Workshop Trade-off Analysis - CGIAR_19 Feb 2013_Keynote Pablo Tittonell
Jeroen Groot, 26 March 2012Quantitative trade-offs analysisin agricultural systems Fields, farms and territoriesPablo TittonellFarming Systems Ecology – Wageningen University, The NetherlandsPablo.email@example.com/FSE.WageningenUR Analysis of Trade-offs in Agricultural Systems Wageningen 19 February 2013
Outline 1. What are trade-offs? 2. How to quantify them? 3. Examples i. Measurements and data ii. Output of a dynamic household model iii. Pareto optimisation through evolutionary design iv. Inverse dynamic modelling (global search alg.) v. Agent-based systems and games
What are trade-offs? Situations in which two or more competing/ conflicting objectives must be simultaneously satisfied to a certain degree Objective B B1” Complementarity B1 Substitution B1’ Objective A A1Tittonell (2013) Chapter on Trade-offs evaluation, CIALCA Conf., Earthscan, in press.
Tradeoffs analysis Objective B B1 A1 A2 A3 Objective A
Services écosystemiques: biodiversité et séquestration de C A Vihiga B Siaya Aboveground C stock (Mg ha-1) 40 40 homegarden annual crop permanent crop 30 30 pasture A) Trees 20 B) Hedgerows 20 40 20 Delta C stock (Mg farm-1) Vihiga 10 Vihiga 10 Siaya l Siaya ntia 30 p ote 0 15 0 tion 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 stra que C-se C 10 Vihiga D Siaya C-sequestration potential 20 Aboveground C density (kg m-2) 8 8 Windrow Individual tree Woodlot 6 6 10 5 4 4 0 0 0 5 10 15 2 20 0 5 10 2 15 20 it wt Current aboveground C stock (Mg farm-1) 0 0 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 g Homegarden index Shannon b lh Food crop hh wlt mh Pasture t e Cash crop Slop Woodlot Henry et al. (2009), Agriculture Ecosystems and Environment 129
Quantifying trade-offs Absolute change Relative change ΔB” ΔB” ΔB’ < ΔB’ ΔA ΔA B0” B0’ Objective B < ΔA ΔA B1”- B0” < B1’- B0’ A0 A0 B0” ΔA ΔA ΔB” B1” Complementarity B0’ ΔB’ Substitution B1’ Objective A A0 A1 ΔA Opportunity costs, shadow prices, payment for environmental services, etc.Tittonell (2013) Chapter on Trade-offs evaluation,relative sensitivity, preference Elasticity of substitution, partial CIALCA Conf., Earthscan, in press. rate, etc.
Mapping trade-offsObjective: 400 Alternative IIncrease 350incomes 300 Alternative II Gross margin ($ ha-1) 250 Complementarity Alternative III 200 Current 150 100 Substitution 50 Alternative IV 0 20 25 30 35 40 45 Objective: Maintain soil Soil organic matter (t ha-1) Modelling: fertility • To generate ‘clouds’ of alternative solutions • To delineate ‘frontiers’ of possibilities Management strategies Objective Indicator Current Alternative I Alternative II To maintain Soil organic matter (t ha-1) 40 28 36 soil fertility To increase Gross margin ($ ha-1) 180 360 280 net incomes Cost of maintaining soil C: 15 $ t-1 25 $ t-1Tittonell (2013) Chapter on Trade-offs evaluation, CIALCA Conf., Earthscan, in press.
Quantitative trade-offs analysis: methods 1. Ad-hoc analysis 1.1 - By looking at data 1.2 - By formalising a problem (discussion, expert knowledge, etc.) 1.3 - By looking at the output of a dynamic model 2. Multi-objective ‘compromising’ using models 2.1 - Using optimisation models (e.g., linear programming) 2.2 - Using search algorithms (e.g., inverse modelling) 2.3 – Agent based-systemsTittonell (2013) Chapter on Trade-offs evaluation, CIALCA Conf., Earthscan, in press.
(v) Agent-based systemsMulti-scale –trade-offs around crop residue biomass herd A village territory representation of the multi-agent modeltypes, communal Figure 2 Schematic of 100 Km2, 4 farmuse in the Zambezi valley Results at village scale Baudron, Delmotte, Herrera, Corbeels, Tittonell 5.5 0 Average change of total soil organic carbon 5 0 kg N ha-1 (a)Intensification through conservation agriculture to preserve habitats and biodiversity -2 0 kg N ha-1 (b) 4.5 20 kg N ha-1 20 kg N ha-1 -4 Average mulch cover (t ha-1) 4 100 kg N ha-1 100 kg N ha-1 in the 0-20 cm ( t ha-1) -6 3.5 3 -8 2.5 -10 2 -12 1.5 -14 1 0.5 -16 0 -18 0 100 200 300 400 0 100 200 300 400 Cattle density (head km-2) Cattle density (heads km-2)
Simulation and gaming - Mexico Mapa de la Reserva de la Biosfera de la Sepultura. Fuente: CONANPSimulation and gaming for improving local adaptive capacity; The case of a buffer-zone community in Mexico E.N. Speelman (2008-2013) Supervisory team J.C.J. Groot, L.E. Garcia-Barrios, P. Tittonell
A methodological framework Landscapes COMPASSAttic LandscapeIMAGES ActorIMAGES Agro-ecosystem diversity, Trajectories and Trade-offs for Intensification of Cereal-based systems Economic Spatial Land use results coherence systems Farms Nutrient Landscape Collective losses metrics decisions Diego Valbuena (WUR) Bruno Gerard (CIMMYT) Nutrient Jeroen Groot (WUR) Water Feed FarmIMAGES balance balance balanceFields, landscape elements Santiago Lopez Ridaura (CIMMYT) FarmDESIGN FarmSTEPS Labor balance Fred Baudron (CIMMYT) Economic results Nutrient losses FarmDANCES Andy McDonald (CIMMYT) Tim Krupnik (CIMMYT) Felix Bianchi (WUR) Katrien Descheemaker (WUR) Nutrient Organic Soil Water FieldIMAGES Pablo Tittonell (WUR) balance matter erosion balance NDICEA Crop yield Nutrient Nutrient Plant RotSOM ROTAT 3 PhD started in 2013 uptake losses diversity A Cimmyt-Wageningen collaboration in the context ofSimulation – Groot and Wheat Co-innovation and Modeling Platform for Agro-ecoSystem the CRP Maize et al., 2012
Summary Trade-offs: situations in which two or more competing/ conflicting objectives must be simultaneously satisfied to a certain degree Quantifying slopes, opportunity costs or substitution rates not always enough – models can be used to map-out tradeoffs, to explore a wider range of options and possibility frontiers Model-aided trade-offs analysis: 1. Dynamic household models (no formal optimisation) 2. Optimisation through linear programming 3. Pareto optimisation through evolutionary algorithms 4. Agent-based systems How to scale? Models typically work for single ‘representative’ farms; typologies, distribution of farm population, etc. How to choose? Objective algortithms can always be calculated, but they cannot replace the insihgt to be gained by involving the actor; combinations of both aproaches are possible
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