bioRxiv ScienceSearch

Biology subjects

Barbraud, C.

Publications and source records attributed to Barbraud, C..

2 recordsLinked to original sources

Dispersal-dependent juvenile survival in a sexually dimorphic long-lived bird, the Greater Flamingo Phoenicopterus roseus

The viability and dynamics of spatially structured populations depend critically upon dispersal behaviour. Yet, in long lived species with delayed maturity, the fitness consequences of post-fledging dispersal, dispersal from the birthplace after independence and before first breeding attempt, are poorly understood although it is a critical determinant of natal dispersal.\n\nWe aimed at estimating sex-specific variations of juvenile survival in a long-lived bird species with sexual size dimorphism, the greater flamingo, as a function of post fledging dispersal destination. Using capture-recapture models, we estimated the survivorship of flamingos ringed in the Camargue (south of France) and wintering in the Mediterranean.\n\nDispersal probability from France was > 0.66 with important annual variations in preferred dispersal destinations. First-year survival increased along the winter temperature gradient with estimates below 0.50 {+/-} 0.07 in France and above 0.60 {+/-} 0.07 in African wetlands. The survival of flamingos wintering in France dropped by 30-50 % depending on sex between fall and spring of their first year.\n\nIn African sites and in Italy, there was no detectable difference of survival between sexes suggesting favorable wintering conditions. Body condition at fledging did not explain variations in first-fall survival within genders. Males wintering in France had a better survival than females.\n\nThese results show that sex and post-fledging dispersal destination affect juvenile survival, support the energetic hypothesis predicting an advantage of large body size to cope with cold temperatures and the competition hypothesis, and suggest the existence of sex-specific post fledging dispersal tactics.

ecology

Dealing with many correlated covariates in capture-recapture models

Capture-recapture models for estimating demographic parameters allow covariates to be incorporated to better understand population dynamics. However, high-dimensionality and multicollinearity can hamper estimation and inference. Principal component analysis is incorporated within capture-recapture models and used to reduce the number of predictors into uncorrelated synthetic new variables. Principal components are selected by sequentially assessing their statistical significance. We provide an example on seabird survival to illustrate our approach. Our method requires standard statistical tools, which permits an efficient and easy implementation using standard software.

ecology