AGRICULTURE GLOBAL PRACTICE CLIMATE-SMART AGRICULTURE INDICATORS WORLD BANK GROUP REPORT NUMBER 105162-GLB JUNE 2016 AGRICULTURE GLOBAL PRACTICE CLIMATE-SMART AGRICULTURE INDICATORS © 2016 World Bank Group 1818 H Street NW Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org Email: feedback@worldbank.org June 2016 This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. 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Credit: Danilo Pinzon/World Bank Top Right: Farmers sort tomatoes. Ethiopia. Credit: Stephan Bachenheimer/World Bank Bottom: Women at work in Sri Lanka. Credit: Lakshman Nadaraja/World Bank CONTENTS Forewordvii Acknowledgmentsix Acronyms and Abbreviations xi Executive Summary xiii Chapter One: Background 1 Climate Change and Agriculture 1 Indicators for Climate-Smart Agriculture 3 Objectives and Scope of the Report 3 Chapter Two: Impact Pathway and Theory of Change 7 Agricultural Sector Impacts 8 Outcomes—Behavioral Change 9 Chapter Three: Indicator Selection and Application 13 CSA Policy Index (CSA-Pol Index) 14 CSA Technology Index (CSA-Tech Index) 20 CSA Results Index (CSA-Res Index) 23 Chapter Four: Key Findings for the CSA Policy Index 27 Top and Bottom Performers for the CSA Policy Index 29 Chapter Five: Testing of Projects with the CSA Technology Index and the CSA Results Index 37 Testing of Projects Using the CSA-Tech Index 37 Testing of Projects Using the CSA-Res Index 49 Chapter Six: Conclusion and the Way Forward 57 References 59 Appendix A: Review of Existing Indices Relating to Agriculture and Climate Change 63 Appendix B: Technical Notes for the CSA Policy Index 67 Appendix C: Technical Notes for the CSA Technology Index 75 Appendix D: Technical Notes for the CSA Results Index 81 FIGURES Figure ES.1: Relationship between CSA-Pol Index and Undernourishment (n = 50) xv Figure ES.2: Relationship between CSA-Pol Index and Cereal Yield (n = 56) xvi Figure ES.3: Relationship between CSA-Pol Index and Cereal Yield Variance (n = 56) xvi Figure ES.4: Relationship between CSA-Pol Index and GHG Emissions Intensity of Milk (n = 84) xvi Figure ES.5: Relationship between CSA-Pol Index and GHG Intensity of Chicken (n = 84) xvi Figure ES.6: Relationship between CSA-Pol Index and GHG Intensity of Paddy Rice (n = 74) xvii Climate-Smart Agriculture Indicators iii Figure 1.1: Global Land Use Change and Agriculture Greenhouse Gas Emissions 2 Figure 1.2: Climate-Related Global Grain Shocks 2 Figure 2.1: Impact Pathway for CSA Interventions and Relation to CSA Indicators 8 Figure 4.1: Relationship between CSA-Pol Index and Undernourishment (n = 50) 28 Figure 4.2: Relationship between CSA-Pol Index and Cereal Yield (n = 56) 28 Figure 4.3: Relationship between CSA-Pol Index and Cereal Yield Variance (n = 56) 28 Figure 4.4: Relationship between CSA-Pol Index and GHG Emissions Intensity of Milk (n = 84) 28 Figure 4.5: Relationship between CSA-Pol Index and GHG Intensity of Chicken (n = 84) 28 Figure 4.6: Relationship between CSA-Pol Index and GHG Intensity of Paddy Rice (n = 74) 28 Figure 4.7: CSA-Pol Index Score for a Sample of Countries: Top 15 Scores; Middle 15 Scores; Bottom 15 Scores 29 Figure 4.8:  Average Aggregate Scores for Countries Grouped by Income across Four Categories of Indicator Aggregation 29 Figure 4.9:  Average Aggregate Scores for Countries Grouped by Region across Four Categories of Indicator Aggregation 30 Figure 4.10: CSA-Pol Scores for Countries in Latin America and the Caribbean  31 Figure 4.11: CSA-Pol Index Scores—Chile 31 Figure 4.12: Specific CSA-Pol Index Scores—Mexico 31 Figure 4.13: Specific CSA-Pol Scores—Brazil 31 Figure 4.14: Specific CSA-Pol Index Scores—Haiti 32 Figure 4.15: Specific CSA-Pol Index Scores—Venezuela 32 Figure 4.16: Specific CSA-Pol Index Scores—St. Lucia 32 Figure 4.17: CSA-Pol Index for Countries in Sub-Saharan Africa  33 Figure 4.18: Specific CSA-Pol Index Scores—South Africa 33 Figure 4.19: Specific CSA-Pol Index Scores—Tanzania 33 Figure 4.20: Specific CSA-Pol Index Scores—Rwanda 33 Figure 4.21: Specific CSA-Pol Index Scores—Sudan 34 Figure 4.22: Specific CSA-Pol Index Scores—Central African Republic 34 Figure 4.23: Specific CSA-Pol Index Scores—Equatorial Guinea 35 Figure 4.24:  Average Aggregate Scores for Countries Grouped by Region across Four Indicators: Economic Readiness, Governance Readiness, Social Readiness, and Adaptive Capacity 35 Figure 5.1: Location of Selected Projects for Testing 38 Figure 5.2: Armenia’s CSA-Tech P, R, M Scores 39 Figure 5.3: Burundi’s CSA-Tech P, R, M Scores 42 Figure 5.4: Bhutan’s CSA-Tech P, R, M Scores 43 Figure 5.5: Brazil’s CSA-Tech P, R, M Scores 45 Figure 5.6: China’s CSA-Tech P, R, M score 47 Figure 5.7: Armenia’s CSA-Res P, R, M Scores 49 iv Agriculture Global Practice Discussion Paper Figure 5.8: Bhutan’s CSA-Res P, R, M Scores 50 Figure 5.9: Brazil’s CSA-Res P, R, M Scores 51 Figure 5.10: Burundi’s CSA-Res P, R, M Scores 53 Figure 5.11: China’s CSA-Res P, R, M Score 54 TABLES Table 1.1: Overview of Existing Indicators 4 Table 1.2: The Three CSA Indices 5 Table 3.1: Structure of the CSA-Pol Index 15 Table 3.2: Structure of the CSA-Tech Index 21 Table 3.3: Structure of the CSA-Res Index 24 Table 3.4: Scoring Table for the CSA-Res Index 25 Table 5.1:  Results from the Armenia Second Community Agriculture Resource Management Competitiveness Project 40 Table 5.2: Results from the Burundi Agricultural Rehabilitation and Sustainable Land Management Practice 41 Table 5.3: Results from the Bhutan Land Management Practice 44 Table 5.4: Results from Brazil Caatinga Conservation and Management—Mata Branca 46 Table 5.5: Results from the China Integrated Modern Agriculture Development Project 48 Table 5.6: Selected Indicators for Armenia—Natural Resources Management and Poverty Reduction Project 50 Table 5.7: Selected Indicators for Bhutan—Sustainable Land Management Project 51 Table 5.8:  Selected Indicators for Brazil—Rio De Janeiro Sustainable Integrated Ecosystem Management in Production Landscapes of the North-Northwestern Fluminense 52 Table 5.9: Selected Indicators for Burundi—Agriculture Rehabilitation and Sustainable Land Management 53 Table 5.10: Selected Indicators for China—Irrigated Agriculture Intensification Project III 55 Climate-Smart Agriculture Indicators v FOREWORD There is by now substantial consensus within the development community over the need for a more climate smart agriculture, which consists of three defining princi- ples: enhancing agriculture’s resilience to climate change, reducing agricultural green- house gas emissions, and sustainably increasing production. With 795 million people still not getting their minimum dietary requirements, there is little scope for trade-offs between increasing production and improving agriculture’s environmental impacts. Making climate smart agriculture operational will rely on our ability to measure pro- duction, resilience, and emissions in a way that informs decision makers about the policies, technologies, and practices that most effectively promotes each. In addition to the direct results of an improved activity or practice, longer term outcomes can lead to fundamental changes in the way that producers, consumers, investors, and others behave—and what they base their production, consumption, and investment decisions on. The indicators described in this document were developed for this purpose. Applying the indicators to examine the agricultural performance of different countries reveals a number of correlates relating to institutions, legal frameworks, and the rela- tionships between agriculture and other sectors like water and energy. Applying them to projects affirms the important advantages of approaches that employ appropriate technologies and that incorporate broader, landscape-based perspectives that recog- nize and allow for competing demands for land and water resources. The type of highly practical empirical evidence that will be amassed by monitoring these indicators is going to be pivotal in mitigating agriculture’s large ecological foot- print, in capitalizing on its potential to provide environmental services, and in guid- ing the forms of intensification that lead to substantially higher and more sustainable production. Juergen Voegele Senior Director Agriculture Global Practice The World Bank Climate-Smart Agriculture Indicators vii ACKNOWLEDGMENTS This report drew from contributions from a range of experts working on agriculture richness food security and climate change. We thank everyone who contributed to its ­ and multidisciplinary outlook. The work was led by Ademola Braimoh, who devel- oped the concepts and provided overall guidance to the team. The preparation of Technology indicators was led by Ijeoma Emenanjo, Policy indicators by Maurice the ­ Rawlins, and the Results indicators by Christine Heumesser. Yuxuan Zhao developed the computer programs for all the indicators, whereas Maria de Rijk, Xiaoyue Hou, Elizabeth Minchew, Wisambi Loundu, and Julia Isabel Espinal provided invaluable research support. The web interface technology for the indicators was coordinated by Xenia Zia Morales and Varuna Somaweera, with invaluable support from Ritesh Sanan and Christopher Nammour. We acknowledge the inputs of all the experts at the three consultative meetings that helped select and prioritize the indicators through a transparent and robust meth- odology. In particular, we thank Eija Pehu, Willem Jansen, Holger Kray, Mona Sur, Edward Bresnyan, Vladimir Stenek, Junu Shrestha, Ravij Nijbrook, Celia Harvey, and Norbert Henninger, Paul R. Koch, Kerri Platais, Michael A. Cullen, and Michelle Jennings for their efforts in reviewing the framework, indicators selection, and con- struction of indices. This report benefited from the comments and advice of the following peer review- ers: Willem Jansen, Marc Sadler, Rob Townsend, George Ledec, Svetlana Edmeades, Tobias Baedeker, Bruce Campbell, Christine Negra, and Ephraim Nkonya. The team also thanks Vikas Choudhary and Åsa Giertz for their suggestions in refining some of the indicators. We thank Gunnar Larson for editing the report. Many others ­provided input and support including Juergen Voegele, Ethel Sennhauser, Mark ­ Cackler, Preeti  Ahuja, Jim Cantrell, Leah Germer, Sarian Akibo-Betts, Beaulah Noble, and Srilatha Shankar. Climate-Smart Agriculture Indicators ix ACRONYMS AND ABBREVIATIONS AFOLU Agriculture, Forestry and Other Land Use LAC Latin America and the Caribbean ARI Agricultural research intensity M Mitigation ASTI Agricultural Science and Technology M&E Monitoring and evaluation Indicators MDG Millennium Development Goal CAIT Climate Analysis Indicators Tool MENA Middle East and North Africa CC Climate change MMT Million metric tons CCAFS CGIAR Research Program on Climate NAMA Nationally Appropriate Mitigation Actions Change, Agriculture and Food Security NAPA National Adaptation Programs for Action CO2-e Carbon dioxide equivalent NCCSC National Climate Change Steering Committee CSA Climate-smart agriculture NCCTC National Climate Change Technical Committee CSA-Pol CSA-Policy Index ND-GAIN University of Notre Dame Global Adaptation CSA-Res CSA-Results Index Index CSA-Tech CSA-Technology Index NRM Natural resource management CV Climate variability P Productivity DRR Disaster risk reduction PDO Project Development Objective EAP East Asia and Pacific R Resilience ECA Europe and Central Asia RAI Rural Access Index FAO Food and Agriculture Organization R&D Research and development GDP Gross domestic product RAI Rural Access Index GEF Global Environment Fund SA South Asia GEO Global Environment Objective SLM Sustainable land management GHG Greenhouse gas SMART Specific, Measurable, Achievable and ha Hectare Attributable, Relevant and Time Bound HANCI Hunger and Nutrition Commitment Index SSA Sub-Saharan Africa ICT Information communication technology SSN Social safety net IEM Integrated ecosystem management t Ton IFC International Finance Corporation (of the 3H Basin Huang-Huai-Hai Basin World Bank) UNFCCC United Nations Framework Convention on IFPRI International Food Policy Research Institute Climate Change IPCC International Panel on Climate Change WRI World Resources Institute ISFM Integrated soil fertility management WTO World Trade Organization kg Kilogram Climate-Smart Agriculture Indicators xi EXECUTIVE SUMMARY Agriculture accounts for 40 percent of the land area and 70 percent of the freshwater resources that humans use, and 24 percent of human- induced greenhouse gas emissions. In addition to its role as a contributor to cli- mate change, agriculture, with its direct reliance on natural resources, is also the sector of the economy that is the most vulnerable to the impacts of climate change. And the pressures that population growth and urbanization are putting on the sector are grow- ing at the same time that many of the resources that agricultural production depends on are diminishing throughout much of the developing world. The human population is projected to increase to 9.5 billion people by 2050, and agricultural demand for water may increase by 30 percent by 2030. The proportion of the human population that resides in water-stressed or water-scarce areas is likely to increase from about 18 percent today to 44 percent by 2050. The increased risks associated with higher frequencies of drought, flooding, and heat stress will have significant impacts on agri- cultural production systems, resulting in lower yields, rising food prices, and increased greenhouse gas emissions. For every degree Celsius of global warming, yields are at risk of declining by 5 percent, leading to further insecurity for the 805 million already food insecure. Agriculture is also the most vital sector of the economy for food security, and employs some 2.6 billion people worldwide. More than any other sector in developing countries, growth in the agricultural sector is associated with poverty reduction. The growth in gross domestic product (GDP) that takes place in agriculture is at least twice as effective in reducing poverty as the growth that takes place in other sectors, and its significance to poverty rates increases roughly in proportion to the size of its role in the larger economy. In the largely agriculture-based economies of the developing world, where poverty rates are the highest and the largest ratios of poor people live in rural areas, its significance is the greatest. Climate-smart agriculture (CSA) in its broadest usage refers to a global agenda with three fundamental elements. The first element is to increase agri- cultural production and incomes to meet increasing demand while ensuring the sustain- ability of the soil and water resources used. The second is to make production systems Climate-Smart Agriculture Indicators xiii more resilient and better able to withstand weather vari- may concern United Nations agencies such as the Food ability and climate shocks, a set of objectives referred to and Agriculture Organization (FAO) and the World Bank, as adaptation to the effects of climate change. The third regional forums such as the African and Asian Develop- element is to reduce the greenhouse gases emitted by agri- ment banks, national and local governments, private culture and to promote the sequestration of greenhouse investors, universities and research institutions, and civil gases in agricultural soils and plants, a set of objectives society and nongovernmental organizations. They may referred to as mitigation. It should be noted that seques- cover baseline snapshots of initial conditions or trends tration of greenhouse gases is not the only mitigation and developments over the immediate-, short-, medium-, method and the quantity of GHG sequestered is not or long-term period. Whereas these indicators do meas- limitless. Although carbon sequestration can be large to ure some dimensions of CSA, most are not sufficient to begin with, the sinks decline as a maximum equilibrium guide policy formulation, prioritize production systems, value is reached (World Bank 2012). Empirical evidence or gauge how successful the adoption of a CSA interven- suggests that these sinks saturate at between 10 and 100 tion has been. The World Bank CSA indicators address years, depending on practices applied, soil type, and cli- these shortcomings and provide policy makers and devel- mate zone (IPCC 2006). Because sinks are also reversible, opment practitioners with a framework for implementing sequestration practices must be maintained even when the the necessary policy, technical, and monitoring and evalu- sinks are saturated. The benefit of carbon sequestration ation (M&E) framework to make CSA fully operational. is that it can provide “breathing space” to make room for other technologies that reduce emissions to come on the The CSA Indices are based on a range of CSA scene. indicators in the areas of policy, technology, and results. The development of the CSA indicators was Because the CSA perspective considers sustainable food informed by an encompassing CSA impact pathway that production, adaptation, and mitigation simultaneously, traces how project outputs can result in behavioral change those interventions that are likely to yield benefits in all (project outcomes). The CSA indicators aim to capture three are often referred to as “triple wins.” CSA tends to direct project outputs and behavioral changes from a assign a high premium to interventions and activities that range of stakeholders such as producers, policy makers, achieve synergies between more than one set of objectives. and civil society. Behavior change is seen as a determin- It also recognizes trade-offs when one set of objectives is ing factor because only when a key group of stakehold- prioritized at the relative expense of another. The level of ers has changed their behavior can the impacts achieved analysis that is employed often extends to the larger land- through a CSA intervention be sustained into the future. scape or watershed in which the intervention is planned. The methodology for the selection and development of In addition to CSA-related interventions themselves, how- the indicators encompassed an extensive literature review, ever, this integrated perspective is intended to inform the a review of the World Bank’s Core Sector Indicators, and formulation of policies, the development of technologies, a number of expert consultations. These allowed for the and the planning and design of investments with a more development of a comprehensive set of indicators that thorough awareness of the wider impacts that the policy, can potentially provide the empirical basis for identifying technology, or investment is likely to have. viable climate-smart options, select contextually relevant technologies and practices, monitor results, and assess Achieving climate-smart agricultural outcomes policies and the necessary enabling activities for CSA. will require transformations at different scales, governance levels, and time horizons. A range of indicators is currently in place to measure agricultural STRUCTURE OF CSA performance, natural resources management, climate INDICATORS change, and a variety of variables relating to food security There are three CSA indices: the CSA Policy and nutrition. These are used to reflect facts and trends Index (CSA-Pol Index), the CSA Technology Index at the global, regional, national, and local scales. They (CSA-Tech Index), and the CSA Results Index xiv Agriculture Global Practice Discussion Paper (CSA-Res Index). The CSA-Pol Index is established whether the indicators measure direct output of a CSA on the national level and measures countries’ institutional project intervention, the CSA enabling environment, or readiness to support CSA interventions. In contrast, the the medium- to long-term outcomes of a CSA interven- CSA-Tech and CSA-Res Indices are applied on the proj- tion. The eight topics include beneficiaries, land use/ ect level. The CSA-Tech Index serves as an ex ante mea- cover, livestock, enabling environment, natural resources, sure of the ability of CSA interventions to reach the CSA emission, yield, and benefits and welfare. In addition, the triple-win goals. The CSA-Res Index can be applied to indicators are assigned to the CSA triple-win areas P, R, measure a project’s success to reach its goals in the CSA and M. The CSA-Res Index can be applied to measure triple-win areas. the project’s performance after project completion, as well as during project implementation. The CSA-Res The CSA Policy Index comprises three themes, 14 Index gives project teams the flexibility to customize the indicators, and 31 subindicators. The first theme, index and adjust it to the context specificity of their CSA Readiness Mechanisms, refers to the capacity of countries intervention. to plan and deliver adaptation, mitigation, economic readiness, governance readiness, and social readiness KEY FINDINGS OF CSA programs in ways that are catalytic and fully integrated with national agricultural development priorities. The INDICES’ TEST APPLICATION second theme, Services and Infrastructure, reflects the ability 1. CSA POLICY INDEX COUNTRY to leverage agricultural investments through the provision ASSESSMENTS of services and enabling environment such as extension, This report highlights the importance of adopt- research and development, roads, social safety nets, GHG ing CSA policies to address food insecurity under inventory and risk management systems, and adaptive changing climatic conditions. A 1 percent increase capacity. The third theme, Coordination Mechanisms, assesses in the CSA-Pol Index is predicted to lead to a 0.4 per- collaboration for disaster risk management, and coordi- cent decline in the proportion of undernourished popula- nation among sectors involved in CSA. The CSA Policy tion (figure ES.1). Cereal yields increase 47 kilograms per indicators enable policy makers and other users to gauge hectare (kg/ha) for every 1 percent increase in the CSA- how a country’s enabling environment for CSA is chang- Pol Index (figure ES.2). A 1 percent increase in CSA-Pol ing over time. They are also useful in identifying gaps in Index is predicted to lead to a 0.08 decrease in coefficient the implementation of CSA activities and in developing of variance of cereal yield (figure ES.3). benchmarks for reform. The CSA Technology and Practices Index com- prises 27 indicators clustered into three main FIGURE ES.1.  RELATIONSHIP BETWEEN themes: Productivity (P), Resilience (R), and Mit- CSA-POL INDEX AND igation (M). Ex ante application of the index reveals UNDERNOURISHMENT (n = 50) how project interventions can lead to productivity gains Prevalence of undernourishment (%) 60 and environmental benefits. It is particularly useful in 50 identifying the most appropriate technologies for a CSA project during its planning and design stages. 40 30 The CSA Results Index comprises 22 indicators, 20 clustered in three categories and eight topics, y = –0.4x + 44 intended to help project leaders measure an agri- 10 R2 = 0.27 cultural project’s performance toward achiev- 0 30 40 50 60 70 80 90 ing the CSA triple wins individually and jointly. Aggregated policy index (%) The three categories have been identified according to Climate-Smart Agriculture Indicators xv FIGURE ES.2.  RELATIONSHIP BETWEEN FIGURE ES.4.  RELATIONSHIP BETWEEN CSA-POL INDEX AND CEREAL CSA-POL INDEX AND GHG YIELD (n = 56) EMISSIONS INTENSITY OF 8,000 MILK (n = 84) 7,000 y = 47.0x – 289 35 Cereal yield kg/ha 6,000 2 R = 0.22 30 5,000 Kg CO2eq/Kg Milk 4,000 25 y = –0.11x + 10.9 3,000 R2 = 0.10 20 2,000 1,000 15 0 10 30 40 50 60 70 80 90 Aggregated policy index (%) 5 Note: Cereal yield refers to the average yields (2010 to 2013) for wheat, rice, 0 maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. 30 40 50 60 70 80 90 Aggregated policy index (%) FIGURE ES.3.  RELATIONSHIP BETWEEN CSA-POL INDEX AND CEREAL YIELD VARIANCE (n = 56) FIGURE ES.5.  RELATIONSHIP BETWEEN 25 CSA-POL INDEX AND GHG 20 INTENSITY OF CHICKEN Coefficient of variance y = –0.08x + 14.3 R2 = 0.06 (n = 84) 15 50 45 10 40 Kg CO2eq/Kg Chicken 35 y = –0.11x + 10.2 5 30 R2 = 0.08 0 25 30 40 50 60 70 80 90 20 Aggregated policy index (%) 15 Note: Cereal yield variance refers to the coefficient of variance of yields from 2010 to 2013 expressed in percentage. 10 5 0 This report also highlights the importance of 30 40 50 60 70 80 90 Aggregated policy index (%) adopting CSA policies to reducing GHG inten- sity in various agricultural products. A 1 percent increase in the CSA-Pol Index is predicted to decrease GHG intensity of milk by 0.11 kilogram of carbon diox- Index ranging from 31 percent for Sudan to 87 percent ide equivalent per kilogram (kg CO2-e/kg) (figure ES.4). for Chile. Latin American and Caribbean (LAC) countries A 1 percent increase in the CSA-Pol Index is also pre- such as Chile, Mexico, and Brazil outperformed other dicted to decrease GHG intensity of chicken by 0.11 kg country groups on the CSA Policy Index scores. CSA CO2-e/kg (figure ES.5). GHG intensity of paddy rice will Policy Index’s services and infrastructure support thematic decrease 0.02 kg CO2-e/kg (figure ES.6). indicators tend to increase with higher levels of income. This suggests that national investments in services such as Country assessments (n = 88) revealed countries crop insurance and market information systems may yield to be at varying stages of adoption of policies and greater productivity and environmental wins than invest- mechanisms to support CSA, with the CSA Policy ments in readiness or coordination mechanisms. xvi Agriculture Global Practice Discussion Paper FIGURE ES.6.  RELATIONSHIP BETWEEN 2. TESTING RESULTS FOR CSA-POL INDEX AND GHG CSA TECHNOLOGY INDEX INTENSITY OF PADDY RICE As part of the test application of the CSA-Tech (n = 74) 5 Index, case studies were developed on five select 4.5 y = –0.02x + 2.2 projects in Armenia, Burundi, Bhutan, Brazil, 4 R2 = 0.10 and China to demonstrate how the tool can be Kg CO2eq/Kg Rice 3.5 used to select highly appropriate existing tech- 3 nologies to achieve triple wins. 2.5 2 1.5 Case Study 1. Armenia: Second community 1 0.5 agriculture resource management and 0 competitiveness project 30 40 50 60 70 80 90 Aggregated policy index (%) To reduce Armenia’s dependence on agricultural imports and to strengthen value chains in the country, links between producers and processors need to be strength- ened, food safety promoted, and processing and market- ing supported. The findings of the assessment also led to Low-income countries are fully capable of for- a recommendation for an increase in the capacity of pub- mulating policies that are highly amenable to lic sector institutions to support improved market access the implementation of CSA. For these countries, gov- and selected value chain development. Coverage of the ernment commitment through national climate change pasture-based livestock system should be extended. policies and strategies can be as important as services in creating an enabling environment for CSA. Tanzania, for instance, emerged among the top performers in Sub- Case Study 2. Burundi: Agricultural Saharan Africa (SSA) using the CSA Policy Index. The rehabilitation and sustainable land country has built strong institutional frameworks through management project a multisectorial approach to support CSA that is facili- Development of productive infrastructure facilities tated by the National Climate Change Technical Com- such as small-scale water-management schemes, irriga- mittee (NCCTC) and National Climate Change Steering tion schemes, and agro-processing infrastructures are Committee (NCCSC). identified to improve yields and soil fertility in the state-­ controlled cash crop sector. Off-farm income-generating In our sample of 88 countries, petroleum-based activities that support agriculture include repairing and economies are among the lowest performers on manufacturing agricultural tools and small equipment, the CSA Policy Index. As a result of heavy reliance on possible subjects for training workshops. petroleum revenues, nonpetroleum-based sectors in these countries remain critically underdeveloped. The lack of diversification of the economy and underdevelopment of Case Study 3. Bhutan: Land the agricultural sector may have contributed to weak insti- management project tutional mechanisms for supporting CSA implementation. The assessment led to recommendations for an increase in In many cases, these countries also lack National Action physical investments such as measures to conserve vegeta- Plans for Adaptations (NAPAs), for example, to support tive cover, terracing, forest and rangeland regeneration, CSA implementation. A noteworthy exception is Nigeria, and reforestation at the farm and community levels, where which has established policies recognizing climate change necessary, to achieve national commitment to environ- as a threat to development and has incorporated adapta- ment sustainability. Sustainable land management (SLM) tion strategies for CSA. activities must be adopted and implemented. Climate-Smart Agriculture Indicators xvii Case Study 4. Brazil: Caatinga conservation gives a value of 3.9. This indicates that the major- and management—Mata Branca ity of indicators have reached or (highly) exceeded The assessment pinpointed investment in the rehabili- those targets that measure the CSA successes at tation of degraded areas as a key recommendation. project completion. Potential investments included reforestation, develop- ment of small grazing corridors, direct vegetation plant- Case Study 2. Bhutan: Sustainable land ing, application of organic fertilizer, and introduction management project of agro-forestry techniques. The assessment findings »» Project objectives: Institutional and community also pointed to development of drought-management capacity must be strengthened for anticipating and projects, terrace development, and the introduction managing land degradation in Bhutan. This can of integrated soil and water–management practices to contribute to more effective protection of trans- reverse current trends of deforestation and unsustain- boundary watersheds in a manner that preserves able irrigation practices. the integrity of ecosystems in Bhutan. »» Assessment results: Two indicators (“Tseri Case Study 5. China: Integrated modern land shifted to sustainable land cover,” “Degraded agriculture development project forestland regenerated and grazing lands Owing to the country’s lack of available water and high improved in pilot geogs”) demonstrated mitiga- rate of fertilizer use, the project assessment revealed that tion benefits and achieved an average score of 5, more efficient water-saving irrigation technologies and implying that expectations were highly exceeded. integrated soil fertility management (ISFM) can help The project achieved an overall average score increase agricultural productivity and improve soil quality of 4.8. and the efficiency of fertilizers and other inputs. Case Study 3. Brazil: Rio de Janeiro 3. TEST RESULTS FOR CSA sustainable integrated ecosystem RESULTS INDEX management in production landscapes of the CSA-Res Index assessments were performed on north-northwestern Fluminense (GEF) project five World Bank projects in the areas of agricul- »» Project objectives: Promote an integrated eco- ture, rural development, and natural resource system management (IEM) approach to guide the management. All projects have been completed and development and implementation of SLM prac- the Implementation Completion and Results reports are tices. Improved capacity and organization for nat- consulted for data/information on the indicator target ural resource management (NRM) and increased values and values at project completion. The CSA-Res adoption of IEM and SLM concepts and practices Index for P, R, and M and jointly is thus derived for the are expected for the primary target group (small- project’s performance in the last project year. A summary holder families and communities). of results for each case study follows. »» Assessment results: The overall average CSA Results Index for the project is 2.9. This figure Case Study 1. Armenia: Natural resource needs to be interpreted with caution because management and poverty reduction project the areas of Resilience and Mitigation contain a »» Project objectives: Adoption of sustainable range of indicators that largely exceed expecta- natural resource management practices helps avert tions. In contrast, the area of Productivity has one further deterioration of natural resource and stabi- indicator that falls short of meeting the target. For lizes incomes in the local communities. achieving the CSA goals, these results may indi- »» Assessment results: The overall CSA-Res cate that more focus could be placed on the aspect Index, as an average of the index for P, R, and M, of Productivity. xviii Agriculture Global Practice Discussion Paper Case Study 4. Burundi: Agriculture resources management and agro-ecological envi- rehabilitation and sustainable land ronmental management in the Huang-Huai-Hai (3H) Basin management project »» Assessment results: Each indicator reaches »» Project objectives: Restore the productive or exceeds the target. The overall average CSA capacity of rural areas through investments in Results Index score is thus 3.6, demonstrating that production and sustainable land management and the project has satisfactorily reached all targets through capacity building for producer organiza- related to achieving the CSA triple wins tions and local communities. »» Assessment results: The overall average score for Productivity performed below expectation; however, the average score for Mitigation exceeded CONCLUSION the target value by more than 20 percent. The The CSA indicators were useful insights into the overall average CSA Results Index score is thus impacts and outcomes of climate-smart policies and 3.3—the project has satisfactorily achieved targets interventions and can be applied with significant flex- related to CSA triple-win goals. ibility, although all three indices require some degree of further development and refinement. The CSA Policy Index, for instance, will need to be developed further Case Study 5. China: Irrigated to capture the performance and coordination of the agriculture intensification project III services that are provided to support CSA policies. For »» Project objectives: Increase water and agricul- both the CSA Technology and CSA Results ­ Indices, the tural productivity in low- and medium-yield farm- diversity of indicators implies that care must be exer- land areas; raise farmers’ income and strengthen cised when comparing projects based on index scores their competitive capacity under post–World Trade because the scores are relative and the underlying indi- Organization (WTO) conditions; and demonstrate cators and their meaning may vary significantly from and promote sustainable participatory rural water project to project. Climate-Smart Agriculture Indicators xix CHAPTER ONE BACKGROUND CLIMATE CHANGE AND AGRICULTURE Global agriculture has a lot on its plate. It is self-evidently the sector that will be most instrumental in feeding nine billion people by the year 2050 and in addressing the needs of the 795 to 805 million people who are food insecure today. It also provides livelihoods for some 2.6 billion people worldwide and accounts for between 20 and 60 percent of the gross domestic product in most developing countries. No other sec- tor of the economy is as effective in raising people out of poverty. And no other sector is as directly reliant on its natural resource base, the land and water resources that are the fundamental elements of crop and livestock production. The sector consumes 40 ­percent of global land area and 70 percent of global freshwater. The other fun- damental element is the climate. And no other sector is as vulnerable to the effects of a changing climate. Throughout much of the world, for instance, grain yields will decline by 5 percent with each degree Celsius the temperature warms. The vulnerability of agricultural systems to climate change are chiefly described in terms of risk, in what is already an exceptionally risky sector. Much of this involves the increased risk associated with more frequent instances of heat stress, drought, and flooding, or what are generally referred to as production risks (as opposed to market or commodity price risks). The price hikes between 2008 and 2010 were caused by natural disasters like wildfires in some of the world’s largest food exporting regions. Severe droughts in the summer of 2012 pushed prices even higher. This vulnerability to the effects of climate change has a dramatic counterpoint in the massive effects that agricultural production has on climate change. Crop and livestock production, including land use change and the use of synthetic fertilizers are a colos- sal source of greenhouse gas emissions, and the principal source of greenhouse gases with exceptionally high carbon equivalence like nitrous oxide and methane. Agriculture accounts for 52 percent of methane emissions and 84 percent of nitrous oxide emis- sions in addition to its role as the principal driver of global deforestation. Agriculture and agriculture-driven land-use change contribute 24 percent of anthropogenic global greenhouse gas emissions. Agricultural practices in their current “business as usual” Climate-Smart Agriculture Indicators 1 form are projected to account for up to 70 percent of total competition for water from other users such as households human-induced emissions by 2050 if global warming is and industries. The demand for water for agriculture may successfully limited to two degrees Celsius (WRI 2014). rise by over 30 percent by 2030 within another larger con- text of declining availability. Projections indicate that the Depleting resources further strains agricultural sys- population living in water-stressed and water-scarce coun- tems. Water scarcity may also result from changes in the tries will increase from about 18 percent today to about global distribution of rainfall in a context of increasing 44 ­percent by 2050. Extreme variability of precipitation may place 2.8 billion people at risk of water shortages. FIGURE 1.1.  GLOBAL LAND USE CHANGE Yet agriculture possesses at least one other unique quality. AND AGRICULTURE Including forestry, it is the only economic sector that can GREENHOUSE GAS EMISSIONS be purposefully employed to actively sequester atmospheric LAND USE CHANGE AGRICULTURE ~11% OF TOTAL ~13% OF TOTAL carbon and reliably store it in soils and plant tissues, if pro- TOTAL EMISSIONS duction is climate smart. Although agriculture emits a large Land Use Agriculture volume of greenhouse gases, its biomass and especially its Change FOREST LAND 13% LIVESTOCK 63% Buildings 11% 62% soils also sequester carbon out of the atmosphere, and this 6.4% role as a carbon sink and as a carbon store can be strate- Electricity & CROPLAND Transport 14% Heat FERTILIZERS 16% gically optimized through proven farming techniques and Production 25% 25% RICE - 10% methods that simultaneously reduce emissions. It should be BURNING BIOMASS OTHER - 12% 11% Industry noted that sequestration of greenhouse gases is not limit- Other Energy 21% 9.6% less. Although carbon sequestration can be large to begin FIGURE 1.2.  CLIMATE-RELATED GLOBAL GRAIN SHOCKS Mexico: China: 2011 White Corn Freeze Russia, Kazakhstan, and Ukraine: 2011 Drought: Wheat reduced national 2010 Drought and Heat Wave: impacting 36% of Colombia: production by 4 MMT or Wheat production reduced by 20.2, winter wheat area in 2010 Flood: –18 %. 9.7, and 4.0 MMT repectively. eight provinces, yields –3,80,000 ha of crop 2009 Drought: Corn reduced by –10 MMT. lands and pastures reduced com yields by flooded & –30,000 3.85 MMT = 15.9% livestock died. relative to previous year. Brazil: 2008 Drought: Reduced soybean production by 3.2 MMT – 5.25% relative to previous year. Paraguay: Soybean 2008 Drought Data Source: USDA 2008 Drought: Reduced reduced production corn production by by 2.9 MMT – 42%. 7.6 MMT – 13%. Indian Ocean: Argentina: Southem Africa: 2011 Spring Cyclones Australia: 2008 Drought: Reduced soybean 2011 Floods caused significant crop destroyed 30% (1 MMT) of 2006 Drought: Reduced yields by 14.2 MMT – 30.7% and livestock losses (Lesotho, Sri Lanka’s rice crop and wheat yields by 14.3 MMT 2008 Drought: Reduced corn yields Zambia, Zimbabwe, Mozambique). reported to have badly –57 %. by 6.52 MMT – 29.6%. No reliable loss data available. damaged most of Madagascar’s rice crop. Note: MMT = Million Metric Tons. 2 Agriculture Global Practice Discussion Paper with, the sinks decline as a maximum equilibrium value innovation geared toward climate change adaptation and is reached (World Bank 2012). Empirical evidence sug- mitigation potential. This has become the focus of partner- gests that these sinks saturate at between 10 and 100 years, ships that bring agriculture, environment, and economic depending on practices applied, soil type, and climate zone. development into the same dialogue, and that are well posi- (IPCC 2006). Because sinks are also reversible, sequestra- tioned to generate knowledge, raise awareness, and dissem- tion practices must be maintained even when the sinks are inate news about best practices to agriculturists and their saturated. The benefit of carbon sequestration is that it can counterparts in other sectors. This type of cooperation provide “breathing space” to make room for other tech- and partnership is best served by having indicators that can nologies that reduce emissions to come on the scene. be readily monitored over time to track progress, measure impacts, and guide investments and policies, assessing their Agricultural mitigation can be achieved through improved effectiveness. The World Bank CSA indicators are designed cropland and grazing land management, restoration of to provide users with a framework that guides actions to degraded land, restoration of cultivated organic soils, and support CSA implementation while acknowledging coun- reduced food waste. Agricultural mitigation potential is try and project contexts. The CSA indicators are divided cost effective, ranging from 7.18 to 10.60 gigatons carbon into three indices: Policy, Technology, and Results. dioxide equivalent (CO2-e) per year at carbon prices up to $100 per ton of CO2-e, about a third of which can be Table 1.1 lists a range of selected existing indicators and achieved at prices up to $20 per ton of CO2-e. indices relating to agriculture and climate change and identifies their limitations. A detailed review can be found The technical elements of CSA are by now well understood. in appendix A. In addition to their technical feasibility, they can be highly pro- ductive and profitable (Lipper et al. 2014). CSA can reverse trends of land degradation and negative ecological footprint, OBJECTIVES AND SCOPE OF sustain food production, enhance resilience, and sequester THE REPORT carbon. CSA is an approach for developing the technical, This report seeks to support countries and project teams policy, and investment conditions to achieve sustainable agri- in establishing the necessary policy, technical, and moni- cultural development for food security under climate change. toring framework to operationalize sustainable agricul- CSA identifies synergies and trade-offs among food security, ture practices under changing climatic conditions. The adaptation, and mitigation as a basis for informing and reori- success and the legitimacy of their efforts will depend, enting policy in response to climate change. It is a transition primarily, on how these stakeholders implement their to agricultural production systems that are more productive programs or policy. The indicators, formulated in this and efficient; more resilient to risks, shocks, and long-term report, will guide investment decisions and assist coun- variability; and that reduce GHG emissions and sequester tries to assess their readiness to implement CSA, and also carbon. CSA is composed of three main pillars: assess the productivity and climate benefits of climate- 1. Sustainably increasing agricultural productivity smart agriculture. and incomes; 2. Adapting and building resilience to climate The Policy indicators may be used for evaluating the extent change; and to which countries have adopted climate-smart policies. 3. Reducing agricultural emissions or optimizing The Technology indicators can be used for selecting climate- production to sequester and store carbon. smart technologies for widespread dissemination in World Bank and other projects, and for evaluating the extent to INDICATORS FOR CLIMATE- which newly generated technologies are climate smart. Lastly, the Results indicators can be used to measure the out- SMART AGRICULTURE puts and outcomes of development projects/activities on A variety of attempts have been made in recent years to set the three dimensions of productivity, resilience, and miti- a global agenda for investments in agricultural research and gation (table 1.2). Climate-Smart Agriculture Indicators 3 TABLE 1.1.  OVERVIEW OF EXISTING INDICATORS Category Index Purpose Limitations Food Security Global Food Security Index Assesses food security of 109 countries. Calculating the composite The indicators are categorized in three index is too complex and a groups—food affordability, availability, theoretical framework is lacking and quality and safety. that explains the rationale for the selection of indicators for the composite index. Hunger and Nutrition Ranks governments on their political Assessing country progress for Commitment Index commitment to tackling hunger and tracking hunger and nutrition undernutrition through the index from year to year is difficult. Agricultural Science and Provides information on agricultural Does not provide a composite Technology Indicators research and development (R&D) systems index that provides a ranking at across the developing world one glance Climate WRI—CAIT Benchmark and provide information Neglects the interdependencies Change on countries’ contribution and of agricultural productivity and vulnerability to climate change and other resilience environment-related information WRI Global Forest Watch Interactive platforms provide indicators No composite index is such as tree cover state, loss and gain by provided. country University of Notre Dame The ND-GAIN shows a country’s current Global Adaptation Index vulnerability to the disruptions that will (ND-GAIN) follow climate change, such as floods, droughts, heat waves, cyclones, and security risks. It also demonstrates their readiness to leverage private and public sector investment for adaptation actions. This study incorporates the readiness index of the ND-GAIN. M&E for CSA Global Donor Platform for Indicators for agriculture and rural Does not track climate change Rural Development development mitigation and resilience to climate change CCAFS Resilience Provides project-level indicators for Agricultural production and monitoring and evaluation projects land use management, as well that seek to increase adaptive capacity, as farmers’ potential to adapt to enhance livelihood and farm functioning and mitigate climate change are not addressed. World Bank Land Quality Indicators tackle ecological resilience Only partially allows for and Sustainable Land excluding the resilience and adaptive monitoring the mitigation Management capacity of households potentials of agriculture Baseline CSA Profiles by CCAFS A set of CSA country profiles for Latin It is difficult to derive policy information America and the Caribbean, which are recommendations from them or for CSA based on the CSA pillars of productivity, recommendations as to which adaptation, and mitigation technology may be the most suitable at the project level. Note: CAIT = Climate Analysis Indicators Tool; CCAFS = CIGIAR Research Program on Climate Change, Agriculture and Food Security; WRI = World Resources Institute. 4 Agriculture Global Practice Discussion Paper TABLE 1.2. THE THREE CSA INDICES The report is structured as follows: Chapter 2 discusses Indices Rationale the impact pathway and theory of change used to develop the indicators. Chapter 3 discusses the criteria for Policy Support The level of adoption of CSA practices selection of indicators, organization, and procedure for and Institutional depends on the enabling environment Readiness Index that is a function of policy and using the indices. Chapter 4 summarizes major findings (CSA-Pol) institutional context in the country. for the CSA-Pol Index country assessments. Chapter 5 Responding to climate change requires tests the usage of the CSA-Tech Index and the CSA-Res national food security adaptation and Index to current World Bank projects. Finally, chapter 6 mitigation strategies. Building farmers’ provides a conclusion and a view to the future. adaptive capacity requires considerable investments above the farm level. Technology Index The applied CSA technologies need to (CSA-Tech) be context specific and prioritized in different landscapes/farming systems. Indicators should be able to capture changes in P, R, and M caused by changes in technologies. Results Index The relative benefits of CSA adoption (CSA-Res) need to be measured. A portfolio of indicators appropriate for the particular intervention is needed. Climate-Smart Agriculture Indicators 5 CHAPTER TWO IMPACT PATHWAY AND THEORY OF CHANGE The CSA indices are informed by an impact pathway and provide a framework for measuring the outputs and outcomes of a CSA intervention highlighting behavio- ral change that will support the achievement of the CSA triple-wins. The impact pathway is a theoretical framework that helps guide program planning, manage- ment, and evaluation. In contrast to the frequently used logical framework, which describes the project by proceeding from inputs and activities to outputs and out- comes to the ultimate goals by an if-then causal logic, the impact pathways provide a more holistic view of the change process. It is a flexible approach that allows investigating change processes independent of concrete interventions by articulat- ing hypotheses as to how impacts are being achieved (Kim et al. 2011). It can incorporate the views of different stakeholders and it is assumed that it can evolve over time, as more knowledge is gained about agricultural innovation processes (Springer-Heinze et al. 2003). To understand which indicators and indices are relevant to monitor and measure the success of a CSA intervention in terms of achieving the CSA triple-win goals, we developed an impact pathway. The pathway is general in nature and does not relate to specific project activities. Instead, we captured how stakeholders’ behavior could change (see the section “Outcomes—Behavioral Change” for further description)— on a project and national scale—to support the achievement and sustainability of CSA goals and impacts in the agricultural sector (see the section “Agricultural Sector Impacts”) and how these relate to the sustainable development goals and the World Bank’s twin goals of shared prosperity and ending extreme poverty. Although we rec- ognize that these relations are partial in nature, it is important to note the sustainability of the CSA impacts can only be achieved when stakeholders change their behav- ior. Thus, the impact pathway provides a conceptual framework for determining a clustered set of indicators, which allow measurement of behavioral change (project outcomes), direct project outputs, and aspects of the enabling policy and institutional environment that may be necessary to support the CSA intervention and subsequently Climate-Smart Agriculture Indicators 7 FIGURE 2.1.  IMPACT PATHWAY FOR productivity can increase food availability and access, as CSA INTERVENTIONS AND well as rural incomes. RELATION TO CSA INDICATORS There are three interrelated benefits for society from enhancing agricultural productivity: (i) economic growth and poverty reduction, (ii) food and nutrition security and Impacts CSA Outputs Outcomes- Agricultural Sector Impacts Sustainable (iii) environmental sustainability (FAO 2013). It is well of CSA behavioral Development intervention intervention change related to the CSA triple-wins Goals; World established that growth in agriculture is twice as effective Bank Twin Goals in reducing poverty as growth originating from other sec- CSA-Tech indicators CSA-Res Indicators tors (World Bank 2007). Productivity growth in agriculture (project level) (farm system level, to support design CSA-Pol Indicators creates income and employment and generates demand of intervention) (project and national level) for other rural goods. This also leads to stimulating growth in other parts of the economy. Productivity determines the price of food, which in turn determines wages and com- petitiveness of the tradable sector (WDR 2008). achieve the long-term development outcomes.1 Some of the project outputs are assumed to be approximate meas- Sustainable production systems are knowledge inten- ures of behavioral change. The assigned indicators are sive, such that investment in intellectual capital, typically part of the CSA Results and CSA Policy Indices, which acquired through research and development and dis- can be used after a specific intervention (see figure 2.1). semination of agricultural technologies and management The CSA Technology Index can be used at the begin- practices, and human capital, acquired through educa- ning of an intervention to support the choice of a CSA tion, training, and extension services, will be relevant to technology. achieve sustainable and climate-smart agriculture. To achieve high levels of investment in human, social, and AGRICULTURAL SECTOR natural capital, action on the national and international IMPACTS levels is needed (FAO 2013). The 2008 World Develop- This section discusses and describes the long-term out- ment Report suggested several activities that can increase comes that CSA interventions typically aim to achieve. agricultural productivity: The behavioral changes from different stakeholder groups »» Improve price incentives and increase the quality that may lead to these long-term outcomes are described and quantity of public investment; in the next section. »» Improve the functioning of producer markets; »» Improve access to financial services and reduce exposure to uninsured risk; INCREASING PRODUCTIVITY »» Enhance performance of producer organizations; Increasing productivity is a dedicated goal of CSA. For »» Promote innovation through science and technol- instance, in many African countries yield levels of many ogy; and commodities are still below the world average. Such low »» Make agriculture more sustainable and a provider levels of productivity are mainly attributable to scarce of environmental services. knowledge of agricultural practices, low-level use of improved seed, low-level fertilizer use, inadequate irriga- These efforts demand broader policy and strategic frame- tion, and the absence of strong institutions and policies works that encompass agro-industrial and agribusiness (IFPRI 2012). It has been demonstrated that increasing services along with farming (IFPRI 2012). Note direct outputs are not described in detail in the impact pathway presented ENHANCING RESILIENCE 1 here. This is a general CSA impact pathway, in which we do not describes out- puts, activities, and inputs of specific CSA interventions. The indicators, how- Increasing occurrence of erratic and extreme weather ever, may describe outcomes or outputs. events and increasing volatility of food prices and 8 Agriculture Global Practice Discussion Paper uncertainties related to the development of global mar- Further investment in both technological and political kets and policies can have a negative impact on food innovations is needed. This may include research, devel- security and agricultural income of consumers, farmers, opment and dissemination of drought-tolerant seed vari- and entire countries. Smallholder farmers who have the eties and bio-fortified crops, replacement of inefficient largest role to play in achieving food and nutrition secu- subsidies, provision of social safety nets, and risk manage- rity are largely “climate dependent” but have the weakest ment tools that support household livelihood strategies capacity to adapt to this increasingly volatile world. Their and preparedness, prevention, response, and recovery resilience needs to be strengthened, through targeted poli- activities in response to shocks and climate change–related cies, investments, and institutions (Fan 2014). Enhancing occurrences (Frankenberger et al. 2014). But enhancing resilience, at every scale and from environmental, eco- resilience also entails strategies such as improving the sus- nomic, and social perspectives, is a crucial goal of CSA tainability of forest management. This not only increases interventions. the forest’s resilience but also contributes to improving water management, protecting the soil from erosion, and There are many definitions of resilience. The Interna- conserving agro-biodiversity (FAO 2013). tional Panel on Climate Change (IPCC) (2014) refers to resilience as “the capacity of social, economic, and REDUCING GREENHOUSE GAS environmental systems to cope with a hazardous event EMISSIONS or trend or disturbance, responding or reorganizing in Reducing greenhouse gas emissions resulting from agri- ways that maintain their essential function, identity, and culture is one of the main aims of CSA. A CSA interven- structure, while also maintaining the capacity for adap- tion should lead to sustainable reductions of agricultural tation, learning, and transformation.” As social, eco- GHG emissions. On the global scale, the Agriculture, nomic, and environmental landscapes change, resilience Forestry and Other Land Use (AFOLU) sector is respon- has to be regarded as a dynamic process rather than a sible for approximately a quarter of anthropogenic GHG static state (Frankenberger et al. 2014). In the social sys- emissions—mainly from deforestation, livestock, and poor tem, resilience may refer to the ability of communities to soil and nutrient management. Mitigation opportunities withstand and recover from stress such as environmental, include both demand-side and supply-side strategies. The social, economic, or political changes. Social systems can demand-side strategies include reducing food waste and plan according to real or perceived changes, thus avoid- losses, changes in diet, and reducing wood consumption. ing damages, minimizing losses, and taking advantage On the supply side, strategies reduce GHG emissions of opportunities. For natural systems, resilience is indi- through improved management of land and livestock. cated by how much disturbance an ecosystem can handle Carbon sequestration in soils and biomass lead to without shifting into a qualitatively different state. The increased levels of terrestrial carbon stocks (IPCC 2014). complexities and relation and interdependence of both systems have to be considered when building resilience to As the global population continues to grow, agricultural climate change (IFPRI 2009). production is also expected to increase, especially in devel- oping countries. By improving efficiency and decoupling To enhance resilience of smallholder farmers, it is rele- production growth from emission growth, as well as by vant to facilitate their access and use of productive assets, enhancing carbon sinks, agriculture can contribute to such as land and water and production inputs. Strength- climate change mitigation and be in line with the “food ening of land and water rights may encourage farmers security first” objective (FAO 2013). to invest, build assets, and diversify. Enhancing access to water, through on-farm water harvesting, the enhance- ment of soil’s capacity to hold moisture, on-farm water OUTCOMES—BEHAVIORAL retention, and more systematic access to groundwater or CHANGE supplementary irrigation can have a positive impact on As noted earlier to sustainably achieve the desired impacts household’s resilience (FAO 2013). of CSA, the proposed intervention must influence behavior Climate-Smart Agriculture Indicators 9 change. This section describes the behavioral changes approach and CSA implementation requires needed for achieving the desired impacts of CSA inter- cooperating across different sectors. Decision mak- ventions among six key stakeholder groups: (1) producers; ers from various ministries and research institutes (2)  policy makers and institutions; (3) extension workers; with different thematic focuses must work together (4) consumers; (5) civil society; and (6) the private sector. to gather and provide timely and relevant infor- mation. This behavioral change in policy makers and institutions aims to facilitate the future avail- 1. PRODUCERS ability of data and information on CSA within a CSA interventions and projects aim to induce the follow- landscape approach. ing observable behavioral changes in producers: iii.  Policy makers utilize a diversity of instruments, i.  Producers adopt appropriate CSA technologies information, and stakeholder inputs for creating and inputs such as seed, fertilizer, pesticides, and incentives and building capacity of producers risk management tools. This outcome demonstrates to implement CSA in an intersectorial manner that producers have taken up the outputs of a spe- and across various stakeholders including tech- cific CSA intervention into their daily practice. nical, research, and extension staff, as well as ii.  Producers demonstrate improved knowledge on nongovernmental stakeholders and international the costs, benefits, and trade-offs of adopting CSA. ­partners. To ensure a sustainable adoption of these CSA iv.  Policy makers establish an institutional framework practices, knowledge and capacity of producers for CSA implementation. Policy makers establish must be developed. This supports the resilience as the legal and regulatory frameworks to promote well as the productivity of farming systems. and mainstream CSA. This behavioral change iii.  Producers engage with extension services, which conveys the commitment and frame for imple- is crucial if the desired impacts are to be achieved menting CSA. Within this framework, policies because such engagement has the potential to and regulations that aim at promoting CSA are empower them to make decisions. drafted. iv.  Producers adopt income improvement strategies v.  Government agencies implement, enforce, and including income diversification and access to monitor and evaluate CSA polices. Thus it is improved financial instruments and services. crucial that policy makers monitor and over- v.  Producers integrate into new markets and engage see CSA compliance across various sectors and with value chains. Access to markets is essential ­institutions. for smallholder producers to generate income, vi.  Government should also commit to regional and strengthen food security, and contribute to sustain- global agreements and mechanisms to support able livelihoods. climate change adaptation and mitigation. This outcome supports the goal of mitigating GHG 2. POLICY MAKERS AND INSTITUTIONS caused by agriculture. CSA interventions and projects aim to induce the follow- ing behavioral changes in policy makers and institutions: 3. EXTENSION WORKERS i.  Policy makers monitor and oversee CSA compli- Extension workers should also engage in multilateral ance. The institutional commitment and support knowledge sharing and strive to be up to date with the of policy makers is crucial to ensure the sustain- latest knowledge on CSA from a variety of sources able adoption and application of CSA not only including the farmers themselves. Extension services are at the farm level but also at the landscape and one of the key channels through which information on national levels. new technologies and practices will be disseminated, and ii.  Institutions cooperate in developing and dissemi- are therefore an important supporting service for CSA nating information. CSA demands a landscape implementation. 10 Agriculture Global Practice Discussion Paper 4. CONSUMERS processes, for instance, becoming vocal about local con- Consumers support CSA practices in consumption deci- cerns and demand measures or services (FAO 2013). Civil sions. Value is captured and determined by consumers society’s engagement can take place on a local to interna- when they buy the product, which then benefits other seg- tional level, and has considerable potential to support the ments in the value chain. Hence consumers, in particu- achievement of the desired impacts. lar those in developed countries, have a large degree of power. Consumers’ behavior should reflect raised aware- 6. PRIVATE SECTOR ness regarding reduction, reuse, and recycling of food The private sector engages in CSA-related activities and that is still fit for human or animal consumption or other supports an environment that furthers the sector goals purposes (for example, compost or biogas) (FAO 2013). of improved productivity, enhanced sustainability and Their behavior should also be reflected in an increased resilience, and reduced GHG emissions. The key private demand for goods that stem from integrated, sustainable sector agents may include farmers themselves, producer value chains that build on CSA practices. Their demand cooperatives, national and international agribusinesses, will support farmers (and value chains) to promote sus- commercial consultancies, and banks and credit and sav- tainable production. ings institutions. Private sector actors provide research, development, education, and extension. Whereas the pri- 5. CIVIL SOCIETY vate sector agents often aim for profits and public per- Civil Society supports CSA-related activities and the sec- ception, favorable behavioral change would include an tor goals of improved productivity, enhanced sustain- enhanced interest in supporting CSA-related activities. ability and resilience, and reduced GHG emissions. Civil These may come about by policy or regulatory incen- society plays a crucial role in mainstreaming CSA activi- tives or by the design of a brand surrounding CSA. As ties to achieve the desired impact. Civil society institutions markets and market engagement of smallholders become readily foster bottom-up engagement and have consider- ever more important, it is relevant to provide outputs that able potential to exercise influence in decision-making change the private sector’s behavior to support CSA. Climate-Smart Agriculture Indicators 11 CHAPTER THREE INDICATOR SELECTION AND APPLICATION The selection and development of the indicators encompassed an extensive literature review, the development of an impact pathway (desirable impacts in the agricultural sector and behavioral changes leading up to it) and theory of change, and three expert consultations. The project team also examined and selected some World Bank Core Sector Indicators that were eventually included in the CSA Results Index. Nearly 80 experts from the World Bank Group and development partners participated in the consultations. A key to an effective assessment of the “CSA-ness” of a project is to strategically select the most accurate indicators for the project of interest. Although there are several indicators that could potentially work, it may be impractical to use more than a few. Effective indicators should be the following (FAO 2010): »» Relevant: The indicator reveals something that you want to know about the system. »» Precise: You can reliably trust the information that the indicator provides. »» Sensitive: As the system changes, the indicator changes in a predictable fashion. »» Easy to understand: The indicator is intuitive to laypersons and decision makers. »» Measurable: The indicator is based on accessible data that are already avail- able or can be collected and interpreted with relatively easily. In the process of indicator selection, indicators were chosen to ensure that indica- tors are Specific, Measurable, Achievable and Attributable, Relevant and Time Bound (SMART). These attributes are defined as follows: i.  Specific: Indicators should reflect simple information that is communicable and easily understood ii.  Measurable: Information can be readily obtained. Are changes objectively verifiable? iii.  Achievable and Attributable: Indicators and their measurement units must be achievable and sensitive to change during the life of the project. Climate-Smart Agriculture Indicators 13 iv.  Relevant: Indicators should reflect information possible synergies between the World Bank and IFPRI’s that is important and likely to be used for manage- effort in this area. ment or immediate analytical purposes. v.  Targeted: Progress can be tracked at a desired fre- Combined with the literature review, these expert con- quency for a set period of time. sultations allowed the project team to develop a compre- hensive set of indicators that could potentially provide the Although SMART is a helpful criterion, indicators should evidence base for identifying viable climate-smart options, be more than that and include a precise definition, be selecting contextually relevant technologies and practices, feasible, and be useful for decision making. The technical monitoring results, and assessing policies and the neces- notes of the CSA-Pol, CSA-Res, and CSA-Tech indica- sary enabling activities. tors typically include information about their justifica- tion, unit, frequency, data source, and calculation method The CSA indicators website (http://csai.worldbank.org) (please see the appendixes for the complete list of indica- summarizes the findings of the CSA-Pol Index and allows tors and technical notes). easy derivation of P, R, and M for CSA-Res and CSA- Tech indicators. The first expert consultation in May 20141 discussed the suitability of the initial large set of indicators for develop- ing the three CSA indices, the structure of the indices, CSA POLICY INDEX and approaches for scoring and aggregating indicators. PURPOSE The results from this consultation led to the development A country’s policies and the capacity of its institutions to of peer-reviewed lists of indicators for each index and rel- implement and administer those policies are vital deter- evant methods for scoring the indicators. minants of whether an enabling environment is in place for making CSA a practical, operational reality. This will The second expert consultation held in October 20142 require substantial coordination between public institu- sought feedback and built consensus on the indicators tions such as agriculture and environment ministries, selected for each CSA index, methodologies applied for as well as research institutions and extension services. scoring and aggregating indicators, and the structure and Entities, whether public or private sector, that provide design of the CSA Index web tool. producers with financial and risk management services, marketing opportunities, and infrastructure likewise play The third and final expert consultation held in Janu- very important roles in defining the environment in which ary 20153 in collaboration with the International Food CSA-related activities and initiatives are carried out Policy Research Institute (IFPRI) assessed the global rel- (Branca et al. 2011b). The enabling landscape for CSA evance and utility of the indicators, and also identified the will look different from one country to the next depending on the existing policy landscape, socioeconomic condi- tions, level of agricultural development, and the specific 1 The first consultation included experts from the following institutions: aWhere, challenges that climate change presents. Conservation International, Croplife International, FAO, Field to Market, Global Environment Fund (GEF), Inter-American Development Bank, Inter- The CSA Policy Index is a collection of indicators, each national Fund for Agricultural Development, International Finance Corpora- with subindicators, that are used to assess the enabling tion (of the World Bank (IFC), IFPRI, International Life Sciences Institute, U.S. Agency for International Development, and World Bank. environment for making CSA operational at the national 2 The second consultation included experts from the following institutions: level in terms of policies, legal frameworks, and the capac- aWhere, Conservation International, GEF, IFC, IFPRI, U.S. Department of ity of important stakeholders such as farmers, investors State, World Bank, and WRI. active in value chains, extension agents, research admin- 3 The third consultation included experts from the following institutions: ASTI, Conservation International, GEF, HarvestChoice, IFC, IFPRI, and World istrators, regulators, and others. The index is designed Bank. to provide a kind of overview of a country’s readiness to 14 Agriculture Global Practice Discussion Paper TABLE 3.1. STRUCTURE OF THE CSA-POL INDEX Themes Indicators CSA Triple-Win Alignment Readiness Mechanisms 1. Agricultural adaptation policy R (3 subindicators) 2. Agricultural mitigation policy M (3 subindicators) 3. Economic readiness R 4. Governance readiness R 5. Social readiness R Services and 6. Extension services P, R, M Infrastructure (2 subindicators) 7. Agriculture R&D P, R, M (2 subindicators) 8. Rural Access Index (RAI) P, R 9. Social safety nets R 10. National GHG inventory system M (2 subindicators) 11. National agricultural risk management systems P, R (6 subindicators) 12. Adaptive capacity P, R Coordination 13. Disaster risk management coordination R Mechanisms (3 subindicators) 14. Coordination mechanism P, R, M (4 subindicators) undertake a program of climate-friendly initiatives, and indicators were selected covering three broad themes: of what needs to happen to improve that readiness. It also (i)  readiness mechanisms; (ii) services and infrastructure; provides a useful framework with which to compare agri- (iii) coordination mechanisms. cultural policy regimes in different countries, potentially encouraging competition and giving public officials who SCORING CSA-POL INDICATORS champion CSA an important source of leverage in pro- The CSA policy scores were calculated using the average moting it. of the 14 indicator scores. Binary scoring was used for the qualitative indicators in the index, and quantitative The 14 indicators of the CSA-Pol Index (table 3.1) are scores were normalized to between 0 and 1. The final clustered into three themes: Readiness Mechanisms, Services score of the indicators was determined as the product of and Infrastructure, and Coordination Mechanisms, and each the assigned weight and the normalized indicator score. indicator is aligned with the CSA triple win of Produc- Final indicator scores were calculated as the average of tivity (P), Resilience (R), and Mitigation (M). Technical this product to a single index score between 0 and 1. In Notes on the indicators and subindicators of the CSA some cases no data could be obtained for the indicator Index can be found in appendix B. and therefore a score of 0 was assigned. DERIVATIVE OF THE INDEX CSA THEME: READINESS MECHANISMS In assessing a country’s institutional arrangements and National policies and strategies represent the readi- readiness mechanisms to support CSA implementation, ness mechanisms for support of CSA implementation. Climate-Smart Agriculture Indicators 15 This aspect for enabling CSA implementation is mea- the whole range of activities in agricultural value sured across five indicators and focused on the following chains (production, processing, and marketing) and subthemes: promote competitiveness by improving productivity, value addition, marketing, and infrastructure (World Indicators #1 and #2—Agricultural Adaptation Policy and Agri- Bank 2013). The private sector is recognized as an cultural Mitigation Policy important actor for CSA investments, as well as in supporting the development of CSA technology. This The multiple challenges of climate change will require indicator assesses whether the enabling environment a major transformation of the agricultural sector. The is conducive to agriculture-led growth, agribusi- integration of these challenges and opportunities into ness investment, and competitiveness. This indicator agricultural development planning is critical and builds on work currently ongoing at the World Bank requires enabling policies to guide this integration to develop Agribusiness Indicators.4 (FAO 2010, 2012). For example, policy support for agricultural systems adapted for climate change must Indicator #4—Governance Readiness consider the barriers to adoption of climate-smart practices, and reduce the impact of income losses The governance readiness subindicators capture associated with extreme climatic events so as to guar- several aspects of governance: (i) political stability antee food security for the more vulnerable households and nonviolence—the relationship between foreign (FAO 2012). A focus on policy for CSA implementa- financial inflow and political stability and violence tion makes sense given that policies are a blueprint for suggests that a stable political environment is more strategies and action plans that support CSA imple- attractive to general investment from outside a coun- mentation and mainstreaming (Duguma et al. 2014). try, including the adaptation investment; (ii) control of Actions to address climate change in the agricultural corruption—corruption is known to have a negative sector are likely to have the greatest impact if they impact on foreign investment and measuring the con- are nested in agriculture policy because this would trol of corruption implies government integrity and suggest that there is some kind of consensus among accountability; (iii) regulatory quality—the quality decision makers on how climate change should be of regulation measures the performance of country addressed. However, recent analysis of enabling con- institutions, an important factor in deploying adapta- ditions for climate change mitigation and adaptation tion actions and adaptation-related policies; (iv) rule measured by Duguma et al. (2014) suggest that the of law is a quality of society that encourages foreign urgency of addressing climate change has resulted in investment in general, hence the adaptation invest- the formulation of strategies and action plans prior to ments (Chen et al. 2015). the development or reform of policies. Strategies and action plans that address CSA are therefore consid- Indicator #5—Social Readiness ered part of the policy mix. In assessing a country’s The social readiness subindicators use socioeconomic policy support for CSA, the index includes subindi- measures to assess society’s overall readiness for adap- cators that examine how a country’s intent to sup- tation. The subindicators include the following ele- port CSA are integrated at the national level across ments: (i) Social inequality causes skewed distribution agricultural policies, country development strategies, incomes and vulnerability, and the exaggerated impacts and other national climate change policies including on the poorest may further skew income distribution. National Action Plans for Adaptation and Nationally Thus, social inequality exacerbates a country’s capac- Appropriate Mitigation Actions. ity to adapt to climate change. (ii) Information com- munication technology infrastructure (ICT) enables Indicator #3—Economic Readiness 4 http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTARD/0,, The inclusion of private sector actors along the agri- contentMDK:23184287~pagePK:148956~piPK:216618~theSite culture and agribusiness continuum tends to improve PK:336682,00.html. 16 Agriculture Global Practice Discussion Paper knowledge integration and learning and key ingredi- widespread adoption of new technologies, farming ents of adaptive capacity, provides technical support techniques, and crop varieties (FAO 2009). Sustained for early warning systems, and can strengthen local investment in research is necessary for achieving organizations that implement adaptation. (iii) Educa- longer-term goals such as food security, poverty reduc- tion is considered an important strategy to build up tion, and economic growth. adaptive capacity and identify adaptation solutions Research and extension services are a major compo- appropriate to local context. (iv) Innovation is the fun- nent of the enabling environment for CSA as climate damental force behind capacity building and climate change impacts will, in many cases, require the adap- change adaptation because research and technology tation of current agricultural systems to manage and are necessary to define adaptation solutions (Chen mitigate impacts. The current agriculture system will et al. 2015). need to take advantage of viable, profitable options with manageable levels of risk. Adaptation will require CSA THEME: SERVICES AND investments in information—for example, increasing INFRASTRUCTURE fertilizer, pesticide, and water use efficiencies requires Several supporting services need to be available for imple- mapping water use over time and calculating where menting and mainstreaming CSA. Many of these services and when inputs are necessary (FAO 2013). A strong are already available in some countries, and CSA prac- science and technology system involving the public tices will require improving and strengthening these as and private sectors is recommended for collecting and necessary where they are already available, and ensuring collating the necessary information, and for dissemi- that there is coordination among deliverers of services for nating information to producers through extension efficiency. Significant financial investments will be needed mechanisms. for providing the supporting services for CSA. Supporting Improving the use of climate science data for agricul- services are measured across seven indicators: tural planning can increase the capacity of farmers and agricultural planners to allocate resources effec- Indicator #6—Extension Services tively and reduce risks associated with climate change To ensure a sustainable adoption of these CSA prac- (FAO 2010, 19). Accordingly, there is need for transla- tices, knowledge and capacity of producers have to tors of climate information who can bridge the divide be developed because many CSA interventions are between climate science and field application and the considerably knowledge intensive. The index includes means of disseminating this ‘translated’ information an indicator to assess the capacity of national exten- (FAO 2010, 19). Extension services are one of the key sion services to provide relevant information and channels through which this information will be dis- advice to farmers for dealing with the impacts of cli- seminated, and are therefore an important supporting mate change on their production system. The index service for CSA implementation. examines policies to support this effort as reflected in national agricultural extension services policies and Indicator #8—Rural Access Index the systems that are in place to provide this infor- The Rural Access Index estimates the proportion of mation such as national programs for disseminating the rural population with adequate access to the trans- weather and climate services to agriculture producers. port system. Measurement of rural access is based on household survey data to estimate the number of Indicator #7—Agricultural R&D people who live within 2 kilometers (or about 25 min- The Food and Agriculture Organization (FAO) of utes of walking time) of the nearest all-weather road. the United Nations reports that boosting agricultural In the absence of such data, however, road network production to the levels needed to feed an expanded models are also applied to calculate the proportion of world population will require a sharp increase in rural habitable areas that are within 2 kilometers of public investment to research and development, and all-weather roads as an approximation. This provides Climate-Smart Agriculture Indicators 17 an indicator of transport access for a broader set of the incorporation of risk management tools into agri- rural livelihoods. cultural systems. Tools identified by the FAO as being important in this regard include buffer stock, emer- Indicator #9—Social Safety Nets gency grain reserves, warehouse receipt systems, tar- Social safety nets (SSNs) are noncontributory transfers iffs and quotas, market information systems, weather in cash or in kind targeted at the poor and vulnerable forecasts, early warning systems, and index-based that can have an immediate impact on reducing pov- insurance (FAO). erty and on boosting prosperity by putting resources Indicator #12—Adaptive Capacity in the hands of those members of society (World Bank 2014). In countries experiencing increased exposure Adaptive capacity describes the availability of social to disasters and climate change consequences, there resources to reduce exposure and sensitivity. In some is a growing recognition of the role SSNs play in pro- cases, these capacities reflect sustainable adaptation viding resilience. SSNs can help to ensure that dur- solutions. In other cases, they reflect the ability of a ing times of hardship, such as during flooding and county to put newer, more sustainable adaptations drought events, farming communities can access into place to address the needs of a particular sec- resources (money, food, and so on) to maintain or tor (ND-GAIN 2015). It is important to note that the improve their living standard. Public works programs adaptive capacity score considers not only adaptive that guarantee employment when needed would capacity within the agricultural sector, but also within effectively build resilience to climate change impacts. the sectors of water, health, infrastructure, transport, Agriculture-related public works activities, such as and environment, and therefore provides a broad hillside terracing or soil and water conservation, can measure of a country’s adaptive capacity to climate improve farm yields and generate sustainable bene- change impacts. fits for household food security. They can also create community assets and infrastructures that are critical CSA THEME: COORDINATION for adaptation (FAO 2013). The World Bank identifies MECHANISMS five different types of SSNs: conditional cash trans- Given their crosscutting nature, climate policies may be fers, unconditional cash transfers, conditional in-kind embedded in several sectors. There is need for coordi- transfers, unconditional in-kind transfers, and public nation among policies for promoting and implementing works expenditure. CSA. The key requirements for an enabling policy envi- ronment to promote and implement CSA are greater Indicator #10—National GHG Inventory System coherence, coordination, and integration between climate National GHG accounting systems may include change, agricultural development, and food security pol- national GHG inventories. An accurate understand- icy processes (FAO 2010). Coordination, planning, and ing of GHG emissions allows governments, compa- support for CSA are measured across two indicators: nies, and other entities to identify opportunities to manage emissions, enhance removals, evaluate the Indicator #13—Disaster Risk Management Coordination success of low-carbon growth strategies over time, As part of adaptation strategies to climate change, the and ensure that resources are targeted toward effec- index also examine whether a country integrates the tive solutions. agricultural sector into disaster risk reduction (DRR) planning, or, conversely, how DRR is integrated into Indicator #11—National Agricultural Risk Management Systems the agricultural sector. Disaster risk reduction and Climate change can be an important threat multiplier management that focus on reducing people’s expo- to food security. It also introduces another source of sure and sensitivity to climate change impacts and risk and uncertainty into food systems from the farm increasing their adaptive capacity to better manage to the global level (Branca et al. 2011). CSA promotes climate change helps to build the resilience of those 18 Agriculture Global Practice Discussion Paper people to the impacts of climate change. In an agri- among land users, lack of harmony and coordination cultural context, building the resilience of people between legal bodies and procedures, poor identifica- (producers); the production system (farms); and the tion of and inadequate consultation with stakehold- agricultural value chain promotes the “increasing ers, and uncoordinated planning (World Bank 2011; resilience” goal of CSA. Policy support for DRR can FAO 2013). Given that the stakeholder groups iden- help to support a systematic and coordinated effort tified herein are the same stakeholders responsible in preparing national systems to be able to predict for development and innovation in the agricultural and anticipate impending disasters, and to respond to sector, it is expected that within some countries CSA disasters in a timely manner that does not result in planning implementation would be challenged by low setback of development efforts (FAO 2013, 414). An capacity or little cooperation. examination of a country’s disaster management or its agricultural policies is required. APPLICATION The benefit of the CSA Policy Index is that it provides a Indicators #14—Coordination Mechanism ranking of a country’s adoption of CSA policies relative to other countries. However, beyond assigning a ranking, CSA implementation requires coordination across the CSA-Pol indicators can allow policy makers and other agricultural sectors (for example, crops, livestock, for- users to compare how a country’s enabling environment estry, and fisheries) and other sectors such as energy for CSA is changing over time; identify gaps in support- and water. Cross-sector development is essential to ing CSA implementation; and provide opportunity to capitalize on potential synergies, reduce trade-offs, develop benchmarks for reform. Indicators can also be and optimize the use of natural resources and eco- used individually, allowing users to compare single indi- system services (FAO 2013). Implementation of cators across countries or across time, identify strengths CSA will require cooperation of four main groups and weaknesses, and prioritize specific areas for interven- of stakeholders within these sectors: (1) government tion. In this regard, the CSA Policy Index represents a policy and decision makers to establish the legal useful tool for initiating or furthering policy dialogue and and regulatory frameworks for CSA and to promote planning on how to adequately and efficiently deal with and mainstream CSA in an intersectorial manner; climate change in the agricultural sector. (2) government technical, research, and extension staff to develop and disseminate CSA practices; (3) agri- businesses including nongovernmental research and LIMITATIONS extension organizations for supporting government Although the index represents a useful tool for identifying efforts to implement CSA; and (4) producers that actu- policies and institutional arrangements that are critical for ally implement CSA practices. Cooperation among enabling CSA, it currently does not measure the perfor- stakeholders in these four groups has the potential mance or quality of various policy measures, services, and to improve the design and implementation of CSA coordination mechanisms to support implementation. For policies by allowing various stakeholders to voice their example, a country may have agro-meteorological services needs and concerns, to be more aware of and respon- or programs for building farmers’ resilience to climate sive to the needs and concerns of other actors, and to change; however, the index does not assess the efficacy create opportunities for knowledge exchange (World of the program or the extent to which farmers are able Bank 2011). Such cooperation should be the standard to access agro-weather information and advisories and among stakeholders in the agricultural sector; how- adopt new practices and technologies as a result of the ever, cooperation in many countries is challenged by agro-meteorological programs. Furthermore, although opportunistic behavior among stakeholders, lack of the index assigns a composite score for each country based trust, lack of incentives for cooperation, difficulty in on the institutional arrangements for enabling CSA inter- setting and enforcing rules, policies that are imposed ventions, it does not provide an aspirational number for without local participation, conflicting interests supporting CSA implementation. It is also worth noting Climate-Smart Agriculture Indicators 19 that the index does not cover the full range of policies is smaller than the target score, we assign a score of −1. and services for CSA implementation in any country. In We then map each indicator score to R, P, and M themes developing reforms to support CSA implementation, pol- to generate an R score, P score, and M score. Each of icy makers should consider measures to assess the quality these scores is generated by the share of “exceed” and of services and performance of coordination and institu- “just met” indicators out of total numbers of indicators tional mechanisms to support implementation. in that theme. Finally, we calculate the average of three theme scores to generate the CSA-Tech Index that ranges from 0 to 1—the larger, the better. CSA TECHNOLOGY INDEX Twenty of the CSA indicators use the Likert scoring sys- PURPOSE tem (1. Strongly disagree, 2. Disagree, 3. Neither agree The value of the CSA Technology Index comes from its nor disagree, 4. Agree, 5. Strongly agree). The target score potential to improve decision making. The index contains for the Likert-based indicators is 3. The remaining seven a set of indicators, formulated as survey questions, with the indicators use actual numbers for the raw score and target strategic intent of diagnosing the relative significance of score. For instance, the 14th indicator in table 3.2 is Crop each of the triple-win (P, R, M) priorities in the proposed Yield (which is based on a “% increase” measurement). intervention area. By being able to diagnose the relative For the actual number indicators, the users need to input contextual importance of the triple-win priorities, project their raw scores and their target scores. The recommenda- task team leaders can choose which CSA technologies are tion on which practice to implement in a particular area most appropriate for their proposed project. Considering is based on the aggregated score of surveyed indicators, CSA in the global context, the CSA Technology indica- with the highest-scoring CSA practice recommended. tors were developed to meet the following criteria: 1. Relevance and suitability at the farming system level APPLICATION 2. Measurability As part of the project preparation process, after the proj- 3. Acceptability to many stakeholders ect area and context have been defined, the CSA-Tech Index survey should be distributed to stakeholders (farm- ers, extension workers, policy makers, academics) famil- DERIVATION OF THE INDEX iar with the project area or similar farming systems. The The CSA Technology Index contains a set of 27 indicators results from the survey should then be collated and project clustered into three main themes: Productivity, Resilience, task team leaders can then assign a relative score for each and Mitigation. In choosing indicators, it is recommended of the CSA priorities (P, R, M) and an aggregate score. that project leaders make their own choices on the selec- The relative score of the triple-win areas, among other tion of indicators based on their perception of the proj- factors, will help project teams to diagnose, for example, ect needs. Taking this into account, the CSA Technology the type and combination of climate-smart technolo- Index is built for “minimal indicator use” and project gies to be implemented by the project; the intensity of leaders can use as few as three indicators for their project. capacity-building efforts for smallholders; the magnitude Table 3.2 provides an overview of the CSA Technology of income diversification activities needed in the project indicators. Technical Notes on the CSA-Tech Index can area; and the mitigation strategies for the project. be found in appendix C. There is a range of technologies that project task team SCORING CSA-TECH INDEX leaders can select based on the project context and farm- To generate a final score, we assign each indicator a raw ing system (irrigated, wetland rice, rain fed, coastal arti- (measured) score and a target score based on whether sanal fishing, urban, or dualistic). This report identifies optimal conditions have been met. If the raw score is five key categories5 of CSA technology applicable to eight greater than the target score, we assign a score of 1 for that indicator; if equal, we assign a score of 0; and if it 5 Similar categories are also used in CCAFS country profiles. 20 Agriculture Global Practice Discussion Paper TABLE 3.2. STRUCTURE OF THE CSA-TECH INDEX Themes Subthemes Indicators Productivity (P) Crop system 1. The technology leads to an increase in yields of the producers (%). 2. The technology reduces the share of agricultural land classified as having moderate to severe water erosion/wind risk (%). 3. The technology enhances soil fertility (%). 4. The technology enhances biodiversity of the farming landscape in comparison with current interventions in similar farming systems. Water use 5. The technology increases the share of irrigated agricultural land as a result of the technology (%). 6. The technology reduces water withdrawal for agriculture use as a share of total water withdrawal (%). Energy 7. The technology reduces the agriculture energy use as a share of total household energy use (%). Pest management 8. The technology increases the share of agricultural land on which integrated pest management practices are adopted (%). Livestock system 9. The technology improves livestock diversification in comparison with current interventions in similar farming systems. 10. The technology improves livestock resource management in comparison with current interventions in similar farming systems. 11. The technology improves feed production in comparison with current interventions in similar farming systems. 12. The technology leads to the diversification of livelihood activities in comparison with current interventions in similar farming systems. Resilience (R) Robustness 13. The technology will improve the human capital (technical skill levels) of producers in the target area. 14. The technology will increase the stability of agricultural production needed to help producers meet their own basic food security and income needs. 15. The technology will promote the diversification of the income and asset bases of producers. 16. The technology will promote crop diversification in the target area. 17. The technology will involve the incorporation of site-specifica knowledge in its application. 18. The producers in the target area will have appropriate access to IPRs needed for the deployment of the CSA technology. Self-organization 19. The technology will facilitate cooperation and networking among producers. 20. The technology will foster local and regional production and supply chains. 21. The intervention will provide opportunities for feedback from extension workers. 22. The CSA service will narrow existing power differentials in the community. 23. The technology will contribute to reducing existing gender inequalities. Cropping system 24. The technology will increase the resilience of the cropping system to drought. Livestock system 25. The technology will increase the resilience of the livestock to drought. Mitigation (M) Emissions intensity 26. The technology meets emissions intensity targets. Sequesters carbon 27. The technology sequesters carbon in comparison with current interventions in similar farming systems. a Indigenous knowledge: “local, orally transmitted, a consequence of practical engagement reinforced by experience, empirical rather than theoretical, repetitive, fluid and negotiable, shared but asymmetrically distributed, largely functional, and embedded in a more encompassing cultural matrix” (Buchmann and Darnhoffer 2010). Climate-Smart Agriculture Indicators 21 broad categories of farming systems that project task 3. Agricultural Irrigated Land: The technology teams can select to achieve their desired project goals. increases the share of irrigated agricultural land because of the technology (%); and Five Key Technologies 4. Yield Variance. »» Water-Smart Technologies »» Energy-Smart Technologies For the CSA-Tech Index, the raw score (also known as »» Nutrient-Smart Technologies actual score) refers to the relative number assigned to an »» Stress-Tolerant Technologies indicator based on the evidentiary assessment of a par- »» Climate-Smart Livestock Technologies ticular technology. This raw score is derived from evi- dence from literature, smallholders, policy makers, and Eight Broad Farming Systems (FAO & World extension workers, in the project area or in a similar farm- Bank 2001) ing system. The target score is the aspirational number »» Irrigated farming systems, embracing a broad against which the raw score for the assessed technology, range of food and cash crop production; in the project area, is graded. For example, a raw score »» Wetland rice–based farming systems, dependent of 4 against a target score of 2 for a specific indicator, in on monsoon rains supplemented by irrigation; the targeted area, shows that the technology is suitable for »» Rain-fed farming systems in humid areas of high that specific intervention. In the case of the Likert score, resource potential, characterized by a crop activity we usually use 3 because that is the midpoint in the Likert (notably, root crops, cereals, industrial tree crops— scale (1–5) and anything above that demonstrates a strong both small scale and plantation—and commercial correlation. horticulture) or mixed crop-livestock systems; »» Rain-fed farming systems in steep and highland COSTS AND BENEFITS OF MONITORING areas, which are often mixed crop-livestock systems; CSA-TECH INDICATORS »» Rain-fed farming systems in dry or cold low-­ The fundamental criterion for choosing to monitor an potential areas, with mixed crop-livestock and indicator is that the benefits from doing so must exceed pastoral systems merging into sparse and often dis- the costs. A decision maker (a farmer, project leader, or persed systems with very low current productivity policy maker) will essentially choose to monitor only those or potential because of extreme aridity or cold; indicators that they consider to be beneficial. »» Dualistic (mixed large commercial and small- holder) farming systems, across a variety of ecolo- Whatever the underlying benefits, the key point is the gies and with diverse production patterns; indirectness of benefits arising from improved decision »» Coastal artisanal fishing, often mixed farming making. This is fundamentally different from benefits systems; and ­ arising, for example, from a new production technology. »» Urban-based farming systems, typically focused on The benefits of monitoring sustainability indicators arise horticultural and livestock production. solely from changing decisions concerning which of the existing production technologies should be used. This has These categories are not intended to be an exhaustive list profound implications, as pointed out below. but rather provide a broad view of the technologies avail- able to implement CSA. The benefits of monitoring a CSA Technology indicator Although project teams may not be able to use all CSA- are conceptually no different from the benefits of other Tech indicators in their projects, we propose a set of core types of monitoring, which are routinely conducted by CSA-Tech indicators for projects: farmers and governments. To a farmer, the gross benefit 1. Cereal Yield: The technology leads to an increase of monitoring a sustainability indicator depends primar- in the yields of the producers (%); ily on the scale of production to which it is relevant (for 2. Emissions Intensity: The technology meets emis- example, the area of land for which the information is use- sions intensity targets; ful) and the benefit per unit of production (for example, 22 Agriculture Global Practice Discussion Paper the benefit per hectare of relevant land). For a govern- similar agricultural and rural development indicators that ment, there is an additional consideration in the level of are typically used in projects’ results frameworks. It allows adoption that is achieved (for example, the number of answering the following questions: How has the project farmers who choose to monitor the indicator and the area performed in reaching its targets in one or all CSA triple- over which they apply the results). win areas over time? Has it performed better in one of the areas over another? How many indicators in the P, R, M areas have reached or exceeded their targets? LIMITATIONS The CSA Technology Index is designed as a diagnos- tic tool to assist project preparers in making investment DERIVATION OF THE INDEX decisions with a focus on the triple-win areas of CSA. The CSA-Res Index is composed of 22 indicators The index provides separate and aggregate scores for (table 3.3), which can be used in projects’ results frame- the Productivity, Resilience, and Mitigation areas based work. The indicators are clustered in three main catego- only on the data provided by the project team, without ries: The first category measures the scope of the CSA taking into account any information that may be avail- intervention and focuses on the outputs of the direct proj- able from any other sources. The scores are relative, so, ect intervention; the second category shows how well the for instance, a zero score for mitigation does not mean enabling environment for CSA in the project area is devel- that the proposed project does not have any mitigation oped, which allows actors to sustainably implement their needs. The CSA Technology Index does not recommend CSA intervention; and the third category indicates the any specific technologies nor does it recommend the size medium- to long-term outcomes of the CSA intervention, or composition of any investment; it merely points to the which may depend on the activities measured by I and II. P, R, M requirements in the proposed project area. Proj- Besides the categories, eight themes have been identified: ect managers should also be mindful that changes toward benefits, land use/cover, livestock, enabling environment, improved CSA technology uptake should build on indig- natural resources, emissions, yields, benefit, and welfare. enous knowledge to allow flexibility and innovation to For the calculation of the CSA-Res Index, the indicators improve the livelihoods of the land users. The major chal- have been assigned to the P, R, M areas. In table 3.3, the lenges to CSA implementation in developing countries default assignment is suggested, which is further explained are the following: in the Technical Notes in appendix D. However, it is »» The lack of adequate labor owing to competing important to note that users assign different P, R, M areas interests and poor well-being is present. as considered appropriate for their project. Several of the »» Low levels of access to inputs and equipment such CSA-Res indicators are closely related to the World Bank as machinery, seeds/seedlings, fertilizers, and so on Core Sector Indicators. The description, justification, and is present. technical details concerning the indicators are further »» All land users have limited knowledge related to explained in the Technical Notes in appendix D. CSA technologies. Although project teams may not be able to use all CSA- CSA RESULTS INDEX Res indicators in their projects, we propose five core CSA- Res indicators for projects focused on crops and livestock, PURPOSE respectively, which have been identified as crucial for The CSA Results Index measures an agricultural proj- monitoring the performance and measuring the success ect’s performance in terms of agricultural productivity, of achieving the CSA goals: adaptation (or resilience), and mitigation—both individu- Number of agricultural actors who adopted CSA 1.  ally and jointly. The CSA Results Index can be applied to practices promoted by the project (R) measure the project’s performance during projects imple- Land area where CSA practices have been 2a.  mentation or after the project has been completed. The adopted as a results of the project (P, M) calculation of the index is based on the set of available Number of livestock units subject to CSA prac- 2b.  CSA indicators (table 3.3), but can be performed with tices as results of the project (P, M) Climate-Smart Agriculture Indicators 23 TABLE 3.3.  STRUCTURE OF THE CSA-RES INDEX CSA Triple-Win Categories Topics Indicators Alignment Indicators measuring Beneficiaries 1. Number of agricultural actors who adopted CSA practices R the direct outputs of a promoted by the project CSA intervention Land use/ 2. Land area where CSA practices have been adopted as a result P, R, M cover of the project 3. Land area provided with new or improved irrigation and P (R, M) drainage services 4. Area restored or re/afforested as result of the project R, M 5. Land area covered by forest R, M 6. Land area under land uses or land cover R, M Livestock 7. Number of livestock units subject to CSA practices as result P, M of the project Indicators measuring Enabling 8. Client days of training on CSA provided R the CSA enabling environment 9. Number of agricultural actors who use ICT services for R environment obtaining information on weather and climate, CSA practices, and market (price) information 10. Number of agricultural actors who are members of an R association 11. Number of agricultural actors using: financial services of R formal banking institutes or nonbank financial services 12. Number of agricultural actors employed in agriculture in the R project area 13. Target population with use or ownership rights recorded as a R result of the project Indicators measuring Natural 14. Annual total volume of groundwater and surface water R the medium- to long- resources withdrawal for agricultural use, expressed as a percentage of term consequences of the total actual renewable water resources (in the project area) CSA intervention 15. Land area affected by medium to very strong/severe soil P, R, M erosion in the project area Emission 16. Net carbon balance (GHG emission in tons of CO2-e M emission/ha/year) of project 17. GHG emission intensity P, M Yield 18. Crop yield in kilograms per hectare and year as result of the P, R project’s CSA intervention 19. Yield variability per hectare and year and crop R 20. Yield per livestock unit and year as result of project P, R Benefits and 21. Annual household income from agricultural activity R welfare 22. Number of beneficiaries who consider themselves better off R now than before the intervention 24 Agriculture Global Practice Discussion Paper 3. Client-days of training on CSA provided (R) TABLE 3.4.  SCORING TABLE FOR THE Net carbon balance (GHG emission in tons of 4.  CSA-RES INDEX CO2-e emission/ha/year) of project (M) Level of Crop yield in kilograms per hectare and year as 5a.  Score Performance Interpretation results of the project (P) 1 Very The indicator’s observed Yield per livestock unit and year as results of the 5b.  unsatisfactory value falls short of the target project (P) value by more than 20%. 2 Rather The indicator’s observed To each triple-win area, two core CSA-Res indicators are unsatisfactory value falls short of the target assigned. value between 1% and 20%. 3 Satisfactory The indicator’s observed value is equal to the APPLICATION indicator’s target value. The CSA-Res Index can be applied to measure the proj- 4 Exceeding The indicator’s observed ect’s performance after project completion, as well as dur- expectations value exceeds the target value ing project implementation. For the calculation, CSA-Res between 1% and 20%. indicators or similar rural development, agricultural, or 5 Highly The indicator’s observed climate change–related indicators that reflect CSA activi- exceeding value exceeds the target value ties can be used. For each indicator, we have suggested expectations by more than 20%. whether it is most suitable to measure one or all of the triple-win areas to measure productivity, resilience, or mitigation. The user is free to vary the assignment of P, the index, the users are recommended to use the R, or M that he or she considers most appropriate for the core CSA-Res indicators (see page 22). project. Thus, the CSA-Res Index method gives project 2. Target values are defined. For each indicator, teams the flexibility to customize the index and adjust it to a baseline value and a target value to be reached the specific context of their CSA intervention. This diver- at the end of the project, and for each fiscal year sity in indicators also implies that care must be exercised or other relevant time interval, are set. when comparing projects based on the index score, as the 3. The indicators are assigned to the CSA underlying indicators and their meaning may vary sig- triple-win areas. The chosen indicators are nificantly. However, the CSA-Res Index allows compari- assigned to the triple-win areas—productivity, son of the performance of one project over time to give resilience, and mitigation, thus indicating that the indications of which triple-win areas performed well over outputs or outcomes that are monitored contrib- time or which other areas could be strengthened. ute in particular to these specific CSA goals. For the set of CSA indicators, a default assignment has The set of CSA-Results indicator will be the basis for the been proposed (see table 3.4 and Technical Notes calculation of the CSA-Res Index, which provides stake- in appendix D). However this default assignment holders with an indication of how the respective pro- can be changed according to the project’s goals or ject has performed in reaching its performance targets in the CSA needs and multiple assignments of a single indica- triple-win areas—resilience, mitigation, and productivity—­ tor are possible. separately and jointly. To derive the index, the following 4. The indicators are scored. In the next step, steps are required: the indicators are scored according to whether they 1. The results framework is designed and the have reached the proposed target value, exceeded indicators are chosen. A project team designs it, or failed to reach it. More specifically, the follow- a results framework and chooses indicators to ing scoring rule is proposed: measure the Project Development Objective and We propose a threshold of 20 percent to deter- the projects’ intermediate results. Ideally, CSA mine whether an indicator has achieved a score of indicators are applied if suitable. For calculating 2 or 4. The scoring can take place at the end of Climate-Smart Agriculture Indicators 25 the project, or throughout project implementation limitations. Whereas a core set of CSA indicators is pro- whenever new M&E data are available. posed to calculate the index, users are given the flexibil- 5. The scores for each triple-win area are ity to select a range of additional indicators from the averaged. In the next step, for each triple-win list of CSA-Res indicators or other indicators related to area, P, R, M, the scores of the indicators that have agriculture, resilience, and climate change. Although this been assigned to the area in step 3 are averaged, enables the application of the index for a range of proj- yielding an overall score for the triple-win area. ects, it complicates comparing CSA-Res indices across Users are recommended to use the core CSA-Res projects as the underlying data and their meaning may indicators. This allows comparing in which area vary significantly. Thus, the focus of application should the project has achieved satisfactory or unsatisfac- be to compare the project’s progress over time. Similarly, tory results or results exceeding expectation, and users are flexible to choose a project-specific assignment thus where there is room for improvement. of P, R, M categories for their indicators, other than the 6. The average score over the triple-win area proposed categories in this text, which may make it more is calculated. In a last step, the average score difficult for the index to be compared across projects. over the triple win areas is calculated, providing To demonstrate the progress of the project in achiev- an overall estimate as to how well the project has ing its targets in the triple-win areas, it is recommended jointly achieved the CSA goals.6 that at least two indicators in each area be used, which are ideally different in meaning and not subcategories LIMITATIONS of one indicator. Finally, although the index can be There are some limitations to the CSA-Result indicators, assessed over the time of project implementation and which are discussed for each indicator in the Technical after project completion, and it can capture the project’s Notes in appendix D. Although the CSA-Results Index performance in the form of a number, it does not give presents a useful tool to measure a project’s performance action-oriented advice as to how the performance could toward achieving the CSA triple-win areas, it has some be improved. 6 A web page has been set up (http://csai.worldbank.org) that allows easy deri- vation of P, R, and M for CSA-Res and CSA-Tech indicators. 26 Agriculture Global Practice Discussion Paper CHAPTER FOUR KEY FINDINGS FOR THE CSA POLICY INDEX An assessment of the adoption of CSA policies was performed on 88 countries includ- ing 32 countries in Sub-Saharan Africa (SSA), 22 in Latin America and the Caribbean (LAC), 12 in Europe and Central Asia (ECA), 9 in East Asia and the Pacific, 8 coun- tries in the Middle East and North Africa, and 5 countries in South Asia. For each country, a composite CSA-Pol Index score was calculated using the weighted average of 31 subindicators. This report highlights the importance of adopting CSA policies to address food inse- curity under changing climatic conditions. A 1 percent increase in the CSA-Pol Index is predicted to lead to a 0.4 percent decline in the proportion of undernourished popu- lation (figure 4.1). Cereal yields increase 47 kilograms per hectare for every 1 percent increase in the CSA-Pol Index (figure 4.2). Appropriate policies, institutions, and sup- port services targeted at farmers can include measures aimed at building economic resilience at farm level by increasing productivity and income, enabling saving, and promoting diversification. A 1 percent increase in CSA-Pol Index is predicted to lead to a 0.08 decrease in coefficient of variance of cereal yield (figure 4.3). A 1 percent increase in the CSA-Pol Index is predicted to decrease GHG intensity of milk by 0.11 kg CO2-e/kg (figure 4.4). A 1 percent increase in CSA-Pol Index is also predicted to decrease GHG intensity of chicken by 0.11 kg CO2-e/kg (figure 4.5). GHG intensity of paddy rice will decrease by 0.02 kg CO2-e/kg (figure 4.6). Countries in the assessment are at varying stages of the adoption of policies to sup- port CSA implementation—the CSA-Pol Index ranged from 31 percent for Sudan to 87 percent for Chile (figure 4.7). CSA-Pol Index, readiness mechanisms, and services and infrastructure support scores increase with increasing level of income (figure 4.8). This suggests that national investments in services that support CSA such as agri- culture crop insurance, social safety nets, and market information systems may yield greater returns in terms of strengthening the country’s enabling environment for CSA than investing in policies or coordinating mechanisms. Climate-Smart Agriculture Indicators 27 FIGURE 4.1.  RELATIONSHIP BETWEEN FIGURE 4.4.  RELATIONSHIP BETWEEN CSA-POL INDEX AND CSA-POL INDEX AND GHG UNDERNOURISHMENT EMISSIONS INTENSITY OF (n = 50) MILK (n = 84) 35 Prevalence of undernourishment (%) 60 30 50 Kg CO2eq/Kg Milk 25 y = –0.11x + 10.9 40 R2 = 0.10 20 30 15 20 10 y = –0.4x + 44 R2 = 0.27 5 10 0 0 30 40 50 60 70 80 90 30 40 50 60 70 80 90 Aggregated policy index (%) Aggregated policy index (%) FIGURE 4.2.  RELATIONSHIP BETWEEN FIGURE 4.5.  RELATIONSHIP BETWEEN CSA-POL INDEX AND CEREAL CSA-POL INDEX AND GHG YIELD (n = 56) INTENSITY OF CHICKEN 8000 (n = 84) 7000 y = 47.0x – 289 50 Cereal yield kg/ha 6000 R2 = 0.22 45 5000 Kg CO2eq/Kg Chicken 40 4000 35 y = –0.11x + 10.2 R2 = 0.08 3000 30 2000 25 1000 20 15 0 30 40 50 60 70 80 90 10 Aggregated policy index (%) 5 0 Note: Cereal yield refers to the average yields (2010 to 2013) for wheat, rice, 30 40 50 60 70 80 90 maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Aggregated policy index (%) FIGURE 4.3.  RELATIONSHIP BETWEEN CSA- FIGURE 4.6.  RELATIONSHIP BETWEEN POL INDEX AND CEREAL YIELD CSA-POL INDEX AND GHG VARIANCE (n = 56) INTENSITY OF PADDY RICE 25 (n = 74) 5 Coefficient of variance 20 y = –0.08x + 14.3 R2 = 0.06 4.5 15 4 Kg CO2eq/Kg Rice 3.5 y = –0.02x + 2.2 R2 = 0.10 10 3 2.5 5 2 1.5 0 1 30 40 50 60 70 80 90 0.5 Aggregated policy index (%) 0 Note: Cereal yield variance refers to the coefficient of variance of yields from 30 40 50 60 70 80 90 2010 to 2013 expressed in percentage. Aggregated policy index (%) 28 Agriculture Global Practice Discussion Paper FIGURE 4.7.  CSA-POL INDEX FOR A SAMPLE FIGURE 4.8.  AVERAGE AGGREGATE OF COUNTRIES: TOP 15 SCORES FOR COUNTRIES SCORES; MIDDLE 15 SCORES; GROUPED BY INCOME ACROSS BOTTOM 15 SCORES FOUR CATEGORIES OF Aggregated policy index (%) Chile INDICATOR AGGREGATION. Czech Republic Upper middle income (per capita GNI $4,125 – $12,736; n = 25) Poland Mexico Lower middle income (per capita GNI $1,045 – $4,125; n = 31) Brazil Costa Rica Low income (per capita GNI <= $1,045; n = 22) India Colombia 80.0 China Ecuador 70.0 Nicaragua South Africa 60.0 Dominican Republic Uruguay 50.0 Score % El Salvador Morocco 40.0 Cambodia Pakistan 30.0 Hungary Mozambique 20.0 Niger Malawi 10.0 Senegal St. Lucia 0.0 Indonesia 1 2 3 4 Kenya Ethiopia Note: (1) CSA-Pol Index; (2) Indicators of theme “Readiness Mechanisms”; Vietnam Cameroon (3) Indicators of theme “Services and Infrastructure”; (4): Indicators of theme Burkina Faso “Coordination Mechanisms.” Russian Federation Sri Lanka Cote d'Ivoire Gabon Tunisia Congo, Dem. Rep. Haiti Lao PDR Yemen, Rep. Algeria Belarus TOP AND BOTTOM Congo, Rep. Equatorial Guinea Central African Republic PERFORMERS FOR THE Sudan 0 10 20 30 40 50 60 70 80 90 100 CSA POLICY INDEX »» Middle-income countries with strong agricultural export markets (Chile, Brazil, Mexico, and South Although the level of economic development in a country Africa) emerged as the highest performers for the appears to be a strong determinant of its ability to pro- CSA Policy Index. These markets are supported vide strong legal frameworks to support services and infra- by services and infrastructure such as market structure for CSA implementation, a commitment from information systems, agriculture crop insurance, the government—demonstrated through national climate warehouse receipts systems, and early warning change policies and strategies—is as important as services systems for weather and pest management that for creating an enabling environment for CSA. For exam- are critical for well-functioning markets and cre- ple, Madagascar emerged among the top performers in ate a strong enabling environment for CSA. The SSA. The country has built strong institutional frame- high performers also apply a collaborative multi- works through regional arrangements supported by the sectorial applied approach to addressing climate Indian Ocean Islands to integrate adaptation strategies change that is well integrated into national strate- and disaster risk response to climate change in national gies and policies. policies and other strategies. »» The lowest performers for the CSA Policy Index are primarily countries heavily reliant on oil-producing The bottom performers on the CSA Policy Index in our industries (Republic of Congo, Gabon, and ­ Russia). sample included countries whose economies rely heavily As a result, nonpetroleum-based sectors such as on petroleum revenues (Republic of Congo, Gabon, and agriculture remain critically underdeveloped (with Russia). In many cases, these countries also lacked NAPAs, the exception of Nigeria). The lack of diversifica- for example, to support CSA implementation. tion in the economy and underdevelopment of the Climate-Smart Agriculture Indicators 29 FIGURE 4.9. AVERAGE AGGREGATE SCORES figure  4.10). Through a combination of well-defined (­ FOR COUNTRIES GROUPED legal and institutional frameworks, strong political will (Mexico is the only country to have submitted five BY REGION ACROSS FOUR national communications to the United Nations Frame- CATEGORIES OF INDICATOR work Convention on Climate Change [UNFCCC]), AGGREGATION. and evidence of a multisectorial and interdisciplinary East Asia & Pacific (EAP; n = 9) Europe & Central Asia (ECA; n = 12) Latin America & Caribbean (LAC; n = 22) approach to addressing climate change that is well inte- Middle East & North Africa (MENA; n = 8) South Asia (SA; n = 5) grated in national policies and strategies, these countries Sub-Saharan Africa (SSA; n = 32) have created a strong, enabling environment for climate- 90.0 smart agriculture. 80.0 70.0 Chile is the highest performer in LAC. The agricultural 60.0 sector is identified as one of the priority lines for adapta- Score % 50.0 tion to climate change in the National Climate Change 40.0 30.0 Action Plan. Agricultural products accounts for a quarter 20.0 of export revenues in the Chilean economy. The export 10.0 markets are supported by services and infrastructure such 0.0 as market information systems and agriculture insurance 1 2 3 4 that have created an enabling environment for CSA. Note: (1) CSA-Pol Index; (2) Indicators of theme “Readiness Mechanisms”; (3) Indicators of theme “Services and Infrastructure”; (4): Indicators of theme Through multisectorial committees such as the Climate “Coordination mechanisms.” Change and Agriculture Council, composed of profes- sionals from the academic, private, and public sectors, the government has created an enabling environment for agricultural sector reflects weak institutional mech- coordination among different sectors and actors involved anism and enabling environment for CSA. in CSA. Figure 4.11 illustrates the specific CSA-Pol Index scores for Chile. DIFFERENCES IN CSA-POL INDEX AMONG REGIONAL GROUPINGS Mexico’s strong political will to address climate change Countries in the LAC region outperformed all of the is well integrated into its national policies and strat- other country groups on the CSA-Pol Index (figure 4.9). egies. The National Strategy for Climate Change Analysis of the top and bottom performers in this region includes as one of its pillars adaptation measures to reveals, among other things, that a strong commitment climate change in the agricultural sector. There is also from the government is also as important as services for an Inter-­Ministerial Commission on Climate Change creating an enabling environment for CSA. In the follow- responsible for coordinating and incorporating national ing sections, trends in index scores of countries in the LAC climate change strategies in sector-specific programs. and SSA regional groupings are analyzed with a view to The committee is composed of seven ministries, includ- understanding the factors that led to some countries per- ing the Ministry of Agriculture, and works with vari- forming well and others poorly. We selected countries in ous stakeholders including civil society and the private the LAC and SSA regional groupings because each group sector to address climate change. In addition, Mexico accounted for a large diversity of countries, from which has well-developed agricultural export markets that are several lessons could be extracted. supported by services and infrastructure such as mar- ket information systems, warehouse receipts systems for TOP POLICY INDICES IN LATIN AMERICA grain markets, and agriculture insurance schemes that AND THE CARIBBEAN also have created an enabling environment for CSA. Chile, Mexico, and Brazil are among the highest per- Figure 4.12 illustrates the specific CSA-Pol Index scores formers in the LAC region for the CSA Policy Index for Mexico. 30 Agriculture Global Practice Discussion Paper FIGURE 4.10.  CSA-POL SCORES FOR FIGURE 4.12.  SPECIFIC CSA-POL INDEX COUNTRIES IN LATIN SCORES—MEXICO Ag. adaptation policy AMERICA AND THE 1 Multisectoral coord. Ag. mitigation policy CARIBBEAN Disaster risk mgt. 0.8 Economic readiness Aggregated policy index (%) coord. 0.6 Chile 0.4 Mexico Ag. capacity 0.2 Governance readiness Brazil Costa Rica 0 Colombia Ag. risk mgt. sys. Social readiness Ecuador Nicaragua Dominican Republic GHG inventory sys. Extension services Uruguay El Salvador Social safety nets Peru Ag. R&D Paraguay Rural access index Bolivia Argentina Guatemala Honduras Grenada Panama Guyana FIGURE 4.13.  SPECIFIC CSA-POL SCORES— St. Lucia Venezuela, RB BRAZIL Haiti Ag. adaptation policy 0 10 20 30 40 50 60 70 80 90 100 1 Multisectoral coord. Ag. mitigation policy 0.8 Disaster risk mgt. Economic readiness coord. 0.6 0.4 Ag. capacity 0.2 Governance readiness FIGURE 4.11.  CSA-POL INDEX SCORES— 0 CHILE Ag. risk mgt. sys. Social readiness Ag. adaptation policy 1 GHG inventory sys. Extension services Multisectoral coord. Ag. mitigation policy Disaster risk mgt. 0.8 Social safety nets Ag. R&D coord. 0.6 Economic readiness Rural access index 0.4 Ag. capacity 0.2 Governance readiness 0 Ag. risk mgt. sys. Social readiness GHG inventory sys. institutions. Figure 4.13 illustrates the specific CSA-Pol Extension services Index scores for Brazil. Social safety nets Ag. R&D Rural access index LOWEST POLICY INDICES IN LATIN AMERICA AND CARIBBEAN REGION Brazil has created a strong institutional framework for Haiti, Venezuela, and St. Lucia are the bottom three per- CSA that is backed by a high level of investment in formers in LAC for the CSA Policy Index (figure 4.10). crop research and farming systems adapted to climate The countries have expressed commitment to adapta- change. It has also declared a number of commit- tion and mitigation to climate change in the agricultural ments to enhance land and water management and sector; however, beyond intent there is no evidence of carbon sequestration through its Reducing Emissions well-defined strategies or mechanisms to support these from Deforestation and Forest Degradation programs. goals. Similarly, the agricultural zoning of climate risk (Zona- mento Agrícola de Risco Climatico) is used as a policy Haiti scored lowest in readiness mechanism (27 percent) instrument to address climate risk and disasters in the in support of CSA. The National Agriculture Policy agricultural sector. These commitments are also backed (2010) and Agriculture Investment Plan (2010) place by strong services and infrastructure to support CSA, a greater emphasis on rebuilding the country’s irriga- including weather monitoring and forecasting, R&D, tion infrastructure and developing agricultural mar- and collaboration among multiple stakeholders and kets through rural credit and postharvest management Climate-Smart Agriculture Indicators 31 FIGURE 4.14.  SPECIFIC CSA-POL INDEX FIGURE 4.16.  SPECIFIC CSA-POL INDEX SCORES—HAITI SCORES—ST. LUCIA Ag. adaptation policy Ag. adaptation policy Multisectoral coord. 1 Ag. mitigation policy Multisectoral coord. 1 Ag. mitigation policy 0.8 0.8 Disaster risk mgt. Disaster risk mgt. Economic readiness 0.6 Economic readiness 0.6 coord. coord. 0.4 0.4 Ag. capacity 0.2 Governance readiness Ag. capacity 0.2 Governance readiness 0 0 Ag. risk mgt. sys. Social readiness Ag. risk mgt. sys. Social readiness GHG inventory sys. Extension services GHG inventory sys. Extension services Social safety nets Ag. R&D Social safety nets Ag. R&D Rural access index Rural access index FIGURE 4.15.  SPECIFIC CSA-POL INDEX climate change. Like its oil-producing counterparts in SCORES—VENEZUELA SSA, Venezuela’s dependence on oil revenues has caused Ag. adaptation policy other sectors of the economy such as the agricultural sec- 1 Multisectoral coord. 0.8 Ag. mitigation policy tor to remain undeveloped, which has accounted for a Disaster risk mgt. coord. 0.6 Economic readiness weak institutional mechanism and enabling environment 0.4 Ag. capacity Governance readiness for CSA. Venezuela scored a zero in multisectorial coor- 0.2 0 dination (figure 4.15). Ag. risk mgt. sys. Social readiness GHG inventory sys. Extension services St. Lucia is heavily dependent on banana production Social safety nets Ag. R&D for its economy and there is room for creating a stronger Rural access index enabling environment to support CSA. However, beyond intent, there are no well-defined strategies and actions plans for CSA. Despite its low aggregate score, St. Lucia received a high (74 percent) score in services and infrastructure including an agriculture research but there is minimal focus on defining strategies for program focused on climate change, early warning addressing the country’s vulnerability to climate change. ­ systems for weather and climate conditions, and pres- However, the country has strengthened services and ence of agricultural risk insurance for banana farmers. infrastructure for disaster risk management in recent St. Lucia scored a zero in agricultural mitigation policy years through the establishment of early warning sys- (figure 4.16). tems for pests and climate, and defined clear guidelines for agricultural crop insurance. Haiti scored a zero in agricultural R&D (figure 4.14). TOP POLICY INDICES IN SUB-SAHARAN AFRICA There exists ample room for improvement for strength- South Africa (77 percent) and Tanzania (76 percent) ening coordination mechanisms among different sectors emerged as the top two performers for the CSA Policy involved in CSA in Venezuela. The agriculture policy Index, whereas Rwanda placed third at 73 percent lacks a clear focus on climate change and there is no multi- (figure 4.17). sectorial committee for enabling implementation of CSA strategies. Generally, there does not appear to be a strong South Africa has built a strong institutional framework political will to address CSA; the country has submitted through the National Climate Change Response Policy only one national communication to the UNFCCC and (2011) and National Development Plan (NDP) 2030 to there is no national adaptation plan of action to address support CSA. For example, the NDP Vision 30 outlines 32 Agriculture Global Practice Discussion Paper FIGURE 4.17.  CSA POL-INDEX FOR FIGURE 4.19.  SPECIFIC CSA-POL INDEX COUNTRIES IN SUB-SAHARAN SCORES—TANZANIA Ag. adaptation policy AFRICA Multisectoral coord. 1 Ag. mitigation policy Aggregated policy index (%) 0.8 South Africa Disaster risk mgt. Economic readiness Tanzania coord. 0.6 Rwanda 0.4 Zambia Ag. capacity Governance readiness Nigeria 0.2 Madagascar 0 Ghana Mali Ag. risk mgt. sys. Social readiness Benin Mozambique Niger GHG inventory sys. Extension services Malawi Senegal Social safety nets Ag. R&D Kenya Ethiopia Rural access index Cameroon Burkina Faso Zimbabwe Botswana Togo Comoros Burundi Uganda FIGURE 4.20.  SPECIFIC CSA-POL INDEX Guinea Chad SCORES—RWANDA Cote d’Ivoire Gabon Ag. adaptation policy Congo, Dem. Rep. Multisectoral coord. 1 Ag. mitigation policy Congo, Rep. 0.8 Equatorial Guinea Disaster risk mgt. 0.6 Economic readiness Central African Republic coord. Sudan 0.4 0 10 20 30 40 50 60 70 80 90 100 Ag. capacity 0.2 Governance readiness 0 Ag. risk mgt. sys. Social readiness FIGURE 4.18.  SPECIFIC CSA-POL INDEX GHG inventory sys. Extension services Social safety nets SCORES—SOUTH AFRICA Ag. R&D Rural access index Ag. adaptation policy Multisectoral coord. 1 Ag. mitigation policy Disaster risk mgt. 0.8 0.6 Economic readiness coord. 0.4 supporting CSA. Figure 4.18 illustrates the specific CSA- Ag. capacity 0.2 Governance readiness 0 Pol Index scores for South Africa. Ag. risk mgt. sys. Social readiness Tanzania’s high score is driven primarily by its high sub- GHG inventory sys. Extension services score in services and infrastructure (78 percent) and coor- Social safety nets Ag. R&D dination mechanisms (100 percent). A commitment to Rural access index addressing adaptation and mitigation to climate change in the agricultural sector is reflected in Tanzania’s NAPA and National Climate Change Strategy. Beyond these two the government vision for low-carbon development and a plans, the National Strategy for Growth and Reduction resilient economy by 2030. The policy includes a mandate of Poverty (MKUKUTA in Swahili) also incorporates for building an evidence-based M&E framework to pro- climate change as a crosscutting issue. A multisectorial vide up-to-date emissions data and establishing a system approach is used to support CSA and is facilitated by the for reporting implementation of adaptation measures at NCCTC and NCCSC. Tanzania scored 100 percent for the sector level. The country has also invested in strong seven indicators (figure 4.19). research capacity backed by legislation to support research on climate change. This has fostered strong coordination Rwanda’s commitment to CSA is reflected in the across different sectors involved in CSA and earned SA a National Strategy for Climate Change and Low Car- perfect score (100 percent) in coordination mechanisms bon Development (2011). The strategy includes a Climate-Smart Agriculture Indicators 33 FIGURE 4.21.  SPECIFIC CSA-POL INDEX FIGURE 4.22.  SPECIFIC CSA-POL INDEX SCORES—SUDAN SCORES—CENTRAL AFRICAN Ag. adaptation policy 1 REPUBLIC Multisectoral coord. Ag. mitigation policy 0.8 Ag. adaptation policy Disaster risk mgt. Economic readiness Multisectoral coord. 1 Ag. mitigation policy coord. 0.6 0.8 0.4 Disaster risk mgt. Economic readiness Ag. capacity Governance readiness coord. 0.6 0.2 0.4 0 Ag. capacity Governance readiness 0.2 Ag. risk mgt. sys. Social readiness 0 Ag. risk mgt. sys. Social readiness GHG inventory sys. Extension services Social safety nets Ag. R&D GHG inventory sys. Extension services Rural access index Social safety nets Ag. R&D Rural access index monitoring framework for its mitigation and adaptation Sudan has expressed commitment to addressing adap- programs and involves various ministries including the tation to climate change through its NAPA; however, Ministry of Agriculture and Animal Resources, Minis- there are no well-defined strategies to address this goal. try of Infrastructure, municipal authorities, and so on. The country also lacks services and infrastructure to The country has also established several public-private support adaptation strategies in the agricultural sector. partnerships to develop services and infrastructure such The county is, however, taking steps to create a stronger as crop insurance and collateral management systems enabling environment. For example, through the Agri- that have the potential to create a strong enabling envi- cultural Revival Program, launched in 2008, the coun- ronment for CSA. Rwanda scored top scores in agricul- try aims to address structural weaknesses in the sector tural adaptation policy, agricultural mitigation policy, and many of the priority areas of intervention coincide agricultural R&D, social safety nets, national GHG with the NAPA objectives. There are also some services inventory system, and disaster risk management coordi- in place with the potential to create a strong enabling nation (figure 4.20). environment for CSA such as the Sudanese Food & Agri- culture Market Information System, which collects and disseminates crop, livestock, and horticultural and animal BOTTOM POLICY INDICES IN product prices to market participants on a weekly basis. SUB-SAHARAN AFRICA As depicted in fi­ gure 4.21, Sudan scored exceptionally Sudan (31 percent), Central African Republic (36 percent), low in agricultural mitigation policy, rural access index, and Equatorial Guinea (37 percent) are the lowest per- and social safety nets. formers in SSA for the CSA Policy Index. The countries were also assigned a high uncertainty rating in the report- Central African Republic does not have a national adap- ing of the policy score given the high observed frequency tation plan of action for climate change but has submitted of no data that could be gathered from secondary desk two national communications to the UNFCCC (2003 and research; however, important lessons and observations 2015). The country lacks legislation or policy on disaster emerged in the reporting of the policy scores. The Repub- risk reduction in the agricultural sector, but has an emer- lic of Congo and Gabon are categorized as lower- and gency response project for the food crisis and relaunch of upper-middle-income countries, respectively, according the agricultural sector. The country has not committed to to the World Bank income classification. The countries adding climate change in agricultural R&D given its cur- are among the top five oil-producing countries in the rent level of agricultural development. Central African region with economies heavily dependent on oil revenues. Republic scored zero in two indicators, agricultural R&D Nonpetroleum-based sectors, such agriculture, remain ­ and social safety nets (figure 4.22). Data were not available critically underdeveloped. for a rural access index. 34 Agriculture Global Practice Discussion Paper FIGURE 4.23.  SPECIFIC CSA-POL INDEX FIGURE 4.24.  AVERAGE AGGREGATE SCORES—EQUATORIAL SCORES FOR COUNTRIES GUINEA GROUPED BY REGION Ag. adaptation policy 1 ACROSS FOUR INDICATORS: Multisectoral coord. Ag. mitigation policy Disaster risk mgt. 0.8 Economic readiness ECONOMIC READINESS, coord. 0.6 0.4 GOVERNANCE READINESS, Ag. capacity Governance readiness 0.2 0 SOCIAL READINESS, AND Ag. risk mgt. sys. Social readiness ADAPTIVE CAPACITY East Asia & Pacific (EAP; n = 9) Europe & Central Asia (ECA; n = 12) GHG inventory sys. Extension services Latin America & Caribbean (LAC; n = 22) Social safety nets Ag. R&D Middle East & North Africa (MENA; n = 8) South Asia (SA; n = 5) Rural access index Sub-Saharan Africa (SSA; n = 32) 70 60 Equatorial Guinea has National Adaptation Plan Actions 50 in Ministry of Environment and Fisheries. It states the 40 Score % mechanisms to implement and monitor activities to address adaptation and mitigation to climate change in the agri- 30 cultural sector. The NAPA also expresses the commitment 20 to address climate change research in particular related to fisheries, environment, and conservation. However, accord- 10 ing to current documents and information, there are no 0 strategies or policy plans on social safety nets and agricul- Economic Governance Social Adaptive readiness readiness readiness capacity tural risk management systems. Equatorial Guinea scored zeros in four indicators: extension services, national GHG inventory systems, agricultural risk management systems, and disaster risk management coordination (figure 4.23). indicators with an average score of 63 percent for Social readiness and Adaptive capacity, 58 percent for Economic Of the 14 policy indicators, the average values of Eco- readiness, and 49 percent for Governance readiness. Eco- nomic readiness (48 percent), Adaptive capacity (42 nomic readiness (40 percent), Adaptive capacity (26 per- percent), Governance readiness (40 percent), and Social cent), and Social readiness (22 percent) are the lowest for readiness (34 percent) are lowest for the 88 countries in the SSA, whereas MENA has the lowest Governance readi- sample. The ECA region ranks the highest for these four ness (33 percent) (see figure 4.24). Climate-Smart Agriculture Indicators 35 CHAPTER FIVE TESTING OF PROJECTS WITH THE CSA TECHNOLOGY INDEX AND THE CSA RESULTS INDEX The CSA-Tech Index and the CSA-Res Index measure a project’s achievements in the CSA triple-win areas. Each indicator in the CSA-Tech and CSA-Res Indices are aligned to one, two, or all of the triple-win P, R, and M goals. To show how the CSA- Tech and CSA-Res Indices cay be applied to projects, the report selected and tested projects from five countries across the world (figure 5.1). These projects were selected for their diverse representation in location and project objectives. Based on the testing results, case studies were developed to determine the appropriate climate-smart technologies for the proposed project. The results from the index testing are described in the following sections. TESTING OF PROJECTS USING THE CSA-TECH INDEX The testing of the CSA-Tech Index has yielded the following insights: 1. Monitoring a CSA-Tech indicator involves establishment costs with benefits occurring at some later time. 2. To calculate the value of a CSA-Tech indicator, it is necessary to determine a short list of optimal technologies in the proposed context. 3. There is likely to be wide variation between the values of different CSA indica- tors in a given situation, and a variation in the value of a given indicator in dif- ferent situations. Each must be assessed separately in different farming systems. 4. In many cases, the costs of using the CSA-Tech Index would fall over time as uncertainty is reduced. 5. The gross value of the CSA-Tech Index can never be negative. At worst, its value would be zero if no values exist. 6. The greater the current level of uncertainty about a variable, the greater is the value of monitoring, as long as monitoring does lead to reductions in uncertainty. Climate-Smart Agriculture Indicators 37 FIGURE 5.1.  LOCATION OF SELECTED PROJECTS FOR TESTING Projects in China China integrated modern Projects in Armenia agriculture development project Second community agriculture resource The irrigated agriculture management competitiveness project intensification project iii Natural resources management and poverty reduction project Projects in Bhutan Land management project Sustainable land management project Projects in Burundi Projects in Brazil Agricultural rehabilitation and Caatinga conservation and management—mata sustainable land management project branca Rio de janeiro sustainable integrated ecosystem management in production landscapes of the North-Northwestern Fluminense (GEF) project CASE STUDY 1: ARMENIA—SECOND Productivity has grown substantially in the agricultural COMMUNITY AGRICULTURE RESOURCE sector in the past decade. The Crop Production Index MANAGEMENT AND COMPETITIVENESS more than doubled from 2002 to 2009, although there PROJECT (P133705) was a substantial drop in 2010 because of inclement Project context weather conditions. During the same period, the Live- Agriculture remains vital to the Armenian economy. In stock Production Index increased by about 60 percent. 2012, including agro-processing, it accounted for about Crop production typically accounts for about two- 23 percent of GDP, 17 percent of export earnings, and thirds of the gross agricultural output, whereas livestock about 44 percent of employment. Rapid economic accounts for one-third. About 60 percent of the agricul- growth over the past decade has generated new oppor- tural land in Armenia is pasture and grassland. Livestock tunities for the agricultural sector, which has grown by production is the most important economic activity in the more than 6 percent annually since 1997 despite the country’s mountainous areas. Productivity increases have downturn in 2009–10. Exports of agricultural products been supported by increased access to inputs, finance have doubled since 2005, mostly beverages and to a lesser (including some foreign investment capital), market link- extent fruit and vegetable products. A significant but pro- ages, and by the improving knowledge and skills of pro- portionally small increase in the export of live animals ducers. Nevertheless, yields are far from their potential, was seen in 2011. However, the sector has been unable to with cereals averaging only 2.5 tons per hectare and cow capitalize fully on the opportunities associated with eco- milk yields approximately 2,000 liters per head based nomic growth and expanding consumer demand for agri- on official statistics, although these figures are substan- cultural products. As a result, much of this demand has tial improvements over the 1990s figures of 2 tons per been met by a substantial increase in imported products, hectare and 1,400 liters per head, respectively. Livestock which have outstripped exports and led to an increasing productivity is constrained mainly by unmanaged and gap between imports and exports. Overall, Armenia is unsustainable use of pasture resources, with severe over- a net importer of agricultural products with imports of grazing and degeneration of nearby pasture areas and US$700 million in 2011 compared with exports of about underutilization of remote pasture areas, poor quality US$230 million. and shortage of winter fodder, animal health problems, 38 Agriculture Global Practice Discussion Paper and poor genetic resources. Livestock productivity could FIGURE 5.2.  ARMENIA’S CSA-TECH P, R, M be increased by 40 percent with improved animal hus- SCORES bandry, feeding, and veterinary care, whereas crop yield P 1 increases of 60 percent would be feasible in the medium 0.8 term, with better varieties and improved management, 0.6 including soil fertility. 0.4 0.2 Agriculture in Armenia is dominated by smallholders, 0 with some 335,000 households with an average landhold- ing of about 1.4 hectares and a generally diversified pro- M R duction system involving both crops and livestock. Only Threshold Actual score a relatively small proportion can be considered truly commercial, and many farmers, especially those in more remote areas, are among the most vulnerable with about one-third still living in poverty and in some of the regions CASE STUDY 2: BURUNDI— this figure reaches as high as 46 percent. A shift toward AGRICULTURAL REHABILITATION AND increased commercialization in the sector has been tak- SUSTAINABLE LAND MANAGEMENT ing place in recent years. Some farmers (approximately Project context 15 percent) now cultivate leased land, although a third Agriculture is the mainstay of the economy, employ- of farmers do not cultivate all their land, mainly because ing more than 90 percent of the active population and of poor land quality, lack of water, or distance from the accounting for 50 percent of GDP and more than 80 per- farm. New agro-processors and small rural businesses are cent of export earnings. Most agricultural production is appearing, an increasing number of contractual arrange- subsistence oriented, with the exception of coffee, tea, ments between processors and producers are in place, rice, sugar, and cotton, which are oriented toward export and producer associations and cooperatives are helping markets. Traditionally, Burundi has been self-sufficient in to consolidate production and markets. Nevertheless, the food production, but during the past decade production links between the food-processing industry and agricul- has not kept pace with population growth. The low pro- tural producers remain weak, and many rural enterprises ductivity is attributable to declining soil fertility, low use of lack technology and know-how that could improve their modern inputs, and adverse incentives for investments in competitiveness. the state-controlled cash crop sector. Together, these had already set in motion a decline in yields before the politi- cal crisis in the early 1990s. CSA-Tech testing The proposed project should (a) extend the coverage Land fragmentation has not been compensated by suffi- of the pasture-based livestock system; (b) support the cient increases in agricultural productivity. Agricultural development of selected value chains important to techniques in Burundi remain extremely basic, using Armenia by providing targeted subproject investments handheld tools and few modern inputs. Fertilizer use is to help strengthen links between producers and proces- very low, and with farm households cultivating on aver- sors, promote food safety, and support processing and age only 0.7 hectare, the country has reached the limit marketing; and (c) increase the capacity of public sec- of traditional land cultivation and has achieved little or tor institutions that can support improved market access no economic diversification. Pressure on the environment and selected value chain development (see figure 5.2 has reached a critical point and requires urgent attention. and table 5.1). Intensive demographic pressure has led to the utilization of marginal land, the shortening of fallow periods, and the conversion of pasture and natural forest into cropland. Climate-Smart Agriculture Indicators 39 TABLE 5.1.  RESULTS FROM THE ARMENIA SECOND COMMUNITY AGRICULTURE RESOURCE MANAGEMENT COMPETITIVENESS PROJECT Raw Target Final Theme Subject Indicator Indicator Description Type Score Score R P M Score Productivity Livestock Resource The technology improves Likert (1–5) 4 3 5 System Management livestock resource management in comparison with current interventions in similar farming systems. Resilience Self- Local Market The technology will foster local Likert (1–5) 4 3 5 organization Networks and regional production and supply chains. Resilience Robustness Income and The technology will increase Likert (1–5) 3 3 3 Food Security the stability of agricultural production needed to help producers meet their own basic food security and income needs. Resilience Self- Cooperation The technology will facilitate Likert (1–5) 2 3 1 organization and Networks cooperation and networking among producers. Mitigation Mitigation Emissions The technology meets emissions Likert (1–5) 1 3 1 Benefits Intensity intensity targets. Mitigation Mitigation Sequesters The technology sequesters Likert (1–5) 1 3 1 Benefits Carbon carbon in comparison with current interventions in similar farming systems. 3 5 1 3.00 A stock of existing technological innovations can be The government is convinced that the private sector must adopted by smallhold farmers to generate productiv- be the engine that drives economic growth. It intends to ity increases. However, agricultural research needs to be disengage from agricultural production and privatize state more closely geared to addressing farmers’ priorities and enterprises. In conjunction with the implementation of concerns. The ongoing generation of new technological the poverty-reduction strategy, the government has called solutions requires a dynamic agricultural research sys- on professional organizations and the private sector to tem with strong capacity to orient, select, and program assume a greater role in the conceptualization and man- research projects. agement of development programs and strategies. Natural resource degradation must be addressed. Environ- mental challenges have reached a critical turning point in Testing results Burundi because of high (2.9 percent) annual population The desk testing for the Burundi project revealed that growth, small average plot sizes, weakening soil fertility, Productivity (3.8) and Resilience (5) are the key areas the shortening fallow periods, and soil erosion. Unless inter- project task team needs to focus on with Mitigation (0) ventions are rapidly implemented, these environmental being less of a concern (table 5.2). This result only reflects threats may very well have a profoundly negative effect the data available at the project appraisal stage and is on economic growth, and hamper any poverty reduction not indicative of any data that may be available during achieved by transitional support lending. project implementation. The spider diagram in figure 5.3 40 Agriculture Global Practice Discussion Paper RESULTS FROM THE BURUNDI AGRICULTURAL REHABILITATION AND SUSTAINABLE LAND TABLE 5.2.  MANAGEMENT PRACTICE Raw Target Final Theme Subject Indicator Indicator Description Type Score Score R P M Score Productivity Water Use Irrigated The technology increases the share of % change 10 10 3 Agricultural irrigated agricultural land (hectare) because from baseline Land of the technology (%). Climate-Smart Agriculture Indicators Productivity Water Use Water The technology reduces water withdrawal % change 7 5 5 Withdrawal (liter/day) for agriculture use as a share of from baseline for Agriculture total water withdrawal (%). Productivity Crop System Crop Yield (% The technology leads to an increase in % change 15 15 3 increase) yields of the producers (%). from baseline Productivity Livestock System Resource The technology improves livestock resource Likert (1–5) 4 3 5 Management management in comparison with current interventions in similar farming systems. Productivity Livestock System Feed The technology improves feed production Likert (1–5) 3 3 3 Production in comparison with current interventions in Technologies similar farming systems. Resilience Robustness Human The technology will improve the human Likert (1–5) 4 3 5 Capital capital (technical skill levels) of producers in the target area. Resilience Robustness Site-Specific The technology will involve the Likert (1–5) 4 3 5 Knowledge incorporation of site-specific knowledge in its application. Resilience Self-organization Cooperation The technology will facilitate cooperation Likert (1–5) 4 3 5 and Networks and networking among producers. Resilience Self-organization Local Market The technology will foster local and regional Likert (1–5) 4 3 5 Networks production and supply chains. Mitigation Mitigation Emissions The technology meets emissions intensity Likert (1–5) 2 3 1 Benefits Intensity targets. Mitigation Mitigation Sequesters The technology sequesters carbon in Likert (1–5) 2 3 1 Benefits Carbon comparison with current interventions in similar farming systems. 5 3.8 1 3.27 41 FIGURE 5.3.  BURUNDI’S CSA-TECH P, R, M with an outstanding range of biodiversity and ecosystems SCORES concentrated in a small area. Bhutan’s record of good P governance and long-standing commitment to environ- 1 0.8 mental sustainability are widely recognized. Since 1974, 0.6 the country’s forest policy has operated under a royal 0.4 mandate stipulating that at least 60 percent of Bhutanese 0.2 territory must remain forested in perpetuity. Commercial 0 logging was nationalized in 1978 in response to concerns about overexploitation, and the timber industry remains tightly regulated. One-quarter of the country’s area has M R been set aside as protected (although not all sites have yet Threshold Actual score come under management plans). A recent “Gift to the Earth” has offered another 9 percent for wildlife corridors to prevent habitat fragmentation. shows the relationship between the triple-win priorities for the Burundi project. Notwithstanding its focus on environmental sustainabil- ity, Bhutan is facing “emerging ecological pressures from rapid The project should promote sustainable land use by seek- urbanization and development,” which pose an increasingly ing options that yield increasing returns from environ- severe threat to the natural environment and which is not mentally sustainable approaches (including integrated adequately addressed by present approaches and institu- pest and nutrient management), to proactively support tions (Kinzang Dorji 2002). Population density per square improved natural resource use (wetland and dry land kilometer of arable land has reached 520, nearly equal to resource use planning protection areas and buffer zones), the level found in South Asia as a whole, more than one- and to provide incentives to smallholders to use land sus- third higher than Sub-Saharan Africa, and double the tainably and protect ecosystem services. level of Latin America and the Caribbean. Proposed technologies Bhutan’s urban growth rate of 6.7 percent has had to Investments in the proposed project should include pro- be accommodated on forested slopes, scarce agricultural ductive infrastructure facilities, including support for (i) land, and wetlands. With arable land accounting for less installation of agricultural production-related infrastruc- than 8 percent of its land area, agriculture is faced with tures such as small-scale water-management schemes (for limited productive land to help feed a growing population. example, small irrigation schemes) and small dams or any Erosion is increasingly evident as farming and horticul- other water resource management facilities; (ii) improve- ture, as well as urban and industrial needs, exhaust flatland ment of small-scale agro-processing infrastructures and areas and shift on to steeper slopes. This is exacerbated by investments for existing and new agricultural and livestock deforestation on steep slopes, geologically unstable soils, products, especially for nontraditional export crops such and intense monsoon rains. Land degradation is having as fruits, flowers, vegetables, essential oils, sugar, rice, and measurable impacts; with 10 percent of agricultural land palm oil; and (iii) off-farm income-generating activities now affected by water erosion, urban settlements such supporting agriculture, such as workshops for repairing/ as Pemagatshel are slipping down the unstable slopes on manufacturing agricultural tools and small equipment. which they were sited, rural households in Trashigang Dzongkhag have had to be relocated to safer areas fol- lowing landslides and ravine formation, local and sea- CASE STUDY 3: BHUTAN—LAND MANAGEMENT PROJECT sonal water shortages are becoming more frequent, and there is evidence of increasing sediment loads in Bhutan’s Project context extensive river system. The latter is a threat to the rap- Bhutan represents a key environmental asset in the eco- idly growing hydropower industry, which needs a reliable logically sensitive Eastern Himalayan ecological region, 42 Agriculture Global Practice Discussion Paper FIGURE 5.4.  BHUTAN’S CSA-TECH P, R, M measures, terracing, forest and rangeland regeneration, SCORES reforestation, and so on, where necessary. P 1 0.8 CASE STUDY 4: BRAZIL—CAATINGA 0.6 CONSERVATION AND MANAGEMENT— 0.4 MATA BRANCA 0.2 Project context 0 In the subequatorial zone, between the Amazon Forest and the Atlantic Forest, is the Caatinga of the Brazilian M R Northeast. The word “Caatinga” originates from the Tupi Threshold Actual score indigenous language, meaning mata branca, or “white for- est” (caa: forest; tinga: white, open). The Caatinga is the largest dry forest in South America and is one of the richest dry forests in the world. Comprising an area of approxi- water supply to sustain much-needed revenue that cur- mately 800,000 square kilometers, it covers approximately rently underwrites some 40 percent of Bhutan’s develop- 11 percent of the national territory, extending throughout ment budget. the states of Piauí, Ceará, Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, Bahia, and Minas Gerais. CSA-Tech testing The climate is semi-arid, with average annual tempera- Based on the project context, the chosen technologies tures between 27°C and 29°C, and with pluviometer should help both to prevent and reverse land degrada- averages less than 800 millimeters. Rainfall is irregular in tion and to mainstream sustainable land management temporal and spatial distribution; rivers are intermittent; into its development-planning framework. The technolo- and soils, situated over crystalline rocks, are shallow, mak- gies should also help the Bhutan government to protect ing even superficial drainage a serious problem. its valuable forests and biodiversity, contribute to sustain- The 1977–79 drought resulted in widespread food scar- ability of agricultural productivity, and help improve live- city, the death of an estimated 500,000 people (4 per- lihoods and well-being of its people. cent of the Brazilian population at the time), and the The results (figure 5.4 and table 5.3) show that the project out-­migration of 3 million others from the region. More will need to finance physical investments at the farm and recently, the drought of 1979–83 affected 18 million community levels, which might include forest conserva- people; almost 80  percent of crop yields were lost in tion measures, terracing, forest and rangeland regenera- some parts of the Northeast, and the government spent tion, reforestation, and so on, where necessary. approximately US$1.8 billion in emergency programs. Historically, the periodic droughts, the erratic character of the rainfall, soil limitations, and other environmental Proposed technologies constraints did not allow the establishment of intensive The project should finance a range of activities includ- agriculture, but stimulated grazing animal production. ing capacity building for community decision making and Presently, about 19 percent of the cattle herd, 50 percent planning, training of extension staff to plan and imple- of the sheep herd, and 90 percent of the goat herd in ment SLM activities in a multisectoral manner, invest- Brazil are raised in the Caatinga. The system is predomi- ments at the community and farm levels to strengthen nantly extensive, overgrazing is the dominant factor, and the adoption of SLM practices, monitoring and evalu- production indices are the lowest in the country. ation to validate SLM investments, and national- and regional-level workshops to discuss results and scaling-up In the past two decades, desertification has advanced implementation. Physical investments at the farm and quickly, caused by the removal of vegetation through char- community levels might include vegetative conservation coal production, overfarming, overgrazing, soil erosion, Climate-Smart Agriculture Indicators 43 44 RESULTS FROM THE BHUTAN LAND MANAGEMENT PRACTICE TABLE 5.3.  Raw Target Final Theme Subject Indicator Indicator Description Type Score Score R P M Score Resilience Robustness Human Capital The technology will improve the Likert (1–5) 4 3 5 human capital (technical skill levels) of producers in the target area. Resilience Robustness Site-Specific The technology will involve the Likert (1–5) 5 3 5 Knowledge incorporation of site-specific knowledge in its application. Resilience Self-organization Cooperation The technology will facilitate Likert (1–5) 4 3 5 and Networks cooperation and networking among producers. Resilience Self-organization Feedback from The intervention will provide Likert (1–5) 5 3 5 Extension opportunities for feedback from Workers extension workers. Productivity Crop System Crop Yield The technology leads to an increase in % change 8 10 2 (% increase) yields of the producers (%). from baseline Productivity Crop System Enhances The technology enhances biodiversity Likert (1–5) 3 3 3 Biodiversity of the farming landscape in comparison with current interventions in similar farming systems. Mitigation Mitigation Emissions The technology meets emissions Likert (1–5) 4 3 5 Benefits Intensity intensity targets. Mitigation Mitigation Sequesters The technology sequesters carbon in Likert (1–5) 4 3 5 Benefits Carbon comparison with current interventions in similar farming systems. 5 2.5 5 4.17 Agriculture Global Practice Discussion Paper and slash-and-burn practices by smallholder farmers FIGURE 5.5.  BRAZIL’S CSA-TECH P, R, M and ranchers. Deforestation and unsustainable irrigation SCORES practices have added to the salinization of the soils and P 1 increased the incidence of drought. Desertification has 0.8 resulted in disruptions of water flows and poor quality of 0.6 water sources, which in turn affects the health of human 0.4 and animal populations. Rural poverty is deep, with the 0.2 poor surviving through short-cycle types of subsistence 0 farming, animal breeding in extensive systems, extrac- tive activities (wood and nontimber products), temporary M R farm employment, and seasonal migration to urban areas. In addition, less than 1 percent of the Caatinga biome is Threshold Actual score protected, and of the few established conservation units, many are inoperative due to lack of consolidation. 10 percent and more than 500 million people have been lifted out of poverty. To sustain this rapid pace of develop- CSA-Tech testing ment, China still has to address a number of challenges, This project should support investments in the following including (a) maintaining high growth rates in the face of a areas: (a) rehabilitation of degraded areas; (b) conserva- complex external environment still reeling from the global tion and sustainable use of biodiversity; (c) water and economic crisis; (b) managing the resource demands and land resources management; (d) development of sustain- the environmental consequences of rapid growth; and able and cost-effective productive systems; (e) cultural and (c) reducing high inequalities in incomes and opportunities. social development; and (f) fostering environmental incen- tives (figure 5.5 and table 5.4). The effects of a changing and variable climate are already visible and are expected to accelerate in the future. Aver- age annual surface temperature increased by 1.2°C over Proposed technologies the past 50 years, and the increase occurred much faster Potential investments include reforestation, development in the northern and northeastern provinces. Extreme cli- of small grazing corridors, direct vegetation planting, matic events are also becoming more severe, with longer application of organic fertilizer, introduction of agro-­ droughts occurring in the north and more severe floods forestry techniques, development of drought-management affecting the southern part of the country. Coping with projects, development of terraces, and the introduction of the significant variability of future climatic impacts may integrated soil and water–management practices. require geographic shifts in agricultural production and more flexible and efficient water resources management. Livestock investments should also include training rural It also requires building the capacity of agricultural sup- producers on small animal livestock management, rumi- port institutions and related stakeholders (for example, nant grazing as an alternative livelihood practice to slash research, extension, agro-meteorology), and improving and burn, and managing herds to avoid environmental the services delivery mechanisms to provide sound and degradation. real time advice to farmers. CASE STUDY 5: CHINA—INTEGRATED Overall, China ranks with the bottom 25 percent of MODERN AGRICULTURE DEVELOPMENT countries in water availability per capita. The PROJECT share in total water use by agriculture is 64 percent. Over- Project context exploitation of water resources, including withdrawals Since 1978, China has gradually shifted from a centrally from rivers and overdraft of groundwater resources caus- planned to a market-led economy. During this period, the ing a drop in water tables, is a common problem, particu- economy has grown at a remarkable annual rate of about larly in the dry northern regions of the country. Raising Climate-Smart Agriculture Indicators 45 46 RESULTS FROM BRAZIL CAATINGA CONSERVATION AND MANAGEMENT—MATA BRANCA TABLE 5.4.  Raw Target Final Theme Subject Indicator Indicator Description Type Score Score R P M Score Mitigation Mitigation Emissions The technology meets emissions intensity Likert (1–5) 4 3 5 Benefits Intensity targets. Mitigation Mitigation Sequesters The technology sequesters carbon in Likert (1–5) 4 3 5 Benefits Carbon comparison with current interventions in similar farming systems. Productivity Livestock Resource The technology improves livestock resource Likert (1–5) 3 3 3 System Management management in comparison with current interventions in similar farming systems. Productivity Crop Crop Yield The technology leads to an increase in yields % change 9 10 2 System (% increase) of the producers (%). from baseline Productivity Crop Soil Erosion The technology reduces the share of % change 6 5 4 System agricultural land classified as having moderate from baseline to severe water erosion/wind risk (%). Productivity Crop Soil Fertility The technology enhances soil fertility (%). % change 7 5 5 System from baseline Resilience Cropping Resilience to The technology will increase the resilience of Likert (1–5) 4 3 5 System Adverse Weather the cropping system to drought. Resilience Livestock Resilience to The technology will increase the resilience of Likert (1–5) 4 3 5 System Adverse Weather the livestock to drought. Productivity Water Use Irrigated The technology increases the share of % change 9 7 5 Agricultural irrigated agricultural land (hectare) because from baseline Land of the technology (%). Productivity Water Use Water The technology reduces water withdrawal % change 10 7 5 Withdrawal for (liter/day) for agriculture use as a share of from baseline Agriculture total water withdrawal (%). Resilience Robustness Human Capital The technology will improve the human Likert (1–5) 4 3 5 capital (technical skill levels) of producers in the target area. Productivity Livestock Feed Production The technology improves feed production Likert (1–5) 3 3 3 System Technologies in comparison with current interventions in similar farming systems. Productivity Livestock Diversification The technology leads to the diversification of Likert (1–5) 4 3 5 System of Livelihood livelihood activities in comparison with current Activities interventions in similar farming systems. 5 4 5 4.67 Agriculture Global Practice Discussion Paper irrigation system efficiencies and improving water produc- FIGURE 5.6.  CHINA’S CSA-TECH P, R, M tivity are key to better managing water resources in agri- SCORE culture. Average water productivity for grains is reported 1 P to be approximately 0.7–0.8 kg/m3, which is much lower 0.8 than the levels of 2.0–2.5 kg/m3 recorded in the more 0.6 industrialized countries. More efficient and productive 0.4 water use may be achieved through the rehabilitation and 0.2 improvement of outdated, dilapidated, and old irrigation 0 and drainage infrastructure, ensuring adequate operation and maintenance of irrigation systems, promoting water- M R saving irrigation technologies, adopting enhanced agri- Threshold Actual score cultural water-management practices, and strengthening the capacity of farmers, water user associations, and other stakeholders involved. China has one of the highest rates of fertilizer and pes- (usually 3 for the Likert scale) and a predetermined per- ticides utilization in the world. The intensive use of centage (for the percentage-based indicators) grounded chemical inputs has led to (a) degradation of soil fertility; in evidence from the project area or a similar Agro-­ (b) pollution of water systems; (c) higher GHG emissions Ecological Zone. For this case study, we used the input GHG; (d) lower profits to farmers; and (e) increasing con- from several World Bank experts on CSA to complete the cerns about food safety. Field evidence suggests that CSA-Tech survey. The results (figure 5.6 and table 5.5) fertilizer use in some areas could be cut by 30–60 show that water-saving irrigation (drip, sprinklers, and percent with little or no loss of crop yields. An low-pressure pipelines) technologies are climate smart and integrated nutrient management approach that incorpo- should be implemented in the project. The project should rates technical measures (soil and water testing, nonpoint also look into implementing local water resource storage source pollution monitoring), capacity building (exten- systems, farm ponds, and water-monitoring and mea- sion and training to farmers), policy aspects (revisiting the surement structures and equipment (flow-measurement subsidies for fertilizers’ manufacturers), and institutional devices, groundwater monitoring). The project should interventions (role of farmers’ groups in knowledge trans- consider using approaches such as integrated soil fertil- fer) is required to address this problem. ity management. ISFM is a set of agricultural practices adapted to local conditions to maximize the efficiency of nutrient and water use and improve agricultural pro- CSA-Tech testing ductivity. ISFM strategies center on the combined use of The appropriate CSA technologies will need to improve mineral fertilizers and locally available soil amendments farmland infrastructure and the reliability and efficiency (for example, lime and phosphate rock) and organic mat- of irrigation and drainage systems and promote the ter (for example, compost and green manure) to replenish use of low nitrogen inputs. For this case study, we ran lost soil nutrients. This improves both soil quality and the the CSA-Tech toolkit to determine the most appropri- efficiency of fertilizers and other agro-inputs. Also, ISFM ate climate-smart technologies for the proposed project. promotes the use of crop rotation or intercropping with The CSA-Tech Index uses a survey method to deter­ legumes (a crop that also improves soil fertility). mine the most appropriate technology, by comparing the project context with available solutions, for the project ­ region.1 The users of the index have to set their thresholds Proposed technologies The main proposed agricultural technologies for this project, based on the CSA-Tech index testing results, are 1 The CSA-Tech Index does not directly recommend specific practices. It serves as a decision support tool and its functionality is limited to comparing different (a) on-farm water-saving technologies, including need-based technologies for interpretation by the users. irrigation; (b) adaptation-oriented agronomic practices Climate-Smart Agriculture Indicators 47 48 RESULTS FROM THE CHINA INTEGRATED MODERN AGRICULTURE DEVELOPMENT PROJECT TABLE 5.5.  Raw Target Final Theme Subject Indicator Indicator Description Type Score Score R P M Score Resilience Robustness Human Capital The technology will improve the Likert (1–5) 4 3 5 human capital (technical skill levels) of producers in the target area. Resilience Robustness Crop/Livestock The technology will promote crop Likert (1–5) 4 3 5 Diversification diversification in the target area. Resilience Self-organization Local Market The technology will foster local Likert (1–5) 3 3 3 Networks and regional production and supply chains. Resilience Self-organization Feedback from The intervention will provide Likert (1–5) 5 3 5 Extension opportunities for feedback from Workers extension workers. Resilience Cropping Resilience to The technology will increase the Likert (1–5) 5 3 5 System Adverse Weather resilience of the cropping system to drought. Productivity Crop System Crop Yield The technology leads to an increase % change 20 20 3 (% increase) in yields of the producers (%). from baseline Productivity Crop System Soil Fertility The technology enhances soil % change 20 20 3 fertility (%). from baseline Productivity Water Use Irrigated The technology increases the % change 50 50 3 Agricultural share of irrigated agricultural land from baseline Land because of the technology (%). Productivity Water Use Water The technology reduces water % change 40 40 3 Withdrawal for withdrawal for agriculture use as a from baseline Agriculture share of total water withdrawal (%). Productivity Pest Pest Management The technology increases the share % change 40 30 5 Management of agricultural land on which from baseline integrated pest management practices are adopted (%). Mitigation Mitigation Emissions The technology meets emissions Likert (1–5) 5 3 5 Benefits Intensity intensity targets. Mitigation Mitigation Sequesters The technology sequesters carbon Likert (1–5) 5 3 5 Benefits Carbon in comparison with current interventions in similar farming systems. 4.6 3.4 5 4.33 Agriculture Global Practice Discussion Paper such as ISFM strategies; (c) agro-ecological activities to FIGURE 5.7.  ARMENIA’S CSA-RES P, R, M improve the resilience of the farm landscape and increase SCORES carbon sequestration; and (d) research on technical and 1 P policy issues related to climate change adaptation and 0.8 mitigation. 0.6 0.4 TESTING OF PROJECTS USING 0.2 THE CSA-RESULTS INDEX 0 To illustrate the calculation and interpretation of the M R CSA-Res Index, we derived a CSA-Res Index for five Threshold Actual score World Bank projects in the areas of agriculture, rural development, and natural resources management. All projects have been completed and the Implementation (soil, water, forest, fisheries, and biodiversity) and stabilize Completion and Results reports were consulted for data/ incomes in the local communities. The Global Environ- information on the indicator target values and values at ment Objectives (GEOs) were to preserve the mountain, project completion. The CSA-Res Index for P, R, and forest, and grassland ecosystems of the Southern Cauca- M and jointly is derived for the project’s performance in sus through enhanced protected area and mountain eco- the last project year. Some of the reviewed projects have system conservation and sustainable management. a large number of indicators in their results framework (up to 38), of which only a selection of indicators is used The project had six Project Development Objective (PDO) for the calculation of the CSA-Res Index. These indica- indicators, two GEO indicators, and eight intermediate tors were chosen based on their similarity with the CSA- results indicators. For illustrative purposes, the CSA-Res Res indicators and on how well they seemed to reflect Index was calculated for a section of indicators, presented components and behavioral change as described in the in figure 5.7 and table 5.6. The project had one indicator theory of change of implementing CSA. The following that measured Productivity (“Increased crop and livestock examples serve to exemplify how the index was derived, productivity in project villages compared with nonproject not to compare the climate smartness of projects. The villages”), which was collected separately for each crop index is less suitable for comparing projects with one and exceeded the target (compared with villages that were another, because the projects may not be using the same not participating in the project) for each crop. indicators, than it is for comparing how well a project is performing over time in reaching its CSA triple-win The indicators exceeded the target values between 14 goals. and 33 percent, thus achieving scores of 4 and 5, and a total score for the area P of 4.6, implying that the project The testing process for the CSA-Res indicators is described exceeded expectations in reaching Productivity goals. For in the final section of chapter 3. the CSA goal of Resilience, all of the following indica- tors were used to make up the score of 3.9. Thus, the CASE STUDY 1: ARMENIA—NATURAL majority of indicators reached or exceeded their target RESOURCES MANAGEMENT AND value. For the category Mitigation, three indicators were POVERTY REDUCTION PROJECT used, which achieved an average score of 3 because two (P057847, P069917) of three indicators reached or highly exceeded their tar- The project’s development objective was the adoption of gets. The overall CSA-Res Index, as an average of the sustainable natural resource management practices and index for P, R, and M, gave a value of 3.9, indicating that alleviation of rural poverty in mountainous areas where the majority of indicators reached or (highly) exceeded degradation has reached a critical point. The project their targets that measured the CSA successes at project will help avert further deterioration of natural resources completion. Climate-Smart Agriculture Indicators 49 TABLE 5.6.  SELECTED INDICATORS FOR ARMENIA—NATURAL RESOURCES MANAGEMENT AND POVERTY REDUCTION PROJECT Target Value at Value Observed Indicator P, R, M Project Completion at Completion Score Increase in income (or expenditure) in project R AMD 542,300 AMD 599,000 4 villages compared with nonproject villages Increased crop and livestock productivity in P, R Values to exceed Exceeded between 5 project villages compared with nonproject nonproject villages nonproject villages by villages (collected separately for wheat, barley, 14% and 33% milk, wool, sheep, cattle weight) Reduction in illegal activities destroying forest R, M Regulatory framework in Illegal Logging Action 3 cover place and implemented Plan developed and implemented Reversal of degradation in pasture vegetation R, M 9,500 ha 7,125 ha 1 cover Increased quality, quantity, and productivity of R, M 70,000 ha 128,000 ha 5 forest cover in the project area Community capacity for sustainable use of R At least 20 communities 40 Communities 5 common resources developed report participation have participated and in natural resources implemented protective management decisions activities on common natural resources in a participatory approach Measures for effective protection of mountain R Up to 50 small grants for 24 small grant schemes 1 biodiversity at watershed level effectively biodiversity conservation and 4 awareness-raising implemented grants implemented Note: AMD: Armenian dram. CASE STUDY 2: BHUTAN—SUSTAINABLE FIGURE 5.8.  BHUTAN’S CSA-RES P, R, M LAND MANAGEMENT PROJECT SCORES (P087039) (2006–2012) 1 P The PDO was to strengthen institutional and commu- 0.8 nity capacity for anticipating and managing land degra- 0.6 dation in Bhutan. The Project Global Objective was to 0.4 contribute to more effective protection of transboundary 0.2 watersheds in a manner that preserves the integrity of 0 ecosystems in Bhutan. R The project had three PDO-level indicators and eight M intermediate indicators. Out of these, seven indicators Threshold Actual score were identified as measuring the CSA triple-win areas. Their P, R, M assignments are shown in figure 5.8, and the indicators are presented in table 5.7. All but one indi- 5; for the area Resilience, an average score of 4.57 was cator exceeded its target, achieving a score of 4 or 5. achieved, indicating that the majority of indicators that measured aspects of Resilience highly exceeded their One indicator (“Tseri land converted to sustainable land targets. Two indicators (“Tseri land shifted to sustain- cover”) measured Productivity, which achieved a score of able land cover,” “Degraded forestland regenerated and 50 Agriculture Global Practice Discussion Paper TABLE 5.7.  SELECTED INDICATORS FOR BHUTAN—SUSTAINABLE LAND MANAGEMENT PROJECT Target Value at Project Value Observed Indicator P, R, M Completion at Completion Score Increase in farmers practicing SLM techniques in R 650 farmers 1,805 farmers 5 pilot geogsa 10% reduction in sediment flows in selected R 10% reduction 44% reduction 5 watersheds in pilot geogs Degraded forestland regenerated and grazing lands R, M 666 acres improved 2,039 acres improved 5 improved in pilot geogs Tseri land (now 5,132 ha) (shifting cultivation lands) P, R, M 4,000 acres 9,173 acres 5 converted to sustainable land cover RNR staff, DYT and GYT members trained in R Plus 80% of staff Plus 93% of staff 4 multisectoral SLM planning Farmers trained in application of SLM technologies R 4,500 farmers 17,237 farmers 5 Sector policies and legislation incorporating SLM R At least 5 5 3 principles a Geog/Gewog: Local government administrative area (block) or lowest level of local administration in Bhutan, set up between village level (Chiog) and district level ­(Dzongkhag). Note: DYT = Dzongkhag Yargay Tshogdu (district development committee); GYT = Geog Yargay Tshogchhung (geographic development committee). grazing lands improved in pilot geogs”) demonstrated FIGURE 5.9.  BRAZIL’S CSA-RES P, R, M Mitigation benefits and achieved an average score of 5, SCORES implying that the expectations were highly exceeded. The 1 P project achieved an overall average score of 4.8. 0.8 0.6 CASE STUDY 3: BRAZIL—RIO DE 0.4 JANEIRO SUSTAINABLE INTEGRATED 0.2 ECOSYSTEM MANAGEMENT IN 0 PRODUCTION LANDSCAPES OF THE NORTH-NORTHWESTERN FLUMINENSE M R (GEF) PROJECT (P075379) (2005–2011) Threshold Actual score The development objective of the proposed project was to promote an IEM approach to guide the development and implementation of SLM practices in the North and Northwest (NNWF) regions of Rio de Janeiro State. The in total land area characterized by biodiversity-friendly desired principal outcomes for the primary target group agricultural practices that enhance soil structure stability (smallholder families and communities) were the follow- in microcatchments”), achieving a score of 5. All indica- ing: (a) improved capacity and organization for NRM, tors were identified as contributing partially to increasing and (b) increased adoption of IEM and SLM concepts Resilience of social or natural systems. and practices. The majority of indicators reached or achieved the set tar- The project had 9 indicators at the global level and 20 gets (figure 5.9 and table 5.8), such that an overall score of indicators measuring intermediate results. We chose 11 3.3 was assigned, which implies satisfactory results. For the main indicators for the analysis. Out of these, one indica- area Mitigation we identified four indicators, of which two tor was assigned to the CSA area Productivity (“Change failed to reach the target by less than 20 percent and two Climate-Smart Agriculture Indicators 51 TABLE 5.8.  SELECTED INDICATORS FOR BRAZIL—RIO DE JANEIRO SUSTAINABLE INTEGRATED ECOSYSTEM MANAGEMENT IN PRODUCTION LANDSCAPES OF THE NORTH- NORTHWESTERN FLUMINENSE Target Value at Project Value Observed Indicator P, R, M Completion at Completion Score Change in total land area characterized by biodiversity- P, R, M 32,000 ha 31,650 ha 2 friendly agricultural practices that enhance soil structure stability in microcatchments Total area of riparian and other native forests rehabilitated R, M 1,440 ha 1,332 ha 2 for biodiversity conservation and hydrology stabilization objectives Area of biodiversity conservation-friendly land use R 1,240 ha 792 ha 1 mosaics established on private lands supporting corridor connectivity in project watersheds Reduction in erosion and downstream sedimentation in at R 3 2 1 least three microcatchments, and amount of CO2 sequestered. M 1.5 tons/ha 80 tons/ha (air) and 5 5 tons/ha (soil) By PY4, 40 rural community organizations created that R 40 48 4 have adopted and implemented IEM/SLM strategies in 40 microcatchments Education, training, and awareness building of beneficiary stakeholders, project executors, and schools—by type of stakeholders: beneficiaries R 3,000 5,730 5 executors R 150 370 5 schools R 25 20 2 IEM and SLM practices adopted, reversing land degradation and improving livelihoods by PY5 (by type): at least 1,900 farmers in 40 communities R 1,900 farmers in 2,254 farmers in 4 40 communities 48 communities microcatchments R, M 40 catchments 48 catchments 4 Microcatchment Development Plans (PEM) and related R 40 catchments 48 catchments 4 individual farm-level plans (PID) developed in at least 40 microcatchments By PY4, 40 rural community organizations created that R 40 catchments 48 catchments 4 have adopted and implemented IEM/SLM strategies in 40 microcatchments At least 200 project executors trained throughout life of the R 200 executors 370 executors 5 project At least 3,000 participants in environmental education R 3,000 5,730 5 events, including stakeholders from 5 project microcatchments (24 municipalities) Note: PY = Program year. 52 Agriculture Global Practice Discussion Paper exceeded and highly exceeded the expectation. The aver- land management practices, contributing to maintenance age score was thus above satisfactory at 3.25. The over- of critical ecosystem functions and structures (including all average CSA Results Index for the project was 2.9. It maintaining agro-ecosystems, stabilizing sediment stor- needs to be interpreted with caution, though, because the age and release in water bodies, and improving carbon area’s Resilience and Mitigation contain a range of indica- sequestration through increase in vegetation cover). tors, largely exceeding expectations, whereas the area of Productivity has one indicator that fell short of meeting The project had 3 indicators at the PDO level and 12 inter- the target. For achieving the CSA goals, these results may mediate results indicators, as well as subindicators at the indicate that more focus could be placed on Productivity. PDO level to measure productivity if several crops. Table 5.9 presents the indicators that we selected for testing and CASE STUDY 4: BURUNDI— AGRICULTURE REHABILITATION AND FIGURE 5.10.  BURUNDI’S CSA-RES P, R, M SUSTAINABLE LAND MANAGEMENT SCORES PROJECT (P064558, P085981) 1 P Project Development Objectives were to restore the 0.8 productive capacity of rural areas through investments 0.6 in production and sustainable land management and 0.4 through capacity building for producer organizations and 0.2 local communities. Beneficiaries would also include war- 0 distressed returnees and internally displaced persons. The project also had a set of Global Environment Objectives. The GEF operational program addressed the causes of M R land degradation by accelerating locally driven sustainable Threshold Actual score TABLE 5.9.  SELECTED INDICATORS FOR BURUNDI—AGRICULTURE REHABILITATION & SUSTAINABLE LAND MANAGEMENT Target Value Value at Project Observed Indicator P, R, M Completion at Completion Score Productivity increase of main agricultural and livestock products in project area: beans P, M 0.9 0.7 1 irrigated rice P, M 5 4.2 2 onions P, M 15 6.3 1 tomatoes P, M 15 7 1 cassava P, M 12 10 2 palm oil P, M 3 3 3 milk P, M 7 5.5 1 Increase in beneficiaries’ net profit (%) R 30 26 2 Area of selected watershed under SLM practices R, M 9,000 ha 11,279 ha 5 Number of productive investment subprojects approved and R 3,300 3,744 4 being implemented Area under irrigation P 1,224 ha 1,573 ha 5 Number of beneficiaries (including women and coffee growers) R 102,000 245,258 5 Number of trees, including local varieties R, M 52,000,000 71,904,786 5 Number of persons day trainings R 108,000 275,388 5 Climate-Smart Agriculture Indicators 53 figure 5.10 shows the P, R, M assignments. All, except one FIGURE 5.11.  CHINA’S CSA-RES P, R, M (“productivity increase of palm oil”), indicators in the cate- SCORE gory P failed to reach the target, two indicators (“productiv- 0.8 P ity increase of irrigated rice” and “cassava”) failed to reach 0.6 the target by equal to or less than 20 percent, and four indi- cators failed to reach the target by more than 20 percent. 0.4 0.2 The overall average score for Productivity indicates that 0 the project performed below expectations in achieving the CSA goal of increasing Productivity. For the area of Resilience, six indicators were assigned, which on average M R achieved a score of 2.8, indicating that seven indicators Threshold Actual score failed to reach the target (the majority of those are the same as for the area Productivity), whereas the remain- ing six achieved or highly exceeded the target. The over- practices through awareness raising, institutional and all result was thus satisfactory. For the area Mitigation, capacity strengthening, and demonstration activities in two indicators were assigned that exceeded their target the 3H Basin. This would assist in mainstreaming climate value by more than 20 percent. The overall average CSA change adaptation measures, techniques, and activities Results Index score was thus 3.3—the project satisfacto- into the national Comprehensive Agricultural Develop- rily achieved the targets related to CSA triple-win goals. ment Program that is China’s largest national investment program in irrigated agriculture. CASE STUDY 5: CHINA—IRRIGATED AGRICULTURE INTENSIFICATION This project had 6 PDO indicators, 6 GEO indicators, PROJECT III—A MAINSTREAMING and 38 intermediate results indicators. Therefore, we CLIMATE CHANGE ADAPTATION IN chose a range of distinctly different indicators (table IRRIGATED AGRICULTURE PROJECT 5.10) to assess the project’s performance toward the CSA (P084742, P105229) goals. The project’s PDO was to increase water and agricultural productivity in low- and medium-yield farmland areas; As is evident from figure 5.11 and table 5.10, each indi- raise farmers’ income and strengthen their competi- cator reached or exceeded or highly exceeded the tar- tive capacity under post-WTO conditions; and demon- get. For the category Productivity, the average score was strate and promote sustainable participatory rural water 3.3; for Resilience, the average score was 3.9; and for resources management and agro-ecological environmen- Mitigation, the average score was 3.5. The overall aver- tal management in the 3H Basin. The Global Environ- age CSA results Index was thus 3.6, demonstrating that ment Objective was to enhance adaptation to climate the project satisfactorily reached all targets related to change in agriculture and irrigation water-management achieving the CSA triple-wins. 54 Agriculture Global Practice Discussion Paper TABLE 5.10.  SELECTED INDICATORS FOR CHINA—IRRIGATED AGRICULTURE INTENSIFICATION PROJECT III Target Value at Project Value Observed Indicator P, R, M Completion at Completion Score Increase per capita income of typical farm households R Y 2,207 Y 3,290 5 Increase high-quality/value and nonpolluting/green crop PR 4.2 mt 4.2 mt 3 production (million ton [mt]) Increase water and agricultural productivity (kg/m3) P, R 1.45 kg/m3 1.55 kg/m3 4 New established no. of Water User Associations (/ha) R 1,014 1,022 4 New established no. of FAs and member coverage (/ha) R 70,400 95,400 5 Climate change adaptation awareness of farmers, technical R 47 56 4 staff, officials (percentage of people) Relevant CC adaptation measures implemented in selected R 186,424 208,152 4 demonstrated areas (ha) by participatory stakeholders (number of households) Increase per capita income of typical farm households R 1,501 1,570 4 because of adaptation measures applied Change in the production per unit of ET (KG/ET) P, R 114,000 114,000 3 Total improved area of low- and medium-yield farmland (ha) P, R, M 505,505 505,505 3 Water-saving irrigated area (ha) P, R 380,456 392,525 4 Number and quality WUAs established and operating R 1,014 1,022 4 On-farm forest belts established (ha) R, M 27,847 30,714 4 Number of counties with groundwater-management plans R 19 19 3 adopted Number of farmers’ professional cooperative organizations’ R 19 20 4 demonstration pilots Farmers’ training (man/month) R 66,036 74,455 4 Quality seed coverage (%) P, R 100 100 3 Increase per capita income of typical farm households R 2,207 3,290 5 Increase high quality/value and nonpolluting/green crop PR 4.2 4.2 3 production (mt.) Increase water and agricultural productivity (kg/m3) P, R 1.45 1.55 4 New established no. of WUA(/ha) R 1,014 1,022 4 New established no. of FAs and member coverage (/ha) R 70,400 95,400 5 Note: ET = evapo-transpiration; FA = farmer associations; WUA = water user associations. Climate-Smart Agriculture Indicators 55 CHAPTER SIX CONCLUSION AND THE WAY FORWARD The report identified three indices to support policy makers and development practi- tioners in identifying and implementing the necessary policy, technical, and monitor- ing framework to enable and operationalizing CSA. The CSA-Pol Index allows policy makers and other users to compare how a coun- try’s enabling environment for CSA is changing over time; identifies gaps in support- ing CSA implementation; and to develop benchmarks for reform. The CSA-Tech Index helps to guide thinking about the values of technology, specifically looking at its potential to improve decision making. The CSA-Res Index measures an agricul- tural project’s performance toward achieving the CSA triple wins individually and jointly. The development of the CSA indicators was informed by the impact pathway and theory of change. It presented the rationale for the selection of the indicators that included a range of policies, technologies, and practices focused on the CSA pillars. To achieve the medium- and long-term goals of environmental sustainability, CSA interventions must be regarded within a landscape approach that is cognizant of the competing demand for land, water, and natural resources use and that equips farmers with an understanding of the cost-benefits or trade-offs of adopting certain practices and technologies. REPORT HIGHLIGHTS »» Adopting CSA policies to address food insecurity under changing climatic con- ditions is critical. A 1 percent increase in the CSA-Pol Index is predicted to lead to a 0.4 percent decline in the proportion of undernourished population. Cereal yields increase 47 kilograms per hecatre for every 1 percent increase in the CSA-Pol Index. »» Public expenditure for services and infrastructure could be more important than readiness mechanisms and coordination mechanisms for achieving CSA goals. Climate-Smart Agriculture Indicators 57 »» Low-income countries may benefit more by focus- national budgets, it should be noted that actual budgets ing on policies that provide for effective CSA dedicated to CSA are critical for converting “readiness” implementation. into action. Some limitations of the CSA-Res Index were »» The results from the CSA-Tech Index assessment also noted, which included difficulties in determining shows how the tool can be used to select contextual whether an enabling environment is a consequence of ready technologies to achieve triple wins. the CSA intervention or of other externalities. For some »» The results from the CSA-Res Index assessment indicators, the CSA-Res Index does not also convey infor- showed how the tool can be used to assess triple mation about the quality of systems or impact of an inter- wins to project objectives. vention at the project level. Although noting their utility in informing national poli- The CSA indicators have been designed with great flex- cies and project development and monitoring, there are ibility in mind. Unlike many of the existing indicators and also some limitations to the indices. For instance, although indices related to agriculture and food security, the CSA the CSA-Pol Index reflects the most significant aspect for indicators are a robust tool for a full range of agriculture enabling CSA at the national level, it does not measure and rural development projects. 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Haddad, Rajith Lakshman, and Karine Gatellier. 2014. “The Hunger and Undernutrition Commitment Index (HANCI 2013).” Evidence Report no. 78, Institute of Development Studies, Brighton. Climate-Smart Agriculture Indicators 61 Torero, Maximo, Nicolas Gerber, and Evita Hanie Pangaribowo. 2013. “Food and Nutrition Security Indicators: A Review.” ZEF Working Paper Series 108, Center for Development Research, Bonn. doi:ISSN1864-6638. World Bank. 2012. “Carbon Sequestration in Agricultural Soils.” Washington, DC: World Bank. http://documents.worldbank.org/curated/en/2012/05/16274087/ carbon-sequestration-agricultural-soils ______. 2013. “Agribusiness Indicators: Kenya. Agriculture and Environmental Services.” http://siteresources.worldbank.org/INTARD/Resources/335807-1250550306324/ ABIKenyaReport.pdf ______. 2014.“Safety Nets Overview.” http://www.worldbank.org/en/topic/safe tynets/overview. ______. 2015. “World Bank—Agriculture Portal.” http://www.worldbank.org/en/ topic/agriculture. World Bank, and International Center for Tropical Agriculture (CIAT). 2014. CSA Country Profiles for Latin America Series. CSA Country Profiles for Latin America Series, Washington, DC. World Resources Institute. 2014. “Climate Access Indicators Tool: WRI’s Climate Data Explorer.” http://cait2.wri.org. 62 Agriculture Global Practice Discussion Paper APPENDIX A REVIEW OF EXISTING INDICES RELATING TO AGRICULTURE AND CLIMATE CHANGE A range of indicator and index initiatives exists. These inform about agriculture and climate change topics, rank countries accordingly, and allow for recommendations toward policy and project-level CSA interventions. However, as the review of indictors shows here, very rarely are the CSA dimensions of food security, agricultural produc- tivity, resilience, climate change mitigation, and sustainable use of natural resources addressed in one indicator. Achieving food security is a determined aim of CSA. There is a range of indica- tors and indices that capture the state of food security and nutrition in developing countries. The available indicators often point toward gaps in the provision of food and nutrition and highlight the importance of good governance to support agricul- tural development. However, these indicators and indices typically fail to capture the interdependencies between food security and productivity; environmental and natu- ral resources management; or agriculture’s impact on climate change or the need for increasing resilience toward climate-induced risks. A prominent example is the Global Food Security Index (from the Economist Intelligence Unit, which comprises 18 indi- cators and assesses food security of 109 countries). The indicators are categorized in three groups—food affordability, availability, and quality and safety. The index encom- passes various dimensions of food demand, production volatility, rural poverty, and nutrition.1 The complexity of calculating the composite index is frequently cited as a weakness because it makes recommendations for policy interventions based on an index score difficult. In addition, a theoretical framework is lacking that explains the rationale for the selection of indicators for the composite index.2 In contrast to measuring the status of food and nutrition security, the HANCI attempts to assess governance and political will to reduce undernutrition and hunger. HANCI is a project of the Institute of Development Studies with funding from Irish Aid, UKAid, 1 http://foodsecurityindex.eiu.com/Home/Methodology. 2 http://www.zef.de/uploads/tx_zefportal/Publications/wp108.pdf. Climate-Smart Agriculture Indicators 63 and Children’s Investment Fund Foundation that ranks GHG inventory analysis that includes data from the agri- governments on their political commitment to tackling cultural sector.4 A similar inventory is provided by FAO hunger and undernutrition. It includes 22 indicators that agricultural emissions data, which allows users to differen- cover three themes—laws, policies, and spending—to tiate emission by agricultural practice and land use.5 Both assess government direct and indirect interventions that inventories provide an understanding of agriculture’s relate to creating an enabling environment to address hun- impact on climate change and the mitigation potential of ger and nutrition.3 Although the indicator is well accepted, several practices on a global scale, thus providing insights there is some criticism that assessing country progress for in the choice of agricultural practices and technologies. tackling hunger and nutrition through the index from year However, the data do not provide support in the selec- to year is difficult. Indicators that focus too closely on legal tion of CSA technologies in specific country or project frameworks such as constitutional rights are not useful contexts because the regional context in terms of suitabil- tools for practitioners to use to track from year to year and ity and enabling environment for the technology is not thus diminish the usefulness of the index. considered. Another noteworthy initiative is the Agricultural Science The Global Forest Watch, provided by WRI, shares and Technology Indicators initiative. Information about important information on land use and land cover man- research and development in agriculture is crucial for agement, a relevant dimension of CSA. The interactive an understanding of the enabling environment for CSA. platforms provide indicators such as tree cover state, loss, ASTI is led by the International Food Policy Research and gain by country. Although no composite index is pro- Institute and provides information on agricultural R&D vided, the country profiles include qualitative information systems across the developing world. In contrast to other on the policy and institutional environment of forest man- index initiatives, it conducts primary surveys to collect data agement. WRI also provides data on an aqueduct project from government, academia, and private and nonprofit and maps production areas under water stress. The over- agencies. It thus covers information on funding sources, arching goal of the tool is to help companies, investors, spending levels and allocations, and human resources governments, and other users to understand where and capacities at both country and regional levels. The index how water risks and opportunities are emerging. provides a benchmarking tool to conduct country rank- ings. However, it does not provide a composite index that Another set of indicators is suitable to inform the results provides a ranking at one glance. framework and can constitute M&E indicators for CSA interventions. For instance, the Global Donor Platform There is another category of indicators and indices that for Rural Development includes a set of agricultural and typically focuses on climate change and natural resources rural development indicators, but does not track climate management, but at the same time often neglects the change mitigation and resilience to climate change.6 interdependencies of agricultural productivity and resil- The resilience indicators instruments from the Consulta- ience. Prominent examples in this category are indica- tive Group for International Agricultural Research and tors provided by the World Resources Institute, which CCAFS7 provide project-level indicators for monitoring benchmark and provide information on countries’ con- and evaluation projects that seek to increase adaptive tribution and vulnerability to climate change and other capacity and enhance livelihood and farm functioning. environment-related information. For instance, the CAIT It focuses on the provision and access to environmental Climate Data Explorer provides a comprehensive collec- services that foster resilience. Agricultural production and tion of global GHG emission data, partially dating back 160 years. From 1990 onward it provides a multisector 4 http://cait2.wri.org/wri#Country GHG Emissions. 5 http://faostat3.fao.org/browse/G1/*/E. http://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/4090/ 3   6 https://openknowledge.worldbank.org/handle/10986/6200. ER78%20HANCI.pdf ?sequence=5. 7 https://cgspace.cgiar.org/handle/10568/56757. 64 Agriculture Global Practice Discussion Paper land use management, as well as farmers’ potential to which are based on the CSA pillars of productivity, resil- adapt to and mitigate climate change, are not addressed. ience, and mitigation. The country profiles provide an Another indicator set is the World Bank indicators for overview of land use, climate change impacts, mitiga- Land Quality and Sustainable Land Management.8 tion potential, and institutional arrangements and poli- These indicators tackle ecological resilience excluding the cies that create an enabling environment for CSA. It also resilience and adaptive capacity of households. Further- highlights financing options to support CSA implemen- more, it only partially allows for monitoring the mitiga- tation. In addition, countries are assigned a “smartness” tion potentials of agriculture. measure in terms of water, energy, nitrogen, weather, and knowledge-smart agricultural practices commonly used in The need to combine all dimensions of climate-smart the country (CGIAR 2014). Although the CCAFS pro- agriculture has been addressed by a recent initiative of files informed country baseline diagnostics, it is difficult to the CGIAR Research Program on Climate Change, Agri- derive policy recommendations from them or recommen- culture and Food Security. CCAFS produced a set of CSA dations as to which technology may be the most suitable country profiles for Latin America and the Caribbean, at the project level. 8 http://elibrary.worldbank.org/doi/pdf/10.1596/0-8213-4208-8. Climate-Smart Agriculture Indicators 65 APPENDIX B TECHNICAL NOTES FOR THE CSA POLICY INDEX # Indicators Data Sources Proposed Scoring Technical Notes Readiness Mechanisms 1 Agricultural National Total Score: 3 In determining a country’s policy support for CSA, one adaptation agriculture 1a. Ag. policy (or the can examine a country’s intent to address the impacts policy legislation, policies, country’s climate change of climate change on agriculture as expressed by its strategies, and adaptation policy, for government, which can be assessed by how the government regulations example the NAPA) expresses this intent within the policy: explicit indication National climate explicitly states an within the policy to deal with the impacts of climate change legislation, intention to address change in the agricultural sector, and the development policies, strategies, adaptation to climate of a strategy for dealing with the impacts of climate and regulations change (1) change in the agricultural sector. In looking beyond intent, one can consider the government’s commitment to the 1b. [If yes to 1a] Is there implementation of the policy by assessing indicators of a strategy to support policy implementation, namely, the development of a implementation of this system for implementation, and also for monitoring the aspect of the policy? (1) impact of the policy in a manner that promotes feedback 1c. [If yes to 1a] Is there learning with the potential for improving the design and a mechanism in place to implementation of the policy, and actual expenditure implement and monitor on the strategy. A country’s policy support for CSA is programs and activities therefore assessed by its intent to adapt agricultural to address adaptation to systems for climate change, and the operationalization and climate change in the Ag. implementation of this intent. Sector? (1) Agricultural policies are expressed in a variety of ways by different countries, and so the broad list of policies considered for the scoring of these indicators include the following: national agricultural policies, strategies, and action plans; national development strategies; rural development strategies; and poverty reduction strategy papers. Climate change policies at the national level are expressed through NAPAs, NAMAs (FAO 2010), and communications to the UNFCCC. Climate-Smart Agriculture Indicators 67 # Indicators Data Sources Proposed Scoring Technical Notes 2 Agricultural National Total Score: 3 In the process of developing the indicators, the study team mitigation agriculture 2a. Ag. policy (or the faced difficulty in accessing national budgets or expenditure policy legislation, policies, country’s climate change reports that reflected implementation of CC adaptation strategies, and mitigation policy, for or mitigation. The indicator is, however, a very important regulations example the NAMA) one for assessing the performance of a policy and so the National climate explicitly states an respective indicators are retained. change legislation, intention to address Subindicators 1a, 1b, 2a, and 2b assess intent of the policies, strategies, mitigation of climate government, and subindicators 1c and 2c assess the and regulations change (1) commitment to implementation of the policy. 2b. [If yes to 2a] Is there a strategy to support implementation of this aspect of the policy? (1) 2c. [If yes to 2a] Is there a mechanism in place to implement and monitor programs and activities to address mitigation to climate change in the Ag. Sector? (1) 3 Economic Doing Business Total Score: 1 Economic readiness captures the ability of a country’s readiness Report 2015 Calculated from the business environment to accept investment that could be ND-GAIN Index “ease of doing business applied to adaptation that reduces vulnerability (reduces index.” Details of sensitivity and improves adaptive capacity). This is the the calculation of “Doing Business Indicator.” the indicator score is included in the ND-GAIN Methodology manual. 4 Governance World Bank Total Score: 1 Governance Readiness: Institutional factors that readiness Governance Calculated as a enhance application of investment for the adaptation Indicators (2013 composite indicator of of financial resources. The governance readiness data) the following variables subindicators capture several aspects of governance: ND-GAIN Index available from World (i) Political Stability and Nonviolence—the relationship Bank’s Governance between foreign financial inflow and political stability Indicators: Political and violence suggests that a stable political environment is Stability and Absence more attractive to general investment from outside of Violence Terrorism; a country, including the adaptation investment; Regulatory Quality; (ii) Control of Corruption—corruption is known to have Rule of Law; Control a negative impact on foreign investment and measuring of Corruption. Details the control of corruption implies government integrity of the calculation of and accountability; (iii) Regulatory Quality—the quality the Indicator score are of regulation measures the performance of country included in the ND-GAIN institutions, an important factor in deploying adaptation Methodology manual. actions and adaptation-related policies; (iv) rule of law is a quality of society that encourages foreign investment in general, hence the adaptation investments (Chen et al. 2015). 68 Agriculture Global Practice Discussion Paper # Indicators Data Sources Proposed Scoring Technical Notes 5 Social Millennium Total Score: 1 The social readiness subindicators use socioeconomic readiness Development Goal Calculated as a measures to assess society’s overall readiness for adaptation. Indicators (2012 composite indicator of The subindicators include the following elements: data) the following variables (i) Social inequality causes skewed distribution incomes World available from World and of vulnerability, and the exaggerated impacts on the Development Bank’s Governance poorest may further skew income distribution. Thus, social Indicators (2013 Indicators: social inequality exacerbates a country’s capacity to adapt to data) inequality; information climate change. (ii) Information communication technology communication infrastructure enables knowledge integration and learning ND-GAIN Index technology and key ingredients of adaptive capacity, provides technical infrastructure; education; support for early warning systems, and can strengthen local and innovation. Details organizations that implement adaptation. (iii) Education of the calculation of is considered an important strategy to build up adaptive the Indicator score capacity and identify adaptation solutions appropriate are included in the to local context. (iv) Innovation is the fundamental force ND-GAIN Methodology behind capacity building and climate change adaptation manual. because research and technology are necessary to define adaptation solutions (Chen et al. 2015). Services and Infrastructure 6 Extension Survey of Total Score: 2 Assessing extension services is often done from the services agriculture 6a. Do the Extension perspective of the recipient of the extension services, wherein ministry Strategy/Action Plan/ questions are asked about timeliness of delivery; accuracy Guidelines include of service; relevance to situation; ease of understanding; a commitment to and opportunity to use/apply information delivered providing producers with (Agholor et al. 2013). Such assessments are very useful for information/advice on understanding the quality of extension services at national dealing with the impacts or subnational scales, and can enhance the outcome of of CC in agricultural this indicator development exercise by providing specific systems? (1) information for countries on the quality and performance of their extension services, but are beyond the scope of this 6b. Are there indicator development exercise. In an attempt to select a national programs for universal indicator that provided an indication of the quality disseminating weather of extension services, we first selected the “ratio of extension and climate services worker to producer/farmer” as an indicator. This indicator is (information and commonly used as a measure of extension, but does not say forecasts) to agricultural anything about how the extension service has the potential producers? (1) to deliver, or actually delivers, CSA-relevant information. An indicator that more adequately captures potential albeit not actual performance of the extension services is the indicator selected as 6a. This indicator assesses the capacity of national extension services to provide information and advice to farmers relevant for dealing with the impacts of climate change on their production system, and therefore examines the systems that are in place to provide this information. Indicator 6b is included to assess the capacity of a country for translation of climate data and information into useful information for producers and extension agents. It also assesses the delivery of CSA-relevant information through ICT channels such as mobile technology, Internet, television, and radio. Climate-Smart Agriculture Indicators 69 # Indicators Data Sources Proposed Scoring Technical Notes 7 Agricultural National accounts Total Score: 2 For this particular indicator we are interested in the evidence R&D data available from 7a. Does the Ag. R&D that a country is investing in research to manage climate the World Bank policy expresses a change impacts in the agricultural sector. This includes Primary surveys commitment to CC and research into increasing the resilience of agricultural systems to collect data Ag. research? (1) to projected impacts of climate change, for example by from government, 7b. Is there a mechanism developing drought, pest, and heat-resistant seeds and higher education, (in place and being livestock varieties. And also research into mechanisms for and nonprofit and implemented) that reducing the output of GHGs from agricultural systems or private agriculture promotes collaborative even reducing the emissions intensity of agricultural systems, R&D agencies for example through introducing improved livestock varieties research, among multiple that utilize food resources more efficiently and produce less stakeholders? (1) methane per kg of feed. Evidence of a country’s investing in CC and agriculture research can be assessed through what the country has committed to do, and what they actually do on CC and Ag. research. We can assess the commitment to undertaking CC and Ag. research within a country by examining what is expressed in the country’s Ag. or Ag. research policy. Accordingly, indicator 7a is included to assess this commitment. In cases where the indicator is not available, a value of zero is assigned to the indicator. 8 Rural Access World Bank Data2 Expressed as a % The World Bank is the main source of data for the RAI. Index (RAI)1 These data are produced at different times and so the data are inconsistent in this way. In cases where the RAI value is not available, a value of No-data is assigned to the indicator and is not included in the calculation of the final score of the indicator. 9 Social safety Surveys of public Total Score: 1 SSNs are noncontributory transfers in cash or in kind nets and private sector SSNs (cash transfers, targeted to the poor and vulnerable that can have an social support food distribution, seeds immediate impact on reducing poverty and on boosting and development and tools distributions, prosperity, by putting resources in the hands of the poorest programs and conditional cash and most vulnerable members of society (World Bank World Bank transfers) identified in 2014). In countries experiencing increased exposure to ASPIRE: Atlas of agriculture policies and disasters and climate change consequences, there is a Social Protection national strategies as a growing recognition of the role SSNs play in providing Indicators of resilience (or coping) resilience. SSNs can help to ensure that during times of Resilience and mechanism (1) hardship, such as during flooding and drought events, Equity farming communities can have access to resources (money, food, and so on) to maintain or improve their standard of living. Public works programs that guarantee employment when needed would effectively build resilience to climate change impacts. Agriculture-related public works activities, such as hillside terracing or soil and water conservation, can improve farm yields and generate sustainable benefits for household food security. They can also create community assets and infrastructures that are critical for adaptation 1 http://www.worldbank.org/transport/transportresults/headline/rural-access.html. 2 http://www.worldbank.org/transport/transportresults/headline/rural-access.html. 70 Agriculture Global Practice Discussion Paper # Indicators Data Sources Proposed Scoring Technical Notes (FAO 2013). The World Bank identifies five different types of SSNs: conditional cash transfers, unconditional cash transfers, conditional in-kind transfers, unconditional in-kind transfers, and public works expenditures. 10 National Survey of relevant Total Score: 2 National GHG accounting systems may include national GHG public sector Does the country have a GHG inventories. An accurate understanding of GHG inventory agencies national GHG inventory emissions allows governments, companies, and other system Reports to the system? (1) entities to identify opportunities to manage emissions, UNFCCC enhance removals, evaluate the success of low-carbon Does the national GHG growth strategies over time, and ensure that resources are inventory system include targeted toward effective solutions. emissions from the Ag sector? (1) 11 National National Total Score: 6 Access to grain stock reserves (indicator 11a) may include agricultural agriculture Grain stock management even access outside of a country to grain reserves. In such risk legislation, policies, cases access may be instituted through a formal agreement 11a. Does the country management strategies, and between the donor and recipient countries. have access to grain stock systems regulations Market information systems (indicator 11d) provide reserves? (1) producers and extension workers with data and information 11b. Are there guidelines on prices for agricultural produce. These systems may take (and standards) for grain on a variety of forms including pamphlets, information stock management such available on websites, mobile messages, or electronic as warehouse receipt billboards. systems? (1) Agricultural insurance 11c. Is there a policy or are there guidelines for agricultural insurance (crop and/or livestock)? (1) Agricultural Information Systems 11d. Is there a market information system for dissemination of trend and forecast information on crop and livestock price information to producers? (1) 11e. Is there an early warning system available for weather/climate? (1) 11f. Is there an early warning system for pests/diseases? (1) Climate-Smart Agriculture Indicators 71 # Indicators Data Sources Proposed Scoring Technical Notes 12 Adaptive ND-GAIN Index Total Score 1 Adaptive capacity describes the availability of social capacity Calculated from resources to put adaptation into place to reduce exposure ND-GAIN capacity and sensitivity. In some cases, these capacities reflect (vulnerability) data. The sustainable adaptation solutions. In other cases, they reflect score equals 1 minus the the ability of a county to put newer, more sustainable original number. adaptations into place to address the needs of a particular sector (ND-GAIN 2015). It is important to note that the adaptive capacity score considers the adaptive capacity not only in the agricultural sector but also in the sectors of water, health, infrastructure, transport, and environment, and therefore provides a broad measure of a country’s adaptive capacity to deal with climate change impacts. Further information on this indicator can be accessed in the technical guidance for the ND-GAIN indicator available at http://index.nd-gain.org:8080/documents/nd-gain_ technical_document_2015.pdf. Coordination Mechanisms 13 Disaster risk National Total Score: 3 In determining how well a country integrates the management agriculture 13a. Legislation and/ agricultural sector into DRR planning, or, conversely, coordination legislation, policies, or policy for DRR how DRR is integrated in the agricultural sector, an strategies, and in the agricultural examination of a country’s disaster management or its regulations sector (or DRR policy agricultural policies is required. National climate includes measures to DRR planning is also often expressed in a country’s report change legislation, address disasters in the to the Hyogo Framework for DRR. The Hyogo Framework policies, strategies, Ag. sector) (1) for Action is the first plan to explain, describe, and detail and regulations 13b. Specific action plan the work that is required from all different sectors and National disaster or strategy (or guidelines) actors to reduce disaster losses. It was developed and agreed management developed for addressing on with the many partners needed to reduce disaster risk— legislation, policies, DRR in agriculture (1) governments, international agencies, disaster experts, and strategies, and many others—bringing them into a common system of 13c. Country is a regulations coordination. The Hyogo Framework for Action outlines signatory to the Hyogo five priorities for action, and offers guiding principles and Framework for DRR (1) practical means for achieving disaster resilience. Its goal is to substantially reduce disaster losses by 2015 by building the resilience of nations and communities to deal with disasters. This means reducing loss of lives and social, economic, and environmental assets when hazards strike (http://www.unisdr.org/we/coordinate/hfa). Agricultural policies are expressed in a variety of ways by different countries, so the broad list of policies considered for the scoring of these indicators include: national agricultural policies, strategies and action plans, national development strategies, rural development strategies, and poverty reduction strategy papers. This indicator assesses a country’s commitment to integration of DRR into agriculture as expressed in relevant policy documents (13a), the development of a strategy or guidelines for DRR implementation in agriculture (13b), and the commitment to the Hyogo framework (13c). 72 Agriculture Global Practice Discussion Paper # Indicators Data Sources Proposed Scoring Technical Notes 14 Multisectoral Survey of relevant Total Score: 4 CSA implementation requires coordination across coordination public sector 14 a. Does the agriculture sectors (for example, crops, livestock, forestry, agencies agriculture policy and fisheries) and other sectors, such as energy and water. express commitment Cross-sector development is essential to capitalize on to coordination among potential synergies, reduce trade-offs, and optimize the sectors involved in CSA use of natural resources and ecosystem services (FAO (for example, climate, 2013). Implementation of CSA will require cooperation environment, water, of four main groups of stakeholders within these sectors: forestry)? (1) (1) government policy and decision makers to establish the legal and regulatory frameworks for CSA and to promote 14b. Is there an existing and mainstream CSA in an intersectorial manner; (2) multisectoral committee governmental technical, research, and extension staff to for climate change that develop and disseminate CSA practices; (3) agribusinesses includes representation including nongovernmental research and extension from the agricultural organizations for supporting government efforts to sector? (1) implement CSA; and (4) producers that actually implement 14c. [If yes to 14b.] CSA practices. Cooperation among stakeholders in these Does the committee four groups has the potential to improve the design and include civil society implementation of CSA policies by allowing various representation? (1) stakeholders to voice their needs and concerns, to be 14d. Does the major more aware and responsive to the needs and concerns of CC strategy (including other actors, and to create opportunities for knowledge NAPA and NAMA) exchange (World Bank 2011). Such cooperation should be express commitment to the standard among stakeholders in the agricultural sector; promoting coordination however, cooperation in many countries is challenged by among sectors including opportunistic behavior among stakeholders, lack of trust, agriculture? (1) lack of incentives for cooperation, difficulty in setting and enforcing rules, policies that are imposed without local participation, conflicting interests among land users, lack of harmony and coordination between legal bodies and procedures, poor identification of and inadequate consultation with stakeholders, and uncoordinated planning (FAO 2013; World Bank 2011). Given that the stakeholder groups identified herein are the same stakeholders responsible for development and innovation in the agricultural sector, it is expected within some countries that CSA planning implementation would be challenged by low capacity or cooperation. Climate-Smart Agriculture Indicators 73 APPENDIX C TECHNICAL NOTES FOR THE CSA TECHNOLOGY INDEX PRODUCTIVITY Indicator (% change # Theme Technical Notes from baseline) Crop System 1 Cereal yield Cereal yield is measured as kilograms per hectare of The technology leads to (% increase) harvested land. Crops harvested for hay or harvested an increase in yields of the green for food, feed, or silage and those used for grazing producers (%) are excluded. Crops include wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. The FAO assigns production data to the calendar year in which most of the harvest took place. 2 Soil erosion Soil conservation and the efficient use of water are very The technology reduces the important in countries affected by climate change. For share of agricultural land example, conservation agriculture can reduce the runoff classified as having moderate to and erosion of the soil and allow it to retain more water severe water erosion risk (%) and nutrients. This technique also permits the soil to The technology reduces the incorporate more carbon and to reduce carbon emissions share of agricultural land from soils. classified as having moderate to severe water wind risk (%) 3 Soil fertility Until recently, farmers’ knowledge of soil fertility has been The technology enhances soil largely ignored by soil researchers, but with increasing fertility (%) use of participatory research approaches, it is becoming clear that farmers have a well-developed ability to perceive differences in the level of fertility between and within fields on their farms. For example, the soil classification systems of the hill farmers of Nepal have already been documented (Tamang 1991, 1992; Turton et al. 1995), and these studies have shown that farmers use a range of criteria, including economic influences, to categorize their Climate-Smart Agriculture Indicators 75 Indicator (% change # Theme Technical Notes from baseline) soils, but that soil color and texture are the dominant criteria. They also see the actual fertility of a soil at any time as a function not only of these longer-term soil properties but also of the current and past management regime. # Theme Technical Notes Indicator (scale 1–5)1 4 Enhances Enhancement includes off-farm benefits (for example, The technology enhances biodiversity catchment protection, biodiversity corridors). Agricultural biodiversity of the farming biodiversity in time and space increases resilience in landscape in comparison with myriad ways: complementary use of soil nutrients and current interventions in similar water, decreased risk from one crop failure, and pest farming systems protection. Indicator (% change Theme Technical Notes from baseline) Water Use 5 Agricultural Water management is a critical component of adaptation The technology increases the irrigated land to both climate and socioeconomic pressures. Practices share of irrigated agricultural (% of total that improve irrigation performance and water land as a result of the agricultural management are critical to ensure the availability of technology (%) land) water both for food production and for competing human and environmental needs. 6 Water Agricultural water withdrawal is a serious concern, The technology reduces water withdrawal for especially in arid and semi-arid areas where water withdrawal for agriculture agriculture is scarce and highly variable from year to year. It is use as a share of total water necessary to irrigate certain crops to obtain reasonable withdrawal (%) yields. •  Estimation of water withdrawal for countries with unavailable national statistics using a water requirement ratio •  Estimation of irrigation water withdrawal by country •  Corrections of agriculture water requirement and water withdrawal •  Pressure on water resources due to agriculture: regional summary of the water requirement ratio Energy 7 Agriculture Future agricultural sustainability will be achieved from an The technology reduces the energy use equilibrated solution of many productive, environmental, agricultural energy use as a and economic issues. Among these, improved energy share of total household energy efficiency and reduced GHG emissions are fundamental. use (%) Pest 8 Pest Many insects, diseases, and weeds, generally defined The technology increases the Management management as crop “pests,” are an integral component of agro- share of agricultural land ecosystems. In naturally established agricultural systems, on which integrated pest “pest” species are in a shifting balance with other species management practices are (including those of their own natural enemies—parasites adopted (%) and predators) and crops as components of local food webs. Understanding the local agro-ecological balance is at the core of most CSA practices. 1 In comparison with other implemented CSA technologies in the same farming system (survey using the Likert system); for example, 1. Strongly disagree, 2. Disagree, 3. Neither agree nor disagree, 4. Agree, 5. Strongly agree. 76 Agriculture Global Practice Discussion Paper # Theme Technical Notes Indicator (scale 1–5)2 Livestock 9 Livestock Maintaining a diverse stock represents a critical The technology improves System diversification adaptation measure. The preference for different livestock livestock diversification in types depends on the availability of fodder, the capacity comparison with current to thrive on crop residues, and disease resistance. interventions in similar farming systems 10 Resource Pastoralists, for example, apply management strategies The technology improves management in times of drought, which include the use of emergency livestock resource management fodder in the form of grazing enclosures, culling of weak in comparison with current livestock, and keeping more than one species of stock. interventions in similar farming systems 11 Feed Many nonrangeland livestock farms rely on crop residues The technology improves feed production or purchased inputs to feed livestock. The pressure for production in comparison with technologies land to produce food for human consumption means current interventions in similar that innovative ways are needed to produce feed such farming systems as agricultural by-products or household and industrial waste products. 12 Diversification Livestock farmers have often turned to crop cultivation The technology leads to the of livelihood as a means of supplementing livestock incomes. Many diversification of livelihood activities former pastoralists are now mixed farmers, sometimes activities in comparison with referred to as agro-pastoralists, combining transhumant current interventions in similar livestock keeping with crop production. farming systems RESILIENCE # Theme Technical Notes Indicator (scale 1–5) 3 Robustness 13 Human capital Human capital includes knowledge, skills, competencies, The technology will improve and attributes embodied in individuals that facilitate the the human capital (technical creation of personal, social, and economic well-being. skill levels) of producers in the It is created through lifelong experience and formal target area education. Human capital within agriculture may be defined to include the years of field-level experience in agriculture, variety and levels of agriculture-related technical skills, and their level of motivation. 14 Income and Participation in off-farm activities increases the incomes The technology will increase food security of the smallholders, provides them with capital to invest the stability of agricultural in farm production, and makes social structures more production needed to help flexible. producers meet their own basic food security and income needs 15 Diversified The technology will promote income the diversification of the income and asset bases of producers 2 Likert scale unless indicated. In comparison with other implemented CSA technologies in the same farming system (Likert survey of project leaders, experts, and farmers); for example, 1. Strongly disagree, 2. Disagree, 3. Neither agree nor disagree, 4. Agree, 5. Strongly agree. 3 Likert scale unless indicated. In comparison with other implemented CSA technologies in the same farming system (Likert survey of project leaders, experts, and farmers); for example, 1. Strongly disagree, 2. Disagree, 3. Neither agree nor disagree, 4. Agree, 5. Strongly agree. Climate-Smart Agriculture Indicators 77 # Theme Technical Notes Indicator (scale 1–5) 16 Crop/livestockCrop diversification ensures that incomes can be derived The technology will promote diversification from produce as different produce have different market crop diversification in the target values. For example, using nitrogen-fixing plants reduces area the need for inorganic fertilizer, thereby reducing the cash expenditure of smallholder farms. 17 Site-specific Indigenous communities have long been recognized as The technology will involve the knowledge being particularly vulnerable to the impacts of climate incorporation of site-specific4 change because of the close connection between their knowledge in its application livelihoods and their environment. However, at the same time, this long-established relationship with the natural environment affords many indigenous peoples with knowledge that they are now using to respond to the impacts of climate change. 18 Intellectual Intellectual property rights provide incentives, for The producers in the target area property example, for research scientists to invest in breeding will have appropriate access rights improved varieties, and for seed companies to invest in to intellectual property rights ensuring that they market homogeneous, high-quality needed for the deployment of seed. These IPRs, if inaccessible, may impede innovation the CSA technology and/or access to improved varieties for smallholders in farming systems in many developing countries. Self- 19 Cooperation This refers to local support networks with roots in the The technology will facilitate organization5 and networks local community. This can also be the basis for a durable cooperation and networking relationship with consumers. among producers 20 Local market Some CSA practices, if properly implemented, can support The technology will foster local networks the development and expansion of smallholders and and regional production and regional food enterprises to increase domestic consumption supply chains of, and access to, locally and regionally produced agricultural products, and to develop new market opportunities for crop and livestock operations serving local markets. 21 Feedback from Sustained communication channels need to be established The intervention will provide extension to provide information and feedback to farmers from opportunities for feedback from workers extension systems. extension workers 22 Power Differential power relations and access to resources The CSA service will narrow differentials between men and women often result in different levels existing power differentials in of vulnerability and adaptive capacity to risks such as the community droughts, floods, and storms. Women often have fewer rights to land, credit, and capital that would facilitate adaptation, and build resilience, to climate change. 23 Gender Even where there is a lack of researched evidence, it is The technology will contribute positive/ commonly recognized that climate change exacerbates to reducing existing gender negative existing inequalities. A gender-sensitive response requires inequalities an understanding of existing inequalities between women and men, and of the ways in which climate change can exacerbate these inequalities. 4 Indigenous knowledge: “local, orally transmitted, a consequence of practical engagement reinforced by experience, empirical rather than theoretical, repetitive, fluid and negotiable, shared but asymmetrically distributed, largely functional, and embedded in a more encompassing cultural matrix” (Buchmann and Darnhoffer). 5 The capacity for self-organization is cited as one of the three properties common to all resilient systems. Individuals, local and regional networks, and smaller institu- tions of governance can be more responsive and adaptable to changing conditions than can larger groups. Any configuration that they create is more likely to contribute to overall system resilience in the long term because it was created by their own initiative. 78 Agriculture Global Practice Discussion Paper # Theme Technical Notes Indicator (scale 1–5) Cropping 24 Resilience For example, a measure of resilience in agriculture, in The technology will increase System to adverse the wake of severe and sustained droughts, is derived as the resilience of the cropping weather the ability to continue farming by saving and carrying system to drought (Milestad and forward water through the adoption of water-efficient Darnhofer technology (Ranjan and Athalye 2008). Findings indicate 2003) that behavioral factors dominate the decision to adopt when the economic factors, such as the price of water, do not capture the true opportunity costs of water. The range of available technological options is crucial, too, because marginal improvements in technology do not lead to adoption. Such resilience refers to a farmer’s ability to secure food, income, safe evacuation during flooding, and recovery after floods. Livestock 25 Resilience In Sub-Saharan Africa, for example, an observable effect The technology will increase System to adverse of drought is the transfer of livestock ownership to crop the resilience of the livestock to weather farmers, which is partially the result of capitalization of drought agricultural surpluses, especially in the cotton-producing areas. Adaptation strategies that pastoralists apply in times of drought include the use of emergency fodder in the form of grazing enclosures and keeping more than one species of stock. Pastoral women play an important role in natural resource management, harvesting wild food during drought and harvesting other products that have market value such as honey. MITIGATION # Theme Technical Notes Indicator (scale 1–5)6 26 Emissions Emission intensity per calorie is computed by summing The technology meets emissions intensity fertilizer, machinery, and labor emissions and dividing intensity targets those by the total calories contained in primary crop products. These targets are different for different farming practices and reflect the lowest observed emission intensities within a group of similar countries. The FAO (FAOSTAT GHG) has computed emissions/carbon intensity for nearly 200 countries for the reference period 1961–2010, covering emissions of non-CO2 gases (CH4 and N2O) from enteric fermentation; manure management systems; synthetic fertilizers; manure applied to soils and left on pastures; crop residues; and rice cultivation. 27 Sequesters Improved agricultural practices can help mitigate climate The technology sequesters carbon change by reducing emissions from agriculture and other carbon in comparison with sources and by storing carbon in plant biomass and soils. current interventions in similar A higher amount of organic carbon in soils would also farming systems lead to increased soil fertility and therefore increased agricultural productivity. 6 In comparison with other implemented CSA technologies in the same farming system (survey using the Likert system); for example, 1. Strongly disagree, 2. Disagree, 3. Neither agree nor disagree, 4. Agree, 5. Strongly agree. Climate-Smart Agriculture Indicators 79 APPENDIX D TECHNICAL NOTES FOR THE CSA RESULTS INDEX The CSA Results indicators are part of the set of three CSA-related indicators: CSA Technology, CSA Policy, and CSA Results indicators. The CSA-Res indicator set has two purposes: i.  It informs stakeholders about indicators for relevant M&E systems in CSA interventions. The CSA Results indicators are associated with an impact pathway (focusing on outputs and medium- to long-term outcomes) and a theory of change, which explains how a CSA intervention can lead to the desirable development impacts in the long term. This embedment is crucial because long-term impacts are not easily measured by this type of indicator. Instead, the CSA Results indicators focus on measurable project results—­ outputs, outcomes—which can eventually lead to these impacts. ii.  The set of CSA Results indicators will be the basis for the calculation of the CSA Results Index, which provides stakeholders with an indication of how the respective project has performed in reaching its targets in the CSA triple-win areas—Resilience, Mitigation, and Productivity—separately and jointly. To derive the index, the following steps are required: 1. Designing the results framework and choosing indicators. A project team designs a results framework and chooses indicators to measure the Project Develop- ment Objective and the project’s Intermediate results. Ideally, CSA indicators are applied if suitable. For calculating the index, the core CSA-Res indicators are recommended (chapter 3, page 22). 2. Target values are defined. For each indicator, a baseline value and a target value to be reached at the end of the project, and for each fiscal year or other relevant time interval, are set. 3. The indicators are assigned to the CSA triple-win areas. The chosen indicators are assigned to one or multiple triple-win areas—Productivity, Resilience, and Mitigation, indicating that the outputs or outcomes that are monitored contribute in par- ticular to these specific CSA goals. For the set of CSA indicators, a default assignment has been proposed. However, for the calculation of the index, the default assignment can Climate-Smart Agriculture Indicators 81 be changed according to the project’s goals or needs; and use the core CSA-Res indicators. This allows compar- of course, multiple assignments of a single indicator ing in which area the project has achieved satisfactory are possible. or unsatisfactory results or results exceeding expecta- 4. Scoring of the indicators. In the next steps, tion, and thus where it has room for improvements. the indicators are scored according to whether they have 6. Averaging scores over the triple-win reached the proposed target value, exceeded it, or failed areas. In a last step, the average score over the triple- to reach it. More specifically, the following scoring win areas is calculated, providing an overall estimate scheme is proposed: as to how well the project has jointly achieved the CSA goals. Level of Score Performance Interpretation Categories: The CSA results indicators are categorized as follows: 1 Very unsatisfactory The indicator’s observed value falls i.  Indicators measuring the direct outputs of a CSA ­intervention short of the target value by more a. Beneficiaries than 20%. b. Land area 2 Rather unsatisfactory The indicator’s observed value falls short of the target value between c. Livestock 1% and 20%. ii.  Indicators measuring the CSA enabling environment (which 3 Satisfactory The indicator’s observed value is may or may not be a consequence of an intervention) equal to the indicator’s target value. iii.  Indicators measuring the medium- to long-term consequences 4 Exceeding The indicator’s observed value of CSA intervention expectations exceeds the target value between 1% a. Resources and 20%. b. Emission 5 Highly exceeding The indicator’s observed value c. Yield expectations exceeds the target value by more d. Benefits than 20%. The first category measures the scope of the CSA We propose a threshold of 20 percent to determine intervention and the results that the intervention has whether an indicator has achieved a score of 2 or 4. achieved; the second category shows the strength of the The scoring can take place at the end of the project enabling environment for CSA in the project area, which or throughout project implementation whenever new allows actors to sustainably implement their CSA; the M&E data are available. third category indicates the medium- to long-term out- 5. Averaging the scores for each triple-win comes (for example, as resulting from activities measured area. In the next step, for each triple-win area P, R, by I and II) achieved by CSA. M, the scores of the indicators that have been assigned to the area in step 3 are averaged, yielding an overall The CSA Results indicators are closely aligned to the score for the triple-win area. Users are recommended to World Bank Core Sector Indicators. 82 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area I. Indicators measuring the direct outputs of a CSA intervention Topic: Beneficiaries 1 Number of Number The indicator measures the number of people/units adopting R agricultural actors CSA practices in the project area. who adopted CSA CSA triple-win area: practices1 promoted ––The assignment to the triple-win area is “Resilience.” by the project Enabling agricultural actors to adopt CSA practices allows (disaggregated by them to enhance their resilience against climate and other gender) environmental shocks. The assignment of R is justified by its Subindicator: explicit focus on actors, instead of for example, land area, which would instead capture the categories Productivity or Mitigation. Number of agricultural actors who adopt a World Bank Core Sector Indicator: specific CSA practice ––This indicator is related to World Bank Core Sector promoted by the project Indicators: “Clients who have adopted an improved agricultural technology promoted by the project (number),” “Land users adopting sustainable land management practices as a result of the project (number)”; GDPRD (2008): “Percentage of farmers who adopted sustainable crop management practices in their farms.” Guidance : ––“Agricultural actors” refers to individuals, such as farmers or producers, farmer organizations, agribusiness, SMEs benefiting from a project/program. –– “Adoption” refers to a change in practices that were introduced or promoted by the project (similar to the Core Sector Indicators) compared with current practices. The term “adopt” is frequently used in a results framework, for example, in the GDPRD 2008 Core Sector Indicators, and rests on the belief that beneficiaries will apply or use the practice once it has been adopted.2 ––If the indicator is used as project monitoring, “adopted” could refer to “newly adopted since the last survey.” This will result in a cumulative number of beneficiaries who have adopted CSA practices as promoted by the project. ––CSA practices: The indicator should make explicit which CSA practice is being promoted by the project and should be expressed separately for each relevant CSA practice promoted by the project. ––Combination of practices: This indicator includes actors who have adopted one or more CSA practice promoted by the project, if several practices are promoted by the project. 1 A list of practices/techniques that are considered CSA will be provided in the Report. CSA practices span agronomic practices such as conservation agriculture, no tillage, applying improved seeds, sustainable management of fertilizer, such as matching the nutrients with plant needs during the growing season, fractioning the total amount in multiple doses, precision farming and placing nutrients closer to plant roots, such as deep placement of urea for improved rice conditions, sustainable management of herbicides, pesticides, and so on, water management, improved feeding strategies, rotational grazing, pasture management or manure treatment, and agro-forestry. 2 If this is not the case, an additional indicator specifying the use or application of a practice should be adopted. Climate-Smart Agriculture Indicators 83 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area The baseline values are typically assumed to be zero at the beginning of the project. ––To measure this indicator, formal surveys can be carried out at regular intervals during the project and at the end of the project. Depending on survey method, the indicator can be measured in percentage of agricultural actors. Subindicators: ––Although the main indicator also encompasses agricultural actors who have adopted one or several practices, this subindicator allows one to specify which specific CSA practices have been adopted. Topic: Land use/cover The following indicators on land use/cover can be used individually or as a set to capture the landscape approach to assess how changes in land use, for example, the adoption of a new CSA practice, affect the landscape and other land covers. 2 Land area where Ha The indicator constitutes a proxy indicator for the effects of P, R, M CSA practices have the adoption of the CSA practice on production, environment, been adopted as a and natural resources from farm scale to landscape scale. result of the project Information about the land area under a CSA practice can Subindicator: serve as a basis to calculate the extent of production, pressure of agricultural practices on the environment and natural Land area where resources, potential for soil carbon sequestration, because the specific CSA environmental impact as such (for example, soil erosion, nitrate practices have been leaching or GHG emission) may be more difficult and costly to adopted as a result of measure than land area. the project CSA triple-win area: ––The indicator is assigned to all categories of “Productivity” and “Mitigation.” It demonstrates changes in production per hectare and changes in GHG emission and soil carbon sequestration as a consequence of the project. It is expected that CSA practices have positive environmental externalities, increasing, for example, soil fertility, soil moisture, and water retention, thus enhancing “Resilience” of the social and natural system. World Bank Core Sector Indicators: ––“Land area where sustainable land management practices have been adopted as a result of the project (ha).” Guidance: ––Although the extent of CSA adoption can be measured by multiplying the number of beneficiaries who have applied the practice by the average land area they possess, the present indicator is expected to provide a more reliable measure. This may be relevant when CSA practices are not applied on the entire cropland, and farm size varies considerably in the project area. ––To measure this indicator, formal surveys should be carried out at regular intervals during the project and at the end of 84 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area    the project. In each survey, the area newly brought under CSA practice should be measured. This will result in a cumulative number of beneficiaries who have adopted CSA practices as promoted by the project. ––“Adoption” refers to a change in practices that were introduced or promoted by the project (similar to the Core Sector Indicators) compared with current practices. ––Baseline at the beginning of the project may be zero. 3 Land area provided On land area under new or improved irrigation and drainage P with systems, allow monitoring of the extent of irrigation activities (R, M) i. new, in a project area. With additional data about the irrigation ii. improved system, it allows calculating the volume and extent of water withdrawal on the farm/field/irrigation system level and irrigation and provides insights on energy use, cost, and profitability of drainage services agricultural production in the area. It does not convey Subindicator Land area information about the water return flows, or pressure on the provided with water resource in terms of quality or quantity or impact on i. new, soil resources. The introduction of irrigation systems also does ii. improved not imply that the irrigation system is adequate in relation to irrigation and drainage the social or environmental context or is economically viable. services that provide Thus, the GDPRD (2008) suggests measuring the adoption of climate change a “functioning (reliable and adequate) irrigation and drainage adaptation or mitigation network.” Observing increasing or decreasing values of this cobenefits indicator must be interpreted within the context of the project, but cannot be automatically assumed to be a positive or negative development. Further, the introduction of irrigation systems cannot automatically be assumed to be a CSA practice. It may improve adaptation and adaptive capacity to climate change but whether there are mitigation cobenefits will depend on the type of irrigation system. The subindicator thus suggests measuring separately those irrigation systems that satisfy the World Bank’s climate change cobenefit criteria. CSA triple-win areas: ––Irrigated agriculture typically increases yields per hectare, thus placing it in the area “Productivity.” The area “Resilience,” is tentatively assigned. Whereas the farmers’ adaptive capacity and thus resilience to climate risk may increase as they can stabilize the production levels through irrigation, the impact on water resources on farm to basin level needs to be examined before category “R” can be assigned with confidence. The category “Mitigation” can be assigned if the mitigation cobenefits can be confirmed. World Bank Core Sector Indicator: ––“Area provided with irrigation and drainage services (ha)” (new/improved) Guidance: ––Changes in the land under irrigation and drainage can be expressed as a percentage of total cropland in the project area. Climate-Smart Agriculture Indicators 85 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area ––Irrigation typically refers to purposely providing land with water other than rain for improving pasture and crop production. Irrigation usually implies the existence of infrastructure and equipment. It also includes manual watering of plants, using buckets, watering cans, or other devices. Land that received at least one controlled irrigation a year is considered irrigated (GDPRD 2008). ––(According to World Bank SDN Core Sector Indicators) “new” irrigation and drainage refers to an area that is newly provided with irrigation and drainage and may have been previously rain fed. “Improved” refers to upgrading, rehabilitation, and modernization of irrigation and drainage services in an area with existing irrigation and drainage services. ––This indicator is applicable to monitoring progress throughout a project and early output of an intervention. When the indicator is used for monitoring purposes and collected on a regular basis, it should capture the ––“Newly provided new/improved irrigation and drainage systems since the last survey.” This will result into a cumulative number of beneficiaries who have adopted CSA practices as promoted by the project. ––The baseline at the beginning of the project may be zero. ––The FAO Statistical Development Series suggests irrigation data collection according to land use type, method of irrigation, and area of specific crops irrigated (FAO 2010). ––Similar indicators provided by, for example, GDPRD (2008): “Irrigated land as percentage of cropland,” “percentage change in the proportion of farmers with access to a functioning (reliable and adequate) irrigation and drainage network,” “percentage change in the number of users.” Climate adaptation and mitigation cobenefits: To qualify for a climate-smart irrigation system, the irrigation systems have to fulfill the criteria of climate adaptation and mitigation cobenefits specified for World Bank projects. The indicator should be collected separately for irrigation systems that provide adaptation benefits or mitigation benefits or both. The indicator should explicitly specify which cobenefits it is collecting. Climate adaptation cobenefits: ––Change irrigation management systems and practices to reduce vulnerability to climate change and climate variability to, for example, improve water distribution strategies, change crop and irrigation schedules to use rainfall more effectively, recycle water, and improve and strengthen farm-level managerial capacity. ––Plant hedges and cover crops to reduce evaporation and soil moisture loss. 86 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area ––Reduce water use in land preparation and loss in crop growth stages. ––Promote technologies that improve water management efficiency and access to irrigation and more efficient irrigation technologies. ––Introduce integrated ecosystem management approaches for watersheds and wetlands to reduce vulnerability to CC and CV. ––Construct dams and water storage systems, for example, rainwater capture to manage changes in the water cycles due to CC and CV. ––Incorporate risks from CC and CV in irrigation and water management planning ––Introduce capacity building for farmers to incorporate CC and CV ––Monitor impacts of CC and CV from water management ––Establish early warning systems to support climate-resilient water management. Climate mitigation cobenefits: ––Introduce or expand water pumping for irrigation using renewable energy sources. ––Replace existing water pumps with more energy-efficient pumps. ––Replace existing diesel pumps with electric pumps. ––Revise irrigation water pricing policies and introduce incentives for increasing water use efficiency. ––Restore natural drainage regime that sequesters carbon. ––Promote sustainable water management practices that promote water use efficiency. 4 Area restored, or re/ Ha This indicator measures the land area targeted by the project R, M afforested as a result that has been restored or re/afforested. of the project Owing to carbon sequestration, forestry has a significant potential to offset GHG emissions from the agricultural sector. CSA triple-win area: ––The indicator measures activities that support “Resilience” of the natural system and “Mitigation.” World Bank Core Sector Indicator: ––“Area restored or re/afforested (ha)” Guidance: ––Baseline value may be zero. ––“Restoration” refers to restoration of degraded land where the objective is to have permanent improvement in the capacity of the forestland area to provide environmental, social or economic services. ––“Re/afforested” refers to planting or deliberately seeding land that had not been previously classified as forest or the reestablishment of forest through planting or deliberate Climate-Smart Agriculture Indicators 87 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area seeding on land classified as forest. This can include assisted natural regeneration, coppicing, or other appropriate methods. According to the CSA sourcebook: re/afforestation is the conversion from other land uses into forest, or the increase of the canopy cover to above a 10% threshold. ––This indicator allows one to calculate the “growing stock per hectare of forest (m3/ha),” which is the volume of standing trees that can be converted to biomass and carbon stocks using conversion factors provided by the IPCC. 5 Land area covered Ha This indicator captures trends in restoration, re/afforestation, R, M by forest and reduced deforestation that may be relevant. It reflects the proportion of forest area to total land area expressed as a percentage. “Forest” is defined in the Food and Agriculture Organization’s Global Forest Resources Assessment as land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10%, or trees able to reach these thresholds in situ. It does not include land that is predominantly under agricultural or urban land use. The indicator is also a Millennium Development Goal (MDG) indicator.3 CSA triple-win area: ––The indicator measures activities that support the “Resilience” of the natural system and “Mitigation.” Guidance: ––Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters (m) in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10% and a tree height of 5 m are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate. ––Includes: Areas with bamboo and palms, provided that height and canopy cover criteria are met; forest roads, firebreaks, and other small open areas; areas in national parks, nature reserves, and other protected areas such as those of specific scientific, historical, cultural, or spiritual interest; windbreaks, shelterbelts, and corridors of trees with an area of more than 0.5 ha and width of more than 20 m; plantations primarily used for forestry or protective purposes such as rubber-wood plantations and cork oak stands. ––Excludes: Tree stands in agricultural production systems, for example, in fruit plantations and agro-forestry systems. The term also excludes trees in urban parks and gardens.4 3 http://mdgs.un.org/unsd/mdg/Metadata.aspx. 4 http://mdgs.un.org/unsd/mdg/Metadata.aspx. 88 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 6 Land area under Ha This indicator aims to measure changes in other land uses or R, M other land uses or land cover classes that are a consequence of changes in areas land cover under CSA. This indicator can be customized according to land covers/uses that may be indirectly affected by the CSA intervention or other changes. Indicators 2–6 monitor and track changes in land use and land cover, and raise awareness for the importance of viewing a CSA intervention within a broader perspective, thus adopting a landscape approach. A sustainable landscape approach describes interventions at spatial scales that attempt to optimize the spatial relations and interactions among a range of land cover types, institutions, and human activities in an area of interest. CSA triple-win area: ––Depending on the type of land cover and land use examined, changes in the indicator may affect the dimensions “Resilience” of the natural system and “Mitigation.” Guidance: ––According to the FAO, land cover represents the observed biophysical cover of Earth’s surface. Land use signifies the arrangements, activities, and inputs people undertake in a certain land cover type to produce or maintain it. ––According to the U.S. Geological Survey Land Cover Institute, land cover classifications include (http://landcover. usgs.gov/classes.php): •  Water, •  Barren (bare rock, sand, clay; transitional), •  Scrublands, herbaceous upland natural (for example, grasslands/herbaceous), •  Wetlands (woody wetlands, emergent herbaceous wetlands), •  Developed (low/high intensity residential; commercial/ industrial/transportation), •  Forested upland, •  Non-natural woody, •  Herbaceous planted/cultivated (pasture, row crops, small grains, fallow, grasses, recreational) Topic: Livestock 7 Number of livestock Livestock contribute to climate change by emitting GHGs units subject to CSA either directly (for example, from enteric fermentation and practices as a result manure management) or indirectly (for example, from feed- of the project production activities, conversion of forest into pasture). Subindicators: Increasing efficiency in resource use (for example, kilograms of phosphorus used per unit of meat produced, or hectares Number of livestock of land mobilized per unit of milk produced) is an important subject to CSA practices component to improving the sector’s environmental by livestock groups sustainability. The concept can be extended to the amount as a result of the project Climate-Smart Agriculture Indicators 89 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area Number of livestock by of emissions generated by unit of output (for example, GHG P, M livestock groups/livestock emissions per unit of eggs produced). Several CSA practices unit subject to specific are suggested to improve reproduction rates, reduce mortality, CSA practices as a and reduce the slaughter age: improved feed conversion result of the project efficiency, thereby reducing enteric emission intensities; better nutrition; improved animal husbandry; regular maintenance of animal health; and the responsible use of antibiotics. All of these measures may therefore increase the amount of output produced for a given level of emissions (FAO, CSA Sourcebook). The indicator helps to capture the extent of CSA practices throughout project implementation as well as on national scale (see the following). CSA triple-win area: ––“Productivity” and “Mitigation” are assigned. Guidance: ––Livestock unit: “Livestock units, used for aggregating the numbers of different categories of livestock, are usually derived in terms of relative feed requirements. Conversion ratios are generally based on metabolizable energy requirements, with one unit being considered as the needs for maintenance and production of a typical dairy cow and calf.” Densities of grazing livestock units per hectare of agricultural land and of total livestock units per person engaged in agriculture may then be calculated. ––Conversion rates suggested by FAO can be found at http:// www.fao.org/docrep/014/i2294e/i2294e00.pdf ––The indicator may be calculated specifically for livestock units by livestock group or specifically for applied CSA practices. ––Livestock groups: Cattle, buffalo, sheep, goats, poultry, pigs, horses, mules, asses5 ––Baseline in the beginning of the project is typically assumed to be zero. II Indicators measuring the CSA enabling environment (which may or may not be a consequence of an intervention) Topic: Enabling Environment 8 Client days of Number This is a Sustainable Development Network CSI. It records the R training on CSA number of CSA agricultural actors targeted by the project who provided have completed the training multiplied by the duration of the (disaggregated by training expressed in days. The agricultural actors, or clients, gender) can refer to farmers, extension agents, community members, business owners, or scientists. Training may include formal or informal training, vocational, on-the-job training, field demonstrations, and so on, completed by the beneficiary. 5 http://www.fao.org/docrep/014/i2294e/i2294e00.pdf, table 1 annex 1. 90 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area The indicator can be complemented by additional indicators that assess the quality and usefulness of training. CSA triple-win area: ––The indicators approximate the capacity and skills of agricultural actors, increasing their adaptive capacity to prevent and withstand shocks and thus they are placed under “Resilience.” World Bank Core Sector Indicator: ––“Client days of training provided (number)” Guidance: ––Baseline may be zero ––“Training” refers to any training organized or provided by the project (formal or informal training degree and nondegree courses, vocational, on-the-job training, field demonstration, study tours, and so on, completed by client. Depending on the project context, the indicator can be collected separately. ––The time interval needs to be defined, for example, referring to beneficiary days since the last survey or beneficiary days per year. 9 Number of Number Agriculture is facing new challenges related to production and R agricultural actors market risks. ICT, that is, any device, tool, or application that who use ICT services permits the exchange or collection of data through interaction for obtaining or transmission, can help in providing timely information to information on: allow prompt action. ICT is an umbrella term that includes a.  weather and anything ranging from radio to satellite imagery to mobile climate phones or electronic money transfers. The increases in their b. C  SA practices affordability, accessibility, and adaptability have resulted in c. m  arket (price) their use even within rural areas relying on agriculture.6 This information indicator can measure the use of ICT by gender, by device, and by topic, for example, ICT used to convey information (disaggregated by related to production risk and thus providing weather and gender) climate information, or related to other risks such as market risks and providing price information. CSA triple-win area: ––ICT tools have the potential to increase actors’ adaptive capacity and thus is placed under “Resilience” Guidance: ––The indicator can be disaggregated by type of information/ service (a–c) or by ICT device. ––If the services are introduced by the project, the baseline may be zero. ––Other similar services related to mobile banking, electronic money transfer, can be considered. 6 http://www.ictinagriculture.org/sourcebook/module-1-introduction-ict-agricultural-development. Climate-Smart Agriculture Indicators 91 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 10 Number of Number This indicator measures the number or share of people or R agricultural actors units who have become or are members of a project-relevant who are members of association. Farmer or producer organizations have been an association identified as important institutions for the empowerment, (disaggregated by poverty alleviation, and advancement of farmers. In many rural gender) areas they may be the only institution that provides goods and services, for example, support in receiving credit or mobilizing capital, to the rural poor and provides benefits such as increased bargaining power and resource sharing, reducing transaction costs and overcoming market entry barriers that lead to food security. Being a member of an association may thus have the potential to facilitate access to goods and services that support the achievement of CSA goals. There are many types of agricultural associations or cooperatives in the developing world (for example, community-based and resource-orientated organizations or commodity-based and market-orientated organizations, which specialize in a single commodity and operate in a competitive environment), but many of them are financially vulnerable and ineffective, so that membership in an association may not deliver the envisaged benefits to the farmers. Strategies have been developed to strengthen these organizations, their management, and business planning. Although membership in an association can enhance benefits and increase farmers’ resilience, the association will have to fulfill certain conditions and provide adequate services to the farmers to be able to improve farmers’ livelihoods, which need to be assessed before using the indicator as measure of increased resilience. CSA triple-win area: ––Being part of an association can increase actors’ capacity to adaptation, learning, skills development and thus is placed under “Resilience” World Bank Core Sector Indicators: ––“Target clients who are members of an association (percentage)” Guidance: ––In the case of a new association, the baseline will be zero. In the case of an existing association, the baseline will be the number of its members. ––An association may include formal producer associations, cooperatives, water user associations, trade associations, which either existed in the project area before the project was started or were created under the project. The indicator should specify which type of organization it is referring to and ensure that the association is well functioning and can deliver benefits to the farmers. ––A member is a beneficiary who is formally registered as a member of an association. ––Depending on the survey method, the indicator can be measured as number or percentage share. 92 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 11 Number of Number Farmers lacking access to credit and markets may be unable to R agricultural actors adopt CSA practices because benefits usually take some time to using materialize and farmers have to bear the costs in terms of labor, a.  financial services land, and cash in the meantime. Strengthening institutions of formal banking to support agricultural markets, financing mechanisms, and institutes, or insurance schemes are thus crucial to sustain the success of b. n  onbank financial CSA (FAO, CSA Sourcebook). The use of financial services services refers to loans, credit cards, and deposit accounts of different types. The agricultural census and surveys are often a source of (disaggregated by information for this indicator because the agricultural census gender) may contain a section on agricultural credit where access and use by type of credit institution are reported. Nonbank financial services refer to leasing and insurance. Insurance or leasing companies may provide information (GDPRD 2008). CSA triple-win area: ––Having access to and using financial services has the potential to increase actors’ adaptive capacity and thus is placed under “Resilience” Guidance: ––This indicator should be collected for specific types of products. For instance, insurances could include weather- index insurance. ––In defining the indicator, it is necessary to define what “using” means—how often and to which extent. 12 Number of Number This indicator is similar to the World Development indicator R agricultural actors “Employment in agriculture (% of total employment).” employed in Employees are people who work for a public or private agriculture in the employer and receive remuneration in wages, salary, project area commission, tips, piece rates, or pay in kind.7 (disaggregated by The indicator aims to measure the population in the project gender) area that is formally employed in the agricultural sector, Subindicator: possibly involved in agricultural value chains. Agricultural Number of agricultural value chains are organizational schemes that enable a primary actors employed in a product to be sold and transformed into consumable end specific activity in the products, adding value at each step of a gradual process project area of transformation and marketing. Smallholder farmers (disaggregated by often integrate in value chains as producers in the primary gender) production segment by supplying products to national and international buyers. Broadly, smallholder farmers engage in agriculture in the following forms: (i) independent primary agricultural production, which can increase their incomes; (ii) dependent primary agricultural production with an effect on incomes and employment; or (iii) value addition (post- harvest handling, processing, value addition, or the value chain 7 http://data.worldbank.org/indicator/SL.AGR.EMPL.ZS. Climate-Smart Agriculture Indicators 93 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area segment of trade and marketing) of agricultural products with an effect on incomes and employment.8 To measure employment in agriculture, this indicator aims to capture (ii) and (iii) that allow farmers to derive a stable and higher income or to diversify their sources of income, which can increase both household income and resilience. This can have a positive impact on investing in and sustaining new technologies and CSA practices on their farms. The indicator does not measure whether value chains are climate smart. The indicator does not measure the quality of employment, but needs to be complemented with additional information/indicators. CSA triple-win area: ––Being formally employed and diversifying income toward off- farm sources of income can increase farmers’ ability to cope and adjust to shocks and thus is placed under “Resilience” Guidance: ––The indicator could measure the percentage share of people in the project area involved in the agricultural sector in the project area. ––It could also measure the number of people employed as a percentage share of total employment in the project area. ––According to the project context, the areas of the value chain can be specified in separate subindicators. 13 Target population Number Several studies show that property rights or tenure security R with use or can have a positive impact on promoting investment on ownership rights land because farmers will be able to capture the returns recorded as a result from investment. It can be an incentive for long-term land of the project improvements, provide collateral for loans, and enable land (disaggregated by transfers. Thus, recorded ownership rights may have a positive gender) impact on the adoption of CSA practices. CSA triple-win area: –– “Resilience” as access to productive assets may be increased. This is a World Bank Core Sector Indicator with the following guidance notes: ––Target population refers to the population of a particular geographic area (project area, national, province, district, indigenous area) targeted by the project or any other group targeted by the intervention. ––Use or ownership rights cover the full consortium of land tenure situations, customary or statutory, individual or collective on private or public lands and can accommodate all ownership systems. 8 http://www.rural21.com/uploads/media/rural2012_04-S12-15_01.pdf. 94 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area ––“Recorded” should be interpreted as a mean to unambiguously record land tenure information in the land administration system that reflects the current situation whether graphically, textually, or numerically. It covers a wide range of mechanisms, including mapping, surveying, titling, registering, or computerizing land tenure rights. It is not restricted solely to registration or recordation of land property rights. III. Indicators measuring the medium- to long-term consequences of CSA intervention Topic: Natural resources 14 Annual total volume % This indicator aims to show the intensity of agricultural uses R of groundwater compared with total renewable but finite water resources and surface water and aims to give an indication of “unsustainable resources withdrawal for use,” in particular when measured over time to see how agricultural use, water withdrawals have evolved. This indicator is frequently expressed as a complemented with indicators measuring water withdrawal percentage of over total actual renewable water resources from other sectors the total actual such as industry and urban and municipality use. This set renewable water of indicators can give indications of increasing competition resources (in the and conflict between water uses. Increases in the value of project area) the indicator is suggested to imply negative effects on the sustainability of the natural resources base, whereas low values of the indicator can indicate potential for increase in water use in a sustainable way (MDGs).9 This measure has shortcomings. Although considering the withdrawal from agriculture over the total resources, it does not consider the return flows from agriculture, which can add up to 50% of water withdrawals (source) and thus tend to overestimate total water withdrawal. Apart from this problematic issue, the indicator provides, again, only a partial assessment of the multiple dimensions of water use. At the project level, it may be difficult to obtain the data needed to measure the indicator. Taken by itself, the indicator may not be meaningful, but could be measured together with water withdrawal from other sectors to give an indication of competing uses between sectors. It may be difficult to determine the references or desirable value that indicates “sustainable” use of the resource. Similar indicators suggested in the literature, for example, developed by the EC External Services Evaluation Unit10 are “Annual extraction from surface and groundwater in relation to its minimum annual recharge rate” and UN-Water’s “Intensity of groundwater use compared to recharge.” 9 http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=768. 10 http://ec.europa.eu/europeaid/how/evaluation/methodology/impact_indicators/wp_water_en.pdf. Climate-Smart Agriculture Indicators 95 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area CSA triple-win area: ––If water resources are used in a sustainable way, “Resilience” of the natural system can be increased. Guidance: ––Renewable water resources include surface water and groundwater resources that are renewed on a yearly basis (without consideration of the capacity to harvest and use this resource).11 ––There is no satisfactory method to take into account return flow in the computation of water resources and use. In countries where return flow represents a substantial part of water withdrawal, the indicator will tend to overestimate total water withdrawal. There is no universally agreed on method for the computation of incoming flows originating outside of countries.12 ––Sustainability assessment tries to fix critical thresholds for this indicator, but there is no consensus on such a threshold. UN-Water is currently working toward the development of a set of more satisfactory water-related indicators.13 ––Water withdrawal is never measured directly but assessed through indirect methods.14 Indirect measures may include areas equipped for irrigation, areas under different crops under irrigated and rain-fed conditions, irrigation intensity and water requirement ratios of different crops, number of irrigations provided by farmers and season, estimates of per capita consumption by animals, and so on. These data may be available from national ministries of water resources or studies using crop and irrigation data from agricultural census/ surveys to estimate water use in agriculture (GDPRD 2008). ––If applied at the project level, the relevant renewable water sources have to be clearly defined at the start of the project. To ensure comparability over time, the related concepts have to be clearly stated. ––It may be necessary to establish the methodology through working groups of local experts or consulting internationally established methods such as provided by FAO Aquastat.15 15 Land area affected Ha Land degradation is the reduction in the capacity of the P, R, M by medium to land to provide ecosystem goods and services and assure very strong/severe its functions over a period of time. Land degradation soil erosion in the encompasses several dimensions such as soil erosion, nutrient project area depletion, salinity, contamination, and physical soil problems. However, as a proportion across all degraded areas, soil erosion 11 http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=768. 12 http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=768. 13 http://mdgs.un.org/unsd/mdg/ Metadata.aspx?IndicatorId=0&SeriesId=768. 14 http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=768. 15 ftp://ftp.fao.org/agl/aglw/docs/PaperVienna2005.pdf. 96 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area is the most extensive factor, causing more than 83% of the area degraded worldwide (ranging from 99% in North America to 61% in Europe) (Oldeman et al. 1991, in Kapalanga, 2008). Thus the indicator focuses on soil erosion as proxy for land degradation. Soil erosion is a natural process, which is accelerated by the use of inadequate farming practices such as overstocking and overgrazing, deep plowing land several times a year, lack of crop rotations, or planting crops down a contour instead of along it.16 The assumption is that adequate farming practices as promoted by CSA will reduce medium to strong or severe soil erosion in the project area. CSA triple-win area: ––The indicator is assigned to “Productivity,” “Mitigation,” and “Resilience,” because decreased land degradation and decreased soil erosion can have a positive impact on all dimensions. Guidance: ––The most common methods used to assess land degradation are qualitative information such as expert or land users’ opinions; field monitoring, observations, and measurement; modeling; or remote sensing.17 ––Soil erosion is frequently classified in several categories, for example, 1–5 from very light, light, mean/medium, strong or severe, to very strong/severe. Berry et al. 2003, in Kapalanga 2008, define the following categories: 1. Very light: Very light erosion signs, the process is incipient and not very evident, some sedimentation is observed in small places where rainwater accumulates. 2. Light: Light erosion, signs begin to be visible. Removal of fine material is visible leaving the thicker material exposed (gravel, small stones), runoff water is not totally clear. 3. Mean/medium: Moderate erosion, clear signs of particle removal from the surface of the ground. Erosion is evident, with the hardpan material clearly exposed on the surface. Some rill erosion is noticeable. 4. Strong or severe erosion: Strong erosion, strong mantle erosion leaves gravel spread on the surface, rill erosion is abundant and increasing, some gullies appear in their initial state of formation. There are very few materials left from the original surface soil, the soil has begun to change in color. 16 http://www.nda.agric.za/docs/erosion/erosion.htm. 17 http://uts.cc.utexas.edu/~wd/courses/373F/notes/lec17ero.html. Climate-Smart Agriculture Indicators 97 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 5. Very strong/severe: Very strong erosion, all original surface materials have been removed, generating a change in color of the soil, a widespread change in soil texture due to the dominance of horizon C on the surface. Active gullies are observed. ––The indicator should reflect the share of cropland on which soil erosion was decreased. The land area in the project thus has to be rated first according to the above (or similar classifications); then the share of land under mean/medium to strong/severe erosion as share of total land area in the project area is calculated. Topic: Emission 16 Net carbon balance tCO2-e/ The AFOLU sector is responsible for just under a quarter M (GHG emission year (10–12 GtCO2-e/year) of anthropogenic GHG emissions, in tons of CO2-e mainly from deforestation and agricultural emissions from emission/ha/year) of livestock, soil, and nutrient management (IPCC 2014). the project This indicator allows tracking the project’s net balance from greenhouse gases, expressed in CO2-equivalents that were emitted or sequestered as a result of project implementation as compared with a business-as-usual scenario. The net carbon balance should account for the emissions from all GHGs, that is, CO2, CH4, and N2O, as well as all kinds of carbon pools that concern the AFOLU sector (above- and below-ground biomass, dead wood, litter, and soil carbon). The IPCC provides a methodology for national and subnational estimation of emissions, based on Tier 1, 2, or 3 methodologies. Tier 1 relies on a universal emission factor combined with activity data; Tier 2 utilizes a country-specific emission factor; and Tier 3 involves direct measurement or modeling approaches. Such estimates are used for both international reporting to the UNFCCC and national and subnational reporting purposes.18 There is a range of GHG accounting tools that allow the estimation of this indicator. For instance, the Ex-ante Carbon- Balance Tool (EX-ACT), developed by the FAO, provides ex ante estimates of the impact of AFOLU projects and can be used for monitoring progress.19 Considering the landscape approach, the net carbon balance can be computed for several activities separately. These activities may include land use change, improvement of crop management practices, and reduction of land degradation. Guidance: ––The net carbon balance is net balance from all GHGs expressed in CO2 equivalent that were emitted or sequestered as a result of project implementation as compared with a business-as-usual scenario. 18 http://www.nature.com/nclimate/journal/v2/n6/box/nclimate1458_BX1.html. 19 http://www.fao.org/tc/exact/ex-act-home/en/. 98 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area ––The indicator can be assessed with the GHG accounting tool EX-ACT. EX-ACT provides information of GHG emission and carbon sequestration in tCO2-e/year or for the total project period for several modules. Depending on the project needs, subindicators can be developed that provide one or more of the following: •  Net carbon balance for the project •  Net carbon balance for specific project activities (for example, deforestation, crop management, livestock) such as those activities that are already captured in CSA indicators 2–6. Gross emissions and sequestration for the total project •  Gross emissions for specific project activities. ––Time periods: Whereas the calculation of the net carbon balance typically considers 20 years (implementation period of the project, which refers to the time period when project interventions are taking place, typically 5 to 7 years; and the capitalization period, which refers to the time period after the project has ended, but biophysical processes related to biomass, soil carbon content, and so on, still continue), EX-ACT expresses the gross results and net carbon balance in tCO2-e/year ––The results can be expressed per hectare or for the entire project area. 17 GHG emission t/t In achieving food security and climate change adaptation, P, M intensity CO2-e/ increases in productivity and resilience to climate change are year the main concern among developing countries; climate change mitigation is often regarded as a cobenefit. The indicator emission intensity, that is, GHG emission per physical unit of output, accounts for these priorities. Measured over time, it shows whether the project could increase or stabilize production while lowering GHG emission per unit; by comparing projects and project activities, this measure indicates which farming systems can be incentivized to achieve the best CSA outcomes of increasing productivity and decreasing emissions. Guidance: ––GHG emission intensity is composed of kg CO2-e as numerator, and product in terms of tons of yield, milk product, animal protein in the denominator, per year, at farm gate (rather than processed products). ––The GHG emissions can be calculated using EX-ACT with Tier 1 coefficients using context-specific Tier 2 coefficients if available. Climate-Smart Agriculture Indicators 99 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area Topic: Yield 18 Crop yield in kg/ha In the past decades, crop production increased significantly, P, R kilograms per mainly owing to intensification of crop production. Although hectare and year intensification and increased input use may lead to increases in GHG emission, studies have concluded that the avoided emission from land use change outweighs this increase (FAO, CSA Sourcebook). Monitoring crop yields per hectare and year allows insights into reaching yield gap, which is essential to improve food security. “Yield gap” refers to the difference between actual and potential yield, where the yield potential should ideally be collected from the project area rather than using national crop statistics (GDPRD 2008). Depending on the project context, crop yield of a specific crop or cereal yield can be considered. “The aggregation of production weights across food types is problematic if roots and tubers with low carbohydrate contents are aggregated with pulses and cereals. If comparisons are made between new year and historic production of all food crops, the usual convention is to calculate total production in cereal equivalents (of the most commonly consumed cereal) and to compare total cereal equivalent production in the new year with the equivalent calculations for past years.”20 CSA triple-win area: ––Increased crop yield relates to increased “Productivity” and household “Resilience,” as they may be better able to withstand shocks. Guidance: ––According to World Development Indicators, cereal yields per hectare and year include wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.21 To convert other crops to cereal, the following FAO conversion rates could be used (ftp://ftp.fao.org/docrep/fao/011/i0515e/i0515e26.pdf): ––Although crop yields per hectare per year can be measured year by year, statistically significant trends in crop yields may become visible only after a few years, as rain-fed production areas often experience high year-to-year fluctuations. This indicator requires a time series of crop yields per unit of land area over the project time period. ––Changes in crop yields are expected to be a longer-term outcome of CSA interventions, which is measured by the indicator “Land area where CSA practices have been adopted as a result of the project.” 20 ftp://ftp.fao.org/docrep/fao/011/i0515e/i0515e26.pdf. 21 http://data.worldbank.org/indicator/AG.YLD.CREL.KG. 100 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area ––Besides providing cereal yield, the indicator can be represented for each crop separately. ––The baseline has to be determined by project-specific surveys. 19 Yield variability per standard Indicator 19 focuses on changes in mean yield as a response to R hectare and year and deviation/ CSA practices. An indicator on yield variability is needed to crop mean assess the stability of food supply. A recent study demonstrated that in the past, climate variability accounted for roughly a third of crop yield variability in key crops (maize, wheat, soybeans), on average 30%, but in some regions even causing more than 60% of the variability. Future increases in yield variability are expected, posing increasing challenges to farmers (Challinor et al. 2014).22 The coefficients of variation measure is frequently used to assess yield variability. It is a relative measure of variation, defined as the standard deviation expressed as a percentage of the mean. Ray et al. (2015) assessed the CV for several crops for a period of 30 years and found that maize yields had a global average variability of ~0.9 tons/ha/year (s.d.), which corresponds to ~22% of the global average yields of ~4 tons/ha/year. The global average rice yield variability was 13% of average rice yields and the global average wheat yield variability (s.d.) was 0.4 tons/ha/ year (~17% of average yields over the study period). CSA triple-win area: ––A low coefficient of variation over a long time period in which, for example, erratic or extreme weather events occur indicates high “Resilience.” Guidance: ––CV is defined as standard deviation over mean per hectare value. ––Time series data are needed to assess the baseline value. ––Depending on the project and data availability, the CV can be assessed for every year in the project or for the time of project completion (for example, if by the time of project completion the CV could be decreased compared with the baseline). 22 http://www.nature.com/nclimate/journal/v4/n4/full/nclimate2153.html. Climate-Smart Agriculture Indicators 101 CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 20 Yield per livestock kg/unit There is a need to improve the resource use and production P, R unit and year as a efficiency of livestock production systems, both to improve result of the project food security and reduce the intensity of GHG emissions Subindicator (FAO 2009a; HLPE 2012a). Yield per livestock unit refers to Yield per livestock by productivity per animal. Yield may refer to milk, eggs, meat, livestock group and year wool, per livestock. Yield per livestock unit may be a long-term as a result of the project result from previously implemented CSA practices. CSA triple-win area: ––Increased yield relates to increased “Productivity” and household “Resilience,” because they may be better able to withstand shocks. Although the introduction of improved feeding and breeding practices can affect yield and reduce GHG emissions from livestock, mitigation cobenefits will be captured by the indicator “GHG emission intensity.” Guidance: ––Comments regarding livestock units and conversion factors, see above. ––Measurement unit can be in kilograms or other relevant physical units. ––There may be more than one product per animal; the indicator should be compiled separately per production species. ––Baseline will be established at the beginning of the project. ––Because seasonality may be important for some products, comparable time periods must be considered. ––Indicator can be upscaled from project level to national level. ––On national level data sources, livestock surveys or FAO yield livestock data are relevant sources. Topic: Benefits and welfare 21 Annual household USD Agricultural household income is considered among the key R income from indicators to monitor and evaluate the results of development agricultural activity policies and interventions. However, national statistical offices often have difficulties in providing this indicator owing to technical difficulties or data availability (Keita and Pizzoli n.d.). Often microdata on household expenditures derived from household surveys is used. Increasing trends in household income as a consequence of the intervention may be realized only several years after the intervention. Similarly, yield increases may be realized only years after the intervention and farmers may have to bear increased costs related to the adoption of the technique in the initial phase of intervention. This indicator could also be expressed in terms of annual growth rate of household income rather than an absolute measure. Complementarily, it may be interesting to look at the income from nonagricultural activities to understand how farmers diversify their income when confronted with climate- induced production risk. 102 Agriculture Global Practice Discussion Paper CSA CSA Results Triple-Win # Indicator Unit Guidance Note Area 22 Number of Number This indicator measures farmers’ perceptions and “better R beneficiaries who off” must not refer to economic improvements but can mean consider themselves different things to different people. The data can be derived better off now from project-specific surveys (GDPRD 2008). The Core Sector than before the Indicators feature an indicator “beneficiaries that feel that the intervention project investments reflected their needs.” Although the World (disaggregated by men Bank Core Sector Indicator focuses on the effectiveness of the and women) project, this indicator aims to capture whether the intervention has increased their beneficiaries’ well-being. The effect may be evident only at the end of the project or even thereafter. Guidance: ––GDPRD 2008: “Percentage of population who consider themselves better off now than 12 months ago” Climate-Smart Agriculture Indicators 103 A G R I C U LT U R E G L O B A L P R A C T I C E W O R L D B A N K G R O U P R E P O R T N U M B E R 105162-GLB 1818 H Street, NW Washington, D.C. 20433 USA Telephone: 202-473-1000 Internet: www.worldbank.org/agriculture Twitter: @WBG_agriculture