FALAKI, Akindeji Ayobanji University of Ilorin, Ilorin, Nigeria - - PowerPoint PPT Presentation
FALAKI, Akindeji Ayobanji University of Ilorin, Ilorin, Nigeria National Orientation Agency , Abuja, Nigeria UNU-WIDER Conference on Climate Change and Development Policy, Helsinki, Finland. 28-29 September, 2012 Local Perceptions of Climate
FALAKI, Akindeji Ayobanji
University of Ilorin, Ilorin, Nigeria National Orientation Agency , Abuja, Nigeria
UNU-WIDER Conference on Climate Change and Development Policy, Helsinki,
The warming of the climate system is un
unequi quivocal…, glo loball lly and the impact is felt the most lo locall lly
to the impacts of climate change.
Human settlements and health Water resources, wetlands and freshwater
ecosystems
Energy, industry, commerce and financial services Coastal zone and marine ecosystems Agriculture, food security, land degradation,
forestry and biodiversity
The negative impacts of climate
Increased risk of hunger and
Decline in rain-fed agricultural yield Crop failure and food shortage Increase in the price of basic food
Shift in crops cultivated
Adaptation and Development
The goals of Adaptation and
Climate change threatens and
Adaptation can help reduce these
Ability to adapt depends on the state
MDGs measures progress towards sustainable
development
Climate change slows the progress towards
sustainable development
Directly through increased exposure to adverse
impacts
Indirectly through erosion of the capacity to
adapt
Most sustainable development plans do not explicitly
include climate change awareness, impact evaluation, adaptation and mitigation practices (only in September 2012 was a climate change policy enacted
Impact of climate change on
Severe inequalities in wealth (e.g.
Regional-based impact (different
Uneven level of preparedness
The Strengthening the Livelihoods of Small Scale
Farmers in Nigeria (SLISSFAN) project co-financed by OXFAM GB and the European Commission.
OXFAM GB is a development, relief and campaigning
solutions to poverty and suffering around the world.
The SLISSFAN project has the specific objective of
improving the livelihoods of 6,000 poor rural households in small communities in the Middle Belt of
Two interventions emphasised: (i) the formation and strengthening of self-managed, business-
(ii) Village Savings and Loans groups (VSL) SLISSFAN project has no climate change component Reports from farmers engaged in the project and partner organisations
working with OXFAM in these communities indicate that climate change is impacting negatively on the farming operations and livelihood of the small scale farmers they are working with thereby creating challenges not planned.
This threatening scenario (could) apply to other agricultural development
sustainable development programmes?
The specific objectives are to;
Define the context in which the farmers carry out
their livelihoods activities
Examine 30 years temperature and rainfall trends Ascertain farmers’ perception of (causes) climate
change
Investigate farmers’ adaptation practices in
response to climate change
Identify constraints impeding adaptation to climate
change
Map of the Study Area: Middle-Belt Nigeria
State Local Government Communities
Communities
Households Plateau Bokkos Kawel, Mbar, Makada, Wumat, Maihakoringol, Folloh, Fagin, Foffai, Bokkos and Kunet 20 2400 Mangu Kerang, Ampang West, Panyam, Bwonpe, Kopal, Gohotkung, Konbring, Kinat, Tyop and Chanso Benue Guma Agasha 5 1600 Vandeikya Mbaduku, Mbayongo Buruku Tyowanye Gboko Utabar Nasarawa Obi Ikposogye, Musha, Tudu Adabu 9 2000 Lafia Kirayi, Assakio, Rafin kudi Nasarawa Eggon Ahenta, Ogbagi, Gbamze West 3 9 34 6000
A multistage sampling technique
For the first stage, purposive sampling was
For the second stage, purposive sampling was
At the third stage, simple random sampling
Sample size was 411 (Plateau = 162,
Data Analysis Tools
Statistical (quantitative) analysis involve: Basic descriptive statistics (frequency counts,
percentages, means…)
Kruskal-Wallis One Way ANOVA Comparisms
(Ranking)
Principal Component Analysis Regression analysis used to determine trends in
temperature and rainfall
Summary of Findings: Contextual Situation
More Females: 51.3% Average Age: 52 years Low Literacy: 39.7% with no formal
Large HH Size: Average 11 No of Related Family in the Village
Contextual Situation
Average Residence Age: 31 years Residence type: 83.4% live in mud
Commonest HH Appliances: Radio
Public erratic electricity supply: 8.3% Petrol powered Private electricity
generator: 23.1%
Bank savings: 15.1%
Main energy source: Fuel wood
Main water sources: dug well (56.2%)
Water treatment: None (29.4%),
Toilet Facility: Nearby bush or
High Disease Burden:
Feverish Illness – 83.4% Cough – 44.5% Diarrhoea – 24.8% HIV/AIDS – 4.5% (in Benue)
Ave farming experience: 33 years Mixed farming (goats, poultry,
Main farm implement is cutlass and
Guaranteed at least 2 meals a day:
Dry season farming (Benue: 15.5%,
Contextual Situation
Contextual Situation
Access to Extension Agents (2011): 59.4%;
Benue – 85.5%, Nasarawa – 44.9%, Plateau – 54%
Ave no of visits by Extension Agent (2011): Benue
– 5, Nasarawa – 3, Plateau - 3
Access to Information on Expected Rainfall
/ Temperature(2011): 48.8%; Benue – 71.3%, Nasarawa – 37.1%, Plateau – 33%
NGOs are the main extension service
providers (57.4%)
Co-farmers, radio and farmers’ association
are leading sources of agric information
Access to agric. credit low (46.9%) Leading Sources of agric. credit: Adashi,
Relatives, NGOs, Neighbours, Farm Association
Main Use of credit: buy farm inputs,
children’s education, start non-farm business
Reasons for not obtaining credit: None,
inadequate information, high interest, no collateral, past credit
Benue Nassarawa Plateau
72% 22% 4% 2%
Pooled Decreased Stayed Same Increased Don’t Know
57% 38% 2% 3% 82% 12% 2% 4% 73% 20% 6% 1%
Distribution Of Respondents According to Perception of
Air Temperature
Benue Nassarawa Plateau
51% 41% 4% 4%
Pooled Decreased Stayed Same Increased Don’t Know
75% 16% 4% 5% 43% 45% 7% 5% 41% 55% 3% 1%
Distribution Of Respondents According to Perception Of
Rainfall Amount
Distribution Of Respondents According to Perception Of Rainfall Pattern
Rainfall Pattern Unpredictable Benue Nassarawa Plateau Pooled % % % % No Yes Total 14.5 85.5 100.0 16.6 83.4 100.0 17.2 82.8 100.0 16.3 83.7 100.0
Trend of Minimum Temperature for Makurdi: 1980 - 2009
Analysis of Minimum Temperature Data for Makurdi: 1980 – 2009
Temperature Values Mean (0C) 22.5 Standard deviation (0C) 0.22
y0=22.5 + 0.003x
Trend (0C/year) 0.003 Total Change from Trend (0C/30years)* 0.10
57% 38% 2% 3%
Trend of Maximum Temperature for Makurdi: 1980 - 2009
Analysis of Maximum Temperature Data for Makurdi: 1980 – 2009 Temperature
Values
Mean (0C)
33.4
Standard deviation (0C)
0.33
y0= 33.4 + 0.016x Trend (0C/year)
0.016 Total Change from Trend (0C/30years)* 0.49
Trend of Minimum Temperature for Jos: 1980 - 2009
Temperature Values Mean (0C) 15.7 Standard deviation (0C) 0.35 y0= 15.7 + 0.02x Trend (0C/year) 0.02 Total Change from Trend (0C/30years)* 0.58
Trend of Maximum Temperature for Jos: 1980 – 2009
Temperature Values Mean (0C) 27.8 Standard deviation (0C) 0.44 y0 = 27.8 + 0.02x Trend (0C/year) 0.02 Total Change from Trend (0C/30years)* 0.55
Trend of Rainfall Amount for Makurdi: 1980 – 2009
Rainfall Values Mean (mm) 98.1 Standard deviation 19.2 Minimum rainfall (mm) 64.2 Maximum rainfall (mm) 147.7 y0 = 98.1 + 1.54x Trend (mm/year) 1.54 Total change from trend (mm/30yrs)* 46.4
Wet Season Average Rainfall Amount (Five yearly Period) for Makurdi: 1980 – 2009
Rainfall Amt. May Jun. Jul. Aug. Sept. Mean 127.94 211.4 180.49 230.13 210.1 Minimum 111.2 137.84 147.26 205.26 166.02 Maximum 174.92 297.14 264.4 270.04 285.76 Trend (mm/year) 5.62 7.79
1.39
Total Change from Trend (mm/30years)* 33.69 46.75
8.33
Trend of Total Annual Rain Days for Makurdi: 1980 – 2009
Rain Days Value
Mean 73 Minimum 44 Maximum 91 y0 = 73 + 0.27x Trend (days/Year) 0.27 Total Change from Trend (days/30Years)* 8 1
Wet Season Rain Days (Five Yearly Average Period) for Makurdi: 1980 – 2009
Rainfall Amt. May Jun. Jul. Aug. Sept. Mean 42 50 60 71 67 Minimum 37 37 48 63 60 Maximum 51 54 72 77 72 Trend (days/year)
1.05
0.37 0.95 Total Change from Trend (days/30years)*
6.3
2.2 5.71
Trend of Rainfall Amount for Jos: 1980 – 2009
Rainfall Values Mean (mm) 102.9 Standard deviation 56.9 Minimum rainfall (mm) 67.9 Maximum rainfall (mm) 131.9 y0 = 102.9 – 0.29x Trend (mm/year)
Total change from trend (mm/30yrs)*
Wet Season Average Rainfall Amount (Five Yearly Period) for Jos: 1980 – 2009
Rainfall Amt. May Jun. Jul. Aug. Sept. Mean 174.4 206.7 205.7 261.0 167.1 Minimum 145.3 183.2 208.0 248.1 145.4 Maximum 197.9 227.0 272.4 297.9 179.8 Trend (mm/year)
2.26
3.04 2.39 Total Change from Trend (mm/30years)*
13.58
18.24 14.35
Trend of Total Annual Rain Days for Jos: 1980 – 2009
Rain Days Value
Mean
102
Minimum
78
Maximum
119
y0 = 91.01 + 7.53x Trend (days/Year)
0.71
Wet Season Rain Days (Five Yearly Average Period) for Jos: 1980 – 2009
Rainfall Days May Jun. Jul. Aug. Sept. Mean 68 82 100 103 79 Minimum 53 71 93 97 71 Maximum 79 96 111 119 90 Trend (days/year)
2.19 2.83 9.55 0.76 Total Change from Trend (days/30years)*
13.14 17 57.28 4.57
Respondents’ Perception of Causes of Climate Change based on kruskal-Wallis One-way Anova Comparisms
Causes of Climate Change Mean Rank Rank Bush Burning Tree Cutting for Human Use Sin Evil Spirits Industrialization 1213.50 1113.50 1048.50 893.50 871.00 1 2 3 4 5 Chi-Square df
168.694 4 .000
Distribution of Respondents by Perception of Causes of Climate Change *Multiple Responses *Perceived Causes
Benue Nassarawa Plateau Pooled (%) (%) (%) (%) Industrialization Bush Burning Tree Cutting Sin Evil Spirits 20.9 58.2 52.7 13.6 8.2 12.3 43.5 50.7 45.7 24.6 4.3 36.8 9.8 24.5 8.0 11.4 44.8 35.0 28.7 13.6
Eigen Values, Variances, Rotated Component Score and Communalities Statistics of Respondents’ Adaptation Response to Climate Change
Eigen Values, Variances, Rotated Component Score and Communalities Statistics of Respondents’ Constraints to Climate Change Adaptation
The poor infrastructural, institutional and socio-
economic context in which the farmers live and carry
drawback to their adaptive capacity.
The climate is changing with disproportionate
impacts at the local level.
Farmers engage in a variety of farm and non-farm
practices to adapt to the changing climate
Constraints limiting the farmers’ adaptation are
poverty, lack of access to necessary resources and information, making them unable to deal with current and indeed future climate change and extreme weather incidences
Farmers are able to correctly perceive the changes in
the climate, but their perception of the causes of the changes is to a great extent erroneous.
Government policies and programmes to address climate change and
agriculture should include awareness creation.
Advocacy and campaign groups has much to do. There is need for government to focus on development that meets their
basic human needs as a major strategy for poverty reduction. Anything done to develop the farmer will equally help build up their adaptive capacity and resilience to the impact of climate change.
Tree planting in the community. They provide shade, fruit, wood, shield the
community against storms, act as carbon sinks/sequestration.
The significance of multi-disciplinary approach cannot be overstated. The
scientist may argue for example that fire wood stove should be stopped completely to protect the environment but the social scientists would be quick to state that cooking with firewood is deeply entrenched in local practices and would require a transition period to move people to new ways
relevant and acceptable to people.
Knowledge sharing and collaboration between the farmers, researchers and
development practitioners.