SonnierShipleyNavas2010a

Référence

Sonnier, G., Shipley, B. and Navas, M.-L. (2010) Quantifying relationships between traits and explicitly measured gradients of stress and disturbance in early successional plant communities. Journal of Vegetation Science, 21(6):1014-1024. (URL )

Résumé

Questions: How can one explicitly quantify, and separately measure, stress and disturbance gradients? How do these gradients affect functional composition in early successional plant communities and to what extent? Can we accurately predict trait composition from knowledge of these gradients? Location: Southern Quebec, Canada. Methods: Using eight environmental variables measured in 48 early successional plant communities, we estimated stress and disturbance gradients through structural equation modelling. We then measured 10 functional traits on the most abundant species of these 48 communities and calculated their community-level mean and variance weighted by the relative abundance of each species. Finally, we related these community-weighted means and variances to the estimated stress and disturbance gradients using general linear models or generalized additive models. Results: We obtained a well-fitting measurement model of the stress and disturbance gradients existing in our sites. Of the 10 studied traits, only average plant reproductive height was strongly correlated with the stress (r2=0.464) and disturbance (r2=0.543) gradients. Leaf traits were not significantly related to either the stress or disturbance gradients. Conclusions: The well-fitting measurement model of the stress and disturbance gradients, combined with the generally weak trait–environment linkages, suggests that community assembly in these early successional plant communities is driven primarily by stochastic processes linked to the history of arrival of propagules and not to trait-based environmental filtering.

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@ARTICLE { SonnierShipleyNavas2010a,
    AUTHOR = { Sonnier, G. and Shipley, B. and Navas, M.-L. },
    TITLE = { Quantifying relationships between traits and explicitly measured gradients of stress and disturbance in early successional plant communities },
    JOURNAL = { Journal of Vegetation Science },
    YEAR = { 2010 },
    VOLUME = { 21 },
    PAGES = { 1014-1024 },
    NUMBER = { 6 },
    ABSTRACT = { Questions: How can one explicitly quantify, and separately measure, stress and disturbance gradients? How do these gradients affect functional composition in early successional plant communities and to what extent? Can we accurately predict trait composition from knowledge of these gradients? Location: Southern Quebec, Canada. Methods: Using eight environmental variables measured in 48 early successional plant communities, we estimated stress and disturbance gradients through structural equation modelling. We then measured 10 functional traits on the most abundant species of these 48 communities and calculated their community-level mean and variance weighted by the relative abundance of each species. Finally, we related these community-weighted means and variances to the estimated stress and disturbance gradients using general linear models or generalized additive models. Results: We obtained a well-fitting measurement model of the stress and disturbance gradients existing in our sites. Of the 10 studied traits, only average plant reproductive height was strongly correlated with the stress (r2=0.464) and disturbance (r2=0.543) gradients. Leaf traits were not significantly related to either the stress or disturbance gradients. Conclusions: The well-fitting measurement model of the stress and disturbance gradients, combined with the generally weak trait–environment linkages, suggests that community assembly in these early successional plant communities is driven primarily by stochastic processes linked to the history of arrival of propagules and not to trait-based environmental filtering. },
    DOI = { 10.1111/j.1654-1103.2010.01210.x },
    ISSN = { 1654-1103 },
    KEYWORDS = { Community weighted mean of trait, Community weighted variance of trait, Environmental filtering, Structural equation model, Trait–environment linkages },
    OWNER = { amriv2 },
    PUBLISHER = { Blackwell Publishing Ltd },
    TIMESTAMP = { 2012.08.27 },
    URL = { http://dx.doi.org/10.1111/j.1654-1103.2010.01210.x },
}

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