climate change adaptation results in bicol region...cam. sur normal (mm) 260.1 175.9 149.29 computed...
TRANSCRIPT
Climate Change Adaptation Results in Bicol Region
(Step 3, AMICAF Project)
DEPARTMENT OF AGRICULTURE RFO-5
BICOLS’ ExperiencePaddy Rice Production in Bicol,
1970-2010
• Provides employment to 40.7% of the labor force and close to 40% of all families derive their income from the sector.
• 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
Poverty Incidences of Familiesby Province, Bicol RegionFirst Semesters of 2006, 2009 and 2012
TCP: DRR/CCA Mainstreaming Framework (AG)
3
Farmer Field School
Adaptability Trials/Field Days
Technology Commercialization
Existing Extension
Approaches DA)
CBA
GP options, HVCA,EWS, PDNA, etc…
Other Interventions
Dep
artm
ent
of
Agr
icul
ture
Local Government
Units
PARTNER AGENCIES, NGO’s, ACADEME, PRIVATE INSTITUTION,
OTHER STAKEHOLDERS
ResilientCommunities
AMICAF Framework:Addressing the Linkage Between Climate Change &Food Security
4
I. Climate Change Impacts Assessment
II. Food Insecurity Vulnerability Analysis
III. Livelihood Adaptation to Climate Change
IV. Awareness Raising and Institutional Mechanism
1. Enhanced national capacities to assess impacts
of climate change on agriculture (two countries)
2. Climate Change impacts on agriculture assessed (two
countries)
3. Enhanced national capacities to analyze and map
household vulnerability to food insecurity in the context
of climate change (two countries)
4. Household vulnerability to food insecurity in the context of climate change analyzed and mapped (two countries)
5. Enhanced capacities of vulnerable
communities to adapt to climate change (one
country)
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)
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)
CLIMATE SMART – FFS Integration Framework
5
Climate Field School(Dumangas/Irosin Model)
• Climate, Pest and Crop Growth and Development
• Cropping Systems and Climate –Related Risks
• Observation of Weather and Climate Parameters
• Weather and Climate Information Products and Sources (Temperature, Rainfall, Evaporation Rate, Humidity)
• Forecast Generation, Climate Forecast Interpretation, Translation and Communication
• Incorporating Climate Forecast in Decision Making
Farmer Field School(PalayCheck)
• Used high quality seeds of a recommended variety.
• No high and low soil spots after final leveling.
• Practiced synchronous planting after a fallow period.
• Sufficient nutrients from tillering to early panicle initiation and flowering stages.
• Avoided excessive water or drought stress that could affect the growth and yield of the crop.
• No significant yield loss due to pests.• Cut and threshed the crop at the right
time.
CLI
MAT
E SM
ART
–FF
S
• Topics and information on Climate/Weather outlooks, forecast, farm advisory, parameters etc…are discussed every meeting in addition to key check systems;
• Proven GP options/adaptation strategies are introduced to participants for adoption/testing;
• Focused on increasing farm productivity, reducing losses from climate related risks and minimize food insecurity.
Project Sites
Target Provinces and Municipalities:Camarines Sur: Buhi, Calabanga, Nabua, Gainza, Bula, Baao, Cabusao, Canaman (Seed Production at DA RFO-5, BEST, Pili)Camarines Norte: BasudMasbate: San Fernando
BUHI
NABUA
CALABANGA
SAN FERNANDO
CANAMAN
BASUD
CABUSAO BAAO
BULA
GAINZA
6
HOW DOES IT WORK?COMMUNITY SELECTION
• High level of dependence on agriculture
• Highly vulnerable to hydro-meteorological hazards
• With existing FFS program with LGU
• With active FO and cooperators
INTERVENTIONS
• CS-FFS Module• Testing of Good
Practice Options for CCAo GSR Lines/ Stress
tolerant varietieso Farming systemso Production
Technologies
OUTPUTS
• Improved understanding on weather/climate info
• Identified GP options, best performing technologies, varieties, lines
• Mainstreamed DRR/CCA in agri.
GSR Lines
Ave. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
Rank
GSR1 2.6 -0.9 -25.7 4.1 -0.8 -16.3 3.1 -0.5 -13.9GSR2 3.8 0.2 5.6GSR5 2.4 -1.1 -31.4 5 0.1 2 3 4.3 0.7 19.4 3GSR5A 3.2 -0.3 -8.6 7 2.1 42.9 1 3.2 -0.4 -0.4GSR8 4.3 0.8 22.8 2 5.9 1 20.4 2 4.4 0.8 22.2 2GSR11 5.7 2.2 62.85 1 4.9 0 0 4.5 0.9 25 1GSR12 3.6 -1.3 -26.5 3.2 -0.4 -11.1GSR Lines ave. 3.6 5.1 3.8Ave. of Check 3.5 4.9 3.6 5.6
WS 2012-2013 (Calabanga) DS 2013 (Calabanga) WS 2013-2014 ( Ave. of 3 sites )
0.1 2.8 0.2 4.1 0.2
Saline Prone Areas
Ave. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
Rank
GSR1 3.4 -0.8 -19 0 0 4 0.7 21.2GSR5A 4.6 0.4 9.5 2.2 -6.7 -75.3 3 0 -3.3 -100GSR8 6 1.8 42.9 2 2.6 -6.3 -70.8 2 5.3 2 60.6 3GSR11 3.5 -5.4 -60.7 1 6 2.7 81.8 1GSR12 1.2 -7.7 -86.5 5.5 2.2 66.7 2HHZ8-SAL14-SAL1-SUB1 5.1 0.9 21.4 3IR 82858-B-B-1 (W142) 3 -1.2 -28.6GSR 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 4Ave. of Check 4.2 8.9 3.3
GSR Lines
WS 2012-2013 (Nabua) DS 2013 (Nabua) WS 2013-2014 ( Ave. of 2 sites )
Submergence Prone Areas
Ave. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
RankAve. Yield
(mt/ha)
Difference over Chk var.
% adv. Over check
Rank
GSR1 6.9 3.9 130 2GSR2 5.7 1.5 35.7 6.9 3.9 130 2 4.3 1.3 43.3GSR5 3.6 3.6 85.7 3 3.6 0.6 20 5.1 2.1 70GSR5A 3.6 3.6 85.7 3 5.4 2.4 80 4.8 1.8 60GSR8 3.9 3.9 92.9 2 1.9 -1.1 -36.7 5.6 2.6 86.7 3GSR11 4.1 -0.1 -2.4 1 6.8 3.8 126.7 3 7.1 4.1 136.7 1GSR12 5.5 5.5 183.3 1 3.9 0.9 30GSR Lines ave. 4.2 5 5.4Ave. of Check 4.2 3 3 2.4 79.5
GSR Lines
WS 2012-2013 (Buhi) DS 2013 (Buhi) WS 2013-2014 ( Ave. of 5 sites )
0 0 2 67.2
Drought Prone Areas
12
Variety/GPOs Yield, mt/ha Variety/GPOs Yield,
mt/ha Variety/GPOs Yield, mt/ha
Rice Duck NSIC Rc222 6 PSB Rc18s1 4.8 PSB Rc182 3.8Nutrient Manager (IRRI) NSIC Rc222 6.5 PSBRc182 3.2Farmer's Practice NSIC Rc222 5.5 NSIC Rc222 5.3 PSB Rc82 5.6
Rice Duck GSR 11 3.5 NSIC Rc 222 8.9 GSR11,2,5 4.4Farmer's Practice NSIC Rc222 5.5 PSB Rc10 4.5 NSIC Rc152) 3.4
Variety/GPOs Yield, mt/ha Variety/GPOs Yield,
mt/haRice Duck PSB Rc68 6.9 PSB Rc18s1 4.7Farmer's Practice Malagkit 4.3 PSB Rc18 2.0
WS 2012
San Ant.-Pob., NabuaWS 2013DS 2013
DS 2013San Isidro Inapatan, San Antonio- Salvacion Baybay,
Igbac, Buhi
San Antonio-Poblacion, Nabua
Salvacion Baybay, CalabangaGPO's conducted
San Isidro-Inapatan, Nabua
Comparative Yield (MT/Ha) of GPOs
13
Rice Lines DS 2012 DS 2013 Maturity days Remarks
GSR1 1.4 3.3 106Rounded grain similar to Bigante
GSR2 3.4 108prone to lodging, small plant base
GSR5 2.1 2.7 108preferred for aroma/good eating quality
GSR5A 2.2 2.7 108GSR8 1.4 3.6 106 ideal for irigated, robustGSR11 2.4GSR12 2.5 106 RTVPSB 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)
Total Area Planted: DS 2012 - 0.04 ha (80 m2/line)DS 2013 - 1.4 ha (2,000m2/line)
Yield (MT/Ha) in Seed Production, DA-BEST
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/EWParticulars 2014 Data Source/Remarks JAN FEB MAR
CAM. SUR Normal (mm) 260.1 175.9 149.29
Computed based on the climate outlook issued by PAGASA last January
Actual Rainfall in Nabua, CS (mm) 20.6 8.4 3.2
AWS installed under AMICAF Project (As of March 13, 2014)
Actual Rainfall in Pili, CS (mm) 33.5 9.1 0.4
Agro-Met Station in CBSUA, Pili, CS (PAGASA), as of March 13, 2014