Living with Deforestation Analyzing Transformations in Welfare and Land Use on an Old Amazonian Frontier
Tropical deforestation is a striking form of land cover transformation resulting in a complex mosaic of shifting land-use patterns across space and time. While research on forest conversion has been prolific, there has been relatively less attention given to long term impacts on the socio-economic welfare of frontier inhabitants along with the reciprocal effects of income and wealth on land use. Moreover, there is limited understanding of how post-deforestation trajectories are related to employment, migration, and inequality. These lacunae are directly related to the difficulty of obtaining the data required to track and evaluate these processes. Nevertheless, as the "old frontier" expands in tropical forest zones, it is critical to understand the dynamic economic and landscape processes that follow deforestation. This project will address these issues by adding a fourth round to a spatial panel of farm households, expanding the database to multiple scales with new secondary data, improving classification methods for remote sensing data, and modeling land use decisions and their consequences in the heavily deforested state of Rondônia, Brazil.
A principle outcome of this project will be a public dataset that can be used by researchers from various disciplines to analyze questions related to the dynamic and spatial processes on forest frontiers. Specifically, spatially-referenced household panel survey data collected (from the same households and farm lots in four time periods) in the core study area of Ouro Preto do Oeste will be combined with several sources of data that cover an expanded study region: cadastral maps matched with satellite imagery to quantify land cover change; spatial data on biophysical factors, markets, and public infrastructure; and secondary data at multiple scales from official sources such as the current agricultural census. A second outcome will be improved land cover classification methods developed through traditional ground referencing and household-reported land use histories. Lastly, this research will draw more general conclusions regarding the co-evolution of land use and socio-economic welfare through combined analysis of complementary secondary data that expands the temporal and spatial range of the detailed household survey and linked remote sensing data.
This project investigated the long term impacts of tropical deforestation on the socio-economic welfare of frontier inhabitants and the reciprocal effects of income and wealth dynamics on land use. To draw conclusions, our field work included the collection of survey data from farm households in the heavily deforested state of Rondônia, Brazil (the fourth round of panel for the years 1996, 2000, 2005, and 2009), expanding our existing database to multiple scales with new secondary data, and adding improved classification methods for remote sensing data that now include a full, unbroken 27 year history of land-cover change from 1984 to 2010. These data were used to analyze post-deforestation trajectories of land use and welfare for the study region (and greater Amazon). Our findings suggest that welfare has improved according to multiple measures at different scales, providing counter evidence for the boom-bust theory and the turnover hypothesis (or the suggestion that deforestation increases income and wealth for residents but this growth reverses once forest degradation is extensive, pushing residents to abandon properties and migrate to an advancing frontier). We also investigated the impact of several recent government initiatives to slow deforestation. Along these lines, our results suggest that the forestry code is not only widely disregarded, but also that there is little evidence to support any visible impact of the current legislation on decision-making at the lot-level. Results also indicate that new settlement designs developed to further social interaction have had a negative impact on land cover and land use transformation, creating incentives to deforest more rather than less. Finally, in regards to carbon storage, we performed high spatial and temporal resolution modeling of carbon stocks and fluxes in the state of Rondônia, Brazil for the period 1985-2009, using annual Landsat-derived land cover classifications and a modified bookkeeping approach. According to these results, Rondônia contributed ~4% of pan-tropical humid forest deforestation emissions over this period. Furthermore, secondary forest, a potential carbon sink, proved to be uncommon and rarely persisted in the landscape. A principle outcome from this project is a public dataset that can be used by researchers from various disciplines to analyze questions related to the dynamic and spatial processes on forest frontiers.
