Competitive dominance in plant communities: Modeling approaches and theoretical predictions. (7th October 2020)
- Record Type:
- Journal Article
- Title:
- Competitive dominance in plant communities: Modeling approaches and theoretical predictions. (7th October 2020)
- Main Title:
- Competitive dominance in plant communities: Modeling approaches and theoretical predictions
- Authors:
- Capitán, José A.
Cuenda, Sara
Alonso, David - Abstract:
- Highlights: 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. Abstract: 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 spatialHighlights: 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. Abstract: 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. … (more)
- Is Part Of:
- Journal of theoretical biology. Volume 502(2020)
- Journal:
- Journal of theoretical biology
- Issue:
- Volume 502(2020)
- Issue Display:
- Volume 502, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 502
- Issue:
- 2020
- Issue Sort Value:
- 2020-0502-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10-07
- Subjects:
- Continuous-time Markov processes -- Birth-death-immigration processes -- Hierarchical competition -- Spatially-explicit stochastic dynamics
Biology -- Periodicals
Biological Science Disciplines -- Periodicals
Biology -- Periodicals
Biologie -- Périodiques
Theoretische biologie
Biology
Periodicals
571.05 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00225193/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jtbi.2020.110349 ↗
- Languages:
- English
- ISSNs:
- 0022-5193
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5069.075000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13549.xml