Journal
ECOLOGY LETTERS
Volume 25, Issue 7, Pages 1618-1628Publisher
WILEY
DOI: 10.1111/ele.14011
Keywords
Bayesian; biological realism; empirical data; exotic; native; species interactions; stochasticity; York gum-jam woodlands
Categories
Funding
- ARC Discovery Grant [DP170100837]
- NSF EPSCoR Track 1 RII [EPS-1655726]
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Modern coexistence theory models often fail to account for the complexity present in natural systems, such as stochastic variation in biological processes, heterogeneity among individuals, and plasticity in trait values. This study uses a Bayesian modelling framework to propagate uncertainty in coexistence outcomes and finds that considering this complexity leads to different predictions of coexistence versus competitive exclusion.
Natural systems contain more complexity than is accounted for in models of modern coexistence theory. Coexistence modelling often disregards variation arising from stochasticity in biological processes, heterogeneity among individuals and plasticity in trait values. However, these unaccounted-for sources of uncertainty are likely to be ecologically important and have the potential to impact estimates of coexistence. We applied a Bayesian modelling framework to data from an annual plant community in Western Australia to propagate uncertainty in coexistence outcomes using the invasion criterion and ratio of niche to fitness differences. We found accounting for this uncertainty altered predictions of coexistence versus competitive exclusion for 3 out of 14 species pairs and yielded a probability of priority effects for an additional species pair. The propagation of uncertainty arising from sources of biological complexity improves our ability to predict coexistence more accurately in natural systems.
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