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Incorporating individual variation in survival, reproduction and detection rates when projecting dynamics of small populations
Ecological Modelling ( IF 3.1 ) Pub Date : 2021-06-11 , DOI: 10.1016/j.ecolmodel.2021.109647
Doug P. Armstrong , Elizabeth H. Parlato , Peter G.H. Frost

Survival, reproduction and detection rates may vary greatly amongst individuals. Failure to account for this variation results in biased inferences about age effects and population size. However, individual variation is not normally considered in population viability analysis, potentially leading to misleading projections for small populations. We present a novel data-augmentation approach for incorporating individual variation in rates in integrated population models. By adding rows to survival and reproduction matrices for hypothetical individuals in both the past and future, inferences about individual variation derived from Bayesian hierarchical modelling are propagated into population projections. We apply this method to a small reintroduced population of hihi (Notiomystis cincta) at Bushy Park, New Zealand, where individuals vary greatly in reproductive success, longevity and detection probability, and ongoing management decisions depend on modelling projections. We compare the results to those from an alternative model that ignores individual variation but incorporates sex and age effects. The modelling confirmed pronounced individual variation in all rates, and greatly altered their interpretation. Estimated survival and reproduction rates of average individuals became much lower and apparent age effects disappeared. In addition, the estimated proportion of fledglings produced by unmonitored females dropped from 23% to 9%. Incorporation of individual variation in the integrated population model resulted in more optimistic population projections over the next four years although the difference was minor in relation to the 95% prediction limits. The methodology presented has broad potential for assessing whether population projections used to guide management of small populations are sensitive to individual variation.



中文翻译:

在预测小种群的动态时,结合生存、繁殖和检测率的个体差异

存活率、繁殖率和检出率可能因人而异。未能解释这种变化会导致对年龄影响和人口规模的有偏见的推断。然而,在种群生存力分析中通常不考虑个体变异,这可能会导致对小种群的预测产生误导。我们提出了一种新的数据增强方法,用于将个体变化率纳入综合人口模型。通过在过去和未来假设个体的生存和繁殖矩阵中添加行,从贝叶斯分层建模得出的关于个体变异的推论被传播到人口预测中。我们将此方法应用于重新引入的小型hihi ( Notiomystis cincta)在新西兰的布什公园,那里的个体在繁殖成功率、寿命和检测概率方面差异很大,持续的管理决策取决于建模预测。我们将结果与忽略个体差异但包含性别和年龄影响的替代模型的结果进行比较。建模证实了所有比率的明显个体差异,并极大地改变了他们的解释。平均个体的估计存活率和繁殖率变得低得多,明显的年龄效应消失了。此外,估计由不受监控的雌性产生的雏鸟比例从 23% 下降到 9%。尽管与 95% 的预测限制相比差异很小,但在综合人口模型中纳入个体变异导致对未来四年的人口预测更加乐观。所提出的方法具有广泛的潜力,可用于评估用于指导小种群管理的种群预测是否对个体变异敏感。

更新日期:2021-06-11
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