A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties

Details

Serval ID
serval:BIB_B0CA3BF49B70
Type
Article: article from journal or magazin.
Collection
Publications
Title
A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties
Journal
Journal of Biogeography
Author(s)
Pellissier L., Espíndola A., Pradervand J.-N., Dubuis A., Pottier J., Ferrier S., Guisan A.
ISSN
0305-0270
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Volume
40
Number
10
Pages
1939-1946
Language
english
Abstract
Aim
Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities.
Location The western Swiss Alps.
Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities.
Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections.
Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results
Keywords
Species distribution models, species richness, phylogenetic diversity, elevation, butterfly, uncertainty, stochasticity
Web of science
Create date
22/04/2013 11:49
Last modification date
20/08/2019 15:19
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