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Cubaynes S.,CNRS Center of Evolutionary and Functional Ecology | Cubaynes S.,Institute Of Mathematiques Et Modelisation Of Montpellier | Pradel R.,CNRS Center of Evolutionary and Functional Ecology | Choquet R.,CNRS Center of Evolutionary and Functional Ecology | And 10 more authors.
Conservation Biology | Year: 2010

Assessing conservation strategies requires reliable estimates of abundance. Because detecting all individuals is most often impossible in free-ranging populations, estimation procedures have to account for a <1 detection probability. Capture-recapture methods allow biologists to cope with this issue of detectability. Nevertheless, capture-recapture models for open populations are built on the assumption that all individuals share the same detection probability, although detection heterogeneity among individuals has led to underestimating abundance of closed populations. We developed multievent capture-recapture models for an open population and proposed an associated estimator of population size that both account for individual detection heterogeneity (IDH). We considered a two-class mixture model with weakly and highly detectable individuals to account for IDH. In a noninvasive capture-recapture study of wolves we based on genotypes identified in feces and hairs, we found a large underestimation of population size (27% on average) occurred when IDH was ignored. © 2010 Society for Conservation Biology.


Cubaynes S.,CNRS Center of Evolutionary and Functional Ecology | Cubaynes S.,Institute Of Mathematiques Et Modelisation Of Montpellier | Lavergne C.,Institute Of Mathematiques Et Modelisation Of Montpellier | Marboutin E.,Office National de la Chasse et de la Faune Sauvage | Gimenez O.,CNRS Center of Evolutionary and Functional Ecology
Methods in Ecology and Evolution | Year: 2012

1. Capture-recapture mixture models are important tools in evolution and ecology to estimate demographic parameters and abundance while accounting for individual heterogeneity. A key step is to select the correct number of mixture components i) to provide unbiased estimates that can be used as reliable proxies of fitness or ingredients in management strategies and ii) classify individuals into biologically meaningful classes. However, there is no consensus method in the statistical literature for selecting the number of components. 2.In ecology, most studies rely on the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) that has recently gained attention in ecology. The Integrated Completed Likelihood criterion (ICL; IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22, 719) was specifically developed to favour well-separated components, but its use has never been investigated in ecology. 3.We compared the performance of AIC, BIC and ICL for selecting the number of components with regard to a) bias and accuracy of survival and detection estimates and b) success in selecting the true number of components using extensive simulations and data on wolf (Canis lupus) that were used for management through survival and abundance estimation. 4.Bias in survival and detection estimates was <0.02 for both AIC and BIC, and more than 0.09 for ICL, while mean square error was <0.05 for all criteria. As expected, bias increased as heterogeneity increased. Success rates of AIC and BIC in selecting the 'true' number of components were better than ICL (68% for AIC, 58% for BIC, and 16% for ICL). As the degree of heterogeneity increased, AIC (and BIC in a lesser extent) overestimated the number of components, while ICL often underestimated this number. For the wolf study, the 2-class model was selected by BIC and ICL, while AIC could not decide between the 2- and 3-class models. 5.We recommend using AIC or BIC when the aim is to estimate parameters. Regarding classification, we suggest taking the classification quality into account by using ICL in conjunction with BIC, pending further work to adapt its penalty term for capture-recapture data. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.


Cubaynes S.,CNRS Center of Evolutionary and Functional Ecology | Cubaynes S.,Institute Of Mathematiques Et Modelisation Of Montpellier | Doutrelant C.,CNRS Center of Evolutionary and Functional Ecology | Gregoire A.,CNRS Center of Evolutionary and Functional Ecology | And 3 more authors.
Ecology | Year: 2012

Studying evolutionary mechanisms in natural populations often requires testing multifactorial scenarios of causality involving direct and indirect relationships among individual and environmental variables. It is also essential to account for the imperfect detection of individuals to provide unbiased demographic parameter estimates. To cope with these issues, we developed a new approach combining structural equation models with capture-recapture models (CR-SEM) that allows the investigation of competing hypotheses about individual and environmental variability observed in demographic parameters. We employ Markov chain Monte Carlo sampling in a Bayesian framework to (1) estimate model parameters, (2) implement a model selection procedure to evaluate competing hypotheses about causal mechanisms, and (3) assess the fit of models to data using posterior predictive checks. We illustrate the value of our approach using two case studies on wild bird populations. We first show that CR-SEM can be useful to quantify the action of selection on a set of phenotypic traits with an analysis of selection gradients on morphological traits in Common Blackbirds (Turdus merula). In a second case study on Blue Tits (Cyanistes caeruleus), we illustrate the use of CR-SEM to study evolutionary trade-offs in the wild, while accounting for varying environmental conditions. © 2012 by the Ecological Society of America.


Cubaynes S.,CNRS Center of Evolutionary and Functional Ecology | Doherty P.F.,Institute Of Mathematiques Et Modelisation Of Montpellier | Schreiber E.A.,Colorado State University | Gimenez O.,Smithsonian Institution
Biology Letters | Year: 2011

Intermittent breeding is an important lifehistory strategy that has rarely been quantified in the wild and for which drivers remain unclear. It may be the result of a trade-off between survival and reproduction, with individuals skipping breeding when breeding conditions are below a certain threshold. Heterogeneity in individual quality can also lead to heterogeneity in intermittent breeding. We modelled survival, recruitment and breeding probability of the red-footed booby (Sula sula), using a 19 year mark-recapture dataset involving more than 11 000 birds. We showed that skipping breeding was more likely in El-Niñ o years, correlated with an increase in the local sea surface temperature, supporting the hypothesis that it may be partly an adaptive strategy of birds to face the trade-off between survival and reproduction owing to environmental constraints. We also showed that the age-specific probability of first breeding attempt was synchronized among different age-classes and higher in El-Niñ o years. This result suggested that pre-breeders may benefit from lowered competition with experienced breeders in years of high skipping probabilities. © 2011 The Royal Society.


Papaix J.,CNRS Center of Evolutionary and Functional Ecology | Cubaynes S.,CNRS Center of Evolutionary and Functional Ecology | Cubaynes S.,Institute Of Mathematiques Et Modelisation Of Montpellier | Buoro M.,CNRS Center of Evolutionary and Functional Ecology | And 3 more authors.
Journal of Evolutionary Biology | Year: 2010

Quantitative genetic analyses have been increasingly used to estimate the genetic basis of life-history traits in natural populations. Imperfect detection of individuals is inherent to studies that monitor populations in the wild, yet it is seldom accounted for by quantitative genetic studies, perhaps leading to flawed inference. To facilitate the inclusion of imperfect detection of individuals in such studies, we develop a method to estimate additive genetic variance and assess heritability for binary traits such as survival, using capture-recapture (CR) data. Our approach combines mixed-effects CR models with a threshold model to incorporate discrete data in a standard 'animal model' approach. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data from a wild population of blue tits (Cyanistes caeruleus) and present the first estimate of heritability of adult survival in the wild. In agreement with the prediction that selection should deplete additive genetic variance in fitness, we found that survival had low heritability. Because the detection process is incorporated, capture-recapture animal models (CRAM) provide unbiased quantitative genetics analyses of longitudinal data collected in the wild. © 2010 European Society For Evolutionary Biology.


Cucala L.,Institute Of Mathematiques Et Modelisation Of Montpellier
Spatial Statistics | Year: 2014

A new spatial scan statistic is proposed for identifying clusters in marked point processes. Contrary to existing methods, it does not rely on a likelihood ratio and thus is completely distribution-free. It applies whatever the nature of the marks: binary, discrete or continuous. This spatial scan test seems to be very powerful against any arbitrarily-distributed cluster alternative. I apply this method first to a classical epidemiological dataset and then to the spatial distribution of incomes in France. © 2014 Elsevier Ltd.

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