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A System Thinking Approach to Understand the Drivers of Change in Ghana’s Backyard Poultry Farming System

  1. Better lives through livestock A System Thinking Approach to Understand the Drivers of Change in Ghana’s Backyard Poultry Farming System Joshua Aboah, ILRI International System Dynamics Conference, 2022 Frankfurt, Germany and Online, 18-22 July 2022
  2. 2 Background Increasing demand for poultry products (eggs & meat) Decreasing local production (Butler, 2016; Etuah et al., 2020; Yevu & Onumah, 2021 ) Backyard Poultry Farming System - Most popular in rural areas - Revenue is an additional source of household income - Supplement household nutritional needs. (esp. festive occasions) BUT Production practice is not the best (Adusei-Bonsu et al., 2021; Kunadu, 2020)
  3. 3 Farmers’ adaptability to socio-economic drivers and internal household economic factors contribute to the observed changes in farming systems (Garcıa-Martınez et al., 2009) BUT There is an underlying assumption of static drivers of change in backyard poultry farming system (Anang et al., 2013) (i) To understand how farm-level drivers of change in the backyard poultry production system evolve. (i) To examine how different production strategies contribute to farm household income in Ghana Objectives
  4. 4 Methodology Qualitative value chain mapping Preliminary quantitative SD model Model structure validation Revised quantitative SD model -60% -40% -20% 0% 20% 40% 60% 80% 100% 120% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 Influence level (%) Time (years) R1 3 stocks 11 variables R2 2 stocks 10 variables B1 2 stocks 8 variables B2 2 stocks 8 variables Loops That Matter Analysis What ifs (Production Strategies)
  5. 5 i) Production Module @ Individual Farm household level • 2 types of farm households - adopters & non-adopters of GAP considered • Captures – production of broilers, layers & eggs • Influenced by the Epidemiological module via the mortality rate (which is endogenised) • Output becomes the inputs for the Financial Module ii) Financial Module @ Individual Farm Household Level This module uses output from the production sector to estimate the profitability, which in turn, influences the production decisions (i.e., feed and water rationing, and vaccine uptake). • Profitability estimation iii) Epidemiological Module @ Aggregate level • This module estimates the mortality rates, which influences deaths of birds in the production module. • Uses an extrapolation of the total number of birds based on outputs from the production sector and the farmer population in the consumption module iv) Consumption Module @ Aggregate Level • This module looks at how the demand and supply patterns influence the price of egg and chicken meat • The price feeds into the financial module at the individual farm household level • Supply and demand are extrapolated from the production module Model Structure Epidemiological Module Production Module Financial Module Consumption Module
  6. 6 Ls (x. z) = [∆x z/∆Z]. sign [∆x z/∆x] (1) Where ∆x z is the change in variable z concerning variable x. ∆x represents the change in the variable x for time(t), and ∆Z is a change in z from time (t) to time (t+1). [∆x z/∆Z] estimates the magnitude of the link score sign [∆x z/∆x] represent the polarity of the link score. Gross income = ∑(P(ij) Q(ij)) – ∑Exp (ij) (2) Where P (ij) is the selling price of egg and poultry meat; Q(ij) is the quantity sold Exp (ij) is the total production cost Methodology E-Driver (change) Loops That Matter Analysis (Eberlein & Schoenberg, 2020) Efficient production strategies
  7. 7 Results 12 loop sets from the epidemiological module 10 loop sets from the production module 2 loop sets from the consumption module 1 loop set (interaction of production, consumption , & financial module) Loop set No reinforcing feedback loops No of balancing feedback loop No of feedback loops describing 80% of model behaviour Main issues highlighted by the dominant feedback loops 1 4R 10B 2R 4B How changes in consumer price affects supply, and the consequential feedback on on-farm profitability 2 - 16B 5B (i) The effect of changes of layers sold on layers stock at the farm level, (ii) the delay in the maturing layers, (iii) proportion of reserved breeders sold 3 - 16B 5B (i) Delay in the sales of layers, (ii) effect of day-old chicks’ death on day-old chick stock, (iii) egg sales effect on stock of eggs 4 1R 2B 1B How vaccination affect the number of recovered birds (day-old chicks GAP) 5 1R 2B 1B How vaccination affect the number of recovered birds (day-old chicks No GAP)  Production module  Epidemiological module  Consumption module  Consumption, financial & production module High Dominant feedback loops (≥ 5%) R is reinforcing feedback loop B is balancing feedback loop
  8. 8 Results s s s o Epidemiological Module.Recovered birds[Dayold, GAP] Epidemiological Module.Susceptible Birds[Dayold, GAP] Epidemiological Module.Total Bird population[GAP, Dayold] Epidemiological Module.Vaccination rate[Dayold, GAP] Epidemiological Module.Vaccination[Dayold, GAP] Epidemiological factors (vaccination of day-old chicks) are critical drivers of change in the backyard poultry system when dominance threshold is set at 50%
  9. 9 Results Dominant Feedback Loops in Loop set 1 Highest cumulative influence for loop set 1 is the reinforcing feedback loop revolving around the effect of price changes on the desired egg price desired (R1) From the onset of simulation run, the balancing feedback loop revolving around changes in the unit price of poultry (B3) initiates the dominance but loses dominance to R1. The dominance of the feedback loop (R1) commences after 6.5 weeks continues to the 9th week and losses dominance to the balancing feedback loop revolving around the supply of egg (B2) on the market till the 22nd week when the feedback loop revolving around the changes in the unit price of egg and desired price (R1) regains dominance In Sum: unit price of egg dictates the supply of eggs on the market, and drives more changes in behaviour (production decisions) of the backyard production system than the changes in the unit price of poultry.
  10. 10 Cumulatively, the balancing feedback loop revolving around the laying stock and adult layers has the highest dominance level (B1) (i.e., total score of 32.62%). From the onset of the simulation, changes of the model behaviour are dominated by the balancing feedback loops revolving around the death of layers (B5) between the 1st and 2nd weeks The balancing feedback loop revolving around the delay in the sales of layers (B3) dominates between the 6th and 7th week In Sum: There is a potential risk that a farm household might encounter when it begins the poultry production with only growers. However, the early sales of broilers and the adoption of homegrown hatcheries can help curtail the risk by ensuring production continuity Results Dominant Feedback Loops in Loop set 2
  11. 11 Profitability (GHS) GAP Strategy 1# Strategy 2+ Strategy 3* Mean (GHS) -2,776.34 11.33 2,260.00 Max (GHS) 0 6,026.36 11,1572.59 Min (GHS) -4,331.27 -2,182.69 -1,577.00 Periods in weeks (<0) 51.00 33.25 22.50 Periods in weeks (>0) 0.00 17.75 28.50 Periods in weeks (=0) 0.25 0.25 0.25 Profitability (GHS) Non-GAP Strategy 1# Strategy 2+ Strategy 3* Mean -1,482.50 669.25 2,216.17 Max 2,099.53 6,799.16 10,433.69 Min -2,912.96 -1,575.54 -1224.98 Periods in weeks (<0) 44.25 28.75 20.50 Periods in weeks (>0) 6.75 22.25 30.50 Periods in weeks (=0) 0.25 0.25 0.25 Results Layer prod (#) 1:0 ratio of layer to broiler day-old chicks purchased Layer & broiler(+) 0.5:0.5 ratio of layer to broiler day-old chicks purchased Broiler prod(*) 0:1 ratio of layer to broiler day-old chicks purchased
  12. 12 Results No statistically significant difference in the profitability for both GAP and Non-GAP adoption households under strategy 3 (i.e., Broiler production) Statistically significant difference in profitability under Strategies 1 & 2. For these strategies (layer production & mixed production) Non-GAP adopting households earn more than GAP-adopting households T stat= -9.81 p-value = 2.2e- 16** T stat= -2.89 p-value = 0.0039** T stat= 0.123 p-value = 0.902
  13. 13 Results Statistically significant difference in the profitability under strategies 2 & 3 when compared with the profitability under strategy 1 for both GAP and Non-GAP adopting households. 1st Broiler production (Strategy 3) 2nd Mixed layer & broiler production (Strategy 2) 3rd Layer production (Strategy 1) Ranking of profitable production strategy
  14. 14 Conclusions  From the onset of the poultry production, disease prevention at different growth stages of the chicken (especially for day-old chicks) is a critical driver of change that has a high but short-lived dominance. Thus, there is a potential for total loss and discontinuation of production activities.  Beyond the grower stage, the changes in the unit price of eggs have a relatively higher and longer influence on production dynamics than changes in the unit price of poultry.  Post-grower stage, the dominance level of the delay in the maturation and sales of layers highlights the need for determining the optimal production strategy that provide a financial cushion for farmer households PROFIT (Non-GAP-Adopters) > PROFIT (GAP-Adopters) Because the unit cost of production is higher than the unit price for poultry meat. Layers Production (only) is NOT a financially viable strategy for GAP-Adopters Broiler Production (only) is a financially viable strategy with mid-year break even for all farmer households E-Driver (change) Profitable Production strategies
  15. 15 Thanks Photo: Ghana Poultry Project
  16. www.cgiar.org
  17. About 620 ILRI staff work in Africa and Asia to enhance incomes and livelihoods, improve food security, and reduce disease and environmental degradation. Australian animal scientist and Nobel Prize laureate Peter Doherty serves as ILRI’s patron. Organizations that fund ILRI through their contributions to CGIAR make ILRI’s work possible. Organizations that partner ILRI in its mission make livestock research for development a reality. www.ilri.org This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence. THANK YOU
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