Land use change emission scenarios: anticipating a forest transition process in the Brazilian Amazon.

Following an intense occupation process that was initiated in the 1960s, deforestation rates in the Brazilian Amazon have decreased significantly since 2004, stabilizing around 6000 km(2) yr(-1) in the last 5 years. A convergence of conditions contributed to this, including the creation of protected areas, the use of effective monitoring systems, and credit restriction mechanisms. Nevertheless, other threats remain, including the rapidly expanding global markets for agricultural commodities, large-scale transportation and energy infrastructure projects, and weak institutions. We propose three updated qualitative and quantitative land-use scenarios for the Brazilian Amazon, including a normative 'Sustainability' scenario in which we envision major socio-economic, institutional, and environmental achievements in the region. We developed an innovative spatially explicit modelling approach capable of representing alternative pathways of the clear-cut deforestation, secondary vegetation dynamics, and the old-growth forest degradation. We use the computational models to estimate net deforestation-driven carbon emissions for the different scenarios. The region would become a sink of carbon after 2020 in a scenario of residual deforestation (~1000 km(2) yr(-1)) and a change in the current dynamics of the secondary vegetation - in a forest transition scenario. However, our results also show that the continuation of the current situation of relatively low deforestation rates and short life cycle of the secondary vegetation would maintain the region as a source of CO2 - even if a large portion of the deforested area is covered by secondary vegetation. In relation to the old-growth forest degradation process, we estimated average gross emission corresponding to 47% of the clear-cut deforestation from 2007 to 2013 (using the DEGRAD system data), although the aggregate effects of the postdisturbance regeneration can partially offset these emissions. Both processes (secondary vegetation and forest degradation) need to be better understood as they potentially will play a decisive role in the future regional carbon balance.

New land-use change scenarios for Brazil: Refining global SSPs with a regional spatially-explicit allocation model.

The future of land use and cover change in Brazil, particularly due to deforestation and forest restoration processes, is critical for the future of global climate and biodiversity, given the richness of its five biomes. These changes in Brazil depend on the interlink between global factors due to its role as one of the main exporters of commodities globally and the national to local institutional, socioeconomic, and biophysical contexts. Aiming to develop scenarios that consider the balance between global (e.g., GDP growth, population growth, per capita consumption of agricultural products, international trade policies, and climatic conditions) and local factors (e.g., land use, agrarian structure, agricultural suitability, protected areas, distance to roads, and other infrastructure projects), a new set of land-use change scenarios for Brazil were developed that aligned with the global structure Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathway (RCPs) developed by the global change research community. The narratives of the new scenarios align with SSP1/RCP 1.9 (Sustainable development scenario), SSP2/RCP 4.5 (Middle of the road scenario), and SSP3/RCP 7.0 (Strong inequality scenario). The scenarios were developed by combining the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model to incorporate the climatic variables in water deficit. Based on detailed biophysical, socioeconomic, and institutional factors for each biome in Brazil, we have created spatially explicit scenarios until 2050, considering the following classes: forest vegetation, grassland vegetation, planted pasture, agriculture, a mosaic of small land uses, and forestry. The results aim to detail global models regionally. They could be used regionally to support decision-making and enrich the global analysis.