Model-based synthesis of locally contingent responses to global market signals

Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals. Synthesis of insights from place-based case studies is a path forward for developing such systematic knowledge. This paper introduces a generalized agent-based modeling framework for model-based synthesis to investigate the relative importance of structural versus agent-level factors in driving land-use and livelihood responses to changing global market signals. Six case-study sites that differed in environmental conditions, market access and influence, and livelihood settings were analyzed. Stronger market signals generally led to intensification and/or expansion of agriculture or increased non-farm labor, while changes in agents' risk attitudes prompted heterogeneous local responses to global market signals. These results demonstrate model-based synthesis as a promising approach to overcome many of the challenges of current synthesis methods in land change science and identify generalized as well as locally contingent responses to global market signals.