Targeting and prioritization
A range of technological, institutional, and policy options for climate-smart interventions exists that have varying environmental and economic impacts and costs. Identifying appropriate interventions requires tradeoffs across levels from farmers to sub-national and national policy makers and consideration by decision-makers about what is appropriate for given contexts. Decision-support tools are therefore needed which can assist relevant stakeholders to prioritize appropriate strategic decisions to improve the resilience, adaptability and efficiency of agriculture and rural livelihoods in the face of climate change.
Targeting and prioritizing approaches narrows an extensive list of possible practices, services, and policies down to a range of best-bet options that can be scaled out, and which may serve to attract investment and funding. Various tools are available, such as the CIAT/CCAFS CSA Prioritization Framework, CCAFS’ CSA Prioritization Toolkit, mitigation optimization tools (e.g. FAO’s EX-Ante Carbon-balance Tool and CCAFS’ Mitigation Optimization Tool), as well as CCAFS compendium of CSA practices. These tools generally aim to provide guidance on the following sub-questions:
- What regions, production systems, and users should adaptation interventions be prioritized for?
- What existing and promising adaptation options should be assessed for investment?
- What criteria should be used to evaluate and prioritize options, e.g. ability to build resilience; achieve co-benefits such as mitigation; economic costs and benefits?
- What barriers to adoption exist, and how can these be overcome for investments to have impact at scale?
- What are the optimal policy options to support adaptation and transformation across spatial and temporal scales?
The CCAFS-CIAT CSA Prioritization Framework (CSA-PF), designed for channeling CSA investments, has the objective to help decision makers identify best-bet CSA investment portfolios that achieve gains in food security, farmers’ resilience to climate change, and low-emissions development of the agriculture sector. The framework is divided into four phases: (i) Initial assessment of CSA options; (ii) Identification of top CSA options (workshop); (iii) Calculation of cost and benefits of top CSA options; and (iv) portfolio development and evaluation of barriers (workshop).
The preparation phase aims to identify the objectives of the prioritization process, the stakeholders to be involved, and the long list of CSA options to consider for investment. A stakeholder analysis needs to be undertaken to identify key natural resource user groups, decision-makers, potential partners, and experts needed to co-determine and/or validate the objectives of the CSA program/initiative.
Given that CSA is highly context-specific, the priorities shift according to the scope and planning timeline in question. The first filter then is to set the scope for the prioritization initiative (e.g. production systems, agro-ecological zones, nature of climate change to be addressed, types of farmers targeted, transformative actions needed). A scoping assessment should be conducted with key users, implementers, and/or funders of the CSA portfolios intended to be designed. Once the scope is clarified, a list of relevant practices, services and policies – linked to stakeholder preferences and the social and ecological context – can be identified. Here, data repositories, such as the CCAFS compendium of CSA practices – a web-tool with more than thousand CSA technologies and practices categorized into geographical domain and potential benefits – or expert assessments can be used for the creation of an overview of CSA options (for tool description see the Monitoring, evaluation and learning section of CSA plan on this website).
Once a list of CSA options is created, practices can be evaluated for the expected (social, environmental and economic) impact they will have in each specific context, and for each type of land user (as well as the community as a whole/the social-ecological system). Indicators related to the three goals of CSA can be selected, based on existing monitoring and evaluation frameworks underlying the CSA goals (see the Monitoring, evaluation and learning section of CSA plan on this website). These indicators should be linked to existing policy or programmatic initiatives (as well as scientific evidence) to better ensure CSA mainstreaming within ongoing frameworks. A brief description of each potential intervention is prepared, including possible constraints and benefits, for use by each relevant stakeholder to help reduce the list of best-bet CSA options.
The options identification phase seeks to reduce the initial long list of CSA options. A broad group of stakeholders is brought together to validate overall objectives, and to define the relative weight that should be given to each of the three pillars of CSA – adaptation/resilience, mitigation/low-emissions development and productivity/food security – as well as to the different sub-indicators related to each CSA goal. Stakeholders will further analyze and discuss the expected impacts different land use practices/development trajectories will have on the CSA goals, as well as the scalability, feasibility and potential beneficiaries of each practice.
The third phase – economic analyses of available options – has the objective to assess the costs and benefits of each CSA option, and of different portfolios of CSA options over time. The tailored menu of CSA options, weighted criteria, and indicators from phases 1 and 2 are used as input into economic modelling prioritization tools (e.g. there are excel and web-based tools designed by CCAFS for cost-benefit analysis [CBA] assessment of CSA initiatives). Data inputs into the CBA modelling can be from primary data, scientific literature and expert knowledge. The short list of CSA options – selected by stakeholders for being agro-ecologically sound, socio-economic relevant, and of benefit to the three CSA goals – is now being ranked based on a cost-benefit or cost-effectiveness analysis of investment.
The final phase – the portfolio analysis and evaluation of barriers – reunites stakeholders to review all previously conducted analyses. Ratings for possible CSA options based on impacts, costs and benefits are visualized to support discussions on trade-offs between different CSA practices. Aggregate benefits from different portfolios of CSA options can then be explored for a final selection of investment priorities.
A critical component of the final workshop is a robust analysis of perceived constraints and barriers to adoption from the perspective of different stakeholder groups. This assessment builds an understanding of social, cultural and economic barriers to a widespread adoption of triple-win CSA options, which can improve design and implementation plans. Portfolios of options and suggested best practices with the greatest prospects of success are then selected by stakeholders for national, regional and/or local implementation.
Figure 1: Overview of different phases of the CCAFS CSA Prioritization Process
Source: Corner-Dolloff C. 2014. Climate-smart agriculture investment prioritization framework. Presentation at COP 20, Lima Peru. http://es.slideshare.net/ciatdapa/climatesmart-agriculture-investment-prioritization-framework
Background and purpose
To be able to assist farmers and policymakers in prioritizing strategic CSA interventions, the CCAFS team in South Asia, together with local partners, is developing a Climate-Smart Agriculture Prioritisation Toolkit (CSAP). The toolkit allows the user to identify robust decisions, that is, the best possible decisions within a set of uncertain circumstances. It is then feasible to carry out a trade-off analysis of alternative climate-smart agriculture development pathways, and thus to support decisions on which crops to cultivate, which climate-smart agricultural technologies and practices to invest in, where to target that investment, and when to make these investments.
Use and users
The CSAP toolkit is built on a spatially-explicit land-use planning framework of agricultural production accounting for (i) spatial crop-yields, inputs/outputs, and production costs, (ii) land, water and labor availability, and (iii) greenhouse gas emissions from agriculture. The toolkit is designed as a linear mathematical programming model, and requires a detailed location-specific database on soil, crop varieties, cropping area, agronomic practices, irrigation and historical weather information along with socio-economic data. This database is set within a spatially-explicit modelling framework that is capable of handling a wide range of constraints and scenarios. The land-use model calculates minimum-cost pathways to meet future demand targets under a range of agricultural growth scenarios. Future crop yields, water-use and emissions are forecasted under different climate-scenarios using crop-modelling techniques and empirical evidence.
CSAP is being tested in the state of Bihar, India, where CCAFS is developing a range of baseline growth scenarios, and assessing their vulnerability to climate-change impacts for the near-term (2020s), mid-term (2050s) and long-term (2080s) under CMIP5-based emission scenarios. Here, the project has been able to demonstrate the potential of the model to identify priorities for investment in: (i) Crops best suited to delivering target growth under impacts of climate change on yields; (ii) Technologies to deliver targeted increases in productivity, based on potential yield increases and the efficient use of resources; and (iii) Locations for priority investment given an existing surplus of productive capacity. Besides, the investment required to climate-proof agricultural development is explicitly identified – providing valuable bottom-up evidence to support top-down estimates of the costs of climate change adaptation.
- A toolkit to prioritise interventions in climate-smart agriculture: https://cgspace.cgiar.org/rest/bitstreams/38402/retrieve
- Blog - New toolkit on climate-smart agriculture can help policymakers make better decisions: https://ccafs.cgiar.org/blog/new-toolkit-climate-smart-agriculture-can-help-policymakers-make-better-decisions
Researchers at the University of Aberdeen, in partnership with CCAFS, the International Centre for Tropical Agriculture (CIAT), and the University of Vermont’s Gund Institute for Ecological Economics, are developing a Mitigation Options Tool for calculating greenhouse gas emissions from different agricultural practices.
The CCAFS Mitigation Options Tool (CCAFS-MOT) estimates greenhouse gas emissions from multiple crop and livestock management practices in different geographic regions, providing policy-makers across the globe access to reliable information needed to make science-informed decisions about emission reductions from agriculture.
Use and users
Several GHG calculators now available calculate emissions from either single crops or whole farms. Unlike these agricultural calculators, CCAFS-MOT:
- Ranks the most effective mitigation options for 34 different crops according to their mitigation potential, and in relation to current management practices as well as spatially-linked climate and soil characteristics.
- Has low-input data requirements – approximately 10 minutes are needed.
- Runs in Excel.
- Will be freely downloadable from the CCAFS website.
CCAFS-MOT joins several empirical models to estimate GHG emissions from different land uses and considers mitigation practices that are compatible with food production. Several studies that informed the mitigation potentials are used in this tool.
- CCAFS Mitigation Option Tool for agriculture: https://ccafs.cgiar.org/mitigation-options-tool-agriculture
Background and purpose
The Ex-Ante Carbon-balance Tool (EX-ACT) is an appraisal system developed by FAO, and provides ex-ante estimates of the impact of agriculture and forestry development projects, programs and policies on the carbon-balance. The carbon-balance is defined as the net balance from all greenhouse gases (GHGs) expressed in CO2 equivalents that were emitted or sequestered during project implementation as compared to a business-as-usual scenario.
Use and users
EX-ACT is a land-based accounting system, estimating C stock changes (i.e. emissions or sinks of CO2) as well as GHG emissions per unit of land, expressed in equivalent tons of CO2 per hectare and year. The tool helps project designers to estimate and prioritize project activities with high benefits in economic and climate change mitigation terms. The amount of GHG mitigation may also be used as part of economic analyses, as well as for the application for additional project funds.
EX-ACT can be applied to a wide range of development projects from all AFOLU sub-sectors including, among others, projects on climate change mitigation, sustainable land management, watershed development, production intensification, food security, livestock, forest management or land use change. Moreover, it is cost-effective, requires a comparatively small amount of data, and provides for features (tables, maps) which can help finding the required information more easily.
While EX-ACT is mostly used at the project level, it may easily be up-scaled to the program/sector level, and can also be used for policy analysis.
- Climate-Smart Agriculture Sourcebook: http://www.fao.org/3/a-i3325e.pdf
Background and purpose
With the concept climate-smart agriculture (CSA) being relatively new, there is a need to test and develop practical and systematic methodologies and approaches for documenting and evaluating CSA practices in the field. The implementation of CCAFS’ Climate-Smart Villages (CSV) involves identifying, assessing and selecting climate-smart farming practices. The report titled 'Participatory identidication of climate-smart agriculture priorities' contains three sections: (i) a framework for identifying and assessing CSA in the field with a long list of CSA indicators in identifying and monitoring CSA interventions; (ii) cost-benefit analysis of some selected climate-smart farming systems; and (iii) the participatory process of prioritizing CSA options with the villagers. The work builds on experiences from the My Loi CSV and its scaling domains in Ky Anh district, Ha Tinh province, in the north-central region of Viet Nam.
- Participatory identification of climate-smart agriculture priorities: https://cgspace.cgiar.org/rest/bitstreams/78307/retrieve