小型中上层海洋鱼类资源评估研究进展
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摘要
小型中上层海洋鱼类是重要的渔业资源,目前其捕捞产量约占到全球海洋渔获量二分之一。小型中上层海洋鱼类具有生命周期短、生长速度快、分布不均匀、易受环境因素影响等生物学特点,近年来,一些小型中上层海洋鱼类渔获量出现下降趋势,为保证其资源的可持续利用,对其进行准确的资源评估研究和制定合理有效的管理策略显得尤为重要。以文献计量统计分析为基础,对20多年来应用于小型中上层海洋鱼类资源评估的模型方法以及所需数据类型进行归纳与回顾,同时对模型中重要的参数估计、不确定性来源进行总结。分析认为,由于缺乏完整、准确的生物学信息导致无法对小型中上层海洋鱼类使用传统的资源评估方法进行评估,因此,其资源评估研究仍处在发展阶段。建议今后研究中应开展以下工作:1)努力提高现有模型的评估精度,尽可能考虑更多影响因素; 2)要进行长期系统的渔业资源独立调查; 3)充分利用体长等易获得数据,开发体长结构模型和基于生态系统的评估模型,降低模型选择的局限性。
Small pelagic marine fish is an important fishery resource and currently accounts for about one-half of global marine catches. It is widely distributed and can be harvested from various fisheries around the world.It is of great commercial value. Small pelagic marine fish have biological characteristics such as short life cycle,fast growth rate,uneven distribution and vulnerability to environmental factors. In recent years,with the expansion of commercial fishing scale,some small pelagic marine fish catches have declined. In order to ensure the sustainable use of small pelagic fish resources,it is particularly important to conduct accurate resource assessment studies and develop reasonable and effective management strategies. Based on bibliometric analysis,this paper summarizes and reviews the model methods and required data types used in the stock assessment of small pelagic marine fish resources for more than 20 years,and at the same time carries out important parameter estimation and studies uncertainty sources in the model. The analysis believes that due to the lack of complete and accurate biological information,it is impossible to evaluate the use of traditional resource assessment methods for small pelagic marine fish. Therefore,its resource assessment research is still in the development stage. The paper discusses the problems in the resource assessment methods for small pelagic marine fish and the future development direction. It is suggested that the following work should be carried out in the future research: 1) Efforts should be made to improve the evaluation accuracy of existing models,and as much as possible multiple influencing factors should be considered; 2)Long-term systematic independent investigation of fishery resource should be considereds; 3) Make full use of body length and other readily available data,develop length structure models and ecosystem-based stock assessment models in order to reduce the limitations of model selection.
Small pelagic marine fish is an important fishery resource and currently accounts for about one-half of global marine catches. It is widely distributed and can be harvested from various fisheries around the world.It is of great commercial value. Small pelagic marine fish have biological characteristics such as short life cycle,fast growth rate,uneven distribution and vulnerability to environmental factors. In recent years,with the expansion of commercial fishing scale,some small pelagic marine fish catches have declined. In order to ensure the sustainable use of small pelagic fish resources,it is particularly important to conduct accurate resource assessment studies and develop reasonable and effective management strategies. Based on bibliometric analysis,this paper summarizes and reviews the model methods and required data types used in the stock assessment of small pelagic marine fish resources for more than 20 years,and at the same time carries out important parameter estimation and studies uncertainty sources in the model. The analysis believes that due to the lack of complete and accurate biological information,it is impossible to evaluate the use of traditional resource assessment methods for small pelagic marine fish. Therefore,its resource assessment research is still in the development stage. The paper discusses the problems in the resource assessment methods for small pelagic marine fish and the future development direction. It is suggested that the following work should be carried out in the future research: 1) Efforts should be made to improve the evaluation accuracy of existing models,and as much as possible multiple influencing factors should be considered; 2)Long-term systematic independent investigation of fishery resource should be considereds; 3) Make full use of body length and other readily available data,develop length structure models and ecosystem-based stock assessment models in order to reduce the limitations of model selection.
引文
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[18]MAUNDERA M N,PUNT A E.A review of integrated analysis in fisheries stock assessment[J].Fisheries Research,2013,142(6):61-74.
[19]HILBORN R,WALTERS C J.Quantitative fisheries stock assessment:Choice,dynamics and uncertainty[M].New York:Chapman and Hall,1992:570.
[20]MESNIL B.The catch-survey analysis(CSA)method of fish stock assessment:an evaluation using simulated data[J].Fisheries Research,2003,63(2):193-212.
[21]SCHAEFER M B.Some aspects of the dynamics of populations important to the management of the commercial marine fisheries[J].Inter-American Tropical Tuna Commission Bulletin,1954,1(2):23-56.
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[23]ARNOLD L,HEPPELL S.Testing the robustness of data-poor assessment methods to uncertainty in catch and biology:a retrospective approach[J].ICESJournal of Marine Science,2015,72(1):243-250.
[24]BENTLEY N.Data and time poverty in fisheries estimation:some approaches and potential solutions[J].ICES Journal of Marine Science,2015,72(1):186-193.
[25]GEROMONT H F,BUTTERWORTH D S.Generic management procedures for data-poor fisheries:forecasting with few data[J].ICES Journal of Marine Science,2015,72(1):251-261.
[26]ROEL B A,BUTTERWORTH D S.Assessment of the South African chokka squid Loligo vulgaris reynaudii:is disturbance of aggregations by the recent jig fisheries having a neglect impact on recruitment?[J].Fisheries Research,2000,48(3):213-228.
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[28]ROEL B A,OLIVERIRA J A A D,BEGGS S.Atwo-stage biomass model for Irish Sea herring allowing for additional variance in the recruitment index caused by mixing of stocks[J].ICES Journal of Marine Science,2009,66(8):1808-1813.
[29]TRENKEL V M.A two-stage biomass random effects model for stock assessment without catches:What can be estimated using only biomass survey indices?[J].Canadian Journal of Fisheries and Aquatic Sciences,2008,65(6):1024-1035.
[30]IBAIBARRIAGA L,FERNANDEZ C,URIARTE A.Gaining information from commercial catch for a Bayesian two-stage biomass dynamic model:application to Bay of Biscay anchovy[J].ICESJournal of Marine Science,2011,68(7),1435-1446.
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[32]MCGARVEY R,LINNANE A J,FEENSTRA J E,et al.Integrating recapture-conditioned movement estimation into spatial stock assessment:a South Australian lobster fishery application[J].Fisheries Research,2010,105(2):80-90.
[33]DERSO R B.Harvesting strategies and parameter estimation for an age-structured model[J].Canadian Journal of Fisheries and Aquatic Sciences,1980,37(2):339-348.
[34]KIMURA D K,BALSIGER J W.Generalized stock reduction analysis[J].Canadian Journal of Fisheries and Aquatic Sciences,1984,41(9):1325-1333.
[35]KIMURA D K.Changes to stock reduction analysis indicated by schnute’s general theory[J].Canadian Journal of Fisheries and Aquatic Sciences,1985,42(12):2059-2060.
[36]SHEPHERD G,CIERI M,POWERS M,et al.Transboundary resources assessment committee:Gulf of Maine/Georges Bank Atlantic herring stock assessment update[R].Massachusetts,Woods Hole,NOAA Fisheries Northeast Fisheries Science Center,2009.
[37]OBOYLE R,OVERHOLTZ W.Proceedings of trans boundary resources assessment committee(TRAC):Benchmark review of stock assessment models for Gulf of Maine and Georges Bank herring[R].Massachusetts,Woods Hole,NOAA Fisheries Northeast Fisheries Science Center,2009.
[38]MICHAEL T,SMITH T.Methods for stock assessment of crustacean fisheries[J].Fisheries Research,2003,65(1):231-256.
[39]ALLEN K R.Some methods for estimating exploited populations[J].Journal of the Fisheries Board of Canada,1966,23(10):1553-1574.
[40]CHAPMAN D G.Estimation of population size and sustainable yield of Sei whales in the Antarctic[J].Report-International Whaling Commission,1974,(24):82-90.
[41]SANTOJANNI A,ARNERI E,BARRY C,et al.Trends of anchovy(Engraulis encrasicolus,L.)biomass in the northern and central Adriatic Sea[J].Scientia Marina,2003,67(3):327-340.
[42]SANTOJANNI A,ARNERI E,BERNARDINI V,et al.Effects of environmental variables on recruitment of anchovy in the Adriatic Sea[J].Climate Research,2006,31(2-3):181-193.
[43]CARPI P,SANTOJANNI A,DONATO F,et al.Ajoint stock assessment for the anchovy stock of the northern and central Adriatic Sea:comparison of two catch-at-age models[J].Scientia Marina,2015,79(1):57-70.
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