Extinction risk depends strongly on factors contributing to stochasticity
Extinction risk depends strongly on factors contributing to stochasticity
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DOI：
10.1038/nature06922
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发表时间：
2008-07-03
期刊：
影响因子：
64.8
通讯作者：
Hastings, Alan
中科院分区：
文献类型：
--
作者：
Melbourne, Brett A.;Hastings, Alan
自然种群的灭绝风险取决于影响个体的随机因素，并通过将这些因素纳入随机模型（1-9）来估计。随机性可以分为四类，包括个体水平上出生和死亡的概率性质（人口统计随机性（2）），人口水平上出生和死亡率在时间或地点之间的变化（环境随机性（1，3）），个体的性别（6，8）和人口中个体之间生命率的变化（人口统计异质性（7，9））。包括所有这些因素的机械随机模型以前没有被开发来研究它们对灭绝风险的综合影响。在这里，我们推导出一个家庭的随机Ricker模型使用不同的组合，所有这些随机因素，并表明灭绝的风险强烈依赖于组合的因素，有助于随机性。此外，我们表明，只有与完整的随机模型可以正确地确定环境和人口的相对重要性的变化，因此灭绝的风险。使用完整的模型，我们发现，随机性的人口统计学来源的赤拟谷盗（红粉甲虫）的实验室人口的变异性的突出原因，而只使用标准的简单的模型会导致错误的结论，环境的变异性占主导地位。我们的研究结果表明，目前对自然种群灭绝风险的估计可能被大大低估，因为变异性被错误地归因于环境，而不是这里描述的人口因素，这些因素对相同的变异性水平带来更高的灭绝风险。
Extinction risk in natural populations depends on stochastic factors that affect individuals, and is estimated by incorporating such factors into stochastic models(1-9). Stochasticity can be divided into four categories, which include the probabilistic nature of birth and death at the level of individuals ( demographic stochasticity(2)), variation in population- level birth and death rates among times or locations ( environmental stochasticity(1,3)), the sex of individuals(6,8) and variation in vital rates among individuals within a population ( demographic heterogeneity(7,9)). Mechanistic stochastic models that include all of these factors have not previously been developed to examine their combined effects on extinction risk. Here we derive a family of stochastic Ricker models using different combinations of all these stochastic factors, and show that extinction risk depends strongly on the combination of factors that contribute to stochasticity. Furthermore, we show that only with the full stochastic model can the relative importance of environmental and demographic variability, and therefore extinction risk, be correctly determined. Using the full model, we find that demographic sources of stochasticity are the prominent cause of variability in a laboratory population of Tribolium castaneum ( red flour beetle), whereas using only the standard simpler models would lead to the erroneous conclusion that environmental variability dominates. Our results demonstrate that current estimates of extinction risk for natural populations could be greatly underestimated because variability has been mistakenly attributed to the environment rather than the demographic factors described here that entail much higher extinction risk for the same variability level.