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Natural mortality and body size in fish populations
Fisheries Research ( IF 2.4 ) Pub Date : 2022-04-19 , DOI: 10.1016/j.fishres.2022.106327
Kai Lorenzen 1 , Edward V. Camp 1 , Taryn M. Garlock 1
Affiliation  

Fisheries stock assessments increasingly account for size-dependence in natural mortality rates, usually by modeling mortality as a power function of body length. Various empirical studies have indicated a scaling of mortality with length in the range of − 0.84 to − 1.11, but substantially different scaling exponents ranging from − 0.75 to − 1.5 have been proposed on theoretical grounds or derived from some empirical models. To resolve these controversies and provide a well-supported default estimate of scaling for stock assessments, we re-analyzed two major data sets used in previous studies that supported different scaling exponents, and a combined data set. Both original data sets and the combined data yielded within-population exponents close to − 1 when analyzed using joint-slope mixed-effects models with population as a random effect. When population effects were disregarded, regression models yielded exponents that did not correctly reflect within-population scaling. The greatest deviations from the correct within-population scaling of approximately − 1 occurred in multiple regression models of mortality, size, and growth parameters. We conclude that within- and among-population scaling of natural mortality should be clearly distinguished, and that within-population scaling of natural mortality with length in fish populations is highly consistent at approximately − 1. We also explored empirical models for predicting the intercept of the mortality-length relationship for a given population from growth parameters.



中文翻译:

鱼类种群的自然死亡率和体型

渔业资源评估越来越多地考虑自然死亡率的大小依赖性,通常通过将死亡率建模为体长的幂函数。各种实证研究表明死亡率在 - 0.84 到 - 1.11 的范围内进行缩放,但基于理论或从一些经验模型中提出了从 - 0.75 到 - 1.5 范围内的显着不同的缩放指数。为了解决这些争议并为种群评估提供有充分支持的默认缩放估计,我们重新分析了先前研究中使用的支持不同缩放指数的两个主要数据集,以及一个组合数据集。当使用人口作为随机效应的联合斜率混合效应模型进行分析时,原始数据集和组合数据均产生接近 - 1 的人口内指数。当忽略人口影响时,回归模型产生的指数不能正确反映人口内的比例。在死亡率、大小和生长参数的多元回归模型中,与正确的大约 - 1 的种群内标度的最大偏差发生了。我们得出的结论是,自然死亡率的种群内和种群间比例应该清楚地区分,并且自然死亡率的种群内自然死亡率与鱼类种群长度的比例在大约 - 1 时高度一致。我们还探索了预测截距的经验模型根据生长参数得出给定人口的死亡率-长度关系。在死亡率、大小和生长参数的多元回归模型中,与正确的大约 - 1 的种群内标度的最大偏差发生了。我们得出的结论是,自然死亡率的种群内和种群间比例应该清楚地区分,并且自然死亡率的种群内自然死亡率与鱼类种群长度的比例在大约 - 1 时高度一致。我们还探索了预测截距的经验模型根据生长参数得出给定人口的死亡率-长度关系。在死亡率、大小和生长参数的多元回归模型中,与正确的大约 - 1 的种群内标度的最大偏差发生了。我们得出的结论是,自然死亡率的种群内和种群间比例应该清楚地区分,并且自然死亡率的种群内自然死亡率与鱼类种群长度的比例在大约 - 1 时高度一致。我们还探索了预测截距的经验模型根据生长参数得出给定人口的死亡率-长度关系。

更新日期:2022-04-20
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