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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
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Futureclimatescenariosforphosphorus and nitrogendynamicsintheGulfofRiga Bärbel Müller-Karulis, LatvianInstitute of AquaticEcology Juris Aigars, LatvianInstituteofAquaticEcology IncolaborationwithJuris Seņņikovs, Laboratory for MathematicalModelling of Environmental and TechnologicalProcesses, Faculty of Physics and Mathematics, University of Latvia Latvian Institute of Aquatic Ecology
Gulf of Rigacharacteristics • Semi-enclosedbasin • Connected to EasternGotlandbasinsurfacewaters • Salinity 5.5 – 6.2 PSU • Shallow: averagedepth 22 m, maximum 56 m • no permamenthalocline, seasonal thermocline, monomicticcirculation • Highfreshwaterand riverine nutrientinput • Regularmonitoringsince 1973 Response to climatechange ?
Modelsetup • Biogeochemicalmodel • phytoplankton, zooplanktonandnutrients • NPZD Boxmodelbasedon Savchuk 2002 • 2 boxes (pelagic, demersal) + sediments • 3 phytoplanktongroups • Zooplankton • NO3, NH4, PO4, O2 • Calibrated to 28-year observationseries • Physicalmodel (1D) • verticaltemperaturedistributionin the GoR • General OceanTurbulenceModel (GOTM) • Coefficients of secondordermodel: Cheng (2002) • Dynamicequation (k-εstyle) for TKE • Dynamicdissipationrateequation Ecosystemresponse Temperaturechange
Climatechangescenario Climate datafrom PRUDENCE. Control: 1961-1990, Scenario A2: 2070-2100 Extradownscaling of RCM data (biascorrectionviahistogramequalisation): 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) Calculationsmade for Gulf of Riga (50 m), 30 yearperiod, dailyoutputdata – watertemperature
Physical model results – I(mean temperature distribution over depth) Surface T increaseclose to air T increase T increaseby 1,5 (bottom) to 3 (surface) degrees
Physical model results – II(mean daily pycnocline depth and its variation) ... stratificationlastslonger Pycnoclinedevelopsearlier...
Physical model results – III(mean time-depth plots of temperature) Contemporaryclimate ClimatechangescenarioA2
Verticalwaterexchange decreasedverticalwaterexchange
Speciessuccession earlierandmorevigorousspringbloom
Speciessuccession largerbiomass of summerspecies
Speciessuccession morecyanobacteria
Pelagicnutrients largerwinterpool earlierdepletion
Demersalnutrients largerdemersalnutrientconcentrationsinsummer
Verticalnutrientflux increaseddemersalconcentrationscompensatestratificationeffect
Nutrientregeneration Pronouncedincreaseinnutrientrecycling!
Conclusions • Increaseinphytoplanktongrowthandprimaryproductivitycausedbyincreasednutrientregeneration • Slightlyincreasedwinternutrientconcentrations • Earlier spring bloom (earlier stratification, no ice cover) • Largersummerphytoplanktonbiomass, morecyanobacteriabecause of moreintensivenutrientregeneration • Lower demersal oxygen concentration caused by more stable and longer stratification • Denitrification – open question for future research