REPUBLIC OF KENYA MINISTRY OF AGRICULTURE, LIVESTOCK, FISHERIES AND COOPERATIVES KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Alliance Citation: Government of Kenya, 2021. Kenya Climate Smart Agriculture Monitoring and Evaluation Framework “All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, photocopying, recording or otherwise, for commercial purposes without prior permission. Otherwise, material in this publication may be used, shared, copied, reproduced, printed and/ or stored, provided that appropriate acknowledgement is given. In all cases the material may not be altered or otherwise modified without the express permission of Ministry of agriculture, livestock, fisheries and cooperatives”. This document has been finalized with the support from the Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) through the Initiative for Climate Action Transparency project (ICAT), initial work in developing this framework was supported through the Integrating Agriculture in National Adaptation Plans program coordinated by the Food and Agriculture Organization of the United Nations (FAO), and the United Nations Development Programme (UNDP). Additionally, this M&EF was supported by the Department for International Development through the Kenya Devolution Support Programme implemented by the UNDP Kenya country office. The views expressed in this document are those of the authors and do not necessarily represent those of the Alliance of Bioversity International and CIAT, FAO, UNDP or UNOPS.  II KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 FOREWORD Kenya’s agricultural sector has committed to contribute to the implementation of nationally determined contributions (NDCs) through the climate-smart agriculture (CSA) approach. To guide the implementation and adoption of CSA, the sector developed the Kenya Climate Smart Agriculture Strategy 2017-2026 (KCSAS) and the Kenya Climate Smart Agriculture Implementation Framework 2018-2017 (KCSAIF). These policy documents are aligned with the Climate Change Act 2016, the overarching legal framework for monitoring, reporting, and verifying climate actions in Kenya, which obligates state departments and public, national, government entities to do the following, inter alia: report on sectoral greenhouse gas (GHG) emissions and the performance and implementation of climate change duties and functions, regularly monitor and review the performance of the integrated climate change functions through sectoral mandates, and undertake investigations and report any unsatisfactory performance by statutory bodies. This mandate requires a robust and comprehensive monitoring and evaluation (M&E) system that would facilitate tracking climate action goals and objectives. This monitoring and evaluation framework (M&EF) for CSA has been developed to foster the effective transformation of the agricultural sector toward resilient, low-carbon development, and to check whether the implementation of the KCSAIF objectives, outcomes, and outputs are proceeding as planned, in order to support optimal planning and efficiency in the utilization of resources. Hon. Peter Munya, EGH Cabinet Secretary, Ministry of Agriculture, Livestock, Fisheries and Cooperatives KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 III ACKNOWLEDGEMENTS The support and goodwill from the Cabinet Secretary of the Ministry of Agriculture, Livestock, Fisheries & Cooperatives (MoALF&C) during the development of this (Monitoring & Evaluation Framework (M&EF) are immensely appreciated. The creation of this M&EF was highly consultative. We most sincerely appreciate every institution and individual that shared their time, perspectives, and expertise during the process of putting this framework together. Further, we wish to thank the technical staff from the ministries, state departments, and agencies that participated in development of this framework for their contributions. Specifically, the MoALF&C Climate Change Unit (CCU), the Kenya Agricultural and Livestock Research Organization (KALRO), the Climate Change Directorate (CCD), and the CSA-MSP members. This document has been finalized with the support from the Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) through the Initiative for Climate Action Transparency project (ICAT), the Integrating Agriculture in National Adaptation Plans program coordinated by the Food and Agriculture Organization of the United Nations (FAO), and the United Nations Development Programme (UNDP). Additionally, this M&EF was supported by the Department for International Development through the Kenya Devolution Support Programme implemented by the UNDP Kenya country office. We are immeasurably grateful for all these forms of support. Finally, we thank the CSA Multi-Stakeholder Platform team drawn from state and non-state organizations that provided expertise towards the completion of this CSA M&EF for a job well done. Prof. Hamadi I. Boga, (PhD), CBS Dr. F.O. Owino, (PhD), CBS Mr. Harry Kimtai, CBS Principal Secretary, Principal Secretary, Principal Secretary, State Department for State Department for State Department Crop Development and Fisheries, Aquaculture for Livestock Agricultural Research and the Blue Economy IV KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 EXECUTIVE SUMMARY The preparation of this M&EF is guided by Kenya Vision 2030, the Constitution, the Third Medium Term Plan 2018-2022, the Big Four Agenda on food and nutrition security, the KCSAS, the KCSAIF, and relevant government blueprints towards economic growth and development. The agricultural sector developed the KCSAS and the KCSAIF in response to climate change impacts. These policy documents are meant to guide the adoption and implementation of CSA in the country. Successful implementation of the CSA strategy and implementation framework will depend on a robust and comprehensive M&EF—hence the development of this Kenya Climate-Smart Agriculture Monitoring and Evaluation Framework. Chapter 1 gives relevant background information about the goals, objectives, and components of the KCSAIF, and about the objectives, purpose, and scope of this CSA M&EF. Chapter 2 outlines institutional arrangements, capacity building, and resource mobilization for the implementation of this framework. These arrangements typically provide the context in which the institutions in charge of coordinating climate action in agriculture carry out M&E roles, including the Ministry of Agriculture, Livestock, Fisheries and Cooperatives (MoALF&C) and county government departments. This chapter therefore describes the roles of the state departments of the MoALF&C; National Climate Change Council; the Climate Change Directorate; the Climate Change Unit (CCU); the national Multi Stakeholder Platform for Climate Smart Agriculture (CSA-MSP); the County Climate Change Units (CCCUs); the County Agriculture Sector Climate Focal Point (CASCFP); and the county CSA multi-stakeholder platforms (MSPs). It also summarizes the capacity building activities and resource mobilization actions undertaken by the MoALF&C and by stakeholders implementing the M&EF to collect data on CSA activities, and examines the infrastructural capacities to implement this framework, observing that implementing partners will develop the necessary infrastructure based on a capacity needs assessment. Within this coordination framework, the sectoral Climate Change Unit will develop a CSA management information system (MIS) and standard monitoring tools for data collection and analysis. The implementation of this CSA M&EF will involve several stakeholders and will require an estimated budget of K Sh 25 billion in the next 10 years. The elaborate M&E matrix that has been developed in Chapter 3 establishes the requisite foundation for stakeholders to efficiently track the progress of climate actions. To ensure harmony and provide coherence in reporting, the repository of indicators in this framework will facilitate efficient tracking of the outputs of the four outcomes outlined in the KCSAIF. This process will be actualized by stakeholders capturing data and information on outputs, and through evaluation of results and outcomes. To support reporting on all climate actions, the framework is flexible enough to enable each stakeholder to identify their entry point and area of specialization and report appropriately on the relevant indicators. The inclusion of metadata to outline the data collection process further enhances the accuracy of the output that this framework will generate. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 V CONTENTS FOREWORD ................................................................................................................ III ACKNOWLEDGEMENTS ............................................................................................ IV EXECUTIVE SUMMARY ................................................................................................V ABBREVIATIONS AND ACRONYMS ......................................................................... VII DEFINITION OF TERMS ............................................................................................VIII CHAPTER 1: INTRODUCTION ...................................................................................... 1 1.1 Introduction .........................................................................................................................1 1.2 Kenya Climate Smart Agriculture Implementation Framework 2018-2027 ................2 1.2.1 Goal and Objectives of the Kenya Climate Smart Agriculture Implementation Framework .................................................................................................................................... 2 1.3 Kenya Climate Smart Agriculture Implementation Framework Components ...........2 1.3.1 Institutional coordination ........................................................................................................... 2 1.3.2 Agricultural productivity and the integration of the value chain approach ....................... 3 1.3.3 Building resilience and appropriate mitigation actions ......................................................... 3 1.3.4 Communication systems for climate-smart agriculture extension and agro-weather issues .............................................................................................................................................. 3 CHAPTER 2. INSTITUTIONAL ARRANGEMENTS, CAPACITY BUILDING, AND RESOURCE MOBILIZATION ......................................................................................... 4 2.1 Climate-smart agriculture monitoring and evaluation institutions and their roles .....4 2.2 Capacity building and resource mobilization .................................................................7 2.2.1 Human capacity ........................................................................................................................... 7 2.2.2 Infrastructural capacity .............................................................................................................. 8 2.3 Resource mobilization .......................................................................................................8 CHAPTER 3: MONITORING AND EVALUATION MATRIX .......................................... 9 3.1 The Kenya Climate-Smart Agriculture Monitoring and Evaluation Framework .........9 3.1.1 Objectives of this monitoring and evaluation framework ...................................................... 9 3.1.2 Purpose and scope of this monitoring and evaluation framework ....................................... 9 3.2 Monitoring and evaluation matrix .................................................................................10 REFERENCES ...............................................................................................................33 ANNEXES ....................................................................................................................34 Annex I: Team of experts who developed this Climate-Smart Agriculture Monitoring and Evaluation Framework .............................................................................. 34 VI KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 ABBREVIATIONS AND ACRONYMS CIAT International Center for Tropical Agriculture CASCFP County Agriculture Sector Climate Focal Point CCCU County Climate Change Units CCD Climate Change Directorate CCU Climate Change Unit CO2e Carbon dioxide equivalent CSA Climate-Smart Agriculture CSA-MSP Multi Stakeholder Platform for Climate Smart Agriculture CSO Civil Society Organization FAO Food and Agriculture Organization of the United Nations GHG Greenhouse gases GoK Government of Kenya KCSAIF Kenya Climate Smart Agriculture Implementation Framework KCSAS Kenya Climate Smart Agriculture Strategy M&E Monitoring and Evaluation M&EF Monitoring and Evaluation Framework MDAs Ministries, Departments and Agencies MIS Management Information System MSP Multi-Stakeholder Platform MoALF&C Ministry of Agriculture, Livestock, Fisheries, and Cooperatives MRV+ Measurement, Reporting and Verification Mt Metric tons NDCs Nationally Determined Contributions NGO Non-Governmental Organization SME Small and Medium-sized Enterprise SMS Short Message Service TIMPs Technologies, Innovations, and Management Practices UNDP United Nations Development Programme KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 VII DEFINITION OF TERMS Term Definition as used in this framework Baseline study An analysis describing the situation in a project area – including or survey data about individual primary stakeholders – prior to a development intervention. Progress, including results and accomplishments, can be assessed and comparisons made against the baseline study. It also serves as an important reference for the completion evaluation. Climate-smart An approach to developing the technical, policy, and investment agriculture conditions to achieve sustainable agricultural development for food (CSA) security under climate change. CSA integrates the economic, social, and environmental dimensions of sustainable development by jointly addressing food security and climate challenges. It entails three main pillars: sustainably increasing agricultural productivity and incomes, adapting and building resilience to climate change, and reducing and/ or removing GHG emissions, where possible. Efficiency A measure of how economic inputs such as funds, expertise, and time are converted into outputs. Evaluation A systematic and objective examination of a planned, ongoing, or completed project. It aims at answering specific management questions and judging the overall value of a development intervention. Evaluations offer information about lessons learned to improve future decision making and commonly seek to determine the efficiency, effectiveness, impact, sustainability, and relevance of the project’s or organization’s objectives. Goal The higher-order program or sector objective to which a program or project is intended to contribute. Indicator A quantitative or qualitative factor or variable that provides a simple and reliable basis for assessing achievement, change, or performance. It is a unit of information measured over time that can help show changes in a specific condition. A given goal or development objective can have multiple indicators. Inputs The financial, human, and material resources necessary to produce the intended outputs of a project. Intervention A combination of program or project elements or strategies designed to produce behavioral changes or improve the status of value chain actors to achieve intended project objectives. VIII KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Term Definition as used in this framework Innovation A modification of an existing technology for a different use than the original intended purpose, or the application of new or existing knowledge or technology in a fresh way or context, to do something better or differently. Knowledge The systematic management of an organization's knowledge assets management for the purpose of creating value and meeting tactical and strategic requirements; it consists of the initiatives, processes, strategies, and systems that sustain and enhance the storage, assessment, sharing, refinement, and creation of knowledge. Management A system of inputting, collating, and organizing data to provide information management with selective information and reports in order to assist system (MIS) in monitoring and controlling a project’s organization, resources, activities, and results. Monitoring It is a log design that provides means for determining the progress of and evaluation a programme or a project or set of activities in regard to achievement framework of the program/project aims/objectives. It is a table that describes (M&EF) verifiable indicators used to effectively measure a program or project progress. Monitoring A table presenting the following information: performance questions; and evaluation information gathering requirements, including indicators; reflection (M&E) matrix and review events with stakeholders; and resources and activities required to implement a functional M&E system. This matrix lists how data will be collected, when, by whom, and where. Metadata Metadata means "data about data". Metadata is defined as data that furnishes information about one or more aspects of other data; it is used to summarize basic information about data which can make tracking and working with that data easier. Monitoring The regular collection and analysis of information to support timely decision making, ensure accountability, and provide a basis for evaluation and learning. Objective A specific statement detailing the desired accomplishments or outcomes of a project at different levels in the short or long term. A good objective meets the criteria of being impact-oriented, measurable, time-limited, specific, and practical. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 IX Term Definition as used in this framework Outcome The results achieved at the level of “purpose” in the objective hierarchy. It is part of impact, a result at purpose and goal level. Output Indicators at the output level of the objective hierarchy, usually indicators describing the quantity of outputs and the timing of their delivery. Outputs The immediate, intended, and tangible—that is, easily measurable and practical—results to be produced through sound management of agreed-upon inputs. Outputs may also include changes resulting from interventions that are necessary to achieve outcomes at the purpose level. Qualitative Something that is not conveyed in numerical form, such as minutes from community meetings and general notes about observations. Qualitative data often describe people’s knowledge, attitudes, and behaviors. Quantitative Something measured by, measurable by, or concerned with quantity and expressed in numbers or quantities. Resilience The capacity of a system or people to recover quickly from a difficult situation such as a prolonged drought. Result The measurable output, outcome, or impact—intended or unintended, positive or negative—of a development intervention. Safety nets Safeguards against possible hardships or difficult circumstances arising from foreseeable or unforeseeable events. Stakeholder An agency, organization, group, or individual that has a direct or indirect interest in a project or program, or who affects or is affected positively or negatively by its implementation and outcome. Stakeholder Active involvement by stakeholders in the design, management, and participation monitoring of a project. Full participation means all representatives of key stakeholder groups at the project site become involved in mutually agreed-upon, appropriate ways. Sustainability The likelihood that the positive effects of a project, such as assets, skills, facilities, or improved services, will persist for an extended period after the external assistance ends. Target A specified objective that indicates the number, timing, and location of that which is to be realized. X KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Term Definition as used in this framework Technology An output of a research process which is beneficial to the target clientele—mainly farmers in this case. Technology can be commercialized and can be patented under intellectual property rights arrangements. Examples include research outputs such as crop varieties, livestock breeds, livestock vaccines, new equipment, and models. Validation The process of cross-checking to ensure that the data obtained from one monitoring method are confirmed by the data obtained from a different method. Value chain The full range of value-adding activities required to bring a product or service through the different phases of production, including procurement of raw materials and other inputs. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 XI CHAPTER 1: INTRODUCTION 1.1 Introduction The agricultural sector is a high-priority economic pillar in Kenya Vision 2030 which aims to achieve an innovative, commercially oriented, modern agricultural sector through institutional reforms, increased productivity, land use transformation, greater access to markets, and the development of arid and semi-arid lands. The sector is predominantly rain-fed and therefore vulnerable to climate change. It is not only impacted by climate change but also contributes to the problem. The agricultural sector is the largest source of GHG emissions and was responsible for one third of Kenya’s total emissions in 2010. Agricultural emissions are likely to jump from 20 metric tons of carbon dioxide equivalent (Mt CO2e) in 2010 to 27 Mt CO2e by 2030, largely driven by livestock methane emissions and land use change, which account for 90% of agricultural emissions and 30% of overall national emissions. Kenya submitted its NDCs to the United Nations Framework Convention on Climate Change, which sets out mitigation contributions intended to abate GHG emissions by 32% by 2030 under the Paris Agreement. Kenya’s Climate Change Act 2016 obligates governments at all levels to integrate and mainstream climate change actions and interventions in all sectors. CSA offers an excellent opportunity for agricultural growth. It requires collaborative actions among various actors including national and county governments, farmers, the private sector, civil society organizations (CSOs), and other value chain actors. To respond to the impacts of climate change in agriculture, the sector developed the KCSAS. This strategy offers a detailed plan to “adapt to climate change, build resilience of agricultural systems while minimizing emissions for enhanced food and nutritional security and improved livelihoods”. To implement the strategy, the KCSAIF was created to address the impacts of climate change challenges on agricultural growth and development. This framework outlines envisaged actions towards the implementation of KCSAS 2017-2026 and is aligned with the government’s commitments and obligations to guide the country’s transition towards a low-carbon, climate-resilient development pathway. The framework seeks to support the implementation of the KCSAS, whose objectives are as follows: (i) to enhance the adaptive capacity and resilience of farmers, pastoralists, and fisher-folk to the adverse impacts of climate change; (ii) to develop mechanisms 1 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 that minimize GHG emissions from agricultural production systems; (iii) to create an enabling regulatory and institutional framework; and (iv) to address crosscutting issues that adversely impact CSA. 1.2 Kenya Climate Smart Agriculture Implementation Framework 2018- 2027 1.2.1 Goal and Objectives of the Kenya Climate Smart Agriculture Implementation Framework GOAL The overall goal of the KCSAIF is to achieve a national, long-term, low-carbon, climate-resilient development pathway whilst realizing the development goals of Kenya Vision 2030. OBJECTIVES The KCSAIF has four objectives: 1. To develop a sustainable system for achieving coordinated, coherent, and cooperative governance of climate resilience and low-carbon growth in the agricultural sector. 2. To mainstream CSA to support the transformation of Kenya’s agricultural sector into an innovative, commercially oriented, competitive, and modern industry that contributes to poverty reduction and improved food security in Kenya. 3. To reduce the vulnerability of agricultural systems by cushioning them against the impacts of climate change and to reduce GHG emissions where possible. 4. To strengthen communication systems pertaining to CSA extension and agro- weather issues. 1.3 Kenya Climate Smart Agriculture Implementation Framework Components The objectives of the KCSAIF will be realized by implementing actions designed around the following four components. 1.3.1 Institutional coordination This component supports the establishment of an inclusive institutional framework for improved agricultural-sector CSA coordination and harmonization, KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 2 and an enabling policy and institutional environment for the realization of the CSA objectives in general. It involves strengthening the coordination on CSA- related issues of inter-ministerial, national, and county governments, the private sector, CSOs, development partners, and other non-state actors. Institutional coordination will enhance the capacity for cross-sectoral planning and communication within and between ministries and government institutions with different mandates regarding CSA. Further, this component will enable sectoral institutions to contribute to and take responsibility for sector-wide coordination and implementation for more effective delivery of their CSA-related mandates. 1.3.2 Agricultural productivity and the integration of the value chain approach Aimed at building resilience along different agricultural value chains through adaptive technologies and enhanced market linkages, this component can play a major role in ensuring improved agricultural productivity. It will also promote commercialization, food safety, and quality control standards along the value chains. 1.3.3 Building resilience and appropriate mitigation actions This component aims at building resilience through adaptation and appropriate mitigation measures through improved management of the natural resource base and through the development of safety nets along value chains. It will also support the identification and deployment of appropriate measures that minimize GHG emissions in agricultural production systems. 1.3.4 Communication systems for climate-smart agriculture extension and agro-weather issues This component aims to strengthen and mainstream communication systems pertaining to CSA, extension, and agro-weather issues among agricultural-sector stakeholders. In addition, it will promote generation of, access to, and enhanced application of CSA knowledge among value chain actors. Further, this component will help strengthen systems for timely provision of climate forecasts to different value chain stakeholders. 3 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 CHAPTER 2: INSTITUTIONAL ARRANGEMENTS, CAPACITY BUILDING AND RESOURCE MOBILIZATION 2.1 Climate-smart agriculture monitoring and evaluation institutions and their roles Institutional arrangements for M&E relate to the roles and responsibilities of stakeholders and partners and how they work together. These arrangements typically provide the context in which the institutions in charge of coordinating climate action in agriculture carry out their M&E roles—in this case, the MoALF&C and county government departments. An effective M&E institutional arrangement fosters the implementation of a robust M&E system, such that each institution undertakes its functions efficiently and in a timely manner to ensure seamless working between relevant institutions. The following institutions will play a pivotal role in the M&E of CSA. a) The National Climate Change Council The National Climate Change Council has a broad-based membership among both state and non-state actors and is chaired by the president; it provides an overarching national climate change coordination mechanism. As the principal decision-making organ on climate change issues in Kenya, the council is a key consumer of M&E reports to track the progress of resilience building in the country. The council does the following: » Ensures the mainstreaming of the climate change functions by the national and county governments. » Sets targets for the regulation of GHG emissions and resilience building. » Approves and oversees implementation of the National Climate Change Action Plan. » Provides ultimate oversight on the implementation of climate change actions. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 4 b) The Climate Change Directorate The Climate Change Directorate is domiciled in the Ministry of Environment and Forestry and is the leading government agency on national climate change plans and actions that provides operational coordination with respect to climate change in the country. As regards Measurement, Reporting, and Verification (MRV+), its functions are the following, among others: » To develop the national MRV+ systems and requisite regulations; » To compile and submit national climate change reports to meet both national and international obligations; » To provide guidance and capacity building on MRV+; » To provide technical support on climate change reporting; » To establish and manage a national registry for appropriate adaptation and mitigation actions by public and private entities; and » In collaboration with other agencies at the national and county government levels, to identify low-carbon, climate-resilient strategies and coordinate related MRV+. At the intergovernmental level, the current Joint Agriculture Sector Consultation and Cooperation Mechanism will be the avenue through which CSA M&E implementation will be guided by each organ’s mandate and responsibility. c) State departments of the Ministry of Agriculture, Livestock, Fisheries and Cooperatives The state departments of the MoALF&C shall: » Set department-specific targets for climate change; » Develop strategies to achieve these targets; » Coordinate CSA M&E at the departmental level; » Develop departmental indicators and baselines; and » Compile and submit CSA M&E reports to the MoALF&C CCU for analysis and forwarding to the Climate Change Directorate. d) The Climate Change Unit The MoALF&C CCU shall: » Provide technical support and policy advisory to stakeholders regarding the implementation of CSA M&E and reporting; » Coordinate the review of the CSA M&EF; » Carry out quality control and quality assurance for CSA data; » Develop a knowledge management hub to provide a repository for all CSA knowledge, technologies, data, and best practices in the country; » Coordinate CSA sensitization, awareness, and capacity building; and » Play a secretariat role in CSA-MSP forum meetings. 5 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 e) Multi Stakeholder Platform for Climate Smart Agriculture The national CSA-MSP is a consortium of actors and partners on CSA and includes public entities, non-governmental organizations (NGOs), donors, academia, researchers, private-sector actors, and others. The platform is composed of nationally based institutions. Its secretariat is located at the ministry headquarters with the CCU. The National CSA-MSP plays the following roles: » Provides high-level consultations between the national and county governments and other key sectoral stakeholders on matters related to CSA; » Makes recommendations on CSA policy matters in the agricultural sector; » Agrees on mechanisms to coordinate CSA forums; » Makes recommendations about CSA programs, strategies, plans, and performance-monitoring instruments brought to their attention; » Ensures that CSA decisions and resolutions are circulated and implemented by relevant entities within the platform; » Deliberates on CSA issues within the areas of responsibility of platform stakeholders in reports and resolutions; » Facilitates national and county M&E systems to implement CSA initiatives; » Coordinates events and functions to follow up about CSA with the national and county governments; and » Uses its forums for joint planning of CSA programs. f) County Climate Change Unit The CCCU is the coordinating body of the climate agenda for all the sectors within a county. Each CCCU is domiciled at the county department of the environment. As a reflection of the county climate change agenda, each sector is expected to provide plans, interventions, and policies to be carried out in the departments responsible for climate action. g) County Agriculture Sector Climate Focal Point The CASCFP fulfills the following expectations: » Coordinates implementation of CSA activities at the county level; » Communicates the decisions of the national CSA-MSP to the county’s implementing entities; » Develops departmental indicators and baselines; » Sets county-specific CSA targets and develops strategies to achieve them; » Mainstreams CSA strategy in the County Integrated Development Plans and the corresponding M&EF and links it to County Integrated Monitoring and Evaluation Systems and the National Integrated Monitoring and Evaluation System; KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 6 » Prepares annual reports on the progress of CSA implementation through the established mechanism; » Creates and manages a registry of climate change actions for all stakeholders at the county level and links the county registry to the national registry; and » Plays a secretariat role in county CSA-MSP forum meetings. h) County Climate-Smart Agriculture Multi-Stakeholder Platforms The county CSA-MSPs are a consortium of actors and partners on CSA that includes public entities, NGOs, donors, academia, researchers, the private sector, and others. The platforms are composed of institutions that are based in or operate on the county level. The secretariat is based at the CASCFP headquarters. The county CSA-MSPs do the following: » Provide high-level consultations between county governments and other key sectoral stakeholders on CSA matters; » Make recommendations about CSA policy in the agricultural sector; » Agree on mechanisms for coordination of the county CSA forums; » Make recommendations about CSA programs, strategies, plans, and performance-monitoring instruments brought to their attention; » Ensure that CSA decisions and resolutions are circulated and implemented by relevant entities within the platforms; » Deliberate on CSA issues in the areas of responsibility of each stakeholder in reports and resolutions; » Facilitate county-level M&E of the implementation of CSA initiatives; » Coordinate preparation, follow-up events and functions between the national and county governments on CSA related issues » Furnish a forum for joint planning on CSA programs; and » Provide and submit reports to the national CSA-MSP for the preparation of national reports on CSA initiatives. 2.2 Capacity building and resource mobilization Implementation of this M&EF will require sufficient financial, human, and infrastructural capacity to empower relevant institutions, organizations, managers, and staff to effectively carry out the M&E tasks. 2.2.1 Human capacity A capacity needs assessment will be conducted to identify the required skills and enable the development of a capacity building program to ensure the availability of adequate human resources for M&E. Sufficient capacity building will be conducted 7 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 among all implementing institutions and partners for effective implementation of this M&EF. Implementing organizations and partners shall retain a critical mass of experts to support the M&E system, who will include M&E specialists, MIS experts, and statisticians, among others. Qualified trainers will roll out the capacity building plan, which will cover the following factors, among others: » CSA indicators » Results-based management » A geographic information system and mapping for M&E » A CSA MIS » Data collection methodologies and statistical analysis » Participatory M&E and advocacy » CSA data collection tools » M&E reporting tools » Resilience characterization and indicators » Survey and case studies methodologies 2.2.2 Infrastructural capacity Implementation of M&E activities requires sufficient infrastructure, including buildings, office equipment, furniture, vehicles, power connections, computers, printers, communication devices, and an internet connection. Other requirements are Global Positioning System equipment, weighing scales, and survey equipment. Implementing partners will develop the necessary infrastructure based on the capacity needs assessment. The CCU will develop a CSA MIS and standard monitoring tools for data collection and analysis. 2.3 Resource mobilization The implementation of this CSA M&EF will involve several stakeholders and will therefore require adequate resources. Based on the budget estimates of the KCSAS strategy at K Sh 500 billion, this M&EF will require a total of K Sh 25 billion in a period of ten (10) years, equivalent to 5% of the KCSAS budget. Resources will be mobilized from a wide range of partners that shall include the national government through exchequer allocations, the county governments through prioritization of CSA M&E in their County Integrated Development Plans and other development plans, development partners, and the private sector. The CCU, counties, and other partners will develop proposals to fund different aspects of implementing this framework and seek support from the respective governments and other funding agencies like Green Climate Fund, Global Environment Facility, and additional development partners. The allocation of government resources for this framework is critically important as climate change is a key consideration in transforming the agricultural sector. This self-reliance is anticipated in the African Union Agenda 2063, of which Kenya is a signatory. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 8 CHAPTER 3: MONITORING AND EVALUATION MATRIX 3.1 The Kenya Climate-Smart Agriculture Monitoring and Evaluation Framework Efficient tracking of the climate actions being undertaken in the agricultural sector is a prerequisite to demonstrate progress towards enhanced productivity, increased resilience, and the mitigation of GHG emissions outlined in the KCSAS. Consequently, this M&EF has been developed as an integral component to ensure that strategic objectives are achieved in a cost-effective, coordinated, and harmonized approach at both the national and county levels. This M&EF aims to guide coordinated and efficient data collection, analysis, and use, and the provision of information that includes indications of impact, outcomes, and outputs. Monitoring will entail gauging the progress of sectoral climate actions at the activity and output levels, while evaluation will involve measuring achievements at the levels of outcomes and impact. This M&EF is expected to foster effective planning to attain optimal utilization of resources, achieve set goals, and transform the agricultural sector towards resilient, low- carbon agriculture. 3.1.1 Objectives of this monitoring and evaluation framework The objectives of this M&EF are as follows: i. To guide M&E of progress toward KCSAIF goals, outcomes, and indicators, in order to ensure efficiency, effectiveness, and accountability during implementation; and ii. To enforce a culture of results-based M&E and provide a foundation for an evidence-based decision-making process. 3.1.2 Purpose and scope of this monitoring and evaluation framework Under the United Nations Framework Convention on Climate Change, the Paris Agreement sets out an enhanced transparency framework for climate change action and support. Kenya is expected to provide information on mitigation, adaptation, and the support received. 9 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Kenya’s transparency framework is based on the MRV+ system defined in the National Climate Change Action Plan 2013-2017 as “an integrated framework for measuring, monitoring, evaluating, verifying, and reporting results of mitigation actions, adaptation actions and the synergies between them.” The MRV+ system generates information for national and international reporting requirements. The purpose of this M&EF is to track whether the scheduled KCSAIF goals, objectives, outcomes, outputs, and other factors are proceeding as planned. An effective M&EF will help guide the implementation of the KCSAIF and by extension the KCSAS. The purpose of this M&EF, therefore, is to ensure that the implementation of the KCSAIF is efficient and stakeholders can measure the progress of initiatives arising from the KCSAS and the KCSAIF. This M&EF is a useful learning tool and will inform potential investment actors for onward planning. Corrective actions will be instituted on an ongoing basis using the annexed monthly, quarterly, and annual reporting formats. Reports will be compiled, analyzed, and shared during the implementation period which will be used at a mid-term review before the second M&E framework is developed. During the M&E process, implementers will identify data gaps and institute mechanisms to rectify any anomalies. The scope of this M&EF is broad enough to accommodate all stakeholders implementing CSA interventions including farmers, public- and private-sector actors, academia, researchers, and CSOs. Elaborate metadata is part of this framework to enhance understanding of the indicators monitored, how they will be measured, and reporting formats. The stakeholders implementing CSA at all levels of government are expected to use this M&EF to report to their sectoral CCU through the communication flow about all CSA interventions as outlined in the M&E tool which shall be online. Subsequently, the CCU will collate the sectoral data on CSA interventions and submit the same to the Climate Change Directorate in the Ministry of Environment and Forestry. 3.2 Monitoring and evaluation matrix A set of appropriate indicators in the form of M&E matrix can effectively track the progress of climate actions in the agricultural sector (Table 1). To ensure coherence, this matrix transforms information from the KCSAIF logical framework into smart, monitorable indicators for proper progress tracking. It provides all stakeholders undertaking agricultural-sector climate actions with the requisite indicators to measure advancements towards the goal, impact, outcomes, and outputs outlined in the KCSAIF, thus enables effective M&E reporting. The M&E matrix is a comprehensive repository of indicators structured to capture both qualitative and quantitative data and information on CSA and is further supported by the metadata (Table.2). KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 10 Table 1: Monitoring and evaluation matrix Result hierarchy Indicators Unit of measure (log frame element) GOAL: A national, Climate change adaptation investments in the agricultural sector K Sh long-term, low- carbon, climate- GHG emissions per unit of agricultural produce or per commodity Kg CO2eq/unit resilient development pathway, alongside Renewable energy investments in the agricultural sector K Sh realization of the The proportion of climate-resilient households % development goals of Kenya Vision 2030 Total agricultural-sector GHG emissions Metric Tons CO2eq IMPACT: Prevalence of severe food insecurity in target areas % Improvement of agricultural livelihoods National average intake of calories per capita Kcal per capita and food, nutritional, and income security Prevalence of stunted children under five years old % through CSA Household dietary diversity score, which is an index of household food Index extension availability, access, utilization, and stability of supply The aim of Outcome 1 is to demonstrate existence of a sustainable system for achieving coordinated, coherent, and cooperative governance of climate-resilient, low-carbon growth in the agricultural sector through improved inter-ministerial and county government coordination; through deepening partnerships between state and non-state actors; and through improved linkages between actors in the agricultural research system, advisory services, and producers. OUTCOME 1. INDICATOR 1.1. Total amount of finances invested in CSA K Sh Institutional coordination of CSA INDICATOR 1.2. Existence of functional CSA coordination mechanism at Descriptive policy and the national and county levels implementation strengthened INDICATOR 1.3. Presence of up-to-date CSA policies and strategies in Descriptiveplace at both national and county levels of governance INDICATOR 1.4. Existence of functional research-extension-farmer Descriptive linkages mechanisms OUTPUT 1.1. INDICATOR 1.1.1. Change in frequency of joint CSA coordination and Descriptive Strengthened partnership forums coordination and INDICATOR 1.1.2. Number of harmonized CSA policies N partnership between state and non-state actors INDICATOR 1.1.3. Number of counties that have mainstreamed national NCSA related policies INDICATOR 1.1.4. Number of collaboration agreements/commitments N related to CSA between the institutions INDICATOR 1.1.5. Existence of approved joint agricultural-sector CSA Descriptive programming and financing mechanism INDICATOR 1.1.6. Number of jointly developed CSA related policy briefs N INDICATOR 1.1.7. Number of joint CSA programmes implemented by N national and county governments INDICATOR 1.1.8. Amount of funding allocated to joint CSA programs by Ksh state and non-state actors OUTPUT 1.2. INDICATOR 1.2.1. Change in number of farmer-research-extension forums N Strengthened held farmer-research- INDICATOR 1.2.2. Composition of stakeholders involved in farmer- Descriptiveextension linkages research-extension linkage INDICATOR 1.2.3. Number of user-driven CSA research technologies N developed OUTPUT 1.3. INDICATOR 1.3.1. Existence of up to date CSA policies, strategies, Descriptive Enhanced enabling guidelines, and regulations environment for CSA 11 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Result hierarchy Indicators Unit of measure (log frame element) OUTPUT 1.4. INDICATOR 1.4.1. Change in expenditure in Climate Smart Agriculture (CSA) K Sh Enhanced organizational INDICATOR 1.4.2. Change in the number of Climate Smart Agriculture (CSA) N capacities to address Specialists CSA issues The aim of Outcome 2 is to mainstream CSA to support the transformation of Kenya’s agricultural sector into an innovative, commercially oriented, competitive, and modern industry that contributes to poverty reduction and improved food security in Kenya. OUTCOME 2. INDICATOR 2.1. Changes in productivity of various value chains Descriptive Agricultural productivity and INDICATOR 2.2. Changes in the quantity of marketed produce or Tonnes integration of the products derived from value-added commodities value chain approach promoted INDICATOR 2.3. Change in number of value chain actors in the Nagricultural sector adhering to market standards INDICATOR 2.4. Volumes of strategic reserves of foods or feeds stored Tonnes INDICATOR 2.5. Percentage change in area of land under efficient % irrigation systems INDICATOR 2.6. Proportion of small and medium-sized enterprises % (SMEs) using green technologies for value addition INDICATOR 2.7. Number of green jobs created N INDICATOR 2.8. Change in percentage of post-harvest losses by value % chain OUTPUT 2.1. INDICATOR 2.1.1. Number of value chain actors adopting the promoted N Improved access to CSA technologies and innovations. and use of CSA technologies and INDICATOR 2.1.2. Types of certification for climate smart produced Descriptive innovations commodities INDICATOR 2.1.3. Number of CSA Technologies and innovations for N post-harvest loss reduction in use OUTPUT 2.2. INDICATOR 2.2.1. Area under efficient irrigation systems Ha Efficient irrigation enhanced INDICATOR 2.2.2. Number of producers using efficient irrigation systems N INDICATOR 2.2.3. Area under both efficient water use and renewable Ha energy-powered irrigation systems INDICATOR 2.2.4. Number of efficient irrigation technological packages N developed OUTPUT 2.3. INDICATOR 2.3.1. Types of value addition green technologies in use across Descriptive Enhanced green value chains technology value addition to INDICATOR 2.3.2. Number of actors using green technologies for value N commodities addition OUTPUT 2.4. INDICATOR 2.4.1. Change in volumes of marketed climate-smart Tonnes Enhanced market commodities access for climate- INDICATOR 2.4.2. Change in number of market outlets trading climate- Nsmart products smart products (labelled & certified) INDICATOR 2.4.3. Number of actors trading in climate-smart commodities N INDICATOR 2.4.4. Number of actors adopting standardization systems N KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 12 Result hierarchy Indicators Unit of measure (log frame element) OUTPUT 2.5. INDICATOR 2.5.1. Change in the number of climate-smart food and feed N Improved food and processing, storage and distribution technologies in use feed storage and INDICATOR 2.5.2. Change in the number and capacity of climate-smart Ndistribution food and feed storage and distribution facilities INDICATOR 2.5.3. Quantity of strategic food reserves, by commodity Tonnes INDICATOR 2.5.4. Change in the quantities of strategic livestock and fish Tonnes feed reserves The aim of Outcome 3 is to reduce the vulnerability of agricultural systems by cushioning them against the impacts of climate change and to reduce GHG emissions where possible. OUTCOME 3. INDICATOR 3.1. Percentage change in GHG emission intensity % Increased resilience with mitigation INDICATOR 3.2. Total land under integrated soil fertility and water Ha benefits management practices INDICATOR 3.3. Total area under Ecosystem management and degraded Ha land rehabilitation INDICATOR 3.4. Volume of water harvested and stored for agricultural use M3 INDICATOR 3.5. Existence of Monitoring Reporting and Verification Descriptive (MRV+) systems OUTPUT 3.1. INDICATOR 3.1.1. Number of farmers adopting integrated soil fertility N Improved soil health management practices and rehabilitation of degraded lands INDICATOR 3.1.2. Land area under integrated soil fertility management Ha practices INDICATOR 3.1.3. Number of farmers adopting soil and water N management technologies and innovations INDICATOR 3.1.4. Number of actors providing soil and water management N services INDICATOR 3.1.5. Area of land under soil and water management Ha technologies and innovations INDICATOR 3.1.6. Area of degraded land rehabilitated Ha OUTPUT 3.2. INDICATOR 3.2.1. Change in area of land under conservation/restoration Ha Enhanced conservation of INDICATOR 3.2.2. Change in number of value chain actors adopting N water and other climate-smart ecosystem conservation measures natural resources INDICATOR 3.2.3. Number of water harvesting and storage structures for N agricultural use INDICATOR 3.2.4. Change in number of non-conventional livelihood N opportunities linked to integrated watershed management OUTPUT 3.3. INDICATOR 3.3.1. Change in access to agricultural safety nets services N Enhanced access to climate risk-related INDICATOR 3.3.2. Change in access to index –based insurance products N agricultural insurance and other safety nets OUTPUT 3.4. INDICATOR 3.4.1. Change in adoption of synergistic adaptation and N Enhanced adoption mitigation initiatives of synergistic INDICATOR 3.4.2. GHG accounting system for adaptation interventions Descriptiveadaptation and with high potential for mitigation mitigation initiatives 13 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 Result hierarchy Indicators Unit of measure (log frame element) OUTPUT 3.5. INDICATOR 3.5.1. Number of institutions with facilities to support GHG N Enhanced capacity accounting for GHG accounting INDICATOR 3.5.2. Number of experts trained in GHG emissions accounting N INDICATOR 3.5.3. Change in GHG emission Metric Tons CO2eq The aim of Outcome 4 is to strengthen communication systems related to CSA extension and agro-weather issues by generating, communicating, and disseminating CSA knowledge; by enhancing access to climate information and agro-weather advisory services and early warning systems; and by developing capacity in climate risk contingency planning. OUTCOME 4. INDICATOR 4.1. Change in total number of actors with access to CSA N Communication information systems related to INDICATOR 4.2. Existence of functional CSA information management DescriptiveCSA extension and systems agro-weather issues strengthened INDICATOR 4.3. Existence of functional contingency plans for climate Descriptive risks response INDICATOR 4.4. Presence of functional CSA communication strategies. Descriptive OUTPUT 4.1. INDICATOR 4.1.1. Number of CSA knowledge products developed N Enhanced CSA knowledge generation INDICATOR 4.1.2. Number CSA best practices documented N OUTPUT 4.2. INDICATOR 4.2.1. Change in access to CSA advisory services N Enhanced CSA knowledge communication and dissemination OUTPUT 4.3. INDICATOR 4.3.1. Change in number of agro-weather advisories N Enhanced access to integrating scientific and indigenous knowledge climate information and agro-weather INDICATOR 4.3.2. Change in number of service providers trained in climate N information and agro-weather advisory service delivery advisory services INDICATOR 4.3.3. Change in access to downscaled climate agro-weather N information to communities and localities in place OUTPUT 4.4. INDICATOR 4.4.1. Change in the number of climate risk contingency plans N Early warning developed systems and INDICATOR 4.4.2. Change in the number of stakeholders implementing the Ncontingency contingency plans plans for climate change responses INDICATOR 4.4.3. Change in the number of climate risk mitigation and N strengthened disaster preparedness measures INDICATOR 4.4.4. Types of functional early warning systems for climate Descriptive change responses KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 14 Table 2. Metadata OUTCOME 1. Institutional coordination of Climate Smart Agriculture (CSA) policy and implementation strengthened. The aim of Outcome 1 is to demonstrate the existence of a sustainable system for achieving coordinated, coherent, and cooperative governance of climate-resilient, low-carbon growth in the agricultural sector through improved inter-ministerial and county government coordination; through deepening partnerships between state and non-state actors; and through improved linkages between actors in the agricultural research system, advisory services, and producers. INDICATOR 1.1. Definition: These are funds in Kenya Shillings invested by the state Total amount of finances and non-state stakeholders (government, CSOs, development partners, invested in CSA private sector, researchers, academia, and others) in CSA activities annually. These are the funds invested by the implementing organizations. Rationale: This will allow progressive increase in climate smart agriculture investments. Disaggregated by: Source (government, CSOs, development partners, the private sector, researchers, academia, and others) and category (loans and grants). Data source: Funding/implementing organizations. INDICATOR 1.2. Definition: Presence of CSA coordination mechanisms that are Existence of functional discharging their mandates of coordinating, planning, implementation CSA coordination and reporting. There will be need for coordination between the two mechanisms at the levels of government. national and county Rationale: This will solve the problem of duplication and build synergy. levels Disaggregated by: Governance level (National and county). Data sources: Departmental climate change focal points. INDICATOR 1.3. Definition: These are the national guidelines aimed at increasing Presence of up-to- productivity and resilience of farming systems through low carbon date CSA policies and pathways. These guidelines are expected to be domesticated at the strategies in place county level. at both the national Rationale: This will create coherence in climate smart agriculture and county levels of interventions. governance Disaggregated by: Governance level (National and county). Data sources: County websites, Ministry of Agriculture websites, CSA-MSP websites. INDICATOR 1.4. Definition: These platforms bring together the three actors in the Existence of functional technology generation, dissemination and adoption. The platform will research-extension- set the agenda for research, dissemination methods and factors to farmer linkage facilitate adoption. mechanisms Rationale: This will create demand-driven research and efficient extension for technology adoption. Disaggregated by: Value chains. Data sources: Reports, journals, brochures, county websites, Ministry of Agriculture websites, CSA-MSP websites etc. 15 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 OUTPUT 1.1. Strengthened coordination and partnership between state and non-state actors INDICATOR 1.1.1. Definition: These are meetings, conferences, seminars, workshops Change in frequency of held between state and non-state actors on matters of CSA. CSA coordination and Rationale: This will address the issue of in-effective coordination partnership forums because of infrequent joint coordination forums. Disaggregated by: National and county. Data sources: County websites, Ministry of Agriculture websites, CSA-MSP websites, meeting minutes and reports. INDICATOR 1.1.2. Definition: These are CSA related policies have been reviewed and Number of harmonized harmonized. CSA policies Rationale: To avoid contradiction among CSA related policies. Disaggregated by: None. Data sources: Ministry departments and meeting reports. INDICATOR 1.1.3. Definition: These are the counties, which have domesticated national Number of counties that CSA policies and are implementing. have mainstreamed Rationale: This will provide for harmonized implementation for CSA national CSA related policies. policies Disaggregated by: Counties. Data source: County website. INDICATOR 1.1.4. Definition: These are the arrangements by CSA actors for joint Number of collaboration planning, funding and implementation of CSA activities. This indicator agreements/ will show the number of partnership agreements for CSA activities. commitments related Rationale: This will enable pooling of resources for upscaling CSA to CSA between the activities. institutions Disaggregated by: State and non-state institutions. Data sources: County website, Ministry of Agriculture website, CSA- MSP website. INDICATOR 1.1.5. Definition: These are official multi-agencies, multi-year CSA plans Existence of approved developed jointly, which specify priorities and objectives and addresses joint agricultural-sector the role of various contributors. CSA programming and Rationale: This will provide financial commitments by agencies and financing mechanism reference document on CSA interventions. Disaggregated by: National and county levels. Data sources: County websites, Ministry of Agriculture websites, CSA-MSP websites. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 16 INDICATOR 1.1.6. Definition: These are communication tools developed through Number of jointly synthesis of research, studies to inform policy makers for decision- developed CSA related making. policy briefs Rationale: This will accelerate implementation of the recommended CSA policy actions by informed decisions. Disaggregated by: Governance level (National and county). Data sources: County websites, Ministry of Agriculture website, CSA- MSP websites. INDICATOR 1.1.7. Definition: This is the number of programmes that will be undertaken Number of joint at national and county levels, bringing together CSA stakeholders to CSA programmes disseminate and share CSA knowledge and technologies. Stakeholders implemented by national refer to individuals, groups, organizations and agencies that have an and county governments interest in CSA. These programmes will enable stakeholders to interact with experts who will share latest CSA knowledge and technologies. Rationale: These programmes will provide an avenue to capacity build stakeholders on CSA knowledge and technologies and centralized reporting. Disaggregated by: Governance level (National and county). Data source: Programme reports. INDICATOR 1.1.8. Definition: These are budgeted funds allocated for joint CSA activities Amount of funding by state and non-state actors. allocated to joint CSA Rationale:This indicator will track financial support on CSA programs. programs by state and non-state actors Disaggregated by: State and non-state. Data sources: Organization budgets, reports. OUTPUT 1.2. Strengthened farmer-research-extension linkages INDICATOR 1.2.1. Definition: This indicator tracks the change in the number of forums in Change in number a year where CSA findings, knowledge and skills are shared amongst of farmer-research- researchers, extension staff and farmers. Forums include CSA extension forums held conferences, meetings, symposiums, farmer field schools, benchmarking, trial/demonstration plots farmer-farmer exchange programs, exhibitions and open days. In these forums, researchers, extensions and farmers exchange and share information, knowledge and skills. Rationale: Strong farmer-research-extension linkages will facilitate effective and efficient CSA knowledge development, dissemination and sharing and the linkages among different knowledge types. Disaggregated by: Value chain, farmers, gender. Data sources: National Agricultural Research System (NARS), Centre Research Advisory Committee (CRAC). 17 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 INDICATOR 1.2.2. Definition: This indicates the category of membership in farmer- Composition of research-extension linkages during the reporting period. This indicator stakeholders involved in will show the extent of representation of farmers, researchers, and farmer-research- extensionists in the linkage. extension linkage Rationale: Diverse membership of stakeholders in the linkage will help increase knowledge exchange on CSA. A strong linkage should have representation from farmers, researchers and extension personnel. Disaggregated by: Membership category. Data sources: National Agricultural Research System (NARS), Centre Research Advisory Committee (CRAC). INDICATOR 1.2.3. Definition: These are the number of research products (technologies, Number of user- innovations and management practices) that are developed during the driven CSA research reporting period. These products are based on user needs and target technologies developed specific agro-ecological/ production systems such as pastoral systems, or targeting specific value chains such as pulses, or specific objectives such as provision of feed and fodder through research in multi-purpose crops. Rationale: This will help in mapping the state of research on CSA and progressively increase research for context-specific CSA needs. Disaggregated by: Value chains. Data sources: Reports, research papers, patent certificates. INDICATOR 1.2.4. Definition: These are financial resources in Kenyan Shillings that are Amount of funding used in developing new knowledge and technologies specific to CSA utilized for user-driven annually. They include financial resources directly from government CSA research (public funding) and from other partner organizations. Rationale: This will facilitate the mapping of available funding for CSA research and inform progressive increase in investments towards climate risk research and development of new knowledge and technologies for CSA. Disaggregated by: Source (government, CSOs, development partners, private sector, researchers, academia, and others) and category (loans and grants). Data sources: Financial reports, voted estimates, funding agreements. OUTPUT 1.3. Enhanced enabling environment for Climate Smart Agriculture (CSA) INDICATOR 1.3.1. Definition: These are the CSA legal and institutional frameworks that Existence of up-to-date have been developed/reviewed during the reporting period to facilitate CSA policies, strategies, an enabling environment for CSA planning and implementation at the guidelines, and national and county levels. regulations Rationale: Sound policies, strategies, guidelines and regulations are critical in outlining the vision, planned actions and mandates in the implementation of CSA. They will create a conducive environment for CSA implementation at all levels of government. Disaggregated by: Types (policies, strategies, guidelines, or regulations); level of government (national, county). Data sources: Kenya Gazette, Kenya Law Reporting, Kenya Law Reforms Commission, sector departments. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 18 OUTPUT 1.4. Enhanced organizational capacities to address Climate Smart Agriculture (CSA) issues INDICATOR 1.4.1. Definition: This refers to the change in amount of financial resources Change in expenditure in Kenyan Shillings used for CSA implementation within the reporting in Climate Smart period. Implementation includes various activities such as promoting Agriculture (CSA) CSA technologies, innovation & management practices, CSA awareness creation or promoting collaborations with other actors. Rationale: Increased financial capacity is key in supporting CSA implementation. This will facilitate the mapping of available funding for CSA and inform progressive increase in investments towards CSA implementation at various scales. Disaggregated by: None. Data sources: Organizations, CCU, The National Treasury. INDICATOR 1.4.2. Definition: This indicator shows the trend in the number of people Change in the number within state and non-state organizations with knowledge and skills to of Climate Smart support the implementation of CSA during the reporting period. This Agriculture Specialists indicator will show the adequacy of specialists with knowledge and skills on CSA. Rationale: Adequacy of human resource is critical in supporting CSA implementation and will inform continued capacity building efforts. Disaggregated by: Value chain. Data sources: Organizational profiles, CSA-MSP database. OUTCOME 2. Agricultural productivity and integration of the value chain approach promoted The aim of Outcome 2 is to mainstream CSA to support the transformation of Kenya’s agricultural sector into an innovative, commercially oriented, competitive, and modern industry that contributes to poverty reduction and improved food security in Kenya. INDICATOR 2.1. Definition: These are the changes in yield per unit of various value Changes in productivity chains (Crop yield per area, aquaculture yield per pond, milk yield per of various value chains cow, carcass weight etc.). Rationale: To track progress in increasing productivity of various agricultural commodities (Crops, Fisheries and Livestock). Disaggregated by: Agricultural commodity (sub sector, value chain). Data sources: Ministry of Agriculture, County websites and CSA MSP websites etc. INDICATOR 2.2. Definition: These are the trends in the volumes (Metric tons) of Changes in the quantity agricultural products marketed coming from processing of agricultural of marketed produce or commodities both food and non-food. products derived from Rationale: This is aimed at increasing the volume of final agricultural value-added commodities products market rather than raw agricultural commodities. Disaggregated by: Value chains. Data sources: KNBS, Kenya Association of Manufacturers (KAM). 19 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 INDICATOR 2.3. Definition: This is the trend in number of value chain actors Change in number of conforming to certain market standards (e.g. GLOBAL G.A.P , GAM, value chain actors in GAP). the agricultural sector Rationale: Value chain actors need to conform to established adhering to market standards (like GLOBAL G.A.P, GAM, and G.A.P) to avoid interceptions standards and rejection of commodities. Disaggregated by: Value Chains, market standards. Data sources: MOALFC, AFFA. INDICATOR 2.4. Definition: Stocks of human food and livestock feed items set aside for Volumes of strategic use in times of scarcity. reserves of foods or feeds Rationale: To maintain food and feed supplies at six months national stored requirements and six months cash requirements. Disaggregated by: Food and feeds. Data sources: Food Security Balance sheet. INDICATOR 2.5. Definition: This will give an indication of the proportion of irrigated Percentage change land using renewable energy powered irrigation systems and efficient in area of land under water use technologies/practices in relation to the total irrigated land. efficient irrigation Rationale: This is intended to reduce the cost and increase productivity systems of irrigation water. Disaggregated by: Energy sources and water use technologies. Data sources: Sector reports. INDICATOR 2.6. Definition: This is the number of SMEs using green energy for value Proportion of small and addition relative to a total number of SMEs using energy. medium-sized enterprises Rationale: To reduce pollution and GHG emissions during processing/ (SMEs) using green value addition of agricultural value chains. technologies for value addition Disaggregated by: Value chains, green technologies. Data sources: MOALFC, Ministry of Energy. INDICATOR 2.7. Definition: These are jobs that preserve or restore the environment Number of green jobs through renewable energy in the agriculture sector. created in the agriculture Rationale: This contributes to transitioning agriculture sector into sector low-carbon development pathway. Disaggregated by: Green technology. Data sources: MOALFC, Ministry of Energy. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 20 INDICATOR 2.8. Definition: This is the trend of % of losses occurring at post-harvest Change in percentage of level for specific value chains. post-harvest losses by Rationale: To track the postharvest losses reductions resulting from value chain CSA interventions. Disaggregated by: Value chains. Data sources: National and county level agriculture sector departments reports. OUTPUT 2.1. Improved access to and use of CSA technologies and innovations INDICATOR 2.1.1. Definition: These are technologies and innovations in crops, livestock Number of value and fisheries that are promoted to increase agricultural productivity, chain actors adopting build resilience and adaptation to climate change. the promoted CSA Rationale: The aim is to increase accessibility to CSA innovations and technologies and technologies for increased productivity and resilience to climate change. innovations. Disaggregated by: Value chain, subsectors, type of technology. Data sources: MSP members and other extension service providers. INDICATOR 2.1.2. Definition: These are the types of certifications used for climate smart Types of certification for produced commodities. climate smart produced Rationale: Availability of standards will allow actors to access premium commodities prices for their produce and enhance environmental conservation and reduced greenhouse gas emissions. Disaggregated by: Type of certificate, value chains. Data sources: KEBS, MOALFC. INDICATOR 2.1.3. Definition: These are CSA technologies and innovations to reduce Number of CSA produce and product losses after harvest; including at storage, Technologies and processing, transportation and marketing stages. innovations for post- Rationale: Track technologies and innovations for upscaling. harvest loss reduction in use Disaggregated by: Value chain. Data sources: MSP members and other service providers. OUTPUT 2.2. Efficient irrigation enhanced INDICATOR 2.2.1. Definition: The indicator refers to the total of all land, in hectares Area under efficient under efficient irrigation systems. Efficient irrigation in this context is in irrigation systems relation to water use efficiency of an irrigation system. (Drip, sprinklers, the water is conveyed to the farm by lined or closed canal or pipe (closed system). Rationale: Enhanced water usage for agricultural production. When used efficiently more actors will have access to it, meaning we can put more land under irrigation using the same quantity of water. Disaggregated by: Value chain, type of irrigation systems, efficient water use, renewable energy. Data sources: County websites, Ministry of Agriculture websites, CSA-MSP websites. 21 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 INDICATOR 2.2.2. Definition: These are farmers using efficient irrigation systems. Number of producers Efficient irrigation in this context is in relation to water use efficiency using efficient irrigation (e.g., drip, sprinklers, or if by furrow or basin, the water is conveyed to systems the farm by closed canal or pipe) and use of renewable energy solar, wind, geothermal, gravity, biomass (bagasse, biogas etc.) or small hydro sources in an irrigation system. Rationale: This indicator aims at tracking access of the efficient irrigation technologies to small scale farmers. Disaggregated by: Water use system, renewable energy, gender. Data sources: County websites, Ministry of Agriculture website, CSA- MSP website, irrigation service providers. INDICATOR 2.2.3. Definition: Renewable energy in the context of this indicator is energy Area under both efficient obtained from solar, wind, geothermal, gravity, biomass (bagasse, water use and renewable biogas etc.) or small hydro sources. The indicator measures area in energy-powered hectares under irrigated crops and/or pasture where renewable energy irrigation systems is being used as the main source of energy supply to drive the irrigation system. Rationale: Use of renewable energy emits less of CO2 therefore contributing to reduction of effects of climate change from agricultural systems. Disaggregated by: Power sources (solar, wind, geothermal, gravity, biomass, small hydro sources) and water use systems/methods (e.g drip, sprinkler). Data sources: County websites, Ministry of Agriculture website, CSA- MSP website, irrigation service providers. INDICATOR 2.2.4. Definition: This refers to the number of irrigation technologies Number of efficient developed that achieve maximum productivity with minimum water irrigation technological losses in relation to water conveyance, application and use. packages developed Rationale: This will track progressive availability of efficient technologies for use by farmers. Disaggregated by: eTechnology types. Data sources: MoALFC website, MSP website (MSP members) and other service providers. OUTPUT 2.3. Enhanced green technology value addition to commodities INDICATOR 2.3.1. Definition: This refers to the green technologies that are used for value Types of value addition addition across the value chains. green technologies in use Rationale: This is to track transitioning from fossil fuel use into green across value chains energy like wind, solar, biogas, bagasse. Disaggregated by: Value chain, type of value addition (drying, storage, transportation, processing). Data sources: MoALFC website, MSP website and other service providers. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 22 INDICATOR 2.3.2. Definition: These are entrepreneurs using technologies that use green Number of actors using energy like wind, solar, biogas, bagasse to change primary agricultural green technologies for commodities to higher value products and longer shelf life. value addition Rationale:This is to track transitioning from fossil fuels to use of green energy. Use of green technologies will reduce emissions hence mitigating climate change. Disaggregated by: Value chain, green technology. Data sources: MoALFC website, MSP website and other service providers. OUTPUT 2.4. Enhanced market access for climate-smart products (labelled & certified) INDICATOR 2.4.1. Definition: This is the change in the annual volumes of commodities in Change in volumes of tonnes produced through climate practices that increase productivity marketed climate-smart without polluting the environment causing more GHG emissions that commodities are sold both locally (in the county/country) and exported outside the country during the reporting period. Rationale: This will provide information climate cautiousness of the consumers and their demand for climate-smart products. Disaggregated by: Type of market (local and export); value chain. Data sources: Agriculture marketing reports, marketing organizations, certification bodies, KEPHIS, DVS. INDICATOR 2.4.2. Definition: This is the number of market outlets, which trade in climate Change in number of smart products over a given a period. market outlets trading Rationale: This will progressively track the diversity of markets outlets climate-smart products trading in Climate smart products for Disaggregated by: Value chains; types of markets (wholesale, retail, local or export). Data sources: Sub-sector reports, market surveys. INDICATOR 2.4.3. Definition: This indicator looks at the number of actors (producers, Number of actors traders, aggregators and processors) who are trading in climate smart trading in climate-smart commodities during the reporting period. commodities Rationale: This allows for increased trade of the climate smart commodities and value share to the different value chain actors. Disaggregated by: Value chain actors; value chain produce. Data sources: Sub sector reports; marketing reports. INDICATOR 2.4.4. Definition: This indicator is meant to track the number of agricultural Number of actors value chain actors adopting approved grading and standardization adopting standardization systems for climate smart products within the reporting period. systems Rationale: The purpose is to increase competitiveness and market access of climate-smart products. Disaggregated by: Value chains. Data sources: Sub sector reports, standardization data base, KeBS. 23 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 OUTPUT 2.5. Improved food and feed storage and distribution INDICATOR 2.5.1. Definition: This indicator intends to measure the trend in the number Change in the number of climate smart food and feed storage technologies in use within the of climate-smart food reporting period. The technologies are value chain specific and use and feed processing, technologies that ensure food and feed preservation using renewable storage and distribution energy, for instance crops (silos, hematic bags, zero energy cooling technologies in use chambers etc.), fisheries (solar drying oven and racks, icing, cooler boxes, etc ) and livestock (pasteurization, chillers, etc.). Rationale: Use of climate smart food and feed storage will contribute to adaptation to climate change with mitigation co-benefits. Disaggregated by: Actor types (producers, processors); Value chain (crops, livestock, fisheries). Data sources: Sub-sector reports. INDICATOR 2.5.2. Definition: This indicator measures the trend in the number and Change in the number capacity of food and feed distribution technologies that have been and capacity of climate- used during the reporting period. smart food and feed Rationale: Use of climate smart food and feed distribution facilities storage and distribution and equipment will contribute to preserving the quality of agricultural facilities produce and can indicate the capacity of producers to take perishable produce to the market. Distribution facilities and equipment are also key in ensuring that the feeds can reach the farmers in a timely and cost-effective manner. Disaggregated by: Actor types; type (public, private); storage capacity (small, medium, large); value chain (crops, livestock, fisheries). Data sources: Sub sector reports. INDICATOR 2.5.3. Definition: This is the change in volume of food reserved according to Quantity of strategic food value chain. e.g. Kilograms of rice, maize, beans, milk. reserves, by commodity Rationale: This is important in capturing the ability to retain food reserves. Disaggregated by: Type of value chain, household, county. Data sources: NCPB, county government and national government. INDICATOR 2.5.4. Definition: This is the change in volume of livestock and fish feeds Change in the quantities strategically put aside for use during period of scarcity during the of strategic livestock and reporting period. fish feed reserves Rationale: This is to increase the availability of livestock and fish feed during hardship periods. Disaggregated by: Feed types (roughages, proteins, energy, minerals and additives). Data sources: NCPB, county government and national government. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 24 OUTCOME 3. Increased resilience with mitigation benefits The aim of Outcome 3 is to reduce the vulnerability of agricultural systems by cushioning them against the impacts of climate change and to reduce GHG emissions where possible. INDICATOR 3.1. Definition: This is the change in measure of GHG emissions per unit of Percentage change of production. GHGs are gaseous compounds such as CO2, CH4, and NO2 GHG emission intensity cause global warming through absorption of infrared radiation. Agriculture is one of the major sources of these GHG emissions. Rationale: To monitor the sequestration and abatement of GHG emissions from the resilience building initiatives. Disaggregated by: Value chains and practices. Data sources: Agriculture departments at national and county levels. INDICATOR 3.2. Definition: This is land area in hectares that has been put under Total land under integrated soil fertility and water management practices through integrated soil fertility various initiatives. and water management Rationale: To attribute the initiatives to the GHG emission abatement practices and sequestration. Disaggregated by: Initiatives/practices. Data sources: Organizations. INDICATOR 3.3. Definition: This is the aggregation of land area that has been put under Total area under ecosystem management and land rehabilitation (agroforestry, ecosystem management watershed management, habitats, and biodiversity conservation, and degraded land rangeland management, wasteland rehabilitation, liming). rehabilitation Rationale: To improve productivity, restoration of ecosystems and habitats and GHG emissions reduction. Disaggregated by: Practice. Data source: Reports. INDICATOR 3.4. Definition: This is the amount of rain water collected and stored for Volume of water use in agricultural activities. harvested and stored for agricultural use Rationale: To conserve water for increased productivity. Disaggregated by: Harvesting type/method. Data source: Reports. INDICATOR 3.5. Definition: MRV refers to a set of measures for collecting data on Existence of Monitoring emissions, mitigation actions to support direct measurement or Reporting and estimated calculations of emission and emission reductions following Verification (MRV+ ) the IPCC Guidelines. MRV+ is aimed at delivering both MRV of systems greenhouse gas (GHG) emissions and mitigation activities and Monitoring and Evaluation (M&E) of the adaptation activities. Rationale: To provide guidance on the implementation of both adaptation and mitigation actions in the form of policies, projects, programmes or business ventures and country help to fulfil international reporting obligations. Disaggregated by: National and county. Data source: Sub-sector CCUs. 25 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 OUTPUT 3.1. Improved soil health and rehabilitation of degraded lands INDICATOR 3.1.1. Definition: This indicator measures the number of farmers adopting/ Number of farmers using (over a period of time) a set of soil fertility management practices adopting integrated soil that combine fertilizer use, organic inputs, improved germplasm, soil fertility management testing, etc. for maximizing efficient use of applied nutrients. practices Rationale: To increase productivity while reducing emissions resulting from unsustainable soil fertility management practices. Disaggregated by: Practices, gender. Data source: Reports. INDICATOR 3.1.2. Definition: This refers to the area of land with integrated soil fertility Land area under management practices. integrated soil fertility Rationale: To increase productivity while reducing emissions resulting management practices from unsustainable soil fertility management. Disaggregated by: Practices Data source: Reports. INDICATOR 3.1.3. Definition: This indicator refers to the number of farmers adopting/ Number of farmers using soil and water management technologies and innovations. Soil adopting soil and and water management technologies and innovations refer to water management techniques that build soil health and better manage water resources. technologies and Adopting refers to extent to which farmers have accepted and innovations incorporated various climate-smart integrated soil and water management in their agricultural practices. Rationale: To enhance soil health and productivity. Disaggregated by: Gender, technologies and innovations. Data sources: Reports, field surveys. INDICATOR 3.1.4. Definition: This is the number of actors providing soil and water Number of actors management services e.g., soil testing. providing soil and water Rationale: To enhance access of the soil and water management management services services which is important for adoption. Disaggregated by: Actor, soil and water management service. Data source: Reports. INDICATOR 3.1.5. Definition: This is the area of land under soil and water management Area of land under soil technologies and innovations which refer to techniques that build soil and water management health and better manage water resources. technologies and Rationale: To reduce land degradation and increase productivity. innovations Disaggregated by: Technologies and innovations. Data sources: Reports and survey maps. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 26 INDICATOR 3.1.6. Definition: This is restoration of land that has lost its natural Area of degraded land productivity through degradation. Degraded land is land whose rehabilitated productivity has been lost because of loss of natural resources (soil, water, vegetation, rocks, air, climate, relief) because of human caused processes that include overgrazing, overuse, deforestation. Rationale: To improve land productivity, carbon sequestration, increased biodiversity, and ecosystem services. Disaggregated by: Type of degradation, rehabilitation method. Data source: Reports, survey maps. OUTPUT 3.2. Enhanced conservation of water and other natural resources INDICATOR 3.2.1. Definition: This indicator measures the trend in total land (in hectares) Change in area of land under conservation for agricultural use within the reporting period. under conservation/ This includes: swamps, riverbanks, critical fish habitats, agroforests, restoration rangelands. Rationale: Increasing land under conservation enhances adaptation and mitigation co-benefits (ecosystem goods and services). Disaggregated by: Land use, conservation measures. Data source: MoALFC, County, MoEF. INDICATOR 3.2.2. Definition: This indicator will track the trend in adoption of climate Change in number smart ecosystem conservation measures. E.g. minimum tillage, zero of value chain actors tillage, range rehabilitation, restocking, agroforestry. adopting climate-smart Rationale: Progressive increase in adoption of climate smart ecosystem conservation ecosystem conservation measures results in increased land under measures conservation that enhances adaptation and mitigation. Disaggregated by: Conservation measures, actors. Data source: CCU. INDICATOR 3.2.3. Definition: Number of water harvesting and storage structures Number of water including, small dams, water pans, farm ponds, water tanks, rock harvesting and catchments that are privately or communally owned. This excludes storage structures for mega structures like the electricity generating dams. agricultural use Rationale: These structures store rainwater that could have caused run off and soil erosion. The water harvesting and storage structures enhance water availability for agricultural use. Disaggregated by: Type of structures (small dams, water pans, farm ponds, water tanks, and rock catchments), actors (HH, communal, public etc.). Data source: County CCUs, WRUAs, WRA. 27 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 INDICATOR 3.2.4. Definition: This indicator seeks to track the number of non- Change in number of non- conventional livelihoods that are considered in the integrated conventional livelihood watershed management. These are considered as an addition to opportunities linked to conventional livelihoods leading to socio-cultural and economic integrated watershed diversification. These include use of gums and raisins, herb and medic. management Rationale: Progressive diversification of livelihoods opportunities in water sheds motivates natural resource conservation. Disaggregated by: Watersheds. Data sources: WRA, County Water Departments. OUTPUT 3.3. Enhanced access to climate risk-related agricultural insurance and other safety nets INDICATOR 3.3.1. Definition: This indicator tracks accessibility of agricultural safety nets Change in access to services that support farmers, livestock producers and fisher folks to agricultural safety nets rebound after hardship of adversity such as weather, endemic disease, services pest infestation etc. This includes subsides, cash transfers, etc. Rationale: The intervention is geared towards supporting farmers, livestock producers and fisher folks from falling into destitution as result of climate disasters. Disaggregated by: Value chains, service providers, actors. Data sources: Reports, MoALFC, NDMA, TNT, MOINC, National Safety Net Programme. INDICATOR 3.3.2. Definition: Index-based insurance refer to schemes where payouts are Change in access to triggered by disasters covering a large area. The trigger is based on a index–based insurance scale of severity of the disaster depending on the deviation from the products normal conditions. Rationale: The insurance scheme is geared at cushioning the insured against possible climate risks of livelihood and build their resilience. Disaggregated by: Value Chain, service providers, actors. Data sources: Survey, synthesis report. OUTPUT 3.4. Enhanced adoption of synergistic adaptation and mitigation initiatives INDICATOR 3.4.1. Definition: This indicator will track the trend of CSA initiatives that have Change in adoption of high potential for synergy between adaptation and mitigation. These synergistic adaptation will include initiatives that have both adaptation and mitigation and mitigation initiatives benefits. Rationale:Progressive increase in initiatives that have both adaptation and mitigation benefits will ensure faster transition of the agricultural sector towards low carbon development pathway. Disaggregated by: Value chains. Data sources: CCU, CCD, sub-sector reports. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 28 INDICATOR 3.4.2. Definition: A system to measure and track emissions arising from GHG accounting agricultural activities. system for adaptation Rationale: It is aimed at monitoring and reporting progress GHG interventions with high emissions arising from climate interventions. potential for mitigation Disaggregated by: Sub-sector, value chain, interventions. Data sources: MoALFC, County Agriculture departments. OUTPUT 3.5. Enhanced capacity for GHG accounting INDICATOR 3.5.1. Definition: These are the number of institutions with infrastructure to Number of institutions conduct assessments, collect data, calculate emissions, assure data with facilities to support quality and reporting. GHG accounting Rationale: To provide a platform for national GHG initiatives and programmes. Disaggregated by: Institution and facility. Data sources: Institutions. INDICATOR 3.5.2. Definition: These are trained personnel with capacity to use the GHG Number of experts accounting tools, facilities, conduct assessments, analyze GHG data and trained in GHG emissions generate accurate reports. accounting Rationale:To ensure that credible GHG reports are generated. Disaggregated by: Sub-sector, gender. Data sources: Sub-sector reports INDICATOR 3.5.3. Definition: This refers to the amount of GHG emissions abated or Change in GHG emissions sequestered because of interventions out in agricultural subsectors expressed in tons of CO2 equivalent. Rationale:To track GHG emission abated or sequestered by implementing resilience building interventions. Disaggregated by: Sub-sector, value chains and interventions. Data sources: Sub-sector reports OUTCOME 4. Communication of CSA information strengthened The aim of Outcome 4 is to strengthen communication systems related to CSA extension and agro- weather issues by generating, communicating, and disseminating CSA knowledge; by enhancing access to climate information and agro-weather advisory services and early warning systems; and by developing capacity in climate risk contingency planning. INDICATOR 4.1. Definition: This is the change in number of actors with access to CSA Change in total number information. This refers to information on climate, agro-weather, CSA of actors with access to technologies and innovations and GHG emissions. CSA information Rationale: To increase availability of CSA information. Disaggregated by: Actors, type of information. Data sources: Organizations. 29 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 INDICATOR 4.2. Definition: This is an operational database where different actors Existence of functional share and store information. CSA information Rationale: To build synergies, trigger necessary action and improve management systems information access. Disaggregated by: Information system. Data sources: Organizations, CSA MSPs websites. INDICATOR 4.3. Definition: These are plans developed for climate risk management by Existence of functional different actors at both county and national levels in the event of a contingency plans for catastrophic climate change disaster (e.g. flood and drought). climate risks response Rationale: To ensure swift and efficient response in the event of a disaster and minimize disruption of agricultural livelihoods. Disaggregated by: Type of risk (droughts, floods, mudslides). Data sources: National and County governments. INDICATOR 4.4. Definition: This indicator tracks the implementation of a Presence of functional communication strategy specifying products, media for different CSA communication audience. strategies Rationale: The communication strategy provides for targeted communication of information and knowledge sharing for effective decision-making. Disaggregated by: Governance level (National and County), National CSA MSP, non-state actors, value chains. Data sources: Counties, CCU, MSP website. OUTPUT 4.1. Enhanced CSA knowledge generation INDICATOR 4.1.1. Definition: This is a summary of best CSA practices or Number of CSA recommendations that provide enough contextual background knowledge products information and the description of the practice. Knowledge products developed refer to brochures, pamphlets, journals, reports, webinars, images, mobile and web based platforms etc. Rationale:To ensure the information is in the right form and content for effective action by the intended users. Disaggregated by: Knowledge product type, actor. Data sources: Organizations. INDICATOR 4.1.2. Definition: CSA best practices include approaches and methodologies Number CSA best that through experience and adoption have proven to reliably lead to practices documented desired results. These practices are generally accepted as superior to the dominant alternatives when they are documented as more productive, resilient and efficient in addressing climatic issues. Rationale: Proven success practices are important for up-scaling CSA, hence the need for documentation and dissemination. Disaggregated by: Value chains, type. Data sources: Organizations, institutions. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 30 OUTPUT 4.2. Enhanced CSA knowledge communication and dissemination INDICATOR 4.2.1. Definition: This indicator tracks the number of value chain actors Change in access to CSA accessing CSA advisory services. advisory services Rationale: Increase the proportion of value chain actors e.g. farmers, suppliers, livestock producer, fisher folks accessing CSA advisory services. Disaggregated by: Value chain actors, type of service. Data sources: Counties, CCU, CSA-MSP. OUTPUT 4.3. Enhanced access to climate information and agro-weather advisory services INDICATOR 4.3.1. Definition: This indicator seeks to track the integration of scientific and Change in number of indigenous knowledge in agro-weather advisories. Scientific knowledge agro-weather advisories includes advisory generated from climatic models whereas indigenous integrating scientific and knowledge entails predictions that are based on the observation of the indigenous knowledge biophysical environment, often by local communities. Rationale: Integration of scientific and indigenous knowledge will enhance the downscaling and accuracy of agro-weather advisories and promote the use of the advisories in decision making for agricultural activities. Disaggregated by: Type of advisory; County. Data sources: KMD. INDICATOR 4.3.2. Definition: This indicator tracks the number of public and private Change in number of extension personnel upskilled (capacity built) on agro-weather and service providers trained climate information. in climate information Rationale: Increase the proportion of farmers, livestock producers and and agro-weather fisher folks accessing climate information agro-weather services. advisory service delivery Disaggregated by: Type of service provider (public, private), county, gender. Data sources: KMD, counties, national government, CSA MSP. INDICATOR 4.3.3. Definition: This indicator shows the trend in the channels of passing Change in access to synthesized and packaged agro-weather information suitable to downscaled climate agro- communities and localities within a given period. weather information Rationale:There is value in packaging agro-weather information in a to communities and simplified format that local communities will understand and therefore localities in place take action. Disaggregated by: County. Data sources: County, Kenya Met, CCU. 31 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 OUTPUT 4.4. Early warning systems and contingency plans for climate change responses strengthened INDICATOR 4.4.1. Definition: This indicator tracks evidence of agriculture sector Change in the number of contingency plans that support prompt and appropriate responses in climate risk contingency the event of climate related risks and hazards. They are designed to plans developed reduce the negative impacts and support recovery. Rationale: Functional contingency plans ensure adverse negative effects to human and environment are minimized and there is fast bounce back to normal situations. Hence, there is need for these plans to be in place to mitigate against negative effect of climate change. Disaggregated by: County. Data sources: Counties, organizations. INDICATOR 4.4.2. Definition: These are stakeholders implementing contingency plans Change in the number made for current and future climate risks and hazards. of stakeholders Rationale: Contingency planning enables efficient and rapid response implementing the to climate change risk and hazards and this indicator tracks the contingency plans number of stakeholders actually implementing the contingency plans in place. Disaggregated by: County, type of stakeholder (state or non-state). Data sources: Organizations, counties. INDICATOR 4.4.3. Definition: These are activities planned ahead of time to ensure Number of climate risk effective response to climate related disasters. mitigation and disaster Rationale: Climate risk mitigation and disaster preparedness measures preparedness measures contributes to overall resilience therefore, this indicator assesses our preparedness for dealing with climate disasters. Disaggregated by: Type. Data sources: Organizations, counties. INDICATOR 4.4.4. Definition: An early warning system is a climate change adaptation Types of functional early strategy that uses integrated communication systems to assist warning systems for individuals, communities, governments or businesses in take timely climate change responses action to reduce climate related disaster risks. Rationale:Functional early warning systems will help planners protect land, infrastructure economies and save lives, jobs etc. therefore this indicator assesses sector preparedness for dealing with hazardous climate related events. Disaggregated by: Types. Data sources: Organizations. KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 32 REFERENCES 1. GoK (2007) Kenya Vision 2030 2. GoK (2018) Kenya Climate Smart Agriculture Implementation Framework 2018-2027. 3. GoK (2018) National Climate Change Action Plan (Vol 1) 2018-2022. 4. GoK (2018) National Climate Change Action Plan (Vol 2) 2018-2022 Adaptation Technical Analysis Report. 5. GoK (2018) National Climate Change Action Plan (Vol 3) 2018-2022 Mitigation Technical Analysis Report. 6. GoK (2017) Kenya Climate Smart Agriculture Strategy 2017-2026. 7. African Union (2017) First Ten-Year Implementation Plan of Agenda 2063 (2013-2023): Core Indicators Profile Handbook for Member States. 33 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 ANNEXES ANNEX I: Team of experts who developed this Climate-Smart Agriculture Monitoring and Evaluation Framework S/N NAME ORGANIZATION 1 Eng. Richard Kanui MOALF&C – Agricultural Engineering Secretary 2 Eng. Laban Kiplagat MOALF&C – Agricultural Engineering Services Directorate 3 Robin Mbae MOALF&C – Climate Change Unit 4 Veronica Ndetu MOALF&C – Climate Change Unit 5 Bernard Kimoro MOALF&C – Climate Change Unit 6 Peter Kimwele MOALF&C – Climate Change Unit 7 Jane Njeri Reuben MOALF&C – Climate Change Unit 8 Benjamin Kibor MOALF&C – Climate Change Unit 9 Davies Makilla MOALF&C – Climate Change Unit 10 Vincent Ongwag’ MOALF&C – Climate Change Unit 11 Julius Mutua MOALF&C – State Department of Livestock 12 Josephine Love MOALF&C – Comprehensive Africa Agriculture Development Programme Desk 13 Jesca Makena MOALF&C – Climate Change Unit 14 Joseph Komu MOALF&C – Central Planning Unit 15 Dr. Michael Okoti Kenya Agricultural and Livestock Research Organization 16 Zipora Otieno FAO Kenya 17 Peter Kuria Africa Conservation Tillage Network 18 Dr. Caroline Alliance of Bioversity International and CIAT Mwongera KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021 34 S/N NAME ORGANIZATION 19 Ivy Kinyua Alliance of Bioversity International and CIAT 20 Stella Kasura Alliance of Bioversity International and CIAT 21 Lucy Njuguna International Livestock Research Institute 22 Joab Osumba International Livestock Research Institute-Climate Change Agriculture and Food Security (CCAFS) 23 Dr. Lucy Ng’ang’a Ministry of Environment and Forestry 24 David Kiboi The National Treasury & Planning Monitoring and Evaluation Department 25 Elizabeth Mwangangi Joint Agriculture Secretariat – Intergovernmental Secretariat 26 John Mutiso The National Treasury & Planning Monitoring and Evaluation Department 27 Bernard Kimutai Monitoring and Evaluation Department-United Nation Development Programme 28 Elizabeth Wamalwa The National Treasury & Planning Monitoring and Evaluation Department 29 Dr.Bosco Okumu The National Treasury & Planning Monitoring and Evaluation Department 30 Cyrus Mageria Ministry of Energy 31 Zephaniah Onyiego MOALF&C – State Department of Livestock 32 Julia Kibor MOALF&C – Central Planning Unit 33 Mary Mutemi Green Africa Foundation 34 John Maina MOALF&C – State Department of Livestock 35 Venancia Wambua Biovision-Kenya 36 Daphne Muchai Women Farmers Association of Kenya 37 Mary Nyasimi ICCASA-Africa 38 Leah Wanja Women Farmers Association of Kenya 39 James Mutunga Nature Kenya 40 Anthony Kwaje ICT Specialist 35 KENYA CLIMATE-SMART AGRICULTURE MONITORING AND EVALUATION FRAMEWORK 2021