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  • Copernicus  (2)
  • 1
    Publication Date: 2008-11-18
    Description: In multi-species communities the stability of a system is difficult to assess from field observations. This is the case for example for competitive interactions in plant communities. If a mathematical model can be formulated that underlies the processes in the community, a community matrix can be constructed whose elements represent the effects of each species onto every other (and itself) at equilibrium. The most common competition model is the Lotka-Volterra equation set. It contains interspecific competition coefficients to represent the interactions between species. In plant community ecology several attempts have been made to quantify competitive interactions and to assemble a community matrix, so far with limited success. In this paper we discuss a method to use pairwise interaction coefficients from experimental plant communities to analyse feasibility and stability of multi-species sets. The approach is contrasted with that of Wilson and Roxburgh (1992) and is illustrated using data from Roxburgh and Wilson (2000a). Results from Wilson and from this study differ (some times substantially), with our approach being more pessimistic about stability and coexistence in plant communities.
    Print ISSN: 2193-3081
    Electronic ISSN: 1399-1183
    Topics: Biology
    Published by Copernicus on behalf of European Ecological Federation.
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  • 2
    Publication Date: 2008-04-29
    Description: Species distributional data based on lattice data often display spatial autocorrelation. In such cases, the assumption of independently and identically distributed errors can be violated in standard regression models. Based on a recently published review on methods to account for spatial autocorrelation, we describe here a new statistical approach which relies on the theory of wavelets. It provides a powerful tool for removing spatial autocorrelation without any prior knowledge of the underlying correlation structure. Our wavelet-revised model (WRM) is applied to artificial datasets of species’ distributions, for both presence/absence (binary response) and species abundance data (Poisson or normally distributed response). Making use of these published data enables us to compare WRM to other recently tested models and to recommend it as an attractive option for effective and computationally efficient autocorrelation removal.
    Print ISSN: 2193-3081
    Electronic ISSN: 1399-1183
    Topics: Biology
    Published by Copernicus on behalf of European Ecological Federation.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
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