Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1073/pnas.2001614117 |
The allometry of movement predicts the connectivity of communities | |
Jack Hartfelder; Chevonne Reynolds; Richard A. Stanton; Muzi Sibiya; Ara Monadjem; Robert A. McCleery; Robert J. Fletcher | |
2020-08-26 | |
发表期刊 | Proceedings of the National Academy of Sciences
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出版年 | 2020 |
英文摘要 | Connectivity has long played a central role in ecological and evolutionary theory and is increasingly emphasized for conserving biodiversity. Nonetheless, connectivity assessments often focus on individual species even though understanding and preserving connectivity for entire communities is urgently needed. Here we derive and test a framework that harnesses the well-known allometric scaling of animal movement to predict community-level connectivity across protected area networks. We used a field translocation experiment involving 39 species of southern African birds to quantify movement capacity, scaled this relationship to realized dispersal distances determined from ring-and-recovery banding data, and used allometric scaling equations to quantify community-level connectivity based on multilayer network theory. The translocation experiment explained observed dispersal distances from ring-recovery data and emphasized allometric scaling of dispersal based on morphology. Our community-level networks predicted that larger-bodied species had a relatively high potential for connectivity, while small-bodied species had lower connectivity. These community networks explained substantial variation in observed bird diversity across protected areas. Our results highlight that harnessing allometric scaling can be an effective way of determining large-scale community connectivity. We argue that this trait-based framework founded on allometric scaling provides a means to predict connectivity for entire communities, which can foster empirical tests of community theory and contribute to biodiversity conservation strategies aimed at mitigating the effects of environmental change. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/293176 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Jack Hartfelder,Chevonne Reynolds,Richard A. Stanton,et al. The allometry of movement predicts the connectivity of communities[J]. Proceedings of the National Academy of Sciences,2020. |
APA | Jack Hartfelder.,Chevonne Reynolds.,Richard A. Stanton.,Muzi Sibiya.,Ara Monadjem.,...&Robert J. Fletcher.(2020).The allometry of movement predicts the connectivity of communities.Proceedings of the National Academy of Sciences. |
MLA | Jack Hartfelder,et al."The allometry of movement predicts the connectivity of communities".Proceedings of the National Academy of Sciences (2020). |
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