Climate Change Adaptation Results in Bicol Region (Step 3, AMICAF Project) DEPARTMENT OF AGRICULTURE RFO-5 BICOLS’ Experience Paddy Rice Production in Bicol, 1970-2010 • Provides employment to 40.7% of the Poverty Incidences of Families labor force and close to 40% of all by Province, Bicol Region families derive their income from the First Semesters of 2006, 2009 and sector. 2012 • The sector accounts for 70% of all commodity outflows of the region (food and live animals) • Poverty incidence is high in rural and coastal areas where majority of livelihoods depend on agri/fishery TCP: DRR/CCA Mainstreaming Framework (AG) Existing Local Extension Government Approaches DA) Units Farmer Field School Adaptability Trials/Field Days CBA Technology Resilient Agriculture Department of Commercialization Communities GP options, HVCA, EWS, PDNA, etc… Other PARTNER AGENCIES, NGO’s, Interventions ACADEME, PRIVATE INSTITUTION, OTHER STAKEHOLDERS 3 AMICAF Framework: Addressing the Linkage Between Climate Change &Food Security IV. Awareness Raising and Institutional Mechanism 6. Enhanced awareness on climate change impacts and vulnerability to food insecurity and improved institutional mechanism to conduct and use impact and vulnerability assessments (one country) II. Food Insecurity I. Climate Change III. Livelihood Adaptation to Vulnerability Analysis Impacts Assessment Climate Change 3. Enhanced national 1. Enhanced national capacities to analyze and map 5. Enhanced capacities capacities to assess impacts household vulnerability to of vulnerable of climate change on food insecurity in the context communities to adapt to agriculture (two countries) of climate change (two climate change (one countries) country) 2. Climate Change impacts 4. Household vulnerability to on agriculture assessed (two food insecurity in the context countries) of climate change analyzed and mapped (two countries) 7. Guidelines developed for implementation in other countries of the integrated approach framework for climate change and food security, and promotion of the framework (Global) 4 CLIMATE SMART – FFS Integration Framework Climate Field School Farmer Field School (Dumangas/Irosin Model) (PalayCheck) • Climate, Pest and Crop Growth and • Used high quality seeds of a Development recommended variety. • Cropping Systems and Climate – • No high and low soil spots after final Related Risks leveling. • Observation of Weather and Climate • Practiced synchronous planting after FFS Parameters a fallow period. – • Weather and Climate Information • Sufficient nutrients from tillering to Products and Sources (Temperature, early panicle initiation and flowering Rainfall, Evaporation Rate, Humidity) stages. • Forecast Generation, Climate Forecast • Avoided excessive water or drought Interpretation, Translation and stress that could affect the growth Communication and yield of the crop. • Incorporating Climate Forecast in • No significant yield loss due to pests. Decision Making • Cut and threshed the crop at the right time. • Topics and information on Climate/Weather outlooks, forecast, farm advisory, parameters etc…are discussed every meeting in addition to key check systems; CLIMATE SMART SMART CLIMATE • Proven GP options/adaptation strategies are introduced to participants for adoption/testing; • Focused on increasing farm productivity, reducing losses from climate related 5 risks and minimize food insecurity. Project Sites BASUD CALABANGA BULA CANAMA N CABUSAO BAAO GAINZA BUHI NABUA SAN FERNANDO Target Provinces and Municipalities: Camarines Sur: Buhi, Calabanga, Nabua, Gainza, Bula, Baao, Cabusao, Canaman (Seed Production at DA RFO-5, BEST, Pili) Camarines Norte: Basud 6 Masbate: San Fernando HOW DOES IT WORK? COMMUNITY INTERVENTIONS OUTPUTS SELECTION • High level of dependence • CS-FFS Module • Improved on agriculture • Testing of Good understanding on • Highly vulnerable to Practice Options for weather/climate info hydro-meteorological CCA • Identified GP options, hazards o GSR Lines/ Stress best performing • With existing FFS tolerant varieties technologies, varieties, program with LGU o Farming systems lines • With active FO and o Production • Mainstreamed cooperators Technologies DRR/CCA in agri. Example of Rainfall Monitoring Recorded rainfall ~48 mm 8 National CBA Conference 2012 Saline Prone Areas WS 2012-2013 (Calabanga) DS 2013 (Calabanga) WS 2013-2014 ( Ave. of 3 sites ) Ave. Differen % adv. Ave. Differen % adv. Ave. Differen % adv. Yield ce over Over Rank Yield ce over Over Rank Yield ce over Over Rank (mt/ha) Chk var. check (mt/ha) Chk var. check (mt/ha) Chk var. check GSR Lines GSR1 2.6 -0.9 -25.7 4.1 -0.8 -16.3 3.1 -0.5 -13.9 GSR2 3.8 0.2 5.6 GSR5 2.4 -1.1 -31.4 5 0.1 2 3 4.3 0.7 19.4 3 GSR5A 3.2 -0.3 -8.6 7 2.1 42.9 1 3.2 -0.4 -0.4 GSR8 4.3 0.8 22.8 2 5.9 1 20.4 2 4.4 0.8 22.2 2 GSR11 5.7 2.2 62.85 1 4.9 0 0 4.5 0.9 25 1 GSR12 3.6 -1.3 -26.5 3.2 -0.4 -11.1 GSR Lines ave. 3.6 5.1 3.8 0.1 2.8 0.2 4.1 0.2 5.6 Ave. of Check 3.5 4.9 3.6 Submergence Prone Areas WS 2012-2013 (Nabua) DS 2013 (Nabua) WS 2013-2014 ( Ave. of 2 sites ) Ave. Differen % adv. Ave. Differen % adv. Ave. Differen % adv. GSR Lines Yield ce over Over Rank Yield ce over Over Rank Yield ce over Over Rank (mt/ha) Chk var. check (mt/ha) Chk var. check (mt/ha) Chk var. check GSR1 3.4 -0.8 -19 0 0 4 0.7 21.2 GSR5A 4.6 0.4 9.5 2.2 -6.7 -75.3 3 0 -3.3 -100 GSR8 6 1.8 42.9 2 2.6 -6.3 -70.8 2 5.3 2 60.6 3 GSR11 3.5 -5.4 -60.7 1 6 2.7 81.8 1 GSR12 1.2 -7.7 -86.5 5.5 2.2 66.7 2 HHZ8-SAL14-SAL1-SUB1 5.1 0.9 21.4 3 IR 82858-B-B-1 (W142) 3 -1.2 -28.6 GSR Lines ave. 4.4 0.2 5.2 PSB Rc18(S1) 7.5 3.3 78.6 1 1.7 -7.2 -80.9 4.6 1.3 39.4 4 Ave. of Check 4.2 8.9 3.3 Drought Prone Areas WS 2012-2013 (Buhi) DS 2013 (Buhi) WS 2013-2014 ( Ave. of 5 sites ) Ave. Differen % adv. Ave. Differen % adv. Ave. Differen % adv. GSR Lines Yield ce over Over Rank Yield ce over Over Rank Yield ce over Over Rank (mt/ha) Chk var. check (mt/ha) Chk var. check (mt/ha) Chk var. check GSR1 6.9 3.9 130 2 GSR2 5.7 1.5 35.7 6.9 3.9 130 2 4.3 1.3 43.3 GSR5 3.6 3.6 85.7 3 3.6 0.6 20 5.1 2.1 70 GSR5A 3.6 3.6 85.7 3 5.4 2.4 80 4.8 1.8 60 GSR8 3.9 3.9 92.9 2 1.9 -1.1 -36.7 5.6 2.6 86.7 3 GSR11 4.1 -0.1 -2.4 1 6.8 3.8 126.7 3 7.1 4.1 136.7 1 GSR12 5.5 5.5 183.3 1 3.9 0.9 30 GSR Lines ave. 4.2 5 5.4 0 0 2 67.2 2.4 79.5 Ave. of Check 4.2 3 3 Comparative Yield (MT/Ha) of GPOs WS 2012 San Isidro-Inapatan, San Antonio- Salvacion Baybay, GPO's conducted Nabua Poblacion, Nabua Calabanga Yield, Yield, Yield, Variety/GPOs Variety/GPOs Variety/GPOs mt/ha mt/ha mt/ha Rice Duck NSIC Rc222 6 PSB Rc18s1 4.8 PSB Rc182 3.8 Nutrient Manager (IRRI) NSIC Rc222 6.5 PSBRc182 3.2 Farmer's Practice NSIC Rc222 5.5 NSIC Rc222 5.3 PSB Rc82 5.6 DS 2013 San Isidro Inapatan, San Antonio- Salvacion Baybay, Rice Duck GSR 11 3.5 NSIC Rc 222 8.9 GSR11,2,5 4.4 Farmer's Practice NSIC Rc222 5.5 PSB Rc10 4.5 NSIC Rc152) 3.4 DS 2013 WS 2013 Igbac, Buhi San Ant.-Pob., Nabua Yield, Yield, Variety/GPOs Variety/GPOs mt/ha mt/ha Rice Duck PSB Rc68 6.9 PSB Rc18s1 4.7 Farmer's Practice Malagkit 4.3 PSB Rc18 2.0 12 Yield (MT/Ha) in Seed Production, DA-BEST Maturity Rice Lines DS 2012 DS 2013 Remarks days Rounded grain similar to GSR1 1.4 3.3 106 Bigante prone to lodging, small plant GSR2 3.4 108 base preferred for aroma/good GSR5 2.1 2.7 108 eating quality GSR5A 2.2 2.7 108 GSR8 1.4 3.6 106 ideal for irigated, robust GSR11 2.4 GSR12 2.5 106 RTV PSB Rc18S1 2.2 128 prone to lodging . Total Area Planted: DS 2012 - 0.04 ha (80 m2/line) DS 2013 - 1.4 ha (2,000m2/line) 13 Findings and Lessons Learned . Under Bicol conditions, GSR generally yielded 2.8 – 5.6% yield advantage relative to check varieties; farmer varieties across 12 sites in the 6 provinces . Top yielders for most of the adverse agro- ecosystems are GSR 11, GSR 12 GSR 5a & GSR 8 . Better understanding of good practice options, climate/ weather forecast & timely delivery of advisories to farmers enhances local disaster preparedness and reduces livelihood losses; AWS Utilization/Upscaling of CS-FFS Climate smart Farmers Field School on corn slated! (http://www.bicol.da.gov.ph/News/2014/Feb%20- %20Climate%20Smart%20Farmers%20Field%20School%20for%20Corn%20slated.pdf) Used for monitoring trends in weather pattern/EW 2014 Particulars Data Source/Remarks JAN FEB MAR Computed based on the CAM. SUR Normal 260.1 175.9 149.29 climate outlook issued by (mm) PAGASA last January AWS installed under Actual Rainfall in 20.6 8.4 3.2 AMICAF Project (As of Nabua, CS (mm) March 13, 2014) Agro-Met Station in CBSUA, Actual Rainfall in 33.5 9.1 0.4 Pili, CS (PAGASA), as of Pili, CS (mm) March 13, 2014 16 National CBA Conference 2012 17.