Template for the Milestone Reports s1

EUROPEAN COMMISSION DIRECTORATE GENERAL JRC JOINT RESEARCH CENTRE Institute of Environment and Sustainability

WFD Intercalibration Phase 2: Milestone 4b report

Coastal Waters Water category/GIG/BQE/ GIG Black Sea horizontal activity: Macroinvertebrates Information provided by: Gabriel Chiriac (?) with preparation of earlier provided info from Member States by Wendy Bonne (JRC)

1. Organisation

1.1. Responsibilities Indicate how the work is organised, indicating the lead country/person and the list of involved experts of every country:

GIG Black Sea Coordinator: Gabriel Chiriac, Romania Romania lead: Camelia Dumitrache Bulgaria lead: Antoaneta Trayanova ,Valentina Todorova

1.2. Participation Indicate which countries are participating in your group. Are there any difficulties with the participation of specific Member States? If yes, please specify:

Romania and Bulgaria

1.3. Meetings List the meetings of the group:

13.01.2010, Varna, Bulgaria 21 - 22 October 2010, Varna, Bulgaria 18 May 2011, Varna, Bulgaria 19-20 September 2011, Constanta, Romania

2. Overview of Methods to be intercalibrated

Identify for each MS the national classification method that will be intercalibrated and the status of the method 1. finalized formally agreed national method, 2. intercalibratable finalized method, 3. method under development, 4. no method developed Member State Method Status BG & RO Assessment method for coastal intercalibratable finalized method waters using macrozoobenthos

3. Checking of compliance of national assessment methods with the WFD requirements (April 2010 + update in October 2010)

Do all national assessment methods meet the requirements of the Water Framework Directive? (Question 1 in the IC guidance) Do the good ecological status boundaries of the national methods comply with the WFD normative definitions? (Question 7 in the IC guidance)

3.1. Methods and required BQE parameters

In the table below it has to be indicated if all relevant parameters indicative of the biological quality element are covered (see Table 1 in the IC Guidance). A combination rule to combine parameter assessment into BQE assessment has to be defined. If parameters are missing, Member States need to demonstrate that the method is sufficiently indicative of the status of the QE as a whole.

Full Disturbance Taxa Combina- Member Taxonomic Bio- BQE Abundance a sensitive Diversity indicative of tion rule of composition mass State method taxa pollution metrics Not in strict Not in strict sense Shannon sense (only Bulgaria (only relative –Wiener’s Specific composition of 5 sensitivity M-AMBI & Yes abundance of 5 index, No opportunistic 5 preclassified classes Romania preclassified species species sensitivity sensitivity classes) richness classes)

- The macroinvertebrates experts, from Romania and Bulgaria, agreed to use to assess the ecological status of the selected common type: M-AMBI index. - During the meeting in Varna in May 2011 for the purposes of the IC exercise Bulgaria and Romania agreed to use samples from one and the same habitat - from 20 m depth. - Both countries agreed to use one and the same sampling season – summer period (July) and use one method for sampling and processing as well as the same indices to assess benthos community. - Romania explain that is not difference in assessment between coastal and transitional waters: M-AMBI is used for coastal and transitional waters;

Method adaptation for AMBI:

The boundaries between the ecological classes are those identified by Borja et al., (2000, 2003) and Muxica et al., (2005). Different from the original species ecological classification, the polychaete worm Aricidea claudiae was moved from group I (species very sensitive to organic enrichment) to group III (species tolerant to excess organic matter). The arguments in support of this shift are that in the Bulgarian Black Sea Aricidea claudiae occurs together with and shows similar ecological preferences as Heteromastus filiformis (ecological group IV), Oligochaeta (ecological group V), Nephtys hombergii (ecological group II), and Melinna palmata (ecological group III). Therefore the middling ecological group from the above – group III is selected as characteristic of A. claudiae. Another argument is the fact that Aricidea claudiae attains high abundance in organically enriched muddy sediments (Todorova et al., 2008). 3.2. National reference conditions

Member Type and period of Number of Location of reference Reference criteria used for State reference conditions reference sites sites selection of reference sites For the Bulgarian Black Sea coastal waters, no reliable data of the “pristine” period Unaffected areas are regarded (before the 1970s) collected as absent in the Bulgarian Black with the same methodology Sea coastal waters nowadays. as we use today, exist. Use The remaining option in of historical data is therefore 5 points at the establishment of condition not an option in determining Dvoinitsa, Irakli, Cocketrise, Bulgaria Bulgarian Black comparable to a reference is to reference conditions. Varvara, Veleka Sea derive it from areas as unaffected Reference values are by human activities as possible developed from the current using the data of slightly best available conditions disturbed benthic communities based on an expert (having at least good status). judgement and knowledge of the conditions under evaluation. The option in establishment of Reference values are condition comparable to a developed from the best 4 sites at the reference is to derive it from available conditions based Eforie South, Costinesti, Romania Romanian Black areas as unaffected by human on an expert judgement and Mangalia, Vama Veche. knowledge, of the conditions Sea activities as possible using the under evaluation data of slightly disturbed benthic communities 3.3. National boundary setting

In the table below it has to be indicated how the High, good and moderate ecological status are set (Boundary setting procedure) in line with the WFD’s normative definitions Type of boundary setting: BSP: Expert judgment – statistical method Member Specific approach for Specific approach for G/M – ecological discontinuity – or tested H/G boundary boundary State mixed for different against boundaries? pressure

Expert judgment 1. Shannon index: The boundaries between the different water status classes are determined as it is 1.Shannon index: H/G assumed that each class range boundary = 4. The (20%) is covering equal ranges from reference value for water 1.Shannon index: G/M boundary the whole status range (100%). bodies with sandy and = 3.1. The boundaries between 2. AMBI: Boundary values are the mixed sediments is derived the ecological classes are set as same as derived by Borja et al., with the assumption that the percentage from average (2000, 2003) and Muxica et al., average community reference values. The interval of (2005). The estimation of the index is diversity index of stations 0.2 between the ecological status optimized by reclassification from reaching good ecological boundaries is equally scaled (80 one ecological group to another status constitutes 75 % from % for good, 60 % for moderate, Bulgaria because they have shown high Yes the high status. etc.) ecological similarity with the species 2. AMBI H/G boundary = 1.2 2. AMBI G/M boundary = 3.3 the from the new group under Black Sea the reference value is boundary identified by Borja et conditions. derived on the basis of the al., (2000, 2003) and Muxica et 3. M-AMBI – the boundaries between domination of sensitive and al., (2005) classes are the same as determined indifferent species. 3. M-AMBI G/M boundary = 0.55 as a result of the intercalibration 3. M-AMBI H/G boundary = the default EQR boundary process for the North Atlantic ocean 0.85 the default EQR according to Borja et al., 2006 (Borja et al., 2006). The index is boundary according to Borja adopted for the conditions of the et al., 2006 Black sea by setting specific boundaries for high/good and poor/bad status of the Shannon index and number of species S.

Romania Expert judgment, Equidistant division 1. H/G boundary H’ = 4 1.Shannon index: G/M boundary YES of the EQR gradient The reference value for = 3 - The MP boundary was set where water bodies with sandy and AMBI G/M boundary = 3.3 the the lower confidence limit of the mixed sediments is derived boundary identified by Borja et sensitive and upper confidence limit with the assumption that the al., (2000, 2003) and Muxica et of the tolerant species intersect. At average community al., (2005) this point there is a low probability diversity index of stations 3. M-AMBI G/M boundary = 0.55 that sensitive species would be at reaching good ecological the default EQR boundary 50% cover, but a high probability that status constitutes 75 % from according to Borja et al., 2006 tolerant species would be at 50% the high status. cover. Very sensitive species are still present, but the community has thus undergone a moderate change. 2. AMBI = 1.2 - The PB boundary is a point at 3. M-AMBI H/G boundary = which highly sensitive species are 0.85 the default EQR extinct and there are very few boundary according to Borja sensitive species. Here the et al., 2006 community is dominated by tolerant species. Clarify if there are still gaps in the national method descriptions information. Summarise the conclusions of the compliance checking:

4. Methods’ intercalibration feasibility check

Do all national methods address the same common type(s) and pressure(s), and follow a similar assessment concept? (Question 2 in the IC guidance)

4.1. Typology Describe common intercalibration water body types and list the MS sharing each type Common IC type Type characteristics MS sharing IC common type IC type 1 Mesohaline, microtidal, shallow, mixed Romania – yes substratum, exposed Bulgaria - yes

Bulgaria Identified 6 WB types are grouped into 2 Also applicable for Romania groups depending on the most important for the distribution of macrozoobenthos factor: bottom substrate. Classification system is developed for types with muddy and sandy/ mixed substrate. What is the outcome of the feasibility evaluation in terms of typology? Are all assessment methods appropriate for the intercalibration water body types, or subtypes? Method Appropriate for IC types / subtypes Remarks Method BG IC type 1 CW-BL1

Method RO IC type 1 CW-BL1

Conclusion Is the Intercalibration feasible in terms of typology ? Yes

The map for the common type will be distributed. RO – Map with the WBT (southern part of the Romanian littoral ) mixed substratum/depths-20 m

Figure 1. Monitoring sampling network of the Romanian Black Sea coastal waters (southern littoral) Figure 2. Monitoring sampling network of the Bulgarian Black Sea coastal waters.

4.2. Pressures Describe the pressures addressed by the MS assessment methods

Method/ Member Strenght of Metrics Pressure Pressure indicators Amount of data State relationship tested Non-point see tables 1 and and point 2; data for the M-AMBI and sources of period 2002-2010 pH of bottom pollution, physico-chemical data, pressure index about Non-point waters (p = - urbanisation, Bulgaria M-AMBI (Volckaert 2007), pressure index with and point sources 0.737); tourism, port activities, data available of pollution, AMBI and As industry urbanisation, in sediments (Table 4) tourism, port (p = 0.948) activities, industry Data for the M_AMBI and Non-point period 2002-2011 heavy metals and point about Non-point in sediments sources of Romania M-AMBI Chemical data, presure index, and point sources Cu: p=0.0077 pollution, , tourism, port pressure index with data available of pollution, Cr:p=0.0073 activities, tourism, port Pb: p=0.0002 activities, industry Cd: p=0.0079

Table 1. Physico-chemical data in bottom waters supporting the biological data (BULGARIA - BG) oxidati Phosp

WB station month.year replicates BOD5 on total Р hates N-NH4 N-NO2 N-NO3 total N ТОС Si рН О2 DO% BG2BS000C002 Tiulenovo 07.06 1 7,6 73,6 6,04 1 9,04 1 3,05 1 2 0,017 <0.003 <0.018 0,001 <0.1 0,235 2,41 0,159 8,25 7,4 69 BG2BS000C003 Rusalka 6,05 1 1,1 0,038 <0.018 0,008 0,548 3,345 0,444 8,18 7,03 78,3 9,05 1 11,05 1 7,06 1 6,06 72,2 BG2BS000C013 Albena 07.06 1 6,2 3,05 1 6,05 1 0,82 0,054 0,007 0,133 <0,005 0,35 8,39 7,04 89 BG2BS000C005 Varna Bay 9,05 1 11,05 1 7,06 1 BG2BS000C006 Kamchia 07.06 1 3,05 1 9,20 0,08 0,08 0,08 0,03 3,98 0,48 3,42 0,31 7,32 71,90 6,05 1 3,52 0,01 0,01 <0.018 2,40 0,03 0,47 3,92 0,22 8,07 5,42 Irakli 9,05 1 11,05 1 BG2BS000C007 07.06 1 8,07 1 <1.0 0,019 0,029 <0,01 0,3 0,004 0,482 2,2 0,982 8,07 2,06 21 Dvoinitsa 10,08 3 9.10 3 8,02 3 11,02 1 3,03 1 6,03 2 6,04 2 9,04 1 3,05 1 11,50 0,02 <0.013 0,05 0,07 4,86 0,37 4,09 0,22 7,25 67,50 BG2BS000C009 Cocketrise 6,05 1 5,32 0,00 0,01 0,05 2,40 0,02 0,51 4,32 0,32 8,61 4,29 9,05 1 11,05 1 7,06 1 0,012 0,08 <0.01 0,015 0,2 0,263 4,28 0,1 8,33 8,07 1 <1.0 0,01 <0.013 <0.01 0,3 5E-04 0,413 2,54 0,673 8,35 2,7 26,9 8,08 1 9.10 3 07.06 1 <1.0 <0.01 <0.03 <0.01 <0.005 0,2 0,286 4,99 0,17 8,24 8,07 1 <1.0 0,011 <0.013 <0.01 0,003 0,3 0,381 2,46 1,69 8,15 BG2BS000C010 Burgas 8,08 1 9.10 3 07.06 1 <1.0 <0.01 <0.03 <0.01 <0.005 0,3 0,303 4,62 0,41 8,1 Varvara 8,07 1 4,47 8,33 2,53 23 10,08 3 6,05 1 3,93 0,007 0,02 <0.018 1,9 0,026 0,31 3,39 0,175 8,15 5,85 BG2BS000C012 9,05 1 Veleka 7,06 1 <1.0 <0.01 <0.03 <0.01 <0.005 0,2 0,294 4,24 0,22 8,03 8,07 1 12,9 8,11 2,63 24,1 10,08 3 Pairw ise data: 2 6 12 7 4 11 12 15 16 14 15 15 11

The cases of pairwise data between macroinvertebrates and physic-chemical data in bottom waters vary from 2 to 16. The correlation coefficient shows significant negative correlation between M-AMBI and pH of bottom waters (r = - 0.737) i.e. the ecological status worsen with the increase of pH (Figure 2). рН = 8.8259-0.8449*x; 0.95 Conf.Int. 8.7 M-AMBI:рН: r2 = 0.5426; r = -0.7366; p = 0.0017; y = 8.8259 - 0.8449*x

8.4 Н р 8.3

8.0 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 M-AMBI Figure 2. Correlation between M-AMBI and pH. Table 2. Heavy metal concentrations in sediments supporting the biological data WB station month.year replicates Zn mg/kg Pb mg/kg Fe mg/kg Cd mg/kg Cu mg/kg Ni mg/kg Co mg/kg Cr mg/kg As mg/kg Hg mg/kg Mn mg/kg BG2BS000C002 Tiulenovo 07.06 1 6,04 1 9,04 1 3,05 1 67,00 30,4 6,37 <0.27 21,5 BG2BS000C003 Rusalka 6,05 1 9,05 1 11,05 1 7,06 1 BG2BS000C013 Albena 07.06 1 3,05 1 6,05 1 BG2BS000C005 Varna Bay 9,05 1 11,05 1 7,06 1 100 173 2,29 0,463 53 46,1 9,6 68 6,57 2,33 632 BG2BS000C006 Kamchia 07.06 1 3,05 1 6,05 1 14,30 7,6 3563 0,08 6,7 10,6 2,6 9,9 1,37 Irakli 9,05 1 11,05 1 BG2BS000C007 07.06 1 8,07 1 Dvoinitsa 10,08 3 9.10 3 8,02 3 11,02 1 3,03 1 6,03 2 6,04 2 9,04 1 3,05 1 2,29 2,43 997 0,23 1,09 2,27 0,66 3,2 1,28 BG2BS000C009 Cocketrise 6,05 1 9,05 1 11,05 1 7,06 1 8,07 1 8,08 1 9.10 3 07.06 1 85 37,3 3,67 0,32 50,6 50,3 14,6 6,61 87 0,256 545 8,07 1 BG2BS000C010 Burgas 8,08 1 9.10 3 07.06 1 Varvara 8,07 1 10,08 3 6,05 1 BG2BS000C0012 9,05 1 Veleka 7,06 1 105 44,5 3,44 0,384 41,4 57,5 12,9 81 8,2 0,384 502 8,07 1 10,08 3 Pairw ise data: 6 6 6 5 6 5 5 5 5 3 3

The cases of pairwise data between macroinvertebrates and heavy metals vary from 3 to 6. The correlation coefficient shows significant positive correlation between AMBI and As in sediments (r = 0.948). The relationship reflects the sensitivity of the index to the toxic effect of heavy metals because this metric has decreasing values with the increasing quality status (Figure 3). As mg/kg = -151.991+68.8361*x; 0.95 Conf.Int. 100 AMBI:As mg/kg: r2 = 0.8988; r = 0.9481; p = 0.0141; y = -151.991 + 68.8361*x 90

k 50 / g m

s 40 A

-10 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 AMBI Figure 3. Correlation between AMBI and As.

Based on available quantitative data and expert judgement the relative importance of the different pressures and impacts were estimated per coastal water body (Table 3). The impact is scored considering the presence of one or more pressures within a water body (Volkaert, 2007). Pressure index is calculated as an average of all pressures considered. No correlation was found between the pressure index and the biotic indices calculated both with average values of indices per water body and with data set of indices for 2006. This is due to the fact that the pressure index is calculated per water body not per sampling point within certain water body.

Table 3. Relative importance of the different pressures (0=absent; 1=very low; 2=low; 3=moderate; 4=high) and values of pressure index per coastal water body.

WB Monitoring organic nutrient hazardous fishing dredging navigation alien physical Harbours Urbaniza Tourism Pressure points loading loading substances species modification tion index

BG2BS000C001 Krapets 2 2 1 1 1 1 2 0 1 1 1 1,18

BG2BS000C002 Shabla - 1 1 2 2 1 2 2 0 2 2 2 1,55 Tiulenovo BG2BS000C003 Rousalka 2 2 1 2 2 1 2 0 1 1 2 1,45

BG2BS000C004 Kaliakra - 4 4 3 4 4 4 3 1 4 4 4 3,55 Albena - BG2BS000C005 VarnaGalata bay 4 4 4 4 4 4 3 3 4 4 4 3,82

BG2BS000C006 Kamchia 4 4 4 4 4 4 3 3 1 2 3 3,27 (river) BG2BS000C007 Dvoinica 2 2 2 2 2 2 2 0 1 2 2 1,73

BG2BS000C008 Bourgas 4 4 3 4 4 4 3 3 4 4 4 3,73

BG2BS000C009 Slanchev 3 3 2 3 3 3 2 1 2 3 3 2,55 (site Sunny BG2BS000C0010 Sarafovobeach) - 4 4 3 4 4 4 3 0 0 3 3 2,91 Sozopol - BG2BS000C0011 noMaslen nos 3 3 1 3 2 3 2 0 2 4 4 2,45

BG2BS000C0012 Varvara - 2 2 1 1 1 1 1 0 0 1 1 1,00 Veleka

The relative importance of the different pressures and their impact were estimated at site level based on available quantitative data and expert judgement (Table 4). Pressure index is calculated as an average of all pressures considered. No significant correlation was found between the pressure index and the biotic indices (Figures 5, 6 and 7). The remaining approach is the inclusion of sediment quality descriptors like organic carbon, extractable matters, PAH, pH, redox potential, heavy metal contamination sampled at the same time and points with macroinvertebrate samples. For this purpose a special study has to be carried out at about 50-60 sampling points in order to capture the full range of the boundary values of biotic indices acompaigned by the environmental peculiarities of the sediment to allow intercalibration.

Table 4. Pressure index with the available data at site level (1=low; 2=moderate; 3=high) and values of M-AMBI.

Non-point Point pollution sources Ports

s t a x e n e u e e

r s o s r l p d i g I t

y u d t a a l

n r s s t n

m n s n u I i B r i l a a c a I e e s a s

o i p z v a u o i B i r t g g e ' B i i h i l r e t r t M t n s t

e r t r r l c r r i n a t H u a e s c c t M s a a p u A W i t u a i g s a o e a - u i c h h l s

m n A S s i b d u t s c c d T v w a r o a r u M s s t r e d r a n f h i i g g r o o f e D I U s n r i d d N I e v A P P T i d r O r F BG2BS000C002 Tiulenovo 2 1 2 1 1 1 8 1,33 0,24 4,79 2,23 BG2BS000C003 Rusalka 2 1 1 2 1 7 1,40 0,43 4,02 2,68 BG2BS000C0013 Albena 3 1 2 2 1 2 2 1 14 1,75 0,19 4,62 2,12 BG2BS000C005 Varna Bay 3 3 3 3 3 3 3 3 3 27 3,00 0,62 2,63 3,18 BG2BS000C006 Kamchia 3 2 3 1 2 2 13 2,17 0,34 4,20 2,58 Irakli 1 1 1 1 1 5 1,00 0,81 2,64 3,84 BG2BS000C007 Dvoinitsa 1 1 1 1 1 5 1,00 0,73 2,97 3,54 BG2BS000C009 Cocketrise 1 1 2 1 2 3 10 1,67 0,67 2,33 3,31 BG2BS000C010 Burgas 2 3 3 3 3 2 3 3 3 25 2,78 0,55 2,95 2,57 Varvara 1 1 2 1 1 1 1 8 1,14 0,79 2,80 3,76 BG2BS000C0012 Veleka 1 2 1 1 1 1 1 1 9 1,13 0,83 2,59 3,79 Pressure Index = 2.1956-0.9297*x; 0.95 Conf.Int. 3.2 M-AMBI:Pressure Index: r2 = 0.0990; r = -0.3146; p = 0.3460; y = 2.1956 - 0.9297*x 3.0

e 2.2 d n I

r 2.0 u s s e

r 1.8 P 1.6

0.8 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 M-AMBI

Figure 5. Correlation between M-AMBI and pressure index.

Pressure Index = 1.6673+0.0013*x; 0.95 Conf.Int. 3.2 AMBI:Pressure Index: r2 = 0.0000; r = 0.0017; p = 0.9961; y = 1.6673 + 0.0013*x 3.0

2.4 x e 2.2 d n I e r 2.0 u s s e r 1.8 P 1.6

0.8 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 AMBI Figure 6. Correlation between AMBI and pressure index. Pressure Index = 3.1265-0.4764*x; 0.95 Conf.Int. 3.2

3.0 H':Pressure Index: r2 = 0.1989; r = -0.4460; p = 0.1691; y = 3.1265 - 0.4764*x

e 2.2 d n I

r 2.0 u s s e

r 1.8 P 1.6

0.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 H' Figure 7. Correlation between H’ and pressure index.

ROMANIAN DATA

Table 1 - Relative importance of the different pressures (0=absent; 1=very low; 2=low; 3=moderate; 4=high) and values of pressure index per coastal water body

WB Non-point Point pollution sources Ha Nutrien Industry Ports Alien Tota Pressur pollution sources zar ts species l e index do pres us sure su bst Agricultu Fres Domestic Orga Indu DIN, Urbani Tour Port Navi D re input h discharge nic strial DIP zation ism activ gatio re wate loads disch ity n d r arge gi input n g Eforie 0 0 2 2 0 2 2 3 3 0 0 0 2 16 1.33 South -20m Costines 0 0 0 0 0 2 0 2 3 0 0 0 1 8 0.62 ti-20 m Mangali 0 0 2 2 0 2 2 3 3 3 2 1 2 22 1.69 a – 20 m Vama 0 0 0 0 0 1 0 1 1 0 0 0 1 4 0.31 Veche Macroinvertebrate data and pressure index (Romania)

Pressure RO -WB/Station Month/year AMBI H' M-AMBI index 1.33 EFORIE SOUTH-20 m 5.04 3.45 2.5161 0.83 8.04 1.85 2.56 0.83 5.05 1.8 2.28 0.89 10.05 3.2 2.28 0.89 4.06 2.58 2.71 0.77 7.07 3 2.72 0.78 7.08 3.07 2.92 0.89 7.09 3.63 2.23 0.56 7.1 2.98 1.59 0.53 7.11 2.51 2.46 0.81 COSTINESTI-20m 0.62 8.02 3.42 0.89 5.03 1.82 3.06 0.72 8.04 3.86 2.13 0.58 8.05 2.31 2.66 0.76 4.06 3.043 3.11 0.85 7.07 3.33 2.66 0.79 7.08 3.14 2.08 0.63 7.09 1.76 1.654 0.63 7.1 3.63 2.21 0.56 7.11 2.78 2.92 0.79 MANGALIA-20m 8.04 2.95 1.55 0.61 1.69 5.05 2.97 2.71 0.93 7.07 3.073 2.97 0.81 7.08 3.09 2.75 0.82 7.09 3.09 2.39 0.68 7.1 4.32 0.73 0.36 7.11 2.63 3.02 0.86

VAMA VECHE-20 m 8.02 3.05 2.23 0.78 0.31 5.03 1.57 1.33 0.67 8.04 2.89 1.68 0.58 5.05 2.61 2.9 0.84 4.06 3.05 2.62 0.79 7.07 2.79 2.63 0.66 7.08 2.55 3.1 0.89 7.09 3.05 2.89 0.8 7.1 1.9 2.79 0.81 7.11 2.45 3.19 0.89 Scatterplot of Pressure index against M-AMBI Pressure index = 1.5891-0.8573*x; 0.99 Conf.Int. M-AMBI:Pressure index: y = 1.5891 - 0.8573*x; r = -0.2134, p = 0.3282; r2 = 0.0455 1.8

1.4 x e 1.2 d n i

e r 1.0 u s s e

r 0.8 P

0.2 0.0 0.2 0.4 0.6 0.8 1.0 M-AMBI Fig. 1 – Correlation between pressure index and M-AMBI There are no significant correlations between pressure index and M-AMBI but the trend line shows increased M-AMBI with lower pressure index.

Table 2 - Macroinvertebrates data set and heavy metal concentrations

M- Cd RO - WB Month/year AMBI Cu µg/g µg/g Pb µg/g Ni µg/g Cr µg/g EFORIE SOUTH 5.04 0.83 108.86 0.55 8.08 34.75 8.04 0.83 43.29 0.65 23.80 31.38 5.05 0.89 62.36 1.55 123.55 42.20 10.05 0.89 54.58 2.44 79.94 36.59 4.06 0.77 26.90 1.38 33.61 68.52 70.83 7.07 0.78 27.94 0.80 4.34 67.85 52.72 7.08 0.89 40.63 0.10 20.98 46.80 52.34 7.09 0.56 7.1 0.53 17.63 0.04 10.38 25.68 44.46 7.11 0.81 22.29 0.09 30.38 21.89 32.66 COSTINESTI 8.02 0.89 39.56 0.83 22.46 5.03 0.72 36.14 0.96 42.46 8.92 8.04 0.58 167.21 1.07 77.96 5.64 12.46 8.05 0.76 58.99 0.98 157.53 36.40 12.95 4.06 0.85 15.91 0.08 11.15 12.21 14.43 7.07 0.79 10.27 0.88 16.42 16.87 20.49 7.08 0.63 10.08 0.52 20.05 29.47 22.05 7.09 0.63 51.23 0.77 28.92 25.40 30.29 7.1 0.56 10.94 5.73 150.78 26.41 30.66 7.11 0.79 63.78 1.56 14.87 45.02 46.88 MANGALIA 8.04 0.61 5.05 0.93 81.36 0.93 77.01 42.99 9.33 7.07 0.81 14.17 1.87 13.91 41.09 49.96 7.08 0.82 19.90 0.12 13.24 29.20 32.33 7.09 0.68 8.16 0.10 11.68 16.39 22.11 7.1 0.36 35.90 0.83 38.62 41.15 62.42 7.11 0.86 14.01 0.02 13.32 13.43 29.59 VAMA VECHE 8.02 0.78 87.02 1.55 40.51 5.03 0.67 81.14 1.14 159.84 8.04 0.58 5.05 0.84 46.23 1.11 25.68 13.30 5.40 4.06 0.79 14.02 0.08 11.21 33.27 70.56 7.07 0.66 9.73 0.10 10.86 21.25 26.84 7.08 0.89 7.09 0.8 63.51 0.20 46.62 49.45 70.82 7.1 0.81 7.11 0.89 14.64 3.45 5.33 27.62 32.59

Scatterplot of Cu against M-AMBI Cu = 234.0133-231.7169*x; 0.99 Conf.Int. M-AMBI:Cu: y = 234.0133 - 231.7169*x; r = -0.5299, p = 0.0077; r2 = 0.2808 180

120 ] g k / 100 g m [ 80 u C 60

0 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 M-AMBI Fig 2 - Correlation between Cu and M-AMBI Scatterplot of Cr against M-AMBI Cr = 71.2273-59.3539*x; 0.99 Conf.Int. M-AMBI:Cr: y = 71.2273 - 59.3539*x; r = -0.6254, p = 0.0073; r2 = 0.3911 70

50 ] g

k 40 / g m [

r 30 C

0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 M-AMBI

Fig. 3 – Correlation between Cr and M-AMBI Scatterplot of Pb against M-AMBI Pb = 267.9283-300.2547*x; 0.99 Conf.Int. M-AMBI:Pb: y = 267.9283 - 300.2547*x; r = -0.6830, p = 0.0002; r2 = 0.4665 180

120 ] g k / 100 g m [ 80 b P 60

0 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 M-AMBI Fig. 4 – Correlation between Pb and M-AMBI Scatterplot of Cd against M-AMBI Cd = 3.984-4.2836*x; 0.99 Conf.Int. M-AMBI:Cd: y = 3.984 - 4.2836*x; r = -0.6203, p = 0.0079; r2 = 0.3848 1.8

1.2 ] g k / 1.0 g m [ 0.8 d C 0.6

0.0 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 M-AMBI Fig. 5 – Correlation between Cd and M-AMBI

Results of heavy metals monitoring in sediments from studied area showed significant correlations (p<0.01) with M-AMBI values for the following elements: lead (r = -0.6830), cadmium (r = -0.6203), chromium (r = -0.6254) and copper (r = -0.5299). These relationships reflect the sensitivity of the index to the toxic effects of heavy metals.

Questions of JRC to be answered: Do you not have any spatial pressure information from the risk assessment Article 5 WFD report that you can use to link with the outcome of your ecological methods ?

Conclusion Is the Intercalibration feasible in terms of pressures addressed by the methods? Feasible

4.3. Assessment concept Do all national methods follow a similar assessment concept? Examples of assessment concept:  Different community characteristics - structural, functional or physiological - can be used in assessment methods which can render their comparison problematic. For example, sensitive taxa proportion indices vs species composition indices.  Assessment systems may focus on different lake zones - profundal, littoral or sublittoral - and subsequently may not be comparable.  Additional important issues may be the assessed habitat type (soft-bottom sediments versus rocky sediments for benthic fauna assessment methods) or life forms (emergent macrophytes versus submersed macrophytes for lake aquatic flora assessment methods) Method Assessment concept Remarks Method RO & BG Yes Soft bottom habitat: only mixed substrates

Conclusion Is the Intercalibration feasible in terms of assessment concepts? Feasible 5. Collection of IC dataset Describe data collection within the GIG. This description aims to safeguard that compiled data are generally similar, so that the IC options can reasonably be applied to the data of the Member States. Make the following table for each IC common type Member State Number of sites or samples or data values Biological data Physico- chemical data Pressure data MS A RO Data coveing the period 1-4 sites, data for the period 2002-2011 are collected 4 bathymetric 2002-2011 about from 4 sites along the contour/replicatesheavy Romanian Black Sea coast metals in sediments for the urbanisation, (37 replicates totally -Ttable period 2002-2011 tourism, Romania) agriculture, industrial and domestic wastewaters MS B BG Data covering the period physico-chemical data data for the period 2002-2010 are collected in bottom waters in the 2002-2010 about from 11 sites along same sampling sites for urbanisation, Bulgarian Black Sea the period 2005-2007 tourism, coast (65 replicates (Table 1); heavy metals agriculture, totally) (Table - Bulgaria) in sediments for 2005 industrial and and 2006 (Table 2) domestic wastewaters

Table. Bulgaria - Number of samples/replicates per station by sampling months and years.

WB station month.year replicates BG2BS000C002 Tiulenovo 07.06 1 6.04 1 9.04 1 3.05 1 BG2BS000C003 Rusalka 6.05 1 9.05 1 11.05 1 7.06 1 BG2BS000C013 Albena 07.06 1 3.05 1 6.05 1 BG2BS000C005 Varna Bay 9.05 1 11.05 1 7.06 1 BG2BS000C006 Kamchia 07.06 1 BG2BS000C007 3.05 1 6.05 1 Irakli 9.05 1 11.05 1 Dvoinitsa 07.06 1 8.07 1 10.08 3 9.10 3 8.02 3 11.02 1 3.03 1 6.03 2 6.04 2 9.04 1 Cocketrise 3.05 1 BG2BS000C009 (Slanchev Briag) 6.05 1 9.05 1 11.05 1 7.06 1 8.07 1 8.08 1 9.10 3 07.06 1 8.07 1 BG2BS000C010 Burgas 8.08 1 9.10 3 07.06 1 Varvara 8.07 1 10.08 3 6.05 1 BG2BS000C012 9.05 1 Veleka 7.06 1 8.07 1 10.08 3

Romania - Number of samples per station by sampling years, months and totally.

Number of 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Station/ samples / Sampling station year and month May Aug May May Aug May Oct Apr July July July July July

Eforie - - - 1 1 1 1 1 1 1 1 1 1 9

Costinesti 1 1 1 1 1 - 1 1 1 1 1 1 10

Mangalia - - - 1 1 1 - 1 1 1 1 1 7 Vama 1 1 1 1 1 1 1 1 1 1 1 1 11 Veche Total number 2 2 2 1 4 4 3 3 4 4 4 4 4 37 of samples

List the data acceptance criteria used for the data quality control and describe the data acceptance checking process and results Data acceptance criteria Data acceptance checking Data requirements (obligatory and Meeting of the criteria per country: optional) Romania - yes Bulgaria - yes The sampling and analytical Van Veen grab samples at about 1 nautical mile from methodology the shore - at about 20 m depth. The samples were initially handled onboard and gently sieved through metal gauze sieves with mesh size 1.0 x 1.0 mm and 0.5 x 0.5 mm. . The collected samples were fixed with 37-41 % buffered formaldehyde and the containers were appropriately labeled for further identification of the sample. The procedures of collection, onboard and laboratory processing of samples were accomplished according to Manual for collection and treatment of soft bottom macrozoobenthos samples (Todorova, Konsulova, 2005). Bulgaria & Romania - yes Level of taxonomic precision Spesies are identified to the lowest possible taxonomic required and taxalists with codes level. Taxalist are according to ERMS 2.0 nomenclature Bulgaria & Romania - yes The minimum number of sites / Romania – yes samples per intercalibration type Bulgaria: yes Sufficient covering of all relevant Romania: only good and high quality classes per type Bulgaria: yes Other aspects where applicable 6. Benchmarking: Reference conditions or alternative benchmarking In section 2 of the method description of the national methods above, an overview has to be included on the derivation of reference conditions for the national methods. In section 6 the checking procedure and derivation of reference conditions or the alternative benchmark at the scale of the common IC type has to be explained to ensure the comparability within the GIG. Clarify if you have defined - common reference conditions (Y/N) - or a common alternative benchmark for intercalibration (Y/N) 6.1. Reference conditions Does the intercalibration dataset contain sites in near-natural conditions in a sufficient number to make a statistically reliable estimate? (Question 6 in the IC guidance) - Summarize the common approach for setting reference conditions (true reference sites or indicative partial reference sites, see Annex III of the IC guidance): Indicative partial reference sites. - Give a detailed description of reference criteria for screening of sites in near-natural conditions (abiotic characterisation, pressure indicators):

- Identify the reference sites for each Member State in each common IC type. Is their number sufficient to make a statistically reliable estimate?

- Explain how you have screened the biological data for impacts caused by pressures not regarded in the reference criteria to make sure that true reference sites are selected:

- Give detailed description of setting reference conditions (summary statistics used)

6.2. Alternative benchmarking (only if common dataset does not contain reference sites in a sufficient number) - Summarize the common approach for setting alternative benchmark conditions (describe argumentation of expert judgment, inclusion of modelling)

- Give a detailed description of criteria for screening of alternative benchmark sites (abiotic criteria/pressure indicators that represent a similar low level of impairment to screen for least disturbed conditions) Minor or absence of anthropogenic impact. - Identify the alternative benchmark sites for each Member State in each common IC type

- Describe how you validated the selection of the alternative benchmark with biological data

- Give detailed description how you identified the position of the alternative benchmark on the gradient of impact and how the deviation of the alternative benchmark from reference conditions has been derived

Describe the biological communities at reference sites or at the alternative benchmark, considering potential biogeographical differences:

7. Design and application of the IC procedure

7.1. Please describe the choice of the appropriate intercalibration option. Which IC option did you use? - IC Option 1 - Same assessment method, same data acquisition, same numerical evalua-tion (Y/N) - IC Option 2 - Different data acquisition and numerical evaluation (Y/N) - IC Options 3 - Similar data acquisition, but different numerical evaluation (BQE sampling and data processing generally similar, so that all national assessment methods can reasonably be applied to the data of other countries)  supported by the use of common metric(s) (Y/N) - Other (specify) (Y/N)

Explanation for the choice of the IC option: IC Option 1. The same method and same metrics (M-AMBI)

In case of IC Option 2, please explain the differences in data acquisition

7.2. IC common metrics (When IC Options 2 or 3 are used)

Describe the IC Common metric: Are all methods reasonably related to the common metric(s)? (Question 5 in the IC guidance) Please provide the correlation coefficient (r) and the probability (p) for the correlation of each method with the common metric (see Annex V of IC guidance).

Member State/Method r p A B Explain if any method had to be excluded due to its low correlation with the common metric:

8. Boundary setting / comparison and harmonization in common IC type

Clarify if - boundaries were set only at national level (Y/N) - or if a common boundary setting procedure was worked out at the scale of the common IC type (Y/N) In section 2 of the method description of the national methods above, an overview has to be included on the boundary setting procedure for the national methods to check compliance with the WFD. In section 8.1 the results of a common boundary setting procedure at the scale of the common IC type should be explained where applicable.

8.1. Description of boundary setting procedure set for the common IC type Not relevant here to fill in Summarize how boundaries were set following the framework of the BSP:  Provide a description how you applied the full procedure (use of discontinuities, paired metrics, equidistant division of continuum)

 Provide pressure-response relationships (describe how the biological quality element changes as the impact of the pressure or pressures on supporting elements increases) We need more information. Comparable pressure/physico-chemical environmental data from sites in Romania and Bulgaria for coastal waters for benchmarking.  Provide a comparison with WFD Annex V, normative definitions for each QE/ metrics and type

8.2. Description of IC type-specific biological communities representing the “borderline” conditions between good and moderate ecological status, considering possible biogeographical differences (as much as possible based on the common dataset and common metrics). 8.3. Boundary comparison and harmonisation Describe comparison of national boundaries, using comparability criteria (see Annex V of IC guidance). The national boundaries have not been compared yet. Describe the conclusions of the comparison at the end

 Do all national methods comply with these criteria ? (Y/N)  If not, describe the adjustment process:

9. IC results

 Provide H/G and G/M boundary EQR values for the national methods for each type in a table Member Classification Ecological Quality Ratios State Method High-good Good-moderate boundary boundary Common metric MS RO M-AMBI 0.85 0.55 M BG M-AMBI 0.85 0.55 MS3 Method 3  Present how common intercalibration types and common boundaries will be transformed into the national typologies/assessment systems (if applicable)

 Indicate gaps of the current intercalibration. Is there something still to be done ? To be done: