The Carbiocial project, in close cooperation with its Brazilian partner project Carbioma, is investigating viable carbon-optimized land management strategies maintaining ecosystem services under changing climate conditions in the Southern Amazon. These are utterly needed to meet the goals set by Brazilian National plans (e.g. ABC-program) and international treaties such as REDD and the Kyoto protocol.
The joint main goals of the research cluster therefore are 1) to perform region-specific analyses in order to improve and apply interdisciplinary sets of models of land use impacts on carbon-stocks, water and GHG balances, 2.) to develop and optimize land management strategies that minimize carbon losses and GHG emission and maximize carbon sequestration, 3.) to assess the trade-offs between land management options and socio-economic impacts in terms of GHG reduction, profitability and ecological sustainability, and last but not least 4.) to support the Brazilian partners to implement the optimized techniques in practice, considering the soy bean value chain and overall carbon balance.
This project therefore aims at providing interdisciplinary solutions for these problems. Three regions along the land use frontier of Southern Amazonia were selected: Southern Pará: most active deforestation; Northern Mato Grosso: young soy bean production; Central Mato Grosso: established cotton and soy bean cultivation (>20 years) and adapted mechanised cropping (no tillage). Analyses focus on soil carbon (C) turnover, climate, ecosystem functions and socio-economic processes.
Simulation models will be combined as software packages to support the decision-taking process based on field and acquired data, including a step-by-step up-scaling from local to landscape and regional scale. All research and implementation activities include direct involvement of the stakeholders. Furthermore, joint field experiments for improving C storage and ecosystem functions will be performed in tight cooperation with an NGO founded by the farmers’ organization of Mato Grosso.
A combined computer-based decision support platform will be developed, including simulation models to run region-specific impacts of different scenarios of land use options and climate change on GHG and C cycling. This will be a highly valuable tool for regional planning authorities. From the scenario calculations simplified versions (e.g. emission factors) will be made available as an easy-to-use decision support system for individual stakeholders. Results will be communicated directly to stakeholders, by human capacity building, and by promoting financially feasible, C-optimized land use techniques throughout tropical areas with similar conditions.