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Local, regional, and global processes affect deforestation and land-use changes in the Brazilian Amazon. Characteristics are: direct conversions from forest to pasture; regional processes of indirect land-use change, described by the conversion of pastures to cropland, which increases the demand for pastures elsewhere; and teleconnections, fueled by the global demands for soybeans as animal fodder. We modeled land-use changes for two scenarios Trend and Sustainable Development for a hot spot of land-use change along the BR-163 highway in Mato Grosso and Pará, Brazil. We investigated the differences between a coupled modeling approach, which incorporates indirect land-use change processes, and a noncoupled land-use model. We coupled the regional-scale LandSHIFT model, defined for Mato Grosso and Pará, with a subregional model, alucR, covering a selected corridor along the BR-163. The results indicated distinct land-use scenario outcomes from the coupled modeling approach and the subregional model quantification. We found the highest deforestation estimates returned from the subregional quantification of the Trend scenario. This originated from the strong local dynamics of past deforestation and land-use changes. Land-use changes exceeded the demands estimated at regional scale. We observed the lowest deforestation estimates at the subregional quantification of the Sustainable Development story line. We highlight that model coupling increased the representation of scenario outcomes at fine resolution while providing consistency across scales. However, distinct local dynamics were explicitly captured at subregional scale. The scenario result pinpoints the importance of policies to aim at the cattle ranching sector, to increase land tenure registration and enforcement of environmental laws. [ABSTRACT FROM AUTHOR]

The calculation of robust estimates of future greenhouse gas emissions due to agriculture is essential to support the framing of the Brazilian climate change mitigation policy. Information on the future development of land use and land cover change (LULCC) under the combination of various driving factors operating at different spatial scale levels, e.g., local land use policy and global demands for agricultural commodities, is required. The spatially explicit land use model, LandSHIFT, was applied to calculate a set of high-resolution land use scenarios for Southern Amazonia. The time frame of the analysis was 2010-2030. Based on the generated maps, emission coefficients were applied to calculate annual NO, CH, and CO emissions from agricultural soils (croplands and pastures). The results indicate that future land use pattern and the resultant greenhouse gas emissions in Southern Amazonia will be strongly determined by global and regional demands for agricultural commodities, as well as by the level of intensification of agriculture and the implementation of conservation policies. [ABSTRACT FROM AUTHOR]

This article describes the design of a new model-based assessment framework to identify and analyse possible future trajectories of agricultural development and their environmental consequences within the states of Mato Grosso and Pará in Southern Amazonia, Brazil. The objective is to provide a tool for improving the information basis for scientists and policy makers regarding the effects of global change and national environmental policies on land-use change and the resulting impacts on the loss of natural vegetation, greenhouse gas emissions, hydrological processes, and soil erosion within the region. For this purpose, the framework combines the regional land-use models, LandSHIFT and alucR, the farm-level model, MPMAS, and the MONICA crop model, with a set of environmental impact models that are operating at the regional and watershed levels. As a first application of the framework, four scenarios with the time horizon 2030 were specified and analysed. Future land-use change will strongly depend on the interplay between the production of agricultural commodities, the agricultural intensification in terms of increasing crop yields and pasture biomass productivity, and the enforcement of environmental laws and policies. On the regional level, the scenarios with the highest increase in agricultural production in combination with weak law enforcement ( Trend and Illegal Intensification) generated the highest losses in natural vegetation due to the expansion of agricultural area as well as the highest greenhouse gas emissions . Also, at the watershed level, these scenarios are characterised by the highest changes in river discharge and soil erosion that might lead to a further decline in soil fertility in the long term. Moreover, the analysis of the Sustainable Development scenario indicates that a shift in agricultural production patterns from livestock to crop cultivation, together with effective law enforcement, can effectively reduce land-use change and its negative effects on the environment. With the scenario analysis, we could illustrate that our assessment framework is capable to provide a large variety of valuable information to support the development of future land-use strategies in the study region. [ABSTRACT FROM AUTHOR]

Our aim with this paper is to present a novel approach for developing story lines and scenarios by combining qualitative knowledge and quantitative data from different disciplines and discussing the results with relevant decision makers. This research strategy offers a solid foundation for perspectives into the future. The "laboratory" is the Brazilian Amazon, one of the hotspots of land-use change where local and global interests both collide and converge: local livelihoods are affected by regional and global climate change and by the loss of biodiversity caused by local and global economic interests in agro-industrial land use; such use contributes, in turn, to climate change. After decades of diverse policy interventions the question arises: What can we learn from past trajectories for a more sustainable development in the future? To answer this question, we combined qualitative story lines for the region, reviewed by local experts, with quantitative land-use scenarios, to study their regional and local manifestations in space. These results were then discussed again with local and national experts. Our findings suggest that in-depth knowledge of the diverging perspectives at a very local level is a fundamental prerequisite for downscaling global scenarios and upscaling local approaches to sustainable land-use management and thus, to producing communicable and applicable results. [ABSTRACT FROM AUTHOR]