Author
Listed:
- Florent Mazel
(Simon Fraser University
University of British Columbia
University of British Columbia)
- Matthew W. Pennell
(University of British Columbia
University of British Columbia)
- Marc W. Cadotte
(University of Toronto-Scarborough
University of Toronto)
- Sandra Diaz
(CONICET and FECFyN - Universidad Nacional de Córdoba)
- Giulio Valentino Dalla Riva
(University of British Columbia)
- Richard Grenyer
(University of Oxford)
- Fabien Leprieur
(Université de Montpellier)
- Arne O. Mooers
(Simon Fraser University)
- David Mouillot
(Université de Montpellier
James Cook University)
- Caroline M. Tucker
(University of North Carolina-Chapel Hill)
- William D. Pearse
(Utah State University)
Abstract
In the face of the biodiversity crisis, it is argued that we should prioritize species in order to capture high functional diversity (FD). Because species traits often reflect shared evolutionary history, many researchers have assumed that maximizing phylogenetic diversity (PD) should indirectly capture FD, a hypothesis that we name the “phylogenetic gambit”. Here, we empirically test this gambit using data on ecologically relevant traits from >15,000 vertebrate species. Specifically, we estimate a measure of surrogacy of PD for FD. We find that maximizing PD results in an average gain of 18% of FD relative to random choice. However, this average gain obscures the fact that in over one-third of the comparisons, maximum PD sets contain less FD than randomly chosen sets of species. These results suggest that, while maximizing PD protection can help to protect FD, it represents a risky conservation strategy.
Suggested Citation
Florent Mazel & Matthew W. Pennell & Marc W. Cadotte & Sandra Diaz & Giulio Valentino Dalla Riva & Richard Grenyer & Fabien Leprieur & Arne O. Mooers & David Mouillot & Caroline M. Tucker & William D., 2018.
"Prioritizing phylogenetic diversity captures functional diversity unreliably,"
Nature Communications, Nature, vol. 9(1), pages 1-9, December.
Handle:
RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05126-3
DOI: 10.1038/s41467-018-05126-3
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Cited by:
- Stock, Michiel & Piot, Niels & Vanbesien, Sarah & Meys, Joris & Smagghe, Guy & De Baets, Bernard, 2021.
"Pairwise learning for predicting pollination interactions based on traits and phylogeny,"
Ecological Modelling, Elsevier, vol. 451(C).
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