2010
DOI: 10.3354/meps08779
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Metapopulation mean life time within complex networks

Abstract: Metapopulation dynamics depend on the exchange of individuals between populations across the landscape. The environment that the migrants must traverse is influenced by many forces, so the connections are often complicated pathways, which can be represented as a network. The structure of these networks will determine which populations will receive more migrants than other populations, and this in turn affects the lifetime of the metapopulation. We present a modification of the Drechsler (2009) formulae for the… Show more

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Cited by 33 publications
(48 citation statements)
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“…Holt 19 catalysed this interest in the context of island biogeography by suggesting that internal island dynamics (for example, rescue effects 20 ) reduced extinction risk of populations, leading to altered predictions for biodiversity on islands; such internal dynamics are analogous to dynamics that may arise within modules. Similarly, a recent metapopulation model contrasting gradients of non-modular and modular metapopulations found that the most persistent metapopulations were those that were most modular 18 . Although theory suggests that modularity is highly relevant to spatial dynamics, the empirical application of modularity concepts to spatial ecology and evolution has been scarce.…”
mentioning
confidence: 89%
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“…Holt 19 catalysed this interest in the context of island biogeography by suggesting that internal island dynamics (for example, rescue effects 20 ) reduced extinction risk of populations, leading to altered predictions for biodiversity on islands; such internal dynamics are analogous to dynamics that may arise within modules. Similarly, a recent metapopulation model contrasting gradients of non-modular and modular metapopulations found that the most persistent metapopulations were those that were most modular 18 . Although theory suggests that modularity is highly relevant to spatial dynamics, the empirical application of modularity concepts to spatial ecology and evolution has been scarce.…”
mentioning
confidence: 89%
“…The emergence of modularity is crucial for population biology because several models suggest that such a structure can greatly influence dynamics [17][18][19] . Holt 19 catalysed this interest in the context of island biogeography by suggesting that internal island dynamics (for example, rescue effects 20 ) reduced extinction risk of populations, leading to altered predictions for biodiversity on islands; such internal dynamics are analogous to dynamics that may arise within modules.…”
mentioning
confidence: 99%
“…Metapopulation theory suggests that changes to habitat area will have disproportionate effects on population size and persistence (Kininmoth et al 2010, Kininmonth et al 2011. With less available habitat, particularly of foundation species, there will not only be less larvae produced, but also potentially longer distances for settlers to travel.…”
Section: Empirical Examplesmentioning
confidence: 99%
“…However, graph models can also incorporate a great deal of biological realism and complexity (Schick and Lindley , Kininmonth et al ). Of relevance to management and conservation of populations at a landscape‐scale, clear connections exist between graph theory and metapopulation theory through the graph‐theoretic implementation of the metapopulation mean lifetime model (MLT; Kininmonth et al ).…”
mentioning
confidence: 99%
“…The MLT model was developed and used by Frank and Wissel (, ) to model metapopulation persistence in heterogeneous landscapes while incorporating variation in patch size and inter‐patch distance. Drechsler () formulated an analytical solution to the MLT based on network properties, which was further modified by Kininmonth et al () to incorporate a graph theory model of dispersal that could accommodate asymmetric dispersal between patches in the network and the strength of connections formed by dispersal. In short, the MLT model is a summary of 4 network properties: the ratio of dispersal range and network size, the ratio of environmental correlation range and network size, the number and size of the patches, and the geometric mean of the number and size of patches (Drechsler ).…”
mentioning
confidence: 99%