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Land degradation is caused by and has impacts on both the social and natural components of coupled human-environment systems. However, few studies integrate both aspects simultaneously. The main objective of this study is to test a method to evaluate land degradation based on the integration of aggregate metrics of biophysical and socio-economic "degradation". We applied a framework that integrates the biophysical and socio-economic dimensions of land degradation to test the hypothesis that macro-economic policies, and in particular agricultural subsidies, are an important driving force of land degradation in marginal regions of the Mediterranean Europe. We analysed the influence of subsidies on the profitability of each crop and livestock type found in a sample of farms in a region of northern Greece. Spatial and socioeconomic data on agricultural households were collected to link remote sensing data and land degradation maps to socio-economic conditions of these households, as measured by the standard gross margin. The results demonstrate that subsidies provide a crucial socio-economic support to maintain the profitability of agricultural activities but may also promote land-use practices with damaging ecological impacts. Different levels of biophysical and socio-economic "degradation" were associated with different land use practices. The integration of the socio-economic and biophysical dimensions of land degradation reveals associations that would not be detectable if indicators along one dimension alone would be used. (C) 2008 Elsevier B.V. All rights reserved.

In past decades, the European Mediterranean has undergone widespread land use transformations. These are largely driven by changes of socio-economic conditions, such as accession to the European Community, and had strong effects on the way the land is being used. Aiming at a systematic description of such change processes on a global level, the syndrome concept was proposed to describe archetypical, co-evolutionary patterns of human–nature interactions, and has been specifically linked to the desertification issue. In this study, we present an adaptation of the syndrome approach to the Iberian Peninsula. We suggest a data processing and interpretation framework to map the spatial extent of specific syndromes. The mapping approach is based on the time series analysis of satellite data. We have characterized vegetation dynamics using NDVI estimates from the coarse scale, hyper-temporal 1-km MEDOKADS archive, which is based on calibrated NOAA–AVHRR images. Results indicate that local patches of abrupt disturbance, mainly caused by fire, are contrasted by a widespread increase in vegetation, which is in large parts attributed to the abandonment of rural areas. Although this questions the dominance of classical desertification traits, i.e. decline of productivity after disturbance, it is concluded that the recent greening presents a different sort of environmental risk, as it may negatively impact on fire regimes and the hydrological cycle.