Introduction

The European Water Framework Directive (WFD) requires the national classifications of good ecological status to be harmonised through an intercalibration exercise. In this exercise, significant differences in status classification among Member States are harmonized by comparing and, if necessary, adjusting the good status boundaries of the national assessment methods.

Intercalibration is performed for rivers, lakes, coastal and transitional waters, focusing on selected types of water bodies (intercalibration types), anthropogenic pressures and Biological Quality Elements. Intercalibration exercises were carried out in Geographical Intercalibration Groups -larger geographical units including Member States with similar water body types -and followed the procedure described in the WFD Common Implementation Strategy Guidance document on the intercalibration process (European Commission, 2011).

In a first phase, the intercalibration exercise started in 2003 and extended until 2008.

The results from this exercise were agreed on by Member States and then published in a Commission Decision, consequently becoming legally binding (EC, 2008). A second intercalibration phase extended from 2009 to 2012, and the results from this exercise were agreed on by Member States and laid down in a new Commission Decision (EC, 2013) repealing the previous decision. Member States should apply the results of the intercalibration exercise to their national classification systems in order to set the boundaries between high and good status and between good and moderate status for all their national types.

Annex 1 to this Decision sets out the results of the intercalibration exercise for which intercalibration is successfully achieved, within the limits of what is technically feasible at this point in time. The Technical report on the Water Framework Directive intercalibration describes in detail how the intercalibration exercise has been carried out for the water categories and biological quality elements included in that Annex.

The Technical report is organized in volumes according to the water category (rivers, lakes, coastal and transitional waters), Biological Quality Element and Geographical Intercalibration group. This volume addresses the intercalibration of the Lake Alpine Phytoplankton ecological assessment methods.

Introduction

In the Alpine Lake Phytoplankton Geographical Intercalibration Group:  Four Member States (Austria, Germany, Italy and Slovenia) compared and harmonised their national lake phytoplankton assessment systems (France withdrew their method in the final stage of the Intercalibration);  All methods address eutrophication pressure and follow a similar assessment principle (including biomass metrics and trophic index based on indicator taxa);  Intercalibration "Option 3" was used -direct comparison of assessment methods using a common dataset via application of all assessment methods to all data available;  The comparability analysis show that methods give a closely similar assessment (in agreement to comparability criteria defined in the IC Guidance), so no boundary adjustment was needed;  The final results include EQRs of Austrian, German, Italian and Slovenian lake phytoplankton assessment systems for 2 common intercalibration lake types: LAL-3 and L-AL4.

Description of national assessment methods

In the Alpine Phytoplankton GIG, four countries participated in the intercalibration with finalised phytoplankton assessment methods (Table 2.1, for detailed descriptions see Annex A).

Table 2.1 Overview of the national phytoplankton assessment methods

MS Method Status AT Evaluation of the biological quality elements, Part B2phytoplankton

Finalized formally agreed national method DE PSI (Phyto-Seen-Index) -Bewertungsverfahren für Seen mittels Phytoplankton zur Umsetzung der EG-Wasserrahmenrichtlinie in Deutschland Finalized formally agreed national method IT Italian Phytoplankton Assessment Method (IPAM) Finalized formally agreed national method SI Metodologija vrednotenja ekološkega stanja jezer s fitoplanktonom v Sloveniji (Ecological status assessment system for lakes using phytoplankton in Slovenia)

Finalized formally agreed national method

Methods and required BQE parameters

All MS have developed full BQE methods (see Table 2.2).

Metric not considered Arithmetic mean of nEQRs

There are many questions regarding the use of blooms in the assessment of lakes using phytoplankton. It is still unclear:

 Whether only Cyanobacteria or also other algal taxa should be regarded;  How to deal with surface scums in routine sampling of the epilimnion or euphotic zone;  How to deal with blooms occurring in sheltered bays while the sampling point is situated in the centre of the lake etc.;  Besides, sampling frequency is most critical when blooms occur only for a short periodwhich is more interesting than persistent blooms in lakes, which will then probably be classified as moderate, poor or bad anyway.

At present it seems that blooms (significant peaks of blue-greens at the surface or within the whole epilimnion) do hardly occur in Alpine lakes under high and good status. As stated by Carvalho et al. (unpubl. WISER deliverable), blooms are rare at TP concentrations of less than 20-25 µg L -1 . The risk of missing a bloom is thus very high, causing a high uncertainty and stochasticity when using a bloom metric. Even under moderate status, many lakes do not have "persistent blooms during summer months" (cf Annex V of WFD). Figure 2.1 shows that an algal bloom is an unlikely phenomenon under high and good status in Alpine lakes. In order not to add a metric with high uncertainty and little relevance to the existing, well working assessment methods, the Alpine GIG has agreed not to include blooms in their classification systems. This approach may be revised as soon as positive experience with the use of the WISER blooms metric becomes available.

As stated by the representative of Germany, the maximum chlorophyll-a concentration as used as a metric in the German method cannot be considered as a bloom metric.

Sampling and data processing

All countries use similar sampling strategies / data processing techniques (Table 2.3).

Table 2.3 Overview of the sampling and data processing of the national phytoplankton assessment methods

MS

National reference conditions

All countries have set national reference conditions based on near-natural reference sites in combination with other approaches (Table 2.4).

National boundary setting

AT/SI and IT: Reference values and class boundaries of total biovolume BV and chlorophyll-a Chl-a were set using the selected population of reference sites. The median was defined as reference value, the 90%percentile as H/G boundaryboth supported by expert judgment.

An alternative approach for setting the class boundaries of Chl-a (regression with total biovolume, as performed in phase 1 of the IC exercise) did not give reliable results and was dismissed.

The other class boundaries of BV and Chl-a were derived using equidistant class widths on a log-scale (as described in phase 1).

AT: The class boundaries for the Brettum index BI were derived in the same way as for BV and Chl-a, supported by expert judgment.

IT: The class boundaries for the Italian PTI were derived using the following criteria: For H/G 10 th percentile of reference sites. G/M boundaries calculated for those lakes classified as good by Brettum index. The distance between H/G -G/M was used to define the position of the other boundaries.

GE:

The class boundaries for the German metrics were set using a combination of methods: Reference values and high-good-boundary e.g. by modelling, following historical data, reference site data (international data set). The ongoing boundaries were set using regression with TP or the LAWA index and were harmonized with the LAWA-Index classes and intercalibration values. BV-boundaries are derived by regression to the Chl-a-boundaries.

Pressures-response relationships

All MS assessment methods address eutrophication pressure (

Results of WFD compliance checking

All MS methods are considered WFD compliant (Table 3.1). FR will submit an updated version of its assessment method later.

Results IC Feasibility checking

Typology

Two common intercalibration types were define din the Alpine GIG -L-AL3 and L-AL4 (Table 4.1). There are several lakes in most MS of the Alpine GIG which do not fall into the range of criteria of the two IC lake types. As decided already in phase 1 of the IC process, these lakes were excluded from the intercalibration, since the criteria for performing the IC (at least 2 lakes in 2 MS each) were not fulfilled. During phase 2, the Alpine GIG could extend the data set, but it was still not possible or justified to create new IC types or to define clear sub-types of L-AL3 or L-AL4 using additional criteria such as geology or biogeography.

Intercalibration is feasible in terms of typology (Table 4.2.).

Pressures

Intercalibration is feasible in terms of pressures addressed by the methods: all methods address eutrophication

Assessment concept

Intercalibration is feasible in terms of assessment concepts as all MS follow the same approach: a combination of a quantitative metric (chlorophyll-a and/or biovolume) and a trophic index.

Collection of IC dataset

Huge dataset was collected within the Alpine Phytoplankton GIG (Table 5.1. Only lakeyears with at least 4 sampling dates per year, where the dates are more or less evenly distributed over the year or the vegetation season, are taking into account (for description of data acceptance criteria, see Table 5.2). Some shallow (Zmean <3 m) and small (<50 ha) lakes are included under L-AL4. This is no criteria for the data selection, but an outcome of the IC exercise. However, considering the range of TP concentration (0.002-0.2 mg L-1), it can be assumed that the data cover all quality classes.

Common benchmarking

A tiered approach to define reference sites of Alpine lakes has been prepared by the Invertebrates and Phytoplankton group of the Alpine GIG and proposed to the Macrophytes and Fish groups (see Annex B).

Reference conditions

Reference sites for phytoplankton total biovolume:  L-AL3: 71 lake-years from 24 sampling sites (AT, DE, SI);  L-AL4: 59 lake-years from 14 sampling sites (AT, DE).

Reference sites for phytoplankton Chlorophyll-a:

 L-AL3: 29 lake-years from 15 sampling sites (AT, DE, SI);  L-AL4: 29 lake-years from 13 sampling sites (AT, DE).

The number is considered sufficient to make a statistically reliable estimate, with support from modelling and expert judgment.

Pre-selected 'reference condition sites' for L-AL3 lakes (for some lake-years chl-a was missing or one of the national method could not be applied. Only lake-years underlined were included in the final comparability checking): Achensee 2008, Alpsee bei Füssen 2001, 2004, Altausseer See 2002, Attersee 1997-1998[START_REF] Wolfram | Distrubution pattern of benthic invertebrate communities in Traunsee (Austria) in relation to industrial tailings and trophy[END_REF], 2003-2004, 2007-2009, Bohinjsko jezero 2005-2007, Eibsee 2005, Fuschlsee 1997[START_REF] Lawa | Gewässerbewertung Stehende Gewässer. Vorläufige Richtlinie für eine Erstbewertung von natürlichen entstandenen Seen nach trophischen Kriterien[END_REF], 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Grundlsee 2002, Heiterwanger See 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Königssee 2000[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Millstätter See 1932-1937, Obersee 2000, 2007, Ossiacher See 1934-1938, Plansee 2008, Starnberger See 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Sylvensteinsee 2007, Traunsee 2007, 2009, Walchensee 1995[START_REF] Lang | Oligochaetes versus chironomids as indicators of trophic state in two Swiss lakes recovering from eutrophication[END_REF][START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Weißensee 1933-1935, 1987[START_REF] Brettum | Algen als Indikatoren für die Gewässerqualität in norwegischen Binnenseen[END_REF], 1993[START_REF] Lang | Oligochaetes versus chironomids as indicators of trophic state in two Swiss lakes recovering from eutrophication[END_REF], 2003[START_REF] Wolfram | Alpine GIG: Boundary setting in Alpine lakes. A. Phytoplankton[END_REF], Wolfgangsee/Gilgen 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Wolfgangsee/St. Wolfgang 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Wörthersee 1931-1938, Zeller See 2000[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF].

Pre-selected 'reference condition sites ' for L-AL4 lakes: Faaker See 1937, 1987, 1990-2003, 2007, Großer Ostersee 2004[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Irrsee 2002-2009, Keutschacher See 2000-2003[START_REF] Wolfram | Alpine GIG: Boundary setting in Alpine lakes. A. Phytoplankton[END_REF], 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Kirchsee 2001, Lago di Ganna 2007, Lago di Segrino 2008, Längsee 1999-2000[START_REF] Wolfram | Distrubution pattern of benthic invertebrate communities in Traunsee (Austria) in relation to industrial tailings and trophy[END_REF], Lustsee 1996-1998[START_REF] Lawa | Gewässerbewertung Stehende Gewässer. Vorläufige Richtlinie für eine Erstbewertung von natürlichen entstandenen Seen nach trophischen Kriterien[END_REF], 2000, Mattsee 1997[START_REF] Lawa | Gewässerbewertung Stehende Gewässer. Vorläufige Richtlinie für eine Erstbewertung von natürlichen entstandenen Seen nach trophischen Kriterien[END_REF], 2007[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF], Pressegger See 2002, Staffelsee 2007, Weissensee (GE) 1997-1998, 2001, Wörthsee 1993-1994[START_REF] Wolfram | Distrubution pattern of benthic invertebrate communities in Traunsee (Austria) in relation to industrial tailings and trophy[END_REF], 2005[START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF].

Screening of the biological data:

 Candidate reference sites were checked for possible impacts from hydromorphological pressures (water level fluctuations), but no significant deviations were found (cf the German report on HMWB & AWB lakes, [START_REF] Wolfram | Reference conditions and WFD compliant class boundaries for phytoplankton biomass and chlorophyll-a in Alpine lakes[END_REF]);  Lakes that have undergone a eutrophicationre-oligotrophication process, but

have not yet reached stable trophic conditions were excluded, even if they already met the reference criteria (e.g. TP already ≤8 µg L -1 , but still decreasing). This was done in order to exclude lakes where the phytoplankton might react with some delay to the improvement;  One lake, which has been affected by mining activities, was excluded from the candidate list of reference sites for safety reasons, although no impact on phytoplankton could be detected;  Very small lakes outside the typology criteria were excluded.

Setting reference conditions (summary statistics used):

1. The arithmetic mean of total biovolume and chlorophyll-a from different years was calculated for each reference site in order to give equal weight to each site; 2. Both parameters, the median of all reference sites was calculated and rounded to 1 digit; 3. Where the reference values for L-AL3 and L-AL4 only slightly deviated from the values already derived in phase 1 of the IC exercise, the old values were accepted also for IC phase 2.

Benchmark standardisation

Benchmark standardization serves to homogenize the EQR results of common datasets where needed, minimising typological and methodological differences between the Member states which may otherwise influence the comparability of their classifications.

Biogeographical differences within the Alpine GIG are considered negligible. Differences in type-specific reference conditions could theoretically occur between northern and southern Alps, but there is no confounding indication in the scientific literature nor was it possible to describe sub-types within the Alpine GIG based on biogeographical aspects. According to the internal guidance benchmark standardization is not needed when there are no significant subtypological differences between Member states. This is the case in the Alpine GIG. Some MS use, however, a kind of fine-tuning of reference values via ranges, in order to cope for variability within the two types L-AL3 and L-AL4, which cannot be used to define separate IC types. The ranges take into account altitude, depth, mixing type and other characteristics (cf [START_REF] Wolfram | Reference conditions and WFD compliant class boundaries for phytoplankton biomass and chlorophyll-a in Alpine lakes[END_REF] and are included in the calculation of the EQR and nEQR.

As required by the JRC guidance mentioned above, we explored if there might exist subtypes in the common type between or within countries. This was done by comparing if the EQR values of a given national method for the benchmark sites (in our case: reference sites) do not differ between Member states.

The following box-whisker-plots (Figure 6.1) show the nEQR values of reference lakeyears from L-AL3 and L-AL4 in different MS as calculated from the three methods available. There is no clear trend of deviation in the boxplots.

In consequence, the checking of comparability was carried out without the standardization step, but starts with the normalization. This was done by manually setting the offset to zero (cells B34:E37 in sheet calc in <IC_Opt3_sub.xlsx>).

Figure

L-AL4 lakes

For the whole GIG, option 3a is followed, since data acquisition was very similar in all MS of the Alpine GIG. The arithmetic mean of the normalized EQR values was used as pseudo-common metric (PCM). No additional common metric was selected.

Results of the regression comparison (National EQRs vs PCM)

All methods have significant correlations with common metrics (Table 7.1):

 The Pearson correlation coefficient ranges from 0.928 to 0.959 in L-AL3 and from 0.944 to 0.955 in L-AL4. The requirement that r ≥ 0.5 is fulfilled in both IC types.  The ratio min R 2 : max R 2 in the regression models between the national methods and the PCM is 0.94 for L-AL3 lakes and 0.97 for L-AL4 lakes. The requirement of a ratio >0.5 is fulfilled in both IC types.

Boundary comparison and harmonisation

All national methods comply with comparability criteria (Table 7.2, Figure 7.1):

 The boundary bias in L-AL3 type ranges between -0.12 and +0.18 for the H/G boundary and -0.14 and +0.18 for the G/M boundary;  In L-AL4 type, the boundary bias ranges between -0.11 and 0.09 for the H/G boundary and -0.24 and +0.24 for the G/M boundary. The boundary bias never exceeds -0.25, which would indicate that a method was too relaxed;  Absolute class differences range from 0.10 to 0.20 in L-AL3 and from 0.19 to 0.22 in L-AL4. They are clearly less than 1 class for all methods.

Correspondence between common intercalibration types and national typologies/assessment systems

In some MS, the national types can be directly related to common IC types (e.g. GE type 4 = IC type L-AL3, AT type B2 = IC type L-AL4). If ranges are used for fine-tuning of typology, the criteria as described in [START_REF] Wolfram | Reference conditions and WFD compliant class boundaries for phytoplankton biomass and chlorophyll-a in Alpine lakes[END_REF] can be used. However, all classification results will be expressed as nEQR, having the same boundaries for all national and IC types: 0.8 for H/G, 0.6 for G/M.

Gaps of the current Intercalibration

 All members of the Alpine GIG recognize standardization of methods as an important issue, although there is no common and agreed view in various methodological questions. Critical issues are: sampling depth and sampling frequency, and the identification of centric diatoms.  The existing CEN standard of Utermöhl counting is overloaded with statistics and thus not practical. It should be revised in near future!  More effort should be undertaken to quantify measurement of uncertainty (sampling, frequency, counting, ...), although the Alpine GIG members are aware that the quantification of analytical results in chemistry (cf EN 17025) and biology are different issues and cannot be performed with the same level of precision.  France has to submit an agreed national assessment method

Description of biological communities and changes across pressure gradient

Biological communities at reference sites

In general, the algal community under reference conditions is comparatively poor in taxa richness. A characteristic feature in the phytoplankton community of many deep Alpine lakes (L-AL3) is a strong dominance of Cyclotella species. This fact is proved by monitoring data from reference sites (also historical data), but also from palaeoreconstruction. Typical accompanying taxa besides Cyclotella are Ceratium hirundinella, Asterionella formosa, various chrysoflagellates, cryptoflagellates and Chroococcales. Some of these taxa may also occur at higher trophic levels, but form a significant part of the community at oligotrophic conditions.

The annual mean biomass under reference conditions is within the same range as it was prior to major urbanisation, industrialisation and agriculture, which can be proved by historical data available from the 1930s. Planktonic blooms do not occur at high status.

In moderately deep lakes (IC type L-AL4), variability and biovolume is slightly higher than in deep lakes (reference conditions = oligo-mesotrophic). The trophic gradient spanned by L-AL4 lakes is however higher than in deep lakes, which makes this group more heterogeneous than the L-AL3 lake group. At the lower trophic end of L-AL4 lakes, biovolume and taxonomic composition is similar to the situation in deep lakes. At the upper trophic end, species richness may be significantly higher than in oligotrophic lakes. Also the proportion of nutrient tolerant taxa such as Fragilaria crotonensis, Stephanodiscus spp., Tabellaria fenestrata or various filamentous blue-green algae (such as Planktothrix rubescens) may be slightly higher than in typical high status lakes of type L-AL3.

Like in L-AL3 lakes, the annual mean biomass under reference conditions in L-AL4 lakes is within the same range as it was prior to major urbanisation, industrialisation and agriculture, which can be proved by historical data available from the 1930s. Planktonic blooms do not occur at high status, but potentially bloom forming taxa such as Planktothrix rubescens may occur in low density (also proven by historical data).

Biological changes across pressure gradient

In most Alpine lakes, the total biovolume of phytoplankton is directly related with nutrient supply. An increase of total phosphorus concentration (which is the limiting nutrient in most cases) will lead to an increase of biomass. The significant positive correlation of TP and BV and Chl-a, resp., has been proved already in phase 1 of the IC exercise.

Each of the four trophic indices used in the Alpine GIG (Brettum index, PTI, PTSI, MCS) is based on list of indicator taxa with different trophic optima. A change in trophic statethat means, a shift along the pressure gradientwill thus cause a change in the trophic index. Like for BV and Chl-a, the significant correlation between TP and the trophic indices was demonstrated already in phase 1 for the first three indices (Brettum Index, PTI and PTSI). As an example, the relation between TP and the Italian PTI is given below (Figure 8.1).

Figure 8.1. Relationship between total phosphorus concentration (TP) and normalised EQR (nEQR) of Italian phytoplankton trophic index (PTIot).

Comparison with WFD Annex V normative definitions

Since L-AL3 (deep) and L-AL4 (moderately deepshallow) just represent two expressions along a continuum of lakes with decreasing depth, the metrics used in the national methods are expected to react in similar way in both lake types. They will thus be discussed together.

Biomass (BV, Chl-a):

NormDef High: The average phytoplankton biomass is consistent with the type-specific physico-chemical conditions and is not such as to significantly alter the type-specific transparency conditions.

NormDef Good: There are slight changes in the composition and abundance of planktonic taxa compared to the type-specific communities. Such changes do not indicate any accelerated growth of algae resulting in undesirable disturbance to the balance of organisms present in the water body or to the physico-chemical quality of the water or sediment.

NormDef Moderate: Biomass is moderately disturbed and may be such as to produce a significant undesirable disturbance in the condition of other biological quality elements and the physico-chemical quality of the water or sediment.

EQR for H/G is 0.60-0.64 (BV) and 0.70-0.75 (Chl-a), EQR for G/M is 0.25-0.26 (BV) and 0.40-0.41 (Chl-a). Hence, phytoplankton biomass under good status is about 1.5-4 times the biomass under reference conditions. This is considered as 'slight' and will not result in disturbance to the balance of organisms present in the water body or to the physico-chemical quality of the water or sediment. Annual mean Secchi depth at good status is 3 to 10.5 m (median 5.7 m) in L-AL4 and 1.3-5 m (median 3.2 m) in L-AL3 lakes (Figure 8.2). In addition to organic turbidity from phytoplankton, biogenic calcification or inorganic turbidity from inflows can reduce Secchi depth.

Taxonomic composition (trophic indices):

NormDef High: The taxonomic composition and abundance of phytoplankton correspond totally or nearly totally to undisturbed conditions.

NormDef Good: There are slight changes in the composition and abundance of planktonic taxa compared to the type-specific communities. Such changes do not indicate any accelerated growth of algae resulting in undesirable disturbance to the balance of organisms present in the water body or to the physico-chemical quality of the water or sediment.

NormDef Moderate: The composition and abundance of planktonic taxa differ moderately from the type-specific communities.

Taxa dominant at high status still play a significant role at good status, but their relative proportion of total biovolume rapidly diminishes under moderate status. This is reflected by the three trophic indices, which are calculated from taxon-specific relative proportions of total biovolume. Nutrient tolerant taxa such as Fragilaria crotonensis, Stephanodiscus spp., Tabellaria fenestrata or various filamentous blue-green algae (such as Planktothrix rubescens) increase in relative proportion.

Blooms:

NormDef High: Planktonic blooms occur at a frequency and intensity which is consistent with the type specific physicochemical conditions.

NormDef Good: A slight increase in the frequency and intensity of the type specific planktonic blooms may occur.

NormDef Moderate: A moderate increase in the frequency and intensity of planktonic blooms may occur. Persistent blooms may occur during summer months.

There are many questions regarding the use of blooms in the assessment of lakes using phytoplankton. It is still unclear whether only Cyanobacteria or also other algal taxa should be regarded, how to deal with surface scums in routine sampling of the epilimnion or euphotic zone, how to deal with blooms occurring in sheltered bays while the sampling point is situated in the centre of the lake etc. Besides, sampling frequency is most critical when blooms occur only for a short periodwhich is more interesting than persistent blooms in lakes, which will then probably be classified as moderate, poor or bad anyway.

At present it seems that blooms (significant peaks of blue-greens at the surface or within the whole epilimnion) do hardly occur in Alpine lakes under high and good status. As stated by Carvalho et al. (unpubl. WISER deliverable), blooms are rare at TP concentrations of less than 20-25 µg L -1 . The risk of missing a bloom is thus very high, causing a high uncertainty and stochasticity when using a bloom metric. Even under moderate status, many lakes do not have "persistent blooms during summer months" (cf Annex V of WFD).

In order not to add a metric with high uncertainty and little relevance to the existing, well working assessment methods, the Alpine GIG has agreed not to include blooms in their classification systems. This approach may be revised as soon as positive experience with the use of the WISER blooms metric becomes available.

(As stated by the representative of GE, the maximum chlorophyll-a concentration as used as a metric in the GE method cannot be considered as a blooms metric.)

Description of IC type-specific biological communities representing the "borderline" conditions between good and moderate ecological status

Biomass: Algal biomass (BV, Chl-a) is about 2.5-4 times the values that can be expected under reference conditions (EQR = 0.25-0.40). Subtypological variability and hydromorphological differences (mixing type, very deep/large lakes) are not reflected in this ratio, but in differences of the absolute reference values for BV and Chl-a.

Taxonomic composition: Taxa dominating under reference conditions are still present at G/M, but clearly differ in their relative proportion of total biovolume. This can be demonstrated by using the Brettum scores for selected trophic classes (Figure 8.3, example only for L-AL3). At the "borderline" G/M, which is defined here by using the Austrian method, the scores for the "best" trophic class (TP <5 µg L -1 ) are <1 in most cases, while the scores for the "lowest" class (TP >60 µg L -1 ) increase. The scores of the third trophic class (8-15 µg L -1 ) have their optimum slightly above the G/M boundary. This is in line with the normative definitions, which require moderate difference in the composition and abundance of planktonic taxa from the type-specific communities. An assessment of the ecological status of lakes using phytoplankton is mainly a classification of their nutrient and productivity levels. The assessment method presented in this manual was developed for Austrian lakes with a surface area >50 ha. The assessment method can be applied for lakes <50 ha, but in every single case it must be determined whether the same trophic reference states developed for larger lakes can be reasonably applied to smaller ones. This is especially true for small lakes in the lowlands.

If necessary, the reference state has to be refined.

The majority of Austrian lakes >50 ha lie in the Alpine and pre-Alpine region. In addition to these lakes, there are a few others in Eastern Austria that also have to be considered: the special lake type represented by the Old Danube and Neusiedler See, and certain large salt (soda) pans in the so-called Seewinkel. The general description of sampling and sample processing, as provided in this manual, is valid also for these lakes; however, an official WFD-compliant assessment method is thus far not available. The assessment methods recently developed for the Neusiedler See and Old Danube still need to be validated and therefore are not considered in this manual.

Principles of the Method

1. According to this manual, assessment of the ecological status of a lake is based on several phytoplankton samples collected from the epilimnion or the euphotic zone at different sampling dates. The chlorophyll-a concentration is determined from an additional sample taken from the same water layer and following the same technique (as a mixed or integrated sample) as used for the phytoplankton sample. 2. The phytoplankton samples are analysed in the laboratory with respect to taxonomy (qualitative analysis), with the abundance and total biovolume of the planktonic algae determined from a subsample observed using an inverted microscope (quantitative analysis after UTERMÖHL 1958, DIN EN 15204/2006, CEN TC 230/WG 2/TG 3/2007). Taxonomic analyses are carried out at the species level, as far as possible with reasonable effort. If the relative proportion of centric diatoms exceeds 10% of the total biovolume per sample, an additional detailed analysis of diatoms is required in order to enhance the degree of confidence in the taxonomic analyses (burn mount, after EN 14407:2004).

Qualitative sampling with a plankton-net after DIN EN 15204/2006 also should be carried out. In the monitoring programme of Austrian lakes, a (formaldehydepreserved) qualitative sample should be taken, storing it for later analysis. The qualitative analysis can be omitted only if the species composition is very well known and the ecological status can be assessed with a high degree of confidence solely on the basis of the quantitative analysis. 3. For the analysis of chlorophyll-a, the respective standards should be consulted.

In principle, chlorophyll-a can be determined spectrophotometrically (reference standard DIN 38412 part 16) or using HPLC. See also GZÜV (BGBl. II 479 from 14 Dec 2006).

4. For each year, the mean chlorophyll-a concentration and, for each taxon, the mean biovolume are determined as the arithmetic means of four or more sampling dates. The mean total biovolume of a lake is calculated as the sum of the mean biovolumes of the single taxa. The relative proportions of the mean biovolumes of these single taxa and the taxon-specific trophic scores are used to calculate the Brettum index.

The final classification of the lake using phytoplankton is based on the mean chlorophyll-a concentration, the mean total biovolume and the Brettum index.

The full manual is available on the homepage of the Federal Ministry of Agriculture and Forestry, Environment and Water Management (Ministry of Life) under www.lebensministerium.at/section "Wasser/Wasserrahmenrichtlinie".

Sampling Frequency and Sampling Dates

Sampling Frequency

The assessment of phytoplankton is based on the annual mean of data acquired from several sampling dates. For large Austrian lakes, at least four sampling dates per year are required to reliably calculate the mean. A higher sampling frequency will improve the confidence in the calculation and avoid biases of the annual means due to outliers. The assessment is carried out on the basis of a running average of three subsequent years.

Selection of the Sampling Date

The minimum requirement for the classification is sampling at four different, limnologically important dates: spring circulation, beginning of the summer stagnation, peak of the summer stagnation, beginning of the autumn circulation (often at the end of autumn).

Selection of the Sampling Site

The morphology of the lake basin of most standing waters in Austria is relatively simple. Hence, most lakes represent a water body as defined by the WFD and are sampled at one sampling site only. Examples of lakes with a more complex basin morphology are Wolfgangsee in Salzburg and the Old Danube in Vienna, both of which are sampled at two sites in accordance with the GZÜV. Several sampling sites are defined for Lake Constance and Neusiedler See.

In general, sampling is carried out from a boat positioned above the deepest point of the lake (or the lake basin). The four sampling sites of Neusiedler See are spread along an imaginary line from north to south (see Annex 9 of the GZÜV).

Sampling Depth

Quantitative samples of phytoplankton (total biovolume and chlorophyll-a) are taken from the epilimnion or, as in some neighbouring countries, from the euphotic zone. To ensure data harmonisation, it is recommended to sample the epilimnion according to the monitoring programmes under the GZÜV. If the euphotic zone is smaller than the epilimnion, the latter must be sampled.

Calculations and Assessment of the Ecological Status

General

The assessment of the ecological status of a lake is a classification of its nutrient and productivity levels. The parameters used in the assessment are: the chlorophyll-a concentration (annual mean), the total biovolume (annual mean) and the Brettum index (calculated from the taxa list and the corresponding annual mean biovolumes). Derivation of the taxon-specific trophic scores, calculation of the Brettum index, calculation of the EQR and normalized EQR values as well as the final assessment are presented in the following sections.

Brettum Index: Basis of the Calculation

In its general outline, calculation of the Brettum index is comparable to that of the saprobic index since it is based on taxon-specific trophic scores, currently for 80 taxa (species and genera). Following the approach of BRETTUM (1989) as modified by [START_REF] Dokulil | Typenspezifische Referenzbedin-gungen für die integrierende Bewertung des ökologischen Zustandes stehender Gewässer Österreichs gemäß der EU-Wasserrahmenrichtlinie. Modul 1: Die Bewertung der Phyto-planktonstruktur nach dem Brettum-Index[END_REF] and WOLFRAM et al. ( 2007), the trophic scores are calculated on the basis of occurrence and on the relative proportion of biovolume within six total phosphorus (TP) concentration levels.

Depending on the occurrence of the phytoplankton taxa within each of the six trophic ranges, the trophic scores are calculated as follows. The first three steps follow the approach described by [START_REF] Dokulil | Typenspezifische Referenzbedin-gungen für die integrierende Bewertung des ökologischen Zustandes stehender Gewässer Österreichs gemäß der EU-Wasserrahmenrichtlinie. Modul 1: Die Bewertung der Phyto-planktonstruktur nach dem Brettum-Index[END_REF].

1. The probability pij to find a taxon i within the trophic range j at a certain relative proportion of the total biovolume of the phytoplankton is calculated as:

i j ij ij b N n p  (2) nij
Number of findings of a taxon i within the trophic range j (presence/absence)

Nj

Total number of all samples within the trophic range j bi Mean relative proportion of the taxon i of the total phytoplankton biovolume within the trophic range j ("dominance") and where j ij N n is a measure of the occurrence of a taxon 2. After the probability pij for each trophic range has been calculated, the TP range with the highest relative proportion of biovolume is given the index value xi = 100.

The index values of the other TP ranges are calculated relative to it, in order to numerically describe the distribution of the taxon along the TP gradient. The more a taxon is confined to one or a few TP ranges, the higher its indicator value.

3. Based on the index values xij for all indicator taxa and on their biovolumes vi (as annual means) a total index Ij is calculated for each of the six trophic level as follows:

     n i i n i ij i j v x v I 1 1 (3)
The trophic assessment now results in six indices Ij. Brettum approach, DOKULIL et al. (2005) andWOLFRAM et al. (2007) did not use a maximum value of 100 but instead distributed 10 points along the trophic gradient with its six different ranges, weighted by the probabilities pij, (analogous to the saprobic index in MOOG 1995). This leads to a higher weight of stenoecious species (refined to a few TP ranges) and to the reduced weight of indifferent species (similar probability along a wider TP gradient).

In their modification of the original

The following example illustrate this step, but also show the database used, which comprises data from lakes in Austria, Slovenia, Italy, Germany and France. 15-30 µg L -1 19 61 31% 0,01% 0,4 0 75perc. 0,011 mg L -1 30-60 µg L -1 8,0 11 13% 0,01% 0,1 0 The values of the Brettum index range between 1 (very nutrient-poor) and 6 (nutrientrich).

max 0,100 mg L -1 >60 µg L -1 1 1 3% 0,01% 0

Note:

The extension and re-calculation of the taxon-specific trophic scores made it necessary to recalculate also the reference values and class boundaries for the Brettum index. Consequently, the index values calculated from the new taxa list in this manual cannot be compared with those calculated following the previous version of the manual. However, the results can be compared at the level of the normalized EQR values.

Taxon-Specific Trophic Scores The calculation described above was carried out for a large number of phytoplankton taxa (from species to class level). The finally selected indicator taxa are listed in Table A.1. The selection was done during the intercalibration process on the basis of the dominance and occurrence of the taxa in the whole Alpine region (with application of the method potentially in other countries as well) and after plausibility checking of the distribution of the single scores xij. 6

1 1 1 0 R0191 Diatoma vulgaris 5 2 1 1 0 R1697 Peridinium pusillum 0 9 1 0 0 R1066 Dinobryon bavaricum 3 3 2 0 0 R1438 Chroococcus limneticus 4 2 2 1 0 R1660 Gymnodinium uberrimum 1 6 2 R0442 Tabellaria flocculosa 1 4 5 0 0 R2174 Ulnaria delicatissima var. angustissima 2 3 3 0 0 R1654 Gymnodinium sp. 1 5 2 1 0 R1691 Peridinium inconspicuum 1 4 3 0 0 R1069 Dinobryon crenulatum 2 2 3 1 0 R1443 Chroococcus minutus 1 3 4 1 0 R0033 Aulacoseira subarctica 0 1 8 0 0 R1209 Cosmarium depressum 2 2 3 1 1 R1704 Peridinium willei 1 4 2 1 1 R0440 Tabellaria fenestrata 1 1 4 0 0 R1642 Glenodinium sp. 0 2 5 0 0 R1151 Uroglena sp. 0 3 3 1 0 R0606 Coenococcus planctonicus 0 1 5 0 0 R1413 Aphanocapsa delicatissima 0 3 3 2 0 R1617 Planktothrix rubescens 1 1 3 1 0 R0582 Didymocystis sp. 0 1 4 1 0 R1510 Snowella lacustris 0 1 4 1 0 R1549 Anabaena spiroides 0 1 6 1 1 R1282 Staurastrum chaetoceras 0 0 3 0 0 R2549 Urosolenia longiseta 0 1 3 3 0 R2556 Crucigeniella irregularis 0 0 4 2 0 R0025 Aulacoseira islandica 0 1 3 2 1 R0083 Stephanodiscus neoastraea 1 2 3 0 R0533 Coenochloris fottii 0 1 3 2 1 R1074 Dinobryon divergens var. schauinslandii 0 0 1 0 0 R2503 Achnanthidium catenatum 0 0 1 1 0 R1081 Dinobryon sertularia 0 1 1 3 0 R1096 Mallomonas acaroides 0 1 2 2 1 R1342 Sphaerozosma sp. 0 0 1 1 0 R1687 Peridinium cinctum 0 1 2 2 1 R0649 Lagerheimia genevensis 0 0 3 4 0 R1303 Staurastrum pingue 0 0 2 3 0 R1375 Chroomonas sp. 0 1 2 5 0 R0048 Cyclotella ocellata 0 1 1 3 1 R0848 Tetraedron minimum 0 1 1 3 1 R0736 Pseudosphaerocystis lacustris 0 0 2 2 1 R1414 Aphanocapsa elachista 0 1 2 4 1

Code Taxon

Trophic range (as TP in µg L-1) ≤5 5-8 8-15 15-30 30-60 >60 R0571 Dictyosphaerium pulchellum

0 0 1 5 4 R1097 Mallomonas akrokomos 0 0 2 4 3 R2169 Staurosira construens 0 0 2 2 6 R1100 Mallomonas caudata 0 0 1 4 5 R1427 Aphanothece clathrata 0 0 1 4 5 R1776 Trachelomonas volvocina 0 0 1 4 5 R2520 Fragilaria capucina ssp. rumpens 0 0 2 3 3 R0555 Crucigeniella rectangularis 0 0 1 5 2 R0690 Nephrocytium agardhianum 0 0 0 5 5 R0782 Scenedesmus ellipticus 0 0 1 5 2 R0935 Chlamydomonas globosa 0 0 1 3 6 R0051 Cyclotella radiosa 0 0 1 3 5 R0682 Monoraphidium sp. 0 0 1 2 7 R0971 Pandorina morum 0 0 2 2 4 R1377 Cryptomonas curvata 0 0 1 3 5 R1536 Anabaena flos-aquae 0 1 1 2 3 R1620 Pseudanabaena catenata 0 1 1 2 3 R1205 Cosmarium bioculatum 0 0 1 1 8 R1506 Rhabdogloea sp. 0 0 1 1 8 R0490 Ankyra lanceolata 0 0 1 3 4 R0762 Scenedesmus armatus 0 0 1 3 4 R0975 Phacotus lenticularis 0 0 1 3 4 R1818 Chrysochromulina parva 0 0 1 3 4 R1004 Mougeotia thylespora 3 7 R0184 Diatoma ehrenbergii 0 0 0 3 7 R1141 Synura sp. 0 0 1 3 3 R0697 Oocystis lacustris 0 0 1 2 5 R0743 Quadrigula lacustris 0 0 1 1 7 R1288 Staurastrum gracile 0 0 0 3 6 R1487 Microcystis flos-aquae 0 1 1 1 3 R0701 Oocystis parva 0 0 1 1 6 R0760 Scenedesmus obtusus 0 0 0 1 9 R0966 Gonium pectorale 0 0 0 1 9 R0996 Tetraselmis cordiformis 0 0 0 2 7 R0998 Volvox aureus 0 0 0 1 9 R1181 Closterium acutum var. variabile 0 0 0 2 7 R1300 Staurastrum paradoxum 0 0 0 2 7 R1519 Synechocystis aquatilis 0 0 0 2 7 R1560 Aphanizomenon gracile 0 0 1 2 4 R1613 Planktothrix agardhii 0 0 1 3 2 R0082 Stephanodiscus minutulus 0 0 0 3 4 R0489 Ankyra judayi 0 0 0 1 8 R0633 Kirchneriella sp. 0 0 0 2 6 R0654 Lagerheimia subsalsa 0 0 0 1 8

Code Taxon

Trophic range (as TP in µg L-1) ≤5 5-8 8-15 15-30 30-60 >60 R0923 Carteria sp.

0 0 1 1 5 R1095 Erkenia subaequiciliata 0 0 1 2 3 R1386 Cryptomonas ovata 0 0 1 2 3 R1199 Closterium pronum 0 0 0 1 8 R1283 Staurastrum cingulum 0 0 0 1 8 R1621 Pseudanabaena limnetica 0 0 0 3 4 R0189 Diatoma tenuis 0 0 1 1 4 R0529 Coelastrum pseudomicroporum 0 0 0 1 7 R0530 Coelastrum reticulatum 0 0 1 2 2 R1726 Euglena sp. 0 0 1 2 2 R0993 Sphaerocystis schroeteri 0 0 0 2 5 R1191 Closterium limneticum 0 0 0 1 7 R1525 Woronichinia naegeliana 0 0 0 3 3 R0891 Gloeocystis sp. 0 0 0 1 6 R0660 Micractinium pusillum 0 0 0 1 6 R0820 Schroederia setigera 0 0 0 1 6 R1482 Microcystis aeruginosa 0 0 1 1 3 R0016 Acanthoceras zachariasii 0 0 0 2 3 R0024 Aulacoseira granulata var. angustissima 0 0 0 2 3 R0343 Nitzschia acicularis 0 0 1 1 2 R0527 Coelastrum microporum 0 0 1 1 2 R1178 Closterium acutum 0 0 1 1 2 R0704 Oocystis solitaria 0 0 0 2 3 R1003 Mougeotia sp. 0 0 0 1 5 R0806 Scenedesmus quadricauda 0 0 0 1 4 R0940 Chlamydomonas reinhardtii 0 0 0 1 4 R0047 Cyclotella meneghiniana 0 0 0 1 4 R0963 Eudorina elegans 0 0 0 2 2 R1176 Closterium aciculare 0 0 0 0 6 R1311 Staurastrum tetracerum 0 0 0 0 6 R1153 Pseudopedinella erkensis 0 0 0 2 2 R0023 Aulacoseira granulata 0 0 0 1 3 R0506 Chlorococcum sp. 0 0 0 0 5 R0698 Oocystis marssonii 0 0 0 1 3 R1518 Synechococcus sp. 0 0 0 0 5 R1558 Aphanizomenon flos-aquae 0 0 0 1 3 R0713 Pediastrum boryanum 0 0 0 0 4 R0722 Pediastrum simplex 0 0 0 1 2 R0725 Pediastrum tetras 0 0 0 1 2 R0754 Scenedesmus acuminatus 0 0 0 0 4 R1499 Microcystis wesenbergii 0 0 0 1 2 R1582 Limnothrix redekei 0 0 0 1 2 R0488 Ankyra ancora 0 0 0 1 1 R0523 Coelastrum astroideum 0 0 0 0 3

Code Taxon

Trophic range (as TP in µg L-1) ≤5 5-8 8-15 15-30 30-60 >60 R0616 Golenkinia radiata Reference Conditions and Class Boundaries

0 0 0 1 8 R0716 Pediastrum duplex 0 0 0 3 7 R0777 Scenedesmus dimorphus 0 0 0 1 8 R1531 Anabaena circinalis 0 0 0 1 8 R1544 Anabaena planctonica 0 0 0 3 7 R1748 Phacus longicauda 0 0 0 1 8 R0078 Stephanodiscus binderanus 0 0 0 2 8 R0079 Stephanodiscus hantzschii 0 0 0 2 8 R0484 Ankistrodesmus sp. 0 0 0 2 8 R0781 Scenedesmus ecornis 0 0 0 2 8 R0999 Volvox globator 0 0 0 2 8 R1622 Pseudanabaena mucicola 0 0 0 2 8 R0503 Chlorella sp. 0 0 0 2 8 R0020 Aulacoseira ambigua 0 0 0 1 9 R0500 Characium sp. 0 0 0 1 9 R1610 Planktolyngbya limnetica 0 0 0 1 9 R0028 Aulacoseira italica 0 0 0 0 10 R0930 Chlamydocapsa planctonica 0 0 0 0 10 A. In alphabetic order 7 0 0 0 R0016 Acanthoceras zachariasii 0 0 0 3 5 R2503 Achnanthidium catenatum 0 0 1 1 0 R1531 Anabaena circinalis 0 0 0 1 8 R1536 Anabaena flos-aquae 0 1 1 3 3 R1544 Anabaena planctonica 0 0 0 3 7 R1549 Anabaena spiroides 0 1 6 1 1 R0484 Ankistrodesmus sp. 0 0 0 2 8 R0488 Ankyra ancora 0 0 0 1 8 R0489 Ankyra judayi 0 0 0 8 1 R0490 Ankyra lanceolata 0 0 1 4 2 R1558 Aphanizomenon flos-aquae 0 0 0 3 6 R1560 Aphanizomenon gracile 0 0 1 4 3 R1413 Aphanocapsa delicatissima 0 3 3 2 0 R1414 Aphanocapsa elachista 0 1 2 4 1 R1427 Aphanothece clathrata 0 0 1 5 0 R0020 Aulacoseira ambigua 0 0 0 1 9 R0023 Aulacoseira granulata 0 0 0 3 6 R0024 Aulacoseira granulata var. angustissima 0 0 0 3 5 R0025 Aulacoseira islandica 0 1 3 2 1 R0028 Aulacoseira italica 0 0 0 0 10 R0033 Aulacoseira subarctica 0 1 8 0 0 R1155 Bitrichia chodatii 4 4 2 0 0 R0493
The reference conditions and class boundaries of the three parameters chlorophyll-a, total biovolume and Brettum index were developed during the intercalibration process and are now harmonised between Slovenia, Italy, France, Germany and Austria. For Austrian lakes, ranges rather than fixed values were defined for the three parameters and the two IC lake types. Any classification following the principles of the WFD is based on a comparison of the status quo with the reference state. The deviation is calculated as the ecological quality ratio for the chlorophyll-a concentration (EQRChl), the total biovolume (EQRBV) and the Brettum index (EQRBI):

EQRChl and EQRBV = reference value/measured value (5) EQRBI = measured value/reference value (6)

In order to enable a combination of EQR values, they are transformed ("normalised") such that the class boundaries are equidistant. This allows the ecological status class to be directly identified from the "normalised" EQR value (nEQR 0.8 = class boundary high / good, 0.6 = good / moderate etc.).

Transformation of EQR to nEQR is done using the following algorithms: The assessment of single years is based on the arithmetic means of the normalised EQR values for chlorohyll-a, total biovolume and the Brettum index:

EQRi nEQRi ≥ 1 1 ≥ EQRH/G (EQRi -EQRH/G) / (1 -EQRH/G) * 0.2 + 0.8 EQRH/G > EQRi ≥ EQRG/M (EQRi -EQRG/M) / (EQRH/G -EQRG/M) *
2 2 ) ( B B I Chl V gesamt nEQR nEQR nEQR nEQR    (7)
The final assessment of the ecological status is based on the average of the final normalised EQR values of three subsequent years. The status classes include the lower class boundary, whereas the upper class boundary is assigned to the higher class (Table A At present, it is not possible to confidently assign reference values to the Neusiedler See, the salt pans in the Seewinkel region and the Old Danube. The assessment methods recently developed by WOLFRAM et al. (2008[START_REF] Wolfram | Bewertung des ökologischen Zu-standes des Neusiedler Sees anhand des Biologischen Qualitätselements Phytoplankton[END_REF] remain to be validated. There are also uncertainties in the definition of the reference state for some Alpine lakes, where either no or limited data on the phytoplankton are available. For instance, there are currently no reference values for the very shallow Almsee (mean depth <3 m) (Table A.4).

Table A .3 Ranges, EQR values and normalised EQR values of the reference conditions and class boundaries of total biovolume (mm3 L-1), chlorophyll-a concentration (µg L-1) and the Brettum index in the two IC lake types, L-AL3 and L-AL4. Within the ranges of the two types, the reference conditions may vary depending on the hydromorphology. For Austrian lakes, the positions within the ranges are given in Table A .4 (1 = minimum value, 2 = median value, 3 = maximum value). Germany: PSI (Phyto-Seen-Index) -Bewertungsverfahren für Seen mittels Phytoplankton zur Umsetzung der EG-Wasserrahmenrichtlinie in Deutschland

Sampling and analyses

The German assessment procedure includes and requires a fixing of standardized methods for sampling, preservation and storage, and microscopic analysis (Nixdorf et al. 2010).

For the assessment six samples per year are needed from epilimnion or euphotic zone (clear water lakes, of which four samples must be taken in the period May-September.

The taxa are counted according the Utermöhl technique and coded by the operational phytoplankton taxa list. To determine indicator species additional diatom preparation is recommended.

Assessment

The German phytoplankton-based assessment system for lakes [START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF]) yields a multi-metric index value, the Phyto-See-Index (PSI), and differentiates between different lake types. It classifies water bodies into one of five status classes in accordance with the Water Framework Directive (WFD). The PSI consists of three mandatory metrics: "biomass", "algal classes" and the "Phytoplankton-Taxa-Seen-Index" (PTSI).

The three compulsory metrics along the stressor "eutrophication" are calibrated and adjusted in accordance with reference sites and trophic reference conditions. Total phosphorus and the actual assessment value of the German Trophic Index (LAWA 1999) served as the stressor scale. The German Trophic Index is based on the combined classification of the common trophic parameters "chlorophyll-a", "total phosphorus" and "secchi depth" as a measure of lake transparency..

The PSI is composed of three mandatory metrics and an optional fourth metric, DI-PROF, latter not included into intercalibration. Some of these metrics are multiparameter variables.

1. Biomass metric: this is composed of: a. The total biovolume of phytoplankton in the epilimnic or euphotic zone of the lake (arithmetic mean in the vegetation period from April to October of six samples); b. Chlorophyll-a concentration (arithmetic mean in the vegetation period from April to October; c. Maximum Chlorophyll-a value, if it deviates from the mean more than 25%.

2. Algal class metric: the biovolume or its percentage of total biovolume in specific annual periods (e.g. mean values of cyanophytes, dinophytes and of chlorophytes from July to October; mean value from chrysophytes from April to October);

3. PTSI (Phytoplankton Taxa Lake Index): this index evaluates the species composition based on lake-type specific lists of indicator species (332 different species) and their special trophic scores and weighting factors. The method works in two steps: a. trophic assignment results in a PTSI index per sample or lake year;

b. assessment by comparing current trophic state with the lake type specific trophic reference status

The results of all components and of the final index are an index value between 0.5 and 5.5 which can be easily transformed to a normalized EQR (y = -0.2x + 1.1).

Table A.5 Transformation of the metric index value to normalized EQR.

German metric index value Normalized EQR 0.5 -1.5 0.8 -1 1.51 -2.5 0.6 -0.8 2.51 -3.5 0.4 -0.6 3.51 -4.5 0.2 -0.4 4.51 -5.5 0.0 -0.2

The final score is summarized using weighting factors of used components before averaging the metric results (details in [START_REF] Mischke | Description of the German system for phytoplankton-based assessment of lakes for implementation of the EU Water Framework Directive (WFD)[END_REF].

Reference and boundary setting

The class boundaries for the total biovolume and the metric algal classes are derived by using a pre-assignment of ecological quality of the lakes. The assignment was based on a trophic score, the German LAWA-index, the estimation of local experts and in consideration of the lake type specific trophic reference state. The trophic reference status of lake types are defined (in first draft) with a view to palaeolimnological investigations, true reference sites without anthropogenic impact and ideas about background concentrations of total phosphorus and morphometric conditions in lakes. Trophic reference status is given as a trophic class according to the German LAWAapproach for assessing lakes (LAWA 1999), which combines criteria for chlorophyll a, total phosphorous and transparency (SD). During the intercalibration exercise the German reference boundaries for chlorophyll a were adjusted to intercalibration results. The trophic scores of indicator species for the PTSI were developed along the trophic gradient, German LAWA index and total phosphorus concentrations.

Introduction

In the Alpine GIG a phytoplankton assessment method based on three parameters was intercalibrated: chlorophyll, biomass and a taxonomic composition metric (PTI ot).

Yearly average of chlorophyll a concentration, biovolume and PTIot are combined in order to calculate the overall index for phytoplankton (ICF), giving the final classification score:

 normalized EQRs of average chlorophyll and biomass metrics are averaged to give the Biomass Index;  the normalized EQR of average PTIot metric is the Composition Index;  Arithmetic mean of Biomass and Composition Indexes gives the final ICF value.

The Italian assessment phytoplankton method was developed from a dataset including natural lakes of the Alpine ecoregion, belonging to L-AL3 and L-AL4 types:  L-AL3 are Lowland or mid-altitude (50-800 m a.s.l.), deep, moderate to high alkalinity (alpine influence), large;  L-AL4 are medium or low altitude lakes (200-800 m a.s.l.), calcareous (alk > 1meq/l), with a surface area higher than 0.5 km 2 and an average depth lower than 15 m.

Metric description: sampling, analyses, principles for setting reference value and boundaries

Sampling strategies

Phytoplankton samples are taken from mid-lake stations, as integrated samples of euphotic water column. Sampling frequency is 6 times per year, according to the seasonal development of phytoplankton succession, as follows:

 Sample 1: period January to mid-March for winter assemblages;

 Sample 2: period April to mid-May for spring assemblages;  Sample 3: period mid-Maymid June for transition between spring and summer assemblages;  Sample 4: period July -August for summer assemblages;  Sample 5: September for transition between summer and autumn assemblages;  Sample 6: period mid-October -November for autumn assemblages.

All the metrics were calculated using data obtained with the same sampling strategy.

Chlorophyll a

Chlorophyll a is determined following extraction using spectrophotometric analysis. Reference values were decided at GIG level and are detailed in the Water Framework Directive Intercalibration Technical Report -Part 2: Lakes (Poikane, 2009) and in the Intercalibration decision (EC, 2008). Reference values and class boundaries of and chlorophyll-a Chl-a were set using the selected population of reference sites. The median was defined as reference value, the 90%percentile as H/G boundaryboth supported by expert judgment. The GM, MP and PB metric boundaries were set using equidistant class widths on a log scale. The chlorophyll a EQR is calculated using Equation 1 below where the Chlaref is the GIG chlorophyll reference value in µg/l and the Chlaobs is the observed growing season mean chlorophyll value in µg/l.

ChlaEQR = Chlaref/Chlaobs

(1)

Total biovolume (mg/l) Phytoplankton samples are counted using the Utermöhl technique and total biovolume is calculated from the sum of the biovolumes of each taxon in the sample (cell number x specific cell volume). Reference values and class boundaries of total biovolume BV were set using the selected population of reference sites. The median was defined as reference value, the 90%percentile as H/G boundaryboth supported by expert judgment. The GM, MP and PB metric boundaries were set using equidistant class widths on a log scale. The biovolue EQR is calculated using Equation 2 below where the BVref is the GIG biovolume reference value in mg/l and the BVobs is the observed growing season mean biovolume value in mg/l. BVEQR = BVref/BVobs (2)

Phytoplankton composition metric (PTIot)

The phytoplankton composition metric provides an indication of the state of community composition and relative abundance in relation to the eutrophication pressure gradient.

Assessment is based on 6 yearly samples, collected as explained above.

Phytoplankton samples are counted following the Utermöhl technique (CEN standard).

Assessment is based on an index called PTIot (Phytoplankton Trophic Index).

The metric has been implemented using the entire dataset of Alpine GIG. A comparison of results obtained with the use of datasets showed that the use of the entire pool of data has allowed us to obtain a better correlation between total phosphorus and PTIot in Lakes / year.

The criteria used to select the species for which to calculate the index were:

 Species present in at least 3 lakes;  Species with a percentage of biovolume higher than 1%.

The necessary condition for the application of the index is that at least 70% of the total biovolume of the species for the water body is used to calculate the index.

The index is based on the calculation of the weighted average (niche centroid, ter Braak & Verdonshot, 1995) of the species k with respect to the gradient of total phosphorus for all the lakes (Equation 3). These values represent the trophic index for each species (TIk). The higher this index, the higher the quality of the trophic species. Prior to the calculation of TIk, the concentrations of total phosphorus have been transformed into logarithmic values and scaled from 1 to 5.

TPi Y Y TI n i k ik k     1 (3)
Where Yik = biomass of species k in site i as annual average, Y+k = biomass of species k in all sites, TPi= Total phosphorus concentration in site i.

In a second step tolerance is calculated, representing the goodness of species as trophic indicator: the higher the tolerance, the worse the indicator quality of a species.

Tolerance was calculated as follows:

       n i k k ik k TI TPi Y Y t 1 2 (4)
From the ratio between tolerance (tk) and trophic index (TIk) were obtained the indicator values (vi), ranging from 1 to 4. When the ratio is higher than 0.8, then vi = 1; when lies between 0.8 and 0.6, vi = 2; when lies between 0.4 and 0.6 vi = 3; when is lower than 0.4, vi = 4. A.5.

Trophic indices and indicator values for each species are reported in Table

Finally, the PTIot value for the lake is obtained from: Reference values and class boundaries for PTIot was done by using the values calculated over the whole AlpGIG dataset. Reference values correspond to the median value of the reference lakes. As H/G boundary the 10 th %ile of the values of the reference lakes was taken. G/M boundary was set as the 10 th %ile of the index values calculated in those lakes classified as Good using the Austrian Brettum Index [START_REF] Dokulil | Bewertung der Phytoplanktonstruktur stehender Gewässer gemäß der EU-Wasserrahmenrichtlinie: Der modifizierte Brettum-Index[END_REF]. We chose this approach because we didn't identified any discontinuity in the relationship between eutrophication gradient and PTiot values, therefore we compared the results obtained by the use of percentile with those obtained using lakes classified as Good by Austrian Brettum index, the only index developed at the time of the first boundary setting procedure. We also analysed the species composition of these lakes and, by an experts judgement, we agreed that the phytoplankton communities would fit with the classification of Good Quality reported by WFD. The results of the 2 intercalibration exercises confirmed the goodness of our choice. EQR for PTIot are calculated as in Equation 6:

   i i i TI i ot v a
EQR = PTIotEQR = PTIotobs / PTIotref (6)

Calculation of EQR and normalised EQR for all metrics

EQR values for the metrics used in the Italian phytoplankton assessment method are calculated as reported in Equation 1, 2 and 6.

When EQR is higher than 1, EQR value must be set to 1. In order to allow combination of all metrics to a whole BQE assessment, each metric EQR has to be converted to the normalised scale with equal class widths and standardised class boundaries, where the HG, GM, MP, and PB boundaries are 0.8, 0.6, 0.4, 0.2 respectively. When using indices with classes ranges different from each other, the normalization equation is based on a linear interpolation between classes boundaries. Moreover, the interpolation process takes into account the reference value as upper limit of the High-Quality class (EQR and normalised EQR equal to 1) as well as the minimum EQR value as the lower threshold of the Bad-Quality class (normalised EQR equal to 0).

Calculation of normalised EQR

Therefore, the normalization equations will be different for each quality class, as below.

EQRnorm = 1 -0.2*(1-EQR)/(1-EQRHG) (7)
Class "High"

EQRnorm = 0,8 -0,2*(EQRHG -EQR)/(EQRHG -EQRGM) (8)
Class "Good"

EQRnorm = 0,6 -0,2*(EQRMP -EQR)/(EQRGM -EQRMP) (9) Class "Moderate" EQRnorm = 0,4 -0,2*( EQRMP -EQR)/(EQRMP -EQRPB) (10) Class "Poor" EQRnorm = 0,2 -0,2*( EQRPB -EQR)/(EQRPB -EQRmin) (11) Class "Bad"
Where: EQR are the measured values, EQRHG, EQRGM, EQRMP, EQRPB are the EQR values (not normalized) at the boundary between two quality classes and EQRmin is the minimum EQR of each metric.

EQRmin is set to 0 for PTIot and to 20 times the value of the P/B threshold for biovolume and chlorophyll.

Combination of metrics to whole quality element result

The following process is used to combine single metrics to a whole quality element results for lake phytoplankton (to be done for a whole growing season only, not for single samples):

 Average the normalised EQRs of chlorophyll a and total biovolume (two biomass metrics). This is important to avoid too heavy weight on the biomass metric relative to the other metrics.  Average the normalised EQRs for the biomass metrics from point 1 with the normalised EQRs of the PTIot. Up to now in Italy we do not have enough data to calculate the boundaries for all the national typologies. Use of the ranges will allow us to discriminate, for example, large deep subalpine lakes, characterized by lower algal production and, therefore, also lower reference values, from the other L-AL3 with a mean depth close to 15 metres. Within L-AL4 lakes, we can separate very shallow polymictic lakes, with higher algal production and reference values, from the other small lakes. In the Italian official phytoplankton assessment method, lakes of the Alpine Eco Region are subdivided in 4 types, coincident with the ranges showed before. Ranges are going to be officially adopted, after the applicability to all the lakes of Italian alpine eco region will be verified. Correlation of Italian combined whole BQE phytoplankton method against pressure (total-P)

Reference values and class boundaries for each type

The Italian Phytoplankton Assessment Method (IPAM) is well correlated with pressure (Total-P) for both lakes typologies . The r 2 vary from 0.56, for L-AL3, to 0.57 for L-AL4 as reported in Figure A.3 and Figure A.4. Figure A.3 Correlation between LogTP and EQR's IPAM for 132 L-AL3 lakes-year of Alpine GIG. Figure A.4 Correlation between LogTP and EQR's IPAM for 165 L-AL4 lakes-year of Alpine GIG

Reference condition setting

Reference condition and class boundaries for the total biovolume, Chlorophyll-a and Brettum index were set during the IC process and harmonized among AT,DE, FR, IT, SI. The base were existing near-natural reference sites, epert knowledge, historical data, modelling (extrapolating model results).

Reference values and class boundaries of the total biovolume BV and chlorophyll-a Chla were set using the selected population of reference sites. The median was defined as reference value, the 95% percentile as H/G boundaryboth supported by expert judgment.

The other class boundaries of BV and Chl-a were derived using equidistant class widths on a log-scale. The class boundaries for the new version of the Brettum index BInew were derived in the same way as for BV and Chl-a, supported by expert judgment.

Reference values for Biovolume, Chlorophyll-a and Brettum-Index were not set as fixed values but interval value.

According to the different type conditions specific »rang« value for each Lake type was selected.

Class Boundary setting

HG boundary derived from metric variability at near-natural reference sites (95th percentile).

The class boundaries of BV and Chl-a were derived using equidistant class widths on a log-scale. The class boundaries for the Brettum index were derived in the same way as for BV and Chl-a.

Introduction

In phase 1 of the intercalibration exercise, the phytoplankton and the macrophyte Alpine GIG defined criteria for selecting reference lakes, which, however, differed in some respect. In 2008, the invertebrate Alpine GIG started its work also with defining reference criteria, which again partly complied, partly differed from what proposed by the other BQE groups. The lack of harmonized criteria for defining reference conditions for the same IC types is criticized in the consistency check report of [START_REF] Pardo | Revision of the consistency in Reference Criteria application in the phase one of the European Intercalibration Exercise[END_REF], who strongly recommended to work on agreed criteria for the whole GIG.

The different approaches for defining reference conditions both between and within GIGs were also criticized by the Reference Conditions Working Group, which contributed to Annex III of the new IC guidance document.

In this document we propose a way to harmonize the criteria for defining reference conditions for Alpine lakes by using a tiered approach. It is based on the Refcond guidance and takes into account the recommendations of [START_REF] Pardo | Revision of the consistency in Reference Criteria application in the phase one of the European Intercalibration Exercise[END_REF] and of the Reference Conditions Working Group proposed for Annex III of the new IC guidance document (Table B.1).

The criteria proposed in this document are used to select:

1. Reference lakes (RL), i.e. lakes that are in reference conditions for all BQE as well as for hydro-morphological and chemical conditions. 2. Reference conditions lakes (RCL), i.e. lakes where at least one BQE is in high status. A can be considered as RCL for phytoplankton, macrophytes, invertebrates or fishor for various combinations of 2 to 4 BQE. 3. Reference conditions sampling sites (RCSS), i.e. sampling sites for invertebrates in the littoral or sublittoral zone, or transects for macrophyte sampling, where both reference criteria valid for the whole lake (such as trophic state, water level conditions) and criteria valid at local scale (such as morphological condition of the shore within a certain area) meet the criteria for reference conditions.

Criteria which are valid one (or at least less then all four) BQE and which are used to define RCL are defined as 'specific criteria'. The sum of the specific criteria for the four BQE give the 'general criteria' that are required to be met in RL. Reference criteria for the pressure 'eutrophication' are defined according to the proposal made by the phytoplankton group in phase 1 of the IC exercise [START_REF] Wolfram | Reference conditions and WFD compliant class boundaries for phytoplankton biomass and chlorophyll-a in Alpine lakes[END_REF].

The other BQE will adopt these criteria.

The criteria focus on TP as proxy for land use as driving force and for eutrophication or nutrient load as pressure (Table B.2). The approach to use TP as proxy rather than the driving force 'land use in the catchment area' is justified by the insufficient correlation between land use and the trophic state of Alpine lake ( B.4). Hence, land use data from the catchment area will not be used as threshold criteria for selecting RCL, but as supporting criteria (Table B.3). In case of conflicts between the strict criteria listed in Table B.2 and the supporting criteria listed thereafter, it has to be proved in each single case whether or not the lake can be treated as RCL. Up to then, the lake is considered as candidate RCL only.

For assessing local trophic impacts, however, land use in the near surrounding will be used (see below).

Figure 2 . 1 .

 21 Figure 2.1. Relationship between total phytoplankton biovolume (total BV) and Cyanobacteria biovolume in Alpine lakes. Low risk (2 mm3/l) and risk threshold (10 mm3/l) of Cyanobacteria blooms shown as horizontal lines. Goodmoderate class boundary for biovolume (1 mm3/l, range 0.8-1.2 mm3/l) in L-AL3 shown as a vertical line.

TP

  : Y = -0.1781 * ln(X) -0.1618 (N = 236, R 2 = 0.62) GE: Y = -0.1762 * ln(X) -0.1415 (N = 410, R 2 = 0.57) IT: Y = -0.1755 * ln(X) -0.1199 (N = 264, R 2 = 0.52) = -0.2296 * ln(X) -0.2523 (N = 132, R 2 = 0.62) GE: Y = -0.2559 * ln(X) -0.3173 (N = 299, R 2 = 0.70) IT: Y = -0.2034 * ln(X) -0.1023 (N = 133, R 2 = 0.52)

Figure 7

 7 Figure 7.1. Comparison of Alpine GIG phytoplankton methods: HG and GM boundary biases (HG -High-Good class boundary, GM-Good-Moderate class boundary)

Figure 8

 8 Figure 8.2. Secchi depth (m) distribution at different ecological status classes in L-AL3and L-AL4 lakes.

Figure 8

 8 Figure 8.3. Brettum scores for selected trophic classes in relation to normalized EQR (L-AL3 type)

Figure A. 1

 1 Figure A.1 Distribution along total phosphorus gradient of Bitrichia chodatii (% of total phytoplankton biovolume)

  TP [mg L -1 ]Calculation of the Brettum IndexTo calculate the Brettum index BI, a weighted average is calculated from the six indices Ij, where the TP ranges j have the values Tj = 6 (<5 µg L -1 ) to 1 (>60 µg L -1 ) in descending order:

  average of biovolume of species I, TIk = trophic index of species I, vi = indicator value of species i.

Figure A. 2

 2 Figure A.2 Regression model between PTIot and Log TP for the Alpine GIG data set.

  Figure B.1 and Figure B.2). This owes to strong model uncertainties, a lack of additional data such as buffer stripes around the lake, the degree of construction of WWTP or the presence of waste water ring channels (Figure B.3 and Figure B.4). In spite of good availability of land use data, the overall model between land use and the biological response is subject to very large uncertainty (Table

Figure B. 1

 1 Figure B.1 Comparison of chlorophyll-a values in reference lakes with different natural land cover in catchments (all GIGs and all lake types) (from: Pardo et al. 2010).

Figure B. 2

 2 Figure B.2Correlation of the CORINE category 'forest' and the TP concentration in oligotrophic Alpine lakes (from[START_REF] Wolfram | Alpine GIG: Boundary setting in Alpine lakes. A. Phytoplankton[END_REF]. The different symbols refer to L-AL3 (filled) and L-AL4 (open) lakes, the bars give the 95% confidence limits (based on time series of monitoring).

Figure B. 3

 3 Figure B.3 Driving force (land use  nutrient production/export), pressure (nutrient load/ eutrophication  nutrient concentration) and state (phytoplankton abundance and taxonomic composition).

  Figure B.4Example 1: Lake chain in the Northern Limestone Alps with upstream lakes serving as sediment and nutrient trap for the downstream Lake Attersee, hence biasing possible effects of land use on the nutrient load and the trophic state. Example 2: Wetlands as buffer zones which reduce the inflow of nutrients into Lake Pressegger See. Example 3: Export of waste water from the catchment area in a ring channel around Lake Wörthersee. Table B.2 Specific reference criteria for the selection of RCL for the BQE phytoplankton in Alpine lakes. Pressure Pressure indicators

  Figure B.5Scheme on the tiered approach to develop a common set of reference criteria in the Alpine GIG.

Table 2 .

 2 2 Overview of the metrics included in the national phytoplankton assessment methods

	MS Biomass	Taxonomic composition and abundance	Algal blooms	Combination rule of metrics
	AT Average of the	Brettum index (calculated from	Metric not	Arithmetic
		nEQR of annual	annual mean relative biovolume,	considered	mean of
		mean total	weighted average of the trophic		nEQRs
		biovolume and	scores for the indicator taxa)
		chlorophyll-a
	DE Total biovolume	Algae groups/classes or	Metric not	Weighted
		(seasonal mean)	combination of groups. Evaluation	considered	average
		and chlorophyll-a	related to type specific decision		metric scores
		concentration	tables
		(seasonal mean	PTSI (Phytoplankton Taxa Seen
		and maximum)	Index) -Evaluation related to log
			transformed biomass and trophic
			weighting factors of indicator
			species
	IT	Average of the	PTIot Phytoplankton Trophic Index.	Metric not	Arithmetic
		nEQR of annual	Log transformed biovolume	considered	mean of
		mean total	(annual mean), weighted average		nEQRs
		biovolume and	of the trophic scores and the
		chlorophyll-a	indicator values for all indicator
			taxa
	SI	Average of the	Brettum index (calculated from
		nEQR of annual	annual mean relative biovolume,
		mean total	weighted average of the trophic
		biovolume and	scores for the indicator taxa)
		chlorophyll-a

Table 2 .

 2 4 Overview of the methodologies used to derive the reference conditions for the national phytoplankton assessment methods

	Member State	Methodology used to derive the reference conditions
	AT	Existing, Expert knowledge, Historical data, Modelling (extrapolating model
		results)
	DE	Existing near-natural reference sites and palaeo-limnological studies
	IT	Existing near-natural reference sites, Expert knowledge, Historical data,
		Modelling
	SI	Existing near-natural reference sites, Expert knowledge, Historical data,
		Modelling (extrapolating model results)

Table 2

 2

	Table 2.5 Pressures addressed by the MS assessment methods (EU -eutrophication,
		TP-total phosphorus concentration, nEQR -normalised Ecological Quality
		Ration of national assessment methods)
	Member State	Metrics tested	Pressure	Pressure indicators	Strength of relationship (determination coefficient R2)
	AT/SI	nEQR	EU	TP	L-AL3 0.62; L-AL4 0.62
	GE	nEQR	EU	TP	L-AL3 0.57; L-AL4 0.70
	IT	nEQR	EU	TP	L-AL3 0.52; L-AL4 0.52

.5, Figure 2.2.)

Table 3 .

 3 1 List of the WFD compliance criteria and the WFD compliance checking process and results

	Compliance criteria	Compliance checking conclusions
	1. Ecological status is classified by one of five	All MS: yes
	classes (high, good, moderate, poor and
	bad).
	2. High, good and moderate ecological status	All MS: yes
	are set in line with the WFD's normative
	definitions (Boundary setting procedure)
	3. All relevant parameters indicative of the	All MS: all parameters except blooms
	biological quality element are covered (see	are included. For abundance/biomass,
	Table 1 in the IC Guidance). A combination	both chlorophyll-a and biovolume (GE,
	rule to combine parameter assessment into	IT, AT/SI) are used.
	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.
	4. Assessment is adapted to intercalibration	All MS: yes
	common types that are defined in line with
	the typological requirements of the WFD
	Annex II and approved by WG ECOSTAT
	5. The water body is assessed against type-	All MS: yes
	specific near-natural reference conditions
	6. Assessment results are expressed as EQRs	All MS: yes, on the level of single
		metrics; these are converted to
		normalized EQR (nEQR; class width =
		0.2) and combined to final nEQR. This
		procedure complies with the approach of
		other GIGs in phase 1 as well as with
		the current phase 2 approach of the
		Alpine macrophyte group.
	7. Sampling procedure allows for	All MS: yes, min 4 samples per year in
	representative information about water body	data set. Future monitoring: GE & IT 6
	quality/ ecological status in space and time	times, AT, FR & SI 4 times per year (in
		AT the 4 sampling dates may distribute
		over the whole year and hence with only
		3 dates during the vegetation season
		March -October)
		Samplings of epilimnion or euphotic
		zone.
	8. All data relevant for assessing the biological	All MS: yes (except blooms)
	parameters specified in the WFD's
	normative definitions are covered by the
	sampling procedure

9. Selected taxonomic level achieves adequate confidence and precision in classification

All MS: yes

Table 4

 4

	.1 Description of common intercalibration water body types and the MS sharing
	each type
	Common IC type	Type characteristics	MS sharing IC common type
	L-AL3	Deep (mean depth usually	All MS
		>15 m), true Alpine catchment
	L-AL4	Moderately deep -shallow	All MS but SI (where both lakes
		(mean depth usually 3-15 m),	>0.5 km2 belong to L-AL3)
		usually pre-Alpine catchment

Table 4

 4

	Method	Appropriate for IC	Remarks
		types/subtypes
	AT method	L-AL3	several national types; ranges are used to cover
		L-AL4	differences between national types
	GE method	L-AL3	4 types are defined for German lakes, 3 of them fit to
		L-AL4	the IC types, some shallow lakes were included to L-
			AL4.
	IT method	L-AL3	For biomass metrics, ranges are used to cover
		L-AL4	variability within the types.
	SI method	L-AL3	Ranges are used to cover variability within the IC
			types (i.e. difference between the two lakes > 0.5 km2,
			both L-AL3)

.2 Evaluation if IC feasibility regarding common IC types

Table 5 .

 5 1 Overview of the Alpine GIG phytoplankton IC dataset

			Number of lake years
	Member State	Biovolume data	Chlorophyll-a data	Total phosphorus data
	L-AL3
	AT	240	65	196
	FR	24	24	24
	DE	148	121	136
	IT	42	39	42
	SI	26	24	24
	L-AL4
	AT	160	12	158
	FR	4	4	4
	DE	75	62	64
	IT	44	40	44

Table 5

 5

	Data acceptance criteria	Data acceptance checking
	Data requirements	1. Both total biovolume and chlorophyll-a data must be
	(obligatory for all MS)	available.
		2. Sampling frequency per year must be four at
		minimum.
		3. Sampling dates must be more or less evenly
		distributed over the year or the vegetation season
		(e.g. Seehamer See 1996 with 5 sampling dates was
		excluded, since sampling started in September)
		4. AT method: only lake-years are included where
		centric diatoms are identified to species level
	The sampling and analytical	1. Sampling of phytoplankton (and chlorophyll-a) must
	methodology (obligatory for all	cover the whole epilimnion or euphotic zone.
	MS)	Samples are taken using an integrating water
		sampler or as a mixed samples of several sampling
		depths.
		2. Total phosphorus is calculated as volume weighted
		annual average. If this is not available, the TP

.2 Overview of the data acceptance criteria used for the data quality control

. Comparison of methods and boundaries 7.1. IC Option and Common Metrics

					L-AL3 lakes
		1.0	AT method	GE method			IT method
		0.8
	nEQR	0.4 0.6
		0.2
		0.0
		AT	GE	SI	AT	GE	SI	AT	GE	SI
		1.0	AT method	GE method			IT method
		0.8
	nEQR	0.4 0.6
		0.2
		0.0
		AT	GE	AT	GE	AT		GE
		6.1. Comparison on nEQR values of reference lake-years from L-AL3 and L-AL4
		in different MS as calculated from the three methods available. Number of
		reference lake-years in L-AL3 type: AT 7, GE 13, SI 1. Number of reference
		lake-years in L-AL4 type: AT 10, GE 7 (IT 2, not included)
	7Option 1 was followed between AT and SI, since both countries use the same method.
	The reference values and class boundaries of total biovolume and of chlorophyll-a are
	fully identical in AT, SI and IT. Hence, the methods from AT/SI and IT differ only in the
	trophic index.

Table 7

 7

	.1	Regression characteristics (National EQRs vs PCM)
		Intercept (c)	Slope (m)
	MS/IC type	L-AL3	L-AL4	L-AL3	L-AL4
	AT/SI	0.117	0.136	0.916	0.828
	GE	-0.038	0.022	0.936	0.959
	IT	0.034	-0.043	0.932	1.022
		Regressions with PCM R2	Pearson R
	AT/SI	0.919	0.884	0.959	0.940
	GE	0.860	0.913	0.928	0.955
	IT	0.899	0.899	0.948	0.948

Ratio min R 2 : max R 2

	0.94	0.97

Table 7 .2 Overview of the IC comparability criteria Class difference (boundary bias) Absolute Class Difference H/G boundary bias G/M boundary bias

 7

	MS/IC type	L-AL3	L-AL4	L-AL3	L-AL4	L-AL3	L-AL4
	AT/SI	0.18	-0.09	0.18	0.24	0.17	0.22
	GE	-0.06	0.05	-0.04	0.07	0.18	0.19
	IT	-0.12	-0.11	-0.14	-0.24	0.20	0.22

Table 7

 7

		.3 Overview of the IC results: EQRs of the Alpine GIG phytoplankton assessment
		methods
		Classification	Ecological Quality Ratios
	MS	Method	High-good boundary	Good-moderate boundary
	AT	Evaluation of the biological quality elements, Part B2 -phytoplankton	0.8	0.6
		PSI (Phyto-Seen-Index) -Bewertungsverfahren
	DE	für Seen mittels Phytoplankton zur Umsetzung	0.8	0.6
		der EG-Wasserrahmenrichtlinie in Deutschland
	IT	Italian Phytoplankton Assessment Method (IPAM)	0.8	0.6
		Metodologija vrednotenja ekološkega stanja
	SI	jezer s fitoplanktonom v Sloveniji (Ecological status assessment system for lakes using	0.8	0.6
		phytoplankton in Slovenia)

Table A .

 A 1 Taxon-specific trophic scores. The scores given for genera are valid for all species belonging to it unless the latter are listed separately.

  Table A.3 lists the ranges of the original values for total biovolume, chlorophyll-a concentration and Brettum index, the EQR values and the normalised EQR values. Following the proposal on the position of the Austrian lakes within these ranges, concrete reference values and class boundaries are now available for each of the 38 Alpine lakes >50 ha listed in Table A.4.

Ecological Quality Ratio and the Classification of the Ecological Status

  .2).The starting point of the assessment is the reference values and EQR class boundaries given inTable A.3and Table A.4. All calculations based on these values (e.g. class boundaries for chlorophyll-a, total biovolume or the Brettum index, normalised EQR values, combination of nEQR values and final calculation) are carried out without rounding off the values.

	Table A.2 Assessment of the ecological status using phytoplankton. Values lying exactly
	on the class boundaries are classified in the higher class (0.8 = high, 0.6 =
	good etc.).
	Ecological status	nEQRtotal
	High	≥0,80
	Good	0,60 -0,80
	Moderate	0,40 -0,60
	Poor	0,20 -0,40
	Bad	<0,20

Table A .

 A 6 reports reference values and class boundaries for the two intercalibrated lake types.

Table A .

 A 6 EQRs, reference values and quality class boundaries for PTIot metric. In Figure A.2 the relationship between Log TP and PTIot is reported. The regression model is based on each lake/year for the whole Alpine GIG data set.

		Ecological Quality Ratio (EQR)		Index values
	Type	H/G boundary	G/M boundary	Reference	H/G boundary	G/M boundary
	L-AL3	0.95	0.89	3.62	3.43	3.22
	L-AL4	0.95	0.85	3.54	3.37	3.01

Table A .

 A 7, TableA.8, and TableA.9 gives all the reference values and class boundaries for the Italian classification system for each metric both as absolute values and as EQRs (non-normalised). The final whole BQE class boundaries are simply the normalised boundaries: 0.8, 0.6, 0.4, and 0.2 for the HG, GM, MP, PB boundaries respectively. Ranges were used instead of fixed values, for biovolume and chlorophyll-a, because IC lake types are rather broad and do not reflect geographical or other typological differences. Fixed values may cause problems when there is the need to transpose the values of the common IC type to their more detailed national typology.

		BV [mm 3 L -1 ]	EQR	BV [mm 3 L -1 ]	EQR
	Ref	0.2-0.3	1.00	0.5-0.7	1.00
	H/G	0.3-0.5	0.60	0.8-1.1	0.64
	G/M	0.8-1.2	0.25	1.9-2.7	0.26
	M/P	2.1-3.1	0.10	5.0-6.9	0.10
	P/B	5.3-7.8	0.04	12.5-17.4	0.04
	Table A.7 Reference values, class boundaries and EQR for the total biovolume (BV) for
		the IC lake types L-AL3 and L-AL4 (GIG agreement).
		L-AL3		L-AL4

Table A .

 A 8 Reference values, class boundaries and EQR for the chlorophyll-a concentration (chl-a) for the IC lake types L-AL3 and L-AL4 (GIG agreement).

		L-AL3		L-AL4
		chl-a [µg L -1 ]	EQR	chl-a [µg L -1 ]	EQR
	Ref	1.5-1.9	1.00	2.7-3.3	1.00
	H/G	2.1-2.7	0.70	3.6-4.4	0.75
	G/M	3.8-4.7	0.40	6.6-8.0	0.41
	M/P	6.8-8.7	0.22	11.7-14.6	0.23
	P/B	12.5-15.4	0.12	22.5-26.7	0.12
	Table A.9 Reference values, class boundaries and EQR for and PTIot
		L-AL3		L-AL4
		PTIot	EQR	PTIot	EQR
	Ref	3.62	1.00	3.54	1.00
	H/G	3.43	0.95	3.37	0.95
	G/M	3.22	0.89	3.01	0.85
	M/P	3.01	0.83	2.64	0.75
	P/B	2.80	0.77	2.28	0.64

Table A .

 A 10 Phytoplankton taxa used in the implementation of PTIot Index. The table reports frequency of occurrence in the dataset, trophic index and indicator values for each species.

	Table A.13	Reference interval, ranges and class boundaries for the Biovolume, Chlorophyll-a and Brettum-Index
	Aphanocapsa Chrysococcus rufescens Cymatopleura elliptica Gloeocystis Monoraphidium contortum Phytodinium globosum Stephanodiscus binderanus R0722 Pediastrum simplex 0,40 0,60 0,80 1,00 1,20 EQR IPAM Taxon Ankyra ancora Ankyra judayi Ankyra lanceolata Aphanizomenon Aphanizomenon flos-aquae Aphanizomenon gracile Taxon Chroomonas Chrysidiastrum catenatum Chrysochromulina Chrysochromulina parva Chrysococcus Chrysococcus minutus Taxon Cyclotella glomerata Cyclotella meneghiniana Cyclotella ocellata Cyclotella pseudostelligera Cyclotella radiosa Cyclotella stelligera Taxon Fragilaria ulna v. acus Fragilaria ulna v. angustissima Fragilaria virescens Glenodinium Gloeocapsa Gloeococcus Taxon Microcystis firma Microcystis flos-aquae Microcystis incerta Microcystis viridis Microcystis wesenbergii Monoraphidium arcuatum Taxon Peridinium willei Phacotus Phacotus lendneri Phacotus lenticularis Phacus Phacus tortus Taxon Staurastrum cingulum Staurastrum gracile Staurastrum paradoxum Staurastrum tetracerum Stephanodiscus Stephanodiscus alpinus Code Taxon Biovolume mm 3 L -1 range type 1 2 R0506 Chlorococcum sp. Ref 0,2-0,3 0,20 0,25 R0698 Oocystis marssonii H/G 0,3-0,5 0,33 0,42 R1518 Synechococcus sp. G/M 0,8-1,2 0,80 1,00 R1558 Aphanizomenon flos-aquae M/P 2,1-3,1 2,00 2,50 R0713 Pediastrum boryanum P/B 5,3-7,5 5,00 6,25	58 21 11 21 63 7 39 Frequency 44 56 60 68 204 16 Frequency 86 51 3 150 29 5 Frequency 27 16 40 19 192 8 Frequency 501 432 11 122 5 4 Frequency 5 47 10 3 23 43 Frequency 187 46 70 43 6 25 Frequency 23 50 59 20 38 74 3 0,30 Ref 0,50 H/G 1,20 G/M <=5 5-8 8-15 15-30 30-60 >60 3.20 2.97 4.19 2.29 3.49 2.38 2.20 0 0 0 1 7 TIk vi 2.55 2.53 2.83 3.38 2.57 2.97 TIk vi 3.34 3.44 3.20 2.92 3.32 3.14 TIk vi 3.87 3.34 2.85 3.38 3.06 3.68 TIk vi 3.42 3.37 2.11 3.59 4.61 4.36 TIk vi 3.37 3.11 2.90 2.89 2.93 2.87 TIk vi 3.37 2.64 2.93 2.74 2.81 3.11 TIk vi 2.39 2.61 2.62 2.52 3.04 3.64 Trophic class (as TP in µg L -1 ) Chlorophyll-a μg L -1 range type 1 2 0 0 0 0 1,50 -1,90 1,50 1,70 5 0 0 0 1 2,10-2,70 2,10 2,40 6 0 0 0 0 3,80 -4,70 3,80 4,25 5 0 0 0 1 3,10 M/P 6,80 -8,70 6,80 7,75 6 0 0 0 0 6 7,50 P/B 12,5 -15,8 12,50 14,15	3 1,90 2,70 4,70 8,70 15,80	Ref H/G G/M M/P P/B	Brettum Index 5,09-5,29 4,21-4,37 3,33-3,46 2,45-2,54 1,57-1,63	1 5,29 4,37 3,46 2,54 1,63	range type 2 5,19 4,29 3,39 2,5 1,6	3 5,09 4,21 3,33 2,45 1,57
	0,20 Aphanocapsa delicatissima Chrysolykos Cymatopleura solea Golenkinia radiata Monoraphidium griffithii Pinnularia Stephanodiscus hantzschii R0725 Pediastrum tetras		143 69 23 10 22 8 57	3.35 3.55 4.05 2.75 2.76 3.33 2.05 0	0	y = -0,3956x + 1,099 R 2 = 0,5642 0 1	7
	Aphanocapsa elachista Closterium aciculare Cymbella Gomphonema Monoraphidium komarkovae Planktonema Stephanodiscus minutulus R0754 Scenedesmus acuminatus 0,00 0 0,5 Aphanocapsa holsatica Closterium acutum Cymbella prostrata Gomphosphaeria Monoraphidium minutum Planktonema lauterbornii Stephanodiscus neoastraea R1499 Microcystis wesenbergii	1	97 61 54 26 42 13 99 4 107 32 46 29 7 205	3.00 3.22 3.56 3.25 3.41 3.97 2.87 0 1,5 2.55 2.85 3.68 4.05 2.19 3.05 3.20 0	0 0	0 0	2	0 1	6 2,5 7
	Aphanothece Closterium acutum v. variabile Diatoma Gomphosphaeria aponina Mougeotia Planktosphaeria gelatinosa Stephanodiscus parvus R1582 Limnothrix redekei		LogTP 90 96 43 39 63 103 9	3.45 2.58 2.36 2.81 2.40 3.27 2.89 0	0	0		1	7
	Aphanothece clathrata Cocconeis placentula Diatoma ehrenbergii Gomphosphaeria lacustris Mougeotia thylespora Planktothrix agardhii Synechococcus R0488 Ankyra ancora		87 31 9 5 29 18 42	3.02 2.78 2.85 3.25 2.66 3.34 2.51 0	0	0		1	8
	Asterionella formosa Coelastrum Diatoma tenuis Gymnodinium Navicula Planktothrix prolifica Synedra acus R0523 Coelastrum astroideum		659 62 68 428 118 8 7	3.29 2.92 3.17 3.51 3.22 2.01 2.52 0	0	0		0	7
	Aulacoseira Coelastrum astroideum Diatoma vulgaris Gymnodinium fuscum Navicula cryptocephala Planktothrix rubescens Synedra ulna R0616 Golenkinia radiata		38 28 69 12 14 424 6	3.36 2.39 3.09 3.43 3.13 3.29 2.76 0	0	0		1	8
	Aulacoseira ambigua Coelastrum microporum Dictyosphaerium Gymnodinium helveticum Navicula radiosa Pseudanabaena catenata Synura R0716 Pediastrum duplex		13 117 45 576 17 58 49	2.80 2.82 2.71 3.32 3.13 3.14 2.90 0	0	0		0	7
	1,20 Aulacoseira granulata Coelastrum pseudomicroporum Dictyosphaerium pulchellum Gymnodinium lantzschii Nephrocytium Pseudanabaena limnetica Synura uvella R0777 Scenedesmus dimorphus		98 20 42 113 56 18 22	2.59 2.43 3.19 3.08 3.18 2.87 2.73 0	0	0		1	8
	1,00 Aulacoseira granulata v. angustissima Coelastrum reticulatum Didymocystis Gymnodinium ordinatum Nephrocytium agardhianum Pseudoanabaena Tabellaria R1531 Anabaena circinalis		74 74 77 5 56 6 11	2.64 3.21 2.66 3.49 2.68 2.92 2.43 0	0	0		1	8
	Aulacoseira islandica Coelosphaerium Dinobryon Gymnodinium uberrimum Nephrocytium lunatum Pseudokephyrion Tabellaria fenestrata R1544 Anabaena planctonica		116 33 324 276 5 24 282	3.16 3.05 3.55 3.54 3.51 3.38 3.28 0	0	0		0	7
	0,60 0,80 Aulacoseira islandica v. helvetica Aulacoseira italica Coelosphaerium kuetzingianum Coenochloris Dinobryon bavaricum Dinobryon crenulatum Gyrosigma acuminatum Gyrosigma attenuatum Nitzschia Nitzschia acicularis Pseudosphaerocystis lacustris Quadrigula lacustris Tabellaria flocculosa Tabellaria flocculosa v.asterionelloides R1748 Phacus longicauda R0078 Stephanodiscus binderanus EQR IPAM Aulacoseira subarctica Coenocystis Dinobryon cylindricum Katablepharis Nitzschia fruticosa Quadrigula pfitzeri Tetrachlorella R0079 Stephanodiscus hantzschii		5 11 53 22 107 109 3 13 61 110 128 35 56 5 19 4 62 29 22 18 16	2.29 1.97 2.72 3.53 3.42 3.38 3.35 3.28 2.64 2.97 3.16 2.88 3.52 3.12 0 0 3.55 2.58 3.50 3.29 2.91 2.48 2.45 0	0 0 0	0 0 0		1 0 0	8 8 8
	0,40 Bitrichia chodatii Cosmarium Dinobryon divergens Kephyrion Ochromonas Radiocystis geminata Tetraedron R0484 Ankistrodesmus sp.		184 191 417 158 213 14 70	3.69 3.33 3.31 3.43 3.39 3.49 3.38 0	0	0		0	8
	Botryococcus Cosmarium bioculatum Dinobryon divergens v. schauinslandii Kirchneriella Oedogonium Rhabdogloea Tetraedron caudatum R0781 Scenedesmus ecornis 0,20 Botryococcus braunii Cosmarium depressum Dinobryon sertularia Korshikoviella Oocystis Rhizosolenia Tetraedron incus R0999 Volvox globator		7 30 13 51 11 35 43 180 145 107 22 191 5 4	2.52 3.15 3.26 2.78 2.52 3.30 2.99 0 3.39 3.38 3.02 4.17 3.42 2.08 3.76 0	0 0	0 0	y = -0,4565x + 1,2354 0 R 2 = 0,5793 0	8 8
	0,00 Carteria Crucigenia Dinobryon sociale Lagerheimia Oocystis borgei Rhizosolenia longiseta Tetraedron minimum R1622 Pseudanabaena mucicola		147 36 244 42 3 16 221	2.86 2.67 3.17 3.75 2.20 2.67 2.85 0	0	0		0	8
	0 Ceratium Crucigenia quadrata Dinobryon sociale v. americanum 0,5 Lagerheimia subsalsa Oocystis lacustris Rhodomonas Tetraselmis cordiformis R0503 Chlorella sp.	1	LogTP 47 20 15 14 163 301 33	1,5 3.89 2.91 2.76 2.42 3.09 3.69 2.85 0	0	0	2	0	2,5 8
	Ceratium cornutum Crucigenia tetrapedia Dinobryon sociale v. stipitatum Limnothrix Oocystis marssonii Rhodomonas lacustris Tetrastrum triangulare R0020 Aulacoseira ambigua		33 103 52 14 78 413 26	3.95 2.65 3.50 2.76 2.29 3.37 2.92 0	0	0		0	9
	Ceratium furcoides Crucigeniella Elakatothrix Limnothrix redekei Oocystis parva Rhodomonas lens Trachelomonas R0500 Characium sp.		5 21 150 10 21 200 125	2.10 3.40 3.36 3.13 2.92 3.00 3.18 0	0	0		0	9
	Ceratium hirundinella Crucigeniella rectangularis Elakatothrix gelatinosa Lyngbya Oocystis solitaria Rhodomonas minuta Trachelomonas oblonga R1610 Planktolyngbya limnetica		657 49 132 17 7 22 3	3.44 3.04 2.88 3.82 2.85 2.82 2.85 0	0	0		0	9
	Chamaesiphon Cryptomonas Elakatothrix genevensis Lyngbya limnetica Oscillatoria Scenedesmus Trachelomonas volvocina R0028 Aulacoseira italica		4 606 33 18 104 193 95	2.41 3.35 3.60 3.53 3.26 2.62 2.79 0	0	0		0	10
	Chlamydocapsa planktonica Cryptomonas Erkenia subaequiciliata Mallomonas Oscillatoria limosa Scenedesmus acutus Tribonema R0930 Chlamydocapsa planctonica		19 3 117 344 22 12 4	1.98 2.66 3.05 3.27 3.28 2.54 2.36 0	0	0		0	10
	Chlamydomonas Cryptomonas curvata Eudorina Mallomonas acaroides Pandorina Scenedesmus costato-granulatus Ulothrix		384 38 14 80 15 3 21	3.41 2.98 2.15 3.12 1.81 2.56 1.94
	Chlamydomonas globosa Cryptomonas erosa Eudorina elegans Mallomonas akrokomos Pandorina morum Scenedesmus ecornis Ulothrix subconstricta		23 201 77 102 116 37 16	2.71 2.98 2.47 3.12 2.76 2.42 2.66
	Taxon Chlamydomonas reinhardtii Cryptomonas erosa var. reflexa Euglena Mallomonas caudata Pediastrum Scenedesmus linearis Uroglena	Frequency 37 8 76 116 20 45 293	TIk 2.22 2.59 3.32 2.80 2.78 2.99 3.40		vi
	Amphora Chlorella Cryptomonas marssonii Euglena acus Mallomonas crassisquama Pediastrum boryanum Scenedesmus obtusus Uroglena americana		11 68 339 24 4 221 42 51	3.14 2.39 3.18 2.47 3.49 2.55 2.37 2.69		2
	Amphora ovalis Chlorella vulgaris Cryptomonas obovata Eunotia Mallomonas elongata Pediastrum duplex Scenedesmus quadricauda Uroglena volvox		25 62 63 20 71 142 127 22	3.33 2.60 3.85 2.88 3.24 2.69 2.87 3.19		4
	Anabaena Chlorolobion Cryptomonas ovata Eutetramorus Mallomonas tonsurata Pediastrum simplex Schroederia setigera Volvox aureus		73 62 263 31 13 23 47 17	3.27 3.49 2.81 3.10 3.30 3.72 2.54 2.15		1
	Anabaena circinalis Choricystis Cryptomonas reflexa Eutetramorus fottii Melosira varians Peridiniopsis Snowella Willea irregularis		18 14 42 133 80 14 3 56	2.87 3.15 2.52 3.01 2.76 3.21 3.47 3.32		1
	Anabaena flos-aquae Choricystis chodatii Cryptomonas rostratiformis Eutetramorus planktonicus Merismopedia Peridinium Snowella lacustris Woronichinia naegeliana		221 12 127 22 45 471 216 33	3.15 3.38 2.72 3.54 3.19 3.53 3.80 2.97		1
	Anabaena planctonica Chromulina Cryptomonas tetrapyrenoidosa Fragilaria Merismopedia glauca Peridinium aciculiferum Sphaerocystis		46 151 3 132 8 61 19	2.19 3.19 2.27 3.49 3.13 3.05 2.53		4
	Anabaena solitaria Chroococcus Cyanodictyon planktonicum Fragilaria berolinensis Merismopedia tenuissima Peridinium bipes Sphaerocystis schroeteri		5 118 11 6 60 7 125	1.85 3.46 3.45 3.63 2.34 3.15 2.74		4
	Anabaena sphaerica Chroococcus limneticus Cyclotella Fragilaria capucina Merispomedia tenuissima Peridinium cinctum Sphaerozosma		3 122 467 81 4 80 28	3.29 3.46 3.69 3.08 3.03 3.13 3.13		4
	Anabaena spiroides Chroococcus minimus Cyclotella bodanica Fragilaria construens Micractinium pusillum Peridinium inconspicuum Spirulina		75 6 92 43 21 139 8	3.47 3.41 3.81 3.29 2.38 3.39 3.22		3
	Anabaena viguieri Chroococcus minutus Cyclotella comensis Fragilaria crotonensis Microcystis Peridinium palatinum Staurastrum		5 82 197 538 157 5 196	2.30 3.54 3.87 3.39 3.45 2.73 3.02		4
	Ankistrodesmus Chroococcus turgidus Cyclotella comta Fragilaria ulna Microcystis aeruginosa Peridinium pusillum Staurastrum chaetoceras		67 19 3 134 173 55 26	3.00 3.32 2.33 3.33 3.17 3.80 3.32		1

Table A .

 A 14 Reference value and EQR value for class boundaries high/good (H/G) and good/moderate (G/M) for Biovolume, Chlorophyll-a and Brettum index for both Slovenian Lakes

	Lake	National Type	IC Type	Range	Ref	Chlorophyll-a H/G	G/M	Ref	Biovolumen H/G	G/M	Ref	Brettum-Index H/G	G/M
	Lake Bled	Prealpine	L-VL3	3	1,50	0,7	0,4	0,20	0,6	0,25	5,29	0,827	0,654
	Lake Bohinj	Alpine	L-VL3	1	1,90	0,7	0,4	0,30	0,6	0,25	5,09	0,827	0,654

Table A

 A

	.15	Recalculation EQRi to normalised nEQR values
	EQRi		nEQRi
	≥ 1		1
	≥ EQRH/G		(EQRi -EQRH/G) / (1 -EQRH/G) * 0.2 + 0.8
	EQRH/G > EQRi ≥ EQRG/M	(EQRi -EQRG/M) / (EQRH/G -EQRG/M) * 0.2 +
			0.6
	EQRG/M > EQRi ≥ EQRM/P	(EQRi -EQRM/P) / (EQRG/M -EQRM/P) * 0.2 +
			0.4
	EQRM/P > EQRi ≥ EQRP/B	(EQRi -EQRP/B) / (EQRM/P -EQRP/B) * 0.2 + 0.2
	< EQRP/B		EQRi / EQRP/B * 0.2
	Table A.16	The final boundary values
	Ecological status	MM_FPL
	Very good	≥0,80
	Good	0,60 -0,80
	Moderate	0,40 -0,60
		Poor	0,20 -0,40
		Bad	<0,20

Table B .

 B 1 List of important REFCOND pressures and potential pressure indicators for each type of pressure per water category.

	Tiered approach
	Tier 1	Rivers	Lakes	Transitional	Coastal
	Type of pressure	Pressure indicators Artificial land use,	Type of pressure	Pressure indicators Artificial land use,	Type of pressure	Pressure indicators Artificial land use,	Type of pressure	Pressure indicators Artificial land use,
	1. Point source		population density,	1. Point source	population density,	1. Point source	population density,	1. Point source	population density,
	pollution		oxygen, phosphate,	pollution	oxygen, phosphate,	pollution	oxygen, phosphate,	pollution (from rivers +	oxygen, phosphate,
			nitrogen		nitrogen		nitrogen	coastline)	nitrogen
	2. Diffuse source		Agriculture land use,	2. Diffuse source	Agriculture land use,	2. Diffuse source	Agriculture land use,	2. Diffuse source	Agriculture land use,
	pollution		phosphate, nitrogen	pollution	phosphate, nitrogen	pollution	phosphate, nitrogen	pollution (from rivers	phosphate, nitrogen
	3. Riparian zone		Riparian use, riparian	3. Riparian zone	Riparian use, riparian	3. Riparian zone	Riparian use, riparian	and costline) 3. Shoreline	Shoreline ocupation,
	vegetation		composition, riparian	vegetation	composition, riparian	vegetation	composition, riparian	modification/harbours	continuity between
			longitudinal and lateral		longitudinal and lateral		longitudinal and lateral	in supralittoral/	coastal perimeter and
			connectivity		connectivity		connectivity	terrestrial	natural settings
	4. Morphological		Sediment transport, river	4. Hydromorphological	Quantity and dynamics of	4. Hydromorphological	Quantity and dynamics of	4. Hydromorphological	Changes in
	alterations		continuity,	alterations	flow, water level,	alterations	flow, water level,	alterations in littoral	deposition/erosional
			channelisation, bank		residence time,		residence time,	and sublittoral	areas, groyns
			stabilisation, siltation,		goundwater connection,		goundwater connection,
			river profile, absence of		depth variation, substrate		depth variation, substrate
			weirs & dams		and structure of shore		and structure of shore
					zone		zone
	5. Water abstraction		Abstraction below a	5. Water abstraction	Abstraction below a
			threshold		threshold
	6. River flow regulation No dams influencing
			natural flow regime,
			storage and seasonal
			patterns not influenced
	7. Biological		No invasive species, no	7. Biological	No invasive species, no	7. Biological	No invasive species, no	7. Biological	No invasive species, no
	pressures		biomanipulation, no	pressures	biomanipulation, no	pressures	biomanipulation, no	pressures	biomanipulation, no
			intensive fishery		intensive fishery		intensive fishery		intensive fishery
			/aquaculture		/aquaculture		/aquaculture		/aquaculture
	8. Other pressures		No intensive recreational	8. Other pressures	No intensive recreational	8. Other pressures,	No intensive recreational	8. Other pressures	No intensive recreational
			use		use	recreational	use		use

Table B .

 B 3 Supporting specific reference criteria for the selection of RCL for the BQE phytoplankton in Alpine lakes.

	Pressure	Pressure	Criteria
		indicators
	Eutrophication Land use in the	>80-90% natural forest, wasteland, moors,
		whole catchment	meadows, pasture (CLC classes 3.1.1, 3.1.2, 3.1.3,
		area	3.2, 3.3, 4 and 5)
			No (or insignificant) intensive crops, vines (CLC
			classes 2.1, 2.2, 2.4.1, 2.4.2)
			No (or insignificant) artificial areas (CLC class 1)
			No deterioration of associated wetland areas

This publication is a Technical Report by the Joint Research Centre of the European Commission.

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This publication is a Technical Report by the Joint Research Centre, the European Commission's in-house science service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication.

JRC88125

EUR 26485

Italy: Italian classification method for phytoplankton in lakes Summary

This document outlines how status is assigned for the biological quality element phytoplankton and how boundaries have been assigned in Italy. The metrics included in the Italian phytoplankton assessment method developed for Alpine lakes are the biomass metrics chlorophyll a and total biovolume and the taxonomic composition metric PTIot. The reference value and HG boundary for each metric and each type were set from the median and the 90 th %ile of the AlpGIG reference sites (lake-years) respectively. The GM, MP and PB metric boundaries were set using equidistant class widths on a log scale. ter Braak & Verdonschot (1995): Canonical Correspondence analysis and relate multivariate methods in aquatic ecology. Aquatic sciences 57/3. Slovenia: Metodologija vrednotenja ekološkega stanja jezer s fitoplanktonom v Sloveniji (Ecological status assessment system for lakes using phytoplankton in Slovenia)

Overview

There are only two natural lakes >50 ha in Slovenia. Both are in the Alpine region and the same IC L-AL3 type. According to the national tipology, Lake Bled belongs to the deep prealpine type and Lake Bohinj to the deep alpine type of lakes. Base for differentiation is different biogeographical region. Slovenia adopted AT phytoplankton method during the process of intercalibration. The only adaptation of AT method for Slovenian lake conditions relate to the sampling depth, all other important things i.e. reference conditions and class boundaries are the same as in AT methodology.

Sampling and data analysis (sampling frequency, depth etc)

Sampling frequency: At the defined sampling points minimal 4-times per year; 1 sampling during spring homothermic period is obligatory.

Sampling depth: integrated water samples from the euphotic zone = 2,5 X Secchi depth; in cases when the euphotic zone exceed 20 m, sampling is carried out from the surface to the depth of 20 m.

Metrics and calculation of final EQRs

Code Taxon Trophic class (as TP in µg L -1 ) <=5 5-8 8-15 15-30 30-60 >60 R2503 Achnanthidium catenatum

Code Taxon Trophic class (as TP in µg L -1 ) <=5 5-8 8-15 15-30 30-60 >60 R0966 Gonium pectorale

B. Tiered approach to define harmonized reference criteria for the Alpine GIG

Tier 2

Reference criteria for the pressure 'hydro-morphology' at whole lake level as well as at sampling site (transect) level are defined as proposed by the macrophyte group in phase 1 of the IC exercise. They take into account water level fluctuations, eutrophication effects of local point sources and local shore line modifications. The other BQE will adopt these criteria.

A 'conversion' of criteria valid for sampling sites to criteria valid for the whole lake is proposed in this document.

The near surrounding is defined as a stripe around the lake between the shore line (0 m) and a distance of 100 to 300 m. Analyses carried out by J. Böhmer (unpubl.) on lakes in the Central Baltic revealed little difference in the general pattern of land use when using a small (0-100 m) or a broad (0-300 m) stripe. The conditions at local scale are derived for a zone of of 50-100 m shore length. A 'conversion' of the criteria 'direct local nutrient input near the sampling site' and 'modifications of the shore line at the sampling site' to whole lake level is not necessary, since possible effects on the trophic state are covered already by the criteria listed in Table B.2. The same is true for the criterion 'recreational use of the water body'.

Additional to the criteria listed in Table B.4, reference condition sites (RCS) for macrophytes should not be situated near tributaries, which may change the typical pattern of the macrophyte community structure.

Tier 3

The reference criteria for the pressure 'eutrophication' and 'hydro-morphological alterations' as defined by the phytoplankton and the macrophyte group Table B.2 and Table B.4) are adopted as specific reference criteria for selecting RCL for benthic invertebrates in the littoral and sublittoral zone. The criteria aiming at the pressure 'hydro-morphological alterations' are not relevant for profundal invertebrates, hence, for this group only the criteria listed in Table B.2 (pressure 'eutrophication') are adopted as specific criteria.

However, additional specific criteria are required for the profundal fauna. They take into consideration the fact that the profundal benthic fauna often shows a delay in recovery from eutrophication. During re-oligotrophication processes, the epilimnetic flora and fauna may show near-natural conditions already, whereas the profundal fauna lags behind and mirrors higher trophic conditions (e.g. [START_REF] Lang | Decreasing phosphorus concentrations and unchanged oligochaete communities in Lake Geneva: how to monitor recovery?[END_REF][START_REF] Lang | Oligochaetes versus chironomids as indicators of trophic state in two Swiss lakes recovering from eutrophication[END_REF][START_REF] Wolfram | Distrubution pattern of benthic invertebrate communities in Traunsee (Austria) in relation to industrial tailings and trophy[END_REF].

Another criterion concerns a change on the mixing behavior, which may cause oxygen depletion in the hypolimnion (e.g. artificial meromixis and development of an anoxic monimolimnion). This can be a result from eutrophication (which then is covered by other criteria already) or by mining activities (e.g. salt intrusion in Lake Hallstätter See). A deviation from natural oxygen conditions is also used as criterion in spite of matching the eutrophication criteria in Table B.2, since it may be caused by other insufficiently known pressures, such as organic pollution. It seems, however, difficult to set a threshold for O2 concentration (above ground vs hypolimnion, extent vs duration of O2 deficiency etc.).

Hence, this criterion is used by expert judgment. The reference criteria for the pressure 'eutrophication' and 'hydro-morphological alterations' as defined by the phytoplankton and the macrophyte group (Table B.2 and Table B.4) as well as the additional specific criteria for the profundal benthic fauna (Table B.6) are adopted as specific reference criteria for selecting RCL for fish, since this BQE inhabits all lake zones and is thus prone to all anthropogenic alterations described above.

Two additional criteria have to be added specifically for fish: the connectivity of tributaries and the outflow, and effects from intensive fisheries and aquaculture (including intensive stocking of indigenous and/or non-indigenous species).

Overview on reference criteria

The BQE specific criteria for selecting reference condition sampling sites (macrophytes and littoral/sublittoral invertebrates) and reference condition lakes are summed up to give the general criteria for selecting reference lakes (Table B.9). The scheme in In total, 83 lake assessment methods were submitted for the 2nd phase of the WFD intercalibration (2008)(2009)(2010)(2011)(2012) and 62 intercalibrated and included in the EC Decision on Intercalibration (EC 2013). The intercalibration was carried out in the 13 Lake Geographical Intercalibration Groups according to the ecoregion and biological quality element. In this report we describe how the intercalibration exercise has been carried out in the Alpine Lake Phytoplankton group.