Abstract

Studying natal dispersal in natural populations using capture-recapture data is challenging as an unknown proportion of individuals leaves the study area when dispersing and are never recaptured. Most dispersal (and survival) estimates from capture-recapture studies are thus biased and only reflect what happens within the study area, not the population. Here, we elaborate on recent methodological advances to build a spatially explicit multi-state capture-recapture model to study natal dispersal in a territorial mammal while accounting for imperfect detection and movement in and out of the study area. We validate our model using a simulation study where we compare it to a non-spatial multi-state capture-recapture model. We then apply it to a long-term individual-based dataset on Alpine marmot Marmota marmota. Our model was able to accurately estimate natal dispersal and survival probabilities, as well as mean dispersal distance for a large range of dispersal patterns. By contrast, the non-spatial multi-state estimates underestimated both survival and natal dispersal even for short dispersal distances relative to the study area size. We discuss the application of our approach to other species and monitoring setups. We estimated higher inheritance probabilities of female Alpine marmots, which suggests higher levels of philopatry, although the probability to become dominant after dispersal did not differ between sexes. Nonetheless, the lower survival of young adult males suggests higher costs of dispersal for males. We further discuss the implications of our findings in light of the life history of the species.

Highlights

  • Dispersal, and especially natal dispersal, is a fundamental process in biology (Dobson, 2013).In practice, all organisms are faced with the decision to move and spread, or to stay and try to access reproduction on their natal site

  • We showed how using the spatial information associated with individual detections in a multi-state capture-recapture model can allow the estimation of unbiased natal dispersal and survival probabilities even when a significant proportion of the population settles outside the study area after dispersal

  • We showed how the magnitude of the underestimation of these demographic parameters by classical multi-state models depends on the mean dispersal distance

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Summary

Introduction

Especially natal dispersal, is a fundamental process in biology (Dobson, 2013).In practice, all organisms are faced with the decision to move and spread, or to stay and try to access reproduction on their natal site. Some individuals may leave the study area and settle permanently outside its boundaries These emigrated individuals are never recaptured and are undistinguishable from dead individuals. In this situation, the most common in CR studies, survival estimates returned by CR models correspond to the probability for an individual to survive and not leave the study area, i.e. the apparent survival (Lebreton et al 1992). The most common in CR studies, survival estimates returned by CR models correspond to the probability for an individual to survive and not leave the study area, i.e. the apparent survival (Lebreton et al 1992) This limitation is even more salient if the target of the study is to estimate animal movement itself. It is crucial to deal with the issues of “apparent survival” and “apparent dispersal”

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