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Journal of Environmental Monitoring
Water quality indices across Europe—a comparison of the good
ecological status of five river basins
w
Peter Carsten von der Ohe,*
a
Andrea Pru¨ ß,
ab
Ralf Bernhard Scha¨ fer,
cd
Matthias Liess,
c
Eric de Deckere
e
and Werner Brack
a
Received 28th March 2007, Accepted 6th July 2007
First published as an Advance Article on the web 30th July 2007
DOI: 10.1039/b704699p
The European Water Framework Directive (WFD) requires the definition of near-natural
reference conditions to determine the extent of water bodies’ deviation from ’’good ecological
status’’ caused by stress gradients. However, the classification of ecological quality depends on the
assessment method applied and the stressor concerned. While assessment methods that are
generally applicable would be favourable, many European countries employ the locally developed
water quality metrics that assess the impact of organic pollution (including eutrophication) and
the associated decrease in dissolved oxygen. These indices do not specifically address stress from
organic toxicants, such as pesticides. The aim of this study was to examine the performance of
presently used assessment methods to identify reference conditions of non-contaminated streams
in five selected European river basins, covering the geographical region from Spain to Finland, as
a crucial prerequisite to indicate toxic gradients. The analysis comprised the Belgium biotic index
(BBI), the biological monitoring working party (BMWP) scoring system and the revised German
saprobic index. For comparison, we included an adaptation of the recently developed SPEAR
index. In two previous field studies, this metric highly correlated with measured pesticide
gradients. In this study, SPEAR was the only indicator that was generally applicable to all
monitoring data and capable of determining ’’high ecological status’’ of reference conditions in all
basins. Thus, based upon previous and own results, the authors suggest the species at risk
(SPEAR) index to be potentially useful as a European-wide index to address deviations from
’’good ecological status’’ due to organic toxicants and recommend it for consideration in
integrated water-resource evaluations under the WFD.
Introduction
true measure of the impact, they should indicate a degradation
gradient according to a dominant stressor.
2,3
A metric that
should be applied at a large spatial scale like Europe, must
therefore be robust to natural and spatial variability compared
to the change in the index values caused by the indicated
stressor.
4,5
In this context, stream-dwelling invertebrate communities
have a long history of being used as biological indicators to
assess the quality of surface waters
6,7
and still represent the
most common used organism group.
8,9
Consequently,
monitoring of resident macroinvertebrate communities has
become a primary component of water-resource evaluations
with regard to the WFD.
1
A tendency to develop its own
national assessment methods could be observed for many
Member States.
10
The Directive enables the Member States
to maintain their own methods, but outlines an intercalibra-
tion procedure of the methods’ outputs, namely the classifica-
tion of ‘‘high’’ and ‘‘good ecological status’’ in the context of a
common implantation strategy.
11
As one example, Birk and
Hering
9
directly compared different assessment methods that
are in current usage or those that are about being implemen-
ted. They found significant intercorrelation for several metrics
that lessens the added value of their simultaneous application.
Nevertheless, it is generally accepted that multimetric assess-
ment methods provide better insight
The protection and preservation of freshwater resources pose
a major challenge to modern societies. The European Com-
mission acted in response and introduced the Water Frame-
work Directive (WFD) as an instrument to sustain and
improve water quality.
1
By 2015, the directive aims to achieve
at least a ‘‘good ecological status’’ for all water bodies, i.e.
streams that are ‘‘only slightly’’ impacted by anthropogenic
stressors. Hence, human activities that result in aberration
from this status have to be identified to implement effective
programmes of measures.
1
This, however, requires appropri-
ate indicators that link observed effects to certain anthropo-
genic stressors.
2
Even though such indicators do not reflect a
a
Department of Effect-Directed Analysis, UFZ Helmholtz Centre for
Environmental Research, Leipzig, Germany
b
Department of Water Management, University of Applied Sciences
Magdeburg-Stendal, Magdeburg, Germany
c
Department of System Ecotoxicology, UFZ Helmholtz Centre for
Environmental Research, Leipzig, Germany
d
Institute for Ecology and Environmental Chemistry, University
Lu¨neburg, Lu¨neburg, Germany
e
Department Biology–Ecosystem Management Research Group,
University of Antwerp, Antwerp, Belgium
w
Presented at the Water Status Monitoring of Aquatic Ecosystems in
the context of the Water Framework Directive meeting, Lille, France
12–14th March, 2007.
in the relationship
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between dominant stressors and ecological status.
12,2
An
example is the German Assessment System Macrozoobenthos
that assesses ecological status of streams in three modules with
respect to the biological quality element (BQE) of benthic
macroinvertebrates constrained by surface water body stream
type. With regard to effects of ‘‘organic pollution’’, defined as
an increase in both organic components (e.g. increased biolo-
gical oxygen demand (BOD); organic pollution sensu stricto)
and nutrient contents (eutrophication) by Sandin and
Hering,
13
the saprobic index is employed. Other countries like
Belgium or Spain apply single assessment methods to imple-
ment the WFD. All these indices are especially powerful in
detecting the effects of oxygen depletion resulting from organic
pollution,
13
but it is unclear if these indices are capable of
detecting adverse effects of organic toxicants. In a study of
Schriever et al.,
14
the saprobic index did not correlate with a
gradient of modelled pesticide input.
In this context, several supportive European Commission
research projects of the fifth and sixth Framework Programme
address the impact of environmental pollutants, i.e. AQUA-
TERRA, HAIR, MODELKEY, REBECCA or STAR. As
one example, the integrated project MODELKEY (511237-
GOCE) aims to develop models for assessing and forecasting
the impact of environmental key pollutants on marine and
freshwater ecosystems,
15
considering among other BQEs the
group of benthic macroinvertebrates. To achieve this aim, the
available monitoring data from three case study river basins
were collated and implemented in the central MODELKEY
database that was used in the present analysis.
According to the WFD, the assessment of the ecological
status of a water body undergoing monitoring requires a
comparison of observed metric values to expected values of
a predefined ‘‘reference condition’’.
1,16
In the context of the
WFD, the reference condition is termed ‘‘high ecological
status’’ and could be defined as group of sites being represen-
tative of totally or nearly undisturbed streams.
17,18
The iden-
tification of reference conditions is a crucial prerequisite to
calculate ecological quality ratios and to determine the dele-
terious effects of anthropogenic stress.
19
As a first step to identify an appropriate indicator for toxic
effects of organic compounds, the aims of this study were to
examine (i) the value of currently employed assessment meth-
ods to correctly determine reference conditions of streams not
contaminated by organic toxicants and (ii) the quality metrics’
general applicability to data of national river monitoring
programmes from different European river basins. Finally,
(iii) the different metrics were analyzed for correlations to
avoid redundant indications. The analysis comprised the
Belgium biotic index (BBI) as the ocial standard method
for biological water quality assessment as employed in the
Flemish part of the Scheldt River, as well as the scoring system
of the biological monitoring working party (BMWP) and its
adaptation for application to the Catalan Llobregat River,
referred to as BMWP (SP). Furthermore, the revised German
saprobic index, further referred to as SI (DE), was applied for
the Lower-Saxony part of the Weser River. An adaptation of
the recently developed species at risk (SPEAR) index,
3
to
detect effects of organic toxicants, was applied for comparison.
In two previous field studies (20 and 29 sites), the SPEAR
index was highly correlated with the measured pesticide
gradients.
3,20
The study of Scha¨ fer and colleagues
20
included
two field surveys in the Scorff (France) and the Porvoonjoki
(Finland) River basins that were included in our analysis to
extend the geographical range.
Materials and methods
Studied river basins
The investigated streams covered different European eco-
regions according to Illies,
21
that spanned the geographical
range from Spain to Finland. It comprised the Spanish
Llobregat (ecoregion no. 1–Iberic-Macronesian region), the
French Scorff (ecoregion no. 13–western plains), the Belgium
part of the Scheldt (ecoregion no. 13), the German Weser
(ecoregions no. 9–central highlands and no. 14–central plains)
and the Finish Porvoonjoki (ecoregion no. 22–Fenno-Scan-
dian shield).
The Llobregat River represented a typical Mediterranean
river basin, whereas the Scheldt River embodied a highly
polluted northwest European river basin. Datasets were ob-
tained from the Agencia Catalana de l’Aigua (ACA, Barcelo-
na, Spain) and the Vlaamse Milieumaatschappij (VMM,
Erembodegem, Belgium), respectively. Moreover, the analysis
comprised the Weser River, representing a central European
river basin in the northern German lowlands that was pro-
vided by the Niedersa¨ chsischer Landesbetrieb fu¨ r Wasser-
wirtschaft, Ku
¨
sten- und Naturschutz (NLWK, Hildesheim,
Germany) and two field studies.
20
From the latter two, the
Scorff catchment represents a western European river basin
that is located in the northwest of France and the Porvoonjoki
catchment a north European river basin situated in the south
of Finland.
Selection of non-contaminated streams
All selected sites were chosen according to criteria to reference
sites of the STAR protocols regarding macroinvertebrates,
2
with a focus on high chemical status. The mandatory criteria
included (1) only minimal anthropogenic disturbances,
(2) coarse woody debris should not be removed, (3) stream
bottoms and margins must not be fixed, (4) natural riparian
vegetation, (5) no point sources of pollution, nutrient input or
eutrophication affecting the site and (6) no sign of acidification
or salinity.
Selection was based upon information from topographical
maps (1 : 10 000–1 : 50 000), i.e. existence of treatment plants,
point sources of pollution or nutrients and other land use
patterns (e.g. mining) led to the exclusion of sites. In the case
of the two field studies, the reference sites were selected
accordingly, in close cooperation with local authorities and
by inspection of sites (INRA, Rennes, France and SYKE,
Helsinki, Finland). The above mentioned requirements
applied only to remote headwater streams and smaller tribu-
taries located in forested catchments. These sites were con-
sidered as being representative of non-contaminated streams
of presumed high ecological status and are referred to as
reference sites in the following discussion. The selection of at
least five of these high quality reaches per basin was hindered
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by the limited availability of sampling data of the national
river monitoring programmes as well as own investigations.
20
It could therefore not consider specific biological reference
conditions of all prevailing stream types in the five ecoregions.
A specific stream typology that was only available for German
streams was used for an analysis of stream type dependency of
the metric results. Hence, the Weser reference sites were
assigned to stream types based upon the map Karte der
biozo¨ notisch bedeutsamen Fließgewa¨ ssertypen Deutschlands
(Stand Dezember 2003).
For the selection of a monitoring site as a reference site, at
least two recent macroinvertebrate samples were required.
Samples were taken in accordance with local protocols which
were presumed to consider potential seasonality in the respec-
tive metric values (see below). Prior to analysis, the average
metric value for all samples was calculated at each site in order
to avoid temporal pseudo-replication. For the Llobregat
River, a total of 34 monitoring sites with samplings between
2001 and 2004 were available, five of which were classified as
reference sites. The 28 samples were taken in spring and
autumn, before and after summer droughts, to account for
the arid climate. In this context, however, Zamora-Mun˜ oz
et al.
22
stated no seasonality in the respective BMWP metric
values. In the Weser River basin, from 279 national monitor-
ing sites with samplings between 1994 and 1999, eleven sites
with 38 samples were classified as reference sites. Please note
that for this study, only samples for the months February to
August have been considered, as required by the AQEM
method.
12
Accordingly, seven of the 236 monitoring sites in
the Scheldt River with 36 sampling data from 2000 to 2004 met
the above-mentioned requirements for a reference site.
Streams in the basin of the river Porvoonjoki and of the Scorff
River basin were each sampled in two successive months in
2005, and five and six sites were selected as reference sites,
respectively.
project (EVK1-CT1999-00027). Respective metric values were
not transformed prior to the analyses.
Species at risk of being affected by organic toxicants
In comparison to the other quality metrics, the recently
developed index of ‘‘species at risk’’
3
was originally developed
to detect the effects of pesticides impacting aquatic commu-
nities in the season of late April to June, the main application
period in the investigated area. The index was especially
powerful in small streams with an agricultural catchment.
The invertebrate species were classified at risk of being affected
by pesticides according to their physiological sensitivity to-
wards organic toxicants
31
as well as additional life history
information,
3
i.e. the recovery potential of species.
32
For many
European species, this information is freely available from the
However, macroinvertebrate communities in larger rivers
and streams with their numerous point and diffuse sources of
organic environmental pollutants (e.g. euents of chemical
plants or intense agricultural areas) are constantly exposed to
various compounds over the years. Therefore, in contrast to a
previous study,
3
only the following two criteria were applied to
classify species to be at risk of organic toxicants: a taxons S-
value, representing its physiological sensitivity, greater than
–0.36 (median sensitivity of all species) and the generation time
is equal or longer than half a year. Hence, the emergence of
insects was not taken into account. Note that this led to only a
minor adaptation of the original SPEAR classification.
3
Limnephilus lunatus and Anabolia nervosa, like the whole
family of Limnephilidae, were classified as being at risk. This
holds also for the family Asselidae, due to the likely presence
of Asellus aquaticus as representative of this family. The low
generation times and high reproduction rates of many Baetis
and Gammarus species led to the classification of SPE
not
AR of
these genera. The same applies for the corresponding families
of Baetidae and Gammaridae. SPEAR was computed as a
ratio of the total abundance of species at risk and the total
abundance of all species (eqn (1)):
Local indices of organic pollution
In case of the Llobregat River, the locally adapted BMWP
(SP)
23
was applied, whereas the original BMWP,
24
reflecting
central European conditions, was applied for the other basins.
Samples were collected from the rie and pool habitats using
an adaptation of the kick-net method and results obtained
were qualitative, on the taxonomic level of the family. The
Belgian BBI
25,26
required quantitative results at the genus
level, expressed as number of individuals per dredge using a
Van Veen dredge engine. The German SI (DE)
27,28
was
applied to historical monitoring data that were sampled
according to the DIN 38410-1 normative with semi-quantita-
tive results at the species level. The application of the revised
saprobic index led to a higher number of valid ‘‘historic’’
samples, due to the higher number of classified taxa compared
to the old saprobic index.
29
Species abundance was classified
into seven abundance classes.
For consistency, the macroinvertebrate data of all basins
were taxonomically adjusted according to the AQEM guide-
lines.
30
The three metrics of organic pollution were automati-
cally calculated using the AQEM assessment software version
3.0 (http//www.aqem.de) that was developed in the AQEM
P
n
a
i
t
i
P
i
¼
1
SPEAR
¼
ð
1
Þ
n
a
i
i
¼
1
where a
i
is the taxons abundance and t
i
is 1 for species
classified at risk, else 0.
To reduce the weights of highly abundant species, the
originally reported abundance was transformed into seven
abundance classes in accordance with the conversion table of
the revised German saprobic index.
12
If only qualitative
abundance information was available, as in the case of the
monitoring data from the Llobregat River (presence of
families), an abundance class of one was assigned to each
family. For convenience, the calculation of the SPEAR index
was implemented into the MODELKEY database.
Ecological status class boundaries
For the classification of the ecological status of the investigated
surface water bodies, the predefined class boundaries of the
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anthropogenic stressors.
19
Consequently, employing similar
class sizes of 14%, the class boundaries were suggested as
r
1%, 1.1–15, 15.1–29, and 29.1–43, corresponding to bad,
poor, moderate, and good ecological status, respectively. The
low class boundary value of
r
1% may surprise, but it con-
sidered the existence of potentially diverse communities at
disturbed sites with almost no species classified as being at risk
of toxicants. The class boundaries suggested here, however,
should be regarded as preliminary.
respective indices were taken from the legal guidance docu-
ment.
33
For the SI (DE), applied in Germany, stream type
specific class boundaries existed with regard to the river typol-
ogy.
27
The selected reference conditions of the Weser basin
consisted of sites of stream type no. 7 (small streams in lower
mountainous areas in Central Europe) as well as stream types no.
14 (small sized, sand bottom streams in the German lowlands)
and no. 16 (small sized gravel bottom streams in the German
lowlands). Predefined class boundary values for the SI (DE) are
reported as 2.1, 2.25 and 2.15 for good ecological status as well as
1.6, 1.8 and 1.65 for high ecological status, respectively.
34
The
predefined class boundaries for the good and the high ecological
status of the BBI were set to 7 and 9, respectively. The scoring
system of BMWPs class boundary for good ecological status
correspond to values of 60 for the BMWP(SP) applied in the
Llobregat and 70 for the BMWP applied in the other basins,
respectively. Sites with BMWP/BMWP (SP) values exceeding
100 were assigned high ecological status.
For the SPEAR index, new class boundaries were derived
from the study of Liess and Von der Ohe
3
to allow for the
classification of ecological status of the selected reference sites.
In the study of Liess and Von der Ohe,
3
a sensitivity threshold
0.36 (median of species sensitivity) was set to classify half of
the determined taxa in that study to be at risk and the other half
to be not at risk. As the classification of species at risk did not
depend on any specific traits of species, a SPEAR metric value
of approximately 50% (according to half of the community)
was expected for communities at undisturbed reference sites.
Interestingly, a mean metric value of 50% (
7% s.d.) was
observed for the four non-contaminated sites (TU
(D. magna)
values were
o
4) of the previous field study.
3
Therefore, a
mean SPEAR value of 50% was set as centre of the high
ecological status class, with equidistant class boundaries of
7% that resulted in a lower class boundary of Z43. The
class size of 14% should cover the natural variability of the
SPEAR metric values at reference conditions. This procedure
allowed for the establishment of an upper anchor for setting
class boundaries and subsequently the identification of depar-
tures from expected reference conditions that may be caused by
Statistical analysis
The ‘‘applicability’’ score of an index referred to the number of
countries where the index could be applied. Note, however,
that invertebrates of our own investigations in the Scorff River
basin were identified to a lower (genus) taxonomic level
compared to the ocial ‘‘national’’ field protocols for the
IBGN index commonly applied in France (Table 1). Data were
checked for departure from the normal distribution using the
Kolmogoroff–Smirnoff test prior to analysis. The means of the
metric values for each reference site were compared between
basins using one-way analysis of variance (ANOVA). Dun-
nett’s multiple comparison test was employed to detect sig-
nificant differences among means. For the Weser River basin,
this comparison was also performed for the different stream
types. To consider the relative variation of the mean index
values, the coecient of variance (cv) was calculated.
The ‘‘predictivity
HES
’’ referred to the ratio of the number of
sites whose computed mean index values fell into the class
boundaries of the high ecological status compared to the total
number of reference sites. It was computed to quantify the
index’s power to detect non-contaminated streams across
Europe. Accordingly, the proportion of sites whose computed
mean index values exceeded at least the class boundaries of the
good ecological status were referred to as ‘‘predictivity
GES
’’.
Intercorrelation among single metrics were determined with
Pearson’s product moment correlation coecient r (significant
correlations for r Z0.60;
a
= 0.05) without standardization
of the metric values. All statistical analyses were carried out
Table 1 Overview of the taxonomic level of determination of the national applied assessment method (AM), the number of reference sites (n)in
each of five European river basins (RB), as well as mean
standard deviation of metric values and descriptive statistics of the assessment methods
Assessment method (AM)
BMWP
f
River basin
(RB)
Country of
RB
National applied
AM
Taxonomic level
of AM
BBI
SI (DE)
SPEAR
n
Llobregat
Spain
BMWP (SP)
Family
5
99
12
—
—
53
8
IBGN
a
Family
b
Scorff
France
6
168
6
9.3
0.4
1.72
0.04
46
3
Scheldt
Belgium
BBI
Genus
8
83
22
7.4
0.6
—
51
5
Weser
Germany
SI (DE)
Species
11
66
21
9.3
0.4
1.95
0.21
52
5
Genus
b
Porvoonjoki
Finland
—
5
102
23
6.9
1.4
2.08
0.07
47
5
Descriptive statistics
Mean cv
19.2%
11.1%
5.3%
9.9%
Applicability
c
5/5
3(4)/5
2(3)/5
5/5
Predictivity
HES d
44%
18%
6%
94%
Predictivity
GES e
76% 59% 100% 100%
a
Calculation of IBGN was not available from the AQEM software and, therefore, not performed.
b
Data available from Scha
¨
fer et al.
20
was
mainly at genus level.
c
Number of countries, where the metric could be applied to monitoring data (+field study of Scha
¨
fer et al.).
20 d
Mean ratio
of correctly classified sites of high ecological status.
e
Mean ratio of correctly classified sites of at least good ecological status.
f
BMWP adapted for
the Iberian Peninsula and respective class boundaries used for Llobregat data set.
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973
using SPSS version 7.5.1.
35
Graphs were created with the
SigmaPlot graphics package.
36
However, no significant differences were found between the
reference sites of the three stream types in the Weser River
basin. For the BBI, significant differences were only observed
between the Scorff River basin and all other basins. For the
SPEAR index, no significant differences between any of the
river basins or stream types were observed, indicating a similar
classification for all reference conditions.
For the SI (DE), single river basin cv values ranged from 2%
at the Scorff River basin and 3% in the Porvoonjoki River
basin to 11% in the Weser River basin. The latter, somewhat
larger cv was mainly attributed to differences in stream
typology (see above). As can be seen from Table 1, the overall
cv that considered data from all basins was computed as 9%.
For the BMWP, the computed cv values ranged from 4% at
the Scorff River basin to 32% at the Weser River basin, the
latter, however, irrespective of the stream typology. This was
reflected in a high overall cv of 41% that stemmed from the
very high BMWP values in the Scorff River basin. For the
BBI, the cv values ranged from 5% at the Scorff River basin
and 8% at the Scheldt River basin to 20% at the Weser River
basin, again irrespective of the stream typology. The latter was
reflected in the overall cv of 16%. Finally, the cv values for the
SPEAR index ranged from 6% in the Scorff River basin to
15% in the Llobregat River basin. The relatively low overall cv
of 11% was therefore comparable to the one of the SI (DE).
Results
General applicability of the indices
The taxonomic level required for calculating the SI (DE) was
the species level, and therefore it was only applicable to the
Weser and Porvoonjoki River basins (Table 1). Although
appropriate data for the Scorff River basin were available
from own investigations,
20
the taxonomic level of the ocial
monitoring programmes were limited to the family level. The
same applies to BBI that required information on the genus
level, which was additionally available for the monitoring data
of the Scheldt River basin. The BMWP required family level
resolution and was therefore applicable to all datasets. The
SPEAR index was also generally applicable as the calculation
of the metric could be adapted to the required level of
taxonomic
resolution of
the national
river monitoring
programmes.
Besides the general applicability, the metric values of an
index should be preferably similar for all river basins to allow
equal classification of water bodies on a European level. For
the SI (DE), significant differences were observed between the
Scorff River basin and the Porvoonjoki River basin (Table 1).
Moreover, the metric values for river types no. 7 (mean SI =
1.83
0.06), no. 14 (mean SI = 2.10
0.12) and no. 16 (mean
SI = 1.96
0.07) differed all significantly within the Weser
River basin (Fig. 1c). For the metric values of the BMWP,
significant differences between basins were found for the Scorff
River basin and all other basins. Moreover, the Weser River
basin differed significantly from the Llobregat River basin as
well as from the Porvoonjoki River basin (Table 1, Fig. 1a).
Detection of non-contaminated sites
For the SI (DE), the predictivity
HES
ranged from 0% for the
Scorff and for the Porvoonjoki River basins to only 10% for
the Weser River basin. The correct classification of all remain-
ing reference sites corresponded to high predictivity
GES
of
90% to 100% (Fig. 1c). The predictivity
HES
for the BMWP
ranged from 9% in the Weser River basin and 25% in the
Fig. 1 Box and whisker plots of mean metric values of all reference sites belonging to one of the five European river basins, separately for each of
the four examined indices: (a) scoring system of biological monitoring working group (BMWP), (b) Belgium biotic index (BBI), (c) German
saprobic index (SI (DE)) and (d) species at risk index (SPEAR). Class boundaries of good and high ecological status are included for comparison.
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