Journal article
Detecting local diversity-dependence in diversification
- Abstract:
- Whether there are ecological limits to species diversification is a hotly debated topic. Molecular phylogenies show slowdowns in lineage accumulation, suggesting that speciation rates decline with increasing diversity. A maximum-likelihood (ML) method to detect diversity-dependent (DD) diversification from phylogenetic branching times exists, but it assumes that diversity-dependence is a global phenomenon and therefore ignores that the underlying species interactions are mostly local, and not all species in the phylogeny co-occur locally. Here, we explore whether this ML method based on the nonspatial diversity-dependence model can detect local diversity-dependence, by applying it to phylogenies, simulated with a spatial stochastic model of local DD speciation, extinction, and dispersal between two local communities. We find that type I errors (falsely detecting diversity-dependence) are low, and the power to detect diversity-dependence is high when dispersal rates are not too low. Interestingly, when dispersal is high the power to detect diversity-dependence is even higher than in the nonspatial model. Moreover, estimates of intrinsic speciation rate, extinction rate, and ecological limit strongly depend on dispersal rate. We conclude that the nonspatial DD approach can be used to detect diversity-dependence in clades of species that live in not too disconnected areas, but parameter estimates must be interpreted cautiously.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 896.6KB, Terms of use)
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- Publisher copy:
- 10.1111/evo.13482
Authors
- Publisher:
- Wiley
- Journal:
- Evolution More from this journal
- Volume:
- 72
- Issue:
- 6
- Pages:
- 1294-1305
- Publication date:
- 2018-04-24
- Acceptance date:
- 2018-02-12
- DOI:
- ISSN:
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0014-3820
- Language:
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English
- Keywords:
- Pubs id:
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1190543
- Local pid:
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pubs:1190543
- Deposit date:
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2021-08-12
- ARK identifier:
Terms of use
- Copyright holder:
- Xu and Etienne.
- Copyright date:
- 2018
- Rights statement:
- ©2018 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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