Landscape transformation under global environmental change in Mediterranean Mountains: Agrarian lands as a guarantee for maintaining their multifunctionality

Diego Varga, Josep Vila Subirós, Carles Barriocanal, Josep Pujantell

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

© 2016 by the authors. The analysis of past and present patterns of agrarian mountain areas allows researchers to characterize the influence of landscape heterogeneity on biodiversity, cultural heritage, and forest fire hazard. This process was mapped, quantified, and described through the use of digital mapping (GIS) and landscape indexes in a protected area in Alta Garrotxa (Catalonia, Spain). These areas require urgent management and modelling to provide alternative management scenarios, in order to maintain and recover habitats. A set of different scenarios have been designed using a multi-criteria evaluation and geospatial information available for the study area to identify the key areas for management action and to predict the potential effects on agricultural lands by prioritizing one or another management objective: biodiversity, landscape structure and perception, cultural heritage, fire hazard, and management cost. The observed progressive land abandonment of open areas with a small size and greater isolation will have a large impact on biodiversity and cultural heritage, and increase fire risk. Sustainable development will require planning objectives compatible with the conservation of biodiversity and the preservation of Mediterranean features with support for agricultural activities. This methodology can contribute to and be easily implemented by land managers, which could help to strengthen the link between managers and stakeholders.
Original languageEnglish
Article number27
JournalForests
Volume9
Issue number1
DOIs
Publication statusPublished - 12 Jan 2018

Keywords

  • Farmlands
  • Global change
  • Landscape homogeneity
  • Landscape metrics
  • Mediterranean mountains
  • Multicriteria analysis

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