globalchange  > 气候变化与战略
DOI: 10.1073/pnas.2001614117
论文题名:
The allometry of movement predicts the connectivity of communities
作者: Hartfelder J.; Reynolds C.; Stanton R.A.; Sibiya M.; Monadjem A.; McCleery R.A.; Fletcher R.J.; Jr.
刊名: Proceedings of the National Academy of Sciences of the United States of America
ISSN: 0027-8424
出版年: 2020
卷: 117, 期:36
起始页码: 22274
结束页码: 22280
语种: 英语
英文关键词: Birds ; Dispersal ; Landscape ; Network ; Translocation experiment
Scopus关键词: allometry ; article ; bird ; community care ; conservation biology ; environmental change ; nonhuman ; theoretical study ; animal ; animal dispersal ; biological model ; bird ; ecosystem ; physiology ; Animal Distribution ; Animals ; Birds ; Ecosystem ; Models, Biological
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. © 2020 National Academy of Sciences. All rights reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/164057
Appears in Collections:气候变化与战略

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作者单位: Hartfelder, J., Interdisciplinary Program in Ecology, University of Florida, Gainesville, FL 32611, United States; Reynolds, C., School of Animal, Plant and Environmental Science, University of the Witwatersrand, Braamfontein, Johannesburg, 2000, South Africa, FitzPatrick Institute of African Ornithology, Department of Science and Technology, National Research Foundation (DST/NRF), Centre of Excellence, University of Cape Town, Rondebosch, Cape Town, 7700, South Africa; Stanton, R.A., Interdisciplinary Program in Ecology, University of Florida, Gainesville, FL 32611, United States; Sibiya, M., Interdisciplinary Program in Ecology, University of Florida, Gainesville, FL 32611, United States; Monadjem, A., Department of Biological Sciences, University of Eswatini, Kwaluseni, M202, Swaziland, Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, Pretoria, 0028, South Africa; McCleery, R.A., Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, Pretoria, 0028, South Africa, Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, United States; Fletcher, R.J., Jr., Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, United States

Recommended Citation:
Hartfelder J.,Reynolds C.,Stanton R.A.,et al. The allometry of movement predicts the connectivity of communities[J]. Proceedings of the National Academy of Sciences of the United States of America,2020-01-01,117(36)
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