Integrated Regional Assessment of Agricultural Systems:

Lessons from AgMIP and REACCH

John M. AntleProfessor of Applied Economics

Oregon State UniversityAgMIP Co-PI and Regional Economics Leader

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Presented at Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models forSustainable Food, Energy, and Water Systems, Iowa State University, Oct 12-13 2015

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Agricultural Model Inter-comparison and Improvement Project (AgMIP.org)

A new global community of science: climate, water, soils, crops & livestock, economics, pests & diseases◦ More than 700 participating scientists◦ Collaborating & supporting institutions

include: ◦ USDA Agricultural Research Service ◦ UKAID (DFID)◦ NASA◦ USAID◦ Bill and Melinda Gates Foundation ◦ National and international agricultural

research centers and programs

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AgMIP Regional Climate Change Impact Assessment Teams 5-year project, DFID funded

8 regional teams, 18 countries, ≈ 200 scientistsData, models, scenarios designed & implemented by multi-disciplinary teams & stakeholders

Small-scale, mixed crop and crop-livestock systems; principal crops vary by region (maize, millet/peanut, rice, wheat) typical of “semi-subsistence agriculture”

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REACCH - Regional Approaches to Climate Change in Pacific Northwest Agriculture

5-year project funded by USDA-NIFAUniversity of IdahoOregon State UniversityWashington State UniversityUSDA-ARS+ 100 scientists & students

Large-scale wheat-fallow and annual cropped systems typical of “industrial commodity agriculture”

Our stakeholders: we know the climate is changing, so what can we do? Is our modeling useful?

Eastern Uganda

Northwest USA

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Integrated Assessment: one scale, multiple disciplines

General Circulation Models

Bio-physical Models

Economic Models

TempPrecip…

YieldWater…

ProductionConsumptionFood Security…

Representative Concentration Pathways

Bio-Physical and Socio-Economic Pathways and

Scenarios System Adaptations

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Global-Regional Integrated Assessment: multiple scales and disciplines – high complexity

RCP

GCM

Global gridded T, P

Global IAM

GDP, PopMacro, Trade & Climate Policy

Global Socio-economic

Pathway

Global RAP

Ag productivity, Cost, Ag Policy

Global PSM & AEM

Regional RAP

Prices, Income, Land Use, Biodiversity

Ag Prices, Yields, Land & Water

Use, GHGs

Farm size, input cost, soil & water, climate

variability

Regional PSM & AEM

Farm production & income, poverty, GHGs

food security

Bio-physical processes (water)

RCM/ Climate downscaling

Water

Bio-physical processes (soil, pests)

Soil, Pests

Regional/down-scaled T, P

Valdivia, R.O., J.M. Antle, C. Rosenzweig, A.C. Ruane, J. Vervoort, M. Ashfaq, I. Hathie, S. Homann-Kee Tui, R. Mulwa, C. Nhemachena, P. Ponnusamy, H. Rasnayaka and H. Singh. (2015). Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impact, Vulnerability and Adaptation. C. Rosenzweig and D. Hillel, eds. Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project Integrated Crop and Economic Assessments, Part 1. London: Imperial College Press.

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Impact, Adaptation & Vulnerability of Ag Systems: AgMIP Regional IA Methods (http://www.agmip.org/regional-integrated-assessments-handbook/#)

Antle, J. M., R.O. Valdivia, K.J. Boote, S. Janssen, J.W. Jones, C.H. Porter, C. Rosenzweig, A.C. Ruane, and P.J. Thorburn. (2015). AgMIP’s Trans-disciplinary Agricultural Systems Approach to Regional Integrated Assessment of Climate Impact, Vulnerability and Adaptation. C. Rosenzweig and D. Hillel, eds. Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project Integrated Crop and Economic Assessments, Part 1. London: Imperial College Press.

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Lessons: 1

Need models of HETEROGENEOUS SYSTEMS, not only LU or AGGREGATE COMMODITY market models E.g., in US ag census data approximately 80% of variation is

within-county, 20% is between-county Methods to link ag systems to market models

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Relative yield distributions: heterogeneity and uncertainty…

Source: Author and collaborators, REACCH-PNA Project

05

1015

Den

sity

.9 1 1.1 1.2 1.3 1.4

GCM 1

02

46

810

Den

sity

.6 .8 1 1.2 1.4

GCM 2

1.5 - 1.61.4 - 1.51.3 - 1.41.2 - 1.31.1 - 1.21 - 1.1.9 - 1.8 - .9.7 - .8

GCM 1

1.5 - 1.61.4 - 1.51.3 - 1.41.2 - 1.31.1 - 1.21 - 1.1.9 - 1.8 - .9.7 - .8

GCM 2

1.5 - 1.61.4 - 1.51.3 - 1.41.2 - 1.31.1 - 1.21 - 1.1.9 - 1.8 - .9.7 - .8

GCM 9

1.5 - 1.61.4 - 1.51.3 - 1.41.2 - 1.31.1 - 1.21 - 1.1.9 - 1.8 - .9.7 - .8

GCM 10

02

46

8D

ensi

ty

.6 .8 1 1.2 1.4

GCM 9

02

46

8D

ensi

ty

.6 .8 1 1.2 1.4

GCM 10

(Using Conventional Tillage)Relative Yields of Spring Pea Projected in 2050 at RCP 8.5

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Lessons: 2 Need models and data capable of estimating well-defined counterfactuals and treatment effects of environmental change, policy, and other drivers of change Impact indicator: V[technology, climate, state of world] H = historical conditions, F = future conditions,

V[H,H,t]

Technology

Clim

ate

V[H,F,t]

V[F,H,t]

V[F,F,t]

Antle, J.M. and C.O. Stöckle. 2015. Perspectives on climate impacts on crops from agronomic-economic analysis. Paper prepared for the symposium on impacts of climate change on agriculture in the Review of Environmental Economics and Policy.

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Treatment effects relevant to science & policy stakeholderso Distinguish climate impact versus “adaptation” in historical, future

conditions o Reduced-form econometric, LU models only represent climate impact

+ adaptation in current (historical) world o “Hybrid structural models” that satisfy “Marshak’s Maxim” can

estimate all relevant treatment effectso Need methods for future scenarios (beyond “Shared socio-economic

pathways” to ag & region-specific)

V[H,H,t]

Technology

Clim

ate

V[H,F,t]

V[F,H,t]

V[F,F,t]

Antle, J.M. and C.O. Stöckle. 2015. Perspectives on climate impacts on crops from agronomic-economic analysis. Paper prepared for the symposium on impacts of climate change on agriculture in the Review of Environmental Economics and Policy.

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Example: estimating the counterfactual for “out-of-sample” test of a hybrid model: adoption of annual cropping in the wheat-fallow region

(CropSyst and TOA-MD models)0

.01

.02

.03

.04

Den

sity

0 20 40 60 80 100

Simulated Winter Wheat Yield in 2007

Winter Wheat-Summer Fallow System Annual Crop System

0.0

5.1

.15

Frac

tion

.5 .6 .7 .8 .9

Relative Yield

-150

-100

-50

0

50

100

0 10 20 30 40 50 60 70 80 90 100

Retu

rns p

er F

arm

($)

MTE ATE ATT ATU

Antle and Stockle, 2015 REEP (in review)

Predicted adoption of annual cropping in wheat-fallow area = 20%actual adoption rate = 23%

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Lessons: 3

AgMIP: need PROTOCOL-BASED approach for model inter-comparison & improvement for transparency, reproducibility in integrated assessmentaddressing SCENARIO and MODEL UNCERTAINTY to evaluate out-of-sample predictionsmultiple models and model ensembles: ONE BIG MODEL IS

NOT THE ANSWER (see CMIP … ) But …. how do you do multi-disciplinary, multi-scale ensembles?

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AgMIP modeling teams: model inter-comparison to understand & reduce uncertainty in crop models

Asseng, S. et al. Uncertainty in Simulating Wheat Yields Under Climate Change. Nature Climate Change 2013.

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AgMIP global modeling team: economic model and scenario uncertainty (what about regional economic models?)

Projected Changes in Commodity Prices in 2050 without Climate Change WHT = wheat, CGR = coarse grains, RIC = rice, OSD = oil seeds, RUM = ruminant animal products

Projections from 9 models, multiple scenarios, no CO2 effects on crops (Nelson et al. PNAS 2014).

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Lessons: 4 To evaluate well-being we need to model FOOD SYSTEMS IPCC AR5, forthcoming USDA assessment report on CC & global

food security beyond food security to health, nutrition

Source: IPCC AR-5, WGII, Ch 7.

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Lessons: 5 Need NextGen data, models and knowledge products

AgMIP NextGen study http://www.agmip.org/blog/2015/04/08/laying-the-groundwork-for-the-next-generation-of-agricultural-system-models/user access to model products: e.g., dashboards, visualizationopen source, modular, inter-operable model componentsnew ICT tools & data systems

Antle, Capalbo and Houston, “Tapping Big Data…”Choices Sept 2015

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Conclusion: lots to do!

Thanks for your attention…

Antle, Capalbo and Houston, “Tapping Big Data…”Choices Sept 2015