Drawing together multiple lines of evidence
from assessment studies of hydropeaking
pressures in impacted rivers
Andreas H. Melcher
, Tor H. Bakken
, Thomas Friedrich
, Franz Greimel
, Nona Humer
, Bernhard Zeiringer
, and J. Angus Webb
Institute of Hydrobiology and Ecosystem Management, University of Natural Resources and Life Sciences (BOKU),
1180 Vienna, Austria
SINTEF Energy Research, 7465 Trondheim, Norway
Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010, Australia
Abstract: Hydropeaking has negative effects on aquatic biota, but the causal relationships have not been studied
extensively, especially when hydropeaking occurs in combination with other environmental pressures. The avail-
able evidence comes mainly from case studies demonstrating river-speciﬁc effects of hydropeaking that result in
modiﬁed microhabitat conditions and lead to declines in ﬁsh populations. We used multiple lines of evidence to
attempt to strengthen the evidence base for models of ecological response to ﬂow alteration from hydropeaking.
First, we synthesized evidence of ecological responses from relevant studies published in the scientiﬁc literature.
We found considerable evidence of the ecological effects of hydropeaking, but many causal pathways are poorly under-
stood, and we found very little research on the interactive effects of hydropeaking and other pressures. As a 2
of evidence, we used results from analyses of large-scale data sets. These results demonstrated the extent to which
hydropeaking occurs with other pressures, but did not elucidate individual or interactive effects further. Thus,
the multiple lines of evidence complemented each other, but the main result was to identify knowledge gaps regard-
ing hydropeaking and a consequent pressing need for novel approaches, new questions, and new ways of thinking that
can ﬁll them.
Key words: Eco Evidence, evidence-based practice, systematic literature review, conceptual model diagrams, ﬁsh,
hydropeaking, hydroelectric power
Global demand for energy is rising, and interest in renew-
able sources of electricity, among which hydroelectric power
is prominent worldwide, is increasing (Wagner et al. 2015,
Zarﬂet al. 2015). However, dams built for hydroelectric power
production are not environmentally benign and have strong
negative effects on ﬁsh and other aquatic fauna. In Europe,
complementary environmental risk and impact assessments
are essential to meet the major aims of the EU Water Frame-
work Directive (WFD) by 2020 (European Commission 2000,
Birk et al. 2012, Hering et al. 2015).
Flow variability is an intrinsic feature of river systems
and is essential for their ecological function (Poff et al. 1997,
Bunn and Arthington 2002). In general, ﬂow ﬂuctuations
caused by hydropeaking are often much more severe than
those experienced in natural ﬂow systems (e.g., Parasiewicz
et al. 1998, Saltveit et al. 2001, Scruton et al. 2003, 2008,
Smokorowski et al. 2011, Young et al. 2011, Nagrodski et al.
2012). Hydropeaking is the rapid rise and fall of discharge
levels when hydroelectric plants are switched on and off, typ-
ically in response to subdaily changes in demand for elec-
*BRIDGES is a recurring feature of FWS intended to provide a forum for the interchange of ideas and information relevant to FWS readers, but beyond
the usual scope of a scientiﬁc paper. Articles in this series will bridge from aquatic ecology to other disciplines, e.g., political science, economics, education,
chemistry, or other biological sciences. Papers may be complementary or take alternative viewpoints. Authors with ideas for topics should contact BRIDGES Co-
Editors, Sally Entrekin (firstname.lastname@example.org) and Allison Roy (email@example.com).
DOI: 10.1086/690295. Received 22 July 2016; Accepted 27 October 2016; Published online 8 December 2016.
Freshwater Science. 2017. 36(1):220–230. © 2017 by The Society for Freshwater Science.
tricity. Hydropeaking causes rapid and large changes in the
subdaily ﬂow regime of rivers (amplitude, rate, frequency,
and timing of ﬂow ﬂuctuations) and is evident from hydro-
graph data (e.g., Greimel et al. 2016). Not all hydropower
plants cause hydropeaking, and among hydropeaking dams,
the level of hydrological effects vary depending on opera-
tional regime and mitigations used. In Austria, ~800 km
of rivers are affected by hydropeaking. Thus, hydropeaking
is not a local pressure, but affects long river stretches (e.g.,
Schmutz et al. 2015).
Fish are affected by hydrological impacts from hydro-
electric power facilities, including hydropeaking (Schmutz
et al. 2015). Ecological effects are severe, but we have little
detailed understanding of the causal mechanisms involved
(Harby and Noack 2013, Forseth and Harby 2014, Bruder
et al. 2016). Hydroelectric power is being marketed as a sus-
tainable form of electricity production, and we need to un-
derstand these mechanisms better so that environmental
effects of hydropeaking can be mitigated (e.g., Moog 1993,
Young et al. 2011).
Many natural environments are affected by multiple hu-
man pressures. Eighty percent of European rivers are af-
fected by altered water quality, hydrology, morphology,
or river connectivity. In 47% of these cases, rivers suffer
from >1 such stressor, and 12% suffer from all 4 stressors
(Schinegger et al. 2012). Human-induced stressors to rivers
can have serious consequences for aquatic life, e.g., ﬁsh
(Dudgeon et al. 2006, Pont et al. 2006, Birk et al. 2012, Eu-
ropean Union 2015), but not all of the potential effects are
well enough understood to guide decisions related to actions
that might alter human pressures on rivers.
Expert-knowledge-based conceptual models of poten-
tial effects of stressors can provide a starting point to guide
decision-making regarding how to manage rivers. Multiple-
lines-of-evidence studies can improve the scientiﬁcunder-
pinnings of such models. Results from case studies can be
combined with monitoring or experimental data to build con-
ceptual models that allow scientists to ask research ques-
tions regarding individual or interacting pressures. In Eu-
rope, such models are becoming increasingly important for
understanding the effects of single- and multistressor im-
pacts in aquatic environments (Feld et al. 2011, Marzin et al.
2014, Hering et al. 2015).
Scientists working within the context of several Euro-
pean projects (e.g., http://eﬁ-plus.boku.ac.at/, http://mars
-project.eu, http://www.cedren.no/Projects/EnviPEAK, http://
hydropeaking.boku.ac.at/) have explored literature-based ev-
idence on effects of multiple pressures and hydropeaking
on ﬁsh to complement data analyses from ﬁeld and artiﬁcial-
channel experiments. In this paper, we build on the methods
these investigators used to synthesize data from gray lit-
erature (i.e., unpublished reports), published peer-reviewed
studies, and data analyses. We chose to focus on the Euro-
pean context because the drive toward renewable energy
and hydropower production in Europe is clashing with the
WFD objective of achieving good ecological status in riv-
ers by 2020. The collated evidence is intended contribute
to the investigation of multiple stressor effects in European
waterways under the MARS project (Managing Aquatic
ecosystems and water Resources under multiple Stress; http://
mars-project.eu), and in particular, to the design of a diag-
nostic tool supporting management of multiple stressors
in aquatic systems under the WFD. In that context, and
within the focus of this BRIDGES cluster, we addressed the
utility of the multiple-lines-of-evidence approach. In par-
ticular, we assessed whether rapid evidence assessment im-
proved our understanding of the ecological effects of hydro-
peaking, including when it occurs in combination with other
METHOD FOR EVIDENCE SYNTHESIS
We were guided by the Eco Evidence method (Norris
et al. 2012) to build a Driver- Pressure-State conceptual model
(DPS) based on evidence in the literature (EEA 2007, Feld
et al. 2011, Humer 2016). We also analyzed existing ﬁeld
data to illustrate how literature-based results might be sup-
plemented by de novo analyses.
We used the results of 3 published literature reviews on
the effects of hydropeaking (Zitek et al. 2006, Bakken et al.
2012, Schmutz et al. 2013). The reviews were undertaken
independently, and their authors focused on literature that
was available online, including review papers and reports
(in multiple languages). Schmutz et al. (2013) also used the
collection of hard-copy papers at the University of Natural
Resources and Life Sciences (BOKU University), Austria. The
authors searched journals systematically on Google Scholar
and ISI Web of Knowledge (Thomson Reuters, Philadelphia,
Pennsylvania) using combinations of the key words: “ﬁsh”,
“benthic invertebrates”,“biota”,“hydropeaking”,“ﬂow ﬂuc-
tuation”,“ecological status”,“river”,and“freshwater”. None
of the authors provided more detail on their search strategies
(e.g., speciﬁc combinations of key words, dates searched), lim-
iting repeatability. We extended the search results with ‘snow-
ball’searches in which we examined references in relevant
papers, and we updated the collection of references based
upon our knowledge of recent literature and suggestions from
colleagues and reviewers.
We searched the initial collection of references for evi-
dence validating hydropeaking cause–effect relationships for
a number of biological indicators (e.g., ﬁsh, benthic inverte-
brates) relevant to the European context (i.e., similar species
or river types). We cross-tabulated the retained literature
results and potential causal relationships in an abiotic and
biotic state interaction matrix and synthesized them into a
DPS conceptual model. We stored information on study type
and location (e.g., waterbody type, ecoregion, biota, pressure
types, causes and effects, experimental design scale) in an
Eco Evidence Database (based on Zitek et al. 2006, Webb
et al. 2015) and uploaded all papers to Mendeley (and open-
Volume 36 March 2017 | 221
access hydropeaking group) so that they would be available
for further use by any interested researchers.
Second, the lack of direct evidence regarding the effect
of multiple stressors from the standardized review led us to
conduct analyses of data from a large-scale ﬁeld-sampling
data set (http://eﬁ-plus.boku.ac.at/; Schinegger et al. 2016).
The EFI1database includes information on ﬁsh, environ-
mental variables, and various human pressures relevant to
the WFD (e.g., hydrology, morphology, connectivity, or water
quality). Data were compiled from 14 European countries,
3100 rivers, and 9330 ﬁsh sampling sites (Schinegger et al.
NARRATIVE SYNTHESIS OF THE
Below, we provide an overview of the review results, but
this presentation is not comprehensive, partly because of
limited space within this cluster. Instead, it serves to show
what the review achieved, and why it was necessary to in-
clude empirical data analysis.
Seventy-eight of 186 articles (from 16 countries) found
in the initial literature searches contained empirical evidence
of hydropeaking impacts on ﬁsh (Fig. 1). The most com-
mon countries from which information on hydropeaking
was found were: USA (45), Switzerland (21), Canada (19),
and Norway (17), followed by Austria (12) and France (11)
and 24 multiple-country studies. The literature review showed
that even partial hydropeaking operations (i.e., hydropeak-
ing in river sections above a ﬁsh sampling site, but that
has only minor effects on hydrology at the sampling site)
have signiﬁcant effects on river geomorphology and biota
(e.g., Smokorowski et al. 2011, Young et al. 2011, Nagrodski
et al. 2012, Harby and Noack 2013, Hauer et al. 2014). Fur-
ther, ﬂow ﬂuctuation rates (e.g., ramping rate: the rate of
stage change) of >~15 cm/h affect ﬁsh assemblages in small-
and medium-sized rivers (Schmutz et al. 2015). Stranding
of organisms is one of the most obvious negative effects
of hydropeaking (e.g., Young et al. 2011, Nagrodski et al.
2012, Harby and Noack 2013, Hauer et al. 2014), although
less is known about the sublethal and long-term effects of
stranding (Nagrodski et al. 2012). A signiﬁcant relationship
between ﬁsh abundance and peak velocity was reported
(Young et al. 2011). Peak velocity causes ﬂushing, leading
to ﬁsh depletion (Schmutz et al. 2015).
Only a few authors focused on the effect of hydropeak-
ing at the community, functional system, or food-chain level
(e.g., Lauters et al. 1996, Flodmark et al. 2002, Lagarrigue
et al. 2002, Robertson et al. 2004, Vehanen et al. 2005, Puffer
et al. 2015). In general, we found little evidence on the ef-
fects of hydropeaking for non-salmonids (e.g., Vehanen and
Lahti 2003, Bond et al. 2015).
Most studies showed that nighttime hydropeaking has
a greater impact on ﬁsh than equivalent ﬂow variation dur-
ing the day (e.g., Sempeski and Gaudin 1995, Bradford 1997).
Moreover, although nocturnally active species may be less
Figure 1. Classiﬁcation and number of hydropeaking studies from the standardized literature search (total 5186). Shaded
portions of the bars represent the 78 studies used to develop the Driver–Pressure–State (DPS) conceptual model (Fig. 2) and the biotic–
abiotic interaction matrix (Table 1). Published case study 5peer-reviewed observational ﬁeld study published in a journal or book,
unpublished case study 5observational ﬁeld study in a report, review 5review of published and unpublished literature in a scientiﬁc
journal, experimental study 5laboratory ﬂume or ﬁeld study in which ﬂow was manipulated, methodological study 5paper/report that de-
scribes and synthesizes techniques related to hydropeaking research, thesis 5MS or PhD thesis, policy article 5government document
related to managing hydropeaking.
222 | Rapid evidence synthesis on hydropeaking A. H. Melcher et al.
likely to be stranded at night than during the day, this
difference can be reversed for salmonids at higher water
temperatures (e.g., Halleraker et al. 2003, Flodmark et al.
Rivers with intense hydropeaking operations, character-
ized by a high ramping rate, extreme water-level variation
including dewatering, high ﬂow peak frequency (number
of peaks per year), and rapid changes (decreases) in the
ramping rate, showed the most negative effects on ﬁsh as-
semblages and their life stages, including spawning and
successful reproduction, especially when habitat was lost
or conditions were poor (e.g., Berland et al. 2004, Hauer
et al. 2013, Person et al. 2014, Schmutz et al. 2015, Casas-
SYNTHESIS OF MULTIPLE PRESSURES
AND EMPIRICAL DATA ANALYSIS
Direct evidence of the interactive effects of other pres-
sures with hydropeaking was difﬁcult to identify in the lit-
erature review. Authors of most of the hydropeaking ﬁeld
studies focused on a single river (e.g., Young et al. 2011,
Harby and Noack 2013). Single rivers are often affected
by multiple pressures, but the lack of replication across en-
vironmental gradients made disentangling the effects of
such stressors impossible within those studies. For exam-
ple, no investigators have used multiple systems and pres-
sures in a comparative framework to study stranding in the
context of hydropeaking (e.g., Young et al. 2011, Nagrodski
et al. 2012, Harby and Noack 2013).
A few authors included consideration of multiple stress-
ors in their discussion sections but did not provide empirical
data. These authors contended that hydropeaking, in com-
bination with river channel straightening and simpliﬁca-
tion (channelization), has severe negative effects (e.g., Moog
1993, Smokorowski et al. 2011, Bruno et al. 2013, Schmutz
et al. 2013, Kennedy et al. 2016). Channelization signiﬁ-
cantly increases loss of habitat and inundation frequency,
and hydropeaking increases scouring and substrate embed-
dedness (e.g., Hauer et al. 2013).
The EFI1data set contained evidence of many inde-
pendent, but co-occurring human pressures and impacts
on ﬁsh but did not enable us to assess their relative impor-
tance or interactive effects (Schinegger et al. 2012, 2013,
Trautwein et al. 2013). A maximum of 12 independent pres-
sure types was found in rivers affected by hydropeaking.
scale categories: hydrology (number of pressure types [n]54),
morphology (n53), water quality (n53), and river connec-
tivity (n52). In addition, ﬁsh sampling sites affected by
hydropeaking (n5632) were affected by a mean of 5.5 other
pressures types (Fig. 3A), whereas 8698 sites not affected
by hydropeaking experienced fewer additional pressures
(mean 53.5 pressure types). Sites partially affected by hy-
dropeaking (n5254) experienced an intermediate number
of additional pressure types (mean 54.9; Fig. 3A). This re-
sult reﬂects the reality that hydroelectric power develop-
ment generally occurs in concert with other forms of hu-
man exploitation of river systems. Species richness of sensitive
ﬁshspecies unable to tolerate habitatdegradation (Segurado
et al. 2011) was lower at sites affected by hydropeaking
(Fig. 3B). Results were much more variable for sites affected
by partial hydropeaking (cf. error bars in Fig. 3B).
Acceptance that hydropeaking causes ecological dam-
age is growing (e.g., Harby and Noack 2013, Forseth and
Harby 2014, Bruder et al. 2016). Nevertheless, in the ab-
sence of strong evidence, few general principles exist for
how best to restore ﬂow regimes while retaining the ben-
eﬁts of hydroelectric power (Bruder et al. 2016). In envi-
ronmental management, identifying the most likely causes
of an observed environmental impact is important for plan-
ning and implementing remediation actions. Ecological re-
sponse models backed by rigorous and transparent evidence
assessment can be used to inform management of hydro-
peaking dams for both environmental and human outcomes.
Our literature review provided many examples of the nega-
tive effects of hydropeaking, but quantifying the response
of speciﬁc biological metrics (e.g., the number of intolerant
ﬁsh species) to speciﬁc changes in the river and habitat was
difﬁcult, especially for different river types. This difﬁculty is
compounded when one attempts to use the existing scien-
tiﬁc literature to assess the generality of results of local ﬁeld
studies. In addition, when investigators use reductionist ap-
proaches and study single human stressors, quantifying and
prioritizing the interactive effects of multiple co-occurring
humanpressuresisextremelydifﬁcult. This difﬁculty mo-
tivated our use of a large-scale data set as a 2
line of ev-
idence in our analysis. This approach enabled us to demon-
strate the prevalence of multiple stressors, but it still did not
enable us to achieve the primary goal of our study, which
was to better elucidate the individual and interactive effects
The methods for evidence synthesis reported in our
paper were developed speciﬁcally for this case study be-
cause no standard method was available. The steps de-
scribed above (literature synthesis supplemented by empir-
ical data) were an attempt to synthesize existing evidence on
the individual and interactive effects of hydropeaking rap-
idly, systematically, and transparently. Two lines of evi-
dence are less than what might normally be considered in
a multiple-lines-of-evidence study (Downes et al. 2002), but
the restriction was caused by the rapid nature of the evi-
dence synthesis undertaken. Our assessment also was re-
stricted to some degree by the fact that it was built on
3 existing reviews. Authors of those reviews did not spec-
ify their search methods or the criteria used to include or
Volume 36 March 2017 | 223
exclude studies from detailed consideration, thereby greatly
reducing the transparency of any conclusions reached. We
recommend that, at a minimum, search methods (dates,
databases, key words) and criteria for inclusion/exclusion
of studies should be reported along with the results.
We identiﬁed substantial amounts of evidence for the
individual effects of hydropeaking, but little information on
the direct pathways linking cause to effect, the interactive
effects of multiple pressures combined with hydropeaking,
or effects on nonsalmonids. Detailed categorization of the
evidence into an abiotic–biotic state interaction matrix of
the evidence (Table 1, Fig. 2) can be used to identify impor-
tant information gaps currently preventing better-informed
decisions. These gaps include the interactive effects of other
pressures with hydropeaking. We conclude that the rapid
evidence synthesis done here was enough to identify the
existence of evidence (or a lack of evidence), but did not
achieve its primary goal because of: 1) the small amount of
evidence on interactive effects of hydropeaking, and 2) the
lack of a speciﬁc method for combining such data to dis-
entangle the effects of multiple pressures. Personnel work-
ing on the MARS project are developing a European data-
base on ecological effects of multiple stressors in European
rivers (Hering et al. 2015) and a method to synthesize ev-
idence on these issues that will be more rigorous than the
ad hoc approach reported here. The standard methods and
tools for synthesis of evidence in the literature from the
USA (Norton et al. 2008) and Australia (Norris et al. 2012,
Webb et al. 2015) also may be able to inform development
of a future standardized method (Webb et al. 2017).
Despite ongoing progress elucidating multiple stressors
in European rivers, Europe presents novel challenges for
synthesizing literature evidence. Peer-reviewed literature on
hydropeaking comes mainly from North America. Studies
from Europe are more difﬁcult to access because they are
mainly published as government reports, often in European
languages other than English (German, French, Italian, or
Norwegian). English language bias and gray literature biases
Table 1. Interaction matrix and classiﬁcation of 78 references based on the Driver–Pressure–State (DPS) conceptual model, which con-
tained empirical data from the standardized review (see Fig. 2). These empirical data illustrate the speciﬁc causal linkages not shown in
Fig. 2. Numbers in the cells are the number of studies that contained empirical evidence on the combination of hydropeaking related
stressors (abiotic factors and state) and biological responses (biotic state). Many studies are counted more than once in the table be-
cause the authors studied multiple combinations. Citations from 2005 to 2015 are provided.
Fluctuation amplitude 27 26 27 21 24 17 11
Ramping rate 23 19 19 16 16 15 8
Frequency of peaking 11 13 13 8 12 8 5
Timing 22 29 20 19 21 18 9
13 13 12 13 8 12 5
Sediment type 8 7 9 19 7 8 4
Turbidity 16 12 13 14 11 9 5
Temperature 18 12 9 14 7 10 5
Number with evidence
138 131 122 124 106 97 52
Total 34 33 29 26 25 21 12
Examples (2004–2015) b, h, m, n,
o, q, r, v, w,
x, bb, cc,
dd, jj, kk
e, h, j, l, p,
v, x, y, aa,
cc, dd, ee,
gg, ii, jj, kk
b, f, q, s, y,
aa, cc, dd,
ff, gg, hh, jj,
b, d, v, x,
y, jj, kk, cc
a, b, c, f,
h, i, k, y, z,
aa, cc, dd,
ff, gg, jj, kk
b, g, l, u,
v, y, dd,
ee, jj, kk
f, h, y,
gg, jj, kk
Arnekleiv et al. 2006,
Bell et al. 2008,
Bond and Jones 2015,
Bond et al. 2015,
Casas-Mulet et al. 2014,
Clarke et al. 2008,
Fette et al. 2007, Flodmark et al.
Garcia et al. 2011,
Golder Associates 2015,
Harby and Noack 2013,
Hauer et al. 2014,
Heggenes et al.
Irvine et al. 2009,
Jones and Stuart 2008,
Korman and Campana 2009,
Marty et al. 2009,
McMichael et al. 2005,
Murchie et al. 2008,
et al. 2012,
Person et al. 2014, Puffer et al.
Sauterleute 2009, Schmutz et al.
Scruton et al. 2008, Smokorowski
Ugedal et al. 2008,
Vehanen et al. 2005,
Young et al. 2011,
Zitek et al. 2006.
224 | Rapid evidence synthesis on hydropeaking A. H. Melcher et al.
(e.g., Bauersfeld 1978, Baumann and Klaus 2003, Bakken et al.
2012, Baumann et al. 2012, Person 2013, Schmutz et al. 2013,
Golder Associates 2015) create problems related to access
to information. These issues may partly explain why we
uncovered comparatively little quantitative evidence on the
effects of hydropeaking, and essentially no evidence on the
interactive effects of other pressures with hydropeaking.
In light of these results, we moved beyond the assessment
Figure 2. A conceptual Driver–Pressure–State (DPS) model summarizing the results from the standardized literature review.
Results are organized hierarchically to show how drivers and pressures link (via inﬂuencing factors) to ecological responses on ﬁsh,
all of which can be assumed to be negative changes in the state variable listed. The arrows and numbers show the number studies
with evidence for that response.
Volume 36 March 2017 | 225
of literature and used empirical data analyses as a 2
of evidence. This additional evidence was still insufﬁcient
to fulﬁll the original goal of the evidence synthesis, but our
incremental approach highlights the advantage of being able
to consider additional lines (e.g., sources) of evidence when
an initial line of evidence is insufﬁcient to reach a conclusion.
Further research and development could lead to an eco-
logical ontology to enhance the searching, sharing, and un-
derstanding of evidence (Ziegler et al. 2015). This ontology
might improve our ability to locate literature sources of ev-
idence constrained by language or publication type in Eu-
rope or elsewhere. Together with large-scale empirical data
sets, this improved ability would provide additional analyti-
cal strength when investigating large-scale patterns and eco-
logical responses to multiple environmental stressors. The
interactive effects of hydropeaking with other pressures have
deﬁed elucidation for many years (Harby and Noack 2013),
and the evidence synthesis we presented does not advance
knowledge in this area. Future advances in our understand-
ing of this area will require novel approaches and new ways
of thinking. One possibility is a greater focus on process-
based studies, potentially in laboratory ﬂumes, that can
directly elucidate causal mechanisms. Another would be
research on cascading ecological consequences caused by mul-
tiple human pressures. These cascading effects could in-
clude changes of hydrology and morphology, continuum dis-
ruption, water quality, and climate change, all of which may
inﬂuence the diversity and resilience of the biota in rivers
subjected to multiple impacts (e.g., Feld et al. 2011, Hering
et al. 2015, Nõges et al. 2015). Such research, evidence data-
bases, and causal analysis methods have the potential to
revolutionize evidence-based practice in environmental man-
agement and policy in Europe.
Author contributions: AHM wrote and structured the man-
uscript following many meetings with THB, TF, FG, NH, SS, BZ
and JAW. All authors provided input and revision to the submitted,
revised and earlier versions.
This work is part of the EnviPEAK project (Effects of rapid
and frequent ﬂow changes) implemented at CEDREN (Centre for
Environmental Design of Renewable Energy) Norway (http://
www.cedren.no/Projects/EnviPEAK) and the MARS project funded
under the 7
EU Framework Programme, Theme 6 (Environment
including Climate Change), Contract Number 603378 (http://
www.mars-project.eu). The data were drawn from the EU research
project “Improvement and Spatial extension of the European Fish
Index (EFI1)”, supported by the European Commission under the
Framework Programme (FP 6) contributing to the implemen-
tation of task “Ecological Status Assessment—ﬁlling the gaps”,Con-
tract Number 044096 (http://eﬁ-plus.boku.ac.at). We thank all ed-
itors, referees, Sue Norton, Sue Nichols, Michael Peat, and Tim
Cassidy for their helpful comments, support, and discussion.
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