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.
Access this resource online at: http://dx.doi.org/10.3390/land4030807