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Constructing stock abundance indices from catch and effort data: Some nuts and bolts

机译:根据捕获量和工作量数据构建库存丰度指数:一些细节

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Construction of annual indices of stock abundance based on the standardisation of catch and effort data remains central to many fisheries assessments. However, while the use of advanced statistical methods has helped catch rates to be standardised accounting for many explanatory variables, some of the more routine aspects of constructing abundance indices, such as how the index is constructed from the model parameters, receives little explanation in many analyses. This has lead to a lack of understanding as to how the indices are constructed and in some instances incorrect techniques have been applied. This lack of understanding can be a particular issue when interactions are used in the standardising model, especially those which contain interactions with the temporal effects over which the time-series of the abundance index is required. Other issues include the use of weighted model fits, the influence of anomalous data values, how best to impute missing values when required, the consequences of model mis-specification, and the use of random-effects. In this study, the basic approach for constructing abundance indices is outlined and a worked example using simulated data is presented to explore the nature of these issues and several techniques are suggested for dealing with them and to overcome potential biases. Finally, the methods presently used by ICCAT scientists for constructing abundance indices are reviewed. (C) 2014 Elsevier B.V. All rights reserved.
机译:基于捕捞量和努力量数据标准化来建立年度种群丰度指数,仍然是许多渔业评估的核心。但是,尽管使用先进的统计方法已帮助将汇率标准化以解释许多解释变量,但在构造丰裕指数的一些较常规方面,例如如何从模型参数构造指数,在许多方面却很少得到解释。分析。这导致对如何构造索引以及在某些情况下使用了不正确的技术缺乏了解。当在标准化模型中使用交互时,尤其是那些包含具有时间效应的交互的交互作用,需要对丰度指数的时间序列进行交互时,这种缺乏理解可能是一个特殊的问题。其他问题包括加权模型拟合的使用,异常数据值的影响,在需要时如何最好地估算缺失值,模型规格不正确的后果以及使用随机效应。在这项研究中,概述了构建丰度指数的基本方法,并给出了一个使用模拟数据的工作示例,以探讨这些问题的性质,并提出了几种处理这些问题并克服潜在偏差的技术。最后,回顾了ICCAT科学家目前用于构建丰度指数的方法。 (C)2014 Elsevier B.V.保留所有权利。

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