1. ECOSTAT Ispra, 20.-21. March 2012 Eastern Continental GIG Phytoplankton

2. Countries involved IC common types Dataset available IC option National methods Pressure selection Boundary setting Pressure-response relationships Country effect investigation Results of comparability analysis Reference community description IC feasibility and compliance check Flaws Explanations Outline

3. HU RO BG Eastern Continental GIG (established in February, 2008)

4. Countries and experts involved Bulgaria: Mina Asenova, Boril Zadneprovski, EEA (Maya Stoineva) Hungary: Gábor Borics (GIG lead), CER Romania: Gabriel Chiriac, Stefan Miron, Levente Nagy, R OWATER )

5. Common IC typeType characteristicsMS sharing IC common type EC1 Lowland very shallow hard water Altitude (m. a.s.l.) <200m Depth (mean depth, m) <3m Conductivity (uS/cm) 300-1000 Alkalinity (meq/l) 1-4 Surface area (km 2 ) <10 Bulgaria, Hungary, Romania EC2 Lowland very shallow, very high alkalinityhard water Altitude (m. a.s.l.) <200m Depth (mean depth, m) <3m Conductivity (uS/cm) >1000 Alkalinity (meq/l) >4-5 Surface area (km 2 ) <10 Hungary EC3 Middle altitude shallow Altitude (m. a.s.l.) 200-800m Depth (mean depth, m) <6m Conductivity (uS/cm) 200-1000 Alkalinity (meq/l) 1-4 Surface area (km 2 ) <10 Bulgaria, Romania EC4 Middle altitude deep Altitude (m. a.s.l.) 200-800m Depth (mean depth, m) <6m Conductivity (uS/cm) 200-1000 Alkalinity (meq/l) 1-4 Surface area (km 2 ) <10 Bulgaria, Romania EC5 High altitude deep Altitude (m. a.s.l.) >800m Depth (mean depth, m) >6m Conductivity (uS/cm) 200-1000 Alkalinity (meq/l) 1-4 Surface area (km 2 ) <10 Bulgaria, Romania Common IC types

6. Pressure dataHUROBG GroupParameter TP 273770 ChemistryTN 273770 COD 27377 0 LakeuseIntensity of fishing 2080 (fish stock) Lakeyears 50180 Database Bulgaria could not provide phytoplankton and stressor data, therefore, BG did not participate in the phytoplankton intercalibration.

7. Option 3: direct comparison of the HU and RO national metrics IC Option

8. Composition metric: Biomass metric (Chl-a): Multimetric index: Hungarian phytoplankton index Romanian phytoplankton index Number of taxa (TAX)5% Relative biomass abundance of cyanobacteria (CYANO)20% Total biomass (BIO)20% Chlorophyll-a (CHL) 50% Diversity index /Shannon-Wiener/ (ID)5% The calculation formula: 0.05×TAX+0.2×CYANO+0.2×BIO+0.5×CHL+0.05×ID = ROmultimetric index National methods

9. Bloom metric Since neither the evenness nor the relative abundance of cyanobacteria seemed to be applicable in the EC-GIG as bloom metric, the use of absolute abundance of cyanobacteria is proposed. Cyanobacteria biomass < 10mg/l: the values of the national metrics should be applied Cyanobacteria biomass > 10mg/l: National EQR > 0.6 The EQR should be reduced by 0.2 National EQR < 0.6 No change

10. TP CHL-a relationship for Hungarian standing waters Stressor selection

12. TP: 94 and 250µgl -1 TN: 1310 and 2370µgl -1 COD: 31.83 and 50mgl -1 321321 Calculation of the multimetric stressor 1: Benchmark 2: Impacted 3: Heavily impacted Pressure selection

14. Benchmark selection criteria 1.absence of major point sources in catchment, 2.no (or insignificant) artificial modifications of the shore line, 3.complete zonation of the macrophytes in the littoral zone, 4.no mass recreation (camping, swimming, rowing), 5.no or low fishing activity ( fishstock < 50kg/ha )

15. Latitude Longitude Atkai-Holt Tisza alsó vége, Algyő46 o 23' 04. 03"20 o 11' 09. 32" Egyek-Kócsi Tározó, Górés47 o 34' 04. 65"20 o 56' 12. 08" Morotvaközi holt meder, Egyek47 o 39' 51. 07"20 o 56' 57. 13" Snagov 44 o 42' 50. 81"26 o 09' 54. 30" Szelidi-tó 46 o 37' 26. 04"19 o 02' 29. 77" Szöglegelői Holt Tisza48 o 04' 15. 51"21 o 27' 41. 14" Tiszadobi Holt-Tisza, Darab Tisza48 o 01' 24. 18"21 o 11' 24. 03" Tiszadobi Holt-Tisza, Falu-Tisza48 o 01' 09. 18"21 o 10' 56. 68" Tiszadobi Holt-Tisza, Malom-Tisza kanyar48 o 01' 13. 72"21 o 11' 26. 53" Tiszadobi Holt-Tisza, Malom-Tisza úszóláp48 o 00' 44. 05"21 o 12' 32. 91" 10 lakes with 25 lake-year data Benchmark lakes

16. Chlorophyll-a in the benchmark, impacted and heavily impacted lake populations Bad Poor Moderate Good High

17. 0.8 0.6 0.4 0.2 Setting boundaries for the HU composition metric Boundary setting

18. HGMPBHGMPB Setting boundaries for the Romanian metric

19. Pressure-response relationships

20. Significant country effects were not found in relationships between national EQR data vs pressure (MAS), Country effect investigation

22. The average absolute class difference is 0.291. The average class difference is 0.255 Results of the comparison using the calculation sheet proposed by the JRC are shown below. The level of acceptable bias is smaller than proposed +/-0.25 value, therefore no additional boundary harmonisation is needed. Results of comparability analysis

23. Reference community description Phytoplankton composition of the lakes in reference status can be characterised by the frequency distribution of the functional groups having higher factor numbers (F7-9) These functional groups (F=9) are A: Urosolenia longiseta, Cyclotella comensis; B: Aulacoseira subarctica, A. islandica; N: Cosmarium spp., X2 Rhodomonas; X3: Chrysococcus spp.; U Uroglena spp. (F=7) D: Fragilaria acus, Stephanodiscus hantzschii, Y: large size cryptomonads; Lo: dinoflagellates; MP: meroplanctic diatoms; K: Aphanothece spp. The relative abundance of these taxa has to be higher than 80%. Algae that belong to functional groups that have factor values F=5; C: Stephanodiscus neoastraea, Aulacoseira ambigua; W2 Trachelomonas spp.; P: Aulacosira granulata, Fragilaria crotonensis; Q: Goniostomum semen, G, latum can also be present but rarely dominate the phytoplankton. The ratio of those taxa that are considered as undesirable in this lake type lower than 30% These groups are the J: Chlorococcalean green algae, the bloom-forming cyanobacteria like M: Microcystis, H1: Anabaena and Aphanizomenon spp. Sn: Cylindrospermopsis raciborskii, S1: Limnothrix spp. Planktothrix spp. S2: Spirulina spp. Arthrospira spp. Biomass expressed in chlorophyll-a can fluctuate during the vegetation period, but the annual mean Chl-a maxima does not exceed 50µgl -1. The mean Chl-a value in the growing season is less than 25 µgl -1. Secchi transparency usually higher than 1.5ms. Blooms do not occur. Decrease of the oxygen concentration might occur towards the deeper layers, but oxygen depletion never develops. Normalised value of the HLPI > 0,8.

24. IC feasibility check Typology -intercalibration is feasible for EC1 lake-type Assessment concept -comparable in terms of habitats, (photic layer is sampled) Relationship with pressure -both national methods have good relationship with pressure (when applying national methods to IC dataset)

25. Representative sampling ✓ All relevant data covered by the sampling ✓ Taxonomic level meets adequate confidence and precision ✓ Five classes of ecological status ✓ All parameters indicative of the BQE ✓ WFD-compliant national boundary setting ✓ Adapted to common intercalibration types ✓ Results in EQR ✓ Type-specific near-natural reference conditions? Compliance criteria

26. Contradiction Contradiction: there are not reference lakes but most of the lakes are assessed as good or high quality. T here are reference lakes, or boundaries are not set correctly. Identification of the alternative benchmark lakes on the gradient of impact is not clear. Separation of the alternative benchmark lakes from reference lakes is not clear. Good status boundary is closer to the median of heavily impacted lakes as to the median of benchmark lakes.

27. Tasks in EC-GIG Data collection (more data for the lower quality classes.) Overview of the H/G and G/M boundaries. Setting more stringent boundaries. Clear separation of the bechmark and reference lakes needed. Updating reference community description.

28. Stressor response relationship with more stringent boundaries

30. Stressor response relationship ( with more stringent boundaries)

31. Reference lakes are separated

32. Acknowledgements This work was financially supported by the HU Ministry of Rural Development, the RO Ministry of Environment and Water Hungarian Academy of Sciences BG – Mina Asenova BG – Maya Stoineva HU – Gábor Várbíró RO – Gabriel Chiriac RO – Stefan Miron RO – Levente Nagy

33. Thanks for your attention!

35. Relationship between the secchi transparency and the depth of oxigen depletion (<2mg/l)

36. Relationship between the chl-a and Secchi transparency 40ugl -1

37. Number of taxa (TAX)5% Relative biomass abundance of cyanobacteria (CYANO)20% Biomass (BIO)20% Chlorophyll-a (CHL) 50% Diversity index Shannon-Wiener (ID)5% The calculation formula is: 0.05×TAX+0.2×CYANO+0.2×BIO+0.5×CHL+0.05×ID = ROmultimetric index Correlation matrix (MAS and different metrics)

38. Latitude Longitude Egyek-K ó csi T á roz ó, G ó r é s47 o 34' 04. 65"20 o 56' 12. 08" Tiszadobi Holt-Tisza, Falu-Tisza48 o 01' 09. 18"21 o 10' 56. 68" Tiszadobi Holt-Tisza, Malom-Tisza ú sz ó l á p48 o 00' 44. 05"21 o 12' 32. 91" Lakes considered reference

40. Relationship between the landuse categories and the Chl-a EQR

41. 2-5 years’ average Pressure-response relationship