The use of pressure response relationships between nutrients and biological quality elements as a method for establishing nutrient supporting element boundary values for the Water Framework Directive Coastal and transitional waters Heliana Teixeira, Fuensanta Salas Meeting on the Best practice guide on nutrients 9-10 Berlin, 2016

Main issues encountered Toolkit analyses tested (examples) Provide examples for the Guidance  on nutrient standards for the WFD – helping the establishment of nutrient concentrations to support good ecological status. Test the Guidance protocol and its suggested approaches in the coastal (CW) and transitional (TRW) waters data; Contribute to adjust the protocol and its recommendations accounting for the specificities of these water categories. Type of data available Main issues encountered Toolkit analyses tested (examples) Next steps - discussion

(MS original nutrient units) 1 Type of data available Transitional waters Estuaries // Lagoons Common Type Supp. Env data Season Nutrient parameters (units) Chla EQR IC boundaries Dataset (MS original nutrient units) Yes/No; parameter   DIN NH4 NO3 NO2 TN TP OrthoP Si Countries (n obs*) TRWBALBT1 (mg L-1) No Su µg L-1 Yes: LT (27); PL (29) TRWMEDpolyCL (µg L-1) -- EQR (MPI) Yes IT/GR (17) (µg L-1) EQR_Phyto Yes: FR (15) TRWNEA11 (µM) Wi EQR_Chla no boundaries (232) using data from the WFD intercalibration  (IC) exercise nutrients used for statistical analysis: TN TP DIN

1 Coastal waters Type of data available Common Type Supp. Env data Season Nutrient parameters (units) Chla EQR IC boundaries Dataset (MS original nutrient units) Yes/No; parameter   DIN NH4 NO3 NO2 TN TP OrthoP Si Countries (n obs*) CWBALBC4 (µmol L-1) No Su µmol L-1 µg L-1 EQR_Chla Yes: LV (92); EE (44) CWBALBC5 (mg L-1) Yes: LT (65); LV (104) CWMEDI shore;T;Sal;pH;Turb;O2D All Yes: IT (88) CWMEDIIAdriatic Yes: IT (336) CWMEDIIThyrrenian Yes: IT (245) CWMEDIIIE -- Yes: GR/CY (99) CWNEA1-26A (µM) Turb;flush Wi Log Yes: FR (45); RoI (45); UK(13); ESWCC (8); NO/ESEC/ESGC (23) CWNEA1-26B TidalRangTurb;flush Yes: FR/NL (7); UKs (41); UKn (16); BE (8) CWNEA1-26C Yes: DK(5);DE(3) CWNEA1-26E Yes: PTsUpW/ES (27); PTUpW (9) CWNEA3-4 no boundaries (14)

1 EQR Boundaries Phytoplankton Type of data available normalising data Common Type Country Dataset H/G G/M M/P P/B TRWBALBT1 LT ds1 0.83 0.57 0.39 0.29 PL ds2 0.77 0.61 0.5 0.4 TRWMEDpolyCL IT/GR ds3 0.78 0.51 -- FR ds4 0.71 TRWNEA11 no boundaries   CWBALBC4 LV ds5 0.82 0.67 0.33 0.23 EE ds6 CWBALBC5 ds7 0.65 0.2 ds8 0.87 0.6 0.28 0.21 CWMEDI IT ds9 0.85 0.62 CWMEDIIAdriatic ds10 0.81 CWMEDIIThyrrenian ds11 0.84 CWMEDIIIE GR/CY ds12 0.66 0.37 CWNEA1-26A ds13 RoI ds14 0.60 UK ds15 0.8 ESWCC ds16 0.44 NO/ESEC/ ESGC ds17 CWNEA1-26B FR/NL ds18 UKsouth ds19 0.63 Uknorth ds20 BE ds21 CWNEA1-26C DK ds22 0.7 DE ds23 CWNEA1-26E PTsUpW/ES ds24 PTUpW ds25 0.56 CWNEA3-4 CW BLACK SEA no data available normalising data

2 Main issues encountered low number of observations (normalising data) overlap of EQS categories (scattered data) insufficient coverage of the gradient of disturbance EQR range >>>1 outliers // range modelled interaction between explanatory variables: nutrients (& other) effects of other factors e.g. pressures (wedge shape data) Toolkit Statistical Analyses: Linear Regression Type II Categorical analysis (4 approaches ) Multivariate Linear Regression Quantile Regression – ongoing not in the toolkit yet

2 Main issues encountered low number of observations (normalise data?) Denmark and Germany CW NEA 1-26C DK DE n 5 3 G/M 0.4 0.6 max EQR 0.275 0.54 n = 8 different EQR boundaries insufficient gradient coverage

2 Main issues encountered overlap of EQS categories (scattered data) Latvia ds5 CW BAL BC4 Estonia ds6 CW BAL BC4 Poland ds2 TRW BAL BT1

2 Main issues encountered insufficient coverage of the gradient of disturbance Italy and Greece ds3 TRW MED polyCL France ds4 TRW MED polyCL In particular if it is in the G/M boundary (good/not good)

2 Main issues encountered EQR range >>>1 Latvia ds5 CW BAL BC4 EQR boundaries set within [0-1] range. Able to capture response signal? Italy ds9 CW MED I

2 Main issues encountered outliers // range modelled Estonia ds6 CW BAL BC4

2 Main issues encountered interaction between explanatory variables: nutrients (& other) Italy ds10 CW MED II Adriatic

2 Main issues encountered effects of other factors e.g. pressures (wedge shape data) Latvia ds7 CW BAL BC5

Summary of toolkit analyses preliminary results 3 Toolkit analyses tested Summary of toolkit analyses preliminary results

Poland ds2 TRW BAL BT1 TN TP

Poland ds2 TRW BAL BT1 Great EQR/EQS classes overlap across nutrient ranges Maybe look for interaction

3 Toolkit analyses tested

3 Toolkit analyses tested

3 Toolkit analyses tested Latvia ds2 TRW BAL BT1 TN TP TP range G/M 25th 75th H/G 25th 75th

3 Toolkit analyses tested Italy ds10 CW MED II Adriatic

3 Toolkit analyses tested TN TP Italy ds10 CW MED II Adriatic EQR ~ TN+TP

3 Toolkit analyses tested TN LQR 90th Italy ds10 CW MED II Adriatic EQR range >>>1 (G/M = 0.6): effect on nutrient boundaries derived? Try in a dataset EQR [0-1]. Outliers TN QRrqss 90th 80th 70th 50th 20th 90th

4 Thank you! Complete analyses for the remaining CW datasets Next steps Complete analyses for the remaining CW datasets Consider all other nutrients available? (and for TRW NEA11 if IC EQR boundaries are finalised) Compare results obtained with nutrient boundaries available in each region (MS, RSCs) Further test statistical approaches such as Mv and QR Discuss with MS the preliminary results obtained Thank you!