Ecosystem responses to climate in the context of multiple drivers

Transcription

1 Ecosystem responses to climate in the context of multiple drivers Thorsten Blenckner Baltic Nest Institute, Stockholm Resilience Centre, Stockholm University, Sweden Aronias 10-årsjubileum i Ekenäs, Finland

2 Outlook of the talk Climate - a part of multiple environmental challenges Observed climate signatures in lakes Findings Case study 1 Observed climate signatures in marine systems Findings Case study 2 Gaps and challenges

3 Todays environmental challenges Climate change and variability Eutrophication Overfishing Land-use changes Hydrologic modification Invasive species Toxic pollution

4 Past climate change EPICA; Vostok ice core Siegenthaler et al (2005) /IPCC(2007)

5 Observed Climate Change

6 Climate and water cycle act globally,..but differ on regional and local scales! The year 1990 Source:NASA

7 Observed climate signatures in lakes

8 Ice in the Northern Hemisphere Magnuson et al. 2000

9 NAO A proxy for winter climate variability in Europe Source: NAO/ NAO Winter (DJFM) PC Index

10 Coherence North Atlantic Oscillation Livingstone et al 2010

11 Case 1 Large-scale European study

12 Questions How long does the winter climate signature persist in lakes? Are there any effects i.e. in the plankton succession? Decoupling of trophic interactions?

13 European Study 20 Lakes across Europe with monthly long-term data from for: Physics: water temp. surface, bottom, timing ice break-up Chemistry: TP, PO 4, TN, NO 3, Si Biology: diatoms, cyanobacteria, dinoflagellates, timing spring bloom, Daphnia, Bosmina, copepods, timing zooplankton peaks each variable was detrended and correlated with the Winter (DJFM) NAO =>interannual variability No effect of trophic status of the lake

14 Synthesis of case 1 NAO Timing Ice Water temperature Diatom Cyanobacteria Spring bloom Daphnia? Cyclopoids CWT Blenckner et al (2007) winter spring summer

15 Heat Wave, Central Europe 2003 Stressor Response Jankowski et al 2006

16 Water Level, Lake Võrtsjärv, Estonia Winter climate signal recorded in the water level Effect extended to summer => high phytoplankton biomass in low-water years Nöges & Nöges 2004

17 Phytoplankton in 5 Lakes in Central Europe Phosphorus concentration more relevant than winter climate variability Jankowski et al in press

18 Cyanobacteria in Lake Zurich, Switzerland Anneville et al (2004) Higher water temperature, increases probability of cyanobacteria blooms

19 Specific patterns on species level Attrill & Power 2002

20 General findings Water temperature +++ Ice cover period --- Water column stability ++/- Deep oxygen depletion ++/= Nutrients +/- Phytoplankton +/- Cyanobacteria ++/- Zooplankton ++/- Fish ++/-

21 Observed climate signatures in marine systems

22 Trophic cascades related to temperature and species richness Frank et al 2007

23 Changes in zooplankton Beaugrand 2004, Beaugrand et al 2008

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26 Concept: regime shifts Folke et al 2004 Ecosystem state Drivers over time

27 Regime shifts in many regions - Black Sea (Daskalos et al 2002, 2007) - North Sea (Weijerman et al. 2005, Alheit et al. 2005, Reid et al 2001, Beaugrand et al. 2003, 2008, Beaugrand 2004, Llope et al 2009) - North West AtlanKc / ScoKan Shelf (Frank et al 2005, 2006,2007) - North Pacific (Hare & Mantua 2000, Wooster & Zhang 2004) - BalKc Sea (Möllmann et al 2000, 2005, 2008a, 2009, Casini et al 2008,2009; Österblom et al 2007, Alheit et al 2007) -. - => disrupkve changes in ecosystem services, i.e., fisheries produckvity - => extensive fluctuakons of harvested fish stocks

28 Case 2: Baltic Sea

29 Methods - Integrated index of ecosystem development & regime shi9 detec:on Principal Component Analysis (PCA) on all biokc variables PC1 as index of ecosystem development Regime shic tests using the sequenkal regime shic deteckon method (STARS Rodionov, 2004) and chronological clustering (Legendre et al 1985) Analysis are perfomed within the HELCOM/ICES working group of the Integrated Assessments of the BalKc Sea

30 Data sets (218 in total) System The Sound Central Baltic Gulf of Riga Gulf of Finland Bothnian Sea Bothnian Bay Biotic Abiotic Sum

31 Regime shifts in all systems Sub- system specific indices of ecosystem development (PC1 from PCA) Regimes idenkfied using STARS on PC1s (red lines) Almost synchronous regime shics in all sub- systems

32 Drivers found in this analysis Basin The Sound Drivers climate, Winter P Significance level Explained variance % < Central Baltic Sea climate, fishing < Gulf of Finland Climate, nutrients, fishing < Gulf of Riga Salinity, winter P < Bothnian Sea salinity < Bothnian Bay salinity, fishing <

33 Regime shift drivers all system analysis (GAMM) Generalized Additive Mixed Model using basins as factors and basin-specific year smoothers to account for spatial and temporal autocorrelation best model: - only winter climate (Baltic Sea Index) as the overall significant driver (p<0.01)

34 Ecosystem Interactions Central Baltic Sea Fishing pressure Reprod. Volume Cod Sprat Pseudo- calanus AcarKa Climate modified from Möllmann et al 2009

35 Conclusion- Baltic Sea Severe changes induced by - climate - overfishing and - eutrophicakon Intensive monitoring of all trophic levels is required - to disentangle drivers - idenkfy thresholds - develop early warning indicators Ecosystem based management must be linked to real data assessments including the enkre ecosystem

36 What did we learn? Gaps, challenges, next steps

37 1. Data Short- and long-term monitoring Automatic stations Wireless network /Scaling => Model Uncertainty

38 Scaling Trade off between models at ecosytem scale and data from the sampling bottle

39 2. Research Thresholds: stochastic events can trigger ecosystem shifts (extremes in climate, variability) Process understanding: Not all responses propagate to the whole ecosystem Interplay of filter components Multiple stressors => Model uncertainty Water quality criteria

40 Future climate change and variability SMHI, 2005

41 3. Stronger Integration of physical/biogeochemical/ biological models Example CLIME ( Decision Support System (DSS) Bayesian Network It combines: modelling, statistical data analysis, experience Example NEST ( Combination of models Catchment and biogeochemical models linked Fast running time free on the web

42 Atmospheric emissions and load Cost minimiza:on model Marine modeling NEST can be used freely with any computer with Internet access from Drainage basin modeling Fishery management Marine and runoff data

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44 Recommendations Interdisciplinary and functional researcher team Continuation of monitoring Installation of automatic stations/network Inclusion of climate variability and other drivers!!! Insignificant results are essential Ecosystem responds as a whole Not all responses propagate to lower trophic levels or whole ecosystem scale

45 The End