Modelling unbiased dispersal kernels over continuous space by accounting for spatial heterogeneity in marking and observation efforts

摘要

1. Although a key demographic trait determining the spatial dynamics of wild populations, dispersal is notoriously difficult to estimate in the field. Indeed, dispersal distances obtained from the monitoring of marked individuals typically lead to biased estimations of dispersal kernels as a consequence of (i) restricted spatial scale of the study areas compared to species potential dispersal and (ii) heterogeneity in marking and observation efforts and therefore in detection probability across space.