Salinity shapes zooplankton communities and functional diversity and has complex effects on size structure in lakes

Abstract

Changes in zooplankton community structure
and function were analyzed in 24 lakes covering a
wide salinity gradient (from 0.5 to 115 g l-1) in a
semiarid region in northwest China. We hypothesized
that species richness (S), species diversity (H), functional
diversity (FD), biomass, and size of zooplankton
would decrease with increasing salinity. We found that
S, H, and FD did decrease with increasing salinity,
whereas zooplankton sizes, size range, and biomasses
did not. In fact, the sizes of microcrustaceans were
mainly regulated by the abundance of small fish.
Besides the impoverishment of FD, the zooplankton
functional groups also varied along the salinity
gradient. A shift occurred from selective raptorial to
more generalist microphagous rotifers, from selective
to more generalist filter feeder cladocerans, and from
dominance of microphagous herbivorous copepods to
microphagous carnivores. Our study indicates that the
ongoing salinization of lakes with climate warming
will result in important changes in the zooplankton,
affecting not only the structure but also the functioning
of this community. A weakened top-down control by
zooplankton on phytoplankton at moderate high
salinities may be an indirect consequence, leading to
a worsening of eutrophication symptoms. Loss of fish
at high salinities may, however, counteract this effect.

Full text

PRIMARY RESEARCH PAPER
Salinity shapes zooplankton communities and functional
diversity and has complex effects on size structure in lakes
Marı
´a Florencia Gutierrez .U
¨lku
¨Nihan Tavs¸anog
˘lu .Nicolas Vidal .
Jinlei Yu .Franco Teixeira-de Mello .Ays¸e Idil C¸ akiroglu .Hu He .
Zhengwen Liu .Erik Jeppesen
Received: 17 July 2017 / Revised: 26 January 2018 / Accepted: 28 January 2018
ÓSpringer International Publishing AG, part of Springer Nature 2018
Abstract Changes in zooplankton community struc-
ture and function were analyzed in 24 lakes covering a
wide salinity gradient (from 0.5 to 115 g l
-1
)ina
semiarid region in northwest China. We hypothesized
that species richness (S), species diversity (H), func-
tional diversity (FD), biomass, and size of zooplankton
would decrease with increasing salinity. We found that
S,H, and FD did decrease with increasing salinity,
whereas zooplankton sizes, size range, and biomasses
did not. In fact, the sizes of microcrustaceans were
mainly regulated by the abundance of small fish.
Besides the impoverishment of FD, the zooplankton
functional groups also varied along the salinity
gradient. A shift occurred from selective raptorial to
more generalist microphagous rotifers, from selective
to more generalist filter feeder cladocerans, and from
dominance of microphagous herbivorous copepods to
microphagous carnivores. Our study indicates that the
ongoing salinization of lakes with climate warming
will result in important changes in the zooplankton,
affecting not only the structure but also the functioning
of this community. A weakened top-down control by
zooplankton on phytoplankton at moderate high
salinities may be an indirect consequence, leading to
a worsening of eutrophication symptoms. Loss of fish
at high salinities may, however, counteract this effect.
Electronic supplementary material The online version of
this article (https://doi.org/10.1007/s10750-018-3529-8) con-
tains supplementary material, which is available to authorized
users.
Handling editor: Karl E. Havens
M. F. Gutierrez (&)
Instituto Nacional de Limnologı
´a, CONICET-UNL,
Ciudad Universitaria, 3000 Santa Fe, Argentina
e-mail: fgutierrez@inali.unl.edu.ar
U
¨. N. Tavs¸ anog
˘lu
Limnology Laboratory, Department of Biology, Middle
East Technical University, 06800 Ankara, Turkey
N. Vidal E. Jeppesen
Department of Bioscience, Aarhus University, Vejlsøvej
25, 8600 Silkeborg, Denmark
N. Vidal E. Jeppesen
Sino-Danish Centre for Education and Research (SDC),
Beijing, China
N. Vidal F. Teixeira-de Mello
Departamento de Ecologı
´a y Gestio
´n Ambiental, CURE,
Universidad de la Repu
´blica, Tacuarembo
´s/n Maldonado,
Montevideo, Uruguay
J. Yu H. He Z. Liu
State Key Laboratory of Lake Science and Environment,
Nanjing Institute of Geography and Limnology, Chinese
Academy of Sciences, Nanjing 210008, China
A. I. C¸ akiroglu
Biofluids and Cardiovascular Engineering Laboratory,
Mechanical Engineering Department, Koc University,
Istanbul, Turkey
123
Hydrobiologia
https://doi.org/10.1007/s10750-018-3529-8

Keywords Functional classification Salinity
gradient Taxon diversity Taxon richness 
Zooplankton size
Introduction
Climate warming may lead to an increase in salinity in
lakes due to increasing temperatures and reduced net
precipitation, not least in arid and semiarid regions of
the world (Brucet et al., 2010). High evaporation
together with enhanced soil erosion following more
extreme rainfall events increases lake salinity and the
concentrations of other harmful substances, affecting
the aquatic biota (Jeppesen et al., 2015). Some studies
have suggested that salinity per se has only a minor
effect on zooplankton community structure and
trophic dynamics in saline lakes (Williams, 1998;
Waterkeyn et al., 2008). However, others have
revealed salinity to be an important environmental
filter that may change zooplankton richness and
diversity, causing a decline at high salinities (Schal-
lenberg et al., 2003; Jeppesen et al., 2007; Brucet et al.,
2009; Jeppesen et al., 2015). Taxon richness and
diversity are, however, also affected by a number of
other variables such as productivity, dispersal limita-
tions (Declerck et al., 2005), and trophic interactions
(e.g., high richness at lower trophic levels may be
promoted by high richness at high trophic levels)
(Jeppesen et al., 2000). Thus, richness and diversity
(as structural attributes of a community) can be
considered highly sensitive to biological and environ-
mental changes, even more than the ecological role
(function) of species, since sensitive species may be
replaced by tolerant ones with similar functions
(Schindler, 1990; Ruesink & Srivastava, 2001; Mano
& Tanaka, 2016). Loss of taxon richness and biodi-
versity can have negative consequences for the overall
functioning of the ecosystem (Flo
¨der & Hillebrand,
2012; Ding et al., 2017) and such an impoverishment
of functional diversity (FD) might result in decreased
resilience, not least in an already perturbed system
(Vandermeer et al., 1998; Flo
¨der & Hillebrand, 2012).
Considering that environmental filtering processes
particularly affect species traits and not so much the
taxonomic structure (Heino, 2008), a classification
based on organism traits associated with their specific
function in the ecosystem may provide key informa-
tion on the effects of salinity on lakes, linking
ecosystem function and biodiversity (Schmera et al.,
2009).
In recent years, an increasing number of studies
have been conducted to classify aquatic communities
based on their functional characteristics in order to
examine FD patterns as well as to find appropriate
functional indicators of environmental changes
(McGill et al., 2006; Barnett et al., 2007; Heino,
2008, Heino et al., 2013; Mason et al., 2013). For
example, phytoplankton trait-based approaches have
been used to characterize lake trophic levels (Rey-
nolds et al., 2002; Kruk et al., 2010) and to elucidate
how environmental conditions determine community
dynamics (Longhi & Beisner, 2010; Gallego et al.,
2012). For aquatic plants, functional classifications
and life-history traits have been used to assess the
effects of eutrophication and drought disturbances in
lakes (Grime, 1973; Nielsen, 2003). It has been found
that increasing productivity selects for the more
competitive species, resulting in decreased functional
richness and dispersion (Arthaud et al., 2012). Inver-
tebrate functional approaches have also been used to
assess the structuring effects of lake size and habitat
complexity (Heino, 2008) as well as to find appropri-
ate indicators of stream conditions for biomonitoring
purposes (Ding et al., 2017). These studies indicate
that functional and taxonomic approaches are often
highly correlated, providing rather similar information
about ecosystem functioning, and that a reduction in
taxa richness could result in a decline in their
functional components (Heino, 2008; Ding et al.,
2017).
Relatively little information exists on how increas-
ing salinity levels may act as an environmental filter
on the whole zooplankton community from a taxo-
nomic and functional perspective. A recent study
documented that salinity was one of the main predic-
tors of the spatial patterns and FD of zooplankton
(Helenius et al., 2016). However, this work refers to
brackish coasts and the functional classification was
performed only for crustaceans.
The size structure and biomass of the different
zooplankton organisms can also be used as a surrogate
of the community function (Obertegger & Flaim,
Z. Liu
Institute of Hydrobiology, Jinan University,
Guangzhou 510632, Guangdong, China
Hydrobiologia
123

2015). Recent studies conducted along a salinity
gradient have demonstrated a shift from dominance of
large and more efficient filter-feeding cladoceran
species at low salinities to dominance of copepods
and small cladoceran species at higher salinities
(Jeppesen et al., 2007; Brucet et al., 2009; Jensen
et al., 2010). Accordingly, it has been suggested that
species replacement may weaken top-down control by
zooplankton on phytoplankton at high salinities,
leading to a worsening of eutrophication symptoms
(Brucet et al., 2009). Besides the shift of species
ranges and the seasonal shifts in life cycle events
(Daufresne et al., 2009), this size reduction pattern has
been considered as the third universal response to
warming for ectotherm organisms. It is therefore
possible that an increasing salinity scenario produced
by climate change may create the same size-decline
trend as warming since the general mechanisms in
both cases include metabolic shifts and energy real-
location (Sheridan & Bickford, 2011).
The objective of this study was to evaluate the role
of salinity in shaping the zooplankton community
from both a taxonomic and a functional perspective by
analyzing 24 lakes along a wide salinity gradient
encompassing freshwater (0.5 g l
-1
) to hypersaline
lakes (115 g l
-1
) in a semiarid region in northwest
China. All lakes are located in the surroundings of
Lake Ulungur (47°160N, 87°200E), covering an area of
7900 km
2
approximately, at 480–550 m altitude in the
Altay region of the Xinjiang province. This large-scale
study including species sharing the same biogeo-
graphical range (i.e., exposed to similar co-evolution-
ary processes and environmental filters) allowed us not
only to elucidate the effects of salinity on system
structure and functioning but also to predict possible
changes in semiarid shallow lakes associated with
climate change. Our hypothesis was that zooplankton
species richness (S), specific diversity (H), and FD
would decrease with increasing salinity because only
tolerant species would be able to survive in high-
salinity lakes, leading to an impoverishment of species
interaction. We further hypothesized that with increas-
ing salinity, zooplankton size and biomass would
decrease together with changes in species composition
and due to physiological constraints (e.g., the energy
requirements for osmoregulation would reduce the
energy input for individual growth). However, at high-
salinity levels, the disappearance of fish (their main
predators) would expectedly favor the occurrence of
other competitively superior zooplankters, and hence
high size ranges, leading to an increase in size and
biomass.
Methods
Study site
The sampling was performed during July 2014 along a
wide salinity gradient in the Ulungur Lake area (from
47°400to 46°300N and 86°500to 88°200E). This area is
located at an altitude ranging from 480 to 550 m in the
Altay region of the Xinjiang province in northwest
China. Twenty-four shallow and deep lakes were
sampled, encompassing freshwater (0.5 g l
-1
)to
hypersaline systems (115 g l
-1
). Lake area and mean
depth ranged from 0.02 to 24 km
2
and 0.5 and 15 m,
respectively.
Chemical and environmental analyses
Salinity (g l
-1
), water temperature (°C), conductivity
(mS cm
-1
), pH, turbidity (NTU), chlorophyll-
a(lgl
-1
), and dissolved oxygen (mg l
-1
) were
measured in situ at the deepest point of each lake
using a YSI multiprob (YSI 6500, YSI Company,
USA). Secchi disc depth (cm) was also measured in
the limnetic area. Three replicates of water samples
(220 ml) were taken and frozen for posterior analysis
of total nitrogen (TN), total dissolved nitrogen (TDN),
total phosphorus (TP), total dissolved phosphorus
(TDP), nitrate (NO
3
-
), ammonium (NH
4
?
), nitrite
(NO
2
-
), and orthophosphate (PO
4
3-
). All these
parameters were measured according to the Chinese
Standard Methods for Monitoring Lake Eutrophica-
tion (Jin & Tu, 1990), which is similar to the US
standards (APHA, 1998). Another water sample
(1–2 l) was taken and filtered through a GF/C glass
fiber filter using an electric pump for measurement of
the chlorophyll-a(Chl-a) concentration. In the labo-
ratory, the Chl-aconcentration was determined using a
90% (v/v) acetone/water solution extraction, followed
by spectrophotometry and calculated without correct-
ing for phaeophytin interference (USEPA, 2002).
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123

Fish
In each lake, survey fishing was undertaken using
gillnets with seven mesh sizes (7, 10, 15, 20, 25, 30,
and 40 mm from knot to knot), each section being
10 m long and 1.5 m high, comprising in total
91.5 m
2
. The gillnets were located perpendicular to
the littoral zones. Fish density and biomass were
calculated as CPUE (Capture Per Unit Effort) (number
of fish net
-1
h
-1
) and Biomass Per Unit Effort
(BPUE) (g net
-1
h
-1
). The fish were determined to
species level and then the standard length (0.1 cm) and
weight (0.1 g) of each fish were measured. For the
analysis, the fish were classified into three size ranges
in length: small (\10 cm), medium (10–25 cm), and
large ([25 cm), considering that their feeding habits
usually change during their growth and that small-
sized fish are typically zooplanktivorous. Fish size
diversity was calculated using individual size mea-
surements (Brucet et al., 2006; Quintana et al.,
2008,2015) and following the non-parametric
methodology of Quintana et al. (2008). Size diversity
is related to the Shannon diversity index but adapted
for continuous variables (i.e., fish length) (Quintana
et al., 2008). Size diversity integrates the amplitude of
the size range and the size evenness, and it therefore
condenses different aspects of the size structure into a
single comparable value (Brucet et al., 2006; Quintana
et al., 2008).
Zooplankton
In all lakes, zooplankton sampling was performed at
one station in the pelagic area and at one station in the
littoral region to obtain an integrated and representa-
tive sample of each lake. Zooplankton samples were
collected with a Patalas sampler encompassing a water
column of approximately 1.5–5 m, depending on the
lake depth. Water samples sized between 15 and 50 l
(depending on the characteristics of the lake) were
filtered through a 20-lm mesh net. The animals
retained on the mesh were pooled and fixed with 4%
Lugol’s solution and stored in 100 ml plastic bottles.
Counting was performed in the laboratory follow-
ing standard methodologies using specific keys (e.g.,
Koste, 1978; Korı
´nek, 1981,2002; Korovchinsky,
1992; Alekseev, 2002). At least three (or more)
homogeneous aliquots were taken from the sample
to obtain 100 individuals of the dominant taxa. For
each sample, countings of every aliquot were averaged
after correcting for the amount of water filtered in
order to calculate individual abundances (ind. l
-1
)
and. Zooplankton larger than 140 lm were counted in
a 5 ml Bogorov counting chamber at 109magnifica-
tion using a stereomicroscope (Nikon Eclipse, E100),
while subsamples between 20 and 140 lm were
counted in a 1 ml Sedgewick-Rafter chamber at 409
magnification.
In the analysis, some species were classified at
genus level because of morphological ambiguities of
preserved species (e.g., Mesocyclops,Acroperus,
Alona, Trichocerca,Synchaeta,Polyarthra,Col-
lotheca). When possible, 20–30 individuals of each
taxon were measured in each sample. After obtaining
length data, biomasses were calculated using length–
weight relationships available from the literature
(Dumont et al., 1975; Bottrell et al., 1976; Ojaveer
et al., 2001). If no information was available (e.g., for
some rotifers), geometric shapes were used instead.
For the functional characterization, the different
zooplankton taxa were divided into different groups
(Table 1) based on several traits such as their feeding
strategies, predator avoidance, and growth according
to Barnett et al. (2007) and Obertegger & Manca
(2011). Rotifers were separated into raptorials (Asco-
morpha,Asplanchna,Collotheca,Gastropus,Ploe-
soma,Polyarthra,Synchaeta, and Trichocerca) and
microphagous (Brachionus,Conochilus,Euchlanis,
Filinia,Keratella,Lecane,Notholca,Testudinella,
and Trichotria). Cladocerans and copepods were
classified into filtering Ctenopoda (Diaphanosoma
and Pseudosida), filtering Anomopoda (Daphnia,
Simocephalus,Ceriodaphnia, and Moina), selective
filter feeders (Bosmina and Bosminopsis), filtering
scrapers (Chydoridae and Macrotricidae), micropha-
gous herbivores (Sinocalanus,Arctodiaptomus, Cala-
noidea copepodites), and microphagous carnivores
(Mesocyclops, Cyclopoidea copepodites). A FD index
was calculated for each lake by using the eight
functional groups mentioned above and the same
formulae as for the Shannon–Wiener diversity index
(Shannon & Weaver, 1964). In addition, the propor-
tion of microphagous rotifers to raptorial rotifers
(microphagous:raptorial ratio) (Obertegger et al.,
2011) was calculated in order to identify possible
replacement of rotifer FGs along the salinity gradient.
Hydrobiologia
123

Statistical analyses
All 24 lakes were grouped according to salinity
following the classification of Hammer (1986)but
unifying two categories for high-saline lakes: subsaline
(Sub; 0.5–3 g l
-1
), which included seven lakes, hypos-
aline (Hypo; 3–20 g l
-1
), which included 13 lakes, and
meso-hypersaline (Meso-hyper:[20 g l
-1
), including
4 lakes. Differences in environmental characteristics
and zooplankton FD among these three salinity cate-
gories were assessed using the non-parametric Krus-
kal–Wallis with Dunn post hoc test (a=0.05).
The similarity analysis was used to compare the
taxonomic composition among lake categories through
the Bray–Curtis dissimilarity index. Results were
displayed in a dendrogram following the method
unweighted pair-group with arithmetic mean
(UPGMA). A similarity percentage procedure (SIM-
PER) with 9999 permutations was performed on the
Bray–Curtis triangular matrix to determine taxonomic
differences among the lakes. A posteriori non-
parametric multivariate analysis of variance (NPMA-
NOVA) was performed to analyze whether those
differences were statistically significant. For this anal-
ysis, eight taxa were used, which included Asplanchna,
Brachionus,Hexarthra,Lecane,Daphnia,Di-
aphanosoma, Calanoidea, and Cyclopoidea. In addi-
tion, beta (b) diversity index or global replacement of
taxa between systems was calculated based on pres-
ence–absence data according to Whittaker (1972), using
the following formula: bw =(S/a)-1, where Sis the
total number of species recorded for the lakes and ais
the average number of species found within lakes.
From an initial set of twenty environmental (phys-
ical, chemical, and biological) variables, a correlation
matrix (Spearman non-parametric correlations, q) was
calculated in order to detect highly correlated vari-
ables. A correlation factor of 0.6 was considered
strong, and from each correlation pair only the
variable with the lowest VIF (Leps
ˇ&S
ˇmilauer,
1998) was retained to diminish the chance of spurious
correlations in the successive steps. Then, a subset of
Table 1 Functional
characterization of the
different zooplankton taxa
based on several traits such
as their feeding strategies,
predator avoidance, and
growth
Modified from Barnett et al.
(2007) and Obertegger &
Manca (2011)
Rotifera Raptorial Ascomorpha
Asplanchna
Collotheca
Ploesoma
Synchaeta
Trichocerca
Polyarthra
Microphagous Brachionus
Conochilus
Euchlanis
Notholca
Trichotria
Filinia
Keratella
Lecane
Testudinella
Cladocera Filtering Ctenopoda Diaphanosoma
Pseudosida
Filtering Anomopoda Daphnia
Ceriodaphnia
Simocephalus
Moina
Selective filter feeders Bosmina
Bosminopsis
Filtering scrapers Chydoridae
Macrotricidae
Copepods Microphagous herbivorous Sinocalanus
Arctodiaptomus
Calanoidae copepodits, etc.
Microphagous carnivores Mesocyclops
Cyclopoidea copepodites, etc.
Hydrobiologia
123

explanatory variables known to influence the zoo-
plankton was selected (Jeppesen et al., 1994,1996;
Kalff, 2002; Schallenberg et al., 2003; Brucet et al.,
2006,2012; Moss, 2009; Helenius et al., 2016). Thus,
the following explanatory variables were considered
in the analyses: lake depth, salinity, temperature, pH,
concentration of NH
4
-N, PO
4
-P, and Chl-a, abundance
of small fish (10–25 cm SL), mean total fish biomass,
and fish size diversity.
Multiple generalized linear models (GLM) were
used to find the model that best explained the
variations in H, FD, S, total zooplankton size (TZS),
and total zooplankton biomass (TZB). From the
above-mentioned considered variables, we selected
three explanatory variables for each response variable
due to the small sample size (n=24), and different
models with all possible combinations were compared
in a set of preliminary analyses. Following the
information theoretic approach, we used the Akaike’s
Information Criterion corrected for small sample size
(AICc) to evaluate the models that best fitted the data
(Burnham & Anderson, 2002). The difference
between the lowest AICc value and AICc from all
other models (DAICc) was also calculated in order to
rank the potential models (Burnham & Anderson,
2002). Also, the AICc weight of a model (w
i
) was
calculated based on all candidate models (Burnham &
Anderson, 2002). For each response variable, an
exploratory analysis was performed, including verifi-
cation of normality, homoscedasticity, and sub- or
over-dispersion. According to that, S, H, TZS, and
TZB were analyzed using GLM with a Poisson error
distribution and a logarithmic link function, while FD
was analyzed using GLM with a Gaussian error
distribution and an identity link function. The selected
explanatory variables used to model S, H, and TZS
were: salinity, depth, and abundance of small fish.
However, in the first case (for S), the quadratic value
of salinity was also incorporated in the model to
include the distant values. To model FD, we used
salinity, depth, and fish size diversity as explanatory
variables, and to model TZB, the selected explanatory
variables were salinity, depth, and fish biomass.
Different multivariate analyses such as canonical
correspondence analysis (CCA) or redundancy anal-
yses (RDA) were performed to explore the controlling
factors of zooplankton composition in the lakes. The
choice of CCA or RDA was based on a previously
conducted detrended correspondence analysis (DCA):
when the response of the biological data was unimodal
we used CCA and when it was linear we used RDA (ter
Braak, 1994). All zooplankton functional groups were
included as response variables. The following biotic
and abiotic variables were used as explanatory ones:
lake depth, salinity, temperature, pH, concentration of
NH
4
-N, PO
4
-P, and Chl-a. Response and explanatory
variables were transformed, when necessary, and
standardized by norm. The explanatory variables
retained in the models were based on forward stepwise
selection (a=0.05) and only those that had an
acceptable VIF value (\20) were finally considered
(Leps
ˇ&S
ˇmilauer, 1998). The significance of each
variable and the combination of all canonical axes
were determined using the Monte Carlo permutation
test (999 permutations).
To analyze the relative importance of environmen-
tal and biological factors in shaping the zooplankton
FD, the variance partitioning procedure was used
(Borcard et al., 1992). We used partial CCA since the
response was unimodal. The whole variation of the
zooplankton matrix was partitioned into ‘‘biological
factors,’’ which included mean fish biomass (CPUE),
abundance of small fish (\10 cm length, CPUE), Chl-
aconcentration, and ‘‘environmental factors,’’ which
included salinity, depth, PO
4
-P, and NH
4
-N. The
significance of these components was evaluated with a
Monte Carlo permutation test.
All statistical analyses were performed using R
software v0.99.903 (R Development Core Team,
2011) with the MASS, MuMIn, vegan, and Biodiver-
sity packages, and CANOCO 5 software (ter Braak &
Smilauer, 2002).
Results
A total of 70 (1–27 per lake) zooplankton taxa were
identified within the groups Rotifera (52 taxa),
Cladocera (12 taxa), and Copepoda (6 taxa). The
diversity index (Shannon–Wiener) ranged between
0.11 (at a salinity level of 21 g l
-1
) and 2.26 (at a
salinity level of 2.1 g l
-1
).
The lake salinity categories (Sub, Hypo, and Meso-
hyper) differed in depth, DO, TN, TP, and K; high-
salinity lakes were, in general, deeper and had low
DO, and higher values of TN, TP, and K were
recorded. In contrast, lake area, Secchi disc depth,
concentrations of Chl-a,NH
4
-N, PO
4
-P, and pH
Hydrobiologia
123

remained practically similar among the three groups
(Table 2). According to the Bray–Curtis dissimilarity
index, subsaline and hyposaline lakes showed the most
similar zooplankton taxa composition, from which the
meso-hypersaline lakes differed (cophenetic correla-
tion: 0.981; NPMANOVA, P=0.042). Mean beta-
diversity (Whittaker index) was 0.53, meso-hyper and
subsaline lakes showed the largest replacement of taxa
(0.38), followed by sub- to hyposaline lakes (0.25).
Only 9 taxa were responsible for 90% of the variation
mentioned above, namely the rotifer genera Bra-
chionus,Hexarthra,Polyarthra,Keratella,Filinia,
and Lecane, the cladoceran Moina, and calanoid
copepods (all species) (SIMPER, P\0.05). A sig-
nificant positive correlation was found between
Shannon–Wiener taxonomic diversity and FD
(q=0.43, P=0.04).
The multiple GLM analyses showed that salinity
was the most significant variable explaining the
variation in species richness (S) and FD. In both
cases, an inverse relationship was observed, where
salinity negatively affected each analyzed variable
(Sand FD). Using the AIC method and the inference of
multiple models, we obtained sixteen candidate mod-
els to consider S (Table 3). The relative importance
(w
i
) of the variable salinity was 0.99 and that of its
quadratic term (salinity)
2
was 0.91. From these values
and the obtained coefficients, the selected final model
included both variables as the main predictors of
zooplankton species richness (Table 4). In the case of
FD, eight candidate models were obtained (Table 3),
but only salinity was retained in the final model as a
significant variable (w
i
=0.75) (Table 4). Although
for H, any explanatory variables were statistically
significant from the GLM, a significant negative
relation was found between H and log-transformed
salinity values (q=-0.45; P=0.027).
For TZS and TZB, none of the explanatory
variables included in the GLM were significant
predictors. In addition, no influence of salinity was
observed on either microcrustacean mean size
(r=-0.23, P=0.278 and r=-0.02, P=0.92,
for cladocerans and copepods, respectively) or on
rotifer mean size (r=-0.288, P=0.182). How-
ever, we found a significant positive correlation
between salinity and TZB (Fig. 1a, b) and that the
size range of zooplankton (maximum size minus
minimum size observed per lake) was highly variable
and high also at high salinities (Fig. 2). Among the
explanatory variables included, total fish biomass and
abundance of small fish correlated negatively with
TZB (Fig. 1c, d). Besides, the particular analysis of
Table 2 Differences in environmental characteristics (Krus-
kal–Wallis with Dunn post hoc test) among the three lake
systems classified according to salinity (modified from Ham-
mer, 1986)
HP Post hoc tests
Sub Hypo Meso-
hyper
Depth 7.83 0.019*
Sub 0.36 0.01
Hypo 1.00 0.03
Meso-
hyper
0.03 0.08
DO 8.74 0.012*
Sub 0.81 0.01
Hypo 1.00 0.01
Meso-
hyper
0.03 0.02
NT 14.92 \0.001*
Sub <0.01 0.01
Hypo 0.01 0.01
Meso-
hyper
0.03 0.02
TP 7.82 0.019*
Sub 0.48 0.02
Hypo 1.00 0.01
Meso-
hyper
0.05 0.04
K18.7 \0.001*
Sub <0.01 0.01
Hypo \0.01 <0.01
Meso-
hyper
0.03 0.01
pH 0.6 0.74
Lake area 0.85 0.652
Secchi 3.92 0.14
Chl-a1.43 0.49
NH
4
-N 3.22 0.19
PO
4
-P 2.18 0.33
Sub subsaline (0.5–3 g l
-1
), Hypo hyposaline (3–20 g l
-1
),
Meso-hyper mesosaline and hypersaline grouped lakes
([20 g l
-1
)
For the comparison within lake categories, the statistic Qis
given in italics and the Pvalues from the Dunn post hoc test
are shown in bold. Asterisks indicate statistical differences
(P\0.05)
Hydrobiologia
123

cladoceran and copepod sizes excluding lakes without
fish (i.e., with salinities above 14 g l
-1
) revealed a
decline in microcrustacean size with increasing fish
abundance (Fig. 3). Fishless lakes were characterized
by the presence of relatively large and salt-tolerant
zooplankton species such as Daphnia magna Straus,
1820, Moina micrura Kurz, 1874, Arctodiaptomus
salinus (Daday, 1885), Sinocalanus tenellus (Kikuchi
K., 1928), and large Brachionus plicatilis Mu
¨ller,
1786.
The functional classification of zooplankton taxa
showed a clear segregation along the salinity gradient
(Fig. 4). Among the cladocerans, selective filter
feeders and filtering scrapers were restricted to the
lower salinities, filtering Ctenopoda occupied an
intermediate niche, whereas filtering Anomopoda
were abundant at high salinities. Within the Copepoda,
calanoids were highly tolerant to salinity, while
cyclopoids disappeared at salinities [7.6 g l
-1
.As
regards to rotifers, a bimodal distribution was
observed for raptorials within a salinity range of
0.5–12 g l
-1
, while microphagous species dominated
at salinity concentrations over 12 g l
-1
(r=0.56,
P=0.008, Fig. 4). The segregation of raptorial and
microphagous was represented by a replacement from
species of Ascomorpha,Asplanchna,Polyarthra,
Synchaeta, and Trichocerca genera to species of
Brachionus (being dominant), Conochilus,Euchlanis,
Filinia,Keratella, and Lecane genera (Fig. 5).
Moreover, within the raptorial rotifers, Asplanchna
was usually the dominant genus in subhaline lakes;
however, at higher salinities they disappeared and
raptorials such as Polyarthra and Hexarthra, mainly
H. oxyurus (Zernov 1903), became dominant.
Among the three salinity groups, freshwaters and
hyposaline lakes hosted on average 6.6 (±1.5) and 3.7
(±1.2) functional groups, respectively; while high-
salinity lakes had on average 2.5 (±2) functional
groups: All three groups differed significantly
(F=13, P\0.001). Also, the calculated FD Index
differed substantially between the two low-salinity
lakes and meso-hypersaline lakes (Fig. 6). Variance
partitioning indicated that both biological and envi-
ronmental factors influenced zooplankton FD. The
overall explained variation in this analysis was 20.3%
(environment alone: 8.1%; biological alone: 2.1%;
environment 9biological: 10.1%). Monte Carlo test
results were significant for environment 9biological
factors (F=1.16, P=0.034) but not for each factor
alone (F=1.5, P=0.088, and F=0.8, P=0.646
for environment and biological factors, respectively).
The first two axes of the RDA accounted for 58.3%
of the variation in total zooplankton FD (axis 1:
33.6%; axis 2: 24.7%) (Fig. 7). Among the copepods,
microphagous herbivores and microphagous carni-
vores were mainly correlated with the salinity gradient
and fish variables (size and diversity). Salinity was
Table 3 Statistics of the GLM
Candidate models KAICc AICc w
i
Richness
sal ?sal
2
3 130.13 0 0.55
absmallfish ?sal ?sal
2
4 132.63 2.5 0.16
area ?sal ?sal
2
4 132.73 2.6 0.15
absmallfish ?area ?sal ?sal
2
5 135.44 5.31 0.04
sal ?sal
2
2 135.55 5.43 0.04
absmallfish ?sal 3 136.16 6.03 0.03
Area ?sal 3 137.48 7.35 0.01
absmallfish ?area ?sal 4 138.11 7.98 0.01
absmallfish ?sal
2
3 140.17 10.04 0
sal
2
2 141.21 11.08 0
absmallfish 2 141.87 11.74 0
absmallfish ?area ?sal
2
4 141.94 11.81 0
Area ?sal 3 143.03 12.9 0
absmallfish ?area 3 143.45 13.32 0
Null 1 145.35 15.22 0
Area 2 147.07 16.94 0
FD
sal 3 20.62 0 0.44
fishzd ?sal 4 22.56 1.94 0.17
Null 2 23.38 2.75 0.11
Area ?fishzd 4 23.52 2.9 0.1
fishzd 3 23.85 3.23 0.09
area ?fishzd ?sal 5 25.78 5.15 0.03
Area 3 25.99 5.37 0.03
Area ?fishzd 4 26.74 6.11 0.02
sal salinity, absmallfish abundance of small fish, fishzd fish size
diversity
Summary of model selection results for candidate models
explaining species richness (S) and functional diversity (FD).
Null model and models with strong support (DAICc B2) are
provided and listed in decreasing order of importance. K(no. of
estimated parameters), AICc (Akaike information criterion
corrected for small sample size), DAICc (difference between
the lowest AICc value and AICc from all other models), and w
i
(AIC weights) for all candidate models are presented
Hydrobiologia
123

also the factor that correlated (negatively) with most
raptorial cladocerans and rotifer abundances. Micro-
phagous copepods (calanoids) and filtering anomopo-
dos (Daphnia,Moina) were positively correlated with
fish size diversity and average fish biomass, indicating
high sensitivity to fish predation pressure in the lakes.
Among all lakes, the sub- and hypohaline ones were
characterized by the presence of fish, raptorial rotifers,
macrophagous copepods, and most cladocerans
(Fig. 7).
Discussion
Zooplankton constitutes a key component in aquatic
food webs and is highly important in the transfer of
Table 4 Weight of each
variable in the final models
explaining species richness
(S) and functional diversity
(FD) using GLM
Estimated variables,
standard errors (SE), and
significance values (P) are
presented
Explanatory variables w
i
Estimated variables SE P
Richness
Intercept 2824 83.56 \2e-16***
Salinity 0.99 -35.9 10.11 0.000381***
Salinity
2
0.91 0.259 0.09175 0.004763**
FD
Intercept -0.20813 0.28982 \2e-16***
Salinity 0.75 -0.01484 0.01635 0.0352*
Fig. 1 Means (±SD) of total and within-zooplankton group
biomasses in the four salinity categories: Sub subsaline
(0.5–3 g l
-1
), Hypo hyposaline (3–20 g l
-1
), Meso-hyper
mesosaline, and hypersaline ([20 g l
-1
)(a). Relationship
between total zooplankton biomass (log-transformed values)
and salinity (log-transformed values) (b). Relationship between
total zooplankton biomass (log-transformed values) and fish
parameters: small fish (fork length between 10 and 25 cm)
abundance (c) and fish biomass (d). Spearman correlation
coefficients (q) and Psignificance values are given for each
correlation graph
Hydrobiologia
123

energy and matter from primary producers to higher
trophic levels. Therefore, changes in their structure
and function as a result of salinity fluctuations would
have serious consequences for ecosystem functioning.
As expected, we found that zooplankton richness (S),
specific diversity (H), and FD decreased with increas-
ing salinity, as in previous studies on zooplankton
(Boix et al., 2008; Brucet et al., 2009; Jensen et al.,
2010; Tavsanoglu et al., 2015), fish (Harrison &
Whitfield, 2006), macroinvertebrates (Brucet et al.,
2012), and macrophytes (Rodrı
´guez-Gallego et al.,
2015). Furthermore, we found that subsaline and
hyposaline lakes had the most similar zooplankton
taxa composition but differed from the meso-hyper-
saline lakes, the salinity group in which the largest
replacement of taxa occurred along the salinity
gradient. Salinity-tolerant species, such as the Bran-
chiopod Artemia sp., the copepod A. salinus, and the
rotifers B. plicatilis,H. oxyurus, and Colurella sp.,
dominated the zooplankton community in the high-
salinity lakes, which agrees with the findings in other
field and experimental studies (Toruan, 2012; Paturej
& Gutkowska, 2015; Tavsanoglu et al., 2015).
Calanoid copepods are considered to be salt-tolerant
taxa because of their marine origin (Sarma et al.,
2006), which explains their high tolerance to salinity,
not only in the lake region studied here but also in
other parts of the world (Brucet et al., 2009). By
contrast, rotifers may be limited by salinity because of
their freshwater origin (De Deckker, 1983); however,
B. plicatilis,H. oxyurus, and Colurella spp. such as C.
uncinata (Mu
¨ller, 1773) are salt-tolerant species and
frequently occur in highly saline systems (Toruan,
2012; Paturej & Gutkowska, 2015), confirming our
first hypothesis that only salt-tolerant species are able
to survive in high-salinity lakes.
Fig. 2 Mean and range size
(in mm) of zooplankton for
each lake along the salinity
gradient. Fishless lakes are
shown as light bars and lakes
with fish as dark gray bars
Fig. 3 Relationship between Cladocera and Copepoda lengths
and the abundance of small fish (standard length between 10 and
25 cm). Pearson correlation coefficient (r) and Psignificance
values are given in each panel. Fishless lakes were excluded in
this analysis (i.e., lakes with salinities above 14 g l
-1
)
Hydrobiologia
123

Functional and species diversity declined together
since a significant positive correlation was found
between the Shannon–Wiener index and the FD index.
Among the three salinity categories, freshwater lakes
hosted significantly more functional groups than
hyposaline and meso-hypersaline categories. The
Fig. 4 Abundance (ind. l
-1
) and distribution of each zooplankton functional group along the salinity gradient in the study lakes.
Fishless lakes are shown with light bars and lakes with fish are shown with dark gray bars
Hydrobiologia
123

filtering scrapers, filtering Ctenopoda, and micropha-
gous copepods, were lost in the last categories.
However, there was not only a loss of FGs with
increasing salinity, for rotifers but also the relative
balance of the FGs changed. While microphagous and
raptorials were equally represented in the low-salinity
lakes, a disproportional increase of microphages
occurred in the most salty lakes. The differences in
food acquisition and processing mechanisms of
microphagous and raptorials might favor their coex-
istence in the low-salinity lakes (Obertegger et al.,
2011). However, in high-salinity lakes, the increase of
microphages may be explained by their stronger
competition ability for food in stressing environments
(Alva-Martı
´nez et al., 2009), and probably because
they are better adapted to salinity than other rotifers
(Viayeh & S
ˇpoljar, 2012).
Both the imbalances and the decrease in FD may
not only result in less control of phytoplankton as
previously suggested (Helenius et al., 2016), but they
may also lead to less efficient nutrient cycling and
lower quality of the supply of food for invertebrates
and small fish at higher trophic levels (Barnett et al.,
2007; Obertegger & Manca, 2011).
The ‘compensation hypotheses’ (Schindler, 1990;
Ruesink & Srivastava, 2001; Mano & Tanaka, 2016)
suggest that sensitive species can be replaced by more
tolerant ones in stress situations, in this way main-
taining the stability of ecosystem functioning (Rue-
sink & Srivastava, 2001; Mano & Tanaka, 2016).
However, the replacements we observed both within
and between FGs in our study partly contradict these
hypotheses. We found that Asplanchna sp., a dominant
genus in subsaline lakes, disappeared at higher
salinities, while species such as Polyarthra sp.,
Synchaeta sp., and H. oxyurus became dominant
(Fig. 5). Although Polyarthra sp., Synchaeta sp., and
Hexarthra are raptorials and members of the same FG
Fig. 5 Abundances of the main raptorial genera (upper left panel), abundances of the main microphagous genera (upper right panel),
and abundances of total raptorial and microphagous rotifers (lower panel) along the salinity gradient
Hydrobiologia
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as Asplanchna, these genera can have quite different
effects on phytoplankton and the microbial web due to
their different sizes, feeding habits, and swimming
behaviors. Apart from the coronal activity, Polyarthra
sp. and Hexarthra possess unusual appendages that
facilitate quick locomotion or saltation movements,
allowing efficient avoidance of predator attacks (e.g.,
from cyclopoid copepods, invertebrates, and small
fish) (Hochberg & Gurbuz, 2008). Asplanchna spp.
has a relatively wide food size spectrum and prey
diversity (Chang et al., 2010) compared with the other
two genera. Its diet includes particulate matter,
phytoplankton, protozoans, bacteria, and even
dinoflagellates (Chang et al., 2010). Thus, the replace-
ment of Asplanchna by Polyarthra sp., Synchaeta sp.,
and Hexarthra along the salinity gradient would
promote a change in the ecological role of the raptorial
FG, with potential consequences for the ecosystem
functioning.
Considering the replacements between FGs, we
found that selective raptorials diminished, while
microphagous rotifers increased along the salinity
gradient. This may have implications for the sizes of
the ingested particles since the former consume large
and the latter smaller-sized particles (between 15 and
20 lm) (Obertegger & Manca, 2011). Among clado-
cerans, a gradual shift occurred from an assemblage
including Bosmina sp. and chydorids to one composed
almost exclusively of Moina micrura and Daphnia
magna at intermediate salinity levels. Although the
latter are mostly generalist feeders and feed on a wide
spectrum of food types and sizes (Jeppesen et al.,
1996), they are more sensitive to toxic cyanobacteria
and large filament sizes than other groups such as
chydorids (To
˜nno et al., 2016). This constraint may
have ecological implications since increased salinity,
apart from causing osmotic stress in the organisms,
may generate blooms of salt-tolerant cyanobacteria
(Paerl & Huisman, 2009) such as Microcystis aerug-
inosa (Tonk et al., 2007), Anabaenopsis sp., and
Nodularia sp. (Moisander et al., 2002). Thus, the
efficiency of cladocerans as a controller of phyto-
plankton might change at increasing salinities, leading
to a worsening of eutrophication symptoms (Jeppesen
Fig. 6 Zooplankton
functional diversity index
(upper panel) and the
contribution of each
functional group to the total
zooplankton community
(lower panel) within the four
lake systems, classified
according to salinity. Sub
subsaline (0.5–3 g l
-1
),
Hypo hyposaline
(3–20 g l
-1
), Meso-hyper
meso-hypersaline
([20 g l
-1
). Lowercase
letters indicate significant
differences
Hydrobiologia
123

et al., 2015). Among the copepods, calanoids (mi-
crophagous herbivores) remained highly tolerant to
salinity, whereas cyclopoids (microphagous carni-
vores) disappeared at salinities [7.6 g l
-1
, as also
seen in other salinity-gradient studies (Brucet et al.,
2009; Jeppesen et al., 2015). This shift may have
implications for other related trophic levels such as
primary producers. In fact, we found that phytoplank-
ton biomass (measured as Chl-a concentration)
remained almost constant along the salinity gradient,
which was probably controlled by the joint pressure of
large calanoids and other microphagous herbivores
favored by the absence of carnivorous cyclopoids.
Our second hypothesis was that zooplankton size
and biomass would decrease due to physiological
constraints with increasing salinity. Yet, contrary to
our expectation, we found that zooplankton mean
sizes, size ranges, and biomasses did not decrease with
increasing salinity. Actually, we found increased size
ranges and biomasses in high-salinity lakes compared
with subsaline and hyposaline ones. This contradicts a
previous study in brackish lakes which revealed no
effect of salinity on zooplankton size and biomass
(Gao et al., 2008) or a decrease in the mean size of
zooplankton with increasing salinity, affecting the
capacity of grazing zooplankton to control phyto-
plankton (Moss & Leah, 1982; Jeppesen et al.,
1994,2007). Our study, however, covered a larger
gradient in salinity (0.5–115 g l
-1
) where fish were
absent when salinity exceeded 14 g l
-1
, allowing the
presence of large-sized zooplankton species such as
Artemia sp. and calanoid copepods (e.g., A. salinus,S.
tenellus) (Pennak, 1991; Tolomeev et al., 2010). We
found that copepod and cladoceran sizes correlated
negatively with the abundance of small fish and total
fish biomass in the lakes with fish. This result indicates
that fish predation rather than salinity was the key
factor determining abundance, biomass, and size of
zooplankton, which is in agreement with previous
studies undertaken in shallow brackish lakes (Brucet
et al., 2010; Jensen et al., 2010).
Fig. 7 First two axes of the RDA based on zooplankton
functional groups (FG) (axis 1 explaining 33.6% and axis 2
explaining 24.7% of the total variation). Zooplankton functional
groups are indicated with blue arrows, explanatory (environ-
mental and biological) variables with gray arrows (a,b), and the
ordination of lakes with circles (b). In the right panel, the circle
sizes are proportional to the abundance of each FG within each
lake. Fishless lakes are shown as white circles, lakes with fish as
gray circles. RRaptr: raptorial rotifers (Ascomorpha,As-
planchna,Collotheca,Gastropus,Ploesoma,Polyarthra,Syn-
chaeta, and Trichocerca); RMicrp: microphagous rotifers
(Brachionus,Conochilus,Euchlanis,Filinia,Keratella,Lecane,
Notholca,Testudinella, and Trichotria); ClFiltCt: cladoceran
filtering Ctenopoda (Diaphanosoma and Pseudosida), ClFiltAn:
cladoceran filtering Anomopoda (Daphnia,Simocephalus,
Ceriodaphnia, and Moina), ClSeleFi: cladoceran-selective filter
feeders (Bosmina and Bosminopsis), ClFilSc: filtering scrapers
(Chydoridae and Macrotricidae), CopMicr: microphagous
herbivores (Sinocalanus,Arctodiaptomus, Calanoidea cope-
podites, etc.) CopMacrf: microphagous carnivores (Mesocy-
clops, Cyclopoidea copepodites, etc.)
Hydrobiologia
123

We conceptually summarize the observed
responses of the zooplankton to increasing salinity
created by a combination of direct (physiological
constraints) and indirect factors (fish predation pres-
sure) from both a structural (taxonomic) and a
functional perspective (Fig. 8). In accordance with
Helenius et al. (2016), we found that salinity acted as a
primary physiological filter structuring species rich-
ness and diversity, while predation was the main
biological driving factor defining the species size
structure. While high abundances of small fish tend to
reduce the overall size of the zooplankton, favoring
smaller taxa such as B. longirostris and rotifers
(Brooks & Dodson, 1965), high salinity, if resulting
in loss of fish, promotes the presence of large and more
saline-tolerant zooplankton species such as D. magna,
Moina spp., large copepods, and large brachionid
rotifers.
Moreover, we found that the distribution and
abundance of each FG depended on the interactions
between different factors (e.g., the turnover between
raptorial and microphagous rotifers responded to
changes in salinity, turbidity, and TP), resembling
the pattern observed in previous works (Litchman
et al., 2013; Vogt et al., 2013).
Fig. 8 Schematic summary of the observed responses of the
zooplankton to increasing salinity induced by a combination of
direct (physiological constraints) and indirect factors (predation
pressure). Considering taxonomy, zooplankton richness (S) and
specific diversity (H) decreased from freshwater to hypersaline
lakes. Sensitive species were replaced by more tolerant ones,
and subsaline and hyposaline lakes (\20 g l
-1
) had the most
similar zooplankton taxa composition. A functional approach
revealed that the number of functional groups (FD) diminished
from subsaline to meso-hypersaline lakes. Zooplankton size and
biomass increased as a consequence of an increase in copepod
and cladoceran sizes, which were favored by the absence of fish
predation. Rotifer sizes did not depend on the salinity gradient
since no relation was found between these two variables
Hydrobiologia
123

It can be concluded that for the zooplankton
community, species diversity (H) and species richness
(S) can be seriously affected by increased salinities
with potential effects on the trophic structure. Func-
tional diversity (FD, based on the differentiation
between functional groups proposed in this work) and
size structure diminished from subsaline to meso-
hypersaline lakes, suggesting that both attributes may
be appropriate indicators of changes in ecosystem
functioning related to changes in salinity (Fig. 7).
More diverse functional groups and wider size struc-
tures may promote more complex and balanced
trophic structures, more productive systems, and more
resistant communities under extreme environmental
variations (Vandermeer et al., 1998; Vaughn, 2010;
Flo
¨der & Hillebrand, 2012). It is evident from our
study that the expected salinity increase in lakes in arid
and semiarid climate zones in a warmer world (e.g.,
Jeppesen et al., 2015) will cause adverse effects on
biodiversity and functioning. However, our conclu-
sions should be interpreted with caution because other
factors may also influence the species responses such
as, among others, their physiological adaptation to
salinity, different biological interactions, and degree
of eutrophication.
Acknowledgements We want to thank the technical staff at
the Department of Bioscience in Silkeborg and NIGLAS in
Nanjing for help with the study in the field and the laboratory,
Drs. Juan Paggi and Susana Jose
´de Paggi for help with
zooplankton species identification, A. M. Poulsen for editorial
assistance, and Mariana Meerhoff for her kind encouragement
and valuable comments on an early version of the manuscript.
The staff at the Agriculture Department of Fuhai is gratefully
acknowledged for fieldwork assistance. This research was
funded by the Sino-Danish Centre for Education and Research
(SDC), Aarhus University (AU). J. L. Y. was supported by the
National Natural Science Foundation of China (31400400). F. T.
M. was supported by SNI-ANII (Uruguay). E. J. was supported
by the MARS project (Managing Aquatic ecosystems and water
Resources under multiple Stress) funded under the 7th EU
Framework Programme, Theme 6 (Environment including
Climate Change), Contract No.: 603378) and the AU Centre
for Water Technology.
References
Alekseev, V. R., 2002. Copepoda. In Fernando, C. H. (ed.), A
Guide to Tropical Freshwater Zooplankton: Identification,
Ecology and Impact on Fisheries. Backhuys Publishers,
Leiden: 123–188.
Alva-Martı
´nez, A. F., R. Ferna
´ndez, S. S. S. Sarma & S. Nan-
dini, 2009. Effect of mixed toxic diets (Microcystis and
Chlorella) on the rotifers Brachionus calyciflorus and
Brachionus havanaensis cultured alone and together.
Limnologica – Ecology and Management of Inland Waters
39: 302–305.
APHA, 1998. Standard Methods for the Examination of Water
and Wastewater, 20th edn. APHA, Washington DC.
Arthaud, F., D. Vallod, J. Robin & G. Bornette, 2012.
Eutrophication and drought disturbance shape functional
diversity and life-history traits of aquatic plants in shallow
lakes. Aquatic Sciences 74: 471–481.
Barnett, A. J., K. Finlay & B. E. Beisner, 2007. Functional
diversity of crustacean zooplankton communities: towards
a trait-based classification. Freshwater Biology 52:
796–813.
Boix, D., S. Gasco
´n, J. Sala, A. Badosa, S. Brucet, R. Lo
´pez-
Flores, M. Martinoy, J. Gifre & X. D. Quintana, 2008.
Patterns of composition and species richness of crustaceans
and aquatic insects along environmental gradients in
Mediterranean water bodies. Hydrobiologia 597: 53–69.
Borcard, D., P. Legendre & P. Drapeau, 1992. Partialling out the
spatial component of ecological variation. Ecology 73:
1045–1055.
Bottrell, H. H., A. Duncan, Z. M. Gliwicz, E. Grygierek, A.
Herzig, A. Hillbricht-Ilkowska, H. Kurasawa, P. Larsson &
T. We˛glen
´ska, 1976. A review of some problems in zoo-
plankton production studies. Norwegian Journal of Zool-
ogy 24: 419–456.
Brooks, J. L., S. I. Dodson, 1965. Predation, body size, and
composition of plankton. Science 150: 28–35.
Brucet, S., D. Boix, R. Lo
´pez-Flores, A. Badosa & X. D. Quin-
tana, 2006. Size diversity and species diversity of zoo-
plankton communities in fluctuant Mediterranean salt
marshes. Estuarine, Coastal and Shelf Science 67:
424–432.
Brucet, S., D. Boix, S. Gasco
´n, J. Sala, X. D. Quintana, A.
Badosa, M. Søndergaard, T. L. Lauridsen & E. Jeppesen,
2009. Species richness of crustacean zooplankton and
trophic structure of brackish lagoons in contrasting climate
zones: north temperate Denmark and Mediterranean Cat-
alonia (Spain). Ecography 32: 692–702.
Brucet, S., D. Boix, X. D. Quintana, E. Jensen, L. W. Nathansen,
C. Trochine, M. Meerhoff, S. Gasco
´n & E. Jeppesen, 2010.
Factors influencing zooplankton size structure at contrast-
ing temperatures in coastal shallow lakes: implications for
effects of climate change. Limnology and Oceanography
55: 1697.
Brucet, S., D. Boix, L. W. Nathansen, X. D. Quintana, E. Jensen,
D. Balayla, M. Meerhoff & E. Jeppesen, 2012. Effects of
temperature, salinity and fish in structuring the macroin-
vertebrate community in shallow lakes: implications for
effects of climate change. PloS one 7: e30877.
Burnham, K. P. & D. R. Anderson, 2002. Model Selection and
Multimodel Inference: A Practical Information-Theoretic
Approach. Springer, New York, NY.
Chang, K. H., H. Doi, Y. Nishibe & S. I. Nakano, 2010. Feeding
habits of omnivorous Asplanchna: comparison of diet
composition among Asplanchna herricki,A. priodonta and
A. girodi in pond ecosystems. Journal of Limnology 69:
209–216.
Hydrobiologia
123

Daufresne, M., K. Lengfellner & U. Sommer, 2009. Global
warming benefits the small in aquatic ecosystems. Pro-
ceedings of the National Academy of Sciences 106:
12788–12793.
De Deckker, P., 1983. Notes on the ecology and distribution of
non-marine ostracods in Australia. Hydrobiologia 106:
223–234.
Declerck, S., J. Vandekerkhove, L. Johansson, K. Muylaert, J.
M. Conde-Porcuna, K. Van Der Gucht, C. Pe
´rez-Martı
´nez,
T. Lauridsen, K. Schwenk, G. Zwart, W. Rommens, J.
Lo
´pez-Ramos, E. Jeppesen, W. Vyverman, L. Brendonck
& L. De Meester, 2005. Multi-group biodiversity in shal-
low lakes along gradients of phosphorus and water plant
cover. Ecology 86: 1905–1915.
Ding, N., W. Yang, Y. Zhou, I. Gonza
´lez-Bergonzoni, J. Zhang,
K. Chen, N. Vidal, E. Jeppesen & B. Wang, 2017. Different
responses of functional traits and diversity of stream
macroinvertebrates to environmental and spatial factors in
the Xishuangbanna watershed of the upper Mekong River
Basin, China. Science of the Total Environment 574:
288–299.
Dumont, H. J., I. Van de Velde & S. Dumont, 1975. The dry
weight estimate of biomass in a selection of Cladocera,
Copepoda and Rotifera from the plankton, periphyton and
benthos of continental waters. Oecologia 19: 75–97.
Flo
¨der, S. & H. Hillebrand, 2012. Species traits and species
diversity affect community stability in a multiple stressor
framework. Aquatic Biology 17(3): 197–209.
Gallego, I., T. A. Davidson, E. Jeppesen, C. Pe
´rez-Martı
´nez, P.
Sa
´nchez-Castillo, M. Juan, F. Fuentes-Rodrı
´guez, D. Leo
´n,
P. Pen
˜alver, J. Toja & J. J. Casas, 2012. Taxonomic or
ecological approaches? Searching for phytoplankton sur-
rogates in the determination of richness and assemblage
composition in ponds. Ecological Indicators 18: 575–585.
Gao, Q., Z. Xu & P. Zhuang, 2008. The relation between dis-
tribution of zooplankton and salinity in the Changjiang
Estuary. Chinese Journal of Oceanology and Limnology
26: 178–185.
Grime, J. P., 1973. Competitive exclusion in herbaceous vege-
tation. Nature 242: 344–347.
Hammer, U. T., 1986. Saline Lake Ecosystems of the World.
Junk, Dordrecht.
Harrison, T. D. & A. K. Whitfield, 2006. Temperature and
salinity as primary determinants influencing the biogeog-
raphy of fishes in South African estuaries. Estuarine,
Coastal and Shelf Science 66: 335–345.
Heino, J., 2008. Patterns of functional biodiversity and function-
environment relationships in lake littoral macroinverte-
brates. Limnology and Oceanography 53: 1446–1455.
Heino, J., D. Schmera & T. Er}
os, 2013. A macroecological
perspective of trait patterns in stream communities.
Freshwater Biology 58: 1539–1555.
Helenius, L. K., E. Leskinen, H. Lehtonen & L. Nurminen,
2016. Spatial patterns of littoral zooplankton assemblages
along a salinity gradient in a brackish sea: a functional
diversity perspective. Estuarine, Coastal and Shelf Science.
https://doi.org/10.1016/j.ecss.2016.08.031.
Hochberg, R. & O. A. Gurbuz, 2008. Comparative morphology
of the somatic musculature in species of Hexarthra and
Polyarthra (Rotifera, Monogononta): its function in
appendage movement and escape behavior. Zoologischer
Anzeiger-A Journal of Comparative Zoology 247:
233–248.
Jensen, E., S. Brucet, M. Meerhoff, L. Nathansen & E. Jeppesen,
2010. Community structure and diel migration of zoo-
plankton in shallow brackish lakes: role of salinity and
predators. Hydrobiologia 646: 215–229.
Jeppesen, E., M. Søndergaard, E. Kanstrup, B. Petersen, R.
B. Eriksen, M. Hammershøj, E. Mortensen, J. P. Jensen &
A. Have, 1994. Does the impact of nutrients on the bio-
logical structure and function of brackish and fresh-water
lakes differ? Hydrobiologia 275: 15–30.
Jeppesen, E., M. Søndergaard, J. P. Jensen, E. Mortensen & O.
Sortkjær, 1996. Fish-induced changes in zooplankton
grazing on phytoplankton and bacterioplankton: a long-
term study in shallow hypertrophic Lake Søbygaard.
Journal of Plankton Research 18: 1605–1625.
Jeppesen, E., T. L. Lauridsen, S. F. Mitchell, K. Christoffersen
& C. W. Burns, 2000. Trophic structure in the pelagial of
25 shallow New Zealand lakes: changes along nutrient and
fish gradients. Journal of Plankton Research 22: 951–968.
Jeppesen, E., M. Søndergaard, A. R. Pedersen, K. Ju
¨rgens, A.
Strzelczak, T. L. Lauridsen & L. S. Johansson, 2007.
Salinity induced regime shift in shallow brackish lagoons.
Ecosystems 10: 47–57.
Jeppesen, E., S. Brucet, L. Naselli-Flores, E. Papastergiadou, K.
Stefanidis, T. No
˜ges, P. No
˜ges, J. L. Attayde, T. Zohary, J.
Coppens, T. Bucak, R. Fernandes Menezes, F. R. Sousa
Freitas, M. Kernan, M. Søndergaard & M. Bekliog
˘lu, 2015.
Ecological impacts of global warming and water abstrac-
tion on lakes and reservoirs due to changes in water level
and related changes in salinity. Hydrobiologia 750:
201–227.
Jin, X. C. & Q. Y. Tu, 1990. Survey Specification for Lake
Eutrophication. Environmental Science Press, Beijing.
Kalff, J., 2002. Limnology: Inland Water Ecosystems.
Kor
ˇı
´nek, V., 1981. Diaphanosoma birgei n. sp. (Crustacea,
Cladocera). A new species from America and its widely
distributed subspecies Diaphanosoma birgei ssp. lacustris
n. ssp. Canadian Journal of Zoology 59: 1115–1121.
Korı
´nek, V., 2002. Cladocera. In Fernando, C. H. (ed.), A Guide
to Tropical Freshwater Zooplankton. Leiden, Backhuys
Publishers, pp. 69–122.
Korovchinsky, N. M., 1992. Sididae & Holopediidae (Crus-
tacea: Daphniiformes). SPB Academic Publishing, The
Hague.
Koste, W., 1978. Rotatoria. Die Ra
¨dertiere Mitteleuropas. Gebr.
Borntraeger, Berlin, Stuttgart: 673 pp. 234 plates.
Kruk, C., V. I. M. Huszar, E. T. H. Peeters, S. Bonilla, L. Costa,
M. Lu
¨rling, C. S. Reynolds & M. Scheffer, 2010. A mor-
phological classification capturing functional variation in
phytoplankton. Freshwater Biology 55: 614–627.
Leps
ˇ, J., & P. S
ˇmilauer, 1998. Multivariate Analysis of Eco-
logical Data. Faculty of Biological Sciences, University of
South Bohemia Ceske
´Budejovice, Czech Republic: 110
pp.
Litchman, E., M. D. Ohman & T. Kiørboe, 2013. Trait-based
approaches to zooplankton communities. Journal of
Plankton Research 35: 473–484.
Longhi, M. L. & B. E. Beisner, 2010. Patterns in taxonomic and
functional diversity of lake phytoplankton. Freshwater
Biology 55: 1349–1366.
Hydrobiologia
123

Mano, H. & Y. Tanaka, 2016. Mechanisms of compensatory
dynamics in zooplankton and maintenance of food chain
efficiency under toxicant stress. Ecotoxicology 25:
399–411.
Mason, N. W., F. Bello, D. Mouillot, S. Pavoine & S. Dray,
2013. A guide for using functional diversity indices to
reveal changes in assembly processes along ecological
gradients. Journal of Vegetation Science 24: 794–806.
McGill, B. J., B. Enquist, E. Weiher & M. Westoby, 2006.
Rebuilding community ecology from functional traits.
Trends in Ecology & Evolution 21: 178–185.
Moisander, P. H., E. McClinton & H. W. Paerl, 2002. Salinity
effects on growth, photosynthetic parameters, and nitro-
genase activity in estuarine planktonic cyanobacteria.
Microbial Ecology 43: 432–442.
Moss, B. R., 2009. Ecology of Fresh Waters: Man and Medium,
Past to Future. Wiley.
Moss, B. & R. T. Leah, 1982. Changes in the ecosystem of a
guanotrophic and brackish shallow lake in eastern Eng-
land: potential problems in its restoration. Internationale
Revue der Gesamten Hydrobiologie 67: 625–659.
Nielsen, K. J., 2003. Nutrient loading and consumers: agents of
change in open-coast macrophyte assemblages. Proceed-
ings of the National Academy of Sciences USA 100:
7660–7665.
Obertegger, U. & G. Flaim, 2015. Community assembly of
rotifers based on morphological traits. Hydrobiologia 753:
31–45.
Obertegger, U. & M. Manca, 2011. Response of rotifer func-
tional groups to changing trophic state and crustacean
community. Journal of Limnology 70: 231–238.
Obertegger, U., H. A. Smith, G. Flaim & R. L. Wallace, 2011.
Using the guild ratio to characterize pelagic rotifer com-
munities. Hydrobiologia 662: 157–162.
Ojaveer, H., L. A. Kuhns, R. P. Barbiero & M. L. Tuchman,
2001. Distribution and population characteristics of Cer-
copagis pengoi in Lake Ontario. Journal of Great Lakes
Research 27: 10–18.
Paerl, H. W. & J. Huisman, 2009. Climate change: a catalyst for
global expansion of harmful cyanobacterial blooms.
Environmental Microbiology Reports 1: 27–37.
Paturej, E. & A. Gutkowska, 2015. The effect of salinity levels
on the structure of zooplankton communities. Archives of
Biological Sciences 67: 483–492.
Pennak, R., 1991. Fresh-Water Invertebrates of the United
States. Wiley Interscience, USA: 628.
Quintana, X. D., S. Brucet, D. Boix, R. Lo
´pez-Flores, S. Gasco
´n,
A. Badosa, J. Sala, R. Moreno-Amich & J. J. Egozcue,
2008. A non-parametric method for the measurement of
size diversity, with emphasis on data standardisation.
Limnology and Oceanography: Methods 6: 75–86.
Quintana, X. D., M. Arim, A. Badosa, J. M. Blanco, D. Boix, S.
Brucet, J. Compte, J. J. Egozcue, E. de Eyto, U. Gaedke, S.
Gasco
´n, L. Gil de Sola
´, K. Irvine, E. Jeppesen, T. L. Lau-
ridsen, R. Lo
´pez-Flores, T. Mehner, S. Romo & M.
Søndergaard, 2015. Predation and competition effects on
the size diversity of aquatic communities. Aquatic Sciences
77: 45–57.
R Development Core Team, 2011. R: A Language and Envi-
ronment for Statistical Computing. R Foundation for Sta-
tistical Computing, Vienna.
Reynolds, C. S., V. Huszar, C. Kruk, L. Naselli-Flores & S.
Melo, 2002. Towards a functional classification of the
freshwater phytoplankton. Journal of Plankton Research
24: 417–428.
Rodrı
´guez-Gallego, L., V. Sabaj, S. Masciadri, C. Kruk, R.
Arocena & D. Conde, 2015. Salinity as a major driver for
submerged aquatic vegetation in coastal lagoons: a multi-
year analysis in the subtropical Laguna de Rocha. Estuaries
and Coasts 38: 451–465.
Ruesink, J. L. & D. S. Srivastava, 2001. Numerical and per
capita responses to species loss: mechanisms maintaining
ecosystem function in a community of stream insect
detritivores. Oikos 93: 221–234.
Sarma, S. S. S., S. Nandini, J. Morales-Ventura, I. Delgado-
Martı
´nez & L. Gonza
´lez-Valverde, 2006. Effects of NaCl
salinity on the population dynamics of freshwater zoo-
plankton (rotifers and cladocerans). Aquatic Ecology 40:
349–360.
Schallenberg, M., C. J. Hall & C. W. Burns, 2003. Conse-
quences of climate-induced salinity increases on zoo-
plankton abundance and diversity in coastal lakes. Marine
Ecology Progress Series 251: 181–189.
Schindler, D. W., 1990. Experimental perturbations of whole
lakes as tests of hypotheses concerning ecosystem structure
and function. Oikos 57: 25–41.
Schmera, D., T. Er}
os & J. Podani, 2009. A measure for assessing
functional diversity in ecological communities. Aquatic
Ecology 43: 157–167.
Shannon, C. E. & W. Weaver, 1964. The Mathematical Theory
of Communication. University Illinois Press, Urbana, IL.
Sheridan, J. A. & D. Bickford, 2011. Shrinking body size as an
ecological response to climate change. Nature Climate
Change 1: 401–406.
Tavsanoglu, U. N., R. Maleki & N. Akbulut, 2015. Effects of
salinity on the zooplankton community structure in two
marine lakes and one freshwater lake in the Konya closed
basin, Turkey. Ekoloji 24: 25–32.
Ter Braak, C. J., 1994. Canonical community ordination. Part I:
basic theory and linear methods. Ecoscience 1: 127–140.
Ter Braak, C. J., & P. Smilauer, 2002. CANOCO Reference
Manual and CanoDraw for Windows User’s Guide: Soft-
ware for Canonical Community Ordination, version 4.5.
www.canoco.com.
Tolomeev, A. P., N. N. Sushchik, R. D. Gulati, O.
N. Makhutova, G. S. Kalacheva & T. A. Zotina, 2010.
Feeding spectra of Arctodiaptomus salinus (Calanoida,
Copepoda) using fatty acid trophic markers in seston food
in two salt lakes in South Siberia (Khakasia, Russia).
Aquatic Ecology 44: 513–530.
Tonk, L., K. Bosch, P. M. Visser & J. Huisman, 2007. Salt
tolerance of the harmful cyanobacterium Microcystis
aeruginosa. Aquatic Microbial Ecology 46: 117–123.
To
˜nno, I., H. Agasild, T. Ko
˜iv, R. Freiberg, P. No
˜ges & T.
No
˜ges, 2016. Algal diet of small-bodied crustacean zoo-
plankton in a cyanobacteria-dominated eutrophic lake.
PloS one 11: e0154526.
Toruan, R. L., 2012. Zooplankton community emerging from
fresh and saline wetlands. Ecohydrology & Hydrobiology
12: 53–63.
USEPA, 2002. National primary drinking water regulations. US
Environmental Protection Agency, Washington, DC.
Hydrobiologia
123

Vandermeer, J., M. van Noordwijk, J. Anderson, C. Ong & I.
Perfecto, 1998. Global change and multi-species agroe-
cosystems: concepts and issues. Agriculture, Ecosystems
& Environment 67: 1–22.
Vaughn, C. C., 2010. Biodiversity losses and ecosystem func-
tion in freshwaters: emerging conclusions and research
directions. BioScience 60: 25–35.
Viayeh, R. M. & M. S
ˇpoljar, 2012. Structure of rotifer assem-
blages in shallow waterbodies of semi-arid northwest Iran
differing in salinity and vegetation cover. Hydrobiologia
686: 73–89.
Vogt, M., T. Hashioka, M. R. Payne, E. T. Buitenhuis, C.
L. Que
´re
´, S. Alvain, M. N. Aita, L. Bopp, S. C. Doney, T.
Hirata, I. Lima, S. Sailley & Y. Yamanaka, 2013. The
distribution, dominance patterns and ecological niches of
plankton functional types in Dynamic Green Ocean Models
and satellite estimates. Biogeosciences Discussions 10:
17193–17247.
Waterkeyn, A., P. Grillas, B. Vanschoenwinkel & L. Brendon-
ck, 2008. Invertebrate community patterns in Mediter-
ranean temporary wetlands along hydroperiod and salinity
gradients. Freshwater Biology 53: 1808–1822.
Whittaker, R. H., 1972. Evolution and measurement of species
diversity. Taxon 21: 213–251.
Williams, W. D., 1998. Salinity as a determinant of the structure
of biological communities in salt lakes. Hydrobiologia 381:
191–201.
Hydrobiologia
123