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Cited by 221

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

INTEGRATIVE APPROACHES TO EVOLUTIONARY ECOLOGY: Anolis Lizards as Model Systems

Losos, Jonathan B.·1994·Annual Review of Ecology and Systematics

Abstract

Two approaches characterize the study of evolutionary ecology. Prospective studies investigate how present-day ecological processes may lead to evolutionary change; retrospective studies ask how present-day ecological conditions can be understood as the outcome of historical events. I argue that the most appropriate test of an evolutionary ecological hypothesis requires an integration of these approaches. I illustrate this approach by examining the hypothesis that interspecific competition has been the driving force behind the evolutionary radiation of Anolis lizards in the Caribbean. This hypothesis is supported by four lines of evidence: 1. Anole communities are structured by competition; 2. Populations alter resource use in the presence of congeners; 3. Microevolutionary adaptation occurs in response to resource shifts; and 4. Macroevolutionary patterns are consistent with interspecific competition as the driving force behind anole adaptive radiation.

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Metadata

Authors
Losos, J. B.
Venue
Annual Review of Ecology and Systematics
Published
1994-11
Volume
25
Issue
1
Pages
467-493
ISSN
0066-4162 (ISSN-L)
OpenAlex
W2152333214
Cited by
221
References
2
FWCI
5.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: INTEGRATIVE APPROACHES TO EVOLUTIONARY ECOLOGY: Anolis Lizards as Model Systems. https://app.cochat.ai/papers/10.1146/annurev.es.25.110194.002343
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Losos, J. B. (1994). INTEGRATIVE APPROACHES TO EVOLUTIONARY ECOLOGY: Anolis Lizards as Model Systems. Annual Review of Ecology and Systematics. https://doi.org/10.1146/annurev.es.25.110194.002343

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.