Farmers’ perception and adaptation to climate change..

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Farmers’ perception and adaptation to climate change: A case study in vulnerable areas in Polonnaruwa District Chamila Chandrasiri

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Hosted by: Farmers’ perception and adaptation to climate change: A case study in vulnerable areas in Polonnaruwa District Chamila Chandrasiri

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Chamila Chandrasiri Agriculture Economist Department of Agriculture Sri Lanka Farmers’ perception and adaptation to climate change: A c ase study in vulnerable areas in Polonnaruwa District

Introduction:

Introduction Statistically significant variation in either mean state of climate or its variability, persisting for an extended period typically decades or longer ( Basnayake , 2011) Climate Change ?

Climate in Sri Lanka:

Climate in Sri Lanka Temperature The mean annual temperature in Sri Lanka In lowlands (up to altitude of 100 m to 150 m) - 27.5 0 C In highlands, the temperature falls with the altitude increases. ( Nuwaraeliya , at 1800 m sea level, is 15.9 0 C) The coldest month is generally January The warmest months are April and August

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The mean annual rainfall varies 900mm in the driest parts (southeastern and northwestern) 5000mm in the wettest parts (western slopes of the central highlands) The rainfall

The impact of climate change on weather :

The impact of climate change on weather Air temperature Air temperature - has increased the past 72 years - 0.97 0 C the past 40 years - 0.64 0 C more recent 22 years - 0.45 0 C Consecutive dry days - increasing in the Dry and IZs Ambient temperature (both mini and max) - increased Numbers of warm days and warm nights - increased Numbers of cold days and cold nights - decreased (ME, 2010) A trend of 0.14 0 C per decade A rate of 0.2 0 C per decade

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Rainfall variability Rainfall amount – decreasing trend (over the past 30- 40 years), but not significant One day heavy rainfall events – Increasing trend Frequency of extreme rainfall events – increase in trend (lead to more floods) Frequency of dry periods and droughts – increase in trend (ME, 2010)

Agriculture sector:

Agriculture sector Main source of livelihoods for most rural communities Provides employment for 31 % of the population Contributes 10.8 % of GDP in the year 2013 (CBSL, 2012) GDP Contribution Employment share

The impact of climate change on agriculture:

Climatic related disasters (drought, cyclones, floods, high winds and extreme temperature) farmers more vulnerable adversely affects agriculture & food security Ex. Being a tropical island, most of the cultivated crops in Sri Lanka operate at a near maximum of the optimum temperature range   Rice – if plant exposed to an ambient temperature that exceeds 35 0 C for 60-90 minutes at flowering stage will injure the plant & results high rate of un-filled grains   The impact of climate change on agriculture is a burning issue of agricultural poor livelihoods The impact of climate change on agriculture

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Agricultural productivity Crop management Irrigation Fertilization Climate Plant protection

Adaptation to climate change ? :

Adaptation to climate change ? Adaptation is the ending result of how farmers’ perception of climate change is translated into agricultural decision making process Adaptation Changing climate Change agriculture management practices Individual responses at farm level Assuming farmers have access to alternative practices and technologies available in the region Adaptation has the potential to reduce negative impacts from climate change

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Smallholder farmers are most vulnerable to climate change as they have low adaptive capacity Minimizing climate change impact on food security – is key strategic thrusts in National Climate Change Adaptation Strategy for Sri Lanka 2011-2016 (ME, 2010) A key challenge for decision makers - to understand the strategies adopted by farmers and their efforts to address climate change-induced water stress

Objectives:

Objectives To recognize the severity of climate change on farm income Farmer perception / awareness on climate change Adaptation options practicing by farmers Determinants of adaptation to climate change Barriers to adaptation

Methodology:

Methodology Primary questionnaire survey Polonnaruwa district (The crop regularly affect to flood condition) The most vulnerable three DS divisions Thamankaduwa - 44 Madirigiriya - 36 Dimbulagala - 35 (Vulnerability maps of Sector Vulnerability Profile Agriculture and Fisheries 2010 (ME,2010) During April - May 2013 Total sample size - 115

Data analysis:

Data analysis The impact of climate change on farm income by mean income loss Farmer perception / awareness on climate change Awareness Score Eight statements on climate change Correct answer was given one mark Score varies from 0 – 8 per individual The level of awareness sample – mean of individual AS The adaptation methods descriptively

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The determinants of adaptation Multivariate Logit model Y = 1 adapt to climate change, Y = 0 not adapt to climate change The independent variables A – age in years Edu – education level HH – House hold size LI – Low land ext.(acres) Irri – Irrigation water availability Sirri – Satisfaction with irrigation water availability WI – Agriculture assets index EAI- Extension availability index ( vary 0-20) Cred – Use of credit facilities Agri I – Seasonal Income from agriculture TI– Total annual income AI– Awareness index on climate change (vary 0-8) PILD – Percentage income loss due to drought PILF – Percentage income loss due to floods 5 . Barriers to adaption and feasible interventions – descriptively

Results and Discussion:

Results and Discussion Affect to climate change – 99% of farmers (last five years) Specially flood 0% 1% 63 % 36% Flood affected Drought affected Latest season affect drought – Yala 2012 Latest season affect flood - Maha 2012/13 99% 64%   Only affect to drought Only affect to flood Affect to both drought & flood Not affect to climate change Thamankaduwa 2 98 66 0 Madirigiriya 0 100 56 0 Dimbulagala 0 100 66 0 Aggregate 1 99 63 0

1. The impact of climate change on farm income :

1. The impact of climate change on farm income Farmers earn 3,00,000 rupees income for normal season It is 80% of total income 76% of Agri. income loss due to flood in each 4 seasons interval 39% of Agri. Income loss due to drought in each 8 seasons interval Latest season affect drought – Yala 2012 Latest season affect floods – Maha 2012/13

Income status and income loss:

Income status and income loss   Total annual Income (Rs) Income from agriculture for normal season (Rs) Agriculture income as a % of total income Affect from drought Affect from flood Income loss of season (2012 Yala ) Income loss as a % of agriculture income Income loss of season (2012/13 Maha) Income loss as a % of agriculture income Thamankaduwa 694,677 327,447 94 136,488 42 236,218 72 Madirigiriya 684,005 280,169 83 104,831 37 207,173 74 Dimbulagala 622,119 280,545 91 104,613 37 233,695 83 Aggregate 669,254 298,373 80 116,877 39 226,358 76

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2. Farmer perception on climate change Awareness score - mean - 4.02 (fairly aware) Temperature aspects are more aware than rainfall     Increased Decreased No change Don’t know Temperature Normal daily temperature 79 3 10 8   Long dry period 60 8 15 17   Day temperature 77 4 15 3   Night temperature 68 16 12 4 Precipitation Rainfall 39 25 23 12   Changes in monsoon rainfall 27 7 28 38   Unexpected rainfall 31 3 23 43   Unusual rainfall 35 2 23 41

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3. Adaptation to climate change   Already adapt to climate change Willingness to adapt to climate change Adapt Not adapt Willing to adapt Not willing to adapt Thamankaduwa 18 82 61 39 Madirigiriya 19 81 72 28 Dimbulagala 0 100 60 40 Aggregate 13 87 64 36 15% of the farmers are in mind that crop cultivation is impossible to manage according to the changes of climate

Already practicing and proposed adaptation methods:

Already practicing and proposed adaptation methods

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4. The determinants of adaptation Variables Coefficient SE P value Odds ratio Age of the farmer - 0.349** 0.138 0.012 0.71 Education level 2.778** 1.294 0.032 16.08 Household size 0.538* 0.290 0.064 1.71 Farming experience in years 0.278** 0.125 0.026 1.32 Low land extent 0.152 0.202 0.452 1.16 Irrigation water availability - 4.15* 2.240 0.064 0.02 Satisfaction with irrigation water availability 2.382* 1.328 0.073 10.83 Wealth index 0.0201 0.015 0.192 1.02 Extension availability index 0.763*** 0.262 0.004 2.15 Use of credit facilities - 4.371** 1.877 0.020 0.01 Seasonal income from agriculture 0.000037* 0.000 0.086 1.00 Total annual income - 0.0000211* 0.000 0.055 1.00 Awareness Index on climate change 0.938** 0.396 0.018 2.56 Percentage income loss due to drought - 0.056* 0.032 0.083 0.95 Percentage income loss due to floods 0.052 0.045 0.251 1.05 Constant - 11.52** 5.760 0.046 No of observations 115 Log likelihood -20.206   0.000   Note : * The coefficients are significant at p = 0.1 level, ** The coefficients are significant at p = 0.05 level, ***The coefficients are significant at p = 0.01 level. Results of the Logistic Regression model

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The characters of the adaptors Young age Educated More years of experience Familiar with climate change Low use of credit facilities Higher connection with extension officers Satisfied with irrigation water availability (not just the irrigation water available) Higher agriculture income ( not the higher overall income)

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5. Barriers to adaptation

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Farmer demands to adapt to climate change

Conclusions:

Conclusions Climate change is a crucial determinant of agricultural income The awareness as well as knowledge on adaptation of their cultivation to climate change is poor Therefore Well focused extension programmes to empower farmers on knowledge on changing climate coupled with suitable inputs Successful programmes to attract educated young farmers to climate smart agriculture

Suggestions to Future Research:

Suggestions to Future Research Identify location specific farmer constrains created by changing climate and solutions coupled with available technology Farmer adaptive capacity Deeper analysis identify the minor successive factors of the existing well adaptors

Thank you:

Thank you

Independent variables:

Independent variables Category Symbol Definition of variable Age of the farmer A Age in years Education level Edu Education rated as 0= no edu, 1= grade1-5, 2 = grade 6-OL, 3=AL, 4 = Graduate Household size HH Household size in numbers Farming experience Exp Experience in agriculture in years Low land extent Ll Paddy land size in acres (Low land) Irrigation water availability Irri Irri =1 if irrigation water is available, = 0 if not Satisfaction with irrigation water availability SIrri SIrri =1 if farmer is satisfied with the available irrigation water, = 0 if not Agriculture assets index WI Agricultural assets index developed by giving proportionate marks ( based on its financial value) of owning selected agriculture machineries and equipments Extension availability index EAI A score developed considering the service of field extension officers Agriculture Instructors and Agriculture Research & Production Assistants considering three characters. 1. The way of meet (no meet = 0, farmer go to officer =1, officer comes to farmer =2, both sides =3), 2. Frequency of meet (no meet=0, once per season=1, twice per season=2, once per month =3, twice per month =4) and 3. Satisfaction with level of service (not =0, fair=1, good=2, best=3) of both. Total score vary from 0 -20. Use of credit facilities Cred Cred=1 if farmer use to obtaining credit, = 0 if not Seasonal income from agriculture Agri I Total income earned from agriculture in non climate disaster affected season in rupees Total annual income TI Total annual income in rupees in non climate disaster affected year Awareness Index on climate change AI Individual score developed as above explained (vary 1 – 8) Percentage income loss due to drought PILD Income loss of agriculture in resent drought affected season (Yala 2012) as a percentage of agriculture income in a normal season Percentage income loss due to floods PILF Income loss of agriculture in resent flood affected season ( Maha 2012/13) as a percentage of agriculture income in a normal season

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