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Response of fish communities to multiple pressures: Development of a
total anthropogenic pressure intensity index
Sandra Poikane
a,
⁎, David Ritterbusch
b
, Christine Argillier
c
,WitoldBiałokoz
d
, Petr Blabolil
e,f
,JanBreine
g
,
Nicolaas G. Jaarsma
h
, Teet Krause
i
, Jan Kubečka
e
,TorbenL.Lauridsen
j
,PeeterNõges
i
,
Graeme Peirson
k
, Tomas Virbickas
l
a
European Commission Joint Research Centre, Directorate for Sustainable Resources, Water and Marine Resources Unit, I-21027 Ispra, VA, Italy
b
Institute of Inland Fisheries, Im Königswald 2, 14469 Potsdam-Sacrow, Germany
c
Irstea, UR RECOVER, 3275 Route de Cézanne CS 40061, 13182 Aix en Provence Cedex 5, France
d
Inland Fisheries Institute, Oczapowskiego 10-719, Olsztyn, Poland
e
Institute of Hydrobiology, Biology Centre of the Czech Academy of Sciences, Na Sádkách 7, 370 05 České Budějovice, Czech Republic
f
Faculty of Science, University of South Bohemia, Branišovská 31, 370 05 České Budějovice, Czech Republic
g
Research Institute for Nature and Forest, Dwersbos 28, B-1630 Linkebeek, Belgium
h
Nico Jaarsma E&F, Klif 25, Den Hoorn, Texel, The Netherlands
i
Centre for Limnology, Institute of Agriculturaland Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51014 Tartu, Estonia
j
Department of Bioscience, Aarhus University, Vejlsøvej 25, 8600 Silkeborg, Denmark
k
Environment Agency, Kidderminster DY11 7RA, UK
l
Nature Research Centre, Akademijos 2, LT-08412 Vilnius-21, Lithuania
HIGHLIGHTS
•Creating a common fish-based assess-
ment system for European lakes has
failed so far.
•Fishes react in a holistic way to a broad
range of cumulative pressure impacts.
•We created a combined pressure index
(TAPI) that reflected fish ecological
quality.
•TAPI includes eutrophication,
hydromorphological alterations and
lake-use intensity.
•TAPI correlated well with 8 out of 10
national lake fish indices tested.
GRAPHICAL ABSTRACT
abstractarticle info
Article history:
Received 17 December 2016
Received in revised form 27 January 2017
Accepted 27 January 2017
Available online xxxx
Editor: D. Barcelo
Lakes in Europe are subject to multiple anthropogenic pressures, such as eutrophication, habitat degradation and
introduction of alien species, which are frequently inter-related. Therefore, effective assessment methods ad-
dressing multiple pressures are needed. In addition, these systems have to be harmonised (i.e. intercalibrated)
to achieve common management objectives across Europe.
Assessments of fish communities inform environmental policies on ecological conditions integrating the impacts
of multiple pressures. However, the challenge is to ensure consistency in ecologicalassessments through time,
across ecosystem types and across jurisdictional boundaries. To overcome the serious comparability issues be-
tween national assessment systems in Europe, a total anthropogenic pressure intensity (TAPI) index was
Science of the Total Environment xxx (2017) xxx–xxx
⁎Corresponding author.
E-mail address: sandra.poikane@jrc.ec.europa.eu (S. Poikane).
STOTEN-21924; No of Pages 10
http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
0048-9697/© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Contents lists available at ScienceDirect
Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
developed as a weighted combination of the most common pressures in European lakes that isvalidated against
10 national fish-based waterquality assessment systems using data from 556 lakes.
Multi-pressure indices showed significantly higher correlations with fish indices than single-pressure indices.
The best-performing index combines eutrophication, hydromorphological alterations and human use intensity
of lakes. For specific lake types also biological pressures may constitute an important additional pressure. The
best-performing index showed a strong correlation with eight national fish-based assessment systems. This
index can be usedin lake management for assessing total anthropogenic pressure onlake ecosystems and creates
a benchmark for comparison of fish assessments independent of fish community composition,size structure and
fishing-gear.
We argue that fish-based multiple-pressure assessment tools should be seen as complementary to single-pres-
sure tools offering the major advantage of integrating direct and indirect effects of multiple pressures over
large scales of space and time.
© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords:
Aquatic ecosystems
Bioassessment
Fish assemblages
Fish-based assessment system
Lakes
Multiple pressures
Pressure-response relationships
Water Framework Directive
1. Introduction
More than half of the surface waters in Europe are degraded due to
human activity, i.e., support less than “good”ecological status, and will
need mitigation and/or restoration measures to reach ‘good’status.
The pressures reported to affect most surface waters are nutrient en-
richment, hydromorphological alterations, invasion of alien species
and chemical pollution (EEA, 2012). These pressures significantly affect
the capacity of ecosystems to provide the services on whichhumans de-
pend (MEA, 2005). In the years to come, these impacts may be exacer-
bated by climate change which can counteract attempts to restore
water bodies, and prevent them from reaching “good”status
(Jeppesen et al., 2012). Therefore, effective methods are needed to as-
sess, protect and help to restore the ecological integrity of inland and
coastal waters (Birk et al., 2012; Karr, 1991). In addition, these systems
have to be compared and harmonised (i.e. intercalibrated) to ensure
consistency in ecological assessments through time, across ecosystem
types, and across jurisdictional boundaries (Birk et al., 2013; Cao and
Hawkins, 2011; Poikane et al., 2014b).
It has been proven that fish are sensitive indicators of environmental
degradation (Fausch et al., 1990; Karr, 1981). Fish show predictable re-
actions to eutrophication (Blabolil et al., 2016; Jeppesen et al., 2000;
Lyche-Solheim et al., 2013; Mehner et al., 2005), habitat destruction
and fragmentation through hydromorphological modifications (Sutela
et al., 2011), acidification (Hesthagen et al., 2008; Tammi et al., 2003)
and climate change (Jeppesen et al., 2012).
The first fish-based ecological assessment methods were developed
for US rivers (Karr, 1981) and have later been adopted to lakes
(Whittier, 1999).
In Europe, the development of biological assessment systems has
been stimulated by the implementation of theWater Framework Direc-
tive (WFD; EC, 2000). The WFD obliges all member states of the Europe-
an Community to achieve a ‘good’ecological status of their surface
waters, and stipulates that ‘good’or ‘not good’should be measured
with biological assessment systems. In addition, the ‘good’status
boundaries should be harmonised via ‘intercalibration’exercise (Birk
et al., 2013; Poikane et al., 2014b).
Therefore, several European countries including Belgium (Breine et
al., 2015), the Czech Republic and France (Blabolil et al., 2016; Launois
et al., 2011), Germany (Ritterbusch and Brämick, 2015), Lithuania
(Virbickas and Stakėnas, 2016) and Sweden (Holmgren et al., 2007)
have developed fish-based tools to assess ecological status. Several
cross-European studies have been carried out to develop common fish
metrics (Argillier et al., 2013) and intercalibrate (i.e. compare and har-
monise) fish-based assessment systems (Poikane et al., 2015).
However, there are two still unresolved issues: (1) Intercalibration
of fish-based assessment syst ems (i.e. harmonisation of the results of bi-
ological assessment methods) among the member states; (2) Develop-
ing of pressure-response relationships which is a key for any ecological
assessment tool applied in river basin management (Birk et al., 2012;
Brucet et al., 2013b; Poikane et al., 2015). There are several reasons for
these difficulties:
- Member states use very different sampling methods and their com-
bination: multi-mesh gillnets, electrofishing, hydro-acoustics,
trawling, seine netting and fyke nets (e.g., Blabolil et al., 2016;
Breine et al., 2015). These differences hinder comparison of assess-
ment systems across boundaries (Benejam et al., 2012; Lepage et
al., 2016). Two approaches have been adopted for intercalibration:
direct comparison of classification outcomes applying each method
to a common dataset and indirect comparison where boundary
values of each assessment method is converted to common biologi-
cal metrics (Birk et al., 2013). Both these approaches have been
proven to be unsuitable for comparisons of fish assessment due to
a variety of sampling gears and protocols, as particular species and
dominant functional groups tend to be gear-specific(Chow-Fraser
et al., 2006);
- Fish communities in lakes are subjected to multiple pressures and,
being at the upper levels of the trophic cascade, integrate effects of
pressures acting at any level below. On the other hand, fish commu-
nities exert a homeostatic effect on lower trophic levels and thus can
contribute to delayed recovery in aquatic ecosystems after anthro-
pogenic pressures have been reduced (Jeppesen et al., 1991). This
means that simple relationships between single pressures and fish-
metrics may be lacking (e.g., Breine et al., 2015).
We hypothesize that because of the broad spectrum and holistic
character of fish sensitivity, the total anthropogenic pressure intensity
would show stronger and more consistent relationships with various
fish metrics throughout an ecoregion than any single pressure index.
A total anthropogenic pressure index could be used for developing pres-
sure-response relationships and for comparing and harmonising fish-
based assessment systems across an ecoregion independent of fishcom-
munity composition, size structure and fishing-gear. The principle of in-
tercalibration using a common pressure index is to translate the
incomparable national fish assessment results into a comparable com-
mon index. A similar approach was used to intercalibrate ecological
classification tools in transitional waters of the North East Atlantic
(Lepage et al., 2016).
Therefore, the purpose of this research is to develop a multiple pres-
sure index for lakes in the Central-Baltic ecoregion
1
which can be used
to characterize the total anthropogenic pressure on lake ecosystems, de-
velop pressure-response relationships and intercalibrate fish-based
assessment tools. Firstly, the fish-based lake assessment systems in dif-
ferent member states are briefly reviewed focusing on the human pres-
sures addressed and metrics included. Next, the construction and
1
An ecological region for inland waters in Europe delineated for river basin manage-
ment purposes comprising the Baltic States, Benelux Countries, Poland, Germany,
Denmark, Czech Republic, Slovakia, Hungary, and part of France and the UK.
2S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
performance of the total anthropogenic pressure index (TAPI) is de-
scribed and the paper is concluded with some thoughts about the use
of fish in the ecological assessment of lakes.
2. Material and methods
2.1. Dataset
Data was collected from 10 countries in the Central-Baltic ecoregion,
comprising in total 556 lakes (Table 1). The dataset included: (1) mor-
phological data: lake area and depth; (2) information on human im-
pacts (see Tables 2 & 3); (3) Ecological Quality Ratio (EQR) values of
the national lake assessment systems based on fish. Information was
compiled using monitoring data of national water agencies, scientific
projects or literature. Lakes were mostly (60%) polymictic and present-
ed a broad range of total phosphorus (TP) and chlorophyll-a(Chl-a)
concentrations. Except the Czech Republic and the Netherlands, which
include mostly heavily modified water bodies, other countries have
low level of shoreline alteration.
Lake depth has a significant impact on lake response to pressures
(Mehner et al., 2005) therefore lakes were classified into polymictic,
stratified and deep stratified according to Ritterbusch et al. (2014).Be-
fore analysis, a thorough data screening was performed. Lakes judged
incomparable were excluded from the analysis (e.g.,saline lakes, rapidly
flushed lakes). Also, very small lakes (area b0.5 km
2
) were excluded
from the finalanalyses as species richnessand diversity is strongly relat-
ed to surface area of lakes, with critical threshold reported between 0.36
and 0.6 km
2
(Brucet et al., 2013a; Eckmann, 1995). Still, for France and
Belgium the analysis was repeated including all lakes, as excluding
small lakes left these countries with very small datasets.
2.2. Construction of the pressure index
Our approach followed well-accepted principles for the develop-
ment of common metrics (e.g., Breine et al., 2015; Hering et al., 2006,
2010; Lepage et al., 2016).
The pressure index construction consisted of 5 steps:
1. Identifying and selecting pressures affecting lake fish community.
Seven critical broad-spectrum pressures impacting fish community were
identified including eutrophication, acidification, hydromorphological
pressures, chemical pollution and contamination, fishing and stocking,
non-native species, and direct lake use (Table 2).
2. Selecting metrics with available data for each pressure.
Each pressure was characterized by several indicators or proxies
(Table 2). These could describe both the cause and effect, for
instance, TP (cause) and Chl-a(effect), shoreline alterations (cause)
and habitat loss (effect).
3. Scoring of metrics.
Pressure variables were assessed on a ranked scale from 5 (no or neg-
ligible impact) to 1 (extreme impact) according to the severity of the
disturbance (Table 3). A complete list of the scoring criteria can be
found in Tables S2 and S3, Supporting information.
For eutrophication metrics type-specific thresholds were used for
polymictic, stratified and deep stratified lakes (Ritterbusch et al.,
2014). For quantitative eutrophication metrics (spring TP, summer
TP, Chl-a)five alternative settings of class boundaries were applied
based on outputs from different studies (Carlson, 1977; LAWA, 2014;
Poikāne et al., 2010; Poikane et al., 2014a; Vollenweider and Kerekes,
1982). These criteria are provided in Annex 1, Supporting information.
4. Calculation of different versions of the TAPI index by selecting different
combinations of pressures and metrics, and modifying the weight for
eutrophication pressure (Table S4, Supporting information).
All TAPIs were calculated as EQR values between 0 (highpressure) and
1 (low pressure) according to the formula described in Hering et al.
(2006):
TAPIx ¼scorex−minx
ðÞ=maxx−minx
ðÞ;
where:
score
x
= metric result;
max
x
= upper anchor (maximum possible score);
min
x
= lower anchor (minimum possible score).
5. Evaluation of the performanceof differentversions of the TAPI index.
The basic criterion for selecting best-performing TAPI versions was a
sufficiently strong correlation (Pearson R N0.6; P b0.05) of the TAPI
with all EQR's generated by fish-based assessment methods evaluat-
ed in this study (Hering et al., 2006).
2.3. Statistical methods
Statistical analyses were performed using the R software package (R
Core Team 2016).
A linear mixed effects model as implemented in library lme4 (Bates
et al., 2015) was used to analyze the effect of pressures (fixed effect) on
strength of relationships using countries and TAPIs as crossed random
effects to account for possible correlations as each country and each
Table 1
Dataset usedin the TAPI construction. BE: Belgium; CZ: Czech Republic;DE: Germany; DK: Denmark; EE: Estonia; FR: France; LT: Lithuania; NL: the Netherlands; PL: Poland; UK: United
Kingdom. Poland participated with two datasets and methods: PL1: method LFI+, PL2: method LFI-CEN.
MS Number of lakes Annual mean
TP (μgL
−1
)
Mean
Chl-a(μgL
−1
)
Shore alteration
b
(mean)
Total Poly
a
Strat
a
Strat deep
a
Range Median Range Median
BE 44 44 ––15–1780 180 3–471 22 4.3
CZ 23 4 10 9 9–403 48 3–72 22 3.6
DE 95 51 30 14 13–508 40 2–288 9 4.1
DK 107 86 21 –11–1091 89 2–203 36 4.8
EE 48 32 16 –12–131 30 2–121 10 4.1
FR 23 12 6 5 7–213 20 1–142 6 4.5
LT 90 39 37 14 7–150 29 2–92 8 5.0
NL 28 23 5 –15–443 80 3–106 24 2.7
PL1 32 13 10 9 4–200 43 4–69 18 4.0
PL2 59 21 16 22 12–466 50 1–122 13 3.9
UK 7 7 ––7–140 90 26–175 50 4.9
Tot 556 332 151 73 44 17 4.4
a
Polymictic, stratified, stratified deep –lake typology according to Ritterbusch et al. (2014).
b
Evaluation of shore alteration in scalefrom 1 (completely altered) to 5 (no alterations), see Table 3.
3S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
TAPI had multiple observations. Tukey HSD tests as implemented in li-
brary multcomp (Hothorn et al., 2008) were used as post hoc test to
compare pressure groups with each other if linear mixed effects
model showed significant effect of pressure group.
3. Results
3.1. Member state fish-based lake assessment systems
Nearly all member statesin the Central-Balticregion have developed
fish-based lake assessment systems (Table 4). The randomized multi-
mesh gillnet sampling (CEN, 2005) was the most common sampling
method, however, not used in all member states. All member states
have addressed eutrophication as a majorhuman pressure in the region.
In many cases, additional pressures such as hydromorphological pres-
sures and human use intensity were tested.
All assessment systems are based on reference condition approach
where natural variability is taken into account using typology frame-
works. Therefore, all member states have developed lake type-specific
reference values; these described the value of an index to be expected
under ‘undisturbed conditions’. The most common approaches, mostly
used in a combination, include historical data, expert judgement and
near-natural sites, only few use modelling or palaeolimnological data.
Reference conditions correspond to the WFD normative definition of
‘high’status where ‘species composition and abundance is consistent
with undisturbed conditions’.
All indices distinguished between five classes of biological quality.
Various approaches were adopted to define ecological boundaries,
Table 2
Anthropogenic pressures and indicators to build TAPI index.
Anthropogenic
pressure/indicators
Description of indicator
Eutrophication
Total phosphorus (spring) Mean value for March–April or while water body is not stratified
Total phosphorus (summer) Mean epilimnetic value for June–September (monthly sampling)
Chlorophyll-a(summer)
Land use intensity Percentage of non-natural land use in catchment
Trophic state class using TP Trophic classification based on total phosphorus
Trophic state class using trophic
index
Trophic classification based on index of eutrophication
Trophic state change The difference of the mean TP concentration between reference and current conditions
Acidification
Acidification level Assesses the level of human-induced acidification
Hydromorphological pressures
Shoreline modification Percentage of anthropogenic alterations of shore structure (beaches, footbridges, marinas, erosion
control structures etc.). The data are estimated with aerial photographs, e.g. Google Earth
Fragmentation Estimates the impact of human barriers on fish species migrating from/to the lake.
Loss of habitats Availability of habitats in undisturbed conditions is estimated and compared to the present number of habitats
Water level regulation Compares the present water level/fluctuations with the pristine situation
Lake use
Lake use intensity Human-use intensity including shipping, boating, bathing etc.
Population density in the vicinity
of the lake
Refers to a ‘catchment area’of human use, i.e. the range in which people come to the lake for recreation
Chemical pollution and contamination
Chemical pollution As defined by the criteria of the EC directive for environmental quality standards (2008/105/EC) Annex I
Visible pollution Assessment of the visible impairments of the fish community by urban discharge, industrial discharge and others
Litter Estimates the amount of litter at the shoreline - a proxy for both pollution and lake use intensity
Biological effects of pollution Estimates the intensity of effects of pollution on biota (not only fish). Examples are shifts in sex ratio,
lack of reproduction, reduced growth, infections or diseases.
Fishing and stocking
Fish removal Assesses the ecological effects of selective fish removal by commercial fisheries and/or angling.
Stocking of native species Assesses the ecological effects of selective fish input by commercial fisheries and/or angling
Non-native species
Alien fish species number The number of fish species present that would be absent in undisturbed conditions (both true aliens, i.e. non-native
in the corresponding region and translocated species, i.e. native in the region but not native in the water body)
Alien fish abundance Percentage of weight of non-native fish
Non-fish aliens Assesses the ecological impact of non-fish aliens
Table 3
Scoring criteria for TAPI metrics (for other metrics see Tables S2 and S3, Supporting information). P –polymictic lakes, S –stratified lakes, D –deep stratified lakes with max depth N30 m.
TAPI metric 5 points least disturbed 4 points minor impact 3 points major impact 2 points strong impact 1 point extreme impact
Eutrophication
Chl-a(μgL
−1
)b11 (P)
b6 (D, S)
11–21 (P)
6–10 (D, S)
21–52 (P)
10–26 (D, S)
52–215 (P)
26–104 (D, S)
N215 (P)
N104 (D, S)
TP spring
TP summer (μgL
−1
)
b32 (P)
b25 (D, S)
32–45 (P)
25–32 (D, S)
45–100 (P)
32–45 (D, S)
100–200 (P)
45–100 (D, S)
N200 (P)
N100 (D, S)
Hydromorphological
alterations and lake use
Shore modification ≤10% 11–30% 31–50% 51–70% N70%
Habitat loss Natural/increased All habitats 1–3 habitats missing 4–6 habitats missing N6 habitats missing
Lake use intensity Low (bath, boat, sail) –Intense (motorboat, ships, dive) –Very intense
4S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
ranging from simple division ofthe EQR scale to more ecologically based
approaches as shifts in fishcommunities i.e. change from dominance of
phytophilic to eurytopic species related to disappearance of habitat for
spawning and of juvenile phytophilic fish.
Ten fish-based lake assessment methods were included in the study,
comprising 45 metrics in total (see Table 4, also Table S1, Supporting in-
formation). Composition metrics were most widely-used in lake assess-
ment (53%) followed by functional metrics (21%). Also abundance and
age structure metrics were used (10%), while richness and sensitivity
metrics were rarely used. The most frequently used composition met-
rics includes share of European perch Perca fluviatilis,decreasingalong
degradation gradient (used by 7 systems) and common bream Abramis
brama (6), white bream Blicca bjoerkna,roachRutilus rutilus,ruffe
Gymnocephalus cernua (4) and pike-perch Sander lucioperca (3) increas-
ing along degradation gradient. Similarly, increase of share of
benthivorous (3) and omnivorous fish (2) were the most frequently
used functional metrics, and increase of Number per unit effort
(NPUE) and Weight per unit effort (WPUE) –abundance metrics. The
synthesis gives a coherent picture on shifts in fish communities in
response to human pressures despite the different metrics used by the
member states (Table 4).
3.2. TAPI development and selection of best-performing models
Nearly all TAPI versionscorrelated significantly to the majority of na-
tional lake fish indices of the member states, except for Belgium and
France (Table S5, Supporting information). Multi-pressure TAPI
indices showed significantly stronger correlations (Tukey's multiple
comparison tests, P b0.0001) (R
mean
=0.67–0.70 ) in comparison to sin-
gle-pressure (eutrophication) indices (R
mean
=0.61).
Eutrophication indices showed moderately strong correlation with
national fish based assessment results in all countries, with the excep-
tion of Belgium (only six lakes with area N50 ha). Including
hydromorphology and direct lake-use significantly improved the TAPI
performance for most member states (especially for Denmark, but not
France). More complex models involving more pressures did not show
significantly better performance (Fig. 1,Table 6).
Table 4
Fish-based lake assessment systems, country abbreviations see Table 1. NPUE –number per unit effort;WPUE –weight per unit effort; %N percentage of total number; %W percentage of
total weight; SpN –species number. ↑- increase along impact gradient; ↓- decrease along impact gradient.
MS Fishing gear Metrics included in the assessment system Reference
BE Fyke nets, electrofishing %N invertivorous individuals↓,%N omnivorous individuals↑, %N specialized spawners ↓, SpN of piscivorous
species↓, %W benthivorous species ↑, tolerance value↓
Breine et al. (2015)
CZ Multi-mesh gillnets (electrofishing,
hydroacoustics)
a
NPUE↑, WPUE ↑, %N ruffe↑, %W bream↑, %W perch ↓, %W rudd↓, %W Salmonidae ↓, SpN of 0+ of six common
species↓
Blabolil et al. (2016)
DE Multi-mesh gillnets
(electrofishing)
WPUE↑, %N bream, %N ruffe ↑, %W bream↑, %W perch↓, %W pikeperch↑, %W ruffe ↑, %W white bream↑,%W
benthic net species↑, %W benthivorous species ↑, median individual weight of bream/perch/roach, SpN
obligatory species↓
Ritterbusch and
Brämick (2015)
DK Multi-mesh gillnets
(electrofishing)
NPUE↑, %W bream + roach ↑, %W piscivorous individuals↓, average individual weight↓Søndergaard et al.
(2013)
EE Multi-mesh gillnets (mini-fyke
nets, commercial gillnets)
NPUE↑, %N perch ↓, %W non-piscivorous individuals↑, % gillnet panels that caught fish ↓, Simpson diversity
index↓
FR Multi-mesh gillnets NPUE ↑, WPUE↑, %N omnivorous individuals↑Argillier et al. (2013)
LT Multi-mesh gillnets %N perch ↓, %W non-native and trans-located species↑, %W white bream ↑, %W benthivorous species↑,%W
perch and stenothermic↓, average individual weight roach ↓, SpN obligatory species↓
Virbickas and
Stakėnas (2016)
NL Trawling, seine netting,
electrofishing
%W bream↑, %W (perch + roach)/eurytopic↓, %W low oxygen tolerant ↓*, %W phytophilic species↓Altenburg et al.
(2012)
PL1 Fisheries statistics: seine, gillnet,
fyke nets
%W large bream↓, %W small bream ↑, %W crucian carp↑, %W perch ↓, %W pike↓, %W large roach↓,%W
pikeperch↑, %W tench ↓, %W white bream↑, %W large bream in total bream ↓, %W large roach in total roach↓
PL2 Multi-mesh gillnets %W bleak↑, %W bream ↑, %W perch↓, %W pikeperch↑, %W roach ↑, %W rudd↓, %W ruffe↑, %W tench ↓,%W white
bream↑
a
In brackets –the sampling gear used for sampling but not for calculation of metrics.
Fig. 1. Box-plots of correlation coefficients between fish-basedlake assessment and TAPI indices including different pressures. The boxrepresents interquartile range, the horizontal line-
the medianR, the middle point - the mean R. a and b show similar groups according to Tukey'smultiple comparison tests (P b0.0001). Eutro - eutrophication,Hymo - hydromorphological
alterations and direct lake-use, Bio –biological pressures, Pollution –chemical pollution and contamination.
5S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
The best-performing TAPI index in terms of correlation strength
(R
mean
= 0.724, P b0.001) consisted of mean scores of two pressure
modules: (1) eutrophication module, (2) hydromorphological and
lake-use module (Table 6). The final TAPI showed highly significant cor-
relation with eight assessment systems with R ranging from 0.63–0.84
(P b0.001). Linear regressions are shown in Fig. 2.
For Belgium, this analysis didnot reveal any significant relationship,
mostly due to the small number of lakes with an area N50 ha (n = 9).
For all lakes of Belgium (median lake area: 10 ha; interquartile range:
3–34 ha), incorporation of biological pressures into the TAPI indices im-
proved the models' performance, comparing with versions with only
eutrophication or eutrophication and hydromorphological pressuresin-
cluded. The best-performing TAPI for Belgium consisted of mean scores
of three pressure modules: (1) eutrophication, (2) hydromorphological
and lake-use, and (3) biological pressures (Table 5).
The French system showed no or very weak relationship with multi-
pressure TAPI indices. However, it showed moderately strong correla-
tions with TAPI indices which included only eutrophication metrics
(R = 0.72 for lakes N50 ha, P b0.001, R = 0.46 for all lakes, P b0.05).
4. Discussion
Recent research has shown that the deterioration of fish communi-
ties is often caused by interwoven multiple pressures such as eutrophi-
cation, habitat loss, chemical pollution, fisheries, and climate change
(Jeppesen et al., 2012). Impacts of these pressures are often synergisti-
cally or antagonistically interrelated (Folt et al., 1999), expressed at dif-
ferent spatial and temporal scales and characterized by various lag
periods. This makes the identification of a single, or even dominant fac-
tor responsible for the change difficult. Therefore, construction of single
pressure-response relationships has failed in many cases, necessitating
the development of multiple pressure models (e.g., Breine et al., 2015).
In the present paper we develop a total anthropogenic pressure
index (TAPI) as a weighted combination of most common pressures in
European lakes that is validated against 10 national fish based water
quality assessmentsystems. This index can be used in lake management
for assessing total anthropogenic pressure on lake ecosystems and
creates a benchmark to overcome serious comparability issues between
national assessment systems caused by methodological differences.
4.1. Response to multiple pressures
In line with a recent review (Nõges et al., 2016) our study showed
that fish performed better asan indicator of multiple rather than single
pressures. We found that the explanatory power of fish based assess-
ment systems increased from 37% to 52% when hydromorphological
alterations and direct lake-use were included in addition to eutrophica-
tion metrics. However, further adding of pressures did not increase the
explanatory power of the models (except for Belgium, where the lake
sample consists of small artificial lakes).
This can be explained by high mobility and complex life history of
fish which exposes different life stagesto conditions pertaining in vari-
ous lake zones. Unlike phytoplankton or phytobenthos, fish do not re-
spond to nutrient enrichment directly. Exceptions might be ammonia
nitrogen which at high pH turns into toxic unionized ammonia that
may cause fish-kills (Camargo and Alonso, 2006) or nitrate enrichment
which can reduce the severity of an ectoparasitic fish infection
(Smallbone et al., 2016). Fish, however, do respond to eutrophication
induced changes such as modified food availability and changes in hab-
itat quality - hypolimnetic oxygen depletion, increased turbidity, and
loss of submerged plants. Also hydromorphological alteration and direct
lake-usedestroy or modify habitatcomplexity, resulting in various det-
rimental effects on fish community: (i) breeding of fish species that
spawn in shallow littoral waters is disturbed by habitat degradation;
(ii) fish production and speciesrichness decrease with habitat degrada-
tion, most likely due to the loss of submerged macrophytes and woody
debris that provide shelter against predation and wave-action, and offer
high abundance and diversity of prey organisms (Lewin et al., 2014;
Mehner et al., 2005).
Therefore, fish community composition reflects habitat and food
availability and the effect of diverse pressures in the lake as a whole –
this is an added value of fish as a biological indicator, compared to mac-
roinvertebrates, macrophytes and phytoplankton. Similar metric re-
sponses to multiple pressures were also found in European rivers
(Schinegger et al., 2013).
Fig. 2. Linear egressions between Member States fish classification method Ecological Quality Ratio (EQR) and the best performing TAPI index including eutrophication,
hydromorphological alterations and direct lake-use. Country abbreviations see Table 1.
6S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
4.2. Pressures included in TAPI
The best performing TAPI version included eutrophication,
hydromorphological alterations and direct lake-use intensity. The re-
vealed importance of eutrophication is not surprising as (1) nutrient en-
richmentis still the predominant pressure responsible for the degraded
ecological status of lakes in Europe (EEA, 2012); (2) most assessment
systems explicitly address eutrophication by including taxonomic and/
or functional metrics based on their acknowledged sensitivity to the ef-
fects of eutrophication.
Large numbers of studies on European lake fish assemblages have
reported shifts in relative abundance of roach, bream, perch, ruffe and
other taxa along the eutrophication gradient (e.g., Mehner et al., 2005;
Tammi et al., 2003). The share of perch, bream, white bream, roach
and ruffe were the most frequently used metrics in the fish-based as-
sessment systems, followed by overall abundance (number or weight
per unit effort), abundance or number of predatory fish species, per-
centage of catch by weight of benthic and benthivorous species, and av-
erage or median individual weight of fish (each present in at least 3
methods). All these metrics have been identified as indicators of nutri-
ent enrichment (Appelberg et al., 2000; Breine et al., 2015,and
Virbickas and Stakėnas, 2016).
The relevance of hydromorphological alterations and direct lake-use
is more disputable. Indeed, several studies fail to show clear fish re-
sponse to these impacts. For instance, Mehner et al. (2005) demonstrat-
ed that shoreline alterations and human use intensity had a negligible
effect on fish communities. Brucet et al. (2013a) did not find any effect
of hydromorphological pressures on fish diversity in lakes. Neverthe-
less, many studies do confirm these relationships (Breine et al., 2015;
Launois et al., 2011; Lewin et al., 2014; Scheuerell and Schindler,
2004; Sutela et al., 2011), ecological rationale for these impacts is
well-established (Ostendorp et al., 2004) andthe reasons for not finding
the impacts are mostly linked to insufficient data quality and quantity
(Mehner et al., 2005).
On the other hand, pressures such as acidification, chemical pollu-
tion and contamination, fishing and stocking and the presence of non-
native species were not retained in the final TAPI as adding these pres-
sures did not improve the TAPI's performance (with exception of Bel-
gian small lakes, see further). Firstly, levels of chemical pollution and
acidification in the lakes were generally low. Secondly, it is difficult to
conclude whether fishing/stocking pressures and alien species genuine-
ly have a low impact on fish communities, or that the fish metrics used
in member states' systemsdo not reflect these pressures. In addition, we
suspect some heterogeneity in the assessment of stocking and fishing
intensity and/or impact. In France, for example, fish communities in
lakes are often manipulated (Argillier et al., 2002). However, it is very
difficult to know exactly the management practices in different lakes,
and the fishing intensity upon different species.
4.3. French assessment system –addressing eutrophication only
Nine out of ten existing national fish indices correlated significantly
with the multi-pressure indices. However, the French system showed a
relationship with eutrophication-only indices. A number of reasons can
be suggested as to why this might be so: (1) the French assessment sys-
tem includes only three metrics (NPUE, WPUE, abundance of omnivo-
rous fish) that are mostly related to lake productivity (Argillier et al.,
2013); (2) the French dataset is relatively small (n = 24) and the shore-
line alteration and lake-use arenegligible (only onelake with significant
shore modification and one - with significant lake-use intensity). It re-
mains to be seen how well this assessment system is able to account
for other anthropogenic pressures. For this, more data on hydrology,
habitat alterations and fish communities are needed (Argillier et al.,
2013).
4.4. Belgian system –best performing model includes also biological
pressures
Belgian dataset consists of small and strongly degraded lakes with
huge impacts of aliens (Belpaire et al., 2000). Therefore, the best rela-
tionships were achieved when all lakes were analyzed (including also
small lakes) and biological pressures were included in the TAPI index.
This shows that biological pressures, mostly negligible for large lakes,
may be of importance for small degraded lakes. Overall, there is no con-
sensus on the role of alien species –in general, the presence of alien spe-
cies as perceived as a negative factor (Belpaire et al., 2000; Karr, 1981),
while Breine et al. (2015) argue that some of alien fish species are
naturalised (e.g., common carp) whilst others (pike-perch) are
Table 5
Selectionof best-performing TAPI index (analysis including lakes N50 ha). Indexes after Rmeanshow similar groups according to Tukey'smultiple comparison tests (P b0.0001). The best
performing model marked in bold.
Pressure(-s) R
mean
of all models in the
pressure group
R
mean
of the best-performing model in the
pressure group
Number of
systems
Notes
Eutro 0.61 (A) 0.610 9 Significantly lower performance comparing to
multi-pressure models0.670 8
Eutro + Hymo 0.67 (B) 0.724 8 Simplest model with best performance
Eutro + Hymo + Bio 0.69 (B) 0.721 8 More complex models do not show improvement
of performanceEutro + Hymo + Bio +
Pollution
0.70 (B) 0.710 8
Table 6
Pressures, metrics and calculation approaches used in TAPI construction (example of calculation in Annex 2, Supporting information), country abbreviations see Table 1.
Pressure module Metrics included Approach
TAPI-EH
Sum of mean scores for each
pressure module
Eutrophication Chl-a,TP
spring
,TP
summer
Best performing model for CZ, DE, DK, EE, LT, NL,
PL, lakes N50 haHydromorphological pressures and
lake use intensity
Shore modification, habitat loss, lake-use
intensity
TAPI-EHB
Eutrophication Chl-a,TP
spring
,TP
summer
, TP-trophic state,
non-native land use
Best performing model for BE, lake area
0.6–89 ha
Hydromorphological pressures and
lake use intensity
Shore modification, habitat loss, lake-use
intensity
Biological pressures Fish removal, fish input, alien fish abundance
7S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
indicators for goodwater qualitydue to their high oxygen demand. De-
pending on the preferred food source and spawning behaviour, either
coexistence or interspecific competition can occur between native and
alien species (Verhelst et al., 2016). In addition alien species can become
an important food source for many native species (Crane et al., 2015).
Also, there is no agreement how alien species have to be included in
ecological assessment across Europe. This is because not all introduced
fishes become established, and the fraction of those that do often have
little appreciable effects on their new ecosystems, while others
exert significant ecological, evolutionary, and economic impacts
(Cucherousset and Olden, 2011). An experiment of Kornis et al.
(2014) provided evidence that invasive species effects may diminish
at high densities, possibly due to increased intraspecific interactions.
So far, only the Lithuanian system for lakes includes explicit metric re-
lated to non-native species (Virbickas and Stakėnas, 2016).The majority
of countries do not take alien species explicitly into account, assuming
that significant pressure by alien species will be detected by other
fish-based metrics (e.g., Breine et al., 2015). However, this is not always
the case, as high-impact invasive alien species have been observed in
water bodies classified as high (near-pristine) status (Vandekerkhove
et al., 2013). This calls for a development of common understanding
on the impacts of alien species and their inclusion in the ecological
assessment.
4.5. Role of fish community in ecological assessment
European freshwaters are affected by a complex of pressures,
resulting from discharges from diffuse and point sources, habitat alter-
ation, water abstraction, overfishing and climate change (EEA, 2012).
Defining the biotic integrity may be the best way to assess the total ef-
fects of these pressures on aquatic environments. As Karr (1991) has
stated: “An ideal indicator would be sensitive to all stresses placed on
biological system by human society”. However, the reality is different:
most of the 62 intercalibrated lake assessment methods address single
pressures, largely eutrophication, with only few methods addressing
acidification, hydromorphological alterations, or multiple pressures
(Poikane et al., 2015).
The broad spectrum of niche diversity among fishes covering differ-
ent trophic levels of the aquatic food-chain from non-predatory
planktivorous and benthivorous species to top predators and different
types of habitats from littoral to benthic and pelagic habitats, makes
fishes very susceptible to multi-pressure situations. We propose that
high sensitivity of fish to a broad spectrum of pressures could provide
both generic tools for detecting complex multiple pressures as well as
more “tailor made”approaches for targeting specific pressure
combinations.
We argue that both single-pressure and multiple-pressure tools
have places in the lake management tool-kit (Table 7). Fish-based mul-
tiple-pressure assessment tools offer the major advantage of integrating
both the direct and indirect effects of multiple pressures over large
scales of space and time should be seen as complementary to other bio-
logical communities(Carvalho et al., 2013; Poikaneet al., 2016)andbio-
markers (Colin et al., 2016) for detection of early signs of ecosystem
disturbance.
5. Conclusions
Fish communities react in a holistic way to a broad range of cumula-
tive pressure impacts. Several European countries have developed fish-
based lake assessment tools, however, their comparability is a major
problem due to a variety of sampling gears and methodologies used.
To overcome these issues, we constructed a combined pressure index,
TAPI, which correlated well with changes in fish community structure
thought to reflect anthropogenic degradation. TAPIincludes eutrophica-
tion, hydromorphological alterations and lake-use intensity and shows
strong correlation with 8 out of 10 national lake fish indices tested.
Therefore, TAPI provides an estimation of the pressure intensity which
is comparable throughout the wide geographic range of the Central Bal-
tic Intercalibration Group. The TAPI index could represent a useful tool
for assessing environmental quality, as well as for developing pressure
–response relationships and intercalibrating fish-based assessment
tools.
Abbreviations
BE Belgium
Chl-achlorophyll-a
CZ Czech Republic
DE Germany
DK Denmark
EE Estonia
EQR Ecological Quality Ratio
FR France
LT Lithuania
NL the Netherlands
NPUE number per unit effort
PL Poland
PL1 method LFI+
PL2 method LFI-CEN
TAPI total anthropogenic pressure index
TP total phosphorus
UK United Kingdom
WFD Water Framework Directive
WPUE weight per unit effort
Acknowledgements
The work of D.R. was funded by the German federal countries' pro-
gram of financing ‘Water, Soil and Waste’. J.B. was financial supported
by the Flemish Environment Agency. The Czech participants were
Table 7
Comparison of single-pressure assessment tools vs multi-pressure assessment tools –examples.
Pressure and pressure indicator Biological community Advantages Disadvantages
Single-pressure tools
Eutrophication (TP) Phytoplankton (Carvalho et
al., 2013)Quantifying relationships between specific
pressures and biological response; Setting
robust targets for the management of
freshwaters, e.g., nutrient targets for limiting
Cyanobacteria blooms
Often degraded to a biological proxy of total
phosphorus; Lacking understanding of
multiple pressures interactions
Acidification (pH or ANC) Benthic invertebrates
(McFarland et al., 2010)
Hydromorphological alterations (water
regulation amplitude)
Macrophytes
(Mjelde et al., 2013)
Multiple-pressure tools
Multiple pressures including eutrophication,
morphological degradation and lake-use
(TAPI)
Fish assessment systems
(this paper)
Integrating direct and indirect impacts of
multiple pressures
Direct derivation of management targets
and restoration measures may be difficult
8S. Poikane et al. / Science of the Total Environment xxx (2017) xxx–xxx
Please cite this article as: Poikane, S., et al., Response of fish communities to multiple pressures: Development of a total anthropogenic pressure
intensity index, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.211
supported by project CEKOPOT (CZ.1.07/2.3.00/20.0204), co-financed
by the European Social Fund and the state budget of the Czech Republic,
and by the Czech Science Foundation (15-01625S). The work of N.J. was
funded by the Dutch Ministry of Infrastructure and the Environment.
The work of T.K. and P.N. was supported by institutional research
funding IUT21-02 of the Estonian Ministry of Education and Research
and by MARS project (Managing Aquatic ecosystems and water Re-
sources under multiple Stress) funded by the European Union under
the 7th Framework Programme, Theme 6 (Environment including Cli-
mate Change), contract no. 603378.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.scitotenv.2017.01.211.
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