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Modelling managed maritime-pine stands undergrowth vegetation composition and diversity in relation to environmental, structural and management variables

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Detalhes bibliográficos
Resumo:A case-study attempting to approach the patterns of species’ composition and diversity of the undergrowth vegetation of maritime-pine (Pinus pinaster Ait.) stands, in relation to environmental factors and forestry practices, is presented. Due to its large area in the rural landscape, forestry-intensive stands still have to be approached as ecologically meaningful. The vegetation patterns in these forests arise mostly from human disturbance related to management along with interactions with natural succession processes. Furthermore, tradeoffs of stand vegetation with the overall landscape-mosaic [neighbouring mass effects] adds further degrees-of-freedom to the problem. Describing and modelling such vegetation patterns asks for powerful multivariate statistical tools, since the main environment-vegetation interactions are expected to be complex and intricate.
Autores principais:Capelo, Jorge
Outros Autores:Mesquita, J.; Sequeira, Miguel; Aguiar, Carlos; Marcos, N.
Assunto:Maritime pine Ecological modelling
Ano:2003
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:A case-study attempting to approach the patterns of species’ composition and diversity of the undergrowth vegetation of maritime-pine (Pinus pinaster Ait.) stands, in relation to environmental factors and forestry practices, is presented. Due to its large area in the rural landscape, forestry-intensive stands still have to be approached as ecologically meaningful. The vegetation patterns in these forests arise mostly from human disturbance related to management along with interactions with natural succession processes. Furthermore, tradeoffs of stand vegetation with the overall landscape-mosaic [neighbouring mass effects] adds further degrees-of-freedom to the problem. Describing and modelling such vegetation patterns asks for powerful multivariate statistical tools, since the main environment-vegetation interactions are expected to be complex and intricate.