In partnership with the Bezos Earth Fund, we are developing low-cost virtual livestock fencing that would benefit farmers and animals, improve public health in developing countries, and combat climate change.
Building on the findings of the first publication, the primary objective of EAT-Lancet 2.0 is to produce a scientific update of the 2019 EAT-Lancet by 2024. Mario and the FSGC will lead the modeling workstream.
A thematic assessment of the interlinkages among biodiversity, water, food and health in the context of climate change.
A Cornell-led project is exploring how to develop a transparent, scientifically defensible, approach for New York State agencies to adjust their food procurement bids formulaically and transparently, after taking into consideration the multiplier effects and spillovers generated by local food procurement.
We seek to more deeply understand informality in the food system by reviewing and developing methodologies for external food environment surveillance systems.
This project aims to identify the key transformative innovations that could significantly help accelerate the adaptation of food systems in low- and middle-income countries to climate change, to map and assess their potential impacts semi-quantitatively, to develop examples of how to build transition roadmaps for their implementation.
FSCI produces publications to measure, assess, and track the performance of global food systems toward 2030 and the conclusion of the Sustainable Development Goals.
Understanding the role of women and men in the food system from a multidisciplinary perspective and how this might affect research, intervention, and policies for food system transformation.
A quantitative evaluation tool for assessing the environmental impacts of livestock interventions aimed at improving both livestock productivity and the livelihoods of smallholder farmers.
Creating a framework for the constant updating of the spatially disaggregated global dataset on crop and livestock production and emissions from a 2013 study published in the Proceedings of the National Academy of Sciences.
The GBADs program is developing a systematic approach to determine the economic burden of animal diseases using a combination of established and innovative methodologies. The program will assess the economic burden in terms of net loss in animal production, animal health expenditure, and the impact on trade. The overall framework is applicable at local, national and global levels and GBADs will develop approaches to identify where the burdens occur, to whom and by causes and risk factors.
SEBI-Livestock mobilizes and improves data and evidence to help the livestock community make better investments for smallholder livestock-keepers in low and middle-income countries. We consolidate and improve hard-to-reach data and employ advanced technologies such as machine learning to acquire data. Our focus is on enhancing access to the best available data, strengthening the generation of high-quality data, and turning data into useful evidence.