CloseCoupling of Ecosystem and Economic Models: Adaptation of Central US Agriculture to Climate Chan

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Close-Coupling of Ecosystem and Economic Models
Adaptation of Central US Agriculture to Climate
Change John Antle, Susan Capalbo, Siân Mooney
Montana State University William Hunt, Keith
Paustian Colorado State University Edward
Elliot University of Nebraska
Montana State University Program on
Climate Change and Greenhouse Gas Mitigation
www.climate.montana.edu
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General Objective To significantly advance the
state of the art in modeling impacts of climate
change in agroecosystems, by moving beyond the
loose coupling of unrelated and independent
disciplinary models.
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Specific Objectives 1. Methods to more closely
couple existing ecological and economic models.
Approach Link processes in ecological models
with land use and input use decisions in economic
models, so that the type and strength of feedback
between ecological and economic processes is
suitably represented.
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Source Antle, Capalbo, Elliott, Hunt, Mooney and
Paustian, Research Needs for Understanding and
Predicting the Behavior of Managed Ecosystems
Lessons from the Study of Agroecosystems,
Ecosystems, 2001.
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Integrated assessment of climate change impacts
in an agricultural production system using
coupled Century and econometric-process
simulation models.
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• Specific Objectives
• Simulate the ecological and economic impacts of
  climate change on agriculture in the central
  U.S., using data at various scales.
• Approach
• Derive climate scenarios from historical climate
  data and from the results of GCMs that have been
  appropriately down-scaled.
• Develop climate data sets to conduct analysis of
  sensitivity to changes in mean temperature and
  precipitation changes, and changes in
  variability.
• Data for ecosystem model (Century) derived from
  existing soils, land use history, yield, other
  data.
• Economic data derived from farm-level surveys
  and secondary data (agriculture census, etc).

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Specific Objectives 3. Investigate the dynamic
and spatial properties of agricultural
ecosystems how are estimates of climate change
impacts affected by the choice of spatial scale,
temporal scale, and degree of model
coupling? Approach Conduct sensitivity analysis
for a matrix of assumptions
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• Accomplishments to Date
• Assembly of bio-physical and economic data.
• Development of econometric-process simulation
  model based on county-scale data.
• Development of methods for closer coupling of
  ecosystem and economic models.
• Analysis of fractal properties of farm and
  county-scale data.
• Testing for chaos in county-scale time-series
  data.
• Development of methods to assess vulnerability to
  climate change and effects of adaptation,
  application to Montana models.
• Focus on 6 in this presentation.

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Accomplishments to Date (cont.) 7. Publications
Antle, J.M., S.M. Capalbo, E.T. Elliott, H.W.
Hunt, S. Mooney, and K.H. Paustian. (2000).
Research Needs for Understanding and Predicting
the Behavior of Managed Ecosystems Lessons from
the Study of Agroecosystems. Ecosystems.December
2001. Antle, J.M. and S.M. Capalbo, Agriculture
as a Managed Ecosystem Implications for
Econometric Analysis of Production Risk. R.E.
Just and R.D. Pope, eds, A Comprehensive
Assessment of Risk in U.S. Agriculture, Kluwer,
2002. Antle, J.M. and S.M. Capalbo, Agriculutre
as a Managed Ecosystem Policy Implications.
Journal of Agricultural and Resource Economics in
press 2002. Antle, J.M., S.M. Capalbo, E.
Elliott, and K. Paustian, Adaptation, Spatial
Heterogeneity, and the Vulnerability of
Agricultural Systems to Climate Change An
Integrated Assessment Approach. Draft ms.
Prepared for submission to to Climatic Change,
January 2002. .
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Preliminary Results Vulnerability and
Adaptation The IPCC identifies the development of
methods to link climate change science to policy
decision-making as a high priority for research
(IPCC 2001, section 5), and concludes
that greater emphasis on the development of
methods for assessing vulnerability is required,
especially at national and sub-national scales
where impacts of climate change are felt and
responses are implemented. Methods designed to
include adaptation and adaptive capacity
explicitly in specific applications must be
developed. (IPCC, 2001, p. 22)
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• Preliminary Results Vulnerability and Adaptation
• Following the IPCC recommendation, we have
• Developed measures of vulnerability to climate
  change that account for both adaptation and
  spatial heterogeneity.
• Used the loosely coupled modeling approach to
  implement these measures, taking into account
  adaptation and spatial heterogeneity, in specific
  applications (Montana done, will do Nebraska and
  central U.S. region)
• We will use these measures of vulnerability in
  our assessments of spatial scale and coupling on
  estimates of climate change impacts.

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Economic analysis of vulnerability and adaptation
to climate change.
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Montana Sub-MLRAs Used in Climate Change Study.
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Yield changes predicted by the Century model for
a climate change scenario.
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Yield changes predicted by the Century model for
a 2xCO2 Scenario.
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Mean net returns for the climate change scenario,
by Montana sub-MLRA.
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Production system utilization for sub-MLRA
52-high.
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• Preliminary Results Vulnerability and Adaptation
• Hypotheses
• those with the least resources have the least
  capacity to adapt and are the most vulnerable
  (IPCC, 2001, p. 7).
• adaptation has the potential to reduce adverse
  impacts of climate change and to enhance
  beneficial impacts, but will incur costs and will
  not prevent all damages and the ability of
  human systems to adapt to climate change depends
  upon such factors as wealth, technology,
  education, infrastructure, access to resources,
  and management capabilities (IPCC 2001, pp.
  7-8).

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Mean versus coefficient of variation of net
returns, by sub-MLRA, for climate change (CC) and
CO2 fertilization scenarios with (A) and without
(N) adaptation. Confirms hypothesis that poorer
endowments are associated with higher risk and
that adaptation mitigates climate risk.
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Mean versus coefficient of variation of net
returns, by sub-MLRA, for climate change (CC) and
CO2 fertilization scenarios with (A) and without
(N) adaptation. Confirms hypothesis that poorer
endowments are associated with higher risk and
that adaptation mitigates climate risk.
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Mean versus coefficient of variation of net
returns, by sub-MLRA, for climate change (CC) and
CO2 fertilization scenarios with (A) and without
(N) adaptation. Confirms hypothesis that poorer
endowments are associated with higher risk and
that adaptation mitigates climate risk.
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Mean versus coefficient of variation of net
returns, by sub-MLRA, for climate change (CC) and
CO2 fertilization scenarios with (A) and without
(N) adaptation. Confirms hypothesis that poorer
endowments are associated with higher risk and
that adaptation mitigates climate risk.
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Relative mean climate vulnerability no
adaptation (RCVN), by Montana sub-MLRA, for low,
medium, and high price scenario Rejects
hypothesis that relative vulnerability is
necessarily associated with poorer endowments,
confirms importance of sensitivity analysis to
economic assumptions.
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Relative mean climate vulnerability adaptation
(RCVA), by Montana sub-MLRA, for low, medium, and
high price scenario Rejects hypothesis that
relative vulnerability is necessarily associated
with poorer endowments, confirms importance of
sensitivity analysis to adaptation.
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Relative threshold climate vulnerability (RTCV),
with (A) and without (N) adaptation, for low,
medium, and high price scenario. Rejects
hypothesis that relative threshold vulnerability
is associated with poorer endowments, confirms
importance of sensitivity analysis.
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Absolute threshold climate vulnerability (ATCV),
with (A) and without (N) adaptation, for low,
medium, and high price scenario. Confirms
hypothesis that absolute threshold vulnerability
is associated with poorer endowments, confirms
importance of sensitivity analysis.
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• Summary of Findings on Adaptation and
  Vulnerability
• Results support the hypothesis that the most
  adverse changes occur in the areas with the
  poorest resource endowments and when mitigating
  effects of CO2 fertilization or adaptation are
  absent.
• Vulnerability of agriculture to climate change
  depends on how it is measured (in relative versus
  absolute terms, and with respect to a threshold),
  and it also depends on complex interactions
  between climate change, CO2 fertilization,
  adaptation, and economic conditions such as
  relative output prices.
• The degree of measured vulnerability of
  wealthier and poorer regions is highly sensitive
  to economic and adaptation assumptions.

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• Summary (cont.)
• Relative measures of vulnerability do not
  generally increase as resource endowments become
  poorer indeed, without adaptation, there may be
  either a positive or negative association between
  endowments and relative vulnerability.
• Vulnerability measured in relation to an
  absolute threshold does vary inversely with
  resource endowments.
• There is a positive relationship between gains
  from adaptation and the resource endowment of a
  region. This finding underlines the particularly
  important role that adaptation plays in
  mitigating climate change impacts in poorer
  regions.

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• Some Implications
• Why have studies of impacts of climate change on
  agriculture typically found small or even
  positive impacts (e.g., as reported in IPCC TAR)?
• Studies based on representative farm models in
  well-endowed regions will fail to represent the
  impacts of climate change on farms that are more
  vulnerable because they are located in areas with
  less favorable resource endowments.
• This finding validates concerns expressed in the
  IPCC Third Assessment Report about the validity
  of the results reported in the literature based
  on large-scale regional and national studies,
  wherein representative farm models are used to
  extrapolate impacts to larger regions.

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• Some Implications (cont.)
• The distribution of the economic impacts of
  climate change across regions with more and less
  favorable resource endowments is likely to depend
  on the ability of farmers in those regions to
  adapt to climate change.
• These findings provide empirical evidence to
  support the hypothesis advanced in the IPCC
  Second and Third Assessment Reports that climate
  change is likely to have its greatest adverse
  impacts on areas where resource endowments are
  the poorest and the ability of farmers to respond
  and adapt is most limited.

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Our research in the next phase of work will
investigate the degree to which these findings
are sensitive to assumptions of model coupling
and spatial scale.
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This presentation and related publications are
available at www.climate.montana.edu
Montana State University Program on
Climate Change and Greenhouse Gas Mitigation
www.climate.montana.edu