SUPERVISOR: Karlheinz ERB, Veronika GAUBE

PROJECT ASSIGNED TO: Bastian BERTSCH-HÖRMANN

Climate change (CC) will likely encompass an increase in the frequency and intensity of extreme weather events (EWE) such as heatwaves, droughts or heavy precipitation events, which can have a profound impact on socio-ecological systems (SES). Thus, there is a pressing need to understand in more depth future consequences of CC and EWE on SES. Research on the impacts of sudden shocks on SES across spatial and temporal scales demands novel approaches to identify the option space to enhance social-ecological resilience.

Of particular interest are vulnerabilities of agriculture to climate change, as well as socioeconomic dimensions of CC impacts in the agricultural sector. CC and EWE are predicted to significantly increase abiotic stress factors such as floods and droughts as well as biotic stresses like pests and disease. To particularly limit negative but also garner positive CC impacts, agricultural actors are challenged to adapt their land management strategies “to moderate or avoid harm or exploit beneficial opportunities” (IPCC, Mach et al. 2014).

Land users’ behavior depends on a diverse range of environmental, socioeconomic, political, cultural and psychological factors. In particular when coping with natural hazards such as CC and EWE, decision-making is also based on a land user’s change orientation, financial capacity, labor availability and local support network, as well as his perception and management of uncertainty and risk, resulting in stark variation in an individual’s willingness to adapt.

The overarching scientific objective of this project is to advance understanding and assessment of land users’ CC adaptation behavior and to further develop a novel methodological approach for investigating the medium- to long-term effects of biophysical, socioeconomic and political framework conditions underpinning land users’ decision-making processes. This will be achieved by combining qualitative and quantitative methods and data in an agent-based model (ABM) applied in the European long-term socio-ecological research (LTSER) platform Doñana, Spain. The research questions are as follows:

  • What are the CC impacts on agriculture in the study region?
  • What are land users‘ adaptation options in specific agricultural sectors?
  • Which factors determine their decision-making and adaptive behaviour?
  • What inferences can be drawn to inform CC adaptation planning and governance?

The agent-based model (ABM) SECLAND, applied in this project, will be able to simulate land users’ decision-making processes under varying framework conditions in the study region. This will allow to explore potential future land-use change and adaptive management strategies driven by gradual as well as sudden changes to the SES on a meso- to macroscale (e.g. climatic, socioeconomic, political). The model's agents are driven by intrinsic factors (e.g. farming style, farmer’s contentment, change orientation, available capital and workforce etc.) and extrinsic factors (e.g. climate, markets, subsidies), governing a series of actions (e.g. intensification/extensification, irrigation, diversification, afforestation, abandonment etc.) specifically defined within the local context of each study region. Development of scenarios with varying framework conditions will enable testing of different governing factors of land-use change and CC adaptation.

SECLAND has been specifically developed for an alpine region in Austria. Model transfer to a new and entirely different study region requires a series of qualitative and quantitative data, which will be gathered in a mixed methods and data approach including expert interviews, focus groups, statistical, survey and geo-spatial data. Implementation of counter-factual scenarios (including socioeconomic, political and climatic variables) will allow for evaluation of the impacts of varying framework conditions. Scenarios will be based on the Shared Socioeconomic Pathways (SSPs) and sector-specific SSPs for the European agriculture and food system (Eur-Agri-SSPs). More extreme counter-factual will also serve to identify potential option spaces for agricultural development in the study region.

These analyses will be used to detect spatial and temporal patterns and dynamics of land-use change and to identify significant correlations between changes in land use and management, intrinsic characteristics and varying framework conditions. Insights and inferences shall be used to inform policy formulation and development of CC adaptation strategies at the local-to-regional level.