1. CW BQE MACROINVERTEBRATES
Fuensanta Salas Herrero (co-BQE lead)

2. Marilena Aplikioti, Marina Argyrou
Country
Experts
Greece
Mika Simboura
Cyprus
Marilena Aplikioti, Marina Argyrou
Italy
Paolo Tomassetti, Marina Penna, Luisa Nicoletti, Benedetta Trabucco, Paola La Valle, Veronica Merusso, Adriana Giangrande
Slovenia
Borut Mavric
France
J.M Amoroux, C.Labrune, N.Desroy, V.Deroilez
Spain
Dulce Subida,Esther Jordana, Susana Pinedo, Pilar Drake, Javier Torres, Fuensanta Salas
BQE lead

3. NATIONAL ASSESSMENT METHODS
ITALY
M-AMBI
SLOVENIA
FRANCE
AMBI
SPAIN (CATALONIA AND BALEARIC ISLANDS)
MEDOCC
SPAIN (VALENCIA, MURCIA AND ANDALUSIA)
BOPA
GREECE
BENTIX
CYPRUS

4. NATIONAL ASSESSMENT METHODS
France
During the first intercalibration phase, France proposed the use of MAMBI. This proposal was based on the bad correlation between AMBI values and human pressures established from an “expert judgement” determining degraded stations.
However, in the second phase, according to recommendations of MED-GIG , this correlation was explored considering quantitative values of pressures and AMBI, MAMBI and diversity indices. In basis on these results, it was decided that AMBI was a more confident index to evaluate the ecological status

5. Feasibility check The five methods follow a very similar philosophy:
AMBI, MEDOCC, BENTIX,BOPA, and MAMBI are methods focused on soft bottom macroinvertebrates.
They are based on the abundance of sensitive/tolerant species faced with the increased or decreased disturbance. Besides, that the MAMBI method also includes the diversity parameter.
All methods have shown a significant response to the pressures, as it was tested with the LUSI index.

6. Feasibility check

7. Feasibility check

8. Feasibility check

9. Feasibility check

10. Feasibility check

11. Compliance checking
The WFD assessment methods based on the composition and abundance of benthic invertebrates in coastal and transitional waters must include diversity, abundance and proportion of sensitive/pollution indicator taxa as indicative parameters.
However…
Spain, Greece, France and Cyprus consider that the diversity is not a good parameter to establish ecological status as stated in the WFD

12. Compliance checking
Most of the biotic indices designed for the marine and estuarine invertebrate benthic communities are based on the Pearson-Rosenberg model of succession in relation to organic enrichment and pollution (Quintino et al., 2006). According to this model, diversity does not show a monotonic trend along both spatial and temporal gradients of pollution. When moving away from the source of pollution, the peak of opportunists is often followed by a maximum value in diversity, which then stabilizes at a slightly lower level. These observations were extended to gradients of chemical contaminants (Thompson & Lowe, 2004).

13. Compliance checking
For the evaluation of the BENTIX, BOPA, MEDOCC and AMBI as national appropriate assessment methods on their own (without diversity metrics), Spain, France, Greece and Cyprus have illustrated that diversity is not a good tool in the assessment of benthic invertebrate fauna for the assessed pressure and type.

14. Compliance checking
BENTIX-Greece and Cyprus

15. Compliance checking
BOPA- Murcia, Valencia and Andalusia regions (Spain)

16. Compliance checking
BOPA- Murcia, Valencia and Andalusia regions (Spain)

17. Compliance checking
MEDOCC-Catalonia and Balearic islands (Spain)

18. Compliance checking
AMBI- France

19. Compliance checking
AMBI- France

20. DATA BASIS Dataset Member State
Number of sites or samples or data values
Biological data
Physico- chemical data
Pressure data
Greece
108 samples
Cyprus
10 stations
Italy
47 stations
Slovenia
53 samples
7 samples
39 samples
Spain (Catalonia and Balearic islands)
105 stations
Spain (Valencia, Andalusia and Murcia)
340 samples
France
45 samples

21. BENCHMARCK -no harbours -no beach regeneration -no urban sewages
-no industrial sewages
-no fish farms
-no desalination plants
-no thermal industries
-no influence of agriculture activities
->3 Km as a distance to the closer city with more than 1000 inhabitants
Spain: 16
Greece: 6
Cyprus: 1
France: 3
Italy: 7
Slovenia: 4
57 Benchmark sites

22. Use of pseudo-common metric (without (P)CM in case of only 2 methods)
INTERCALIBRATION OPTION
Direct comparison (combined with regression) (Option 3a)
Indirect comparison through regression (Option 2)
Option 3
Option 2
Direct comparison (without regression) (Option 3b)
Q3. How many methods are participating in the exercise?
Q1. Is intercalibration performed based on commonly assessed sites?
Q2. Is the gradient of ecological quality sufficiently covered by the existing data?
Yes No 3
<3
or >3
Use of pseudo-common metric
and/or common metric
(without (P)CM in case of only 2 methods)
Q3. In case of 3 methods, is 1 method very different from the other 2 methods ?

23. INTERCALIBRATION OPTION
Feasibilty check
Relationship must be significant depending on the size of the dataset (from p≤0.05 to p≤0.001).
(Pseudo-) common metric must adequately represent all methods: correlation between each method and the (pseudo-) common metric should be ≥ r = 0.5 (Pearson’s correlation coefficient).
Slope of the regression should be tested to be significantly different from 0.
Observed minimum r2 should be at least half of the observed maximum r2.
All necessary assumptions of a linear regression need to be checked (normally distributed error and variance (homoscedasticity) and independence of model residuals of the regression).

24. INTERCALIBRATION OPTION

25. INTERCALIBRATION OPTION

26. IC OPTION
Then, we thought that due to habitat specification, or sample size, maybe it was not possible to use the diversity metric on the datasets of all the intercalibrating member states, and therefore we needed to shift to an Option 2 approach.

27. Use of pseudo-common metric (without (P)CM in case of only 2 methods)
INTERCALIBRATION OPTION
Direct comparison (combined with regression) (Option 3a)
Indirect comparison through regression (Option 2)
Option 3
Option 2
Direct comparison (without regression) (Option 3b)
Q3. How many methods are participating in the exercise?
Q1. Is intercalibration performed based on commonly assessed sites?
Q2. Is the gradient of ecological quality sufficiently covered by the existing data?
Yes No 3
<3
or >3
Use of pseudo-common metric
and/or common metric
(without (P)CM in case of only 2 methods)
Q3. In case of 3 methods, is 1 method very different from the other 2 methods ?

28. FEASIBILITY CHECK
COMMON METRIC: AMBI

29. FEASIBILITY CHECK
COMMON METRIC: %sensitive species

30. FEASIBILITY CHECK
COMMON METRIC: %sensitive species

31. FEASIBILITY CHECK
COMMON METRIC: %sensitive species

32. Spain, Greece, France, Cyprus
INTERCALIBRATION OPTION
Spain, Greece, France, Cyprus
Italy and Slovenia
Special IC Option 3 between 2 countries
Option3_TwoMS_Final
IC Option 3a
IC_Opt3_sub v1.24.

33. FEASIBILTY CHECK
MEDOCC, BOPA, AMBI, BENTIX (SPAIN, GREECE, CYPRUS, FRANCE)
No subtypes, as it was shown in the Milestone 2.
MEDOCC
BENTIX
BOPA
AMBI
intercept (c)
0,275
0,223
0,251
-0,085
slope (m)
0,718
0,739
0,537
1,074
Pearson's r
0,903
0,660
0,807
0,880 R²
0,816
0,435
0,651
0,775

34. BOUNDARY COMPARISON AND HARMONIZATION
MEDOCC, BOPA, AMBI, BENTIX (SPAIN, GREECE, CYPRUS, FRANCE)
The boundary comparison and harmonization has been done following the steps defined in the step 7 of the Annex V of th IC Guidance.
Boundary biass
MEDOCC
BENTIX
BOPA
AMBI
H/G biass
0,169
0,062
-0,744
-0,059
G/M biass
0,273
0,769
-0,113
-0,353
Boundary biass must not exceed 0.25 units. In our case, AMBI is relaxed in the G/M boundary. BOPA method is also relaxed, but in the H/G Boundary. MEDOCC and BENTIX show a desviation >0.25 in the G/M boundary, but in their cases these desviations indicate that these methods are more precautionary than 0.25 of a class. Willby and Birk (2010) stated that in this case, these methods or countries can opt not to modify their boundaries.

35. Ecological Quality Ratios Good-moderate boundary
BOUNDARY EQR VALUES
Member State
Classification
Ecological Quality Ratios
Method
High-good boundary
Good-moderate boundary
France
AMBI
0,83
0, ,58
Greece
BENTIX
0,75
0,58
Cyprus
Spain (Catalonia-Balearic islands)
MEDOCC
0,73
0,47
Spain (Murcia-Valencia-Andalusia regions)
BOPA
0, ,95
0,54
Class agreement
MEDOCC
BENTIX
BOPA
AMBI
Absolute class diference
0,3448
0,4626
0,3889
0,3573

36. MAMBI Boundary Slovenia
MAMBI METHOD (ITALY and SLOVENIA)
Reference conditions and boundaries are different. So, it was needed the comparison and harmonization of their boundaries with the help of the IC sheet “Revised_Option3_Two MS_Final.xls”.
Analysing the parameters composing the M-AMBI in the Italy and Slovenian benchmark sites, and comparing them with Italy and Slovenia values set for reference conditions, we can see that difference existing is due to the particular natural differences charactering the Slovenian habitat sampled. Then, Slovenia was then treated as sub typology.
MAMBI Boundary Italy
MAMBI Boundary Slovenia
Max
1,17
1,25 HG
0,81
0,83 GM
0,61
0,62

38. Standardization – EQRs Bivariate distribution – Regression line after standardization
Data from 7 BM sites from IT and 4 from Slovenia, which are under the comparable pressure level were chosen to define the correction factor, representing natural difference (depth, habitat), and have been used to calculate the sEQR with “division”.

39. Ecological Quality Ratios Good-moderate boundary
Boundary comparison and harmonization
Then the application on revised_option 3_TwoMS_Final.xls revealed the following bias:
IT: H/G= , G/M=
SLO: H/G= 0.041, G/M= 0.056
Member State
Classification
Ecological Quality Ratios
Method
High-good boundary
Good-moderate boundary
Italy
MAMBI
0,81
0,61
Slovenia
0,83
0,62

40. Ecological Quality Ratios Good-moderate boundary
BOUNDARY EQR VALUES
Member State
Classification
Ecological Quality Ratios
Method
High-good boundary
Good-moderate boundary
Italy
MAMBI
0,81
0,61
Slovenia
0,83
0,62

41. Diversity method/No diversity methods
Overall class agreement analysis between M-AMBI and other methods
Kappa analysis- Results:
We have compared the level of agreement between classifications using the multi-rater kappa coefficient.
Kappa values indicated a low or poor agreement among all indices (0.29).
Meanwhile, Kappa analyses indicated an acceptable agreement (>0.4) between AMBI, MEDOCC, BOPA and BENTIX.
This result is coherent with the results obtained along the IC exercise, and it is suggested that the diversity parameter is the main responsible of the low relation between MAMBI and the rest of the methods.

42. CONCLUSIONS
The existence of two IC groups is understood by the MED GIG experts as a normal and valid result, as it can be reported in numerous scientific works.
Many studies have shown the different response of the diversity to the disturbance, being in some cases inverse to the pressure level, as it is expected, but in other cases showing high values at the end of the disturbance gradient, depending on the area, habitat, pressures, etc.
So, the results showed in the present IC exercise are in accordance to those obtained in other studies, showing the expected behavior of the diversity against the pressures gradient in some areas (as it occurs in the stations of Italy and Slovenia), or the uselessness of the diversity in the establishment of the ecological status in other zones (as it occurs in the stations of France, Spain, Greece and Cyprus).

43. Thank you!