Speaker: Dr. Darla Munroe (The Ohio State University)
Title: The interdependence of forest transition pathways at the household level in Yunnan, China
Date: Wednesday, April, 25th, 2012
Category: Seminar
Abstract
Prior research on “forest transitions,” or the observation of sustained forest recovery following past forest clearing, has often employed the concept of forest “pathways” to elucidate the variation in key drivers and mechanisms across diverse case studies. Recent forest recovery in China is generally attributed to a state response to prior environmental degradation, including the Sloping Land Conversion Program (SLCP) implemented at a household level. This explanation is prioritized against competing alternative processes, including socioeconomic development and associated off-farm employment opportunities or the shifting livelihood strategies of rural households. Drawing from a broader understanding of how policies were implemented and the related land-use changes that have occurred in Yunnan over the last 20 years, we discover that these forest pathway alternatives are actually interconnected processes at the household level. We employ multivariate discriminant analysis to associate household variations in tree planting (through, or independent of, SLCP) to a set of variables intended to capture a broader set of processes that influence households’ ability and willingness to make land-use changes. We find that tree-planting activities relate to a combination of factors, including policies, migration (available labor and off-farm income) and agricultural profitability. Thus, we suggest that forest transition research should more explicitly examine pathway interconnections in understanding forest recovery.
Keywords: forest transition, pathways, household survey, land-use change, discriminant analysis, China
Darla Munroe is an economic geographer who studies land use/cover change. She is interested in how economic restructuring (e.g., neoliberalism and globalization) and political changes (e.g., land reform) lead to changes in agricultural and forested landscapes. In order to understand processes underlying land-use/cover change and associated socioecological effects, she employs a variety of techniques including statistics, spatial statistics and more recently, complex systems frameworks and agent-based modeling.
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