Fisheries Reference Points under Varying Stock Productivity and Discounting: European Anchovy as a Case Study


Published: Oct 14, 2022
Keywords:
European anchovy age-structured bioeconomic model fisheries reference points stock productivity Black Sea Turkey
SEZGIN TUNCA
MARKO LINDROOS
MARTIN LINDEGREN
Abstract

European anchovy (Engraulis encrasicolus) is the main commercially exploited fish stock in the Black Sea region, providing a vital source of livelihood and revenue for local communities and national economies. In recent decades, the Black Sea anchovy stock has faced many human-induced threats, including overfishing, eutrophication, invasive species, and climate change while these threats have raised concerns about the status and long-term productivity of the stock. To ensure sustainable levels of exploitation under potential future changes in stock productivity, we here estimate and compare a suite of biological and economic reference points under different levels of stock productivity and discount rates using an age-structured bioeconomic model setup. Our model simulations showed that optimal fishing mortalities achieving maximum sustainable yield (FMSY) and maximum economic yield (FMEY) increase at higher stock productivity but are always lower than the historically high mean levels of exploitation. Furthermore, we illustrate that the stock biomass at maximum economic yield (BMEY) is larger than the stock biomass at maximum sustainable yield (BMSY) at all stock productivities and discount rates, except at low stock productivity under high levels of discounting (i.e., 10%, 20%). By illustrating the ecological and economic benefits of reducing exploitation rates, we expect that our estimated reference points can add value to the decision-making process for the management of the European anchovy fishery and ensure long-term sustainable management even under future climate-driven changes in stock productivity.

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References
Allison, E.H., Ellis, F. 2001. The livelihoods approach and management of small-scale fisheries. Marine Policy, 25, 377-388.
Bartolino, V., Margonski, P., Lindegren, M., Linderholm, H.W., Cardinale, M. et al., 2014. Forecasting fish stock dynamics under climate change: Baltic herring (Clupea harengus) as a case study. Fisheries Oceanography, 23, 258-269.
Bromley, D.W., 2009. Abdicating Responsibility: The Deceits of Fisheries Policy. Fisheries, 34, 280-290.
Castilla-Espino, D., García-del-Hoyo, J.J., Metreveli, M., Bilashvili, K., 2014. Fishing capacity of the southeastern Black Sea anchovy fishery. Journal of Marine Systems, 135, 160-169.
Chashchin, A.K. 1996. The Black Sea populations of anchovy. Scientia Marina, 60, 219-225.
Checkley, D.M., Jr., Asch, R.G., Rykaczewski, R.R., 2017. Climate, Anchovy, and Sardine. Annual Review of Marine Science, 9, 469-493.
Christensen, V., 2010. Mey = Msy. Fish and Fisheries, 11, 105-110. Clark, C.W., Munro, G.R., 1975. The Economics of Fishing and Modern Capital Theory: A Simplified Approach. Journal of Environmental Economics and Management, 2, 92-106.
Clark, C.W., Munro, G.R., Sumaila, U.R., 2010. Limits to the Privatization of Fishery Resources: Reply. Land Economics, 86, 614-618.
Daskalov, G.M., 2003. Long-term changes in fish abundance and environmental indices in the Black Sea. Marine Ecology Progress Series, 255, 259-270.
Daskalov, G.M., Grishin, A.N., Rodionov, S., Mihneva, V., 2007. Trophic cascades triggered by overfishing reveal possible mechanisms of ecosystem regime shifts. Proceedings of the National Academy of Sciences of the United States of America, 104, 10518-10523.
Dichmont, C.M., Pascoe, S., Kompas, T., Punt, A.E., Deng, R., 2010. On implementing maximum economic yield in commercial fisheries. Proceedings of the National Academy of Sciences of the United States of America, 107, 16-21.
Döring, R., Egelkraut, T.M., 2008. Investing in natural capital as management strategy in fisheries: The case of the Baltic Sea cod fishery. Ecological Economics, 64, 634-642.
Dulvy, N.K., Sadovy, Y., Reynolds, J.D., 2003. Extinction vulnerability in marine populations. Fish and Fisheries, 4, 25- 64.
Eero, M., Vinther, M., Haslob, H., Huwer, B., Casini, M. et al., 2012. Spatial management of marine resources can enhance the recovery of predators and avoid local depletion of forage fish. Conservation Letters, 5, 486-492.
FAO, 2020. The State of World Fisheries and Aquaculture 2020. Sustainability in action. Rome. https://doi.org/10.4060/ ca9229en (Accessed 30 August 2022).
Froese, R., Branch, T.A., Proelß, A., Quaas, M., Sainsbury, K. et al., 2011. Generic harvest control rules for European fish eries. Fish and Fisheries, 12, 340-351.
Goulding, I.C., Stobberup, K.A., O’Higgins, T., 2014. Potential economic impacts of achieving good environmental status in Black Sea fisheries. Ecology and Society, 19 (3), 32.
Grafton, R.Q., Kompas, T., Hilborn, R.W., 2007. Economics of overexploitation revisited. Science, 318, 1601.
Grafton, R.Q., Kompas, T., Chu, L., Che, N., 2010. Maximum economic yield. Australian Journal of Agricultural and Resource Economics, 54, 273-280.
Grafton, Q.R., Kompas, T., Che, T.N., Chu, L., Hilborn, R., 2012. BMEY as a fisheries management target. Fish and Fisheries, 13, 303-312.
Gücü, A.C., Genç, Y., Dağtekin, M., Sakınan, S., Ak, O. et al., 2017. On Black Sea Anchovy and Its Fishery. Reviews in Fisheries Science & Aquaculture, 25, 230-244.
Gücü, A.C., Genç, Y., Başçınar, N.S., Dağtekin, M., Atılgan, E. et al., 2018. Inter and intra annual variation in body condition of the Black Sea anchovy, Engraulis encrasicolus ponticus. Potential causes and consequences. Fisheries Research, 205, 21-31.
Guillen, J., Macher, C., Merzéréaud, M., Bertignac, M., Fifas, S. et al., 2013. Estimating MSY and MEY in multi-species and multi-fleet fisheries, consequences and limits: an application to the Bay of Biscay mixed fishery. Marine Policy, 40, 64-74.
Hilborn, R., 1985. Apparent Stock Recruitment Relationships in Mixed Stock Fisheries. Canadian Journal of Fisheries and Aquatic Sciences, 42, 718-723.
Holma, M., Lindroos, M., Romakkaniemi, A., Oinonen, S., 2019. Comparing economic and biological management objectives in the commercial Baltic salmon fisheries. Marine Policy, 100, 207-214.
Hoshino, E., Pascoe, S., Hutton, T., Kompas, T., Yamazaki, S., 2018. Estimating maximum economic yield in multispecies fisheries: a review. Reviews in Fish Biology and Fisheries, 28, 261-276.
Hutchings, J.A., Taylor, E., Minto, C., Ricard, D., Baum, J. K. et al., 2010. Trends in the abundance of marine fishes. Canadian Journal of Fisheries and Aquatic Sciences, 67, 1205-1210.
Kanik, Z., Kucuksenel, S., 2016. Quota implementation of the maximum sustainable yield for age-structured fisheries. Mathematical Biosciences, 276, 59-66.
Knowler, D., 2007. Estimation of a stock–recruitment relationship for Black Sea anchovy (Engraulis encrasicolus) under the influence of nutrient enrichment and the invasive comb-jelly, Mnemiopsis leidyi. Fisheries Research, 84, 275-281.
Knowler, D., Barbier, E.B., 2005. Managing the Black Sea Anchovy Fishery with Nutrient Enrichment and a Biological Invader. Marine Resource Economics, 20, 263-285.
Kompas, T., Grafton, R.Q., Che, T.N., 2010. Bioeconomic losses from overharvesting tuna. Conservation Letters, 3, 177- 183.
Li, J., Convertino, M., 2021. Temperature increase drives critical slowing down of fish ecosystems. PLoS One, 16, e0246222.
Lindegren, M., Brander, K., 2018. Adapting Fisheries and Their Management To Climate Change: A Review of Concepts, Tools, Frameworks, and Current Progress Toward Implementation. Reviews in Fisheries Science & Aquaculture, 26, 400-415.
Lindegren, M., Mollmann, C., Nielsen, A., Stenseth, N.C., 2009. Preventing the collapse of the Baltic cod stock through an ecosystem-based management approach. Proceedings of the National Academy of Sciences of the United States of America, 106, 14722-14727.
Lindegren, M., Checkley, D.M., Quinn, T., 2013a. Temperature dependence of Pacific sardine (Sardinops sagax) recruitment in the California Current Ecosystem revisited and revised. Canadian Journal of Fisheries and Aquatic Sciences, 70, 245-252.
Lindegren, M., Checkley, D.M., Jr., Rouyer, T., MacCall, A.D., Stenseth, N.C., 2013b. Climate, fishing, and fluctuations of sardine and anchovy in the California Current. Proceedings of the National Academy of Sciences of the United States of America, 110, 13672-13677.
Lisovenko, L.A., Andrianov, D.P., 1996. Reproductive biology of anchovy (Engraulis encrasicolus ponticus Alexandrov 1927) in the Black Sea. Scientia Marina, 60 (Supl. 2), 209- 218.
Mackenzie, B.R., Gislason, H., Möllmann, C., Köster, F.W., 2007. Impact of 21st century climate change on the Baltic Sea fish community and fisheries. Global Change Biology, 13, 1348-1367.
Merino, G., Quetglas, A., Maynou, F., Garau, A., Arrizabalaga, H. et al., 2015. Improving the performance of a Mediterranean demersal fishery toward economic objectives beyond MSY. Fisheries Research, 161, 131-144.
Norman-López, A., Pascoe, S., 2011. Net economic effects of achieving maximum economic yield in fisheries. Marine Policy, 35, 489-495.
Oguz, T., Dippner, J.W., Kaymaz, Z., 2006. Climatic regulation of the Black Sea hydro-meteorological and ecological properties at interannual-to-decadal time scales. Journal of Marine Systems, 60, 235-254.
Pascoe, S., Vieira, S., Thebaud, O., 2015. Allocating repairs and maintenance costs to fixed or variable costs in fisheries bioeconomic models. Applied Economics Letters, 22, 127-131.
Patterson, K., 1992. Fisheries for small pelagic species: an empirical approach to management targets. Reviews in Fish Biology and Fisheries, 2, 321-338.
Pianosi, F., Beven, K., Freer, J., Hall, J.W., Rougier, J. et al., 2016. Sensitivity analysis of environmental models: A systematic review with practical workflow. Environmental Modelling & Software, 79, 214-232.
Polonsky, A., Voskresenska, E., Belokopytov, V., 1997. p. 11- 24. Variability of Northwestern Black Sea Hydrography and River Discharges As Part of Global Ocean-Atmosphere Fluctuations. In: Sensitivity to Change: Black Sea, Baltic Sea and North Sea. Özsoy, E., Mikaelyan A. (Eds). Springer, Dordrecht.
Punt, A.E., Smith, A.D. M., Smith, D.C., Tuck, G.N., Klaer, N.L., 2014. Selecting relative abundance proxies for BMSY and BMEY. ICES Journal of Marine Science, 71, 469-483.
R Core Team, 2014. R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria. Sandberg, P., 2006. Variable unit costs in an output-regulated industry: The Fishery. Applied Economics, 38, 1007-1018.
Schaefer, M.B., 1954. Fisheries dynamics and the concept of maximum equilibrium catch. p. 53-64. In: Proceedings of the Gulf and Caribbean Fisheries Institute, November 1954. Gulf and Caribbean Fisheries Institute, Florida.
Schwartzlose, R.A., Alheit, J., Bakun, A., Baumgartner, T.R., Cloete, R. et al., 1999. Worldwide large-scale fluctuations of sardine and anchovy populations. South African Journal of Marine Science, 21, 289-347.
Skern‐Mauritzen, M., Ottersen, G., Handegard, N.O., Huse, G., Dingsør, G.E., et al., 2015. Ecosystem processes are rarely included in tactical fisheries management. Fish and Fisheries, 17, 165-175.
STECF, 2014. Scientific, Technical and Economic Committee for Fisheries (STECF) – Black Sea Assessments (STECF-14-14). ICES Document EUR 26896 EN, 1-421.
Sumaila, U.R., Hannesson, R., 2010. Maximum economic yield in crisis? Fish and Fisheries, 11, 461-465.
Tahvonen, O., Quaas, M.F., Voss, R., 2018. Harvesting selectivity and stochastic recruitment in economic models of age-structured fisheries. Journal of Environmental Economics and Management, 92, 659-676.
TURKSTAT, 2017. Fisheries and Aquaculture Statistics 2016. Turkish Statistical Institute, Ankara.
Tutar, Ö., 2014. Stock Assessment of the Black Sea Anchovy. MSc Thesis. Middle East Technical University, Turkey, 88 pp.
Ünal, V., Göncüoglu-Bodur, H., 2020. Analysis of the third generation buy-back program for fishing vessels in Turkey. Ege Journal of Fisheries and Aquatic Sciences, 37, 251-258.
van Deurs, M., Brooks, M. E., Lindegren, M., Henriksen, O., Rindorf, A., 2021. Biomass limit reference points are sensitive to estimation method, time‐series length and stock development. Fish and Fisheries, 22, 18-30.