multiple stress of eutrophication and climate change in lakes: projected effects of future climate...

Towards recovery of Europe’s waters

Multiple stress of eutrophication and climate change in lakes:

projected effects of future climate scenarios for phytoplankton in Northern European lakes

Jannicke Moe1, Anne Lyche Solheim1, Niina Kotamäki2, Hege Gundersen1, Laurence Carvalho3, Birger Skjelbred1, Marko Järvinen2, Geoff Phillips4

1) Norwegian Institute for Water Research (NIVA); 2) Finnish Environment Institute (SYKE); 3) Centre for Ecology and Hydrology (CEH), UK; 4) University of Stirling, UK

SIL conference1-5 August 2016Torino, Italy

The MARS project (“Managing Aquatic ecosystems and water resources under multiple stress”) is funded by the European Union under the 7 th Framework Programme, contract no. 603378.

Limnology in the 21th century: science gaps

Kendra S. Cheruvelil: Limnology in the 21th century: incorporating data-intensive research, open science, and team science to address broad-scale problems (plenary lecture Wednesday morning)

• Extrapolation to unstudied lakes• Scaling up to larger spatial scales• Forecasting to future periods

Aim of our study

• To assess the impact of nutrients in combination with climatic stressors on lakes in Northern Europe based on phytoplankton indicators, under current and future conditions.

• How will future temperature increase affect the ecological status of phytoplankton, under different scenarios of TP concentrations?

What is new in this study?

• Large-scale study – Northern GIG (UK, NO, SE, FI)– Data from 1100 lakes

• EU project WISER (Moe et al. 2013)– New European "broad lake types"

• Future climate scenarios– Based on IPCC scenarios

• Response: phytoplankton trophic index (PTI)(Ptacnik et al. 2009)– Species composition and TP preferences– One of the 3 components of ecological status

of lake phytoplankton cf. WFD

Approach: statistical and predictive modelling

Nutrientconcentrations

Phytoplanktonindices

WISER dataStatistical model

Temperature

Precipitation

Climate data

HISTORICAL DATA(1988-2009)

Nutrient concentrations


Temperature

Precipitation

MARS climate scenarios

FUTURE SCENARIOS(2010, 2030, 2090)

"What if" scenarios

WISER data

Predictivemodel

The Phytoplankton Trophic Index (PTI)

• Indicator score based on each genus'TP optima (sj), weighted by its biomass (aj)

• PTI differs between lake types• PTI responds to climatic variables (Phillips et al. 2013)

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jj

n

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Historical climate data

• Downloaded from Joint Research Centre– http://agri4cast.jrc.ec.europa.eu

• Spatial resolution: 25 km x 25 km grid• Temporal resolution: daily• Variables used in analysis:

– Mean summer air temperature(Jun-Aug)

– Total summer precipitation

From Richardson et al. (in prep)

New European "broad lake types"

ETC/ICM, 2015. European Freshwater Ecosystem Assessment: Cross-walk between the Water Framework Directive and Habitats Directive types, status and pressures

Statistical method: hierarchical regression model

• In our current model, different lake types have ...– Different PTI level (intercept)– Different effect of TP– Same effect of temperature– Same interaction effect TP * temperature

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Higher relevance,higher accuracy

9 lake types

In our study:

1100 lakes

4600 samples(lake-months)

Approach: statistical and predictive modelling




Temperature

Precipitation

JRC climate data




Temperature

Precipitation



"What if" scenarios

WISER data

Predictivemodel

Climate scenarios:"Consensus world" vs. "Fragmented world"

Climate Scenario 2010 2030 2090"Consensus World" (RCP 4.5)

15.9 17.1 18.1

"Fragmented World" (RCP 8.5)

15.9 17.4 21.3

"2010" (2006-2015) "2030" (2026-2035) "2090" (2086-2095)

Mean summer airtemperature (°C)

Predicted mean summer air temperature (°C)• Climate model: IPSL-CMSA-LR• Spatial resolution: 0.5 x 0.5° grid• Temporal resolution: daily• More info: MARS fact sheet #03

Predicted change in PTI for different climate scenarios

Climate scenario 4.5: Consensus World

Climate scenario 8.5: Fragmented World

Predicted change in PTI for different climate scenarios

• Consensus World: increased PTI for only 3 lake types

• Fragmented World: increased PTI for most lake types



Focus on lake type 2: Lowland siliceous

Type 2: Lowland siliceous (34% of the lakes in this study)

Type 7: Mid-altitude siliceous (16%)

Type 1: Very large lakes (9%)

Focus on lake type 2: Lowland siliceous

Type 2: Lowland siliceous (34% of the lakes in this study)

"What if" scenarios for TP

Phillips & Pitt 2015. A comparison of European freshwater nutrient boundaries used for the WFD: A report to ECOSTAT.

3 scenarios (applied to all years):

1) 50% lower TP– Based on the average difference

between the current TP and the target TP (Good/Moderate boundary) for the lake type

2) 100% TP– The current TP concentration of each

lake

3) 50% higher TP

Lake type 2 (Lowland siliceous)

How will warmer climate affect PTI under different scenarios of lake TP concentrations?








• Best case CC scenario (Consensus world):– TP 100%: warmer climate will increase PTI in the long run– TP +50%: warmer climate will increase PTI already in 2030– TP -50%: warmer climate will not increase PTI




Climate scenario 4.5: Consensus World• Worst case CC scenario (Fragmented world):

– TP 100%: warmer climate will increase PTI in the long run– TP +50%: warmer climate will increase PTI already in 2030– TP -50%: warmer climate will still increase PTI in the long run

How much will PTI increase for individual lakes?Lake type 2 (Lowland siliceous)


• Best case CC scenario (Consensus world):– Increases in PTI due to climate change are generally below 0.25– Probably no change in WFD status class


• Worst case CC scenario (Fragmented world):– Increases in PTI due to climate change are often >0.25– These lakes have higher risk of obtaining lower ecological status– Applies to 5-25% of the lakes, depending on the TP scenario

Conclusions - Lake type 2

• Even if current TP concentrations would remain, warmer climate will increase PTI and may thereby reduce the ecological status of lakes in the long run (2090).

• If TP concentrations were 50% higher, temperature-induced increase in PTI could be expected also in the short run (2030).

• If TP concentrations were 50% lower (cf. WFD targets), temperature-induced increase in PTI could still be expected in the worst-case CC scenario.

• Temperature-induced change in PTI probably not sufficient to reduce ecological status class of lakes

Conclusions - general

• Large-scale data sets with high taxonomic resolution are valueable for assessing effects of multiple stressors on lake ecosystems

• Different properties of lake types are important

• Different future scenarios should be compared

• Large-scale analyses should be supplemented with in-depth analyses of individual lakes – cf. Carvalho et al. (this session)

Is this approach useful?




Temperature

Precipitation

Climate data




Temperature

Precipitation



"What if" scenarios

WISER data

Predictivemodel

Is this approach useful?

John Downing: Robert H. Peters: the way to theory, scientific revolution, knowledge typology, the art of the soluble, and predictive ecology (Session 37 Predictive limnology revisited, Wednesday morning)

Fix design

How to course-correct the science that we do:• Harness the immense power of shared data,

shared platforms, collaborative research, international networks, and heretofore unimaginable computing tools to create imperfect anwers

Thank you for the attention!

Acknowledgements:• The data owners providing data to the former EU

project WISER• The MARS Geodatabase team (Lidija Globevnik,

Maja Koprivšek and others)• NIVA colleagues for help with the climate

scenario data (Raoul-Marie Couture, Anna Birgitta Ledang and James Sample)

• EU 7th FP, contract no. 603378

References

• ETC/ICM, 2015. European Freshwater Ecosystem Assessment: Cross-walk between the Water Framework Directive and Habitats Directive types, status and pressures, ETC/ICM Technical Report 2/2015, Magdeburg: European Topic Centre on inland, coastal and marine waters, 95 pp. plus Annexes.

• Faneca Sanchez, M. et al. (2015) Report on the MARS scenarios of future changes in drivers and pressures with respect to Europe’s water resources. Part 4 of MARS Deliverable 2.1: Four manuscripts on the multiple stressor framework.

• Moe, S. J., A. Schmidt-Kloiber, B. J. Dudley & D. Hering, 2013b. The WISER way of organising ecological data from European rivers, lakes, transitional and coastal waters. Hydrobiologia 704(1):11-28.

• Phillips, G., A. Lyche-Solheim, B. Skjelbred, U. Mischke, S. Drakare, G. Free, M. Järvinen, C. Hoyos, G. Morabito, S. Poikane & L. Carvalho, 2013. A phytoplankton trophic index to assess the status of lakes for the Water Framework Directive. Hydrobiologia 704(1):75-95.

• Phillips, G., Pitt, J.-A. 2015. A comparison of European freshwater nutrient boundaries used for the Water Framework Directive: A report to ECOSTAT.

• Ptacnik, R., A. Solimini & P. Brettum, 2009. Performance of a new phytoplankton composition metric along a eutrophication gradient in Nordic lakes. Hydrobiologia 633(1):75-82.

Potential improvements

• Use future land-use scenarios for more realistic future TP scenarios (MARS)

• Full ecological status for all lakes• Non-linear relationships in empirical model• More predictors (e.g. TN, precipitation)• Compare outcome for different lake types• Info from MARS studies of single lakes

(cf. Carvalho et al., this session)• Expand to larger parts of Europe

(cf. Richardson et al. in prep)