Selective extinctions resulting from random habitat destruction lead to under‐estimates of local and regional biodiversity loss in a manipulative field experiment
Selective extinctions resulting from random habitat destruction lead to under‐estimates of local and regional biodiversity loss in a manipulative field experiment
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随机栖息地破坏导致的选择性灭绝导致在现场操作实验中低估了当地和区域生物多样性丧失
DOI：
10.1111/gcb.15464
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发表时间：
2020
影响因子：
11.6
通讯作者：
Smith, Kevin G.
中科院分区：
文献类型：
--
作者：
Almeida, Ryan J.;Berro, Alexander A. G.;Lippert, Alston;Clary, Jake;McKlin, Sam;Scott, Erin V.;Smith, Kevin G.
土地利用变化是人类活动的一个重要原因，随着大多数生物群落的栖息地转换，人类活动可能会继续并加速。了解栖息地丧失对生物多样性影响的一种方法是通过改进工具来预测因栖息地丧失而丧失的物种数量和身份。有相对较少的方法来预测预测和更少的机会，严格评估这些预测的质量。在本文中，我们解决了这些问题，通过应用一种新的方法，稀疏的基础上预测物种损失后，随机，但聚集，栖息地丧失。我们比较了三个稀疏模型的预测，基于个体，基于样本和空间聚类，从常用的灭绝估计方法，物种面积关系（SAR）。我们将每种方法应用到一个围隔生态系统实验中，在实验中，我们的目标是预测物种丰富度和节肢动物栖息地损失50%后立即。虽然每个模型在栖息地丧失干扰后立即对物种丰富度进行了惊人准确的预测，但每个模型都显著低估了在局部（围隔生态系统内）和区域（处理范围）尺度上发生的灭绝数量。尽管我们的小规模，短期和随机应用的栖息地丧失实验具有随机性，但我们发现了灭绝选择性的令人惊讶的明确证据，例如，当栖息地丧失后灭绝概率低的丰富物种被灭绝时。即使在这个人为的实验系统中，选择性灭绝也扮演着重要的角色，这表明生态驱动的、基于特征的干扰与随机灭绝扮演着同样重要的角色，即使干扰本身没有明确的选择性。因此，中性随机零模型，如SAR和稀疏可能会低估栖息地丧失所造成的损失。尽管如此，由于预测灭绝的困难，零模型提供了有用的基准保护规划提供最小的估计和物种灭绝的概率。
Land‐use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual‐based, sample‐based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species–area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within‐mesocosm) and regional (treatment‐wide) scales. Despite the stochastic nature of our small‐scale, short‐term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait‐based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.
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关于物种面积曲线使用的一些评论
影响因子：
2.9
作者：
Peter H. Haas
通讯作者：
Peter H. Haas
影响因子：
5.7
作者：
Kevin G. Smith;Ryan J. Almeida
通讯作者：
Kevin G. Smith;Ryan J. Almeida
影响因子：
2.7
作者：
D. Simberloff
通讯作者：
D. Simberloff
使用栖息地适宜性模型和物种-面积关系来预测南非沿海森林的灭绝债务
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
Pieter I. Olivier;R. Aarde;A. Lombard
通讯作者：
A. Lombard
影响因子：
4.6
作者：
Garcia-Valdes, Raul;Bugmann, Harald;Morin, Xavier
通讯作者：
Morin, Xavier