唐政^1,2, 单秀娟^3,2, 金显仕^3,2
1.上海海洋大学 海洋科学学院, 上海 201306;2.中国水产科学研究院 黄海水产研究所, 农业农村部海洋渔业可持续发展重点实验室, 山东省渔业资源与生态环境重点实验室, 山东 青岛 266071;3.青岛海洋科学与技术试点国家实验室 海洋渔业科学与食物产出过程功能实验室, 山东 青岛 266237

摘要:
渔业资源调查是指利用一定的采样设计，对渔业种群进行空间布点采样，以获取研究区域内鱼类时空分布以及生物学和生态学信息。但是大量的研究表明，不同的鱼类分布适合不同的采样设计，需要根据鱼类的分布特点和调查目标（种群丰度等）优化采样设计，保证数据的准确性和精度。近年来，相关的研究有很多，涉及不同采样设计的比较和应用以及影响数据质量因素的探究。作者着重介绍了定点采样、传统方法、适应性方法和基于地理统计学方法，叙述了计算机模拟及重采样技术在采样设计优化中的应用以及相对偏差、相对估计误差、设计效果和变异系数等评价采样设计性能的指标，同时对采样设计中需要注意的问题进行介绍，最后进行了总结并对未来的研究工作进行展望。
关键词:渔业资源调查采样设计优化计算机模拟重采样
DOI：10.11759/hykx20180910001
分类号:S932
基金项目:国家重点研发计划（2017YFE0104400）；国家重点基础研究发展计划（2015CB453303）；山东省泰山****专项基金项目；青岛海洋科学与技术国家试点实验室‘鳌山人才’培养计划项目（2017ASTCP-ES07）

A review of optimization of sampling design for fishery-independent surveys
TANG Zheng^1,2, SHAN Xiu-juan^3,2, JIN Xian-shi^3,2
1.College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;2.Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs of PR China, Shandong Provincial Key Laboratory of Fishery Resources and Ecological Environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China;3.Function Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266237, China
Abstract:
Fishery-independent surveys involve sampling in certain areas according to study designs based on statistical principles for collecting high-quality abundance details and biological and ecological data at species and community levels. A large number of studies have demonstrated that different distribution patterns of fishes are suitable for different sampling designs. Therefore, it is necessary to optimize the sampling design according to the distribution characteristics of fishes and the objective (such as population abundance). Several related studies have been recently conducted on the comparison of different sampling designs and their applications, as well as on the exploration of factors affecting data quality. In this paper, we introduce the stationary sampling method, the traditional sampling method, the adaptive sampling method, and the geostatistical sampling method. We then describe the application of computer simulation of sampling in the optimization of sampling designs. In addition, we introduce the indicators of performance for sampling designs, such as relative bias, relative estimation error, design effect, and coefficient of variation. Finally, we provide a discussion regarding the problems associated with sampling designs and present the prospects of their future development.
Key words:fishery-independent surveyssampling designoptimizationcomputer simulationresample method





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