适用于数据缺乏渔业的资源评估方法研究进展  

Review on stock assessment methods applicable to data-limited fisheries

作　　者：石永闯 樊伟[1,2] 张衡[1,2] 周为峰[1,2] 唐峰华[1,2] 吴祖立[1,2] 程田飞[1,2] 赵国庆 张孝民 SHI Yongchuang;FAN Wei;ZHANG Heng;ZHOU Weifeng;TANG Fenghua;WU Zuli;CHENG Tianfei;ZHAO Guoqing;ZHANG Xiaomin(Key Laboratory of East China Sea&Oceanic Fishery Resources Exploitation and Utilization,Ministry of Agriculture and Rural Affairs,East China Sea Fisheries Research Institute,Chinese Academy of Fishery Sciences,Shanghai 200090,China;Key and Open Laboratory of Oceanic Laboratory of Remote Sensing Information Technology in Fishing Resource,East China Sea Fisheries Research Institute,Chinese Academy of Fishery Sciences,Shanghai 200090,China;College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;Shandong Marine and Fishery Research Institute,Shandong Provincial Key Laboratory of Restoration for Marine Ecology,Yantai 264006,China)

机构地区：[1]中国水产科学研究院东海水产研究所农业农村部东海与远洋渔业资源开发利用重点实验室,上海200090 [2]中国水产科学研究院东海水产研究所渔业资源遥感信息技术重点开放实验室,上海200090 [3]上海海洋大学海洋科学学院,上海201306 [4]山东省海洋资源与环境研究院山东省海洋生态修复重点实验室,山东烟台264006

出　　处：《中国水产科学》2021年第5期673-691,共19页Journal of Fishery Sciences of China

基　　金：国家重点研发计划项目(2019YFD0901405);国家重点研发计划项目(2018YFC1406802);农业农村部外海渔业开发重点实验室开放基金项目(LOF2018-01);大洋渔业资源可持续开发教育部重点实验室开放基金项目(A1-2006-00-301109)。

摘　　要：开展渔业资源评估研究是制定渔业可持续发展策略的重要前提,而数据有限是全球渔业资源评估面临的普遍挑战。传统资源评估方法具有数据需求量大、要求高等特点,无法应用于数据缺乏渔业的资源评估中。数据缺乏方法(data-limited method)可结合少量易获得数据和相关历史生物学信息对渔业资源状况、生物学参考点以及资源量等进行评估,已经成为全球区域性渔业管理组织和资源评估学者的关注热点。本文在分析数据缺乏资源评估方法文献的基础上,对近几年开发的数据缺乏评估方法模型结构、模型输入输出、假设以及不确定性来源和分析方法等进行了回顾和归纳,同时对数据缺乏评估方法未来的研究重点和方向进行了展望。分析认为,数据缺乏渔业资源评估研究仍处于发展阶段,若渔获量和体长数据均可用,则应考虑整合了两种类型数据的模型,如LIME(length-based integrated mixed effects,基于体长的综合混合效应)模型和SSS(simple stock synthesis,简化资源整合)模型。建议今后研究中应加强以下几个方面的工作:(1)积极开展长时间、多海域、全覆盖的渔业资源独立科学调查,以获得具有代表性的样本数据;(2)对现有数据缺乏模型进一步优化,综合考虑各种因素对评估结果的影响;(3)进行完整、准确的基础生物学研究,获得较为准确的历史生物学信息,从而降低评估结果的不确定性;(4)开展基于渔获量模型和基于体长模型的模拟测试研究,提高模型对统计偏差和数据质量问题的包容性。Fisheries stock assessment is an important prerequisite for formulating sustainable fishery development strategies.Limited data is a common challenge to global fishery stock assessment,with traditional stock assessment methods inapplicable to the stock assessment of data-limited fisheries,because of the need for reliable biological information for accurately estimating species abundance.Owing to limited funding and large datasets required in such surveys,only 1%of fish stocks have had systematic assessments conducted.Therefore,it is difficult to assess the maximum sustainable yields(MSY)or determine allowable catches for most commercial fish species using traditional methods.The development of data-limited methodologies that can evaluate the status of fish stock,biological reference points and biomass in using a small amount of available data and biological information,has become the focus of global regional fishery management organizations and fishery resource scholars.Based on bibliometric analysis,we summarize and review the model structure,model input and output,assumptions,sources of uncertainty,and analysis methods of the following catch-based and length-based assessment models:catch-maximum sustainable yield(Catch-MSY),depletion based stock reduction analysis(DB-SRA),depletion corrected average catch(DCAC),simple stock synthesis(SSS),an extension of Catch-MSY(CMSY),length-based spawning potential ratio(LBSPR),length-based integrated mixed effects(LIME),length-based Bayesian(LBB),and length-based risk analysis(LBRA).The focus and direction of future research are proposed based on this analysis.The results indicate that owing to the characteristics of data-limited fisheries,stock assessment is still in the development stage.If the catch and body length data are available,a model that integrates the two types of data,such as the LIME model and the SSS model,should be considered.It is suggested that the following work should be carried out in future research:(1)to actively carry out long-term,multi-sea,and ful

关 键 词：数据缺乏渔业 资源评估 渔业管理 资源丰度 

分 类 号：S931[农业科学—渔业资源]