Predictive modeling of the relationships among infrastructure, resource extraction, and environmental governance in Latin American forests
The loss of tropical forest plays a significant role in climate change, biodiversity loss and livelihood disruption. Large-scale infrastructure, often linked to extractive industries and agro-industrial expansion, may catalyze forest conversion in sensitive socio-ecological zones. Global financial flows, national political settlements, and local rights also influence patterns of forest conversion in the context of new infrastructure. Extensive data on these elements exist, but consistent and careful analysis across boundaries and data types is lacking. This pursuit will synthesize geospatial data and existing qualitative research to ask: (1) what are likely future scenarios for relationships among infrastructure investment, forest cover and communities; (2) how do different forms of environmental governance affect these scenarios; (3) how are these different forms of environmental governance explained: what factors bring them into being?
The pursuit will: (1) collate existing qualitative data into data sets on environmental governance, policy processes and infrastructure investment; and (2) relate these to data sets on financial flows, forest loss, resource extraction, infrastructure, indigenous and community territories, and protected areas. These combined data sets will be used to (3) develop predictive socio-ecological models of the relationships among investment flows, large-scale infrastructure, resource extraction and forest cover; and (4) incorporate into these models forms of environmental governance and the socio-political factors that drive governance regimes. The pursuit focuses on Latin America with a view to developing models and frameworks of relevance to forested regions of Indonesia and Central Africa also experiencing increased infrastructure investment.