1. BLACK SEA PHYTOPLANKTON INTERCALIBRATION - BS GIG
COASTAL AND TRANSITIONALWATERS INTERCALIBRATION WORKSHOP
Casa Don Guanella, November, 2011
BLACK SEA PHYTOPLANKTON INTERCALIBRATION - BS GIG
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
5IBSS,2 Nakhimov Ave. Sevastopol, Ukraine

2. OUTLINE – MILESTONE 5
FEASIBILITY CHECK
PHYTOPLANKTON METRICS
PRESSURE/RESPONSE APPROACH
CONCLUSSIONS

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

4. Stations coordinates and depths BG RO
Profil
Station
Coordinates
Max Depth LT LG
(m)
Cazino
CZ5M
44.242
28.642 6
CZ20M
28.708 20
CT1
44.167
28.683
 Contanta
CT2
28.783 32
CTS5M
44.083
28.647
CTS20M
28.688 21
Costinesti
CS5M
43.945 7
CS10M
43.933
28.650 11
CS20M
28.677
Eforie Sud
EF5M
44.043
28.660
EF20M
28.670
Mangalia
MG5M
43.817
28.633
MG10M
43.783
28.600
MG20M
43.792
28.628
Vama Veche
VV5M
43.750
28.603
VV10M
43.733
VV20M
28.620
Water Body
Station
Coordinates
Station depth
Lat
Long
BG2BS000C001
Krapetz
43°37.113
28°36.068 21
Krapetz'
43°34.866
28°36.788 20
BG2BS000C002
Shabla
43°31.861
28°36.399
BG2BS000C003
Rusalka
43°25.46
28°33.202 23
BG2BS000C004
Kaliakra
43°22.039
28°25.032 16
Balchick
43°22.868
28°11.845
BG2BS000C013
Albena
43°19.411
28°05.801
V-Gala
43°09.753
28°00.145
BG2BS000C005
VB-III Buna
43°12.193
27°57.288
VBay
43°11.054
27°56.254
BG2BS000C006
Kamchia
43°01.638
27°54.333 19
BG2BS000C007
Dvoinitza
42°46.147
27°55.368 30
BG2BS000C008
Nesebar
42°40.838
27°46.826
Rosenetz
42°27.816
27°31.07 15
Sarafovo
42°30.150
27°48.000 36
BG2BS000C009
Koketrais
42°38.799
27°53.28 17
BG2BS000C010
Burgas 2
42°30.019
27°40.22 28
BG2BS000C011
Sozopol
42°25.963
27°43.511 40
BG2BS000C012
Maslen nos
42°20.174
27°49.206 47
Veleka
42°05.067
27°00.233 45

5. COMMON METRICS Total abundance [cells/l] Total biomass [mg/m3]
Chlorophyll a [mg/m3]
Taxonomic composition
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, )
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).

6. 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).

7. Classification system
BIOMASS [mg/m3] - Summer
Metric
High
Good
Moderate
Poor
Bad
Biomass (mg/m3)
750
2501– 5000
>5000
EQR
<0.80
0.8
0.42
0.17
> 0.17
CHLOROPHYLL a [mg/m3]Summer
Metric
High
Good
Moderate
Poor
Bad
Chl a, µg/l
< 1.5
1.5 – 2.05
2.05 – 3.19
3.19 – 7.10
> 7.10
EQR
< 0.80
0.80 – 0.67
0.67 – 0.43
> 0.19
ABUNDANCE [cells/l] Summer
Metric
High
Good
Moderate
Poor
Bad
Total abundance (103 cells/l)
500
>3000
EQR
<0.80
0.8
0.45
0.16
>0.16
Metric
High
Good
Moderate
Poor
Bad
Index Menhinick (1964)
Index Sheldon (1969)
Taxonomic metric
High
Good
Moderate
Poor
Bad
Microflagellates, Euglenophyceae, Cyanophyceae (МЕС) - % total abundance 2 25 50 75
>75
C strategy species -% of the total abundance of Dinoflagellates)
EQR
<0.75
0.75
0.50
0.25
>0.25

8. 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

9. 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

10. COMMON DATA SET Average BAC [cells/l] stdev CV% 2318659 261722 11.3
Average abundance [cells/l] stdev and CV [%] by partners
Average BAC [cells/l]
stdev
CV% RU
261722
11.3 BG
26535
7.0 RO
UK2
294579
7.8
All
613651
20.0
Average B [mg/m3]
stdev
CV% RU
372
19.2 BG
103
4.5 RO UK 4
0.16
All
489
19.5
Based on testing the reproducibility of the in-house analysis (replicates) and employing the CV < 20% assumption for the total numerical abundance the results reveal a good reproducibility of the in-house replicates and very close results between the different labs, with the exception of Ukraine, where the difference was between 25-30%

11. Bacillariophyceae Dinophyceae Prymnesiophyceae Small flagellates
1.Cerataulina pelagica
2.Chaetoceros socialis
3.Chaetoceros curvisetus
4. Nitzschia tenuirostris
5. Proboscia alata
6. Pseudo-nitzschia p-delicatissima
7. Skeletonema costatum
8.Thalassionema nitzschioides
Dinophyceae
Ceratium fusus -1
Gyrodinium fusius -2
Heterocapsa triquetra -3
Prorocentrum compressum -4
Prorocentrum micans -5
Protoperidinium bipes -6
Protoperidinium granii -7
Scrippsiella trochoidea -8
Prymnesiophyceae
Emiliania huxleyi
Small flagellates
For the common species biovolume comparative analysis reveal very close values between BG and RO

12. Chlorophyll a [mg/m3]
Station BG RO
RUS
S-BG01-05 (M301)
7.53
8.08
7.13
7.85
6.11
7.97
10.19
7.92
average
7.54
8.70
7.19
stdev
0.42
1.29
0.95
CV%
5.6
14.8
13.3
S-BG01-13
0.61
0.68
0.46
0.72
0.59
0.38
0.69
0.48
0.00
0.02
0.15
3.06
30.41
S-BG01-08 (M304)
6.33
6.24
4.18
6.32
6.29
3.82
6.86
6.84
4.71
6.50
6.46
4.24
0.31
0.33
0.45
4.75
5.16
10.50
The results of chlorophyll a measurements reveal good in-house reproducibility for BG and RO and higher than 10% difference for RU The difference between the BG and RO data is within the (range average ±s 1stdev)

13. DATA BASE
ROMANIA – sampling/stations

14. BULGARIA – sampling/stations

15. Inventory Pressures 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 km3/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

18. Pressures by stations

19. Correlation Coefficient r
Romania
Bulgaria
Correlations for summer data ( ) Marked correlations are significant at p < N=46 (Casewise deletion of missing data)
NO3 (µM)
NO2 (µM)
NH4 (µM)
DIN (µM)
DIP (µM)
Phytoplankton Abundance (cells/l)
-0.10
0.33
0.28
Phytoplankton Biomass (mg/m3)
-0.27
0.08
0.06
0.05
0.10
Chl a
-0.13
0.32
0.31
0.41
Correlations for hot spot data ( ) Marked correlations are significant at p < N=11 (Casewise deletion of missing data)
NO3 (µM)
NO2 (µM)
NH4 (µM)
DIN (µM)
DIP (µM)
Phytoplankton Abundance (cells/l)
-0.07
0.87
0.64
0.41
Phytoplankton Biomass (mg/m3)
-0.16
0.71
0.53
0.52
0.35
Chl a
-0.17
0.83
0.79
0.78
0.72
Correlation Coefficient r
Interpretation
Slight, almost negligible correlation
Low, quite small correlation
Moderate correlation
High correlation
Very high correlation

21. Summary of Metric values and physicochemical parameters averaged per station (common RO-BG set)

22. Statistical summaries of correlation coefficients (in red statistical significant at p< .05000)

24. Pressure scoring for the common type sites (1-low; 2-moderate; 3-high)

26. 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

27. Indicate gaps of the current intercalibration
Indicate gaps of the current intercalibration. Is there something still to be done ?
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

28. THANK YOU FOR THE ATTENTION?
THANK YOU FOR THE ATTENTION

29. 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 – EQRGood/Moderate = 2*(EQR Good/Moderate– EQRPoor/Bad)
EQRPoor/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):
EQRHigh/Good = 0.5*EQR Ref/High + 0.5*EQRGood/Moderate = 0.81
EQRModerate/Poor = 0.5*EQR Good/Moderate + 0.5*EQRPoor/Bad = 0.43

30. EQR-IBI- Pressure index