Literature DB >> 23224646

Using species spectra to evaluate plant community conservation value along a gradient of anthropogenic disturbance.

José A P Marcelino1, Luís Silva, Patricia V Garcia, Everett Weber, António O Soares.   

Abstract

The aim of this study was to assess the impact of anthropogenic disturbance on the partitioning of plant communities (species spectra) across a landcover gradient of community types, categorizing species on the basis of their biogeographic, ecological, and conservation status. We tested a multinomial model to generate species spectra and monitor changes in plant assemblages as anthropogenic disturbance rise, as well as the usefulness of this method to assess the conservation value of a given community. Herbaceous and arborescent communities were sampled in five Azorean islands. Margins were also sampled to account for edge effects. Different multinomial models were applied to a data set of 348 plant species accounting for differences in parameter estimates among communities and/or islands. Different levels of anthropogenic disturbance produced measurable changes on species spectra. Introduced species proliferated and indigenous species declined, as anthropogenic disturbance and management intensity increased. Species assemblages of relevance other than economic (i.e., native, endemic, threatened species) were enclosed not only in natural habitats, but also in human managed arborescent habitats, which can positively contribute for the preservation of indigenous species outside remnants of natural areas, depending on management strategies. A significant presence of invasive species in margin transects of most community types will contribute to an increase in edge effect that might facilitate invasion. The multinomial model developed in this study was found to be a novel and expedient tool to characterize the species spectra at a given community and its use could be extrapolated for other assemblages or organisms, in order to evaluate and forecast the conservation value of a site.

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Year:  2012        PMID: 23224646     DOI: 10.1007/s10661-012-3019-9

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


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