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

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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

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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

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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.

National CBA Conference 20128

Recorded rainfall

~48 mm

Example of Rainfall Monitoring

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

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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

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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

National CBA Conference 201216

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