1. PRESENTATION OF RESEARCH FINDINGS AT THE 2 nd 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)

2. 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

3. 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

4. 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

5. 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

6. 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%

7. Map: Position of Monze in Zambia

8. 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

9. 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.

10. 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

11. 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

12. 10 consolidated indicators used for community resilience analysis (Graphic presentation)

13. 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

14. Research Questions i.How were the agricultural development projects designed that were implemented in Monze? ii.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?

15. 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?

16. 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

17. Community resilience analytical model : Diagrammatic

18. 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

19. SL & project mgt intergraded model used to analyse impact of developmental project on community resilience building: Diagrammatic

20. 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

21. 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

22. Sampling for Sample survey / Quantitative method Was done at two levels Sub district level Household level

23. 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

24. 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) Vulnerabil ity index (poverty) Vulnerabili ty Index (Food insecure) Weighted Magnitude of Risk Comment 27Hamusakwa21122210 28Nteme31123313 29Keemba20222210Sampled 30Banakaila31102310 31Bweengwa32102210 32Chuungu32122212 33Malundu32112211 34Naluntanda21122210Sampled

25. 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 – Choong o ADP Project 6 (Dunav ant Cotton) Project 7 (Allian ce Ginner y ) Total Number of Projects Implemented (Currently) Comment 27Hamusakwa112 28Nteme111115 29Keemba11111117Sampled 30Banakaila1113 31Bweengwa1113 32Chuungu1113 33Malundu112 34Naluntanda1113Sampled

26. 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) Keemba231,1618,126710 Nalutanda127234,438310

27. Summary of Households Sampled Keemba Agric CampNalutanda Agric Camp StrataSubstrataGender sub strata Total MaleFemaleMaleFemale Affluent Members of community that had lived in the area for at least 10 years Adults444416 Youth444416 Poor headed households that had lived in the area for at least 10 years Adults444416 Youth444416 Village heads leaved in area at least 10 years Adults444416 Totals 20 80

28. 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

29. 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

30. Public agricultural developmental projects analysed: ( those known by the sampled communities in Monze) SnProject NameImplementation period Financier 1Farmer Input Support Project (FISP)2003- todateGovt. 2Small Livestock Investment Project (SLIP)2006 – 2013IFAD 3 Farmer Input Support Response Initiative Project (FISRI) to rising cost of agricultural commodities in Zambia 2009 – 2012EU 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- 2022WV Korea 6Dunavant cotton2001 - ongoing Private investment for public 7Alliance Ginnery 2007- ongoing Private investment for public

31. Projects not analysed ( those not known by the sampled communities in Monze ) SnProject NameImplementation period Financier 1Targeted Food Security Pack Project (FSP)2000- ongoingGovt. 2 Agricultural Development Support Programme -Small Holder Commercialisation (ADSP-SC) 2006 – 2012World Bank 3 Conservation Agriculture Scaling up for Increased Productivity and Production (CASPP) 2008 – 2012FAO 4 Small Agribusiness Promotion Programme (SAPP) 2010 – 2016IFAD, 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

32. Enhanced human assets: Demographics VariableKeembaNalutanda Average for the for the two communities Female-headed HH (%)373134 Male-Headed HH (%)636966 Education level of HH head (%) No formal education1307 Primary education635057 Secondary245036 Marital Status of HH head (%) Single1307 Married537262 Divorced888 Separated000 Widowed261722

33. Respondent age comparison: Compares well between the two communities

34. Household size comparison: Compares well between two communities

35. Major Sources of Livelihoods:

36. Land for crop farming: Compares were among households in the two communities

37. Cropping land

38. 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 PigsDonkeyChickensDovesOther Keemba3823651165055456 Nalutanda360120318019555078013 Total7421568296245510618519

39. How households acquired livestock: Own servings is major source & not project soft loans

40. Reason for livestock increase: Not due to projects. Decrease due to livestock disease. That is low livestock project support

41. Access to other physical assets: More in Nalutanda

42. Milk Sales: Insignificant overall but relatively more in Nalutanda than Keemba

43. Milk sales insignificant but has potential : low milk outputs due to livestock disease, poor pasture, low veldt mgt, stock thefts

44. 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)

45. Enhanced hazard awareness capacity: Generally high but insignificant difference between two communities

46. Normal hazard perception: High for drought, floods & corridor bovine disease, then HIV/AIDS

47. Most vulnerable groups: Communities’ perception

48. Early warning communication proactiveness: High on indigenous knowledge & radio programmes, insignificant difference in two communities

49. Spontaneous reasons for increased risk awareness : High personal experience & radio programmes. Insignificant difference between two communities

50. Community awareness of community disaster mgt & risk reduction committees organised by projects

51. Coping strategies in adversity: Nalutanda has more sustainable ways to cope than Keemba

52. Community cohesion: Nalutanda community more cohesed

53. Projects known & benefited from

54. 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)

55. 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)

56. 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.

57. 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’.

58. Acknowledgements DiMTEC, University of the Free State, Bloemfontein, South Africa Ministry of Agriculture and Livestock, Departments of Agriculture & Extension, Monze, Zambia

59. Contact Address Bowen Banda, (Alumni DiMTEC, UFS, Bloemfontein) Monze, Zambia email: bowenbanda@yahoo.com,bowenbanda@yahoo.com Dr. Andries J. Jordaan, Director, DiMTEC, UFS, Bloemfontein, South Africa email: jordaana@ufs.ac.zajordaana@ufs.ac.za