Assessing natural selection on a phenotypic trait in wild populations is of primary importance for evolutionary ecologists. To cope with the imperfect detection of individuals inherent to monitoring in the wild, we develop a nonparametric method for evaluating the form of natural selection on a quantitative trait using mark-recapture data. Our approach uses penalized splines to achieve flexibility in exploring the form of natural selection by avoiding the need to specify an a priori parametric function. If needed, it can help in suggesting a new parametric model. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data for a wild population of sociable weavers (Philetairus socius) to investigate survival in relation to body mass. In agreement with previous parametric analyses, we found that lighter individuals showed a reduction in survival. However, the survival function was not symmetric, indicating that body mass might not be under stabilizing selection as suggested previously.
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1 March 2006
NONPARAMETRIC ESTIMATION OF NATURAL SELECTION ON A QUANTITATIVE TRAIT USING MARK-RECAPTURE DATA
Olivier Gimenez,
Rita Covas,
Charles R. Brown,
Mark D. Anderson,
Mary Bomberger Brown,
Thomas Lenormand
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Evolution
Vol. 60 • No. 3
March 2006
Vol. 60 • No. 3
March 2006
Bayesian inference
Cormack-Jolly-Seber model
fitness function
individual covariates
penalized splines
random effects
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