Department of Chemical and Physical Sciences, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, Canada L5 L 1C6.
Department of Earth and Environmental Sciences, Vanderbilt University, 5726 Stevenson Center, Nashville, TN 37240, USA.
Proc Biol Sci. 2022 Jul 27;289(1979):20220440. doi: 10.1098/rspb.2022.0440.
Many authors have noted the apparent 'decoupling' of the taxonomic and ecological severity of mass extinction events, with no widely accepted mechanistic explanation for this pattern having been offered. Here, we test between two key factors that potentially influence ecological severity: biosphere entropy (a measure of functional redundancy), and the degree of functional selectivity (in terms of deviation from a pattern of random extinction with respect to functional entities). While theoretical simulations suggest that the Shannon entropy of a given community prior to an extinction event determines the expected outcome following a perturbation of a given magnitude, actual variation in Shannon entropy between major extinction intervals is insufficient to explain the observed variation in ecological severity. Within this information-theoretic framework, we show that it is the degree of functional selectivity that is expected to primarily determine the ecological impact of a given perturbation when levels of functional redundancy are not substantially different.
许多作者已经注意到，大规模灭绝事件的分类学和生态严重程度似乎出现了“脱钩”，但对于这种模式，尚未提出广泛接受的机械论解释。在这里，我们检验了两个潜在影响生态严重程度的关键因素：生物圈熵（衡量功能冗余的指标），以及功能选择性的程度（相对于功能实体的随机灭绝模式的偏差）。虽然理论模拟表明，给定群落在灭绝事件之前的香农熵决定了给定幅度的扰动后的预期结果，但主要灭绝间隔之间的香农熵实际变化不足以解释观察到的生态严重程度的变化。在这个信息论框架内，我们表明，当功能冗余水平没有实质性差异时，功能选择性的程度预计将主要决定给定扰动的生态影响。
