Bärbel Müller-Karulis, Latvian Institute of Aquatic Ecology

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Presentation transcript:

Future climate scenarios for phosphorus and nitrogen dynamics in the Gulf of Riga Bärbel Müller-Karulis, Latvian Institute of Aquatic Ecology Juris Aigars, Latvian Institute of Aquatic Ecology In colaboration with Juris Seņņikovs, Laboratory for Mathematical Modelling of Environmental and Technological Processes, Faculty of Physics and Mathematics, University of Latvia Latvian Institute of Aquatic Ecology

Gulf of Riga characteristics Semi-enclosed basin Connected to Eastern Gotland basin surface waters Salinity 5.5 – 6.2 PSU Shallow: average depth 22 m, maximum 56 m no permament halocline, seasonal thermocline, monomictic circulation High freshwater and riverine nutrient input Regular monitoring since 1973 Response to climate change ?

Mean temperature (period 1973-2008)

Mean oxygen (period 1973-2008)

Model setup Biogeochemical model Physical model (1D) phytoplankton, zooplankton and nutrients NPZD Box model based on Savchuk 2002 2 boxes (pelagic, demersal) + sediments 3 phytoplankton groups Zooplankton NO3, NH4, PO4, O2 Calibrated to 28-year observation series Physical model (1D) vertical temperature distribution in the GoR General Ocean Turbulence Model (GOTM) Coefficients of second order model: Cheng (2002) Dynamic equation (k-ε style) for TKE Dynamic dissipation rate equation Ecosystem response Temperature change

Climate change scenario Climate data from PRUDENCE. Control: 1961-1990, Scenario A2: 2070-2100 Extra downscaling of RCM data (bias correction via histogram equalisation): relative humidity (used variable td2m) air temperature (used variable t2m) Original RCM data: sea level pressure (used variable MSLP) cloudiness (used variable clcov) wind speed (used variable w10m) wind direction (used variable w10dir) Calculations made for Gulf of Riga (50 m), 30 year period, daily output data – water temperature

Physical model results – I (mean temperature distribution over depth) Surface T increase close to air T increase T increase by 1,5 (bottom) to 3 (surface) degrees

Physical model results – II (mean daily pycnocline depth and its variation) ... stratification lasts longer Pycnocline develops earlier...

Physical model results – III (mean time-depth plots of temperature) Contemporary climate Climate change scenario A2

Vertical water exchange decreased vertical water exchange

Demersal oxygen – GR mean

Species succession earlier and more vigorous spring bloom

Species succession larger biomass of summer species

Species succession more cyanobacteria

Pelagic nutrients larger winter pool earlier depletion

Demersal nutrients larger demersal nutrient concentrations in summer

Vertical nutrient flux increased demersal concentrations compensate stratification effect

Nutrient regeneration Pronounced increase in nutrient recycling!

Denitrification

Nitrate uptake/release (oxygen control)

Ammonium versus nitraterelease

Mean nitrate (period 1973-2008)

Conclusions Increase in phytoplankton growth and primary productivity caused by increased nutrient regeneration Slightly increased winter nutrient concentrations Earlier spring bloom (earlier stratification, no ice cover) Larger summer phytoplankton biomass, more cyanobacteria because of more intensive nutrient regeneration Lower demersal oxygen concentration caused by more stable and longer stratification Denitrification – open question for future research