RECONNASSANCE ASSESSMENT OF SUSTAINABLE LAND MANAGEMENTMEASURES IN THE WESTERN USAMBARA HIGHLANDS-LUSHOTO

TANZANIA

By

Juma M. Wickama and Annadomano W. Nyanga

December, 2009

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AcknowledgementsWe wish to thank WOTRO for financing this work to itscompletion. Having said this we also wish thank oursupervisors in the Netherlands at the WageningenUniversity and Research Center (Dr. Aad Kessler, LarsHeins and Rolf), Utretcht University (Dr Geert Sterk) forhaving supported this idea from its inception. We aregrateful to our local supervisors (Dr. Barrack Okoba atKARI-Headquarters in Nairobi-Kenya, Dr. Albino Tenge atDodoma University-Tanzania and Dr. George Ley at ARI-Mlingano for their support during the conduction of thiswork. We are specifically indebted to Dr Jeremias Mowo atICRAF-Nairobi and the AHI site coordinator for LushotoMr. Charles Lyamchai at Selian-ARI in Arusha for availingthe team with logistical support with which we were ableto travel and reach out to the sites. We wish to put onrecord our appreciation of the constant encouragement andideas we received from our group chair Professor LeoStroosnidjer.

We are grateful to DALDO’s office (Mr. HusseinShelukindo) for support and advices during the entirework. Much thanks are given to colleagues, leaders,farmers and all people in Shashui and Sunga. We herebymention Ms Beatrice Shemdoe, Hon. Ernest Mbondei (localcouncilor for Sunga Ward), Mzee Said Musa, divisionofficers for Mtae and Soni (Mr. Vedastus Luseko and MsSofia Msuya) of the two places and our very many friendsfor their support.

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List of abbreviationsACEDE - Associacion Cientifica de Economia y Direccion de la Empresa AFRIWAG -African Women Aids Working GroupDALDO - District Agricultural and Livestock Development OfficerPADEP - Participatory Agricultural Development ProgramSACCOS - Saving and Crediting Cooperative Society TANESCO -Tanzania Electricity Supply CompanyTASAF - Tanzania Social Action Fund TIP -Traditional Irrigation ProgrammeUPATU - A name given to informal rotating saving schemesVICOBA -Village Community Banks ZANTEL -Zanzibar Telecommunication Company Ltd

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Table of Contents

Acknowledgements.......................................iiList of abbreviations.................................iiiINTRODUCTION............................................1MATERIALS AND METHODS...................................2The study sites.........................................2How the study was conducted.............................3Pre-field work preparations.............................3Field work conduction...................................4Post field work activities..............................6RESULTS AND DISCUSSION..................................7A. Results..............................................7(i) Perception of land degradation, sustainable land management measures.....................................7(ii) Factors influencing choice of SLM measures.........9(iii) Categories of SLM measures across the sites.......9(iv) Relationship between socio-economic factors and choice of SLM..........................................12(v) Role of institutions and their interactions with farming households.....................................16(vi) Historical perspectives...........................16(vii) Selection of the final research site(s)..........17B. Discussion..........................................18Perception of land degradation and sustainable land management.............................................18Perception on the factors governing choice of SLMs.....19Suitable site for research.............................20C. Conclusions and recommendations.....................21References.............................................22Appendices:............................................23

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LIST OF FIGURESFigure 1a. Rainfall pattern of Lushoto (70 yrs) ......... 3 Figure 1b. The Agro-ecological zones of Lushoto ......... 5 Figure 2. Farmers participating in data generation duringfield work .............................................. 6 Figure 3. Facilitation of the data collection with farmers in Sunga Ward ................................... 7 Figure 4. Some SLM-measures in Shashui village .......... 8 Figure 5. Research team in a post field work collective action .................................................. 9 Figure 6. Proportion of divergent views on land degradation ............................................ 11 Figure 7. This is an example of SLM category one plot in Shashui village ........................................ 12 Figure 8. In Sunga, this piece of field is ranked as verypoor ................................................... 18 Figure 9. Anna holding a sample of cabbage waiting to besold ................................................... 23 Figure 10. View of Soni market from a distance ......... 31 Figure 11. Impressive terraces (behind Juma) and stone terraces .............................................. 32

LIST OF TABLESTable 1. Inventory of measures constituting good SLM practice ............................................... 11 Table 2. Perception of the factors determining variation in choice of SLM ....................................... 13 Table 3. Characteristics and proportion of the various SLM categories ......................................... 14 Table 4. SLM categories and their proportion in Shashui/Soni ward ...................................... 16 Table 5. Similarity of SLM category one across the candidate catchments ................................... 17 Table 6. Similarity of SLM category 4-poor between Sunga and Shashui ............................................ 17 Table 7. Social wealth rank groups in Sunga ward ....... 19 Table 9: Produce, its market outlets and challenges .... 23 Table 10: Analysis of institutions against community interactions ........................................... 24 Table 11: Historical trends in Sunga Basin ............. 25

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Table12. Basis of selecting Shashui against Sunga village. ............................................... 27 Table 13. Analysis of factors determining choice of SLM measures ............................................... 29

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INTRODUCTIONLand degradation is one of the most reported socio-ecological problems on the East African Highlands(Gachene et al. 1997, Johanson 2001). Because of landdegradation, farmlands have been realizing decliningyields per unit area through falling soil fertility, andtop soils are being lost through accelerated soil erosionfrom cultivated fields (Ongwenyi et al. 1993). Severalefforts have been introduced to combat it. The majorityof these efforts have yielded only minimal positiveresults (Maddox, 2006).A number of studies have linkedthe observed land degradation in this region toinefficient soil management and land resource usepractices (Lyamchai et al. 1998, Dejene et al 1997).

The Wageningen UR, through the WOTRO project “Scaling upSustainable Land Management in the Highlands of Kenya andTanzania” is conducting studies in the Western Usambarahighlands (Lushoto district) in north eastern Tanzaniawhere land degradation has been observed to occur mostlyin the smallholder farmers’ fields. The studies arebasically meant to shed light towards understanding thereasons why scaling up of the sustainable land management(SLM) measures has generally failed to move from onelocality in either district to another at a satisfactoryrate. The studies take a biophysical, socio-economic,policy and institutional dimension of the problem inorder to understand the factors underlying the adoption,non-adoption, scaling up and non scaling-up of the SLMmeasures.

The district of Lushoto where this assessment wasconducted had already been earmarked as one of the sitesfor the research project in the proposal for which thesePhD studies were to be funded by the WOTRO programme.What was lacking was the identification of where inLushoto the final research would be conducted. Inessence, the study we are reporting here was conducted asa rapid assessment of two candidate areas in Lushoto inorder to arrive at the final site for future detailedresearch. The candidate areas were chosen afterconsultations with district stakeholders during the kick-

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off workshop at the launching of the PhD research projectin the district. These workshops served to provide theresearch team with places which were both degraded andwere high on the stakeholders priority list for researchand extension intervention. This assessment was thereforedone with the following specific objectives;

(i) Assess the local perception as regarding landdegradation, sustainable land management measuresand establish their inventory in the candidatesites

(ii) Analyze the factors influencing choice of SLMmeasures

(iii) Establish categories of SLM measures across thesites

(iv) Investigate the relationship between socio-economic factors and choice of the identified SLM measures

(v) Establish role of different institutions in the sites and assess their interactions with famers

(vi) Investigate possible linkage of historical perspectives to current practices

(vii) Establish criteria and select a suitable sitefor research

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MATERIALS AND METHODS

The study sites The study was conducted in Lushoto district. The districtis situated in north eastern Tanzania within latitudes 40

22’ to 50 08 and longitudes 380 5 to 380 38’’, Lushotodistrict covers 3500 km2 out of which 2000 km2- are arable(Mowo et al., 2002). Its population of 420,000 (NationalBureau of Statistics, 2002). Gives it a populationdensity of 120 people per km2. The topography of Lushotois mountainous and its altitude ranges from 600 meters to2300 meters above sea level. The geological material fromwhich the soils of Lushoto are derived include themetamorphic rocks like schists and gneisses. These coverthe bulk of the district (Ngailo et al., 1998). Meliyo et al,(2002) have indicated the major soil types in Lushoto asbeing Humic and Chromic Acrisols, Luvisols and Lixisolsfor most of the mountainous hillands while the valleybottoms have Fluvisols and some pockets of Gleysols.Rainfall in Lushoto is bimodal and the precipitationvaries from 900 to 1300 millimeters per annum. Figure 1ashows rainfall pattern in Lushoto for the last 70 years.

Annual rainfall record - Lushoto DALDO no. 943803

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Figure 1a. Rainfall pattern of Lushoto (70 yrs)

According to Pfeifer (1990) rainfall in Lushoto isgreatly influenced by the agro-ecological zone of anarea. Pfeifer reports four agro-ecological zones (AEZ)for the district: The Humid Warm Zone; The Dry Warm Zone;The Dry Cold Zone and the Dry Hot Zone. De Pauw (1984)

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also has four AEZ, but these are based on the topography,parent materials and rainfall. Shashui village falls inAEZ E12 while Sunga falls in AEZ E2 (Figure 1b). Thedistrict is famous for tea, coffee, maize, banana, beans,sugarcane, and a number of other temperate fruits.Administratively, Lushoto has eight divisions that aresubdivided into 32 wards with a total of 176 Villages.The town of Lushoto is the largest in the district andserves as the district headquarters. According to theLushoto District Profile (2005) the demography in thedistrict is the largest and most densely populated inTanga Region. According to this report the population ofLushoto district has increased almost thrice since 1957from about 150,000 to 423,000 in 2002 (National Bureau ofStatistics, 2002).

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Figure 1b. The Agro-ecological zones of Lushoto

How the study was conductedThe study was conducted through the following steps;

Pre-field work preparationsPre-field work preparations included a kick-off workshopin Lushoto at the Montessori Sisters Convent. Otheractivities included team meetings, literatureacquisitions, resource persons consultations andlogistical planning. The kick off workshop was meant togive this research team both exposure to the problems andthe resources in the study district which could be put toits use. Some of the major deliverables from thisworkshop are in Appendix 1 through 2. Team meetingsinvolved the sharing of roles for team members, anddevelopment of a checklist of the issues meant to becollected in the forthcoming meetings. Literatureacquisition involved seeking reports, maps and any otherrelevant information about the places to visited. Forresource persons consultations the team involved andcollected opinions of the people who have worked in theareas of interest. Logistical planning involvedaccommodation bookings (important for Sunga Ward). In allplaces appointments for meetings were made before actualmeetings. Meeting resource people meant meeting membersof other departments, NGOs and other stakeholders beforemeeting farmers.

Field work conductionField work was conducted largely in three phases. Phaseone involved meeting leaders of the villages and WardDevelopment Committee. Resource people were also invitedin these meetings. In these meetings, the team did thefollowing; confirmed severity of the land degradationissues in the locality; recorded the efforts done toarrest it; got a historical perspective of how theproblem developed; got the leaders’ perspective onsustainable land management; developed criteria andcategories of sustainable land management practices and;

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established criteria and categories for social wealthranking.

Figure 2. Farmers participating in data generation during field work

Group discussions and open plenary meetings were the maintools used to conduct this phase. Meetings with leadersended with propositions on where to meet farmers forextended consultations. During meetings with the wardleaders the team largely developed SLM definition, SLMcategory criteria and final villages selection criteria.These included;

1. Availability of SLM - 2. Availability of practitioners and none practitioners 3. Presence of institutions formal and informal 4. Availability of relevant information5. Presence of implemented project on SLM6. Accessibility and distance from district head quarter7. Representation of the area to district physical and socio-economics8. Severity of land degradation9. Willingness to participate

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Phase two involved meetings with farmers . These wereconducted a day after meeting with ward and villageleaders and resource persons. These meetings wereconducted as plenary sessions. Data collected included;verifying the criteria and categories on sustainable landmanagement practices; verifying the criteria andcategories on socio-economic wealth ranking; categorizingfarmers (through own criteria) into both the SLM andsocio-economic; recording where each of the classifiedfarmer is located.

Figure 3. Facilitation of the data collection with farmers in Sunga Ward

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Phase three involved resource inspection in which theteam visited some of the nearest ecological resourceslike water sources or fields to assess the degradation.These visits were done in collaboration with farmers.

Figure 4. Some SLM- measures in Shashui village

Post field work activitiesThe post field work activities included evaluating theprocess used in data collection, translating the flipchart data into workable documents, sharing and comparingnotes among team members and planning for the nextencounter with farmers. This phase also included mendingthe car and preparing it for the next field work.

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Figure 5. Research team in a post field work collective action

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RESULTS AND DISCUSSION

A. Results(i) Perception of land degradation, sustainable landmanagement measures and their inventoryFor most farmers, land degradation was defined as thedeclining ability of the soil to support strong crop growth andsupport livelihoods. During meetings with resourcepersons and farmers this team learned that around 85-95%of them were of the opinion that land degradation is amajor problem in their area. In Sunga ward farmers andleaders were able to give a detailed description of themanifestations of land degradation in their area. Thisincluded: low crop yields; poor crop performance; soil erosion; frequentfloods; declining household incomes; poor soil fertility; declined naturalvegetation; dependence on external nutrients sources e.g. industrial fertilizer;weakening of soil structure (light soils); deforestation; rock or stones growing.To reverse land degradation farmers recommended thefollowing measures; conservation of land; reforestation;planting grass strips; use of animal manure; use cut offdrains in affected areas; educating farmers on landconservation; formulation and enforcement of NRM relatedbylaws which protect the environment and ecologicalresources.

0

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Degraded Not degraded

perception am ong leaders and farm ers of land degradation as a problem in lushoto

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Figure 6. Proportion of divergent views on land degradation

Yet, there was some difference when the team askedfarmers and leaders on their perception of whatsustainable land management (SLM) is, and what measurescomposed it. In the kick off-workshop in Lushoto, thestakeholders definition of SLM had the following keywords; soil conservation; stable returns; future use; increased production.Participants also mentioned that SLM measures can be;physical measures like terraces, Fanya juu, Fanya chini, andcut off drains. But it also involves biological measuressuch as tree planting, crop rotation, micro-contourlines, organic farming, water source conservation, covercrops. On the other hand farmers and leaders in Sungaward-Lushoto defined SLM as land conservation whichincorporates use of nutrients sources, grass strips,trees and all these with an intention of meeting futureuse. Participants stressed that for a land use to qualifyas being an SLM, then each time you use the land itshould incorporate one of the measures meets thatcriteria e.g. each time you plant you should use animalmanure. Farmers agreed that SLM is a form of land usewhich does not destroy resource base for future use andtakes into account NRM bylaws. In Shashui village,farmers and leaders defined SLM as practicingconservation agriculture all the time including croprotation, replenishing soil fertility nutrients, goodagronomic practices, with the aim of increasing incomeand maintaining its productivity for the future.

Inventory of the SLM measures commonly found in theirareas and which constitute sound SLM practices in Lushotosites is presented in Table 1.

Table 1. Inventory of measures constituting good SLM practice

s/no

Sunga (Lushoto) Shashui (Lushoto)

1 Terraces Terrace2 Tree planting Tree plating3 Fanya juu Grass strips4 Planting grass strips Use of farm yard manure 5 Cut off drains Good agricultural

husbandry

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6 Application of livestock manure

Cut-off drains

7 Application of good agricultural husbandry

Contour ploughing

8 Mulching Use of compost manure9 Crop rotation Livestock keeping10 Use of composite manure Mulching11 Livestock keeping Traditional nutrient

sources e.g tughutu12 Knowledge on type of

fertilizer, soils and suitablecrops

Existence of irrigation water

13 Furrowing -Source: Data from field survey

Figure 7. This is an example of SLM category one plot in Shashui village

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(ii) Factors influencing choice of SLM measuresOne pattern kept repeating itself across the four sites.The percent of households described as following properSLM practices were considerably lower compared to thosewho did not. In both sites only 5-10% of the householdswere reported by leaders being good SLM managers. Thisresearch team wanted to find out why there was such atrend. According farmers, there are many reasons why theychoose to adopt certain SLM measures and leave out therest. Comparison of the variation of the factors betweenSunga Ward-Lushoto and Shashui/Soni ward is presented inTable 2.

Sunga ward Shashui/Soni WardAvailability of irrigation water Willingness of the community to

acquire and practice SLM measures

Cost of maintenance of some SLMmeasures

Economic viability of specific SLM options

Existence of facilitating agencyeg TIP, SECAP

Capability of the measure to improve yields and quality of farm produce

Laziness of the farmer Contribution of the measure to household food self-sufficiency

Selling of labour Improvement of environmental quality

Owning valley bottom land parcels

Limited access to knowledge on land conservation

Limited resource capacity eg money and labour

Limited capital

Lack of livestock Poor farming practicesDiversified sources of income weak enforcement of by-lawsDistant farms and distant farmers (owning farms in a village but living in urban areas)

-

Lack of farming plans -

Table 2. Perception of the factors determining variation in choice of SLM measures

From the above reasons Sunga ward has a higher priorityfor irrigation water and external assistance. This isunderstandable given the fact that their area is in the

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drier agro-ecological zone of Lushoto district and for solong their area enjoyed support from an NGO called TIP(Traditional Irrigation Improvement Programme) forinstallation of terraces and supply of irrigation water.For farmers and leaders in the Soni/Shashui the reasonswere much different. Shashui/Soni belongs to anotheragro-ecological zone which enjoys more rainfall comparedto Sunga Ward. Besides, Soni has one of the highestcommercial activities in the district. Here it is thewillingness and the socio-economic returns of themeasures which serve as the driving force.

(iii) Categories of SLM measures across the sitesIn this study a category of an SLM means a package of SLMmeasures that a farmer usually implements in his/ herfield as part of routine means of managing the land. Forthis reason when the study reports as a certainproportion of farmers as belonging to a certain SLMcategory it means those farmers have similar practicetowards managing their fields. A proportion (given inpercentage) in this case means the relative number ofhouseholds which implement that combination of SLMmeasures for every one hundred household found in thevillage or that area.These categories were self generated by leaders andfarmers themselves. In each site, the possible number ofthe SLM categories were first proposed by farmers. Thistook deliberations until compromises were struck. Then, aset of criteria was developed which was peculiar to thatspecific SLM-category. Eventually farmers were allowed toclassify themselves and their close neighbours intospecific SLM categories. A village register was also usedto assist in the classification. Names of farmers andtheir respective SLM-category are in Appendix 4. Anexample of characteristics used to create some SLMs ispresented in Table 3.

Table 3. Characteristics and proportion of the various SLM categories in SungaCategory Indicator % households Good Tree planting 5

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Terraces of good qualityFanya juuPlanting grass stripsCut off drainsApplication of livestock manureApplication of good agricultural husbandryMulchingCrop rotation Use of compost manureLivestock keepingKnowledge on type of fertilizer, soils and suitable crops

Average Few TreesTerraces of moderate qualityFanya juuPlanting grass stripsCut off drainsApplication of livestock manureApplication of good agricultural husbandryMulchingCrop rotation Use of compost manureFew Livestock keptKnowledge on type of fertilizer, soils and suitable crops

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Poor No TreesNo TerracesMay have Fanya juuPlanting grass stripsCut off drainsNo application of livestock manureNo application of good agricultural husbandryMulchingCrop rotation Use of compost manureNo Livestock keepingLack knowledge on type of fertilizer, soils and suitable crops

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In Shashui, leaders and farmers identified fourcategories of SLM measures (Table 4). But unlike Sungathey indicated some SLM measures which were optional foreach class. Absence of these measures did not mean thefamer was a poor manager but only that the circumstancesof the enterprises were different. For example, while

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they recognized need of mulching vegetable plots, it wasimpractical that the same farmer would mulch his maizefield.

Table 4. SLM categories and their proportion in Shashui/Soni ward

Category Indicators Percentage of households

1 TerraceTree platingGrass stripsUse of farm yard manure Good agricultural husbandryLivestock keepingCut-off drainsContour ploughingMulching

5

2 TerraceUse of farm yard manure Good agricultural husbandryLivestock keepingMulchingCut-off drainsContour ploughing

7.5

3 No terrace,No treesUses of farm yard manure Livestock keepingContour ploughing

60

4 Trees,Grass strips(on contour lines), Contour ploughing

27.5

NB. Letters in blue mean the practice is optional

Across the two sites there was a close similarity in the characteristics which farmers used to create the categories. There was reference to soil and moisture conservation, protection of the land against deforestation, erosion, adoption of sound agricultural advice, livestock keeping, nutrient application and high value cropping. A similarity of the features used by farmers for an SLM category rated as the best group is presented in Table 5.

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Table 5. Similarity of SLM category one across the candidate catchments

s/no

Sunga Soni/Shashui

1 Tree planting Terrace2 Terraces Tree plating3 Fanya juu Grass strips4 Planting grass strips Use of farm yard manure5 Cut off drains Good agricultural

husbandry6 Application of livestock manure Cut-off drains7 Application of good agricultural

husbandryMulching

8 Mulching Livestock keeping9 Crop rotation Contour ploughing10 Use of composite manure11 Livestock keeping12 Knowledge on type of fertilizer,

soils and suitable crops

In contrast to this category is the category they ranked as being the last. Here, farmers reported that this grouphad minimal amount of SLM measures in their fields. The majority of members belonging to this group either had notrees in their homesteads, no livestock and did not adhere to proper agricultural advice (Table 6).

Table 6. Similarity of SLM category 4-poor between Sunga and Shashui

s/no Sunga Ward Soni/Shashui1 No terrace, Contour ploughing2 No livestock No Tree planting3 No tree Only Grass strips

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Figure 8. In Sunga, this piece of field is ranked as very poor. In Shashui it could score category 3 because of past terraces.

(iv) Relationship between socio-economic factors and choice of SLM measuresAcross the two sites, the team established that there wasa very close relationship between belonging to a certainSLM-category and belonging to a specific social wealthrank. The wealth ranking was done in two stages. In stageone the team asked for possible socio-economic classes inthe candidate site from leaders and resource persons.This was also accompanied by an approximation of suchclasses by same people. In stage two, farmers werepresented with the classes proposed by their leaders andresource persons. This was to verify the criteria and addor subtract some characteristics. Once the final criteriawas in place farmers were asked to classify themselvesand their fellows in their respective social wealthranks. For example for Sunga ward farmers reported thefollowing indicators as being important for social-wealthranking;

1. Ownership of land 2. Ownership of house3. Number of livestock kept4. Engagement on business activities

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5. Labour availability6. Education status of the households7. Ownership of means of transportation8. Ownership of improved farming equipments9. Capital ownership10. Ownership of water/soil harvesting11. Memberships in informal groups and institutions12. Ownership of solar energy equipments

Based on these indicators, farmers and leaders identified4 social-wealth categories in Sunga basin. These have thefollowing characteristics (Table 7).

Table 7. Social wealth rank groups in Sunga wardResource endowment

Indicators Proportion of households (%)

High resource-1

At least has 7 out of the 12 indicators plus- Has permanent house- Educated children to secondary and university levels

5

Medium-2 Has land, good house, keep livestock, at secondary level of education for some household member

20

Low-3 Has land, house, limited number and local type of livestock

70

Poor of the poor-4

Sells own labour, family poorly educated and most have very big families

5

By combining the SLM categories against the social wealthgroup to which a farmer belongs a close relationshipbetween the two parameters could be seen. Here is oneexample taken from a hamlet called Majini in Sunga ward-Lushoto (Table 8). However, on very close examinationthis data tends to indicate that there are many farmersbelonging SLM category 1 while not belonging to socio-economic class 1. This may imply farmers were mostprobably classifying their colleagues based on how theyassess external qualities of the soil conservationstructures like the terraces while not considering all

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other criteria. This anomaly may need further closefollow-up on the ground to establish the actual wealthranks of different SLM category members once intense datacollection reaches the area.

Major Socio-economic challenges/ConstraintsAcross the four sites the team established the following constraints affected farmers though at a varying scale;1. Lack of farm inputs2. Limited capital3. Limited value addition initiatives 4. Low quality of produce5. Shortage of extension service6. Poor road/communication network7. Shortage of rainfall8. Unreliable internal markets and limited number of

markets outlets

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Table 8. Social wealth rankings against SLM category in Sunga ward (Lushoto)

Name of household SLM category Wealth rank Hamlet locatedHoseni Ikera 1 2 MajiniRashidi Juma 2 2 MajiniHamisi Hoseni 3 3 MajiniBakari Alfani 1 1 MajiniHemedi Alimasi 2 3 MajiniHoseni Alimasi 2 3 MajiniNuhu Alimasi 3 3 MajiniAliamini Athumani 1 3 MajiniHashamu Athumani 1 3 MajiniHamdala Athumani 1 2 MajiniMusa Selemani 1 2 MajiniHatibu Barua 1 3 MajiniHatibu Musa 1 2 MajiniAmiri Musa 2 2 MajiniAli Musa 3 3 MajiniJuma Musa 3 3 MajiniMohammed Mussa 3 3 MajiniRabahani Mohammed 1 2 MajiniIbrahim Mohammed 3 3 MajiniHemed Omari 1 1 MajiniAsadi Ally 2 2 MajiniSelemani Adamu 2 2 MajiniRajabu Mohammed 1 1 MajiniMohammed Rabahani 3 3 MajiniAnasi Ali 1 1 MajiniSalimu Ramadhani 1 2 MajiniMahafudh Shehe 1 1 MajiniMaulid Abedi 1 2 MajiniRajabu Abedi 1 2 MajiniAbdi Abedi 1 2 MajiniArafat Ali 1 1 MajiniHoseni Ali 3 3 MajiniAbedi Ali 1 1 MajiniHussein Ally 3 3 MajiniBakari Mswaki 2 2 MajiniMusa Rashidi 1 2 MajiniSalehe Juma 3 3 MajiniAhamadi Athuman 3 3 Majini

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Farm produce and their marketing and challengesAcross Sunga and Shashui, issues of marketing were foundto be one of the bottlenecks towards favourable returnsto farm produce. But among the factors which serve tominimize their returns are the small plots per householdon crops are grown. Though the two catchments are exposedto a strong culture of producing vegetables for thesurrounding cities (Tanga, Arusha, Moshi, Dar-es-Salaamand Mombasa), this team learned that the actual marketingchain was overwhelmingly in favour of traders andtransporters (Table 9). Despite efforts of farmers tolink themselves with external markets it was themiddlemen, transporters and traders who actuallydominated the value chain. The other challenge wasexistence of seasonal gluts where farmers had loads ofsame products all maturing within the same periods. Thistrend tends to saturate markets at such periods andplummet the producer prices.

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Figure 9. Anna holding a sample of cabbage waiting to be sold at the Soni Market

Table 9: Produce, its market outlets and challenges faced by farming households in Lushoto

Internal markets

crops Seller Buyer Season

Sunga Amaranthus, Irish potatoes, beans, cabbages, tomatoes, onions

Farmer,Middleman

Consumer, Middleman

Mambo Tomatoes, beans, cabbage, onions, Irishpotatoes, Amaranthus

Farmer,Middleman

Consumer, Middleman

External marketsTanga (Ngamiani)

CarrotsIrish potatoesPepperTomatoesCabbages

Farmer Trader/ transporter

April-June; April-DecJan-June;Dec-April; Dec-Jul;Jan-June

Dar (Kariokoo)

Fruits,Irish potatoesTomatoes,Cabbage,Carrot,Pepper

Farmer Trader/ transporter

April-June; April-Dec;Jan-June; Dec-April; Dec-Jul;Jan-June

(v) Role of institutions and their interactions with farming householdsAcross the sites, the team established that there was a close interaction between certain institutions with the community in question. Yet farmers preferred to classify those interacting with them in three classes (Table 10).

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Table 10: Analysis of institutions against community interactions across Lushoto sites

Village/site High interaction

Limited interaction

No interaction

Sunga ward TIP, Communication networks (Zain, ZANTEL), religion, forest department, local healers,UPATU (local lending institutions),PADEP, TASAF

Health/dispensary, primary schools, traditional midwives, secondary schools, Co-operative office, Village government, Road infracture, judiciary institutions, Ward Judiciary Council

Water department, TANESCO for electricity supply

Soni/Shashui Religious organizations,village government, local market, primary and secondary schools, health centers, Village community banks (VICOBA)

PADEP, TASAF, AFIWAG, SACCOs, Tanzania Electricity Supply Company (TANESCO), Traditional Irrigation Programme (TIP), Posta, Mponde Tea factory.

Tourist hotels, ACEDE, judiciousinstitutions (courts) and financialinstitutions such as banks.

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The implication of this set up is that for effective institutional analysis this team will have to find out the potential role of those institutions which have significant interaction with communities and how this interaction can be used for promotion of scaling up. Thisis crucial for PhD 2 (Anna).

(vi) Historical perspectivesThe history of the two catchments is part and parcel ofthe history of the larger part of the district and indeedthat of the country. Collection of this history was doneby the more elderly members of the group. Even whencompared (between Shashui and Sunga) we found that theelders could only start with the German colonization ofarea. This may also imply that the arrival of Germansmarks the era in which formal reservation of historicalevents began because before this, the country was insmall and countless tribal kingdoms. The history isindicative of repeated cycles of famine (after each 25-30years). The elders associate compulsive terracing withfamine which occurred during the British rule. Howevermore studies are needed to understand how past history inthese catchments play the current role in SLM adoptionand scaling up. An example from Sunga Basin is given inTable 11.

Table 11: Historical trends in Sunga BasinPeriod Event Remarks1900-1914

German colonial governance Good crop yields

1914-1918

World War I

1918-1939

British colonial governance

1939-1945

World War II Famine ‘Chankola’

1945-1954

British colonial governance Compulsory terracingFamine continuedStarted extension serviceCompulsory of bananas and Makana

1954-1960

Campaign for independence

1961 Gained independence Clearance of Cedar forest, de-tribalization

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1962 Became Republic1964 Union between Tanganyika

and Zanzibar1967 Arusha Declaration Nationalization of big farms,

houses and other resources,Strong Tanzanian shilling

1970 Lushoto Integrated Development Program

1972 Economic hardship Shortage of basic goods, 1974- Famine ‘Yanga’ Yellow maize1978-1979

War with Uganda Caused more economic hardship for18 monthsDevaluation of Tsh.

1983 Tarmaced of Mombo-Lushoto road

1985 SECAP implemented Conservation of land which involved tree planting

1992 Introduction of multi-partism

1993 Floods People perished, some farms were submerged and eroded

1996 Construction of first secondary school, Soni Day

1997 Serious drought Serious famine1998 El-Nino rains Damage to farms, roads and deaths2005-2009

Reduced rainfall Decline in food production

2006 Hunger2008 International market was

initiated at Soni2008-2009

International economic crisis

Increased fuel prices

(vii) Selection of the final research site(s)The catchments that stakeholders earlier suggested couldbe suitable for our research are in Appendix 2. Forreasons based on logistics and time we could not visitthem all. Time and resources allowed us to visit only twoout of the five mentioned. The criteria of selectingthese two were the fact that they belonged to differentagro-ecological zones and were rated higher in the votingexercise during the kick-off workshop. However when webegan collecting data in the two areas we were led by thecriteria (see section on methodology under field work)already mentioned above. The points were scored out of

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ten and the final marl was reached by consensus betweenresearchers. The final results are in Table 12.

Table12. Basis of selecting Shashui against Sunga village.

Criteria Sunga ShashuiAvailability of SLM 8 7Availability of SLM practitioners and none practitioners

7 8

Presence of institutions formal and informal 8 6Availability of relevant information 8 6Presence of implemented project on SLM 7 7Accessibility and distance from district head quarters

4 9

Representation of the area to district physical and socio-economics

6 8

Severity of land degradation 8 7Willingness to participate 8 7Total score 62 65

B. Discussion

Perception of land degradation and sustainable land managementKebe and Defoer (1998) reported that land degradation isone of the factors contributing to the agriculturalcrisis in Africa. This view is widely shared with farmersin the two catchments. In Shashui village, farmersdescribed land degradation as manifested by; soilerosion; low crop yields; limited soil water holdingcapacity; crop failure; decrease in natural vegetativecover; low soil fertility; water shortage due to dryingup of water sources; saline water taste; increasedtemperature; declined household economy; disappearance ofsome crops e.g coffee. The fact that 90% of leaders andfarmers in the two sites were of the opinion that landdegradation was high in their area, actually supportswhat Sanchez (1994) observed earlier that one of theregions where land degradation is reported to activelyhappen in Africa is on the East African highlands. Ourfindings are similar to other studies and we are of theopinion that selection of Lushoto (Western Usambarahighlands) for this research was correct and logical.

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Dumanski et al. (1991) defined sustainable land management-SLM as “technologies applied at all levels of land use,which individually or in aggregate contribute tosustainable agriculture”. This is again the view of allfarmers and leaders in the places we visited. In bothcatchments farmers insisted there is no sustainabilitywhich relies on a single practice.

In this study what came out as unique was to have farmersdescribe the categories of their SLM measures,approximate their proportion and locate them. Earlierstudies have tended to classify farmers and theirpractices based on their resource endowments. In thiscase it was not the overriding factor.

Perception on the factors governing choice of SLMsIn this study the approach used to solicit why farmerswere doing or not doing certain SLM practices was basedon mutual information sharing and group discussions. Thisapproach seems to be effective and reliable. In fact asimilar approach was used by Kessler and Stroosnijder(2006) in Bolivia to assess land degradation and gavegood results. In our case, we have established that thelimited application of SLM options across the twocatchments was attributed to lack of adequate technicaladvice on soil nutrient status, suitable fertilizers andrates, smaller quantities of farm yard/compost manure,unsuitable crop varieties, lack of irrigation waterespecially during dry seasons, unpredictable weatherpatterns, laziness and continuous cultivation of samecrops with minimal rotations. Decreasing land sizes, lowinvolvement of the youth in agricultural activities,fewer off-farm incomes and poor on-farm returns were alsomentioned in Shashui as underlying factors thataccelerate land degradation. These reasons are similar tothose mentioned earlier by Gachene et al (1997) whenstudying land degradation on the East African highlandsand those of Ongwenyi et al (1993) who also reported theKenyan and Tanzanian cases of land degradation. Thefactors mentioned by farmers as influencing their choiceof the SLM measures (see Table 2) are socio-economic,

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biophysical, institutional and of policy nature. Thesecan be summarized as follows (Table 13).

Table 13. Analysis of factors determining choice of SLMmeasures in Shashui and SungaCatchment Socio-economic Biophysical Institutional PolicyShashui-Soni

Economic viability of specific SLM options

Capability ofthe measure to improve yields and quality of farm produce

Limited access to knowledge on land conservation

Improvement of environmental quality

Contribution of the measure to household food self-sufficiency

Improvement of environmental quality

Poor farming practices

Limited capital weak enforcement of by-laws

Poor farming practicesWillingness of the community to acquire and practice SLM measures

Sunga Ward Cost of maintenance of some SLM measures

Availability of irrigationwater

Existence of facilitating agency eg TIP, SECAP

Laziness of the farmer

Owning valley bottom land parcels

Selling of labourOwning valley bottomland parcels

Distant farmsand distant farmers (owning farmsin a village but living inurban areas)

Limited resource capacity eg moneyand labourLack of livestockDiversified sources of incomeLack of farming plans

NB: Letters of same variant color imply the issue is cross-cutting

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From the above analysis it will be seen that theconstraints towards adopting the SLM measures in Sungaare overwhelmingly socio-economic in nature. Constraintsrelated to policy were not mentioned or probably thequestioning was not tactical enough. In Shashui thescenario is balanced across the factors though socio-economic factors took the lead. The overall pattern forSunga is Socio-economic > Biophysical > Institutional.That for Shashui is Socio-economic > Institutional >Biophysical > Policy. For Shashui the pattern isdebatable considering that poor faming methods are across cutting factor. Tenge (2005) conducted a study inLushoto in which adoption of soil conservation issueswere analysed. In his study he also found that socio-economic reasons were instrumental in leading farmersselect the measures.

Suitable site for researchConsidering factors such as distance (budget), presenceof Soni market (institutional economics), Interactionwith district based stakeholders (horizontal scaling)Shashui and Kisiwani villages look more favorable andrepresent the rest of the villages in the district. Forthese reasons we preferred it to be the prime researchsite. On the other hand we recommend Sunga villages to beused as villages for validating the research initiated inShashui.

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Figure 10. View of Soni market from a distance

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C. Conclusions and recommendationsWe therefore have the following conclusions and recommendations;1. The perception of land degradation and sustainable

land management by farmers in Lushoto is comparableto that of research scientists. The majordifference is the fact that farmers do understandtheir own practices fast and hence the easiness withwhich they can classify themselves into where theybelong. We recommend some study into understanding howfarmers and leaders of these areas develop their priority settingprocess in identifying the measures and putting in one class.

2. Despite a theoretical linkage elsewhere,reconnaissance data from Sunga indicates that it isnot always true that only farmers with high resourceendowment are good SLM managers. The factor“willingness” given in Shashui seems to carrysubstantial weight. We recommend a close study ofunderstanding the prime determinants of final choice plus profiling thetype of households most likely to be moved by such factors.

3. Land degradation is a real problem in Lushoto andtherefore its choice as a site for this project isboth logical and correct. But are the causes of thedegradation and stagnated adoption of thetechnologies meant for its reversal well known andbeing addressed? We recommend a serious study in this direction.Do you know that most well terraced fields in Shashui, Sunga andindeed many parts of Lushoto are almost devoid of trees! Is there anychance that wrong prescriptions have been meted to farmers all thistime? This needs to be addressed.

Figure 11. Impressive terraces (behind Juma) and stone terraces on theright. But where are the trees? This is Sunga Ward

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4. In the two study sites the weighting of factors foradopting the SLM measures was found to be in theform of socio-economics > institutional >biophysical > policy. The role of policy andbiophysical factors become more appreciated tofarmers and leaders only when better explained forthem to comprehend. We recommend efforts be made for farmersand leaders to equally dig into the possible role of these other potentialareas of contribution.

5. The impact of past historical events like faminesand coercion in terracing on the current uptake ofthese technologies is unclear. This needs to be studied indetail. Probably a sociologist can be tasked to study it.

6. Given its immediate accessibility to theseresearchers and fewer institutional influences forwe are of the opinion that Shashui/Soni (3 km off atarmac road and 14 km from Lushoto) area shouldserve as the hub of our research activities. Sunga(53 km from Lushoto and impassable during heavyrains) serve the validation role.

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References Dejene, A., E. Shishira, P,Yana and F. Johnsen. 1997. Land Degradation in Tanzania: Perception from the Village. World Bank Technical Paper No. 370. Washington

De Pauw (1984). Physiography and Agro-ecological zones of Tanzania, CropMonitoring and Early Warning Systems Project. Ministry of Agriculture, Dar-es-Salaam

Dumanski, J., H. Eswaran, E. Pushparajah and A. Smyth (ed.). 1991. Evaluation for sustainable land management in the developing world. Vol. 1. Towards the Development of an International Framework. International Board for Soil Research and Management, Bangkok, Thailand. IBSRAM Proceedings No. 12.

Gachene C., N. Jarvis, H. Linner and J. Mbuvi. 1997. Soil erosion effects onsoil properties in a highland Area of central Kenya. Soil Sci. Soc. Am. J. 61:559-564.

Johansson, L. 2001. Ten Million Trees Later: Land use Change in the West Usambara Mountains.The Soil Erosion Control and Agro-forestry Project in Lushoto District. Deutsche Gessellschaft fur Technische Zusammenarbeit (GTZ) GmbH, Dag-Hammarskjold-Weg 1-5, 65760 Eschborn, Germany

Kebe, D. and T. Defoer .1998. ‘Gestion de la fertilit´e des sols: challengepour les syst`emes nationaux de recherche agricole en AfriqueSubsaharienne’, in G.A. Renard, N.K. Becker, and M.V. Oppen (eds), Soil FertilityManagement in West African Land Use Systems (Gestion de la fertilit´e des solsdans les syst`emes d’exploitation d’Afrique de l’Ouest), Margraf Verlag, pp.453–462.

Kessler, C. and L. Stroosnijder. 2006. Land Degradation by Farmers in Bolivia mountain valleys. Land Degradation & Development 17, 235-248 (2006)

Lyamchai C, Owenya M, Ndakidemi P, Massawe N. 1998. Participatory Rural Appraisal in Kwalei catchment Lushoto, Tanzania. In Lyimo SD, Ndondi RV (Eds). Selian Agricultural Research Institute, Arusha. Tanzania

Maddox, G. 2006. Sub-Saharan Africa: An Environmental History, ABC-CLIO UK. ISBN-13: 978-1851095551, pp 355

Meliyo J, W., Kabushemera Tenge A. 2002. Characterization and mapping soils of Kwalei subcatchment, Lushoto district. Agricultural Research Institute Mlingano, Tanga.

Mowo J.,, S. Mwihomeke, J. Mzoo, and Msangi T. 2002. Managing natural resources in the West Usambara mountains: A glimmer of hope in the horizon. http/www.mtnforum.org/resources/library/mowo02a.htm of 24/12/2004.

National Bureau of Statistics 2002. Tanzania Population Census Results for 2002. National Government Website http://www.tanzania.go.tz/statisticsf.html

Ngailo, J., J. Wickama, and A. Nyaki. 1998. Nutrient Flow Analysis for Selected Farming Systems in Northern Tanzania: The case of Mbulu, Moshi rural, and Lushoto districts. Report from a FAO sponsored project. ARI Mlingano, Tanga, Tanzania

Ongwenyi, S., S. M. Kithiia and F. O. Denga. 1993. An Overview Of The Soil Erosion Erosion and Sedimentation problems in Kenya In: Sediment Problems:

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Strategies for Monitoring, Prediction and Control (Proceedings of the Yokohama Symposium, July 1993). IAHS Publ. no. 217, 1993. Yokohama, Japan

Pfeiffer, R., 1990. Sustainable Agriculture in practice – The production potential andEnvironmental effects on Macro-contourlines in the West Usambara mountains of Tanzania. PhD –Dissertation. University of Hohenheim. Germany.

Sanchez, P. 1994. Alternatives to slash and burn: a pragmatic approach for mitigating tropical deforestation’, in J.R. Anderson, Agricultural Technology Policy Issues for the International Community, CAD International, pp. 451–480.

Tenge, A., B. Okoba, G. Sterk, R. Hessel. 2005. Physical Effectiveness and Farmers’ Preferences of Soil and Water Conservation in the East African Highlands. Submitted to Agriculture, Ecosystems & Environment

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Appendices:

Appendix 1. What each stakeholder can contribute into this research

Serial

Institution Contribution

Dodoma University

Provision of technical know how and social economic issues.Supervision of students

SARI Provision of technical know how ( all aspects)Willingness to share existing information.Direct participation in actual field implementation if need arises

AHI Part of SARIContribution of existing information and ten years experiences will be shared.ASARECA – Institution and ILAC by lawsinformation will be shared between andwith WOTRO project.Ready to provide transport on cost sharing basisReady to provide office space

SACCOS- Kwalei

Provision of information if need arisesThey will provide expertise and information

CRDB- Tanga Ready to provide information that willbe needed by students during research period.

UDSM - Incubator

Sharing information and experiences gathered.Provision of internet access free of charge

Division officer

Provision of support (security, information and mobilization).

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CHAMAVITA Ready to provide all data and information linked to agricultural , domestic and water resources

District Community Development

Ready to collaborate in social and community development issues

Makau_ Agrovet

Ready to supply improved seeds, fertilizer and tree seedling. (inputs information)

Agriculture- Coops

Ready to provide information on Cooperatives and micro finance institutions.Ready to participate I n data collection related to cooperatives.

Ward Executive Officers of Sunga and Mtae

Security and logistic support

DALDO- Contribution of experiences and information on past projects.Provision of supporting staffDADPs (District Agricultural Development Plans) will provide financial support villages that will be selected

TIP- Lushoto Ready to provide information based of their experiences on land management and irrigation.Ready to Participate in data collection when need arises.

KIBO Seed company

Ready to provide information agronomicpractices and various improved seeds.

ARI- Mlingano Donated a studentReady to provide literature on land management issuesReady to provide laboratory facilitiesProvision of GIS facilitiesProvision of technical support on landresource studies

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DED Contribute collaborative technical officers in the district

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Appendix 2. Catchments proposed by stakeholders as being suitable for Wotro research

1. Baga (Baga-Kwekitui-Kwesine-Dule-Kwalei-Bumbuli-Kwadoe-Wena-Kwehangala-Funta-Balangai-Tamota-Kwanguruwe-Mayo-Shembekeza)

2. Umba (Chambogo-Rangwi-Makose-Goka/Shagayu-Mwangoi-Moa-Mlalo-Hentoye, Mshangai-Malibwi-Mbwei-Mlola-Mdando-Mn’garo-Kauzeni-Umba, Mtae-Mpanga-Kweshindo-Kishangazi-Nkombo-Mbaramo-Zimbiri

3. Soni (Irente-Bangala, Gare-Boheloi, Kibohelo-Mkuzi, Shume-Lukozi-Nkinko-Masange, Magilla-Kwadoe-Shashui-Soni)

4. Sunga-Tema-Masereka-Mamboleo5. Pangani (Kweminyasa-Mponde-Kwemhafa-Nkamai-

Kwandoghoi-Buti-Vuga)

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Appendix 3. Names of farmers and their SLM/wealth categories (Sunga Ward-

Name of household SLM category Wealth rank Hamlet locatedMohammed Hemed 1 1 Kizungu Mahamud Hemed 2 2 KizunguOmari Hemed 1 1 Kizungu Ramadhani Hemed 2 2 KizunguIssa Hemed 1 1 Kizungu Hussein Hemed 2 2 KizunguSwaibu Alfani 2 2 Kizungu Alfani Swaibu 2 2 KizunguZaniali Hemedi 1 1 Kizungu Kamru Zaniali 2 2 KizunguYunusu Zaniali 2 2 Kizungu Salim Zaniali 2 2 KizunguAhmed Ramadhani 2 2 Kizungu Seleman Ahmed 2 2 KizunguYahaya Saidi 2 2 Kizungu Musa Yahaya 2 2 KizunguAbedi Yahaya 2 2 Kizungu Adam Omari 2 2 KizunguIssa Selemani 2 2 Kizungu Alfani Hashimu 2 2 KizunguIbrahim Saidi 2 2 Kizungu Sadiki Ramadhani 3 3 KizunguRamadhani Fihli 4 4 Kizungu Nisira Ramadhani 2 2 Kizungu

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Name of household SLM category Wealth rank Hamlet locatedNuhu Hussein 1 2 KishumiIssa Omari 1 1 KishumiIddi Abdi 2 2 KishumiJuma Ibrahim 1 1 KishumiYasin Ali 2 2 KishumiMusa Issa 1 1 KishumiMusa Awadh 1 1 KishumiAziza Hatibu 2 2 KishumiDini Ali 2 2 KishumiAthumani Ali 1 2 KishumiAli Ngomandodo 3 3 KishumiRamadhan Hatibu 3 3 KishumiRashid Awadh 3 3 KishumiOmari Awadh 3 3 KishumiZuhura Awadh 3 3 KishumiAdamu Ali 3 3 KishumiHamisi Ali 1 1 KishumiHusseini Amiru 1 1 KishumiAwadh Amiri 1 1 KishumiAthuman Ali 1 1 KishumiAthuman Mbashiru 3 3 KishumiZawadi Selemani 4 4 KishumiHashamu Ali 4 4 KishumiJuma Nuhu 1 2 KishumiMhidina Msilimu 2 2 KishumiHemedi Rashid 2 2 KishumiAdinani Athuman 4 4 KishumiAli Msilimu 3 3 KishumiIddi Rashid 3 3 KishumiTaimuru Abdallah 4 4 KishumiAwaziTaimuru 3 3 KishumiMbashara Abdalah 4 4 KishumiMwenjuma Abdallah 4 4 KishumiAli Rashid 4 4 KishumiNuhu Halidi 3 3 KishumiAlimasi Nuhu 4 4 KishumiAthumani Abdi 4 4 KishumiAli Halidi 2 2 KishumiMujibu Halidi 2 2 KishumiAli Nuhu 1 1 KishumiAhamed Hemedi 4 4 KishumiHakimu Ahmadi 4 4 KishumiYusuphu Ahamadi 4 4 KishumiJuma Ahamadi 4 4 KishumiFadhili Ahamadi 4 4 Kishumi

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Name of household SLM category Wealth rank Hamlet locatedHoseni Ikera 1 1 MajiniRashidi Juma 2 2 MajiniHamisi Hoseni 3 3 MajiniBakari Alfani 1 1 MajiniHemedi Alimasi 2 3 MajiniHoseni Alimasi 2 2 MajiniNuhu Alimasi 3 3 MajiniAliamini Athumani 1 1 MajiniHashamu Athumani 1 1 MajiniHamdala Athumani 1 1 MajiniMusa Selemani 1 2 MajiniHatibu Barua 1 2 MajiniHatibu Musa 1 2 MajiniAmiri Musa 2 2 MajiniAli Musa 3 3 MajiniJuma Musa 3 3 MajiniMohammed Mussa 3 3 MajiniRabahani Mohammed 1 2 MajiniIbrahim Mohammed 3 3 MajiniHemed Omari 1 1 MajiniAsadi Ally 2 2 MajiniSelemani Adamu 2 2 MajiniRajabu Mohammed 1 1 MajiniMohammed Rabahani 3 3 MajiniAnasi Ali 1 1 MajiniSalimu Ramadhani 1 2 MajiniMahafudh Shehe 1 1 MajiniMaulid Abedi 1 1 MajiniRajabu Abedi 1 1 MajiniAbdi Abedi 1 1 MajiniArafat Ali 1 1 MajiniHoseni Ali 3 3 MajiniAbedi Ali 1 1 MajiniHussein Ally 3 3 MajiniBakari Mswaki 2 2 MajiniMusa Rashidi 1 2 MajiniSalehe Juma 3 3 MajiniAhamadi Athuman 3 3 Majini

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Name of household SLM category Wealth rank Hamlet locatedMinihaji Ramadhani 1 1 KwebandaMohammed Hassani 1 1 KwebandaDini Ramadhani 1 1 KwebandaMustafa Ramadhani 1 1 KwebandaTwaha Amiri 1 1 KwebandaHamisi Omari 1 1 KwebandaRamadhani Saidi 1 1 KwebandaAlim Halfani 1 1 KwebandaMusa Mkufya 1 1 KwebandaWaziri Hassani 2 2 KwebandaNuru Iddi 1 2 KwebandaSiraji Iddi 2 2 KwebandaRukia Bakari 3 3 KwebandaAbdallah Musa 1 1 KwebandaFaki Musa 1 1 KwebandaRamadhani Hasani 2 2 KwebandaShamsi Rashidi 1 1 KwebandaShemdoe Nuru 2 2 KwebandaHadinani Athuman 2 3 KwebandaSelemani Amiri 1 1 KwebandaNasibu Amiri 2 2 KwebandaOmari Amiri 2 3 KwebandaMajama Amiri 2 3 KwebandaSharifa Fihili 1 2 KwebandaNabahani Halfani 1 1 KwebandaHija Nabahani 2 2 KwebandaIssa Halfani 1 1 KwebandaMahamudu Halfani 1 1 KwebandaRashidi Halfani 1 1 KwebandaFatuma Halfani 2 2 KwebandaSadiki Ramadhani 2 2 KwebandaRamadhani Fihili 3 3 Kwebanda

43