12. Climate Change Rohan Nelson

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Transcript 12. Climate Change Rohan Nelson

Turning analysis into adaptation
What are the research priorities?
Climate Adaptation Flagship
Rohan Nelson
Resource Economist, CSIRO Sustainable Ecosystems
with Steven Crimp, Mike Dunlop, Mark Howden,
Peter Brown & many other colleagues
…creating cognitive dissonance
…changing how you see the world
Outline
• Climate change in Tasmania
• …the science
• Analysis paralysis
• …and the science-policy relevance gap
• How did we get into this mess?
• …alternative modes of science-policy engagement
• Closing the policy relevance gap
• …and empowering rural communities
Trend in Tasmania temperature and rainfall
Temperature
1970 – 2008
Source: www.bom.gov.au
Rainfall
1970-2008
Tasmania’s rainfall declining (1970-2007)
Summer
Winter
Autumn
Spring
Tasmanian warming accelerating…
•
12.0
1910-2007
•
+0.08oC/decade
•
1950-2007
+0.11oC/decade
1990-2007
+0.31oC/decade
Mean annual temperatures
Temperature (C)
11.5
11.0
2030
10.5
10.0
9.5
9.0
8.5
1910
1920
1930
1940
Source: www.bom.gov.au
1950
1960
1970
1980
1990
2000
5
CO2 emissions
exceed
all SRES (2000)
Recent
emissions
0
scenarios
1850
1900
1950
2000
2050
2100
CO2 Emissions (GtC y-1)
10
9
8
7
Actual emissions: CDIAC
Actual emissions: EIA
450ppm stabilisation
650ppm stabilisation
A1FI
A1B
A1T
A2
B1
B2
SRES (2000)
growth rates in
% y -1 for
2000-2010:
2007
2006
2005
Observed
2000-2007
3.5%
6
5
1990
A1B: 2.42
A1FI: 2.71
A1T: 1.63
A2: 2.13
B1: 1.79
B2: 1.61
1995
2000
2005
Raupach et al., Canadell et al (2007)
2010
Uncertainty across models & scenarios
Models
Emissions scenarios
Projected change to 2030 relative to
average from 1980 to 1999
http://www.climatechangeinaustralia.gov.au
Tasmania likely to get warmer (av across models)
• 0.6 to 1oC warmer by 2030.
• Warmer in summer & autumn
Projected change (av. across models) to
2030 relative to average from 1980 to 1999
http://www.climatechangeinaustralia.gov.au
Tasmania likely to get warmer (av across models)
• 2% less rainfall by 2030
• Less in summer & spring
Projected change (av. across models) to
2030 relative to average from 1980 to 1999
http://www.climatechangeinaustralia.gov.au
Are we causing it?
Outline
• Climate change in Tasmania
• …the science
• Analysis paralysis
• …and the science-policy relevance gap
• Closing the policy relevance gap
• …and empowering rural communities
The problem – in philosophical terms
Humanity is suffering from a massive, institutionalized philosophical
blunder. The pursuit of scientific knowledge dissociated from the more
fundamental tackling of problems of living is, as we have seen, a
recipe for disaster…
…If academic inquiry were to help promote human welfare rationally,
then at the very least, it would give intellectual priority to the tasks of:
(1) articulating and clarifying problems of living; and
(2) proposing and critically assessing possible solutions –
possible and actual actions.
Nicholas Maxwell, Emeritus Reader in the Philosophy of Science
University College London
Philosophy Now, vol 65, January/February 2008, pg12
Typical Budget Allocation – USCCSP
NRC 2007
CCSP FY 2006 ($millions)
450
423.8
400
Estimated $25-30M per year.
350
Adaptation likely less than $10M.
300
257.3
250
233
202.6
200
164.8
150
100
75.2
50
25
0
Atmospheric
Composition
Climate Variability
and Change
Carbon Cycle
Water Cycle
Ecosystems
Land Use and
Land Cover
Change
Human
Contributions and
Responses
NRC. 2007. Evaluating Progress of the U.S. Climate Change Science Program: Methods and Preliminary Results.
National Academies Press, Washington, DC. http://www.nap.edu/catalog.php?record_id=11292
The US problem (last 20 years)
$22 billion
$200 million
Source: Back of the envelope estimate
The Australian problem
($ per year)
Australian Research Investment to 2007
$25 million
$30,000,000
$25,000,000
$20,000,000
$15,000,000
$10,000,000
$5,000,000
$2 million
$0
Projections
Adaptation
Source: Back of the envelope estimate – proportions are similar for Australia
Translating impacts into vulnerability assessment
5) Community/industry
adaptation
Policy/decision
options
Scenario analysis
Policy/decision relevance gap
1) Impacts
Rainfall, temperature, species distributions, etc
The problem in practical terms
The right answer to the wrong
question….
• The types of knowledge we have
been emphasizing for the past
decade or so, despite their
significant scientific value, are not
those we will most need in
dealing with the challenge of
climate change.
• It’s as if the National Institute of
Health focused its research on
making better projections of when
people will die, rather than
seeking practical ways to
increase health and life
expectancy.
Pielke and Sarewitz (2003)
Wanted: Scientific Leadership on Climate
Issues in Science & Technology p.28
Risk management meets uncertainty
The problem of focusing on what we can
measure…
http://www.pritchettcartoons.com/
Analysis paralysis and limits to prediction
Uncertain
… & likely to stay that way
for the conceivable future…
Integrated assessment of vulnerability
Exposure
Vulnerability
?
Adaptive capacity
Rainfall
variability
High
Medium
Low
Low
High
High
Moderate
Medium
High
Moderate
Low
High
Moderate
Low
Low
The challenge of uncertainty
Adaptive capacity
Generic capacity
to adapt
Attributes of
management
practices
Capacity of rural
households
Adoption of specific
practices
Aspirations of rural
households
Uncertain future
challenges
Degree of uncertainty of threat
Response to
specific drivers
National, State
Scale
Local/household
How will we respond to this challenge?
Outline
• Climate change in Tasmania
• …the science
• Analysis paralysis
• …and the science-policy relevance gap
• How did we get into this mess?
• …alternative modes of science-policy engagement
• Closing the policy relevance gap
• …and empowering rural communities
Alternative model of science/policy engagement
Tragedy of the
commons
Positivism
Logical empiricism
Self-interest &
Centralised,
non-cooperation reductionist knowledge
Centralised expert
management
Experimental
economics
Altruism &
cooperation
Self-organised
community
NRM
Integrated science
&
local knowledge
Adaptive
governance
derived from Ostrom 1990 & 1999; Dietz et al. 2003; Brunner & Steelman 2005
Centralised expert management
National
Policy goals
predefined
Goals simplified to
fit methods
Standard methods are chosen
& applied by experts across all contexts
Experts allocate resources
informed by reductionist science
Communities asked to
comment on expert solution
Policy implemented
centrally across large areas
Policy adaptation avoided,
difficult, with conflict
Adaptive governance
National & State
Negotiate goal
intersection, resolve
conflict
Transfer learning
across local
contexts
Build on local
communication
& governance
Regional
(allocation, sanctions,
monitoring, etc)
Policy trialled
in local contexts
Integrate
scientific & local
knowledge
Design local
policy
…from Ostrom (1999)
Local
Outline
• Climate change in Western Australia
• …the science
• Analysis paralysis
• …and the science-policy relevance gap
• Closing the policy relevance gap
• …and empowering rural communities
The challenge of uncertainty
Adaptive capacity
Generic capacity
to adapt
Attributes of
management
practices
Capacity of rural
households
Adoption of specific
practices
Aspirations of rural
households
Uncertain future
challenges
Degree of uncertainty of threat
Response to
specific drivers
National, State
Scale
Local/household
Converting analysis into action
Vulnerability = fn( Impacts
, Adaptation)
Exposure &
sensitivity
Adaptive capacity &
resilience
Coping to maintain
existing activities
Transformative
change to create new
options
…derived from Holling (1978)
A nested model of adaptation
[Adaptive governance to create a facilitating environment]
Sectors &
trade
Trade policy
National policy
Industry
mix
Regional &
industry policy
Livelihood
options
Enterprise
mix
Agribusiness &
NRM extension
Adoption &
adaptation
Alternative
management
practices
Field
Farm
Region
National
Global
…& nested methodologies…
GE models &
Multi-agent
IGM, etc
PE models &
total
livelihood
productivity
Trade policy
National policy
Regional &
industry policy
Agribusiness &
NRM extension
Adoption &
adaptation
Rural
livelihoods
analysis
Whole farm
simulation &
optimisation
Capacity to
change
management
(Rogers +)
Field
Farm
Region
National
Global
Converting analysis into action
Vulnerability = fn( Impacts
, Adaptation)
Exposure &
sensitivity
Adaptive capacity &
resilience
Coping to maintain
existing activities
Transformative
change to create new
options
…derived from Holling (1978)
Translating impacts into vulnerability assessment
Policy/decision
options
5) Community/industry
adaptation
Scenario analysis
Vulnerability, resilience, and adaptive
capacity
4) Social
Coping strategies
[Technical adaptation]
3) Economic
Socioeconomic livelihoods analysis
Policy/decision
relevance
Profitability, incomes,
land use gap
and regional economic impacts
Bioeconomic, PE & GE models
2) Biophysical
1) Impacts
Crop/pasture growth
Biodiversity
Agroecological models
Ecology
Water, energy, etc
Production models
Rainfall, temperature, species distributions, etc
Transforming climate information
Scale
Output
down
Global climate
models
Limited area
model
Interpolation
Crop
& pasture
Application
models
Bioeconomic
models
$
Analysis
Prediction
products
Adaptation in wheat cropping
More pasture
Source: Steve Crimp
More residue
More fallow
Are we measuring what we can change?
Current exposure to
climate variability
Exposure to climate
change in 2030
no data
Farm incomes
least
moderate
Pasture
most
Rainfall
Regional impacts of climate change
Heyhoe et al. 2007
Global agricultural productivity
2020s
Increased agricultural
productivity in mid to high
latitude regions due to warmer
& wetter conditions
2050s
• Reduced in the tropics and
sub-tropics due to warming
and rainfall changes
2080s
Source: IPCC 2001
Converting analysis into action
Vulnerability = fn( Impacts
, Adaptation)
Exposure &
sensitivity
Adaptive capacity &
resilience
Coping to maintain
existing activities
Transformative
change to create new
options
…derived from Holling (1978)
The challenge of uncertainty
Adaptive capacity
Generic capacity
to adapt
Attributes of
management
practices
Capacity of rural
households
Adoption of specific
practices
Aspirations of rural
households
Uncertain future
challenges
Degree of uncertainty of threat
Response to
specific drivers
National, State
Scale
Local/household
Rural livelihoods & household capacity
Outcomes
Livelihood
platform
Access modified
by
In the context
of
Social relations
Natural
based activities
Trends
Livelihood
strategies
Institutions
Shocks
Physical
Organisations
Financial
H’hold
capacity
Composed
of
With effects
on
Capacity of rural
Natural Resource
households
Human
Social
Resulting
in
Policy and other
external influences
non -NR
based activities
Attributes of
management practices
Livelihood
security
Environ’l
sustainability
Aspirations
…from Ellis (2000)
Adaptive capacity & substitution
Human
5
•household
•property
•catchment
•region
•state
•country
4
3
2
Financial
Social
1
0
Region 1
Region 2
Physical
Natural
…from Carney 1998
Financial
Human
Social
Natural
Adaptive Capacity
Physical
(Nelson et al. 2007)
Operator education
Human capital
Spouse education
Health – self assessed
Adaptive capacity of catchments
High
Moderate
Low
Regionalising adaptive capacity measures
Human
5
4
3
Financial
2
Social
1
0
Physical
Natural
Self-assessed adaptive capacity
Triggering collective action between communities & governments
Western plains
Human
5
4
Central slopes
& plains
3
Financial
2
Social
1
Western plains
0
Central slopes
& plains
Slopes & hills
Slopes & hills
Physical
Natural
Integrated analysis of vulnerability
Priority setting
Exposure to income risk
Vulnerability to income risk
Adaptive capacity
High
Medium
Low
Low
High
High
Moderate
Medium
High
Moderate
Low
High
Moderate
Low
Low
Rural livelihoods
context
Vulnerability,
Adaptive capacity
Resilience
Attributes of
management
practices
Capacity of rural
households
Bonding
Bridging
Aspirations of rural
households
Codesign practical
adaptation strategies
Data &
methods
Prioritising action
Human
Financial
Participatory
monitoring &
evaluation
Physical
Social
Natural
Inducing action, not just analysis
http://www.csiro.au/org/ClimateAdaptationFlagship.html