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Low-dimensional trade-offs fail to explain richness and structure in species-rich plant communities

  • Mathematical models and ecological theory suggest that low-dimensional life history trade-offs (i.e. negative correlation between two life history traits such as competition vs. colonisation) may potentially explain the maintenance of species diversity and community structure. In the absence of trade-offs, we would expect communities to be dominated by 'super-types' characterised by mainly positive trait expressions. However, it has proven difficult to find strong empirical evidence for such trade-offs in species-rich communities. We developed a spatially explicit, rule-based and individual-based stochastic model to explore the importance of low-dimensional trade-offs. This model simulates the community dynamics of 288 virtual plant functional types (PFTs), each of which is described by seven life history traits. We consider trait combinations that fit into the trade-off concept, as well as super-types with little or no energy constraints or resource limitations, and weak PFTs, which do not exploit resources efficiently. The model isMathematical models and ecological theory suggest that low-dimensional life history trade-offs (i.e. negative correlation between two life history traits such as competition vs. colonisation) may potentially explain the maintenance of species diversity and community structure. In the absence of trade-offs, we would expect communities to be dominated by 'super-types' characterised by mainly positive trait expressions. However, it has proven difficult to find strong empirical evidence for such trade-offs in species-rich communities. We developed a spatially explicit, rule-based and individual-based stochastic model to explore the importance of low-dimensional trade-offs. This model simulates the community dynamics of 288 virtual plant functional types (PFTs), each of which is described by seven life history traits. We consider trait combinations that fit into the trade-off concept, as well as super-types with little or no energy constraints or resource limitations, and weak PFTs, which do not exploit resources efficiently. The model is parameterised using data from a fire-prone, species-rich Mediterranean-type shrubland in southwestern Australia. We performed an exclusion experiment, where we sequentially removed the strongest PFT in the simulation and studied the remaining communities. We analysed the impact of traits on performance of PFTs in the exclusion experiment with standard and boosted regression trees. Regression tree analysis of the simulation results showed that the trade-off concept is necessary for PFT viability in the case of weak trait expression combinations such as low seed production or small seeds. However, species richness and diversity can be high despite the presence of super-types. Furthermore, the exclusion of super-types does not necessarily lead to a large increase in PFT richness and diversity. We conclude that low-dimensional trade-offs do not provide explanations for multi-species co-existence contrary to the prediction of many conceptual models.show moreshow less

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Metadaten
Author details:Alexandra Esther, Jürgen Groeneveld, Neal J. Enright, Ben P. Miller, Byron B. Lamont, George L. W. Perry, Britta TietjenORCiD, Florian JeltschORCiDGND
DOI:https://doi.org/10.1007/s12080-010-0092-y
ISSN:1874-1738
Title of parent work (English):Theoretical ecology
Publisher:Springer
Place of publishing:Heidelberg
Publication type:Article
Language:English
Year of first publication:2011
Publication year:2011
Release date:2017/03/26
Tag:Boosted regression tree; CART; Co-existence; Individual-based model; Plant diversity; Plant functional types; Regression tree analysis; Spatially explicit model
Volume:4
Issue:4
Number of pages:17
First page:495
Last Page:511
Funding institution:German Research Foundation (DFG) [JE 207/2]; Australian Research Council [DP0343511]; European Community [MOIF-CT-2006-40571]; European Union [MTKD-CT-2006-042261]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
Peer review:Referiert
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