Research line: Human societies and biodiversity
In the context of rapid anthropogenic global change, the research line “Human Societies and Biodiversity” at the Estación Biológica de Doñana (CSIC) examines human–nature relationships to inform biodiversity management. This research is strongly applied and closely linked to decision-making and policy design. Spanning temporal scales from past to present, and organisational levels from species to landscapes, we investigate how these relationships are shaped, perceived, and valued, and how they may be restored to support biodiversity conservation and human well-being.
Through historical ecology, we analyse how human perceptions and interests have driven species use, decline, and biological invasions, while reconstructing past species distributions and ecosystem states. By assessing the ecological and economic impacts of invasive species, alongside their effects on human well-being and their invasion potential, we contribute to improved prioritisation and management strategies.
Addressing climate change as a key driver of global change, we quantify both direct and ecosystem-mediated effects on human health, as well as evaluate the effectiveness of heat–health action plans and early warning systems. At the landscape scale, we employ spatial modelling to examine connectivity between aquatic and terrestrial ecosystems, assess ecological status, and identify conservation priorities that guide restoration and protection efforts.
Restoration strategies are supported and evaluated across natural and agricultural systems within adaptive management frameworks, emphasising participatory design and implementation. Social–ecological approaches underpin long-term monitoring and the facilitation of agroecological transitions in the Doñana region and beyond.
This research integrates diverse data sources, including historical documents and paintings, surveys, interviews, deliberative processes (e.g. Living Labs), mental models, satellite imagery, and large-scale health and socio-economic datasets.
