Snejana Moncheva1, Laura Boicenko 2 1Institute of Oceanology-BAS, Parvi Mai str., No 40, P.O.Box 152, Bulgaria 2NIMRD “Grigore Antipa”, Mamaia bul., No 300, Constanta 3, RO IBSS,2 Nakhimov Ave. Sevastopol, Ukraine COASTAL AND TRANSITIONALWATERS INTERCALIBRATION WORKSHOP Casa Don Guanella, November, 2011

Exposed-moderately exposed shallow, mezohaline RO BG Common WB type

COMMON METRICS Total abundance [cells/l] Total biomass [mg/m3] Chlorophyll a [mg/m3] Taxonomic composition 1)C strategy species - colonists, sensu Smayda, Reynolds (2003), as a proportion of the total abundance of Dinoflagellates - (DE %) Heterocapsa rotundata, Heterocapsa triquetra, Scrippsiella trochoidea, Prorocentrum minimum, Prorocentrum micans and Gymnodinium/Gyrodinium ; the classification boundaries are based on expert judgement, the high (2%) value is selected as an averaged value for historical data set (only for summer season) (source: Smayda, T.J. and C.S. Reynolds “Strategies of marine dinoflagellate survival and some rules of assembly”. Journal of Sea Research 49, ) 2)The sum of the Abundance [cells/l] of species of 3 taxonomic groups (microflagellates + Euglenophyceae + Cyanophyceae) as a % from the total abundance of the phytoplankton community with the suggested classification boundaries as shown below. The classification boundaries are based on expert judgement, the high (2%) value is selected as an averaged value for historical data set (only for summer season).

Diversity (non-mandatory parameter) Two nonparametric indices – Biodiversity Index Menhinick (1964) and Evenness Index Sheldon (1969) developed originally as a phytoplankton metric for the Mediterranean Sea (source: Spatharis S., G. Tsirtsis, “Ecological quality scales based on phytoplankton for the implementation of Water Framework Directive in the Eastern Mediterranean”, Ecological Indicators, ). The proposed classification boundaries are not changed. Frequency and intensity of algal blooms - So far a classification system based on frequency and intensity of microalgal blooms has not been developed due to the lack of relevant data set and adequate frequency of sampling. The reference data ( ) are seasonal, as well as the recent data which makes quantification and the application of the 6 years monthly frequency records as suggested by some expert groups (WFD ITR, 2007) impossible. The records for the species that were the most frequent drivers of ecosystem disfunction (Prorocentrum minimum and the related hypoxia events in summer during the eutrophication period – Moncheva et al., 1995, 2001) are of little use due to the shifts in the phytoplankton taxonomic composition after 2000 (Moncheva et al, 2006).

BIOMASS [mg/m3] - Summer MetricHighGoodModeratePoorBad Biomass (mg/m 3 ) – 5000>5000 EQR< > 0.17 Classification system CHLOROPHYLL a [mg/m3]Summer MetricHighGoodModeratePoorBad Chl a, µg/l< – – – 7.10> 7.10 EQR < – – > 0.19 ABUNDANCE [cells/l] Summer MetricHighGoodModeratePoorBad Total abundance (10 3 cells/l) >3000 EQR< >0.16 MetricHighGoodModeratePoorBad Index Menhinick (1964) Index Sheldon (1969) Taxonomic metricHighGoodModeratePoorBad Microflagellates, Euglenophyceae, Cyanophyceae (МЕС) - % total abundance >75 C strategy species -% of the total abundance of Dinoflagellates) >75 EQR< >0.25

REFERENCE CONDITIONS Historical data from “reference” period 1960 – The threshold “bad” was based on the 90 percentile of the long-term data set from the highly eutrophication period (80-ies) and expert judgement N, B and Taxonomic based metrics Chlorophyll a BG- Due to lack of chlorophyll a measurements from the reference period and before 1990, the 10 percentile from a long-term data set ( ) was determined and its applicability tested against the results from the analysis of the phytoplankton data set – RO historical data (1976 – 1978, the earliest data from the Romanian coastal waters) using 90th percentile and expert judgement

For the diversity indexes the reference conditions and boundaries set for the Mediterranean Sea developed by Spatharis S. and G. Tsirtsis (2010) are used Combination rule of metrics As the single metrics reflect different aspects of phytoplankton response to environmental pressures, an integrated biological index (IBI) was calculated assuming equal weight of the single components: Abundance [cell/l]; Biomass [mg/m3], the taxonomically based indices (MEC% and DE%). The IBI was calculated as an average score of the EQR value calculated for each sample and for each single metrics to yield a final integrated score (EQR- IBI) based on which the final ecological category is assigned (the combination rule). For this integrated IBI we apply the equidistant EQR class boundaries (Spatharis S., G. Tsirtsis, 2010) EQR-IBI = (EQR-N+EQR-B+EQR-DE%+EQR-MEC%)/4 EQR-IBI-1= (EQR-N+EQR-B+EQR-DE%+EQR-MEC%+EQR-SH + EQR-M )/6 All the metrics were intercalibrated for the summer season We take only summer season because it is considered critical for the ecological status

ROMANIA – sampling/stations DATA BASE

BULGARIA – sampling/stations

Pressure data Agricultural diffuse inputs - - the data represented by total agriculture surface (ha) in county - - surface of cultivated area (ha) and percent (%) in county Agricultural area as % from the 1.5 km coastal land Number of stocks breeding farms and domestic animals per water body for the year 2003 Lack of adequate data of fertilizers or nutrients from diffuse sources River input - - nutrients data as km 3 /year at Sulina branch Average annual discharge and total N and P loads [t/y] for of major rivers Domestic discharges (nutrients) - - Data from WWTP North, South, Eforie South, Mangalia - - sChemical parameters registered are: CBO5 (mgO2/l), NH4, NO2, NO3, Nt, Pt (mg/l), in total 1446 of data; WWTP ‘s discharge and nutrient N &P annual loads [t/y] for the period Organic loads (BOD5) - - Data from WWTP Constanta North, South, Eforie South, Mangalia; 391 number of BOD5 (mgO2/l) data WWTP ‘s discharge and annual loads of BOD5 [t/y] - irregular data Industrial discharges - - Data from Rompetrol refinery, SC Canopus Star, U.M. Midia and Mangalia - - A number (289) of chemical parameters as BOD5 (mgO2/l), NH4, NO2, NO3, Nt, Pt (mg/l), are registered Average annual data for N and P for Burgas only Urbanization - - Data are not adequate, so pressure range was calculated based on expert judgment Number of population and % of urban area in the 1.5 km coastal for the water body Tourism (nutrients) - - Data as accommodation capacity (no of places), arrivals, nights spent, indices of accommodation capacity use (%) Number of arrivals and nights spent for the resorts Port activity - - Data are not adequate, so pressure range was calculated based on expert jugdement. Data of ship inspections for Burgas and ports Inventory Pressures

Scater plot of Integrated Biological Index (IBI-EQR) to the Total pressure score by stations: A) integrated BG and RO; B) BG stations C)RO stations. Both RO and BG response is identical suggesting the applicability of common classification boundaries for M/G /H (no biogeographical differences) although the confidence is low due to the inadequacy of the data sets

EQR boundary between Reference status and High status is always set equal to 0.95 (HELCOM, 2010) and represents, together with the boundary between Good and Moderate status, fixed points for estimating the remaining boundaries We consider the span of highest classes is two times larger than the span of the next two classes so that: EQR Ref/High – EQR Good/Moderate = 2*(EQR Good/Moderate – EQR Poor/Bad ) EQR Poor/Bad = 0.19 The boundaries between High and Good status and Moderate and Poor status are defined as midpoints between the two adjacent boundaries (HELCOM, 2010): EQR High/Good = 0.5*EQR Ref/High + 0.5*EQR Good/Moderate = 0.81 EQR Moderate/Poor = 0.5*EQR Good/Moderate + 0.5*EQR Poor/Bad = 0.43

There is a gap of systematic phytoplankton data and complimentary pressure data, which is essential in the efforts for validation of the proposed metrics and the classification system with sufficient confidence The taxonomically based metrics are promissing if correlated to meaningful pressures at the necessary confidence level (enough data) The use of Pressure Index is promissing but the sites should be properly scored Frequency of sampling improved Pressure data with adequate time-spatial variability complimentary to the phytoplankton data Indicate gaps of the current intercalibration. Is there something still to be done ?