Agroforestry Options in Northwest Vietnam · 2018-09-12 · Agroforestry Options in Northwest...
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Agroforestry Options in Northwest Vietnam Hoa Do 1 , Cory Whitney 2,3 , Eike Luedeling 3 Land degradation and subsequent crop yield decline are the main causes of poverty and food insecurity. These are major livelihood challenges in the mountainous areas of northwestern Vietnam, home to many of the country’s ethnic minority groups. • The most likely risks are extreme climate events such as drought, hot westerly wind and frost. • Agroforestry interventions generate higher profits compared to monocultures in all model results. • The most important uncertainties are discount rate, yields of fruit, coffee, macadamia and tea, as well as prices of crops. • High initial investment and long payback periods are the main challenges that prevent local farmers from adopting agroforestry. Probability assessment Model development Simulation and sensitivity assessments Refine model Participatory Expert calibration Consistency Personal judgments Probability distributions Uncertainty Monte Carlo simulation Probability distributions Added information Decision Analysis process applied in Northwestern Vietnam: rectangles represent the main stages of model development • Identify the main costs, benefits and risks of ICRAF’s seven agroforestry interventions. • Develop a conceptual cost-benefit model that includes risk factors involved in these interventions. • Estimate confidence intervals for the net economic benefits of these interventions. 1 University of Bonn, Agricultural Sciences and Resource Management in the Tropics and Sub-tropics (ARTS), Germany, 2 University of Bonn, Center for Development Research (ZEF), Germany, 3 University of Bonn, Horticultural Sciences, Germany Model output distributions of net present value over 20 years for seven agroforestry interventions and maize monoculture system as control. The calculation was estimated for one hectare of land. Conceptual model of costs, benefits and risk factors of agroforestry options. Green boxes represent estimated variables, red boxes represent simulated variables. “Tree” indicates Shan tea, sontra, longan, mango, plum and macadamia. Decision analysis is an approach that aims to assist in decision making under risk and uncertainty. Decision analysis … • can address uncertainty and provide cost-effective basic assessments • incorporates multiple sources of information including expert knowledge • aims to consider all risks and uncertainty • uses probabilistic methods to handle uncertain inputs and represent uncertainty in the form of ranges or probability distributions (Luedeling et al. 2015, Luedeling & Shepherd 2016) We used participatory methods to create conceptual cost-benefit models of ICRAF’s agroforestry interventions and coded these models in the R programming language (R Core Team, 2017). We predicted intervention outcomes using Monte Carlo simulation functions from the decisionSupport package (Luedeling and Goehring, 2017). Agroforestry interventions Decision Analysis Study objectives Key findings Map of study regions in Northwest Vietnam The World Agroforestry Centre (ICRAF) has trialed seven agroforestry interventions in the region. We use decision analysis methods to produce assessments of their long-term performance considering all inherent risks and uncertainties. Results The seven agroforestry interventions were categorized into three groups. Method References 1. Luedeling E, Shepherd K, 2016. Solutions 7(5), 46-54. 2. Luedeling E, Oord AL, Kiteme B, Ogalleh S, Malesu M, Shepherd KD and De Leeuw J, 2015. Frontiers in Environmental Science 3, article 16, 1-18. 3. Luedeling E, Goehring L, 2017. R package version 1.103.6. 4. R Core Team, 2017. R Foundation for Statistical Computing. Shan tea-forage Sontra-forage Acacia-mango-maize-forage Longan-maize-forage Acacia-longan-coffee-annual crop-forage Teak-plum-coffee-annual crop-forage Macadamia-coffee-annual crop Selection criteria Guiding principles Methodologies Modelling tool Model output Maize-based systems Simple systems Tree yield Coffee yield Grass biomass Revenue Timber yield Net present value Establishment costs Discount rate Agroforestry intervention Coffee risks Maintenance costs Monoculture benefit Annual crop Total costs Tree risks Timber risks Maize risks Maize yield Crop prices Soil loss prevention Coffee-based systems Willingness Identification of experts Expertise Experiences Engagement
Transcript of Agroforestry Options in Northwest Vietnam · 2018-09-12 · Agroforestry Options in Northwest...
Agroforestry Options in Northwest VietnamHoa Do1, Cory Whitney2,3, Eike Luedeling 3
Land degradation and subsequent crop yield decline are the main causes of poverty and food insecurity. These are major livelihood challenges in the mountainous areas of northwestern Vietnam, home to many of the country’s ethnic minority groups.
• The most likely risks are extreme climate events such as drought, hot westerly wind and frost.
• Agroforestry interventions generate higher profits compared to monocultures in all model results.
• The most important uncertainties are discount rate, yields of fruit, coffee, macadamia and tea, as well as prices of crops.
• High initial investment and long payback periods are the main challenges that prevent local farmers from adopting agroforestry.
Probability assessment
Modeldevelopment
Simulation and sensitivity assessments
Refine model
Participatory
Expert calibration
Consistency
Personal judgments
Probability distributions
Uncertainty
Monte Carlosimulation
Probability distributions
Ad
de
d in
form
atio
n
Decision Analysis process applied in Northwestern Vietnam: rectangles represent the main stages of model development
• Identify the main costs, benefits and risks of ICRAF’s seven agroforestry interventions.
• Develop a conceptual cost-benefit model that includes risk factors involved in these interventions.
• Estimate confidence intervals for the net economic benefits of these interventions.
1University of Bonn, Agricultural Sciences and Resource Management in the Tropics and Sub-tropics (ARTS), Germany, 2University of Bonn, Center for Development Research (ZEF), Germany, 3University of Bonn, Horticultural Sciences, Germany
Model output distributions of net present value over 20 years for seven agroforestry interventions and maize monoculture system as control. The calculation was estimated for one hectare of land.
Conceptual model of costs, benefits and risk factors of agroforestry options. Green boxes represent estimated variables, red boxes represent simulated variables. “Tree” indicates Shan tea, sontra, longan, mango, plum and macadamia.
Decision analysis is an approach that aims to assist in decision makingunder risk and uncertainty. Decision analysis …• can address uncertainty and provide cost-effective basic assessments• incorporates multiple sources of information including expert knowledge• aims to consider all risks and uncertainty• uses probabilistic methods to handle uncertain inputs and represent
uncertainty in the form of ranges or probability distributions (Luedelinget al. 2015, Luedeling & Shepherd 2016)
We used participatory methods to create conceptual cost-benefit models of ICRAF’s agroforestry interventions and coded these models in the R programming language (R Core Team, 2017). We predicted intervention outcomes using Monte Carlo simulation functions from the decisionSupportpackage (Luedeling and Goehring, 2017).
Agroforestry interventions
Decision Analysis
Study objectives
Key findings
Map of study regions in Northwest Vietnam
The World Agroforestry Centre (ICRAF) has trialed seven agroforestry interventions in the region.
We use decision analysis methods to produce assessments of their long-term performance considering all inherent risks and uncertainties.
Results
The seven agroforestry interventions were categorized into three groups.
Method
References1. Luedeling E, Shepherd K, 2016. Solutions 7(5), 46-54.2. Luedeling E, Oord AL, Kiteme B, Ogalleh S, Malesu M, Shepherd KD and De Leeuw J, 2015.
Frontiers in Environmental Science 3, article 16, 1-18.3. Luedeling E, Goehring L, 2017. R package version 1.103.6.4. R Core Team, 2017. R Foundation for Statistical Computing.
Shan tea-forage Sontra-forage
Acacia-mango-maize-forage Longan-maize-forage
Acacia-longan-coffee-annual crop-forage Teak-plum-coffee-annual crop-forage Macadamia-coffee-annual crop
Selection criteria
Guiding principles
Methodologies
Modelling tool Model output
Maize-based systemsSimple systems
Tree yield
Coffee yield
Grass biomass
Revenue
Timber yield
Net present value
Establishment costs
Discount rate
Agroforestry intervention
Coffee risks
Maintenance costs
Monoculture benefit
Annual crop
Total costs
Tree risks
Timber risks
Maize risks Maize yieldCrop prices
Soil loss prevention
Coffee-based systemsWillingnessIdentification
of experts Expertise Experiences
Engagement
