Transcript Document

Impacts of and vulnerability to
global change in Europe
Dagmar Schröter and the ATEAM consortium
Potsdam Institute for
Climate Impact Research
Overview
1
Vulnerability
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2
European vulnerability assessment
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3
Elements
General objective
Specific objectives
Environmental dimension of vulnerability
Consistent set of exposure scenarios
Potential impacts on ecosystem service supply
V = f(potential impacts, adaptive capacity)
Digital atlas: The ATEAM mapping tool
Recap questions, draw conclusions
Vulnerability: potential for harm
exposure
sensitivity
potential impact
vulnerability
adaptive capacity
General objective
of vulnerability assessment
• to inform the decision-making of stakeholders
about options for adapting to the effects of
global change
 facilitate sustainable development
Schröter, Polsky, and Patt 2004. Mitigation and Adaptation Strategies for Global Change, next issue. In press.
European vulnerability study
Examples
Specific
of questions
Objectives
to tackle
1. To assess potential impacts of global change on
• ecosystem
Which regionsservices
are most in
vulnerable
Europeto global change?
• Which sectors are the most vulnerable in a certain region?
translate
impacts
into
of our
•2. To
Which
scenariothese
is the least
harmful
formaps
a sector?
vulnerability
ATEAM-project, www.pik-potsdam.de/ateam
17 partners and sub-contractors, Funded by the European Union, 2001-2004.
food production
slope stability
fire prevention
water storage
fibre production
The environmental dimension of
vulnerability
biodiversity
fodder production
flood protection
recreation
• Ecosystems provide services that sustain
and fulfill human life (see MA book, Alcamo
et al. 2003)
 to know the potential impacts of global
change on ecosystem services within a
specific region is to understand an essential
part of this region’s vulnerability.
stabilising micro-climate
game reserve
shelter for life stock
pollination
carbon sequestration
tourist attraction
beauty
European Vulnerability Assessment
Methodology
multiple
scenarios of
global
change:
CO2
climate,
socio-econ.
land use,
N deposition
ecosystem
models
changes in
ecosystem
services
combined
indicators
socioeconomic
changes in
adaptive
capacity
dialogue between stakeholders and scientists
Metzger & Schröter 2004 (submitted).
maps of
vulnerability
Exposure: Multiple coupled drivers
NOx
CO2
NHy
CH4
Consistent global change scenarios
As input to our ecosystem and adaptive capacity models.
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Based on SRES narratives A1fi, A2, B1, B2
Spatially explicit: downscaled to 10' x 10' (ca. 16 x 16 km)
4 time slices (1990, 2020, 2050, 2080)
4 Socio-Economic Scenarios
4 Emission Trajectories (greenhouse gases)
17 Climate Scenarios (four climate models, one control)
7 Land Use Scenarios
4 Nitrogen Deposition Scenarios
Multiple drivers, multiple
plausible scenarios.
Climate scenarios: relative to 1961-1990
Temperature Change (°C)
2
6
Precipitation Change (%)
Temperature Change (°C)
7
5
4
3
2
1
0
2001 2011 2021 2031 2041 2051 2061 2071 2081 2091
Precipitation Change (%)
0
-2
-4
-6
-8
-10
2001 2011 2021 2031 2041 2051 2061 2071 2081 2091
years
years
range of all scenarios
average
Europe, 4 GCMs, 4 SRES
Mitchell, Hulme et al. 2004 (in review).
range of all scenarios
average
Climate change
scenarios –
temperature
Regional variability and
comparison of different
climate models (GCMs).
Anomaly
2091-2100 vs. 1991-2000
(SRES A2)
Mitchell, Hulme et al. 2004 (in review).
Climate change
scenarios –
precipitation
Regional variability and
comparison of different
climate models (GCMs).
Anomaly
2091-2100 vs. 1991-2000
(SRES A2)
Mitchell, Hulme et al. 2004 (in review).
Land use change scenarios
A1 FI - hadcm3 : 2080 -baseline
A2-hadcm3 : 2080-baseline
15.00%
15.00%
10.00%
10.00%
5.00%
5.00%
0.00%
0.00%
surplus
others
surplus
others
biofuels
forest
-15.00%
B1-hadcm3 : 2080-baseline
B2-hadcm3 : 2080-baseline
15.00%
15.00%
10.00%
10.00%
5.00%
5.00%
0.00%
0.00%
biofuels
% of European land surface
forest
-15.00%
grassland
-10.00%
arable
-5.00%
Urban
Rounsevell, Reginster et al. 2004 (in prep).
others
-15.00%
surplus
biofuels
forest
grassland
arable
Urban
-10.00%
grassland
-10.00%
-15.00%
-5.00%
arable
-5.00%
Urban
others
surplus
biofuels
forest
-10.00%
grassland
arable
Urban
-5.00%
Nitrogen deposition
Comparison with pre-industrial times
Northern hemisphere temperate ecosystems
8
pre-industrial
contemporary
average deposition
-1
(kg N ha )
7
6
5
4
Nitrogen3 effects biodiversity, the carbon cycle and
all ecosystem
services that are linked to these.
2
1
+
et
la
nd
w
Holland et al. 1999, Biogeochemistry 46, 7-43.
ic
e
es
zo
n
s
rip
ar
ia
n
fo
rm
lif
e
m
ix
ed
fo
re
st
s
gr
as
s
la
nd
0
N deposition scenarios
...under construction...
Posch 2002, Alcamo et al. 2002, IMAGE 2001
European Vulnerability Assessment
Methodology
multiple
scenarios of
global
change:
CO2
climate,
socio-econ.
land use,
N deposition
ecosystem
models
changes in
ecosystem
services
combined
indicators
socioeconomic
changes in
adaptive
capacity
dialogue between stakeholders and scientists
Metzger & Schröter 2004 (submitted).
maps of
vulnerability
Sectors, ecosystem services and modelled indicators
Sectors
Services
Indicators
Agriculture
Food & fibre production
Bioenergy production
• Agricultural land area (Farmer livelihood)
• Suitability of crops
• Biomass energy yield
Forestry
Wood production
• Tree productivity: growing stock & increment
Carbon storage
Climate protection
• Carbon storage in vegetation
• Carbon storage in soil
Water
Water supply (drinking,
irrigation, hydropower)
Drought & flood prevention
• Runoff quantity
• Runoff seasonality
Biodiversity
Beauty
Life support processes
(e.g. pollination)
• Species richness and turnover (plants,
mammals, birds, reptiles, amphibian)
• Shifts in suitable habitats
Mountains
Tourism (e.g. winter sports)
Recreation
• Snow (elevation of snow line)
Metzger & Schröter 2004 (submitted).
Agriculture
• Decline in arable land (cropland, grassland)
• Surplus land (up to over 10% of European
land surface)
• Land demand for bioenergy may go up,
CO2 offset may approach 15% of 1990emissions in 2080
• Climate driven decline in soil organic
carbon, partly counteracted by land use and
stimulated plant growth
• Crop suitabilitiy changes; some current
agricultural areas become too hot and too
dry to support agriculture
Mean
soil
C
stock
30cm
ha-1)
- excluding
Mean
soil
stock
toto
30cm
(t (t
CC
ha-1)
- excluding
to 30cm (t
C ha-1)
-Cexcluding
highly
organic
soils
highly
organic
soils
hly organic soils
78 Mean soil C stock (t C ha-1)
Mean soil C stock (t C ha-1)
89
Soil organic carbon stocks
PCM B1CGCM
B2
CSIRO2
A1FI
A2
HadCM3
Four climate models,
one emission trajectory
1
12
111
12
23
122
2020
23
34
133
34
45
144
45
2050
56
155
56
67
166
67
78
177
2080
78
89
188
89
100
199
100
2000
111
111
122
122
2020
133
133
144
144
155
2050
155
166
166
177
177
2080
188
188
199
199
1
100
2000
67
100
100
9595
B1
9090
B2
8585
8080
A1FI
7575
A2
7070
6565 One climate model,
6060 four emission trajectories
5555
5050
Years after 1900
Years
after
1900
Years
after
1900
Grassland soils may lose carbon (up to 22% of Kyoto committment).
Smith et al. 2004 (in prep).
Forestry
• Increase in forest area under all but one
socio-economic scenario
• Positive effects of climate change on
growing stocks in Northern Europe
• Negative effects in some regions, e.g.
drought and fire in the Mediterranean
• Distribution of tree species is projected to
change, e.g. cork oak, holm oak, some pine
species
Mediterranean: increased fire risk
Example Spain
15000
# fires per year
12500
10000
7500
5000
2500
# fires per year
15000
0
1950
12500
1975
2000
2025
2050
2075
2100
10000
7500
A1 HadCM3
5000
2500
Zaehle et al. 2004 (in prep).
B1 HadCM3
A2 HadCM3
B2 HadCM3
Carbon storage
• Europe‘s terrestrial biosphere currently acts
as a small carbon sink
• Despite considerable regional differences all
scenarios show a weakening of this carbon
sink after 2050
• Positive effects of reforestation, negative
effects of climate change
– Forests accumulate carbon
– Soil loses carbon in boreal forests
(more than trees take up)
– Drought stress and increased fire risk
in Mediterranean
Declining carbon sink after 2050
0.05
0.04
Land use and climate change together:
negative effect, sink declines
0.03
0.02
0.06
0.06
0.06
-0.02
0.04
0.04
0.04
-0.03
-0.04
-0.05
1950
1975
1900
2000
1925
0.02
0.02
0
0
2025
2050
1950
1975
-0.02
-0.02
2075
2000
B1-0.04
A2B2
Land useA1fchange
only:
-0.04
positive effect,
sink increases
-0.06
A2
-0.06
-0.08
-0.08
1900
1900
Zaehle et al. 2004 (in prep).
1925
1925
NBE [PgC yr-1 ]
-0.01
0
NBE [PgC yr-1 ]
0.08
NBE [PgC yr-1 ]
0.08
0.08
0.01
NBE [PgC yr-1 ]
NBE due to landuse change [PgC yr
-1
]
0.06
0.02
0
2025
-0.02
B1
0.08
0.06
0.04
0.02
0
2050
-0.02
-0.04
-0.04B2
-0.06
-0.06
2075
-0.08
-0.08
1950
1975
1900
1950
1900
1975
1925
A1f
A1f
B1
B1
2000
1925
2000
1950
2025
2050
2075
1950
1975
2000
2025
2025
1975
2050
2000
2075
2025
20
pre-industrial natural variation
pre-industrial natural variation
pre-in
A2
A1f
A1f
A2
A2
B2
B1
B1
B2
B2
Water
• By the 2030s runoff increases in Northern
Europe (by up to 10% annually) and
decreases in Southern Europe
(by up to 25% annually)
• Runoff seasonality changes in Northern and
upland Europe (increasing proportion of
precipitation falls as rain rather than snow)
• Pattern in seasonality change in alpine
catchments
- loss of water storing snow cover
- Monthly peak flow shifts to earlier date and
decreases
- reduction in summer runoff
Alpine runoff regimes
Example Dischma valley, 2051 - 2080
400
current
A1FI HadCM3
A2 HadCM3
B1 HadCM3
mm
300
B2 HadCM3
A2 CGCM2
A2 CSIRO2
A2 PCM2
200
100
0
1
2
3
4
5
6
7
month
Zierl et al. 2004 (in prep).
8
9
10
11
12
Mountain tourism
• Elevation of a reliable snow cover will rise
between 200 and 400 m from about 1300 m
today to 1500-1700 m at the end of the 21st
century.
• Presently about 85% of Swiss ski areas
have sufficient snow. A 300 m rise of the
snow line would reduce this to ca. 63%.
• Increase in winter precipitation can partly
compensate, but cannot prevent upward
shift.
Elevation of snow reliability (m a.s.l.)
Alptal
Hirschbichl
Dischma
2400
2400
2400
2000
2000
2000
1600
1600
1600
1200
1970
1200
1970
1200
1970
2000
2030
2060
2000
year
2030
2060
year
Saltina
2000
2030
year
Verzasca
2400
2400
2000
2000
1600
1600
1200
1970
1200
1970
2000
2030
year
2060
A1FI
A2
B1
B2
A2_CGCM2
A2_CSIRO2
A2_PCM2
2000
2030
2060
year
Elevation moves up ca. 150 m per degree °C warming.
Zierl et al. 2004 (in prep).
2060
Biodiversity
• Changes in plant and animal species
composition in the order of 40% in
many parts of Europe by 2050
(projections of 1350 plant, 157 mammal, 383
breeding bird, 108 reptile and amphibia species)
• Hot spots of change: Iberian
Peninsula, Central Europe, and
Scandinavia.
• Nature reserves may lose 6-11% of
species in next 50 years due to
climatic shifts
European Vulnerability Assessment
Methodology
multiple
scenarios of
global
change:
CO2
climate,
socio-econ.
land use,
N deposition
ecosystem
models
changes in
ecosystem
services
combined
indicators
socioeconomic
changes in
adaptive
capacity
dialogue between stakeholders and scientists
Metzger & Schröter 2004 (submitted).
maps of
vulnerability
Integration: Vulnerability
Visual overlay
PI
PI
V
1.0
PI
low
1.0
0
-1.0
AC
Sstr
1.0
vulnerability
adaptive capacity
potential impact
2080A1
0
high
0.0
AC high
-1.0
low
V = f(PI, AC)
A relationship that is not specified beyond high PI and low AC  high V, etc...
… our digital atlas: ATEAM mapping tool
Ca. 3200 maps and many more
summarising charts. Under construction...
...which areas, and who is vulnerable
to global change?
How can we adapt?
multiple
scenarios of
global
change:
CO2
climate,
socio-econ.
land use,
N deposition
ecosystem
models
Potential
impacts
combined
indicators
socioeconomic
changes in
adaptive
capacity
maps of
vulnerability
dialogue between stakeholders and scientists
Schröter et al. 2004 (in press), Metzger & Schröter 2004 (submitted).
Conclusions: Vulnerability in Europe
•
Vulnerable region: Mediterranean seems most vulnerable within Europe multiple potential impacts and low generic adaptive capacity
•
Vulnerable sectors:
- Agriculture? Soil. Potential for less intensive farming. How do farmers
decide? CAP...
- Forestry? Fire risk. Biofuel potential. Shift to other species.
- Carbon storage. Soil respiration and fire vs. plant growth: Declining sink 2050.
- Mountain tourism. Reliable snowcover declines. Risks and discomfort?
- Water. Droughts, floods. Seasonality changes. Hydropower, storage capacity.
- Biodiversity. Current debate. Syndrome of impoverishment? Dynamic reserve
management.
Dialogue between science and stakeholders is an important part of the results.
Should be informed by best science, fair, focussed and sustained. Coordination,
moderation, social learning.
•
•
The digital Atlas developed with stakeholders is a useful communication tool in this
dialogue. Which results, scales, scenarios will be most helpful to stakeholders?
The ATEAM
Partners
Thank you!
Project leader: Wolfgang Cramer & steering committee
Scientific coordinator: Dagmar Schröter
Wageningen Universiteit
University of Life Sciences
The Netherlands
Toledo
Spain
Paris, France
Barcelona, Spain
Silsoe Bedford,
United Kingdom
European Forest Institute
Joensuu, Finland
Montpellier, France
Max Planck Institute for
Biogeochemistry,
Germany
United Kingdom
UCL, Belgium
Institute of Arable Crops
Research, Rothamsted,
United Kingdom
Switzerland
University of
Sheffield
United Kingdom
Department of Plant &
Soil Science
United Kingdom
Finnish Environment
Institute, Helsinki, Finland
Sweden
www.pik-potsdam.de/ateam
USA
PIK, Germany
Next slides may help for specific
questions from the audience...
Adaptive capacity
‘the capacity to innovate’ (Paul Raskin)
•
Knowledge
– Awareness
– Understanding
•
Will
–
–
–
–
•
Trust
Motivation
Values
Urgency
Power
–
–
–
–
Freedom
Equity
Technology
Wealth
Countries
Provinces
Cities
Villages
Sectors
Groups
Individuals
Adaptive Capacity
‘the ability to implement planned adaptation measures’
Indicators
Female activity rate
Income inequality
Literacy rate
Enrolment ratio
R & D expenditure
Number of patents
N. of telephone lines
Number of doctors
GDP per capita
Age dependency ratio
World trade share
Budget surplus
Determinants
Components
(based on IPCC TAR)
Index
Equality
Awareness
Knowledge
1990
Technology
Ability
Adaptive
Capacity
Infrastructure
2080A1
Flexibility
Action
Economic Power
0.0 –1.0
Adaptive Capacity 2080
economic
economic
A1
A1
A2
A2
This may be one useful dimension, but...
global
global
What does this index really show?
What about the individual dimension?
regional
regional
Can AC be captured by a quantitative
indicator?
B1
B1
B2
B2
environmental
environmental
Klein et al., in prep.
Schröter et al. 2003. Paper presented at the Open Meeting of the Human Dimensions of Global Environmental Change
Research Community, Montreal, Canada. Available online http://sedac.ciesin.columbia.edu/openmtg/.
Why does N matter?
EU transect:
N gradient
Euglypha strigosa
Nebela lageniformis
Actinomycete spores
Schoenbornia humicola
Cantharellus cibarius
Bullinularia indica
Acari
atmospheric N
Decomposer
deposition
0
negligible
food web
N intermediate
high
• N deposition effects: NN
shift in food web structure
(fungal based  bacterial based)
and enhanced mineralisation rates
• could that counteract increased C
storage in vegetation?
Nematode mouthparts
Schröter et al. 2003. Oikos 102: 294-308.
Dicyrtoma fusca
Motivation: Observed impacts
• Recent reviews summarise observations of global change effects
in a wide range of ecosystems on various scales
• climate change only: Parmesan and Yohe 2003, Root et al. 2003,
O'Brien et al. 2004, Stenseth et al. 2002, Walther et al. 2002
• a variety of global change drivers: Smith et al. 1999, Sala et al. 2000,
Stevens et al. 2004
• Effects on phenology, species ranges and distribution of plants and
animals, and the composition and dynamics of communities
- But why should we care?