Abstract

Land use change due to human activity can have serious, often irreversible effects on the environment. It affects ecosystem functions and the sustainability of protected natural areas. Problems such as fragmentation, low habitat connectivity or a decline in a territory’s ability to capture carbon are some of its consequences. By studying past land use trends we can simulate future land uses, and modeling such trends is essential if a preventive approach to the management of protected areas is to be adopted. The aim of this chapter is to simulate different change scenarios in protected natural areas in the urban region of Madrid, from National and Nature Parks to Special Areas of Conservation and Special Protection Areas. To this end we study land use changes both inside and around these protected areas. CORINE Land Cover maps from 1990, 2000 and 2006 are used. Cross-tabulation techniques are applied in order to study trends in land use change. Three scenarios are designed: a baseline or trend scenario, an economic crisis scenario and a green scenario. The CLUE model (based on logistic regression) is used. LCM (based on neural networks) is also used but only in the trend scenario. Biophysical, socio-economic and accessibility factors and incentives and restrictions are considered. FRAGSTATS and GUIDOS are used to analyse the effect of infrastructure and built-up land growth on connectivity and fragmentation. In recent decades, the region of Madrid has experienced intense urban and infrastructure development (48,332 ha). Protected areas have been affected by this urbanization process. Built-up areas have grown at an average annual rate of 5.52% in protected areas and around them. According to the trend scenario, the built-up area will increase by 28,000 ha over the period 2006–2025 to 7.6% of the study area. No fragmentation processes are expected in the National Park. However, fragmentation of agricultural and natural habitats around protected areas is expected to increase by 7.2% during this period. These findings should alert land use planners and the managers of protected areas to the potential threats.

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