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  1. The utility of covariances: a response to Ranta et al

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    Author(s): J.E. Houlahan; K. Cottenie; G.S. Cumming; D.J. Currie; C.S. Findlay; U. Gaedke; P. Legendre; J.J. Magnuson; B.H. McArdle; R.D. Stevens; I.P. Woiwod; S.M. Wondzell
    Date: 2008
    Source: Oikos. 117: 1912-1913
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    DOI: https://doi.org/10.1111/j.1600-0706.2008.17078.x
    PDF: Download Publication  (589.63 KB)

    Description

    In an earlier publication (Houlahan et al. 2007) we reviewed trends in population covariances within communities across a range of long-term empirical data sets. We used these results to argue that compensatory dynamics are rare in natural communities. Ranta et al. (2008) explored interspecific interactions in a simulated environment and showed that 'negative community covariance can be absent even in strongly competitive communities and can be found present in communities without competitive interactions'. On this basis they conclude that 'the negative community covariance method . .. is of limited practical value when attempting to detect the presence of interspecific interactions among species in a community, or the relative importance of competition and environment in driving population fluctuations.' There are three closely related points to consider here: first, exactly what is shown by demonstrating an absence of negative community covariance in some strongly competitive communities; second, what is shown by demonstrating negative community covariance in the absence of competition; and third, what these results say about the general utility of the community covariance method.

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    Citation

    Houlahan, J.E.; Cottenie, K.; Cumming, G.S.; Currie, D.J.; Findlay, C.S.; Gaedke, U.; Legendre, P.; Magnuson, J.J.; McArdle, B.H.; Stevens, R.D.; Woiwod, I.P.; Wondzell, S.M. 2008. The utility of covariances: a response to Ranta et al. Oikos. 117: 1912-1913.

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    Keywords

    diversity, competition, community dynamics, biological interactions, neutral models

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