气候变化领域集成服务门户(CCPortal): How to make more out of community data? A conceptual framework and its implementation as models and software

CCPortal

DOI	10.1111/ele.12757
	How to make more out of community data? A conceptual framework and its implementation as models and software
	Ovaskainen O.; Tikhonov G.; Norberg A.; Guillaume Blanchet F.; Duan L.; Dunson D.; Roslin T.; Abrego N.
发表日期	2017
ISSN	1461-023X
EISSN	1461-0248
卷号	20 期号:5
英文摘要	Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R- and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd
英文关键词	Assembly process; biotic filtering; community distribution; community modelling; community similarity; environmental filtering; functional trait; joint species distribution model; metacommunity; phylogenetic signal
学科领域	biotic factor; community ecology; conceptual framework; data set; phylogenetics; software; spatiotemporal analysis; time series analysis; Bayes theorem; biodiversity; ecosystem; software; theoretical model; Bayes Theorem; Biodiversity; Ecosystem; Models, Theoretical; Software
语种	英语
scopus关键词	biotic factor; community ecology; conceptual framework; data set; phylogenetics; software; spatiotemporal analysis; time series analysis; Bayes theorem; biodiversity; ecosystem; software; theoretical model; Bayes Theorem; Biodiversity; Ecosystem; Models, Theoretical; Software
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/118397
作者单位	Department of Biosciences, University of Helsinki, P.O. Box 65, Helsinki, FI-00014, Finland; Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, N-7491, Trondheim, Norway; Department of Mathematics and Statistics, McMaster University, 1280 Main Street West HamiltonON L8S 4K1, Canada; Département de biologie, Faculté des sciences, Université de Sherbrooke, 2500 Boulevard Université SherbrookeQC J1K 2R1, Canada; Department of Statistical Science, Duke University, P.O. Box 90251, Durham, United States; Department of Ecology, Swedish University of Agricultural Sciences, Box 7044, Uppsala, 75651, Sweden; Department of Agricultural Sciences, University of Helsinki, P.O. Box 27, Helsinki, FI-00014, Finland
推荐引用方式 GB/T 7714	Ovaskainen O.,Tikhonov G.,Norberg A.,et al. How to make more out of community data? A conceptual framework and its implementation as models and software[J],2017,20(5).
APA	Ovaskainen O..,Tikhonov G..,Norberg A..,Guillaume Blanchet F..,Duan L..,...&Abrego N..(2017).How to make more out of community data? A conceptual framework and its implementation as models and software.Ecology Letters,20(5).
MLA	Ovaskainen O.,et al."How to make more out of community data? A conceptual framework and its implementation as models and software".Ecology Letters 20.5(2017).