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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.
Legal Notice
This publication is a Technical Report by the Joint Research Centre, the
European Commission’s in-house science service.
It aims to provide evidence-based scientific support to the European policy-
making process. The scientific output expressed does not imply a policy
position of the European Commission. Neither the European Commission nor
any person acting on behalf of the Commission is responsible for the use which
might be made of this publication.
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.
Page 1
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
Page 2
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)
Finalized agreed national method
UK CPET: Chironimidae Pupal Exuviae
Technique (all-lake eutrophication)
Finalized agreed national method
Page 3
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
Relative abundance (%)
Diptera
Relative abundance (%)
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)
Page 4
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).
Page 5
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
Page 6
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
Page 7
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;
Page 8
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.
Page 9
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;
Page 10
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
Page 11
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
SE: yes; UK: yes; FI: yes; NO: yes
9. Selected taxonomic level achieves adequate
confidence and precision in classification
SE: yes; UK: yes; FI: yes; NO: yes
Page 12
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
Ecoregion 14, clear and humic, low
and moderate alkalinity
Ecoregion 22, clear and humic, low
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
Ecoregion 14, clear and humic,
low and moderate alkalinity
Ecoregion 22, clear and humic,
low and moderate alkalinity
Only SE had an assessment system
Page 13
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
Page 14
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
eutrophication lakes)
Whole lake assessment (repr Profundal+Littoral)
Structural community features (chironomid pupal
exuviae)
Represents
different lake
zone
ASPT (SE
eutrophication lakes)
Littoral, Exposed stony shorelines Structural
community features (sensitive and tolerant taxa)
Represents
different lake
zone
Page 15
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
Page 16
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.
Page 17
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 sub- types. 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):
Page 18
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.
Lake littoral acidification:
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
(med EQR of ref site)
SE MILA
(med EQR of ref site)
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:
Page 19
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;
Page 20
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).
Lake littoral acidification:
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:
Page 21
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.
Page 22
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.
Page 23
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
Page 24
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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of the EPA‟s Rapid Bioassessment benthic metrics: metric redundancy and variability
among reference stream sites. Environmental Toxicology and Chemistry 11: 437 – 449.
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.
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Tolonen, KT; Holopainen, IJ; Hamalainen, H; Rahkola-Sorsa, M; Ylostalo, P; Mikkonen, K;
Karjalainen, J. 2005. Littoral species diversity and biomass: concordance among
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conservation 14: 961–980.
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.
Page 27
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
Page 28
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).
Page 29
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.
Page 30
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
Page 31
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
Page 32
(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).
Page 33
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)
Page 34
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.
Field sampling/surveying
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,
Page 35
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:
Page 36
EQR = calculated ASPT / reference value
Reference conditions
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
Page 37
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
Page 38
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:
Page 39
“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
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, 84 p.
[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: 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:
Page 40
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
The ecological quality ratio (EQR) is calculated as follows:
EQR = the calculated BQI / reference value
Reference conditions
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
Page 41
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
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, 84 p.
[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).
Field sampling/surveying
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);
Page 42
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.
The ecological quality ratio (EQR) is calculated as follows:
EQR = calculated MILA /reference value
Reference conditions
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:
Page 43
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
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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.
Field sampling/surveying
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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.
Reference conditions
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
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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.
Page 47
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
Page 48
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
-NA
-26510-E
N-N