Phase II Intercalibration:

Phase II Intercalibration:
Mediterranean GIG Transitional waters - Invertebrates ECOSTAT, Brussels October 2011 Isabel Pardo

Intercalibration Common Types
1.Oligohaline 2. Mesohaline-chocked 3. PolyEuhaline-Chocked 4. PolyEuhaline-Restricted Isabel Pardo

1.Oligohaline

1.Oligohaline type Participating countries & methods
ES – MIBIN France – MAMBI ES - QAELS Database description Number of reference and assessment samples by country. * only 4 samples with MAMBI values Total number of samples.. Note: Spain-QAELS were not used in the analyses between pressure indexes and EQRs. Isabel Pardo

1.Oligohaline type MS EQRs response to pressures
Pearson correlation between EQR MS TW_FLUSI and TRIX and other pressure variables. Marked correlations are significant at p< 0.05. The French M-MAMBI, with only few samples did not respond to pressures, the two Spanish methods were related with some of the tested pressure variables

1.Oligohaline type Reference benchmarking
Only Spain-MIBIN provided reference sites (minimum TRIX and TW_LUSI values of 3.99 and 0.75, respectively) Reference values from Spain_MIBIN show low level of impairment on the light of low TW_LUSI values and nutrients values. Not enough French samples to generate an alternative benchmark, and they were not related with pressures The exercise was made with reference samples form Spain

1.Oligohaline type Invertebrate communities
Ordination at the family level using the most common taxa, and excluding all zooplankton taxa Significant relationships between the invertebrate composition and common families with the pressure indexes and variables

1.Oligohaline type Option 2. Intercalibration common metric
The common metric was developed with databases from Spain-MIBIN and France Metric Expected response to pressure Reverse (max value 4.5) Transformation Rescaled Corophidae + Hydrobidae + Nereidae + Tubificidae + yes log(x+1) Median ref.

ICM EQR response to pressures EQR ICM vs LUSI Pearson correlations between pressures and EQR ICM EQR ICM vs TRIX The ICM was related with pressure variables, suggesting that it may be appropriate for its use in intercalibration

ICM EQR response to MS EQR EQR ICM vs MAMBI (FR) Good correspondence between the ICM metric and the MS_EQRs, suggesting that it may be appropriate for its use in IC EQR ICM vs ES-MIBIN

1.Oligohaline type Option 2. Intercalibration common metric.
MSs intercalibration with the common metric (ICM1) Option 2. Use of the common metric. The calculations for Class width bias are provided individually for FR and ES to illustrate the comparison. The French regression is not significant P=

1.Oligohaline type CONCLUSIONS:
A common metric index (ICM) was developed for the IC of Spanish and French data, using reference samples from Spain It was impossible to use benchmarking due to the low number of sites from France. The FR_MAMBI data did not respond to pressures The exercise indicated the possibility for the intercalibration of the Oligohaline type using option 2, but only the ES_MIBIN provided a robust database

2. Mesohaline-chocked

2. Mesohaline-chocked type
Participating countries & methods ES– MIBIN ES-QAELS France – MAMBI Italy – MAMBI & BITS Database description Only ES-MIBIN and ES-QAELS provided reference sites for the types France Italy Spain_QAELS Spain_MIBIN Punctual_Salinity (PSU) Mean 29.16 16.12 SD 15.18 9.60 Median 35.64 11.85 P25 13.24 8.55 P75 44.59 22.05 N 13 25 Annual_Mean_Salinity (PSU) 10.00 18.29 2.97 2.40 9.00 18.44 18.04 13.00 6 France Italy Spain_BI Spain_CA Total 6 10 25 13 %Artificial %Agriculture Punctual_TN µg/l Punctual_TP µg/l TRIX Punctual_N-NO2 µg/l Punctual_N-NH4 µg/l Punctual_P-PO4 µg/l Punctual_N-NO3 µg/l TW-FLUSI Assessment Reference France 6 Italy 10 Spain_MIBIN 17 8 Spain_QAELS 7 Total 39 15 Number of reference and aseessment sites per Member State (MS) Number of sites and pressure data within the database

MS EQR response to pressures Good correspondence between the ES-MIBIN and ES-QAELS with TW-FLUSI and TRIX, respectively. The Italian and French MAMBI and the IT BITS were not related with pressures. Pearson & Spearman correlations between EQR MS and pressures variables. Note: marked correlations are significant with p<0.05. N.A. = no data available.

Reference benchmark Only ES-MIBIN and ES-QAELS provided reference sites We checked the level of pressures on the reference provided to harmonize the pressure criteria. We selected 6 of the 8 references provided by ES_MIBIN Criteria: (LUSI ≤ 2; TRIX ≤ 5) 2.5 Option 1. Common assessment method MAMBI Problems for applying option 1 are: FR & IT, MAMBI did not respond to pressures The two Spanish methods respond to pressures but cannot be used for option 1

Option 2. Common intercalibration metric(s) (cont.) Metric construction (cont) Samples Ordination: all data except data from ES_QAELS. Without ES-QAELS NMDS1 NMDS2 NMDS3 logPunctual_TN µg/l -0.534 -0.106 -0.257 p=.00 p=.569 p=.163 logPunctual_TP µg/l 0.603 0.143 0.002 p=.000 p=.441 p=.993 logPunctual_N-NO2 µg/l -0.653 -0.182 -0.060 p=.328 p=.749 logPunctual_N-NH4 µg/l -0.282 -0.228 0.092 p=.124 p=.217 p=.624 logPunctual_N-NO3 µg/l -0.585 -0.118 -0.261 p=.001 p=.526 p=.156 logDIN -0.455 -0.176 -0.209 p=.010 p=.344 p=.259 logPunctual_P-PO4 µg/l 0.315 0.062 -0.017 p=.084 p=.740 p=.927 TRIX 0.026 -0.004 -0.128 p=.893 p=.985 p=.501 TW-FLUSI -0.370 0.367 0.465 p=.044 p=.046 Spearman correlations %Artificial -0.101 -0.116 0.358 %Agriculture -0.763 0.173 -0.248 NMDS of MSs samples with indication of references samples and other assessment samples. Without ES-QAELS. Pearson and Spearman correlations between NMDS axis and pressures. Marked correlations are significant at p< 0.05.

Expected response to pressure
2. Mesohaline-chocked type Option 2. Common intercalibration metric(s) (cont.) Metric construction (cont) We tested the relationship existing between the 23 taxa and the pressure variables and indexes and with NMDS axes Both sets of correlations resulted in similar significant sensitive/tolerant responses of taxa (see document for more details) We identified a list of potential indicator taxa: Three ICM EQRs were built: ICM1-sensitive taxa ICM2-tolerant taxa ICM3- tolerant + sensitive taxa Metric Expected response to pressure Reverse Transformation Re-scaled ICM1 (Sensitive taxa) - No Median ref. ICM2 (Tolerant taxa) + Yes ICM3 (Sensitive & Tolerant taxa) -/+ Yes(tolerant taxa) (1-x)

Option 2. Common intercalibration metric(s) (cont.) EQR ICM3a response to pressures Good correspondence between all together MSs EQR ICM3a and pressures (better with N forms) The ICM3a_EQR in the IT database has good correspondence with N-NO3) Pearson and Spearman correlations between EQR ICM (1, 2 and 3) with pressure variables. Note: Marked correlations are significant at p < *Pearson correlations **Spearman correlations.

Option 2. Common intercalibration metric(s) (cont.) EQR ICM response to MS EQR

Option 2. Common intercalibration metric(s) (cont.) MSs intercalibration with the common metrics Regression between MS-EQRS and the ICM3 (tolerant+sensitive taxa).

CONCLUSIONS: Among the 15 reference sites submitted by ES_MIBIN and ES_QAELS we selected only 6 sites with consistent pressure levels (LUSI ≤ 2; TRIX ≤ 5) There were no relationships between methods with pressures , thus no possibilities for benchmarking Of the 4 methods only the Spanish methods (MIBIN and QAELS) responded to pressures Option 1 for M-AMBI was not possible for IT and FR because MAMBI was not related with pressures There were strong differences in fauna richness and densities between ES_QAELS and the other countries, for that ES_QAELS samples were not used in the metrics construction. But we applied to these samples the resulting metrics and analyses Option 2. The best suited ICM is the EQR ICM3a (Sensitive + tolerant taxa), being related with pressure variables, but only related with one MS method. There were many statistical problems limiting the application of the Option 2 to the boundary comparison. Meanwhile, the only satisfactory methods fulfilling statistically the relationship with the ICM3 were the IT_MAMBI and Bits - If we can assume that the IT –MAMBI responds to pressures throughout its relationship with the ICM3

3. PolyEuhaline-Chocked

Participating countries & methods Spain – MIBIN France – MAMBI Greece – MAMBI Italy – MAMBI & BITS Database description Only ES-MIBIN provided reference sites for the types Salinity France* Greece * Italy * ES-MIBIN** MEAN 20.67 24.40 23.24 51.24 SD 2.08 0.00 6.95 27.79 MEDIAN 20.00 24.03 39.90 P25 19.00 18.20 28.20 P75 23.00 29.49 72.55 n 3 87 21 * Salinity mean from Annual_Mean_Salinity (PSU) ** Salinity from Punctual_Salinity (PSU) Country France Greece Italy Spain-MIBIN Total 3 89 21 %Artificial %Agriculture Punctual_TN µg/l Punctual_TP µg/l 71 TRIX Punctual_N-NO2 µg/l 87 Punctual_N-NH4 µg/l Punctual_N-NO3 µg/l TW-FLUSI Punctual_P-PO4 µg/l Assessment Reference Total ES-MIBIN 14 7 21 France 3 Greece Italy 89 Number of reference and aseessment sites per Member State (MS) Number of sites and pressure data within the database

MS EQRs response to pressures Spearman correlations between EQR MS and land uses (%).Note: marked correlations are significant with p<0.05. In red negative correlations. Pearson correlations between EQR MS and pressures variables. Note: marked correlations are significant with p<0.05. N.A. = no data available. Good correspondence between the Italian BITS and TP and P_PO4, and between Spanish-MIBIN and % artificial For the other MAMBI methods, FR and GR have provided limited data for the IC (n=3), and few pressure data, being the relationships not significant, or positive

Reference benchmarking Only Spain-MIBIN provided reference sites that correspond to naturally nutrient enriched systems of small size)  We discarded the ES-MIBIN systems as reference sites It was impossible to use benchmarking due to the absence of relationship between methods and pressures Best available benchmarks (23 sites ) LUSI ≤ 2 DIN ≤ µg/L Sites selected like alternative benchmarcks (Varano)

Reference benchmarking Ordination of samples without ES-MIBIN and Venezia samples.

Option 1. Common assessment method MAMBI Problems for applying Option 1: Two of the 3 countries having MAMBI as assessment method, FR and GR, only have 3 samples each, thus their IC seems not possible with option 1 Meanwhile, none of the FR, IT and GR MAMBIs were related with pressures Only the IT-BITS and ES-MIBIN responded to some pressure variables, and they cannot be used for option 1

3. PolyEuhaline-Chocked Option 2. Common intercalibration metric(s Metric construction Taxa were related with pressures (Table 8 see document) Three ICM EQRs were built: Type Metric Expected response to pressure Reverse Transformation Re-scaled PolyEuhaline-CHO ICM1 Sensitive taxa - no log(x+1) Median ref. ICM2 Tolerant taxa + Yes (5 – x) Median ref ICM3 Sensitive+Tolerant taxa -/+ Yes(only tolerant taxa)

Option 2. Common intercalibration metric(s) EQR ICMs response to pressure indexes Pearson and Spearman correlations between EQR ICM, MAMBI and BITS with pressure variables. Note: Marked correlations are significant at p <

Option 2. Common intercalibration metric(s) EQR ICM response to MS (M_AMBI EQR)

Option 2. Common intercalibration metric(s) MSs intercalibration with the common metric (ICM) Regression between MS-EQRS and the ICM1 (sensitive taxa). Regression between MS-EQRS and the ICM2 (tolerant taxa). Regression between MS-EQRS and the ICM3 (tolerant+sensitive taxa).

CONCLUSIONS: Chocked small lagoons in the Mediterranean, isolated from the sea, suffer from strong annual water level fluctuations. The fauna is more similar to inland saline lakes than to more matine fauna of big lagoons close to the sea. Spain is the only country presenting small systems for this IC type, and we consider they belong to another type and cannot be IC within this type (big size) The Venize lagoon on the other side, was characterized for a fauna that was more similar to the other Venize data belonging to the PE restricted type. Samples were removed fro the PE CHO type. It was impossible to use alternative benchmarking due to the low number of sites from France and Greece. We selected a Best available sites benchmark (not reference samples). The results indicate only a good correspondence between the Italian BITS and TP and P_PO4, and between Spanish-MIBIN and % artificial. For the other MAMBI methods, FR and GR have provided limited data for the IC (3 samples each), and the relationship with the IT M_AMBI was not significant. Option 1 for M-AMBI was not possible as only IT had representative data. Option 2. From the 3 produced ICMs, only the ICM2 allowed a statistically sound boundary comparison between the IT BITS and IT MAMBI. The use of the best available benchmark (Varano Lagoon samples) requires the definition based on pressures of its status class. Italy can use the present results to see the main differences between BITS and MAMBI class comparisons. -

4. PolyEuhaline-Restricted

Participating countries & methods Greece - MAMBI France – MAMBI Italy – MAMBI & BITS Database description Country Assessment Best sites Reference Total France 16 3 2 21 Greece 17 4 Italy 115 148 6 157 Number of reference, assessment and best sites within the database. Number of samples and data form each pressure indexes and variables by MS

MS_EQRs response to pressures IT FR IT IT FR FR GR Pearson & Spearman correlations between MS EQR pressure variables. Marked correlations are significant at p< 0.05. N.A= non available data. Not possible to do benchmarling, few samples, and small overlap in pressure conditions The results indicate only a good correspondence between the French and Italian MAMBI and TN.

Reference benchmark The results indicate that the pressure level influencing Greek reference sites was higher than the level of pressures in French reference samples. In the latter one, some sites had low level of impairment on the light of low TW_LUSI values and also lower TN values. The reference samples form France were used as a Reference benchmark New reference benchmark: TW_FLUSI ≤ 2.0 ; TRIX (France) ≤ 5.020 New reference sites selected that corresponded to a TW_FLUSI value ≤ 2.0. Note: rows in pink are the sites that were discarded because they presented a very different community from the reference group (FO15PR), or because its TRIX value was over 5 (FO25PR).

Option 1. Common assessment method MAMBI Option 1. The class width bias for the Italian H/G and G/M boundaries is higher than the mean. The French H/G is lower The absence of relationships between pressures and the Greek MAMBI precludes their Option 1 intercalibration with the French and Italian MAMBI (both responding to TN)

4. PolyEuhaline-Restricted Option 2. Common intercalibration metric(s) Metric construction We tested the relationship between punctual TN and the 34 families that most contributed (up to 60%) to the dissimilarity between reference and assessment samples. We selected the taxa showing a sensitive response in a ICM. Metric Expected response to pressure Reverse Transformation Re-scaled Sensitive taxa - no log(x+1) Median ref.

Option 2. Common intercalibration metric(s) EQR ICM response to pressure indexes Relationship between punctual TN and EQR ICM for all MS. Pearson correlation between EQR ICM, punctual TN, punctual TP, TW-FLUSI and TRIX. Note: Marked correlations are significant at p < MS: Member States. NA (non available data).

Option 2. Common intercalibration metric(s) EQR ICM response EQR MS Scatterplot between EQR ICM and EQR MS (FR, IT (MAMBI & BITS), GR-MAMBI.

Option 2. Common intercalibration metric(s) MSs intercalibration with the common metric (ICM) Regression summary between MS-EQRS and the ICM. All countries (FR+GR+IT) together and individually

CONCLUSIONS: The French and Italian MAMBI respond to TN, the greek MAMBI did not Option 1. The comparability of boundaries for MSs MAMBI (FR and IT) seems possible. But the option 1 does not include the BITS Option 2. The ICM was related with pressures being a valid method for IC. In general, the regressions between the ICM and the MSs methods provided not good relationship for all countries. Several statistical deficiencies in the relationships for GR, FR and the IT BITS precluded the option 2 intercalibration, after testing several ICMs. Only the IT_MAMBI fulfills the requirements for going through option 2. Anyhow, an attempt was made to compare the boundaries between the fully compliant in statistical terms IT_MAMBI, and the GR-MAMBI (having only a close to significant relationship with ICM P= 0.63, and with the relationship R2 to R not fulfilled) But results were different for Italy in Option 1 and 2, indicating the need for a more robust comparison with all countries involved (3), nor just the two fulfilling each option

Invertebrates TW MED GIG: Final conclusions
The IC of invertebrates in the MED TW GIG was promising in many aspects, and some countries did provided consistent databases for it Some MSs still need to either improve or validate their classification systems with pressures, because there was a general problem because data submitted for the national classification systems did not respond to a number of pressures tested. This fact restricted the number of possible comparisons for using option 1 Meanwhile, the search for ICMs within the types databases proved to be promising, in the sense that the new ICMs made with the IC databases did respond to pressures. Also the significant relationship between the ICMs with some Mss classification systems in some types proved their utility for the IC exercise There is a need for more data and further work, to test the possibility for the comparison of classification systems in the invertebrates TW MED GIG

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