Inferring contemporary dispersal processes in plant metapopulations: comparison of direct and indirect estimates of dispersal for the annual species Crepis sancta

Abstract

A Dornier and P-O CheptouAnalyzing population dynamics in changing habitats is a prerequisite for population dynamics forecasting. The recent development of metapopulation modeling allows the estimation of dispersal kernels based on the colonization pattern but the accuracy of these estimates compared with direct estimates of the seed dispersal kernel has rarely been assessed. In this study, we used recent genetic methods based on parentage analysis (spatially explicit mating models) to estimate seed and pollen dispersal kernels as well as seed and pollen immigration in fragmented urban populations of the plant species Crepis sancta with contrasting patch dynamics. Using two independent networks, we documented substantial seed immigration and a highly restricted dispersal kernel. Moreover, immigration heterogeneity among networks was consistent with previously reported metapopulation dynamics, showing that colonization was mainly due to external colonization in the first network (propagule rain) and local colonization in the second network. We concluded that the differences in urban patch dynamics are mainly due to seed immigration heterogeneity, highlighting the importance of external population source in the spatio-temporal dynamics of plants in a fragmented landscape. The results show that indirect and direct methods were qualitatively consistent, providing a proper interpretation of indirect estimates. This study provides attempts to link genetic and demographic methods and show that patch occupancy models may provide simple methods for analyzing population dynamics in heterogeneous landscapes in the context of global change.

The rescue effect and inference from isolation–extinction relationships

“…Yet, studies frequently use occupancy data to infer dispersal rates and distances from relationships between colonisation and isolation (Driscoll et al 2014). Attempts to validate this approach with tracking or genetic data have sometimes been successful (Dornier & Cheptou 2013;Hall et al 2018), and other times unsuccessful (Poos & Jackson 2012).…”