Sample size optimization for cluster design of bottom trawl fish surveys in the Yellow River estuary

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 黄河口鱼类底拖网调查采样断面数的优化 DOI: 作者: 作者单位: 1. 中国海洋大学 水产学院, 山东 青岛 266003;2. 上海海洋大学 海洋科学学院, 上海 201306;3. 国家远洋渔业工程技术研究中心, 上海 201306;4. 青岛海洋科学与技术国家实验室, 海洋渔业科学与食物产出过程功能实验室, 山东 青岛 266000 作者简介: 王晶(1990-),女,博士研究生,主要从事渔业资源与生态学研究.E-mail:wangjing9_1@sina.cn 通讯作者: 中图分类号: S932 基金项目: 公益性行业（农业）科研专项经费项目（201303050）. Sample size optimization for cluster design of bottom trawl fish surveys in the Yellow River estuary Author: Affiliation: 1. College of Fisheries, Ocean University of China, Qingdao 266003, China;2. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;3. National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;4. Laboratory for Marine Fisheries Science and Food Production Processes;Qingdao National Laboratory for Marine Science and Technology, Qingdao 266000, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:优化调查采样设计方案，利用有限的调查成本获取准确可靠的渔业资源数据，对于开展独立于渔业的科学调查十分重要。根据2013年8、10月和2014年2、5月在黄河口及其邻近水域进行的渔业资源底拖网调查数据，选取短吻红舌鳎（）作为目标鱼种，以其平均个体体长、平均个体体重为调查采样优化目标，利用计算机模拟方法对黄河口水域的渔业资源底拖网调查生物学数据进行再抽样，以平均体长、平均体重估计值的相对估计误差（REE）、相对偏差（RB）和变异系数（CV）作为优化评价指标，对基于整群抽样方法的黄河口及邻近海域的调查采样断面数进行优化。结果表明，对于目标鱼种的平均体长、平均体重指标，模拟估计值的REE、RB和CV均随着断面数的减少不断增加，调查断面数少于3时，各指标的变化幅度较大。断面数由5减少至3，REE值平均增加2%，RB值平均增加0.13%，CV值平均增加1.95%，同时渔获量降低近40%。因此，断面数为3可视为黄河口及邻近海域可接受的最优调查断面数。 Abstract:Fishery-independent surveys are essential for collecting high-quality data to support the stock assessments and management of regular fisheries. In general, such programs are more costly and time-consuming than commercial fishery-dependent programs. Thus, considerable interest exists in using computer simulations to optimize methods for obtaining high-quality data with limited sampling effort. Currently, high intensity fishery-independent bottom trawl surveys may negatively affect and disturb fish populations and the ecosystem of fragile estuarine habitats. These areas support many important fishery species; however, they are also among the most extensively affected and threatened aquatic environments due to fishing pressure and environmental stressors such as coastal development. In this study, we developed computer simulations to evaluate and optimize sampling of mean body length and weight of target fish species in a cluster sampling survey. For use in simulations, bottom trawl surveys were conducted in the Yellow River estuary and its adjacent waters during 2013 (August, October) and 2014 (February, May) to collect abundance and biological-trait data on red tongue sole (). The relative estimation error (REE), relative bias (RB), and coefficient of variation (CV) were used to measure the performance (accuracy, precision, and efficiency) of sampling schemes. These indices increased for simulated data when the number of sampling sections decreased. In the current survey design, a reduction in sampling-section number from five to three would reduce sampling effort by 40%, while increasing REE by only~2% in about 40% of the catches. Thus, three sections are acceptable for surveys designed to obtain size-based indicators. This study also showed that sampling-effort optimization may vary between different survey objectives. Therefore, a post-survey analysis will improve fishery-independent survey designs based on specific survey goals, thereby yielding more effective survey data. 参考文献 相似文献 引证文献