数据缺乏资源评估方法在渔业资源养护中的应用研究进展  

A review of data-limited assessment methods and their applications in fishery resource conservation

作　　者：王扬 耿喆[1,2] 朱江峰 戴小杰[1,2] WANG Yang;GENG Zhe;ZHU Jiangfeng;DAI Xiaojie(College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources,Ministry of Education,Shanghai 201306,China)

机构地区：[1]上海海洋大学海洋科学学院,上海201306 [2]农业农村部大洋渔业开发重点实验室,上海201306

出　　处：《海洋渔业》2022年第5期631-639,共9页Marine Fisheries

基　　金：国家重点研发计划(2019YFD0901404)。

摘　　要：全球范围内多数鱼种缺乏足够的数据以支撑完整的资源评估,随着近年来数据缺乏资源评估方法的开发和应用,很多数据缺乏渔业能被科学有效的评估和管理。参考以往研究,概述了3类数据缺乏方法的研究进展:基于渔获量数据缺乏方法、基于体长数据缺乏方法以及适用于多鱼种情形的数据缺乏方法,并对各个模型的结构及优缺点进行了分析。重点探讨如何在资源养护中合理应用模型结果提出决策建议,并阐明在实践中需注意的问题。在后续工作中,除了加强相关数据收集工作,还可以增加管理策略评价(management strategy evaluation,MSE)和捕捞控制规则(harvest control rules,HCRs)环节,以提高渔业资源养护措施的容错性和有效性。Scientific stock assessments are the key for fishery management.They support sustainable fisheries by providing fisheries managers with the information necessary to make sound decisions.However,due to the high cost of data collection,the majority of the world’s fisheries are data-limited which lack sufficient data to carry out full stock assessment.In the United States,59%of stocks are data-limited;165 out of 262 stocks in Europe have varying degrees of data deficiency;in China,most catches data are counted by the aquatic products categories which are not specific single species.Based on these situations,scientists have been seeking simple and low-cost methods to achieve stock assessment.Therefore,data-limited methods(DLMs)have developed rapidly in the last two decades.Many fisheries that are difficult to carry out traditional stock assessment are now able to be scientifically managed.The domestic researches about DLMs are still finite,and few of them has reviewed how the results of these models can be used to help managers to develop conservation strategies.Model structures of DLMs are generally simple,and their results are therefore different from those obtained by traditional stock assessment methods.Appropriate interpretation and rational use of the results from DLMs are crucial to the determination of management measures.In this study,we divide DLMs into three categories according to data requirements:catch-based models,length-based models,and multi-species models.And we briefly summarize and review the model data requirements,model output,and the advantages and disadvantages.Then,we mainly discuss the appropriate application of DLMs into fisheries resource conservation and highlight the issues that need to be focused on in practice.Catch data are the most common fishery data.Therefore,catch-based models are the most explored and developed models.Widely used models are depletion-corrected average catch(DCAC),depletion-based stock reduction analysis(DB-SRA),an extension of catch-MSY(CMSY),catch only model-s

关 键 词：数据缺乏 资源评估 渔业资源养护 可持续产量 生物学参考点 

分 类 号：S931[农业科学—渔业资源]