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The use of plant community attributes to detect habitat quality in coastal environments

The monitoring of biodiversity has mainly focused on the species level. However, researchers and land managers are making increasing use of complementary assessment tools that address higher levels of biological organization, i.e. communities, habitats and ecosystems. Recently, a variety of framewor...

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Autores principales: Del Vecchio, Silvia, Slaviero, Antonio, Fantinato, Edy, Buffa, Gabriella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940507/
https://www.ncbi.nlm.nih.gov/pubmed/27255516
http://dx.doi.org/10.1093/aobpla/plw040
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author Del Vecchio, Silvia
Slaviero, Antonio
Fantinato, Edy
Buffa, Gabriella
author_facet Del Vecchio, Silvia
Slaviero, Antonio
Fantinato, Edy
Buffa, Gabriella
author_sort Del Vecchio, Silvia
collection PubMed
description The monitoring of biodiversity has mainly focused on the species level. However, researchers and land managers are making increasing use of complementary assessment tools that address higher levels of biological organization, i.e. communities, habitats and ecosystems. Recently, a variety of frameworks have been proposed for assessing the conservation status of communities or ecosystems. Among the various criteria proposed, all the protocols suggest considering (i) spatial aspects (range and area), and (ii) qualitative aspects of specific structures and functions. However, changes to ecological function are difficult to quantify and many protocols end up by using qualitative criteria. The aim of this work was to test the efficacy of some plant community attributes for the detection of vegetation quality in sand dune plant communities. We chose plant community attributes that either help to distinguish a habitat from others (diagnostic components) or play a significant role in habitat function and persistence over time. We used a diachronic approach by contrasting up-to-date vegetation data with data from previous studies carried out within the same areas. Changes in species composition were detected through detrended correspondence analyses (detrended correspondence analyses), Multi-Response Permutation Procedures and Indicator Species Analysis, while structural changes were analyzed by comparing species richness, total species cover, ecological groups of species and growth forms through null models. Ecological groups such as native focal species and aliens, and growth forms proved their efficacy in discriminating between habitat types and in describing their changes over time. The approach used in this study may provide an instrument for the assessment of plant community quality that can be applied to other coastal ecosystems.
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spelling pubmed-49405072016-07-13 The use of plant community attributes to detect habitat quality in coastal environments Del Vecchio, Silvia Slaviero, Antonio Fantinato, Edy Buffa, Gabriella AoB Plants Research Article The monitoring of biodiversity has mainly focused on the species level. However, researchers and land managers are making increasing use of complementary assessment tools that address higher levels of biological organization, i.e. communities, habitats and ecosystems. Recently, a variety of frameworks have been proposed for assessing the conservation status of communities or ecosystems. Among the various criteria proposed, all the protocols suggest considering (i) spatial aspects (range and area), and (ii) qualitative aspects of specific structures and functions. However, changes to ecological function are difficult to quantify and many protocols end up by using qualitative criteria. The aim of this work was to test the efficacy of some plant community attributes for the detection of vegetation quality in sand dune plant communities. We chose plant community attributes that either help to distinguish a habitat from others (diagnostic components) or play a significant role in habitat function and persistence over time. We used a diachronic approach by contrasting up-to-date vegetation data with data from previous studies carried out within the same areas. Changes in species composition were detected through detrended correspondence analyses (detrended correspondence analyses), Multi-Response Permutation Procedures and Indicator Species Analysis, while structural changes were analyzed by comparing species richness, total species cover, ecological groups of species and growth forms through null models. Ecological groups such as native focal species and aliens, and growth forms proved their efficacy in discriminating between habitat types and in describing their changes over time. The approach used in this study may provide an instrument for the assessment of plant community quality that can be applied to other coastal ecosystems. Oxford University Press 2016-07-11 /pmc/articles/PMC4940507/ /pubmed/27255516 http://dx.doi.org/10.1093/aobpla/plw040 Text en Published by Oxford University Press on behalf of the Annals of Botany Company. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Del Vecchio, Silvia
Slaviero, Antonio
Fantinato, Edy
Buffa, Gabriella
The use of plant community attributes to detect habitat quality in coastal environments
title The use of plant community attributes to detect habitat quality in coastal environments
title_full The use of plant community attributes to detect habitat quality in coastal environments
title_fullStr The use of plant community attributes to detect habitat quality in coastal environments
title_full_unstemmed The use of plant community attributes to detect habitat quality in coastal environments
title_short The use of plant community attributes to detect habitat quality in coastal environments
title_sort use of plant community attributes to detect habitat quality in coastal environments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940507/
https://www.ncbi.nlm.nih.gov/pubmed/27255516
http://dx.doi.org/10.1093/aobpla/plw040
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