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首页> 外文期刊>Canadian Journal of Fisheries and Aquatic Sciences >Quantifying habitat associations in marine fisheries: a generalization of the Kolmogorov-Smirnov statistic using commercial logbook records linked to archived environmental data
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Quantifying habitat associations in marine fisheries: a generalization of the Kolmogorov-Smirnov statistic using commercial logbook records linked to archived environmental data

机译:量化海洋渔业中的栖息地协会:使用链接到已归档环境数据的商业日志记录,对Kolmogorov-Smirnov统计进行概括

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摘要

Understanding species-habitat associations is critical for designing marine reserves, defining essential fish habitat, and predicting the impacts of climate change on fisheries. For many species, however, there is a paucity of fisheries-independent data that simultaneously track abundance and environmental variables, as is the case for widow rockfish (Sebastes entomelas), a commercially important fishery off the west coast of the United States. In this paper, I generalize a previous approach to identifying habitat associations so that fisheries-dependent data can be used. In analyzing Oregon commercial logbook records and archived environmental data from the National Oceanographic Data Center, I found three environmental variables (bottom depth, vertical depth of fish in the water column, and temperature) to be statistically adequate. Using a generalized Kolmogorov-Smirnov test statistic, I compared an empirically derived cumulative distribution function (CDF) of the habitat sampled to a CDF weighted by widow rockfish catch. Results suggest that the significant habitat association for widow rockfish includes bottom depths between 136 and 298 in, vertical depths between 101 and 197 in, and temperatures between 7.1 and 8.1degreesC. This novel use of commercial logbook data, which links disparate data sources and explicitly accounts for unequal spatial sampling, is a methodological advance that also provides initial insights into widow rockfish habitat preferences.
机译:了解物种-栖息地协会对于设计海洋保护区,定义基本的鱼类栖息地以及预测气候变化对渔业的影响至关重要。但是,对于许多物种而言,很少有与渔业无关的数据能够同时追踪丰度和环境变量,寡妇石鱼(Sebastes entomelas)就是这种情况,寡妇是美国西海岸的重要商业渔业。在本文中,我概括了一种用于识别栖息地关联的先前方法,以便可以使用依赖于渔业的数据。在分析俄勒冈州的商业日志记录和国家海洋数据中心的存档环境数据时,我发现三个环境变量(底部深度,水柱中鱼的垂直深度和温度)在统计上是足够的。使用广义的Kolmogorov-Smirnov检验统计量,我将根据经验得出的栖息地采样累积分布函数(CDF)与寡妇石鱼捕获加权的CDF进行了比较。结果表明,寡妇石鱼的重要生境关联包括136-298英寸的底部深度,101-197英寸的垂直深度以及7.1-8.1摄氏度的温度。商业日志数据的这种新颖用法可以链接不同的数据源,并明确说明不平等的空间采样,是一种方法学的进步,也为寡妇石鱼的栖息地偏好提供了初步见识。

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