PRESENTATION OF RESEARCH FINDINGS AT THE
2nd BIANNUAL CONFERENCE FOR SOUTHERN AFRICAN SOCIETY FOR DISASTER REDUCTION
HELD AT UNIVERSITY OF NAMIBIA, WINDHOEK
6 - 8 OCTOBER 2014
Enhancing community resilience through public agricultural development projects in Monze district of Zambia?
By Bowen Banda (MOM) & Andries J. Jordan (PhD)
Reason for livestock increase: Not due to projects.
Decrease due to livestock disease. That is low livestock project support
Access to other physical assets:
More in Nalutanda
Milk Sales:
Insignificant overall but relatively more in Nalutanda than Keemba
Milk sales insignificant but has potential:
low milk outputs due to livestock disease, poor pasture, low veldt mgt, stock thefts
Per capita income generated from crops and livestock sales: insignificant difference between two communities but very low in both (less than 2 US$ per day)
How households acquired livestock:
Own servings is major source & not project soft loans
Livestock numbers in two communities among respondents:
Significant difference between two communities
(p values 0.034 cattle; 0.10 sheep & goats)
Camp
Total number of household interviewed
Dairy cattle
Beef cattle and oxen
Goats & sheep
Pigs
Donkey
Chickens
Doves
Other
Keemba
38
2
365
116
5
0
554
5
6
Nalutanda
36
0
1203
180
19
55
507
80
13
Total
74
2
1568
296
24
55
1061
85
19
Cropping land
Projects not analysed
(those not known by the sampled communities in Monze)
Sn
Project Name
Implementation period
Financier
1
Targeted Food Security Pack Project (FSP)
2000- ongoing
Govt.
2
Agricultural Development Support Programme -Small Holder Commercialisation (ADSP-SC)
2006 – 2012
World Bank
3
Conservation Agriculture Scaling up for Increased Productivity and Production (CASPP)
2008 – 2012
FAO
4
Small Agribusiness Promotion Programme (SAPP)
2010 – 2016
IFAD, Govt.
5
Adapting to the Effects of Climate Variability and Change in Agro-ecological I & II
2012 – 2015
GEF, FAO, Govt., UNDP, Conservation farming Unit NGO, Zambia Meteorological Dept
Respondent age comparison:
Compares well between the two communities
Household size comparison:
Compares well between two communities
Major Sources of Livelihoods:
Land for crop farming:
Compares were among households in the two communities
Enhanced hazard awareness capacity:
Generally high but insignificant difference between two communities
Normal hazard perception:
High for drought, floods & corridor bovine disease, then HIV/AIDS
Most vulnerable groups:
Communities' perception
Summary of results:
end user perspective
low project effects at enhancing all the 10 community resilience indicators overall, apart from risk awareness capacity through radio campaigns
On the overall both community members did not attribute the little increases in physical assets due to current or past projects' being implemented
but attributed the little increase to own survival mechanisms & knowledge
little increase on already low outputs does not translate / is not community resilience but economic strengthening
Comparatively, Nalutanda with less projects exhibited more resilience with 3 major indicators of
i. Social cohesion/asset
Willingness to assist their community members during times of adversity
ii. Physical assets
Relatively significant higher livestock numbers
Relatively better assess to irrigation facilities during adversity
Relatively better market gardening
More access to livestock dipping (spaying) services during adversity
iii. Natural assets
More & enough access to communal grazing land during adversity (Kafue flats)
Conclusion
Keemba community with more projects was expected to have more resilience but did not. Therefore agric projects were considered to have less effects at increasing community resilience. Risk (hazard & vulnerability) magnitude was constant in analysis.
The study suggests that projects were not properly designed to focus on community resilience as well given the above outcome, lack of disaster risk analysis at pre-design stage, coupled with centrally designed projects (top down) in Lusaka (200km away)
Negative hazards impacts were not the only cause for this low resilience but low human social security management as well
Generally poverty levels were still very high among households with less livestock in the two communities assessed. Poor people tend to be more vulnerable and less resilient.
Way forward
Professional public social-economic project designers should appreciate increased conceptual knowledge in drr more, and incorporate disaster risk analysis at pre-project design in disaster prone areas like Monze
Project designers and implementers should also involve the community more, in planning and implementation process in 'real sense' and not 'superficially'.
Acknowledgements
DiMTEC, University of the Free State, Bloemfontein, South Africa
Ministry of Agriculture and Livestock, Departments of Agriculture & Extension, Monze, Zambia
Contact Address
Bowen Banda, (Alumni DiMTEC, UFS, Bloemfontein) Monze, Zambia email:
[email protected],
Dr. Andries J. Jordaan, Director, DiMTEC, UFS, Bloemfontein, South Africa email:
[email protected]
Summary of results:
professional planner perspective
5 out 7 projects were planned centrally in Lusaka, capital of Zambia with less 'real' input / participation from the target community
No comprehensive disaster risk analysis was done in 6 out 7 projects
Risk analysis undertaken by designers was in context of project administration constraints in the log frame. (This is not the same as multi-hazard nor single hazard disaster risk analysis)
Projects known & benefited from
Community cohesion:
Nalutanda community more cohesed
Early warning communication proactiveness:
High on indigenous knowledge & radio programmes, insignificant difference in two communities
Spontaneous reasons for increased risk awareness:
High personal experience & radio programmes. Insignificant difference between two communities
Community awareness of community disaster mgt & risk reduction committees organised by projects
Coping strategies in adversity:
Nalutanda has more sustainable ways to cope than Keemba
Public agricultural developmental projects analysed:
(those known by the sampled communities in Monze)
Sn
Project Name
Implementation period
Financier
1
Farmer Input Support Project (FISP)
2003- todate
Govt.
2
Small Livestock Investment Project (SLIP)
2006 – 2013
IFAD
3
Farmer Input Support Response Initiative Project (FISRI) to rising cost of agricultural commodities in Zambia
2009 – 2012
EU through FAO
4
Small Holder Dairy Farming Improvement Project (Monze Dairy Farmers Co-operative Organisation Project)
2000- ongoing
Member contribution, revolving funds, Govt, DFID, Land O' Lakes,
Coop AFRICA,
5
World Vision Zambia (WVZ): Chief Choongo Area Integrated Development Project
2007- 2022
WV Korea
6
Dunavant cotton
2001 - ongoing
Private investment for public
7
Alliance Ginnery
2007- ongoing
Private investment for public
Enhanced human assets: Demographics
Variable
Keemba
Nalutanda
Average for the for the two communities
Female-headed HH (%)
37
31
34
Male-Headed HH (%)
63
69
66
Education level of HH head (%)
No formal education
13
0
7
Primary education
63
50
57
Secondary
24
50
36
Marital Status of HH head (%)
Single
13
0
7
Married
53
72
62
Divorced
8
8
8
Separated
0
0
0
Widowed
26
17
22
Results presentation format
Number of projects analyzed
Results based on indicators of resilience
Enhanced human assets: demographics
Livelihood sources
Physical & natural assets
Financial assets
Risk awareness as part of community resilience capacity
Enhanced hazard awareness capacity
Perceived hazards of highest magnitude
Enhanced vulnerability awareness capacity
Enhanced early warning capacity
Attribution for increased risk awareness capacity
Community resilience definition (contd)
It is a process, and outcome of a resilient community
It is a metaphor to refer to resilient communities
It is more than food security
It is more than coping ability
It is part of the disaster management continuum
It is the inverse of social vulnerability
But resilient communities also have households that are not yet resilient and need help thus process and reason to study it
Summary of community resilience indicators used in the study
1. PRE-DISASTER MITIGATION CAPACITY / LIVELIHOOD ASSETS
inherent physical and psychological capacity to
anticipate (including early warning indicators)
prepare (human, physical, social, financial, natural assets)
2. POST-DISASTER RESPONSE & MITIGATION CAPACITY / LIVELIHOOD ASSETS
recover and bounce forward from disaster outcome (social networks, community cohesion, livelihood assets, proactiveness, ability to mobilise external support)
2. ACTUAL PREPAREDNESS & RESPONSE PLAN
actual good preparedness and response plans owned by community
3. SOCIAL RISK GOVERNANCE CAPACITY
proactive leadership
political enlightenment
community cohesion
10 consolidated indicators used for community resilience analysis
(Graphic presentation)
Study assumption?
Agric development projects are not contributing effectively to reducing poverty and social vulnerability to food insecurity (or to increasing community resilience) due to poor designing and implementation
Community resilience is the flip side of social vulnerability (R = (SocVul /Com Res) x (H/M). (Jordan 2006; Wisner, Gaillard & Kelman 2012:24)
Community resilience more positive way of looking at risk reduction.
Increased community resilience cannot be measured directly
Hence need to measure projects' effects in context of poverty reduction, developmental and drr enhancement in disaster prone district to link effects with projects' design and implementation in absence of baseline, holding hazards impacts and vulnerability constant
Research Questions
How were the agricultural development projects designed that were implemented in Monze?
Was there a link between designing and implementation of agricultural development projects with increased or reduced community resilience for people at risk?
iii. Did planners undertake comprehensive disaster risk assessment at pre-project design stage?
Community resilience definition
..are resilient communities that have inherent capacity to anticipate, prepare, respond, recover and bounce forward from disaster outcome when hazards affect their livelihoods (Birkmann 2006:468).
resilient communities should also have good preparedness and response plans (Poland, 2010:194).
resilient communities should also have leaders that take deliberate action to enhance the personal and collective capacity of their members and local institutions to respond to, and influence the course of social and economic change (Centre for Community Enterprise, 2000:9).
All this inherent capacity further involves indigenous and other acquired knowledge on early warning indicators to predict potential impending hazard.
Study Problem
Are agricultural development projects effectively contributing to reducing social vulnerability to food insecurity or enhanced community resilience in Monze?
If they are, why is there increased social vulnerability to food insecurity in Monze among farmers dependant on rainfed agriculture?
Is it due to multi hazard impact on livelihoods, or poor project design, implementation & management?
Potential reasons for not contributing to increasing community resilience:
Low productivity (yields, outputs & livestock off takes)
Poor value chains
Negative drought impact
Negative flood impacts
Negative HIV /AIDS impact
Poor markets
Low marketable surplus
But all these are economic resilience indicators
Community resilience include these indicators plus social governance / social risk management capacity
Map: Position of Monze in Zambia
Presentation Outline
Study Justification
Local problem in Zambia
Study Area
Study problem
Concept definition
Study Assumptions
Research Questions
Research Design & Methods
Results
Conclusion
Way forward
Study Justification
There is much debate globally & regionally on role of agric development projects to enhance social-economic development, in developing countries, at household to national level through increased
productivity, yields, outputs, marketable surplus, improved value chains, sustainable production methods and thus increased household incomes and wealth (Livelihood assets)
There is also debate, and an urge to use social economic developmental projects such as agriculture to enhance community resilience (HFA 2005)
Conceptual knowledge on DRR mainstreaming has increased
Local problem in Zambia & Monze District
There is still high social vulnerability to food insecurity among the poor and vulnerable in disaster prone areas, despite recorded bumper maize harvests in Zambia
Rainfed maize production is a major indicator of food security performance in Zambia
Agric based livelihoods are highly dependant on rainfed maize for rural sustenance
There is still high food insecurity despite so many agricultural developmental projects in Monze
Monze (rural) district is just an example of food insecure districts in Zambia agro-ecological II
Study Area
Conducted in Monze district, Southern Zambia
District is 6,687 square kilometres
In region II of the Zambia agro-ecological zones
Average annual rainfall is 801 mm. About 120 growing days
District population: 195,921 (49% are male and 51% are female)
About 32,653 households
Farmers: 19,034 households of which 99% or 18,932 are small scale
Study Area (Contd)
Predominantly rural district
Agricultural activity is major livelihood
Major hazards prevalence in last 35 years:
Major drought: 1992/93; 1995/96; 2003/04
Major floods: 1997/8; 2007/08 season
Major livestock diseases' outbreaks: corridor bovine disease. First experienced 1981-82. Second wave outbreak 1990 to 1997
HIV/AIDS prevalence: 14%
Research Questions (Contd)
iv. What was the role of the community in the designing and implementation of these agricultural development projects in Monze?
v. How did the community perceive these projects towards enhanced community resilience?
vi. How did the community define community resilience? Was it compatible with how the technocrats define resilience?
Results presentation format (Contd)
Political assets as part of community cohesion
Community disaster preparedness plan & co-ordinating committees
Coping response mechanisms
Social assets as part of community cohesion
Community willingness to assist other vulnerable members
Other findings from user perspective
Irrigation facilitation
Communal cereal and seed banks
WVZ community disaster preparedness planning facilitation
Overall community perception of projects' impact
Findings from planner's perspective
Community resilience analytical model : Diagrammatic
Sub-district level Sampling: Detail
Systematically sampled two (2) agric camps from thirty four (34) in the district
(Agricultural camp is the smallest agric admin unit used for public agric developmental management & public targeting of projects in Zambia (Local government uses different admin units (wards), Central Statistical Office also use different unit. Disaster management department uses both local government or agric units depending on programme / intervention)
Sampled two camps with same magnitude of risk
But with different number of developmental projects.
Camp with 7 projects was intervention
Camp with 3 projects was the control
Conceptual design framework
Used disaster risk definition (DistrRisk = (V /CR) x (H/M).
Study focused on community resilience in the disaster risk formula
Then analyzed how agric projects effectively contributed to increasing community resilience
Used modified Sustainable Livelihood (SL) model and not PAR & Access model to analyse community resilience
Adapted the SL to include other indictors of social risk governance capacity
Sub-district level Sampling: Detail (Contd)
Number of current public agricultural development projects being implemented in the area
Camp number
Name of Agric Camp
Project 1
(FISP)
Project 2
(SLIP)
Project 3
(FISRI)
Project 4
(Small Holder Dairy)
Project 5
(WVZ – Choongo ADP
Project 6
(Dunavant Cotton)
Project 7
(Alliance Ginnery )
Total Number of Projects Implemented (Currently)
Comment
27
Hamusakwa
1
1
2
28
Nteme
1
1
1
1
1
5
29
Keemba
1
1
1
1
1
1
1
7
Sampled
30
Banakaila
1
1
1
3
31
Bweengwa
1
1
1
3
32
Chuungu
1
1
1
3
33
Malundu
1
1
2
34
Naluntanda
1
1
1
3
Sampled
Summary of agric camps sampled
Name of Agricultural Camp Selected
Number of Villages 2010
2010 Actual Number of HH
2010 Actual Population
Total Number of Projects Being Implemented
Weight of all hazards that impacted the camps in last 10 years (2002-12)
Keemba
23
1,161
8,126
7
10
Nalutanda
12
723
4,438
3
10
Summary of Households Sampled
Keemba Agric Camp
Nalutanda Agric Camp
Strata
Substrata
Gender sub strata
Gender sub strata
Total
Male
Female
Male
Female
Affluent Members of community that had lived in the area for at least 10 years
Adults
4
4
4
4
16
Youth
4
4
4
4
16
Poor headed households that had lived in the area for at least 10 years
Adults
4
4
4
4
16
Youth
4
4
4
4
16
Village heads leaved in area at least 10 years
Adults
4
4
4
4
16
Totals
20
20
20
20
80
Sampling for Sample survey / Quantitative method
Was done at two levels
Sub district level
Household level
Sub-district level Sampling: Detail (Contd)
Multi-Hazard Risk Analysis
Camp number
Name of Agric Camp
Hazard index for Hazard 1 (Drought)
Hazard index for Hazard 2
(Floods)
Hazard index for Hazard 3
(Bovine Diseases)
Hazard index for Hazard 4 (HIV/AIDS prevalence)
Vulnerability index (poverty)
Vulnerability Index (Food insecure)
Weighted Magnitude of Risk
Comment
27
Hamusakwa
2
1
1
2
2
2
10
28
Nteme
3
1
1
2
3
3
13
29
Keemba
2
0
2
2
2
2
10
Sampled
30
Banakaila
3
1
1
0
2
3
10
31
Bweengwa
3
2
1
0
2
2
10
32
Chuungu
3
2
1
2
2
2
12
33
Malundu
3
2
1
1
2
2
11
34
Naluntanda
2
1
1
2
2
2
10
Sampled
Justification for research design
Community resilience could not be measured directly but through proxy indicators and community perceptional views
Analyzed the effectiveness of the projects from user and planner perspective
All research philosophical perspectives were addressed in the study
Thus used mixed design participatory action research
Research Methods
Used sample survey, content analysis, focused group discussions
- Used pre-designed questionnaires to guide interviews with sampled 80 community members
- Generated and used standard checklist to guide interviews with 8 project planners
- Used content analysis to analyse project documents
- Used focused group discussions to triangulate sample survey results & obtain perceptional views
Modified SL model in the Project mgt framework
Incorporated modified SL model in social economic project planning, monitoring and evaluation framework to analyse proper planning and project implementation
SL & project mgt intergraded model used to analyse impact of developmental project on community resilience building: Diagrammatic
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Camps with same magnitude of risk were selected to avoid bias during result interpretation. Study was not on impact of risk on agric, but other way round, impact of agric on risk reduction. Was not a vulnerability analysis either for food security. Was developmental project evaluation on resilience for long term prevention measures.
Hazard Ranking values were: 3 for worst affected; 2 for Moderately affected; 1 for lowly affected; 0 for not affected
Poverty Ranking values were: 3 with most poor hh; 2 with moderate levels of poverty for most hh in the camp; 1 was for low numbers of poor households in the camp
Food insecurity ranking values: 3 was for the worst food insecure; 2 was for moderately food insecure ; 1 was for less food insecure)
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These indicators strengthens the SL model
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Community resilience analyses 'enhancement capacity' Vulnerability analysis just analyses 'capacity' in passive way.
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