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Sustainable futures for the Costa Rica dairy sector: optimising environmental and economic outcomes
General
Expansion of poor quality and low productivity pasture livestock production in Central and Southern America is a major cause of deforestation, and leads to significant environmental pressures including loss of natural capital, air and water pollution, and greenhouse gas emissions. Trade liberalization is causing major structural changes to livestock sectors in Central American countries, with profound implications for the livelihoods of farmers and rural communities, land use policy objectives, climate change, air and water quality, and for other sectors such as tourism that are reliant on natural resources. In this multi-actor, proof of concept project we will integrate measurement and mined data to model a range of scenarios of potential transitions for the dairy sector in Costa Rica, in order to propose promising pathways of sustainable intensification for the dairy and wider land use sectors that balance socio-economic and environmental outcomes. In this proposal we bring together an interdisciplinary team of researchers with proven expertise of delivering evidence that supports development of practical and cost-effective strategies for livestock production. The project consortium is complemented by a key industrial collaborator in Costa Rica that dominates the dairy sector, accounting for >80% of the dairy processing, and a stakeholder group comprising policy makers for agriculture and environment, other agriculture industry sector bodies, and farmers. Our joint expertise includes soil science; measurements and mitigation of diffuse pollutants to air and water; carbon footprinting and life cycle assessment; agroforestry and livestock production; socio-economics; agricultural economics and extension, and policy formulation. This unique blend of skills is essential to deliver our objectives and to meet GCRF and ODA goals, and to build the interdisciplinary capacity needed to deliver holistic solutions to promote sustainable land use for future livestock production in Central American LMIC countries. The main aim of this project is to develop sustainable futures for food production in the tropics, using the Costa Rican dairy sector as a case study. The approach we develop will be an exemplar that can be rolled out to other agricultural sectors, to other Central American countries and beyond. To achieve this, the project team will collate existing data of trends in livestock numbers, sectoral greenhouse gas emissions, and other information on energy, water, tree-pasture-animal relations, genetics, and nutrient inputs and outputs, and determine their robustness and suitability for the models the project will develop. We will adopt the best protocols for measuring greenhouse gas and ammonia emissions to air, and nitrate and phosphorus losses to water, on the CATIE dairy farm, and then apply these protocols to three commercial dairy farms of various scales, along an intensification gradient. To build the legacy of the project, we will train Costa Rican and other Central American researchers in a range of diffuse pollution measurement methodologies, as well as in carbon foot-printing, LCA and farm-scale modelling. Mined and measured data will be used to calculate environmental and economic balances for the CATIE and three commercial dairy farming systems (and their products), and model sensitivity to specific management practices and technologies that would be representative of trends in intensification, as well as explore more sustainable intensification strategies. The measured and modelled data will then be used to scale up and assess the potential trade-offs and synergies for specific dairy development pathways between environmental and productive/economic goals at the national and global level. These findings will be used to advise key actors (Ministries of Agriculture and Environment & Energy, National Milk Chamber - CNPL), via a final Workshop in Costa Rica at the end of the project.
Objectives
The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Towards a Fire Early Warning System for Indonesia (ToFEWSI)
General
The severe El Niño episode of 2015 led to a major and damaging increase in Indonesian peatland fire, highlighting an urgent need to develop operational systems to forecast potentially severe fire events in order to mitigate the impacts of fire and haze. 10 ASEAN states have formally agreed to control peatland and forest fires and urgently need an early fire warning system: a need that we address in this proposal. An operational 'early warning' system for forecasting dangerous burning conditions is within reach using state-of-the-art modelling tools, such as the ECMWF's System 4 seasonal forecast model, but is currently hampered by insufficient knowledge about the influence of fluctuations in peat moisture on fire, particularly during periods of extreme drought, highlighted by the 1997-98 and 2015 El Niño episodes- the strongest and second strongest on record. The majority of present-day fires in Indonesia result from deliberate burning for land clearance, and this human factor means that burning can be influenced by policy and altered land management practice. The translation of scientific research into evidence-based policy and the official regulation and restriction of burning do not work well in Indonesia and new approaches are needed. We plan to both develop a new scientific forecasting tool for fire danger and to influence policy and fire regulations: a novel combination of urgent science and policy research. This project will develop a suite of climate-, hydrological- and agent-based modelling to predict the incidence of peat fires based on computations and observations for the period 1997 to 2014, and will use the 2015 El Niño event to benchmark the forecast tools. Our working hypothesis is that the increased fire risk associated with dry peat does not trigger appropriate changes in the management practices adopted by local landowners in their use of fire, if there are no incentives provided by policy. Our anticipated outputs are: * An operational model of peatland fire occurrence, based on a tropical peatland hydrology model, an agent-based model, and seasonal climate data derived from state-of-the-art reanalysis data and seasonal forecasts, and Earth Observation Data. * An operational early fire warning system for peatlands based on seasonal climate forecasts. * A more complete understanding of how climate, socio-economic and geographic factors interact to drive peatland fires. * Evidence-based policy tools for reducing the number of fires and area burned each year in Riau province, Sumatra. * Evidence-based proposals towards new Indonesian fire reduction management strategies and policy input. The forecasting system will be web-based and accessible, and will predict the risk of peatland fire occurrence up to three months ahead, enabling sufficient time to spread awareness of the impending risk through the community, and to mobilise fire-fighting resources and other fire prevention measures if required. Consideration of non-climate drivers of peatland fire occurrence is critically important because this will help us capture the spatio-temporal patterns in fire in different regions displaying similar climate regimes. Non-climate driven factors also present the most tractable means to develop mitigation actions. We will combine the results of our work on climate, socio-economic and geographic factors to generate a multi-factorial model for peatland fire occurrence. The model system will be developed in close collaboration with Indonesian stakeholders following the operational needs of agencies, municipalities and companies in the area. Key stakeholders include the Indonesian peatland restoration agency, Indonesia ministry, ASEAN Regional Haze Support Unit, local communities, forestry companies, local and international researchers. The model system will be robust and simple enough for in-house daily use by our Indonesian stakeholders, who will take over the system, and run and maintain it on their own servers.
Objectives
The Newton Fund builds research and innovation partnerships with developing countries across the world to promote the economic development and social welfare of the partner countries.
Asserting the land rights of the marg. commu. i.e. tribal, Dalit, nomad.etc.
General
Sicherung + Institut. v. Landrechten marginal. Gemeinschaften, Fortführung
Objectives
Sicherung + Institut. v. Landrechten marginal. Gemeinschaften, Fortführung