Improving spatial predictions of taxonomic, functional and phylogenetic diversity

Details

Serval ID
serval:BIB_574B39D33520
Type
Article: article from journal or magazin.
Collection
Publications
Title
Improving spatial predictions of taxonomic, functional and phylogenetic diversity
Journal
Journal of Ecology
Author(s)
D'Amen M., Mateo R.G., Pottier J., Thuiller W., Maiorano L., Pellissier L., Ndiribe C., Salamin N., Guisan A.
ISSN
1365-2745
ISSN-L
0022-0477
Publication state
Published
Issued date
2018
Peer-reviewed
Oui
Volume
106
Number
1
Pages
76-86
Language
english
Abstract
In this study, we compare two community modelling approaches to determine their ability to predict the taxonomic, functional and phylogenetic properties of plant assemblages along a broad elevation gradient and at a fine resolution. The first method is the standard stacking individual species distribution modelling (SSDM) approach, which applies a simple environmental filter to predict species assemblages. The second method couples the SSDM and macroecological modelling (MEMSSDM-MEM) approaches to impose a limit on the number of species co-occurring at each site. Because the detection of diversity patterns can be influenced by different levels of phylogenetic or functional trees, we also examine whether performing our analyses from broad to more exact structures in the trees influences the performance of the two modelling approaches when calculating diversity indices. We found that coupling the SSDM with the MEM improves the overall predictions for the three diversity facets compared with those of the SSDM alone. The accuracy of the SSDM predictions for the diversity indices varied greatly along the elevation gradient, and when considering broad to more exact structure in the functional and phylogenetic trees, the SSDM-MEM predictions were more stable. SSDM-MEM moderately but significantly improved the prediction of taxonomic diversity, which was mainly driven by the corrected number of predicted species. The performance of both modelling frameworks increased when predicting the functional and phylogenetic diversity indices. In particular, fair predictions of the taxonomic composition by SSDM-MEM led to increasingly accurate predictions of the functional and phylogenetic indices, suggesting that the compositional errors were associated with species that were functionally or phylogenetically close to the correct ones; however, this did not always hold for the SSDM predictions.Synthesis. In this study, we tested the use of a recently published approach that couples species distribution and macroecological models to provide the first predictions of the distribution of multiple facets of plant diversity: taxonomic, functional and phylogenetic. Moderate but significant improvements were obtained; thus, our results open promising avenues for improving our ability to predict the different facets of biodiversity in space and time across broad environmental gradients when functional and phylogenetic information is available.
Keywords
assemblage modelling, ecological assembly rules, macroecological models, similarity effect, SOrensen dissimilarity index, stacked species distribution models, vegetation
Web of science
Create date
08/01/2018 9:11
Last modification date
03/03/2018 17:23
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