Dispersal modelling:integrating landscape features, behaviour and metapopulations

In human-dominated landscapes, populations and species extinctions are directly related to habitat destruction and fragmentation. To provide genetic diversity as well as population viability, individual exchanges among isolated populations must be maintained. Therefore, animal dispersal processes in fragmented landscape become an important topic for ecologists, and ecological networks planning has become one of the major challenges for landscape planners. Identification of habitat patches as well as assessment of the effect of ecological networks is badly needed. Since little information on the effect of landscape heterogeneities on animal dispersal is available, simulation models are being developed. As dispersal pattern and success strongly depend on the spatial context, species' interactions with landscapes, species behaviour and species ability to disperse, these models must be able to simulate them explicitly. This research work therefore aims first at developing methods and models that allow realistic animal dispersal simulations in fragmented landscapes. Second it aims at evaluating the effect of landscape heterogeneities and animal behaviour on dispersal and on species persistence. Additionally, the ability of such a model to estimate gene flow is analysed. To carry on this research, the following fields have been explored: landscape ecology, metapopulation dynamic, animal behaviour, genetics, Geographical Information Systems, modelling approaches and programming. A method, based on properties provided by Geographical Information Systems software, is first proposed to generate ecological networks by simulating animal dispersal according to animal movement constraints induced by human infrastructures. The resulting maps provide a spatial identification of ecological networks, corridors and conflicting areas. This model has proved to be a useful and straightforward tool for landscape planning, even if this model, similar to other present-day models used in dispersal simulations, presents numerous technical and scientific limitations. To improve models for animal dispersal, a feature-oriented landscape model associated with an expert system has been developed. Its conceptualisation, its formalism, its data structure and its object-oriented design implementation provide a very accurate representation of landscape features and simulation of complex interactions between model entities (individuals and landscape features) based on simple rules. It allows the spatial identification of simulated processes. The ability of this model to incorporate states, relations and transition rules between entities makes it applicable to simulate large ranges of dispersal processes according to specific behaviour and/or landscape uses. To analyse the influence of landscape heterogeneities and species behaviour on dispersal and their incidence on metapopulation dynamics, the proposed feature-oriented model has been coupled with an animal model. The latter assigns different cognitive and dispersal abilities to individuals. Based on simulations according to three movement strategies (corresponding to the cognitive abilities of the simulated species), two measures evaluate the effect of cognitive abilities on dispersal: the colonisation probability between habitat patches and the ecological distance (due to landscape heterogeneities). These measures give an estimation of metapopulation structures (the habitat patches belonging to the metapopulation) and metapopulation dynamics induced by the landscape heterogeneities (for example, the habitat patches which release individuals). The complexity of dispersal processes, considering species behaviours and dispersal abilities, can therefore be reproduced and analysed at different levels. This application has shown the importance of animal behaviour on metapopulation dynamics and structure. Since tracking animals and providing sufficient data remain difficult, calibration and validation procedures of dispersal models are difficult to perform. One approach proposed here is to measure one of the consequences of dispersal: genetic differentiation among populations. Geographical distances are in general used to explain a part of the genetic differentiations. But as our fundamental assumption states that landscape heterogeneities and spatial arrangements of landscape features may strongly affect dispersal successes, genetic distance between populations must be better explained by the estimate of a model which considers these factors. We have tested this assumption with the greater white-toothed shrew (Crocidura russula). Scenarios considering various behaviours and dispersal abilities of C. russula have been performed. Relating measures of genetic, geographical and ecological distances (the latter emerge from scenario simulation results) highlights the model capability to reproduce dispersal of C. russula by explaining a greater part of the genetic differentiation than that explained by the geographical distances. This application has not only pointed out the ability of the model to quantify connectivity between habitat patches but also the difficulty to relate gene dispersal and individual dispersal