Counteracting desertification and abandonment in the rural Spanish landscape
Revealing potentialities of regeneration through a local sensitive adaptive strategy
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Abstract
Desertification and depopulation are mutually reinforcing processes that cause global socio-ecological ecosystem vulnerability through land degradation. The dehesa landscape in Spain is especially vulnerable, facing severe threats from these combined pressures and urgently needing strategic intervention. This research explores the potential of adaptive strategic planning to mitigate the socio-environmental impacts of depopulation and desertification in the rural regions of northern Extremadura, Spain, particularly focusing on the dehesa landscape. By integrating a combination of qualitative and quantitative research methods, this study analyses historical conditions and forecasts future scenarios, providing a holistic approach to environmental, ecological, social, economic, and political factors.
The use of cartography and GIS tools enhances spatial understanding and visualisation of impact distributions. The fieldwork, characterised by landscape photography and semi-structured interviews establishes a baseline understanding of the landscape’s health and land management practises. Furthermore, surveys delve deeper into community- and landscape identity, offering insights into local values and potential engagement in future scenarios.
These narratives reveal a strong community willingness to restore landscapes, dependent on clear visions for change, structured help in the form of technical knowledge of nature-based solutions, and incentives for ecosystem services. The findings suggest that an adaptive strategy, focusing on the active regeneration of the trees in the dehesa through a framework that integrates diverse actions over time, can reverse negative trends in landscape restoration. This research contributes to existing knowledge by highlighting the importance of community-engaged fieldwork and sustainable land management on a local scale to minimise effects of global processes.
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