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Combined Presentations for climate-smart agriculture (CSA) Tools for Africa webinar

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Combined Presentations for climate-smart agriculture (CSA) Tools for Africa webinar

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On 12th October 2015 the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), East Africa through its regional knowledge sharing platform The Climate and Agriculture Network for Africa (CANA) organized a webinar dubbed Climate-Smart Agriculture Tools for Africa.

On 12th October 2015 the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), East Africa through its regional knowledge sharing platform The Climate and Agriculture Network for Africa (CANA) organized a webinar dubbed Climate-Smart Agriculture Tools for Africa.

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Combined Presentations for climate-smart agriculture (CSA) Tools for Africa webinar

  1. 1. Agroforestry What Works, Where: The CSA Compendium and X-Ray Nutrition security Poverty alleviation Natural resource Improved cook-stove Conservation agriculture Increased yields Soil quality & carbon Erosion Dietary diversity Intercropping Participatory approach Todd Rosenstock & Christine Lamanna World Agroforesty Centre (ICRAF) | Nairobi
  2. 2. Large Scale Initiatives and Investments Launched Sept 2014 80+ members Some CSA initiatives
  3. 3. Not CSA CSA What is CSA and what is not CSA?
  4. 4. Not CSA CSA Many practices can be CSA somewhere But none are likely CSA everywhere Context What is CSA and what is not CSA?
  5. 5. Photo: K. Tully What works where?
  6. 6. Key word search Abstract/title review Full text review Data extraction 144,567 papers 16,254 papers 6,100 papers ~175,000 data points Systematic review and meta-analysis 68 practices/28 indicators of CSA outcomes
  7. 7. Response ratio = ln(mean(treatment) /mean(control)) Effect size = weighted mean of response ratios ●● ● ●● ● ●●● ●●● ●● ●● ● ● ●● ●● ent on zer try −1.0 −0.5 0.0 0.5 Effect size Agroforestry Inorganic fertilizer Crop rotation Imp. diets Impact of select practices on productivity (N = 9,940)
  8. 8. ●● ● ●● ● ●●● ●●● ●● ●● ● ● ●● ●● ent on zer try −1.0 −0.5 0.0 0.5 Effect size Agroforestry Inorganic fertilizer Crop rotation Imp. diets ● ●● ●●● ●● ●● ●●● non−Legumionous Leguminous −1.0 −0.5 0.0 0.5 Effect size ● ●● ●●● ●● ●● ●●● non−Legumionous Leguminous −1.0 −0.5 0.0 0.5 Effect size - N fixing trees + N fixing trees ● ● ● Alt. feeds Inc. protein −0.2 0.0 0.2 0.4 Effect size Selecting ‘best bets’ for CSA by practice at global level Alt. feeds Inc. protein
  9. 9. Selecting ‘best bets’ for CSA for a place Productivity Resilience −1 0 −1 0 1 2 −1 0 1 2 Crop ManagementDiet ManagementIntercropping AgroforestryNutrient ManagementPostharvest StorageSoil ManagementTree ManagementWater Management Practice EffectSize Country Tanzania Uganda P1 P2 P3 P4 P5 P6 P7 P8 Productivity Resilience
  10. 10. Selecting ‘best bets’ for CSA for a place Productivity Resilience −1 0 −1 0 1 2 −1 0 1 2 Crop ManagementDiet ManagementIntercropping AgroforestryNutrient ManagementPostharvest StorageSoil ManagementTree ManagementWater Management Practice EffectSize Country Tanzania Uganda P1 P2 P3 P4 P5 P6 P7 P8 Productivity Resilience Predictable
  11. 11. Selecting ‘best bets’ for CSA for a place Productivity Resilience −1 0 −1 0 1 2 −1 0 1 2 Crop ManagementDiet ManagementIntercropping AgroforestryNutrient ManagementPostharvest StorageSoil ManagementTree ManagementWater Management Practice EffectSize Country Tanzania Uganda P1 P2 P3 P4 P5 P6 P7 P8 Productivity Resilience Predictable Less so
  12. 12. −1.0 −0.5 0.0 0.5 1.0 −1.0 −0.5 0.0 0.5 1.0 Productivity SOC Productivity (Effect size) Resilience(Effectsize) 11% 15% 56% SynergiesTradeoffs Tradeoffs Synergies and tradeoffs with CSA 19%
  13. 13. Practices differ in magnitude of co-benefits
  14. 14. Practices differ in magnitude of co-benefits
  15. 15. Studies with indicators for at least 1 component of CSA
  16. 16. Studies with indicators on 2 or more CSA objectives ~40% of the available research
  17. 17. Studies with indicators for all 3 components 1.5% of the available research
  18. 18. Turning data in decision-support ‘CSA X-ray’ Evidence-based and digestible assessments of CSA practices and places Figures and icons: Morningstar
  19. 19. Financial support: CCAFS, UN FAO, IFAD, CIFOR-EBF Contributors: K Tully, C. Corner-Dolloff, E Girvetz, D-G Kim, M Lazaro, A Jarvis, P Bell, S Chesterman, S MacFatrige, H Strom, A Madalinska, A-S Eyrich, C Champalle, W English, A Akinleye, A Poultouchidou, A Kerr, H Neufeldt, A Arshan, J Rioux, F. Atieno, M Ravina, C Zhuo, S Abwanda, W Zhuo, C Ardilla, P Laderach, D Grunzel, S Vermuellen, O Bonilla-Findji, K Morris, J Dohn, M Richards, B Campbell, A Arslan, J Rioux Thank you, t.rosenstock@cgiar.org Data will be publically available in 2016
  20. 20. Directing Investment in Climate-Smart Agriculture (CSA) CSA Prioritization Framework Climate-Smart Agriculture Tools for Africa Webinar 13 October 2015 Caitlin Corner-Dolloff CIAT, Decision and Policy analysis c.corner-dolloff@cigar.org Miguel Lizarazo (CCAFS-LAM), Andreea Nowak (CIAT), Fanny Howland (CIAT), Nadine Andrieu (CIAT/CIRAD), Osana Bonilla (CCAFS), Ana Maria Loboguerrero (CCAFS-LAM), Andy Jarvis (CIAT-CCAFS) © CIAT/Neil Palmer
  21. 21. Alliance for CSA in Africa Vision 25 x 25 West Africa CSA Alliance (WACSAA) Global momentum building for CSA Map of a selection of CIAT-ICRAF CSA initiatives with CCAFS, WB, USAID from 2014-2105 6 million farmers by 2021 Linking 19 countries 500 million farmers globally CSA one of 5 priority investment areas Niger, Kenya 200 million in CSA
  22. 22. A set of filters for evaluating CSA options & establishing CSA investment portfolios CSA Prioritization Framework Multi- level Linkable Stakeholder Driven Flexible Simple Intended users 1° National and sub-national decision makers 2° Donors, NGOs, implementers
  23. 23. CSA Prioritization Framework Filters for selecting CSA investment portfolios *Identify scope *Match practices with context *Participatory metrics selection Long list of CSA practices *Ex-ante assessment based on CSA indicators *Stakeholder workshop Ranked short list of priorities *Economic analysis – assess costs and benefits, including externalities Ranked short list based on CBA *Integrated analysis of opportunities & constraints * Stakeholder workshop CSA investment portfolios Pilots underway Ethiopia Ghana Uganda
  24. 24. Workshop 1 Guatemala Filtering: Indicators of CSA Pillars Workshop Literature review Expert interview + + Lessons: • Participatory indicator selection - link science with desired change • Improved communications and visualization of data key for CSA decision-making Ranked long list of possible CSA Practices ScoreCSA Practices
  25. 25. Guatemala Filtering: Economic Evaluation Lesson: Econ analysis in high demand - data and tools needed to better assess and easily visualize options
  26. 26. Prioritized Practices Portfolios Designers Producers Research MoAgr Agroforestry systems: live fence  Varieties tolerant to pests & diseases  1: low resource farmers Varieties tolerant to drought and water stress   1: low resource farmers Conservation agriculture  2: FS, drought Crop rotation (maize-beans)  Reservoirs + Drip irrigation X: FS, drought Guatemala Filtering: Integrated Analysis CSA indicators, CBA, externalities, barriers and opportunities Lesson: Prioritization does not imply one output • Multi-variate analyses allow users to create differentiated portfolios based on intended application and beneficiaries
  27. 27. Lesson: Process is as important as the content • Discussions of data create space for collaborative integrated planning between users • EU modifying calls based on results – other potential applicants linked from beginning Mali CSA at the Regional Level Policy/Research forums (AEDD) Regional governments NGOs (C-GOZA, Sahel Eco) Donors (EU, Swedish Embassy) CONTEXT POTENTIALUSERS
  28. 28. Lesson: Local ownership is critical to prioritization • Local communities act as researchers • Minimize extractive data collection • Adapt metrics to local context and socialize prior to users. Training on Survey Discussion on indicators Colombia CSA at the Local Level © CIAT/Andreea Nowak
  29. 29. CSA-Plan Uptake of CSA Plan components, including CSA PF, in 15+ countries in Asia and Africa 2015-2018 ICRAF - T. Rosenstock, C. Lamanna CIAT - E. Girvetz, C. Corner-Dolloff
  30. 30. Ongoing CSA initiatives
  31. 31. Caitlin Corner-Dolloff c.corner-dolloff@cigar.org additional information at: ccafs.cgiar.org/climate-smart-agriculture-prioritization-framework Thank you!
  32. 32. Climate Smart Agriculture Rapid Appraisal (CSA-RA) Caroline Mwongera, Leigh Winowiecki, Kelvin Mashisia, Jennifer Twyman, Peter Laderach, Edidah Ampaire, Steve Twomlow 13 October 2015
  33. 33. Climate Smart Agriculture Rapid Appraisal (CSA-RA) • Combine socio-economic and biophysical realities across scales in order to prioritize, implement and out-scale CSA A tool for Prioritization of Climate Smart Agriculture across Landscapes PRA Tools Scale 1. Village resource maps 2. Climate calendars 3. Historical calendars 4. Cropping calendars 5. Organizatio n mapping using Venn diagrams Household- farm Community- landscape Sub-regional scales  Gendered lens  climate focus
  34. 34. CSA-RA Methodology Participatory Approach 1. Farmers’ Workshops 2. Expert Interviews 3. Farm visits (interviews / transect walk) Gender disaggregated Site-specific targeting of CSA interventions Expert opinion Socio- economic data 1. Crop & Livestock listing/uses/ge nder association 2. Community/ village resource maps 3. Cropping calendar 4. Historical calendar 5. Climate calendar 6. Institutional mapping  Challenges  Current practices  Community resources  Climate impacts  Local organizations for:  Women  Men  Youth (< 30 yrs.)  Farming systems  Current practices  Recommend ations on site-specific CSA intervention s  Barriers and constraints to adoption  HH size, farm size  HH food sufficiency  Labor (HH & hired)  Production (crop/livestock)  Yield  HH consumption  Sales  Off farm income  Remittances, donations, savings  HH expenses  Use of agricultural inputs  Current practices CSA Prioritization o Awareness and use of agricultural o Prioritization of practices by gender & AEZ o Ranking indicators considered in adopting a practice o Demonstratio n plots o Practic es o Sites 3. Prioritizatio n Workshops
  35. 35. Cropping calendar Identifies most important crops by gender, division of responsibilities and different crop management activities Crop management activities by month for groundnut, cassava and sesame as detailed by the male participants in the farmer workshop in March 2014 in Gulu district of Uganda. Logograms indicate whether men or woman undertake the activity Crop management activities by month for beans, cassava and sesame as detailed by the female participants in the farmers workshop in March 2014 in Gulu district of Uganda. Logograms indicate whether men or woman undertake the activity.
  36. 36. Organization mapping Organization mapping and linkages as detailed by the female participants (left panel) and male participants (right panel) in the farmers workshop in September 2014 in Mbarali district of Tanzania. Blue circles denote those ranked as of high importance, yellow circles of medium importance, and pink circles of low importance. Acronyms represent the organizations. Indicate organization linkages, as well as gendered differences in their ranking
  37. 37. Climate calendars Reveal climate variability perceptions over time, gendered impacts and vulnerability Organization mapping and linkages as detailed by the female and male participants in the farmers workshop in September 2014 in Mbarali district of Tanzania. Blue circles denote those ranked as of high importance, yellow circles of medium importance, and pink circles of low importance. Acronyms represent the organizations.
  38. 38. CSA Prioritization Prioritization of agricultural practices in Anaka, Northern Uganda by gender and by agro-ecological zone
  39. 39. Targeting & Out-scaling site-specific CSA practices • Guide agricultural investments • PRELNOR Project (IFAD) • Select project sites • Socio-economic surveys • Land Health Surveys • Select location of CSA demonstration sites • Institutional support • Local stakeholders/organizations
  40. 40. Manual and Reports Available at CCAFS Harvard Dataverse: https://dataverse.harvard.edu/datas et.xhtml?persistentId=doi:10.7910/ DVN/28703 Output for the CIAT-led, project “Increasing Food Security and Farming System Resilience in East Africa through Wide-Scale Adoption of Climate-Smart Agricultural Practices” funded by IFAD
  41. 41. Participatory Scenario Planning: A decision support approach for Climate-Smart Agriculture Adaptation Learning Programme – CARE International CSA Tools in Africa CCAFS, CARE Webinar 13th October 2015
  42. 42. Known and unknown? Changing climate and weather patterns. Growing challenge for smallholder farmers, pastoralists, VCA. Future climate risks, opportunities? Future climate impacts - agricultural productivity, incomes, vulnerable communities, women, men? WWW.CARECLIMATECHANGE.ORG
  43. 43. What needs to be done? • Adaption in agriculture & building resilience to climate (CSA)…How? • Community-based adaptation: social decision-making processes + support to technical adaptation strategies WWW.CARECLIMATECHANGE.ORG • Climate informed decision making and planning… But: Uncertain climate information – planning for inexact is challenging Large vs local scale
  44. 44. Participatory Scenario Planning (PSP) WWW.CARECLIMATECHANGE.ORG Multi-stakeholder forum for: • Accessing, understanding seasonal climate forecasts and • Collectively interpreting them – locally relevant, actionable information for decision making and planning.
  45. 45. Why PSP? • Scenarios: planning for likely & less certain outcomes • Earlier, better informed: advisories to take advantage of opportunities, reduce risks WWW.CARECLIMATECHANGE.ORG • Learning now to continually manage seasonal climate variability, risks and uncertainties […] provide potential pathways for strengthening stakeholders’ adaptive capacities to manage climate change in the long term (Niang, et al., 2014)
  46. 46. Step 1. Designing the PSP process Developing a well thought out, locally relevant and appropriate PSP process, including deciding the level (national, county/province, district etc.) at which to conduct PSP and forming partnerships for sustainability of the process Step 2. Preparing for a PSP workshop Engaging stakeholders, bringing out their information needs for the coming season and using this to plan for targeted workshop outcomes. Step 3. Facilitating a PSP workshop Multi-stakeholder forum – access, understanding & combining meteorological & local seasonal forecasts; interpretation into locally relevant and actionable information for seasonal decision making & planning. Step 4. Communicating advisories from a PSP workshop Reaching all actors who need to use the information, in good time to inform decisions and plans. Step 5. Feedback, monitoring and evaluation Two-way communication and feedback between producers, intermediaries and users of climate information enabling continuous, iterative and shared learning and improving the PSP process and outcomes. PSP is an iterative learning process The PSP process
  47. 47. Value of PSP in climate-smart agriculture WWW.CARECLIMATECHANGE.ORG Building adaptive capacity & resilience…
  48. 48. Value of PSP in Climate-Smart Agriculture WWW.CARECLIMATECHANGE.ORG Building adaptive capacity… • Institutions, entitlements and governance – multi-stakeholder dialogue, responsiveness & accountability • Regular planning – informed by changing risks, vulnerability, capacity, resources, knowledge and information
  49. 49. Way forward? • Projects, programmes: e.g. Kenya Agriculture Sector Development Support Programme – link with VCA platforms • Development plans, budgets: e.g. N. Ghana DMTDP; Kenya Garissa County CIDP, Agriculture work plan • Policy: e.g. Malawi Meteorology Policy WWW.CARECLIMATECHANGE.ORG Integration of PSP in…
  50. 50. Thank You! Adaptation Learning Programme (ALP) www.careclimatechange.org/adaptation-initiatives/alp alp@careclimatechange.org Joto Afrika Special Issue 12 on Climate communication for adaptation: http://www.alin.net/Joto%20Afrika Building resilience to climate change and enhancing food security in north eastern Kenya: http://www.careclimatechange.org/files/stories/ALP_Kenya_Noor_Aug2012_final.pdf Facing Uncertainty: the value of climate information for adaptation, risk reduction and resilience in Africa: www.careclimatechange.org/files/Facing_Uncertainty_ALP_Climate_Communications_Brief.pdf Coming soon “Climate information for resilient agricultural decision-making and planning in rural communities: A Guide to Participatory Scenario Planning” WWW.CARECLIMATECHANGE.ORG ALP is supported by
  51. 51. targetCSA - a decision support tool to target CSA practices - Patric Brandt, Marko Kvakić, Klaus Butterbach-Bahl and Mariana Rufino March, 3 2014
  52. 52. Key elements • National - regional scale • Spatially explicit • Combining vulnerability indicators & CSA practices • Participatory process • Consensus oriented ?
  53. 53. targetCSA – the framework
  54. 54. Vulnerability indicators CSA practices Example
  55. 55. targetCSA – the framework
  56. 56. Expert opinions • Stakeholder preferences on prioritizing: • Vulnerability indicators • CSA practices • Consensus = minimized dissent NGOGO Sci. Priv. Optimization model
  57. 57. targetCSA – the framework
  58. 58. Spatial indices Aggregated & consensually weighed by stakeholder opinions + Maps are based on example data. majority vs. minority Identifying regions of high vulnerability & CSA suitability
  59. 59. targetCSA: Take home • Problem structuring & complexity reduction • Spatial indices built on consensus & evidence • Exploring consensus scenarios may lead to higher acceptance • Demand-based assessment of CSA potential • Transferability & flexibility
  60. 60. Asanteni sana!

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