A R4D Impact Pathway approach on CSA: Key dimensions how to target, scale-up & measure policy outcomes. Coherent Policies for Climate Smart Agriculture, OECD, MAFRA, Jeju, June 2015 Presentation by Ioannis Vasileiou, CCAFS Science Officer
Presentation Outline CCAFs: a R4D Impact Pathway approach on CSA, what, how & why? Key dimensions how to target, scale-up & measure policy outcomes on CSA Discussion Enabling and evaluating outcomes in a highly political context
A R4D Impact Pathway approach on CSA: what, how & why? Background CCAFS Phase 1 Theme-based research, region-based influence Log frame based planning Output focused = Supply driven research
A R4D Impact Pathway approach on CSA: what, how & why? Background CCAFS Phase 2 Flagship x region matrix Regional priorities focused = Demand driven Defined steps to impact Outcome focused Taking responsibility
Enabling Outcomes
ML&E of a Complex TOC Process Harmonization of IPs & ToCs Research on Institutional Transformation Indicators & Baselines Co-monitoring CCAFS M&E System Modules Accountability Assessment & Bonus allocation Reflective Spaces and Activities Co-reflection Reporting Responsibility
Discussion 1. A combined approach to program planning and linked ML&E allows for: Structured linear thinking: linear logic with assumptions for how change happens Complex systems thinking: flexibility to react according to lessons and opportunities arising during implementation 2. TOC creates opportunities for synergies and interdisciplinary approaches 3. There are Challenges! changing the culture of science Taking responsibility for the actions necessary to achieve outcomes Taking ownership of the development process Embracing partnerships amongst equals as a strategy to achieve outcomes 4. Research alone does not lead to impact, but: Generates knowledge which next-users can put into use to generate development outcomes We need to proactively bridge the gap between knowledge generation and development outcomes 5. Economies of scale research directly linked in our TOC to strategies for change brings us closer to enabling outcomes in the highly political context of climate smart agriculture
CCAFS Flagship 4: Global R4D program on Policies and institutions for climate-resilient food systems Vision for CCAFS Flagship 4: National, regional and global policies and institutions enable equitable food systems that are resilient to a variable and changing climate. Targets: 2 + 3 1 + 2 15 equitable national/subnational food system policies enacted that take into consideration climate smart practices and strategies, informed using knowledge, tools and approaches derived from CCAFS science 10 regional/global organisations inform their equitable institutional investments in climate smart food systems using CCAFS outputs. 20 equitable national/subnational jurisdictions will have increased institutional investments in climate smart food systems
FP4 Impact Pathway: a way to achieve impact and scale-up There needs to be an enabling institutional environment if millions of farmers are to practise climate smart agriculture Food system policies addressing climate impacts and adaptation options; climate policies addressing the agricultural sector and food security Policies to reduce inequity and the socially disadvantaged Adaptation will need widespread behavioural changes Addressing formal/informal strategies, norms and procedures (producer organizations, NGOs, local governance structures, businesses) Appropriately channelled international climate finance and global investment in CSA can help overcome adoption constraints
Flagship Program 4 Regional Priorities Mainstream adaptation strategies into national policies, agricultural development plans, and key regional agricultural-climate change processes (all regions) Learning alliances and national exchange platforms to support cogeneration of knowledge, enhance science-policy dialogue, promote evidence-based policy outcomes (all regions) Tools, case studies for food security planning including crop yield forecasting (SA, SEA, WA) & tools, case studies to inform decision-making on investments in climate-smart agriculture technologies and practices (all regions) Participatory scenarios developed for agriculture and food security and priority setting in the context of climate change to inform national and regional plans (all regions) Cross-regional synthesis on effective scaling up/out processes for CSA, including engagement mechanisms with policy-makers, evidence base of social learning effectiveness, equitable food systems governance
FP4 Portfolio in the regions East Africa West Africa Latin America South Asia Southeast Asia Policy action for climate change adaptation (IITA) National and regional partnerships to support CC in food systems policies Science policy exchange platforms to mainstream CC into national food systems policies (ICRISAT) Science-policy-practice interface in CC adaptation (ILRI) Scaling up CSA: technologies, practices, tools Influencing food systems policies with targeted CC information (CIAT) Climate smart agricultural sector planning Climate smart village models Scaling up climate smart agriculture though policies and institutions (IFPRI) Scaling out CSA: decision support tools and adaptation plans Global policy support for biologically diverse, climate resilient agriculture (Bioversity) Climate Change Impacts in Philippine Agriculture (IFPRI) Policy information and response platform on CC and Rice (IRRI) Mainstreaming CSA in national governments Governance and institutions for climate resilient food systems (FP4, IDS, IFPRI, U Indiana, U Osnabrueck, U Pretoria) Cross-regional syntheses of engagement strategies, governance mechanisms and learning systems (FP4, CU) Climate change and social learning: community of practice and evidence base to help scale outcomes (FP4, ILRI, IIED, IDRC, CSIRO) Scenario-guided policy and investment planning (FP4, regions, U Oxford) Climate science tools and engagement (FP4, U Reading) Global modeling tools and targeted engagement (IFPRI & IIASA) Strengthening resilience and climate change adaptation in the Pacific (WorldFish) CCAFS Global Policy Engagement for CC in Food Systems and vice versa (CU)
Toolkit to help prioritizing climatesmart interventions and investments Builds from bottom-up biophysical and socio-economic datasets Spatially explicit, integrated modeling framework Addresses climatic and socioeconomic scenarios Supports multi-objective trade-off analyses Supports more informed decision making on: Which crops to cultivate; Which climate-smart agriculture (CSA) technologies and practices to invest in; Where to target that investment and when those investments should be made. National Adaptation Plans (NAPAs/ NAPs) and National Mitigation Action plans (NAMAs)
Projected changes in Aboveground Net Primary Productivity (ANPP) in Africa s rangelands Mean changes for 2 emissions pathways: intermediate (RCP4.5, blue) and high-end (RCP8.5, orange) Spatial distribution of percentage change by 2050s and RCP8.5 in relation to 1971-1980 Thornton, Boone & Ramirez (2015)
Influencing and linking policies and institutions for the development and adoption of climate-resilient food systems Seeks to influence, and link, national to local policies and institutions, to support the development and adoption of climate-resilient food systems. In addition, seeks to influence policy implementation that encourages climatesmart agricultural practices across multiple scales. This to be done by strategically integrating the scientific community with policy actors. Engagement actions to be carried out through national level multistakeholder learning alliances. Main countries: Tanzania and Uganda Main actors: MoA, MoE, MoF, local governments, NGOs, media, civil society, private sector and research organizations, CCAFS, CGIAR Centres especially International Institute for Tropical Agriculture (IITA).
Agricultural production impacts Global partial-equilibrium multicommodity agricultural sector model. Links country-level supply & demand through global market interaction and prices. Further development: climate variability and shocks, robust food security indicators Outputs: Impacts of different technologies on market prices in the 2050s under different scenarios robust investment choices
Flagship 4 Key Learnings Moving to an outcome-orientated approach takes time, resources, new/different capacities Make systems good enough and practical, not the best they could be Coherent impact pathways help projects, regions, flagships set priorities and make activities more demand-led Big potential for cross-regional syntheses to distil major lessons on upscaling and what works where
Key dimensions how to measure policy outcomes on CSA We have to start monitoring CSA implementation We have to target CSA investments To increase the effectiveness of CSA interventions we need good approaches to target interventions but also better metrics for tracking outcomes and impacts Improved metrics will help us to better understand how CSA can deliver economic, adaptation and mitigation outcomes and any trade-offs between them While some facets of CSA have a long history in agricultural development (e.g. the goal of increasing productivity), and work on food security and vulnerability is well advanced, others are relatively new and open to diverse interpretations (e.g. climate modelling and vulnerability and suitability assessments for program design; the goal of building resilience and reducing emissions). See www.ifad.org/hfs/tools/hfs/fs_frameworkpub/foodsecurity.pdf
Key dimensions how to measure policy outcomes on CSA Monitoring. Which metrics are appropriate for measuring outcomes of CSA programs? How does one measure increased resilience or enhanced adaptive capacity? How can one measure mitigation benefits given the many difficulties of such measurements? Is it sufficient to measure adoption of CSA practices as a proxy for adaptation and mitigation benefits? What counts as an agreed upon CSA practice? Targeting. How much emphasis should be given to climate modelling, and vulnerability and suitability studies in shaping CSA programs? Which vulnerability metrics are most appropriate?
Targeting CSA Vulnerability assessment useful, but not obligatory, and ROI should be carefully considered, effort carefully measured Need to be a means to an end, and not be considered an end in itself Step wise CSA planning process allows for different levels of ex ante assessment to roll out CSA Can we ever answer the question: CSA practice/technology X is smarter than Y? Need good metrics, and common understandings of them View CSA as a spectrum: CSA policies/practices: can be CSA somewhere but none are likely to be CSA everywhere Growing evidence base can inform how climate smart an option is in a given context and scale
Metrics for Targeting and Monitoring CSA Agree on CSA by agro-ecological zone (practices and services) Use uptake approach In some places go deeper ToC approach or detailed questionnaires to see what CSA uptake is meaning in terms of resilience Is it feasible to track mitigation benefits & a proposal for moving forward Guidelines for mitigation metrics well developed, but estimating mitigation still constrained Emissions can be calculated as type and extent of activity x an emissions factor, according to the IPCC guidelines. GHG emissions can be estimated with relatively few indicators. Calculators exist such as the EX-ACT tool to support these estimates. Most calculators tend to overestimate emissions in tropical smallholder systems and have high uncertainty. The single most important impact on mitigation usually will be land use change, and secondarily in livestock emissions.
Key summaries from a CSA metrics meeting with the global community Summary of contexts Project Guidance, priority setting Ex ante assessments, impact analysis, screening. Project logframes (aims, tracking progress) Appraisals/evaluation Organizational/fund commitments to CSA, reductions Targets, objectives Criteria for investment National policy indicators and results frameworks (OECD, WB, IFAD) National stocktaking from surveys Global level such as SDGs Summary of types of metrics Goals and target indicators, suggested v. required indicators, logframes, indicators of project objectives and progress, index, household surveys, criteria related to processes Indicators of technologies v. enabling environment v. other sectorial influences and impacts (e.g. OECD)
Thank you! Contact Ioannis Vasileiou: i.vasileiou@cgiar.org