Chalmandrier, Loic and Stouffer, Daniel B. and Purcell, Adam S. T. and Lee, William G. and Tanentzap, Andrew J. and Laughlin, Daniel C. (2022) Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering. ECOLOGY LETTERS, 25 (5). pp. 1277-1289. ISSN 1461-023X, 1461-0248
Full text not available from this repository. (Request a copy)Abstract
All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Approaches to understanding abiotic filtering and competitive interactions have generally been developed independently. Consequently, integrating those factors to predict species abundances and community structure remains an unresolved challenge. We introduce a new synthetic framework that models both abiotic filtering and competition by using functional traits. First, our framework estimates species carrying capacities along abiotic gradients. Second, it estimates pairwise competitive interactions as a function of species trait differences. Applied to the study of a complex wetland community, our combined approach more than doubles the explained variance of species abundances compared to a model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances, bringing us closer to more accurate predictions of biodiversity structure in a changing world.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | PLANT FUNCTIONAL TRAITS; COMMUNITY; COEXISTENCE; FRAMEWORK; MODELS; DISTRIBUTIONS; RELATEDNESS; MECHANISMS; DYNAMICS; RULES; abiotic filtering; community modelling; competition; functional trait; plant ecology; species abundances; wetland |
| Subjects: | 500 Science > 580 Botanical sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Pflanzenwissenschaften > Group Theoretical Ecology (Prof. Dr. Florian Hartig) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 16 Feb 2024 08:33 |
| Last Modified: | 16 Feb 2024 08:33 |
| URI: | https://pred.uni-regensburg.de/id/eprint/58002 |
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