Hitayezu p 20150708_1730_upmc_jussieu_-_room_101_(building_14-24)
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Transcript of Hitayezu p 20150708_1730_upmc_jussieu_-_room_101_(building_14-24)
Analysis of Factors Shaping Small-scale Famers’ Perceptions About
Climate Change in South Africa: A Behavioral Approach
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Patrick Hitayezu, Edilegnaw Wale, Gerard Ortmann
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Introduction
Climate change (CC) poses a real threat to South African farmers’ livelihoods.
Yet, small-scale farmers hardly recognize the climate trends.
Assessment of factors shaping farmers’ perceptions is scarce.
This study appraises the current perceptions and analyses their socio-psychological, cultural and institutional determinants.
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Conceptual framework
Behavioural model of climate risk perception and response
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Study area
uMshwathi local municipality, KwaZulu-Natal Midlands, a hotspot of CC in South Africa.
152 randomly selected farmers were interviewed.
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Data
Dependent variables
Variable name
Variable description Mean SD
PERCEPTION 1 = local climate is changing; 0 = otherwise 0.684 0.466
CCP1 PCA index from PC1 of CC perception (contributed 45% to total variation in data)
-0.433 1.355
CCP2 PCA index from PC2 of CC perception (explained 24.7% of the variation in data)
-0.060 0.958
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Data
Independent variables
Variable name Variable description Mean SD
AFFECT -2= CC is very bad/unpleasant/detrimental, … 2= very good/pleasant/advantageous
-0.101 0.051
KNOWLEDGE Number of correct responses about years with particularly abnormal rainfall
1.480 0.456
EGALITARIANISM Index of belief in human equality with respect to social, political and economic rights (α=0.81)
13.29 2.59
INDIVIDUALISM Index of belief in moral worth of an individual (α=0.73)
9.34 3.02
AGE Age of the household head in years (continuous) 58.940 12.83
GENDER 1 = Female-headed household; 0 = otherwise 0.532 0.400
EDUCATION Years spent by the household head in the formal education
6.552 3.951
: Aspects of vulnerability to climate change (sensitivity and adaptive capacity)
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Data
Independent variables
Variable name Variable description Mean SD
EXTENSION Number of contact with extension workers in 2012 (count)
3.539 4.557
TRUST 1= don’t trust anyone, …, 4 = everyone is trustworthy 2.743 0.767
ADULTS Number of adult-equivalent members of the household
5.105 2.591
LAND Total operated area in hectares 1.596 1.515
RIVER Walking distance (in minutes) to the nearest river/dam
43.723 32.725
ROAD Minutes taken on arrive at the nearest tarmac road 12.559 17.774
AGRO-ECOLOGY 1 = Windy Hill Mistbelt (Mthuli); 0 = Wartburg/Fawnleas (Gcumisa)
0.322 0.468
: Aspects of vulnerability to climate change (sensitivity and adaptive capacity)
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Actual climate trends
Annual rainfall (mm) and temperature (oC) records at Wartburg - Bruyns Hill Station (1972-2013)
A decreasing trend in rainfall is juxtaposed with a slightly increasing annual minimum temperature.
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Actual climate trends Monthly rainfall (mm) records (1972-2013)
Decreasing summer rainfall and increasing winter rains
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Actual climate trends Monthly min and max temperatures (oC) records (1972-2013)
Increasing minimum temperatures (particularly in winter)
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Perceived climate trends
Unlike CCP1, CCP2 shows similarities with the actual trends.
Perception dimensions CCP1 CCP2 CCP3
Winter season is getting:
Abnormally colder 0.390 0.045 -0.297
Abnormally warmer 0.205 0.405 0.332
Abnormally dryer 0.315 0.169 0.107
Abnormally wetter 0.288 0.548 0.086
Summer (farming) season is getting:
Abnormally cooler 0.193 0.095 -0.104
Abnormally hotter 0.489 0.182 0.399
Abnormally dryer 0.852 0.390 -0.087
Abnormally wetter 0.019 -0.067 0.178
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Results
Probit model results: Probability of perceiving abnormal climate
(showing variables with significant coefficients)
Variables Coefficient S.E. Marginal Effect P>|z|
AFFECT 1.025 (0.359) 0.201 0.005
EGALITARIANISM 0.445 (0.224) 0.095 0.046
AGE 0.238 (0.091) 0.051 0.013
GENDER 0.258 (0.111) 0.187 0.027
EDUCATION -0.056 (0.032) -0.022 0.082
AGRO-ECOLOGY 0.204 (0.075) 0.170 0.008
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Results
Truncated model results: Strength of perceiving abnormal climate
(Showing variables with significant coefficients)
Variables CCP1 CCP2
Coefficient S.E. P>|z| Coefficient S.E. P>|z|
AFFECT 0.902 0.345 0.010 0.017 0.014 0.452
KNOWLEDGE 0.005 0.004 0.253 0.635 0.188 0.001
AGE 0.079 0.029 0.008 -0.183 0.152 0.494
EDUCATION 0.103 0.085 0.408 0.578 0.171 0.001
EXTENSION 0.132 0.083 0.174 0.133 0.066 0.048
TRUST 0.434 0.328 0.483 0.458 0.254 0.073
RIVER 0.053 0.018 0.005 0.012 0.008 0.198
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Major findings
Congruent to the findings of other studies:
1. Affect is the most important predictor of the probability of perceiving climate risk among South African farmers.
2. The low probability of perceiving climate risk is not a result of knowledge deficit.
3. Perceptions about CC are deeply entrenched in farmers’ egalitarian values.
4. Women are more likely to perceive CC risk than men.
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Major findings
5. Affect heuristics are the most important processes of ‘biased’ learning about CC among farmers (CCP1).
6. Knowledge (cognitive ability) is the most important predictor of the accuracy with which farmers perceiving climate risk.
7. Farmers’ investment in education and training increases their ability to receive and process climate information.
8. Farmers’ distrust in their community decreases their ability to perceive climate risk accurately.
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Recommendations
CC information should relate to local farming realities.
Information on extreme weathers can be more persuasive.
CC communication should frame CC as a risk about which to worry.
CC communication should be well aligned to local beliefs, values and norms.
Awareness campaigns should involve affected farmers.
CC information should be communicated by locally trusted sources.
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