d i s c u s s i o n pa p e r n u m B e r 5 august 2010 d e v e l o p m e n t a n d c l i m at e c h a n g e d i s c u s s i o n pa p e r s 1 56663 d e v e l o p m e n t a n d c l i m a t e c h a n g e Cost of Adaptating Fisheries to Climate Change D I S C U S S I O N PA P E R N U M B E R 5 AUGUST 2010 D E V E L O P M E N T A N D C L I M A T E C H A N G E Cost of Adapting Fisheries to Climate Change By Ussif Rashid Sumaila Fisheries Research Economic Unit, Fisheries Centre University of British Columbia, Vancouver, Canada, V6T 1E4 and William W. L. Cheung School of Environmental Sciences University of East Anglia, Norwich, U.K. NR4 7TJ Papers in this series are not formal publications of the World Bank. They are circulated to encourage thought and discussion. The use and citation of this paper should take this into account. The views expressed are those of the authors and should not be attributed to the World Bank. Copies are available from the Environment Department of the World Bank by calling 202-473-3641. © 2010 The International Bank for Reconstruction and Development / THE WORLD BANK 1818 H Street, NW Washington, DC 20433, U.S.A. Telephone: 202-473-1000 Internet: www.worldbank.org/climatechange E-mail: feedback@worldbank.org All rights reserved. August 2010 This volume is a product of the staff of the International Bank for Reconstruction and Development / The World Bank. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgement on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. 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III Table of ConTenTs Key Findings vi 1. Background and Context 1 1.1 Potential Impacts of Climate Change On Capture Fisheries 1 1.2 Who (Across Countries) is Likely to Be Most Affected? 2 1.2.1 Geographically 2 1.2.2 By income or vulnerability class 2 1.3 What Experience is there with Adaptation in the Sector? 3 1.3.1 Private sector adaptation 3 1.3.2 Public sector investment 3 1.4 What is the Nature and Extent of Adaptation/Development Deficit in This Sector? 3 1.5 How will Emerging Changes in Development and Demographics Influence Adaptation? 3 1.6 Uncertainties 4 2. Literature Review 5 2.1 Previous Studies 5 2.1.1 Nature and extent of damages 5 2.1.2 Nature of adaptation and its cost, private and public 7 2.2 How our Study Complements Existing Work 7 3. Methodology 9 3.1 Determining the Potential Loss/Gain in Catches due to the Redistribution of Fish Biomass 9 3.2 Adjusting Catch Potential to Account for Other Climate Change and Fishing Impacts 10 3.2.1 Climate-induced coral reef degradation 10 3.2.2 Other climate-induced impacts 11 3.2.3 Impacts of declining fish catch from unsustainable fishing 11 3.3 Determining the Potential Economic Loss/Gain in Landed Values and Household Incomes 11 3.4 Calculating the Amount of Endowment Needed to Replace Lost Gross Revenues from the World's Fisheries 11 3.5 Estimating Actual Adaptation Cost for the Countries that will Suffer Losses Under Climate Change 11 3.6 How We Represent the Future ­ 2010 to 2050 12 3.6.1 The baseline 12 3.6.2 Without climate change 12 3.6.3 Climate change scenarios 12 IV C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E 3.7 How Costs of Adaptation are Defined 12 3.8 How Costs of Adaptation are Calculated 13 3.9 Data (Sources, Assumptions, and Simplifications) 13 4. Results 14 4.1 The Potential Loss/Gain in Landed Values due to Climate Change 14 4.2 The Potential Loss/Gain in Household Incomes due to Climate Change 15 4.3 The Amount of Endowment Needed to Replace Lost Catch Revenues 16 4.4 Estimated Actual Adaptation Cost Under Different Climate Change 17 4.5 Summary of Adaptation Costs Relative to the Baseline (with 5 Percent Discount Rate) 18 5. Limitations 22 5.1 Treatment of Extreme Events 22 5.2 Treatment of Technological Change 22 5.3 Treatment of Inter-Temporal Choice 22 5.4 Treatment of "Soft" Adaptation Measures 22 5.5 Treatment of Cross-Sector Measures 22 5.6 Areas for Follow-up Work and Research Advances 23 Conclusions 24 References 25 Tables 4.1 Annual loss in landed value under different climate change scenarios (constant 2005 $ billion). Numbers in parentheses represent projected gain in landed value. 14 4.2 Annual loss in household income under different climate change scenarios (constant 2005 $ billion). Numbers in parentheses represent gains instead of loss. 15 4.3 Annual amount of endowment required to offset the potential impacts under different climate change scenarios (constant 2005 $ billion). Numbers in parentheses represent gains instead of loss. 16 4.4 Estimated annual actual adaptation cost under different climate change scenarios (constant 2005 $ billion). Numbers in parentheses represent gains instead of loss. 17 4.5A Summary results: Loss in gross revenues with 5 percent discount rate (constant 2005 $ billions). Numbers in parentheses represent gains instead of loss. 18 4.5B Summary results: Loss in household income (constant 2005 $ billions). Numbers in parentheses represent gains instead of loss. 19 4.5C Summary results: Endowment needed to make up for loss in gross revenues (constant 2005 $ billions). Numbers in parentheses represent gains instead of loss. 20 4.5D Summary results: Estimated actual adaptation cost (constant 2005 $ billions). Numbers in parentheses represent benefits rather than costs. 21 D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S V Figures 1 Projected rate of (A) species invasion and (B) extirpation by 2050 relative to the 2000S under the SRES A1B scenario (Co2 concentration of 720 ppm by 2100) (Cheung et al. 2009a) 6 2 Projections of change in global catch potential by 2055 under the SRES A1B scenario (Cheung et al. 2009b). 7 VI Key findings · The world's developing and most vulnerable coun- tries, who contribute very little to climate change, are predicted to suffer most of the estimated losses. · Climate change will have significant impacts on the · The losses in gross revenues from high seas' fisheries world's fisheries through losses in catch and gross are predicted to be high--much higher than we revenues. expected at the beginning of the study. · The world stands to lose up to 50 percent of current gross revenues of about $80 billion per year from the This study has revealed a number of important insights. world's fisheries in the face of severe climate change First, adapting fisheries to climate change will not be and continued overfishing in global fisheries. cheap, especially for developing countries, many of · The loss in gross revenues could result in billions of whom lack adaptive capacity. Second, overfishing plus dollars in lost income by fishing households world- climate change means severe depletion of the world's wide, with serious economic and social fishery resources, with about half of current gross reve- consequences. nues predicted to be lost under severe climate change · Replacing the predicted loss in gross revenues due to scenarios. Third, the combination of climate change and climate change globally will require an endowment the lack of effective management of the high seas mean in the hundreds of billions of dollars. heavy losses. To stem this tide, well-functioning · The direct cost of adapting global fisheries to cli- management systems need to be quickly put in place for mate could run into tens of billions of dollars. the high seas. 1 1. baCKground and ConTexT fisheries as a result of climate change. It should be noted that we have not been able to include more direct welfare related measures (e.g., calorie consumption) because of This study has two objectives. The first is to help deci- lack of readily available relevant data. sion makers, especially in developing countries, to better understand and assess the risks posed by climate change, This report focuses on marine capture fisheries, not and to better design strategies to adapt their fishing inland or aquaculture, for a number of reasons. In the sectors to climate change. The second objective is to first place, the study of the impact of climate change on develop global estimates of adaptation costs in the fish- fisheries is more advanced in the case of capture fisher- eries sector of countries to inform the international ies, so we have the necessary basic scientific information community's efforts, including UNFCCC and the Bali on which to base our analysis. Second, marine capture Action Plan, to provide access to adequate, predictable, fisheries are still over 50 percent of the total value of and sustainable support, and to provide new and addi- global fisheries (capture, inland, and aquaculture) and tional resources to help the most vulnerable developing support a large number of economically vulnerable countries meet adaptation costs. Adaptation is here people in coastal communities of the world, especially in understood to mean any action taken to reduce the risk developing countries. Third, there are indications that posed by the impact of climate change in a given sector both inland fisheries and aquaculture are likely to suffer of the economy, for example, fisheries. Adaptation cost similar challenges identified for marine capture fisheries. is then the cost of taking such action. Hence, the results from this study can provide insights about the potential cost of adapting inland fisheries and To help meet these two objectives, this study is global in aquaculture to climate change. its scope. First, we will provide country/regional adapta- tion costs to contribute to the discussion on climate 1 . 1 P o Te nTi a l i m Pa C Ts o f C l i m aTe change leading up to the Copenhagen conference in late C h a n g e o n C aP Tu r e f i s h e r i e s 2009. Second, this work will begin to develop the procedures that will be needed to generate aggregate Marine fisheries productivity is likely to be affected by adaptation cost numbers once country case studies are the alteration of ocean conditions--including water completed. temperature, ocean currents, upwelling, and biogeo- chemistry--as a result of climate change (IPCC 2007; We use four variables to help us capture the cost of Diaz and Rosenberg 2008). Empirical observations and adapting fisheries to climate change in a broad sense: (1) climate models both indicate that global climate and the estimated cost of adjusting fisheries to catch declines ocean conditions have been changing over the last 100 as a result of climate change; (2) the potential loss in years and will likely change more rapidly in the future gross revenues or landed values due to climate change; (IPCC 2007). The major changes include ocean warm- (3) the capital that will be required as an endowment to ing, acidification, and expansion of oxygen minimum replace the predicted loss in gross revenues through time; zones (Brewer & Peltzer 2009). Biological responses to and (4) the potential loss in household incomes from these ocean changes have been observed in the marine 2 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E biomes (Perry et al. 2005; Dulvy et al. 2008; Hiddink · There are currently 407 dead zones in the global and Hofstede 2008; Richardson 2008; Cheung et al. ocean. There has been a doubling of dead zones each 2009). For instance, nearly two-thirds of exploited decade since 1960. This means that there are now 16 marine fishes in the North Sea shifted in mean latitude times more dead zones than there were in 1960. or depth or both over 25 years as sea temperature Dead zones are areas without oxygen where no fish increased (Perry et al. 2005; Dulvy et al. 2008). Also, or invertebrates can survive. Climate change is one annual growth rates for the juveniles of eight long-lived of the likely factors that increase the number and fish species in the southwest Pacific increased in shal- intensity of dead zones. low waters where ocean warming occurred, and · Oxygen minimum zones in the open ocean may decreased in deep waters where ocean cooling occurred expand under climate change. (Thresher et al. 2007). These responses are suggested to · Climate change is acidifying the ocean, which be due to changes in physiology, distribution ranges, increases dissolved CO2 and decreases ocean pH, car- and population dynamics as ocean conditions change bonate ion concentration, and calcium carbonate min- (Hiddink and Hofstede 2008; Richardson 2008; eral saturation in the ocean (Cooley and Doney 2009). Cheung et al. 2009). Such changes affect primary productivity, species distribution, and community and We divide marine climate change impacts on fisheries foodweb structure, which have direct and indirect into two main types. First, we focus on impacts on fish- impacts on distribution and productivity of marine ing sectors through shifts in the distribution of fish organisms. biomass and changes in productivity. Second, we exam- ine climate change impacts through other mechanisms Specifically, climate change is likely to affect marine such as acidification of the ocean from higher CO2 living resources in a number of ways: levels and through climate change-included loss of criti- cal habitats. The latter includes degradation of coral · Many fish and shellfish are likely to shift their dis- reefs through coral bleaching. These two impact types tribution as a result of changes in ocean conditions are interrelated. For example, ocean acidification may and habitats. lead to changes in fish habitats and therefore cause · Changes in ocean conditions will result in changes shifts in biomass. Hence, such division is mainly for in primary productivity, population dynamics and operational purposes in this analysis. marine food chain, thereby reducing ocean fish productivity. 1 . 2 W h o ( aCr o s s Co u nTr i e s ) i s l iK e ly · Change in phenology (timing) of marine organisms To b e m o s T a f f eC Te d ? (such as planktons) may lead to a mismatch between food availability and predator requirement. This may 1.2.1 geographically have impacts on the foodchain. · The warming of the global ocean may result in the We see from our data, models, and analysis that: symbiotic algae on corals dying; that is, it may lead to what is described in the literature as coral bleach- · Fish will generally redistribute away from tropical ing. This is predicted to have devastating effects on countries toward cooler temperate countries; thus fish species associated with coral reefs. tropical countries may generally suffer larger impacts. · With climate change, it is highly likely that the vol- · Countries that are heavily dependent on coral reef ume of water in the sea may increase to such an resources are likely to suffer big impacts. extent that many of the world's corals will drown, · Countries and regions with large areas of dead again with potentially serious consequences for spe- zones--for example, the Gulf of Mexico--are likely cies associated with coral reefs. to see declines in their catches. · Climate change is modifying the chemistry of the ocean, which can result in undesirable conse- 1.2.2 by income or vulnerability class quences--for example, a rapid increase in the num- ber of areas in the global ocean without Given that most of the world's developing and poor oxygen--and hence cannot support living creatures. countries are situated in the tropics, and the fact that D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 3 most coral reef resources are also found in developing States--have been compelled to buy fishing access regions such as the Coral Triangle in the Western rights from mainly developing countries as an adapta- Central Pacific, it is clear from both earlier work tion measure to keep their bloated fishing capacity busy (Allison et al. 2009) and the current analysis that low- and supply fish to meet the growing demand at home. income, developing, and mostly already economically vulnerable countries are the ones that will suffer the Countries also have sought to adapt to declining marine most from the vagaries of climate change. fishing opportunities by investing in the development of the fish farming sector, with mixed results. 1.3 WhaT ex PerienCe is T here W iTh ada PTaTion in The seCTor? In general, some countries have tried to use "soft" adap- tation by using policies and regulations to adapt their 1.3.1 Private sector adaptation fisheries to changing times. Unfortunately, however, most of these efforts have been reactive rather than The private sector has been undertaking continuous anticipatory in nature, with huge economic conse- adaptation because of declining fish stocks over time. quences. A case in point is the cod fishery off Fishers have had to go further into the deep and high Newfoundland. The Canadian government spent over seas to catch fish at much higher cost. They have had to $3 billion in reaction to the cod stock collapse in 1992, acquire bigger vessels and sophisticated gear that will yet a much smaller amount could have been spent allow them to stay out fishing for days. Some fisheries earlier to avert the destruction of the fish stocks and the have suffered declines in the number of fishers as the communities that depend on them. opportunities for fishing have diminished. Particularly, private sectors in developed countries have high adap- 1 . 4 W h aT i s Th e n aTu r e a n d e xTe n T tive capacity. For example, some fisheries--such as o f a d aP TaTi o n / d e v e l oPm e n T Norwegian herring fisheries--have experienced change d e f iC i T i n Th i s s eC To r ? in species distribution and species composition; many of these fishing sectors were able to adjust and adapt to Our analysis and the literature show that the nature and the changes, especially with active assistance from extent of adaptation to climate change and the develop- government. Moreover, as fish stocks decline, some fish- ment deficit varies greatly depending on the country ers in both developed and developing countries have and region of the world. The nature and extend of attempted to diversify their income by engaging in adaptation and the development deficit depends on a other non-fishing livelihood activities, such as aquacul- number of factors, including (a) how climate change ture and shipping. will affect the distribution of fish to or away from a country's EEZ; (b) how other impacts of climate Environmental nongovernmental organizations have change such as ocean acidification and hypoxic (low- and continue to play important roles in helping to adapt oxygen) zones will affect the abundance and productiv- fisheries to changing opportunities. ity of the fish species in a country's waters; and (c) how rich, diverse, advanced and adaptable an economy is. 1.3.2 Public sector investment 1.5 hoW Will emerging Changes in Over time, the public sector has invested resources in the d e v e l oPm e n T a n d d e m o g r aPh i C s fishing sector of various countries to deal with diminish- i n f l u e nCe a d aP TaT i o n ? ing catches and fishing opportunities. Some of the adap- tation measures that have been employed by governments Changes in development and demographics will have a include (a) fisheries buybacks, (b) individual transferable great deal of impact on the ability of developing coun- quotas, and (c) livelihood diversification measures. tries, in particular, to cope and adapt to climate change. A combination of factors--increasing population, low In addition to the above, some countries--such as gross domestic product, low scores on the UN Human members of the European Union and the United Development Index (HDI), and low economic 4 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E development--together with decreasing opportunities observed in the last few decades. However, projections of from ocean fisheries due to climate change, is likely to changes in the potential catch, and their effects on the ensure that developing countries face increasing chal- fishing sectors, are considered uncertain (Cheung et al. lenges with time. in press). Also, the effects of climate change on exploited fish stocks--through ocean acidification, hypoxic zones, 1.6 u nC erTainTies coral bleaching, etc.--have not been quantified by previ- ous studies. Moreover, the synergistic effects of fishing Certain aspects of potential impacts of climate change and other human impacts on the ocean--such as pollu- on fishing sectors are considered likely, but the overall tion and habitat destruction--with climate change are impacts and the capacity and cost for adaptation are not well-understood. In socioeconomic terms, the poten- considered uncertain. Specifically, it is very likely that tial response of seafood markets to climate change or climate change will result in a shift in the distribution of changes in seafood demand and supply are unclear. fish stocks. In fact, a climate-induced shift in distribu- These add uncertainty to our understanding of the tions of major commercial fish stocks have been potential impacts of climate change on the fishing sector. 5 2. liTeraTure revieW Climate change may lead to changes in ocean produc- tivity, affecting the potential catch of exploited stocks. Using an empirical model to predict ocean primary production with outputs from global circulation models, 2.1 Previous sT udies Sarmiento et al. (2004) estimated that global primary production may increase by 0.7­8.1 percent by 2050, with very large regional differences--such as decreases 2.1.1 nature and extent of damages in productivity in the North Pacific, the Southern Ocean, and around the Antarctic continent, and Climate change affects the distribution of biomass of increases in the North Atlantic region. Such changes in marine species that are exploited by fisheries. In the primary productivity will affect marine species along the ocean, distribution of marine species, notably for fish food chain. Recently, Cheung et al. (in press) examined and invertebrates, is strongly related to environmental the potential global change in future fisheries catch factors. Specifically, observations and theory suggest potential by the mid-21st century resulting from that marine species respond to ocean warming by shift- changes in primary productivity and species distribution ing their latitudinal range (Perry et al. 2005; Parmesan ranges. They suggest that climate change may cause 2006; Hiddink and Hofstede 2008; Mueter and Litzow large-scale redistribution of catch potential, with a 2008) and depth range (Dulvy et al. 2008). For exam- considerable reduction in catch potential in the tropics ple, in the North Sea, nearly two-thirds of exploited and increase in high latitude regions (Figure 2). Such a marine fishes shifted in mean latitude or depth or both shift in catch potential will directly affect the fishing over 25 years as sea temperature increased (Perry et al. sectors. For example, it is estimated that climate change 2005; Dulvy et al. 2008). Recently, a study using a may cause a 35 percent reduction in the overall dynamic bioclimate envelope model (Cheung et al. economic value of Australian fisheries by 2070 (Winn 2008a; Cheung et al. 2009) examined the potential 2008). Another study found that climate change may global shift in the distribution ranges of 1,066 have been reducing the maximum production of cod at exploited marine fish and shellfishes by 2050. The a rate of 32,000 metric tons per decade since 1980 study found that distribution of most species may (Pinnegar et al. 2007). continue to shift toward the pole at an average rate of around 40 km per decade. The projected distribution Other marine climate change effects may have addi- shift may result in high rates of species invasion in the tional negative impacts on fish stocks. Changes in ocean high latitude regions and local extinctions along the temperature, ocean acidification, changes in ocean tropics and semi-enclosed seas (Figure 1). A distribu- chemistry (e.g., expanded area with low oxygen) and sea tion shift of exploited species will result in changes in level are likely to damage marine habitats such as coral abundance and composition of species in each region. reefs that are ecologically important to many exploited Fisheries may be affected by the potential shift in fish- species. Ocean acidification may have additional impacts ing grounds of targeted species and the associated on other calcifying organisms. Many of the potentially changes in the cost of fishing. affected species are commercially valuable or are 6 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E figure 1. ProjeCTed raTe of (a) sPeCies invasion and (b) exTirPaTion by 2050 relaTive To The 2000s under The sres a1b sCenario (Co 2 ConCenTraTion of 720 PPm by 2100) (Cheung et al. 2009a) Species invasion 0 > 0­0.15 > 0.15­0.30 > 0.30­0.45 > 0.45­0.60 > 0.60­0.90 > 0.90­1.20 > 1.20­1.80 > 1.80­2.80 > 2.80­4.00 > 4.00 Species extirpation 0 > 0­0.005 > 0.005­0.010 > 0.010­0.015 > 0.015­0.025 > 0.025­0.035 > 0.035­0.045 > 0.045­0.060 > 0.060­0.080 > 0.080­0.120 > 0.120 ecologically important to targeted species. Increased ports. There will also be many social, cultural, and insti- severe weather conditions may affect fishing operations. tutional implications. For example, if fish move from On the other hand, retraction of sea ice, particularly in one part of a country to another part, will it be possible the Arctic, may allow fishing operations in previously for people who will lose fish to «follow» their fish? Even inaccessible fishing grounds. within countries, this is not a trivial question, and when it comes to transboundry and straddling stock, this In summary, climate change will affect the distribution question becomes even more challenging. The current of fish in the ocean and the fish population that the report focuses more on the economic impacts and world's fisheries depend on. These will obviously have therefore covers impacts related to the loss/gain in gross serious impacts on the gross revenues to be derived revenues and the cost of fishing that is likely to occur from fisheries and the cost of fishing. In addition, it will with climate change. have impacts on fishing infrastructure such as fishing D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 7 figure 2. ProjeCTions of Change in global CaTCh PoTenTial by 2055 under The sres a1b sCenario (Cheung et al. 2009b). Change in catch potential (percent relative to 2005) < ­51 < ­50 to ­31 < ­30 to ­16 < ­15 to ­1 0 5­14 15­29 30­50 > 50 2.1.2 nature of adaptation and its Cost, Private · Countries, especially, developing ones with large and Public subsistence fishing communities, will have to find alternative sources for meeting the animal protein The private and public sectors will need to adapt to needs of their people. the following realities under climate change: 2.2 hoW our sTudy ComPlemenTs · Some of the species of fish they currently catch will exisTing WorK disappear, meaning that those who currently catch these fishes will have to find something else to do. This work is groundbreaking in a number of ways. · Some of the fishes caught by a given fishing fleet First, as far as we know, this is the first time anyone may move to other parts of the country or even out has looked at the cost of adapting fisheries to climate of the country's EEZ. This will be costly in a num- change at the global level in a quantitative fashion. We ber of ways because fishers may have to "follow" the know that climate change is likely to affect the goods fish, which in many instances will mean a higher and services provided by ecosystems. In particular, it cost of fishing. will impact on the ability of marine ecosystems to · Predictions of future productivity and revenue from continue to serve as a reliable source of seafood supply, fish stocks may be more uncertain, making it more with direct implications for the welfare of human difficult for the private sector to set their investment society (Antle et al. 2001; Easterling et al. 2007; goals or for fisheries management agencies to decide Battisti and Naylor 2009). Such impacts and their cost management strategies and tactics. and benefits have been quantified in terrestrial · In many countries, climate change will result in a systems. For example, food-crop production is significant reduction in revenues from fishing. This projected to be negatively affected under the more will mean that the public sector will need to find intensive CO2 emission scenarios, with most severe ways that not only help fishers replace their lost impacts projected for low-latitude regions (Fischer et incomes, but also compensate for the lost tax reve- al. 2005; Parry et al. 2004, 2005; Easterling et al. nues that this will entail. 2007). Similar projections for pastures and livestock 8 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E production have also been made (Easterling et al. benefits of climate change impacts on fisheries, let alone 2007). Although such projections are uncertain, they estimation of the actual adaptation cost to the society. allow analysis of potential socioeconomic vulnerability, Various studies investigated the vulnerability and adap- impacts on global food security and benefits and costs tive capacity of countries or communities to climate of climate change. change impacts on fisheries (Allison et al. 2009). They show that tropical developing countries are socioeco- In the marine biome, except the modeling studies that nomically most vulnerable to climate change; not only are included in this chapter (Cheung et al. 2009, in will the impacts of climate change be felt most in these press), studies of climate change impacts on fisheries regions, but also these countries are the most vulnerable focus largely on a few species, regional climate variabil- in terms of their ability to absorb the cost of adapting ity, and regime shifts, or qualitative inferences of poten- to climate change. Unfortunately, there are few, if any, tial changes (Lehodey 2001; Lehodey et al. 2003; national adaptation efforts in these regions. Our study is Drinkwater 2005; Brander 2007; Roessig et al. 2004). global and therefore will give a broader view of the situ- There are currently few studies estimating the costs and ation than most current studies. 9 3. meThodology incomes from global fisheries under different cli- mate-change and demand-growth scenarios. · Determine the amount of endowment needed to Our methodology consists of the following main replace lost gross revenues in the case of countries components: that lose catch revenues, and the amount of capital that will be gained in the case of countries that may · We determine the potential loss/gain in catches due make extra catch revenues. to the redistribution of fish biomass and changes in · Finally, we will estimate the actual cost of adapting primary production in the global ocean under dif- marine fisheries to climate change worldwide using ferent climate change scenarios, for all maritime historical cost data for adjusting fisheries after big countries of the world and the high seas. declines in catches such as in the case of northern · Since change in the distribution of fish populations cod off Newfoundland, Canada. and primary production--and therefore catches-- will likely not be the only important impact, we will 3 . 1 d eTe r m i n i n g T h e P o Te n Ti a l l o s s / examine--based on spatial knowledge of the loca- g a i n i n C aT Ch e s d u e To T h e tion of different fish species in the global ocean-- r e d i sT r i b uTi o n o f f i s h b i o m a s s the potential effects of climate change through changes in (a) acidification of the oceans from The potential loss/gain in catches is based on estimates higher CO2 levels; (b) loss of coral reefs from ocean from Cheung et al. (in press). Such estimates include warming and acidification; and (c) other changes in changes in maximum potential catch for 1,066 exploited ocean biogeochemistry such as oxygen levels. We fish and shellfish species and are segregated spatially then modify the potential impact of climate change into 0.5 degree latitude x 0.5 degree longitude. This on fish catches, identifying climate change vulnera- includes a wide range of taxonomic groups, ranging bility hotspots insofar as fisheries are concerned. from krill, shrimps, anchovy and cod to tuna and sharks. · As many fish stocks are fully exploited, overex- Overall, they contributed 70 percent of the total ploited, or depleted, the global fish catch may not be reported global fisheries landings from 2000­04 (Sea sustainable (Pauly et al., 2003). Thus, the current Around Us Project database: www.seaaroundus.org). fisheries catch (and thus revenue) level may decrease There are three steps involved in the projection of in the future. The additional effect of the decline in future fisheries catch potential: (1) projecting future fish stocks on adaptation costs of the fisheries sector species distribution ranges with a simulation model to climate change is considered as a separate (Cheung et al. 2009); (2) projecting primary production scenario. in the future with empirical models (Sarmiento et al. · Steps 1 to 3 will help us isolate the impact of cli- 2004); and (3) calculating potential change in catch mate change on fisheries from impacts coming from with an empirical model (Cheung et al. 2008b, in press). other sources, such as overfishing and pollution. · Determine the potential loss/gain in ex - vessel We simulated future changes in the distribution by landed values or gross revenues and household using a dynamic bioclimate envelope model (Cheung et 10 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E al. 2008a, 2009). First, the distribution map of each Log 10 MSYt = ­2.991 + 0.826 log10 Pt ­ 0.505 species in recent decades (i.e., 1980--2000) was derived log10(At) ­ 0.152 + 1.887 from an algorithm described in Close et al. (2006). The log10 CT + 0.112 log10 HTC + model identified species' degree of preference to and association with environmental conditions that include where t is year and is the error term. The spatial sea water temperature (bottom and surface), salinity, distribution of the calculated maximum catch potential distance from sea-ice, and habitat types (coral reef, estu- was assumed to be proportional to the predicted relative aries, seamounts, and coastal upwelling). Second, species' abundance of each species in each 30' x 30' cell. environmental preferences were then linked to the expected carrying capacity in a population dynamic We computed the projected future maximum catch model in which growth, mortality, and spatial dynamics potential for all the 1,066 species included in this study of adult movement and larval dispersal along ocean by 2050 under the "severe' and "mild" climate change currents were explicitly modeled (Cheung et al. 2008a, scenarios (Cheung et al. in press). The projected 2009). Finally, given the projected changes in ocean changes in catch potential are by exclusive economic conditions and advection fields from an ocean-atmo- zones and exploited species. Assuming that ex-vessel sphere-coupled global circulation model (GCM) under prices remain constant from now to 2050, we calculated climate change scenarios, the model simulated the the projected landed value by 2050. It equals to the annual changes in distribution of relative abundance of product of the landed value in 2000 and the projected each species on the global 30' x 30' grid. changes in landed value. We used projections of future primary production esti- 3 . 2 a d j u sT i n g C aT Ch P o Te n Ti a l To mated from the methods documented in Sarmiento et a C Co u nT f o r o Th e r Cl i m aTe al. (2004). To predict ocean primary production, we C h a n g e a n d f i s h i n g i mPaC Ts employed three different published algorithms described in Carr (2002), Marra et al. (2003), and Behrenfeld and We modify the potential loss/gain determined under Falkowski (1997) that calculate phytoplankton primary section 3.2 above to take into account the other effects productivity as a function of the modeled surface cholo- of marine climate change--such as ocean acidification, rophyll content and its distribution, light supply and coral bleaching, and other changes in ocean biogeo- vertical attenuation, and sea surface temperature chemistry--and the additional impact of overfishing. (Sarmiento et al. 2004). All the physical parameters Specifically, we considered two scenarios of the effect of were outputs of the NOAA/GFDL's coupled model. climate-induced coral reef degradation, ocean acidifica- Spatial resolution of the estimated annual average tion, and other impacts on future catch potential and primary productivity is scaled onto a 30' lat. x 30' long. landed values. In addition, we include a scenario where grid. Thus we predicted annual primary production unsustainable fishing resulted in an overall reduction in from the world ocean from 2001 to 2060 for the two global fish catch. climate change scenarios from each of the above algorithms. 3.2.1 Climate-induced coral reef degradation Using a published empirical model described in Cheung In the severe climate change impact scenario, catch et al. (2008b), we calculated the annual maximum catch potential of coral-reef-associated species are assumed to potential for each of the 30' x 30' grid cells. The empiri- decrease by a maximum of 50 percent by 2050. Since cal model estimates a species maximum catch potential different species have different levels of dependency on (MSY) based on the total primary production within its coral reefs, their levels of impact will also be different. exploitable range (P), the area of its geographic range First, we divide exploited species into five broad catego- (A), its trophic level (), and includes terms correcting ries according to their degree of association to coral the biases from the observed catch potential (CT: reef: no, low, medium, high, very high. Their degree of number of years of exploitation, and HTC: catch association is based on a published index of association reported as higher taxonomic level aggregations): to coral reef (see www.seaaroundus.org for details). This D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 11 index scales from 0 to 1, with 1 having the strongest determined in 3.1 and 3.2 above, we (a) calculated the association to coral reefs. Thus, the categories are difference in catch between the mild and the baseline assigned the index values of: 0, >0 & <=0.4, >0.4 & scenarios, and between the severe and baseline scenar- <=0.6, >0.6 & <=0.8, >0.8 for no, low, medium, high, ios; (b) applied ex vessel prices to the catch changes to and very high categories, respectively. Next, the related obtain the loss/gain in landed values or gross revenues impacts of coral reef degradation on the species' catch to the fishing sector under our mild and severe climate potential increases with their association to coral reefs: change scenarios; and (c) used an input-output table no (0 percent), low (30 percent), medium (50 percent), approach (Dyck and Sumaila 2009) to determine the high (70 percent), and very high (100 percent). Species losses/gains in household incomes under the two with very high association to coral reefs will thus receive climate change scenarios based on the losses/gains in full impact (that is, 100 percent x 50 percent reduction gross revenues. in catch potential), while those with low coral reef asso- ciation will only suffer from partial impact (30 percent x 3 . 4 C a lCu l aTi n g T h e a m o u nT o f 50 percent reduction in catch potential). e n d oWm e n T n e e d e d To r e Pl aC e l o sT g r o s s r e v e n u e s f r o m Th e 3.2.2 other climate-induced impacts World's fisheries We assume that other potential climate change impacts The premise for calculating the amount of endow- such as ocean acidification or increased hypoxic zones ment needed to replace lost fisheries' gross revenues will reduce the overall maximum catch potential. In the under climate change is that the ultimate goal of severe climate change impact scenario, these other adaptation in economic terms should be to replace the impacts are assumed to reduce overall catch potential by loss in gross revenues from the fisheries sector under 30 percent. Under the mild climate change impact climate change. This approach is further justified scenario, coral-reef-associated species will receive a maxi- because data on actual adaptation cost is very scanty mum of 10 percent reduction in catch potential, while for this sector, with the implication that any estimate the impacts from other ocean climate change impacts of actual adaptation costs will be limited. The endow- will reduce the overall catch potential by 5 percent. ment approach asks the following question: What is the capital that a country, region, or the world will 3.2.3 impacts of declining fish catch from need to have in other to replace the loss in gross reve- unsustainable fishing nues that is likely to be incurred as a result of climate change? We consider two scenarios: The first scenario considers an optimistic scenario where most fish stocks are prop- 3.5 esTimaTing aCTual adaPTaTion erly managed from now on, and global fish catch is CosT for The CounTries ThaT Will maintained at the year 2000 levels for the next 50 years. suffer losses under ClimaTe The second scenario is a "worst-case scenario," which is Change presented in Pauly et al. (2003). Reported statistics suggest that the global marine fish catch has been To deal with diminishing catches and fishing opportu- decreasing since the late 1980s. Extrapolating from this nities, countries around the world have invested trend results in a nearly 40 percent reduction in global resources in the fishing sector of their countries over fish catch by 2050 (Pauly et al. 2003). We assume this time. The adaptation measures that have been used by decline in the worst-case scenario. governments are fisheries buybacks (Clark et al. 2005), individual transferable quotas (Clark et al., in press) and 3.3 d e Termining T he P oT enT ial livelihoods diversification measures (Teh et al. 2008). e C onomiC loss/gain in land e d Countries such as members of the European Union and values and household inC o m e s the United States have been compelled to buy fishing access rights from mainly developing countries as an Using our estimates of potential catches of fish globally adaptation measure to keep their bloated fishing capac- under our baseline, mild and severe scenarios as ity busy and supply fish to meet the growing demand at 12 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E home. Furthermore, countries have sought to adapt to With economic and demographic projections declining marine fishing opportunities by investing in The United Nations Population Division, in a recent the development of a fish farming sector, with mixed projection (United Nations, Department of Economic results. and Social Affairs 2007) predicts a global population of 8.04 billion for the year 2025 and 9.37 billion for 2050. To provide a first estimate of the actual cost of adapting According to this estimate, therefore, there will be about fisheries to climate change, we first collected data for 50 percent more people to feed by 2050. Also, incomes instances where these measures have been applied to in many emerging economies, some of them large deal with declines in fish catches in the past. The data developing countries (China, India, and Brazil, for collected include the amount of money spent relative to example), are projected to increase dramatically in the either the quantity of fish catch the spending was meant coming decade. In addition it is expected that the to take care of, or the number of boats or fishers it was march of economic integration and globalization that meant to ease the declining fishery. was witnessed in the last several decades will continue into the future, resulting in further cointegration of the We split the world's maritime countries into two markets for fish and fish products. The first two trends groups, made up of developing and developed coun- are likely to increase demand and put pressure on the tries, based on the World Bank's classification. We price of fish even without considering the impact of then searched the literature and the World Bank's climate change. On the other hand, market integration database for the data needed for our analysis. In all, is likely to put downward pressure on the price of fish we obtained data for seven developing and five devel- as fish moves quickly from areas of low demand to oped countries. We then calculated the average cost those of high demand. This latter point may be the per metric ton of fish that a given reported amount reason for the apparent lack of noticeable increases in supported in terms of, for example, buying fishers out the real price of fish in general recently (Sumaila et al. of a fishery suffering catch declines for these two 2007). For the purposes of the current analysis there- groups. The calculated averages are then applied in fore, we assume fish prices will increase enough over the case of countries we could not find data for. time to make up for inflation, leaving real prices Clearly, this is a first approximation only. Data for constant. more countries are needed to improve the current estimate. 3.6.3 Climate change scenarios 3.6 h oW We reP resenT T he · Global severe climate change impact. Ocean conditions fuT ure--2010 To 2050 change as projected under the "business as usual" scenario (Special Report on Emission Scenario 3.6.1 The baseline A1B) in which CO2 concentration will stabilize at 720 ppm by 2100, and ocean acidification, coral 3.6.2 Without climate change bleaching, and other ocean changes have a large impact on fisheries productivity. We assume that without climate change, global fisheries · Global mild climate change impact. Ocean conditions may either be able to maintain the current level (year change as projected under the scenario in which 2000) of catch or continue with the declining trend seen greenhouse gas concentrations are maintained at the since the 1980s, depending on other things such as fish- 2000 level (380 ppm), an ocean acidification, coral eries management interventions, etc. The total gross bleaching, and other ocean changes have a low fisheries revenues for the baseline (without climate impact on fisheries productivity. change) scenario was thus calculated from the net pres- ent value from 2010 to 2050 with (1) annual landed 3 . 7 h o W C o s Ts o f a d aP TaT i o n a r e value and catch maintained at the 2000 level, and (2) defined annual landed value and catch decreases by 20 percent by 2050 to take into account the potential for continued Adaptation is here understood to mean any action taken overfishing of the world's fish stocks. to reduce the risk posed by the impact of climate change D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 13 on the gross revenues obtained from fisheries worldwide. 3 . 9 d aTa ( s o u rC e s , a s s u mP Ti o n s , a n d The cost of adapting fisheries to climate change is then s i m P l i f iCaT i o n s ) the cost of taking such action to reduce the risk of losing revenues from fishing as a result of climate change. To Ex vessel price data for each taxonomic groups and fish- capture this cost, we used two approaches. First, we pose ing countries were obtained from Sumaila et al. (2007). the question: What is the capital that a country will We calculated the ex vessel landed values by exclusive need in terms of an endowment to replace the loss that economic zones and the high seas for the world ocean is likely to be incurred as a result of climate change? in year 2000 in constant 2005 dollars. We obtained Second, we use historical cost data for adjusting fisheries catch data from the Sea Around Us project to evaluate in crisis worldwide because of declines in catches as a the trends of reported global fish catch. The Sea Around basis for calculating what the cost of adapting fisheries Us project developed an algorithm that disaggregated to climate change is likely to be. reported catch data from 1950 to 2004 into a 30' lat. x 30' lon. grid of the world ocean (see Watson et al. 2004 3.8 h oW Cos Ts of adaPTaT ion a r e and www.seaaroundus.org for details). The main source Cal CulaTed of catch data is the fisheries statistics from the Food and Agriculture Organization of the United Nations First, we determine the potential loss/gain in ex vessel (FAO), which is modified where appropriate with more landed values or gross revenues. We do this because of reliable data. the lack of cost data that would have allowed us to calculate economic rent. Second, we calculate estimated We only included exploited stocks that were reported in household incomes from global fisheries under different the catch statistics as species-specific groups (a total of climate change scenarios. Third, we determine the 1,066 species). We excluded groups that were aggre- amount of endowment needed to replace lost gross gated under higher taxonomic units, e.g., groupers, revenues at the global and regional levels. Finally, we snappers, and sharks. Species composition of these estimate direct (actual) adaptation cost under climate higher taxonomic groups are generally unknown and change using historical cost data for adjusting fisheries the methodology employed here to simulate future after big drops in catches such as in the case of north- changes in fish distributions and catch potential does ern cod off Newfoundland, Canada. not account for these groups. For economic data (e.g., the direct cost of adaptation) we searched the literature, These four variables together capture the cost of adapt- the Internet, and the World Bank's project database for ing fisheries to climate change in a broad sense. relevant data. 14 4. resulTs billion in constant 2005 dollars as a result of climate change. As can be seen in Table 4.1, this loss is distrib- uted unevenly across different continents. Specifically, 4.1 The PoTenTial loss/gain in landed developing countries are likely to suffer a two to three values due To ClimaTe Change times larger loss in landed value or gross revenue under the more intensive and less intensive scenarios, respec- Globally, the fishing sector may have an annual loss in tively. For example, under the more intensive severe landed values or gross revenues of between $17 to $41 climate change scenario, the calculated potential loss of Table 4.1. annual loss in landed value under differenT ClimaTe Change sCenarios (ConsTanT 2005 $ billion). numbers in ParenTheses rePresenT ProjeCTed gain in landed value. Mild scenario ($ billions) Severe scenario ($ billions) Less intensive4 More intensive5 Over- exploitation6 Less intensive More intensive Over-exploitation Global 16.75 31.31 9.64 21.59 40.99 19.32 Developed country1 4.13 8.07 2.27 5.02 10.36 4.56 Developing country1 11.19 18.77 7.02 15.16 24.93 13.18 World bank region Sub-Saharan Africa2 1.37 2.22 0.87 1.68 2.80 1.45 East Asia & Pacific2 7.02 10.94 4.63 10.83 15.49 9.18 Europe & Central Asia2 0.32 1.31 (0.01) (0.26) 1.26 (0.06) Latin America & the 1.21 2.17 0.73 1.42 2.72 1.28 Caribbean2 Middle East & North 0.61 0.84 0.43 0.67 0.98 0.57 Africa2 South Asia2 0.44 0.96 0.21 0.55 1.26 0.51 Other developing3 0.22 0.34 0.16 0.28 0.42 0.25 countries High seas 1.43 4.47 0.35 1.40 5.70 1.58 1 The numbers for developed and developing countries do not sum to the global total because of the high seas. The regional numbers do not add up because coun- tries that are not eligible for World bank loans are not included in the six regional classification; and also because the high seas numbers are not included. 2 only includes countries that are considered by the World bank in their regional classification. 3 all other countries (excluding high seas) that are not considered by the World bank. We assume that all countries that are eligible to receive loans from the World bank are developing countries. 4 for the mild scenario, this refers to a maximum of 10 percent reduction in annual catch of coral-reef-associated species due to climate-related coral reef impacts and 5 percent reduction in overall catch resulting from other impacts. for the severe scenario, this refers to a maximum of 20 percent of reduction in coral reef catch and 10 percent of overall catch. 5 for the mild scenario, this refers to a maximum of 30 percent reduction in annual catch of coral-reef-associated species due to climate-related coral reef impacts and 20 percent reduction in catch resulting from other impacts. for the severe scenario, this refers to a maximum of 50 percent of reduction in coral reef catch and 30 per- cent of overall catch. 6 The scenario where the severe scenario (footnote 5) relative to a baseline scenario of 20 percent reduction in catch by 2050 from 2000 because of overfishing. D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 15 annual landed value in developing countries is $25 various scenarios, global loss in household income may billion, while the equivalent number for developed coun- be between $6­$14 billion per year depending on the tries is $11 billion per year. In terms of World Bank climate change scenario. Households in developing regions, East Asia and the Pacific is predicted to suffer countries may suffer a bigger loss of $3.9­$8.4 billion the largest loss in landed value ($7­$16 billion). relative to those in developed countries ($1.6­$4.2 billion) as a result of decreased landed value from their 4.2 The P o TenT ial loss/gain in EEZs. Under the severe climate change scenario, the household inC omes due To East Asia and the Pacific region suffers the biggest ClimaTe Change loss of up to $6 billion per year. This is followed by Latin America and the Caribbean and Sub-Saharan The projected loss in household income shows similar Africa. trends as the potential loss in landed values. Under the Table 4.2. annual loss in household inCome under differenT ClimaTe Change sCenarios (ConsTanT 2005 $ billion). numbers in ParenTheses rePresenT gains insTead of loss. Mild scenario ($ billions) Severe scenario ($ billions) Less intensive1 More intensive2 Over- exploitation Less intensive More intensive Over- exploitation Global3 5.90 10.94 3.41 7.58 14.30 6.77 Developed country 1.57 3.09 0.86 1.90 3.96 1.73 Developing country 3.89 6.48 2.45 5.25 8.59 4.56 World bank region Sub-Saharan Africa 0.44 0.72 0.27 0.53 0.92 0.47 East Asia & Pacific 2.66 4.11 1.76 4.02 5.75 3.41 Europe & Central Asia 0.10 0.40 0.00 (0.07) 0.39 (0.01) Latin America & the 0.33 0.64 0.19 0.34 0.77 0.31 Caribbean Middle East & North Africa 0.15 0.21 0.11 0.17 0.24 0.14 South Asia 0.14 0.30 0.07 0.18 0.40 0.17 Others developing 0.07 0.10 0.05 0.08 0.12 0.07 countries3 High seas 0.44 1.37 0.11 0.43 1.74 0.48 1 The numbers for developed and developing countries do not sum to the global total because of the high seas. The regional numbers do not add up because coun- tries that are not eligible for World bank loans are not included in the six regional classification; and also because the high seas numbers are not included. 2 only includes countries that are considered by the World bank in their regional classification. 3 all other countries (excluding high seas) that are not considered by the World bank. We assume that all countries that are eligible to receive loans from the World bank are developing countries. 16 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E 4.3 The amounT of endoWmen T countries may require $277­$605 billion to offset the needed To reP la Ce los T CaT Ch loss from their EEZs, while developed countries may revenues require $106­$278 billion under the various scenarios. Regionally, under all scenarios, East Asia and the Pacific The loss in landed value and household income may are predicted to require the largest endowment ($175­ require a total of $419­$1025 billion endowment to $387 billion), followed by the Latin America and the offset by 2050 under the various scenarios of climate Caribbean ($30­$68 billion) and Sub-Saharan Africa change and fishing impacts (Table 4.3). Developing regions ($34­$70 billion). Table 4.3. annual amounT of endoWmenT required To offseT The PoTenTial imPaCTs under differenT ClimaTe Change sCenarios (ConsTanT 2005 $ billion). numbers in ParenTheses rePresenT gains insTead of loss. Mild scenario ($ billions) Severe scenario ($ billions) Less intensive1 More intensive2 Over- exploitation Less intensive More intensive Over- exploitation Global3 418.75 782.76 240.88 539.80 1024.78 482.90 Developed country 103.31 201.69 56.66 125.59 259.09 114.05 Developing country 279.81 469.23 175.46 379.09 623.22 329.45 World bank region Sub-Saharan Africa 34.21 55.44 21.73 41.88 70.05 36.34 East Asia & Pacific 175.38 273.38 115.66 270.68 387.13 229.41 Europe & Central Asia 8.00 32.72 (0.19) (6.49) 31.52 (1.39) Latin America & the 30.32 54.26 18.15 35.53 68.04 31.93 Caribbean Middle East & North 15.33 20.99 10.78 16.73 24.38 14.17 Africa South Asia 10.97 24.03 5.35 13.75 31.52 12.84 Others countries 5.61 8.41 3.99 7.02 10.57 6.15 Developing High seas 35.63 111.84 8.76 35.11 142.47 39.40 1 The numbers for developed and developing countries do not sum to the global total because of the high seas. The regional numbers do not add up because coun- tries that are not eligible for World bank loans are not included in the six regional classification; and also because the high seas numbers are not included. 2 only includes countries that are considered by the World bank in their regional classification. 3 all other countries (excluding high seas) that are not considered by the World bank. We assume that all countries that are eligible to receive loans from the World bank are developing countries. D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 17 4.4 esTimaTed aCTual adaPTaTion CosT $5­$14 billion of adaptation cost per year, while devel- under differenT ClimaTe Change oped countries may require $3­$12 billion depending on the scenario being considered. Again, because of the We estimated that the annual direct adaptation cost higher loss in potential fisheries catches, the East Asia required for the fishing sectors is between $7­$30 and the Pacific region is likely to require the highest per billion (Table 4.4). Developing countries may require annum direct adaptation costs for fishing. Table 4.4. esTimaTed annual aCTual adaPTaTion CosT under differenT ClimaTe Change sCenarios (ConsTanT 2005 $ billion). numbers in ParenTheses rePresenT gains insTead of loss. Mild scenario ($ billions) Severe scenario ($ billions) Less intensive1 More intensive2 Over-exploitation Less intensive More intensive Over-exploitation Global3 7.44 21.75 2.19 9.89 29.47 9.91 Developed country 3.09 8.78 0.99 3.82 11.66 3.88 Developing country 5.11 10.98 2.54 6.84 14.71 6.27 World bank region Sub-Saharan Africa 0.24 0.73 0.06 0.38 1.05 0.37 East Asia & Pacific 2.80 4.89 1.69 4.55 7.10 3.90 Europe & Central Asia 0.27 1.12 (0.02) (0.50) 0.88 (0.26) Latin America & the 1.25 3.19 0.49 1.90 4.48 1.78 Caribbean Middle East & North 0.19 0.28 0.12 0.29 0.40 0.24 Africa South Asia 0.31 0.64 0.16 0.16 0.66 0.18 Others countries 0.07 0.13 0.04 0.06 0.15 0.06 developing High seas (0.76) 1.99 (1.34) (0.78) 3.10 (0.24) 1 The numbers for developed and developing countries do not sum to the global total because of the high seas. The regional numbers do not add up because coun- tries that are not eligible for World bank loans are not included in the six regional classification; and also because the high seas numbers are not included. 2 only includes countries that are considered by the World bank in their regional classification. 3 all other countries (excluding high seas) that are not considered by the World bank. We assume that all countries that are eligible to receive loans from the World bank are developing countries. 18 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E 4.5 summary of adaPTaTion CosTs required to offset the losses over time increases from the relaTive To The baseline (WiTh 5 short term (2010­19), peak in the mid-term (2020­40), PerCenT disCounT raTe) and then declines slightly by the long term (2040­49) under all climate change scenarios and with a 5 percent The potential loss or endowment/adaptation costs in discount rate. A similar temporal pattern is consistent in the fishing sector resulted worldwide due to climate developed/developing countries or in the major World change are not evenly distributed across the next 40 Bank regions. It should be noted that the reduction in years (2010­50) (Table 4.5a). Globally, the loss in gross cost in the long term is due to the "diminishing" effects revenues, household income, and the endowment of discounting with time. Table 4.5a. summary resulTs: loss in gross revenues WiTh 5 PerCenT disCounT raTe (ConsTanT 2005 $ billions). numbers in ParenTheses rePresenT gains insTead of loss. Time profile of cost ($ billion) Region Scenario 2010­19 2020­29 2030­39 2040­49 Global Mild 13.92 29.39 30.84 26.79 Severe 56.45 119.21 125.09 108.66 Overexploit 16.05 33.89 35.56 30.89 Developed Mild 3.43 7.25 7.61 6.61 Severe 14.81 31.27 32.81 28.50 Overexploit 3.79 8.00 8.40 7.30 Developing Mild 9.30 19.64 20.61 17.90 Severe 31.95 67.47 70.80 61.50 Overexploit 27.46 64.33 68.87 60.32 World bank region Sub-Saharan Africa Mild 1.14 2.40 2.52 2.19 Severe 3.64 7.68 8.06 7.00 Overexploit 1.21 2.55 2.68 2.32 East Asia & Pacific Mild 5.83 12.31 12.92 11.22 Severe 18.20 38.44 40.33 35.04 Overexploit 7.62 16.10 16.89 14.67 Europe & Central Asia Mild 0.27 0.56 0.59 0.51 Severe 2.82 5.95 6.24 5.42 Overexploit (0.05) (0.10) (0.10) (0.09) Latin America & the Caribbean Mild 1.01 2.13 2.23 1.94 Severe 3.76 7.93 8.32 7.23 Overexploit 1.06 2.24 2.35 2.04 Middle East and North Africa Mild 0.51 1.08 1.13 0.98 Severe 1.16 2.46 2.58 2.24 Overexploit 0.47 0.99 1.04 0.91 South Asia Mild 0.36 0.77 0.81 0.70 Severe 1.87 3.95 4.14 3.60 Overexploit 0.43 0.90 0.95 0.82 Other developing countries Mild 0.19 0.39 0.41 0.36 Severe 0.50 1.07 1.12 0.97 Overexploit 0.20 0.43 0.45 0.39 High seas Mild 1.18 2.50 2.62 2.28 Severe 9.69 20.47 21.48 18.66 Overexploit 1.31 2.76 2.90 2.52 D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 19 Table 4.5b. summary resulTs: loss in household inCome (ConsTanT 2005 $ billions). numbers in ParenTheses rePresenT gains insTead of loss. Time profile of cost ($ billion) Region Scenario 2010­19 2020­29 2030­39 2040­49 Global Mild 4.90 10.34 10.86 9.43 Severe 19.63 41.46 43.50 37.79 Overexploit 5.62 11.88 12.46 10.83 Developed Mild 1.31 2.76 2.89 2.51 Severe 5.69 12.01 12.60 10.94 Overexploit 1.44 3.04 3.19 2.77 Developing Mild 3.23 6.82 7.16 6.22 Severe 10.98 23.19 24.33 21.14 Overexploit 9.44 22.11 23.67 20.73 World bank region Sub-Saharan Africa Mild 0.36 0.77 0.81 0.70 Severe 1.20 2.54 2.66 2.31 Overexploit 0.39 0.82 0.86 0.75 East Asia & Pacific Mild 2.21 4.67 4.90 4.25 Severe 6.77 14.29 15.00 13.03 Overexploit 2.83 5.98 6.27 5.45 Europe & Central Asia Mild 0.08 0.18 0.18 0.16 Severe 0.86 1.81 1.90 1.65 Overexploit (0.01) (0.02) (0.02) (0.02) Latin America & the Caribbean Mild 0.28 0.58 0.61 0.53 Severe 1.14 2.40 2.52 2.19 Overexploit 0.26 0.55 0.58 0.50 Middle East and North Africa Mild 0.13 0.27 0.28 0.24 Severe 0.28 0.60 0.63 0.55 Overexploit 0.12 0.25 0.26 0.23 South Asia Mild 0.12 0.25 0.26 0.23 Severe 0.59 1.24 1.30 1.13 Overexploit 0.14 0.29 0.31 0.27 Other developing countries Mild 0.06 0.12 0.12 0.11 Severe 0.15 0.31 0.33 0.28 Overexploit 0.06 0.13 0.13 0.12 High seas Mild 0.36 0.76 0.80 0.70 Severe 2.96 6.26 6.57 5.71 Overexploit 0.40 0.85 0.89 0.77 20 C OST OF ADAPTING FISHERIES TO CLIMATE CH A N G E Table 4.5C. summary resulTs: endoWmenT needed To maKe uP for loss in gross revenues (ConsTanT 2005 $ billions). numbers in ParenTheses rePresenT gains insTead of loss. Time profile of cost ($ billion) Region Scenario 2010­19 2020­29 2030­39 2040­49 Global Mild 347.92 734.67 770.92 669.67 Severe 1411.33 2980.15 3127.19 2716.46 Overexploit 401.22 847.22 889.03 772.26 Developed Mild 85.83 181.25 190.19 165.21 Severe 370.17 781.65 820.22 712.49 Overexploit 94.76 200.10 209.97 182.40 Developing Mild 232.48 490.91 515.13 447.47 Severe 798.85 1686.85 1770.08 1537.59 Overexploit 686.54 1608.20 1721.80 1507.95 World bank region Sub-Saharan Africa Mild 28.42 60.02 62.98 54.71 Severe 90.94 192.04 201.51 175.05 Overexploit 30.19 63.76 66.90 58.12 East Asia & Pacific Mild 145.72 307.69 322.88 280.47 Severe 455.08 960.95 1008.36 875.92 Overexploit 190.61 402.49 422.35 366.87 Europe & Central Asia Mild 6.65 14.03 14.72 12.79 Severe 70.41 148.67 156.00 135.51 Overexploit -1.16 -2.45 -2.57 -2.23 Latin America & the Caribbean Mild 25.19 53.19 55.82 48.49 Severe 93.93 198.33 208.12 180.78 Overexploit 26.53 56.03 58.79 51.07 Middle East and North Africa Mild 12.74 26.89 28.22 24.51 Severe 29.12 61.50 64.53 56.06 Overexploit 11.78 24.86 26.09 22.66 South Asia Mild 9.11 19.24 20.19 17.54 Severe 46.75 98.72 103.59 89.99 Overexploit 10.66 22.52 23.63 20.53 Other developing countries Mild 4.66 9.84 10.32 8.97 Severe 12.62 26.64 27.96 24.28 Overexploit 5.11 10.79 11.33 9.84 High seas Mild 29.61 62.52 65.60 56.99 Severe 242.30 511.65 536.89 466.38 Overexploit 32.73 69.12 72.53 63.00 D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 21 Table 4.5d. summary resulTs: esTimaTed aCTual adaPTaTion CosT (ConsTanT 2005 $ billions). numbers in ParenTheses rePresenT benefiTs raTher Than CosTs. Time profile of cost ($ billion) Region Scenario 2010­19 2020­29 2030­39 2040­49 Global Mild 6.18 13.05 13.69 11.89 Severe 47.20 99.66 104.58 90.84 Overexploit 22.86 48.27 50.65 44.00 Developed Mild 2.57 5.42 5.69 4.94 Severe 18.75 39.60 41.55 36.09 Over-xploit 9.04 19.09 20.04 17.41 Developing Mild 4.24 8.96 9.40 8.17 Severe 21.36 45.11 47.34 41.12 Overexploit 11.52 24.33 25.53 22.18 World bank region Sub-Saharan Africa Mild 0.20 0.42 0.44 0.38 Severe 1.65 3.47 3.65 3.17 Overexploit 0.81 1.72 1.80 1.56 East Asia & Pacific Mild 2.32 4.91 5.15 4.47 Severe 8.86 18.70 19.62 17.05 Overexploit 5.63 11.89 12.48 10.84 Europe & Central Asia Mild 0.22 0.47 0.49 0.43 Severe 2.33 4.91 5.15 4.48 Overexploit 0.63 1.34 1.40 1.22 Latin America & the Caribbean Mild 1.04 2.19 2.30 2.00 Severe 6.73 14.20 14.90 12.95 Overexploit 3.50 7.39 7.76 6.74 Middle East and North Africa Mild 0.15 0.32 0.34 0.30 Severe 0.46 0.98 1.02 0.89 Overexploit 0.32 0.67 0.70 0.61 South Asia Mild 0.26 0.54 0.57 0.49 Severe 1.13 2.38 2.49 2.17 Overexploit 0.51 1.07 1.12 0.98 Other developing countries Mild 0.06 0.12 0.12 0.11 Severe 0.22 0.47 0.49 0.43 Overexploit 0.12 0.25 0.26 0.22 High seas Mild (0.63) (1.33) (1.40) (1.21) Severe 7.08 14.96 15.69 13.63 Overexploit 2.30 4.85 5.09 4.42 In addition to computing the present values using a would be expected, the lower discount rate produced discount rate of 5 percent, we also run sensitivity analy- much larger adaptation costs because future costs are sis using discount rates of 3 percent and 7 percent. As given higher weights. 22 5. limiTaTions points in time. This relationship is usually simplified to today and some future date. Economists incorpo- rate inter-temporal choice through the process of discounting future values (Sumaila and Walters 2005). 5.1 TreaTmenT of exT reme eve nTs Inter-temporal choice is fundamental to the study of environmental and natural resource use and can Our analysis focuses largely on the effects of changes in single-handedly determine the outcome of economic mean conditions of ocean conditions, while we did not analysis in natural resource economic models (Sumaila consider the effects of extreme weather events such as and Walters 2005). The baseline discount rate used for changes in frequency and intensity of storms and hurri- this analysis is 5 percent. Sensitivity analysis using canes. These extreme events are likely to have a strong discount rates of 3 percent and 7 percent showed that impact on the fishing sectors as these events may affect the lower discount rate produced much larger adapta- fishing operations, increase risk of fishing, or damage tion costs because future costs are given higher fishing gear or infrastructure. Consideration of these weights. events may thus increase the amount of endowment and adaptation cost required for the fishing sectors under 5 . 4 T r e aTm e nT o f " s o fT " a d aP TaTi o n marine climate change. measures 5.2 TreaTmenT of Te Chnologi C a l Our estimates focus largely on "soft" adaptation Change measures that are needed to facilitate fishing sectors' ability to adapt to climate change. Such soft adaptation Technological change is partially and implicitly consid- measures focus largely on reducing excessive fishing ered in the analysis. In our analysis, we assume that the capacity resulting from loss of potential fisheries catch fishing sectors would develop or modify fishing gear or under marine climate change. However, we did not technology to cope with the change in species composi- consider "hard" adaptation measures such as develop- tions resulting from the shift in species distributions ment of fishing equipment and fisheries infrastructure and fishing grounds. However, we do not consider the (fishing ports or processing plants) that may be affected potential improvement in the efficiency of fishing from by climate change. new technology, which may reduce fishing cost, or new technology that allows the fishing sector to target previ- 5 . 5 T r e aTm e nT o f Cr o s s - s eC To r ously unexploited stocks. measures 5.3 TreaTmenT of inT er-T emP or a l We did not explicitly address cross-sector measures. We Choi Ce assume that fishers displaced from the loss of fishing revenues due to climate change could be transferred to Inter-temporal choice is the study of the relative value other livelihoods given that sufficient funds are provided people assign to two or more payoffs at different to them either directly or indirectly. D E V E L O P M E N T A N D C L I M AT E C H A N G E D I S C U S S I O N PA P E R S 23 5.6 a reas for follo W-uP Wor K a n d effects of changes in potential fisheries catch on costs of researCh advanC es fishing should be better understood to improve the assessment of climate change effects of the economics of fishing. Third, alternative scenarios of changes in There are several major areas of research that could seafood demand and prices under marine climate improve the estimates of cost of adaptation to climate change and its implications for the fishing sector could change in fisheries in the future. Firstly, we should be developed and considered. Moreover, there is improve our understanding of the effects of climate currently scarce information on the potential cost of change on fisheries productivity. We have identified implementing climate change adaptation strategies for areas of major uncertainty in our projections of poten- fishing sectors. Future studies could provide better esti- tial change in fisheries catch. These include the effects mates on the potential adaptation cost to different of marine climate change on primary productivity, regions and fishing sectors. In addition, the implication distributions and abundance of fish stocks, the impacts of extreme events for the fishing sectors could be of change in ocean chemistry including acidification, considered when a better understanding of the effects of and increased hypoxic zones and habitat impacts (e.g., extreme events on the cost of fishing are gained. coral bleaching) on fisheries production. Second, the 24 ConClusions costs than developed countries under all the scenarios considered in this study. This study provides the first estimate of the potential Regionally, East Asia and the Pacific suffers the most in cost of adapting the world's fishing sector to climate losses and in the need for endowment and adaptation change. We found that, globally, the fishing sector may costs. This is followed by Latin American and the suffer from $17­$41 billion of annual loss in landed Caribbean and Sub-Saharan Africa. These regions value depending on how mild or severe climate change consist of some of the countries that have been identi- is likely to be. This may result in an annual loss in fied as most socioeconomically vulnerable to climate household income of $6­$14 billion. Given these change impacts through fisheries. potential losses, the fishing sector may require an endowment of $420­$1025 billion to offset the impacts This study represents the first attempt to estimate of climate change. Moreover, the estimated annual adaptation costs to climate change in the fishing adaptation cost is from $7 to $30 billion depending on sector. As a result, the numbers presented are uncer- the assumptions on the severity of climate change. tain and may be a conservative estimate of the poten- tial costs. However, by exploring different scenarios, Impacts to fishing sectors in developing countries in we provide a set of reasonable and robust estimates terms of loss in landed values or gross revenues from that will support current international work on how to fishing and household incomes is estimated at about adapt fisheries to climate change. 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