When are extinctions simply bad luck? Rarefaction as a framework for disentangling selective and stochastic extinctions
When are extinctions simply bad luck? Rarefaction as a framework for disentangling selective and stochastic extinctions
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DOI：
10.1111/1365-2664.13510
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发表时间：
2019
影响因子：
5.7
通讯作者：
Kevin G. Smith;Ryan J. Almeida
中科院分区：
文献类型：
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作者：
Kevin G. Smith;Ryan J. Almeida
保护生物学的一个关键挑战是，并非所有物种在面临干扰时都有同样的灭绝可能性，但灭绝概率的这种差异有多种重叠的原因。物种灭绝风险的差异可能代表灭绝选择性，这是一个非随机过程，物种灭绝的风险是由基于特征的适应性差异引起的。此外，低丰度和/或占有率的稀有物种比普通物种更有可能灭绝，原因仅仅是随机的机会，也就是说，运气不好。除非生态学家和保护生物学家可以解开随机和选择性灭绝过程，那么预测和预防未来的灭绝将继续是一个难以捉摸的挑战。我们建议，一个常见的零模型程序，稀疏化的修改版本，可以用来解开随机物种损失的影响，从选择性非随机过程。为此，我们将基于稀疏的零模型应用于三个已发表的数据集，以描述物种稀有性在三个生物多样性丧失事件后驱动生物多样性丧失的影响：（a）疾病相关的蝙蝠下降;（B）疾病相关的两栖动物下降;（c）栖息地丧失和入侵物种相关的腹足动物下降。对于每个案例研究，我们使用稀疏化来生成生物多样性损失和物种特定灭绝概率的零期望。在我们的每个案例研究中，我们都找到了随机和非随机（选择性）灭绝的证据。我们的研究结果突出了明确考虑某些物种灭绝是随机过程的结果的重要性。换句话说，我们发现了灭绝过程中运气不佳的重要证据。我们的研究结果表明，稀疏性可以用来解开随机和非随机假设，并指导管理决策。例如，稀疏可以追溯性地用于确定风险物种的下降何时可能是由选择性而不是随机机会造成的。稀疏也可以用来前瞻性地制定物种损失的最小预测，以应对假设的干扰。鉴于其最低的数据要求和生态学家的熟悉程度，稀疏化可能是识别和保护最容易遭受全球灭绝的物种的有效和通用的工具。
A key challenge in conservation biology is that not all species are equally likely to go extinct when faced with a disturbance, but there are multiple overlapping reasons for such differences in extinction probability. Differences in species extinction risk may represent extinction selectivity, a non‐random process by which species’ risks of extinction are caused by differences in fitness based on traits. Additionally, rare species with low abundances and/or occupancies are more likely to go extinct than common species for reasons of random chance alone, that is, bad luck. Unless ecologists and conservation biologists can disentangle random and selective extinction processes, then the prediction and prevention of future extinctions will continue to be an elusive challenge.We suggest that a modified version of a common null model procedure, rarefaction, can be used to disentangle the influence of stochastic species loss from selective non‐random processes. To this end we applied a rarefaction‐based null model to three published data sets to characterize the influence of species rarity in driving biodiversity loss following three biodiversity loss events: (a) disease‐associated bat declines; (b) disease‐associated amphibian declines; and (c) habitat loss and invasive species‐associated gastropod declines. For each case study, we used rarefaction to generate null expectations of biodiversity loss and species‐specific extinction probabilities.In each of our case studies, we find evidence for both random and non‐random (selective) extinctions. Our findings highlight the importance of explicitly considering that some species extinctions are the result of stochastic processes. In other words, we find significant evidence for bad luck in the extinction process.Policy implications. Our results suggest that rarefaction can be used to disentangle random and non‐random extinctions and guide management decisions. For example, rarefaction can be used retrospectively to identify when declines of at‐risk species are likely to result from selectivity, versus random chance. Rarefaction can also be used prospectively to formulate minimum predictions of species loss in response to hypothetical disturbances. Given its minimal data requirements and familiarity among ecologists, rarefaction may be an efficient and versatile tool for identifying and protecting species that are most vulnerable to global extinction.