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Decision Support Tools: Application in policy, planning and implementation

  1. Climate Governance, Diplomacy and Negotiations Leadership Program Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) Module 6, Unit 2: Decision support tools Application in policy, planning and implementation Laura Cramer, AICCRA Theme Leader on Policies and Priorities for CSA Virtual presentation to Cohort IX of the AGNES Climate Leadership Program 22 August 2022
  2. Climate Governance, Diplomacy and Negotiations Leadership Program Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) SESSION TEAM WITH MATERIAL FROM PHILIP THORNTON TODD ROSENSTOCK CONSTANCE NEELY SABRINA CHESTERMAN ROMY CHEVALLIER ANDREEA NOWAK CINIRO COSTA JUNIOR  LAURA CRAMER, ILRI/AICCRA Part 1, Introduction Part 2, Examples  ARUN KHATRI-CHHETRI, CONSULTANT  EVAN GIRVETZ, ALLIANCE OF BIOVERSITY & CIAT
  3. Objectives Understand the range of tools available for helping evaluate adaptation and mitigation interventions within different agriculture sub-sectors Recognize different strategies for developing baselines and undertaking planning under conditions of low data availability Be familiar with some available tools to generate long-term projections Be aware of resources for additional information and help from national or regional partners Appreciate the need to evaluate trade-offs across different sectors affected by and contributing to climate change
  4. Today’s plan Session 1 1:30 pm Opening and introductions (AGNES) 1:35 pm Overview of the topic of decision support tools and their uses (Laura Cramer) 2:00 pm Q&A 2:10 pm Bringing results of DSTs into planning processes and addressing socio-economic issues not covered in data-driven models 2:20 pm Instructions for self-led exercise 2:30pm Session closes Session 2 4:00 pm Opening, recap of what was covered earlier (Laura) 4:05 pm Feedback on self-led exercise on use of DSTs for decisions making 4:15 pm Example of a DST: gender hotspot mapping in Rwanda (Arun) + Q&A 5:00 pm DST examples for adaptation planning (Evan) 5:45 pm Final Q&A 6:00pm Session closes
  5. Key lessons on previous topics on long-term policy planning?
  6. Hazards, exposure, risk, vulnerability Planning, implementation Aids to decision making Context
  7. IPCC (2014)
  8. Godde et al. (2021)
  9. Decision support tools
  10. Decision support tools What are they? Ways of storing, visualizing and interpreting data and information to help people make decisions Who builds them? Anyone who wants to codify information & knowledge to strengthen the scientific basis of decisions
  11. Many tools available to supply different information needs Address uncertainty | Address multiple (competing) objectives | Evaluate the consequences of certain actions/ pathways | Provide a legitimate process and Basic analyses (graphs, maps, spreadsheets, reports, GIS); Impact models (e.g., ecosystem models, crop models, water resource models, disease models) Earth systems models (e.g., general circulation models, climate forecast models) Emission calculators (e.g., Life Cycle Analysis, GHG accounting, Carbon sink accounting tools) Economic models (e.g., cost- effectiveness and cost-benefit analysis) Policy simulations (role play workshops, computer-based simulations) Integrated assessment models (climate, energy, economic, etc.) Participatory processes (stakeholder/ expert elicitation)
  12. What kind of decisions might you make based on these maps? What other info would you need to pair with this? https://www.icpac.net/seasonal-forecast/
  13. “LOST WITHOUT INFORMATION” Insufficient information, poor quality “LOST IN INFORMATION” Lots of valuable data, inadequately packaged ADEQUATE INFORMATIO N FOR BETTER DECISIONS. Source: https://3st.com/work/big-data-editorial-illustration
  14. An example of a theory of change for decision support tools StakeHolder Approach to Risk informed and Evidence-based Decision-making - www.worldagroforestry.org/shared
  15. Many types of climate information for many user types and needs Emissions reductions scenarios (Rwanda NDC) Source: https://unfccc.int/sites/default/files/NDC/2022-06/Rwanda_Updated_NDC_May_2020.pdf (pg. 3)
  16. Many types of climate information for many user types and needs GHG inventory (Rwanda NDC)
  17. Many types of climate information for many user types and needs Composite vulnerability in Africa (Univ. of Texas/ Robert S. Strauss Center)
  18. How to visualize information depends on various factors • Information type • Availability of data • Audience • Skills, qualifications, resources for data analysis • Others The way data / information is packaged influences its accessibility
  19. Q&A
  20. Choose one of the following decision support tools to explore during the break Click around, looking at inputs needed, time needed, and possible outputs Come prepared to discuss in the next session Interactive exercise
  21. Example decision support tools: 1. ICPAC East Africa Hazards Watch: https://eahazardswatch.icpac.net/ 2. Cool Farm Tool: https://coolfarmtool.org/ 3. En-ROADS simulation: https://en- roads.climateinteractive.org/ 4. Geoportail Senegal: https://retd1.teledetection.fr/climap/pr oj/

Editor's Notes

  1. Impacts of climate change on the livestock food supply chain; a review of the evidence https://doi.org/10.1016/j.gfs.2020.100488 It’s a lot to think about. How do we make sense of it all? This example is from the livestock sector. Is there literature documenting effects on the sector you represent or are interested in?
  2. If we want evidence-informed decision-making, we need DSTs We see DSTs in our everyday lives
  3. How do we achieve all the things listed at the bottom? With Decision Support Tools…
  4. https://3st.com/work/big-data-editorial-illustration
  5. Ask if people are familiar with theory of change
  6. Rwanda NDC Univ of Texas: https://www.sciencedirect.com/science/article/pii/S096014811730527X Peter 2017: https://www.sciencedirect.com/science/article/pii/S0013935117315712
  7. Rwanda NDC Univ of Texas: https://www.sciencedirect.com/science/article/pii/S096014811730527X Peter 2017: https://www.sciencedirect.com/science/article/pii/S0013935117315712
  8. Rwanda NDC Univ of Texas: https://www.sciencedirect.com/science/article/pii/S096014811730527X Peter 2017: https://www.sciencedirect.com/science/article/pii/S0013935117315712
  9. Information type Some visualizations are more useful for certain information types than others; qualitative and quantitative data is reported in different formats Availability of data E.g., if you want to use a trendline, you need to have data for multiple timeframes (years, months). Otherwise, you’d show it in a table Audience Technical audiences may require more complex visualizations compared to a non-academic public Skills, qualifications, resources for data analysis Design skills of data analysists of the data
  10. En-ROADS: Energy Rapid Overview and Decision-Support Senegal help video in French: https://retd1.teledetection.fr/climap/
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