water framework directive intercalibration technical...

Report EUR 26510 EN

20 14

Leonard Sandin, Ann-Kristin Schartau,

Jukka Aroviita, Fiona Carse, David Colvill,

Ian Fozzard, Willem Goedkoop, Emma Göthe,

Ruth Little, Ben McFarland, Heikki Mykrä

Edited by Sandra Poikane

Northern Lake Benthic invertebrate

ecological assessment methods

Water Framework Directive Intercalibration Technical Report

European Commission

Joint Research Centre

Institute for Environment and Sustainability

Contact information

Sandra Poikane

Address: Joint Research Centre, Via Enrico Fermi 2749, TP 46, 21027 Ispra (VA),

Italy

E-mail: [email protected]

Tel.: +39 0332 78 9720

Fax: +39 0332 78 9352

http://ies.jrc.ec.europa.eu/

http://www.jrc.ec.europa.eu/

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

European Commission.

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European Commission’s in-house science service.

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JRC88340

EUR 26510 EN

ISBN 978-92-79-35465-6 (pdf)

ISBN 978-92-79-35466-3 (print)

ISSN 1831-9424 (online)

ISSN 1018-5593 (print)

doi: 10.2788/74131

Cover photo: Sandra Poikane

Luxembourg: Publications Office of the European Union, 2014

© European Union, 2014

Reproduction is authorised provided the source is acknowledged.

Printed in Ispra, Italy

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 Northern

Benthic invertebrate ecological assessment methods.

Contents

1. Introduction ............................................................................................................................ 2

2. Description of national assessment methods ............................................................ 2

3. Results WFD compliance checking ................................................................................ 9

4. Results IC Feasibility checking ...................................................................................... 12

5. IC dataset .............................................................................................................................. 15

6. Common benchmarking ................................................................................................. 16

7. Design and application of the IC procedure ........................................................... 18

8. Description of the biological communities and changes along pressure

gradient ................................................................................................................................. 22

Annexes

A. Northern lake GIG Benthic invertebrate assessment methods ......................... 26

B. Exclusion of abundance and diversity metrics of benthic invertebrate

assessment systems ........................................................................................................... 47

1. Introduction

In the Northern Lake Benthic invertebrates Geographical Intercalibration Group (GIG):

Four Member States (Finland, Norway, Sweden and UK) submitted seven benthic

invertebrates assessment methods (as Sweden submitted 3 methods and UK – 2

methods, addressing different human impacts);

After evaluation of feasibility, two groups of methods were included in the IC

exercise: two methods evaluating profundal eutrophication (SE BQI and FI BQI)

and three methods - littoral acidification (SE MILA, NO MultiClear and UK LAMM);

Reference sites selected by pressure criteria were used for common

benchmarking;

Intercalibration “Option 3” was used - direct comparison of assessment methods,

for littoral acidification method pseudo-common metric (average of MS EQRS)

was used;

The comparability analysis show that acidification methods give a closely similar

assessment (in agreement to comparability criteria defined in the IC Guidance),

so no boundary adjustment was needed, for eutrophication methods a slight

adjustment of boundaries was necessary;

The final results include EQRs of SE and FI benthic invertebrates assessment

systems (SE BQI and FI BQI) for eutrophication (clear and humic low alkalinity

lake types) and NO, SE and UK systems for acidification (only clear water type).

2. Description of national assessment methods

In the Northern Benthic invertebrates GIG, four countries participated in the

intercalibration with 5 finalised benthic invertebrate lake assessment methods (Table 2.1,

more details in Annex A).

Table 2.1 Overview of the national lake benthic invertebrate assessment methods in the

Northern GIG.

MS Method Status

Lake littoral acidification

NO MultiClear: Multimetric Invertebrate Index

for Clear Lakes (lake acidification)

Intercalibratable finalized national

method

SE MILA: Multimetric Invertebrate Lake

Acidification index (lake acidification)

Finalized agreed national method

UK LAMM (lake acidification) Finalized agreed national method

Lake eutrophication

FI BQI (profundal eutrophication) Finalized agreed national method

SE BQI (profundal eutrophication) Finalized agreed national method

SE ASPT: Average Score per Taxon (littoral

eutrophication)


UK CPET: Chironimidae Pupal Exuviae

Technique (all-lake eutrophication)


Methods and required BQE parameters

Not all parameters required by the WFD Annex V were included in all the methods, see

below description and explanation:

FI BQI - diversity not included;

SE ASPT - relative abundance not included, SE BQI -diversity not included, SE

MILA - includes all parameters;

NO MultiClear - includes all parameters;

UK LAMM - diversity not included, UK CPET - diversity and abundance not

included.

Table 2.2 Overview of the metrics included in the national benthic invertebrates

assessment methods

MS

metho

d

Taxonomic

composition Abundance

Disturbance

sensitive taxa Diversity

FI BQI Benthic Quality Index

(BQI)

RA included

BQI Not included

SE

ASPT

Average Score per

Taxon

RA not included

(see footnote)

Average Score per

Taxon

Not included

SE BQI Benthic Quality Index RA included

Benthic Quality

Index

Not included

SE

MILA

Relative abundance (%)

of Ephemeroptera


Diptera


of predators

RA included

British AWIC index

Number of

mollusc taxa

(Gastropoda)

Number of

mayfly taxa

NO

MultiCl

ear

Acidification indicator

taxa

AWIC-family index

Adj. Henriksson and

Medin’s index

RA included

Acidification

indicator taxa

AWIC-family index

Adj. Henriksson

and Medin’s index

Number of

snail

(Gastropoda)

Number of

mayfly

(Ephemeropte

ra) taxa

UK

LAMM

Lake Acidification

Macroinvertebrate

Metric

RA included

Lake Acidification

Macroinvertebrate

Metric

Not included

UK

CPET

CPET RA not incl CPET Not included

1 RA: Relative abundance (abundance of single taxa or groups relative to the total

abundance of macroinvertebrates or groups of macroinvertebrates)

Abundance was not directly used in the assessment methods:

Rhis parameter is known to be highly variable in aquatic invertebrate

communities (Resh, 1979; Barbour et al., 1992; Resh and Jackson, 1993; Johnson,

1998);

Invertebrate abundance was the least informative of ten metrics tested by Sandin

and Johnson (2000) as it had the lowest effect size (a measure of the magnitude

of impact) and highest spatial, temporal and sample variability;

Invertebrate abundance is rarely, if ever, used in ecological assessment due to the

difficulties associated with detecting anthropogenic change with any degree of

confidence (Osenberg et al., 1994).

Diversity: not included in SE and FI BQI methods

Some of the methods do not explicitly take diversity into account. Regarding

eutrophication, the BQI indices of Sweden and Finland both take abundance and number

of sensitive and insensitive taxa into account. The reason for not including a measure of

diversity is that from a theoretical ecological point of view the diversity at low nutrient

levels and medium-high nutrient levels should be similar, whereas at medium nutrient

levels the diversity will actually be increased (a hump-shaped relationship). At very high

nutrient levels, the diversity will of course decrease. Thus there is not a continuous (always

going in the same direction) and/or linear pressure-response relationship and therefore

diversity is not suitable for inclusion in a profundal eutrophication metric for benthic

macroinvertebrates. See e.g. Tolonen (2005) who found a unimodal relationship between

taxa richness and trophic gradient, possibly indicating that intermediate disturbance

enhances species richness (Cornell and Lawton, 1992), and unpublished results on

Swedish data (McGoff & Sandin). In addition, BQI explains a substantial amount of the

whole natural macroinvertebrate community variation in lake profundal (see e.g.

Jyväsjärvi et al. 2009).

Diversity: not included in UK methods

The UK methods for lakes do not include explicit diversity measures as the metrics that

are included in the current metrics more than adequately describe the pressures. A

diversity metric (or sub metric) would not improve the methods response to, or

discrimination of pressure and status. Some testing of this has been done as part of the

NGIG intercalibration work, where a large number of indicators were correlated with the

pressures pH, and ANC. In these analyses explicit diversity measures very rarely came out

with statistical significant relationships to the acidification pressure.

See also Annex B (analysis of IE data showing that abundance is too variable to be

included in the benthic invertebrate assessment systems).

Sampling and data processing

FI BQI: One occasion per sampling season: September to October. Six replicate

samples are taken from the deepest point of lake.

SE BQI: One occasion per sampling season: September to October. Five Ekman samples

are collected from a 100 m2 area in the middle of the lake (or over the deepest region).

SE MILA: One occasion per sampling season: September to November. Standardized

Kick-sampling, SSEN-27828 (20 s x 1 m; 0,5 mesh; 5 replicates taken in autumn).

Substratum is disturbed by kicking for 20 s and moving a distance upstream of 1 m

NO Multiclear: Preferably two occasions per sampling season: April to May and October

to November. A sample consists of one or several sampling units taken from preferably

one habitat type at the sampling site. The hand-net of 200-300 µm mesh-size is used as

'kick-net'. Sediments must be disturbed to a depth of 15 cm (where possible) depending

on substrate compactness.

SE ASPT: One occasion per sampling season: September to November. Wind exposed

hard bottom (stony) substrates. Standardized kick-sampling. Substratum is disturbed by

kicking for 20 s and moving a distance upstream of 1 m (20 s x 1 m; 0,5 mesh; 5 replicates

taken in autumn).

UK LAMM: 2 samples are taken in each spring survey (March-June). One spring survey

is enough for classification. However, 3 year’s data will reduce uncertainty in classification.

To apply the method, invertebrates should be collected from a stony-bottomed section

of the littoral zone of the lake with a depth of 75 cm. Two samples should be collected

from each location sampled. Sampling should normally be undertaken between March

and May. The invertebrates should be collected by disturbing the substratum with the

feet ("kick sampling") and passing a hand net (nominal mesh size: 1 mm) through the

water above the disturbed area. All habitats in the chosen sampling site should be

sampled within a 3-minute period. In addition, a pre-sample sweep to collect surface

dwelling invertebrates and a post sample manual search, lasting one minute, should be

undertaken during which any invertebrates attached to submerged plant stems, stones,

logs or other solid surfaces should be collected by hand and placed in the net.

See Annex A for details.

2.1. National reference conditions

FI BQI: Existing near-natural reference sites, 80 sites from the whole Finland. Data has

been collected between 1992 and 2006.Reference criteria: No point source pollution,

percentage of agriculture within catchment less than 15 %.

SE ASPT: Existing near-natural reference sites, ca 300, whole of Sweden.Use of pressure

filter to identify reference conditions.

SE BQI: Existing near-natural reference sites, ca 110, whole of Sweden. Use of pressure

filter to identify reference conditions.

SE MILA: Existing near-natural reference sites, ca 300, whole Sweden.

Reference conditions for MILA (Multimetric Index for Lake Acidification) indices were

established using a pressure filter approach, i.e. lakes and streams judged to be

perturbed using catchment land use and water chemistry (Johnson and Goedkoop 2007

(in Swedish)) were removed to isolate the gradient of interest. For example, to calibrate

the response of MILA to acidity we excluded sites affected by pressures such as

eutrophication, liming, urbanization etc to isolate the “acidity” gradient.

NOR MULTICLEAR: Existing near-natural reference sites, 7 lowland and boreal lakes

belonging to the low alkalinity clear lakes in Southern Norway (South coast and Eastern

parts), Rural areas in South-Eastern part of Norway (counties: Akershus, Hedmark),

Southernmost part of Norway (county: Aust-Agder) and Mid-Norway (county: Sør-

Trøndelag). Data from non impacted lakes, 2007-2009.

Pressure criteria: < 10% intensive agriculture, <1% artificial land use, < 10 p.e./km2

pop.dens., no acid load exceedance. Chemical criteria: ANC (Acid Neutralizing Capacity)

> 30 µeq/L, pH > 6. Biological criteria

UK LAMM: Existing near-natural reference sites, Expert knowledge, Historical data,

Modelling (extrapolating model results)

Reference sites: 8 sites for clear-water lakes, 6 for humic-water lakes, representative lakes

throughout UK at risk from acidification

Reference sites screened using the Damage matrix. See table 6.1 in /'Macroinvertebrate

Classification Diagnostic Tool Development/' SNIFFER Report WFD60. This matrix

assesses sites based on their Acid Neutralising Capacity (ANC) in relation to Ca content.

2.2. National Boundary setting

The description of national boundary setting procedures in detail, graphs showing dose-

relationships and description of high, good and moderate communities are to be found

in Annex A.

FI BQI: Boundaries are derived as follows: H/G = 0.75, G/M = 0.60, M/P = 0.30, and P/B

= 0.10

SE ASPT: Equidistant division of the EQR gradient.

SE BQI: Equidistant division of the EQR gradient.

SE MILA:

The reference value was defined as the median MILA index value of unperturbed

sites stratified by type (here defined simply by ecoregion);

EQR values for the reference population were calculated as observed value

divided by reference (established by typology) value;

The borderline between High and Good status was defined as the 25th percentile

of the distribution of the reference data;

A threshold approach was used for setting the Good/Moderate boundary. EQR

MILA values normalized for ecoregion differences were regressed against mean

annual pH and the intercept at pH 5.6 was used as the borderline between

Good and Moderate quality. A pH value of 5.6 was selected since many

previous studies have shown marked changes in fish and invertebrate

assemblages at this threshold (e.g. Johnson et al. 2007). In addition, variability in

the regression supports this threshold; variance appears to collapse (funnel

shaped response) at around pH below 6.0 (Figure 2.1);

The remaining class boundaries were set using equidistance.

Nor Multiclear

The H/G boundary: assigned to represent the lower 5th percentile of scores for all

reference sites (i.e. that 95 % of all sites identified as reference sites are assigned to high

ecological status). At present this value represent all reference sites since the number of

reference sites are so few (N=7).

The H/G boundary value on the MultiClear scale has been set to 4.0 (absolute value)

representing an EQR = 0.95.

Figure 2.1 EQR values of MILA regressed against mean annual pH. The different colors

reflect the three main ecoregions (regions14, 22 and 20), the different symbols

show reference (crosses) and putative acidified (circles).

The G/M boundary and the subsequent boundaries: The boundaries G/M, M/P and

P/B are based on the exponential relationship between MultiClear and AcidIndex1

(Forsuringsindeks 1; see www.vannportalen.no) which in turn represent an equidistant

division of the subsequent EQR gradient (from Good to Bad). The reason for this

approach is that

1. The relationship between AcidIndex1 and MultiClear is clear and strong (R2 =

0.95);

2. The relationship between acidification and changes in AcidIndex1 are also clear

and strong; R2 = 0.6 with pH as the predictor variable;

3. AcidIndex1 has been widely used in Norway for more than 20 years and proven

reliable;

4. The borders between the categories based on AcidIndex1 are easily defined and

based on changes in ecosystem structure in accordance with the normative

definitions by the Water Framework Directive (WFD; 2000/60/EC).

AcidIndex1 is a very simple index based on the presence or absence of selected indicator

taxa assigned as very tolerant (score=0), slightly sensitive (score=0.25), moderately

sensitive (score=0.5) and highly sensitive to acidification (score=1). The value of the index

varies between 0 and 1. A value of zero means that (slightly, moderately or highly) acid

sensitive macroinvertebrates are absent. A value of one means that at least one specimen

of the most (highly) acid-sensitive taxa is present. However, a score of one based on a

single individual from one sample may constitute an unreliable result. Therefore, in the

Norwegian assessment method, assigning the ecological status is based on mean index

values calculated from at least four, preferably more samples, including both spring and

autumn samples.

For AcidIndex1 the G/M boundary has been set to 0.75 (absolute value). Based on the

relationship between AcidIndex1 and MultiClear, the G/M boundary value on the

MultiClear scale has been set to 3.13 (absolute value) representing an EQR = 0.74 (Table

3.1).

Figure 2.2 MultiClear vs AcidIndex1 (RADDUM1) for Norwegian low alkalinity, clear lakes

(non-linear regression, N=15).

UK LAMM:

Using discontinuities in the relationship of anthropogenic pressure and the biological

response.

Where discontinuities could not be found then partitioning based on the Damage Matrix

was used.

Detailed description of boundary setting procedure, pressure-response relationship and

communities at high, good and moderate status is given in McFarland et al. (2009).

Distinct discontinuities along the ANC pressure gradient were only found at humic sites

at ANC 23 µeq/l to derive a good-moderate boundary. These were consistent using

pressure metrics (e.g. LAMM), diversity measures (e.g. Shannon) and functional groups

(e.g. grazers). Where no consistent breakpoints/step-changes were found, sites were

grouped by the damage matrix according to class. The mean LAMM scores of the two

adjacent classes were then added together and divided by two to form the boundary.

Conclusions on boundary setting :

Finland BQI:

Based on deviation from reference condition (H/G-boundary = 75 % of

reference value);

statistical (not equidistant) division of the EQR gradient;

Norway MultiClear:

The HG boundary was identified as the lower 5th percentile of scores of all

reference sites (due to low number of reference sites this equals to the

whole reference population; small adjustments may be necessary when

more data is available);

GM = the point where only 50 % of the samples from a site contain very

sensitive taxa and the remaining 50 % of the samples contain moderately

sensitive taxa;

Sweden ASPT and BQI: Based on a statistical division of the EQR gradient

(equidistant);

Sweden MILA – using pH 5.6 as the threshold point of GM boundary;

UK CPET: Using paired metrics (relative abundance of sensitive and tolerant taxa)

that respond in different ways to the influence of the pressure;

UK LAMM:

Using discontinuities in the relationship of anthropogenic pressure (ANC)

and the biological response (LAMM, diversity measures and functional

groups).

Where discontinuities could not be found then partitioning based on the

Damage Matrix was used.

3. Results WFD compliance checking

Intercalibration was carried out in 2 separate groups: lake littoral acidification and lake

profundal eutrophication, therefor ethe evaluation of WFD compliance was carried out

separately too.

Lake littoral acidification:

SE, UK, NO national assessment methods comply with requirements of WFD;

IE and FI have little acidification pressure / data and do not have national

methods. In FI, humic lakes can be acidic, but this is a natural phenomenon in

boreal peatlands.

Summary for acidification pressure:

Three countries compliant (SE, UK, NO);

Two countries have no national methods data (IE, FI);

Several of the methods do not include either the parameter abundance, or the

parameter diversity (explanations above,).

Lake eutrophication – profundal:

SE and FI has compliant national assessment methods (SE BQI and FI BQI) using

profundal invertebrates;

The BQI methods do not include the parameter diversity per se (explanations

above considered compliant).

Lake eutrophication – littoral:

SE has compliant national methods using littoral (ASPT) invertebrates.

Lake eutrophication – the whole lake:

UK has a compliant method using chironomid exuviae (CPET).

IE and NO do not have any national method for assessment of lake

eutrophication.

Summary for eutrophication pressure :

Three countries compliant - SE (ASPT and BQI), FI (BQI), UK (CPET).

IE has no method. NO has no method / data.

Table 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

classes (high, good, moderate, poor and

bad).

Sweden; Yes, all metrics have 5 classes.

UK; LAMM for clear waters has 4 classes,

poor/bad combined. LAMM for humic

waters has three classes, moderate, poor,

bad combined. WFD-AWICsp and CPET

have all 5 classes.

Finland; Yes, BQI has 5 classes.

Norway: Yes, all metrics have 5 classes.

2. High, good and moderate ecological status

are set in line with the WFD’s normative

definitions (Boundary setting procedure)

See above

3. All relevant parameters indicative of the

biological quality element are covered (see

Table 1 in the IC Guidance). A combination

rule to combine para-meter assessment

into BQE assessment has to be defined. If

parameters are missing, Member States

need to demonstrate that the method is

sufficiently indicative of the status of the QE

as a whole.

Not all parameters included for all

metrics, see description and explanation

why not all parameters are included.

4. Assessment is adapted to intercalibration

common types that are defined in line with

the typological requirements of the WFD

Annex II and approved by WG ECOSTAT

SE: The Swedish assessment methods

based on macroinvertebrates (lakes and

rivers) does not distinguish between

clear water and humic waters. The

assessment is adapted to

biogeographical differences and the

country is devided into three ecoregions

(Illies 14, 20, and 22).

UK: This is true for LAMM. For WFD-

AWICsp the typology is based on

Scottish humic and clear waters (cutoff

at 10 mg/l) and a Welsh/English

typology. CPET is site specific.

FI: yes; NO: yes

5. The water body is assessed against type-

specific near-natural reference

conditions

SE: yes; UK: yes

FI: Yes. Lakes are assessed against near-

natural reference conditions where

expected (reference) values for BQI are

derived with a regression model for each

site.

NO: yes

6. Assessment results are expressed as EQRs SE: yes; UK: yes; FI: yes; NO: yes

7. Sampling procedure allows for

representative information about water

body quality/ ecological status in space

and time

SE: yes; UK: yes; FI: yes; NO: yes

8. All data relevant for assessing the biological

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


4. Results IC Feasibility checking

Typology

Five common intercalibration types were defined in the Northern GIG (Table 4.1).

Table 4.1 Common intercalibration water body types and list the MS sharing each type

Common IC type Type characteristics MS sharing IC common type

Lake acidification:

IC type 1 & 2: 1 – IC

types from the 1st

round, but

combined

Clear, low alkalinity lake types (L-

N2+L-N5)

Humic, low alkalinity lake types (L-

N3+L-N6)

NO: yes; UK: yes

SE: Intercalibration of humic

lakes did not succeed since the

SE assessment system does not

take differences in reference

values and EQRs among clear

and humic lakes into account.

Lake profundal

eutrophication:

Ecoregion 22, clear and humic, low

alkalinity

SE: yes; FI: yes

Lake littoral

eutrophication


and moderate alkalinity


and moderate alkalinity

SE: yes

Lake acidification:

Intercalibration is feasible for the clear water lakes excluding lakes with very low

calcium levels (Norwegian type exclusively - naturally low proportions of acid

sensitive taxa).

It is not feasible to intercalibrate humic lake types for acidification. The SE

method does not distinguish between clear and humic lakes. Explorations from a

typology perspective showed that the SE data fitted the clear lake typology best

and intercalibration proceeded on this basis.

Lake profundal eutrophication: intercalibration is feasible.

Lake littoral eutrophication: only SE has a lake littoral method.

Table 4.2 Evaluation if IC feasibility regarding intercalibration common types

Method Appropriate for IC types /

subtypes

Remarks

Lake acidification Clear water type

Humic water type

Clear water is feasible, excluding

lakes with very low Ca

concentrations;

Humic waters is not feasible

Lake profundal

eutrophication

Ecoregion 22, clear and humic,

low alkalinity

Intercalibration was restricted to

lakes with area ≥ 1 km2 and

deepest point ≥ 6 m.

Lake littoral

eutrophication


low and moderate alkalinity


low and moderate alkalinity

Only SE had an assessment system

Pressures

Acidification: intercalibration is feasible.

Eutrophication (profundal): intercalibration is feasible

Eutrophication (littoral and all lake assessment) not feasible:

relationships between the pressure (TP or land-use) and littoral invertebrate

communities measured as ASPT were weak albeit significant in ecoregions 14 and

22 in Sweden;

A significant relationship between the pressure (TP) and littoral invertebrate

communities could not be found in the data for IE and UK, therefore no lake

littoral eutrophication intercalibration could be undertaken;

The relationship between CPET and ASPT in the Irish dataset was very low and no

intercalibration could be performed between lake littoral and CPET methods.

Table 4.3 Evaluation if IC feasibility regarding pressures addressed by assessment systems

Method Pressure Remarks

SE: MILA

UK: LAMM

NO: MultiClear

Acidification

(lakes)

Methods address the same pressure: IC feasible

SE BQI (profundal)

FI: BQI (profundal)

Eutrophication

(lakes)

SE and FI BQI address the same pressure: IC feasible

SE: ASPT (littoral)

UK: CPET (whole

lake)

Eutrophication

(lakes)

IC not feasible as:

ASPT (littoral) and BQI (profundal) are not

correlated and thus do not address the same

pressure (ASPT weakly correlated to TP,

whereas BQI is strongly correlated to TP)

ASPT (littoral) and CPET (all lake) address the same

pressure but do not respond in the same way

Table 4.4 Pressure response relationships of national lake assessment methods

MS Method Pressure Pressure

indicators Strenght of relationship

Addification

NO Multi

Clear

AC pH, ANC,

LAl

MultiClear vs pH: R2=0.64, p<0.001, 15 lakes

(other pressure indicators: R2 in range 0.44-

0.49, all significant). Test of difference

between reference / impacted lakes, p<0.00

SE MILA index AC pH MILA vs pH: R2=0.54, EQR MILA vs pH:

R2=0.70, p<0.0001, 70 lakes

All metrics sign correlated with pH (R in

range 0.33-0.70)

UK LAMM AC pH, ANC Clear lakes: LAMM vs ANC: R2= 0.64, LAMM

vs pH: R2= 0.37; Humic lakes: LAMM vs ANC:

R2=0.82, LAMM vs pH: R2=0.80. All tests: p

< 0.001, n=106

MS Method Pressure Pressure

indicators

Strenght of relationship

Eutrophication profunda

FI BQI EU TP R2=0.25-0.35, p<0.05

SE BQI EU TP, other

pressure

indicators

t-test between reference and impacted lakes,

sign with p < 0.005

Eutrophication littoral

SE ASPT EU TP and

land use

Region 14 (see Figure 2.1): ASPT vs Tot-P:

R2=0.22, p< 0.001; ASPT vs agricultural land-

use: R2=0.39, p=0.0174

Region 22: ASPT vs Tot-P: R2=0.15, p<0.001;

ASPT vs agricultural land-use: R2=0.26,

p<0.001

UK CPET EU TP R2=0.78, p<0.001

Pressure response relationships described in table below.

Table 4.5 Evaluation if IC feasibility regarding assessment concepts

Method Assessment concept Remarks

Acidification

MultiClear (NO

acidification lakes)

Littoral (one littoral and one outlet sample is

combined), Stony shorelines, Structural community

features (tax comp, acid sensitive vs tolerant taxa)

Includes both

littoral and

outlet

samples

MILA (SE acidification

lakes)

Littoral, Exposed stony shorelines

Structural community features (acid tolerant and

sensitive taxa)

LAMM (UK

acidification lakes)

Littoral, Exposed stony shorelines

Structural community features (acid tolerant and

sensitive taxa)

Eutrophication

BQI (SE

eutrophication lakes)

Profundal, Soft bottom sediments

Structural community features (sensitive and

tolerant chironomids)

BQI (FI eutrophication

lakes)

Profundal, Soft bottom sediments

Structural community features (sensitive and

tolerant chironomids)

CPET (UK


Whole lake assessment (repr Profundal+Littoral)

Structural community features (chironomid pupal

exuviae)

Represents

different lake

zone

ASPT (SE


Littoral, Exposed stony shorelines Structural

community features (sensitive and tolerant taxa)

Represents

different lake

zone

Assessment concept

The IC is feasible in terms of assessment concepts for:

Lake acidification (Norway uses one littoral and one outlet sample combined, but

it is still possible to intercalibrate, since UK and SE uses one littoral sample;

Lake eutrophication (profundal).

The IC is not feasible in terms of assessment concepts for lake eutrophication (littoral and

all lake assessment) as the two methods (ASPT, CPET) represent two different concepts

regarding pressure responses.

5. IC dataset

Huge dataset was collected within the Northern GIG (Table 5.1).

Table 5.1 Overview of the Northern GIG benthic invertebrates IC dataset

Member State Number of sites or samples or data values

Biological data Physico- chemical data Pressure data

Lake acidification (clear type)

NO 15 lakes 15 lakes 15 lakes

SE 14 lakes 14 lakes 14 lakes

UK 75 lakes 75 lakes 75 lakes

Lake eutrophication profundal

FI 196 lakes 196 lakes 196 lakes

SE 25 lakes 25 lakes 25 lakes

Table 5.2 Data acceptance criteria used for the data quality control

Data acceptance criteria Data acceptance checking

Data requirements (obligatory and

optional)

A rule based system for the matching of biological and

chemical data has been set up for lake and river

acidification based on a specific number of chemistry

samples (2 or 4) within the year before the biological

sample. This requirement is obligatory. For lake

profundal only “deep” (sampling depth ≥ 6 m) lakes

with area ≥ 1 km2 were accepted in the final

intercalibration. For lake profundal only one sample was

included from each sampled lake.

The sampling and analytical

methodology

Similar sampling and analysis methods for lake and river

acidification as well as for lake littoral eutrophication

and profundal eutrophication methods. The CPET

method is fundamentally different and intercalibration

of ASPT versus CPET is not possible.

Level of taxonomic precision

required and taxalists with codes

For acidification the taxonomic precision required are

agreed, based on the countries operational taxalists

used in national monitoring schemes

Data acceptance criteria Data acceptance checking

For lake profundal eutrophication the same taxonomic

precision is used by both SE and FI

The minimum number of sites /

samples per intercalibration type

We have at least 100 samples in total for each of lakes

and rivers acidification, and for lake profundal.

Sufficient covering of all relevant

quality classes per type

Yes, but for river acidification clear type only SE

reference sites were found in the dataset (thus not

intercalibrated because of lack of a pressure gradient in

the dataset. No for lake profundal eutrophication (poor

and bad classes do not exist in the dataset).

6. Common benchmarking

Selection of reference lakes was common approach used IC bencgmarking.

Common referene criteria

Setting reference criteria was based on:

summarizing what types of pressure data were available from the different

countries

comparing and agreeing on common reference condition cut off values for these

pressures,

screening the individual countries data using the national reference criteria

screening the whole dataset using a set of common reference criteria

Eutrophication Lakes - Reference sites must meet the following criteria:

Agriculture <10% agriculture in catchment

Forestry: <10% catchment consists of commercial plantations or clear cut areas

Urbanisation: < 0.1% urbanised areas

Hydromorphological: No regulation on lake water level

Invasive species: No invading plant or animal species that may negatively impact

the structure, productivity, function and diversity of the ecosystem

Point Source: No major point source pollution

Acidification: Lakes must not be subjected to anthropogenic acidification

Shore morphology: No artificial modification of littoral zone within 100m of

sampling site

Other pressures: No fish farms, no limed lakes

Acidification Lakes:

Reference sites must meet the same criteria as for lake eutrophication

The reference criteria also include national acidification pressure information

such as pH, ANC, labile ANC and TOC.

All data were screened using the UK damage matrix to rule out any sites that

were possibly not commonly seen as references. Very few (<5 lakes were

removed using the common criteria).

Reference sites

Number of reference sites was sufficient to make a statistically reliable estimate:

lake littoral acidification (clear: 26 reference sites);

lake eutrophication/profundal (78 reference sites).

Screening of Reference sites:

UK: Sites believed to be reference status chemically were screened according to

the WFD definition of reference community status. This was done using lists of

acid sensitive taxa with a minimum number of acid sensitive taxa required to be

present for a site to pass. Further taxonomic analysis was undertaken to establish

reference communities for the different subtypes. This was then checked using

functional trait analysis. Mcfarland (2010) (Unpub) & Mcfarland et al (2009) give

further details of biological reference screening.

NO: The communities of the sites have to correspond with the description of the

reference community. Otherwise the site is checked more thoroughly to exclude

the possibility that the site is impacted by other known or unknown pressures.

Eventually the site is excluded as a reference site.

With the strict physical and chemical criteria SE and FI did not screen the

biological data to identify sites as affected. This was to avoid the circular

reasoning in identifying references based on the biology and then use this

information in a biological assessment. We are relatively confident that the SE

and FI data meet reference criteria considering the extensive list of physical and

chemical screening parameters used (see above), which also indirectly includes

other pressures (e.g. amount of agricultural land in the catchment related to

possible pesticide contamination of the ecosystem).

Description of setting reference conditions

All countries have used summary statistics (mean, median or percentile values or a site

specific model (FI)) to derive reference values for each lake and river type. As a common

exercise the biological data (in terms of metric values) for the identified reference sites

were tested for differences among countries using ANOVA analyses.

6.1. Benchmark standardisation

Lake profundal eutrophication:

We tested for differences between SE and FI reference sites for both FI BQI and SE BQI

metrics (EQR values):

Using the SE BQI there was no difference between countries sites (p > 0.05),

whereas using the FI BQI method there was a statistically significant difference

between the two countries sites (p < 0.0005).

The main difference is that the FI BQI method takes sampling depth into account.

Also, in the FI dataset the variation in the EQR reference values was larger in the

relatively shallow lakes than in the deeper lakes. The SE dataset includes only

relatively shallow lakes. Low reference EQR values were not present in the SE

dataset.

Benchmark standardisation was applied to the FI method so that the EQRs were

divided by the corresponding median EQR at benchmark sites, as described in IC

Guidance Annex V.


We tested whether benchmark standardisation was necessary using the SE, UK, and NO

clear lake typology dataset. The reference data (NO = 7, SE = 10, UK = 9) was used and

each countries method was calculated using the data also from the other two countries.

ANOVAs were used to compare the reference values for the three countries and the three

methods. There were no statistical difference for either the Swedish MISA method or the

Norwegian Multiclear method (p > 0.05), there was however, a difference for the UK

LAMM method (p < 0.005) where UK had significantly higher LAMM scores for the

reference data than SE and NO. Because of this we used the benchmark standardisation

that is done in the Excel sheet for option 3 where the class boundaries are standardised

and normalised.

Table 6.1 Comparison of EQRs at reference sites, NO, SE and UK.

UK LAMM

(med EQR of ref site)

NO Multiclear


SE MILA


NO 0.74 1.00 0.91

SE 0.65 0.81 0.76

UK 0.93 0.99 0.74

Total 0.77 0.92 0.079

P 0.003 0.113 0.616

7. Design and application of the IC procedure

IC option:

Lake acidification: IC option 3 (direct comparison of site assessment by different

assessment systems);

Lake profundal eutrophication: IC option 3b (comparison on 2 methods via

regression);

IC Common metric:

Lake acidification: PCM, the pseudo common metric calculated by the Excel

intercalibration spreadsheets, no other common metric has been used

Lake profundal eutrophication: since SE and FI both use versions of the BQI

index, no common metric is needed.

Lake profundal eutrophication:

The BQI national metric was calculated on both SE and FI data (Pearson r

between the 2 methods' EQRs = 0.66, p < 0.001, N=221).

Benchmark standardisation was applied to the FI method so that the EQRs were

divided by the corresponding median EQR at benchmark sites, as described in IC

Guidance Annex V (r = 0.68, p < 0.001, N=221).

The national EQRs were compared with each other using the Excel template

provided by JRC in November 2011;

In the template, a piecewise linear rescaling of class boundaries to allow

comparisons of the assessment systems is done. The relationships were used to

calculate the boundary differences in EQRs. The boundary bias is the deviation

from the global mean which in this case was the average of the two countries.

The biases were (marked red as > 0.25 boundary bias)

Table 7.1 Correlation coefficients (r) and the probability (p) for the correlation of each

method with the common metric

Member State/Method r p

Lake acidification (PCM)

SE/MILA 0.45 <0.001

UK/LAMM 0.66 <0.001

NO/MultiClear 0.75 <0.001

Lake eutrophication profundal (BQI)

FI and SE EQR-BQI 0.64 < 0.001

Table 7.2 Comparability criteria values for NGIG benthic invertebrates profundal

eutrophication methods

Boundary FI

average

class bias

SE

average

class bias

FI excess

as classes

FI

harmonized

boundary

SE excess

as classes

SE

harmonized

boundary

GM -0.480 0.362 0.23 (0.621)

0.634*

0.112 0.672

HG -0.097 0.540 0 no change 0.29 0.842

*Boundary transformed back to original boundaries

The boundary comparisons indicate that the following changes in member state class

boundaries are required to meet the level of acceptability given in IC Guidance Annex V

(≤ 0.25) for the methods to be intercalibrated:

Finland has a lower G/M boundary than Sweden (and thus Finland needs to

change G/M boundary from EQR=0.6 to EQR=0.634;

Sweden has a higher G/M boundary than Finland and thus Sweden needs to

change its G/M boundary from EQR=0.7 to EQR=0.672;

For the H/G boundary, Finland meets level of acceptability and no change is

needed;

For the H/G boundary Sweden needs to change its H/G boundary from EQR=0.9

to EQR=0.842;

The mean absolute class difference based on 3 classes between SE and FI methods was

0.45 (based on 5 classes 0.58), and thus indicates the level of acceptability given in IC

Guidance Annex V (≤1.0 class difference).


The intercalibration was done according to Option3 and PCM, the pseudo common

metric calculated by the Excel intercalibration spreadsheets, were used as the common

metric.

After plotting values of the PCM (each country separate) against the pressure gradient it

seemed like differences between countries diminished with an increasing pressure.

Therefore benchmark standardization was made according to the division method.

Regression characteristics were fulfilled (except R for SE MILA method, explanation

provided)

The intercept was acceptable for all three metrics when correlated with the PCM

(< 0.30);

The slope was acceptable for the SE and UK methods, whereas it was a little bit

too low for the NO data (0.44);

The Pearsons r was acceptable for NO and UK, whereas it was a little bit too low

for the SE method (0.45). There is also a warning that the Min R² is < 0.5 Max R².

The Swedish MILA index is a multimetric index to assess acidification effects in the lake

littoral. In the intercalibration with UK (using the LAMM index) and Norway (using the

Multiclear index), the MILA index had a lower correlation to the PCM than the other two

indices. As the Intercalibration Guidance suggest a Pearson r value above 0.5 to be

included in the intercalibration exercise, the relatively low MILA Pearson r (0.45) was

therefore discussed and evaluated during the last intercalibration meeting in the NGIG

WG macroinvertebrates. It was then agreed that :

The relationship between the MILA EQR and the PCM was clearly similar (positive

relationship) in comparison with the two other indicators,

The difference (0.45 vs 0.5) was relatively small,

The IC guidance is a recommendation not based on any specific scientific

evidence or testing that there would be a specific threshold at a Pearson r of 0.5

and that the intercalibration exercise would be negatively affected by a value

lower than that.

Compliance criteria:

the H/G and G/M boundary bias was acceptable for all assessment methods (<

0.25 class difference);

The mean absolute class difference between SE, NO and UK varies between 0.52

and 0.63 (average 0.57) and thus indicate the level of acceptability given in IC

Guidance Annex V (≤1.0 class difference).

Table 7.3 Comparability criteria values for NGIG benthic invertebrates littoral acidification

methods

Comparability

criteria Allowable limit UK-LAMM

NO-

MULTICLEAR SE-MILA

H/G boundary bias From -0.25 to 0.25 0.15 -0.05 -0.06

G/M boundary bias From -0.25 to 0.25 -0.02 -0.02 0.06

Absolute Class

Difference 1.0 (preferably 0.5) 0.52 0.53 0.63

In summary, the boundary comparisons indicate that the following changes:

Lake profundal eutrophication – FI BQI needs to change G/M boundary from

EQR=0.6 to EQR=0.63,

Lake profundal eutrophication - SE BQI needs to change its H/G boundary from

EQR=0.9 to EQR=0.84; G/M boundary from EQR=0.7 to EQR=0.67;

Lake littoral acidification (clear type): All 3 methods complied, no adjustments

needed

Table 7.4 Final H/G and G/M boundary EQR values for the national methods

Member

State

Classification Ecological Quality Ratios

Method High-good boundary Good-moderate

boundary

Common metric

Lake profundal - eutrophication

SE BQI 0.84 0.67

FI BQI 0.75 0.63

Lake littoral acidification

SE MILA 0.85 0.60

UK LAMM 0.86 0.70

NO Multiclear 0.95 0.74

The intercalibration types essentially fitted the national subtypes, thus no transformation

is needed to include the results into the national assessment systems with the exception

of the boundary changing details above.

Gaps of the current Intercalibration:

Pressures: hydromorphological impacts not covered.

Intercalibration types: All pressure types: high altitude lakes and river types (> 800 m)

not covered. Lake acidification: humic lakes not included in current IC. Lake

eutrophication: large lakes and very shallow lakes (< 6 m maximum depth) not included.

Habitats not covered: lake littoral not included (eutrophication). SE lake littoral method

(ASPT) not intercalibrated.

8. Description of the biological communities and changes along

pressure gradient

Biological changes along pressure gradient

UK: Lake acidification: The UK uses an abundance weighted index based on acid

sensitive/tolerant taxa. Essentially the response of the index below the high/good

boundary is essentially smooth with no obvious discontinuities – boundaries below this

are set using the UK Acid damage matrix. Essentially numbers and presence of acid

sensitive taxa decline linearly (together with a concomitant increase in tolerant taxa

abundance & N Species) below the H/G boundary –status in each of the classes is then

determined by faunal composition at demonstrated levels of chemical (ANC/Ca) damage.

River acidification: A variety of discontinuities in biological community responses were

used to develop boundaries for the UK method including overall abundance, functional

trait analysis and pressure/WFD AWIC response. Boundaries were verified using the UK

Acid Damage matrix. Detail of taxonomic composition at each status class can be found

in

NO: Lake and river acidification: Taxonomical richness and proportion of acid sensitive

macroinvertebrates (belonging to Hirudinea, Gastropoda, Bivalvia, Crustacea,

Ephemeroptera or Trichoptera) decreas with increasing pressure (decreasing pH and

ANC, increasing concentration of labile aluminium). At good status the majority of

samples containe specimens of highly sensitive macroinvertebrates. Exceedance of the

critical limit for the most sensitive taxa (G/M boundary) are followed by a rapid decrease

in the proportion of sensitive taxa towards a dominance of acid tolerant taxa (M/P). At

poor status no highly sensitive taxa of Hirudinea, Gastropoda, Bivalvia, Crustacea,

Ephemeroptera or Trichoptera is present in any of the samples representing the site.

SE: Lake acidification: Number of taxa of snails (Gastropoda) markedly decreases at pH

6.3, whereas the number of taxa of mayflies (Ephemeroptera) shows a steadily decrease

in relation to pH. The abundance of mayflies (Epehemeroptera) also shows a decrease in

relation to pH with a threshold around pH 6.3.

River acidification: Several of the indicators in the MISA acid river index showed a non-

linear response to pH, e.g. number of species of gastropoda, the abundance ratio of

mayflies and stoneflies individuals.

Lake profundal eutrophication: a non-linear relationship between the BQI and total P was

found when developing the Swedish Ecological Quality Criteria for lake profundals. See

also section 8.2.

Lake littoral eutrophication: the ASPT indexwas linearly related to water column total

phosphorus concentration and catchment land use classified as agriculture.

FI: Lake profundal eutrophication: The structure of profundal macroinvertebrate

assemblages and also BQ-index shows a depth-dependent continuous change along

eutrophication impairment gradient. For many of the indicator taxa in BQI this is

described in section 8.2.

Description of the biological communities at reference sites

Lake profundal eutrophication: Basin depth is a predominant factor that influences the

natural (i.e. reference) variation of boreal lake profundal macroinvertebrate communities

(see e.g. Jyväsjärvi et al 2009). Discrete benchmark communities need to be therefore

described by taking lake depth into account. In shallow lake basins with maximum depth

< 10 m and minor anthropogenic disturbance, typical components of the profundal fauna

are chironomid midges larvae such as Zalutschia zalutschicola, Cladopelma viridula,

Tanytarsus spp., Chironomus plumosus and Chironomus anthracinus and phantom

midges (Chaoborus spp.). In deeper profundal basins (depth range around 10-40 m)

representing nearly or totally undisturbed conditions, chironomid larvae such as

Sergentia coracina, Stictochironomus rosenschoeldi, Monodiamesa bathyphila,

Heterotanytarsus apicalis and Protanypus morio, oligochaete worms (e.g. Spirosperma

ferox), mussels (Pisidium spp.) and water mites are typical inhabitants. In basins with

depth over 40 m representing reference conditions, chironomid larvae such as

Paracladopelma nigritula, Micropsectra spp., Procladius spp and Heterotrissocladius

subpilosus and oligochaete worms Stylodrilus heringianus, Lamprodrilus isoporus,

Potamothrix hammoniensis / Tubifex tubifex and crustacean Monoporeia affinis and

Pisidium spp. mussels are typical components of the profundal fauna.

Lake littoral eutrophication: Littoral lake communities at reference status are often

typified by Heptageniidae (e.g. Heptagenia fuscogrisea), Capniidae (e.g. Capnia sp.) and

Leptophlebiidae (Leptophlebia sp.) mayflies and Phryganeidae caddisflies. All of these

taxa are given a score of 10 according to Armitage et al. (1983), resulting in high ASPT

values. Other important constituenst are Asellus aquaticus and chironomid midge larvae.

Since many Swedish lakes are situated in boreal forested catchments, electrical

conductivity is generally low, resulting in the low richness and abundance of gastropods.

Lake acidification (clear lakes): Clear lake communities at reference status are

dominated by Dipteran (Typically Chironomidae), Trichopteran, Crustacea & Plecopteran

taxa. Other important components in these typically lentic faunas include molluscs,

Hemipterans & leeches.

Description of biological communities at good ecological status

Lake profundal eutrophication: The structure of profundal macroinvertebrate

assemblages shows a depth-dependent continuous change along eutrophication

impairment gradient. The composition and abundance of profundal macroinvertebrate

assemblages that represent quality class "good" show only slight changes from the

reference communities. In shallow lakes with maximum (i.e. sampling) depth < 40 m, the

communities typically include Chironomus-larvae C. plumosus and C. anthracinus.

Chironomus plumosus is usually absent at high status class but present at moderate

status class, whereas Chironomus anthracinus may often be absent or occur at low

numbers at moderate status. Pisidium spp. mussels are usually present. Sergentia

coracina may be absent at good status. In deep lakes (max depth >40 m) good status

assemblages typically include Sergentia coracina, Stictochironomus rosenschoeldi and C.

anthracinus (but not C. plumosus) whereas Heterotrissocladius subpilosus and

Micropsectra spp. may be absent. From oligochaetes, Spirosperma ferox is present,

whereas Stylodrilus heringianus and Lamprodrilus isoporus may be missing at good

status.

Lake littoral eutrophication: At “Good” status is typified by ASPT values between 0.7

and 0.9 for ecoregions 14 and 22, whilst for the northernmost region (ecoregion 20) the

borderline is set to 0.45. The families Capniidae, Leptophlebiidae, and Phryganeidae are

commonly found in unperturbed lakes, resulting in high ASPT scores (these taxa each

score 10 according to Armitage et al. 1983).

Lake acidification (clear lakes): At “Good” Status faunas are still dominated by diptera

(once again dominated by Chironomidae), however Ephemeropterans assume increasing

importance at this status – with large numbers of Leptophelebiids. Crustaceans and

molluscs are reduced in abundance from reference status and decline toward the G/M

boundary.

References

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macroinvertebrates. (Eds. D.M. Rosenberg and V.H. Resh) Pages 195 – 223. Chapman and

Hall. New York.

Sandin, L. and Johnson, R.K., 2000. The statistical power of selected indicator metrics

using macroinvertebrates for assessing acidification and eutrophication of running

waters. Hydrobiologia 422: 233–243.

Tolonen, KT; Holopainen, IJ; Hamalainen, H; Rahkola-Sorsa, M; Ylostalo, P; Mikkonen, K;

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Intercalibration of biological elements for lake water bodies

14/01/2014 Page 26 of 48

Annexes

A. Northern lakes GIG: Benthic invertebrates

Finland: Finnish lake profundal macroinvertebrate method:

Benthic Quality Index [Pohjanlaatuindeksi]

General information

Pressures addressed: Eutrophication. The index is tested against total P with many

different data sets. In general, there has been statistically significant (p < 0.05)

relationship, but the amount of explained variation has been rather low (25 -35 %).

Pertinent literature of mandatory character: Pintavesien ekologisen luokittelun

vertailuolot ja luokan määrittäminen. Finnish Environment Institute, Finnish Game and

Fisheries Research Institute 2009.

Scientific literature: Jyväsjärvi, J., J. Nyblom & H. Hämäläinen, 2009. Palaeolimnological

validation of estimated reference values for a lake profundal macroinvertebrate metric

(Benthic Quality Index). Journal of Paleolimnology (in press). Wiederholm, T., 1980. Use

of benthos in lake monitoring. J. Wat. Pollut. Cont. Fed. 52: 537?547.

Field sampling/surveying

Six replicate samples are taken from the deepest point of lake using Ekman grab.

Sampling/survey month: September to October, one occasion per sampling season. 6

replicates are taken with surface area = 250-300 cm2 per Ekman-grab sample.

Minimum size of organisms sampled and processed: 500 µm

Data evaluation

List of biological metrics: Site-specific prediction of expected value of Benthic Quality

Index with linear regression using lake mean depth or log(sampling depth) as predictor

variable.

Different type-specific and site-specific approaches have been tested for prediction of

expected values for BQI. Best performing approach (currently used) was selected based

on its precision and performance in detection of impairment.

Reference conditions

Key source(s) to derive reference conditions: : Existing near-natural reference sites

Number of sites: 80. Geographical coverage: Whole Finland. Data time period: Data has

been collected between 1992 and 2006. Criteria: No point source pollution, percentage

of agriculture within catchment less than 15 %.

Boundary setting

Boundaries are derived as follows: H/G = 0.75, G/M = 0.60, M/P = 0.30, and P/B = 0.10

Pressure relationships has not been used in setting the class boundaries.

Norway: Multimetric assessment method for acidification

of clear lakes (MultiClear) – a Norwegian assessment

system for lake acidification

General information

Status of the method

The metric Multimetric assessment method for acidification of clear lakes (MultiClear)

was developed by the Northern GIG WG Macroinvertebrates (McFarland et al.,

unpublished). The metric was tested as one of several potential common intercalibration

metrics for the intercalibration of national lake assessments methods across Northern

Europe. For Norway this method was adopted as a preliminary national method of choice

for inter-calibration purposes the 8th November 2010. It will be included in the first

revision of the classification guidance document (official publication) in autumn 2012.

Lake types

The method is tested only for clear (humic content: < 30 mg/L; TOC: > 5 mg C/L) and low

alkalinity lakes (calcium content: 1-4 mg/L; alkalinity: 0.05-0.2 meq/L) below the upper

tree line (<800 m a.s.l.). According to the IC typology this covers the lake types L-N2 and

L-N5 but excluding lakes with very low alkalinity (calcium content: <1 mg/L; alkalinity:

<0.05 meq/L).

According to the Norwegian typology several national lake types are included; i.e. lakes

of all size and depth categories in addition to the categories of humic content, alkalinity

and altitude specified above. Nevertheless, the use of the method should be restricted

to Eastern Norway and the Southern coast of Norway. Due to data scarcities the method

has not been tested for other eco-regions. At the same time, these other eco-regions are

not affected by acidification or do not contain the relevant lake types.

Surveying guidelines

General

Water bodies to which the MultiClear applies must be sampled at least twice a year (April-

May and October-November). For each date one sample from the littoral and preferably

one from the outlet river are taken. Both samples may include several "sampling units",

depending of the distribution of the preferred substrate. Results from these two samples

are pooled before the macro-invertebrate parameters are calculated. Adjusted reference

value and boundaries are established for the purpose to assess lakes for which samples

from outlet river is missing.

Littoral macro-invertebrate samples are sampled according to:

ISO 7828 Water quality - Methods of biological sampling - Guidance on hand-net

sampling of aquatic benthic macro-invertebrates

National specification of the surveying method is given in:

Guidance document 02:2009 Monitoring of environmental status in waters.

Guidance on aquatic monitoring in accordance with the Water Framework

Directive, version 1.5. (Direktoratsgruppa Vanndirektivet 2009a).

Sampling

A sample consists of one or several sampling units taken from preferably one habitat

type at the sampling site.

Preferably hard bottom substrate incl. stones/cobbles are sampled but also soft bottom

incl. fine substrate/detritus if areas with hard bottom are limited.

From each sampling site (lake’ littoral, outlet river) 2-3 min. kick sampling, depending on

the abundance of macroinvertebrates, are conducted.

The hand-net (200-300 µm mesh-size) is used as 'kick-net'. Sampling starts by gently

sweeping the surface within the targeted area by hand to dislocate surface-dwelling

animals and sweeping them into the net (if the habitat consists of cobbles, stones,

pebbles). The remaining substrate is disturbed by foot to dislodge sediment and

organisms into the water column and the net is wept through the suspended cloud of

sediment to capture the dislodged animals. Sediments must be disturbed to a depth of

15 cm (where possible) depending on substrate compactness. Large debris are rinsed

from animals in the field and as much water as possible are excluded from the sample.

The sample is preserved with 96% alcohol to a final concentration of about 70%.

Sample processing

The sample is carefully homogenized prior to sub-sampling. A fraction of the sample, for

instance one eights, is processed and the individual macroinvertebrates identified. A

minimum of 200 organisms (preferably 300) are analysed. Only rare and hitherto

unobserved species is recorded and enumerated when processing the following sub-

samples. This procedure should be repeated until the whole sample has been processed.

In addition, the fractions on which the recordings are based need to be noted for

subsequent abundance estimations. n.a.

Level of taxonomical identification: Tricladida (class: Turbellaria), Hirudinea, Gastropoda,

Bivalvia (except Pisidium), Crustacea (except Copepoda and Cladocera), Ephemeroptera,

Plecoptera, Trichoptera (except Hydroptilidae), Megaloptera, Elmidae (and other

Coleoptera if adults) to species level. Other taxa to genus level except for Chironomidae

and Simuliidae, which are identified to family level, and Oligochaeta which are identified

to class level.

The record of abundance is given as number of individuals per sample (in addition

sampling time is indicated).

Parameter description and calculation

Metrics

MultiMetric is a multi-metric index that is based on (i) the acidification indicator taxa as

agreed within the Northern GIG and (ii) four macroinvertebrate metrics:

1. Number of snail (Gastropoda) taxa

2. Number of mayfly (Ephemeroptera) taxa

3. AWIC-family (Acid Water Indicator Community, family-level version): mean score of

all scoring families represented in a sample. The score of the individual taxa, and of

the index itself, ranges from 1 to 6.

4. NGIG adjusted Henriksson and Medin’s index: the list of indicator taxa has been

adjusted compared to the original index. The score of the index ranges from 0 to 14.

This index is in itself a multi-metric index and composed of the following metrics:

4.1 EPT (Ehpemeroptera, Plecoptera, Trichoptera) indicator taxa scores. The score ranges

from 0 to 3.

4.2 Presence of Gammaridae and Crangonyctidae*. If present, the score has been set to

3.

4.3 Presence of a) Hirudinea, b) Elmidae, c) Gastropoda and d) Unionidae and

Margaretiferidae. The score of each group has been set to 1.

4.4 Relative abundance of sensitive Ephemeroptera belonging to the genera Baetis,

Alainites, Labiobaetis*, Nigrobaetis (sometimes all classified as Baetis) compared to

Plecoptera, The relative abundance is calculated from the number of individuals; the

score ranges from 0 to 2.

4.5 Number of taxa present relative to a standardized list of taxa. The score ranges from

0 to 2.

The metrics are combined in the following way:

For each of the four metrics the original score is rescaled: the clear lakes metric scores

(Cs) may obtain the values 1, 3, or 5. For instance, a NGIG adjusted Henriksson and

Medin’s metric score (HMs) of zero or one is set to Cs = 1, a HMs value of two is set to

Cs = 3, and any HMs value exceeding two is set to Cs = 5. MultiClear is calculated as the

sum of the rescaled score of individual clear lakes metric divided by the number of clear

lake metrics (in this case four metrics).

4

CsmetricClearMulti

Hence, the numerical values of the acidification index MultiClear may vary from a

minimum of 1 to a maximum of 5. A score of 5 can only be obtained if all four constituent

metrics have a score of 5.

The assessment is based on mean values, calculated from at least four samples, including

both spring and autumn samples from two years or more.

Assessment system

Reference sites

Criteria for selection of reference sites followed a national approach including pressure

criteria as well as chemical criteria:

Pressure criteria: < 10% intensive agriculture, <1% artificial land use, < 10 p.e./km²

pop.dens., no water level regulation, no artificial modification of littoral zone, no acid

load exceedance

Chemical criteria: ANC (Acid Neutralizing Capacity) > 30 µeq/L, pH > 6

In the final evaluation of potential reference sites biological criteria have been used only

to ensure that no other pressures (unknown or non-detectable) were present, meaning

that the communities of the sites had to correspond with the description of the reference

community description.

Dose-response relationship

The applicability of MultiClear, as well as other candidate macroinvertebrate metrics, for

assessment of lake’ acidification has been evaluated by Schartau & Petrin (2010). Below

follows a short summeray of the results most relevant for the establishment for reference

value and boundaries.

Fifteen clear Norwegian lakes that were sampled during summer and autumn between

2007 and 2009 were included in the data set. The lakes were classified by their

acidification status (acidified vs. reference) and characterized by the acidification related

chemical variables. Multiple ANOVAs and regression analyses were employed to study

the effects of the reference state and the different water chemistry variables, respectively,

on the acidification metrics.

Acidification showed a clear and strong effect on the value of the MultiClear index as well

as the more simple macroinvertebrate metric AcidIndex1 (see description below) (Table

A.1 and Table A.2). pH was consistently the strongest predictor of acidification (Table A.2,

Figure A.1).

Table A.1 Summary statistics of the effects of acidification status (acidified vs. reference

sites) on macro-invertebrate metrics. ANOVA was used to test the difference.

Macroinv. metric R2

(adjusted) p-value

MultiClear 0.928 <0.001

AcidIndex1 0.800 <0.001

Table A.2 Summary statistics of the effects of acidification (pH, ANC1: Acid Neutralizing

Capacity – ion balance method, ANC3: Acid Neutralizing Capacity - Cantrell

method; LAl: Labile aluminum) on macro-invertebrate indices MultiClear and

AcidIndex1 for Norwegian low alkalinity, clear lakes. Regression analysis was

used to estimate the relationship.

Macroinv. metric Chemical variable F ratio R2 (adjusted) p-value

MultiClear pH 25.9 0.640 <0.001

ANC1 14.2 0.485 0.002

ANC3 13.2 0.465 0.003

LAl 11.8 0.436 0.004

AcidIndex1 pH 22.3 0.603 <0.001

ANC1 8.9 0.361 0.011

ANC3 9.4 0.374 0.009

LAl 9.8 0.386 0.008

Reference value

All together seven (7) lakes fulfilling the typology criteria (see section 1) and the reference

criteria (see section 4 above) was used as basis for assigning the reference conditions.

The reference value was set as the mean of all reference sites (Table A.3).

Boundary setting

The H/G boundary was assigned to represent the lower 5th percentile of scores for all

reference sites (i.e. that 95 % of all sites identified as reference sites are assigned to high

ecological status). At present this value represent all reference sites since the number of

reference sites are so few (N=7).

The G/M boundary and the subsequent boundaries M/P and P/B are based on the

exponential relationship between MultiClear and AcidIndex1 (Forsuringsindeks 1 or

Raddum1; see www.vannportalen.no) which in turn represent an equidistant division of

the subsequent EQR gradient (from Good to Bad). The reason for this approach is that 1)

the relationship between AcidIndex1 and MultiClear is clear and strong (R³ = 0.95), 2) the

relationship between acidification and changes in AcidIndex1 are also clear and strong;

R³ = 0.6 with pH as the predictor variable (Table A.2), 3) AcidIndex1 has been widely used

in Norway for more than 20 years and proven reliable, and 4) the borders between the

categories based on AcidIndex1 are easily defined and based on changes in ecosystem

structure in accordance with the normative definitions by the Water Framework Directive

(WFD; 2000/60/EC). AcidIndex1 is a very simple index based on the presence or absence

of selected indicator taxa (see annex 1 in Guidance document 01:2009 (Direktoratsgruppa

Vanndirektivet 2009b; www.vannportalen.no)) assigned as very tolerant (score=0),

slightly sensitive (score=0.25), moderately sensitive (score=0.5) and highly sensitive to

acidification (score=1). The value of AcidIndex1 varies between 0 and 1 (see Figure A.2).

A value of zero means that (slightly, moderately or highly) acid sensitive macro-

invertebrates are absent. A value of one means that at least one specimen of the most

(highly) acid-sensitive taxa is present. However, a value of one based on a single

individual from one sample may constitute an unreliable result1.

Figure A.1 Norwegian macroinvertebrate index for assessment of lake acidification; EQR

MultiClear vs pH for Norwegian low alkalinity, clear lakes included in the IC

exercise (N=15). Blue dots: reference site; Red dots: non-reference site.

For AcidIndex1 the G/M boundary has been set to 0.75 (absolute value). This means that

sensitive taxa of macro-invertebrates are present in all samples and highly sensitive taxa

are present in more than half of the samples representing a site in good status (no sample

may include only slightly sensitive or very tolerant taxa). At the G/M boundary the highly

sensitive taxa are replaced by less sensitive and tolerant taxa. Based on the relationship

between AcidIndex1 and MultiClear, the G/M boundary value on the MultiClear scale has

been calculated to 3.13 (absolute value) representing an EQR = 0.74 (Table A.3).

1The AcidIndex1 do not satisfy all the criteria required by the WFD regarding assessment methods. For

instance, it is not possible to establish a reference value for AcidIndex1and an index value = 1 is considered

not to be reliable enough to distinguish between god and high status. Therefore, the reference- and the H/G

value of MultiClear are established by another approach (see above).

Figure A.2 MultiClear vs AcidIndex1 (RADDUM1) for Norwegian low alkalinity, clear lakes

(non-linear regression, N=15).

Table A.3 Norwegian classification system for acidification of lakes based on littoral

macro-invertebrate assemblages.

AcidIndex1 abs.

value MultiClear abs. value MultiClear EQR

Reference value n.a. 4.21 1

Boundaries

H/G 4.00 0.95

G/M 0.75 3.13 0.74

M/P 0.5 2.58 0.61

P/B 0.25 2.31 0.55

References

Direktoratsgruppa Vanndirektivet 2009a. Guidance document 02:2009 Monitoring of

environmental status in waters. Guidance on aquatic monitoring in accordance with the

Water Framework Directive, version 1.5. The directorate group for implementation of the

Water Framework Directive in Norway. (In Norwegian).

Direktoratsgruppa Vanndirektivet 2009b. Guidance document 01:2009. Classification of

environmental status in waters. Ecological and chemical classification system for coastal

waters, ground waters, lakes and rivers. The directorate group for implementation of the

Water Framework Directive in Norway. (In Norwegian).

http://www.vannportalen.no/enkel.aspx?m=31151&amid=1657299 (date: 24.09.2012)

Schartau, A.K. & Petrin, Z. Development of a Norwegian classification system for lakes’

acidification using littoral macroinvertebrates. Note to the Norwegian Directorate for

Nature Management, dated 13.10.2010 (not published).

Sweden: Swedish lake littoral macroinvertebrate method:

Average Score per Taxon

General information

Detected pressure: General degradation

Pertinent literature of mandatory character: Johnson, R.K. & W. Goedkoop, 2007.

Bedömningsgrunder för bottenfauna i sjöar och vattendrag ? Anväändarmanual och

bakgrundsdokument, Swedish University of Agricultural Sciences, Report 2007: 4, 84p.

[Background report for benthic fauna in lakes and watercourses - User manual and

background document]. Report 2007: 4. Department of Environmental Analysis Swedish

University of Agricultural Sciences (SLU).

Scientific literature: Armitage, P.D., D. Moss, J.F. Wright & M.T. Furse, 1983. The

performance of a new biological water quality score system based on macroinvertebrates

over a wide range of unpolluted running-waters. Water Research 17: 333-347.


Sampling/Survey guidelines: Standardized Kick-sampling using handnet SSEN-27828 (20

s x 1 m; 0.5 mesh; 5 replicates taken in autumn). Substratum is disturbed by kicking for

20 s and moving a distance upstream of 1 m. Specification of sampled habitat: Wind

exposed hard bottom (stony) substrates.

Sampling/survey months: September to November, One occasion per sampling season,

5 replicates per site. The sampling device: kicknet 0.25 (width of kick net) x 1 m with 0.5

mm mesh size

Data evaluation

ASPT exploits the differences in tolerance among different families of benthic

macroinvertebrates and the order Oligochaeta (earthworms). Very sensitive families give

high indicator values, while those with high tolerance give low indicator values. The index

value for ASPT is a mean value for included taxa and is calculated by adding indicator

values and dividing them by the number of included taxa (families).

Indicator values for ASPT for different families.

Indicator value 10

Aphelocheiridae, Beraeidae, Brachycentridae, Capniidae,

Chloroperlidae, Ephemeridae, Ephemerellidae, Goeridae,

Heptageniidae, Lepidostomatidae, Leptoceridae,

Leptophlebiidae, Leuctridae, Molannidae, Odontoceridae,

Perlidae, Perlodidae, Phryganeidae, Potamanthidae,

Sericostomatidae. Siphlonuridae, Taeniopterygidae

Indicator value 8

Aeshnidae, Astacidae, Agriidae, Cordulegasteridae,

Corduliidae, Gomphidae, Lestidae, Libellulidae,

Philopotamidae, Psychomyiidae

Indicator value 7

Caenidae, Limnephilidae, Nemouridae,

Polycentropodidae, Rhyacophilidae (incl. Glossosomatidae)

Indicator value 6

Ancylidae, Coenagriidae, Corophiiidae, Gammaridae,

Hydroptilidae, Neritidae, Platycnemididae, Unionidae,

Viviparidae

Indicator value 5

Chrysomelidae, Clambidae, Corixidae, Curculionidae,

Dendrocoelidae, Dryopidae, Dytiscidae, Elminthidae,

Gerridae, Gyrinidae, Haliplidae, Heledidae,

Hydrophilidae (incl Hydraenidae), Hydropsychidae, Hygrobiidae,

Hydrometridae, Mesoveliidae, Naucoridae, Nepidae,

Notonectidae, Planariidae, Pleidae, Simuliidae, Tipulidae (inkl. Pediciidae)

Indicator value 4

Baetidae, Piscicolidae, Sialidae

Indicator value 3

Asellidae, Erpobdellidae, Glossiphoniidae, Hirudidae,

Hydrobiidae, Lymnaeidae, Planorbidae, Physidae,

Sphaeriidae, Valvatidae

Indicator value 2

Chironomidae

Indicator value 1

Oligochaeta

The ecological quality ratio (EQR) is calculated as follows:

EQR = calculated ASPT / reference value


Key source(s) to derive reference conditions: Existing near-natural reference sites

Number of sites: ca 300. Geographical coverage: whole of Sweden. Location of sites: whole

of Sweden Data time period: 2000 national survey and Trend Streams (national

monitoring programme). Criteria: Use of pressure filter to identify reference conditions.

Reference community description: Littoral lake communities at reference status are often

typified by Heptageniidae (e.g. Heptagenia fuscogrisea), Capniidae (e.g. Capnia sp.) and

Leptophlebiidae (Leptophlebia sp.) mayflies and Phryganeidae caddisflies. All of these

taxa are given a score of 10 according to Armitage et al. (1983), resulting in high ASPT

values. Other important constituenst are Asellus aquaticus and chironomid midge larvae.

Since many Swedish lakes are situated in boreal forested catchments, electrical

conductivity is generally low, resulting in the low richness and abundance of gastropods.

Boundary setting

Setting of ecological status boundaries: Equidistant division of the EQR gradient

Pressure response relationships

The reference value was defined as the median ASPT index value of unperturbed sites

stratified by type (here defined simply by ecoregion). EQR values for the reference

population were calculated as observed value divided by reference (established by

typology) value. The borderline between high and good ecological quality was set as the

25th-percentile of the reference distribution of EQRs. The remaining class boundaries

were set using equidistance.

Table A.4 ASPT classification system for littoral benthic invertebrate assemblages of

Swedish lakes. Modified from Johnson and Goedkoop (2007).

Central Plains

(region 14, n =44)

Fennoscandian Shield

(region 22, n=195)

Reference value 5.85 5.8

Uncertainty

(median s for EQR in

ecoregion)

0.057 0.07

High ≥ 0.95 ≥ 0.90

Good 0.70 – 0.95 0.70 – 0.90

Moderat 0.50 – 0.70 0.45 – 0.70

Poor 0.25 – 0.50 0.25 – 0.45

Bad < 0.25 < 0.25

Figure A.3 Bivariate Fit of EQR_ ASPT with TotP µg/l – Fennoscandian Shield. R2 =0.12,

N=212.

Figure A.4 Bivariate Fit of EQR ASPT with agriculture – Fennoscandian. R2 =0.26, N=44

Figure A.5 Bivariate Fit of EQR ASPT with TotP µg/l – Central Plains. R2 =0.23, N=120

Figure A.6 Bivariate Fit of EQR ASPT with agriculture – Central Plains. R2 =0.39, N=14

"Good status" community:

“Good” status is typified by ASPT values between 0.7 and 0.9 for ecoregions 14 and 22,

whilst for the northernmost region (ecoregion 20) the borderline is set to 0.45. The

families Capniidae, Leptophlebiidae, and Phryganeidae are commonly found in

unperturbed lakes resulting in high ASPT scores (these taxa each score 10 according to

Armitage et al. 1983).

Uncertainty

Uncertainty in classification was established using typology, i.e. both reference and

uncertainty were established for each of the three main ecoregions. In brief, the

probability of misclassification is established using a simple macro and “normal

distribution” function in Excel.

References

Johnson R.K. & W. Goedkoop. 2007. Bedömningsgrunder för bottenfauna i sjöar och

vattendrag – Användarmanual och bakgrundsdokument, Swedish University of

Agricultural Sciences, Report 2007:4, 84 p.

Sweden: Swedish lake profundal macroinvertebrate

method: Benthic Quality Index

General information

Detected pressure: Eutrophication



bakgrundsdokument, Swedish University of Agricultural Sciences, Report 2007: 4, 84 p.




Scientific literature: Wiederholm, T., 1980. Use of zoobenthos in lake monitoring. Journal

of the Water Pollution Control Federation 52: 537-547.

Sampling/Survey guidelines: Use of Ekman sampler, SS 028190 (0.5 mesh; 5 replicates

taken in autumn). Five Ekman samples are collected from a 100 m2 area in the middle of

the lake from soft bottom (or over the deepest region).

Sampling/survey months: September to November, one occasion per sampling season

Level of taxonomical identification: Species/species groups

Data evaluation

BQI exploits knowledge of the varying tolerance of different species of midges to low

oxygen levels at lake bottoms. BQI is calculated on the basis of the presence and

population density of different indicator taxa of midge larvae in the samples. BQI is

calculated as:

BQI=∑ ki x ni / N

Where:

ki = 5 for Heterotrissocladius subpilosus (Kieff.),

ki = 4 for Paracladopelma sp., Micropsectra sp.,

Heterotanytarsus apicalis (Kieff.),

Heterotrissocladius grimshawi (Edw.),

Heterotrissocladius marcidus (Walker) and

Heterotrissocladius maeaeri (Brundin)

ki = 3 for Sergentia coracina (Zett.), Tanytarsus sp. and Stictochironomus sp.,

ki = 2 for Chironomus anthracinus (Zett.),

ki = 1 for Chironomus plumosus L.,

ki = 0 if these indicator taxa are not present in the sample

ni = the number of individuals within the indicator group in

N = the total number of individuals in all indicator groups


EQR = the calculated BQI / reference value


Key source(s) to derive reference conditions: Existing near-natural reference sites.

Number of sites: ca 110. Geographical coverage: whole of Sweden. Criteria: Use of

pressure filter to identify reference conditions.

Reference community description: In shallow lake basins with maximum depth < 10 m

and minor anthropogenic disturbance, typical components of the profundal fauna are

chironomid midges larvae such as Zalutschia zalutschicola, Cladopelma viridula,

Tanytarsus spp., Chironomus plumosus and Chironomus anthracinus and phantom

midges (Chaoborus spp.). In deeper profundal basins (depth range around 10-40 m)

representing nearly or totally undisturbed conditions, chironomid larvae such as

Sergentia coracina, Stictochironomus rosenschoeldi, Monodiamesa bathyphila,

Heterotanytarsus apicalis and Protanypus morio, oligochaete worms (e.g. Spirosperma

ferox), mussels (Pisidium spp.) and water mites are typical inhabitants. In basins with

depth over 40 m representing reference conditions, chironomid larvae such as

Paracladopelma nigritula, Micropsectra spp., Procladius spp and Heterotrissocladius

subpilosus and oligochaete worms Stylodrilus heringianus, Lamprodrilus isoporus,

Potamothrix hammoniensis / Tubifex tubifex and crustacean Monoporeia affinis and

Pisidium spp. mussels are typical components of the profundal fauna.

Setting of ecological status boundaries: Equidistant division of the EQR gradient

"Good status" community

The composition and abundance of profundal macroinvertebrate assemblages that

represent quality class "good" show only slight changes from the reference communities.

In shallow lakes with maximum (i.e. sampling) depth < 40 m, the communities typically

include Chironomus-larvae C. plumosus and C. anthracinus. Chironomus plumosus is

usually absent at high status class but present at moderate status class, whereas

Chironomus anthracinus may often be absent or occur at low numbers at moderate

status. Pisidium spp. mussels are usually present. Sergentia coracina may be absent at

good status. In deep lakes (max depth >40 m) good status assemblages typically include

Sergentia coracina, Stictochironomus rosenschoeldi and C. anthracinus (but not C.

plumosus) whereas Heterotrissocladius subpilosus and Micropsectra spp. may be absent.

From oligochaetes, Spirosperma ferox is present, whereas Stylodrilus heringianus and

Lamprodrilus isoporus may be missing at good status.

Sweden: Swedish lake littoral macroinvertebrate method

(Acidification)

Method: Multimetric Index for Lake Acidity [MILA]

General information

Detected pressure: Acidification



bakgrundsdokument, Swedish University of Agricultural Sciences, Report 2007: 4, 84 p.





Standardized Kick-sampling, SSEN-27828 (20 s x 1 m; handnet 0.25 (width of kick net) x

1 m with 0.5 mm mesh size; 5 replicates taken in autumn). Substratum (hard bottom) is

disturbed by kicking for 20 s and moving a distance upstream of 1 m. Sampling/survey

months: September to November, one occasion per sampling season.

Level of taxonomical identification: Species/species groups

Data evaluation

List of biological metrics:

MILA is constructed from six different simple indices and responds to acidity. The indices

are:

1. relative abundance (%) of mayflies (Ephemeroptera);

2. relative abundance (%) of true flies (Diptera);

3. the number of mollusc taxa (Gastropoda);

4. the number of mayfly taxa;

5. the value for the British AWIC index;

6. the relative abundance (%) of predators in the sample.

Values for these simple indices must be normalised so that each has a value (indexnorm)

between 0 and 10 (see Table A.6). The normalised values are then added together and

re-scaled by dividing the sum of the normalised index values by the number of simple

indices included (a mean value) and multiplying this mean value by 10 according to the

following: MILA = 10 x sum indexnorm/6

MILA thus acquires a value that can vary between 0 and 100.

Table A.5 Guide for nomalising of index values

Index ASTERICS name Indexnorm=10

if index is

Indexnorm=0

if index is

% mayflies

(of total abundance)

Ephemeroptera|%] >27 <0.05

% true flies (of total

abundance)

Diptera|%| <26 >86

Molluscs (number of taxa) -Gastropoda >8 <0

Mayflies (number of taxa) -Ephemeroptera >6 <1

AWICfamily index AWIC Index >5.4 <4.8

% predators (of total

abundance)

-|%| Predators <8.7 >19

MILA shows the benthic fauna`s response to acidity. It cannot be determined from the

MILA classification whether the acidity is natural or of anthropogenic origin.


EQR = calculated MILA /reference value


Key source(s) to derive reference conditions: Existing near-natural reference sites.

Reference conditions for MILA (Multimetric Index for Lake Acidification) indices were

established using a pressure filter approach, i.e. lakes judged to be perturbed using

catchment land use and water chemistry (Johnson and Goedkoop 2007 (in Swedish))

were removed to isolate the gradient of interest. For example, to calibrate the response

of MILA to acidity we excluded sites affected by pressures such as eutrophication, liming,

urbanization etc to isolate the “acidity” gradient.

Reference site characterization:

Number of sites - ca 300;

Geographical coverage - whole of Sweden;

Criteria -Use of pressure filter to identify reference conditions.

Reference community description: Clear lake communities at reference status are

dominated by Dipteran (Typically Chironomidae), Trichopteran, Crustacea & Plecopteran

taxa. Other important components in these typically lentic faunas include molluscs,

Hemipterans & leeches.

Boundary setting

The MILA index was strongly related to acidity (EQR MILA regressed against mean annual

pH, r2 = 0.54, p < 0.001, n = 90 lakes) (Figure A.7), but regional differences were evident,

in particular for the northern parts of the country where acidification is generally not

considered to a serious environmental issue. Normalizing EQR values for regional

differences in expected (reference) values resulted in a better fit (r2 = 0.70, p < 0.0001).

Initial estimates showed that type 2 errors were low (11.5%). Type 2 error was estimated

by comparing the number of sites deemed to be acidified that had index values higher

than the 25th percentile of the reference dataset.

Figure A.7 EQR values of MILA regressed against mean annual pH. The different colors

reflect the three main ecoregions (regions14, 22 and 20), the different symbols

show reference (crosses) and putative acidified (circles).

The reference value was defined as the median MILA index value of unperturbed sites

stratified by type (here defined simply by ecoregion). EQR values for the reference

population were calculated as observed value divided by reference (established by

typology) value. The borderline between High and Good status was defined as the 25th

percentile of the distribution of the reference data. A threshold approach was used for

setting the Good/Moderate boundary. EQR MILA values normalized for ecoregion

differences were regressed against mean annual pH and the intercept at pH 5.6 was used

as the borderline between Good and Moderate quality. A pH value of 5.6 was selected

since many previous studies have shown marked changes in fish and invertebrate

assemblages at this threshold (e.g. Johnson et al. 2007). In addition, variability in the

regression supports this threshold; variance appears to collapse (funnel shaped response)

at around pH below 6.0 (Figure A.7). The remaining class boundaries were set using

equidistance.

Table A.6 MILA classification system for littoral benthic invertebrate assemblages of

Swedish lakes. Modified from Johnson and Goedkoop (2007).

Fennoscandian

Shield, region 22,

n=32)

Reference value 49.4

Uncertainty

(median S for EQR in

ecoregion)

0.202

High ≥ 0.85

Good 0.60 – 0.85

Moderat 0.40 – 0.60

Poor 0.20 – 0.40

Bad < 0.20

"Good status" community:

At “Good” status clear lakes’ fauna is still dominated by diptera (once again dominated

by Chironomidae), however Ephemeropterans assume increasing importance at this

status – with large numbers of Leptophelebiids. Crustaceans and molluscs are reduced in

abundance from reference status and decline toward the G/M boundary.

UK lake macroinvertebrate method (Acidification)

Method: Lake Acidification Macroinvertebrate Metric [LAMM]

Methods development

Macroinvertebrate kick samples taken in spring from 49 clear-water lakes (< 5mg/l DOC)

and 35 humic-water lakes (=> 5 mg/l DOC) and matched to chemistry from the

preceding year. A minimum of two chemical samples had to be available. Only sites with

mean ANC <150 ueq/l and mean Ca < 5 mg/l, were included. Linear regression of LAMM

vrs. Cantrell ANC at clear-water lakes resulted in r2 = 0.64, P < 0.001. Linear regression of

LAMM vrs. Cantrell ANC at humic-water lakes resulted in r2 = 0.82, P = <0.001.


Sampling guidelines are outlined in UKTAG Lake Assessment Methods. Benthic

Invertebrate Fauna. Lake Acidification Macroinvertebrate Metric (LAMM). Water

Framework Directive - UK Advisory Group.

Short description: To apply the method, invertebrates should be collected from a stony-

bottomed section of the littoral zone of the lake with a depth of ? 75 cm. Two samples

should be collected from each location sampled. Sampling should normally be

undertaken between March and May. The invertebrates should be collected by disturbing

the substratum with the feet ("kick sampling") and passing a hand net (nominal mesh

size: 1 mm) through the water above the disturbed area. All habitats in the chosen

sampling site should be sampled within a 3-minute period. In addition, a pre-sample

sweep to collect surface dwelling invertebrates and a post sample manual search, lasting

one minute, should be undertaken during which any invertebrates attached to

submerged plant stems, stones, logs or other solid surfaces should be collected by hand

and placed in the net. The sampling method used should comply with BS EN 27828:1994,

ISO 7828-1985 Water quality. Methods for biological testing. Methods of biological

sampling: guidance on handnet sampling of aquatic benthic macro-invertebrates.

Level of taxonomical identification: Family, Genus, Species/species groups

Specification of level of determination:

Ephemeroptera – species

Plecoptera – species

Trichoptera – species

Gastropoda – species

Leeches – species

Bivalvia – genus

Diptera – family

Coleoptera – species

Biological metrics: The observed value of the parameter, LAMM, should be calculated

using the equation:

Sum of Shk x Whk x Hhk / Sum of Whk x Hhk

where: Shk is the acid sensitivity score for taxon k

Whk is the corresponding indicator weighting score for taxon k

Hhk is the relative abundance score.


Key sources to derive reference conditions: Existing near-natural reference sites, Expert

knowledge, Historical data, Modelling (extrapolating model results)

Reference site characterisation: Number of sites: 8 sites for clear-water lakes, 6 for humic-

water lakes. Geographical coverage: Representative lakes throughout UK at risk from

acidification. Criteria: Reference sites screened using the Damage matrix. See table 6.1

in /'Macroinvertebrate Classification Diagnostic Tool Development/' SNIFFER Report

WFD60. This matrix assesses sites based on their Acid Neutralising Capacity (ANC) in

relation to Ca content.

Reference community description: Reference community characterised by high

abundances of highly sensitive Ephemeroptera. Presence of sensitive species of

Trichoptera and Plecoptera. Often species of gastropod, leeches and sensitive Coleoptera

present.

Boundary setting

Setting of ecological status boundaries: Using discontinuities in the relationship of

anthropogenic pressure and the biological response. Where discontinuities could not be

found then partitioning based on the Damage Matrix was used. Detailed description of

boundary setting procedure, pressure-response relationship and communities at high,

good and moderate status is given in McFarland et al. (2009).

Boundary setting procedure: Distinct discontinuities along the ANC pressure gradient

were only found at humic sites at ANC 23 µeq/l to derive a good-moderate boundary.

These were consistent using pressure metrics (e.g. LAMM), diversity measures (e.g.

Shannon) and functional groups (e.g. grazers). Where no consistent breakpoints/step-

changes were found, sites were grouped by the damage matrix according to class. The

mean LAMM scores of the two adjacent classes were then added together and divided

by two to form the boundary.

"Good status" community: Expected to be lower abundances of some HS taxa. Lower end

of good status classes tend to have higher number of tolerant species as a prercentage

contribution to the metric.

Uncertainty

The approach to uncertainty assessment assumes that the estimated mean LAMM EQR

is normally distributed with a standard deviation that is a modelled function of EQR.

Using the estimated standard deviation and number of samples collected we determine

the confidence that the observed mean EQR lies within particular class boundaries. The

approach follows that of Ellis (1990) (available at http://publications.environment-

agency.gov.uk/

epages/eapublications.storefront/4b100774024a67a6273fc0a802960648/Product/View/

GEHO1006BLOR&2DE&2DE) and has been used for the majority of the UK classification

methods.

References:

UKTAG Lake Assessment Methods. Benthic Invertebrate Fauna. Lake Acidification

Macroinvertebrate Metric (LAMM). Water Framework Directive.

http://www.wfduk.org/bio_assessment/bio_assessment/lakes_invertebrates

McFarland, B., Carse, F. & Sandin, L. 2009. Littoral macroinvertebrates as indicators of lake

acidification within the UK. Aquatic Conserv.: Mar. Freshw. Ecosyst. Published online in

Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/aqc.1064.

http://www.wfduk.org/bio_assessment/bio_assessment/lakes_invertebrates

http://www.interscience.wiley.com/

Johnson, R.K., 1998. Spatio-temporal variability of temperate lake macroinvertebrate

communities: detection of impact. Ecological Applications 8: 61-70.

Jyväsjärvi J., Tolonen K.T. & Hämäläinen H. 2009. Natural variation of profundal

macroinvertebrate communities in boreal lakes is related to lake morphometry:

implications for bioassessment. Canadian Journal of Fisheries and Aquatic Sciences 66:

589–601.

Osenberg, C.W., Schmitt, R.J., Holbrook, S.J., Abu-Saba, K.E. and Flegal, A.R., 1994.

Detection of environmental impacts: natural variability, effect size and power analysis.

Ecological Applications 4: 16-30.

Resh, V.H., 1979. Sampling variability and life history features: basic considerations in the

design of aquatic insect studies. Journal of the Fisheries Research Board of Canada 36: 290-

311

Resh, V.H. and Jackson, J.K., 1993. Rapid assessment approaches to biomonitoring using

benthic macroinvertebrates. In: Freshwater biomonitoring and benthic

macroinvertebrates. (Eds. D.M. Rosenberg and V.H. Resh) Pages 195 – 223. Chapman and

Hall. New York.

Sandin, L. and Johnson, R.K., 2000. The statistical power of selected indicator metrics using

macroinvertebrates for assessing acidification and eutrophication of running waters.

Hydrobiologia 422: 233–243.

Tolonen, KT; Holopainen, IJ; Hamalainen, H; Rahkola-Sorsa, M; Ylostalo, P; Mikkonen, K;

Karjalainen, J. 2005. Littoral species diversity and biomass: concordance among organismal

groups and the effects of environmental variables. Biodiversity and conservation 14: 961–

980.

B. Exclusion of abundance and diversity metrics of benthic

invertebrate assessment systems

From the Water Framework Directive (Annex V, Section 1.2) :“(vi) Where it is not possible

to establish reliable type-specific reference conditions for a quality element in a surface

water body type due to high degrees of natural variability in that element, not just as a

result of seasonal variations, then that element may be excluded from the assessment

of ecological status for that surface water type. In such circumstances Member States

shall state the reasons for this exclusion in the river basin management plan”.

IE sampled three low and three high alkalinity reference lakes in April of one year (mean

TP from 5 – 12 µg/l). Five 2-minute kick samples were collected from five exposed, stony

shorelines in each lake (5 samples x 5 sites x 6 lakes: one sample lost post-collection, n =

149). Summary statistics for invertebrate abundance in each of the lakes is presented in

the table below.

Table B.1 Summary statistics of the total number of invertebrates recovered from each

lake, the minimum, maximum and mean number of invertebrates recovered

from a single sample and the range in invertebrate abundance among samples.

(n = 149. n = 25 in each lake apart from L. Rea, n = 24).

Alkalinity Lake Total Minimum Maximum Mean Range

Low Ardderry 11 826 295 735 473 440

Low Inagh 14 095 373 917 564 544

Low Nafooey 22 693 383 1,891 907 1508

High Bunny 9 850 205 700 394 495

High Carra 29 150 310 2,574 1,166 2264

High Rea 29 079 583 2,332 1,329 1749

The greatest difference in abundance between samples in the low and high alkalinity

lakes was 1 596 and 2 ,369 invertebrates, respectively. One-way ANOVAs indicated that

there were statistically significant differences (p < 0.0001) in invertebrate abundance

among lakes in both the low and the high alkalinity lake types. All samples were

taken within a three week window to minimise temporal variability. All samples were

collected from exposed stoney shorelines to limit spatial variability associated with

habitat type. All samples were collected and processed by a single operator to elimate

associated sources of variation, however statistically significant differences in

invertebrate abundance between lakes remain.

The high degree of natural variability in this metric at reference condition leads

to its exclusion from the assessment of ecological status for this quality

element. We propose only to exclude this metric from the assessment method

and not the element itself.

Regarding the direct inclusion of a diversity measure despite evidence indicating it does

not have a good response to the pressure and that it does not improve the overall

response of the metric, Annex V, section 6.7 of Guidance Document No. 13 states that

“…averaging the results for parameters that are sensitive to a pressure with those that are

relatively insensitive to that pressure could conceal failures to meet the conditions specified

in the WFDs normative definitions of ecological status”.

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European Commission

EUR 26510 EN – Joint Research Centre – Institute for Environment and Sustainability

Title: Water Framework Directive Intercalibration Technical Report: Northern Lake Benthic fauna ecological

assessment methods

Authors: Leonard Sandin, Ann-Kristin Schartau, Jukka Aroviita, Fiona Carse, David Colvill, Ian Fozzard,

Willem Goedkoop, Emma Göthe, Ruth Little, Ben McFarland, Heikki Mykrä

Edited by Sandra Poikane

Luxembourg: Publications Office of the European Union

2014– 48 pp. – 21.0 x 29.7 cm

EUR – Scientific and Technical Research series – ISSN 1831-9424 (online), ISSN 1018-5593 (print)

ISBN 978-92-79-35465-6 (pdf)

ISBN 978-92-79-35466-3 (print)

doi: 10.2788/74131

Abstract

One of the key actions identified by the Water Framework Directive (WFD; 2000/60/EC) is to develop ecological

assessment tools and carry out a European intercalibration (IC) exercise. The aim of the Intercalibration is to ensure

that the values assigned by each Member State to the good ecological class boundaries are consistent with the

Directive’s generic description of these boundaries and comparable to the boundaries proposed by other MS.

In total, 83 lake assessment methods were submitted for the 2nd phase of the WFD intercalibration (2008-2012) 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 Northern Lake Benthic fauna IC group.

ISBN 978-92-79-35465-6

LB

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-26510-E

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water framework directive intercalibration technical...

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