Premium
Predictions of biodiversity are improved by integrating trait‐based competition with abiotic filtering
Author(s) -
Chalmandrier Loïc,
Stouffer Daniel B.,
Purcell Adam S. T.,
Lee William G.,
Tanentzap Andrew J.,
Laughlin Daniel C.
Publication year - 2022
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.13980
Subject(s) - abiotic component , ecology , competition (biology) , trait , biodiversity , pairwise comparison , biology , community structure , community , coexistence theory , limiting , ecosystem , computer science , artificial intelligence , engineering , mechanical engineering , programming language
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.