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Evaluation of the project "Livestock Environmental Assessment and Performance (LEAP) Partnership

Project code: GCP/GLO/369/MUL











Management response


FAO. 2022. Evaluation of the project "Livestock Environmental Assessment and Performance (LEAP) Partnership". Project Evaluation Series, 05/2022. Rome.



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    Home Country Measures that Promote Responsible Foreign Agricultural Investment 2016
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    This paper summarizes the good practices by nine selected OECD countries that seek to promote responsible foreign investment in developing country agriculture, primarily by investors in their territory or jurisdiction. The study provides examples of the increasing trend of home countries in establishing binding legal norms and other mechanisms as safeguards that are relevant for agricultural investment. It finds that States apply some specific provisions to hold private corporate actors investin g in agriculture abroad accountable, for example in regard to bribery of foreign public officials. Investment home countries are also increasingly using safeguards relevant for agricultural investment for companies that are controlled by the State or seek its support. Furthermore, Public-Private Partnerships are increasingly used in development assistance projects as a means to promote responsible agricultural investment. In these cases, the safeguards usually imply the use of negotiated and app roved instruments such as the Voluntary Guidelines on the Responsible Governance of Tenure of Land, Fisheries and Forests in the Context of National Food Security (VGGT). The Principles for Responsible Investment in Agriculture and Food Systems (CFS-RAI), endorsed in 2014 by the Committee on World Food Security (CFS), will possibly become a major guidance instrument, given recent declarations by the G7 and G20.
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    Version 1
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    The aim of the methodology developed in these guidelines is to introduce a harmonized international approach assessing nutrient flows and impact assessment for eutrophication and acidification for livestock supply chains taking the specificity of the various production systems involved into consideration. The methodology strives to increase understanding of nutrient use efficiency and associated environmental impacts and to facilitate the improvement of livestock systems’ environmental performance. The guidelines are a product of the Livestock Environmental Assessment and Performance (LEAP) Partnership, a multi-stakeholder initiative whose goal is to improve the environmental sustainability of livestock sector through better metrics and data. Nutrient use in livestock production systems increased over the last decades due to the increased demand for livestock production. This demand is mainly driven by the increase in the population growth, population income, and urbanization. Consequently, in livestock supply chains, nutrient losses into the environment have contributed to environmental burdens such as climate change, air and water pollution, degradation of soil quality, loss of biodiversity and human health issues. Therefore, there is strong interest in measuring nutrient flows to improve the environmental performance of the livestock sector. The objectives of these guidelines are: • To develop a harmonized, science-based approach resting on a consensus among the sector’s stakeholders; • To recommend a scientific, but at the same time practical, an approach that builds on existing or developing methodologies; • To promote a harmonised approach to assess nutrient flows and impact assessment, relevant for global livestock supply chains; • To identify the principal areas where ambiguity or differing views exist concerning the methodological framework. During the development process, these guidelines were submitted for technical review and public review. The purpose is to strengthen the advice provided and ensure it meets the needs of those seeking to improve nutrient use efficiency and environmental performance through sound assessment practice. This document is not intended to remain static. It will be updated and improved as the sector evolves and more stakeholders become involved in the LEAP, and as new methodological frameworks and data become available. The guidelines developed by the LEAP Partnership gain strength because they represent a multi-actor coordinated cross-sectoral and international effort to harmonize assessment approaches. Ideally, the harmonization leads to greater understanding, transparent application and communication of metrics, and, not least, real and measurable improvement in environmental performance.
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    Measuring and modelling soil carbon stocks and stock changes in livestock production systems – A scoping analysis for the LEAP work stream on soil carbon stock changes 2019
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    In order to build consensus on methods to measure and model soil carbon stocks and stock changes, the Steering Committee of the Livestock Environmental Assessment and Performance (LEAP) Partnership mandated a task force to develop this scoping analysis and pave the way towards the formation of the LEAP Tecnical Advisory Group on soil carbon stock changes. Soil carbon sequestration and storage in grasslands offers a significant potential to compensate for GHG emissions from livestock, but the lack of consensus on the appropriate methodologies to account for soil carbon stock changes hinders robust and standardized assessments. In this report, we reviewed several published soil organic carbon (SOC) models, and evaluated their aptitude to combine them with life cycle assessments (LCAs). Among contentious issues, the most relevant are: a) the lack of universal models, b) the uneven data availability, comparability and quality between countries and regions, and c) the difficulty to match measurable SOC fractions with those determined by the models. Taking this into account, a tiered approach is proposed, according to the availability of original data to run the models. The use of IPCC carbon (C) accounting system appears to be the simplest approach suitable to countries with scarcity of original C data. Conversely, more complex models such as Century (Parton 1987, 1988) or Roth C (Smith 1998) are likely to perform better and give less uncertainty when original input data are easily available.

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