Morpho-Functional Groups and phytoplankton development in two deep lakes (Lake Garda, Italy and Lake Stechlin, Germany)
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Hydrobiologia (2007) 578:97–112
DOI 10.1007/s10750-006-0437-0
P H Y T O P L A N K T O N W O RK S H O P
Morpho-Functional Groups and phytoplankton
development in two deep lakes (Lake Garda, Italy
and Lake Stechlin, Germany)
Nico Salmaso Æ Judit Padisák
Springer Science+Business Media B.V. 2007
Abstract Phylogenetic classifications of plants Lake Garda, southern Alps, zmax = 350 m; bien-
often do not reflect their ecological functions. In nium 2002–2003) and Lake Stechlin (north-east
fact, the functional mechanisms of biological com- Germany, zmax = 67 m; 1995, 1998 and 2001). In
munities may be better understood if species are both lakes, the temporal evolution of the phyto-
pooled into groups having similar characteristics. plankton communities within individual years fol-
The objective of this work is to evaluate, with the use lowed a regular annual cycle, with the exception of
of multivariate methods, classifications based on the Lake Stechlin in 1998, when an irregular phyto-
morphological and functional characteristics (size plankton pattern was caused by a sudden mass
and form, mobility, potential mixotrophy, nutrient appearance of Planktothrix rubescens in the spring
requirements, presence of gelatinous envelopes) of and summer months, resulting in a collapse of the
cyanobacteria and eukaryotic algae to explain the whole community in autumn. Overall, the temporal
seasonal dynamic of the phytoplankton community. developments of the phytoplankton communities
The analyses involve data from two deep lakes: obtained on the basis of patterns of the morpho-
functional groups appeared highly comparable
with those obtained, in the single years, on the
Guest editors: M. Albay, J. Padisák & L. Naselli-Flores basis of the original phytoplankton species matri-
Morphological plasticity of phytoplankton under different ces. The comparison of the morpho-functional
environmental constraints
groups of the lakes Garda and Stechlin showed
N. Salmaso (&) important differences in the abundance and sea-
Natural Resources Department, Limnology and Fish sonality of the dominant phytoplankton types.
Research Unit, IASMA Research Center, The results obtained in this study underline that
Via E. Mach, 1, I-38010
S. Michele a/Adige (Trento), Italy the use of classifications based on the adaptive
e-mail: nico.salmaso@iasma.it strategies of the single species may represent a
useful tool to investigate the community evolution
J. Padisák and to compare phytoplankton assemblages of
Department of Limnology, University of Veszprém,
Egyetem u. 10, Veszprem H-8200, Hungary different lakes, overcoming problems related to
e-mail: padisak@almos.vein.hu possible differences of taxonomic accuracy and
identification.
J. Padisák
Leibniz-Institut für Gewässerökologie und
Binnenfischerei, Alte Fischerhütte 2, D-16775 Keywords Phytoplankton Morpho-Functional
Stechlin-Neuglobsow, Germany groups Seasonal cycles Deep lakes
12398 Hydrobiologia (2007) 578:97–112
Introduction ciations, with each comprising species that coexist
and increase or decrease in numbers simulta-
The need to understand relationships between neously. The species of a particular association
structural and functional properties of the eco- share common ecological attributes so that they
systems has initiated a number of classifications of may potentially dominate or co-dominate. Suc-
aquatic biota on basis of their taxonomy or cessively, this approach was refined and expanded
functional and structural characteristics. Such (Reynolds, 1997; Padisák & Reynolds, 1998). At
classifications are of practical use for generalisa- present, the system comprises 31 associations
tions across species and represent necessary tools accomodated on the basis of expert judgement
for scientific communication and water-body and experience (Reynolds et al., 2002). Subse-
analysis (Körner, 1993). quent studies defined three further associations
The taxonomic classification of the living (Padisák et al., 2003a, 2006).
organisms recently has benefited from the use Reynolds (1988) defined another system of
of genetic and molecular techniques. However, classification based on the functional properties of
despite the support of these recent methods and the phytoplankton species. Adapting the C–R–S
the refinement of the phylogenetic classifications, concept formulated by Grime (1977) for the
ecologists have often been dissatisfied with the terrestrial plants, he classified the phytoplankton
taxonomic assemblages because they do not species into three groups based on their suscep-
always and necessarily reflect the perceived tibility to disturbance, stress and utilisation of
ecological functions (Solbrig, 1993). A taxo- limited resources. In this model, the C-strategists
nomic unit may be composed, especially at (competitive species) dominate in lakes with low
higher taxonomic levels (e.g., classes), by species intensity of disturbance and stress. The S-strate-
possessing very different structural and func- gists (stress-tolerant species) develop in situations
tional properties. Considering phytoplankton, we of low disturbance and high stress, whereas the R-
may refer to examples from Chlorophyceae strategists (‘‘ruderals’’) dominate at high distur-
which include types characterised by very differ- bance intensity and low stress.
ent structure and life strategies, ranging from The different groups defined in these classifi-
single picoplanktonic cells (Stockner & Antia, cations generally include species with common
1986) to long filaments and large multicellular features (Reynolds et al., 2002), indicating that
colonies. To overcome these problems, ecologists the algae belonging to a specific group have
have tried to group organisms with similar common morphological characteristics which are
structural and functional characteristics with the powerful predictors of optimum dynamic perfor-
aim to obtain a better understanding, and mance (Reynolds & Irish, 1997). In fact, the
possibly generalisation, of the functioning of different strategies of different phytoplankton
the ecosystems. The functional groups may be organisms are strongly related to differences in
defined utilising elements that bear a certain set geometrical dimensions and shapes. Morpholog-
of common structural and/or functional features. ical characteristics are essential features that
These include quality criteria (size/form, physi- influence sinking properties (Padisák et al.,
ological and life strategy characteristics), tempo- 2003b, d; Salmaso, 2003), growth rates (Sommer,
ral appearance and distributional characteristics, 1981; Tang, 1995), efficiency of nutrients and light
whereas, at the species level, the functional utilisation (Sommer, 1984; Tilzer, 1984), and
groups may include taxonomic units as well susceptibility to grazing (Lehman, 1988). These
(Körner, 1993). elements, together with the ability to regulate
One of the first formal attempts to define a buoyancy, the requirement for specific resources
system of classification based on the functional (e.g., silica) and the ability to obtain alternative
properties of the phytoplankton was proposed by carbon and nutrient sources, represent strong
Reynolds (1980, 1984). Utilising long series of selective factors that are able to select the best
phytoplankton observations from a group of lakes competitors under different environmental con-
in Northwest England, he distinguished 14 asso- straints (Weithoff, 2003).
123Hydrobiologia (2007) 578:97–112 99
In this work we evaluate, with the use of Materials and methods
multivariate methods, classifications based on the
morphological and functional characteristics of Methods in the field and laboratory
cyanobacteria and eukaryotic algae to capture
much of the seasonal phytoplankton variations in In Lake Garda, samples were collected every
two deep lakes located at the southern border of 4 weeks between January 2002 and December
the Alps (Lake Garda) and in north-east Ger- 2003 at the deepest zone of the lake (out of
many (Lake Stechlin). Brenzone; zmax = 350 m); sampling was not car-
ried out in January 2003. The average values of
the chemical variables and phytoplankton abun-
Study sites dance in the upper 20 m were estimated from
samples collected at the integrated depths of 0–
Detailed hydrological, morphological as well as 2 m, 9.5–11.5 m and 19–21 m. Phytoplankton
limnological descriptions of these large and deep samples were fixed with acetic Lugol’s solution
water bodies can be found in Salmaso (2003, and counting was performed with inverted micro-
2005) and Koschel & Adams (2003). scopes following the criteria reported by Lund et
Concentrations of total phosphorus (TP) in the al. (1958). Biovolumes were calculated from
euphotic layer (0–20 m) of Lake Garda show recorded abundances and specific biovolumes
typical seasonal fluctuations from around 5 lg l–1 approximated to simple geometric solids (Rott,
(summer) to 20 lg l–1 (spring overturn); corre- 1981). Zooplankton was collected by vertical tows
sponding fluctuations of Soluble Reactive Phos- from 0 to 50 m using nets with mesh size of 80 lm
phorus (SRP) range from below detection limit (Salmaso & Naselli-Flores, 1999). Zooplankton
up to 10 lg l–1 (Salmaso, 2005). During summer, biomass was computed according to de Bernardi
the nitrate concentrations in the productive layers & Canale (1995). Euphotic depths (zeu) were
may decrease to very low levels (down to estimated from direct measurements made with a
100 lg l–1). NH4–N concentrations are generally radiometer LiCor, model Li-192SA. A detailed
below 20 lg l–1. Thermal stratification begins in description of the analytical methods used in the
May (10–12C at the surface), and strong thermal laboratory was reported by Salmaso (2002, 2005).
stratification persists from June to September The phytoplankton patterns selected for this
(20–25C). Winter euphotic depths (zeu) are study from Lake Stechlin include 3 years: 1995,
around 25–40 m, whereas, during summer, the 1998 and 2001. Phytoplankton abundances were
lower limit of zeu is between 15 and 20 m estimated from pooled samples collected from six
(Salmaso, 2003). depths evenly distributed within the 0–25 m layer.
The annual average TP concentrations in Lake Sampling frequency was weekly between March
Stechlin vary between 12 and 21 lg l–1. SRP in and October, and biweekly throughout the rest of
the euphotic layer is below the limit of detection the year. The statistical analyses were carried out
(1–2.5 lg l–1) with maximum values (4–5 lg l–1) using monthly averages of the phytoplankton
after the autumnal overturn. Dissolved inorganic biovolumes. Phytoplankton samples were treated,
nitrogen (DIN: NOx–N + NH4–N) in the eupho- counted, and biomass was estimated as described
tic zone is rather low, varying from the detection for Lake Garda. To make the data comparable to
limit to around 100 lg l–1 (with occasional peaks those from Lake Garda, picophytoplankton was
up to 150 lg l–1). The DIN/SRP ratios in the removed from the data-set. Samples for chemical
euphotic zone vary between 2 and 159 (average: analyses were collected from 0 to 25 m and
30). Low values occur typically in the period July– analysed according to the OECD standards and
October. Thermal stratification begins in May standards of Deutsche Einheitsverfahren. Crusta-
(10–12C at the surface) and begins to be strongly cean zooplankton was collected by vertical tows
pronounced in July, lasting to middle September from 0 to 22 m using nets with mesh size of
(20–25C). Euphotic depth during the stratified 90 lm. Biomass of the single individuals was
period extends to the upper 25 m. estimated following Bottrell et al. (1976) and
123100 Hydrobiologia (2007) 578:97–112
Kasprzak (1984). Euphotic depths were estimated light and nutrient conditions in heterogeneous
from zs, the Secchi disk depths (zeu = zs · 2.7). environments (Reynolds, 1997). Within flagel-
Detailed description of the analytical methods lates, the second division separates the large
was reported by Padisák et al. (2003c). The group of the Phytomonadina from the other
chemical and trophic characteristics of the two (large and small) flagellates; this division corre-
lakes during the examined periods are summar- sponds roughly to the separation of the potential
ised in Table 1. mixotrophs from mostly autotrophic algae (Isaks-
In both lakes, relative thermal resistance son, 1998; Jones, 2000), though, at present, no
(RTR) was computed by the density difference complete information exists about the importance
in the examined strata (0–20 m, Garda and 0– of mixotrophy for the single species. As for the
25 m, Stechlin) compared to the density differ- other non-flagellated organisms, a further division
ence between 4 and 5C (Kalff, 2002); water separates the cyanobacteria and diatoms from the
densities were estimated from temperature val- remaining groups. Cyanobacteria are prokaryotes
ues. and exhibit defined morphological and physiolog-
ical differences compared with the eukaryotic
Identification of the Morpho-Functional phytoplankton. Among these, the ability to reg-
groups ulate the vertical position through the formation
of gas-vescicles (aerotopes) and the ability to fix
The list of the Morpho-Functional Groups atmospheric nitrogen constitute a set of unique
(MFG) is reported in Table 2. The criteria features (Whitton & Potts, 2000). Similarly, the
adopted to discriminate the groups include motil- siliceous walls of the diatoms distinguishes these
ity, the potential capacity to obtain carbon and organisms from other taxa and causes severe
nutrients by mixotrophy, specific nutrient require- survival problems in stratifyed pelagic environ-
ments, size and shape, and presence of gelatinous ments due to the enhanced susceptibility to
envelopes (Weithoff, 2003). These criteria, along sinking losses of the heavier cells (Padisák et al.,
with the separation of the Cyanobacteria from the 2003d). Further subdivisions (3rd column of
other algae and a further subdivision based Table 2) were based on size and shape. In this
considering different life strategies, resulted in work, the separation of the large and small taxa
differentiation of 31 groups. has been based on the susceptibility to grazing.
The first division is based on the presence or However, a clear-cut delimitation of the graze-
absence of flagella. Despite their small size, many able fraction for the entire phytoplankton com-
flagellates can move vertically within the water munity is not possible. On practical grounds,
column for tens of centimeters to several meters single cells and small colonies with linear dimen-
daily (Wetzel, 2001). Motility offers the ability to sionsHydrobiologia (2007) 578:97–112 101
Table 2 Morpho Functional groups (MFG; see explanation in the text)
Flagellates Potential 1 Large (colonial or 1a Large Chrysophytes/Haptophytes 1a-
mixotrophs unicellular) LargeChry
1b Large Dinophytes 1b-
LargeDino
1c Large Euglenophytes 1c-LargeEugl
2 Small (unicellular) 2a Small Chrysophytes/Haptophytes 2a-
SmallChry1
2b Small Dinophytes 2b-SmallDino
2c Small Euglenophytes 2c-SmallEugl
2d Cryptophytes 2d-Crypto
Mostly 3 Phytomonadina 3a Unicellular Phytomonadina 3a-UnicPhyto
autotrophs 3b Colonial Phytomonadina 3b-ColoPhyto
Without Cyanobacteria 4 Unicellular 4 Unicellular cyanobacteria 4-UnicCyano
flagella 5 Colonies 5a Thin filaments (Oscillatoriales) 5a-FilaCyano
5b Large vacuolated Chroococcales 5b-
LargeVacC
5c Other large colonies, mostly non-vacuolated 5c-
Chroococcales OtherChroo
5d Small colonies, Chroococcales 5d-
SmallChroo
5e Nostocales 5e-Nostocales
Diatoms 6 Large 6a Large Centrics 6a-LargeCent
6b Large Pennates 6b-LargePenn
7 Small 7a Small Centrics 7a-SmallCent
7b Small Pennates 7b-SmallPenn
Others— 8 Large 8a Large unicells—Unicellular 8a-
Unicellular Conjugatophytes/Chlorophytes LargeCoCh
8b Large unicells—Other groups 8b-LargeUnic
9 Small 9a Small unicells—Conjugatophytes 9a-SmallConj
9b Small unicells—Chlorococcales 9b-SmallChlor
9c Small Chrysophytes 9c-
SmallChry2
9d Small unicells—Other groups 9d-SmallUnic
Others— 10 Filaments 10a Filaments—Chlorophytes 10a-
Colonial FilaChlorp
10b Filaments—Conjugatophytes 10b-FilaConj
10c Filaments—Xanthophytes 10c-FilaXant
11 Non filament. 11a Chlorococcales—Naked colonies 11a-
colonies NakeChlor
11b Chlorococcales—Gelatinous colonies 11b-
GelaChlor
11c Other colonies 11c-OtherCol
Besides grazing, size and shape are important for in the dynamic evolution of different taxonomic
influencing losses from suspension (Padisák et al., groups sharing common morphological features.
2003b). The final list of MFG in Table 2 inte-
grates other two discriminant elements, i.e. the Data analysis
presence of large gelatinous envelopes, with the
separation of the naked and gelatinous Chloro- Phytoplankton matrices (taxa · sampling dates)
coccales, and taxonomy. As for this last point, the were analysed considering the original data (the
subdivisions were carried out considering the biomass of the single species) and two synthetic
existence of different life strategies; in turn, this matrices obtained by considering the Morpho
gives the opportunity to identify real differences Functional Groups and the phylogenetic algal
123102 Hydrobiologia (2007) 578:97–112 classes. The three matrices were ordinated sepa- using the program CANOCO 4.5 with focus on rately, for every lake and year, by applying Non interspecies distances and biplot scaling (ter Metric Multidimensional Scaling (NMDS). The Braak & Šmilauer, 2002). Before the computa- ordinations were applied to Bray & Curtis’ tion, the biovolumes of the single MFG were log- dissimilarity matrices (Podani, 2000). Before transformed to reduce the weight of the most computation, the data were transformed by dou- abundant groups. The significance of the axes ble square root to reduce the weight of the more obtained by the CCA analysis was tested by abundant taxa/groups (Salmaso, 1996). The re- means of Monte Carlo permutations (ter Braak & sults of the ordinations obtained from the MFG Šmilauer, 2002). and the algal classes were compared with those obtained utilising the phytoplankton data. As in NMDS the orientation of the axes is arbitrary, Results before the comparison the configurations ob- tained from the MFG and the classes were Dominant classes and phytoplankton rotated and transposed by orthogonal Procrustes rotation to maximise their fit with the corre- The temporal development of the algal classes in sponding phytoplankton ordinations (Podani, the lakes Garda and Stechlin is reported in Fig. 1. 2000). Axes I and II from the phytoplankton, The dominant classes in Lake Garda were the MFG and classes ordinations were compared by cyanobacteria, diatoms and chlorophytes. These parametric and non-parametric correlations. three classes were dominated by Planktothrix The comparison of the phytoplankton commu- rubescens, Fragilaria crotonensis and Mougeotia nities of the lakes Garda and Stechlin was carried sp., respectively. The cyanobacteria showed their out considering the differences in the structure of maximum development in summer and/or au- their respective MFG. The common matrix, tumn (Fig. 1a). Besides Planktothrix, other including the biovolumes of the MFG of the two important cyanobacteria were large colonies of lakes, was analysed by Principal Components Aphanothece/Aphanocapsa. Also, in the 2 years Analysis calculated from the correlation matrix, studied Anabena lemmermannii developed epi- followed by orthogonal rotation (varimax meth- sodic oligotrophic blooms (sensu Salmaso, 2000) od). Before computation, the data were log- strictly localised to the upper few centimetres of transformed, Yi = log(Xi + 1), to reduce the the water column and with low overall biovo- weight of the most abundant taxa. The ordination lumes (
Hydrobiologia (2007) 578:97–112 103
spp. In the successive year, despite the lack of a teria were between 8 and 23 mm3 m–3 in all
discernible spring peak, the diatoms developed 3 years. Apart from the cryptophytes (developing
seasonally with the same pool of species. The irregularly with Cryptomonas erosa/ovata, Rho-
chlorophytes showed a comparable development domonas lens and R. minuta), the remaining
in the 2 years studied, with a small spring classes developed substantial biovolumes and
increase, followed by large early and mid-summer showed repetitive patterns in the three studied
growth. Though with low biovolumes, besides years. Chlorophytes were mainly present from
Mougeotia other chlorophytes showed a notice- early spring to early autumn; the most abundant
able development from early summer to late were Neocystis policocca, Pseudosphaerocystis
summer/early autumn (Ankyra judayi, Coela- lacustris and Scenedesmus costato-granulatus.
strum spp., other coccal greens and Chlorococ- The contribution of dinophytes was mainly due
cales). The remaining classes developed lower to Ceratium hirundinella and Gymnodinium hel-
biovolumes. The xanthophytes (Tribonema sp.) veticum. In the 3 years considered here, the
showed their maximum development from April biovolume of the chrysophytes and haptophytes
to the end of June, whereas the chrysophytes was mainly provided by Chrysochromulina parva,
mainly occurred in late spring (Dinobryon diver- Dinobryon sociale and Ochromonas sp. Xantho-
gens, D. sociale and Ochromonadaceae). The phyceae and Euglenophyceae showed low occur-
dinophytes showed a greater biovolume peak rences and low biovolumes.
from late summer to early autumn (Ceratium
hirundinella); Gymnodinium helveticum was Phytoplankton ordinations—single lakes
detectable also during the spring months. The
cryptophytes (mainly Plagioselmis nannoplanctica The configurations of the phytoplankton samples
and Rhodomonas minuta) showed a more irreg- of Lake Garda obtained by mean of NMDS are
ular distribution over the 2 years. reported in Fig. 2. For the 2 years considered,
The temporal development of the phytoplank- the configurations obtained utilising the phyto-
ton in Lake Stechlin showed a different pattern plankton classes and the MFG were superim-
(Fig. 1b). The two more abundant classes in the posed to the corresponding configurations
examined period were the diatoms and the obtained utilising the phytoplankton species.
cyanobacteria. However, the diatoms peaked high The stress values (Kruskal & Wish, 1978) of
in 1995 and 2001, whereas the cyanobacteria, the six NMDS configurations ranged between
largely Planktothrix rubescens, showed a conspic- 0.05 and 0.13. The configurations obtained with
uous development exclusively in 1998, from the phytoplankton species showed an ordered
January to September; in October Planktothrix and cyclic development. In 2002, the annual
underwent a complete breakdown and the com- development based on the phytoplankton classes
munity was composed exclusively of a few followed a different pattern compared with the
diatoms and chlorophytes. The spring peaks of ordination based on the phytoplankton samples;
the diatoms in 1995 and 2001 were due to the differences were marked along the first axis,
different species, namely Cyclotella spp., and whereas the ordination of the samples along the
Aulacoseira islandica with a minor contribution second axis showed a comparable ranking
of Cyclotella spp., respectively. Moreover, the between the two configurations (Fig. 2a; Ta-
annual development of the diatoms in 2001 was ble 3). Though less evident, the differences
also characterised by Asterionella formosa in between the two ordinations were detected also
spring and Fragilaria crotonensis in early autumn. in 2003, but with the major discrepancies being
Excluding Planktothrix, the contribution of the present along the second axis (Fig. 2b; Table 3).
other cyanobacteria was always very low. Anaba- In contrast, the ordinations obtained on the basis
ena lemmermannii was detected with low abun- of the Morpho-Functional Groups (MFG)
dances (annual peaks of ca. 20–100 mm3 m–3) matched those achieved from the complete
between June/July and August/October. The phytoplankton matrices very closely (Fig. 2c, d;
annual biovolume peaks of the other cyanobac- Table 3).
123104 Hydrobiologia (2007) 578:97–112
Fig. 2 Lake Garda. Phytoplankton species
Ordination of Classes
phytoplankton samples in 5
the two-dimensional Non 1 7 1
Metric Multidimensional
Scaling configurations; the 4 6 7
5
NMDS Axis 2
arabic numbers indicate 7
9
the month of sampling. 0 3 9 4
a, c: 2002; b, d: 2003 10 6
1 0 10
2 8
8 1 11
-1 12 11 3
(a) (b) 2 12
-1
-1 0 1 -2 -1 0 1
Phytoplankton species
MFG
1 1
NMDS Axis 2
0
0
-1
(c) (d)
-1
-1 0 1 -2 -1 0 1
NMDS Axis 1 NMDS Axis 1
The NMDS ordinations of the Lake Stechlin distribution of the data) showed a better agree-
samples are reported in Fig. 3. In 1995 and 2001, ment between the phytoplankton species and
the temporal succession of the samples based on MFG configurations.
the phytoplankton data followed a clear cyclic
pattern (Fig. 3a, c; black circles), whereas in 1998 Phytoplankton ordinations—joint analysis
the seasonal evolution was strongly typified by
the separation of the October sample from the The results of the ordination of the samples of the
remaining ones (Fig. 3b). This sample, as dis- lakes Garda and Stechlin by PCA are reported in
cussed above, was characterised by a sudden Fig. 4 and Table 4. The analysis does not include
collapse of Planktothrix rubescens and other the data recorded in Lake Stechlin in 1998, in
dominant seasonal phytoplankton species. As in order to simplify the interpretation of the ordi-
the case of the Lake Garda, in 1995 and 2001 the nation diagram. A two factor solution explaining
ordinations of the MFG agreed more closely with 40% of the total variance was computed. (Ta-
those for the phytoplankton species as did those ble 4). In addition to the significant proportion of
based on the algal classes; however, the algal the explained variance, this solution was chosen
classes performed better than for the Lake Garda because it yielded the most straightforward inter-
samples, as evidenced by the high significance of pretation without loss of significant information.
the relationships between the couples of axes The relative position of the single samples in
(Table 3). As for the 1998 configurations, in Fig. 4 was confirmed by the application of the
which the parametric correlations were strongly NMDS ordination (figure not shown); after
determined by the October sample, the Spearman orthogonal Procrustes rotation of the NMDS
correlations (which are independent from the configuration, the first and second axis of the
123Hydrobiologia (2007) 578:97–112 105
Table 3 Correlation coefficients between the first two species (Phyto) and the corresponding NMDS axes
axes of the Non Metric Multidimensional Scaling (NMDS) obtained with the algal classes and Morpho-Functional
configurations obtained on the basis of the phytoplankton Groups
A B
Lake Garda Axes classes Axes MFG Axes classes Axes MFG
2002 Axis 1 Phyto 0.35 0.99 0.48 0.99
Axis 2 Phyto 0.96 0.99 0.97 0.99
2003 Axis 1 Phyto 0.87 0.99 0.81 0.99
Axis 2 Phyto 0.41 0.87 0.30 0.83
C D
Lake Stechlin Axes classes Axes MFG Axes classes Axes MFG
1995 Axis 1 Phyto 0.83 0.98 0.67 0.97
Axis 2 Phyto 0.90 0.95 0.90 0.94
1998 Axis 1 Phyto 0.98 0.99 0.55 0.64
Axis 2 Phyto 0.77 0.90 0.50 0.80
2001 Axis 1 Phyto 0.93 0.97 0.92 0.94
Axis 2 Phyto 0.80 0.87 0.82 0.85
For example, in the first column, the entries 0.35 and 0.96 refer to the correlations between Axis 1 Phyo and Axis 1 Classes,
and Axis 2 Phyo and Axis 2 Classes, respectively. A,C: Pearson correlations; B,D: Spearman correlations. The significant
correlations are reported in bold (P < 0.01) and italics (P < 0.05)
Phytoplankton species
1 1
5 6 Classes
4 4-9 1 6
3 4
3 7 10 7
8 5
NMDS Axis 2
NMDS Axis 2
NMDS Axis 2
0 0 2
3 0
2 1
9 2 8
1 1 10
12 9
12 11
10 11 -1
-1 11 -1
(a) (b) 12 (c)
-2
-1 0 1 2 -1 0 1 2 3 -2 -1 0 1
Phytoplankton species
1 1
MFG
1
NMDS Axis 2
0 0 0
-1
-1 -1
(d) (e) (f)
-2
-1 0 1 2 -1 0 1 2 3 -2 -1 0 1
NMDS Axis 1 NMDS Axis 1 NMDS Axis 1
Fig. 3 Lake Stechlin. Ordination of phytoplankton samples in the two-dimensional Non Metric Multidimensional Scaling
configurations; the arabic numbers indicate the month of sampling. a, d: 1995; b, e: 1998; c, f: 2001
PCA ordination showed a strong and significant to Lake Stechlin (right panel). In both cases, the
(P < 0.01) correlation with the corresponding annual development of the samples followed a
NMDS axes (r = 0.93 and r = 0.88, respectively). cyclical pattern, although less evident compared
Two main differences became apparent in the to those reported in the analyses of the single
spatial arrangement of the samples of the two years (Figs. 2, 3). The cyclical patterns of the two
lakes (Fig. 4). The samples formed two distinct lakes followed a common direction only along the
groups belonging to Lake Garda (left panels) and second axis, and an opposite direction along the
123106 Hydrobiologia (2007) 578:97–112
Table 4 Principal components analysis with varimax 3 Garda 2002
rotation: percentage of explained variance and correla- Garda 2003
tions between the first two factors and the input variables Stechlin 1995
2 Stechlin 2001
PCA Axis I II
Variance explained 23.2% 16.7% 1
9d—SmallUnic 0.84 –0.11
Axis 2
7b—SmallPenn 0.76 –0.10
2b—SmallDino 0.74 0.27 0
2a—SmallChry1 0.63 0.32
10a—FilaChlorp 0.56 0.13
7a—SmallCent 0.52 0.25 -1
11a—NakeChlor 0.48 0.57
5a—FilaCyano –0.84 –0.07
10b—FilaConj –0.74 –0.14 -2
3a—UnicPhyto –0.71 0.22 -2 -1 0 1 2
8a—LargeCoCh –0.61 0.11 Axis 1
10c—FilaXant –0.60 –0.10
6b—LargePenn –0.49 –0.12 Fig. 4 Ordination of the samples by principal components
5e—Nostocales –0.09 0.86 analysis with varimax rotation. The arrows indicate the
5c—OtherChroo –0.07 0.66 direction of the temporal sequences. Succession of the
1b—LargeDino –0.27 0.61 months as in Figs. 2 and 3
11c—OtherCol 0.22 0.60
9c—SmallChry2 0.36 0.59
11b—GelaChlor 0.34 0.56 Garda stood out for the presence of large func-
9a—SmallConj 0.14 0.54
tional units, both filamentous or unicellular. The
1a—LargeChry –0.09 0.52
3b—ColoPhyto –0.06 0.48 second axis showed a strong and positive corre-
6a—LargeCent 0.19 –0.58 lation with 11 MFG; these groups assumed a
9b—SmallChlor –0.36 0.25 progressive and greater importance from the
5b—LargeVacC –0.30 0.15
winter to the summer samples. In contrast, the
2c—SmallEugl 0.06 0.31
5d—SmallChroo 0.09 0.24 large centric chain-forming diatoms showed a
2d—Crypto 0.24 –0.23 negative correlation with the second axis (Ta-
The significant correlations are reported in bold (P < 0.01)
ble 4). This second set of MFG included phyto-
and italics (P < 0.05). Variables are abbreviated as in plankton types with more comparable temporal
Table 2. Underlining of Morpho-Functional Groups patterns in the two lakes.
indicates high abundance (see text) The more abundant MFG in Table 4 are
underlined. These groups reached biovolume
first axis. This shows that the spring and summer peaks greater or equal than 100 mm3 m–3 at least
samples were characterised by the greater differ- in one lake and in 1 year. With this criterion it
ences, with a major comparability of the phyto- was possible to discriminate the eleven groups
plankton features during the autumn and early represented in Fig. 5. Among the ‘‘discriminat-
winter months. ing’’ MFG, the small centric diatoms showed a
The analysis of the factor loadings (Table 4) different seasonal development in the two lakes,
allowed to interpret in terms of MFG composi- whereas the filamentous cyanobacteria, conju-
tion the different patterns observed in the two gatophytes and xanthophytes, and the large pen-
lakes. The first axis showed a strong correlation nate diatoms were typically present in the
with thirteen MFG; among these, only the naked plankton of Lake Garda. However, as for the
Chlorococcales showed a positive correlation also filamentous cyanobacteria, it is important to
with the second axis. This first set of MFG emphasise that this analysis does not include the
constituted the discriminant phytoplankton types contribution of the 1998 data for Lake Stechlin,
in the two lakes. In particular, the MFG typical of which is characterised by a huge development of
the Lake Stechlin were represented by small and Planktothrix rubescens. The remaining groups in
mostly unicellular species, whereas the Lake Fig. 5 are represented by ‘‘common’’ MFG;
123Hydrobiologia (2007) 578:97–112 107
300 600
7a-SmallCent 5a-FilaCyano 3000 10b-FilaConj
-3
200 400
mm m
2000
3
100 200 1000
0 0 0
400
10c-FilaXant 1500 6b-LargePenn 100 5c-OtherChroo
300
-3
mm m
1000 75
200
3
50
100 500
25
0 0 0
300 1b-LargeDino 400 11b-GelaChlor 1a-LargeChry
300
-3
mm m
200 300 200
3
100 50 100
0 0 0
J F MA MJ J A SOND
1200 6a-LargeCent 250 2d-Crypto
200 Garda 2002
1000
-3
mm m
150 Garda 2003
800
3
150 100 Stechlin 1995
100 50 Stechlin 2005
50
0
J F MA MJ J A S ON D J F MA MJ J A SOND
Fig. 5 Seasonal development of the dominant MFG (abbreviations as in Table 2) in the lakes Garda and Stechlin
among these, some differences were observed in to 0.19 and 0.08, which contributed a percentage
the gelatinous chlorococcales, which showed a of explained variance of 28.5% and 11.2%,
more ample temporal development in Lake respectively. The application of the Montecarlo
Stechlin (spring–early autumn) compared with tests to evaluate the significance of the extracted
Lake Garda (summer–early autumn). axes yielded highly significant results for the
whole set of axes and for the first axis
MFG and environmental variables (P < 0.01). Excluding RTR (linked with the
second axis) and, partly, SRP, the first axis was
Figure 6 reports the simultaneous ordination of strongly linked to the whole set of variables. The
the samples and MFG of the lakes Garda (Fig. 6a, first axis distinguishes the late winter and spring
b) and Stechlin (Fig. 6c, d) in relation to the samples from the summer and early autumn
principal environmental variables and zooplank- samples; the second axis contributes to separate
ton biomass obtained by the application of the late spring and summer samples from the late
Canonical Correspondence Analysis. As in the autumn ones (Fig. 6a). During the annual cycle,
case of PCA, the CCA analysis applied to Lake from winter to late summer the samples were
Stechlin does not include the data recorded in characterised by a progressive decrease in the
1998. Moreover, the group 2c (small eugleno- nutrient and light availability, and by a progres-
phytes) was excluded, because it was present only sive increase of thermal stability and grazing
in two occasions and with very low biovolumes pressure. Figure 6b shows a contraposition be-
(108 Hydrobiologia (2007) 578:97–112
1.0
1.0
6
RTR RTR
7 7
10c-FilaXant 1a-LargeChry
6
5 8 Temp. Temp.
11 7 5d-SmallChroo
12 2a-SmallChry1 11b-GelaChlor
5b-LargeVacC
5 10b-FilaConj 9b-SmallChlor
10 5e-Nostocales
4 1 Biom. Copepoda 8a-LargeCoCh 3b-ColoPhyto
0.0
0.0
Biom. Copepoda
DIN 3 7 DIN 6b-LargePenn
11 9 8 Reactive-Si 1b-LargeDino 5c-OtherChroo
Reactive-Si Zeu
Biom. Cladocera Zeu Biom. Cladocera
4
6a-LargeCent 2b-SmallDino 11a-NakeChlor
2
SRP 2 10 9 SRP
3
(b)
-1.0
(a)
-1.0
12
-1.0 0.0 1.0 -1.0 0.0 1.0
1.0
1.0
7
5 8
4 1a-LargeChry
Biom. Copepoda Biom. Copepoda
4 RTR 9d-SmallUnic RTR
3 9c-SmallChry2
SRP 7b-SmallPenn 5d-SmallChroo
Temp. 8a-LargeCoCh Temp.
SRP 11b-GelaChlor 3a-UnicPhyto
DIN 3 6
7 DIN
0.0
0.0
6b-LargePenn
1 Biom. Cladocera 6a-LargeCent 7a-SmallCent Biom. Cladocera
12 6 5e-Nostocales
2 1 9 9 1b- LargeChry
2d-Crypto 10b-FilaConj
Reactive-Si 10 9b-SmallChlor
5 Reactive-Si
2 8 Zeu 5c-OtherChroo 11c-OtherCol
Zeu
11 5a-FilaCyano 9a-SmallConj
11
3b-ColoPhyto
12
-1.0
-1.0
(c) 10 (d)
-1.0 0.0 1.0 -1.0 0.0 1.0
Fig. 6 Ordination of samples (left panels) and Morpho- indicate the month of sampling. The four MFG without
Functional Groups (right panels) of (a, b) Lake Garda and labels around the origin in (b) are: 3a-UnicPhyto, 5a-
(c, d) Lake Stechlin in the CCA plane defined by the first FilaCyano, 7a-SmallCent and 2d-Cryp. The four MFG
two axes. Samples refer to (a) 2002 and 2003 (shaded and around the origin in (d) are: 2a-SmallChry1, 2b-SmallDi-
empty circles, respectively), and (c) 1995 and 2001 (shaded no, 10a-FilaChlorp and 11a-NakeChlor. MFG are abbre-
and empty circles). The arabic numbers in (a) and (c) viated as in Table 2
As for Lake Stechlin (Figure 6c, d), the eigen- (which were associated more with the second
values associated to the first two axes were equal axis), the other variables showed a closer link
to 0.16 and 0.03, which contributes a percentage with the first axis. An important difference in the
of explained variance of 33.7% and 7.0%, respec- ordination of the MFG of the two lakes is
tively. The Montecarlo tests to evaluate the represented by the position of the filamentous
significance of the extracted axes yielded highly conjugatophytes (10b) in the two ordination
significant results for the whole set of axes and for diagrams (Fig. 6b, d); however, in the Lake
the first axis (P < 0.01). With a few differences, Stechlin this group was always identified with
the ordination of the samples (Fig. 6c) showed a very low quantities and only in one occasion with
pattern comparable with the results obtained for moderate biovolumes (June 2001;Hydrobiologia (2007) 578:97–112 109
location of the common MFG (i.e. the groups if they increased or decreased in abundance at the
both present in Fig. 6b, d) along the first axes of same time and at the same place. With the
the two configurations followed a similar ranking, deductive approach (see Gitay et al., 1999),
with Pearson and Spearman correlations between functional classifications are derived from state-
the two set of coordinates equal to 0.57 (P = 0.01) ments established a priori on the basis of the
and 0.54 (P < 0.05), respectively. importance of specific processes (e.g., physiology)
or properties (e.g., morphology). The C–R–S
classification of phytoplankton based on morpho-
Discussion logical descriptors of the specific taxa proposed
by Reynolds (1988: p. 396: Fig. 10-2) conforms to
Functional groups were used in different fields of this procedure. Moreover, successive refinements
ecological research, including vegetation studies of the classifications based on the recognition of
(e.g. Leishman & Westoby, 1992; Pillar, 1999), associations (Reynolds et al., 2002) integrate
prediction of effects of global climate change some of the elements of the deductive approach.
(Gitay et al., 1999), conservation biology (Gitay Recognising that the separation of the phyto-
et al., 1999; Pressey et al., 1993), studies of plankton species on the basis of their morpho-
microorganisms (Meyer, 1993), fungi (Oberwin- logies coincides with the distributions of the same
kler, 1993), macrophytes (Shipley et al., 1989) and species in different habitats with different light
macroinvertebrates (Usseglio-Polatera et al., and nutrient resources, these authors proposed to
2000). Irrespective of the type of organisms employ the morphological properties to fit hith-
studied, a common goal was to find classifications erto functionally unclassified taxa into existing
useful to define and understand the dynamic functional categories. The results presented here
behaviour of groups of species in relation to appear to support Reynolds’ approach (see also
environmental variation. This approach assumes below). The different sets of characters may also
that the characteristics of a community can be be processed with multivariate techniques to
better understood and managed if species are group species with similar properties in clusters
grouped into classes that possess similar charac- (‘‘data-driven approach’’; Gitay et al., 1999).
teristics or behave similarly (Solbrig, 1993). In the work presented here, the deductive
However, these general statements, though sim- approach has been used to identify the morpho-
ple to understand and accept on an intuitive basis, functional groups on the basis of predetermined
prove quite difficult in their practical implemen- relevant traits that influence essential functional
tation. In fact, the structural and functional processes and ecological characteristics of the
classifications does not produce exclusive and phytoplankton organisms. These traits have been
ultimate solutions because the species may be chosen considering their relevance as proxies for
grouped utilising different criteria. population performances and their facility of
In the context of phytoplankton ecology, it is measurement or definition, discarding other char-
convenient and simple to distinguish two ap- acters more difficult to determine or extract from
proaches to obtain functional classifications: literature (e.g., growth rates; see Weithoff, 2003).
dynamic and deductive. The most straightforward Some final subdivisions, based on taxonomy and
method of establishing functional groups is based different life strategies, reflect the actual spectra
on the temporal development of the species: of algae present in the lakes Garda and Stechlin,
identifying groups that show similar dynamic so that it could not be exhaustive for lakes with
behaviour; this method is based on the implicit different characteristics; this would require some
notion of groups of species responding similarly minor integrations and arrangement of the final
to a set of particular environmental conditions groups for other specific studies.
(e.g., Fabbro & Duivenvoorden, 2000; Salmaso, The analyses carried out on the lakes Garda
2003). The phytoplankton associations originally and Stechlin demonstrate a correspondence
defined by Reynolds (1980, 1984) are essentially between the seasonal development of the com-
based on this approach. Species were put together munities based on the MFG and phytoplankton
123110 Hydrobiologia (2007) 578:97–112
species. This suggests that the differentiation are needed to substantiate the reliability of this
among phytoplankton on the basis of specific approach.
adaptations, requirements and morphological In both lakes, the temporal development of
characters determines the formation of groups phytoplankton within individual years followed a
of species sharing more or less similar ecological regular annual cycle, with the exception of Lake
characteristics. This might be, in part, confirmed Stechlin in 1998, due to a sudden mass appearance
by the temporal dynamic of the MFG, which is of Planktothrix rubescens in the spring and sum-
characterised by delimited temporal develop- mer months. Reasons for development to Plank-
ments. However, these aspects will require tothrix dominance have not been clear since water
further in-depth studies regarding specifically chemical variables did not indicate any conspicu-
the degree of comparability of the ecological ous foregoing change; the only unusual event prior
requirements of single species belonging to the dominance of this species was the long lasting
the same MFG in different phytoplankton ice in the winter of 1995/1996 (Padisák, 2003a).
communities. Excluding the 1998 case documented in Lake
The CCA analysis showed that some groups— Stechlin, the regular cycles observed in the other
such as the cyanobacteria (with the exclusion of years in the two lakes were determined only in
Oscillatoriales), colonial Chlorococcales and Phy- part by the development of the same dominant
tomonadina, and the large chrysophytes—appeared MFG. This suggests that if aquatic habitats con-
more adapted to low nutrient concentrations and, strained by particular combinations of environ-
due to their size, higher grazing pressure. These mental variables will support more than one likely
groups showed a different sensitivity to the water MFG with appropriate adaptations, this does not
column stability; the MFG with the higher scores necessarily imply that these groups will be present
along the RTR gradient showed various adaptations with similar relative biomasses (or that, in some
against sinking, i.e. the presence of flagella, gas cases, that they will be there; cf. also Reynolds et
vescicles and large gelatinous envelopes. The late al., 2002). This aspect raises further questions and
winter and spring MFG were composed also by perspectives about the identification of alternative
large and potentially rapidly sinking colonies, i.e. causal factors able to explain the dominance of
organisms that require low stability of the water different MFG in these two lakes.
column. Moreover, the winter and spring groups In essence, the identification and use of MFG
developed with conditions of high nutrient avail- may constitute a useful tool for the synoptic
ability and euphotic depth. analysis of phytoplankton communities, particu-
The ability of the MFG to mimic the seasonal larly comparing different lakes. However, the
development of the phytoplankton community has usefulness of this approach in predicting the
important practical consequences and opens inter- development of probable phytoplankton types
esting perspectives. MFG may represent a useful as a result of different combinations of environ-
tool to investigate concurrently the community mental factors needs to be analysed in detail
evolution of different lakes based on the adaptive considering other lakes with different physio-
strategies of the single species, overcoming graphic and trophic characteristics.
problems related to the comparison of different
taxa and to the existence of possible differences Acknowledgements The limnological research in Lake
Garda was partially funded by the Veneto Region and
of taxonomic accuracy and identification. More- ARPAV (Veneto Region Environment Protection
over, MFG could contribute to predicting the Agency). We are grateful to Dr Giorgio Franzini and Dr
development of most probable phytoplankton Fabio Decet (ARPAV) for their logistic support in the
types as a result of different combinations of field and laboratory. We thank the technical staff of the
IGB and especially Mrs Johanna Dalchow, Mrs Elke
environmental factors. In this regard, the com- Mach, Mrs Monika Papke, Mrs Uta Mallok and Mrs
parable responses of the MFG common to the Adelheid Scheffler for their careful technical assistance.
lakes Garda and Stechlin to the same set of We wish also to thank Dr Ingrid Chorus and Dr Luigi
physical, chemical and biological variables con- Naselli-Flores for helpful comments on the first draft of
the manuscript.
stitute promising elements, though more studies
123Hydrobiologia (2007) 578:97–112 111
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