Doctoral Dissertation Research: Ethnohistorical and Geographical Analysis of Livelihood and Institutional Drivers of Landscape Change

University Of California-Santa Cruz, Santa Cruz CA

Investigators

Abstract

In the research supported by this award, University of California, Santa Cruz, doctoral student, Robert Davenport, with direction from anthropologist Dr. Andrew Mathews, will investigate social factors that may drive variation in forest land use and management in a context of social change and livelihood development. For most of human history, anthropogenic effects on forest ecosystems unfolded slowly over long periods of time. But now scientists are observing changes in forest cover that occur over mere decades, dramatically accelerated by such human activities as large-scale agriculture and road construction. With growing concern over the loss of biodiversity worldwide, scientific research on global land use change has emphasized the environmentally destructive impacts of human colonization and settlement, especially in the tropics where recent human arrivals often lack the institutions and techniques to counter the effects of commercial agriculture and logging and keep forests standing. However, while some scientists have modeled deforestation as the direct result of the expansion of agriculture, others have argued that not all farming is the same and that small-scale agroecological farming methods can actually reduce deforestation and enhance biodiversity while still using the forests productively. A critical question for forest ecosystems is how the social organization of livelihoods and institutions can encourage new relationships to emerge between agriculture and biodiversity. To date, research on socio-ecological systems has tended to focus on traditional environmental management, paying less attention to shifts between types of land use as a function of evolving social organization on market peripheries. But better knowledge of these latter dynamics is critically needed: U.S. and state policies for mitigating climate change involve international incentives to reduce tropical deforestation but lack necessary understanding of social and livelihood development processes for the populations that inhabit the forests. To further these understandings, this project will analyze an observed change in tropical forest cover that counters conventional wisdom: unusually, it involves a transition from deforestation to reforestation, rather than the other way around, despite having been subject to colonization since 1970. Davenport will assess how livelihoods, institutional arrangements, and cultivation decisions have variously impacted land use changes in time and space. The site of the research is the municipality of Medicilândia on the TransAmazon highway in Brazil, which has seen many of its small farmer majority population develop manual labor intensive and species diverse agroforestry systems with cacao trees (Theobroma cacao) and açai palms (Euterpe oleracea). While deforestation has continued apace in other areas of Medicilândia located farther from the highway, most land inside a ten kilometer range, deforested a quarter-century ago, is today either a forest farm or a regrowth secondary forest. The researcher will compare socio-ecological interactions on farms with distinct land use change trajectories. Three questions will be used to guide the analysis. First, how have the rural poor adapted distinct livelihood strategies over time, and involving what labor, logistical, subsistence and commercial arrangements? Second, how have institutions, colonist outlooks and attitudes shaped rules and norms concerning the land? The latter involves land tenure rights, local social organization and the evolving relationship of the locality with state agencies and regulatory systems, including the national Brazilian forest code. Third, how have agroecological techniques and species cultivation decisions varied in relation to livelihood and institutional factors, and what land use change has resulted? Quantitative and qualitative datasets will be constructed using survey, ethnographic and ethnobotanical methods; these will be integrated with remote sensing analysis of 30 years of satellite images and aerial photography to map and model human shaping of the environment over time.