age-structured approach. Moreover, age-structured assessment models have proven most useful when  addressing  population  level  impacts  of  disease  on  wild  fish  populations,  where impact  can  occur  across  life  history  stages,  not  just  at  the  harvestable  adult  stages. Examples include assessments of fungal infections in North Sea herring (Clupea harengus) (Patterson  1996);  herpesvirus  in  Australian  pilchard  (Sardinops  sagax)  (Murray  and Gaughan  2003);  and  viral  hemorrhagic  septicaemia  virus  in  Pacific  herring  (Clupea pallasii)  (Marty  et  al.  2003).  Therefore,  an  age-structured  model  is  considered  to  be  an appropriate framework for this study. Equation (4.1) illustrates an age-structured model in detail.  )11 jstNt eNNb--=                                                             (4.1a) )1,1, ataata m--                                                          (4.1b) )1,1,1, AtAAtAAtA m---                                      (4.1c) Where,  t,0  is  the  numbers  of  salmon  at  age  0 ,  in  year  t ,  as  determined  by  a  Ricker recruitment model at the fry stage;  0,0 , the initial number of age 0 fish, is given;  st 1-  is the  number  of  spawning  individuals  in  year  1 ,  j  is  a  population  productivity parameter  at  the  fry  stage; j  is  the  unfished  equilibrium  population  size  (numbers  of individuals)  at  the  fry  stage;  subscript  j  represents  the  fry  (juvenile)  stage  of  wild salmon; ta, is the number of fish at age a and  year t; sa is age-specific natural survival rate;  a is age specific maturity rate; tA, is the number of fish at the last age group A, in year t;  tA, ? 0 because I assume that all fish in the last age group mature and return to spawn  (i.e.,  1A ).  The  spawning  biomass st 1-  is  determined  under  our  two management policies as follows:         i)  fixed exploitation rate:          =-=- -=TtaAast zmNN1101 )1( ,   t"                    (4.1d1) ii) target escapement:                )1 Est =- ,    t                                        (4.1d2) Where,  z  and  E  are  a  fixed  exploitation  rate  and  target  escapement,  respectively,  and different for pink and chum salmon, their calculations are detailed in the following section.   82  I assume chum has six age classes (i.e., a =0, 1, 2, 3, 4, 5), while pink has three age classes (i.e., a = 0, 1, 2). The time horizon of the model is 30 years (i.e., t = 1, 2, 3, ?, 30).  Since  the  farm-derived  sea  lice  may  cause  the  mortality  of  wild  salmon  juveniles,  I introduce  a  sea  lice  induced  mortality  factor  into  the  fry  production  model,  i.e., )11,01,1 mtt -- ,  where f  is  the  sea  lice  induced  mortality  rate  and  captures the  salmon  farm  derived  sea  lice  induced  mortality  on  wild  salmon  fry  production,  and occurs only in the first age class ( 1).   4.3.2 Catch Function The  catch  functions  for  pink  and  chum  salmon under  the  two  management  strategies,  a fixed exploitation rate and target escapement, are defined as follows:  Fixed exploitation rate policy: The total catch for pink or chum salmon, zs , is written as:        ==Aasasasazs wmNzH1                                                      (4.2) Where subscript  s  represents pink and chum salmon, respectively;  zs  is the total catch of pink or chum salmon;  s  is the exploitation rates for pink or chum salmon;  sa  is the age specific weight for pink or chum salmon;  sa  and  sa  are as defined earlier.  Target escapement policy: The total catch for pink or chum salmon, Es , is expressed as:                                                                         -  ==AasasasAasasasaEsmEwmNH11)1                                  (4.3a)    Where,  Es  is the total catch of pink or chum salmon;  s  is a target escapement level for pink or chum; and other variables are as defined earlier.    83  4.3.3 Cost Function The total cost of fishing is assumed to be a function of catch,  t , population size, t  and the  unit  cost  of  fishing,  c :  )ttt N .  I  define  a  specific  total  cost  function  as tttt HNHcTC ?        ?= , where tNH / is the catch-population ratio representing the population effect.   In theory, the cost of fishing is assumed to be a function of fishing effort  f , where c  is  unit  cost  of  fishing  effort,  and f is  total  fishing  effort  (Clark  1990).  Based  on  the Schaefer production model, catch is  assumed to be  a  function of fishing  effort and fish population size ( Nqf ), where, H is catch, N is fish population and q is catchability. Thus,  fishing  effort, qNf / ,  which  is  positively  related  to  catch  and  negatively related  to  fish  population  size.  Further,  most  BC  salmon  fishing  fleets  have  multiple fishing  licenses,  target  multiple  salmon  species  and  populations,  and  operate  across different fishing grounds. Thus, fishing effort deployed in a given period is highly variable depending on the allowable catch determined in the fishing area, other vessels? activities during the same period, and on the market price. This is especially so in the case of pink salmon because its price is so low that fishers are often unwilling to target the species. Moreover, the catch-population ratio is used when there are no detailed fishing effort data available (e.g., Laukkanen 2001; Doole 2005).   4.3.4 Profit Function Given the catch obtained under the two management policies, the annual profits for pink or chum  salmon  fisheries  are  determined  by  the  annual  total  revenue  (TR)  and  total  costs (TC). The annual total revenue is assumed to be a function of catch,  t and market price, p ,  t . Where,  t = { zs or Es  }, and are as defined above. The annual total cost is  tttt HNHcTC ?        ?= , where  c , tH and tN  are as defined before.    84  It  is  assumed  that  the  biological  constraints  are  enforced  by  two  management  policies: fixed exploitation rate and target escapement. The profit maximization problem is written as:               i)  Discounted profits, using conventional discounting is defined as follows:                        Max    =         ?        ?-=-= TtffffTtt HNHcPHTCTR1) r                     (4.4a) Where  t is the discount factor,  tt r) , and r is the discount rate.  ii)  Discounted profits, using intergenerational discounting:  Conventional  discounting  applies  a  single  discount  rate  to  discount  all  future  costs  and benefits (i.e., revenues) of a project or an operation, such as fishing activity over the time horizon of the project, and a net benefit is calculated. Conventional discounting works well using  a  social  discount  rate  when  evaluating  short-term  projects  (e.g.,  5  -  10  years). However, when it is applied to value natural resources and environmental services in the long run, there is an ongoing debate about whether or not conventional discounting is an appropriate tool to be used for generations in the far future. Some argue that the costs and benefits  to  current  and  future  generations  should  be  discounted  using  different  social discount  rates  for  different  time  periods  (e.g.,  Weitzman  2001;  Newell  and  Pizer  2003) because of, for instance, uncertainty about the future.   In fact, the net benefits to future generations in conventional discounting are discounted based  on  the  current  generation?  time  perspective,  effectively  meaning  that  future generations  are  given  much  less  consideration  than  the  current  generation.  In  order  to weight  future  generations  equally  with  the  current  generation,  I  adopt  the  methods  of Sumaila  (2004)  and  Sumaila  &  Walters  (2005):  intergenerational  discounting  using different discounting clocks. They argue that the flow of net benefits should be discounted separately  for  each  generation,  using  a  discounting  ?clock?  for  each  generation  because each generation has its own life span. The net benefits to future generations from having fish protein will be discounted based on their own time perspective, not simply using the current  generation?s  time  perspective.  Sumaila  &  Walters  (2005)  introduced  a   85  mathematical expression (  =      ++TtttGtrNBNPV01)1( , where NPV is net present value, NB is  net  benefit,  r  is  discount  rate  and  G  is  generation  time)  to  deal  with  overlapping generations.  This  approach  results  in  less  discounting  of  future  generations?  flows  of benefits  from  natural  and  environmental  resources  than  in  the  case  of  conventional discounting  (Sumaila  2004;  Sumaila  &  Walters  2005).  Thus,  discounted  profits  using intergenerational discounting is defined as follows: max          +?        ?        ?-=-=   = GtHNHcPHTCTR TtffffTtt 1)(1r           (4.4b) Where G is generation time, here assuming G = 20 years;  )Gt  is an intergenerational discounting factor.   4.3.5 Potential Ecological and Economic Effects of Sea lice Two  scenarios  are  explored:  i)  scenario  1_no  lice,  assuming  where  no  sea  lice  induced mortality occurs; and ii) scenario 2_lice, assuming where sea lice induced effects occur. Hence,  the  ecological  effects  of  farm-derived  sea  lice  are  determined  by  the  difference between  the  outcomes  of  these  two  scenarios  and  expressed  in  terms  of  changes  in recruitment and catch. The economic effects of farm-derived sea lice are determined by the difference between the outputs of the two scenarios and expressed in terms of changes in the  discounted  profits.  Conventional  and  intergenerational  discounting  approaches  are applied to estimate these discounted profits.   4.4 The Data  Some  of  the  data  and  parameters  needed  for  this  study  are  directly  available  from  the literature, while other figures and parameters have to be estimated from raw data.     86  4.4.1 Ecological Parameters Estimating Parameters for Chum Salmon   Productivity and equilibrium population size:   The productivity of the population at fry stage,  cj , is estimated based on a regression of time series data of female spawners and fry recruited11.  cj  for chum salmon is estimated to be ~4.9. The unfished equilibrium population size at fry stage  cj  is calculated based on the  unfished  equilibrium  population  size  ( ca )  at  adult  stage,  and  cj .  For  the  detailed derivation of  cj  see Appendix 4.2.           )]545443321 sjcjcjcaj +++= aab                                    (4.5) Where, sj,  s1,  s2,  s3, s4, s5 are the survival rates at the fry  stage, and age 1,2,3,4  and 5, respectively; m3, m4 and m5 are the proportion of mature fish at age 3, 4 and 5, respectively. Thus,  cj  for chum salmon is estimated to be ~ 2,494,570 in numbers (Table 4.1a).  In  order  to  get  the  initial  data  ( 0,0 )  for  the  age-structured  models  at  year  0,  I  first calculate the age specific numbers based on the numbers of current spawners (e.g., chum: average  1953  -  1997;  pink:  1953  -  2003),  fecundity  per  female,  egg  efficiency,  egg retention,  age  specific  survival  rates.  Then,  I  run  the  models  without  fishing  until  the populations reach equilibrium. I use equilibrium values as the initial number of individuals at the first age class in year 0 (i.e.,  0,0  for pink salmon and chum salmon). There are two reasons for using equilibrium values instead of using current populations? numbers: i) lack of  age  specific  data;  and  ii)  chum  and  pink  salmon  in  the  Broughton  Archipelago  have been experiencing dramatic declines compared to historical average levels, and are both currently overexploited. Therefore, it is very  difficult to examine the effects of  a single factor (e.g., sea lice induced mortality) on the decline of overexploited salmon populations.                                                    11 Source: Ransom Myer?s database: http://fish.dal.ca/~myers/welcome.html.   87  Fixed exploitation rate and target escapement:   According to the management policies implemented for fisheries in the Johnstone Strait area, the target escapement in the study area set by DFO was ~546,000 (Ryall et al. 1999). Therefore, I use this as the target escapement. The fixed exploitation rate is estimated by using the productivity parameter a  since there is a relationship between exploitation rate and productivity parameter  2msy (Hilborn and Walters 1992). Since a  is known to be  7 (Luedke 1990), the fixed exploitation rate, msy , is ~32% (Table 4.1a).   Mortality rate induced by sea lice from farmed salmon   Based  on  2004/2005  field  data,  Krko?ek  et  al.  (2005)  developed  a  series  of  spatial transmission dynamic models of sea lice to examine the magnitude of sea lice infection from  salmon  farm  to  wild  juvenile  salmon.  Later,  combining  field  data  with  survival models and empirical lab experiments, they estimated cumulative mortality rates, ranging from  20%  to  60%  for  chum  juveniles  based  on  estimates  for  the  Tribune  Channel  and Knight Inlet datasets (Krko?ek et al. 2006). As the mortality rate induced by sea lice from salmon farms on chum salmon varies considerably and depends on many different factors (water temperature, salinity, proximity of wild fish to farm, lice density on farm, etc.), I use a range of mortality rates for chum salmon with a lower limit of 20% and an upper limit of 60%. Mortality rates are randomly picked within this range, and are included in year one ( 1 ) in the age-structured models. A Monte Carlo simulation is used to simulate the mortality rates and compute the results. Each Monte Carlo run can randomly pick a number (i.e., a mortality rate) within this range and repeat simulations and computations for a thousand times (i.e. 1,000 iterations). In addition, snapshots for a series of mortality rates are simulated as part of the sensitivity analyses included in this chapter (Table 4.1a).  Table 4.1a. Parameter values for chum salmon.  Parameters  Adult  Juvenile Productivity a   0.7  4.9 Unfished population b   1,287,822  2,494,570 Fixed exploitation rate ( z )  0.32  / Target escapement in # ( E )  546,000  / Sea lice induced mortality rate (f )  /  0.2 ? 0.6   88  The  other  parameters,  such  as  age-specific  natural  survival  rates,  proportion  of  mature salmon, and weight are extracted or estimated from the literature. These estimates and their sources are given in Table 4.1b.   Table 4.1b. Parameter values for chum salmon.                     Age Class  Parameters  1  2  3  4  5       Sources Proportion mature (ma )  0  0  0.30  0.75  1  Salo (1991);  Ryall et al. (1999) Weight (wa, kg)  0.36  2.51  3.72  4.72  5.35  Salo (1991);  Bigler et al. (1996) Survival rate (sa)  0.08  0.70  0.70  0.70  0.70  Salo (1991);  Ryall et al. (1999)   Estimating Parameters for Pink Salmon   Productivity and equilibrium population size:   The parameters  pj  and  pj are estimated using the same methods and procedures as for chum salmon earlier. For pink salmon  pj  is estimated to be ~5.2, while   pj  is estimated to be ~4,456,618 in numbers (Table 4.2a).   Fixed exploitation rate and target escapement  There  is  no  target  escapement  set  in  the  study  area  for  pink  salmon.  Thus,  I  have  to calculate it based on some parameters estimated earlier. I use the productivity and capacity parameters a and  b  for  adult  pink  salmon,  and  formulae  for  estimating  optimum  catch rate  MSY  [ 2MSY ]  and  optimum  population  size  MSY  [ )MSY , Hilborn and Walters 1992]. The exploitation rate is estimated to be  ~0.76,  yielding  a  target  escapement  level  of  ~766,581  individuals.  I  use  these  two estimates as the fixed exploitation rate and target escapement for pink salmon, respectively (Table 4.2a).     89  Mortality rate induced by sea lice from farmed salmon   The mortality rate induced by sea lice from salmon farms for pink juveniles ranged from 20%  to  80%  based  on  estimates  for  the  Tribune  Channel  and  Knight  Inlet  datasets (Krko?ek et al. 2006). I use a range of mortality rates for chum salmon with a lower limit of 20% and an upper limit of 80%. The running procedure is the same as for chum salmon, described earlier (Table 4.2a).   Table 4.2a. Parameter values for pink salmon.  Parameters  Adult  Juvenile Productivity a   2.2  5.2 Unfished population b   2,228,309  4,456,618 Fixed exploitation rate ( z )  0.76  / Target escapement in # ( E )  766,581  / Sea lice induced mortality rate (f )  /  0.2 ? 0.8   The  other  parameters,  such  as  age-specific  natural  survival  rates,  proportion  of  mature salmon, and weight are extracted or estimated from the literature. These estimates and their sources are given in Table 4.2b.   Table 4.2b. Parameter values for pink salmon.  Age Class Parameters  1  2        Sources Proportion of mature (ma )  0  1  Heard (1991) Weight (wa)  0.52  1.43  Heard (1991); Bigler et al. (1996) Survival rate (sa)  0.06  0.50  Heard (1991); Beamish et al. (2005)   4.4.2 Economic Parameters Estimating Parameters for Chum Salmon  Ex-vessel prices: Ex-vessel price is the price received by fishers for the salmon landed at the dock. Based on total landing and landed values of chum salmon in British Columbia (DFO statistics12), I calculate  the  ex-vessel  prices  of  chum  salmon  by  dividing  landed  values  by  the  total                                                  12 http://www.dfo-mpo.gc.ca/communic/statistics/commercial/index_e.htm   90  landings.  The  ex-vessel  price  is  $1.05  per  kg  for  chum  salmon  in  2005.  Based  on  the literature, I assume constant price through time.   Costs of fishing: Since 1995, no systematic and complete financial surveys of BC fishing fleets have been carried  out.  The  latest  fishing  cost  data  available  are  the  total  fishing  cost  for  salmon fisheries  in  200213 (GSGislason  &  Associates  2004).  Thus,  I  use  this  total  fishing  cost, fishing  days,  and  catch  to  estimate  the  fishing  costs  for  pink  and  chum  salmon.  To calculate them, I follow the steps listed below: ?  Calculate the fishing cost per day based on the total fishing cost and days fished (DFO statistics) in 2002; ?  Estimate  the  total  fishing  days  used  for  each  salmon  species  based  on  the proportion of total revenue per species multiplied by the total fishing days for all the species; ?  Compute the total fishing cost per species by the fishing days used for that species multiplied by the cost per fishing day based on the assumptions of no change in fishing  technology  between  2000  -  2005,  so  the  fishing  cost  per  day  is  also  to remain constant; ?  Estimate  the  fishing  cost  by  dividing  the  total  catch  for  each  species  for  2000  - 2005 by the total fishing cost; and ?  Calculate the average fishing cost for the period 2000 - 2005 for each species.  From this procedure, the unit fishing cost for chum salmon is estimated to be at about 0.86 per kg.   Estimating Parameters for Pink Salmon  Ex-vessel prices: Using  the  same  method  described  for  chum  salmon  earlier,  the  ex-vessel  price  for  pink salmon is calculated at ~ $0.33 per kg in 2005.                                                   13 Fishing  cost  here  refers  to  the  operating  costs  directly  related  to  fishing,  also  called  ?noncapital  cost? (Schwindt et al. 2000). It includes operating expenses (e.g., fuel, oil, wages and others), and fixed costs (e.g., repairs/maintenance, net, gear and others).     91  Costs of fishing: The method and procedure for estimating fishing cost for pink salmon is the same as for chum described earlier. The unit fishing cost for pink is estimated to be at about $0.37 per kg. From the fishing cost and ex-vessel price estimated, it can be seen that the fishing cost is  greater  than  the  ex-vessel  price  for  pink  salmon.  As  rational  fishers,  they  won?t  go fishing.  However,  fishing  vessels  have  multiple  fishing  licenses  and  harvest  at  different fishing grounds. Harvesting pink salmon is not a main fishing activity for the fishers.   4.4 Results  4.4.1 Chum Salmon Recruitment in scenario 1_no lice is the same under both management policies, whereas in scenario 2_lice recruitment is higher under a target escapement policy than under a fixed exploitation rate policy. There is virtually no catch under a target escapement because the total returning fish is less than the target escapement. The discounted profits over 30 years are greater under a fixed exploitation rate than under a target escapement. Table 4.3 shows the numbers of recruitment, escapement and catch when populations are in equilibrium, and the total discounted profits over 30 years.  Table 4.3. Summary of recruitment, harvest, escapement and total discounted profit under a fixed exploitation rate and a target escapement policy for chum salmon.   Under a fixed exploitation rate  Under a target escapement Scenario 1_no lice Scenario 2_lice* Scenario 1_no lice Scenario 2_lice* Recruitment (million #)  0.74  0.35 (47%)  0.74  0.43 (58%) Harvest (million #)  0.24  0.11 (46%)  0.19  0.00 Escapement (million #)  0.50  0.23 (46%)  0.55  0.55 Exploitation Rate  0.32  0.32  0.26  0.00 Conventional discounted profit (million $)  10.02  4.73 (47%)  1.98  0.00 Intergenerational discounted profit (million $)     15.40  7.24 (47%)  3.05  0.00  * The numbers in the parentheses indicate the percentage of scenario 2_lice to scenario 1_no lice.    92  Ecological and Economic Impacts of sea lice The  ecological  and  economic  impacts  of  sea  lice  vary  greatly  under  the  different management policies. Under a fixed exploitation rate policy, on average, the numbers of recruits, catch and discounted profit decline by 53% when we allow for sea lice induced mortality. Under a target escapement policy, on average, the numbers of recruits decline by 42%, while the discounted profit declines by ~100% over 30 years since there is no catch. When  sea  lice  induced  mortality  is  incorporated  into  the  production  model,  the  total number of returning fish is on average less than the target escapement level. However, in terms  of  absolute  numbers,  the  recruitment,  catch  and  discounted  profit  under  a  fixed exploitation rate are higher than under a target escapement. In sum, the potential ecological impacts  under  a  fixed  exploitation  rate  policy  are  more  severe  than  under  a  target escapement policy, and economic impacts under a target escapement are more severe than with a fixed exploitation rate (Figure 4.2).   93  0.00.10.20.30.40.51 5 9 13 17 21 25 29.YearsRecruitment_z Catch_zRecruitment_E Catch_ENumbers of fish (millions) 0.00.10.20.30.40.51 5 9 13 17 21 25 29.YearsConventional_zIntergenerational_zConventional_EIntergenerational_EDiscounted profits (million$) Figure  4.2.  Ecological  and  economic  impacts  of  sea  lice  on  chum  salmon  under  the  two management policies. The top graph shows ecological effects in terms of recruitment and catch, while the bottom graph shows economic effects in terms of discounted profit. Legend:  z and  E  represent under a fixed exploitation rate and a target escapement policy, respectively.   4.4.2 Pink Salmon Under a fixed exploitation rate, the population in scenario 2_lice collapses after ten years, while in scenario 1_no lice it declines over the first several years before reaching a steady state. Thus, in scenario 2_lice, there are very limited catches and discounted profits in the first  several  years.  Under  a  target  escapement  policy,  the  population  in  both  scenarios reaches a steady state. Recruitment in scenario 1_no lice arrives at a level twice as high as that in scenario 2_lice. There is little catch in scenario 2_lice in the first few years. As a result, the discounted profits are quite different between the two scenarios. The recruitment   94  in scenario 2_lice under a target escapement is slightly lower than that in scenario 1_no lice under a fixed exploitation rate (Table 4.4).    Table 4.4. Summary of recruitment, harvest, escapement and the total discounted profit under a fixed exploitation rate and a target escapement policy for pink salmon.   Under a fixed exploitation rate  Under a target escapement Scenario 1_no lice Scenario 2_lice* Scenario 1_no lice Scenario 2_lice* Recruitment (million #)  0.88  0.08 (9%)  1.67  0.79 (47%) Harvest (million #)  0.67  0.06 (9%)  0.91  0.00 Escapement (million #)  0.21  0.02 (10%)  0.77  0.77 Exploitation Rate  0.76  0.76  0.54  0.00 Conventional discounted profit (million $) 0.63  0.10 (16%)  2.07  0.51 (25%) Intergenerational discounted profit (million $)    0.95  0.12 (13%)  3.19  0.80 (25%)  * The numbers in the parentheses indicate the percentage of scenario 2_lice to scenario 1_no lice.   Ecological and Economic Impacts of sea lice Under  a  fixed  exploitation  rate  and  exposed  to  farm-amplified  lice  densities,  the  pink salmon  population  collapses  after  several  years  resulting  in  significant  ecological  and economic impacts. On average, both recruitment and catch are reduced by almost 100%. The  discounted  profits  drop  by  75%.  Under  a  target  escapement  policy,  on  average, recruitment  is  reduced  by  53%.  Since  there  is  virtually  no  catch  available  when  farm-induced lice mortality is taken into account, the discounted profits approach zero. Hence, the  ecological  impacts  under  a  target  escapement  management  are  higher  than  under  a fixed  exploitation  rate  in  terms  of  numbers.  However,  the  ecological  impacts  are  more severe  under  a  fixed  exploitation  rate  than  under  a  target  escapement  because  the population collapses under a fixed exploitation rate. In sum, both ecological and economic impacts under a fixed exploitation rate are greater than under a target escapement (Figure 4.3).   95  0.00.20.40.60.81.01 5 9 13 17 21 25 29YearsRecruitment_zRecruitment_ECatch_zCatch_ENumber of fish (millions)  0204060801001201401 5 9 13 17 21 25 29YearsConventional_zConventional_EIntergenerational_zIntergenerational_EDiscounted profit (?000$) Figure 4.3. Ecological and economic impacts of pink salmon under two management strategies. The  top  panel represents  ecological effects  in  terms of recruitment  and  catch, while  the  bottom panel represents economic effects in term of discounted profits. Legend:  z and  E  represent a fixed exploitation rate and target escapement policy, respectively.   4.5 Sensitivity Analysis There are uncertainties surrounding the values of some key parameters in these analyses, so a sensitivity analysis is carried out to estimate the robustness of the results to variations in  these  parameters.  First,  I  compare  the  effects  of  sea  lice  induced  mortality  with  all mortality factors combined. I then test the effects of different sea lice induced mortality   96  rates on ecological and economic impacts. Finally, I estimate robustness of the results vis-?-vis changes in productivity and capacity parameters as well as costs and ex-vessel prices.   4.5.1 The Effects of Combined Factors Obviously, salmon farm-derived sea lice are not the only mortality factor that negatively affects  wild  salmon  populations.  Climate  change,  disease,  destruction  of  habitat  and pollution are among many other significant factors. Thus, I introduce a stochastic variable that represents combined effects of environmental factors and human interventions (fishing is not included). This stochastic variable is integrated into a Ricker population-recruitment model.  The  stochastic  variable  is  estimated  from  the  standard  deviation  of  the  average recruit  per  spawner.  The  theoretical  foundation  and  model  description  can  be  found  in Appendix 4.3. I use the same Monte Carlo method to simulate the stochastic variable as introduced above. The stochastic variables used range from -0.6 to 0.0 for chum salmon, and  from  -2.4  to  0.0  for  pink  salmon.  Monte  Carlo  simulations  can  pick  up  a  random number  each  time  from  these  ranges  and  repeat  them  for  a  thousand  times.  I  use  the changes in recruitment as an example to demonstrate how farm-induced lice factors and all combined factors affect the recruitment of chum and pink salmon under two management policies.   97  Under a fixed exploitation rate_Chum0.00.20.40.60.81.01 5 9 13 17 21 25 29YearsScenario 1_no liceScenario 2_liceStochastic variableRecruitment (million#) Under a target escapement_Chum0.00.20.40.60.81.01 5 9 13 17 21 25 29YearsScenario 1_no liceStochastic variableScenario 2_liceRecruitment (million#) Figure 4.4. Recruitment changes under three scenarios: scenario 1_no lice, scenario 2_lice and combined factor (i.e., stochastic variable) for chum salmon under two management policies.   The  results  for  both  chum  and  pink  salmon  are  the  same  (Fig.  4.4  &  4.5).  The  salmon population with the stochastic variable collapses under a fixed exploitation rate, while the recruitment with stochastic variable is smaller than that in scenario 1_no lice and larger than that in scenario 2_lice under a target escapement. These results for chum and pink salmon are expected under a fixed exploitation rate policy as the combined effects should have larger impacts on the populations than only disease effect. However, under a target escapement  policy,  the  scenarios  with  sea  lice  have  greater  impacts  on  chum  and  pink salmon populations than the scenarios with stochastic variables. This may imply that high mortality rate incurred at the early stages of salmon populations may have stronger impacts on salmon populations than that at the late stages of salmon populations.   98  Under a fixed exploitation rate_Pink0.00.51.01.51 5 9 13 17 21 25 29YearsScenario 1_no liceStochastic variableScenario 2_liceRecruitment (million#) Under a target escapement_Pink0.00.51.01.52.01 5 9 13 17 21 25 29YearsScenario 1_no liceStochastic variableScenario 2_liceRecruitment (million#)  Figure 4.5. Recruitment changes under three scenarios: scenario 1_no lice, scenario 2_lice and combined factor (i.e., stochastic variable) for pink salmon under two management policies.    4.5.2 Mortality Rate Induced by Sea Lice from Salmon Farm The exact mortality rates of wild pink and chum salmon induced by farm-derived sea lice are unknown owing to the complex interactions among potential mortality factors. In the base scenario, random mortality rates within the ranges for pink (20% ? 80%) and chum salmon (20% ? 60%) are used over 30 years. These mortality rates are estimates based on the  datasets  from  two  areas  over  a  two-year  period,  and  a  series  of  lab  experiments (Krko?ek et al. 2006). However, I test the mortality rate from the lower limit at 10% to upper  limit  at  80%  for  both  pink  and  chum  salmon.  The  mortality  rate  is  increased  in   99  increments of 10%. Each simulation uses one single mortality rate which remains constant over 30 years.  Chum salmon: Under a fixed exploitation rate the salmon population fluctuates for the first several years and reaches a steady state at all the mortality rates. The population collapses when the mortality rate > 60%. It should be noted that the higher the mortality rate, the lower the steady state. The recruitment is lower than the target escapement level when the mortality rate is above 20%. The discounted profit decreases with increasing mortality rate. It  decreases  by  less  than  20%  when  mortality  rate  is  below  20%,  while  it  decreases  by more than 50% when mortality rate is more than 40% (Fig. 4.6).  Under a fixed exploitation rate-1002003004005006007008001 5 9 13 17 21 25 29Yearsno lice?_0.1?_0.3?_0.5?_0.6?_0.7Recruitment (?000#)Under a fixed exploitation rate-1002003004005006007008001 5 9 13 17 21 25 29Yearsno lice ?_0.1?_0.3 ?_0.5?_0.6 ?_0.7Discounted profit (?000$) Figure 4.6. Recruitments and discounted profits at various mortality rates for chum salmon under a fixed exploitation rate policy. The top graph shows the recruitments; and the bottom graph shows the discounted profits.   100  Under a target escapement policy, the population also fluctuates first and then reaches a steady  state  across  all  mortality  rates.  Recruitments  and  discounted  profits  decline  with increasing mortality rates. Recruitments are lower than the target escapement level when mortality rate is  ? 30%. The population collapse when the mortality is > 70%. Discounted profits decrease by over 80% when mortality rate is over 20%, and is zero when mortality rate is  ? 30% as no catch is allowed (Fig. 4.7). Under a target escepement policy-1002003004005006007008001 5 9 13 17 21 25 29Years?_0.1?_0.3?_0.5?_0.7?_0.8Recruitment (?000#)Under a target escapement policy-204060801001201401 5 9 13 17 21 25 29Years?_0.1?_0.2?_0.3Discounted profit (?000$) Figure 4.7. Recruitments and discounted profits at various mortality rates for chum salmon under a target escapement policy. The top graph shows the recruitments; and the bottom graph shows the discounted profits.   Pink salmon: Under a fixed exploitation rate, the pink salmon population declines at all mortality rates, and eventually reaches a steady state if the mortality rate is   20%, and the population  collapses  sooner  or  later  when  the  mortality  rate  is  >  20%.  The  higher  the mortality  rate,  the  sooner  the  population  collapses.  The  discounted  profits  gradually improve  with  declining  mortality  rate,  and  decrease  by  30%  and  57%  compared  to  the   101  discounted  profits  in  scenario  1_no  lice  for  the  mortality  rates  of  10%  and  20%, respectively.  Recruitment  is  higher  than  the  target  escapement  level  only  when  the mortality rate is below 10% (Fig. 4.8).  Under a fixed exploitation rate-2004006008001,0001,2001 5 9 13 17 21 25 29Yearsno lice0.10.20.3Under a fixed exploitation rate01020304050601 5 9 13 17 21 25 29Yearsno lice0.10.20.3Discounted profit (?000$) Figure 4.8. Recruitments and discounted profits at various mortality rates for pink salmon under a fixed exploitation rate policy. The top graph shows the recruitments; and the bottom graph shows the discounted profits.   Under a target escapement, the pink salmon population fluctuates initially, then reaches a steady state for all mortality rates. Recruitment is higher than the target escapement when the mortality rate is below 60%. Discounted profits decrease with increasing mortality rate (Fig. 4.9).   102  Under a target escapement0.40.60.81.01.21.41.61.81 5 9 13 17 21 25 29Yearsno lice0.10.30.50.6Recruitment (millions #)Under a target escapement0.030.060.090.0120.0150.01 5 9 13 17 21 25 29Yearsno lice0.10.30.5Discounted profit (?000 $) Figure 4.9. Recruitments and discounted profits at various mortality rates for pink salmon under a target escapement policy. The top graph shows the recruitments; and the bottom graph shows the discounted profits.  4.5.3 Productivity and Capacity Parameter The productivity parameter a  is presumed to be similar within a species over a defined spatial range, while the capacity parameter may vary depending on the size of area and the specific  dynamics  of  a  population  (Hilborn  and  Walters  1992).  However,  recent  studies indicate  that  ocean  climate  change  can  alter  the  productivity  parameter  of  a  population (Peterman et al. 2000; Beamish et al. 2004). Thus, for chum salmon, I test the robustness of our  j estimate of 4.9 by re-running the analysis using values of 5.1 and 4.7. Similarly, for pink salmon I test  j  set to 5.0 and 5.4 rather than the base value of 5.2. I also increase   103  and decrease the capacity parameter  j  by 10% and 20% for both salmon species. I use recruitment in scenario 1_no lice as an example to demonstrate these changes.  Results  suggest  recruitment  of  both  species  is  positively  related  to  productivity  and capacity,  though  the  magnitude  of  change  is  different.  For  capacity  parameters,  the magnitude of recruitment changes is at almost the same magnitude as capacity parameters regardless of management policies for the pink and chum salmon populations. However, for productivity parameters, the magnitude of recruitment changes is different  for chum and pink salmon and different management policies. Under a fixed exploitation rate, the magnitudes of recruitment changes for pink and chum salmon are similar, ranging from 14% to 20%, as well as for chum salmon under a target escapement. But, under a fixed exploitation rate, the magnitude of recruitment change for pink salmon is great, ranging from 70% to 80%. Likewise, the ecological and economic impacts of sea lice also co-vary with productivity and capacity changes, but the magnitude of these effects in both species is minor because recruitment, catches and discounted profits change in similar magnitudes in both scenarios.   4.5.4 Costs and Price In  the  base  scenario,  a  population  effect  is  added  into  the  cost  function  using  a  catch-population ration term. This catch-population ratio is an arbitrary value between 0 and 1. If this population effect is removed from the cost function, the total cost is simply a function of catch since the unit cost of fishing is assumed to be constant. As a result, the discounted profits  decrease  proportionally  for  chum  salmon,  and  they  become  negative  for  pink salmon because the unit cost of fishing is higher than the ex-vessel price. However, the economic  impacts  for  chum  salmon  are  almost  the  same  since  the  discounted  profits decrease in equal proportion for both scenarios.   It is assumed that ex-vessel prices remain unchanged over 30 years. This assumption is not likely  to  be  true  because  the  ex-vessel  prices  for  pink  and  chum  salmon  have  widely fluctuated over the years and trended downward gradually over the last decade due to the increasing  supply  of  farmed  salmon.  However,  I  believe  that  wild  salmon  fisheries  are   104  price inelastic in the short term, while they may be price elastic over the long term due to economic viability of catching and processing. If a salmon management goal is to sustain escapement, the catch is determined by the total numbers of returning individuals, not by ex-vessel prices. But if fishing cost is higher than the ex-vessel price, as in the case of pink salmon, this may affect fishers? incentives to go fishing. Fishers may go out to fish if they believe that the price would be higher or they may be compensated (e.g., if there is high demand  from  processors),  if  they  expect  less  catch  of  other  salmon  species  or  if  they expect a subsidy. Certainly, price is a very important driver of fishing  effort  and catch, which may have large ecological and economic impacts on fisheries and fishers.  4.6 Discussions and Conclusions  In this study,  I examine the potential ecological and economic impacts of salmon farm-derived sea lice on wild pink and chum salmon at a population level by incorporating sea lice induced mortality into age-structured models. I also explore how the combined effects of all environmental factors and human interventions may affect salmon populations and fisheries  by  incorporating  a  stochastic  variable  into  population-recruitment  models.  The initial populations used are equilibrium (i.e. populations without fishing). Thus, the salmon populations do not represent the current pink and chum salmon populations in the study area. All simulations are conducted based on this fundamental assumption. The following findings are drawn from the analyses:     Salmon  farm-derived  sea  lice  have  ecological  and  economic  effects  on  wild  salmon populations and fisheries, but to varying degrees. These effects are minor at low mortality rates (<20%), but can be substantial as mortality rates increase. For instance, populations change  marginally  when  the  mortality  rate  is  ?  20%  for  pink  and  chum  salmon;  the population  can  collapse  when  the  mortality  rate  is  higher  (60%  for  chum  and  30%  for pink). Other studies have demonstrated that the high level of lice infestation does pose a mortality risk to out-migrating salmon smolts (Bjorn and Finstad 2002; Gargan et al. 2002; Holst  et  al.  2003;  Morton  et  al.  2004;  Krko?ek  et  al.  2005  &  2006).  Increasing  the mortality level of migratory salmon smolts could have major impacts on the size of the   105  returning populations, contributing to overall wild salmon population declines in the region (Carr and Whoriskey 2004; McVicar 2004). The results from this study are consistent with these findings.   To  fishers,  the  decline  in  (or  collapse  of)  populations  means  less  (or  no)  catches  and economic returns; to society, it may mean extensive social and ecological costs because the society  may  need  to  compensate  fishers  for  their  losses,  as  well  as  bear  the  costs  for restoring the collapsed populations. The exact costs are unknown, but certainly it will be significant if populations collapse. Additionally, current pink and chum populations in the study area are in decline. The increased mortality due to salmon farm-derived sea lice may accelerate  these  declines,  especially  for  some  small  and/or  weak  stocks  when  they  are managed as one single mixed population.   The  ecological  and  economic  effects  of  sea  lice  from  farmed  salmon  on  wild  pink  and chum  salmon  are  similar  to  those  attributable  to  the  combined  effects  of  all  factors, including sea lice. This indicates that sea lice may have significant impacts on wild salmon than other factors. Wild salmon populations in BC have fluctuated considerably over time, and have seen dramatic decline since the late 1980s.  The decline, nevertheless, is believed to be due to a combination of factors, including overfishing, climate change (Mueter et al. 2005; Pyper et al. 2001&2002; Brooks 2005; Beamish et al. 2005 & 2006), destruction of freshwater habitats (Bradford and Irvine 2000), and salmon farming (e.g., Noakes 2002; Krko?ek et al. 2005). These factors have various degrees of importance in contributing to the decline of different wild salmon populations. This study reveals that on average the combined factors have greater impacts on pink and chum salmon populations than just the sea  lice  induced  mortality  factor.  However,  impacts  can  be  severe  when  the  sea  lice induced  mortality  rate  is  high.  A  high  rate  of  return  in  the  adult  spawning  population cannot be attained with very low survival at the early stage, regardless of survival at the adult stage.      106  The ecological and economic effects of sea lice vary greatly under different management policies.  A  target  escapement  policy  is  more  ecologically  promising  than  a  fixed exploitation  rate  because  its  priority  is  to  ensure  sufficient  recruitment.  A  fixed exploitation rate can drive an overexploited population to collapse although it may provide benefits  to  fishers  over  the  short  term.  In  stable  populations,  both  strategies  may  be appropriate.  However,  given  uncertainties  with  population  assessment,  environment change,  and  time-area-gear  control,  a  fixed  exploitation  rate  policy  may  be  a  more appropriate policy than a target escapement management policy (Walters and Parma 1996; Grout and Cass 2006). To an overexploited population, a target escapement management policy  is  more  desirable  from  an  ecological  perspective  than  a  fixed  exploitation  rate policy  because  overexploited  populations  can  rebuild  quickly  to  reach  the  target escapement level. Moreover, it can also result in the largest possible average catch over the long term. The exploitation rate used in this study for pink salmon is very high compared to  management  implemented  in  the  current  fisheries,  in  which  there  is  virtually  no commercial fishing, and the priority is given to aboriginal and recreational fishing (DFO 2006).    Changing the productivity parameter,a , and capacity parameter,  b , have slight ecological and  economic  effects  on  pink  and  chum  salmon.  Recent  studies  suggest  that  ocean conditions (e.g., temperature, current) exhibit a strong influence on salmon survival and productivity  (Peterman  et  al.  2000;  Beamish  et  al.  2004).  Increasing  productivity  and capacity can enhance recruitment to some extent. However, in this study, the changes of these  parameters  have  marginal  ecological  and  economic  effects  because  recruitment increases simultaneously in both cases.   Varying fishing cost and ex-vessel price may have extensive impacts on pink and chum salmon  through  changing  fishers?  behaviour.  Chum  salmon  have  a  relatively  high  ex-vessel  price,  which  exceeds  the  cost  of  fishing,  thus,  fishers  make  a  positive  economic return from fishing, and therefore fishing will continue. On the other hand, pink salmon have an ex-vessel price that is lower than fishing cost, thus, fishers have no incentive to go   107  fishing. Population size may change fishing cost to some degree, but a large catch is not necessary to generate a high economic return.   Pink salmon is more sensitive to the changes of parameter values and management policies than  chum  salmon.  Compared  to  chum  salmon,  pink  salmon  population  changes dramatically  when  sea  lice  induced  mortality  and  combined  environmental  factors  are incorporated. This is because pink salmon have a two year life cycle, and any change in mortality can extensively alter their population dynamics. However, because of this, pink salmon  are  also  capable  of  rebuilding  from  overexploitation  faster  than  chum  salmon (Walters and Korman 1999).   This study is the first attempt to examine the ecological and economic impacts of farm-derived sea lice on wild salmon from a population level. We have to recognize that the high mortality rate induced by sea lice has considerable ecological and economic impacts on salmon populations and fisheries. There is no doubt that the debate over the impacts of sea  lice  on  wild  salmon  will  continue,  and  salmon  farming  is  unlikely  to  alter  its development, at least over the short term. What should we do and what can we do? Salmon aquaculture in BC is a relatively new industry, thus, policy makers and the salmon industry should  learn  from  the  failed  and  succeed  experiences  of  their  counterparts  in  other jurisdictions.  The  precautionary  principle  should  be  adopted  and  an  appropriate management  scheme  and  policy  strategy  should  be  developed  in  order  to  improve  the husbandry  practice  of  salmon  farming,  and  minimize  sea  lice  problem  stemming  from salmon  farms.  As  mentioned  earlier,  this  study  is  based  on  a  number  of  simplifying assumptions  because  the  data  are  very  limited  both  in  accuracy  and  in  scale,  and  the simulations are based on populations at equilibrium, not current salmon populations in the study areas ? making findings conservative.        108  4.7 References Bakke, T.A. and P.D. Harris, 1998. Diseases and parasites in wild Atlantic salmon (Salmo salar) populations. Canadian Journal of Fisheries and Aquatic Sciences 55(Sup. 1): 247-266.  Beamish, R. J.,  J.T. Schnute, A.J. Cass, C.M. Neville and R.M. Sweeting, 2004. The influence of Climate on the Population and Recruitment of Pink and Sockeye Salmon from the Fraser River, British Columbia, Canada. Transactions of the American Fisheries Society 133:1396?1412.  Beamish, R.J., S. Jones, C-E. Neville, R. Sweeting, G. Karreman, S. Saksida and E. Gordon, 2006. Exceptional marine survival of pink salmon that entered the marine environment in 2003 suggests that farmed Atlantic salmon and Pacific salmon can coexist successfully in a marine ecosystem on the Pacific coast of Canada. ICES Journal of Marine Science 63: 1326-1337.  Beamish, R.J., C.M. Neville, R.M. Sweeting and N. Ambers, 2005. Sea lice on adult Pacific salmon in the coastal waters of Central British Columbia, Canada. Fisheries Research 76: 198-208.  Bigler, B.S., D.W. Welch and J.H. Helle, 1996. A review of size trends among North Pacific salmon. Canadian Journal of Fisheries and Aquatic Sciences 53(2): 455-465.   Bjorn, P.A. and B. Finstad, 2002. Salmon lice, Lepeophtheirus salmonis (Kroyer), infestation in sympatric populations of Arctic char, Salvelinus alpinus (L.), and sea trout, Salmo trutta (L.), in areas near and distant from salmon farms. ICES Journal of Marine Science 59:131-139.  Bradford, M.J. and J.R. Irvine, 2000. 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Fish. Res. Board Can. 32: 1777-1784.  Weitzman, M.L, 2001. Gamma discounting. American Economic Review 91(1): 260-271.            113  Chapter 5 Economic Analysis of Netcage Versus Sea-bag Production Systems for Salmon Aquaculture in British Columbia14  5.1 Introduction Conventional  open  netcage  systems  for  salmon  aquaculture  are  under  scrutiny  and criticism  partly  because  they  are  believed  to  generate  environmental  problems,  such  as waste discharge, spread of disease, and escaped fish. Such problems could have potential impacts on other resource users and on the surrounding marine environment (SAR, 1997; Volpe et al., 2000 & 2001; Naylor et al., 2003; Morton et al., 2004; Naylor et al., 2005; Krko?ek et al., 2006). In a netcage system, there are no solid barriers between the cages and the surrounding environment. Therefore, it can be difficult to effectively mitigate or prevent these environmental or ecological problems. Enclosed systems, such as land-based and sea containment systems, have been proposed and promoted for salmon aquaculture in response to the criticism of conventional open netcage systems. These enclosed systems physically  isolate  cultured  fish  from  the  surrounding  environment.  Some  environmental problems  created  by  netcage  systems  mentioned  earlier  can  be  prevented  or  minimized. For  example,  the  solid  waste  could  be  collected  and  treated,  and  wastewater  could  be filtered before released into the environment.   In British Columbia, a few trials using enclosed systems for salmon aquaculture have been conducted since 2003. These operations are directed by the British Columbia Provincial Government  and  supported  by  the  Federal  Government  with  tax  credits  given  by  the Canadian Customs and Revenue Agency (CCRA, 2004) under the program of Scientific Research and Experimental Development. The results from the first cycle of these trials were mixed. On the one hand, enclosed systems appear to be biologically, environmentally,                                                  14 A version of this chapter has been published. Liu, Y. and Sumaila, U.R.(2007) Economic analysis of Netcage versus sea-bag production systems for salmon aquaculture in British Columbia. Aquaculture Economics and Management 11(4):371-395.   114  and technically promising; on the other hand, they are financially demanding due to the high initial capital and operational costs entailed.  A  prerequisite  for  a  successful  aquaculture  venture  is  the  ability  to  generate  sufficient economic returns to cover all costs, including repayment of capital investment. It should also  satisfy  producer?s  expectations.  For  instance,  the  goal  of  a  subsistence  aquaculture activity  is  to  sustain  the  farmer?s  livelihood,  while  a  commercial  aquaculture  operation, like salmon aquaculture, aims to maximize its profits. In general, commercial producers will  not  engage  in  an  operation  that  does  not  make  a  positive  net  economic  return. Aquaculture  operations  require  natural  and  human  resources  to  generate  outputs  and services, while they also have potential to impose environmental costs on the environment and  natural  resources.  If  these  environmental  costs  are  not  incorporated  into  their production making process, the society as a whole has to bear them. Therefore, evaluating the feasibility of an aquaculture venture should also account for these environmental costs. In other words, a successful aquaculture operation should not only be financially profitable to an aquaculture producer, but it should also be socially and environmentally benign. Like any  economic  activity,  both  open  netcage  and  sea-bag  systems  for  salmon  aquaculture potentially  create  environmental  costs.  However,  anecdotal  evidence  suggests  that enclosed systems impose less external costs on other resource users and the surrounding environment  than  netcage  systems  in  terms  of  waste,  diseases,  escapees  and  interaction with  marine  mammals,  even  though  this  system  has  higher  initial  capital  and  operating costs. Thus, this research examines the profitability of netcage and sea-bag systems with and without environmental costs embedded on salmon aquaculture practice in BC.  5.2 Materials and Methods 5.2.1 Salmon Aquaculture Systems At present, two culture systems for salmon aquaculture are employed: open netcage and enclosed  systems,  including  sea-bag  and  land-based  systems.  Almost  all  commercially farmed  salmon  worldwide  are  produced  in  open  netcage  systems.  However,  enclosed   115  systems have received increasing interest for the last decade. Small- or experimental scale operations  in  have  been  carried  out,  such  as  land-based  systems  in  Iceland  and  sea-bag systems  in  Australia,  Canada  and  the  United  States  (pers.  comm.:  Clark,  Future  Sea  Technologies Ltd; G?stavsson, Holar University, Iceland; and Meilahn, MariCulture Ltd; SAR 1997).  Land-based systems for the salmon  grow-out stage have been shown to be economically unfeasible in British Columbia due to considerably high capital costs (SAR, 1997;  Walker,  AgriMarine  Industries  Inc.  pers.  comm.).  Thus,  land-based  systems  are excluded, and I only consider open netcage and sea-bag systems in this study.    Open Netcage System A typical open netcage system is made up of a steel or HDPE (High Density Polyethylene) frame, over which treated nets are stretched. A bird net covers the top of the netcage in order to prevent birds from diving for fish, and a predator net is strung beneath and around the  cage  in  order  to  deter  marine  mammals  from  attacking  fish.  Cages  are  arranged  in double rows, typically in sets of 6, 10, and 16, and they are anchored in the shelter inlets and bays near shore. The sizes of cages vary, ranging from 15 x 15 x 15 m to 40 x 40 x 20 m,  depending  on  production  capacity,  stage  of  operation  and  availability  of  operating capacity. The small cages (15 x 15 x 15 m) are preferred for the early stage and transition period, while larger cages (30 x 30 x 15 m) are preferred for the grow-out stage.  Sea-bag Systems The  sea-bag  system  analyzed  in  this  study  is  designed  and  produced  by  Future  Sea Technologies Inc. based in BC (http://www.futuresea.com/). The systems use soft (?non- ridged?)  bags,  which  float  on  the  sea  surface.  A  typical  module  of  a  sea  bag  system includes four bags (2,000 m3 each), a walkable flotation collar, 12 kWh electric pumps, 20 m intake depth, waste treatment (including four waste traps and one concentrator), four bag oxygen monitoring systems, bird nets and one harvest device (Clark, pers. comm.). Deep water  is  continuously  pumped  into  the  bags  for  replenishing  oxygen,  with  additional oxygen injected when large amounts of fish are confined. Solid waste is collected in the waste traps for disposal. Soluble wastewater is discharged into the sea hundreds of meters   116  away  from  the  systems,  mostly  without  treatment.  Each  aquaculture  operation  can  have one or more modules of sea-bag systems dependent on production capacity. However, sea-bag systems are still in the early stages of development for salmon grow-out in the open waters, and more trials on large commercial scales are needed to test their viability.   5.2.2 Production Capacity/Farm Size Based  on  salmon  aquaculture  operations  in  British  Columbia,  I  simulated  salmon aquaculture practices with three different production capacities (small, medium and large). The size of the cage for netcage system is different from the size of the bag for sea-bag systems. Assuming the size of netcage systems is about 12,000 m3 (30 x 30 x 15 m) per cage,  and  the  size  of  the  sea-bag  system  is  2,000  m3  per  bag.  The  average  fish  density through  the  whole  grow-out  stage  is  assumed  to  be  approximately  10  -  12  kg/m3  for netcage  systems,  and  30  -  35  kg/m3  for  sea-bag  systems.  The  density  assumptions  are conservative  for  netcage  systems  because  some  salmon  farmers  operate  at  higher  fish densities. Nevertheless, aquaculture operations face lower risks of susceptibility to disease problems  at  lower  fish  densities.  Based  on  the  sizes  of  cage  and  bag  and  fish  density assumed, on average, the production level of netcage systems is estimated at about 120 tonnes per cage, while the production level of the sea-bag system is set at about 60 tonnes per bag. Hence, the respective production capacities of the designed farm sizes from small, medium to large are 720, 1,200 and 1,920 tonnes, which correspond to 6, 10, and 16 cages and the number of sea-bag modules  of 3, 5 and 8, respectively. A single farmed salmon growth  cycle  is  estimated  to  be  between  16  -  24  months  dependent  on  location, temperature and feeding (Bj?rndal, 1990). For the analysis herein, I assume that a single marine growth cycle is 20 months (including fallowing period) for both systems, which implies that the two systems operate 12 cycles within a 20-year time horizon. Twenty year is the average tenure for an aquaculture licence in British Columbia. I assume that smolts are released into cages or sea bags at the same time in Year t , and salmon are harvested after  each  growth  cycle.  In  fact,  farmers  prefer  to  release  smolt  and  harvest  salmon  at different times of the year in order to take advantage of high market prices.   117  5.2.3 Economic Analysis  I  use  capital  budgeting  and  investment  appraisal  analyses  to  compare  the  financial performance  of  the  two  systems.  These  approaches  are  widely  used  in  aquaculture economic  studies  (e.g.,  Hatch  and  Tai,  1997;  Engle  et  al.,  2005;  Pomeroy  et  al.,  2006; Whitmarsh et al., 2006). First, I construct a capital budget analysis of both systems using biological  and  physical  components  of  salmon  aquaculture  in  the  two  systems,  and financial data associated with the costs and prices of farmed salmon. Due to the physical structural differences of the two systems, the capital costs differ between them.  Then, I apply investment appraisal analysis to examine the financial feasibility of the two systems using the net present value (NPV) criteria. The aquaculture operation bears costs and yields revenues  over  time,  and  the  future  revenues  and  costs  must  be  discounted  into  present values.  The  net  present  values  (NPVs)  from  the  aquaculture  operations  are  determined based on the expected revenues and the costs incurred over the time horizon of the project. In  NPV  analysis,  a  discount  rate  which  is  the  minimum  desired  rate  of  refund  for  the project  is  used.  If  the  NPV  is  positive,  it  indicates  that  the  project  is  financially worthwhile, and vice versa. Further, I also construct projected cash flow analysis to check the cash into and out of the operation in each growth cycle. Since some capital costs are replaced periodically, capital costs vary in different growth cycles.  In addition to NPVs, other financial/economic indicators, such as internal rate of  return (IRR), break-even analysis (i.e., break-even price and production) are  also applied.  IRR calculates the break-even rate of return from a capital investment. In other words, it is the rate when the NPV equals zero. If the discount rate used for calculating NPVs is below IRR,  it  indicates  that  the  NPV  is  positive,  vice  versa.  The  higher  an  IRR,  the  more desirable it is to invest. Break-even analysis usually calculates production level and sales price  at  the  break-even  point  at  which  sales  revenues  equal  production  costs.  Any production  level  or  sales  price  which  is  above  break-even  values  represents  increased profits.  Some  key  variables  in  our  analyses  face  different  degrees  of  uncertainties; therefore, sensitivity analyses are carried out to examine the robustness of the results of these variables. The following section will describe the estimates of initial capital costs, annual operating costs and revenues of both systems for each farm size.   118  Costs Licensing and Leasing Costs  To get a salmon aquaculture license in British Columbia, a number of fees must be paid. These  fees  include  a  tenure  application  fee,  an  aquaculture  license  fee,  environmental assessment and public consultation fee, and a fee for leasing and licensing crown land. The single  biggest  expense  is  environmental  assessment  and  public  consultation  fee,  which ranges  from  $50,000  to  $500,000  (Matthews,  Seafood  Development  Branch,  British Columbia  Ministry  of  Agriculture,  Food  &  Fisheries,  and  Williams,  Land  and  Water British Columbia Inc., pers. comm.). All the values in this paper are in Canadian dollars unless otherwise specified. This study assumes an average fee of $300,000. The estimates of other costs are based on the new British Columbia policy for finfish aquaculture that came into effect on April 1, 2004 (http://lwbc.bc.ca/02land/tenuring/aquaculture/finfish/). On average, the total cost of obtaining a salmon aquaculture license is estimated at about $315,386; $327,644 and $342,163 for the production capacities of 720, 1,200 and 1,920 tonnes, respectively. The same guidelines and application procedures are applied to both open netcage and sea-bag cultured systems (Matthews and Williams, pers. comm.). Thus, I assume that netcage and sea-bag systems face the same licensing and leasing costs at the same production capacity. A five-year licence is issued initially until the site is determined to be viable by the Provincial Government, and then a 20-year lease is offered which is the standard term for a lease (LWBC, 2004).    Initial Capital Costs   The capital investment costs include the costs of farm facilities on land and in the sea and associated supporting facilities. The facilities in the sea consist of netcage/sea bag systems, treated nets/bags, predator nets for marine mammals and sea birds, mooring or installation systems, feeding and monitoring systems, barge (floating house), storage, dock; while land facilities include the administration and general service building, storage building for nets and feed, and office supplies (e.g., telephone, computer, printer). The associated supporting facilities include boats, pumps, generators, and diving equipments. I applied 2004 prices for raw materials.  A 10% contingency is included in the capital cost to account for the uncertainty of cost items, in particular, the price fluctuation of components for the facilities.   119  This is the lower end of the 10 - 35% contingency proposed for land-based aquaculture facility  (SAR,  1997).  The  data  sources  for  cost  estimations  are  very  diverse,  including government documents, survey reports, personal interviews, and consultation with experts, and these are detailed in the notes under Table 5.1 & 5.2. These costs are incurred in Year 0 and replaced periodically based on their useful life. I assume that salvage values of cost items at the end of the project are zero.  Table 5.1. Estimated capital investment costs and annual depreciation for netcage systems by different cost items. Cost by size ($)  Annual depreciation by size ($) Cost item  720 t  1,200 t  1,920 t Useful life  (yrs)  720 t  1,200 t  1,920 t Netcage system1  450,000  750,000  1,200,000  10  45,000  75,000  120,000 Treated nets/bags2  75,000  135,000  236,000  4a  18,750  33,750  59,000 Predators nets3  35,000  64,000  126,000  4a  8,750  16,000  31,500 Anchor4  26,000  52,000  98,000  10  2,600  5,200  9,800 Mooring/Installation5  42,000  63,000  95,000  10  4,200  6,300  9,500 Feeding system6  125,000  150,000  180,000  10  12,500  15,000  18,000 Monitoring system7  10,000  15,000  25,000  10  1,000  1,500  2,500 Barge (floating house)8  50,000  50,000  50,000  20  2,500  2,500  2,500 Storage building (floating)9  30,000  30,000  30,000  20  1,500  1,500  1,500 Boats10  32,000  32,000  32,000  20  1,600  1,600  1,600 Boat motors11  13,000  13,000  13,000  10  1,600  1,600  1,600 Water pumps12  4,000  4,000  4,000  10  1,300  1,300  1,300 Generators13  14,000  21,000  28,000  10  400  400  400 Diving/lab equipment14  20,000  20,000  20,000  10  1,400  2,100  2,800 House/storage (on land)15  60,000  60,000  60,000  20  2,000  2,000  2,000 Office supplies16  20,000  20,000  20,000  5  3,000  3,000  3,000 Contingency (10%)  100,000  148,000  222,000    4,000  4,000  4,000 Grand Total  1,106,000  1,627,000  2,439,000    112,100  172,750  271,000  1 The costs of netcage systems are estimated using the information from WaveMaster Canada Ltd., and the costs of sea bag systems are estimated using the information from Future Sea Technologies Inc.; 2 & 3 The costs of treated/predator nets are estimated using the information from Cards Aquaculture Products Ltd.; 4 Anchor estimate is determined using information from WaveMaster Canada Ltd.; 5 Mooring/installation estimate is determined by using information for netcage systems from G3-Consulting (2000) and for sea-bag systems from Future Sea Technologies Inc.; 6 & 7 Feeding and monitoring system estimates are determined using information provided by the Norcan Electrical Systems Inc.; 7-16  The other estimates are based on data in BCACFB (1989) and adjusted with an increase of 10-20% of original values; a These items are replaced every two growth cycles (about 3.3 years) in netcage systems.   120  Table 5.2. Estimated capital investment costs and annual depreciation for sea-bag systems.  Cost by size ($)  Annual depreciation ($) Cost item  720 t  1,200 t  1,920 t  Useful life (yrs) 720 t  1,200 t  1,920 t Sea-bag system1  2,112,000  3,440,000  5,312,000  8b 264,000  430,000  664,000 Mooring/Installation5  56,000  70,000  83,000  8b  7,000  8,750  10,375 Feeding system6  125,000  150,000  180,000  10  12,500  15,000  18,000 Monitoring system7  10,000  15,000  25,000  10  1,000  1,500  2,500 Barge (floating house)8  50,000  50,000  50,000  20  2,500  2,500  2,500 Storage building (floating)9  30,000  30,000  30,000  20  1,500  1,500  1,500 Boats10  32,000  32,000  32,000  20  1,600  1,600  1,600 Boat motors11  13,000  13,000  13,000  10  1,300  1,300  1,300 Water pumps12  4,000  4,000  4,000  10  400  400  400 Generators13  28,000  42,000  56,000  10  2,800  4,200  5,600 Diving/lab equipment14  20,000  20,000  20,000  10  2,000  2,000  2,000 House/storage (on land)15  60,000  60,000  60,000  20  3,000  3,000  3,000 Office supplies16  20,000  20,000  20,000  5  4,000  4,000  4,000 Contingency (10%)  256,000  395,000  588,000         Grand Total  2,816,000  4,341,000  6,473,000    303,600  475,750  716,775  1 The costs of netcage systems are estimated using the information from WaveMaster Canada Ltd., and the costs of sea bag systems are estimated using the information from Future Sea Technologies Inc.; 2 & 3 The costs of treated/predator nets are estimated using the information from Cards Aquaculture Products Ltd.; 4 Anchor estimate is determined using information from WaveMaster Canada Ltd.; 5 Mooring/installation estimate is determined by using information for netcage systems from G3-Consulting (2000) and for sea-bag systems from Future Sea Technologies Inc.; 6 & 7 Feeding and monitoring system estimates are determined using information provided by the Norcan Electrical Systems Inc.; 7-16  The other estimates are based on data in BCACFB (1989) and adjusted with an increase of 10-20% of original values; b Replaced at the growth cycle of 5 and 10 (about 8.3 and 16.7 years, respectively), and only one fourth of system, including sea-bag, pumps, waste management device, etc are replaced, not the whole sea-bay system.   Annual Operating Costs  Operating  costs  are  expenses  incurred  during  aquaculture  operations  each  year.  They include variable and some elements of fixed costs. Variable costs consist of feed, smolts, labour,  energy,  maintenance/repairs,  drugs  and  transportation;  while  fixed  costs  include overhead  (administrative  and  general  service),  asset  insurance  premiums,  depreciation, annual  land  leasing  and  licensing  fee.  Due  to  commercial  confidentiality  and  lack  of records, it is very difficult to get first-hand data on operating costs directly from salmon   121  aquaculture  producers.  However,  Statistics  Canada  has  been  conducting  an  annual experimental survey nationwide since 1997, and its reported value added data are used to estimate  annual  operating  costs  for  netcage  systems.  These  data  cover  all  aquaculture sectors,  including  finfish  and  shellfish  aquaculture,  and  sources  of  output  and  product inputs. However, salmon aquaculture dominates the BC aquaculture industry accounting for 90 - 95% of the total values and production (DFO, 2005).   The survey data show that total operating costs declined from 1997 ? 2002, and increased in the years 2003 and 2004 (Figure 5.1). The declining trend seen from 1997 ? 2002 was mainly  because  of  increased  efficiency  of  feeding  and  feed  conversion  ratios,  increased supply  of  smolts,  increased  efficiency  in  fish  processing  and  distribution,  economies  of scale and better management practices (Bj?rndal, et al., 2002 & 2003). It should be noted that  the  cost  of  feed,  labour,  therapeutants  and  depreciation  showed  increasing  trends during the last few years. The reason for the increasing cost of feed may be the increasing demand  of  fish  feed  for  finfish  aquaculture  worldwide,  which  has  been  growing dramatically. The reason for the increasing costs of other factors may be associated with growing risks associated with operations. For instance, disease and parasite occurrence has been increasing  and this has become one of the limiting factors for the development of salmon aquaculture.  -1.02.03.04.05.06.07.01997 1998 1999 2000 2001 2002 2003 2004Cost ($/kg)Feed SmoltLabour DepreciationTotal cost Figure 5.1. Nominal costs of some input factors for salmon aquaculture in British Columbia from 1997 ? 2004.    122  Based on production inputs and total production, I calculated the cost per kg of production for each input item. Among production inputs, the costs of feed and smolts are determined by  using  the  production  of  finfish  aquaculture,  and  the  rest  is  estimated  by  using  the production of all aquaculture, including finfish and shellfish. The average cost of each item from 1997 ? 2004 is calculated and assumed to be the operating costs of netcage systems.   The operating costs of sea-bag systems are estimated based on a couple of data sets and related information, including a pilot project and operations for other species (e.g., trout) in other  geographic  locations.  The  pilot  project  was  a  joint  operation  between  Future  Sea Technologies  and  Marine  Harvest  for  salmon  grow-out  in  Salt  Spring  Island,  BC.  The results from the first cycle of operation showed a lack of technical efficiency with little economic  promise  due  to  logistics  and  technical  difficulties  (Clark,  pers.  comm.  and Dubreuil, 2003). A second operation is underway. However, the sea-bag system has been successfully used for trout farming and finfish hatcheries in Chile and Eastern Canada, as well as a full grow-out for salmon aquaculture in Tasmania (G3-Consulting, 2000). Further, the  operating  costs  between  cage  systems  and  sea  bag  systems  for  Coho  salmon  in  the Kisutch Inlet, British Columbia has also been assessed (G3-Consulting, 2000).   Based on these data and the estimated capital costs, I differentiate the costs between both systems  in  order  to  estimate  the  operating  costs  for  sea-bag  systems:  i)  depreciation  is estimated based on the capital investment for sea-bag systems; ii) labour cost is estimated to be 10% higher in sea-bag systems than those in netcage systems reflecting increased person-hours  for  cleaning  the  bags,  pumps,  waste  collections  and  maintaining  other facilities; iii) the amount of interest paid on loans for sea-bag systems is around 2.3 times that  for  netcage  systems  based  on  the  ratio  of  capital  costs  for  netcage  and  sea-bag systems;  iv)  energy  use  in  sea-bag  systems  is  assumed  to  be  five  times  higher  than  in netcage  systems  because  of  oxygen  consumption  and  fuel  consumption  for  pumping (oxygen & electricity) in sea-bag systems; it could be even higher if there is an inadequate supply  of  oxygen;  and  v)  other  inputs  are  assumed  to  have  the  same  costs  as  netcage systems. Table 5.3 summarizes annual revenues and operating costs for both systems.   123   Table 5.3. Summary of the enterprise budget over a single production cycle of netcage and sea-bag production systems.     Netcage system  Sea-bag system Production (tonnes)  720  1,200  1,920  720  1,200  1,920 Revenue @$4.47/kg (?00$)  3,218  5,364  8,582  3,218  5,364  8,582  Cost items (?00$)                Variable cost                     Feed  1,416  2,360  3,776  1,416  2,360  3,776        Smolt  222  369  591  222  369  591        Labor  489  815  1,304  538  897  1,435        Insurance  61  101  162  61  101  162        Energy  51  85  137  256  427  684        Maintenance  117  195  313  117  195  313        Professional  53  88  141  53  88  141        Therapeutants  54  91  145  54  91  145        Others  223  372  595  223  372  595    Total variable cost  2,686  4,476  7,164  2,940  4,900  7,842     Fixed cost                    Interest  93  156  249  215  358  572        Leasing/licensing  12  22  37  12  22  37        Depreciation  111  172  270  128  189  274    Total fixed cost  216  350  556  532  857  1,327 Environmental cost (EC)  39  55  78  -  -  - Grand Total cost without including EC  2,902  4,826  7,720  3,472  5,757  9,169 Grand Total cost with including EC  2,941  4,881  7,798  3,472  5,757  9,169  I  have  acknowledged  that  it  would  be  more  useful  if  the  operating  costs  are  estimated based on the quantity used and their market prices.  As it is almost impossible to do so, I have to use the operating costs estimated based on the financial surveys for the analyses. However, for the benefit of readers in the future, I have estimated the costs of major items, such as feed, smolt and labor, based on the quantity used and their price/wage (see Table 5.4  ?  5.6)  I  assumed.  The  costs  for  smolt  and  feed  are  very  close  between  the  two estimates, but there is a bigger difference for labor cost. In the financial survey, labor cost is  about  18%  of  total  variable  cost,  on  average,  which  is  reasonable.  In  this  estimate,  I calculated labor cost based on the possible number of employees, their weekly wages, and benefits paid for employees (15% of total wages). I divided employees into five categories: general worker, site supervisor, administrator, manager and consultants. Their wages are estimated based on the study conducted by Ralph Matthews (unpublished). In the analyses   124  below, these estimates for feed, smolt and labor are not used because their estimates were based on a number of assumptions, which are difficult to validate in BC. Instead, I had to use the results from annual surveys conducted by the government.   Table 5.4. Estimated Feed cost based on the quantity used and price Production capacity  Quantity* (tonnes)  Price ($/t)  Cost** (?00$) 720  900  1,200  1,350 1,200  1,500  1,200  2,250 1,920  2,400  1,200  3,600 *   The quantity of feed is estimated based on feed conversion ratio, 1.25; **   Additional 25% of feed cost is included as transport, temporary storage and special feed need, such as medicated feed and dyed feed.  Table 5.5. Estimated smolt cost based on quantity used and price Production capacity  quantity (?00#)  Price ($/smolt)  Cost* (?00$) 720  270  ~1.0  270 1,200  450  ~0.9  405 1,920  720  ~0.8  576 * It is estimated based on survival rate (90%), weight at harvest (3kg) and smolt weight (0.5kg/smolt).  Table 5.6. Estimated labour cost based on the numbers of employee assumed and their weekly wages.  Production capacity Type of employee  quantity (#) Wage ($/week) Cost (?00$) Worker  6  500  179 Supervisor  2  700  84 Administrator  2  500  60 Consultant@2,000/month    24 Manager  1  900  54 720     Total      401 Worker  8  500  239 Supervisor  2  700  84 Administrator  2  500  60 Consultant@2,000/month    24 Manager  1.5  900  81  1,200      Total      487 Worker  9  500  269 Supervisor  2  700  84 Administrator  2  500  60 Consultant@2,000/month    24 Manager  2  900  108 1,920     Total      544     125  Price and Revenue Over the years, the average prices for farmed salmon have fluctuated, with a steady decline mainly due to increasing supply and declining costs of production worldwide (Figure 5.2) (Bj?rndal  et  al.,  2002;  Knapp,  2005).  The  decline  has  accelerated  in  recent  years  with dramatically increasing supply from Chile (Bj?rndal et al., 2003; Sumaila et al., 2007). It is  predicted  that  the  price  for  farmed  salmon  will  continue  to  decline  if  farmed  salmon production  continues  to  increase  while  the  cost  of  production  keeps  declining  (Knapp, 2005). It should be noted that Chile is planning to double its current production level over the next five years. However, in addition to the production level and production cost, the market  price  of  farmed  salmon  is  also  affected  by  other  factors,  such  as  wild  salmon landings and development in international markets.   3.04.05.06.07.01988 1990 1992 1994 1996 1998 2000 2002 2004Price/Cost ($/kg)PriceProduction cost Figure 5.2. Nominal production cost and price of salmon aquaculture in British Columbia from 1988 ? 2005.  BC accounts for less than 5% of the total world farmed salmon production, and most of BC?s  salmon  products  are  exported  to  US  markets.  Thus,  BC  alone  has  no  power  to influence world prices for farmed salmon; in contrast, prices for farmed salmon in BC are determined  by  other  larger  players,  such  as  Norway  and  Chile.  Atlantic  salmon  (Salmo salar) is the dominant farmed species in BC, and it generally obtains slightly lower prices than  native  farmed  Pacific  salmon.  In  this  study,  the  average  market  price  for  farmed salmon in BC from 1997 ? 2004 is estimated and used, which is about $4.47 per kg in live weight.  The  market  price  is  calculated  by  dividing  the  farmgate  production  with  the farmgate value each year (DFO, 2005). The reason for using this average price instead the   126  current price is that current price is lower than operating cost, therefore is no need to conduct any further analysis. However, a sensitivity analysis using different prices is conducted. I assume that the market price for salmon will remain constant because it is difficult to predict the price changes in the future.   Environmental Costs Like  any  economic  activity,  both  systems  potentially  generate  environmental  costs  that may  be  imposed  on  other  resource  users  and  the  environment.  In  general,  the  major problems  causing  environmental  costs  in  netcage  systems  are  waste  discharge,  escaped fish, spread of disease and interactions with marine mammals, while sea-bag systems have little  or  none  of  these  problems  because  of  the  distinct  confinement.  The  types  and magnitudes of these environmental costs vary depending on a number of factors, such as location, production level, topography and management practice. It is difficult to directly capture  these  environmental  costs  due  to  the  complexity  of  the  impacts  and  the  lack  of market mechanisms. Several studies have estimated the environmental costs related to the waste discharge from netcage systems for salmon and from flow-through systems for trout (e.g., Folke et al., 1994; Smearman et al., 1997; EPA, 2002a&b). These studies indicated that the  environmental  costs  ranged  widely,  from  the  highest,  at  US$1.35,  to  the  lowest,  at US$0.032  per  kg  of  production.  These  estimates  applied  different  economic  methods, which generated different results. Some results, however, are debatable (e.g., Black et. al., 1997; Folke et al., 1997).   Instead of using environmental costs directly estimated from the damages associated with environmental  problems,  I  use  treatment  or  compliance  costs  of  implementing environmental  regulations  designed  by  the  authorities  as  a  proxy  in  this  study.  For example, the US Environmental Protection Agency (EPA) proposed a series of technical and  practical  options  as  regulatory  requirements  and/or  guidance  to  minimize  and/or prevent wastes from netcage systems for salmon aquaculture being produced in the natural environment. These regulatory requirements include feed management ? best management plans  (including  solid),  drugs  and  chemical  best  management  plans  and  active  feed monitoring.  The  cost  of  implementation  of  these  requirements  consists  of  capital  costs   127  (e.g.,  underwater  camera  with  computer  interfaces),  one-time  costs  (e.g.,  professional service and training), and operational and management costs (e.g., extra labour and time). The methodology and process of cost estimation can be found in EPA (2002a & 2002b). There is no regulation and cost for the facilities for salmon production less than 215 tonnes (i.e., < 475,000 pounds), and for the production levels larger than 215 tonnes, there are regulations and associated costs applied (EPA, 2002b).  The compliance cost changes with different production capacities. For instance, Engle et al. (2005) revealed that the different farm sizes bear different treatment costs. However, based  on  the  information  provided  and  costs  estimated  in  the  EPA?s  report,  I  have identified and estimated capital and operational costs for different production capacities. The  environmental  costs  are  estimated  to  be  about  $0.054,  $0.046  and  $0.041  for  the production capacities of 720, 1,200 and 1,920 tonnes, respectively (EPA, 2002b; Naylor et al., 2003). These costs are about 1% - 1.4% of total production costs. As mentioned earlier, sea-bag systems include waste collection and treatment devices and require a high level of maintenance,  thus,  sea-bag  systems  should  also  have  environmental  costs,  for  instance, implementing BMP plans. If I calculate environmental costs for sea-bag system based on the  estimates  for  netcage  system,  the  environmental  costs  for  sea-bag  systems  are negligible relative to their very high production costs. Therefore, I have to make another strong  assumption:  there  is  zero  compliance  cost  for  sea-bag  systems  in  terms  of  waste matter.   5.3 Results Tables 5.7&5.8 list the projected cash flows of selected growth cycles which represent the capital  replacement  costs.  Projected  20-year  (i.e.,  12  cycles)  cash  flows  indicate  that netcage systems at all production capacities have positive profit gains except when capital investment cost is first incurred or replaced in Cycles 1 and 6 (equivalent to Years 1 and 10, respectively). Sea-bag systems have net losses during Cycles 1, 5, 6 and 10 (roughly equivalent  to  Years  1,  8-10,  16),  and  they  have  positive  profit  gains  in  other  cycles. Further, the magnitude of positive profit gains is relatively small compared to net losses in   128  sea-bag systems. The higher production capacities have larger profit gains or losses than lower production capacities (Tables 5.7&5.8).   Table 5.7. Summary of projected 20-year cash flows in thousand Canadian dollars for netcage production systems    Cycle 1 (yr1-2) Cycle 3 (yr 5) Cycle 5 (~yr8) Cycle 6 (yr 10) Cycle 9 (yr 15) Cycle 12 (~yr 20)  (i) projected 20-year cash flow for netcage system with a production level of 720 tonnes Beginning cash balance  0  -569  +427  +317  +427  +317 Capital equipment purchase  -1,422  -129  -109  -723  -129  0 Cash receipts/sale income  +3,218  +3,218  +3,218  +3,218  +3,218  +3,218 Cash outflow/operating expenses  -2,792  -2,792  -2,792  -2,792  -2,792  -2,792 Ending cash balance  -995  +297  +317  -296  +297  +427  (ii) projected 20-year cash flow for netcage system with a production level of 1,200 tonnes Beginning cash balance  0  -535  +790  +510  +709  +510 Capital equipment purchase  -1,953  -219  -199  -1,091  -219  0 Cash receipts/sale income  +5,364  +5,364  +5,364  +5,364  +5,364  +5,364 Cash outflow/operating expenses  -4,655  -4,655  -4,655  -4,655  -4,655  -4,655 Ending cash balance  -1244  +490  +510  -381  +490  +709  (iii) projected 20-year cash flow for netcage system with a production level of 2,000 tonnes Beginning cash balance  0  -512  1,133  +772  +1,133  +772 Capital equipment purchase  -2,779  -382  -362  -1682  -382  0 Cash receipts/sale income  + 8,582  + 8,582  + 8,582  + 8,582  + 8,582  + 8,582 Cash outflow/operating expenses  -7,449  -7,449  -7,449  -7,449  -7,449  -7,449 Ending cash balance  -1,646  +752  +772  -548  +752  +1,133                       129  Table 5.8. Summary of projected 20-year cash flows in thousand Canadian dollars for sea-bag production systems    Cycle 1 (yr1-2) Cycle 3 (yr 5) Cycle 5 (~yr8) Cycle 6 (yr 10) Cycle 9 (yr 15) Cycle 12 (~yr 20)  (i) projected 20-year cash flow for sea-bag system with a production level of 720 tonnes Beginning cash balance  0  -3,030  -2,947  -3,497  -3,544  -3,994 Capital equipment purchase  -3,133  -20  -584  -219  -20  0 Cash receipts/sale income  +3,218  +3,218  +3,218  +3,218  +3,218  +3,218 Cash outflow/operating expenses  -3,167  -3,167  -3,167  -3,167  -3,167  -3,167 Ending cash balance  -3,081  -32  -533  -167  +32  +52  (ii) projected 20-year cash flow for sea-bag system with a production level of 1,200 tonnes Beginning cash balance  0  -4,500  -4,353  -5,199  -5,212  -5,911 Capital equipment purchase  -4667  -20  -930  -263  -20  0 Cash receipts/sale income  +5,364  +5,364  +5,364  +5,364  +5,364  +5,364 Cash outflow/operating expenses  -5,280  -5,280  -5,280  -5,280  -5,280  -5,280 Ending cash balance  -4,584  +64  -864  -179  +64  +84  (iii) projected 20-year cash flow for sea-bag system with a production level of 2,000 tonnes Beginning cash balance  0  -6550  -6305  -7584  -7504  -8538 Capital equipment purchase  -6,815  -20  -1411  -317  -20  0 Cash receipts/sale income  +8,582  +8,582  +8,582  +8,582  +8,582  +8,582 Cash outflow/operating expenses  -8,450  -8,450  -8,450  -8,450  -8,450  -8,450 Ending cash balance  -6,682  +112  -1,279  -185  +112  +132  The  NPVs  reported  herein  are  the  net  present  values  before  tax.  The  discount  rate  is assumed to be 7%. The reason for choosing this rate is because Nature Resources Canada generally uses a real discount rate ranging from 5% to 10%, and with a most frequently used rate of 7% for its analyses. Table 5.7 & 5.8 summarizes the financial performance of the two systems. For netcage systems, the NPVs at all production capacities are positive except the NPV is negative at the production capacity of 720 tonnes when environmental cost  is  included.  The  NPVs  are  greater  at  higher  production  capacities.  For  sea-bag systems, all the NPVs are negative. The reasons for the differences in NPVs between two systems are because netcage system has a relatively low capital cost, and the market price is greater than its annual operating cost; while sea-bag system has a very high capital cost, and the market price is lower than its annual operating cost. When environmental costs are included,  the  NPVs  for  netcage  systems  are  considerably  reduced,  but  most  are  still positive. It indicates that the investment in netcage systems is still financially worthwhile when environmental costs are incorporated.    130  Furthermore, netcage systems have lower breakeven prices and production levels than sea-bag  systems  regardless  of  whether  environmental  costs  are  incorporated  or  not.  These results  are  consistent  with  their  respective  annual  operating  costs  and  the  market  price. Thus, sea-bag systems need to obtain higher market prices to cover their high operating costs, or higher production levels for covering the capital costs. All the IRRs for netcage systems are positive and greater than the discount rate (7%) except the IRR is lower than 7%  at  the  production  capacity  of  720  tonnes  when  environmental  cost  is  included.  The IRRs  are  lower  when  environmental  costs  are  included.  The  IRRs  are  higher  at  larger production capacities. Sea-bag systems incur negative IRRs at all production capacities.   In summary, the results from NPVs, break-even, IRR and cash flow analyses demonstrate that  open  netcage  systems  have  better  economic  performance  than  sea-bag  systems whether  environmental  costs  are  incorporated  or  not.  They  further  suggest  that  the investment in netcage system is financially worthwhile, and the higher financial benefits are achieved at higher production capacities. In contrast, the investment in sea-bag system is not financially worthwhile at any production capacity.   Table 5.9. Financial performance of netcage and sea-bag systems.  Production capacity (tonnes) 720 t  1,200 t  1,920 t Economic indicators  Netcage  Sea-bag  Netcage  Sea-bag  Netcage  Sea-bag NPV without EC (million$)  0.23  -4.62  0.93  -6.84  2.08  -9.90 NPV with EC (million$)  -0.08  -4.62  0.49  -6.84  1.46  -9.90 Breakeven price without EC ($/kg)  4.03  4.82  4.02  4.80  4.02  4.77 Breakeven price with EC ($/kg)  4.09  4.82  4.07  4.80  4.06  4.77 Breakeven production without EC (t)  649  737  1,080  1,224  1,727  1,952 Breakeven production with EC (t)  658  737  1,092  1,224  1,744  1,952 IRR without EC (%)  10.1  -  15.8  -  20.5  - IRR with EC (%)  5.9  -  11.8  -  16.8  -  5.4 Sensitivity Analysis Salmon aquaculture is a relatively complex economic activity, which involves biological, environmental and economic factors. Thus, there are a number of uncertainties involved   131  with these factors.  Although salmon aquaculture producers have a lot of control over the production process, there are still certain factors that are beyond their control. For instance, feed price, salmon price, environmental impacts, and unforeseen diseases are difficult to predict  or  control.  Some  parameters  are  crucial  and  may  have  substantial  impacts  on aquaculture investments and operations, such as operating costs, market prices, discount rates and environmental costs. As mentioned earlier, since I have made some assumptions in  the  analyses,  I  therefore  undertook  sensitivity  analyses  to  test  the  robustness  of  the results to key parameter changes.  5.4.1 Discount Rate Choosing an appropriate discount rate is crucial in using the NPV method for investment feasibility  analysis  because  the  future  economic  returns  on  the  investment  have  to  be discounted into present values in order to capture the time value and risks of investments. When discount rates are higher, the NPVs decline considerably because high discount rates value future benefits less than low discount rates (Sumaila and Walters, 2005). I find that no matter what discount rate is used, the NPVs for sea-bag systems are always negative because of high capital costs. The NPVs for netcage systems are higher at lower discount rates. The NPVs are higher for larger production capacities under the same discount rates. The differences in NPVs between production capacities become smaller when the discount rates increase. The NPVs become negative faster at lower production capacities, and vice versa. The NPVs are approaching zero at the discount rates of 10.1%, 15.8% and 20.5% for  respective  production  capacities  of  720  t,  1,200  t  and  1,920  t  (Figure  5.3).  These discount  rates  are  consistent  with  the  IRRs  mentioned  earlier.  In  general,  aquaculture producers adopt a higher discount rate because investment in this sector is very risky, and therefore  they  require  a  risky  premium.  However,  there  are  many  ways  to  capture  risk factors, and the use of discount rates in aquaculture investment is one of these ways.    132  -1.002.003.004.000 1 3 5 7 9 11 13 15 17 19 21 23Discount rate (%)production_720 tproduction_1,200 tproduction_1,920 tNPVs (million$) Figure 5.3. Net present values for netcage systems at different discount rates for different production capacities.  5.4.2 Feed Costs Due  to  increased  demand  for  fishmeal  and  fish  oil  and  the  stagnant  availability  of  the resources used for these products, fishmeal and fish oil prices are expected to rise in the future. A 3%, 5%, 10%, 15% and 20% increase in the feed cost was simulated while the costs of other inputs remained constant. In contrast, due to the technological improvement of feed formulation, fishmeal and fish oil have been replaced at a smaller amount by non-fish protein, such as soy beans (Tacon, 2004). Some believe that the use of non-fish protein sources in feed may decrease feed costs. Thus, a 1%, 3%, 5%, 10% and 20% decrease in feed cost was also performed.   For netcage systems, the results show that the NPVs remain positive when the feed cost increases by less than 3%. When increased by 3%, 5% and 10%, the NPV turns negative at the  production  capacities  of  720,  1,200  and  1,920  tonnes,  respectively.  NPVs  increase slowly when feed costs decrease by less than 5%, and increase dramatically when feed cost decreases  by  over  5%.  Overall,  increases  or  decreases  in  feed  cost  have  considerable effects on the financial performance of netcage systems, as expected because feed cost is the  single  greatest  cost  for  salmon  aquaculture,  and  it  accounts  for  40%  -45%  of  total operating cost. Further, the increases or decreases in feed cost have much larger impacts on lower production capacities than on higher production capacities (Figure 5.4). For sea-bag systems, NPVs are still negative when feed cost decreases by 20%.  It indicates that the   133  gains from decreases in feed cost do not offset the high capital and operating costs for sea-bag systems. 0.01.02.03.04.05.0-10 -5 -3 -1 0 1 3 5 10Feed cost  (%)Production_720 tProduction_1,200 tProduction_1,920 tNPVs (million$) Figure 5.4. Net present values for netcage systems when feed costs increase and decrease in the percentage of feed cost for different production capacities.    5.4.3 Environmental Costs Assumed environmental costs of $0.054, $0.046 and $0.041 per kg are used in the base analyses for netcage systems, which is about 1.2% of the total production costs, on average. Because  I  have  not  estimated  environmental  costs  directly  from  salmon  aquaculture,  I apply a series of environmental costs of $0.05, $0.07, $0.10, $0.13, $0.15, $0.20, $0.25 and $0.30 per kg of farmed salmon for netcage systems. In terms of proportion of operating cost,  these  comprise  1.2%,  1.7%,  2.5%,  3.2%,  3.7%,  5.0%,  6.2%,  and  7.4%  of  total operational costs, respectively. The results reveal that all NPVs for netcage systems decline when  environmental  costs  increase.  The  NPVs  turn  negative  when  environmental  costs increase to $0.05/kg (1.2%) for a production capacity of 720 tonnes, and $0.10/kg (2.5%) for production capacity of 1,200 tonnes and $0.13 (3.2%) for the production capacity of 1,920 tonnes. It implies that an environmental cost of 3.0% of total production cost will make salmon production economically infeasible (Figure 5.5).   134  0.00.51.01.52.00.00 0.05 0.07 0.10 0.13Environmental cost ($/kg)Production_720 tProduction_1,200 tProduction_1,920 tNPVs (million$) Figure 5.5. Net present values for netcage systems under different environmental costs for different production capacities.  5.4.4 Market Price In the base analysis, I assumed that both systems obtain the same market price for their products.  However,  some  consider  the  salmon  produced  in  enclosed  systems  as environmentally friendly products, which may command a price premium (Sumaila et al., 2007).  For  instance,  the  salmon  produced  in  the  land-based  facility  at  Cedar,  BC  was labelled as ?Eco-Salmon?, for which some consumers were willing to pay a price premium, 10%  to  20%  higher  than  the  market  prices  achieved  by  salmon  produced  in  netcage systems  (Walker,  pers.  comm.).  Therefore,  I  assume  that  salmon  produced  in  sea-bag systems can also command a price premium. To test this effect, I ran our models under the assumptions of prices 10%, 15% and 20% higher than market price for sea-bag produced salmon, or prices of $4.92, $5.14, and $5.37 per kg, respectively. The results revealed that the NPVs for sea-bag systems are still negative when a less than 15% price premium is assumed, but the NPVs turn positive when a 20% price premium is achieved. The NPVs are greater at high production levels under the same price premium. Therefore, for sea-bag systems to achieve positive NPVs, a price premium of at least 20% higher than the market price for netcage systems would need to be obtained (Table 5.10).   As mentioned earlier, the salmon price used in the base analysis is price averaged across the period of 1997-2004. The yearly price during this period is either higher or lower than   135  this averaged price, but always within  ? 10%. Thus, I reduced the market price by 10% for netcage systems, to $4.02/kg, which is lower than the break-even price. The results show that,  under  these  assumptions  all  NPVs  turn  negative  whether  environmental  costs  are included or not.  5.4.5 Feed Conversion Ratio and Survival Rate  Compared to open netcage systems, closed sea-bag systems could theoretically improve feed conversion ratio (FCR) and survival rate due to the improved environment for salmon growth  and  management  according  to  the  producer?s  suggestions  (Clark,  pers.  comm.). Thus,  I  assume  that  the  FCR  for  sea-bag  systems  is  around  1.20  compared  to  1.25  for netcage systems; survival rate is 92% for sea-bag systems compared to 90% for netcage systems.  There  currently  are  no  data  from  commercial  farmers  to  substantiate  this assumption.  However,  trout  farmers  from  Chile  provided  some  positive  results  in  the freshwater environment (Clark, 2004, pers. Com). I evaluated this scenario by adjusting the feed cost and smolt cost for sea-bag systems based on the assumed FCR and survival rates. The NPVs for sea-bag systems improved slightly compared to the results in the base analysis, and were still negative. Thus, the improved levels of FCR and survival cannot compensate for the lower NPVs (Table 5.10).  5.4.6 Growth Cycle In  the  base  case  analysis,  I  assumed  that  the  growth  cycles  were  20  months  for  both systems. Salmon in sea-bag systems may have short growth cycles without the need for that longer fallowing period required in open netcage systems. Here, I assume that sea-bag systems reduce their growth cycles from 20 months to 18 months. The results showed that the NPVs for sea-bag systems are even lower than in the base analyses (20 months). This is expected because their operating costs per unit production (kg or tonne) are higher than the market price (Table 5.10).      136  Table 5.10. Net present values under different values of input factors for sea-bag systems.  Production capacity (tonnes) Value changes of inputs  720 t  1,200 t  1,920 t The base NPVs at the market price ($4.47/kg) Netcage without EC  0.23  0.93  2.08 Netcage with EC  -0.08  0.49  1.46 Sea-bag   -4.62  -6.84  -9.90  (i) Price premium for sea-bag system 10% ($4.92/kg)  -2.31  -2.62  -3.13 15% ($5.14/kg)  -0.83  -0.49  0.28 20% ($5.37/kg)  0.45  1.64  3.69  (ii) FCR/ survival rate 1.20/0.92  -4.14  -6.03  -8.60  (iii) Growth cycle 18 month  -4.66  -6.89  -9.96  (iv) Combination (FCR + survival rate + growth cycle + price premium) 10% ($4.92/kg)  -1.45  -1.55  -1.42 15% ($5.14/kg)  -0.11  0.69  2.17 20% ($5.37/kg)  1.24  2.93  5.75  5.4.7 A Combination of Input Factors Input factors for sea-bag systems were combined into a new scenario as follows: (i) the FCR  is  improved  from  1.25  to  1.20;  (ii)  survival  rate  increases  from  0.90  to  0.92;  (iii) growth cycle is shortened from 20 months to 18 months; and (iv) the price premium for sea-bag products are 10%, 15% and 20% higher than the market price received by netcage systems. Table 5.10 summarizes the results of changing different input factors (i.e., price, FCR, survival rate and growth cycle). The NPVs are still negative with those combined factors. When a 15% price premium is assumed together with other factors, the NPVs for sea-bag  systems  are  close  to  those  for  netcage  systems  when  environmental  costs  are included. When a 20% price premium is assumed along with the improved FCR, survival rate and growth cycle, the NPVs at all production capacities turn positive, and they become much  higher  than  the  NPVs  for  netcage  systems  when  environmental  costs  are  not incorporated (Table 5.10).   137  Fish Density The  fish  density  used  in  the  base  analysis  was  10-12  kg  per  cubic  meter  for  netcage systems. This density assumption may be a lower that used by some producers who operate at higher fish densities. Thus, I tested the effects when fish densities increased to 20 kg/m3. As a result, the capital investment cost decreased by 15%, 23% and 25% for the production capacities of 720, 1,200 and 1,920 tonnes, respectively. The NPVs increased by 65%, 49% and 39% for the production capacities of 720, 1,200 and 2,000 tonnes, respectively.   5.5 Discussions and Conclusions In  this  study,  I  have  compared  the  economic  performance  of  open  netcage  and  sea-bag systems  with  and  without  incorporating  environmental  costs.  The  main  economic indicators used included the NPV, IRR, cash flow, break-even price and production level. I also conducted a sensitivity analysis for some key variables to test the robustness of the results. The key findings from this study are:  ?  Under the same operating conditions, netcage systems have much better financial performance than sea-bag systems; ?  The NPVs for netcage systems decreased considerably when environmental costs are  included;  and  netcage  systems  perform  better  economically  than  sea-bag systems when moderate environmental costs (<$0.13/kg) are included; ?  The higher the production capacity, the better the economic performance of netcage systems; ?  Market prices have substantial impacts on the NPVs for both systems; when the price  of  salmon  declines  by  10%,  netcage  systems  achieve  negative  NPVs  at  all production capacities, sea-bag systems achieve positive NPVs when they enjoy at least a 20% price premium; ?  Feed cost, fish density, environmental cost and discount rate have great effects on the economic performance of net-cage systems;  ?  Feed  conversion ratio, survival rate, and  growth cycle have minor effects on the financial performance of sea-bag systems.     138  To summarize, investment in netcage systems is more financially worthwhile than in sea-bag  systems  when  environmental  costs  are  modest.  Investment  in  sea-bag  systems  is worthwhile only when the price premium is at least 15% higher than the base price. When the market price declines by 10%, investment in netcage systems is also not financially worthwhile.  Given  current  slumping  market  prices  for  farmed  salmon,  it  is  difficult  to achieve positive financial returns for either system. For instance, in 2002, 2003 and 2004, salmon  prices  were  below  the  operating  costs.  Sea-bag  systems  may  be  more environmentally friendly than netcage systems, but they are more financially demanding given the high capital and operating costs. Salmon farmers have no incentive to adopt sea-bag  systems  without  regulatory  and  market  incentives.  Sea-bag  systems  are  still  in  the early  developmental  stage,  with  more  trials  and  research  needed,  in  particular,  on  large commercial scale closed systems. Open netcage systems are well established, and are still widely used for salmon aquaculture worldwide.   It should be noted that this research is based on data from salmon aquaculture operations in British  Columbia,  some  assumptions  had  to  be  made  where  data  were  unavailable. Although this study has significance to other salmon producers and finfish enterprises in general,  the  quantitative  results  may  be  extrapolated  only  with  careful  assessment  of assumptions to other operations in other geographical areas. However, this study does have some  common  implications/conclusions,  which  may  be  applicable  to  salmon  farming  in other jurisdictions, even for other finfish aquaculture.          139  5.6 References BCACFB, 1989. Estimated Costs and Returns for Chinook Salmon Production in the Campbell River Area. Aquaculture and Commercial Fisheries Branch, British Columbia Ministry of Agriculture and Fisheries, Victoria, BC, 25p.  Black, E., R. Gowen, H. Rosenthal, E. Roth, D. Stechy and F.J.R. Taylor, 1997. The costs of eutrophication from salmon farming: implications for policy?a comment. Journal of Environmental Management 50(1):105-109.  Bj?rndal, T., 1990. The Economics of Salmon Aquaculture. Blackwell Scientific Publications, London, 118p.  Bj?rndal, T., G.A. Knapp, and A. Lem, 2003. Salmon: a study of global supply and demand. SNF/Centre for Fishery Economics Series/Report no.: 92. 154p.  Bj?rndal, T., R. Tveter?s and F. Asche, 2002. The development of salmon and trout aquaculture. In Paquotte, p., C. Mariojouls and J. Young (Eds): Seafood Market Studies for the Introduction of New Aquaculture products. Cahiers Options M?diterran?ennes 59: 101-115.  CCRA, 2004. Scientific Research and Experimental Development Program: Supporting Canadian Innovation. Canada Revenue Agency, available at http://www.cra-arc.gc.ca/taxcredit/sred/menu-e.html, accessed in August 2004.  DFO, 2005. Statistical Services - Aquaculture. Fisheries and Oceans Canada, available at http://www.dfo-mpo.gc.ca/communic/statistics/aqua/index_e.htm, accessed in November 2005.  Dubreuil, M., 2003. Economic Performance of Atlantic Salmon in the Sea System II Relative to Conventional Netcages. Future Sea Ltd and Ministry of Agriculture, Food and Fisheries Province of British Columbia, 3p.  Engle, C.R., S. Pomerleau, G. Fornshell, J.M. Hinshaw, D. Sloan and S. Thompson, 2005. 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The costs of eutrophication from salmon farming - implications for policy. Journal of Environmental Management 40(2): 173-82.    140  G3-Consulting, 2000. Salmon Aquaculture Waste Management Review & Update. Environment & Resource Management, Pollution Prevention & Remediation Branch, BC Ministry of Environment, Lands and Parks, Burnaby, BC, 141p.  Hatch, U. and C.F. Thai, 1997. A survey of aquaculture production economics and management. Aquaculture Economics and Management 1(1): 13-27.  Knapp, G., 2005. Implications of aquaculture for wild fisheries: the case of Alaska wild salmon. Presentation for the Bevan Sustainable Fisheries Lecture Series, University of Washington, Seattle, Washington, Feb. 10. Available at http://www.iser.uaa.alaska.edu/iser/people/knapp/Knapp_UW_Bevan_Series_Salmon_Lecture_050210.pdf  Krko?ek, M., M.L. Lewis, A. Morton, L.N. Frazer and J.P. Volpe, 2006. Epizootics of wild fish induced by farm fish.  Proceedings of the National Academy of Sciences 103: 15506-15510.  LWBC, 2004. Aquaculture Policy. Land and Water British Columbia Inc., 116p.  Morton,  A.,  R.  Routledge,  C.  Peet,  and  A.  Ladwig,  2004.  Sea  lice  (Lepeophtheirus  salmonis) infection rates on juvenile pink (Oncorhynchus gorbuscha) and chum (Oncorhynchus keta) salmon in the nearshore marine environment of British Columbia, Canada. Canadian Journal Fishery and Aquatic Science 61: 147-157.  Naylor, R.L., J. Eagle and W.L. Smith, 2003. Salmon Aquaculture in the Pacific Northwest - a Global Industry. Environment 45(8): 19-39.  Naylor, R., K. Hindar, I.A. Fleming, R. Goldburg, S. Williams, J.P. Volpe, F. Whoriskey, J. Eagle, D. Kelso and M. Mangel, 2005. Fugitive salmon: Assessing the risks of escaped fish from net-pen aquaculture. Bioscience 55(5): 427-437.  Pomeroy, R.S., J.E. Parks, and C.M. Balboa, 2006. Farming the reef: Is aquaculture a solution for reducing fishing pressure on coral reefs? Marine Policy 30: 111-130.  SAR, 1997. Salmon Aquaculture Review. Environmental Assessment Office, Victoria, BC, Canada, Vol 3, 201p.  Smearman, S.C., G.E. D?ouza and V.J. Norton, 1997. External costs of aquaculture production in West Virginia. Environmental and Resource Economics 10(2): 167-75.  Sumaila, U.R., 2005. Differences in economic perspectives and the implementation of ecosystem-based management of marine resources. Marine Ecology Progress Series 300: 279-282.  Sumaila, U.R. and C. Walters, 2005. Intergenerational discounting: a new intuitive approach. Ecological Economics 52 (2): 135-142.  Sumaila, U.R., J.P. Volpe, and Y. Liu, 2007. Potential economic benefit from sablefish farming in British Columbia. Marine Policy 31(2): 81-84.  Tacon, A.G.J, 2004. Use of fish meal and fish oil in aquaculture: a global perspective.  Aquatic Resources, Culture and Development 1(1): 3-14.    141  Volpe, J.P., B.R. Anholt and B.W.Glickman, 2001. Competition among juvenile Atlantic salmon (Salmo salar) and steelhead (Oncorhynchus mykiss): relevance to invasion potential in British Columbia. Canadian Journal of Fisheries and Aquatic Sciences 58(1): 197-207.  Volpe,  J.P.,  E.B.  Taylor,  D.W.  Rimmer  and  B.W.  Glickman,  2000.  Evidence  of  natural reproduction  of  aquaculture-escaped  Atlantic  salmon  in  a  coastal  British  Columbia  river. Conservation Biology 14(3): 899-903.   Whitmarsh, D.J., E.J. Cook and K.D. Black, 2006. Searching for sustainability in aquaculture: an investigation into the economic prospects for an integrated salmon-mussel production system. Marine Policy 30(3): 293-298.                                           142  Chapter 6 Conclusions, Policy Implications and Recommendations15   6.1 Summary This dissertation has addressed issues related to the management and economics of salmon aquaculture  with  an  emphasis  on  environmental  impacts.  The  overall  objectives  of  this dissertation are to examine the economic consequences of environmental issues associated with  salmon  aquaculture,  and  to  explore  policy  implications  and  recommendations  for reducing  environmental  impacts  and  the  future  development  of  salmon  aquaculture.  A number  of  analyses  associated  with  salmon  aquaculture  are  conducted.  In  chapter  1, salmon aquaculture and its associated environmental and economic impacts are reviewed. The  economic  concept  of  externality  and  methods  or  techniques  for  measuring environmental costs are also discussed. Chapter 2 assesses whether salmon aquaculture can continue  growing  at  the  current  pace  as  many  have  optimistically  predicted.  Chapter  3 estimates pollution abatement costs from a production economic perspective. In Chapter 4, whether sea lice from salmon farms have ecological and economic impacts on wild salmon populations  and  fisheries  is  examined.  A  comparative  analysis  of  netcage  vs  sea-bag production  systems  for  salmon  aquaculture  is  conducted  in  Chapter  5.  Together,  these analyses yield a relatively comprehensive picture of salmon aquaculture.   In the last chapter of this dissertation, first current environmental management strategies and policies for reducing environmental impacts are described; then key findings for each of  the  previous  chapters  are  summarized,  and  policy  implications  and  recommendations emerging from the findings in each chapter are explored; and finally conclusions are drawn based on the findings and policy implications derived from the previous chapters.                                                    15 A version of this chapter will be submitted for publication. Liu, Y., Chuenpagdee, R. and Sumaila, U.R. Salmon Aquaculture and the Environment: Economic Perspectives for Policy Development.   143  6.2 Current Environmental Management Strategies and Policies Current environmental management strategies and policies for salmon aquaculture are in the forms of a series of environmental regulations, management planning and monitoring procedures.  The  formulation  and  implementation  of  these  environmental  regulations  are complex.  Ecological,  environmental,  social-economic  and  political  aspects  must  be balanced during the formulation process. Aquaculture, in general and salmon aquaculture, in particular is managed and governed by multi-layered authorities, including international, national, provincial or state, regional and local agencies.   At the international level, the Food and  Agriculture Organization of the  United Nations (FAO) is the leading agency. The Code of Conduct for Responsible Fisheries in Article 9 specifically  presents  guidelines  for  the  development  and  management  of  aquaculture. Regional  organizations  such  as  the  North  Atlantic  Salmon  Conservation  Organization (NASCO)  and  the  European  Union  (EU)  have  also  given  specific  guidance  on  salmon farming. For instance, NASCO signed the famous ?Oslo Resolution? in 1998, aiming the Resolution by the Parties to the Convention for the Conservation of Salmon in the North Atlantic Ocean to Minimize Impacts from Salmon Aquaculture on the Wild Salmon Stocks. The EU has implemented special requirements for aquaculture in its Common Fisheries Policy. However, salmon aquaculture is directly regulated at national, provincial and local levels, involving different government agencies.   At the national and regional level, the authorities involved in managing and regulating the salmon  aquaculture  industry  may  include  the  Ministry  of  Fisheries  (or  Department  of Fisheries and Oceans Canada), the Ministry of Environment, the Ministry of Agriculture, and  other  departments  associated  with  salmon  aquaculture.  These  authorities  are responsible  for  making  aquaculture  regulations  and  laws.  Fishery  Acts  and  Aquaculture Acts  are  the  main  legislative  instruments  for  formulating  most  regulations  and  laws  for salmon aquaculture (FAO 2007).  Although  different  countries  and  regions  have  their  own  regulations,  monitoring procedures and guidelines, they all have concentrated on the same environmental issues or   144  problems,  including:  i)  siting  criteria;  ii)  waste  management  and  regulation;  iii)  escape prevention and response plan; and iv) disease and parasite prevention and control, and uses of chemicals and drugs.   Siting  Criteria:  First, the sites must be physically suitable for salmon aquaculture.  For instance, water quality, tide, current, access to the freshwater and roads need to be met. Second,  a  guideline  describing  a  number  of  environmental  and  social  criteria  or requirements is used to determine whether to issue a license or allow aquaculture operation to continue. In the case of British Columbia, such environmental criteria include minimum distance from First Nation?s reserves, salmon streams, herring spawning grounds, shellfish beds, intensive areas for marine mammals, ecological reserves, protected parks and areas and  existing  farms.  A  farm  also  cannot  be  sited  in  an  important  commercial  and recreational fishing ground, and/or a cultural or heritage significant area (MAFF 2003a). In Norway, a number of the National salmon watercourses and fjords have been established to protect wild salmon stocks. New licenses cannot be located in or existing salmon farms have to be relocated from these salmon watercourses and fjords  (S?nvisen 2003; Porter 2005).  Waste Management and Regulation: The waste control regulations may include waste discharge  standards,  stocking  requirements,  domestic  sewage  requirements,  best  waste management  practices,  monitoring  and  reporting,  remediation,  fees  and  penalties.  There are also requirements for reporting quantities and types of feed, chemicals and drugs used. Amongst  these,  regular  monitoring  (or  inspection)  and  reporting  are  mandatory  for  all producers  (Dow  2004).  Different  countries  and  regions  have  specific  requirements  for these regulations and monitoring. For instance, Norway has developed and implemented a Modelling-Ongrowing fish farms-Monitoring system (MOM) since 1997 (Maroni 2000). The frequency of monitoring depends on the environmental quality in the sediments under the farms and water body near the farms. Further, Norway also imposes limitations on fish density per production and water volume per licence (Dow 2004).    145  Escapees:  The  management  and  regulation  for  escapees  include  installation  and maintenance  of  all  facilities  and  staff  training,  prevention  plan  (i.e.,  site  inspection), recording, best management practice plan and response plan for escape prevention (MAFF 2002). Fines may be charged if salmon farms violate the regulations or laws. For serious cases,  licenses  may  be  suspended.  In  addition  an  intensive  monitoring  and  inspection program is needed (Dow 2004).   Disease  and  Parasite:  Disease  and  parasite  prevention  and  control  include  special guidelines or standards to deal with disease prevention, dead fish, risk factors, monitoring, recording  and  responding  disease  and  hygiene,  uses  of  drugs  and  chemicals.  In  British Columbia,  a  Fish  Health  Management  Plan  has  been  developed  based  on  federal  and provincial regulations/policies directly related to fish health management (MAFF 2003b). This plan serves as a principle or a template. Individual farms have to develop their own facility management plans following this plan (MAFF 2006). In Norway, a Fish Disease Act is created to specially manage and regulate disease and parasite problems. In order to reduce or minimize the risks, Norway also has limits on fish density, farm size, and length for fallowing, as well as requirements for slaughtering and bleeding. The amount and type of drugs and chemicals are only administered by veterinary prescription. Antibiotics are mainly administered through feed. There are withdrawal times for all therapeutants. The sale of medicated feeds and drugs are monitored. In the case of sea lice, there are special regulations on the numbers of sea lice per farmed fish allowed in different seasons. Also, regularly sampling farm sites are required to monitor the level of sea lice. If the level of sea lice exceeds the required level, immediate treatments must be carried out with prescribed drugs.  The  drugs  for  treating  sea  lice  are  either  administered  through  feed  or  ?bath? treatments.  In  sum,  current  management  strategies  and  environmental  policies  are  guidelines  and standards.  Some  are  mandatory,  while  some  are  voluntary.  They  can  be  categorized  as input and output controls. Input controls include limited entry, feed quota, feed conversion ratio, quantity and type of drugs and chemicals, while output controls include limitations on  the  levels  of  production  and  pollutants.  Although  environmental  management  and   146  policies have become more comprehensive, covering more areas, and some impacts have reduced, environmental problems, such as disease, continue to occur, and some problems have not been solved. Some strategies and policies are not very efficient in reducing or minimizing  environmental  impacts  because  they  fail  to  provide  incentives  to  salmon farmers.   6.3 Key Findings, Policy Implications and Recommendations In  this  section,  policy  implications  and  recommendations  are  explored  based  on  the analyses conducted in different chapters of this dissertation. They are organized chapter by chapter.  6.3.1 The Growth of Salmon Aquaculture Chapter  2  examines  whether  salmon  aquaculture  can  continue  to  expand  at  the  current pace. Based on time series farmed salmon production, a 5-year moving average  growth rate is computed in four leading producing countries and the world as a whole. Further, the growth rates of all finfish aquaculture and capture fisheries is compared. The results show that the year-to-year growth rate of salmon production quickly reaches a peak, and then begins sliding down towards zero. The growth rates of all finfish aquaculture and capture fisheries have followed the same trend. The conclusion of this analysis is that the ability of salmon aquaculture to keep growing at its current pace is doubtful. This analysis implies that aquaculture in general, salmon aquaculture, in particular may not continue growing at its current pace as many have optimistically predicted, and the convenient assumption by many that the world need not worry about the pending demise of capture fisheries may be unfounded. A key policy recommendation from this analysis is that let?s manage our wild fish  stocks  as  best  we  can  while  we  develop  sustainable  and  sensible  aquaculture  to compliment. The idea that aquaculture can take over is simply a pipe dream.  In addition, to make salmon aquaculture a long term sustainable industry, a comprehensive analysis  should  be  carefully  conducted  before  an  aquaculture  license  is  issued  or  an   147  operation is launched. For those who are already in the business, further assessment should be carried out before expansion is made. Salmon aquaculture is a commercial activity, and driven  by  profit-making,  hence,  salmon  aquaculture  has  to  be  a  profitable  operation. Further, salmon aquaculture also generates environmental impacts and social conflicts to the environment and society, therefore, it has to be socially acceptable and environmentally sustainable. A number of factors such as market, production inputs, consumer awareness and environmental concerns may affect salmon aquaculture production and development. To foster a sustainable salmon industry in the long term, a comprehensive assessment of a salmon  aquaculture  is  needed.  Given  current  slumping  market  price  for  farmed  salmon, production cost and strong environmental concerns, the profit margin is very thin. Salmon producers  have  little  incentive  to  expand  their  production.  Chile  may  be  an  exception because  it  has  the  lowest  production  cost  and  less  environmental  regulations  than  its counterparts.  In  addition,  although  the  amount  of  seafood  supply  from  aquaculture  is increasing,  major  seafood  supply  still  comes  from  capture  fisheries.  As  this  analysis suggests that aquaculture is unlikely to continue to grow at its current rate, the dependence on wild capture fisheries for seafood supply  will carry  on in the future, thus, concerted efforts to sustain and rebuild depleted wild fish stocks need to continue.  6.3.2 Pollution Abatement Cost In Chapter 3, pollution abatement costs of salmon aquaculture are estimated. I develop and apply a joint production function approach to model good output (salmon production) and bad  outputs  (pollution)  simultaneously.  Two  environmental  production  technologies  are proposed,  namely,  regulated  and  unregulated  technologies.  Two  production  function models with different mapping rules are used in the analysis. Pollution abatement costs are estimated based on a series of data from the Norwegian salmon aquaculture industry. The results  reveal  that  pollution  abatement  costs  vary  among  observations  and  models.  On average, pollution abatement cost is 2.6% in terms of total farmed salmon production and 4.6% in terms of total revenue of farmed salmon.     148  The analyses indicate that pollution from salmon aquaculture can impose environmental costs  on  salmon  aquaculture  producers.  However,  salmon  aquaculture  has  operated relatively efficiently in the last several years. Hence, reducing pollution means that salmon production has to be reduced at the same time. The policy recommendations for salmon producers and policy makers from this analysis are stated below:   To  salmon  producers:  The  development  of  innovative  technologies  may  be  the  top priority to reduce pollution. This analysis suggests that reducing the amounts of production inputs is the cost-efficient means to reduce pollution. For instance, feed is the single largest production cost and source of pollution. Over the last decade, feed formula and feeding technology  have  greatly  improved.  The  feed  conversion  ratio,  for  example,  has  been reduced dramatically from around 4.0 in the early 1980s to about 1.2 at present (Asche et al. 1999; Bj?rndal et al. 2002; Tacon 2006). Feeding technology has also improved from hand feeding to timely automatic feeders. The improvement of feed and feeding has been incorporated  into  salmon  production  decision  making.  As  a  result  of  technological innovations in feed, waste discharges have been reduced per unit of production. However, further technological development in feed and feeding is needed.   To policy makers: Environmental tax/charge needs to be used as an economic instrument to reduce pollution. According to the Polluter-Pays-Principle, an environmental tax is a fee levied on a producer. In principle, it should be equal to the environmental damages caused by  the  activity,  e.g.,  salmon  aquaculture.  Environmental  taxes/charges  can  encourage producers to reduce their pollution to the point at which the marginal abatement cost (i.e., tax/charge)  equals  the  marginal  damage  cost.  Sylvia  et  al.  (1996)  indicated  that  an emission tax can be an effective tool to reduce emissions from salmon aquaculture. Setting a tax is a very challenging task because it requires a full understanding of the sources of an environmental problem and its associated impacts and costs. In most cases, marine water pollution is non-point source pollution, that is, pollution comes from multiple sources. The revenues collected from the tax imposed on producers can be used to mitigate the negative effects or compensate for pollution damages by redistributing them between polluters and pollutees.  The  estimates  of  pollution  abatement  costs  in  Chap.  3  could  be  used  as  a   149  reference point to establish an environmental tax/charge level. Recently, some lawmakers in  Chile  file  a  bill  to  tax  salmon  producers  about  5%  of  monthly  profit  to  cover  the environmental costs caused by salmon farming (Carvajal 2007).  6.3.3 Impacts of Sea Lice on Wild Salmon Populations and Fisheries Chapter  4  examines  whether  sea  lice  from  salmon  farms  have  ecological  and  economic impacts  on  wild  salmon  populations  and  fisheries.  Age-structured  salmon  dynamic  and bioeconomic models are applied. Pink and chum salmon in the Broughton Archipelago, British  Columbia  are  used  as  case  studies.  It  is  shown  that  recruitments,  catch  and discounted profits have declined when sea lice induced mortality is incorporated into the production  models  of  wild  salmon.  The  populations  collapse  when  sea  lice  induced mortality  is  assumed  to  be  high.  Pink  population  collapses  faster  than  chum,  and discounted profits are lower for pink salmon fisheries than for chum salmon fisheries due to the low market price for pink salmon.   These analyses imply that sea lice from farmed salmon can have ecological and economic effects on salmon populations and fisheries. These effects are minor when sea lice induced mortality rate is low (<20%), and the effects can be severe if sea lice induced mortality is high (>30%). Sea lice have greater ecological and economic impacts on pink salmon than on  chum  salmon.  These  effects  are  greater  under  a  fixed  exploitation  rate  than  under  a target escapement policy. Policy recommendations drawn from the analyses are:  To  salmon  producers:  To  prevent  outbreaks  of  sea  lice,  better  farm  husbandry management  is  needed.  Current  management  practice  and  design  should  be  updated  or revised in response to the best available knowledge and technologies.  For instance, farm maintenance,  fish  husbandry  and  inspections  should  be  carried  out  on  a  regular  basis. Treatment should be applied immediately when an outbreak occurs. Biological treatment approaches instead of medicine should be considered and developed. For example, Wrasse (Ctenolabrus rupestris) has been successfully used to treat sea lice in Norway and Scotland   150  (Rae 2002). Salmon farmers in British Columbia should consider the use of this kind of biological approach to treating sea lice rather than depending on medicines.  To  policy  makers:  Stringent  management  practice  and  regulations  are  needed.  For instance, setting maximum production/fish density allowed for salmon farms, the timing and period of fallowing, number of sea lice per fish, types and quantities of medicines and drugs  allowed  for  treating  disease;  relocating  farms  and  separating  age  classes  are  all needed. In some very important water corridors or passageways, salmon farms should be forbidden. For instance, Norway has established a number of watercourses and fjords to protect wild salmon stocks from salmon farms (S?nvisen 2003; Porter 2005).  6.3.4 Open Netcage vs Sea-bag Production Systems In Chapter 5, the economic performances of open netcage and sea-bag production systems for salmon aquaculture are compared. Capital budget and investment appraisal analyses are used to compare the profitability of the two production systems. For sea-bag systems, on average, the capital investment costs are 2.6 times, and operating costs are 1.2 times higher than for open netcage systems. Projected 20-year cash flows showed that sea-bag systems produce negative gains in more growth cycles than netcage systems, and the magnitude of positive gains is relatively small compared to net losses in sea-bag systems. For netcage systems, the net present values are all positive except for one production capacity, while for sea-bag systems, the net present values are all negative. Netcage systems have lower breakeven  prices  and  production  levels  than  sea-bag  systems.  All  the  internal  rates  of return  for  netcage  systems  are  positive  and  greater  than  the  discount  rate  except  at  the production  capacity  of  720  tonnes.  Sea-bag  systems  produce  negative  internal  rates  of return at all production capacities.  Netcage  production  systems  appear  to  be  more  economically  profitable  than  sea-bag systems  when  environmental  costs  are  either  not  or  only  partially  considered.  Sea-bag systems are not financially feasible because of their high capital investment and operating costs. They can be financially profitable only when they produce fish that achieve a price   151  premium. Sensitivity analyses reveal that the market price has the most important impact on the profitability of both systems; changes in discount rates, fish density, feed costs, and environmental costs also have large impacts on the profitability of netcage systems. Policy recommendations emerging from the analyses are presented below:  To salmon producers: Salmon producers should be instructed to label their products. Eco-labeling is a market-based instrument to direct consumers? purchasing behavior. It creates market-based  incentives  for  environmentally  friendly  seafood,  and  takes  into  account product attributes other than price (Cochrane and Willmann 2000). Seafood with an eco-label in general, can command a price premium because it has been shown that consumers are  willing  to  pay  a  higher  price  to  compensate  for  the  higher  production  costs  that  it entails.  Eco-labeling  has  been  advanced  as  an  effective  way  to  provide  consumers? awareness about the seafood they buy (Naylor et al. 2003). To the best of my knowledge, there are currently no eco-labeled farmed salmon products in the market. However, farmed salmon  products  produced  in  land-based  systems  in  British  Columbia,  Canada  were labeled as ?Eco-salmon?, which was self-named by the producers. This was accepted by the retailers, and some consumers were willing to pay a price premium for it. However, this land-based system operation is currently out of business. There is a growing demand for  markets  for  eco-labeled  seafood  products  as  consumers  are  more  aware  of environmental problems and food safety issues.   To policy makers: As an alternative to levying a pollution tax on producers to correct the negative  externalities  of  salmon  aquaculture,  a  subsidy  programs  may  be  used  to  create positive  externalities.  Since  enclosed  production  systems  can  reduce  environmental impacts associated with salmon aquaculture, establishing a subsidy program may motivate producers  to  adopt  such  technologies.  Some  may  argue  that  you  cannot  use  general taxpayers?  money  to  subsidize  a  small  group  of  individuals  who  happen  to  be  salmon farmers.  So,  we  first  collect  taxes  from  producers  who  use  open  netcage  production systems, and then we can use these tax revenues to subsidize producers who are willing to adopt  enclosed  technologies.  For  instance,  a  subsidy  program  such  as  tax  credits  was   152  established  and  supported  by  both  the  Federal  and  Provincial  government  agencies  in British  Columbia,  Canada  in  2004,  some  producers  have  taken  this  subsidiary  offer  to adopt enclosed production systems in small-scale experiments. Since salmon aquaculture continues  its  development,  adopting  cleaner  and  innovative  technologies  to  reduce environmental problems is one of the approaches and options that can produce overall long term benefits for both private producers and society.  6.4 Conclusions  Based  on  the  key  findings  of  the  previous  chapters,  conclusions  are  made:  i)  salmon aquaculture  cannot  keep  growing  at  the  current  pace;  ii)  pollution  abatement  costs  are significant; iii) sea lice from farmed salmon have various ecological and economic impacts on  wild  salmon  populations  and  fisheries;  and  iv)  enclosed  production  technology  is  a promising  solution  to  reduce  environmental  impacts,  but  it  is  very  economically demanding.   Currently,  environmental  policies  have  been  the  main  measures  to  regulate  salmon aquaculture to reduce or minimize environmental impacts. Most of them are in the form of guidelines,  standards  and  management  practices.  Such  environmental  policies  do  not necessarily guarantee outcomes with great environmental or social benefits. However, the control of environmental impacts can be achieved by a number of approaches and options from  the  industry,  the  public  and  authorities  (Naylor  et  al.  2003).  Some  environmental management strategies and policies, such as, improved husbandry management, pollution tax, subsidy, eco-labeling and enclosed production systems, have been proposed based on this study.  In most cases, environmental impacts are highly uncertain and complex, and the type and extent of environmental impacts vary over time and space, hence, it is very challenging to design  an  appropriate  environmental  policy.  The  standards  and  guidelines  have  been widely  used,  and  can  be  relatively  easily  adjusted.  Technological  innovation  is  the  top choice, but it has to be feasible to be adopted by producers. Economic-based instruments   153  can  be  used  when  an  accurate  environmental  cost  is  known.  There  is  no  single environmental management option that can regulate salmon aquaculture in an effective and efficient way. A combination of technological innovations and environmental policies is required.  Sound  environmental  management  and  policy  should  be  formulated, implemented and enforced. Environmentally friendly technologies need to be developed and popularized into sound farm management practices and legislations under the context of a coastal zone management.    To  develop  a  sustainable  aquaculture  industry,  a  comprehensive  long-term  cost-benefit analysis should be conducted before any aquaculture investment is approved. Sustainable development  of  aquaculture  should  be  established  on  three  defined  and  interrelated dimensions: environmental, social and economic. From an economic perspective, salmon farms have to be financially profitable. From a social perspective, it has to be socially fair and  environmentally  acceptable  from  society?s  point  of  view.  That  is,  different stakeholders?  concerns  in  a  community  need  to  be  taken  into  consideration,  including relevant  Government  agencies,  aquaculture  industry  and  allied  associations,  commercial and recreational fishing sectors, non-governmental organizations (NGOs), local residents, First Nations, secondary supporting sectors and the general public. From an environmental perspective, it should harmonize with the surrounding environment and natural resources. All costs and benefits should be identified and assessed before a new aquaculture operation is launched.  Although this study has focused on salmon aquaculture, results and policy implications can be  adopted  for  other  types  of  aquaculture,  in  particular  industrialized  aquaculture  of carnivorous species within a similar context. This dissertation provides some insights and understandings to salmon producers, policy makers and the general public regarding the development  of  salmon  aquaculture  and  the  environmental  impacts  associated  with  it. However, salmon aquaculture is a relatively young industry, and more research needs to be conducted to support its sustainable development into the future.    154  6.5 References  Asche, F., A. Guttormsen, and R. Tveter?s, 1999. Environmental problems, productivity and innovations in Norwegian salmon aquaculture. Aquaculture Economics and Management 3(1): 19-29. Bj?rndal, T., R. Tveter?s and F. Asche, 2002. The development of salmon and trout aquaculture. In Paquotte, P., C. Mariojouls and J. Young (Eds): Seafood Market Studies for the Introduction of New Aquaculture products. Cahiers Options M?diterran?ennes 59: 101-115. Carvajal, p., 2007.  Chile seeks tax on salmon profits. Intrafish, p39.  Cochrane, K. and R. Willmann 2000. Eco-labelling in Fisheries Management. Proceedings of the 2000 Conference by the Centre of Ocean Law and Policy, University of Virginia, and FAO on Current Fisheries Issues and the Food and Agriculture Organization of the United Nations. Rome, Italy, 16-17 March. 18p.  Dow, A., 2004. Norway vs. British Columbia: A Comparison of Aquaculture Regulatory Regimes. The Environmental Law Centre Society, University of Victoria. Victoria, BC, Canada. 35p.  FAO, 2007. National Aquaculture Legislation Overview ? Canada and Norway. Available at http://www.fao.org/fi/website/FISearch.do?dom=legalframework, access May 2007.  Naylor, R.L., J. Eagle and W.L. Smith, 2003. Salmon aquaculture in the Pacific Northwest - A global industry. Environment 45 (8): 18-39.   Maroni, K., 2000. Monitoring and regulation of marine aquaculture in Norway. Journal of Applied Ichthyology 16: 192-195.  MAFF,  2002.  Preventing  Escapes  to  Support  a  healthy  Aquaculture  Industry.  British  Columbia Ministry of Agriculture, Food and Fisheries. 9p.  MAFF, 2003a. Guide to Information Requirements for Marine Finfish Aquaculture Applications. Aquaculture Development Branch, British Columbia Ministry of Agriculture, Food and Fisheries. ISBN 0-7726-4994-4. 76p.  MAFF, 2003b. Required Elements of a Fish Health Management Plan for Public and Commercial Fish Culture Facilities in British Columbia. British Columbia Ministry of Agriculture, Food and Fisheries. 11p.  MAFF, 2006. Template for Development of Facility ? Specific Fish Health Management Plans. British Columbia Ministry of Agriculture, Food and Fisheries. 63p.  Porter, G. 2005. Protecting Wild Atlantic Salmon from Impacts of Salmon Aquaculture: A Country-by-Country Progress Report 2nd Edition. World Wildlife Fund and Atlantic Salmon Federation. 58p.  Rae, G.H., 2002. Sea louse control in Scotland, past and present. Pest Management Science 58: 515-520.    155  S?nvisen, S.A., 2003. Integrated Coastal Zone Management (ICZM): the Allocation of Space in Norwegian Aquaculture ? from Local Lottery to Central Planning? Norwegian College of Fishery Science, University of Troms?. 95p.  Sylvia, G., J.L. Anderson, D. Cai, 1996. A multilevel, multi-objective policy model: the case of marine aquaculture development. American Journal of Agricultural Economics 78 (1): 79-88.   Tacon, A.G.J., M.R. Hasan and R.P. Subasinghe, 2006. Use of fishery resources as feed inputs for aquaculture development: trends and policy implications. FAO Fisheries Circular No.1018, Rome, FAO, 99p.        156  Appendix 4.1. Location of Salmon Farms in Broughton Archipelago Area  (Source: raincoast society: http://www.raincoastresearch.org/graphics/images/broughton-watersheds.jpg)     157  Appendix  4.2.  Calculation  of  the  Population  Capacity  at  Chum  Salmon  Juvenile Stage.   When  a  chum  salmon  population  is  in  equilibrium,  the  number  of  fish  recruits  is determined as: 5++= tNmNmNmN                                                       (a) Where,  (.)  is the age mature rate.  The numbers of fish recruits at ages 3, 4 and 5 are defined, respectively, as follows:  3)3 ssssNeN jNtcjcj ba -- =                                                        (b)      4321)/1(4 sssssNeN jNt cjcj ba -- =                                                      (c)         54321)/1(5 ssssssNeN jNt cjcj ba -- =                                                    (d) Where,  (.) is age specific survival rate. Substitute Equations b, c and d into Equation a: )545443321)/1( sjN jj +- ba                              (e) When a chum salmon population is in equilibrium,  ca . Solving Equation 2,  cj is:  )]545443321 sjcjcjcaj +++= aab                 158  Appendix 4.3.  Ricker Population-recruitment Model with Stochastic Variable   It  is  well  accepted  that  populations  are  self-regulated  by  density-dependent  biological systems  (e.g.,  Ricker  model).  Recent  studies  have  increasingly  shown  that  salmon populations are also controlled by exogenous environmental forces, such as sea surface temperature, climate change, logging and construction of dams (e.g., Walter and Param 1996; Ryall et al. 1999; Bradford and Irvine 2000; Pyper et al. 2001; Koslow et al. 2002; Pyper et al. 2002; Mueter et al. 2002; Beamish et al. 2004). These factors have different impacts  on  the  survival  rates  at  different  development  stages  of  salmon  populations (Ryall et. al. 1999; Beamish et al, 2004). The impacts vary considerably  from  year to year,  from  population  to  population  and  from  development  stage  to  stage.  Also,  the survival  rates  may  be  caused  by  a  combination  of  environmental  factors  and  human interventions. It is difficult to separate the effect of one factor from another in most cases. In  the  literature,  some  studies  use  stochastic  rather  than  deterministic  variables  to represent these effects (Luedke 1990; Costello et al.1998; Sethi et al. 2005). Based on this principle, I will apply a Ricker recruitment model to integrate stochastic variations representing the combined effects of environmental forces.  e--= )/1(11 ABtAt eBR                                                  (1.2) Where,  At  represents recruitment at adult stage at year t ,  1-t is spawners at year  1, Aa  is  the  productivity  of  the  population  in  adult  stage,  Ab  is  the  unfished  equilibrium population size at adult stage, e  is a stochastic variable to represent combined effects of environmental factors on survival, including disease induced mortality.   Walters (1986) provided a theoretical explanation for this stochastic variable. He pointed out that  e can be viewed as a random survival resulting from several independent and multiplicative  environmental  factors  operating  in  series.  Thus,  e  represents  a  sum  of several random factors and should be normally distributed according to the central limit theorem (Luedke 1990). In the literature, e  is either assumed to be the residual error term that is normally distributed based on time series data of recruitment and spawners (Ryall et al. 1999; Pyper et al. 2001 & 2002), or assumed to be a normally-distributed random variable that is estimated based on identified environmental factors, such as sea surface temperature  (Chen  and  Irvine  2001;  Mueter  et  al.  2002).  The  ratio  of  recruit-spawner implies the survival rate of a population, and log Ricker model shows that log recruitment   159  to spawner is a linear relationship with e . Therefore, the magnitude of e  is determined by the standard deviation of an average recruit per spawner. Because the factors such as disease,  destruction  of  habitat  and  pollution  mainly  have  negative  impacts  on  wild salmon populations, the stochastic variables ranging from -0.6 to 0.0 for chum salmon and from -2.4 to 0.0 for pink salmon are used.  Parameters of population recruitment and stochastic variables The  parameters  for  population  productivity  and  capacity,  and  stochastic  variables  are needed in order to use the models for simulations. Based on time series of recruitment and  escapement  data,  I  estimate  the  standard  deviations  for  pink  and  chum  salmon populations,  respectively.  I  assume  that  these  standard  deviations  are  the  stochastic variables in the analysis. On average, the stochastic variables e  are estimated to be 0.60 and 2.41 for chum salmon and pink salmon, respectively. The e  for chum salmon is very close to the  estimate (e =0.5) by  Luedke  (1990).  Since stochastic variable can be  any value in certain ranges, I use the same Monte Carlo method to simulate the stochastic variable as introduced earlier.   Chum salmon: the productivity of the population,  a , is extracted from Luedke (1990); the unfished equilibrium population size (capacity)  a  is the average of two estimates: bopt  (Hilborn and Walters 1992), and  opt  (Luedke 1990 cited Walters 1975); I assume that  opt = opt , which is the target escapement (~ 546,000) set by DFO for the areas of Kingcome Inlet and Bond to Knight Inlet (Ryall et al. 1999).  Pink  salmon:  a  and  a  are  estimated  based  on  the  regression  of  time  series  data  of recruitment and escapement in DFO Area 12.  Appendix. Table 5.1. The recruitment parameters and stochastic variables for chum and pink salmon.   Chum  Pink a   0.7  2.2 b   1,287,822  2,228,309 e   [+0.36, 0, -0.36]  [+2.41, 0, -2.41]   

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