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EUROPEAN SURFACE WATERS Review Paper
Assessment of the ecological status of European surfacewaters: a work in progress
Peeter Noges Æ Wouter van de Bund ÆAna Cristina Cardoso Æ Angelo G. Solimini ÆAnna-Stiina Heiskanen
Published online: 29 July 2009
� Springer Science+Business Media B.V. 2009
Abstract The ‘normative definitions’ of ecological
water quality classes given by the Water Framework
Directive (WFD) are narrative descriptions of the
conditions present in water bodies of different
qualities relative to reference conditions found in
unimpacted sites. In order to fill these descriptions
with a more solid content, the definitions have been a
subject of intensive development of quantitative
methodologies for ecological status assessment as
well as for rules and criteria for setting of reference
conditions and ecological status boundaries for
classification of water bodies. In this article, we
recall the basic principles of the WFD that sometimes
have been overlooked and point out some gaps
remained and problems arisen during the ongoing
implementation of the directive. Defining type-spe-
cific reference conditions for water bodies and finding
biological metrics that sensitively reflect only the
anthropogenic deviations from those conditions are
the biggest challenges that the ecological status
assessment faces. So far, there is no guarantee that
reference conditions are comparable across EU
Member States due to a lack of common criteria,
which need still to be elaborated. Defining site-
specific reference conditions instead of type specific
is a novel approach that allows for minimizing
uncertainties introduced by applying broad types.
Search for new metrics has led to a real boom of
multimetric indices which ought to be the adequate
tool to measure the multiple human impairments but
which should pass a thorough check before being
included in monitoring programs. Curiously, some
biological indices constructed as surrogates for
chemistry (especially nutrients) start ‘living their
own life’ and continue indicating the disturbance
when the controlling factors change. This shows the
obvious advantage of biological indicators against
chemical ones. New challenges to WFD implemen-
tation are brought about by the need to consider the
Guest editors: P. Noges, W. van de Bund, A. C. Cardoso,
A. G. Solimini & A.-S. Heiskanen
Assessment of the Ecological Status of European Surface
Waters.
P. Noges (&) � W. van de Bund � A. C. Cardoso �A. G. Solimini � A.-S. Heiskanen
Institute for Environment and Sustainability, Joint
Research Centre, Via E. Fermi 2749, 21027 Ispra,
VA, Italy
e-mail: [email protected]
P. Noges
Centre for Limnology, Institute of Agricultural and
Environmental Sciences, Estonian University of Life
Sciences, 61117, Rannu, Tartumaa, Estonia
A. G. Solimini
Department of Experimental Medicine, Sapienza
University of Rome, Viale Regina Elena 324,
00161 Rome, Italy
A.-S. Heiskanen
Marine Research Centre, Finnish Environment Institute
(SYKE), Research Programme for the Protection of the
Baltic Sea, P.O. Box 140, 00251 Helsinki, Finland
123
Hydrobiologia (2009) 633:197–211
DOI 10.1007/s10750-009-9883-9
effects of alien species and climate change in the
assessment framework, and by the nonlinear dose—
response relationships dominating in biological sys-
tems. Attempts to diminish uncertainties in quality
assessment have become a new labour-intensive field
for researchers.
Keywords Water Framework Directive �Intercalibration � Multimetric index �Biological indicators � One out/all out principle
Introduction
The launch of the Water Framework Directive (WFD;
Directive, 2000) to provide a holistic framework for
management and protection of all waters in the
European Union (EU), was parallel to the develop-
ment of the Ecosystem Approach (EA), which was
adopted as the primary framework for action under
the convention of the biological diversity (CBD;
UNESCO, 2000) for management and conservation
of nature. The WFD follows many principles of the
EA which is a holistic framework for protection of
biodiversity and for the sustainable management of
natural resources in the context of the ecological,
socio-economical and cultural aspects. The WFD
includes management at the lowest appropriate level
(river basin management) in accordance with com-
mon principles and environmental objectives, stake-
holder involvement in the definition of management
objectives, restoration goals and planning of mea-
sures. It requires initial characterization of water
bodies, and analysis of human pressures impacting
the aquatic ecosystems, assessment of ecological and
chemical status, and economic analysis of cost-
effective protection measures. At present, the
recently adopted EU Marine Strategy Framework
Directive (Directive, 2008) is following the principles
of EA, while providing less detailed definitions on the
environmental objectives and criteria for the good
environmental status than the WFD. This may be an
advantage as it allows more flexible approaches that
can be adapted for regional seas that are different in
many ecological features, but on the other hand, it
may also make diversification of approaches in the
setting of ‘good environmental status objectives’
between the regional seas.
The WFD implements the principles of the EA
requiring management and protection of the aquatic
ecosystems as whole, ensuring sustainable function-
ing and healthy structure of the ecosystems, as well as
acknowledging the critical role of human societies in
managing those systems. However, contary to that
stated in the CBD definition of EA: The objectives of
management of land, water and living resources are a
matter of societal choice (UNESCO, 2000), the WFD
requires definitions of criteria and standards for good
ecological status that is the objective for protection
and restoration of water bodies. The interpretation
and application of Article 4 in the Directive, which
describes the environmental objectives and sets out
the so-called exemptions, does not compromise the
rule that the criteria for ‘good status’ are based on the
scientific knowledge of the aquatic ecosystems and
set by the intercalibration exercise between the
Member States (CIS, 2009). However, there may be
differences in views of the level of ambition how the
criteria for good ecological status have been defined
and applied in practical implementation of the
Directive (e.g., Moss, 2008), and, of course, expert
opinions are necessary in all stages of the assessment.
These criteria (i.e. the ‘normative definitions’) are
described in narrative terms in the Annexes of the
Directive, and have been a subject of intensive
development of quantitative methodologies for eco-
logical status assessment as well as for rules and
criteria for setting of reference conditions and
ecological status boundaries for classification of
water bodies. In this article, the authors recall the
basic principles of the WFD, which sometimes have
been overlooked or misinterpreted and point out some
gaps remained and problems arisen in the ecological
status assessment during the ongoing implementation
of the directive.
Ecological status and reference conditions
The Ecological Status assessment of the WFD
combines information on several hydromorphologi-
cal, chemical and biological parameters to acquire a
comprehensive picture of the overall status on
functioning and structure of the ecosystem. Hydro-
morphological (e.g. depth, flow rate, salinity, sedi-
ment types, etc.) and some chemical parameters (e.g.
alkalinity) are used to identify water body types,
198 Hydrobiologia (2009) 633:197–211
123
which are sufficiently similar while chemical param-
eters (e.g. nutrient and oxygen concentrations) are
supporting parameters that are applied to identify
reference conditions and good status (CIS, 2003a, b).
Biological parameters are the basis for the eco-
logical status assessment. WFD requires that the
status assessment of the water bodies is made based
on biological ‘quality elements’, such as phytoplank-
ton, macrophytes and phytobenthos, macroalgae and
angiosperms, macroinvertebrates and fish, combina-
tion of which is depending on the surface water
category (e.g., fish is not a quality element in coastal
waters, but required for all other surface waters
including transitional waters). The initial status
assessment should be based on all biological quality
elements required for each specific water category to
obtain an overall view of the status of biological
communities. Biological quality elements express
also the sensitivity to different pressures. Commonly,
phytoplankton is reacting first to human impact and
provides a fast response to, e.g. eutrophication
pressure, while macrophytes and fish may be more
sensitive for various degrees of hydromorphological
pressures (e.g., Solimini et al., 2006).
The selection and development of indicators
representative for the biological quality elements
are crucial in the assessment process. For instance,
chlorophyll a measurements are widely used as a
proxy for phytoplankton biomass. Moreover, also the
way of calculation of the metrics is important to
provide required robustness to the indicator. For
instance, if seasonal monitoring is carried out for
phytoplankton chlorophyll, the indicator calculated
should make use of all available data instead of
reducing datasets for summer period only, unless it is
proven that a more precise indicator can be obtained
from a subset of data (Carstensen, 2007). In the case
of coastal phytoplankton, either the 90th percentile or
the summer mean are most widely used as metrics for
chlorophyll a (Carletti et al., 2009). The robustness of
the selected indicator metrics is crucial, since several
biological parameters with a large natural variability
cannot be used for ecological status assessment as it
is not possible to identify reference conditions for
them with sufficient accuracy.
One of the big challenges of the WFD is to find
common approaches for defining reference conditions
that act as the anchor point for the ecological
assessment. A very purist approach—defining
reference conditions as the total absence of any
anthropogenic influence on the ecosystem—would
leave us with no real reference sites at all. This
realization could lead to the other extreme where the
concept of reference conditions is abandoned and
replaced with a focus on ecosystem services and
human benefits (Dufour & Piegay, 2009). In practice,
however, compromises between these two extreme
approaches are usually found, e.g. if reference condi-
tions are based on measurements from reference sites
with a minimum level of anthropogenic pressure. The
weak point so far is that there is no guarantee that
reference conditions are comparable across Member
States due to a lack of common criteria; further study
will be needed to resolve this issue. Setting reference
conditions is especially difficult for those water body
types lacking credible natural reference sites, includ-
ing lowland rivers, large rivers and lakes, and certain
types of estuaries and coastal waters.
As the driver or pressure is diminishing, the
recovery of ecosystems may not follow a similar
pathway and to return linearly to the initial state that
prevailed before the pressure increase. In a recent
article, Duarte et al. (2009) describe four coastal case
studies where nutrient loading reductions did not
bring a decline in phytoplankton biomass to about the
level before nutrient enrichments. Changes in the
species composition, internal ecosystem processes
and food web interactions may have caused a shift in
the ecosystems and the restoration of the previous
stage may not be possible, but after the pressure relief
a new alternative steady state will emerge. They
raised a question whether static reference conditions
are justified or instead shifting base lines should be
accepted to provide realistic prospects and public
motivation for restoration and ecosystem recovery.
Similarly, the changing and warming climate is
affecting many characteristics of surface waters. As a
result, some water bodies, especially those located
near the type boundaries, may even change their type.
Compared to typology characteristics, water quality
parameters and biological indicators are even more
labile and may be easily affected by climate change
(Noges et al., 2007). The review of the river basin
characterization every sixth years, as required by the
WFD, needs also encompassing re-evaluation of
reference conditions according to the changes
observed using potential reference site monitoring
networks, or modelling tools that enable distinction
Hydrobiologia (2009) 633:197–211 199
123
of climate change effects. As a consequence, the
restoration targets (i.e., the good ecological status)
would also need to be evaluated periodically, accept-
ing that some changes (as loss or immigration of
some species, or permanently elevated biomass levels
of phytoplankton being fed by internal sources of
nutrients) have become permanent.
Intercalibration exercise
There is a large variety of indicator metrics, both single
and multimetric indices, which are developed for
different water categories, ecoregions and surface
water types and applied by the different EU Member
States. The comparativity of such metrics and classi-
fication results based on these indicators is one of the
key questions at the EU level. The WFD intercalibra-
tion aims to provide a process for comparison of
assessment results on quality element or on single
parameter level. In many cases the assessment meth-
ods were still in development at the time of the
intercalibration exercise that had to be carried out
based on a limited amount of available data. Results of
the intercalibration exercise have been achieved for
the most widely used methods (Carletti et al., 2009;
Poikane, 2009; van de Bund, 2009), but has not been
finalized; some of the more challenging quality
elements are yet to be addressed. Because the focus
of existing and often more traditional methods with the
results that have been laid down in a legal document,
there is the risk that intercalibration will limit the
development of new and innovative approaches. This
leaves a considerable challenge for the scientific
community to develop methods that are ecologically
sound and to show how they can improve current
methodologies. On the positive side, the intercalibra-
tion exercise has catalysed an exchange of information
in the expert groups, leading to more comparable
approaches in ecological quality assessment.
Biological elements
Annex V of the WFD sets out quite clearly the
biological elements that need to be monitored for
freshwater and coastal ecosystems. However, it
allows the elements with high natural variability to
be excluded from classification schemes. This
exemption together with the reduced probabilities of
a correct classification with increasing number of
elements used, have been considered responsible for
a restriction to the range of biological elements
sampled in routine monitoring in comparison with the
Annex V shopping list (Irvine, 2004). Indeed, a
Commission Decision on Intercalibration (European
Commission, 2008) published the classification cri-
teria for only a fraction of the required biological
elements and parameters (e.g., taxonomic composi-
tion, abundance) within the elements. This may not
only reflect difficulties associated to the development
of biological assessment methods but also a cautious
approach to the inclusion of several biological
elements in classification.
Not only the number of biological elements but
also the choice of the elements included in the
Directive has been the subject to criticism. The
omission of zooplankton among the biological ele-
ments for the assessment of lakes and coastal areas
has been particularly criticized (e.g. Moss, 2007)
given the important role of this group in reflecting
food web efficiency (e.g., Calbet & Landry, 2004;
Jeppesen et al., 2004). In particular, zooplankton
plays a key role in shaping shallow lakes’ food
webs—whereby in clear water state these lakes are
dominated by submerged macrophytes—used by
zooplankton as refuge against planktivorous fish
(e.g. Schriver et al., 1995; Stansfield et al., 1997),
and high zooplankton/phytoplankton ratio suggesting
zooplankton control on phytoplankton biomass (e.g.
Schriver et al., 1995; Søndergaard & Moss, 1998).
Another important subject to criticism regards the
exclusion of fish from the coastal waters assessment.
The role of fishes in the food web structure and
ecological process in coastal water is well known.
The magnitude of the direct pressure on this element
(i.e. through fishing) and its consequent cascade
effects on food webs (e.g. Daskalov, 2002) is also
well documented. Nonetheless, the Directive allows
for some flexibility in inclusion of other biological
elements, if their importance for the ecological
assessment is justified as it allows for exemptions
to mandatory biological elements. However, the
already significant monitoring efforts may discourage
Member States from including elements other than
those directly prescribed by the WFD.
Another gap regards the assessment of ecosystem
impacts from alien species (Cardoso & Free, 2008).
Although these species are not specifically mentioned
200 Hydrobiologia (2009) 633:197–211
123
in the text of the WFD, they represent a significant
biological pressure as many of them have an invasive
behaviour and can alter the native biological structure
and ecological processes of aquatic systems (e.g.
Olenin et al., 2007). According to the WFD Annex II,
alien species can fall in the category of ‘other
pressures’. Whereas, in the Directive’s Annex V, the
definition of ‘high status for each biological quality
element’ states the taxonomic composition corre-
sponds totally or nearly totally to undisturbed
conditions, therefore the departure from naturalness
underlines the entire ‘spirit’ of the WFD, and the
presence of alien species indicates such a state. Thus,
alien species simultaneously indicate high pressure
and poor or bad ecological status and should be
considered in ecological assessment tools.
In reality, alien species are a widespread problem
affecting all biological quality elements but water
body management is based on the assumption that
ecosystems naturally improve following reductions in
human impacts. However, alien species are a self-
perpetuating pressure which is very difficult to
eradicate once established, and ecological status
declines accordingly. This problem is further aggra-
vated because the impacts of alien species are not
reliably measured by the classification tools that have
been developed for the WFD. For example, inverte-
brate kick sampling does not adequately collect
species such as crayfish and family level identifica-
tion may fail to detect some alien species.
Metrics
(i) Type-specific or site-specific approach?: The
efficiency of water body assessment depends most
crucially on two aspects: (1) the appropriate typology
that adequately takes into account regional geo-
graphic and climatic differences and guarantees the
correct application of reference conditions, and (2)
the selection of right metrics that change quantita-
tively and consistently across a range or gradient of
human influence.
As shown by Borja et al. (2009), WFD typology
schemes have often been criticized for being over-
simplified and not reflecting the high heterogeneity of
habitats within the different types and water bodies.
Transitional waters represent especially big chal-
lenges for typifying and intercalibration on a Euro-
pean scale, due to the heterogeneity of water bodies
including wide size spectra of both estuaries and
coastal lagoons with a large variety of connections to
the open sea and to continental waters. Defining site-
specific reference conditions is a novel approach that
allows minimizing uncertainties introduced by apply-
ing broad types. In large unique water bodies for
which long-term historical data exist, this approach
has been proved useful (Lyche Solcheim, 2005). With
the help of modelling, however, site-specific refer-
ence conditions can be determined also for a larger
variety of water bodies (e.g., within broad types) as
functions of watershed attributes. Carvalho et al.
(2009) recommend site-specific reference conditions
for chlorophyll in lakes in preference to type-specific
reference conditions, as they use the individual
characteristics of a site known to influence phyto-
plankton biomass, rather than adopt standards set to
generally represent a large population of lakes of a
particular type.
(ii) Difficulties finding appropriate metrics: In
1997, in an article that has became a classic in the
field of biomonitoring of surface waters, Karr & Chu
formulated most of the leading principles that form
the basis of the nowadays WFD: the concept of good
water status (‘biotic integrity’ in their terminology),
the need for a water body type-specific approach, the
supremacy of biological indicators and the assess-
ment scheme based on comparison of present status
with reference conditions. According Karr & Chu
(1997), selection of those among the multitude of
measurable biological attributes that provide reliable
and relevant signals about the biological effects of
human activities but remain insensitive to extraneous
conditions is a step of extraordinary importance. Only
these attributes are called metrics.
The authors warn about attempts of measuring all
possible attributes and argue that some attributes are
poor candidates for monitoring metrics because of their
underlying biology. In particular, they indicate abun-
dance, population size, density and production as
attributes that vary too much even in pristine areas to be
reliable indicators of human influence. According to
Karr & Chu (1997), the belief that biology is too
variable to be of practical use in monitoring comes not
from a lack of good indicators but from the fact that
studies of naturally variable attributes such as popu-
lation size, density and abundance have dominated
ecology for[50 years. They show also that ratios (e.g.,
of the abundances of two trophic groups), although
Hydrobiologia (2009) 633:197–211 201
123
they may intuitively seem useful, are inherently flawed
as they mix independent parameters in ways that make
it hard to discern their relative influence. Further, two
large numbers and two small numbers may yield the
same ratio, although the biological meaning of small
and large numbers may be very different. As one of the
rare exceptions, relative abundance (number of indi-
viduals in a taxonomic or other target group divided by
the total number of individuals in the sample) repre-
sents ratios that may reveal consistent dose–response
relationships.
Karr & Chu (1997) also show that a small number
of attributes of biological elements—such as taxa
richness and percentages of individuals belonging to
tolerant taxa—consistently emerge as reliable indi-
cators of biological condition at sites influenced by
different human activities in different geographic
areas.
Moss (2008) goes further from such a simple and
empirical division of ecological attributes into good
and bad metrics for measuring human impact and
formulates four primary characteristics of ecological
quality which intactness should be measured to
decide about impactedness of sites. These primary
characteristics include nutrient parsimony (efficiency
in recycling scarce materials), characteristic of phys-
ical settings and food web structure that ensure this
parsimony and maintenance of the intactness of the
system as a whole structure in its several aspects,
connectedness and size. Moss argues that secondary
features such as concentrations of substances or lists
of species do not adequately measure these funda-
mental characteristics, unless these are used in ways
to diagnose the state of the more fundamental
characteristics.
In the light of the above mentioned arguments by
Karr & Chu (1997) and Moss (2008), a question
arises as regards how to evaluate the common
practice of using chlorophyll concentration as one
of the main biological metrics in WFD implementa-
tion (Carvalho et al., 2009; Carstensen & Henriksen,
2009; Wolfram et al., 2009). On the one hand,
chlorophyll clearly belongs to the abundance/popu-
lation size or density attributes criticized for their
large variability, but, on the other hand, increase of
chlorophyll and algal biomass are symptomatic signs
of alteration in nutrient parsimony and food chain
structure related to eutrophication and as such are
included also in the normative definitions of
ecological status classes for all the surface water
categories. Obviously, Karr & Chu (1997) in their
division of biological attributes to suitable and non-
suitable metrics for measuring human impact had in
mind macroinvertebrates or fish rather than phyto-
plankton which, as a primary producer, has its own
specific features.
New concepts in ecology stemming from the
theory of ecosystem resilience and alternative stable
states affect also the selection of metrics and their
calibration against pressure gradients. As Borja et al.
(2009) note, the selection of ecologically relevant
attributes to be used within any methodology, should
emphasize metrics that respond to both degradative
and restorative anthropogenic action. One aspect that
complicates this approach is the different lags of
biotic metrics to changes in pressure. A long-term
study carried out in Lake Mondsee (Dokulil &
Teubner, 2005) showed that reductions in phyto-
plankton biovolume were delayed by about 5 years
relative to reduction in total phosphorus (TP) con-
centration while phytoplankton species differed in
timing of their responses to changing nutrient condi-
tions. While Planktothrix rubescens declined con-
comitantly with the decline in TP concentration, other
species indicative of higher phosphorus concentra-
tions, such as Tabellaria flocculosa var. asterionello-
ides, tended to increase further. In such situations, the
efficiency of restoration measures can be evaluated
differently depending on how closely the selected
metric follows the changes in pressure.
(iii) Are biological indicators surrogates for
chemical analyses?: For standing waters (lakes,
transitional and coastal waters), eutrophication is a
major pan-European problem and the biggest threat
for biodiversity (Watt et al., 2007) and reaching good
ecological status of surface waters (CIS, 2005).
Phytoplankton is the first group of organisms to
respond to nutrient enrichment with excessive growth
and shifts in community composition resulting in
increased turbidity, subsequent loss of submerged
aquatic vegetation and oxygen deficiency in bottom
waters. A number of trophic state indices have been
created based on simple parameters such as TP,
Secchi depth and chlorophyll concentration (Carlson,
1977) or scores of algal (LAWA, 1999) or macro-
phyte species (Schneider & Melzer, 2003) given to
them according to phosphorus ranges in which they
occur. Even the taxon-specific optima of littoral
202 Hydrobiologia (2009) 633:197–211
123
invertebrates along a TP gradient have been used to
develop an ecological classification model (Donohue
et al., 2009). The latter type of indices has been
criticized for being surrogates for driving pressures
(nutrients), against which they have been calibrated
(Moss, 2008). Moss points out that such pressures can
be independently chemically measured with greater
accuracy, but admits also that the biological commu-
nity has an integrating component that spot analyses
do not have. It seems to be rather a rule rather than an
exception that biological communities affected by
eutrophication show a delayed recovery in the
oligotrophication phase (Dokulil & Teubner, 2005;
Hajnal & Padisak, 2008; Padisak & Reynolds, 1998)
or do not reflect at all the decrease in phosphorus
(Kaiblinger et al., 2009; Noges et al., submitted) even
if indices initially calibrated against phosphorus are
used. Obviously, these phytoplankton indices are able
to capture ecological status in circumstances where
factors other than nutrients (e.g. changes in light
conditions, food chain or salinity; Borics et al., 2000;
Padisak et al., 2006) take over the control over
community structure creating a resistance to restora-
tion efforts.
A trophic index although relating community
composition to eutrophication pressure, cannot be
used for a WFD-compliant assessment of ecological
quality unless reference conditions and class bound-
aries are defined. The species list and scoring system
for species may remain the same for all lake types, for
example, in the Swedish (Willen, 2007) or Austrian
system (Dokulil et al., 2005) or different species lists
and sensitivities are applied for different types, for
example in German system (Mischke et al., 2008).
WFD represents a transition from chemically to
ecologically based assessment of water quality. In
principle, the ecological quality assessment must be
based on the structure and functioning of aquatic
ecosystems. Thus, there is a need to assess the impact
of toxic substances on aquatic populations and
communities. A probabilistic, community-based
approach for defining environmental quality and
assessing risk for ecosystems is to calculate the
number of species potentially affected by a given
concentration of a toxic chemical assuming that the
sensitivity of different species toward a given stress
factor (e.g. a toxic chemical) follows a normal
distribution (see Vighi et al., 2006 for summary).
The benefit of this approach is that it is based on the
structure of the biological communities present in a
given environment and not on toxicological data
produced on standard organisms. On the negative
side, data for such assessment of toxicity impacts on
community or population level are not yet available.
This would require deeper knowledge on structure
and functioning of natural communities as well as
toxicity data on a large number of organisms. At
present such data is available only for a very low
number of chemicals. On the other hand, toxicity
tests on the basic ecotoxicological test organisms like
algae, Daphnia, and fish, are no longer sufficient for
assessing toxicological stress on the communities
(Vighi et al., 2006).
(iv) Is there hope to discover new powerful
metrics?: Since the first attempts to use biological
indicators in water quality assessment (Kolkwitz &
Marsson, 1908, 1909), vast amounts of information on
biological indicators have been accumulated and
certain traditions established, e.g. that of using
macroinvertebrates for river assessments and phyto-
plankton for lakes. The implementation of the WFD
has induced a massive search for new biological
methods to measure the anthropogenic impact on
water bodies. We may ask: Is there any hope to
discover new powerful metrics or develop more
sensitive and selective methods? After 15 years’
research in selecting metrics for ecological status
assessment of water bodies, Karr & Chu (1997) came
to a striking conclusion that the same major biological
attributes arose recurrently and served as reliable
indicators in diverse circumstances. The recent pro-
liferation of indices is so extensive that the assessment
and comparison of their suitability for quality assess-
ment have become a new labour-intensive field for
researchers that adds an element of confusion back
into what environmental managers had hoped to
simplify (Borja et al., 2009). On the other hand, the
intensive research, especially in less traditional areas,
has already yielded and will yield in the future new
metrics, methods and analysing techniques more
specific for the widening gamma of pressures.
(v) Multimetric approaches for multivariately
determined conditions: One of such fast developing
areas is the construction of multimetric indices. The
theoretical basis of this approach has reached already
a maturity level where ‘cook books’ for designing
such indices (Hering et al., 2006) can be produced to
guide researchers to the best solutions and helping
Hydrobiologia (2009) 633:197–211 203
123
them to avoid the already known pitfalls. As the
relationships between occurrence of particular spe-
cies, genera or groups and environmental conditions
are multivariately determined (Moss, 2007), a multi-
metric index attempting to represent the multitude of
impacts on different biotic levels, ought to be the
adequate tool to measure the multiple human impair-
ments. By combining different categories of metrics
(e.g. taxa richness, diversity measures, proportion of
sensitive and tolerant species, trophic structure)
reflecting different environmental conditions and
aspects of the community, the multimetric assessment
is regarded as a more reliable tool than assessment
methods based on single metrics (Hering et al., 2006).
The best multimetric indices are more than a
community-level assessment because they combine
measures of condition in individuals, populations,
communities, ecosystems and landscapes (Karr &
Chu, 1997). Since the first multimetric index, the
Index of Biotic Integrity developed by Karr (1981),
which used fish as stream quality indicators, numerous
multimetric indices have been developed. In this
issue, the Austrian Macrophyte Index (Pall & Moser,
2009) based on metrics like ‘vegetation density’,
‘vegetation limit’, ‘characteristic zonation’, and ‘spe-
cies composition’ represents a multimetric approach.
A novel approach—an extension to environmental
science currently a matter of study—is the use of
Fuzzy Logic—a way of using linguistic variables to
describe and assess complex systems. It is becoming
popular in Spain in studies related to the implemen-
tation of the WFD (Ocampo-Duque et al., 2007; see
also Borja et al., 2009). One of the main advantages
of fuzzy logic is the ability to model expert human
knowledge, a necessary feature to be considered in
the complex process of environmental management.
In a case study where the fuzzy model approach was
applied in the Ebro River Basin (Ocampo-Duque
et al., 2006), the four components surveyed corre-
sponded rather well to the four primary characteris-
tics of ecological status listed by Moss (2008): total
riparian vegetation cover (= size), cover structure
(= characteristic structure in its several aspects),
cover quality (&nutrient parsimony), and channel
alterations (= connectedness).
(vi) Dominant versus less frequent taxa and the
question of taxa sensitivity: Discussing the informa-
tion that biological samples contain, Reynolds (1998)
wrote: ‘An experienced plankton scientist, confronted
with an undefined sample of phytoplankton under a
moderate quality microscope, would have little
difficulty in gleaning sufficient information from the
assemblage to be able to deduce a lot about the water
body from which it was collected—whether oligo-
trophic or eutrophic, acidic or alkaline, shallow or
deep, mixed or stratified and, in all probability, what
month of the year it was taken.’ The same is valid not
only for phytoplankton but also for other major
biological groups (or ‘elements’ in the WFD vocab-
ulary). The question is, which components of the
biological sample contain this information: is it coded
in the dominants or in some minor indicator species?
Based on a general assumption that a healthy
environment will have the species appropriate to it, a
study (Devlin et al., 2009) was carried out in the
United Kingdom to identify whether abundance and
species richness of 20 most frequently occurring
marine phytoplankton species were predictable across
seasons and typology, and whether the deviation
away from a reference condition in different risk
conditions was sufficient to apply phytoplankton
measurements into a management tool for assessment
of environmental quality. The preliminary study
showed that it may be possible to have one or very
few generic lists of species that should occur at a
particular time of year and could be used for
ecological assessment of marine waters.
On the other hand, using the most frequent species
with respect to ecological status classification has
been criticized (Rawson, 1956), as it appears that the
dominant species are often those with rather wide
tolerance (eurybionts), and thus, they may be even
less indicative of aquatic condition than the less
frequent species. In geobotany, the fidelity concept,
one of the most important aspects of the Braun-
Blanquet (1925) approach, has been widely used to
diagnose particular types of natural plant communi-
ties. Fidelity is the degree to which a species is
concentrated in a given vegetation unit, while the
most specialized ones, often occurring with medium
or low frequencies, are called diagnostic species that
are used to delimit associations. Their diagnostic
power, however, has been tested only for natural
environments (reference conditions) and cannot tell
us anything about human-caused degradation. In
order to find out, which species or metrics merit
watching for these signs, analysis should focus on
species tolerance and community changes across the
204 Hydrobiologia (2009) 633:197–211
123
range from minimal to severe human impact. This
approach has yielded several lists of aquatic organ-
isms divided into sensitive, indifferent and tolerant
taxa. In some cases, this search for indicators has led
to in-depth studies of a single species, applying
different metrics combined into a multimetric index
(Lopez y Royo et al., 2009).
Information on taxa sensitivity or tolerance has
been used in the assessment methods in various ways.
The mere presence of very sensitive taxa is a strong
indicator of good ecological status while their relative
abundance should not necessarily be high. Presence
alone of tolerant taxa, on the other hand, says little
about ecological status since tolerant groups inhabit a
wide range of places and conditions, but as conditions
deteriorate, their relative abundance rises (Karr &
Chu, 1997). Most community composition indices,
however, do not consider this difference and use the
abundance-based approach (species score multiplied
by abundance) for both sensitive and tolerant species.
Results of such approach will be strongly biased
towards the tolerance level of the dominant species.
Karr & Chu (1997) recommended that only about
10% of taxa in a region should be identified as
sensitive or tolerant avoiding the use of the remaining
70–90% taxa with intermediate tolerances, which
would swamp the strong signal coming from presence
of the most sensitive or most tolerant taxa. A
compromise option that takes into account both the
abundance and the diagnostic power of species is to
add a weighing factor to the index that depends on the
stenoecy, i.e. the species tolerance range, as it has
been done, for instance, in the German Phytoplank-
ton-Taxa-Lake-Index (Mischke et al., 2008).
One-out–all-out principle. What does the practice
to date show?
Until now, the focus of research supporting the
implementation of the WFD has been on the devel-
opment of individual indicators at the level of the
Biological Quality Element (BQE) or single param-
eters within a BQE; hundreds of such studies
proposing such indicators have appeared in the
scientific literature in recent years, including some
articles in this volume (e.g. Kaiblinger et al., 2009;
Ptacnik et al., 2009; Pall & Moser, 2009; Donahue
et al., 2009; Lopez y Royo et al., 2009). Also, the
intercalibration exercise has been carried out at the
BQE level. For the final classification of water
bodies, it is of crucial importance how classification
results for the different BQEs are combined in an
assessment of ecological status. The WFD prescribes
the ‘one-out–all-out’ approach, where the BQE
showing the worst classification determines the
ecological status. Moss et al. (2003) showed that
the one-out–all-out principle will tend to downgrade
sites unjustifiably, depending on the number of
metrics included in the assessment. Errors within
individual quality elements and metrics tend to show
considerable variation (Johnson et al., 2006). If these
are combined using the one-out–all-out principle,
reliable, precise metrics tend to be overruled by less
reliable metrics in a large proportion of water bodies.
Alternative approaches to the one-out—all-out prin-
ciple could be considered, where pressures are more
specifically taken into account. Now that WFD
monitoring programmes have been established in
most EU member states and data will be available, it
will be possible to evaluate the strengths and
weaknesses of the one-out–all-out and alternative
approaches.
Variability in ecological status assessment
and resulting classification
Ecological indicators typically exhibit non-linear
responses to anthropogenic pressures together with
great spatial and temporal variability, which underpin
emerging key characteristics of natural systems
(Solimini et al., 2009). Predicting the causes and
consequences of human activities on freshwater
ecosystems requires a quantitative assessment of the
level of uncertainty associated with our understand-
ing of ecological structure and processes. The
assessment based on Ecological Quality Ratios
(EQRs) ultimately results in the assignment of a
given site to a certain ecological status class.
However, to what extent are we confident that the
resulting classification is the true one for that site?
Here, the problem is to estimate the level of
confidence of the class assignment for a given site
or, in other words, the risk of site misclassification
which is relevant for decision makers.
The assessment of ecological status and the result-
ing classification of water bodies are complicated by
Hydrobiologia (2009) 633:197–211 205
123
the inherent variability of biological communities. In
the normative terms, the WFD refers to uncertainty
as ‘level of confidence’ and/or level of ‘precision’
when dealing with reference conditions (Annex II)
and when dealing with monitoring (Annex V). In the
first case, the methods and the number of sites used
to set spatially derived reference conditions must
provide a sufficient level of confidence about the
values for the reference conditions to ensure that the
conditions so derived are consistent and valid for
each surface water body type. In the case of
monitoring, estimates of the level of confidence and
precision of the results provided by the monitoring
programmes must be given in the river management
plan. The frequency of monitoring should be chosen
so that an acceptable level of confidence and
precision are achieved. Accordingly, several recent
articles on WFD compliant metrics, whole assess-
ment systems or reference conditions include an
estimation of uncertainty basically linked to spatial
or temporal factors (Kelly et al., 2009; Carstensen &
Henriksen, 2009; Carvalho et al., 2009; Erba et al.,
2009; Wolfram et al., 2009). However, the total
uncertainty associated with the classification of
ecological status reflects also technical, economical
and political constraints of the assessment methods
(Fig. 1).
Abiotic factors in freshwater ecosystems are
highly variable in time and space and often account
for a significant proportion of the variation of
community patterns in terms of species diversity,
abundance, biomass and production. Therefore, most
of the variances in EQR-derived classification prob-
ably derive from the unspecified sampling variability,
resulting from this spatial heterogeneity of abiotic
factors at multiple time scale that, in turn, affect the
biotic community structure. In addition, other sources
of variation include (Fig. 1): the choice of sampling
sites within a region or catchment (how many sites?),
the sampling effort (how many samples and of what
dimension?) and the frequency of sampling (how
often?). Imposed over the natural variation of
biological metrics, the human activities produce
different pressures that interact with abiotic and
biotic factors in shaping the structure of communities
and dissecting the natural from the human-induced
variance can be extremely difficult. A possible
strategy to reduce the overall uncertainty is to include
significant site-specific features in the models used,
e.g. to derive reference conditions (Carstensen &
Henriksen, 2009). The inclusion of site-specific
features will also provide more realistic boundary
values for managing specific water bodies as well as
provide more certainty in the boundary estimates
(Carstensen & Henriksen, 2009).
A variety of errors and biases can be introduced
into the final classification result when considering
also the various field and laboratory methods
Fig. 1 Sources of
uncertainty associated with
the classification of
ecological status of water
bodies
206 Hydrobiologia (2009) 633:197–211
123
(sampling design and collection, sorting, taxonomy)
and the metric used. Often the calculation of metrics
involve several intermediate steps, all with associated
errors and all potentially adding to the resulting
overall uncertainty. It should be emphasized that the
size of the various sources of error change depending
on the water bodies considered. For example,
lowland, deep and turbid rivers require assessment
techniques and have an associated variability that is
different from those used in wadeable piedmont
rivers or streams (see, for example Solimini et al.,
2000). Similarly, assessment systems of small lakes
might differ from those used for larger systems
(Solimini et al., 2008).
A degree of uncertainty is associated with both
components of EQR: the expected and the observed
value. The reference value of a given metric comes
with an associated error because of the difficulties of
defining the reference conditions for many water
bodies. Therefore, an assessment in the uncertainty
associated with the reference condition values should
also be included in the overall risk of misclassifi-
cation of a site. It is clear that metrics should be
selected after examining their variability in natural,
undisturbed conditions. For example, Erba et al.
(2009) supposed that the highest metric variability
due to natural factors can be observed at reference
sites. Metrics too variable, even at reference sites, are
unlikely to be effective for the assessment programs.
Although, relevant typology factors of water bodies
can be included to diminish variability in reference
values for ecological measures, variability may
remain high. For example, a recent assessment of
TP values in a large dataset of reference European
lakes led to coefficient of variation ranging from 1%
to over 69% depending on the lake type and sample
size (Cardoso et al., 2007). The same authors studied
a regression model to predict reference values for TP
in European lakes from simple edaphic factors, which
gave a variance explained of 51%, similar to other
models present in literature (Cardoso et al., 2007). In
another recent article, Carvalho et al. (2009) describe
the development of a series of regression models for
predicting reference chlorophyll concentrations on a
site-specific basis. None of the regression models
developed has a particularly strong predictive ability,
and the authors speculate that uncertainty arises from
errors in the data used to develop the models
(including natural temporal and spatial variability in
data) and also from additional explanatory variables
not considered in the models, particularly nutrient
concentrations, retention time and grazing (Carvalho
et al., 2009). Also Wolfram et al. (2009) found high
variability (with r2 ranging between 0.33 and 0.40)
when regressing TP and total biovolume (e.g. algal
biomass) even on a larger TP range. Nevertheless,
site-specific reference conditions should result in
reduced error in ecological status classifications,
particularly for lakes close to typology boundaries
(Carvalho et al., 2009). Water managers may face the
problem of deciding whether the uncertainty associ-
ated with the predicted average value is small enough
to detect changes with the actual lake conditions.
For decision makers, the importance of the risk of
misclassification of a given site depends on the
context of the decision to be taken and increases with
larger spatial scales and longer time horizons. In the
case of ecological data, the complexity of error
budget and the magnitude of resulting uncertainty
estimates may be very large and so the necessary
effort (e.g. the cost) for its estimation. For this reason,
many forms of uncertainty are not acknowledged in
the models that support decisions or, in some cases,
are ignored altogether (Burgman et al., 2005; but see
Kelly et al., 2009). Recently, ecologists have become
more and more sophisticated in realizing suitable
metrics that are stable and robust enough to assess
ecological status in a reliable manner (see Ptacnik
et al., 2009; Kelly et al., 2009) but it is also necessary
that the quantification of EQR related uncertainty is
implemented in future assessment programs. Notably,
Kelly et al. (2009) found that variability (expressed as
the standard deviation of samples through time) could
be modelled using a polynomial function, from which
the risk of misclassification could be calculated.
Moreover, in general, if the EQR assessment outcome
can be incorporated into a modelling framework
resulting in an overall estimation of the risk of
misclassification, then the related uncertainty might
be assessed through careful evaluation of model
predictions. A possible approach is to account for as
many forms of uncertainty as possible (such as error
propagation and sensitivity analyses see, for example
Blukacz et al., 2005; Lo, 2005) and to use several
modelling frames and examine whether the choice
makes a difference to management decisions (Burg-
man et al., 2005). Advanced computational tech-
niques, such as fuzzy logic or neural networks, may
Hydrobiologia (2009) 633:197–211 207
123
be effective in dealing with the sources of uncertainty
that affect the process of metric development (Borja
et al., 2009).
Acknowledgements The study was supported by EU FP7
grant 226273 (WISER). Special thanks go to Dr. Judit Padisak
for her valuable comments and suggestions.
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Author Biographies
Peeter Noges (b. 1957)
graduated from Tartu Uni-
versity, Estonia (PhD:
1987), biologist–algologist,
leading researcher at Esto-
nian University of Life
Sciences. In the period from
2003 to 2009 he worked as
a national expert and con-
tractual agent at the Insti-
tute of Environment and
Sustainability, Joint
Research Centre of Euro-
pean Commission in Ispra, Italy. His main research areas are
ecology of shallow lakes and the impact of climate change on
lake ecosystems. He was one of the guest editors of special
volume of Hydrobiologia 599 dedicated to European large
lakes, reprinted in Developments in Hydrobiology 199.
210 Hydrobiologia (2009) 633:197–211
123
Wouter van de Bund(PhD: University of
Amsterdam 1994) is an
aquatic ecologist, currently
employed as a scientific
officer at the Institute of
Environment and Sustain-
ability, Joint Research Cen-
tre of European Commission
in Ispra, Italy. As the co-
leader of the Working Group
on Ecological Status under
the Common Implementa-
tion Strategy of the Water Framework Directive, his field of study
is focussed on harmonization of ecological quality assessment
systems in Europe.
Ana Cristina Cardoso (b.
1966) graduated at the
University of Algarve, Por-
tugal (1991; PhD: 1999),
aquatic ecologist. Since
then, she has been a scien-
tific officer at the Institute
of Environment and Sus-
tainability, Joint Research
Centre of European Com-
mission in Ispra, Italy. She
is currently Action leader of
the Action European Eco-
logical Water Quality assessment and Intercalibration (EE-
WAI), supporting the implementation of the Water Framework
Directive (WFD). Her main research area is ecology of lakes in
relation to the impact from nutrients.
Angelo G. Solimini (degree
in Biology, 1993; PhD in
Animal Biology, 1999) is
currently researcher in
Environmental Health at
Sapienza University of
Rome. His research and
teaching interests are the
environmental impact
assessment in aquatic eco-
systems, water-related dis-
eases, the structure and
functioning of aquatic food
webs and their relation with human pressures. He has been
involved in several European projects and working groups
supporting the WFD implementation and guest editor of a
special issue in Freshwater Biology on structure and func-
tioning of running water ecosystems. Solimini has published
about 60 scientific articles, book chapters, reviewed reports and
commentaries.
Anna-Stiina Heiskanen (b.
1961) graduated from Uni-
versity of Helsinki, Finland
(PhLic: 1991; PhD: 1998),
marine biologist. She has
worked at Finnish Environ-
ment Institute (SYKE), at
the Finnish Institute of
Marine Research, at the
universities of Helsinki and
Oslo, and at the Academy
of Finland. For eight years
(2001–2008), and also
worked as a scientific officer at the Institute of Environment
and Sustainability, Joint Research Centre of European Com-
mission in Ispra, Italy. Her field of profession was research and
coordination of ecological quality classification of surface
waters, and she led the Action European Ecological Water
Quality Assessment and Intercalibration (EEWAI). Since 2008,
she is a research manager of the SYKE Marine Research
Centre that aims at evaluating the state of the Baltic Sea and its
coastal waters and also the effectiveness and adequacy of
environmental conservation measures.
Hydrobiologia (2009) 633:197–211 211
123