Linking dendritic network structures to population demogenetics: the downside of connectivity
2008
Labonne, Jacques | Ravigné, Virginie | Parisi, Bruno | Gaucherel, Cedric | Ecologie Comportementale et Biologie des Populations de Poissons (ECOBIOP) ; Institut National de la Recherche Agronomique (INRA)-Université de Pau et des Pays de l'Adour (UPPA) | Centre de Biologie pour la Gestion des Populations (UMR CBGP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [Occitanie])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | BotAnique et BioinforMatique de l'Architecture des Plantes (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut de Recherche pour le Développement (IRD [France-Ouest])-Centre National de la Recherche Scientifique (CNRS)
International audience
Mostrar más [+] Menos [-]Inglés. Spatial structures strongly influence ecological processes. Connectivity is known to positively influence metapopulation demography and genetics by increasing the rescue effect and thus favoring individual and gene flow between populations. This result has not been tested in the special case of dendritic networks, which encompass stream and cave ecosystem for instance. We propose a first approach using an individual based model to explore the population demography and genetics in various dendritic networks. To do so, we first generate a large number of different networks, and we analyze the relationship between their hydrographical characteristics and connectivity. We show that connectivity mean and variance of connectivity are strongly correlated in dendritic networks. Connectivity segregates two types of networks: Hortonian and non-Hortonian networks. We then simulate the population dynamics for a simple life cycle in each of the generated networks, and we analyze persistence time as well as populations structure at quasi-stationary state. Our main results show that connectivity in dendritic networks can promote local extinction and genetic isolation by distance at low dispersal and diminish the size of the metapopulation at high dispersal. We discuss these unexpected findings in the light of connectivity spatial distribution in dendritic networks in the case of our model.
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