[1] Widespread cropland abandonment occurred after the collapse of socialism across the former Soviet Union, but the rates and spatial patterns of abandoned lands are not well known. As a result, the potential of this region to contribute to global food production and estimates of the carbon sink developing on currently idle lands are highly uncertain. We developed a spatial allocation model that distributes yearly and subnational sown area statistics to the most agriculturally suitable plots. This approach resulted in new, high-resolution (1 km 2 ) annual time series of cropland and abandoned lands in European Russia, Ukraine, and Belarus from 1990 to 2009. A quantitative validation of the cropland map confirms the reliability of this data set, especially for the most important agricultural areas of the study region. Overall, we found a total of 87 Mha of cropland and 31 Mha of abandoned cropland in European Russia, Ukraine, and Belarus combined, suggesting that abandonment has been severely underestimated in the past. The abandonment rates were highest in European Russia. Feeding our new map data set into the dynamic vegetation model LPJmL revealed that cropland abandonment resulted in a net carbon sink of 470 TgC for 1990 to 2009. Carbon sequestration was generally slow in the early years after abandonment, but carbon uptake increased significantly after approximately 10 years. Recultivation of older abandoned lands would be associated with high carbon emissions and lead to substantial amounts of carbon not being sequestered in vegetation formations currently developing on idle croplands. Our spatially and temporally explicit cropland abandonment data improve the estimation of trade-offs involved in reclaiming abandoned croplands and thus in increasing agricultural production in this globally important agricultural region.

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Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

Forests in lowland Bolivia suffer from severe deforestation caused by different types of agents and land use activities. We identify three major proximate causes of deforestation. The largest share of deforestation is attributable to the expansion of mechanized agriculture, followed by cattle ranching and small-scale agriculture. We utilize a spatially explicit multinomial logit model to analyze the determinants of each of these proximate causes of deforestation between 1992 and 2004. We substantiate the quantitative insights with a qualitative analysis of historical processes that have shaped land use patterns in the Bolivian lowlands to date. Our results suggest that the expansion of mechanized agriculture occurs mainly in response to good access to export markets, fertile soil, and intermediate rainfall conditions. Increases in small-scale agriculture are mainly associated with a humid climate, fertile soil, and proximity to local markets. Forest conversion into pastures for cattle ranching occurs mostly irrespective of environmental determinants and can mainly be explained by access to local markets. Land use restrictions, such as protected areas, seem to prevent the expansion of mechanized agriculture but have little impact on the expansion of smallscale agriculture and cattle ranching. The analysis of future deforestation trends reveals possible hotspots of future expansion for each proximate cause and specifically highlights the possible opening of new frontiers for deforestation due to mechanized agriculture. Whereas the quantitative analysis effectively elucidates the spatial patterns of recent agricultural expansion, the interpretation of long-term historic drivers reveals that the timing and quantity of forest conversion are often triggered by political interventions and historical legacies.