SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

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Institution
Title
SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages
Journal
Journal of Biogeography
Author(s)
Guisan A., Rahbeck C.
ISSN
0305-0270
Publication state
Published
Issued date
2011
Peer-reviewed
Oui
Volume
38
Number
8
Pages
1433-1444
Language
english
Abstract
Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.
Keywords
Biodiversity, community properties, ecological assembly rules, ecological niche modelling, macroecological constraints, species richness, species sorting, species source pool, stacked species predictions
Web of science
Open Access
Yes
Create date
11/03/2011 17:01
Last modification date
20/08/2019 15:22
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