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Using Social Science Case-Studies to Help Parameterize Land Change Models

The disconnection between the different research perspectives, and the disciplinary communities involved in the different approaches, causes land change models to neglect the knowledge gained by the narrative and empirical perspectives. A specific approach to bridge the different research approaches in land change research and generalize local findings across larger regions has been the use of meta-analysis of case studies. Meta-analysis is a form of systematic review aimed at the statistical evaluation of a large number of case studies and can provide the empirical base for designing simulation models. Meta-analysis is especially useful if new (and possibly more structured) data collection is not feasible due to the large time and financial investments required. Such systematic review of studies is useful in land science since globally valid explanations of what factors drive land use change remain largely incomplete (Rudel 2008). Common understanding of the causes of land change is dominated by simplifications that, in turn, underlie many land change models. Within case studies of land change, based on either the narrative or empirical research approach, a wealth of in-depth information on decision making in human environment interactions is available. Meta-analysis can help to identify commonalities across these case studies and identify which factors (variables) cause different cases to behave differently. Case studies on land change often contain information on the proximate causes of land change and their underlying driving factors and provide insight in the decision making processes leading to changes in land use and management. The main approach to systematic review of the knowledge in case studies in the field of land science has been the synthesis of proximate causes and driving factors for specific land change processes resulting in a listing of the globally most frequently mentioned drivers of land change. Examples of such systematic review or meta-analysis are available for deforestation (Geist and Lambin 2002; Rudel 2005), desertification (Geist and Lambin 2004), agricultural intensification (Keys and McConnell 2005) and shifting cultivation (van Vliet et al. 2012). These meta-analysis support the conclusion that the simple answers found in population growth, poverty and infrastructure rarely provide an adequate understanding of land change. Rather, individual and social responses follow from changing economic conditions, mediated by institutional factors. Opportunities and constraints for new land uses are created by markets and policies, increasingly influenced by global factors (Lambin et al. 2001). A weakness of the existing meta-analysis in land use is that it is mainly tended towards understanding the broad, macro-scale social forces that affect nature-society relationships and less attention is given to the role of the space-time context in determining these relationships, i.e. mostly the humanenvironment system is investigated following the first conceptual model in Fig. 8.1. At the same time, the case studies included tend to be biased towards the most interesting regions with dramatic land changes.

For a more limited set of case studies Rindfuss et al. (2007) tried to more specifically identify the important factors explaining differences in land change processes between frontier regions. However, as case studies are often made by different teams and with different objectives, the quantitative comparison of such cases turned out to be more troublesome; indicating the need for more clearly documenting common sets of case study findings and harmonizing case study methods in order to be able to contextualize case study findings. Such harmonization will ensure that case study results can more easily be contextualized, allowing the use of the findings in land change models.

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