Climate change predictions tied to Amazon deforestation scenarios are increasingly being used by government and non-government organisations for near-future planning applications. Despite incorporating a wide range of biophysical variables, these models neglect future scenarios of land use for adjoining regions, such as the Central Brazil Cerrado, which has been deforested by more than 50%. In this study, we investigate the impact of different Amazon and Central Brazil deforestation scenarios on the rainfall regime of the 'arc-of-deforestation' in Amazonia. We demonstrate that both Amazon and Cerrado deforestation contribute to an increase of the duration of the dry season in this region. Combining the effects of both scenarios, the dry season may increase from 5 months to 6 months, which may change the biosphere-atmosphere equilibrium in this region. This study demonstrates that the assessment of future Cerrado land use scenarios is also necessary to understand the future climate and ecosystem health of Amazonia.

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Deforestation on Amazonia and central Brazil Cerrado could change regional climate, possibly shifting forest equilibrium into a bioclimatic envelope typical of savannas. Although impacts of climate change induced by deforestation are likely to vary subregionally, the potential geographic variation of these effects and the thresholds of rainforest and Cerrado removal that will affect Amazonian bioclimatic equilibrium remain unknown. We evaluate the effects of deforestation scenarios of increasing severity on the bioclimatic equilibrium of Amazon subregions. Results indicate that subregional precipitation responds in three distinct ways to progressive deforestation: a near‐constant rate of reduction, a rapid drop for low deforestation levels, and a decrease after intermediate deforestation levels. Additionally, while inner forest regions remain inside rainforest bioclimatic envelope, outer forest regions may cross forest‐savanna bioclimatic threshold even at low deforestation levels. We argue that at least 90% of Amazonia and 40% of Cerrado should be sustained to avoid subregional bioclimatic savannization.

In southern Amazonia, more than half of all cropland is devoted to the production of two rainfed crops per year, an agricultural practice known as “double cropping” (DC). Climate change, including feedbacks between changes in land use and the local climate, is shortening the extent of the historical rainy season in southern Amazonia, increasing the risk of future detrimental environmental conditions, and posing a threat to the intensive DC agriculture that is currently practiced in that region, with potential negative consequences at regional, national, and even global scales. We argue that the conservation of undeveloped forests and savannas in southern Amazonia is supported by socioeconomic justifications and is in the best interests of agribusiness, local governments, and the public.

The Amazon rain forest constitutes one of the major global stocks of carbon. Recent studies, including the last Intergovernmental Panel on Climate Change report and the Coupled Climate Carbon Cycle Model Intercomparison Project, have suggested that it may reduce in size and lose biomass during the twenty-first century through a savannization process. A better understanding of how this ecosystem structure, dynamics, and carbon balance may respond to future climate changes is needed. This article investigates how well a fully coupled atmosphere-biosphere model can reproduce vegetation structure and dynamics in Amazonia to the extent permitted by available data. The accurate representation of the coupled climate-biosphere dynamics requires the accurate representation of climate, net primary production (NPP), and its partition among the several carbon pool components. The simulated climate is validated against precipitation (within 5% of four datasets) and incident solar radiation (within 7% of observations). The authors also validate (i) simulated land cover, which reproduces well the observed patterns; (ii) NPP, within 5% of observations; and (iii) respiration rates, within 15% of observations. The performance of simulated variables that depend on carbon allocation, like NPP partitioning, leaf area index, and aboveground live biomass, although good on a regional mean, is significantly low when spatial patterns are considered. These errors may be attributed to fixed carbon allocation and residence time parameters assumed by the model. Carbon allocation apparently varies spatially, and to simulate this spatial variability is quite a challenge.

Low productivity cattle ranching, with its linkages to rural poverty, deforestation and greenhouse gas (GHG) emissions, remains one of the largest sustainability challenges in Brazil and has impacts worldwide. There is a nearly universal call to intensify extensive beef cattle production systems to spare land for crop production and nature and to meet Brazil's Intended Nationally Determined Contribution to reducing global climate change. However, different interventions aimed at the intensification of livestock systems in Brazil may involve substantial social and environmental tradeoffs. Here we examine these tradeoffs using a whole-farm model calibrated for the Brazilian agricultural frontier state of Mato Grosso, one of the largest soybean and beef cattle production regions in the world. Specifically, we compare the costs and benefits of a typical extensive, continuously grazed cattle system relative to a specialized soybean production system and two improved cattle management strategies (rotational grazing and integrated soybean-cattle) under different climate scenarios. We found clear tradeoffs in GHG and nitrogen emissions, climate resilience, and water and energy use across these systems. Relative to continuously grazed or rotationally grazed cattle systems, the integreated soybean-cattle system showed higher food production and lower GHG emissions per unit of human digestible protein, as well as increased resilience under climate change (both in terms of productivity and financial returns). All systems suffered productivity and profitability losses under severe climate change, highlighting the need for climate smart agricultural development strategies in the region. By underscoring the economic feasibility of improving the performance of cattle systems, and by quantifying the tradeoffs of each option, our results are useful for directing agricultural and climate policy.

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