2008
DOI: 10.1111/j.0030-1299.2008.16976.x
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Linking dendritic network structures to population demogenetics: The downside of connectivity

Abstract: 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… Show more

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Cited by 113 publications
(106 citation statements)
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References 56 publications
(54 reference statements)
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“…The lattice structure provides a good representation of natural systems (e.g., linear edge habitat, topological area of land, or ocean volumes), as well as a framework for classic population genetic models such as the linear stepping-stone (Kimura and Weiss 1964), island (MacArthur and Wilson 1967), and infinite-islands (Wright 1931) models. Recently, ecologists and geneticists have begun to explore the influence of a dendritic representation of nature on population genetic structure, community dynamics, and species distribution (Fagan 2002;May 2006;Campbell Grant et al 2007;Labonne et al 2008;Rodriguez-Iturbe et al 2009). While studies have shown that dendritic arrangements of populations have ecological properties that are not found in lattice models, they have not yet incorporated influences of asymmetric movement of individuals on the genetic structure of dendritic metapopulations.…”
Section: Introductionmentioning
confidence: 99%
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“…The lattice structure provides a good representation of natural systems (e.g., linear edge habitat, topological area of land, or ocean volumes), as well as a framework for classic population genetic models such as the linear stepping-stone (Kimura and Weiss 1964), island (MacArthur and Wilson 1967), and infinite-islands (Wright 1931) models. Recently, ecologists and geneticists have begun to explore the influence of a dendritic representation of nature on population genetic structure, community dynamics, and species distribution (Fagan 2002;May 2006;Campbell Grant et al 2007;Labonne et al 2008;Rodriguez-Iturbe et al 2009). While studies have shown that dendritic arrangements of populations have ecological properties that are not found in lattice models, they have not yet incorporated influences of asymmetric movement of individuals on the genetic structure of dendritic metapopulations.…”
Section: Introductionmentioning
confidence: 99%
“…The arrangement of dendritic networks can influence many aspects of metapopulation ecology, including source and sink dynamics (Fagan 2002;Lowe 2002), genetic relatedness (Labonne et al 2008), predator-prey interactions (Cuddington and Yodzis 2002), resistance to invasion (Pulliam 1988), and the distribution of local productivity (Lowe and Bolger 2002; Campbell Grant et al 2007). In addition, the linear nature of migration removes the independence of population exchange often found in lattice networks, because individuals are forced to travel and interact with potentially multiple nodes to reach a location (Labonne et al 2008). Recently, dendricity has been shown to also influence patterns of community diversity within the metacommunity framework (Rodriguez-Iturbe et al 2009).…”
Section: Introductionmentioning
confidence: 99%
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“…In species that are restricted to network branches, dispersal is constrained by network structure (17), and consequently, population stability and local extinction risk are predicted to be highly sensitive to network position and direct connections among occupied branches (18). A capacity for overland dispersal between branches is predicted to increase population stability and decrease extinction risk significantly by providing periodic connectivity among spatially isolated reaches (4,9).…”
mentioning
confidence: 99%
“…The simplest network then is a linear network, where each reach connects to exactly one upstream reach, the most complex is the complete binary network with exactly two. We generate intermediate geometries numerically according to a stochastic branching process [3]. Starting from the root, the tree graph is generated using a probability triplet, indicating the probabilities of a reach connecting to zero, one or two reaches upstream.…”
Section: Graphs Of Dendritic Networkmentioning
confidence: 99%