Economic Impacts of Global Warming a Study of the Fishing Industry in North Norway

Fisheries Research 56 (2002) 261–274

Economic impacts of global warming A study of the ﬁshing industry in North Norway Arne Eide*, Knut Heen1 The Norwegian College of Fishery Science, University of Tromsø, N-9037 Tromsø, Norway Received 29 June 2000; received in revised form 27 March 2001; accepted 14 June 2001

Abstract

Several studies have been carried out on the possible physical and biological effects of global warming in the Barents Sea area. Based on these studies this paper discusses the effects global warming may have on the Barents Sea fisheries and the implications for the North Norwegian economy. The first has been studied using the multispecies, multifleet model ECONMULT, and the latter by applying an Input–Output model. A range of possible environmental scenarios based on the physical and biological studies of the effects of global warming has been examined. Both positive and negative biological growth effects have been considered, changing the current growth rates by 25%. A more narrow range of management regimes has been applied, reflecting the current management rules and fishery policy in the region. The paper analyses the potential of global warming for changing the catches, profitability, employment impacts and income generation by the Barents Sea fisheries. # 2002 Elsevier Science B.V. All rights reserved.

Keywords: Global warming; Fisheries management; Economic impact; North Norwegian ﬁsheries; ECONMULT

1. Introduction assuming that natural climate variability and the structure and strength of ocean currents remain about This paper discusses some possible economic the same. The positive effects of warming, such as effects of global warming on the fish resources in longer growing seasons, lower natural winter mortal- the Barents Sea and the implications for the North ity, and faster growth rates in higher latitudes, may be Norwegian economy. The analyses are carried out offset by negative factors such as changes in estab- applying the ECONSIMP2 simulation model (Eide lished reproductive patterns, migration routes, and and Flaaten, 1998) and the Input–Output model of the ecosystem relationships. Furthermore, there could North Norwegian economy (Heen and Aanesen, 1993). be regional differences within the mid/higher latitudes In their second assessment the Intergovernmental particularly due to changes in ocean currents. In Panel on Climate Change (Everett, 1997) suggest warmer areas negative factors may include increased that high-latitude production is likely to increase, summer anoxia, increased demand for food to support higher metabolism and reduced thermal habitat for cold water species. * Corresponding author. Tel.: þ47-77-64-55-83; Øiestad (1990) studied the possible effect of global fax: þ47-77-64-60-21. E-mail address: [email protected] (A. Eide). warming on the Barents Sea system, while the impact 1 Senior authorship is not assigned. Authors are listed alphabe- of natural (year-to-year) fluctuation in sea temperature tically. on fish populations has been the focus of a number of

0165-7836/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0165-7836(01)00324-1 262 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 studies (Sætersdal and Loeng, 1987; Loeng et al., 1995; Newton, 1997). Human activities might have a more Ottersen, 1996; Ottersen et al., 1998; Ottersen and immediate impact on the fish stocks and productions Loeng, 2000). In addition to the overall consensus that than climate change. To be able to isolate the effects higher temperature is beneficial to the stocks, a critical of global warming, a bioeconomic model is applied issue has been the close link between the main water to predict future stock production and catches under currents and the sea temperature in the region. In various management regimes, initially without cli- particular, an increased winter inflow of warm Atlantic mate change (baseline scenario), thereafter with cli- water along the north European continent into the mate change. The baseline scenarios differ greatly Barents Seawouldleadtoincreasedwatertemperatures. depending on the management regime applied. The Barents Sea is a particularly interesting areawith Attention is focused on the consequences of global respect to research on the impact of global warming. warming for selected policy goals including stock The Barents Sea fisheries are among the most pro- conservation, profitability, employment and income ductive in the world, and an increase in temperatures generation, though it is beyond the scope of this paper in the Arctic is expected to be significantly higher than to consider possible trade-off between different goals the predicted average global temperature increases of in relation to the global warming scenarios (Leung 0.5–2.0 8C over the next 50 years. Estimates as high as et al., 2001). of þ5 8C for the Barents Sea are found in the literature (Ottersen et al., 1998). North Norway includes the three most northern counties of Norway (Nordland, 2. The fisheries of the Barents Sea Troms and Finnmark). The North Norwegian economy is highly dependent on fish resource utilisation 2.1. The ecosystem (Heen, 1989). In terms of both regional product and employment, the fishing industry counts for about The Barents Sea (Fig. 1) contains some of the most 8%. The fishing industry’s contribution to the North abundant fish resources in the world. Plankton forms Norwegian economy is however substantially higher the basis of the biological production system, with sea if the indirect effects of the industry are included mammals at the top of the biological hierarchy, prey- (Heen and Aanesen, 1993). ing both on cod, pelagic fish and shrimp, while cod The scenarios in this paper include both physical prey on pelagic fish and shrimp. Our focus is on that and biological processes as agents for change. The part of the ecosystem defined by the cod and pelagic physical processes include changes in air temperature fish stocks and on the vessel groups and processing that influence the water temperature. An increase in sector associated with those species: together they the air temperature in the Arctic region of 5 8C would form the most important components of the Barents increase the water temperature by 1–2 8C, and these Sea ecosystem and regional economy. physical processes may further influence the patterns The main commercial species of the Barents Sea of sea currents. The biological processes relate to ecosystem are the north-east Arctic cod (Gadus mor- spawning, individual growth rates, migration, recruit- hua L.) and capelin (Mallotus villosus L.). A third ment and overall distribution of the species. To cover species, Norwegian spring-spawning herring (Clupea the most probable effects, a range of scenarios based harengus L.), may also play an important role. Herring on results from a global circulation model has been is normally located in the Norwegian Sea, south-west considered to predict temperature changes caused by of the Barents Sea, but in some years young herring global warming processes. The scenarios include move into the Barents Sea and remain there for 3 years growth changes of some key species and changes in before migrating southward. migration pattern: they cover both increases and de- The most important pelagic fisheries off the coast of creases in biological growth rates, since either colder North Norway are herring and capelin. After the or warmer environment in the Barents Sea could be the capelin stock collapsed in the mid 1980s, this stock consequence of global warming. has been protected in the Barents Sea. The spawning The fishing industry in most countries is charac- stock remains below the critical level agreed upon by terised by overcapacity and overfishing (Garcia and Russia and Norway for allowing the setting of catch A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 263

Fig. 1. The Barents Sea covers the shallow water basin bounded by the ice shelf in the north-east, Svalbard in north-west, the Norwegian coastline and the Norwegian Sea in south-west and west and Novaja Zemlja and the Russian coastline in south-east and east. quotas through the actions of the joint Russian– These groups are compatible with the vessel groups Norwegian Fishery Commission which meets an- in the profitability study made by the Directorate nually to decide total allowable catches (TACs) for of Fisheries in Norway, which is the main source the three shared stocks: cod, haddock and capelin. The of data for the fish-harvesting sectors in the I–O herring fishery takes place mainly in the Norwegian table. Sea. As a result the cod fisheries dominate the eco- The small-scale vessels and the coastal fleet have a nomic exploitation of the Barents Sea ecosystem, and delivery pattern that is very different from that of the the economic impacts of global warming on the region trawlers. They depend basically on fish taken in the are therefore assessed for different management coastal waters and use mainly passive gears (gillnets, regimes of the cod fisheries only. hand and long lines) and less commonly purse and Danish seines, with each trip lasting from one to a 2.2. The fleet few days. The trawlers, on the other hand, fish the offshore waters and are normally at sea from 1 week The fleet fishing for cod consists of a number of (fresh fish trawlers) to several months (industrial different vessel groups that vary in size, gear use, and trawlers). handling of the fish, and so influence the composition and the quality of the fish landed. In the ECONMULT 2.3. The fish processing industry model the cod fishing fleet consists of 24 groups using six different types of gears. In the I–O model the fishing The catches are destined for the following: fleet have been aggregated into three vessel groups: traditional products (salted and dried fish); small-scale vessels (<13 m); frozen products (frozen fillets with varying degree coastal fleet except trawlers (>13 m); of processing); trawlers. fresh fish (generally exported on ice in boxes). 264 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274

Although the raw fish is delivered either to traditional reflected in the recruitment processes, which are be- wet fish producers or to the freezing plants, both types lieved to show the strongest dependence on environ- of factories will export some of their supplies as fresh mental changes. Technically this is reflected in the half fish, while some freezing plants may also handle value parameter in the Beverton recruitment function. traditional products. All recruitment is at age 0. The use of cod landed in North Norway can vary The fleet model (ECONMULT) is a straightforward from year to year. Possible explanations include rela- production model, assuming the catch to follow a tive price change of the final product, changes in the Cobb Douglas production equation. Twenty-nine fleet management system, increased fishing for other spe- groups are identified, all differently parameterised and cies, and changes in the quotas of the different types of defined by fishing gear, boat size and fishing pattern. cod. In this paper, we assume that future harvesting Typically the seasonal profile has a peak in the first or and delivery pattern remain as at the 1992 level. second quarter of the year. The period length used in According to the bioeconomic model only the cod is ECONSIMP2 is 3 months. harvested, leaving the capelin as food for the cod, ECONMULT is a fleet model from which it is pos- while the juvenile herring leaves the Barents Sea sible to estimate economic effects on different man- before capture. The structure of the pelagic sector is agement regimes. Today’s regulation of the Barents therefore not be presented here. Sea resources is based on two management rules. One is to maintain spawning stock biomasses above critical minimum sizes. The other is to keep the fishing mor- 3. Methods and models tality rate close to the so-called Fmed value, which represents an exploitation rate maintaining a stock 3.1. ECONSIMP2 greater than, but close to, the stock size producing the maximum sustainable yield. An alternative manage- Two different models have been applied to the ment strategy may be to keep a constant quota over analysis of the economic consequences of global several years. From the viewpoint of the processing warming on the fisheries of the Barents Sea and the industry this might have some advantages, assuming North Norwegian economy. The first is ECONSIMP2 the raw fish delivery to be more stable. (Eide and Flaaten, 1998), which predicts the ecological consequences of the Barents Sea ecosystem 3.2. The I–O impact model and the economic exploitation of this system. The ECONSIMP2 model includes the ecosystem model The input–output (I–O) model used in this paper AGGMULT (Tjelmeland and Bogstad, 1998) and the is a closed, static, intraregional, industry-by-industry fleet model ECONMULT (Eide and Flaaten, 1998). model. In a closed model, household is treated as an The harvest data produced from the ECONSIMP2 endogenous industry. The model is based on an I–O model are inputs to the second model, the I–O impact table that can be defined in terms of the following model. equation: The ecosystem model AGGMULT, developed at Xs the Norwegian Marine Research Institute, is a model xij þ Yi ¼ Xi ði ¼ 1; 2; ...; sÞ (1) of high resolution covering the economically most j¼1 important fish species of the Barents Sea. AGGMULT is currently used for management purposes, especially where xij is the sales from regional industry i to in the essential cod–capelin relationship. regional industry j, Yi the sales from regional industry Previous environmental variation may be included i to final demand, Xi the total sales of industry i, and s in AGGMULT. In the deterministic version of the number of industry sectors. AGGMULT, which is the version included in ECON- By assuming constant I–O coefficients and constant MULT, this variation is represented as a cyclic pro- employment and income coefficients, the above equa- cess, assuming the environmental conditions to have tion can be transformed to an operational multiplier properties of repetition. Basically these changes are model. As a helpful tool in quantifying the impact, A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 265 the income and employment multipliers are computed. found by studying the flow chart in Fig. 2. For the sake These multipliers can be of Type I or Type II nature of simplicity, the fish processing is treated as one depending upon whether the households sector is trea- industry (Fig. 2), thus reducing the number of multi- ted endogenously or not. The present study uses the pliers: one for the fish processing industry receiving Type II multipliers. These multipliers capture the the raw fish from the small-scale vessels; the second direct, indirect and induced impact of an exogenous for the fish processing/coastal vessel combination; change in final demand. For a more comprehensive the third for the processing/trawler combination. The presentation of the multiplier concept, see Richardson future composition of exports for each of the three (1972), Schaeffer (1976), and Miller and Blair (1985). processing alternatives (frozen, traditional products In this paper, the income and employment multi- and fresh fish) is assumed to be the same as in the pliers (Type II) for industry j are mathematically 1992 data. The uncertainty in the climate circula- defined as follows: tion models and the possible consequences of global Xs warming for the fish stocks justifies such a simplifica- Ij ¼ bijwi (2) tion. This simplification will have no consequences i¼1 for the regional economic impact. Xs The employment (EI) and income (II) impact mod- Ej ¼ bijli (3) els can now be written in the following terms: i¼1 X3 where bij is the elements in the Leontief inverse matrix which shows the direct, indirect and induced effect in EI ¼ EjPijVjXij (4) industry i of a one-unit change in final demand from i¼1 X3 industry j, wi the wage income coefficient, which is the ratio of total wages in industry i to total sales of II ¼ IjPijVjXij (5) i¼1 industry i, and li the employment coefficient, which is the ratio of the number, employed in industry i to where the index i denotes the three types of fishing total sales of industry i. vessels and the index j represents the fish processing The number of multipliers necessary to include as industry, Ej and Ij are respectively the employment and input into the regional economic impact model can be income multipliers for processing industry with raw

Fig. 2. Flow chart showing the inter relation between the two models applied in this paper, ECONSIMP2 and the I–O model. Global warming and ﬁsheries management are indicated as external factors while ecosystem- and ﬂeet-dynamics and regional economic impacts are explained in the model. 266 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274

fish delivered from vessel group i. Xij is the amount When a management regime is based on a fixed of raw fish in tonnes delivered from vessel group i fishing mortality rate, as in the current regulation sys- to the fish processing industry. Pij is the average price tem, both a TAC distributed to trawl and other gears, of raw fish in NOK/tonne delivered from vessel group and a common TAC covering all vessels, have been i to processing industry j. Vj is the conversion factor of considered. raw fish delivered to the processing industry repre- Only the cod fishery has been active in the simula- senting the export value of one NOK raw fish. tions carried out. This is due to the low capelin stock level. According to the management regime of today, a capelin fishery could not be started during the 4. Management regimes and data simulation period. However capelin plays a signi- in ECONSIMP2 ficant role in the ecosystem, primarily for its transport of energy from the Arctic region into the central The analyses consist of eight different manage- Barents Sea where it is the most important prey ment regimes and four environmental scenarios, for the cod. including the current state situation. The management regimes include open access (or no management), limited entry, quota regulation and combinations of 5. Data for the I–O model the last two. The regulations are set close to current exploitation level and type of management means in The I–O table for North Norway 1987 (Heen and order to produce comparable and realistic results. Aanesen, 1993) provides the necessary data for the Quota regulations could involve either constant I–O model except for the fish-harvesting sectors. quota allocations over the simulation period or TACs The I–O table for 1987 includes only one sector for based on constant fishing mortality (F). This repre- the harvesting and two fish processing sectors. For this sents two different ways of managing the resource, analysis, the fish-harvesting sector was disaggregated keeping the catch constant even when the stock bio- into four fish-harvesting industries, of which three mass changes, or keeping the fishing pressure con- harvest cod. The fourth comprises ‘‘the rest of the stant, even when this will reduce or increase the catch. fleet’’. The fish processing sector is subdivided into A fixed fishing effort may represent the latter. In this two industries, one exclusively for cod processing, and study however, many fleet segments are represented. the second for ‘‘other processing’’ including the pro- Change in age composition of the stock will be cessing of other fish species. reflected in the catches, altering the share of the total The data used for splitting up the fish-harvesting catch of each fleet segment. The principle of constant sector were taken from the profitability studies con- fishing pressure therefore has to be related to the actual ducted by the Directorate of Fisheries in Norway fishing mortality experienced by the stock. (1988a,b). In the case of fixed fleet structure, the fleet structure The conversion parameters (Vj) are found in the I–O of 1994 has been used. In the case of dynamic fleet table developed for this analysis. The conversion structure, the production of fishing effort by the diffe- factor for the processing industry is 1.873 meaning rent fleet segments is assumed to increase by 5% per that one NOK of raw fish delivered to the processing year when the profit is positive. When the profitis industry has an average export value of 1.873 NOK negative, the effort is assumed to decline at an annual after processing. rate of 2%. In all cases fishing effort will not be produced when the contribution margin is negative. In all cases involving a constant TAC, the 6. Environmental scenarios Norwegian share of the quota has been 200 thousand tonnes, which is 50% of the total international quota. Four environmental scenarios have been considered, The TAC is in this case always separated into two including the present situation (Scenario 0). The sce- equal parts, one for trawl fisheries, the other for all narios are based on results from global circulation other vessels. models. A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 267

6.1. Scenario 0 distribution will be altered: 1. Growth rate of cod and herring will be reduced The standard version of ECONSIMP2 (Eide and by 25%. Flaaten, 1998) is parameterised on the basis of histor- 2. Recruitment to the cod and herring stocks will be ical data and surveys over the last 30 years. reduced. Assume average number of 3-year old cod will be reduced from 600 to 400 millions. 6.2. Scenario 1 Similarly the herring recruitment will be reduced to one-third. Most global circulation models (GCMs) show an increase of perhaps 5–10 8C in air temperature in the 6.4. Scenario 3 northern regions including the Barents Sea over the next 100 years. Based on these it is realistic to assume As Scenario 0, but now herring never enter the an increase in mean sea temperature of 2 8C over some Barents Sea. decades. Year-to-year variability is assumed to be as present. 7. Results 6.2.1. Consequences 7.1. ECONSIMP2 1. Growth rate of cod and herring increases by 20%. We assume that the amount of primary and sec- Thirty-two simulations have been carried out, repre- ondary production increases sufficiently to allow senting eight different management regimes and four increased growth. environmental scenarios, including the current state 2. Increased recruitment of cod and herring. Number situation. The management regimes include open of recruits at age 3 for cod is increased from a access (or no management), limited entry, quota reg- historic average of just above 600–800 millions. ulation and combinations of the last two. The results The increase of the herring recruitment will be up are presented in Tables 1–4. The stock developments to 30%. during the simulation years are shown in Fig. 3, while the tables present only average values and standard deviations over the simulation period for some key 6.3. Scenario 2 variables. In Tables 1–4 the open access solution of each The average inflow to the Barents Sea of warm scenario can be read in bold. Apart from the left Atlantic water masses is significantly reduced leading column, the lower part of each table represents pure to an average reduction in sea temperature of 3 8C, quota fisheries. The upper part combines different while standard deviation is assumed to remain con- quota regimes with limited entry, keeping the fleet of stant. This might happen either as a result of a general the initial year (1994). As seen from the first row of reduction in the flow of the Gulf Stream or in the all figures, the fleet structure of 1994 is close to an branch of it entering the Barents Sea. Even with a open access solution of the cod fishery. Fig. 3 shows reduction of 3 8C the summer temperatures in the the substantial variation behind the average values western Barents Sea will be higher than in other of Table 1, also reflected in the standard deviations oceans at similar latitudes. of Table 1.

6.3.1. Consequences 7.2. Results from the I–O impact model Such a dramatic change in temperature may com- pletely alter the ecosystem including the species com- Recall Eqs. (4) and (5), Vj remains constant what- position. In this case, we assume that cod, capelin and ever vessel/processing combination is chosen. The herring, at least in an intermediate period, will still impact per tonne is due to differences in the multi- be the main species, but growth, recruitment and pliers (Ej and Ii) and for the prices (Pij). 268 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274

Table 1 Average cod stock biomass (in thousand tonnes) during the simulation period for the different scenarios and possible management regimes. The standard deviations of the time-series are given in the parenthesis with the average biomass

Fleet composition Scenario Type of management

No quota Constant quota Constant fishing mortality rate ðTAC ¼ 200Þ TAC separated on Common TAC trawl and others

Fixed fleet equal to the 0 1404.11 (626.94) 1935.98 (526.49) 2044.05 (511.85) 2066.97 (499.65) fleet structure of 1994 1 2058.35 (712.79) 2532.73 (579.42) 2424.24 (527.00) 2302.76 (529.92) 2 961.75 (545.43) 1294.12 (474.58) 1689.91 (320.08) 1698.44 (327.28) 3 1410.73 (620.55) 1936.03 (521.20) 2054.96 (509.60) 2075.95 (496.96) Dynamic fleet structure 0 1271.01 (678.21) 1781.07 (533.74) 2032.44 (475.82) 2070.79 (502.44) 1 1933.88 (767.75) 2486.65 (562.52) 2357.98 (540.82) 2325.87 (540.09) 2 888.44 (573.73) 1258.60 (475.26) 1678.68 (329.75) 1694.49 (333.15) 3 1272.88 (674.38) 1794.35 (527.73) 2040.58 (473.37) 2079.21 (499.95)

Table 5 shows the income- and employment-impact also produce relatively high employment impacts, 82 per tonne or thousand tonnes raw fish by the various jobs per thousand tonnes. The trawlers produce the fleet/processing combinations. Deliveries from small- lowest employment impact per thousand tonnes raw scale vessels to the processing industry produce fish, only 70 jobs. Even though the prices received by by far the highest employment impact, 99 jobs per the coastal vessels on average are lower than for the thousand tonnes. Even though the average price for trawlers, the higher employment multiplier for the small-scale vessels is lower than for coastal vessels processing industry receiving raw fish from the coastal and trawlers, the high employment multiplier for the vessels explains this difference. processing industry receiving raw from the small- The differences in the income multipliers for the scale vessels is decisive to the high impact. The main various fleet/processing combinations are small. The reason to this high multiplier is that small-scale vessels differences in the income impact are therefore mainly are labour intensive. Deliveries from the coastal fleet explained by differences in prices. The income impact

Table 2 Average annual catch of the cod (in thousand tonnes) during the simulation period for the different scenarios and possible management regimes. The standard deviations of the time-series are given in the parenthesis with the average catch

Fleet composition Scenario Type of management

No quota Constant quota Constant fishing mortality rate ðTAC ¼ 200Þ TAC separated on Common TAC trawl and others

Fixed fleet equal to the 0 176.94 (85.66) 181.19 (55.83) 182.70 (63.13) 182.69 (62.45) fleet structure of 1994 1 201.75 (84.91) 188.13 (50.06) 190.97 (61.12) 194.38 (62.61) 2 161.51 (84.56) 166.47 (64.57) 154.18 (53.68) 155.58 (54.32) 3 177.63 (84.71) 181.35 (55.41) 183.47 (62.72) 183.39 (62.08) Dynamic fleet structure 0 178.16 (90.26) 182.30 (55.79) 182.05 (62.74) 183.08 (62.34) 1 208.15 (82.37) 192.51 (46.76) 194.66 (63.70) 196.05 (61.31) 2 160.91 (91.52) 165.66 (64.83) 153.74 (54.56) 155.06 (54.91) 3 178.68 (89.78) 183.29 (54.56) 182.73 (62.42) 183.77 (61.99) A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 269

Table 3 Average annual profit (wage paying ability) of the cod fisheries (in million NOK) during the simulation period for the different scenarios and possible management regimes. The standard deviations of the time-series are given in the parenthesis with the average profit

Fleet composition Scenario Type of management

No quota Constant quota Constant fishing mortality rate ðTAC ¼ 200Þ TAC separated on Common TAC trawl and others

Fixed fleet equal to the 0 118.46 (481.23) 151.47 (332.03) 155.65 (388.51) 276.93 (361.62) fleet structure of 1994 1 272.82 (495.25) 203.55 (301.76) 225.18 (362.67) 314.36 (356.06) 2 12.69 (451.66) 44.19 (368.28) 6.72 (329.15) 111.23 (308.60) 3 122.67 (475.60) 151.79 (329.87) 160.51 (386.10) 281.30 (358.70) Dynamic fleet structure 0 30.89 (538.30) 22.41 (377.50) 67.36 (401.96) 185.40 (410.66) 1 192.42 (519.97) 81.85 (333.48) 91.17 (427.65) 242.95 (401.88) 2 68.10 (513.53) 11.84 (388.82) 5.16 (333.58) 58.24 (333.75) 3 31.91 (534.98) 19.14 (374.83) 71.88 (399.38) 190.63 (407.02)

Table 4 Present values (in billion NOK) of the flow of profit (wage paying ability) in the cod fisheries with a discount rate of 5%, during the simulation period for the different scenarios and possible management regimes. The corresponding value with a discount rate of 10% is given in parenthesis

Fleet composition Scenario Type of management

No quota Constant quota Constant fishing mortality rate ðTAC ¼ 200Þ TAC separated on Common TAC trawl and others

Fixed fleet equal to the 0 2.744 (2.593) 2.686 (2.283) 2.542 (2.089) 4.052 (3.010) fleet structure of 1994 1 4.326 (3.413) 3.282 (2.622) 3.573 (2.816) 4.787 (3.620) 2 1.277 (1.624) 1.287 (1.496) 0.508 (0.800) 1.978 (1.698) 3 2.768 (2.592) 2.682 (2.276) 2.580 (2.098) 4.085 (3.016) Dynamic fleet structure 0 1.793 (2.101) 1.316 (1.577) 1.582 (1.581) 3.109 (2.546) 1 3.455 (2.958) 1.963 (1.926) 2.108 (2.046) 4.005 (3.208) 2 0.388 (1.163) 0.789 (1.190) 0.621 (0.856) 1.432 (1.436) 3 1.787 (2.085) 1.275 (1.552) 1.622 (1.594) 3.155 (2.561)

is highest when raw fish is delivered from the traw- Table 5 lers, 15.000 NOK per tonne. For the coastal fleet the Employment and income impact per tonne or thousand tonnes of income impact per tonne is 14.000 NOK. The fact that raw fish (gutted and dressed) by various fleet/processing combination (x ) the raw fish from the trawlers receive on average ij higher prices explains this difference. The small-scale Fleet (i) Employment Income impact vessels produce an income impact of 13.100 NOK impact (jobs/ (thousand thousand tonnes) NOK/tonne) per tonne. The low price of raw fish is the main expla- nation to the low impact. x1j Small-scale vessels 99 13.1 To compute the total employment and income x2j Coastal vessels 82 14.0 x Fresh fish trawlers 70 15.0 impact of the various scenarios, the catches by vessel 3j 270 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274

Fig. 3. Cod biomass in thousand tonnes during the simulation period. The solid lines connecting diamonds represent the current environmental situation. The dotted lines connecting stars are the Scenario 1 simulations, ﬁlled squares represent Scenario 2 and ﬁlled triangles represent Scenario 3 simulations. The values on the x-axis indicate the simulation years.

groups have to be multiplied by the employment and period. Table 6 gives the total catches and total income impact reported in Table 5. For all scenarios, employment and income impact of the scenarios. In the ﬂuctuations in the cod catches over the simula- addition to the base line scenario, only the impact tion period are high. In the calculation of the regional of the highest (Scenario 1) and the lowest catches employment and income impact, we have therefore (Scenario 2) are presented to indicate the probability used average catches (Table 2) for the simulation area. A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 271

Table 6 a Employment and income impact of three scenarios by various ﬂeet/processing combination (xij) Vessel group Catch Employment impact Income impact (thousand tonnes) (number of jobs) (in million NOK)

Scenario 0 (base line) Small-scale vessels 14 1386 183 Coastal vessels 74 6068 1036 Trawlers 36 2520 540 Total 124 9974 1759

Scenario 1 Small-scale vessels 22 2178 288 Coastal vessels 90 7380 1260 Trawlers 34 2380 510 Total 146 11938 2058

Scenario 2 Small-scale vessels 5 495 66 Coastal vessels 53 4346 742 Trawlers 50 3500 750 Total 108 8341 1558

a Scenario 3 is not included in the table because the maximum/minimum are lower/higher than the maximum impact of Scenario 1 and the minimum of Scenario 2.

8. Discussion employment impact of 9950 jobs and generates an income of 1750 million NOK. This impact counts for For all scenarios the fluctuations in the cod stock 5% of the total employment in North Norway and biomass and catches over the simulation period are generates 7% of total income. This clearly shows the high. In the calculation of the regional employment great importance of the cod fisheries for the North impact, we have therefore used average catches for Norwegian economy. the simulation period. 8.2. Scenario 1 8.1. Scenario 0 ECONSIMP2. The highest average catch of Sce- ECONSIMP2. The present value of the flow of nario 1 is about the same for the management system profit over the simulation period (20 years) is 0.8– based on no TAC, using either pure limited entry or 2.5 billion NOK in the case of limited entry regulation. open access. The latter alternative produces an aver- The optimal solution is probably higher, involving age catch of 207 thousand tonnes under this scenario. both possible changes in fleet structure and quota Fig. 3 indicates that the fluctuations in the cod stock setting. In the case of free fleet adjustment the corre- biomass are increased, the cod stock reaching biomass sponding range is 0.4 to 1.5 billion NOK, which levels well above 3 million tonnes and fast declines gives an idea of the amount of resource rent converted down to 1 million tonnes. into fleet capital. I–O model. The highest average catch of Scenario 1 I–O model. The average catch of Scenario 0 shows is about the same for the management system based little difference in catch applying different manage- on no TAC, using either pure limited entry or open ment regimes. The total impact using a yearly catch access. The latter alternative produces an average of 177 thousand tonnes (round fish) produces an catch of 207 thousand tonnes (round fish) under this 272 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 scenario. This again produces an employment impact might be an effect of global warming. As expected the of 11,900 jobs; this is an increase of 1950 jobs results from Scenario 1 suggest that this will have a compared to Scenario 0. The total number of jobs positive effect on both annual catches (Table 2) and in North Norway is increased by about 1% compared profitability (Table 3) in the Barents Sea fisheries. The to the current employment figures. The income im- annual catches, however, are primarily determined by pact is 2050 million NOK; an increase of 300 million the quota regulation, which is the same in all scenar- NOK compared to the base line scenario. The total ios. The largest increase in average annual catches is income generation in the North Norwegian economy obtained in the case of open access. The total number is increased by 1.3%. of jobs in North Norway is increased by about 1% compared to the current employment figures. The 8.3. Scenario 2 corresponding increase in income generation in the North Norwegian economy is 1.3%. ECONSIMP2. The lowest average catch is about the The increase in average annual catches in the quota same for the management system where the TAC is regulated fisheries of Scenario 1 compared to the base- based on constant fishing mortality equally distributed line scenario (Scenario 0) reflects how increased on trawl and conventional gears with limited entry profitability allows the fleet to take catches closer to regulation (current regime) as for total quota regula- the quota values. During the simulation period the tion. The latter regime produces the lowest average annual catches in some years drop below the quota catches of 154 thousand tonnes yearly. level. This is caused by negative contribution margins I–O model. The lowest average catches of 154 (revenue minus variable costs), which force the vessels thousand tonnes yearly is about the same for the to stop fishing until the contribution margins reach management system where the TAC is based on con- non-negative values. The average annual catch value stant fishing mortality equally distributed on trawl may increase up to 10% (Scenario 1 under TAC and conventional gears with limited entry regulation management of constant fishing mortality rate and a (current regime) as for total quota regulation. The common quota) by reducing these interruptions in the regional employment impact of these catches is 8300 fisheries. The standard deviation of the average catch jobs; this is a reduction of in the number of jobs 1650 will also be reduced by this effect. compared to Scenario 0. Compared to the current The catches under Scenario 1 show small changes employment level, this reduction counts for about with a dynamic fleet structure (Table 2), while the 0.8% of the current employment. The income impact changes in the average annual profits are substantial is 1550 million NOK, a reduction of 200 million NOK. (Table 3). This reflects primarily the change in stock The reduction also counts for 0.8% of the current biomass with increased growth (see Table 1, Scenario income generation. 1) while keeping the same catch quotas. Even in the open access situation (dynamic fleet size adjustment 8.4. Scenario 3 and no quota regulation), the average annual profit increases more than six times the profit of the base- ECONSIMP2. The results of the simulations based line scenario. This is caused by the fluctuations in the on this scenario differ only marginally from the simu- cod stock biomass over the simulation period, which lations of Scenario 0. This might be due to the specific are more pronounced in an open access fishery than initial values and only few changes in management under quota regulations. The fleet is unable to adjust regimes. Other ecosystem development patterns that at the same rate, which makes it possible to obtain a might be possible could therefore have been hidden. resource rent even in an open access fishery. The highest annual profit (Table 3) and present value of flow of profit over the simulation period (Table 4) is 9. Concluding remarks obtained in the case of a limited entry and quota regulated fishery, using the constant fishing mortality With reference to the literature cited in the intro- rate management rule and a total quota for all vessel duction of this paper, an increased biomass growth groups. The average annual profit in this case is more A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274 273 than 10 times the profit obtained in the open access It is not the purpose of this study to find the optimal fishery. An interesting relevant observation is that a management scheme of the different environmental highly regulated fishery aims to increase only the scenarios, but to compare possible effects of global wage paying ability (which includes the opportunity warming keeping a realistic management regime with cost of labour and the resource rent) by 40% com- the baseline scenario (Scenario 0). The different man- pared to the open access situation in Scenario 1. In- agement situations therefore represent only a narrow creased growth seems to increase the biomass range of possible variations on today’s management fluctuations (see Fig. 3 and the standard deviation regime. Keeping in mind that different vessel groups values in Table 1) and accordingly makes it harder for may be managed differently, present management lies the fleet to adjust to the current open access fleet size closest to a constant fishing mortality rate combined level. Increased biomass may increase cannibalism in with a limited entry fishery where quotas are given the stock and cause fast stock reduction even when separately for bottom trawlers and others. Although the fishing pressure is low. If a more stable stock the management regimes applied are close to each situation is favourable for the fishing industry, the other, the results vary substantially. In fact a wider loss due to a decrease in growth rates may partly be variety is shown within rather than between different compensated by a more stable stock situation over management regimes of each scenario shown in years. Possible positive effects in the herring fisheries Tables 1–4. This indicates that even though global in the Norwegian Sea are not considered here. warming may have a great potential for altering A comparison between Scenario 0 (baseline sce- catches, profitability, employment and income gen- nario) and Scenario 2 follows to a large extent eration from the cod fisheries (for better or worse), the conclusions above with the difference of having changes in management may even have a bigger negative sign. It should however be noted that the potential in influencing the results. percentage increase in catches when no quota is set, in The employment impact in the North Norwegian Scenario 1 compared with the baseline scenario (14– economy of increased growth rates is potentially very 16% according to Table 2), is much larger than the significant, especially in a marginal region already corresponding decrease in Scenario 2 (about 9%), suffering a degree of contraction in its basic fishing while the opposite is the situation in the cases of activities. quota regulations (correspondingly plus 4–7% and In summary, the results show that even a narrow minus 9–15%). The most significant decreases in range of management regimes has a variety of possible catches are obtained by mortality-related quota setting economic outcomes. A wider variety is shown within (in Scenario 2), while the most significant increases different management regimes of each scenario than are obtained without quota regulation (in Scenario 1). between the different environmental scenarios of each This might reflect that the applied quotas were management regime. This strongly indicates that even relatively low, in particular in the situation of in- though global warming may have a great potential for creased growth (Scenario 1). changing the catches, profitability, employment The decline in catch in Scenario 1 compared with impact and income generation from the cod fisheries Scenario 0 reduces the profitability of the fisheries (for better or worse), changes in management may and puts it close to the break-even point. Even have an even bigger potential in influencing the though the most significant decline occurs in the results. By keeping the management regime constant, fishing mortality-related quota regulated fisheries, the changes in profitability of the fisheries are a the most serious economic impacts are found in the function of variations in the biological growth rates. fisheries without quota regulation (Table 4). This The employment impact in the North Norwegian reflects a less cost efficient harvest in the unregulated economy from changes in the biological growth is fisheries. around 1% increase or decrease in the total employ- The regional employment impact is an employment ment in the region, depending on the biological growth reduction a little less than 1%. The corresponding being increased or reduced. The income generation in reduction in income generation will be of the same the North Norwegian economy is increased/reduced in percentage as the employment reduction. the same range. 274 A. Eide, K. Heen / Fisheries Research 56 (2002) 261–274

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