Carbon dioxide removal (CDR) will become an important instrument of future climate change mitigation efforts, especially if climate action is further delayed. Several CDR options and technologies exist and have been assessed with respect to their potential for net carbon dioxide removal from the atmosphere and their socioeconomic suitability. Agroforestry has been identified as one of the most promising land-based CDR options, but it has not received as much attention as other more prominent CDR opportunities. This is surprising, because agroforestry promises decisive net long-term accumulation of carbon in soil organic matter and biomass. More importantly, and in contrast to many other options, agroforestry may face low implementation barriers, since it can deliver a range of co-benefits in terms of agricultural productivity, food security, biodiversity conservation, protection against soil erosion, pest-control etc. While a few biophysical agroforestry models have been proposed, credible representations of agroforestry remain absent from all major land-use models, precluding the consideration of agricultural systems with trees from large-scale scenario analyses. This deficiency is particularly striking when it comes to economic assessments, which have so far fallen short of accounting for the multitude or provisioning, regulating and cultural ecosystem services provided by agroforestry systems. This lack of appropriate models precludes comprehensive assessments of the climatic and societal benefits of large-scale agroforestry implementation, as well as hindering simulations on the effects of particular policy actions taken to promote such systems. This project intends to develop and use a suite of models to assess (a) the suitability of agroforestry systems for carbon dioxide removal, (b) the productivity of agroforestry systems, as well as trade-offs and synergies with other sustainability goals, (c) the economic performance of agroforestry systems, and (d) the suitability of agroforestry systems in comparison to other tCDR (terrestrial Carbon Dioxide Removal) technologies. In close collaboration with farmers, policy-makers and other stakeholders, this project will explore in detail the feasibility of agroforestry adoption for land managers, based on a comprehensive appraisal of costs, benefits, risks, advantages and drawbacks, and covering biophysical, economic and social dimensions. Applying decision analysis procedures to a set of sample systems, the project will identify critical barriers to adoption and key uncertainties and propose ways of overcoming such impediments. An analysis of policy scenarios will assess, how these obstacles can be overcome with incentives and regulation. This project is designed to smoothly interact with the overarching “Synthese- and Begleitvorhaben” CDRSynTra to contribute to a harmonized assessment scheme and metrics and by providing improved knowledge for agroforestry as CDR to the synthesis project. ABCDR will also collaborate with other projects within this call to harmonize on scenario assumptions and consistency in the analyses and comparative assessments.
The ABCDR project aims to assess the biophysical and socio-economic potential of agroforestry to sequester atmospheric carbon dioxide. A comprehensive model-based analysis framework will be developed and made available for further research and to other stakeholders. The project aims to facilitate decision making by (national and international) policy-makers and by farmers on the adoption of agroforestry practices. To this end, ABCDR will identify knowledge gaps and uncertainties that hamper decision making and supply information to fill these gaps.
PIKs engagement will focus on simulation-model based assessments of agroforestry with respect to its biophyiscal consequences and socio-economic requirements and consequences. The biophysical consequences will be simulated using the global gridded vegetation, crop and hydrology model LPJmL. It includes the carbon dioxide removal potentials around the world, the productivity with respect to crop and forest products, as well as potential environmental impacts. The socio-economic analysis will be carried out using the global land and food system modeling framework MAgPIE. It will use the biophysical estimates by LPJmL and will look at direct and indirect effect of an up-scaled agroforestry adoption for a suite of environmental and social target indicators.
