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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Languages: English
Types: Doctoral thesis
Subjects: extinction, theoretical ecology, food webs, metapopulation, Ecology, Environmental Science, metacommunity, trophic levels
Traditionally, community models have focused on density-dependent factors. More recently, though, studies that consider populations interacting on a spatial (as well as temporal) scale have become very popular. These metacommunity models often use the patch-occupancy approach, where the focus is on regional dynamics (patches are classied as simply occupied or vacant). A few studies have extended this work by modelling local dynamics explicitly, although the food webs involved have been relatively simple. This paper takes the next step and considers a spatially explicit habitat where species interact across three trophic levels. The aim is to investigate how web connectance, patch abundance and dispersal patterns aect a community's ability to recover from the loss of a species. I nd that asynchrony among patch dynamics may arise from relatively low rates of migration, and that the inclusion of space signicantly reduces the risk of cascading extinctions. It is shown that communities with sparsely connected food webs are the most sensitive to perturbations, but also that they are particularly well stabilised by the introduction of space. In agreement with theoretical studies of non-spatial habitats, species holding the highest trophic rank are the most susceptible to secondary extinctions, although they often take the longest to die out. This is particularly pronounced in spatial habitats, where the top predator appears to be the least well adapted to exploit the stabilising properties of space. Results such as these are discussed in detail, and their implications are set in the context of habitat management.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • Department of Mathematics, University of York, York, North Yorkshire, YO10 5DD, UK. E-mail address:
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    The results below are discovered through our pilot algorithms. Let us know how we are doing!

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