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首页> 外文期刊>PLoS Computational Biology >Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method
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Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method

机译:用经验贝叶斯方法确定增长的个体差异及其对生活史和人口过程的影响

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The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.
机译:生活在同一种群中的生物之间的人口统计学和生命历史过程差异对生态和进化动力学具有重要影响。现代的统计和计算方法允许对观察到的生长变化的单个决定因素和共享决定因素(在同质群体中)进行调查。我们使用经验贝叶斯方法,使用具有随机效应的冯·贝塔朗菲增长模型来估计体细胞生长的个体和共享变化。为了说明该方法的强大功能和通用性,我们考虑了生活在斯洛文尼亚溪流中的两个鳟鱼鲑鱼(Salmo marmoratus)种群,这些个体中带有单独标签的鱼已经采样了15年以上。我们使用出生年份队列,生命第一年的人口密度以及个体随机效应作为von Bertalanffy增长函数的参数k(增长率)和(渐近大小)的潜在预测指标。我们的结果表明,在两个种群的整个大理石鳟鱼一生中,规模等级基本保持不变。根据Akaike信息准则(AIC),最佳模型显示了不同的出生年份队列增长模式,并且在考虑了队列效应后,增长轨迹存在明显的个体差异。对于这两个人群,包括生命第一年的密度在内的模型都表明,随着生命早期人口密度的增加,增长趋于下降。模型验证表明,使用随机效应模型对个体生长轨迹的预测要比基于鱼类平均年龄的预测更为准确。

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