Analysis of Trade-Offs in Agricultural Systems

Lotte Klapwijk19 February 2013

Methods and their strengths and weaknesses

Content

• Introduction• History of Trade-Off Analysis • Definition• Methods for Trade-Off Analysis• Strengths + weaknesses• Conclusion

Introduction

• Mission: “Reduce poverty and hunger, improve human health and nutrition, and enhance ecosystem resilience”

• Holistic view• Sustainability assessment• System Thinking• Trade-off Analysis…

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Scopus-search: 'Trade-off Analysis'

Year

Occure

nces

… is very “hot”

History

• Some examples:– de Wit, van Keulen, Seligman and Spharim

(1988)– Rabbinge and van Latesteijn (1992)– Stoorvogel, Antle and Crissman (2004)– Laborte, Van Ittersum and Van den Berg

(2007) – Naudin et al. (2012)

Laborte et al., 2007

The different scales of analysis

Average-IR

Better-off

Average-RF

Poor

Farm types

Municipality

Province

Farm

Provincial explorations

Optimization Rice production Farmers’ income

Without water-sharing Rice Production (103 t) 507 221 Farmers’ income (109 P) 6 50 Biocide use (t) 121 192 With water-sharing Rice Production (103 t) 726 273 Farmers’ income (109 P) 6 58 Biocide use (t) 160 251

Naudin et al., 2012

Science / Research

• Tasks– Analysis and charecterisation of

agricultural systems– Design of agricultural systems /

scenarios– Ex-ante integrated assessment of

scenarios and policies

• Integrated assessment of sustainability

Tackling a (TO) research question:

• Define the problem + objective• Describe components + indicators• Set boundaries / focus• Describe assumptions• Set goals (multiple optimization)

EXPERIMENTAL

PARTICIPATORY

MODELING

Quantitative

Qualitative

Trade-offs

• Definition Trade-off: “An exchange that occurs as a compromise”

• One more example: MSc thesis on viability of ‘One-cow-per-poor-family’-program, Rwanda

Trade-Off Analysis:

I. QualitativeII. Empirical or experimentalIII. SimulationIV. Optimization

I. Qualitative

• Participatory methods: fuzzy cognitive mapping, resource flow mapping, games, role-playing, etc.

• Companion modeling• “People are part of farming systems

and their views cannot be ignored” (Lawrence, 2011)

II. Empirical-experimental

• Frontier analysis• Data Envelopment Analysis• Randomized controlled trial

Modeling

• Model = simplified representation of reality

• Goal: to show processes, structure and/or function of a system

• Qualitative or quantitative• Simulation or optimization• Descriptive or explanatory• Static or dynamic

III. Simulation

• Bio-Economic Farm Models • APSIM• Midas• CLUE-model• FarmSIM• …

III. Simulation

• Trade-off Analysis model (Stoorvogel et al., 2004)

IV. Optimization

• Multiple Goal Linear Programming• Inverse modeling

– Pareto optimality

• FSSIM

SWOT of methods

• Advantages & disadvantages– Qualitative vs. quantitative– Based on expert knowledge, empirical data

and/or theory and process knowledge– Which objectives/indicators can be

accounted for?– Data demand– Pareto-optimality– Stakeholder involvement

Conclusion

….?

Acknowledgements

• Martin van Ittersum, PPS• Ken Giller, PPS (and the whole chair group)• Phil Thornton, CCAFS• Piet van Asten, IITA• Everyone interviewed within Wageningen

University as well as the CGIAR

Questions? Remarks?

Thank you for your attention!

One for you:Who’s interested to help me with a publication?

Quantitative QualitativeModelingScale

Farm level

Landscape + Watershed level

Regional + Global level

FarmSIMFarmDESIGNMGLPAPSIM…

Bio-economic (BEFM)Inverse modeling-method(DYNBAL + MOSCEM)Pareto-optimalFarm System Simulator (FFSIM)MIDAS (?)CLUE model

Participatory:- Companion modeling(agent-based)- Interviews- Plenary discussion- Games / role-playing- Resource flow mapping- Feedback workshop- Rural appraisal (?)- PIPA (Douthwaite, 2007

ExperimentsMeasurementsSurveys

Trade-Off Analysis model

Multiple criteria analysis

DEED.SMARTDfID.

Experiments (NUANCES)

Multi-objective optimization

Achieving impact = next phase, separated.Communication: radio.

And where goes semi-quantitative...

Trade-off level

APPROACH:

Experiments MGLP BEFM Inverse modeling (MOSCEM)

TOA-(MD)

Farm

Landscape + Watershed

Regional + Global

Quantitative QualitativeModelingScale

FarmSIMFarmDESIGN…

Bio-economic (BEFM)Inverse modeling-method(DYNBAL + MOSCEM)Pareto-optimalFarm System Simulator (FFSIM)

Participatory:- Interviews- Games

MeasurementsExperiments

Trade-Off Analysis model

“FRAMEWORK”

Farm level

Landscape + Watershed level

Regional + Global level