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The risk of flawed inference in evolutionary studies when detectability is less than one
Olivier Gimenez1, Anne Viallefont, Anne Charmantier
1Centre d'Ecologie Fonctionnelle et Evolutive, Centre National de Recherche Scientifique, Unité Mixte de Recherche 5175, 1919 Route de Mende, 34293 Montpellier Cedex 5, France. olivier.gimenez@cefe.cnrs.fr.
Studying wild populations is hard due to uncertain detection. Using mark-recapture models improves evolutionary biology research by accurately accounting for this, preventing flawed conclusions about natural selection and aging.
Area of Science:
- Evolutionary biology
- Ecology
- Wildlife population dynamics
Background:
- Studying wild organisms from birth to death is crucial for evolutionary questions but challenging due to difficulties in resighting or recapturing individuals.
- The assumption of perfect detectability in evolutionary studies of wild populations can lead to inaccurate inferences.
Purpose of the Study:
- To highlight the challenges of uncertain detection in wild populations for evolutionary studies.
- To demonstrate how imperfect detectability can alter evolutionary inference.
- To advocate for the use of mark-recapture models in evolutionary biology.
Main Methods:
- The study implicitly uses mark-recapture modeling principles to analyze detection processes.
- It examines the impact of imperfect detectability on evolutionary parameters using case studies.
Main Results:
- Assuming perfect detectability can significantly alter the inferred form of natural selection, as shown in sociable weavers' body mass.
- The rate of senescence in roe deer is underestimated when detection probabilities less than one are not considered.
Conclusions:
- Inference in evolutionary biology can be flawed if imperfect detectability is ignored.
- Mark-recapture models offer a robust framework for integrating and modeling detection processes in wild populations.
- The use of mark-recapture models is strongly recommended for addressing evolutionary questions in wild populations.
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