The Relative Importance of Socioeconomic and Environmental Variables in Explaining Land Change in Bolivia, 2001–2010

Annals of the Association of American Geographers (Impact Factor: 2.09). 07/2012; 102(4):778-807. DOI: 10.1080/00045608.2012.678036


This study assesses the relationship between trends in land change from 2001 to 2010 and socioeconomic and environmental variables in Bolivia at multiple spatial scales using a nonparametric, tree-based modeling approach. It also explores the theoretical dimensions surrounding the debate over the relative importance of socioeconomic and environmental variables in explaining land change. Results from the land change analysis show several hotspots of dynamic change. The majority of woody vegetation loss occurred in the eastern lowlands of Santa Cruz, Beni, and Pando and was attributable to the expansion of industrial agriculture. Gains in woody vegetation took place in the drylands of Santa Cruz and Beni savanna, and these changes were attributed to shifting patterns in precipitation and fire rather than human-induced change. Other hotspots of woody vegetation gain were attributed to abandonment of agriculture and herbaceous lands in the intermontane valleys of the southern Andes. Regression analyses showed that population and other demographic variables were poor predictors of land change. There is a clear relationship, however, between changes in woody and agriculture/herbaceous vegetation and environmental variables such as precipitation, temperature, and elevation. Municipalities with adequate precipitation and moderate temperature tended to show increases in agriculture and herbaceous vegetation and woody vegetation declines. Woody vegetation tended to increase in municipalities at higher elevations. This study also shows that explanations of only wealth or population as the main drivers of land change undervalue the role that natural features, like topography and precipitation, play in limiting or permitting certain land-use decisions.

Download full-text


Available from: Matthew Clark, Feb 13, 2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: Although over 40 years of satellite imagery has greatly helped in documenting the location and extent of human impact, especially deforestation, our ability to confidently detect current patterns of land change at broad spatial scales needs improvement. To address this challenge, we have developed a cost-effective mapping procedure based on 250-m MODIS imagery that produces annual land-use/land-cover (LULC) maps for Latin America and the Caribbean (LAC). This procedure uses annual spectral statistics, collection of references samples with a Web-based tool, and tree-based Random Forests classifiers stratified by biome map regions to produce wall-to-wall, annual LULC maps for 2001 to 2010 that cover all of LAC. Across 26 map regions, overall pixel-level accuracy averaged 80.2 ± 8.1% for eight basic LULC classes, and 84.6 ± 6.5% for a five-class scheme. Municipality-scale area change between 2001 and 2010 in the three dominant classes (woody vegetation, mixed woody/plantation, and agriculture/herbaceous vegetation) was then estimated using regression models fit to 10 years of data, thus minimizing the impact of inter-annual class variation on change statistics. Closed-canopy forest area and change between 2001 and 2009 were well correlated with high-resolution maps of the Brazilian Legal Amazon (PRODES project). Our LAC-wide analysis of significant change revealed the recent extent and magnitude of deforestation hotspots, such as in the Amazon moist forests and the dry forests of Argentina, Paraguay and Bolivia. Our data also revealed biome-specific clusters of municipalities with increasing woody vegetation due to forest recovery, reforestation, or woody encroachment. Taken as a whole, our MODIS-based mapping and trend modeling methodology can provide reliable land change data, not just for the tropics or for forest cover, but for all biomes and municipalities in LAC and including multiple LULC classes. Because this information can be produced quickly on an annual time scale, with internally-consistent data sources, it is a very useful tool for resource managers, policy makers, scientists and conservationists interested in tracking recent land change across broad-scale, political and environmental gradients.
    No preview · Article · Nov 2012 · Remote Sensing of Environment
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Increasing water use and droughts, along with climate variability and land use change, have seriously altered vegetation growth patterns and ecosystem response in several regions alongside the Andes Mountains. Thirty years of the new generation biweekly normalized difference vegetation index (NDVI3g) time series data show significant land cover specific trends and variability in annual productivity and land surface phenological response. Productivity is represented by the growing season mean NDVI values (July to June). Arid and semi-arid and sub humid vegetation types (Atacama desert, Chaco and Patagonia) across Argentina, northern Chile, northwest Uruguay and southeast Bolivia show negative trends in productivity, while some temperate forest and agricultural areas in Chile and sub humid and humid areas in Brazil, Bolivia and Peru show positive trends in productivity. The start (SOS) and length (LOS) of the growing season results show large variability and regional hot spots where later SOS often coincides with reduced productivity. A longer growing season is generally found for some locations in the south of Chile (sub-antarctic forest) and Argentina (Patagonia steppe), while central Argentina (Pampa-mixed grasslands and agriculture) has a shorter LOS. Some of the areas have significant shifts in SOS and LOS of one to several months. The seasonal Multivariate ENSO Indicator (MEI) and the Antarctic Oscillation (AAO) index have a significant impact on vegetation productivity and phenology in southeastern and northeastern Argentina (Patagonia and Pampa), central and southern Chile (mixed shrubland, temperate and sub-antarctic forest), and Paraguay (Chaco).
    Full-text · Article · Mar 2013 · Remote Sensing
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Forest cover change directly affects biodiversity, the global carbon budget, and ecosystem function. Within Latin American and the Caribbean region (LAC), many studies have documented extensive deforestation, but there are also many local studies reporting forest recovery. These contrasting dynamics have been largely attributed to demographic and socio-economic change. For example, local population change due to migration can stimulate forest recovery, while the increasing global demand for food can drive agriculture expansion. However, as no analysis has simultaneously evaluated deforestation and reforestation from the municipal to continental scale, we lack a comprehensive assessment of the spatial distribution of these processes. We overcame this limitation by producing wall-to-wall, annual maps of change in woody vegetation and other land-cover classes between 2001 and 2010 for each of the 16,050 municipalities in LAC, and we used nonparametric Random Forest regression analyses to determine which environmental or population variables best explained the variation in woody vegetation change. Woody vegetation change was dominated by deforestation (-541,835 km2), particularly in the moist forest, dry forest, and savannas/shrublands biomes in South America. Extensive areas also recovered woody vegetation (+362,430 km2), particularly in regions too dry or too steep for modern agriculture. Deforestation in moist forests tended to occur in lowland areas with low population density, but woody cover change was not related to municipality-scale population change. These results emphasize the importance of quantitating deforestation and reforestation at multiple spatial scales and linking these changes with global drivers such as the global demand for food. © 2012 by The Association for Tropical Biology and Conservation.
    Full-text · Article · Mar 2013 · Biotropica
Show more