Post on 25-Jan-2023
PRIMARY RESEARCH PAPER
Epiphytic, littoral diatoms as bioindicators of shallow laketrophic status: Trophic Diatom Index for Lakes (TDIL)developed in Hungary
Csilla Stenger-Kovacs Æ Krisztina Buczko ÆEva Hajnal Æ Judit Padisak
Received: 25 October 2006 / Revised: 27 March 2007 / Accepted: 30 March 2007 / Published online: 21 June 2007� Springer Science+Business Media B.V. 2007
Abstract Littoral diatoms are important con-
tributors of the primary production in shallow
aquatic ecosystems and they can be used as
indicators of the trophic status. The aim of the
study was to develop an index to assess trophic
status of Hungarian lakes as suggested by the
Water Framework Directive. In spring of 2005
and 2006, epiphytic diatom samples were col-
lected from 83 shallow lakes. Weighted average
method was used to develop and test the TP
model. In the developed TP model correlation
between the observed and diatom inferred TP
was high (r2 = 0.96, n = 67). The optimum and
tolerance TP parametrics of 127 species were
determined and trophic indicator and sensibility
values were defined for the Trophic Diatom
Index for Lakes (TDIL). The TDIL was appli-
cable to assess the ecological status of Hungarian
shallow lakes. According to the TDIL the
ecological status of 4 lakes were in excellent,
25 in good, 21 in medium, 21 in tolerable and 12
in bad status.
Keywords Lakes � Littoral diatoms � Optimum �Tolerance � TP � Trophic state � Water
Framework Directive
Introduction
Eutrophication can be defined as an intensified
accumulation of plant biomass generally due to
an increase in nutrients (primarily phosphorus
and nitrogen). The decomposition of this biomass
may reduce the oxygen level leading to secondary
impacts on aquatic ecosystems (Vollenweider,
1989). These events interfere with different kinds
of human water use (e.g. recreation, fishery/
angling, transport, drinking water supply, etc.).
During the eutrophication, the original flora and
the fauna change (Padisak, 2005; Istvanovics
et al., 2007) and the ecosystem behaviour might
become unpredictable.
Handling editor: K. Martens
Electronic supplementary material The online version ofthis article (doi: 10.1007/s10750-007-0729-z) containssupplementary material, which is available to authorizedusers.
C. Stenger-Kovacs (&) � E. Hajnal � J. PadisakDepartment of Limnology, University of Pannonia,Egyetem u. 10, 158, Veszprem 8200, Hungarye-mail: stenger.kovacs@almos.uni-pannon.hu
E. Hajnale-mail: hajnal.nagy@t-online.hu
J. Padisake-mail: padisak@almos.uni-pannon.hu
K. BuczkoBotanical Department of Hungarian Natural HistoryMuseum, 222, Budapest 1476, Hungarye-mail: buczko@bot.nhmus.hu
123
Hydrobiologia (2007) 589:141–154
DOI 10.1007/s10750-007-0729-z
Littoral diatoms are important contributors of
the primary production in shallow aquatic eco-
systems (Wetzel, 1990). Therefore, they can serve
as good indicators of the ecological status of
lakes. A number of methods (Coste in Cemagref,
1982; Rumeau & Coste, 1988; Descy & Coste,
1991; Dell’Uomo, 1996, Lenoir & Coste, 1996;
Kelly, 1998; Prygiel & Coste, 2000) were devel-
oped for use of diatoms as bioindicators of
changing environment, especially in rivers. The
applicability of these indices has been spatially
limited, even for rivers, since distribution of
species may differ markedly (Wu, 1999). As most
described diatom indices were developed and
applied for running waters (Brabecz & Szoszkie-
wicz, 2006), applications for lakes are sporadic
and in many cases doubtful. Although eutrophi-
cation is a common water quality problem in lake
ecosystems all over the world (e.g. Reckhow &
Chapra, 1983), ecological monitoring programs
that include diatoms are rare (Acs et al., 2005).
A number of paleolimnological studies aimed
to reconstruct past eutrophication of lakes based
on paleolimnological evidences (Taylor et al.,
2006) using diatom valves preserved in lake
sediments (Anderson et al., 1993; Alefs et al.,
1996; Reavie et al., 2002) with the weighted
averaging method (ter Braak & van Dam, 1989).
Later this method was used in modern lake and
river monitoring (Schonfelder & Gelbrecht, 2002;
Kovacs et al., 2006; Soininen & Niemela, 2002)
because species-specific environmental optima
and tolerances of modern diatom species (Birks
et al., 1990) are also different.
The EC Water Framework Directive (WFD;
EC Parliament and Council, 2000) initiated a
number of research focusing on basic concepts
(Furse et al., 2006), typology of surface waters
(Sandin & Verdonschot, 2006) and various kinds
of methodical approaches (Comte et al., 2005;
Besse-Lototskaya et al., 2006; Persson et at.,
2006; Springe et al., 2006).
The aim of this study was to develop a trophic
diatom index on the basis of diatom species’
optimum and tolerance characteristics along the
total phosphorus (TP) gradient in a diverse set of
Hungarian lakes. As littoral diatoms (phytoben-
thos) are one of the biotic indicator group
included in the WFD it was an urgent need to
develop diatom-based method that is suitable for
monitoring trophic state of lakes.
Materials and methods
Sampling
During April–June 2005 and April–July 2006 alto-
gether 83 epiphytic diatom samples were collected
in Hungarian shallow (average depth < 4 m) lakes
with surface areas ranging 4 m2 and 594 km2
(important information on the sampled lakes are
given in the Electronic supplementary material).
According to the Hungarian lake typology 10 water
types were investigated (Table 1).
Diatom samples were taken in the littoral
region of the lakes from Phragmites australis
stems or, if it was absent, from other emergent
macrophytes. Sampling of epilithon, epipsammon
or epipelon was preferably avoided in accordance
with earlier studies by Poulıckova et al. (2004)
demonstrating that diatom assemblages on reed
indicate different trophic state than those on
stone or mud. Restriction of sampling to a single
preferred substratum helps to avoid differences
originating from different substrate preference of
the indicator species (Hofmann, 1994). Another
advantage of standardization of sampling to
P. australis lies in its cosmopolitan distribution
and common occurence in the littoral region.
Seasonal and vertical distribution of the epiphytic
diatom assemblages can be markedly different
(Hoagland & Peterson, 1990; Muller, 1994).
Therefore, diatom samples were taken preferably
from stem sections 5–20 cm below the water
surface, in spring (Buczko & Acs, 1996/1997; Acs
et al., 2005) from April to the beginning of July.
Exceptions included some saline lakes and
oxbows in 2006, where sampling time extended
to the summer due to uncommon wheather
conditions (unusually high precipitation and/or
surface shrinking of the small/shallow saline
lakes).
The diatom valves were cleaned by hot hydro-
gen peroxide method and were embedded in
synthetic resin (Zrax�). At least 400 valves were
counted in each sample. The comparability of
identifications was ensured with intercalibration.
142 Hydrobiologia (2007) 589:141–154
123
Diatoms were identified at least to species level
using light microscopy according to Krammer &
Lange-Bertalot (1991–2000), Lange Bertalot
(1995–2002) and Krammer (2002). The counts
were converted to relative abundance.
The physical and chemical parameters of the
water were measured on the field and in parallel
samples taken for water chemistry. TP was
determined by spectrophotometry (Pote & Dan-
iel, 2000) according to international standards.
Model development and statistical analyses
Weigthed average method (WA) was used to
derive the autecological data of the diatoms. The
theorethical base of this method is, that the species
occur in the highest abundance near their ecolog-
ical optima (Birks et al., 1990). The optimum can
be calculated according to the following equation:
uk ¼Xn
i¼1
yikxi=Xn
i¼1
yik regression step ð1Þ
where, uk is the average optimum of the given
environmental parameter for a k taxon, xi is the
value of the environmental variable at site i and
yik is the abundance of species k at site i.
Subsequently, applying the previously-known
optima, the inferred environmental parameter
(xi) can be calculted (Stoermer & Smol, 2001) as:
xi ¼Xm
k¼1
yikuk=Xm
k¼1
yik calibration step ð2Þ
The regression step was used for development of
a TP model with using data from 67 sampling sites
and calculating the TP optima and tolerance levels
(defined as 1 standard deviation) of the individual
species. The calibration step served for testing of
this model by the calibration against with 16
sampling sites. The calculations were performed
with the computer program C2 version 3.1 (http://
www.campus.ncl.ac.uk/staff/Stephen.Juggins). The
root mean squared error of prediction (RMSE)
was calculated directly from the calibration set.
According to the calculated TP optima and
tolerances, trophic indicator values were deter-
mined to only those species which occured in at
least three samples. TP optima were categorized
into 6 classes running from 0 (hypertrophic) to 5
(oligotrophic). The resulting categories had TP
values (0) > 1.500 (1) 0.401–1.500 (2) 0.300–0.400
(3) 0.190–0.299 (4) 0.100–0.189 (5) < 0.090 mg l–1.
According to requirements of the Water Frame-
work Directive (WFD), trophic categories (inter-
vals of quality classes) were equipped with
common qualification (bad, tolerable, medium,
good, excellent). Tolerance values of the species
were sorted into three categories: 1-sensitive
(tolerance: 0.01–0.09 mg l–1), 2-slightly sensitive
(tolerance: 0.1–0.3 mg l–1) and 3-tolerant (toler-
ance: 0.3–3 mg l–1). Trophic Diatom Index for
Lakes (TDIL) was calculated applying the equa-
tion by Zelinka & Marvan (1961):
TDIL ¼P
akskvkPaksk
where a is the relative abundance, s is the
sensibility and v is the trophic indicator value of
the species k. The value of the index varies
between 0 and 5. According to the trophic status
assessed by TDIL 5 water quality classes were
defined similarly to other indices (Padisak et al.,
2006) developed for the purposes of the WFD
Table 1 The investigated 10 lake types according to the Hungarian lake typology (Szilagyi et al., 2004)
1. Lowland, calcareous, 3–15 m depth, large, permanent lakes.2. Lowland, saline, 1–3 m depth, large, permanent lakes.3. Lowland, saline, 1–3 m depth, medium, permanent lakes.4. Lowland, calcareous-saline, < 1 m depth, small, permanent lakes.5. Lowland, calcareous-saline, < 1 m depth, small, temporary lakes.6. Lowland, calcareous-organic, < 4 m depth, small, permanent lakes.7. Lowland, saline, < 3 m depth, small, permanent lakes.8. Lowland, calcareous-saline, < 1.5 m depth, small, temporary lakes.9. Lowland, calcareous-organic, < 3 m depth, small, permanent lakes.10. Lowland, calcareous-organic, < 1.5 m depth, small, temporary lakes
Hydrobiologia (2007) 589:141–154 143
123
(Table 2). In the data analyses Shannon diversity
was also calculated (Shannon & Wiener, 1949).
Results
In the 83 lakes altogether 361 species of diatoms
were identifed but only 247 species (with relative
abundance > 0.5%) were used for the further
analyses. The most common taxa (Achnanthidium
minutissimum, Amphora pediculus, Cocconeis
placentula, Gomphonema parvulum, Navicula
cryptotenella, Navicula veneta and Nitzschia pale-
acea) were cosmopolitan and widely distributed
in inland Hungarian waters. The average species
richness and the standard deviation was 26 ± 8.
The lowest species richness (8) was found in the
Fulop-szek in 2005 (FUL397), the highest (53) in
Lake Balaton in 2006 (BalBD1). The average
diversity was 2.7 ± 0.8 (eveness was 0.6 ± 0.1).
The TP concentrations per sample ranged be-
tween 0.01 and 5.72 mg l–1 in the sample set
(average: 0.50 ± 0.51 mg l–1). The TP model
(Fig. 1) was developed by weighted averaging
without tolerance downweighting regression
(WAtol) with inverse deshrinking to infer TP
concentrations of the lakes. This method pro-
duced the best statistical data (Table 3). Strong
correlation (r2 = 0.96, n = 67) was found between
the measured and the inferred TP concentrations
in the developed TP model. The RMSE was
0.17 mg l–1. The correlation in the test set was
lower (r2 = 0.59, n = 16).
The TP optimum, tolerance and indicator
value of 127 species were determined (Table 4).
Cymbella helvetica, Gomphonema angustum and
Diatoma moniliformis were sensitive and charac-
teristic species for low trophic state. On the other
edge of the trophic spectrum there were several
tolerant, eutrophic taxa e.g. Nitzschia communis,
Amphora veneta, Craticula cuspidata. The taxon
list in Table 4 compared to the list of TDI Austria
(Rott et al., 1999) provided new, applicable indi-
cator values for 31 taxa and, additionally, there
Table 2 Class boundaries and trophic status according tothe TDIL
Class boundary Ecological status
4–5 Excellent3 < 4 Good2 < 3 Medium1 < 2 Tolerable0 < 1 Bad
0.01
0.1
1
10
0.01 0.1 10
log diatom inferred TP
log
mea
sure
d T
P
r2 = 0.96
RMSEP = 0.17
r2 (test set) = 0.59
1
Fig. 1 Relationship between log observed TP and diatominferred TP using weighted averaging without tolerancedownweighting regression (WAtol) with inverse deshrin-king. (empty circles: training set; full triangle: test set)
Table 3 Correlation and root mean squared error (RMSE) of prediction for the weighted averaging and linear regression inthe training and test set
Code of the method Method and deshrinking RMSE(traning set)
r2
(training set)r2
(test set)
WA_INV Weighted averaging model(inverse deshrinking) for TP
0.46 0.71 –
WA_CLAS Weighted averaging model(classical deshrinking) for TP
0.55 0.71 –
WATOL_INV Weighted averaging model(tolerance downweighted,inverse deshrinking) for TP
0.17 0.96 0.59
WATOL_CLA Weighted averaging model(tolerance downweighted,classical deshrinking) for TP
0.17 0.96 –
144 Hydrobiologia (2007) 589:141–154
123
Ta
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4L
ist
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Hydrobiologia (2007) 589:141–154 145
123
Ta
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90
.08
94
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rag
ila
ria
dil
ata
ta(B
reb
isso
n)
La
ng
e-B
ert
alo
t4
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––
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gil
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ula
ta(C
.A.
Ag
ard
h)
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ng
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00
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54
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ila
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na
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na
La
ng
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ren
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gil
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zsch
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Go
mp
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nem
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m(K
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om
ph
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ud
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ug
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La
ng
e-B
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alo
t4
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03
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.75
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mp
ho
nem
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um
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cke
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om
ph
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Eh
ren
be
rg1
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24
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ntz
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xy
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60
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ata
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itk
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ay
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ya
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ste
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ng
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icu
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ato
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iata
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rma
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icu
laci
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hre
nb
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40
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35
3.4
146 Hydrobiologia (2007) 589:141–154
123
Ta
ble
4co
nti
nu
ed
Fu
llN
am
eA
uth
or
nT
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PT
PT
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ng
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vic
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ard
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ren
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71
.3
Hydrobiologia (2007) 589:141–154 147
123
Ta
ble
4co
nti
nu
ed
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llN
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ren
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3–
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ryb
lio
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rica
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no
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nn
41
.43
61
.19
01
35
3.9
148 Hydrobiologia (2007) 589:141–154
123
were 20 new records in comparison to the list
of trophic index by van Dam et al. (1994).
Furthermore, 73% of the species indicate eutro-
phic or hypereutrophic conditions according van
Dam indicator values (van Dam, 1994). Hofmann
(1999) in her TI provided indicator values for
only 50 species in our data set.
Comparison of the TDIL index values
(2.5 ± 0.9) to two other well-known indices
(IPS and IBD; Coste in Cemagref, 1982; Lenoir
& Coste, 1996) showed that the IPS values varied
in the widest range (10.4 ± 4.4); the variability
range of the IBD was smaller (9.7 ± 3.5).
According to the TDIL, the ecological status of
4 lakes were in excellent, 25 in good, 21 in
medium, 21 in tolerable and 12 in bad. Each
tolerable or bad sampling site was shallow, saline
lake with naturally high TP content. The assessed
trophic status by the three indices are shown in
each sampling site on Fig. 2.
0.0
1.0
2.0
3.0
4.0
5.0
Ágas06
Akas06
Alcs06
Atka06
Bába06
BA
L148B
AL149
BA
L150B
AL151
BA
L152B
AL153
BA
L154B
AL155
BalB
D1
BalB
D5
BalB
É3
Bibi06
BO
D187
BO
R180
Bödd06
Büdö06
BüdP
06C
iba06C
SA
188C
sár06C
SE
156C
SI157
Cson06
EG
Y158
EG
Y183
FA
D159
Fegy06
Fehé06
FE
R160
FU
L397F
ülö06
HA
L161H
AM
189H
att06
sampling sites
ind
exva
lue
of
IPS
/4,I
BD
/4an
dT
DIL
IPS/4
IBD/4
TDIL
(a)
0.0
1.0
2.0
3.0
4.0
5.0
KA
R162
Kard06
KE
L163K
ele06K
EN
164K
isr06K
OL165
Kolo06
Kond06
KU
N166
Kurj06
LAZ
167Lázá06LIP
168M
áma06
NA
G169
Nyék06
OR
G398
Orgo06
OS
Z170
Pere06
PE
T171
PIR
172P
irt06S
árk06S
zap06S
zar06S
zarv06S
zelA06
SzelB
06S
zív06S
ZO
184T
IS173
TO
L174
Újla06
VE
L176V
EL177
VE
L178V
örö06Z
AB
179Z
abs06
sampling sites
inde
xva
lue
ofIP
S/4
,IB
D/4
and
TDIL
IPS/4
IBD/4
TDIL
BAD
TOLERABLE
MEDIUM
GOOD
EXCELLENT
BAD
TOLERABLE
MEDIUM
GOOD
EXCELLENT
(b)
Fig. 2 The values of IPS, TDI and TDIL in the different water classes
Hydrobiologia (2007) 589:141–154 149
123
Discussion
On a global scale, the eutrophication is the most
recognized kind of human impact in lakes
(Harper, 1992). Although human activities have
been threatening the lakes from point and diffuse
sources since a long time, consequences became
notorious only the last 100 years (Fritz, 1989).
Phosphorus accumulation typically occurs after
human pollution and only few cases report about
natural reasons (Hickman et al., 1990).
According to OECD (1982) system, all but one
lake included in this study belonged to the
eu-hypertrophic category although far not each
received pollutants of human origin. It is a good
indication that the OECD boundary levels are
not suitable for ecological status assessment of
the Hungarian lakes what agrees with observa-
tions (Kitner & Poulıckova, 2003) in lakes in the
Czech Republic.
The standardization of sampling method is
essential in biomonitoring. The most important
question is the type of the substratum and the
sampling time. In productive water bodies, espe-
cially in foodplain lakes (Kitner & Poulıckova,
2003) where stones – which offer abiotic surfaces
for algae – are absent. Regardless of lack of
stones, epiphytic samples should be collected
from the similar substrata to ensure the compa-
rability between water bodies (King et al., 2006).
The recommended type specific natural substra-
tum (Schaumburg et al., 2004), young reed
(Phragmites australis), the most suitable substra-
tum for the assessment of the lakes’ trophic status
(Poulıckova et al.; 2004), can be commonly found
in the littoral region of shallow lakes (Blanco
et al., 2004) and appropriate for monitoring
purposes (Acs et al., 2005). The need for using
young reed temporarily limits sampling to spring
(from April to the beginning of July) and also
excludes further complications coming from sea-
sonal and successional changes in the composition
epiphytic assemblages (Castenholz, 1960; Hof-
mann, 1994; Muller, 1994; King et al., 2006)
during the year. Sampling from young reed
represents the early successional phase respond-
ing the actual chemical parameters (Poulıckova
et al., 2004) and frequency of dead diatoms from
the previous seasons (Round, 1991) or diatom
cells from the phytoplankton can also be mini-
mized. For the above reasons, and also to average
variations of vertical distribution (Hoagland &
Peterson, 1990), 5–7 stem sections, 5–20 cm below
the water surface are preferred for sampling
(Buczko & Acs, 1996/1997; Acs et al., 2005) in
shallow lakes. In the case of sampling series the
samples shoud be taken within three weeks.
The methods of bioindication cannot replace
physical or chemical analyses, but they comple-
ment them (Kitner & Poulıckova, 2003). If so, real
trophic state can be better assessed by development
of an adaquate bioindicator method (suitable
index) than by the chemical analyses (Blanco et al.,
2004; Poulıckova et al., 2004) and it also harmo-
nizes with the recommendations of the EU WFD.
Instead of the non-unimodal and asymmetrical
response of the species to nutrients, symmetrical
response can be applied using WA method with a
single indicator value, when the aim is to develop
a regional index (Potapova et al., 2004). Using the
WA technique, a robust and accurate TP transfer
function was developed spanning from 0.01 to
5.72 mg l–1 TP. In our Hungarian sample set,
diatom assemblages occurred along wider TP
gradient than the range of other diatom-based
models (Anderson et al., 1993: 25–800 lg l–1; Hall
& Smoll, 1992: 5–28 lg l–1). In the TP model the
correlation was strong (r2 = 0.96, RMSE = 0.17)
using weighted averaging without tolerance
downweighting regression (WAtol) with inverse
deshrinking. Bennion (1994) found a weaker
correlation and similar error in her TP transfer
function (r2 = 0.79, RMSE = 0.16) for shallow,
eutrophic ponds in southeast England. The error
of the model cannot be considerably reduced as a
consequence of the complexity of eutrophic lakes,
particulary if they are shallow and highly produc-
tive (Bennion, 1994).
The TP model was suitable for calculating the
optima and tolerances of the species and estab-
lishing the indicator values of the species at
different TP levels. Indicator values of 127 species
provide the basis of the developed TDIL index.
These species are the most frequent ones in
Hungarian lakes.
Comparing the species list of the TDIL to that
of TDI Austria (Rott et al., 1999), 31 species were
absent in our material, mostly centric diatoms.
150 Hydrobiologia (2007) 589:141–154
123
The consequence of the absence of centric
diatoms indicating nutrient-rich conditions is that
the TDI Austria index can underestimate (opti-
mistic) the trophic status of lakes (Kitner &
Poulıckova, 2003). The TDI Austria developed
for rivers and was used all over Europe (Rott
et al., 2003). It proved to be applicable for
samples from reed stems with actual and average
TP for perialpine lakes, since character of these
lakes was similar to that of the alpine stream
ecosystems (Poulıckova et al.; 2004). Further-
more, 73% of the species in our material were
eutrophic or hypertrophic according to the van
Dam trophic index (van Dam et al., 1994) which
would predict unacceptably high trophic level
similarly to the OECD system. Although in Czech
fishponds the van Dam’s index was appropriate to
recognise extremes (clear and dirty) of lake
environments (Kitner & Poulıckova, 2003), for
the Hungarian lakes it was not suggested (van
Dam et al., 2005). The TI (Hofmann, 1999) was
well applicable in Germany (Schaumburg et al.,
2004) but it includes indicator value for only 50
species of the 127 most frequent diatom species in
the Hungarian shallow lakes. Therefore, the TI
would carry a considerable uncertainity if applied
to assess lake trophic status in Hungary.
Blanco et al. (2004) and Acs et al. (2005)
tested some existing diatom indices. Although
these studies gave satisfactory results, they were
limited by some factors: the analyses of the
Spanish study (Blanco et al., 2004) involved only
6 lake samples while the Hungarian one (Acs
et al., 2005) was restricted to only one single lake
with minor variations of the TP content.
The index values provided by different indices
may differ significantly because they apply differ-
ent indicator values for some, sometimes for
many, species. This is a fundamental problem,
which originates from several different sources:
(a) the published indicator values derive from
other kinds of ecosystem (for example lentic/
lotic) (b) extension of databases (number of the
samples) is different; (c) different taxonomic
approach (together with identification problems)
and (d) different phycogeographical regions.
These examples support the recommendation by
Poulıckova et al. (2004), that each region needs
own ecological calibration.
Water quality management and lake restora-
tion emphasized the necessity of development of
an adaquate diatom index to assess the ecological
status of lakes and there is strong suggestion by
the WFD to a 5 level ecological classification.
Accordingly, the absolute value (optima) of the
TP for the individual species were expressed on a
convenient scale, ranging from 0 to 5. According
to the TDIL, the ecological status of 4 lakes were
in excellent, 25 in good, 21 in medium, 21 in
tolerable and 12 in bad status, which appears
representative for the status of the Hungarian
lakes. Most of the sampling sites in bad or poor
status by the TDIL were shallow, saline lakes with
naturally high TP content and high conductivity.
In these cases further modifactions will be neces-
sary to assess the real ecological status (Stenger-
Kovacs et al., in prep.).
According to the recommendation on basis of
an extended study in Hungary (ECOSURV, van
Dam et al., 2005), a suitable index was necessary
to develop because the existing indices did not
perform satisfactorily in Hungarian freshwater
lakes. The TDIL developed in Hungary is appli-
cable for lake types, which are lowland, shallow
(z < 4 m), permanent or temporary with calcar-
eous or calcareous-saline hydrogeochemistry
(conductivity < 3000 lS cm–1), where the con-
centration and variation of nutrients are higher
than in other standing water types, therefore the
traditional classification cannot be applied. This
problem was recognized already in the Mediter-
ranean region (Blanco et al., 2004), which pro-
vides a good opportunity for testing further the
TDIL in other countries.
Acknowledgements We thank Ms. Ildiko Kiralykuti forher help careful technical assistance in chemical analysesand Ms. Kata Kovacs for her help in field samplings. Thisproject was supported by the Ministry of Environment andWater (ECOSURV) and by the National Foaaundationfor Research and Technology (NKFP 3B/022/2004).
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