Unfolding relations between land cover and farm management: high nature value assessment in complex silvo-pastoral systems

• Autor(a) principal: Almeida, Mara
• Data de Publicação: 2013
• Outros Autores: Guerra, Carlos, Pinto-Correia, Teresa
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/10230; https://doi.org/10.1080/00167223.2013.848611
• topic: High Nature Value; Silvo-pastoral system; Land management; Vegetation cover

The high nature value (HNV) concept, proposed by the European Environment Agency, recognizes that specific farming systems support high biodiversity levels, mainly as a result of extensive management practices. The Portuguese montado is one of the most significant HNV systems in southern Europe. However, considering the great complexity characterizing these systems both in land management and in landscape structure, a specific context-oriented methodology to assess which montado areas are likely to be classified as HNV farmland is needed. In this sense, the aim of this study is to explore a methodological approach which makes it possible to assess land management pressures through land cover information on these complex silvo-pastoral systems. The proposed methodology was tested through a local case study in a montado area in southern Portugal, assessing the relation between management practices and a vegetation cover index. Results show that in similar montado areas different land management strategies varying in stocking density, but also in type of grazing animals and shrub control practices, configure different vegetation cycles. These results indicate there is a way to develop a straightforward methodology to assess the HNV value of Mediterranean silvo-pastoral systems based on land cover indicators. These would make it possible to assess the HNV of montado areas with direct and objective information and independent of farmer’s surveys or other farm-based data.