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Impacts of and vulnerability to global change in Europe Dagmar Schröter and the ATEAM consortium Potsdam Institute for Climate Impact Research Overview 1 Vulnerability – – 2 European vulnerability assessment – – – – – – 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. • • • • • • • • 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 2 6 0 Precipitation Change (%) Temperature Change (°C) Temperature Change (°C) 7 5 4 3 2 1 0 2001 2011 2021 2031 2041 2051 2061 2071 2081 2091 Precipitation Change (%) -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 average deposition -1 (kg N ha ) 7 pre-industrial contemporary 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 sl an d 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 -0.04 -0.06 0.08 0.06 0.04 0.02 0 2050 -0.02 2075 -0.04B2 -0.06 -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 B2 HadCM3 A2 CGCM2 A2 CSIRO2 A2 PCM2 mm 300 200 100 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 Saltina 2030 year 2060 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? TheThank ATEAM you! Project leader: Wolfgang Cramer & steering committee Partners 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?