Approximately 2.5 × 10 ⁶ square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year ⁻¹ ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year ⁻¹ ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

India has the second largest population in the world and is characterized by a broad diversity in climate, topography, flora, fauna, land use, and socioeconomic conditions. To help ensure food security in the future, agricultural systems will have to respond to global change drivers such as population growth, changing dietary habits, and climate change. However, alterations of how food is produced in the future may conflict with other UN Sustainable Development Goals (SDGs), such as the protection of land resources and climate change mitigation. It is crucial for decision‐makers to understand potential trade‐offs between these goals to find a balance of human needs and environmental impacts. In this paper, we analyze pathways of agricultural productivity, land use, and land‐cover changes in India until 2030 and their impacts on terrestrial biodiversity and carbon storage. The results show that in order to meet future food production demands, agricultural lands are likely to expand, and existing farmlands need to be intensified. However, both processes will result in biodiversity losses. At the same time, the projections reveal carbon stock increases due to intensification processes and decreases due to conversions of natural land into agriculture. On balance, we find that carbon stocks increase with the scenarios of future agricultural productivity as modeled here. In conclusion, we regard further agricultural intensification as a crucial element to help ensure food security and to slow down the expansion of cropland and pasture. At the same time, policies are required to implement this intensification in a way that minimizes biodiversity losses.

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.