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将范围大小与威胁相匹配,以对生物多样性风险进行稳健预测。

Scaling range sizes to threats for robust predictions of risks to biodiversity.

机构信息

Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Sydney, NSW 2052, Australia.

New South Wales Office of Environment and Heritage, Hurstville, NSW 2220, Australia.

出版信息

Conserv Biol. 2018 Apr;32(2):322-332. doi: 10.1111/cobi.12988. Epub 2018 Feb 20.

Abstract

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems.

摘要

对生物多样性风险的评估通常依赖于物种和生态系统的空间分布。在这些评估中广泛使用的范围大小指标,如占有面积 (AOO),对测量尺度敏感,因此有人提出在更精细的尺度或根据生物分布的形状或生态特征在不同的尺度上测量它们。尽管 AOO 在数十年的红色名录评估中占据主导地位,但预测物种灭绝或生态系统崩溃风险的适当 AOO 空间尺度仍未得到检验和争议。目前还没有对 AOO 作为预测风险的指标的尺度敏感性、最佳 AOO 尺度与威胁尺度之间的关系以及网格不确定性的影响进行定量评估。我们使用随机模拟模型来探索具有聚类、分散和线性分布模式的生态系统和物种的风险,这些模式受到不同频率和空间范围的威胁事件的影响。AOO 是风险的准确预测指标(0.81<|r|<0.98),当用网格细胞测量时,网格细胞的大小是事件最大可能受威胁面积的 0.1-1.0 倍,表现最佳。与之前的断言相反,在这些相对较粗的尺度上估计 AOO 比在更精细的 AOO 尺度上估计(例如,当测量单元小于最大威胁面积的 1%)更好地预测风险。最优尺度取决于威胁的空间尺度,而不是生物分布的形状或大小。尽管我们发现网格测量误差有很大的潜力,但 IUCN 目前用于估计 AOO 的指南消除了几何不确定性,并为评估物种和生态系统面临的景观尺度威胁所带来的风险纳入了有效的缩放程序。

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