A farm-level analysis for carbon sequestration in Ghana using IMPACT linked with the DSSAT, Household and Ruminant models E. González-Estrada 1, V.K. Walen 2, J. Naab 3, P.K. Thornton 1 and M. Herrero 1 1 International Livestock Research Institute, PO Box 30709, Nairobi, Kenya 2 University of Florida, PO Box , Gainesville, FL, USA 3 Savanna Agricultural Research Institute, PO Box 494, Wa, Upper West Region, Ghana
Case study: CRSP-SM field trials in Wa, Upper West region of Ghana Objective: Explore the role of crop-livestock interactions in the carbon dynamics at the farm level
IMPACT Integrated Modelling Platform for Mixed Animal-Crop Systems Household Optimization Model Multiple-Criteria linear programming DSSAT Crops Ruminant Livestock Framework
Case study Piisi, Upper West Region, Ghana Household size: 12 (5 adults & 7 children) Plot IDSizeCrop 10.8 haGroundnuts 21.6 haRice 31.2 ha Millet Cowpea Sorghum 40.3 haBambara nuts 50.6 haYams 60.4 haMaize
Case study –2- LivestockNumber Cattle2 Sheep3 Goats 2 Pigs3 Chicken15 Guinea fowl8
IMPACT’s base line scenario analysis: Net income: 160 USD Total carbon balance in agricultural land (Inputs-Outputs): kg Food security status: Low energy and protein intake during June-October
IMPACT Integrated Modelling Platform for Mixed Animal-Crop Systems Household Optimization Model Multiple-Criteria linear programming DSSAT Crops Ruminant Livestock Framework
ILRI’s household model: Integrates biological, social and economic aspects of smallholder farming systems Linear programming model –An objective function (i.e. maximize net income) –A set of production activities –A set of constraints Runs for a period of 1 year in monthly timesteps
The model maximises gross margins subject to: –Land constraints (fixed farm size and number of plots) –Satisfying food security for the household –Labour constraints –Cash constraints (cannot spend more than what is generated) –Seasonal production constraints for crop and livestock activities Other objectives can be maximised or minimised (i.e minimise costs, nutrient losses) ILRI’s household model - constraints -
HH model Output 1. Food security - Role of livestock within the system - Base-line analysis: Only chicken, pigs, guinea fowls and a goat are sold or consumed by the household Ruminants are kept for dowry, sacrifices, savings (no cash expenses for their maintenance other than 7,000 cedis a year for health) Optimised management (food security achieved throughout the year, no land-use changes): Two tropical livestock units (TLU) are sold to generate cash to “buy food security”.
HH model Output 2. Maximize net income Change of land-use pattern: Increase the number of TLU that are sold!!! Increase the proportion of fodder-yielding crops (e.g. maize) No practical solution!!! Farmer’s attitude towards risk.
HH model Output 3. Maximize carbon fixation Net income: 96 USD (-40%) Total carbon balance in agricultural Land (Inputs-Outputs): 1930 kg Food security: Achieved Ground nuts Rice Bambara nuts Millet Sorghum Yams Maize Current land use Ground nuts Rice Bambara nuts Maize Optimized land use “Where is my Fufu???”
Back to: HH model Output 1. - Role of livestock within the system - Base-line analysis: Only chicken, pigs, guinea fowls and a goat are sold or consumed by the household Ruminants are kept for dowry, sacrifices, savings (no cash expenses for their maintenance other than 7,000 cedis a year for health) Optimised scenario by the household model (food security achieved throughout the year, no land-use changes): Two tropical livestock units (TLU) are sold to generate cash to “buy food security”.
Some more on the role of livestock within the system and carbon sequestration Field trials. CRSP plots in Ghana. Improved MAIZE management Crop residue incorporated to the soil Simulate grain yield in response to maize stover incorporated to the soil DSSAT-Century Simulate TLU maintenance in response to maize stover availability Ruminant
Rainfall distribution in Wa, and its effect on fodder resources utilization Homestead native fodder Maize stover
Trade-off analysis by simulated output of number of TLU vs grain yield Grain yieldNumber of TLU
Conclusion Is the household of this case study ready for adopting technologies to improve carbon sequestration? Household level analyses for priority setting Produce a household typology for a given ecoregion Identify farm types that are capable to modify management strategies towards a better use of carbon
La fin Merci!