Rotifer–crustacean interactions in a pseudokarstic lake:influence of hydrology

Ulrike Obertegger Æ Andrea Borsato ÆGiovanna Flaim

Received: 14 December 2008 / Accepted: 5 August 2009

� Springer Science+Business Media B.V. 2009

Abstract Zooplankton abundance was related to

hydrological and environmental variables in a hydro-

logically dynamic lake fed by a pseudokarstic aquifer.

The study period (2002–2006) in Lake Tovel covered

different hydrological situations with water residence

time (WRT) having the lowest values in 2002 and the

highest values in 2003. WRT was negatively corre-

lated with silica concentrations and algal biovolume.

Furthermore, the biovolume of small algae was

highest in spring and summer, while large algae did

not show any pattern. In multivariate analysis, high

abundance of crustacean species in autumn and winter

was positively related to WRT and negatively to algal

biovolume, while high abundance of rotifer species in

spring and summer was negatively related to WRT

and positively to algal biovolume. With the exception

of Keratella cochlearis and Gastropus stylifer, rotifers

showed a pattern of crustacean avoidance, and three

groups were distinguished: (i) Ascomorpha ecaudis

and Polyarthra dolichoptera, (ii) Asplanchna prio-

donta and Synchaeta spp., and (iii) Filinia terminalis

and Keratella quadrata. These groups were associated

with different food sources and depths. We suggest

that WRT influenced the rotifer–crustacean relation-

ship by wash-out effects and competition for food

resources. The dynamics of single rotifer species were

attributable to specific feeding requirements and

adaptations. In summary, WRT determined the plat-

form for abiotic and biotic interactions that influenced

population dynamics of crustaceans and rotifers.

Keywords Water residence time �Zooplankton � Algal food � Competition �Depth preference

Introduction

Limnology has moved forward from treating lakes as

isolated basins to studying them as complex ecosys-

tems influenced by their catchments and surroundings.

Exterior factors such as solar irradiance, allochtho-

nous nutrient input, water inflow and anthropogenic

impacts affect the dynamics of organisms living

within an ecosystem (Wetzel 2001). Much is known

about the influence of several internal factors such as

temperature (Gillooly et al. 2002), oxygen (Mikschi

1989), food availability (Pourriot 1977), predation

(Brooks and Dodson 1965) and competition (Declerck

et al. 2003) on zooplankton dynamics. In the last

decade, however, many studies in reservoirs, ponds

and rivers have shown that different aspects of water

U. Obertegger (&) � G. Flaim

IASMA Research and Innovation Centre, Fondazione

Edmund Mach, Environment and Natural Resources Area,

Via E. Mach 2, 38010 San Michele all’Adige, TN, Italy

e-mail: ulrike.obertegger@iasma.it

A. Borsato

Museo Tridentino di Scienze Naturali, Via Calepina 14,

38100 Trento, TN, Italy

123

Aquat Ecol

DOI 10.1007/s10452-009-9285-0

movement (i.e. water-level fluctuations, length of wet

phase, water residence time (WRT) and flow rate)

explicitly or implicitly influence zooplankton abun-

dance and composition (e.g. rivers: Basu and Pick

1997; Thorp and Mantovani 2005; reservoirs: Naselli-

Flores and Barone 1997; Campbell et al. 1998; Hart,

2004; Geraldes and Boavida 2007; Mac Donagh et al.

2009; ponds: Girdner and Larson 1995; Brucet et al.

2005). In flood plains and apidly flushed lakes, lotic or

lentic conditions mediate rotifer or crustacean dom-

inance, and zooplankton dynamics are similar to that

in rivers (Walz and Welker 1998; Baranyi et al. 2002).

In shallow lakes, the influence of hydrology on

zooplankton has recently attracted research (de Souza

Cardoso and da Motta Marques 2009; Rennella and

Quiros 2006), while in deep lakes, WRT has seldom

been considered.

Lake (L.) Tovel is a deep (maximum depth 39 m)

lake fed by a pseudokarstic aquifer that surfaces in

several perilacustrine springs in the SW basin (Bor-

sato and Ferretti 2006). Karstic lakes originate by

limestone and/or gypsum dissolution; however, in the

case of L. Tovel, the depositions of a retreating

glacier account for the porous aquifer (Ferretti and

Borsato 2006). The quantification of water input by

karstic aquifers requires particular instrumentation

and long-term data. For this reason, the hydrology of

L. Tovel was subject to detailed studies of its aquifer

and basin (Borsato and Ferretti 2006; Ferretti and

Borsato 2006). Based on its dynamic and well studied

hydrology, this lake can function as a model for

ecosystem–hydrology interactions, evermore relevant

in a changing landscape.

We analysed a 5-year data set (2002–2006) to

address the following questions: (i) what are the

environmental factors that determine species interac-

tions?, and (ii) do all crustacean and rotifer species

exhibit the same relation with WRT and environ-

mental factors?

Materials and methods

Study site

L. Tovel (46�150 N, 10�570 E; area = 38 ha, volume

= 7.4 9 106 m3, maximum depth = 39 m, mean

depth = 19 m) is located 1,178 m above sea level

(a.s.l.) in the Adamello Brenta Natural Park—

Trentino, Italy (Fig. 1). The lake has a large and

deep (39 m) NE basin and a small and shallow (4 m)

SW basin and is frozen from December to April. Its

hydrology is extensively described in Borsato and

Ferretti (2006), Ferretti and Borsato (2006) and

Obertegger et al. (2007). Briefly, the S. Maria

Flavona tributary disappears 1 km above the lake in

the pseudokarstic aquifer (Pozzol) and reappears as

several perilacustrine springs in the SW basin which

account for the main water inflow (Fig. 1). The mean

daily water residence time (WRT) was calculated as

the ratio between the lake volume and the water

inflow based on mean daily data (24 measurements

per day); the temperature of the perilacustrine springs

in the SW basin was measured by thermo-sensors.

Sampling and sample processing

Samples were collected at biweekly (2002) or monthly

(2003, 2004, 2005 and 2006) intervals. However,

during winter the lake was often inaccessible. On each

sampling date, vertical profiles of water temperature

and dissolved oxygen (DO) saturation (Hydrolab

DS4a multiprobe) and Secchi disk readings were

taken. Zooplankton samples (total number for the

whole study period = 560) were taken with a 3-L

Kemmerer-like sampler at discrete depths (surface, 1,

2, 5, 10, 15, 20, 25, 30 and 35 m) in the NE basin of the

lake, filtered through a 10 lm plankton net, and fixed

with formalin (1% v/v final concentration). Phyto-

plankton samples (total number = 448) were taken in

Fig. 1 Part of the watershed area of Lake Tovel. Insert shows

geographical location

Aquat Ecol

123

conjunction to zooplankton samples and were also

collected at discrete depths (surface, 1, 2, 5, 10, 15, 20

and 25 m) in the euphotic zone (diffuse attenuation

coefficient of photosynthetically active radiation:

KdPAR = 0.19 m-1, Obertegger et al. 2008). Subsam-

ples were fixed with acid Lugol’s solution, and algae

were counted according to the Uthermohl technique

(1958). Algal biovolume was estimated from cell

dimensions. Furthermore, because zooplankton ability

to ingest algae may depend on cell size, algal

biovolume was separated by the greatest axial linear

dimension (GALD) into a small (B30 lm) and large

fraction ([30 lm) according to Naselli-Flores and

Barone (1997). For more detailed information see

Obertegger et al. (2007).

Data analysis

The depths 0, 1 and 2 m were not included in data

analyses because these layers are highly influenced

by ultraviolet radiation (Obertegger et al. 2008). We

consequently considered strata deeper than 2 m to

avoid confounding the strong impact of ultraviolet

radiation with other parameters influencing zooplank-

ton dynamics. Therefore, all statistical analyses were

based on the 5–25 m depths.

We used multivariate ordination methods to

investigate zooplankton dynamics dependent on

environmental variables. The decision about what

ordination to use was based on a Detrended Corre-

spondence Analysis according to the length of the

gradient measuring beta diversity of community

composition (Ter Braak and Smilauer 2002). Linear

multivariate techniques (i.e. Principal Components

Analysis—PCA and Redundancy Analysis—RDA)

were applied. The significance of eigenvalues of the

RDA was tested by Monte Carlo permutation tests

(n = 1,000) that were constrained to keep the tem-

poral sequence of data. Zooplankton species abun-

dance was log transformed to give equal importance

to each species. Environmental variables such as

WRT and algal biovolume were also log-trans-

formed, while the variables indicating astronomical

seasons (i.e. spring, summer, autumn and winter) and

depth were coded as dummy binary variables. In the

analysis, species data were centred to unit variance

and zero mean, and scaling was done with the focus

on species correlation. Additionally, the technique of

variance partitioning (Borcard et al. 1992) was used

to quantify the variation explained by explanatory

variables related to the first and second axis. Variance

partition is performed by a partial RDA: the amount

of variability explained by group variables Y (e.g.

variables related to the first axis) was determined

once the variability explained by the group variables

X (e.g. variables related to the second axis) was taken

into account. All statistical analyses were performed

using CANOCO 4.5 software (Ter Braak and Smil-

auer 2002).

Non-parametric correlations (Spearman) and mul-

tiple comparisons were performed in R (R Develop-

ment Core Team 2005) and were used to relate

environmental variables to each other.

Results

Chemical and physical properties of the lake

In the years investigated, L. Tovel showed weak

thermal stratification in summer. The temperature of

the perilacustrine springs was between 5 and 6�C

throughout the year (mean 5.5�C, standard deviation

(SD) 0.1�C) (Fig. 2). The lake’s surface water

Fig. 2 Upper panel: upper line—water residence time for the

study period, lower line—temperature of the perilacustrine

springs. Multi-annual seasonal mean biovolumes of small algae

(lower left panel) and large algae (lower right panel). Box plots

show percentiles (5th circle, 10th, 25th, 50th, 75th, 90th, and

95th circle)

Aquat Ecol

123

temperature was highest in summer 2003 (20.4�C).

Furthermore, water temperature was positively cor-

related with DO saturation and negatively correlated

with small and large algae (Table 1). Generally, DO

was high (DO at 25 m: mean 63%, SD 17%), and

anoxia was never a problem. Total phosphorus (mean

3.7 mg l-1, SD 1.7 mg l-1) was always low, while

inorganic nitrogen (mean 372 mg l-1, SD 42 mg l-1)

was always high.

WRT showed a large variability for the study

period (median = 205 days, minimum = 23, maxi-

mum = 652) with 2002 having the lowest and 2003

the highest values (Fig. 2). Furthermore, WRT

showed the lowest values in spring (mean 127 days,

SD 45 days), and the highest values in winter (mean

414 days, SD 157 days) (multiple comparisons

(m.c.): P \ 0.01) and was positively correlated with

temperature and negatively correlated with small and

large algae and silica (Table 1).

Small algae were positively correlated with silica

(mean 0.72 mg l-1, SD 0.18 mg l-1) (Table 1).

Their biovolume was higher in spring and summer

than in autumn and winter (m.c.: P \ 0.01), and was

generally higher than that of large algae (m.c.:

P \ 0.001) (Fig. 2). In addition, the 5–25 m layer

was characterised by a homogenous distribution of

algal biovolume with no marked difference between

depths (m.c.: P [ 0.05). Secchi disk transparency

(mean 12.0 m, SD 3.6 m) was higher in autumn

compared to other seasons (m.c.: P \ 0.001).

Interaction between the zooplankton community

and environmental parameters

During the study period (2002–2006), rotifer diversity

was high with nine numerically important taxa in the

plankton: Ascomorpha ecaudis Perty, Asplanchna

priodonta Gosse, Filinia terminalis Plate, Gastropus

stylifer Imhof, Keratella cochlearis Gosse, Keratella

quadrata O.F.Muller, Synchaeta gr. stylata-pectinata

sensu Ruttner-Kolisko, Synchaeta gr. tremula-oblon-

ga sensu Ruttner-Kolisko, and Polyarthra dolichop-

tera Idelson. These species however, showed large

variations in temporal abundance (Table 2a). Overall,

rotifers numerically dominated the zooplankton

(median = 97%, minimum = 16%, maximum =

100% of rotifers with respect to total zooplankton

abundance). Cladocerans, especially Daphnia lon-

gispina O.F.Muller and Bosmina longirostris

O.F.Muller, made up most of the remaining zoo-

plankton and also showed large temporal variability

(Table 2b).

In a PCA based on abundance of zooplankton, the

first two axes accounted for 62.4% of species

variability. We could discriminate among rotifers,

cladocerans and nauplii and copepodites/adults of

Cyclops strenuus Fischer by their different relation to

the first two axes (Fig. 3). On the basis of this result,

we further investigated species distribution by a RDA.

The RDA explained 22.9% of total species variability,

with the first two axes explaining 60.2% of species–

environment relation. The eigenvalues of the RDA

were statistically significant according to Monte Carlo

permutations (sum of all axes; P \ 0.001). In the

RDA, species showed specific relations with environ-

mental variables leading to a discrimination between

two main groups (Fig. 4). In the first group, copepods,

nauplii, B. longirostris, D. longispina, G. stylifer and

K. cochlearis were positively related to WRT, Secchi

disk transparency, temperature, DO, depth of 5 and

10 m and autumn, while they were negatively related

to small and large algae, depth of 20 and 25 m and

spring. In the second group, Ascomorpha ecaudis,

P. dolichoptera, Asplanchna priodonta, S. gr. tremu-

la-oblonga, S. gr. stylata-pectinata, K. quadrata and

F. terminalis were negatively related to WRT, Secchi

disk transparency, and autumn. Additionally within

the latter group, three subgroups could be distin-

guished that showed this general pattern but had

different trends regarding other parameters: (i)

Table 1 Non-parametric correlation of environmental vari-

ables: the upper section gives significance (*P \ 0.05, **

P \ 0.01, *** P \ 0.001), the lower section gives correlation

(sections separated by the shaded areas); missing values refer

to non-significant correlations; DO is dissolved oxygen, temp is

temperature, B30 lm refers to small algae, [30 lm refers to

large algae, and SiO2 is silica

DO temp ≤ 30 µm

> 30 µm

SiO2 WRT

DO *** ***

temp 0.65 *** ** *** * ≤ 30 µm -0.17 *** *** ***

> 30 µm -0.24 0.19 * SiO2 -0.58 -0.49 0.25 ** WRT 0.32 -0.50 -0.29 -0.45

Aquat Ecol

123

A. ecaudis and P. dolichoptera were positively related

to large algae, summer and a depth of 5, 10 and 15 m,

while negatively related to a depth of 20 and 25 m, (ii)

A. priodonta, S. gr. tremula-oblonga and S. gr. stylata-

pectinata were positively related to small and large

algae, summer and spring and a depth of 5, 10 and

15 m, while negatively related to a depth of 25 m and

(iii) F. terminalis and K. quadrata were positively

related to small algae, spring and winter and to a depth

of 20 and 25 m, while negatively related to large

algae, summer and autumn and a depth of 5, 10 and

15 m.

Based on the correlation of variables with the axes

(Table 3), we discriminated between variables related

to the first (i.e. WRT, SD, small algae and autumn)

and second axis (i.e. temperature, DO, large algae,

Table 2 Species abundance (individuals m-3) for the study period; med is median, min is minimum, and max is maximum value

A. ecaud A. priod F. term G. stylifer K. cochl K. quad P. doli S. gr. trem-obl S. gr. styl-pect

a

2002 med \1 1455 2380 \1 \1 \1 4364 364 \1

min \1 \1 \1 \1 \1 \1 \1 \1 \1

max 9818 46545 148727 8364 107636 5091 465818 51272 29964

2003 med \1 \1 727 6582 \1 \1 1455 \1 3273

min \1 \1 \1 \1 \1 \1 \1 \1 \1

max 2909 25455 495636 78545 28364 3273 32364 11636 238545

2004 med \1 \1 \1 \1 2909 \1 6727 727 364

min \1 \1 \1 \1 \1 \1 \1 \1 \1

max 1818 210182 64364 38909 124727 2909 156727 28364 300000

2005 med \1 \1 \1 \1 3455 \1 1818 364 7455

min \1 \1 \1 \1 \1 \1 \1 \1 \1

max 364 \1 3636 364 212727 7636 173091 18545 128364

2006 med \1 \1 \1 \1 \1 \1 18727 \1 \1

min \1 \1 \1 \1 \1 \1 364 \1 \1

max 10909 9455 364 \1 20364 3273 213818 2545 4364

B. longirostris D. longispina C. strenuus nauplii

b

2002 med \1 \1 \1 \1

min \1 \1 \1 \1

max 25818 19273 51273 364

2003 med 727 \1 \1 \1

min \1 \1 \1 \1

max 166545 14182 727 1818

2004 med \1 \1 \1 \1

min \1 \1 \1 \1

max 28364 2545 2182 2545

2005 med 546 \1 \1 364

min \1 \1 \1 \1

max 60000 16364 5455 6909

2006 med \1 \1 727 \1

min \1 \1 \1 \1

max 21091 14545 26545 24364

A. ecaud = A. ecaudis, A. priod = A. priodonta, F. term = F. terminalis, K. cochl = K. cochlearis, K. quad = K. quadrata. For

additional abbreviations see Fig. 4

Aquat Ecol

123

spring, summer, winter, 5, 10, 15, 20 and 25 m).

Therefore, the partial RDA was performed with these

two groups of variables. The variables related to the

first axis explained 15% of the total variability, the

variables related to the second axis explained 59%,

and the remaining 26% were related to the shared

effect of the two groups, as shown by variance

partitioning.

Discussion

In L. Tovel, the pseudokarstic aquifer surfaces as

perilacustrine springs and is the largest contributor of

water inflow ([80%) (Borsato and Ferretti 2006). The

aquifer, furthermore, smoothes water inflow peaks

(Borsato and Ferretti 2006), functions as a natural

filter determining low DOC values (\1 mg l-1;

Tardio et al. 2006), determines nutrient inputs

(Corradini and Boscaini 2006 and this study) and

algal composition (Tolotti et al. 2007), and constantly

introduced cold water (this study). Considering these

effects, it seemed reasonable to suggest that WRT, as

determined through water input by the aquifer, also

influenced zooplankton dynamics in this lake. In fact,

WRT can influence crustacean or rotifer dominance

in deep lakes (Obertegger et al. 2007), in shallow

Fig. 3 PCA ordination of zooplankton (k1 = 0.367, k2 =

0.258). Lambda (k) defines the amount of variability explained

by the single axis. Copepods refer to copepodites and adults of

C. strenuus

Fig. 4 RDA ordination of zooplankton taxa in relation to

environmental variables. (k1 = 0.084, k2 = 0.044). Groups

are circled; variables are coded as in the PCA. Abbreviations of

species names: G. stylifer = G. styl, S. gr. stylata-pectinat-a = S. gr. styl-pect, S. gr. tremula-oblonga = S. gr. trem-obl,P. dolichoptera = P. doli, copepodites/adults of C. strenu-us = copepods, B. longirostris = B. longi

Table 3 Correlation coefficients between environmental

variables and the first and second axis with the greater pair-

wise value emboldened

Factor Axis 1 Axis 2

WRT 20.61 0.01

Secchi Disk -0.61 0.01

Small algae 0.42 20.15

Winter 20.04 -0.17

Autumn -0.59 20.06

DO 20.35 0.53

Temperature 20.53 0.56

5 m 20.11 0.24

10 m 20.14 0.22

15 m 0.01 0.11

20 m 0.11 -0.12

25 m 0.14 -0.44

Large algae 0.42 0.58

Summer 0.24 0.65

Spring 0.31 -0.63

Aquat Ecol

123

lakes (Rennella and Quiros 2006), and in reservoirs

(Geraldes and Boavida 2007).

Our analysis indicated that rotifers, cladocerans

and copepods tended to exclude each other. In fact, in

temperate lakes zooplankton usually show a temporal

succession with rotifers followed by crustaceans

(Sommer et al. 1986). In addition to temporal

distribution, spatial distribution also has to be con-

sidered. Zooplankton position themselves in the

water column to maximise growth but several

parameters result in trade-offs between survival and

reproduction. We found that rotifers were separated

from crustaceans based on two gradients: the first

gradient corresponded to WRT, Secchi disk transpar-

ency and small algae and was related to autumn,

while the second gradient corresponded to depth

distribution, temperature, DO and large algae and was

related to spring, summer and winter.

The relation of zooplankton with WRT can be

explained by wash-out effects (e.g. Campbell et al.

1998; Walz and Welker 1998; Baranyi et al. 2002;

Rennella and Quiros 2006). Rotifers’ shorter gener-

ation time gives them a decisive advantage over

crustaceans by permitting a faster recovery from

wash-out (Baranyi et al. 2002). Furthermore, juvenile

stages have reduced swimming capacities as shown

for copepods (Maar et al. 2003) and for Daphnia pulex

(Dodson and Ramcharan 1991). In our analysis, all

life stages of copepods were positively related to

WRT, and it seemed reasonable to suggest that the

effect of WRT on adults was indirectly mediated by

the lack of juveniles, more susceptible to wash-out

effects than adults. Furthermore, highest abundance of

crustaceans occurred in autumn and winter in contrast

to spring and summer. These seasons had sufficiently

long periods with high WRT (WRT [ 193 for

23 days) to favour crustacean abundance as indicated

by Obertegger et al. (2007). However, even if

cladocerans and copepods were present in other

seasons, they had their highest abundance in autumn

and winter, confirming the positive relationship

between WRT and crustacean abundance.

Crustaceans’ dominance in autumn and winter also

coincided with a decrease of algal food. This decrease

could be related to different factors such as zoo-

plankton grazing or nutrient decline. Grazing by

rotifers can result in a reduction of algae (Herzig

1987; Gosselain et al. 1998). However, Tolotti et al.

(2007) note the low influence of zooplankton grazing

on diatom abundance in L. Tovel. Furthermore,

crustaceans and rotifers can affect algal abundance

and composition not only directly through grazing but

also indirectly through nutrient regeneration (Carillo

et al. 1990; Urabe 1993). We suggest that in autumn

factors other than grazing were responsible for algal

decline while nutrient regeneration might be impor-

tant in spring and summer when rotifers and algal

food were abundant.

The concentration of nutrients is another important

factor for algal composition and abundance. In

L. Tovel, the negative correlation of WRT with

algae and silica indicated that increasing WRT might

result in a decline of silica and consequently in a

decline of diatoms because of reduced silica input

and concomitant algal consumption.

In periods of high WRT, crustaceans might

compensate the reduced food sources by their higher

filtration capacity compared to rotifers (Herzig 1987).

However, even if rotifers also could be favoured by

high WRT, only few species were associated with

crustaceans. Crustacean-rotifer interactions are deter-

mined by predation (Williamson 1993), exploitative

competition for food of similar size, and mechanical

interference (Burns and Gilbert 1986). These inter-

actions often result in a marked seasonality with

suppression of rotifers by crustaceans. Based on our

analysis, the rotifers G. stylifer and K. cochlearis

were surprisingly associated with crustaceans, and we

suggest that only specific autecological traits might

faciliate this coexistence. While illoricate G. stylifer

might not possess any evident morphological

defence, a lorica with spines might plausibly reduce

predation on K. cochlearis. In fact, copepods such as

Mesocyclops edax have to break the lorica that

hinders ingestion (Williamson 1993). Even if mor-

phological defenses are a necessary condition to

maintain high rotifer abundance in the presence of

abundant mesozooplankton, these characteristics are

not sufficient (Yoshida et al. 2003). Apart from their

resistance to predation, the compensatory effects of

reproduction should also be considered. The short

development time of rotifers with respect to crusta-

ceans is of general importance in maintaining a stable

population (Walz 1995). This characteristic might

allow for fast recovery from predation losses even if

dependent on temperature and food supply. In

addition, competition for food under reduced

resources might be generally important. Keratella

Aquat Ecol

123

cochlearis is adapted to low food concentrations

(Walz 1995), while G. stylifer preferentially feeds on

dinoflagellates (Nogrady et al. 1993) that are abun-

dant in L. Tovel (Flaim et al. 2003). Among

dinoflagellates Gymnodinium uberrimum Kofoid and

Swezy was the most abundant species with which

G. stylifer showed a positive correlation (r = 0.22,

P \ 0.01). Additionally, population dynamics of this

species are positively related to water temperature

(Herzig 1987; Spoljar et al. 2005). In fact, G. stylifer

had its highest abundance in the hot summer and

autumn of 2003. In summary, K. cochlearis and

G. stylifer might compensate scarce food sources and

population losses caused through crustacean preda-

tion by (i) low resource competition, (ii) specific

feeding strategies, (iii) short generation time and (iv)

having the advantage of being the only rotifer species

exploiting resources in coexistence with crustaceans.

Apart from food, temperature and oxygen are other

important parameters for the spatial and temporal

variation in rotifer abundance (Mikschi 1989). Tem-

perature per se determines development rates (Gillo-

oly et al. 2002), and DO saturation is crucial for

direct uptake and respiration rates in rotifers. How-

ever, Armengol et al. (1998) relate the importance of

temperature and oxygen to other associated factors

such as food availability and competition. In L. Tovel,

most species seemed to prefer the 5–15 m layer that

was characterised by high DO values and abundant

algal food; deeper layers were inhabited by species

mainly feeding on bacteria. We suggest that oxygen

supply was not critical and species were adapted to

the low water temperatures at depths lower than 5 m

(summer mean at 5 m 10�C, SD 2.9�C). However in

L. Tovel, some species migrate to the surface layer at

night to take advantage of warmer temperatures

(Obertegger et al. 2008).

Within the main rotifer group, three subgroups

could be distinguished. In the first group, A. ecaudis

feeds on large food cells and dinoflagellates, and

P. dolichoptera feeds on diatoms, crysomonads and

cryptomonads (Pourriot 1977). In our study, both

species were closely related to large algae; we

suggest that these rotifers could exploit food sources

inaccessible to others, and therefore probably had a

competitive advantage. In the second group, Syncha-

eta species feed on small and on large food particles

and Asplanchna is omniphagous (Pourriot 1977).

These species were among the largest rotifers in

L. Tovel, indicating a high food demand according

to the size-efficiency theory of Stemberger and

Gilbert (1987). In the third group, K. quadrata and

F. terminalis are adapted to cold temperatures and

feed on small algae, flagellates, bacteria and detritus

(Nogrady et al. 1993). These characteristics may have

favoured their occurrence in the deeper layers and

simultaneously offered the possibility to avoid com-

petition with crustaceans and other rotifer species.

In summary, we suggest that rotifers generally

responded in the same way to WRT and competition

with crustaceans, and the differentiation among

rotifers was mainly related to specific food require-

ments and adaptations.

While the influence of WRT on plankton dynamics

in shallow lakes is known (de Souza Cardoso and da

Motta Marques 2009; Rennella and Quiros 2006), the

effects of hydrology in deeper lakes can remain

hidden when adequate hydrological parameters are

not used (Spoljar et al. 2005). By using the appro-

priate hydrological variable (i.e. WRT), our study

underlined the importance of hydrology for rotifer

species dynamics in a deep lake. We suggest that

WRT directly determined wash-out effects of zoo-

plankton and patterns of algal food, and consequently

also indirectly determined zooplankton dynamics.

Therefore, we hypothesised that WRT was the

starting point for abiotic and biotic factors. This

coupling of abiotic and biotic processes is in line with

the ‘‘multiple driving force hypothesis’’ of Pinel-

Alloul (1995). In fact, environmental variables shared

effects on species distribution, and therefore interre-

lation among parameters could not be neglected. In

the present study, specific species related to WRT in

different ways, and experimental studies are required

to quantify the influence of WRT on single species. In

addition, the unexplained variability of species

abundance could be determined by other factors such

as fish predation (Brooks and Dodson 1965), parasit-

ism (Nogrady et al. 1993), crowding (Stelzer and

Snell 2006), or intra-species competition (Declerck

et al. 2003) that also influence zooplankton dynamics.

In conclusion, the pseudokarstic catchment mark-

edly influenced the plankton of its associated lentic

ecosystem, and the dynamics of crustaceans and

rotifers were based on WRT and competition for

algal food.

Aquat Ecol

123

Acknowledgements This study was partially supported by

ECOPLAN and CERCA Research Grants (Province of Trento,

Italy), and by research activity funded by FEM-IASMA. We

thank Flavio Corradini for providing chemical data, Gino

Leonardi and Vigilio Pinamonti for help with sampling, and

Damaso Calliari and Federica Fiammingo for phytoplankton

counting.

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