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Koutsias N.,University of Ioannina | Martinez-Fernandez J.,CSIC Spanish Research Council | Allgower B.,Science City Davos
GIScience and Remote Sensing | Year: 2010

This paper describes the results of a geo-statistical analysis carried out at the provincial level in Southern Europe to model wildfire occurrence from socio-economic and demographic indicators together with land cover and agricultural statistics. We applied a classical ordinary least squares (OLS) linear regression together with a geographically weighted regression (GWR) to explain long-term wild-fire occurrence patterns (mean annual density of >1 ha fires). The explanatory power of the OLS model increased from 52% to 78% as a result of the non-constant relationships between fire occurrence and the underlying explanatory variables throughout the Mediterranean Basin. The global model we developed (i.e., OLS regression) was not sufficient to fully describe the underlying causal factors in wildfire occurrence modeling. Indeed, local approaches (i.e., GWR) can complement the global model in overcoming the problem of non-stationarity or missing variables. Our results confirm the importance of agrarian activities, land abandonment, and development processes as underlying factors of fire occurrence. The identification of regions with spatially varying relationships can contribute to the better understanding of the fire problem, especially over large geographic areas, while at the same time recognizing its local character. This can be very important for fire management and policy. Source


Nainggolan D.,University of Leeds | Nainggolan D.,University of Aarhus | de Vente J.,CSIC Spanish Research Council | de Vente J.,CSIC - Center of Edafology and Applied Biology of the Segura | And 5 more authors.
Agriculture, Ecosystems and Environment | Year: 2012

An understanding of land use change and its drivers in semi-arid Mediterranean agro-ecosystems is important for informing ways to facilitate adaptation to future environmental and socioeconomic pressures. In this paper, we mapped and quantified land use changes in the semi-arid Mediterranean agro-ecosystem of Torrealvilla catchment between 1956 and 2008. Subsequently, we detected signs of landscape fragmentation and examined the relationship between land use change trajectories and a set of biophysical factors using Generalized Additive Models (GAMs). Finally, we qualitatively evaluated the role of socioeconomic drivers on the land use change trajectories. The study provides accounts of multidirectional land use trajectories in semi-arid Mediterranean landscapes. Our analysis shows that more than 72% of the study area has undergone significant changes over the past five decades with pronounced effects on landscape composition and structure. Both biophysical and socioeconomic factors are strongly related to the observed spatial and temporal changes in land use. Three major trajectories were observed. Firstly, rain-fed agriculture is becoming less dominant; future abandonment of rain-fed agriculture should be anticipated. Secondly, expansion of forested areas is evident in higher altitudes. The trend is still likely to continue given the possibility of further abandonment of rain-fed farming and existing subsidies for reforestation of arable land. Thirdly, intensification has been observed which has occurred mainly in lower parts of the landscape on flat to gentle slopes and near main roads. Further intensification is likely to be subject to market drivers, irrigation water availability, and future rural development and agricultural policy. Overall, the study shows that even within a given locality, contrasting land use trajectories can emerge as a result of local responses to multiple drivers of change and these need to be carefully taken into account in future policy development. © 2012 Elsevier B.V. Source

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