EUROPEAN COMMISSION DIRECTORATE … Research Centre/jrc...EUROPEAN COMMISSION DIRECTORATE GENERAL JRC ... macroinvertebrate expert), Sergi Sabater, Elisabet Tormes, ... Maria Rita

EUROPEAN COMMISSION

DIRECTORATE GENERAL JRC

JOINT RESEARCH CENTRE

Institute of Environment and Sustainability

WFD Intercalibration Phase 2: Milestone 4 report

Water category/GIG/BQE/

horizontal activity: Rivers/Mediterranean GIG/Benthic

macroinvertebrates

Information provided by: Maria João Feio

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:

The Mediterranean GIG met once or twice every year, under the coordination of Maria Teresa

Ferreira. On these annual meetings the progression of the BQE was discussed, either at the BQE

level or collectively. Some independent BQE meetings also took place and other relevant

meetings were attended by the BQE leaders.

The BQE macroinvertebrate working group leader was Maria João Feio, Portugal, responsible for

the collection of data, data analyses, harmonisation and reporting.

List of national elements attending the meetings (not necessarily all meetings):

Portugal: Maria Teresa Ferreira, Maria João Feio (macroinvertebrate expert), Salomé Fernandes,

Pedro Segurado, Francisca Aguiar, João Ferreira

Cyprus: Gerald Dörflinger (macroinvertebrate expert), Iakovos Tziortzis (macroinvertebrate

expert), Skevi Manolaki, Stamatis Zogaris

Spain: Narcis Part (macroinvertebrate expert), Sergi Sabater, Elisabet Tormes, Nuno Caiola,

Antoni Munné (macroinvertebrate expert), Ana Lara, Fernando Gurucharri, Irene Carrasco,

Jaume Cambra, José Luis Moreno

France: Martial Férreol (macroinvertebrate expert), Christian Chauvin, Laurence Blanc, Michael

Cagnant, Nicolas Roset, François Delmas, Yorik Reyjol

Slovenia: Gorazd Urbnic (macroinvertebrate expert), Mateja Germ, Nina Stupnikar, Vesna

Petkovska

Italy: Maria Rita Minciardi, Laura Mancini, Camilla Puccinelli, Stefania Marcheggiani, Stefania

Erba (macroinvertebrate expert), Andrea Buffagni (macroinvertebrate expert)

Greece: Eva Papastergiadou, Stamatis Zogaris, Phoebe Vayanou, Michalis Maroulakis, Ioannis

Karavokyris

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:

Participating countries in the BQE river macroinvertebrates: Portugal, France, Spain, Cyprus,

Slovenia and Italy.

Greece did not contribute with indices or data to the second intercalibration exercise of

macroinvertebrates. Nevertheless, we had a few contacts with and from the water administration

of Greece. Two academic elements related to the macrophyte and fish BQEs followed the IC.

These and other Greek elements were either present in the meetings or following the exercise by

e-mail. Further, Greece was present on the 1st IC exercise and was able to successfully

intercalibrate the types RM1, RM2 and RM41.

Malta did not rely to e-mails and contacts.

On 24-05-2011, there was an e-mail contact from the water administration of Bulgaria,

expressing interest to follow our group activities. They were invited to the next Mediterranean

GIG meeting in 19-20 September 2011 in Madrid.

1.3. Meetings

List the meetings of the group:

1st Mediterranean GIG General Meeting, Lisbon June 2008

Rivers Steering Group Meeting, London, January 2009

2st Mediterranean GIG General Meeting, Lisbon January 2009

Reference Conditions Meeting, Oviedo Spain September 2009

Mediterranean macroinvertebrates BQE meeting, Milan, June 2009

3st Mediterranean GIG General Meeting, Nicosia, Cyprus September 2009

4st Mediterranean GIG General Meeting, Lisbon March 2010

River invertebrates meeting, Vigo, August 2010

5st Mediterranean GIG General Meeting, Ljubljana September 2010

6st Mediterranean GIG General Meeting, Rome, March 2011

7st Mediterranean GIG General Meeting, Madrid, October 2011

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 Reported

in Wiser

Portugal

Rivers Biological Quality Assessment Method-

Benthic Invertebrates (IPtIN, IPtIS)

1 Yes

Spain 1

Iberian Biological Monitoring Working Party

(IBMWP)

1 Yes

Spain 2 Iberian Mediterranean Multimetric Index—using

quantitative data (IMMi-T)

1 Yes

France

Global biological normalized index (IBGN) 1 Yes

Cyprus STAR Intercalibration Common Metric Index 1 Yes

1 Ferreira, J, J.M. Bernardo & M.H. Alves (2008) Exercício de Intercalibração em rios no âmbito da

Directiva Quadro da Água. 9º Congresso da Água, Lisboa. Centro de Congressos do Estoril, 8 p.

(STAR-ICMi)

Slovenia

Slovenian Ecological Status assessment system for

rivers using benthic invertebrates

1,2 Yes

Italy Based on STAR_ICM index calculation (MacrOper) 1,2 Yes

National method descriptions for Med GIG invertebrate intercalibration

MS National method Reference conditions setting at National

level

Portugal

Rivers Biological Quality Assessment

Method-Benthic Invertebrates (IPtIN, IPtIS)

Method used in 1st IC.

Described in: Annex 2.4.1e from

Intercalibration Technical Report - Rivers and

J. Ferreira, J.M. Bernardo, M.H. Alves (2008).

Exercício de intercalibração em rios no âmbito

da Directiva-Quadro da Água. Acta do 9º

Congresso da Água, Lisboa.

Multimetric indices based on the following

metrics: number of taxa, number of EPT

families, eveness, IASPT, log (sel. ETD+1),

log (sel. EPTCD+1)

Reference conditions followed the guidelines

and pressure screening criteria provided by the

Working Group 2.3 – REFCOND and

described on CIS WFD Guidance Document Nº

10 - Rivers and Lakes – Typology, Reference

Conditions and Classification Systems. The

applied methodology included spatial analysis,

historical data analysis and expert judgment.

Semi-quantitative analysis was used in order to

assess the magnitude of 9 pressure variables

(Land Use, Riparian Zone, Sediment Load,

Hydrological Regime, Acidification and

Toxicity, Morphological Condition, Organic

Matter Contamination and Nutrient

Enrichment, River Continuity) a procedure

adapted from European Project FAME -

Development, Evaluation and Implementation

of a Fish-based Assessment Method for the

Ecological Status of European Rivers. A

Contribution to the Water Framework Directive

(Contract EVK1-CT-2001-00094). This

procedure was applied according to the

specificities of the different river types and lack

of true reference sites in some river types lead

to the selection of ―best available sites‖. A final

biological screening was also made in order to

exclude sites with communities typical of

degraded sites.


level

Spain 1

Iberian Biological Monitoring Working Party

(IBMWP)


It’s a biotic index based on species sensitivity

to contamination.

Last description in:

Alba-Tercedor, J., P. Jáimez-Cuellar, M.

Álvarez, J. Avilés, N. Bonada, J. Casas, A.

Mellado, M. Ortega, I. Pardo, N. Prat, M.

Rieradevall, S. Robles, C.E. Sáinz-Cantero, A.

Sánchez-Ortega, M.L Suárez, M. Toro, M.R.

Vidal-Abarca, S. Vivas & C. Zamora-Múñoz,

2004. Caracterización del estado ecológico de

ríos mediterráneos ibéricos mediante el índice

IBMWP (antes BMWP’). Limnetica 21 (3-4):

175-185.

Based on near-natural reference sites. Selected

by expert knowledge. The selection followed

the REFCOND guidance and GIGs criteria (1st

phase).

Spain 2

Iberian Mediterranean Multimetric Index—

using quantitative data (IMMi-T)

New method described in Munné & Prat,

2009. Use of macroinvertebrate-based

multimetric indices for water quality

evaluation in Spanish Mediterranean rivers: an

intercalibration approach with the IBMWP

index. Hydrobiologia 628: 203-225.

This index is a multimetric index based on the

metrics number of families, EPT, IASPT and

log (Sel EPTCD+1).

Described also in Munné & Prat 2009.

Based on near-natural reference sites. Selected

by expert knowledge. The selection followed

the REFCOND guidance and GIGs criteria (1st

phase).

France

Global biological normalized index (IBGN).


Described in: Terrasson, I., 2004. The IBGN-

its history, sampling and future. Technical

synthese. ENGREF Centre de Montpellier.

The IBGN is a combination of 2 metrics:

- the total number of taxa (at the family level

for Insecta, Crustacea, Mollusca, Acheta; class

for the other groups), is expressed in 14

classes of taxonomic richness. The Metric CV:

Classes de Variété, varies from 14 (> 50 taxa)

to 1 (1-3 taxa) .

- the Indicator Faunistic Group representing

the presence/absence of 39 indicator taxa,

grouped in 9 classes of sensitivity to pollution.

The Metric GFI: Groupe Faunistique

Indicateur, varies from 9 (very sensitive taxa

present) to 1 (only very tolerant taxa

remaining).

All the IBGN values were then transformed in

EQR-IBGN; for this calculation, the minimum

IBGN value is set at IBGN = 1.

IBGN is the French historical assessment

method applied since 1992 in our national

monitoring network. This methodology was not

entirely compliant with the WFD requirements

therefore it is presently being modified. Yet, the

intercalibrated method was the same used in 1st

phase.

Reference sites were selected in the monitoring

network on the basis of the national reference

criteria, following a procedure compliant with

the REFCOND Guidance. A set of reference

criteria, officially endorsed by the French

Ministry of Environment

(Circulaire MEDD/ DE/ DCE 08 du 23

Décembre 2004) has been applied at the

national level.


level

Cyprus

STAR Intercalibration Common Metric Index

(STAR-ICMi)

Method used in 1st IC and common metric.

Described in: Buffagni A., Erba S., Cazzola

M., Murray-Bligh J., Soszka H. & Genoni P.,

2006. The STAR common metrics approach to

the WFD intercalibration process: Full

application for small, lowland rivers in three

European countries. Hydrobiologia, 566: 379-

399

Multimetric index based on the following 6

metrics: average score per taxon, log 10

(sel_EPTD+1), 1-GOLD, total number of taxa

Families, number of EPT taxa (Families) and

the Shannon-Wiener diversity index.

Followed the REFCOND Guidance criteria

based on pressure criteria. The absence of

pressures had to be illustrated and this was done

by using methods and indices such as SH_RHS,

LRD (Lentic-lotic River Descriptor), HMS

(Habitat Modification Score), HQA (Habitat

Quality Assessment), LIM (Livello

inquinamento macrodescrittori - Pollution

Macrocostituents Level), IFF (Index of Fluvial

Functioning), LUI (Land Use Index) from

CORINE and CARAVAGGIO.

Slovenia

Slovenian Ecological Status assessment

system for rivers using benthic invertebrates

From Wiser:

The index includes the following metrics. The

metrics were combined

Saprobic index (SI = Sum of (Indicator Taxa

Abundance * Saprobic value* Indicator

weight) / Indicator Taxa Abundance* Indicator

weight), Slovenian multimetric index for

hydromorphological alteration/general

degradation (SMEIH = Weighted average of

three or four metrics - depends on river type)

The Slovenian method was presented to all

MS at the CY meeting.

The criteria for the selection of the potential

reference sites in the rivers include

hydromorphological and physico-chemical

condition of the site, riparian vegetation,

floodplain and land use properties, saprobic

index values, and some pressures presence.

Potential reference sites were defined without

considering the criteria of biotic pressures that

includes allochthonous species and fishery

management.

Italy Based on STAR_ICM index calculation

(MacrOper).

Method used in 1st IC and common metric.

Described in: Buffagni A., Erba S., Cazzola

M., Murray-Bligh J., Soszka H. & Genoni P.,

2006. The STAR common metrics approach to

the WFD intercalibration process: Full

application for small, lowland rivers in three

European countries. Hydrobiologia, 566: 379-

399

Multimetric index based on the following 6

metrics: average score per taxon, log 10

(sel_EPTD+1), 1-GOLD, total number of taxa

Families, number of EPT taxa (Families) and

the Shannon-Wiener diversity index.

Followed the REFCOND Guidance criteria

based on pressure criteria. The absence of

pressures had to be illustrated and this was done

by using methods and indices such as SH_RHS,

LRD (Lentic-lotic River Descriptor), HMS

(Habitat Modification Score), HQA (Habitat

Quality Assessment), LIM (Livello

inquinamento macrodescrittori - Pollution

Macrocostituents Level), IFF (Index of Fluvial

Functioning), LUI (Land Use Index) from

CORINE and CARAVAGGIO.

3. Checking of compliance of national assessment methods with the WFD

requirements

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)

List the WFD compliance criteria and describe the WFD compliance checking process

and results (the table below lists the criteria from the IC guidance, please add more

criteria if needed)

Compliance criteria Compliance checking conclusions

1. Ecological status is classified by one of

five classes (high, good, moderate, poor

and bad).

PT-yes

SP-yes; SP2-yes

FR-yes

IT-yes

SI-yes

CY-yes

2. High, good and moderate ecological

status are set in line with the WFD’s

normative definitions (Boundary

setting procedure)

PT-yes; High-Good classes boundary: 25th percentile

of reference sites; the range below was divided in 4

equal classes; Good-Moderate = H/G x 0.75; Moderate-

Poor = H/G x 0.50; Poor-Bad = H/G x 0.25

SP-yes; EQR class boundaries are set according to the

relationship between pressures and EQR values. High-

Good classes boundary: 25th percentile of reference

sites; the range below was divided in 4 equal classes;

Good-Moderate = H/G x 0.61; Moderate-Poor = H/G x

0.36; Poor-Bad = H/G x 0.15.

SP2-yes; High-Good classes boundary: 25th

percentile of reference sites; the range below was

divided in 4 equal classes; Good-Moderate = H/G x

0.75; Moderate-Poor = H/G x 0.50; Poor-Bad = H/G x

0.25

FR-yes; High-good boundary derived from metric

variability at near-natural reference sites.

IT-yes; Pressures were quantified using various

indices and tested positively for correlation with STAR

ICMi through a gradient of pressures covering sites

from high to bad status. The H/G boundary was set as

the 25th percentile of STAR ICMi values at reference

sites. The G/M boundary was set as H/G

boundary*0.75. The M/P boundary was set as H/G

boundary*0.5. The P/B boundary was set as H/G

boundary*0.25.

SI-yes; a) Saprobic index; High-Good clasess

boundary: 25th percentile of reference sites; Other

boundaries; equidistant division of the EQR gradient.

b) SMEIH index; All class boundaries were derived

using paired metrics that respond in different ways to

the influence of the hydromorphological pressure.

CY-yes; Equidistant division of the EQR gradient;

High-Good class boundary derived from 25th

percentile of reference sites. The rest of the boundaries

derived from equidistant division of the EQR gradient:

Good-Moderate = H/G x 0.75; Moderate-Poor = H/G x

0.50; Poor-Bad = H/G x 0.25

For all MS, the class boundaries were established

through statistical analysis. In all cases the 25th

percentile of reference sites defined the HG boundary.

3. All relevant parameters indicative of

the biological quality element are

covered (see Table 1 in the IC

Guidance)2. 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.

PT-yes

SP- abundance and diversity are not used;

SP2-yes

FR- abundance class in progress (see wiser)

IT-yes

SI-yes

CY-yes

4. Assessment is adapted to

intercalibration common types that are

defined in line with the typological

requirements of the WFD Annex II and

approved by WG ECOSTAT

PT- yes

SP- yes; SP2-yes

FR- yes

IT- yes

SI-yes

CY- yes

5. The water body is assessed against type-

specific near-natural reference

conditions

PT-yes

SP-yes; SP2-yes

FR-yes

IT-yes

SI-yes

CY-yes

6. Assessment results are expressed as

EQRs

PT-yes

SP-yes; SP2-yes

FR-yes

IT-yes

SI-yes

CY-yes

7. Sampling procedure allows for

representative information about water

body quality/ ecological status in space

and time3

PT- sampling done in 1 occasion in the year:

February-June

SP- 1 occasion: Spring; SP2: 1 occasion:

Spring

FR- 1 occasion June-September

IT- 2 (temporary rivers, Spring and Winter)

2 Diversity is used by the common metric (ICMi), which is also the IT and CY method. PT method uses

equitability as a metric, which is also derived from Shannon-Wiener diversity. FR includes the total number

of taxa and SP2 the total number of families. All methods are highly correlated with the common metric

(except SP with a lower correlation), which is fully compliant and has reliable responses to pressures. 3 Sampling takes place 1-3 times depending on the MS. Spring (month varies according to geographical

location) is common to all MS. Testing with the present data set suggests that the time variability is not

relevant in terms of EQR variability, even in Mediterranean conditions (please refer to Section 6.1).

or 3 occasions (Spring, Winter and

Autumn/Summer)

SI - 1 occasion: March to September

CY- 3 occasions: Winter, Spring and Autumn

8. All data relevant for assessing the

biological parameters specified in the

WFD’s normative definitions are

covered by the sampling procedure

PT-yes

SP-yes; SP2-yes

FR-yes

IT-yes

SI-yes

CY-yes

9. Selected taxonomic level achieves

adequate confidence and precision in

classification4

PT-yes

SP-yes; SP2-yes

FR-yes

IT-yes

SI-yes

CY-yes

All methods, except SI use family level. SI

method uses mostly genus/species level.

Clarify if there are still gaps in the national method descriptions information.

Summarise the conclusions of the compliance checking:

The compliance checking indicates that there is no problem to intercalibrate.

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

RM1 catchment <100 km2; mixed

geology (except non-

siliceous); highly seasonal

SP, FR,IT,PT,SI

RM2 catchment 100-1000 km2 ;

mixed geology (except non-


SP, IT,PT,SI

RM3 catchment 1000-10000 km2 ;

mixed geology (except


This type cannot be

intercalibrated due to the lack of

comparability between MS

methods and insufficient number

of reference sites.

4 The common identification level was Family to avoid major biogeographical differences.

RM4 non-siliceous streams; highly

seasonal

IT,CY,SP,FR

RM5 temporary rivers SP,IT,PT,CY,SI

Note: The borders of the types were redefined for a better adjustment to the ecological reality.

The redefinition was based on ordination data treatment, and presented, discussed and agreed in

the General Mediterranean GIG meetings. The biological analysis furthermore revealed a poor

segregation between types RM1, 2 and 4. Therefore these types were treated together throughout

the IC process.

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?

Conclusion Is the Intercalibration feasible in terms of typology?

All MS assessment methods are appropriate for the IC types RM1, RM2, RM4 and RM5.

RM3 type could not be intercalibrated due to the lack of comparability between MS methods

and insufficient number of reference sites.

4.2. Pressures

Method Pressure Remarks

Method PT General degradation, acidification,

eutrophication, flow modification, Habitat

destruction, hydromorphological degradation,

pollution by organic compounds, pollution by

organic matter, riparian vegetation alteration

Method SP1 Pollution by organic matter

Method SP2 General degradation: catchment land use,

eutrophication, pollution by organic matter,

riparian habitat alteration

Method FR Catchment land use, eutrophication, general

degradation, pollution by organic matter

Method SI General degradation, hydromorphological

degradation, pollution by organic matter

Method CY Catchment land use, flow modification,

general degradation, habitat destruction,

hydromorphological degradation, pollution by

organic matter, riparian habitat alteration

Method IT Catchment land use, flow modification,

general degradation, habitat destruction,

hydromorphological degradation, pollution by

organic matter, riparian habitat alteration

Conclusion Intercalibration is feasible in terms of pressures addressed by the methods:

1 – feasible; all methods but one address general degradation, and some address more than

one kind.

The above table refers to the information gathered in Wiser and provided by each MS.

Additionally, and using the MedGIG database, we tested the response of the common metric

(STAR-ICMi) to: 1) individual types of pressures (Table 1) and 2) to a general degradation

gradient (obtained from PCA axes scores), assuming that if the national methods are well

correlated to the common metric (see 7.2) and if the common metric responds well to

individual and global pressure, then the national methods do it too. This comes in addition to

all published information about the national indices and the common metric (Buffagni et al.

2006).

The Spearman correlations of the common metric to the individual pressures (based on

reference and disturbed sites dataset) are:

Note: In bold are highly significant correlations (rho>0.5 and p<0.00001).

The above results show that the ICMi index responds well to most of the individual pressures

found in MedGIG streams, and mainly to local habitat alteration, degradation of riparian

vegetation, organic contamination, and artificial land use.

A PCA based on pressure data of all sites of the MedGIG showed that the first 3 axes explain

60% of the variation and PC1 alone explains 32% of the variation. This axis (PC1) traduces a

general degradation gradient and is mainly related with morphological changes (0.4), N-NO3-

(0.4) and PO4 (0.4) contamination, degradation of riparian vegetation (0.5), artificial areas (0.4)

and intensive agriculture (0.3).

This axis is highly correlated with the ICMi values for the MedGIG database:

Pearson correlation PC1

STAR_ICM index R=0.774

Reference and Disturbed sites ICMi

(Spearman rho, p, n)

Channelization (class) -0.409, p<0.00001, 997

Bank alteration (class) -0.399, p<0.00001, 979

Connectivity (class) -0.132, p<0.0001, 999

Local habitat alteration (class) -0.487, p<0.00001, 715

Stream flow (class) -0.144, p<0.00001, 999

Upstream dams influence (class) -0.137, p<0.0001, 998

Hydropeaking (class) 0.341, p<0.00001, 989

Riparian vegetation (class) -0.664, p<0.00001, 979

O2 (%) 0.085, p<0.01, 1030

N-NH4+ (mg/l) -0.445, p<0.00001, 1052

N-NO3- (mg/l) -0.447, p<0.00001, 1080

P-Total (mg/l) -0.363, p<0.00001, 424

P-PO4 (mg/l) -0.543, p<0.00001, 1032

BOD5 (mg/l) -0.219, p<0.00001, 545

Artificial areas (%) -0.593, p<0.00001, 1148

Intensive agriculture (%) -0.423, p<0.00001, 1148

Extensive agriculture (%) -0.0208, p>0.05, 1148

Semi-natural areas (%) 0.423, p<0.00001, 1151

p<0.00001

N=802

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 PT Multi habitat sampling, structural assessment of

communities

Method SP1, SP2 Multi habitat sampling, structural assessment of

communities

Method FR Multi habitat sampling, structural assessment of

communities

Method SI Multi habitat sampling, structural assessment of

communities

Method CY Multi habitat sampling, structural assessment of

communities

Method IT Multi habitat sampling, structural assessment of

communities

Conclusion

Intercalibration is feasible in terms of assessment concepts:

1 – feasible; all methods involve sampling of different relevant habitats in the reach and

include taxa or taxa groups which are sensitive to different kinds of degradation

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 types:

Member State Number of samples

Biological data Physico- chemical data Pressure data

RM1

Portugal 30 30 30

Spain 340 340 340

France 97 97 97

Italy 8 8 8

Slovenia 34 34 34

Cyprus - - -

RM2

Portugal 30 30 30

Spain 86 86 86

France 31 31 31

Italy 7 7 7

Slovenia 13 13 13

Cyprus - - -

RM3

Portugal 22 22 22

Spain 1 1 1

France 1 1 1

Italy - - -

Slovenia - - -

Cyprus - - -

RM4

Portugal - - -

Spain 195 195 195

France 240 240 240

Italy 6 6 6

Slovenia - - -

Cyprus 85 85 85

RM5

Portugal 30 30 30

Spain 59 59 59

France - - -

Italy 5 5 5

Slovenia 8 8 8

Cyprus 56 56 56

Note: Some countries have provided RM3 sites but the number of sites, particularly of reference, is

insufficient for intercalibration purposes, and some methods were not comparable.

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

optional)

Common pressure data, common environmental

data, correctly checked typologies and

geographical location and biotic data, all

properly introduced in harmonized excel files.

The sampling and analytical

methodology

All MS sampling methods use a multi-habitat

approach. All MS have indicated a response of

their indices to pressure using statistical tools.

Level of taxonomic precision

required and taxa lists with codes

Family level is required.

The minimum number of sites /

samples per intercalibration type

A minimum of 15 reference sites by IC type are

available.

Sufficient covering of all relevant

quality classes per type

Yes. See Figure 1 below of the distribution of

classes per type. Note: SI, PT, SP, FR and CY provided information for both reference and disturbed sites.

Figure 1. Distribution of classes of IC benchmarks by type from MedGIG database for invertebrates.

6. Benchmarking: Reference conditions or alternative benchmarking (October 2010

+ later updates)

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)

- or a common alternative benchmark for intercalibration (N)

The Mediterranean GIG has developed common reference conditions. Following data treatment

by Maria João Feio, a proposal for reference conditions thresholds was brought to the General

GIG meetings, and intensively discussed till a final collective decision was made. The same and

common thresholds were used for the BQEs macroinvertebrates, phytobenthos and macrophytes.

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)

RM1

Class1

Class2

Class3

Class4

Class5

RM2

Class1

Class2

Class3

Class4

Class5

RM4

Class1

Class2

Class3

Class4

Class5

RM5

Class1

Class2

Class3

Class4

Class5

- Summarize the common approach for setting reference conditions (true reference

sites or indicative partial reference sites, see Annex III of the IC guidance):

Reference sites exist in the common data base for all IC types, except for RM3; the sites

considered reference sites were those minimally disturbed, corresponding to best available

situation in the present, in the Mediterranean region, and assuming that pristine conditions no

longer exist.

The selection of IC reference sites was done through a 3 steps procedure. Steps 1 and 2, up to the

establishment of reference thresholds, were performed with the information for MS reference

sites provided to the MedGIG database. We used sites supplied to the MedGIG for invertebrates,

diatoms and macrophytes databases. The global database was composed of a total of 919 member

states reference sites distributed through the 4 IC river types (RM1, RM2, RM4, RM5) and 7 MS

(CY, FR, GR, IT, PT, SI, SP).

Step 1. Original national reference sites are selected only if all their categorical variables have

class 1, no impact or minimal impact.

Step 2. Reference thresholds are calculated for numerical pressure variables using the common

data base, based on reference sites selected in Step 1 and for each IC type. Extreme values for

each pressure variable and IC type were previously excluded after histograms and boxplots

inspection. These observed ranges characterize the pressure levels existent in the minimally

impacted sites, for each IC type, in the Mediterranean region.

A unique value for each pressure variable (Reference thresholds) was afterwards calculated for all

IC types, corresponding to the maximum pressure acceptable overall Mediterranean types, in

order to reach a common tolerance level. However, for RM5, the temporary rivers, different

ranges for water oxygenation were established for low water periods.

The following table describes the thresholds established and applied for each pressure variable

and used by the MEDGIG for IC. The values are common to all IC types except for O2, with a

different limit for RM5.

References are accepted if

Pressure variables RM1+RM2+RM4 RM5

Channelization (classes 1-4)

≤ 2

Bank alteration (classes 1-4)

Connectivity (classes 1-4)

Local habitat alteration (classes 1-4)

Stream Flow (classes 1-4)

Upstream dams influence (classes 1-4)

Hydropeaking (classes 1-4)

Riparian Vegetation (classes 1-4)

DO (mg/L) 1 6,39-13,70

O2 (%) 73,72-127,92 60,34-127,92

N-NH4+

(mg/L) ≤0,09

N-NO3- (mg/L) ≤1,15

P-Total (mg/L) ≤0,07

P-PO43-

(mg/L) ≤0,06

% Artificial areas (catchm) ≤1

% Intensive agriculture (catchm) ≤11

% Extensive agriculture (catchm) ≤32

% Semi-natural areas (catchm) ≥68

% Urbanisation (reach) 2

≤1

% Land use (reach) 2 ≤20

% Agriculture (reach) 2 ≤20

1 for macrophytes only, instead of O2 (%)

2 for diatoms only, instead of land use in the catchment

Step 3. Final abiotic screening of reference sites. Potential reference sites, left out in Step I, are

rescreened and those with categorical variables in class 2 (any number) but simultaneously with

numerical variables values within the thresholds defined in Step 2 are chosen and added to the

reference set of Step 1.

After this screening, we checked if for the same site some samples passed step 3 and others not.

We re-included in the IC benchmarks all samples belonging to sites for which the mean values

passed the thresholds.

Finally, for MS with a low cover of reference sites for a given type, we looked at those sites

supplied as disturbed (at the national level) and if they passed the established quantitative

thresholds they were also included also in the set of benchmarks. This happened however, only

for Slovenia for types RM1 and RM2, for the invertebrate’s dataset.

- Give a detailed description of reference criteria for screening of sites in near-natural

conditions (abiotic characterisation, pressure indicators):

See above.

- Identify the reference sites for each Member State in each common IC type. Is their

number sufficient to make a statistically reliable estimate? Yes.

Number of benchmark samples finally selected to the IC process by the MedGIG for macroinvertebrates,

by the MS and by type. Spring-Summer samples are within parentheses.

RM1 RM2 RM4 RM124 RM5 Total

CY - - 25(14) 25(14) 12(9) 37 (23)

FR 53(37) 6(5) 94(65) 153(107) - 153 (107)

IT 8(2) 7(6) 6(2) 21(10) 5(3) 26 (13)

PT 8(8) 5(5) - 13(13) 3(3) 16 (16)

SI 6(4) 4-1*(4-1*) - 11(9) 1(0) 12 (9)

SP 18(18) 1(1) 25(25) 44(44) 25-2*(25-2*) 69 (69)

Total 93 (69) 25 (23) 150 (106) 268(198) 46 (40) 314 (240)

*sample eliminated due to exceptionally low ICMi value. See figure 2.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 10 20 30 40 50 60 70 80

ICMiRM1refallMS

SI_ReSK0808

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 5 10 15 20 25

ICMiRM2refallMS

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

0 20 40 60 80 100 120

ICMiRM4refallMS

ESL44070508 ESL45200405

ESL45270404

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

0 5 10 15 20 25 30 35 40 45 50

ICMiRM5refallMS

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:

For subsequent analyses, after the abiotic screening, ICMi distribution plots were made by IC

type and extremes (low values) were excluded. This resulted however in the exclusion of only

one sample from RM2 and two samples from RM5, as shown above.

Figure 2. Distribution of ICMi values of benchmark sites, by type, for all MS. The value considered an extreme value

that was excluded from subsequent analyses is signed in red.

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

0 10 20 30 40 50

ICMi

RM2

Winter-Autumn

Spring-Summer

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

2.000

0 10 20 30 40 50

ICMi

RM5

Winter-Autumn

Spring-Summer

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0 10 20 30 40 50

ICMi

RM4

Winter-Autumn

Spring-Summer

Moreover, we run Spearman rank correlations between pressure variables and ICMi values for

reference sites only, assuming that these correlations should be low; furthermore, those

correlations were compared with the same correlations for reference and disturbed sites (see 4.2),

where higher correlations were expected. Both our expectations were confirmed. The IC

benchmark sites include sites with small changes at the connectivity level and land use, which

was the accepted level for common thresholds.

The table shows the Spearman rank correlations between reference sites ICMi EQR values and

pressure data.

Finally it was analysed whether the seasonal variability felt in Mediterranean countries,

especially in temporary rivers (RM5) would result in a difference in the EQR values obtained

for reference sites. This was part of the MedGIG working plan for the 2nd

phase of the IC.

Reference sites ICMi

(rho, p, n)

Channelization (class) -0.023, p>0.05, 234

Bank alteration (class) 0.016, p>0.05, 234

Connectivity (class) -0.145, p<0.05, 236

Local habitat alteration (class) -0.023, p>0.05, 128

Stream flow (class) -0.112, p>0.05, 236

Upstream dams influence (class) 0.000, p>0.05, 236

Hydropeaking (class) 0.080, p>0.05, 236

Riparian vegetation (class) -0.015, p>0.05, 234

O2 (%) -0.100, p>0.05, 227

N-NH4+ (mg/l) -0.035, p>0.05, 226

N-NO3- (mg/l) -0.103, p>0.05, 229

P-Total (mg/l) 0.182, p<0.05, 164

P-PO4 (mg/l) -0.028, p>0.05, 217

BOD5 (mg/l) -0.145, p<0.05, 210

Artificial areas (%) -0.224, p<0.001, 236

Intensive agriculture (%) -0.216, p<0.001, 236

Extensive agriculture (%) -0.079, p>0.05, 236

Semi-natural areas (%) 0.155, p<0.05, 236

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 10 20 30 40 50

ICMi

RM1

Winter-Autumn

Spring-Summer

Figure 3. Comparison between winter-autumn and spring-summer ICMi values by type, considering all MS and only

reference sites.

The results indicate that, in general, the ICMi values of reference sites obtained in different

seasons cannot be distinguished and also that in within seasons there is a high variability of

values. However in RM1 (smaller rivers) the values for autumn and winter samples seem to be

generally lower that those of spring and summer even though there are also some equivalent

lower values within that season.

In the calculations for intercalibration and harmonization, the data that was used was nevertheless

restricted to spring-summer data, with the exception of CY and IT, as for the remaining MS the

boundaries were defined based on spring-summer data.

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

For ICM calculation purposes the median of the selected reference sites values per MS was used

in order to recalculate the original EQR values. The only exception was for RM5, for SI, as due to

the absence of reference data and after considering other possibilities (as alternative

benchmarking), the best solution found was the use of other MS reference sites data of the same

type. RM1, RM2 and RM4 were treated as only one type.

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)

- 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:

The SIMPER analysis (Bray-Curtis similarity; Primer 6) was used to determine the taxa

(families) that contribute the most (up to 90% of cumulative contribution) to the average

similarity within type. The results are comparatively shown in the following table with the

average abundances of the most representative taxa of the reference sites of each type/group of

types. In bold are highlighted the taxa that are exclusive of that type.

Representative taxa RM1, RM2, RM4 RM5

CHIRONOMIDAE 992.31 CHIRONOMIDAE 211.50

BAETIDAE 676.26 SIMULIIDAE 84.09

SIMULIIDAE 540.22 BAETIDAE 61.16

HEPTAGENIIDAE 154.78 HYDROPTILIDAE 23.02

LEUCTRIDAE 157.92 HYDRACARINA 42.27

ELMIDAE 368.07 OSTRACODA 50.57

EPHEMERELLIDAE 322.28 GAMMARIDAE 35.82

HYDROPSYCHIDAE 82.20 CERATOPOGONIDAE 19.68

GAMMARIDAE 683.67 OLIGOCHAETA 22.68

OLIGOCHAETA 312.08 CAENIDAE 8.86

HYDRACARINA 199.41 HEPTAGENIIDAE 9.32

NEMOURIDAE 171.65 DYTISCIDAE 5.00

LEPTOPHLEBIIDAE 72.55

LIMONIIDAE 57.59

LIMNEPHILIDAE 78.53

Note: only reference samples and spring data (even for CY) were used.

These results should be considered a trend, as the within sites similarity of the two types is low

(ca. 20%), which is expectable, due to the large geographical distance included (from PT to CY).

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

evaluation (N)

- IC Option 2 - Different data acquisition and numerical evaluation (Y)

- 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) (N)

- Other (specify) (Y/N)

Explanation for the choice of the IC option:

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

Option 2, since there are minor differences in field data acquisition, sampling protocols and area

sampled, as well as the way to express qualitative/quantitatively the data.

Also, the Slovenian method uses a taxonomic level lower than the methods from other MS

(family); therefore the Slovenian method cannot be applied to the datasets of the other MS.

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

Describe the IC Common metric:

We used a common metric previously developed in the first intercalibration exercise, the

Intercalibration Common Metric index (ICMi), described in Buffagni A., Erba S., Cazzola M.,

Murray-Bligh J., Soszka H. & Genoni P., 2006. The STAR common metrics approach to the

WFD intercalibration process: Full application for small, lowland rivers in three European

countries. Hydrobiologia, 566: 379-399

The ICMi is a multimetric index covering the aspects of the normative definition for the

ecological status classification (WFD Annex V, 1.2.1). The following 6 metrics are used: average

score per taxon, log 10 (sel_EPTD+1), 1-GOLD, total number of taxa Families, number of EPT

taxa (Families) and the Shannon-Wiener diversity index.

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/type

Linear regression* Pearson r

Method PT/ RM124 ICMi = 0.856 IPtI + 0.086 R=0.94

Method PT/ RM5 ICMi = 0.867 IPtI + 0.053 R=0.98

Method SP1/ RM124 ICMi = 0.632 IBMWP + 0.244 R= 0.89

Method SP1/ RM5 ICMi = 0.437 IBMWP + 0.656 R= 0.49***

Method SP2/ RM124 ICMi = 0.898 IMMi-T + 0.05 R= 0.94

Method SP2/ RM5 ICMi = 1.177 IMMi-T + 0.090 R= 0.86

Method FR/ RM124 ICMi = 0.833 IBGN + 0.143 R=0.89

Method Sl/ RM124 ICMi = 0.695 Sl index + 0.327 R= 0.87

Method Sl/ RM5 ICMi = 0.678 Sl index + 0.543 R= 0.82

Method CY y=x** 1**

Method IT y=x** 1**

* Normality of residuals was met.

** The correlation is assumed to be 1 since the national method is the common metric (ICMi) itself.

***As this regression obtained with the MedGIG data set was only marginally acceptable, it was decided to

remove this index from the IC calculations and harmonization of 2nd

IC phase for RM5 type in order to

provide a better harmonization among the other MS metrics for RM5. The IBMWP class boundaries used

by Spain for the RM5 river type were intercalibrated and harmonizated in the 1st. intercalibration phase and

class boundaries can be found there.

Explain if any method had to be excluded due to its low correlation with the common

metric:

The regression for the IBMWP for type RM5 is only marginally acceptable (R=0.5) which may

affect the following results. The slope (0.427) in the same regression is also low, even though

close to the minimum value recommended in the Annex V (0.5). For temporary rivers (RM5), the

relationship between pressures and IBMWP values is not completely lineal. Moreover, dry and

wet periods can increase the reference variability for IBMWP, and samples must be carefully

checked. Sites and samples for Spanish RM5 were properly selected in the 1st intercalibration

phase in order to provide suitable information for the harmonization procedure. The Spanish

IBMWP index for RM5 river type was successfully intercalibrated in the 1st Phase.

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

Clarify if

- boundaries were set only at national level (Y)

- 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

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)

National boundaries are established and are translated to ICM using the regression equation

after 1st phase. Some MS adjusted later on their boundaries due to revision of reference

criteria, such as SP. SI provided the national boundaries which weren’t derived from the 1st

IC as this MS didn’t participate in the process before.

Provide pressure-response relationships (describe how the biological quality

element changes as the impact of the pressure or pressures on supporting elements

increases)

The ICMi values are well correlated with the increase of global pressure and with some

individual impacts, such as habitat alteration, degradation of riparian vegetation, organic

contamination, and artificial land use, as shown in the tables of sections 4) and 5). Since the

ICM is well correlated to all other national methods, we assume identical correlations. It is

not possible to do this analysis for each MS individual as this would result in a very low

number of sites for some MS and river types. Furthermore, MS indicate that they have done

this work at the national level previously.

Provide a comparison with WFD Annex V, normative definitions for each QE/

metrics and type See section 3.

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).

SIMPER analysis (no transformation; Bray-Curtis coefficient; up to 90% of contribution to av.

Similarity; Primer 6) was performed on RM1, RM2 and RM4 together and on RM5 types, with

the taxonomic composition (families) to determine the taxa contributing the most to the average

Bray-Curtis dissimilarity between the sites classified as Good and those classified as moderate,

according to national classification systems (before harmonization).

Results for RM1, RM2 and RM4:

Taxa contributing to dissimilarity Good (av. Abundance) Moderate (av. Abundance)

CHIRONOMIDAE 297.78 442.62

BAETIDAE 147.5 196.48

OLIGOCHAETA 73.24 100.05

SIMULIIDAE 65.06 69.6

GAMMARIDAE 42.83 47.23

CAENIDAE 28.43 77.22

TUBIFICIDAE 72.37 27.55

HYDROBIIDAE 11.32 164.64

ANCYLIDAE 37.52 13.64

0

50

100

150

200

250

300

350

400

450

500

CHIRONOM

IDAE

BAETIDAE

OLIGOCHAETA

SIMULIIDAE

GAMMARIDAE

CAENIDAE

TUBIFICIDAE

HYDROBIIDAE

ANCYLIDAE

OSTRACODA

EPHEMERELLIDAE

HYDROPSYCHIDAE

LEPTOPHLEBIIDAE

HYDRACARINA

ELMIDAE

DYTISCIDAE

HEPTAGENIIDAE

LEUCTRIDAE

HYDROPTILIDAE

PHYSIDAE

LYMNAEIDAE

ERPOBDELLIDAE

CORIXIDAE

GERRIDAE

BITHYNIIDAE

PLANORBIDAE

LIMONIIDAE

PERLODIDAE

SPHAERIIDAE

Good

Moderate

OSTRACODA 19.06 25.07

EPHEMERELLIDAE 29.01 7.5

HYDROPSYCHIDAE 28.43 10.5

LEPTOPHLEBIIDAE 25.74 6.07

HYDRACARINA 13.37 14.48

ELMIDAE 16.79 6.94

DYTISCIDAE 13.06 10.17

HEPTAGENIIDAE 14.05 3.38

LEUCTRIDAE 12.8 7.58

HYDROPTILIDAE 10.65 13.7

PHYSIDAE 17.28 10.92

LYMNAEIDAE 15.85 3.64

ERPOBDELLIDAE 6.69 12.13

CORIXIDAE 2.4 10.4

GERRIDAE 9.62 5.21

BITHYNIIDAE 4.12 17.45

PLANORBIDAE 5.19 10.51

LIMONIIDAE 6.64 8.16

PERLODIDAE 6.23 3.24

SPHAERIIDAE 6.74 9.12

Results for RM5: Taxa contributing to dissimilarity Good (av. Abundance) Moderate (av. Abundance)

CHIRONOMIDAE 230.13 264.1

SIMULIIDAE 256.42 258.4

BAETIDAE 384.85 115.4

TUBIFICIDAE 22.96 195.6

COENAGRIONIDAE 1.08 157.55

OSTRACODA 45.28 14.55

HYDRACARINA 71.6 0.65

BITHYNIIDAE 0 92.05

CAENIDAE 27.74 47.35

OLIGOCHAETA 31.89 6

LIMNEPHILIDAE 2.04 69.55

GAMMARIDAE 33.55 0.8

PLANORBIDAE 32.47 4.2

HYDROPTILIDAE 18.6 2.65

ELMIDAE 26.06 10.2

PHYSIDAE 3.28 10.25

CORIXIDAE 2.7 11.6

PERLODIDAE 11.83 1.4

DYTISCIDAE 12.85 5.9

ASELLIDAE 0.83 5.95

LYMNAEIDAE 15.13 2.05

GERRIDAE 12.51 2.5

ERPOBDELLIDAE 1.72 19.85

VELIIDAE 12.17 0.1

LEPTOPHLEBIIDAE 4.74 4.5

For both types/groups of types the changes found between good and moderate classes are mainly

due to the loss (in more sensitive taxa) or gain of individuals (more tolerant or opportunistic) than

in the loss of taxa. This may however only happen at family level (the level of identification used

by most MS).

8.3. Boundary comparison and harmonisation

Describe comparison of national boundaries, using comparability criteria (see Annex V

of IC guidance).

Following the Annex V, the result of boundary comparison is illustrated in the following tables

and figures. The tables illustrate the calculations necessary for boundary bias checking and the

initial result. The figures show the final localization of MS boundaries ± quarter of class width,

and the common ICM boundary (blue line), by type. As a unique boundary was defined within

the MedGIG for types RM1, RM2 and RM4, the respective MS boundaries are show within the

same picture.

Typological codes used in following figures and tables.

Code MS Type

CY-Type 1 CY R-M4

0

50

100

150

200

250

300

350

400

450

CHIRONOM

IDAE

SIMULIIDAE

BAETIDAE

TUBIFICIDAE

COENAGRIONIDAE

OSTRACODA

HYDRACARINA

BITHYNIIDAE

CAENIDAE

OLIGOCHAETA

LIMNEPHILIDAE

GAMMARIDAE

PLANORBIDAE

HYDROPTILIDAE

ELMIDAE

PHYSIDAE

CORIXIDAE

PERLODIDAE

DYTISCIDAE

ASELLIDAE

LYMNAEIDAE

GERRIDAE

ERPOBDELLIDAE

VELIIDAE

LEPTOPHLEBIIDAE

Good

Moderate

CY-Type 2 CY R-M5

FR-Type 1 FR R-M1

IT-Type 1 IT R-M1

IT-Type 2 IT R-M2

IT-Type 3 IT R-M4

IT-Type 4 IT R-M5

PT-Type 1 N1≤100

PT-Type 2 N2

PT-Type 3 N3

PT-Type 4 N1≥100

PT-Type 5 S1<100

PT-Type 6 S3

SI-Type 1 SL R-M1

SI-Type 2 SL R-M2

SI-Type 3 SI R-M5

SP1-Type 1 IBMWP R-M1



SP1-Type 4 SP1 R-M5

SP2-Type 1 IMM R-M1

SP2-Type 2 IMM R-M2

SP2-Type 3 IMM R-M4

SP2-Type 4 SP2 R-M5

Results of boundary bias checking and adjustment of HG and GM boundaries:

ORIGINAL

PT-Type1 PT-Type2 PT-Type3 PT-Type4 SP1-Type1 SP1-Type2 SP1-Type3 SP2-Type1 SP2-Type2 SP2-Type3 FR-Type1 IT-Type1 IT-Type2 IT-Type3 SL-Type1 SL-Type2 CY-Type1 MedianH/GOriginal

HighMax(maximumofnationalEQR) 1.163 1.163 1.163 1.163 1.181 1.181 1.192 1.181 1.181 1.192 1.356 1.037 1.132 1.057 1.117 1.001 1.285 0.831

H/GBoundary+0.25H 0.914 0.888 0.901 0.920 0.848 0.848 0.865 0.872 0.831 0.908 1.034 0.987 0.988 0.969 0.941 0.912 1.050

H/GBoundary(foreachMS) 0.831 0.796 0.814 0.839 0.737 0.737 0.756 0.768 0.715 0.813 0.926 0.970 0.940 0.940 0.883 0.883 0.972

H/GBoundary-0.25H 0.784 0.749 0.758 0.792 0.707 0.707 0.724 0.724 0.672 0.766 0.899 0.908 0.880 0.880 0.848 0.848 0.911

H/GMedGIGMedian 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831

H/Gquarter(+) 0.083 0.092 0.087 0.081 0.111 0.111 0.109 0.103 0.117 0.095 0.107 0.017 0.048 0.029 0.058 0.029 0.078

H/Gquarter(-) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.045 0.043 0.047 0.027 0.063 0.060 0.060 0.035 0.035 0.061

Good/moderateMax 0.831 0.796 0.814 0.839 0.737 0.737 0.756 0.768 0.715 0.813 0.926 0.970 0.940 0.940 0.883 0.883 0.972 MedianG/MOriginal

G/M+0.25H 0.689 0.655 0.647 0.698 0.647 0.647 0.661 0.634 0.587 0.672 0.845 0.783 0.760 0.760 0.779 0.779 0.790 0.642

G/MBoundary(foreachMS) 0.642 0.608 0.591 0.651 0.617 0.617 0.630 0.589 0.544 0.625 0.818 0.720 0.700 0.700 0.744 0.744 0.729

G/MBoundary-0.25H 0.595 0.561 0.535 0.604 0.587 0.587 0.598 0.544 0.501 0.578 0.791 0.658 0.640 0.640 0.709 0.709 0.668

M/PMin 0.454 0.420 0.368 0.463 0.497 0.497 0.503 0.409 0.373 0.436 0.709 0.470 0.460 0.460 0.605 0.605 0.486

G/MMedGIGMedian 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642

G/Mquarter(+) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.045 0.043 0.047 0.027 0.063 0.060 0.060 0.035 0.035 0.061

G/Mquarter(-) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.045 0.043 0.047 0.027 0.063 0.060 0.060 0.035 0.035 0.061

Statistic 0.00 -0.09 -0.05 0.05 -0.21 -0.21 -0.17 -0.15 -0.25 -0.05 0.88 0.56 0.46 0.46 0.38 0.38 0.58

Statistic 0.00 -0.18 -0.23 0.05 -0.21 -0.21 -0.10 -0.30 -0.58 -0.09 1.62 0.31 0.24 0.24 0.73 0.73 0.36

Harmonized

PT-Type1 PT-Type2 PT-Type3 PT-Type4 SP1-Type1 SP1-Type2 SP1-Type3 SP2-Type1 SP2-Type2 SP2-Type3 FR-Type1 IT-Type1 IT-Type2 IT-Type3 SL-Type1 SL-Type2 CY-Type1 MedianH/Gharmonizado

HighMax(maximumofnationalEQR) 1.163 1.163 1.163 1.163 1.181 1.181 1.192 1.181 1.181 1.192 1.356 1.037 1.132 1.057 1.117 1.001 1.285 0.831

H/GBoundary+0.25H 0.914 0.888 0.901 0.920 0.848 0.848 0.865 0.872 0.831 0.908 1.010 0.916 0.939 0.921 0.941 0.912 0.979 0.876

H/GBoundary(foreachMS) 0.831 0.796 0.814 0.839 0.737 0.737 0.756 0.768 0.715 0.813 0.894 0.875 0.875 0.875 0.883 0.883 0.877

H/GBoundary-0.25H 0.784 0.749 0.758 0.792 0.707 0.707 0.724 0.726 0.690 0.766 0.831 0.832 0.831 0.831 0.826 0.826 0.832

H/GMedGIGMedian 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831 0.831

H/Gquarter(+) 0.083 0.092 0.087 0.081 0.111 0.111 0.109 0.103 0.117 0.095 0.115 0.041 0.064 0.046 0.058 0.029 0.102

H/Gquarter(-) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.042 0.024 0.047 0.063 0.044 0.044 0.044 0.057 0.057 0.046

Good/moderateMax 0.831 0.796 0.814 0.839 0.737 0.737 0.756 0.768 0.715 0.813 0.894 0.875 0.875 0.875 0.883 0.883 0.877 MedianG/MHarmonizado

G/M+0.25H 0.689 0.655 0.647 0.698 0.647 0.647 0.661 0.642 0.642 0.672 0.706 0.745 0.744 0.744 0.712 0.712 0.741 0.642

G/MBoundary(foreachMS) 0.642 0.608 0.591 0.651 0.617 0.617 0.630 0.600 0.618 0.625 0.643 0.701 0.700 0.700 0.655 0.655 0.695

G/MBoundary-0.25H 0.595 0.561 0.535 0.604 0.587 0.587 0.598 0.552 0.557 0.578 0.643 0.643 0.640 0.640 0.643 0.643 0.643

M/PMin 0.454 0.420 0.368 0.463 0.497 0.497 0.503 0.409 0.373 0.436 0.709 0.470 0.460 0.460 0.605 0.605 0.486

G/MMedGIGMedian 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642 0.642

G/Mquarter(+) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.042 0.024 0.047 0.063 0.044 0.044 0.044 0.057 0.057 0.046

G/Mquarter(-) 0.047 0.047 0.056 0.047 0.030 0.030 0.032 0.048 0.061 0.047 0.000 0.058 0.060 0.060 0.013 0.013 0.052

Statistic 0.00 -0.09 -0.05 0.05 -0.21 -0.21 -0.17 -0.15 -0.25 -0.05 0.25 0.25 0.25 0.25 0.23 0.23 0.25

Statistic 0.00 -0.18 -0.23 0.05 -0.21 -0.21 -0.10 -0.25 -0.25 -0.09 0.00 0.25 0.24 0.24 0.25 0.25 0.25

PT-Type1

PT-Type2

PT-Type3

PT-Type4

SP1-Type1

SP1-Type2

SP1-Type3

SP2-Type1

SP2-Type2

SP2-Type3

FR-Type1

IT-Type1

IT-Type2

IT-Type3

SL-Type1

SL-Type2

CY-Type1

0.600

0.700

0.800

0.900

1.000

1.100

1.200RM1,RM2&RM4-originalboundaries

H/GBoundary(foreachMS)

MedianH/GOriginal

PT-Type1

PT-Type2

PT-Type3

PT-Type4

SP1-Type1

SP1-Type2

SP1-Type3

SP2-Type1

SP2-Type2

SP2-Type3

FR-Type1

IT-Type1

IT-Type2

IT-Type3

SL-Type1

SL-Type2

CY-Type1

0.400

0.500

0.600

0.700

0.800

0.900

1.000RM1,RM2&RM4-originalboundaries

G/MBoundary(foreachMS)

MedianG/MOriginal

PT-Type1

PT-Type2

PT-Type3

PT-Type4

SP1-Type1

SP1-Type2

SP1-Type3

SP2-Type1

SP2-Type2

SP2-Type3

FR-Type1

IT-Type1

IT-Type2

IT-Type3

SL-Type1

SL-Type2

CY-Type1

0.600

0.700

0.800

0.900

1.000

1.100

1.200 RM1,RM2&RM4-harmonizedboundaries


MedianH/Gharmonizado

PT-Type1

PT-Type2

PT-Type3

PT-Type4

SP1-Type1

SP1-Type2

SP1-Type3

SP2-Type1

SP2-Type2

SP2-Type3

FR-Type1

IT-Type1IT-Type2

IT-Type3

SL-Type1

SL-Type2

CY-Type1

0.400

0.500

0.600

0.700

0.800

0.900

1.000 RM1,RM2&RM4-harmonizedboundaries


MedianG/MHarmonizado

ORIGINAL

PT-Type5 PT-Type6 SP2-Type4 IT-Type4 SL-Type3 CY-Type2 MedianH/GOriginal

HighMax(maximumofnationalEQR) 1.237 1.237 1.591 1.057 1.300 1.130 0.976

H/GBoundary+0.25H 0.967 0.921 1.198 0.992 1.139 1.019

H/GBoundary(foreachMS) 0.877 0.816 1.067 0.970 1.085 0.982

H/GBoundary-0.25H 0.822 0.768 1.005 0.910 1.051 0.921

H/GMedGIGMedian 0.976 0.976 0.976 0.976 0.976 0.976

H/Gquarter(+) 0.090 0.105 0.131 0.022 0.054 0.037

H/Gquarter(-) 0.054 0.048 0.062 0.060 0.034 0.061

Good/moderateMax 0.877 0.816 1.067 0.970 1.085 0.982 MedianG/MOriginal

G/M+0.25H 0.714 0.673 0.882 0.790 0.984 0.798 0.734

G/MBoundary(foreachMS) 0.660 0.625 0.820 0.730 0.950 0.737

G/MBoundary-0.25H 0.606 0.578 0.758 0.670 0.916 0.676

M/PMin 0.443 0.434 0.573 0.490 0.814 0.492

G/MMedGIGMedian 0.734 0.734 0.734 0.734 0.734 0.734

G/Mquarter(+) 0.054 0.048 0.062 0.060 0.034 0.061

G/Mquarter(-) 0.054 0.048 0.062 0.060 0.034 0.061

H/GStatistic -0.28 -0.38 0.37 -0.07 0.81 0.02

G/MStatistic -0.34 -0.57 0.35 -0.01 1.59 0.01

HARMONIZED

PT-Type5 PT-Type6 SP2-Type4 IT-Type4 SL-Type3 CY-Type2 MedianH/GHarmonizado

HighMax(maximumofnationalEQR) 1.237 1.237 1.458 1.057 1.300 1.130 0.976

H/GBoundary+0.25H 0.975 0.975 1.144 0.992 1.114 1.019

H/GBoundary(foreachMS) 0.888 0.888 1.039 0.970 1.052 0.982

H/GBoundary-0.25H 0.836 0.836 0.976 0.910 0.976 0.921

H/GMedGIGMedian 0.976 0.976 0.976 0.976 0.976 0.976

H/Gquarter(+) 0.087 0.087 0.105 0.022 0.062 0.037

H/Gquarter(-) 0.052 0.052 0.063 0.060 0.076 0.061

Good/moderateMax 0.888 0.888 1.039 0.970 1.052 0.982 MedianG/MHarmonizado

G/M+0.25H 0.733 0.733 0.851 0.790 0.825 0.798 0.734

G/MBoundary(foreachMS) 0.681 0.681 0.788 0.730 0.750 0.737

G/MBoundary-0.25H 0.621 0.619 0.734 0.670 0.750 0.676

M/PMin 0.443 0.434 0.573 0.490 0.814 0.492

G/MMedGIGMedian 0.734 0.734 0.734 0.734 0.734 0.734

G/Mquarter(+) 0.052 0.052 0.063 0.060 0.076 0.061

G/Mquarter(-) 0.059 0.062 0.054 0.060 0.000 0.061

Statistic -0.25 -0.25 0.25 -0.07 0.25 0.02

Statistic -0.25 -0.25 0.25 -0.01 -0.25 0.01

PT-Type5

PT-Type6

SP2-Type4

IT-Type4

SL-Type3

CY-Type2

0.600

0.700

0.800

0.900

1.000

1.100

1.200

1.300

1.400RM5-originalboundaries


MedianH/GOriginal

PT-Type5PT-Type6

SP2-Type4

IT-Type4SL-Type3 CY-Type2

0.400

0.500

0.600

0.700

0.800

0.900

1.000

1.100

1.200 RM5-originalboundaries


MedianG/MOriginal

PT-Type5 PT-Type6

SP2-Type4

IT-Type4

SL-Type3

CY-Type2

0.600

0.700

0.800

0.900

1.000

1.100

1.200

1.300

1.400RM5-harmonizedboundaries


MedianH/GHarmonizado

PT-Type5 PT-Type6

SP2-Type4

IT-Type4

SL-Type3

CY-Type2

0.400

0.500

0.600

0.700

0.800

0.900

1.000

1.100

1.200RM5-harmonizedboundaries


MedianG/MHarmonizado

Do all national methods comply with these criteria ? (N)

If not, describe the adjustment process:

No. For several cases, the boundaries were too high or too low, compared to the common

median boundary. During the process the adjustments were made in both situations. The final

values presented above correspond to the adjusted by the existent deviations to the common

boundary (median of all MS boundaries for the same type).

9. IC results

Provide H/G and G/M boundary EQR values for the national methods for each

type in a table

National EQR Original National EQR Harmonized

Type H/G G/M H/G G/M

PT-Type 1 0.870 0.650 0.870 0.650

PT-Type 2 0.830 0.610 0.830 0.610

PT-Type 3 0.850 0.590 0.850 0.590

PT-Type 4 0.880 0.660 0.880 0.660

PT-Type 5 0.950 0.700 0.963 0.724

PT-Type 6 0.880 0.660 0.963 0.724

SP1-Type 1 0.780 0.590 0.780 0.590

SP1-Type 2 0.780 0.590 0.780 0.590

SP1-Type 3 0.810 0.610 0.810 0.610

SP2-Type 1 0.800 0.600 0.800 0.612

SP2-Type 2 0.740 0.550 0.740 0.632

SP2-Type 3 0.850 0.640 0.850 0.640

SP1-Type 4 1.019 0.931 1.019* 0.931*

SP2-Type 4 0.830 0.620 0.830 0.620

FR-Type 1 0.940 0.810 0.940 0.810

IT-Type 1 0.970 0.720 0.970 0.720

IT-Type 2 0.940 0.700 0.940 0.700

IT-Type 3 0.940 0.700 0.940 0.700

IT-Type 4 0.970 0.730 0.970 0.730

SL-Type 1 0.800 0.600 0.800 0.600

SL-Type 2 0.800 0.600 0.800 0.600

SL-Type 3 0.800 0.600 0.800 0.600

CY-Type 1 0.972 0.729 0.972 0.729

CY-Type 2 0.982 0.737 0.982 0.737

Note: Although the calculations showed in section 8 consider both the increase of low boundaries and the

decrease of high boundaries, the final results here only consider changes in the boundaries that were low (in

red). The original values of high boundaries were maintained.

* For the method SP1 and Type 4, the boundaries indicated here are those intercalibrated in phase 1 of IC

but not intercalibrated here (see 7.2)

Present how common intercalibration types and common boundaries will be

transformed into the national typologies/assessment systems (if applicable)

The results were translated from the common metric to the national EQRs through the

regression shown in 7.2. At the MS level, the harmonized values will be adapted to the

national typologies included in each IC type.

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

All goals for intercalibration work programme 2008-2011 dated from 24th September 2008,

version 3.2, were achieved, namely translation of IC results into national systems, refinement

of criteria for setting reference conditions between MS, intercalibration of new and updated

methods, intercalibration of most pressures. Seasonality appears to be of little influence.

However, large rivers were not intercalibrated.

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EUROPEAN COMMISSION DIRECTORATE … Research Centre/jrc...EUROPEAN COMMISSION DIRECTORATE GENERAL JRC ... macroinvertebrate expert), Sergi Sabater, Elisabet Tormes, ... Maria Rita