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Livestock–Water Interactions: TheCase of Gumara Watershed in theUpper Blue Nile Basin, EthiopiaMengistu Alemayehu AsfawDep...
Outline• Introduction Problem statement Objectives• Materials and Methods Description of study area Study design and t...
The Ethiopian Highlands3Rugged mass ofmountains covering 40%of the country’s land areaHave moderate temp. andadequate rain...
Mixed Farming Systems in theHighlands4Integratedmixed crop-livestockfarming
Multi-functions of livestock in mixedfarming• Nutritious products for home consumption• Income source from livestock sales...
Farm resource base of the mixedfarming1. Land tenure system• Land is under stateownership• Farmers have use right• Grazing...
Specific Objectives1) Refine the methodology for assessing LWP in theframework of Life Cycle Assessment2) Assess LWP in th...
Assessing LWP in mixed farmingsystems, Ethiopia
1.1 MATERIALS AND METHODSStudy site- Gumara watershed wasselectedReasons• Part of a big project inthe Nile basin• Represen...
Study DesignThree distinct scenarios ofmixed farming systemsi) Rice/noug basedfarming complex(RNF)• Crop residues andafter...
Study Design…ii)Tef/finger millet basedfarming complex(TMF)• Crop residues,pastureland andaftermath grazing –major feed re...
Study Design…iii) Barley/potato basedfarming complex(BPF)• Grazing land- majorfeed resource base• Livestock species-Sheep,...
Determination of LWP• LWP was determinedusing the frameworkof Life cycleassessment (LCA) andwater foot printingconcept13nk...
Data CollectionIn applying LWP toGumera watershed– 62 farmers weremonitored for about 1.5years– Sample farmers werestratif...
Statistical analysisT-test analysis – for comparing early off-take (at 2 years of age) and lateoff-take (at 4 years of age...
Farming system N CWP se(USD m-3)LWP se(USD m-3)Water use se(m3 kg-1 lwt)RNF 12 0.46 0.01a 0.057 0.003 b 50.6 2.5bTMF 27 0....
Wealth status N CWP2 se(USD m-3)LWP se(USD m-3)Water use se(m3 kg-1 lwt)Poor 23 0.37 0.01b 0.060 0.003b 46.8 2.1abMedium 2...
1.2 RESULTS AND DISCUSSIONOff-taketypeN LWP se(USD m-3)Sale income se(USD TLU-1)Water use se (m3kg-1 lwt)Early 62 0.09 0.0...
1.2 RESULTS AND DISCUSSIONLivestockspeciesN Liv.no./hhLWP se (USDm-3)Water use se(m3 kg-1 lwt)Small ruminant 50 5.3 0.053 ...
Impact of Collective Management onCommunal Grazing Lands
Study DesignParameterGLM typeRestrictedcommunalPrivateholdingFreely opencommunalGrazing duration(days/month)12 10 30Restin...
•Vegetation attributes:-Hrebacious biomass yield- Ground coverdetermined along a 50mtransect line in threereplications•Run...
23Stocking density, stocking rateand carrying capacity• Dry matter yield per ha• Daily feed intake of animals -using avera...
Statistical analysisParametric and non-parametric analysis were runuing a 3x2 factorial design24Yij=µ+Gi+Sj+(G*S)ij+Eijkwh...
2500.511.522.5051015202530Restricted communal private holding Freely open communalStockingrate(TLU/ha)GLM typeStocking den...
2. 2 RESULTS AND DISCUSSIONMeasuredparameterRestricted communalGLMPrivate holding GLM Freely open communalGLMSEM<10% slope...
MeasuredparameterRestrictedcommunal GLMPrivate holdingGLMFreely opencommunal GLMSEM<10%slope15-25%slope<10%slope15-25%slop...
Table7. Bulk density and soil moistureMeasuredparameterRestricted communalGLMPrivate holding GLM Freely opencommunal GLMSE...
Determinant Factors to Good PastureCondition of Restricted CommunalGrazing Land
3.1 Study area and design• A cross-sectionalstudy was carried outin barley/potatobased farming system• 42 villages wereran...
• Explanatory variables to pasture condition• 7 variables were used to explain the dependent variable• Area of communal gr...
• Proxy indicators to pasturecondition (PROGRAZEmanual, 1996)• Herbage DM yield using aquadrat,• Legume proportion,• Diges...
• Binary dependent variable -logisticregression model• For DMY – Ordinary Least Squares (OLS)method was used333.2 Statisti...
3. 2 RESULTS AND DISCUSSIONExplanatory variable OLS LogitDM yieldLegumeproportiondigestibility Ratio of carryingcapacity t...
CONCLUSIONS ANDRECOMMENDATIONS• CWP was higher than LWP• LWP varied across different farming systems and wealthstatus• Cat...
• Livestock mortality – is one of the main causes todecrease LWP• Overstocking is the major problem that aggravatesovergra...
37THANK YOU FOR YOURATTENTION
38
Conceptual framework of livestock–waterinteractions to assess LWP (Peden et al.2007)Fig. 4. LWP conceptual frame work 39
Data CollectionDetermination of LWP40nknjnmnlljkninjjnjjiiDGmSDETMSCPOLWP1 1 111 11)*(
Fig.1. Quadratic relationship between soil loss and runoff on each rainfall event.y = -0.002x2 + 0.098x - 0.144R² = 0.8750...
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Livestock–water interactions: The case of Gumara Watershed in the upper Blue Nile Basin, Ethiopia

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Presented by Mengistu Alemayehu at ILRI, Addis Ababa, 18 April 2013


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Livestock–water interactions: The case of Gumara Watershed in the upper Blue Nile Basin, Ethiopia

  1. 1. Livestock–Water Interactions: TheCase of Gumara Watershed in theUpper Blue Nile Basin, EthiopiaMengistu Alemayehu AsfawDepartment of Crop and Animal SciencesHumboldt Universität zu Berlin
  2. 2. Outline• Introduction Problem statement Objectives• Materials and Methods Description of study area Study design and treatments Statistical analysis• Results and Discussion Livestock water productivityCollective management on communal grazing lands Determinants of good pasture condition• Conclusions and Recommendations2
  3. 3. The Ethiopian Highlands3Rugged mass ofmountains covering 40%of the country’s land areaHave moderate temp. andadequate rainfall80% of the human & 78%of the livestockpopulation of thecountry concentrate here
  4. 4. Mixed Farming Systems in theHighlands4Integratedmixed crop-livestockfarming
  5. 5. Multi-functions of livestock in mixedfarming• Nutritious products for home consumption• Income source from livestock sales• Asset accruing functions• Renewable farm power source• Manure5At National level•Livestock make 45% of the totalagricultural GDP (Behnke and Metaferia,2011)
  6. 6. Farm resource base of the mixedfarming1. Land tenure system• Land is under stateownership• Farmers have use right• Grazing is communalDue to increasing ruralpopulation– Land scarcity is critical– Pasture area is marginalized62. Water scarcity-Rain fed farming practice- Highly seasonal- Erratic rainfall- No water harvestingtechnology3. Feed scarcity- Heavy reliance on cropresidues- Over-exploitation ofcommunal grazing lands- Critical during croppingperiodA need to increaseresource productivityin a sustainablemannerThe presentstudy focusedmuch on waterproductivity
  7. 7. Specific Objectives1) Refine the methodology for assessing LWP in theframework of Life Cycle Assessment2) Assess LWP in the mixed farming systems of theEthiopian highlands73) Explore the impact of collective management onsustaining pasture ecosystem and land degradation4) Identify the determinant factors influencing goodpasture condition
  8. 8. Assessing LWP in mixed farmingsystems, Ethiopia
  9. 9. 1.1 MATERIALS AND METHODSStudy site- Gumara watershed wasselectedReasons• Part of a big project inthe Nile basin• Represents differentmixed farming systems• Availability ofhydrological information9Major features• Topography varies fromrolling rugged mountainsto vast flat lands• Altitude ranges between1780-3740 m above sealevel• Rainfall distribution isuni-modal (1300-1500mm) in 3-4 monthswith low temperature
  10. 10. Study DesignThree distinct scenarios ofmixed farming systemsi) Rice/noug basedfarming complex(RNF)• Crop residues andaftermath grazing –major feed resourcebase• Livestock species-Cattle and equine10
  11. 11. Study Design…ii)Tef/finger millet basedfarming complex(TMF)• Crop residues,pastureland andaftermath grazing –major feed resources• Livestock species-Cattle, equine, sheep,goats• Equines are used aspack animals 11
  12. 12. Study Design…iii) Barley/potato basedfarming complex(BPF)• Grazing land- majorfeed resource base• Livestock species-Sheep, cattle, equine• Use of horse and mulefor ploughing cropland12
  13. 13. Determination of LWP• LWP was determinedusing the frameworkof Life cycleassessment (LCA) andwater foot printingconcept13nkninwaterdepletedlossmortalitybenefitslivestockLWP11LCA is used to compile inventory in adefined system boundary (from cradle tofarm gate –in the present study)The water foot print accounting was basedon LCA frame of the herds productive lifetime (birth to end of productive life)•Out puts (milk, meat)•Services (draught power)•Asset (stock capital)•ManureValued inmonetarytermsDepleted water –water used in livestock andno longer available for reuse in the domainwater for•Feed production (pasture and cropresidues)•Drinking water• hygiene and processing
  14. 14. Data CollectionIn applying LWP toGumera watershed– 62 farmers weremonitored for about 1.5years– Sample farmers werestratified based on theirwealth status14Wealth status (Poor, Mediumand Rich)Stratification criteria• Land holding• Livestock holding• Annual grain harvest• Additional income
  15. 15. Statistical analysisT-test analysis – for comparing early off-take (at 2 years of age) and lateoff-take (at 4 years of age)15Yij=µ+Si+Eijwhere;Yij=response variable suchas LWP, water use;µ=the overall mean,Si = Livestock speciesEij= error term.Yijk=µ+Fi+Wj+(F*W)ij+Eijkwhere;Yijk=response variable such as LWP, wateruse;µ=the overall mean,Fi=ith farming system,Wj=jth wealth status of smallholder farmers,(F*W)ij=interaction between farmingsystem and wealth status,Eijk= error term.
  16. 16. Farming system N CWP se(USD m-3)LWP se(USD m-3)Water use se(m3 kg-1 lwt)RNF 12 0.46 0.01a 0.057 0.003 b 50.6 2.5bTMF 27 0.38 0.01b 0.066 0.002 a 42.7 1.7aBPF 23 0.33 0.01c 0.066 0.002a 42.4 1.9aMean 0.39 0.01 0.063 0.003 45.2 2.0F-test ** ***Table 1. LWP and CWP under three different mixed farming systems.1.2 RESULTS AND DISCUSSION16MorewaterlossCWP-crop water productivity; LWP-livestock water productivity; USD- United StatesDollars20%additionalwater
  17. 17. Wealth status N CWP2 se(USD m-3)LWP se(USD m-3)Water use se(m3 kg-1 lwt)Poor 23 0.37 0.01b 0.060 0.003b 46.8 2.1abMedium 23 0.38 0.01b 0.058 0.002 b 48.0 1.9bRich 16 0.43 0.01a 0.072 0.003 a 40.9 2.2aMean 0.39 0.01 0.063 0.003 45.2 2.1F-test ** ** *Table 2. LWP across wealth status of smallholder farmers in Gumara watershed.1.2 RESULTS AND DISCUSSION17CWP-crop water productivity; LWP-livestock water productivity; USD- United StatesDollars
  18. 18. 1.2 RESULTS AND DISCUSSIONOff-taketypeN LWP se(USD m-3)Sale income se(USD TLU-1)Water use se (m3kg-1 lwt)Early 62 0.09 0.003 272.1 2.3 13.2 0.6Late 62 0.068 0.001 265.3 1.2 29.6 1.0Mean 0.079 0.002 268.7 1.7 21.4 0.8t-test ** ** **18Table 3. LWP under two off-take managements.Reducedby >50%LWP- livestock water productivity; USD- United States Dollars;TLU- tropical livestock unit
  19. 19. 1.2 RESULTS AND DISCUSSIONLivestockspeciesN Liv.no./hhLWP se (USDm-3)Water use se(m3 kg-1 lwt)Small ruminant 50 5.3 0.053 0.002b 37.9 5.7bCattle 62 5.9 0.077 0.002a 37.6 5.0bEquine 44 1.4 0.037 0.002c 143.2 5.9aMean 0.057 0.002 67.4F-test ** **19Table 4. LWP for different livestock speciesLWP – Livestock water productivity; USD- United States Dollars
  20. 20. Impact of Collective Management onCommunal Grazing Lands
  21. 21. Study DesignParameterGLM typeRestrictedcommunalPrivateholdingFreely opencommunalGrazing duration(days/month)12 10 30Resting season August –November;May - JuneJuly-OctoberNo restingDominant grazerspeciesoxen cattle Cattle,sheep andequine21Table 6. Description of different types of grazing landmanagement (GLM).• Three types of Grazing LandManagement (GLM) undertwo slope gradients (<10%,15-25%)The GLMs are:I. restricted communalGLMII. private holding GLMIII. freely open communalGLM•Identified villagers are recognized asmembers to have use right•The grazing land management is governedby local by-laws•Only fixed number of animals are allowedfor grazing•Open for livestock in the village• Kept by a farm household for making hay andafterward grazing
  22. 22. •Vegetation attributes:-Hrebacious biomass yield- Ground coverdetermined along a 50mtransect line in threereplications•Runoff and soil loss:-measured from 18 plotseach with 4x2 m2 demarcatedusing galvanized iron sheetSoil moisture and bulk density- Samples taken from eachplotData Collection22
  23. 23. 23Stocking density, stocking rateand carrying capacity• Dry matter yield per ha• Daily feed intake of animals -using average animal weightmethod (Pratt and Rasmussen,2001)• Grazing duration• Livestock number• Area of grazing landData CollectionStocking density - is the actualnumber of livestock grazingon specific area of the pasturefor specified period of timeStocking rate- is the number oflivestock grazing on the entireof the pastureland for the entiregrazing periodCarrying capacity - is themaximum number of livestockthat can be supported by a unitof grazing land for the entiregrazing period without harm inthe long term
  24. 24. Statistical analysisParametric and non-parametric analysis were runuing a 3x2 factorial design24Yij=µ+Gi+Sj+(G*S)ij+Eijkwhere;Yij=response variable;µ=the overall mean,Gi=ith type of GLM,Sj=jth slope of grazing land,(G*S)ij=interaction between GLM and slope,Eijk= error term.
  25. 25. 2500.511.522.5051015202530Restricted communal private holding Freely open communalStockingrate(TLU/ha)GLM typeStocking densityCarrying capacityStoking ratebiomass removedby livestockAnnualbiomassremoved(t/ha)46% of theherbagebiomass isremoved80% of the herbage biomass is removed2. 2 RESULTS AND DISCUSSION
  26. 26. 2. 2 RESULTS AND DISCUSSIONMeasuredparameterRestricted communalGLMPrivate holding GLM Freely open communalGLMSEM<10% slope 15-25%slope<10% slope 15-25%slope<10% slope 15-25%slopeHBY (t DM/ha)3.9ab 2.8 bc 5.2 a 2.7 c 2.8 bc 2.5 c 0.3GCw (%) 85.0a 76.4a 87.6a 78.3a 44.3b 42.7b 4.626HBY – aboveground herbaceous biomass yield; GCw - ground cover after end of wet season; SEM –standard error of meanTable 5. Vegetation attributes across different types of GLM
  27. 27. MeasuredparameterRestrictedcommunal GLMPrivate holdingGLMFreely opencommunal GLMSEM<10%slope15-25%slope<10%slope15-25%slope<10%slope15-25%slopeRO (mm) 172.3d 167.3d 343.5b 255.9c 284.2c 491.3a 27.0SL (t/ha) 6.1e 14.0c 6.4e 10.9d 24.5b 31.7aRunoff and SoilLossRestrictedcommunal GLM•Reduce surfacerunoff by morethan 40%•Curb the rate ofsoil erosion bymore than 50%27RO = cumulative surface runoff per year; SL= annual soil loss; SEM – standard error ofmean2. 2 RESULTS AND DISCUSSIONTable 6. Runoff and soil loss as affected by different types of GLM
  28. 28. Table7. Bulk density and soil moistureMeasuredparameterRestricted communalGLMPrivate holding GLM Freely opencommunal GLMSEM3<10%slope15-25%slope<10%slope15-25%slope<10%slope15-25%slopeSM (%)1 34.5a 24.3cd 29.4b 26.3bc 26.8bc 22.6d 1.1BD (g/cm3)2 0.82c 1.02ab 0.87bc 0.94abc 1.06a 1.08a 0.032. 2 RESULTS AND DISCUSSION28
  29. 29. Determinant Factors to Good PastureCondition of Restricted CommunalGrazing Land
  30. 30. 3.1 Study area and design• A cross-sectionalstudy was carried outin barley/potatobased farming system• 42 villages wererandomly selected• 140 smallholderfarmers were selectedusing multistagesampling technique30
  31. 31. • Explanatory variables to pasture condition• 7 variables were used to explain the dependent variable• Area of communal grazing land• Area of restricted grazing land• Area of cropland at household level• Oxen number in a village• Livestock density in a village• Pasture resting period• Soil fertility313.1 Data collection
  32. 32. • Proxy indicators to pasturecondition (PROGRAZEmanual, 1996)• Herbage DM yield using aquadrat,• Legume proportion,• Digestibility (Tilley andTerry, 1963 )• Carrying capacity/stocking rate323.1 Data collection
  33. 33. • Binary dependent variable -logisticregression model• For DMY – Ordinary Least Squares (OLS)method was used333.2 Statistical analysis
  34. 34. 3. 2 RESULTS AND DISCUSSIONExplanatory variable OLS LogitDM yieldLegumeproportiondigestibility Ratio of carryingcapacity tostocking rateArea of communal grazing land -0.01928 0.0661 0.6337 0.0660Area of restricted grazing land 0.02906 -0.00640 2.1685* 2.0641**Area of cropland -0.55043 -3.5360* -1.0045 -0.2110Oxen number 0.00282 -0.00221 -0.0560** -0.0507**Livestock density -0.00205 -0.0123 -0.00874 -0.00375Pasture resting period 0.05221*** -0.00640 0.0563 0.0245Soil fertility 0.38756 4.2194*** 11.8126* 2.7193Intercept -6.29490*** 5.1111 -12.4499 -6.3015Log-likelihood functions ad-R2= 0.74 -109.496 -103.944 -116.256Model chi-square - 23.8368 38.933 37.150234* significant at 10% level; ** significant at 5% level; *** significant at 1% levelTable 8. Logit regression coefficients of variables affecting pasture condition
  35. 35. CONCLUSIONS ANDRECOMMENDATIONS• CWP was higher than LWP• LWP varied across different farming systems and wealthstatus• Cattle had higher LWP due to more values of the multiplefunctionalities and better feed utilization efficiency• Early off-take management scenario increased LWP35
  36. 36. • Livestock mortality – is one of the main causes todecrease LWP• Overstocking is the major problem that aggravatesovergrazing and eventually reduces LWP• Management of communal grazing land can beimproved using local institutions and policy supports36CONCLUSIONS ANDRECOMMENDATIONS
  37. 37. 37THANK YOU FOR YOURATTENTION
  38. 38. 38
  39. 39. Conceptual framework of livestock–waterinteractions to assess LWP (Peden et al.2007)Fig. 4. LWP conceptual frame work 39
  40. 40. Data CollectionDetermination of LWP40nknjnmnlljkninjjnjjiiDGmSDETMSCPOLWP1 1 111 11)*(
  41. 41. Fig.1. Quadratic relationship between soil loss and runoff on each rainfall event.y = -0.002x2 + 0.098x - 0.144R² = 0.87500.10.20.30.40.50.60.70.80.910 5 10 15 20Soilloss,ton/haRun off, mm2. 2 RESULTS AND DISCUSSION41

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