1. The effect of non-linear competitive interactions on quantifying niche and fitness differences
- Author
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Frederik DeLaender, Po-Ju Ke, Remi Millet, Jurg W. Spaak, and Andrew D. Letten
- Subjects
Coexistence theory ,Alternative methods ,Ecology ,Computer science ,media_common.quotation_subject ,Ecological Modeling ,Niche ,Inference ,Standard methods ,Competition (biology) ,Nonlinear system ,Community dynamics ,Econometrics ,media_common - Abstract
The niche and fitness differences of modern coexistence theory separate mechanisms into stabilizing and equalizing components. Although this decomposition can help us predict and understand species coexistence, the extent to which mechanistic inference is sensitive to the method used to partition niche and fitness differences remains unclear. We apply two alternative methods to assess niche and fitness differences to four well-known community models. We show that because standard methods based on linear approximations do not capture the full community dynamics, they can sometimes lead to incorrect predictions of coexistence and misleading interpretations of stabilizing and equalizing mechanisms. Specifically, they fail when both species occupy the same niche or in the presence of positive frequency dependence. Conversely, a more recently developed method to decompose niche and fitness differences, which accounts for the full non-linear dynamics of competition, consistently identifies the correct contribution of stabilizing and equalizing components. This approach further reveals that when the true complexity of the system is taken into account, essentially all mechanisms comprise both stabilizing and equalizing components and that local maxima and minima of stabilizing and equalizing mechanisms exist. Amidst growing interest in the role of non-additive and higher order interactions in regulating species coexistence, we propose that the effective decomposition of niche and fitness differences will become increasingly reliant on methods that account for the inherent non-linearity of community dynamics.
- Published
- 2023