International graduate, PhD, and postdoc students
One of the main challenges facing interdisciplinary research on drylands is the analysis of the interaction between social and ecological systems within and across spatial and temporal scales. Scale is an important concept to transcend disciplinary boundaries between ecological and social phenomena because there often is a mismatch between the ecological scale of certain issues and the social scale in which this issue is dealt with. At the same time, the epistemologies and ontologies of data collection and analysis within different disciplines and scale levels often "mismatch" and lead to all kinds of stumble blocks and misunderstandings in interdisciplinary research. Hence, one of the main scientific challenges is to find methodologies to overcome these issues.
Wide ranges of methodological approaches are used to link environmental data with social and cultural data. Recently, in addition to regression models and time-series analyses, agent-based modelling has been providing a tool to link decision-making of individuals with factors influencing decisions. The main challenge is the combination of point data with gridded data and almost continuous data with discrete data of various data categories (e.g. numeric, ordinal). Data on the socio-economic and socio-political situation are comparably sparse in space and time. They often come from infrequent census campaigns and are aggregated to larger political administration levels. Thus, they are difficult to link with migration processes, as population movement is only partly quantified along migration routes, and it is often estimated. The demographic development is measured, estimated, and projected with scenarios. New developments include mobility profiles using social media and an increasing control of movement at border posts using digital methods. Data obtained from case studies might be used for unravelling mechanisms and modes of interaction between different levels rather than be used for quantitative analysis. These will be employed to increase the quality and validation of models developed at higher scale levels. Besides the different data types and data scales, the quality of the above-listed data sources is of utmost importance, as are the uncertainties related to the data. Land cover data and precipitation data are very different in quality, even from the same data providers. As is the case for bio-physical data, data quality is of utmost importance for socio-political and socio-economic data. A wide range of sources and methods for validation will be used for this.
After the course, the participants should have:
- A basic understanding of the main concepts related to issues of scale and complexity of social-ecological systems in drylands
- The ability to relate these basic concepts to own research and epistemological and ontological positions
- The ability to understand the different scales and data qualities and to evaluate these issues
- The ability to select the appropriate methods for the available data
- The ability to debate and discuss these issues with people working on other scale levels and in other disciplines
- A basic ability to apply these skills in the design of new research
For more detailed information on the course content and lecturers, please visit our website.