Volume 41 Issue 3
Mar.  2022
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Qinqin Lin, Yuying Zhang, Jiangfeng Zhu. Simulating the impacts of fishing on central and eastern tropical Pacific ecosystem using multispecies size-spectrum model[J]. Acta Oceanologica Sinica, 2022, 41(3): 34-43. doi: 10.1007/s13131-021-1902-3
Citation: Qinqin Lin, Yuying Zhang, Jiangfeng Zhu. Simulating the impacts of fishing on central and eastern tropical Pacific ecosystem using multispecies size-spectrum model[J]. Acta Oceanologica Sinica, 2022, 41(3): 34-43. doi: 10.1007/s13131-021-1902-3

Simulating the impacts of fishing on central and eastern tropical Pacific ecosystem using multispecies size-spectrum model

doi: 10.1007/s13131-021-1902-3
Funds:  The National Natural Science Foundation of China under contract No. 41676120.
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  • Corresponding author: Email: jfzhu@shou.edu.cn
  • Received Date: 2021-02-26
  • Accepted Date: 2021-04-23
  • Available Online: 2021-11-23
  • Publish Date: 2022-03-01
  • The size-spectrum model has been considered a useful tool for understanding the structures of marine ecosystems and examining management implications for fisheries. Based on Chinese tuna longline observer data from the central and eastern tropical Pacific Ocean and published data, we developed and calibrated a multispecies size-spectrum model of twenty common and commercially important species in this area. We then use the model to project the status of the species from 2016 to 2050 under five constant-fishing-mortality management scenarios: (1) F=0; (2) F=Frecent, the average fishing mortality from 2013 to 2015; (3) F=0.5Frecent; (4) F=2Frecent and (5) F=3Frecent. Several ecological indicators were used to track the dynamics of the community structure under different levels of fishing, including the mean body weight, slope of community size spectra (Slope), and total biomass. The validation demonstrated that size-at-age data of nine main catch species between our model predictions and those empirical data from assessments by the Western and Central Pacific Fisheries Commission matched well, with the R2>0.9. The direct effect of fishing was the decreasing abundance of large-sized individuals. The mean body weight in the community decreased by ~1 500 g (21%) by 2050 when F doubled from Frecent to 2Frecent. The higher the fishing mortality, the steeper the Slope was. The projection also indicated that fishing impacts reflected by the total biomass did not increase proportionally with the increasing fishing mortality. The biomass of the main target tuna species was still abundant over the projection period under the recent fishing mortality, except Albacore tuna (Thunnus alalunga). For sharks and billfishes, their biomass remained at relatively higher levels only under the F=0 scenario. The results can serve as a scientific reference for alternative management strategies in the tropical Pacific Ocean.
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  • [1]
    Andersen K H, Beyer J E. 2006. Asymptotic size determines species abundance in the marine size spectrum. The American Naturalist, 168(1): 54–61. doi: 10.1086/504849
    [2]
    Andersen K H, Blanchard J L, Fulton E A, et al. 2016a. Assumptions behind size-based ecosystem models are realistic. ICES Journal of Marine Science, 73(6): 1651–1655
    [3]
    Andersen K H, Brander K, Ravn-Jonsen L. 2015. Trade-offs between objectives for ecosystem management of fisheries. Ecological Applications, 25(5): 1390–1396. doi: 10.1890/14-1209.1
    [4]
    Andersen K H, Jacobsen N S, Farnsworth K D. 2016b. The theoretical foundations for size spectrum models of fish communities. Canadian Journal of Fisheries and Aquatic Sciences, 73(4): 575–588. doi: 10.1139/cjfas-2015-0230
    [5]
    Andersen K H, Pedersen M. 2010. Damped trophic cascades driven by fishing in model marine ecosystems. Proceedings of the Royal Society B: Biological Sciences, 277(1682): 795–802. doi: 10.1098/rspb.2009.1512
    [6]
    Andersen K P, Ursin E. 1977. A multispecies extension to the Beverton and Holt theory of fishing: with accounts of phosphorus circulation and primary production. Meddelelser fra Danmarks Fiskeri- og Havundersø gelser, 7: 319–435
    [7]
    Bauer B, Horbowy J, Rahikainen M, et al. 2019. Model uncertainty and simulated multispecies fisheries management advice in the Baltic Sea. PLoS ONE, 14(1): e0211320. doi: 10.1371/journal.pone.0211320
    [8]
    Beverton R J H, Holt S J. 1957. On the Dynamics of Exploited Fish Populations. Fisheries Investigations Series 2, Volume 19. London: U. K. Ministry of Agriculture and Fisheries, 1–533
    [9]
    Billfish Working Group Report. 2015. Stock assessment update for striped marlin (Kajikia audax) in the Western and Central North Pacific Ocean through 2013. Kona, HI, USA: International Scientific Committee for Tuna and Tuna-like Species in the North Pacific Ocean, 97
    [10]
    Billfish Working Group Report. 2016. Stock assessment update for blue marlin (Makaira nigricans) in the Pacific Ocean through 2014. Sapporo, Hokkaido, Japan: International Scientific Committee for Tuna and Tuna-like Species in the North Pacific Ocean, 90
    [11]
    Blanchard J L, Andersen K H, Scott F, et al. 2014. Evaluating targets and trade-offs among fisheries and conservation objectives using a multispecies size spectrum model. Journal of Applied Ecology, 51(3): 612–622. doi: 10.1111/1365-2664.12238
    [12]
    Brown J H, Gillooly J F, Allen A P, et al. 2004. Toward a metabolic theory of ecology. Ecology, 85(7): 1771–1789. doi: 10.1890/03-9000
    [13]
    Casini M, Lövgren J, Hjelm J, et al. 2008. Multi-level trophic cascades in a heavily exploited open marine ecosystem. Proceedings of the Royal Society B: Biological Sciences, 275(1644): 1793–1801. doi: 10.1098/rspb.2007.1752
    [14]
    Chai T, Draxler R R. 2014. Root mean square error (RMSE) or mean absolute error (MAE)? —Arguments against avoiding RMSE in the literature. Geoscientific Model Development, 7(3): 1247–1250. doi: 10.5194/gmd-7-1247-2014
    [15]
    Collie J S, Botsford L W, Hastings A, et al. 2016. Ecosystem models for fisheries management: finding the sweet spot. Fish and Fisheries, 17(1): 101–125. doi: 10.1111/faf.12093
    [16]
    Daan N, Gislason H, Pope J G, et al. 2005. Changes in the North Sea fish community: evidence of indirect effects of fishing?. ICES Journal of Marine Science, 62(2): 177–188. doi: 10.1016/j.icesjms.2004.08.020
    [17]
    Dai Xiaojie, Wu Feng, Wang Xuefang. 2017. Annual report to the commission Part 1: information on fisheries, research and statistics. Information paper SC13-AR/CCM-03. In: Report to Thirteenth Regulation Session of the WCPFC Scientific Committee (SC13). Rarotonga, Cook Islands: Western and Central Pacific Fisheries Commission
    [18]
    DeMartini E E, Uchiyama J H, Williams H A. 2000. Sexual maturity, sex ratio, and size composition of swordfish, Xiphias gladius, caught by the Hawaii-based pelagic longline fishery. Fishery Bulletin, 98(3): 489–506
    [19]
    Dulvy N K, Polunin N V C, Mill A C, et al. 2004. Size structural change in lightly exploited coral reef fish communities: evidence for weak indirect effects. Canadian Journal of Fisheries and Aquatic Sciences, 61(3): 466–475. doi: 10.1139/f03-169
    [20]
    Farley J, Eveson P, Krusic-Golub K, et al. 2017. Project 35: Age, growth and maturity of bigeye tuna in the western and central Pacific Ocean. Working paper WCPFC-SC13-2017/SA-WP-01 Rev 1. In: Report to Thirteenth Regulation Session of the WCPFC Scientific Committee (SC13). Rarotonga, Cook Islands: Western and Central PacificFisheries Commission
    [21]
    Feng Huili, Zhu Jiangfeng, Chen Yan. 2019. Construction and historical comparison of ecosystem structure of the eastern tropical Pacific Ocean based on Ecopath model. Journal of Shanghai Ocean University, 28(6): 921–932
    [22]
    Food and Agricultural Organization of the United Nations. 2001. What is the code of conduct for responsible fisheries?. Rome, Italy: Food and Agricultural Organization of the United Nations
    [23]
    Francis M, Griggs L, Maolagáin C Ó. 2004. Growth rate, age at maturity, longevity and natural mortality rate of moonfish (Lampris guttatus). In: Final Research Report for the Ministry of Fisheries Research Project TUN2003-01. Taihoro, Nukurangi: National Institute of Water and Atmospheric Research
    [24]
    Genner M J, Sims D W, Southward A J, et al. 2010. Body size-dependent responses of a marine fish assemblage to climate change and fishing over a century-long scale. Global Change Biology, 16(2): 517–527. doi: 10.1111/j.1365-2486.2009.02027.x
    [25]
    Gerrodette T, Olson R, Reilly S, et al. 2012. Ecological metrics of biomass removed by three methods of purse-seine fishing for tunas in the eastern tropical Pacific Ocean. Conservation Biology, 26(2): 248–256. doi: 10.1111/j.1523-1739.2011.01817.x
    [26]
    Giacomini H C, Shuter B J, Baum J K. 2016. Size-based approaches to aquatic ecosystems and fisheries science: a symposium in honour of Rob Peters. Canadian Journal of Fisheries and Aquatic Sciences, 73(4): 471–476. doi: 10.1139/cjfas-2016-0100
    [27]
    Gibbs R H Jr. 1960. Alepisaurus brevirostris, a new species of lancetfish from the western North Atlantic. Museum of Comparative Zoology, 123: 1–14
    [28]
    Gislason H, Rice J C. 1998. Modelling the response of size and diversity spectra of fish assemblages to changes in exploitation. ICES Journal of Marine Science, 55(3): 362–370. doi: 10.1006/jmsc.1997.0323
    [29]
    Hartvig M, Andersen K H, Beyer J E. 2011. Food web framework for size-structured populations. Journal of Theoretical Biology, 272(1): 113–122. doi: 10.1016/j.jtbi.2010.12.006
    [30]
    Houle J E, Farnsworth K D, Rossberg A G, et al. 2012. Assessing the sensitivity and specificity of fish community indicators to management action. Canadian Journal of Fisheries and Aquatic Sciences, 69(6): 1065–1079. doi: 10.1139/f2012-044
    [31]
    Jacobsen N S, Burgess M G, Andersen K H. 2017. Efficiency of fisheries is increasing at the ecosystem level. Fish and Fisheries, 18(2): 199–211. doi: 10.1111/faf.12171
    [32]
    Jacobsen N S, Essington T E, Andersen K H. 2015. Comparing model predictions for ecosystem-based management. Canadian Journal of Fisheries and Aquatic Sciences, 73(4): 666–676
    [33]
    Jacobsen N S, Gislason H, Andersen K H. 2014. The consequences of balanced harvesting of fish communities. Proceedings of the Royal Society B: Biological Sciences, 281(1775): 20132701. doi: 10.1098/rspb.2013.2701
    [34]
    Jennings S, Greenstreet S P R, Reynolds J D. 1999. Structural change in an exploited fish community: a consequence of differential fishing effects on species with contrasting life histories. Journal of Animal Ecology, 68(3): 617–627. doi: 10.1046/j.1365-2656.1999.00312.x
    [35]
    Law R. 2000. Fishing, selection, and phenotypic evolution. ICES Journal of Marine Science, 57(3): 659–668. doi: 10.1006/jmsc.2000.0731
    [36]
    Lin Qinqin, Zhu Jiangfeng. 2020. Topology-based analysis of pelagic food web structure in the central and eastern tropical Pacific Ocean based on longline observer data. Acta Oceanologica Sinica, 39(6): 1–9. doi: 10.1007/s13131-020-1592-2
    [37]
    M’Kendrick A G. 1925. Applications of mathematics to medical problems. Proceedings of the Edinburgh Mathematical Society, 44: 98–130. doi: 10.1017/S0013091500034428
    [38]
    Miyake M, Guillotreau P, Sun C H, et al. 2010. Recent developments in the tuna industry: stocks, fisheries, management, processing, trade and markets. FAO Fisheries and Aquaculture Technical Paper, 543: 1–125
    [39]
    Myers R A, Baum J K, Shepherd T D, et al. 2007. Cascading effects of the loss of apex predatory sharks from a coastal ocean. Science, 315(5820): 1846–1850. doi: 10.1126/science.1138657
    [40]
    Pauly D, Christensen V, Dalsgaard J, et al. 1998. Fishing down marine food webs. Science, 279(5352): 860–863. doi: 10.1126/science.279.5352.860
    [41]
    Polovina J J, Abecassis M, Howell E A, et al. 2009. Increases in the relative abundance of mid-trophic level fishes concurrent with declines in apex predators in the subtropical North Pacific, 1996−2006. Fishery Bulletin, 107(4): 523–531
    [42]
    Polovina J J, Woodworth-Jefcoats P A. 2013. Fishery-induced changes in the subtropical Pacific pelagic ecosystem size structure: observations and theory. PLoS ONE, 8(4): e62341. doi: 10.1371/journal.pone.0062341
    [43]
    Reum J C P, Blanchard J L, Holsman K K, et al. 2019. Species-specific ontogenetic diet shifts attenuate trophic cascades and lengthen food chains in exploited ecosystems. Oikos, 128(7): 1051–1064. doi: 10.1111/oik.05630
    [44]
    Rice J, Gislason H. 1996. Patterns of change in the size spectra of numbers and diversity of the North Sea fish assemblage, as reflected in surveys and models. ICES Journal of Marine Science, 53(6): 1214–1225. doi: 10.1006/jmsc.1996.0146
    [45]
    Rochet M J, Trenkel V M. 2003. Which community indicators can measure the impact of fishing? A review and proposals. Canadian Journal of Fisheries and Aquatic Sciences, 60(1): 86–99. doi: 10.1139/f02-164
    [46]
    Schindler D E, Hilborn R. 2015. Prediction, precaution, and policy under global change. Science, 347(6225): 953–954. doi: 10.1126/science.1261824
    [47]
    Scott F, Blanchard J L, Andersen K H. 2013. Multispecies, Trait and Community Size Spectrum Ecological Modelling in R (Mizer). Luxembourg: Publications Office of the European Union, 196
    [48]
    Scott F, Blanchard J L, Andersen K H. 2014. mizer: an R package for multispecies, trait-based and community size spectrum ecological modelling. Methods in Ecology and Evolution, 5(10): 1121–1125. doi: 10.1111/2041-210X.12256
    [49]
    Sheldon R W, Prakash A, Sutcliffe W H Jr. 1972. The size distribution of particles in the ocean. Limnology and Oceanography, 17(3): 327–340. doi: 10.4319/lo.1972.17.3.0327
    [50]
    Shelley C, Sato M, Small C, et al. 2014. Bycatch in longline fisheries for tuna and tuna-like species: a global review of status and mitigation measures. FAO Fisheries and Aquaculture Technical Paper, 588: 1–199
    [51]
    Shin Y J, Cury P. 2004. Using an individual-based model of fish assemblages to study the response of size spectra to changes in fishing. Canadian Journal of Fisheries and Aquatic Sciences, 61(3): 414–431. doi: 10.1139/f03-154
    [52]
    Shin Y J, Rochet M J, Jennings S, et al. 2005. Using size-based indicators to evaluate the ecosystem effects of fishing. ICES Journal of Marine Science, 62(3): 384–396. doi: 10.1016/j.icesjms.2005.01.004
    [53]
    Sibert J, Hampton J, Kleiber P, et al. 2006. Biomass, size, and trophic status of top predators in the Pacific Ocean. Science, 314(5806): 1773–1776. doi: 10.1126/science.1135347
    [54]
    Simpson S D, Jennings S, Johnson M P, et al. 2011. Continental shelf-wide response of a fish assemblage to rapid warming of the sea. Current Biology, 21(18): 1565–1570. doi: 10.1016/j.cub.2011.08.016
    [55]
    Sissenwine M, Murawski S. 2004. Moving beyond “intelligent thinking”: advancing an ecosystem approach to fisheries. In: Perspectives on Ecosystem-based Approaches to the Management of Marine Resources. Marine Ecology Progress Series, 274: 269–303. doi: 10.3354/meps274269
    [56]
    Ursin E. 1973. On the prey size preferences of cod and dab. Meddelelser fra Danmarks Fiskeri-og Havundersø gelser, 7: 85–98
    [57]
    von Foerster H. 1959. Some remarks on changing populations. In: Stohlman J F, ed. The Kinetics of Cellular Proliferation. New York: Grune and Stratton, 382–407
    [58]
    Woodworth-Jefcoats P A, Blanchard J L, Drazen J C. 2019. Relative impacts of simultaneous stressors on a pelagic marine ecosystem. Frontiers in Marine Science, 6: 383. doi: 10.3389/fmars.2019.00383
    [59]
    Worm B, Sandow M, Oschlies A, et al. 2005. Global patterns of predator diversity in the open oceans. Science, 309(5739): 1365–1369. doi: 10.1126/science.1113399
    [60]
    Zhang Chongliang, Chen Yong, Thompson K, et al. 2016. Implementing a multispecies size-spectrum model in a data-poor ecosystem. Acta Oceanologica Sinica, 35(4): 63–73. doi: 10.1007/s13131-016-0822-0
    [61]
    Zhang Chongliang, Chen Yong, Xu Binduo, et al. 2018. Evaluating fishing effects on the stability of fish communities using a size-spectrum model. Fisheries Research, 197: 123–130. doi: 10.1016/j.fishres.2017.09.004
    [62]
    Zhu Jiangfeng, Xu Liuxiong, Dai Xiaojie, et al. 2012. Comparative analysis of depth distribution for seventeen large pelagic fish species captured in a longline fishery in the central-eastern Pacific Ocean. Scientia Marina, 76(1): 149–157. doi: 10.3989/scimar.03379.16C
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