1. Supporting Small Scale Farmers Access to Climate Information (Roundtable)

2. Seasonal forecast

3. Type of forecast and comms method Agricultural decisions Seasonal (agric extension, barazas, churches and mosques, farmer groups, radio) o What crops to grow o What varieties to grow o Soil moisture conservation strategies to adopt o Modification of grazing strategies o Use of conserved forage o Purchasing feed before prices rise o Livestock breeding and sale o Renovation of flood protection measures Short-term (agric extension, SMS, radio, community/FG centre notice board) o Application of fertiliser/manure o Use of irrigation/rationing of irrigation resources o Weed and pest control measures o Movement of livestock o Forage conservation o Crop drying

4. So combine to increase use and relevance of the seasonal forecast + = (if LIs predict early start/finish to rains) 20% B 35% N 45% A 20% B 35% N 45% A or

5. How to interpret probabilistic information… A 45%+12 N 35%+2 B 20%-13 Two ideas…

6. Hedging – making proportionate decisions about crops to grow, seed to buy… A 45% N 35% B 20% As LIs have confirmed increased risk of early rains cessation, put veg plot into cassava? V Wetter season option e.g. high yield H maize Dry season option e.g. millet, sorghum Average season option e.g. composite maize and beans If rains are good, all these options will produce well anyway, so certain element of no-regrets here, but ultimately it is up to the farmer to decide Roughly 45% Roughly 20% Roughly 35%

7. But also taking into account… Seed supply and choice Other input supply Soil variation across the farm Access to irrigation Staple food preferences Market opportunities Perennial crops already cultivated Prevalence of pests and diseases

8. Thresholds – go for one strategy if the threshold is passed… A 45%+12 N 35%+2 B 20%-13 A+N80% N+B55% If A+N is 80% or more, the likelihood of a good season is high enough to bet the farm?

9. What sort of results should we expect… Evidence from Zimbabwe has demonstrated a yield improvement for maize from 9.4 – 18.7% due to increased access to meteorological information (Suarez et al, 2005). Farmers in Mali receiving short-term forecasts (10 day bulletins, 3 and 1 day forecasts) likewise achieved yield benefits for millet, sorghum and maize of 10 – 48% due to their increased use of climate information (Helmuth et al, 2010) Reasonable expectation – 10% to 20% yield enhancement and a fully functioning farmer forecasting service