Tradeoff Analysis and Minimum-Data Modeling John Antle Jetse Stoorvogel Workshop on Adaptation to Climate Change, Nairobi September

The challenge: policy-relevant assessment of agricultural sustainability How to quantify concept of sustainability to support informed policy decision making? Identify stakeholder priorities (indicators) and strategies (scenarios) Understand how indicators respond to changes in the system (tradeoffs and win-wins)

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenarios

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenarios Identify key sustainability indicators and tradeoffs Identify technology and policy scenarios

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenariosCoordinated Disciplinary Research

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenariosCoordinated Disciplinary Research Identify key disciplines in research team Define spatial and temporal scales of analysis for disciplinary integration and policy analysis

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenariosCoordinated Disciplinary Research Communicate results to stakeholders

The Challenge: Support informed decision making The Approach: Tradeoff Analysis Public stakeholders Policy makers Scientists Indicators, tradeoffs and scenariosCoordinated Disciplinary Research Communicate results to stakeholders A participatory process, not a model

Implementing the TOA Approach: the TOA Software A modular approach to integrate spatial data and disciplinary models to simulate agricultural systems on a site-specific basis and aggregate to a level relevant for policy analysis.

Farm Income Health & Environment Tradeoff Analysis: assessing technology & policy options Tradeoff curves: feasible combinations of sustainability indicators Technology and policy scenarios: using data and modeling tools to explore options and find win-win solutions. People may choose to trade off income for health or environmental quality, or vice-versa! Why not do BCA?

Example: Using TOA for analysis of CC mitigation, impacts & adaptation in Machakos, Kenya ( Antle & Stoorvogel, Env & Dev Econ 2008 ) climate models: data and downscaling of IPCC scenarios w/wo aerosols crop and livestock models: suitability for CC analysis of impacts & adaptation economic data and models: adaptation through changes in land use, management environmental process models

semi-subsistence farming system, maize, vegetables, subsistence crops & livestock serious soil nutrient & SOM depletion more than 60% of households below poverty line ($1/day/person)

The Machakos case study

The critical role of spatial heterogeneity

Main issues Population pressure

Main issues Population pressure Land degradation

Main issues Population pressure Land degradation Climate (drought) Low farm incomes Low farm productivity Low soil fertility

Climate change, poverty and nutrient depletion with maize price scenario

Climate change, poverty and nutrient depletion with vegetable price scenario

Vegetable prices with irrigation investment

Spatial distribution of poverty (poverty mapping)

Towards the Minimum-Data Approach TOA is one way to quantify the concept of agricultural sustainability but data requirements are very high, models are complex for some questions (e.g., technology adoption, ecosystem services) we can use simpler models with lower data requirements to obtain a first-order estimate of economic feasibility of new technologies

Comparison of EP and MD models: Carbon contract participation in Machakos, Kenya Case Study (Full model = 700 parms, MD = 75)

Plan for the Rest of the Workshop Systems modeling: the Machakos case Minimum-Data modeling: economics Minimum-Data modeling: bio-physical Minimum-Data software Exercises Improved maize variety Climate change impacts Sweet potato adoption Adaptation to climate change Project planning