Upload
ingrid-le-ru
View
119
Download
0
Embed Size (px)
Citation preview
Transdisciplinary and Multi-scale Agricultural Projections
of Climate Change Impacts
Cynthia Rosenzweig
NASA GISS
Our Common Future Under Climate Change Conference
Paris, July 8, 2015
India USA Kenya Sri Lanka
• Overview of AgMIP
• Lessons Learned
-- Crops, Sites, and Processes
-- Regional Integrated Assessments
-- Global Crops and Economics
• Ways Forward
-- Coordinated Global and Regional Assessments
,
Outline
AgMIP Mission
3
Near Arusha, Tanzania
Provide effective science-based agricultural
decision-making models and assessments of climate
variability and change and sustainable farming systems to achieve
local-to-global food security
4
Worldwide Science Community
2nd Global Oct 2011 1st Global Oct 2010
Sub-Saharan Africa #3 South Asia #3
3rd Global Oct 2012
4th Global Oct 2013 5th Global Feb 2015
Partnerships
5 Some of the many partners and donor institutions involved in AgMIP
Phase 2 (2015-2020) Science Approach
6
Rosenzweig et al., 2013 AgForMet
Multi-model assessments
Track 1: Develop/Test NextGen Agricultural Systems Models
Track 2: Conduct Multi-Model Assessments for Sustainable
Farming Systems and Climate-Smart Agriculture
AgMIP Sentinel Sites
Platinum
Gold
Silver
Current and Prospective Activities
7
GEOGLAM
Sustainable Nutrition
Security
Ozone
Natural Resources &
Ecosystems
Statistical & Dynamic
Approaches
AgMIP Teams and
Activities
• Co-Leaders
• Written Plan with
Goals and Research
Questions
• Protocols
• External Science
Advisors
• Review & Attribution
• Budget & Funding
Strategy
• Quality Assurance
• Documentation of
Model Improvement
• Publications
Current
In Development
Coordinated Global & Regional Assessments
Key Components
8
AgMIP Teams and
Activities
• Co-Leaders
• Written Plan with
Short and Long-
Term Goals
• Protocols
• External Science
Advisors
• Review & Attribution
• Budget & Funding
Strategy
• Quality Assurance
• Documentation of
Model Improvement
Current
In Development
GEOGLAM
Sustainable Nutrition
Security
Ozone
Natural Resources &
Ecosystems
Statistical & Dynamic
Approaches
Handbook of Climate Change and Agroecosystems
Just published
Crops, Sites, and Processes
,
K. J. Boote and P. J. Thorburn
Wheat, Maize, Rice, Sugarcane, Potato, Sorghum,
Peanut, Soil, Bioenergy, Water-ET Teams
0˚ 90˚ -90˚
-45˚
AgMIP Sentinel Sites
= Wheat
= Maize
= Rice
= Sugarcane
0˚
45˚
Shizukuishi
Nanjing
Morogoro
Wongan Hills
Balcarce
North America
Ames South
Asia
Delh
i
Ludhiana
Ayr
Los Baños
Piracicaba
Rio Verde
La Mercy
Haarweg
Lusignan
South
America
Sub-Saharan
Africa
Europe
Asia*
Australia*
• Wheat, maize, rice, sugarcane, millet/sorghum, groundnut, potato, canola, grassland/pastures, soils and crop rotations; bioenergy; crop water/ET Teams
• Sentinel site experiment data, sensitivity tests • Focus on uncertainty, processes, and model improvement
Crop Model Intercomparison and Improvement Studies
K. J. Boote and P. J. Thorburn
Crop Modeling Leaders Rosenzweig et al., 2013
Ensemble of
models predicted
yields accurately
True under poorly
and well calibrated
conditions
Most individual
models did not
predict all sites
well across varying
environments
1
2
Asseng et al. 2013
Nature Climate Change
Ensembles better than individual
models
27 wheat models
13
Number of models needed
may be relatively small
13 rice models
Li et al., 2015 Global Change Biology
~5-10 models needed to replicate observations across sites
No major difference in CO2 responsiveness associated
with photosynthesis method
Large variation in response at high levels of CO2
14
13 rice models
Positive response to CO2
key source of uncertainty
Li et al., 2015 Global Change Biology
Regional Integrated Assessments
,
John Antle, Jim Jones, Alex Ruane,
Roberto Valdivia
Regional Research Teams
AgMIP
Regional Research Teams
16
5-year project, UK DFID funded 8 regional teams, 18 countries, ~200 scientists Protocols for data, models, scenarios designed and implemented by multi-disciplinary teams
and stakeholders
Rosenzweig and Hillel (Eds) Handbook of Climate Change and
Agroecosystems Imperial College Press, 2015
Pretoria, South
Africa 2013
Katmandu, Nepal, 2013
17
• Farming systems
• Transdisciplinary:
biophysical/
socio-economic
• Multi-scale:
field, farm, region,
global data and
models
• Multiple climate and
crop models
• Distributional results:
impacts on poverty
AgMIP Regional Integrated
Assessment – 5 Attributes
Antle et al., 2015
18
Yield or
value
time current future
Q1
Q3 Q2
Yield or
value
time current future
Q1
Q3
Q2
RAPS
Q1) What is the sensitivity of current agricultural production systems to
climate change?
Q2) What is the impact of climate change on future agricultural production
systems?
Q3) What are the benefits of climate change adaptations?
3 Core Questions
RAPS
Negative climate change effects Positive climate change effects
Antle et al., 2015
West Africa
Crop Model Results
Simulated variability in millet
yields with DSSAT and APSIM
crop models, for current base
technology (BT)
compared to adapted
future changed technology (CT)
under 5 CMIP5 GCM climate
change scenarios for Nioro,
Senegal and Navrongo, Ghana
Adiku et al., 2015
APSIM tended to be more
positive than DSSAT in both
baseline and future climate
Phase 2: Determine why and
institute model improvements
West Africa
Climate Change Impacts
20
Adaptation
packages can
raise incomes
and lower
poverty rates,
but do not
always
compensate
crop yield
losses
completely
Adiku et al., 2015
Global Crops and Economics
,
Joshua Elliott, Christophe Mueller, Keith
Weibe, and Hermann Lotze-Campen
And Global Gridded Crop Model Initiative and
Global Economics Teams
─ Lower latitudes are more vulnerable to climate change
─ [CO2] effects key to understanding future impacts and uncertainty
─ Models that incorporate realistic nitrogen see significantly less
gains from [CO2] effects at present-day fertilizer levels 2
2
Global agricultural productivity
End-of-century (2070-
2099) climate impact.
Median of 7 GGCMs
and 5 GCMs. Hatched
areas indicate model
agreement in sign
Rosenzweig et al., 2014 PNAS 111(9): 3268-3273
Uncertainty Cascade
23
Effects of climate change on agricultural prices
(S3-S6 results in 2050 relative to results without climate change in 2050)
AgMIP Global
Economic s Model
Intercomparison
10 Global Economics
Models, 2 GCMs,
2 crop models
Von Lampe et al.,
Agricultural
Economics,
2013
Climate change is projected to exert upward pressure on agricultural
prices, but with large uncertainty that is being connected to model
approaches
S3 S4 S5 S6
GCMs
GGCMs
Model uncertainty
GEM > GGCM > GCM
Ways Forward
,
3 Focus Areas
25
Coordinated Global and Regional
Multi-Model Assessments
26
RRTs – Farming systems
biophysical and
socioeconomic models
GGCMI -- High-resolution
gridded crop modeling for gap-
filling and aggregation in each
region
Global Economics –
Model analysis of
world and regional
prices
Production systems and
regional economics
respond to price changes
RCPs
SSPs
RAPs
Key Points
27
• Uncertainty cascade shows that focus on improving
rigor of impact assessments is highly warranted.
• Crops, livestock, sites, and processes are important to
full understanding and credibility of global simulations.
• Regional integrated assessments of farming systems
are needed to identify vulnerable groups and regions.
• At the global scale, ‘pre-assessment’ validation is
essential to advance the capability of crop and
economic models.
• Building blocks and community are now in place for
coordinated global and regional assessments for food
security.
• AgMIP Phase 2 Fundamentals
Workshop, Victoria Falls,
Zimbabwe, Jun 24-30, 2015
• AGCI AgMIP Coordinated
Global & Regional
Assessments Workshop,
Aspen, Sep 13-18, 2015
• 6th AgMIP Global Workshop,
TBC, Spring 2016
Workshop Highlights
For protocols, up-to-date events and news,
and to join AgMIP listserve* – www.agmip.org
28