Competitive dominance in plant communities: Modeling approaches and theoretical predictions

• Published in: Journal of theoretical biology Vol. 502; p. 110349
• Main Authors: Capitán, José A., Cuenda, Sara, Alonso, David
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 07.10.2020
• Subjects: Birth-death-immigration processes; Continuous-time Markov processes; Hierarchical competition; Spatially-explicit stochastic dynamics; Birth-death-immigration processes; Hierarchical competition; Continuous-time Markov processes; Spatially-explicit stochastic dynamics
• ISSN: 0022-5193; 1095-8541; 1095-8541
• DOI: 10.1016/j.jtbi.2020.110349

•Quantifying species coexistence processes is a subject of paramount importance.•Two Markov models based on trait hierarchies competitive dominance are proposed.•The spatially-implicit model predicts a significant degree of trait clustering.•The spatially-explicit model yields clustering patterns across spatial scales.•Our predictions are amenable to empirical testing in plant communities. Quantitative predictions about the processes that promote species coexistence are a subject of active research in ecology. In particular, competitive interactions are known to shape and maintain ecological communities, and situations where some species out-compete or dominate over some others are key to describe natural ecosystems. Here we develop ecological theory using a stochastic, synthetic framework for plant community assembly that leads to predictions amenable to empirical testing. We propose two stochastic, continuous-time Markov models that incorporate competitive dominance through a hierarchy of species heights. The first model, which is spatially implicit, predicts both the expected number of species that survive and the conditions under which heights are clustered in realized model communities. The second one allows spatially-explicit interactions of individuals and alternative mechanisms that can help shorter plants overcome height-driven competition, and it demonstrates that clustering patterns remain, not only locally but also across increasing spatial scales. Moreover, although plants are actually height-clustered in the spatially-explicit model, plant species abundances are not necessarily skewed to taller plants.