Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is of...Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.展开更多
为客观地揭示世界大洋性鱿钓渔业的研究态势及研究热点,促进我国大洋性鱿钓渔业的可持续发展,基于Web of Science核心合集数据,利用文献计量学方法,对其文献的增长趋势及期刊分布进行分析,并基于作者和机构合作网络、关键词共现的知识...为客观地揭示世界大洋性鱿钓渔业的研究态势及研究热点,促进我国大洋性鱿钓渔业的可持续发展,基于Web of Science核心合集数据,利用文献计量学方法,对其文献的增长趋势及期刊分布进行分析,并基于作者和机构合作网络、关键词共现的知识图谱及突变检测等方法,探究世界大洋性鱿钓渔业的研究热点及其研究前沿,结果表明:研究文献总体上呈递增趋势,且文献的科研影响力及国际关注度非常高;作者、机构间均形成了频繁而稳定的合作关系,作者合作方面形成了以陈新军、陈勇等作者为核心及以RODHOUSE等为核心的两大作者合作群,机构合作方面分别以上海海洋大学和英国南极调查局为核心的机构间建立了广泛的合作关系;海洋淡水生物学、渔业、海洋学和生态学等为世界大洋性鱿钓渔业的优势学科领域。当前世界大洋性鱿钓渔业的研究前沿有4个方向:(1)开展重要大洋性经济鱿鱼种类的基础生物学和生态学研究;(2)研究大洋性鱿鱼资源评估及其资源对全球气候和环境变化的响应机理;(3)结合海洋遥感信息研究渔业栖息地及跨学科交叉融合;(4)开展基于生态系统的大洋性鱿钓渔业资源综合管理研究。展开更多
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA092303)the Public Science and Technology Research Funds Projects of Ocean(No.20155014)+2 种基金the Shanghai Leading Academic Discipline Projectthe Funding Program for Outstanding Dissertation in Shanghai Ocean UniversitySupported by SHOU International Center for Marine Studies and Shanghai 1000 Talent Program
文摘Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.
文摘为客观地揭示世界大洋性鱿钓渔业的研究态势及研究热点,促进我国大洋性鱿钓渔业的可持续发展,基于Web of Science核心合集数据,利用文献计量学方法,对其文献的增长趋势及期刊分布进行分析,并基于作者和机构合作网络、关键词共现的知识图谱及突变检测等方法,探究世界大洋性鱿钓渔业的研究热点及其研究前沿,结果表明:研究文献总体上呈递增趋势,且文献的科研影响力及国际关注度非常高;作者、机构间均形成了频繁而稳定的合作关系,作者合作方面形成了以陈新军、陈勇等作者为核心及以RODHOUSE等为核心的两大作者合作群,机构合作方面分别以上海海洋大学和英国南极调查局为核心的机构间建立了广泛的合作关系;海洋淡水生物学、渔业、海洋学和生态学等为世界大洋性鱿钓渔业的优势学科领域。当前世界大洋性鱿钓渔业的研究前沿有4个方向:(1)开展重要大洋性经济鱿鱼种类的基础生物学和生态学研究;(2)研究大洋性鱿鱼资源评估及其资源对全球气候和环境变化的响应机理;(3)结合海洋遥感信息研究渔业栖息地及跨学科交叉融合;(4)开展基于生态系统的大洋性鱿钓渔业资源综合管理研究。
