Factors influencing vegetation cover change in Mediterranean Central Chile (1975-2008)
IdentifiersPermanent link (URI): http://hdl.handle.net/10017/22897
This work was financed by the REFORLAN Project, INCO Contract CT2006-032132 (European Commission), with additional input from projects CGL2010-18312 (Spanish Ministry of Science and Innovation) and S2009AMB-1783 (Madrid Government REMEDINAL-2). We are in- debted to Javier Salas and Cristian Echeverría for their input in this project. The manuscript benefited from useful comments from Jorge Aubad and two anonymous reviewers, who improved the contents and presentation of this study
Applied Vegetation Science, 2011, v. 14, n. 4, p. 571-582
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Las figuras y apéndices que contiene el documento se localizan al final del mismo.
Info:eu-repo/REFORLAN/(Programa INCO CT2006-032132)
CGL2010-18312 (Ministerio de Ciencia e Innovación)
S-2009/AMB-1783/ REMEDINAL-2 (Comunidad de Madrid)
Atribución-NoComercial-SinDerivadas 3.0 España
© Wiley, 2011
© International Association for Vegetation Science, 2011
Questions: Which are the factors that influence forest and shrubland loss and regeneration and their underlying drivers? Location: Central Chile, a world biodiversity hotspot. Methods: Using land-cover data from the years 1975, 1985, 1999 and 2008, we fitted classification trees and multiple logistic regression models to account for the relationship between different trajectories of vegetation change and a range of biophysical and socio-economic factors. Results: The variables that most consistently showed significant effects on vegetation change across all time-intervals were slope and distance to primary roads. We found that forest and shrubland loss on one side and regeneration on the other often displayed opposite patterns in relation to the different explanatory variables. Deforestation was positively related to distance to primary roads and to distance within forest edges and was favoured by a low insolation and a low slope. In turn, forest regeneration was negatively related to the distance to primary roads and positively to the distance to the nearest forest patch, insolation and slope. Shrubland loss was positively influenced by slope and distance to cities and primary roads and negatively influenced by distance to rivers. Conversely, shrubland regeneration was negatively related to slope, distance to cities and distance to primary roads and positively related to distance from existing forest patches and distance to rivers. Conclusions: This article reveals how biophysical and socioeconomic factors influence vegetation cover change and the underlying social, political and economical drivers. This assessment provides a basis for management decisions, considering the crucial role of perennial vegetation cover for sustaining biodiversity and ecosystem services.
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