气候变化领域集成服务门户(CCPortal): Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

CCPortal

DOI	10.1111/ele.12770
	Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks
	Staniczenko P.P.A.; Sivasubramaniam P.; Suttle K.B.; Pearson R.G.
发表日期	2017
ISSN	1461-023X
EISSN	1461-0248
卷号	20 期号:6
英文摘要	Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.
英文关键词	Bayesian networks; biotic interactions; climate change; community ecology; geographical range; networks; species distribution models
学科领域	abiotic factor; Bayesian analysis; biotic factor; climate change; community ecology; ecological modeling; environmental conditions; grassland; macroecology; network analysis; prediction; range expansion; spatial distribution; California; United States; Bayes theorem; biological model; California; ecology; ecosystem; grassland; Bayes Theorem; California; Ecology; Ecosystem; Grassland; Models, Biological
语种	英语
scopus关键词	abiotic factor; Bayesian analysis; biotic factor; climate change; community ecology; ecological modeling; environmental conditions; grassland; macroecology; network analysis; prediction; range expansion; spatial distribution; California; United States; Bayes theorem; biological model; California; ecology; ecosystem; grassland; Bayes Theorem; California; Ecology; Ecosystem; Grassland; Models, Biological
来源期刊	Ecology Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/118384
作者单位	National Socio-Environmental Synthesis Center (SESYNC), Annapolis, MD, United States; Department of Biology, University of Maryland, College Park, Maryland, MD, United States; Centre for Biodiversity and Environment Research, University College London, London, United Kingdom; School of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, United Kingdom; Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
推荐引用方式 GB/T 7714	Staniczenko P.P.A.,Sivasubramaniam P.,Suttle K.B.,et al. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks[J],2017,20(6).
APA	Staniczenko P.P.A.,Sivasubramaniam P.,Suttle K.B.,&Pearson R.G..(2017).Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.Ecology Letters,20(6).
MLA	Staniczenko P.P.A.,et al."Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks".Ecology Letters 20.6(2017).