Limnol. Oceanogr., 54(4), 2009, 1306–1322
2009, by the American Society of Limnology and Oceanography, Inc.
E
Lake-wide distributions of temperature, phytoplankton, zooplankton, and fish in the
pelagic zone of a large lake
Karsten Rinke,a,1,* Andrea M. R. Huber,a Sebastian Kempke,b Magdalena Eder,c Thomas Wolf,d
Wolfgang N. Probst,a and Karl-Otto Rothhaupta
a Limnological
Institute, University of Konstanz, Konstanz, Germany
Bodensee-Wasserversorgung, Sipplingen, Germany
c Institute of Hydraulic Engineering, University of Stuttgart, Stuttgart, Germany
d Institut für Seenforschung, Langenargen, Germany
b Zweckverband
Abstract
We studied three-dimensional distribution patterns of temperature, phyto- and zooplankton, and fish in the
large, prealpine Lake Constance during spring 2007. A strong westerly wind induced an intense eastward
displacement of epilimnetic water and upwelling of hypolimnetic water in the western part of the lake. This led to
the formation of an internal front separating cold, hypolimnetic water depleted of chlorophyll in the western part
from epilimnetic, warm water with high chlorophyll concentrations in the eastern part. Hydroacoustic detection
of zooplankton (by Acoustic Doppler Current Profiler) and juvenile fish (by echosounding) revealed both to be
passively transported by the wind. Consequently, zooplankton and fish showed comparable horizontal
distributions as temperature and chlorophyll. During periods of low wind velocities (,6 m s21), water
temperature was more evenly distributed, whereas phytoplankton distribution was still heterogeneous, probably
because of local differences in resource supply. The relative influence of biotic factors for the distribution of
organisms increased when external forcing was low. At periods with weak wind forcing, phytoplankton typically
showed highest concentrations in the metalimnion, where zooplankton also aggregated in thin layers. In
conclusion, we found spatial distributions of temperature and organisms to be strongly controlled by wind forcing
when wind velocities were sufficiently high, whereas the importance of internal biotic factors for distribution of
organisms increased when wind velocities were less strong. Abiotic factors appeared to act over relatively large
spatial scales and affected distributions within the entire ecosystem, whereas biotic factors affected distributions
of algae, zooplankton, and fish on a more local scale.
Abiotic and biotic processes commonly cause lake-wide
distributions of plankton to be highly variable and
heterogeneous, resulting in considerable patchiness (Folt
and Burns 1999). The ecological consequences of patchy
distributions of organisms are manifold; metapopulation
ecology has shown that spatial heterogeneity is important
for species persistence and population dynamics (Hanski
1981; Bascompte and Solé 1995), rendering the phenomenon of patchiness a key factor for mediating species
coexistence and maintenance of high species diversity
(Hastings 1988, 2001). Patchy distribution of prey organisms affects the intensity and dynamics of predator–prey
interactions (Eggers 1976; Hastings 2001) and enhances
ecosystem productivity (Rovinsky et al. 1997; Brentnall
et al. 2003). For a thorough understanding of ecosystem functioning, the aspect of spatial distribution
patterns and their consequences therefore need to be taken
into account.
Model applications have demonstrated that it is an
intrinsic property of plankton distributions to be spatially
heterogeneous because of the interaction of physical and
biological processes that work on different spatial and
temporal scales (Turing 1952; Abraham 1998; Brentnall
* Corresponding author; email: karsten.rinke@uni-konstanz.de
1 Present address: University of Konstanz, Limnological Institute, Konstanz, Germany
et al. 2003). Nevertheless, freshwater ecologists often
assume horizontal homogeneity and exclusively concentrate on vertical gradients. In fact, most lake monitoring
programs and modeling approaches in limnology explicitly
exclude heterogeneity in the horizontal plane (Anneville
et al. 2004; Peeters et al. 2007). However, given the fact that
spatial distributions of plankton are typically patchy, these
studies involve a sampling error caused by spatial
heterogeneity, which is not easily quantifiable and introduces additional noise into long-term data sets. In order to
pave the way for a spatial ecology of lakes, we therefore see
a strong need for studies providing detailed information on
lake-wide, three-dimensional distribution patterns of organisms and the processes involved in their dynamics.
Previous studies documented the spatially heterogeneous
distributions of bacteria, phytoplankton, and zooplankton,
and even of large invertebrates like mysids (Jones et al.
1995; Pinel-Alloul et al. 1999; Pothoven et al. 2004).
Dominant factors explaining spatial variations are windinduced circulations (Lacroix and Lescher-Moutoué 1995;
Thackeray et al. 2004), water temperature (Patalas and
Salki 1992; Pinel-Alloul et al. 1999), basin morphology
(Pothoven et al. 2004) or local eutrophication, e.g., by river
inflows (Patalas and Salki 1992; Fietz et al. 2005). Such
factors inducing patchy plankton distributions in lakes may
be separated in two different modes of patch generation
(George and Heaney 1978); factors inducing spatial
variation in the rate of population increase or decrease,
1306
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Lake-wide organism distribution
e.g., local differences in resource availability, predation
pressure or temperature, and factors bringing about a
spatial redistribution of the population.
Because of this multitude of factors that come into play
in structuring spatial distributions of organisms in lakes,
Pinel-Alloul and Ghadouani (2007) promoted a multiscale
perspective on spatial distributions of plankton communities. They pointed out that abiotic and biotic processes
driving spatial distribution patterns range over spatial and
temporal scales from millimeters to hundreds of kilometers
and from seconds to several years. These spatial and
temporal scales are viewed as a system of nested
hierarchical levels interacting with each other in a
continuum. In line with the multiscale perspective, PinelAlloul (1995) introduced the ‘‘multiple driving forces
hypothesis’’ (MDFH), stating that neither biotic nor
abiotic processes alone can explain observed spatial
distribution patterns. There are rather several—biotic and
abiotic—driving forces involved, interacting over multiple
temporal and spatial scales. The MDFH furthermore states
that the relative importance of processes is scale-dependent:
physical processes predominate at large scales whereas
biotic processes predominate at finer scales. For example,
George and Winfield (2000) found the lake-wide distributions of different zooplankters to be controlled by windinduced basin-scale currents. However, external wind
forcing alone was not able to explain the distribution
patterns completely, because vertical depth selection
behavior of the zooplankters, i.e., a biotic process,
determined their vertical position and by that the direction
of the respective current acting on them.
Vertical distributions of organisms are often strongly
controlled by behavioral traits, i.e., by biotic processes, like
diurnal vertical migration of zooplankton or depth-specific
shoaling of fish (Masson et al. 2001). In line with the
MDFH, however, besides these strong biotic control
factors, abiotic processes also act simultaneously on
emerging vertical distribution patterns, for instance, windinduced vertical mixing (Webster and Hutchinson 1994;
Serra et al. 2007) or internal seiching (Marce et al. 2007;
Rinke et al. 2007). Finally, it may also appear that the time
scales of large-scale transport processes overlap with
ecological timescales of phytoplankton growth and community dynamics, i.e., dynamics in spatial distribution of
organisms possibly affect population dynamics (Reynolds
1990; Rojo and Alvarez-Cobelas 2001).
The aim of our study was to achieve a lake-wide
assessment of the spatial distributions of physical and
ecological parameters in a large lake of about 500 km2
surface area. In an extensive field campaign, we measured
synoptically the three-dimensional distribution patterns of
water temperature, phyto- and zooplankton, and fish
abundance by using conductivity, temperature, depth
(CTD) probes, fluorometry, and hydroacoustic techniques.
Deployment of thermistors and drifters complemented the
sampling design by characterizing the hydrodynamic
environment. Based on these data, we mapped distribution
patterns and the degree of patchiness on the basis of a
multiscale approach, resolving vertical distributions from
scales of a few centimeters to horizontal distributions up to
Limnology limn-54-04-41.3d 4/5/09 15:22:59
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Cust # 08-241
1307
the ecosystem scale. Because we measured external driving
forces (e.g., wind), hydrodynamic processes, and ecological
processes simultaneously, our campaign provides information about underlying processes affecting lake-wide distributions as well as the temporal and spatial scales of their
dynamics. We hypothesize physical factors to be very
important on larger scales affecting the distribution
patterns over the whole system, whereas ecological
processes are more relevant on local scales.
Methods
Study site—Lake Constance is a large, monomictic,
prealpine lake situated on the northern edge of the central
European Alps along the borders of Germany, Switzerland,
and Austria. With a surface area of 473 km2, an average
depth of 100 m, and a maximal depth of 254 m, Lake
Constance is among the largest and deepest lakes in
Europe. The lake suffered from eutrophication between
1960 and 1980 and since then underwent intensive
reoligotrophication. Nowadays, the lake is almost returned
to its natural state and is classified as oligotrophic (Güde et
al. 1998). Phytoplankton community in spring is dominated
by centric diatoms and cryptophytes, and zooplankton
consist mainly of cladocerans and calanoid and cyclopoid
copepods (Gaedke 1998; Straile and Geller 1998). The
pelagic fish community is dominated in terms of biomass
by lake whitefish (Coregonus lavaretus; Eckmann and
Rösch 1998). The main axis of the lake is oriented along
northwestern and southeastern directions (Fig. 1). Wind
fields over the lake are highly variable and the associated
patterns in basin-wide circulations are diverse, including
the occurrence of complete upwelling—strong thermocline
tilts causing deep upwelling and the occurrence of cold,
hypolimnetic water at the lake’s surface—and internal
fronts during storm events (Bäuerle et al. 1998).
Temperature and chlorophyll measurements—We used
three multiparameter probes (Sea and Sun Technology,
http://www.sea-sun-tech.com) equipped with CTD and
chlorophyll sensors for measurement of vertical profiles
of temperature and chlorophyll. Data acquisition rate of
the probes was set to 2 Hz, resulting in a vertical resolution
between 10 and 15 cm. A sensor comparison showed that
measured temperatures were almost identical among all
probes. However, chlorophyll concentrations measured by
the fluorometers (microFlu-Chl, TriOS GmbH; HB176,
Chelsea Instruments; Back Scat Fluorometer, MEElectronics) differed slightly because of different sensor
design and mounting. We first intercalibrated the three
probes by calculating linear regression between the
readings from the three probes and converted the readings
from two probes to the third probe (probe3 5 0.41 3
probe2 2 0.95, R2 5 0.848; probe3 5 0.68 3 probe1 2 1.57,
R2 5 0.850). Secondly, we compared readings from this
third probe to chlorophyll measurements obtained from
photometric determination of chlorophyll a after wet
extraction in ethanol according to Stich and Brinker
(2005). Again, a linear regression was calculated to convert
the readings from all probes into measured chlorophyll
1308
Rinke et al.
Fig. 1. Left panel: map of Lake Constance and location of the longitudinal cross section (black line) and the 7 transversal cross
sections (A–G, grey lines) sampled during the field campaign. Positions of five thermistors (T1–T5) in the littoral zone (at 1.5-m depth)
are indicated by arrows. Right panel: schematic diagram of the drifters used.
55 m, 65 m, 85 m, 95 m, 125 m, and 145 m. We used a
depth-dependent horizontal sampling scheme instead of an
equidistant design in order to account for potential effects
of water depth and shore distance on primary production
(e.g., mediated by wind sheltering, sediment contact, or
mixing depth) or species distributions (Pothoven et al.
2004). The sampling of all transects resulted in 48
profiles taken quasi-synoptically by three research
vessels, which sampled all transects within 6–7 h depending
on the wind conditions. Although distribution patterns in
the lake are always subjected to dynamic changes, we
believe spatial patterns did not change appreciably within
this 6–7 h because of the relatively large spatial scales and
because wind direction and velocity varied little during
sampling.
A longitudinal section along the main axis of the lake
(Fig. 1) was sampled by two research vessels on 07 May
2007, i.e., 3 d before the first whole-lake assessment
(Table 1). This sampling took place within 8 h and was
comprised of 26 profiles. The horizontal distance between
these sampling points varied between 250 m and approximately 3.5 km.
(chlorophyll 5 2.16 3 probe3 2 0.64, R2 5 0.856). These
calibration procedures were also performed to avoid
systematic errors and statistical problems introduced by
the sampling strategy (Avois et al. 2000).
Measurements were taken along seven transects in Lake
Constance covering the whole lake (Fig. 1, transects A–G).
In order to assess the lake-wide three-dimensional distribution of temperature and chlorophyll, all transects were
sampled during two campaigns, on 10 May 2007 and 16
May 2007 (Table 1). In addition, transects C and D were
also sampled on 25 April 2007 and on 03 May 2007, i.e., 1
and 2 weeks, respectively, before the whole-lake campaign.
We conducted the sampling at this time of the year because
at the spring bloom relatively high plankton biomasses are
reached that are well above the detection limit of the probes
used. At transects B to F, seven profiles were taken, located
at the deepest point of the transect and at the locations
where water depths was 65 m, 35 m, and 15 m. The
easternmost transect (G) contained only 5 measurement
points because the deepest point had a water depth of only
55 m. The westernmost transect (A) contained eight
measurement points, at water depths of 15 m, 35 m,
Table 1.
Overview of the schedule of the different samplings and the drifter experiment.
Transversal cross sections
Date (2007)
25
03
07
08
10
16
*
{
Apr
May
May
May
May
May
A
B
C
D
X*
X*
X*
X*
E
F
G
Longitudinal cross section
Drifter experiment
X
X
X
X
X
X
X{
X{
X{
X{
X
X
X
X
X
X
Sampling occasion included a hydroacoustic assessment of zooplankton distribution.
Sampling occasion involved hydroacoustic assessment of zooplankton and fish distributions.
Limnology limn-54-04-41.3d 4/5/09 15:22:59
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Cust # 08-241
Lake-wide organism distribution
Because quasi-synoptic sampling with CTD probes can
provide only an instantaneous mapping of the distribution
patterns and not a mapping of their dynamics, we
employed 5 thermistors (TR 1050, RBR, www.rbr-global.
com) in the littoral zone of Lake Constance (T1–T5; see
Fig. 1). These thermistors, distributed almost equally
around the lake’s shore, achieved a continuous temperature
measurement over the whole sampling period, and thus
provided information about the dynamics of temperature
distributions and the spatial extent of upwelling events. All
thermistors were fixed at a water depth of 1.5 m. The
measurement interval was set to 10 s but was afterwards
aggregated to one temperature measurement per minute by
calculating the arithmetic mean.
Hydroacoustic measurements—Zooplankton: The acoustic backscatter from a 614-kHz Acoustic Doppler Current
Profiler (ADCP; RDI Workhorse, RD Instruments, www.
rdinstruments.com) was used for hydroacoustic detection
of zooplankton. Detailed studies in lakes and reservoirs
have demonstrated that the ADCP backscattering strength
showed a good correlation with zooplankton abundance
and therefore provides information about vertical distribution of zooplankters at a relatively high spatial resolution
(Lorke et al. 2004; Rinke et al. 2007). Hydroacoustic
measurements with the ADCP were conducted exclusively
on transects C and D on 25 April, 03 May, 10 May, and 16
May 2007, i.e., in parallel to the CTD profiling (Table 1).
The ADCP was mounted to the side of a boat approximately 0.6 m below the water surface, facing downward.
The applied ADCP was equipped with four acoustic beams
(transducer diameter, 73 mm; beam width, 1.5u), which
were tilted by 20u to the vertical axis. We measured with a
ping rate of 0.5 s and an averaging interval of 1.5 s. The
blanking distance below the ADCP was 0.5 m. A vertical
resolution (depth cell size) of 0.6 m was used for data
collection and analysis. Note that the CTD probes worked
at a much finer vertical scale (10–15 cm) and about 5
measurements for temperature and chlorophyll were
available per ADCP depth cell. The center of the first of
128 depth cells was at a depth of 1.48 m, the center of the
last one at 77.98 m. Backscattering intensities (counts)
obtained from the ADCP were corrected for absorption by
water and the spreading of the acoustic beams and finally
converted to absolute volume backscattering strength (dB)
according to Lorke et al. (2004). In parallel to the ADCP
measurements, the geographical position of the boat was
recorded by a global positioning system (GPS). Note that
the ADCP provides no information about taxonomic
composition or size distribution of the organisms.
For a quantitative interpretation of backscatter strength
with respect to zooplankton density, a calibration of
zooplankton samples was performed. Zooplankton samples
were taken by vertical hauls with a closing plankton net
(Apstein plankton net, opening diameter 17 cm, Hydrobios) equipped with a mesh size of 100 mm. Calibration
samples were taken at the profiling stations, and in total 48
samples were taken in variable depths between 0 and 25 m
along the transects in spring 2006 and 2007. We used data
from both years for calibration to have a higher number of
Limnology limn-54-04-41.3d 4/5/09 15:23:01
1309
Cust # 08-241
1309
samples and because zooplankton community composition
in spring was similar in these years. The samples were fixed
in 4% sucrose–formaldehyde solution, and later taxonspecific abundance was assessed by counting under a
dissecting microscope in the laboratory. A positive
correlation was found between the log-transformed abundance of Daphnidae (D, consisting of the genus Daphnia
and Bosmina) and acoustic backscatter strength (abs),
which was averaged over the same depth interval from
which the respective zooplankton samples were taken
(abs 5 4.71 3 log[D] 2 100.26, R2 5 0.54, F1,72 5 83.71,
p , 0.001).
Fish: A hydroacoustic assessment of spatial distribution
of fish was conducted on 10 May and 16 May at transects C
and D (Table 1). For the hydroacoustic recordings a
SIMRAD EK60 (2007) echosounder equipped with an
E120-7C split-beam transducer (120 kHz, nominal circular
beam width of 7u, SIMRAD) was used. The EK60 was
operating with a power output of 100 W, a pulse length of
0.256 ms, and 8.71-kHz bandwidth. Ping intervals during
the surveys ranged from 0.2 to 1.3 s per ping and were
adjusted to avoid false bottom echoes. Data were stored on
a laptop computer, which was also used to control the
echosounder settings. A GPS system was connected to the
computer in order to map the position of the boat. The
echosounder system was calibrated in May 2007 with a 22mm-diameter copper sphere of 240.4 dB reference target
strength (at 1490 m s21 sound speed) according to the
manufacturer’s manual. Hydroacoustic data were analyzed
with the software SONAR5_Pro 5.9.6 (Balk and Lindem
2006). The settings for single-echo detection (SED) were set
to a returned pulse length between 0.8 and 1.6 of the
transmitted pulse and a maximum one-way gain compensation of 3 dB. For data conversion, the base thresholds
were set at 2100 dB in the 40 log R (SED) and 20 log R
(amplitude) echograms.
The recorded echosounder data were post-processed by
erasing disturbances attributable to waves, false bottom
echoes, and probes during CTD sampling from the
echograms. Fish echoes were separated from background
noise by including only SEDs within the range from 280 to
260 dB. To determine the spatial distribution of fish
larvae, the post-processed echograms from the crosssectional lake transects were horizontally divided into
subtransects of lengths of 100 m and vertically into bins
of 1-m thickness. For each cell of this 100 3 1-m grid the
volume density of SEDs was calculated by scaling the
volume backscatter coefficient sv by the mean backscattering cross section sbs (Simmonds and MacLennan 2005;
Balk and Lindem 2006). With this feature, only the echo
energy from the SED is integrated, which reduces the
contribution of noise to the estimation of fish larvae density
(Simmonds and MacLennan 2005; Balk and Lindem 2006).
The lower signal threshold of integrated SED was set to
280 dB, including small echoes from young-of-the-year
fish as well as echoes from larger individuals. At this time
of the year the pelagic fish community in Lake Constance is
dominated by larval burbot Lota lota, perch Perca
1310
Rinke et al.
fluviatilis (Wang and Appenzeller 1998), and age 1+ lake
whitefish (C. lavaretus; Appenzeller 1998).
Meteorological conditions and drifters—Meteorological
conditions (air temperature, wind velocity, and wind
direction) were measured by the German Weather Service
at the Konstanz station. Measurements were provided as
hourly averaged values.
At the time of peak wind velocities on 08 May 2007
(Table 1) a set of three drifters was deployed in the bay of
Friedrichshafen (large bay at the center of the northern
shore in the vicinity of the thermistor T2). Drifters (Fig. 1)
consisted of a small floating buoy, equipped with a GPS
connected to a data logger, which was tied to a suspended
drifting canvas by a fine line (4 mm diameter). The canvas
was made of open cylindrical plastic tubes (diameter 0.5 m,
length 2.5 m) that had both ends fixed to metal rings. In
this configuration the drifting canvas was floating within
the depth layer between 5 and 7.5-m depth. The position of
the drifters was logged every 5 s. Location precision of the
GPS receiver was estimated to be approximately 1 m. The
drifting velocity was calculated by comparing position
shifts within time intervals of 10 min over the whole time
series of GPS recordings.
Statistical methods—We analyzed the lake-wide horizontal distribution of temperature and chlorophyll by
calculating Moran’s I spatial autocorrelation coefficient
(Cliff and Ord 1981) using depth-averaged values between 0
and 15-m depth. We chose this depth range because most of
the variability in the horizontal plane was observed within
these depths. The index quantifies the degree of spatial
autocorrelation between observations within a definite
distance range and can take values between 21 (negative
autocorrelation) and +1 (positive autocorrelation). A lack
of spatial autocorrelation is indicated by values close to
zero. The analysis for spatial patterns is based on
calculating Moran’s I for distinct distance classes covering
the entire range of Euclidean distances between the
sampling stations. Because we sampled 48 locations per
campaign, overall 48 3 47 combinations of sampling
locations existed, resulting in 2256 distance measures. We
used 11 distance classes and defined upper and lower
bounds of the classes in such a manner that each class
contained a similar number of sampling location combinations (approximately 205 combinations per class; PinelAlloul et al. 1999). The distances of sampling point
combinations in our data set varied over three orders of
magnitude ranging from 50 m to over 60 km. Significance
of the spatial autocorrelation index was tested by a
randomized Moran’s test for spatial autocorrelation (Cliff
and Ord 1981). This procedure includes the estimation of
the expectation value of Moran’s I for random spatial
distributions (usually slightly less than zero; see Table 2)
and its variance. All calculations were performed with the
spdep package (v0.4-17, function moran.test) within the R
environment (R 2.6.2; R Development Core Team 2008).
Because the significance test was performed for each
distance class, we applied a Bonferroni correction of the
significance level, i.e., a 5 0.05/11. We checked for spurious
Limnology limn-54-04-41.3d 4/5/09 15:23:02
1310
significance by comparing the results from the randomized
test with a permutation test (function moran.mc). Spatial
scales of distribution patterns were identified by correlograms plotting Moran’s I of each distance class against the
median of the distance class.
For further analyzing spatial autocorrelation of chlorophyll and temperature and for testing whether chlorophyll
concentrations were still spatially structured when the
effect of water temperature on chlorophyll distribution was
accounted for, we calculated Mantel tests and partial
Mantel tests with the vegan package in R (v1.13-1, function
mantel and mantel.partial). For statistical testing we used a
permutation-based test with 1000 permutations. The
resulting standardized Mantel statistic was calculated as a
Pearson-based product moment correlation.
Because zooplankton and fish distributions were not
recorded on all transects (see Table 1) and thus no lakewide distribution data were available as for temperature
and chlorophyll, we did not apply spatial autocorrelation
analysis to these data. We rather used linear models and
analysis of covariance (ANCOVA) for studying which
environmental factors explain the observed variability in
zooplankton and fish abundances. Note that because of
spatial autocorrelation in our data, the p values of the
ANCOVAs have to be interpreted carefully. Results from
ANCOVAs should rather be interpreted in an explorative
manner as a measure to assess the relative importance of
the different environmental factors. In a first step, we
compared spatial distributions of fish and zooplankton at
transects C and D on 10 and 16 May 2007. For that
analysis, ADCP and echosounder data from both transects
were aggregated into segments of 100 m in the horizontal
dimension and 0.6 m in the vertical dimension. In a second
step, vertical fish and zooplankton distributions at the
CTD sampling sites were extracted from the hydroacoustics
data in order to allow a comparison with the chlorophyll
and temperature distributions. A consistent dataset containing temperature, chlorophyll, and zooplankton could
thus be achieved from sampling stations at transects C and
D on 25 April as well as on 3, 10, and 16 May 2007. A
consistent dataset for those variables and fish, in addition,
could be generated from sampling stations at the same
transects on 10 and 16 May 2007. We used Akaike
information criteria (AIC) for choosing among competing
linear models. The preferred model is indicated by the
lowest AIC value.
Results
The period covered by our measurement campaign
was characterized by very different meteorological conditions. Although during the first half only low wind
velocities of varying directions prevailed, a major storm
event with strong westerly winds occurred between 08
and 10 May 2007 (Fig. 2). At this time, wind velocities
of up to 10 m s21 were reached and wind direction
remained almost constant. After the storm event, wind
velocities were lower and more variable but rarely exceeded
5 m s21.
Cust # 08-241
Lake-wide organism distribution
1311
Table 2. Calculated Moran’s I spatial autocorrelation coefficients for all 11 distance classes, including the statistically derived
estimates of the expectation value, the variance, and the significance level. Significant values of Bonferroni-corrected Moran’s I are set in
bold type. The analysis was performed for depth-averaged temperature and chlorophyll values (0–15-m depth) for 10 and 16 May 2007.
Variable
Distance (km)
Moran’s I
Expectation
Variance
p
Temperature 10 May 07
1.8
7.7
10.2
12.9
16.9
19.6
23.9
28.6
35.0
39.4
51.1
1.8
7.7
10.2
12.9
16.9
19.6
23.9
28.6
35.0
39.4
51.1
1.8
7.7
10.2
12.9
16.9
19.6
23.9
28.6
35.0
39.4
51.1
1.8
7.7
10.2
12.9
16.9
19.6
23.9
28.6
35.0
39.4
51.1
0.839
0.430
0.441
0.529
0.207
0.088
0.114
20.131
20.570
20.677
20.805
0.585
0.390
0.372
0.462
0.249
0.023
0.000
20.183
20.597
20.616
20.457
0.784
0.569
0.349
0.298
20.011
0.137
0.162
20.450
20.581
20.691
20.374
0.519
0.355
20.056
20.003
20.261
20.321
20.308
20.276
20.071
0.323
0.100
20.021
20.024
20.026
20.027
20.029
20.027
20.026
20.027
20.022
20.025
20.038
20.021
20.024
20.026
20.027
20.029
20.027
20.026
20.027
20.022
20.025
20.038
20.021
20.024
20.026
20.027
20.029
20.027
20.026
20.027
20.022
20.025
20.038
20.021
20.024
20.026
20.027
20.029
20.027
20.026
20.027
20.022
20.025
20.038
0.0093
0.0090
0.0089
0.0088
0.0081
0.0084
0.0086
0.0091
0.0089
0.0087
0.0061
0.0091
0.0089
0.0088
0.0087
0.0080
0.0083
0.0084
0.0089
0.0087
0.0086
0.0060
0.0088
0.0085
0.0084
0.0083
0.0076
0.0079
0.0081
0.0085
0.0084
0.0082
0.0056
0.0086
0.0083
0.0082
0.0080
0.0074
0.0077
0.0079
0.0083
0.0082
0.0080
0.0055
,0.001
,0.001
,0.001
,0.001
0.009
0.209
0.129
0.274
,0.001
,0.001
,0.001
,0.001
,0.001
,0.001
,0.001
0.002
0.580
0.774
0.099
,0.001
,0.001
,0.001
,0.001
,0.001
,0.001
,0.001
0.837
0.065
0.036
,0.001
,0.001
,0.001
,0.001
,0.001
,0.001
0.734
0.787
0.007
,0.001
0.001
0.006
0.592
,0.001
0.061
Chlorophyll 10 May 07
Temperature 16 May 07
Chlorophyll 16 May 07
Distribution of temperature, chlorophyll, and zooplankton
before the storm—On 25 April we found the thermocline to
be shallower on the northern shore than in the center of the
lake and at the southern shore (Fig. 3). The vertical
distribution of zooplankton over the transect (Fig. 4)
followed the pattern of the thermocline depth, and the
zooplankton was concentrated in a shallow surface layer
(,10 m) on the northern shore, whereas in the center and
on the southern shore zooplankters were abundant down to
greater depths (.10 m). High zooplankton abundances
were restricted to the epi- and metalimnion, and the spatial
distribution of zooplankton showed a pattern similar to
the temperature distribution. A comparable pattern of the
Limnology limn-54-04-41.3d 4/5/09 15:23:02
1311
Cust # 08-241
zooplankton distribution was observed on 03 May, when
the thermocline was tilted towards the southern shore. On
both sampling dates, chlorophyll concentrations peaked in
the lower metalimnion. However, on 03 May this
chlorophyll peak in the lower metalimnion was particularly
pronounced on the southern shore, forming a thin layer
structure (Fig. 3). Zooplankton was observed to aggregate
within this distinct, chlorophyll-rich layer, forming itself a
thin layer at a depth of approximately 18 m (Fig. 4). The
temperature profiles at these southern locations at transect
D were characterized by a particular steep temperature
gradient in the thermocline (about 2.5 K m21). Zooplankton abundance was low within this layer and aggregated
1312
Rinke et al.
Fig. 2. Wind direction (upper panel) and velocity (lower
panel) at the Konstanz station during the field campaign.
Triangles mark sampling dates of the field campaigns.
only below (at low temperature but high chlorophyll
concentration) or above (at high temperature but low
chlorophyll concentration).
One day before the storm started, the sampling along the
longitudinal transect showed a heterogeneous distribution
of temperature and chlorophyll (on 07 May; Fig. 5).
Maximal chlorophyll concentrations varied between 2.5
and 4 mg L21 and surface temperatures varied between
12.5uC and 16uC. The northwestern basin of the lake was
characterized by slightly warmer water temperature and
markedly higher chlorophyll concentrations in the upper
30 m. In the center and the eastern part of the lake,
temperature and chlorophyll concentration were lower and
most chlorophyll was found in subsurface layers in close
association with the thermocline. The vertical position of
the thermocline was irregular along the longitudinal
section, indicating internal wave activity.
Effects of the storm on distribution patterns—The wind
force of the storm event between 08 May and 10 May 2007
induced strong surface currents downwind, i.e., in the
eastern direction. Drifters deployed on 08 May 2007 were
transported in southeastern directions along a rounded
drifting path and reached maximum velocities of
0.21 m s21. Average drifting velocities were in the range
between 0.12 and 0.15 m s21 (Table 3). As a consequence
of the storm, strong upwelling occurred in the western part
of the lake, inducing rapid reductions in surface temperatures (see thermistor recordings at locations T1, T5, and
T2, Fig. 6). The drop in temperature at T2 was less
pronounced than at the other two locations, indicating that
T2 was close to the maximum spatial extension of the
upwelling in the westward direction.
The effect of the storm event on lake-wide distribution of
temperature and chlorophyll concentration was still
prominent during the campaign at 10 May 2007. The very
Limnology limn-54-04-41.3d 4/5/09 15:23:03
1312
intense upwelling in the western part of the lake led to the
formation of an internal front in the horizontal plane
separating cold, hypolimnetic water with low chlorophyll
concentrations on the western side from warm, epilimnetic,
and chlorophyll-rich water on the eastern side (Fig. 7).
When using the isotherm of 8uC as separator between
hypolimnetic and epilimnetic water, approximately 27% of
the lake’s surface was covered by hypolimnetic water.
Maximum temperature and maximum chlorophyll concentrations were observed at the far eastern bay of the lake
because of the wind transport. As a consequence,
horizontal variation in the vertical temperature distribution
was high on that day, and surface temperatures ranged
from 6uC to 15uC (Fig. 8). Spatial chlorophyll distribution
showed a highly similar pattern. Because high chlorophyll
concentrations and temperatures could be observed only in
surface waters having an epilimnetic origin, vertically
averaged (upper 15 m) temperatures and chlorophyll
concentrations correlated positively (R2 5 0.71, F1,46 5
114.7, p , 0.001; Fig. 8C).
Because of the unidirectional wind forcing, the Mantel
test showed a highly significant spatial autocorrelation in
the horizontal distribution of vertically averaged chlorophyll and temperature (Table 4). However, when horizontal distribution of chlorophyll was corrected for the
variability attributable to temperature, spatial autocorrelation of chlorophyll was no longer detectable (partial
Mantel test, rM 5 0.02, p 5 0.35). This result indicates that
distributions of phytoplankton and temperature were
similar to each other and statistically not independent
from each other because both were simultaneously driven
by wind forcing. Correlograms with Moran’s I provided a
deeper insight into spatial autocorrelation of the lake-wide
horizontal distribution of temperature and chlorophyll
(using depth-averaged values) on 10 May (Fig. 9; Table 2).
They indicated high positive spatial autocorrelation over
short distances (,15 km) and negative spatial autocorrelation over long distances (.30 km). Because the storm
event was the driving force for the horizontal distribution
and affected temperature and chlorophyll simultaneously,
values of Moran’s I for temperature and chlorophyll over
all distance classes were positively correlated to each other
with high significance (R2 5 0.95, F1,9 5 172.7, p , 0.001).
On 10 May the internal front separating hypolimnetic
from epilimnetic water (compare Fig. 7) crisscrossed
transect D. Although in the center of transect D cold
hypolimnetic water with almost no phytoplankton was
found, warm epilimnetic water with higher chlorophyll
content remained on the shores (Fig. 3). This characteristic
signature was congruently mirrored in the zooplankton
distribution (Fig. 4). In the central reach of the transect, the
backscattering intensity at the surface was as low as in the
hypolimnion, whereas near the shores high backscattering
intensities were recorded in the upper water layers,
indicating high zooplankton abundance in these regions
(approximately up to distances of 3 km away from the
shoreline). The effects of the tongue-shaped internal front
of upwelled hypolimnetic water were also noticeable in the
spatial distribution of larval fish (Fig. 10), which was
consistent with our observations of plankton distributions.
Cust # 08-241
Lake-wide organism distribution
Fig. 3.
1313
Vertical profiles of water temperature and chlorophyll concentration at transect D for all four sampling dates.
In the center of the transect, where water temperatures were
low, only low abundances of fish were found, whereas high
fish densities were recorded near the shores, especially close
to the northern shore.
Distribution patterns 1 week after the storm—One week
after the storm (16 May) there was still a temperature
gradient from east to west, with warmer water in the
Limnology limn-54-04-41.3d 4/5/09 15:23:04
1313
Cust # 08-241
eastern basin, but no internal front was visible (Fig. 7). A
patch of cold water was observed at the northern shore of
transect C, indicating local upwelling. At this location
chlorophyll concentrations were also lower than elsewhere.
However, lake-wide distribution of chlorophyll concentration showed a more complex pattern and was not as
strongly associated with temperature as observed on 10
May 2007. Although average temperature and average
1314
Rinke et al.
Fig. 4. Horizontal and vertical variation of ADCP backscattering intensity as a proxy for
spatial distribution of cladoceran zooplankton at transect D on all sampling dates.
chlorophyll showed again a positive correlation (Fig. 8F;
R2 5 0.27, F1,46 5 17.3, p , 0.001), the significance of this
relationship disappeared if the three cold profiles from the
northern edge of transect C were removed (R2 5 0.01, F1,43
5 0.6, p 5 0.45). Whereas the spatial variation in vertical
temperature profiles appeared to decrease from 10 May to
16 May, the spatial variation in chlorophyll profiles
remained almost the same (Fig. 8). This pattern became
even more prominent if the variability of temperature and
Limnology limn-54-04-41.3d 4/5/09 15:23:04
1314
chlorophyll in the horizontal plane (i.e., using depthaveraged values) was considered (Fig. 9A,D). Although
variance in depth-averaged temperature decreased significantly between 10 May and 16 May (one-sided F-test, F47
5 2.19, p 5 0.004) the variance in depth-averaged
chlorophyll concentrations even increased (one-sided Ftest, F47 5 0.56, p 5 0.026).
A Moran correlogram for water temperature on 16 May
revealed a similar pattern as on 10 May, with positive
Cust # 08-241
Lake-wide organism distribution
1315
Fig. 5. Spatial distribution of temperature and chlorophyll along the longitudinal cross section sampled on 07 May 2007. Triangles
at the surface indicate the locations of the samplings (n 5 26).
autocorrelation over short distances and negative autocorrelation over long distances. This was a consequence of the
still-prominent temperature gradient along the west–east
axis. Accordingly, the Mantel test also indicated highly
significant spatial autocorrelation, which was not the case
for chlorophyll (Table 4). Hence, the Moran correlogram
for chlorophyll was different from the one for temperature
and showed positive spatial autocorrelation only over very
short and very long distances, whereas negative spatial
autocorrelation was evident for medium distance ranges
(around 20 km; Fig. 9F). As a consequence, values of
Moran’s I for temperature and chlorophyll over all distance
classes were not correlated with each other on 16 May (R2
5 0.08, F1,9 5 0.78, p 5 0.40), indicating that temperature
development and chlorophyll dynamics were controlled by
different environmental factors.
The vertical structures of temperature and chlorophyll
became less heterogeneous along transect D 1 week after
the storm and the thermocline was tilted towards the north,
similar to the period prior to the storm event (Fig. 3).
Chlorophyll concentrations increased in comparison to the
week before and maximal concentrations were always
recorded above the thermocline. Zooplankton and fish
were found over the whole transect in the upper 15–20 m,
but showed distinctly higher abundances in regions not
farther than 2.5 km from the shoreline (Figs. 4, 10). We
again observed a thin layer of zooplankton in depths
between 15 and 20 m below a rather steep temperature
Table 3.
gradient in the thermocline. However, no deep chlorophyll
maximum at those depths was observable.
Environmental factors explaining variability in distribution patterns of higher trophic levels—Spatial distributions
of zooplankton and fish along transects C and D on 10 and
16 May 2007 showed remarkably similar patterns. For a
linear model between fish density and zooplankton
concentration, an ANCOVA indicated a highly significant
relationship (Table 5). Taking data from both dates and
transects together, zooplankton density explained 20% of
the variability in fish densities. When calculating this linear
model for each date and transect separately (Table 5), a
clear difference became apparent between 10 and 16 May.
Directly after the storm (10 May 2007) zooplankton and
fish densities were only weakly correlated and coefficients
of determination were below 0.1. However, 1 week after the
storm (16 May 2007), zooplankton and fish densities were
closely related to each other and coefficients of determination were above 0.4.
Combining the hydroacoustic data with the data
obtained by the vertical profiling enabled us to quantify
the effects of depth, temperature, and chlorophyll on
zooplankton and fish density. Zooplankton density was
highly correlated with water depth and temperature
(Table 6), but showed a much weaker relationship with
chlorophyll concentration. However, in a multifactorial
ANCOVA all three factors were highly significant and
Initial and final positions of drifters and the calculated average drifting velocities.
Drifter
Starting position
Final position
Drifting velocity mean (m s21) 6 SD
1
2
3
47.613uN, 9.481uE
47.604uN, 9.490uE
47.619uN, 9.484uE
47.596uN, 9.489uE
47.581uN, 9.500uE
47.598uN, 9.499uE
0.124 6 0.023 (n 5 3977)
0.151 6 0.022 (n 5 3657)
0.154 6 0.039 (n 5 3596)
Limnology limn-54-04-41.3d 4/5/09 15:23:18
1315
Cust # 08-241
1316
Rinke et al.
zooplankton abundance (F1,1014 5 10.4, p 5 0.001) and the
significance of this relationship was in the same order as
that of chlorophyll concentration (F1,1014 5 8.64, p 5
0.003).
Fish density showed highly significant correlations with
water depth and temperature, chlorophyll, and zooplankton concentration (Table 6). Again, a multifactorial model
with all factors was the preferred model, as indicated by
AIC, and explained 34% of the variability in fish density.
The significance of the abiotic factors water depth and
temperature for fish distribution was high in comparison to
that of the biotic factors chlorophyll and zooplankton,
whereas the latter explained more variance than chlorophyll. When the same analysis was conducted separately
with data collected on 10 or 16 May 2007, the significance
of zooplankton was higher on 16 May in comparison to 10
May (the F values for the zooplankton in the respective
ANCOVA were F1,438 5 19.2 on 10 May and F1,571 5 89.1
on 16 May).
Discussion
Fig. 6. Time series of water temperature measured by
thermistors T1–T5 (locations of the thermistors are given in
Fig. 1). The triangles on the top of each panel indicate the four
sampling dates. Note that the storm event was between the second
and third samplings and that the lake-wide campaigns were
conducted on 10 and 16 May 2007 (i.e., samplings 3 and 4).
explained 68% of the variability in zooplankton densities.
The AIC showed that the full model with all factors
included was the preferred model (Table 6). When the same
analysis was repeated with those data collected exclusively
on 10 May 2007, i.e. at the end of the storm event, we
found chlorophyll to be not significant (F1,665 5 2.46, p 5
0.12), whereas it was highly significant when applying the
data collected 1 week after the storm on 16 May 2007
(F1,655 5 12.8, p , 0.001). Finally, we included fish density
in this data set as a further independent variable and
repeated the ANCOVA (Table 6). Note that this data set
necessarily contained only data collected on transects C
and D on 10 and 16 May 2007, when fish distribution was
recorded. Fish density was a highly significant factor for
Limnology limn-54-04-41.3d 4/5/09 15:23:22
1316
Our study provides information about lake-wide spatial
distributions of temperature, plankton, and fish and
documents the importance of physical processes for lakewide transport of planktonic organisms. The spatial
distributions of temperature and biota appeared to be
highly dynamic on the ecosystem scale. In the study period
from 25 April to 16 May 2007, a strong storm event
induced a downwind drift of the epilimnion and strong
upwelling at the upwind side of the lake, and consequently
led to the formation of an internal front in the horizontal
plane. Directly after the storm, 27.5% of the lake surface
consisted of cold, chlorophyll-depleted hypolimnetic water.
Assuming an average thermocline depth of 15 m, this
internal front is the result of an eastward displacement of
about 6.4 km3 of epilimnetic water. By extrapolating the
water current velocities measured by the drifters, it can be
estimated that during the 2 d of its highest intensity the
storm provoked horizontal displacements over distances of
more than 25 km, which fits with our observations.
A steering role of hydrodynamic processes on the
distribution of pelagic organisms is well documented
(George and Winfield 2000; Marce et al. 2007; Serra et al.
2007). An indirect effect from wind forcing is mediated by
internal wave activity inducing local upwelling (Fig. 7),
tilting of the thermocline (Fig. 3), and the accompanying
changes in the vertical distributions of planktonic organisms like algae or zooplankters (Hedger et al. 2004; Rinke
et al. 2007). Both direct and indirect effects of wind forcing
lead to increased vertical mixing and thus to an upward
flux of nutrients promoting phytoplankton growth after the
storm event. The latter was also observed in our campaign,
in which we found higher chlorophyll concentrations 1
week after the storm. Although chlorophyll maxima were
observed always below the thermocline before the storm,
they were found above the thermocline afterwards.
Although our results document the steering role of
external forcing by wind and hydrodynamic processes on
spatial distributions of organisms, we found at the same
Cust # 08-241
Lake-wide organism distribution
1317
Fig. 7. Lake-wide horizontal distribution patterns of temperature and chlorophyll at a depth of 5 m on 10 May 2007 and 16
May 2007.
time clear evidence for internal biological factors leading to
patchy distributions of organisms. This statement is
justified by the results from our multifactorial statistical
model analyses of spatial distributions of zooplankton and
fish (Table 6). Although we in these models explicitly
controlled for the effects of depth and temperature on
organism distributions, i.e. the effects of large-scale
physical forcing, we still found a significant effect of
biological drivers on organism distributions. For example,
chlorophyll concentration significantly affected zooplankton density or zooplankton density significantly affected
fish density. These effects from internal, biotic factors
became particularly apparent when the strength of external
forces was low, i.e., the correlation between zooplankton
and fish distributions became more significant when the
wind-induced currents and the resulting advection of both
Fig. 8. Vertical profiles of (A, D) temperature and (B, E) chlorophyll measured during the lake-wide campaigns on 10 May (upper
panels, 1 d after the storm event) and 16 May 2007 (lower panels, 1 week after the storm event). All profiles of the 48 sampling locations
are plotted together in each panel. The panels C and F depict depth-averaged temperatures (0–15-m depth) plotted against depthaveraged chlorophyll concentrations for both sampling times. Lines depict linear regressions (regression statistics are given in the text).
Limnology limn-54-04-41.3d 4/5/09 15:23:23
1317
Cust # 08-241
1318
Rinke et al.
Table 4. Results of Mantel tests for spatial distributions of vertically averaged (0–15 m) chlorophyll (Chl) and temperature (Temp)
data. Sampling positions were converted to x–y coordinates (x–y). For the measurements taken on 10 May 2007, a partial Mantel test
between chlorophyll concentration and coordinate was calculated while controlling for the spatial distribution of temperature.
Variable 1
Variable 2
Variable 3 (partial)
Mantel statistic rM
p
Temp 10 May 2007
Chl 10 May 2007
Chl 10 May 2007
Temp 16 May 2007
Chl 16 May 2007
x–y
x–y
x–y
x–y
x–y
—
—
Temp 10 May 2007
—
—
0.699
0.475
0.0191
0.441
20.035
,0.001
,0.001
0.347
,0.001
0.697
groups had ceased on 16 May 2007. Likewise, at this date
the distribution of phytoplankton and temperature maxima
did not overlap, indicating that different processes are
responsible for the spatial distribution patterns of temperature and chlorophyll under low wind conditions. Maximal
phytoplankton concentrations were found at shallow
locations where tributaries enter the system, whereas
temperature was still maximal in the far-eastern bay of
the lake (Fig. 7). Nutrient inputs by tributaries lead to local
eutrophication and might promote phytoplankton growth.
We further hypothesize that algal growth may have been
enhanced in shallow regions as a consequence of improved
light supply and locally elevated nutrient concentrations
because of nutrient release from littoral sediments.
In contrast to this, when external forcing is strong, e.g.,
during a storm event as in our study, distribution patterns
of biota are almost entirely under the control of winddriven hydrodynamics. Because external forcing affects
both temperature and organisms simultaneously, spatial
distributions of temperature and organisms are similar to
each other and closely related. These findings also comply
with the MDFH (Pinel-Alloul 1995); we found biotic and
abiotic processes acting together on spatial distributions of
organisms. Although abiotic processes (e.g., the storm
event) affected distributions over the whole ecosystem, i.e.,
at large spatial scales, biotic processes became more
important on local scales, as exemplified by increasing
chlorophyll concentrations in shallow regions or by vertical
distribution of zooplankton. A new aspect our data can
add to the MDFH is that internal, biotic processes acting
on organism distributions are hardly observable when
external forcing is very strong, e.g., because of heavy storm
events.
During both lake-wide campaigns we found a west–east
gradient in water temperature, with the warmest water in
eastern bay of the lake. This seems to be a typical feature of
Lake Constance: by comparing temperatures from the
thermistor recordings at T1 and T3, we found that in 71%
of the total time span covered by the thermistor recordings
the water temperature at the eastern part was higher than at
the western part of the lake. The average difference in water
temperature between both sites was 0.93 K and was highly
Fig. 9. Statistical analyses of depth-averaged (0–15 m) temperature (A–C) and chlorophyll concentrations (D–F) measured on 10
and 16 May 2007. (A, D) Box plots show median, 25th and 75th percentiles, and data range. Correlograms showing Moran’s I spatial
autocorrelation coefficient plotted against distance are given for (B, C) temperature and (E, F) chlorophyll for both sampling dates of the
lake-wide campaign. Significance of Moran’s I is indicated by closed dots.
Limnology limn-54-04-41.3d 4/5/09 15:23:27
1318
Cust # 08-241
Lake-wide organism distribution
1319
Fig. 10. Horizontal and vertical distribution of fish (in individuals 1000 m23) at transect D
at 10 May (1 d after the storm event) and 16 May 2007 (1 week after the storm event).
significant (Welch two-sample t-test, t 5 52.5, df 5 220,
140, p , 0.001).
The strong effect of wind-induced water currents on the
distribution of organisms is ultimately related to the fact
that phyto- and zooplankton as well as juvenile fish
aggregate in the epilimnion. While algae rely on light
availability for photosynthesis, zooplankton and fish
prefer the epilimnion because of increased resource
availability and warmer temperatures. Because birth
rates of zooplankters are highly sensitive to temperature
(Rinke and Petzoldt 2003), it is a common phenomenon
that zooplankton concentrates in the epilimnion (unless
they perform diel vertical migration, which is the case in
Lake Constance during late spring and summer; Stich
1989).
Whereas the occurrence of warmer temperature is
obviously restricted to the epilimnion, this is not necessarily
the case for phytoplankton. We often found deep
chlorophyll maxima at the lower end of the metalimnion,
i.e., at relatively cold water temperatures. In these
situations, zooplankton face a dilemma because high food
availability and good temperature conditions are spatially
separated. Experiments in plankton towers revealed that in
this situation zooplankters maximize their fitness by
spending a part of their time in the warm, food-depleted
epilimnion and the remaining time below the thermocline
where food concentrations are maximal (Lampert et al.
2003; Kessler 2004) Our observations of zooplankton
distributions in Lake Constance provide field evidence for
this experimental finding. At places with a high chlorophyll
concentration below the thermocline, we found zooplankton forming a thin layer in exactly this depth (compare
Figs. 3 and 4). Such thin layers have recently received
increased attention in marine ecology, and meanwhile a
body of evidence has emerged that they are frequently
occurring phenomena (Dekshenieks et al. 2001; McManus
et al. 2003).
At the time of our campaign, the most abundant fish in
the pelagic zone of Lake Constance were larval burbot (L.
lota) feeding almost exclusively on zooplankton (Wang and
Appenzeller 1998), whereas perch (P. fluviatilis) had not yet
experienced peak hatching at that time in 2007 (W. N.
Table 5. Linear models with zooplankton density (as backscattering strength, dB) as independent variable and fish density (ind 3
1000 m23) as response variable. Fish densities were log(n + 1) transformed.
Transect
C
D
C
D
All
Date
10
10
16
16
Limnology limn-54-04-41.3d 4/5/09 15:23:27
May 2007
May 2007
May 2007
May 2007
All
1319
Cust # 08-241
F
p
R2
F1,3730 5 4.0
F1,5657 5 431.7
F1,3688 5 3850
F1,5749 5 4132
F1,18830 5 4744
0.046
,0.001
,0.001
,0.001
,0.001
0.001
0.07
0.51
0.42
0.20
1320
Rinke et al.
Table 6. Linear models calculated with zooplankton density and fish density, respectively, as response variables and different
independent variables. Each independent factor was first tested separately in a one-factorial model and afterwards in a multifactorial
model with all factors included. Models were compared by Akaike Information Criteria (AIC). Fish densities were log(n + 1) transformed.
Independent variable
F
p
Zooplankton density (as backscattering strength, dB) as response variable
One-factorial models
Temperature
F1,2595 5 3255
,0.001
,0.001
Depth
F1,2671 5 4158
Chlorophyll
F1,2595 5 113.7
,0.001
Multifactorial model without fish
Temperature
F1,2593 5 4502
,0.001
Depth
F1,2593 5 983
,0.001
Chlorophyll
F1,2593 5 14.4
,0.001
Multifactorial model with fish (only data from transects C and D on 10 and 16 May 2007)
Temperature
F1,1014 5 1025
,0.001
Depth
F1,1014 5 288.0
,0.001
Chlorophyll
F1,1014 5 8.64
0.003
Fish
F1,1014 5 10.42
0.001
Fish density (individuals 3 1000
One-factorial models
Temperature
Depth
Chlorophyll
Zooplankton
Multifactorial model
Temperature
Depth
Chlorophyll
Zooplankton
m3 )
R2
AIC
0.56
0.61
0.04
14,281.7
14,366.5
16,281.1
0.68
13,440.9
0.57
5189.2
as response variable
F1,1024
F1,1087
F1,1024
F1,1037
5
5
5
5
392.5
445.8
238.5
325.5
,0.001
,0.001
,0.001
,0.001
0.28
0.29
0.19
0.24
3535.3
3797.5
3653.5
3641.7
F1,1014
F1,1014
F1,1014
F1,1014
5
5
5
5
419.3
85.7
7.2
10.4
,0.001
,0.001
0.007
0.001
0.34
3418.4
Probst unpubl.). The observed individual echo strengths
during our campaign varied between 268 and 278 dB,
which also points to larval burbot as dominating fish in the
pelagic zone. Although the swimming capacity of larval
burbot is high enough to allow the active selection of
preferred depths, our observations indicate that burbot
larvae are not able to withstand large-scale circulation
patterns.
Because theoretical studies have revealed that spatial
heterogeneity in ecosystems affects species interactions and
diversity and thus affects community dynamics and
biomass production (Bascompte and Solé 1995; Hastings
2001; Brentnall et al. 2003), we assume that the observed
complex patterns in spatial distribution of organisms in
lakes, and their dynamics, influence ecosystem functioning.
Spatial heterogeneity increases the variety of available
ecological niches and keeps ecosystem dynamics in a
transient state far away from equilibrium (Hastings 2004).
We see a strong need for more studies providing detailed
synoptical information about spatial distribution of abiotic
and biotic variables in lakes. This will pave the way to a
better understanding of spatial and temporal distributions
and their influence on lake ecology. Accordingly, the
simulation of spatial effects on plankton community
dynamics will be a promising field for future research,
and may help to generate testable hypotheses on spatial
variability of organisms and their effects on ecosystem
functioning. A first approach to this may be to compare
model outputs from classical one-dimensional, coupled
hydrodynamic–ecological models (Bruce et al. 2006; Peeters
Limnology limn-54-04-41.3d 4/5/09 15:23:31
1320
et al. 2007) with the results obtained from three-dimensional models (Robson and Hamilton 2004).
Acknowledgments
We thank the crews of the research vessels involved in the field
campaigns. Gregor Thomas, Miriam Windler, Julia Rottberger,
Klaus Zanker, and Patrick Lang helped to conduct the field
measurements. Two anonymous reviewers and Frank Peeters
provided valuable comments to an earlier version of the
manuscript. Andreas Lorke provided support on the analysis of
the Acoustic Doppler Current Profiler data. We thank Roger
Bivand for his help on the statistics and for providing the spdep
package in R. The German Weather Service (Deutscher Wetterdienst, DWD) kindly provided meteorological data for the
Konstanz station. We are grateful to financial support by the
German Science Foundation (DFG, Deutsche Forschungsgemeinschaft) and the Federal Ministry of Education and Research
(BMBF, Bundesministerium für Bildung und Forschung) to the
BodenseeOnline-Project (grants Ro 1008/11-1, Ko 528/19, and
02WT00552). A.M.R.H. was financially supported by DFG under
grant Lo 1150/2-2.
References
ABRAHAM, E. R. 1998. The generation of plankton patchiness by
turbulent stirring. Nature 391: 577–580.
ANNEVILLE, O., S. SOUISSI, S. GAMMETER, AND D. STRAILE. 2004.
Seasonal and inter-annual scales of variability in phytoplankton assemblages: Comparison of phytoplankton dynamics in
three peri-alpine lakes over a period of 28 years. Freshw. Biol.
49: 98–115.
Cust # 08-241
Lake-wide organism distribution
APPENZELLER, A. R. 1998. Persistent large scale heterogeneity
of pelagic fish in upper Lake Constance and its possible
causes. Arch. Hydrobiol. Spec. Issues Adv. Limnol. 53:
303–316.
AVOIS, C., P. LEGENDRE, S. MASSON, AND B. PINEL-ALLOUL. 2000.
To what extent may the sampling strategy interfere with the
study of spatio-temporal variation of zooplankton communities? Can. J. Fish. Aquat. Sci. 57: 1940–1956.
BALK, H., AND T. LINDEM. 2006. SONAR5_Pro, version 5.9.6,
http://folk.uio.no/hbalk/sonar4_5/index.htm.
BASCOMPTE, J., AND R. V. SOLÉ. 1995. Rethinking complexity:
Modelling spatiotemporal dynamics in ecology. Trends Ecol.
Evol. 10: 361–366.
BÄUERLE, E., D. OLLINGER, AND J. ILMBERGER. 1998. Some
meteorological, hydrological, and hydrodynamical aspects
of Upper Lake Constance. Arch. Hydrobiol. Spec. Issues
Adv. Limnol. 53: 31–83.
BRENTNALL, S. J., K. L. RICHARDS, J. BRINDLEY, AND E. MURPHY.
2003. Plankton patchiness and its effect on larger-scale
productivity. J. Plankton Res. 25: 121–140.
BRUCE, L. C., D. HAMILTON, J. IMBERGER, G. GAL, M. GOPHEN, T.
ZOHARY, AND K. D. HAMBRIGHT. 2006. A numerical simulation of the role of zooplankton in C, N and P cycling in Lake
Kinneret, Israel. Ecol. Model. 193: 412–436.
CLIFF, A. D., AND J. K. ORD. 1981. Spatial Processes. Pion.
DEKSHENIEKS, M. M., P. L. DONAGHAY, J. M. SULLIVAN, J. E. B.
RINES, T. R. OSBORN, AND M. S. TWARDOWSKI. 2001.
Temporal and spatial occurrence of thin phytoplankton
layers in relation to physical processes. Mar. Ecol. Prog.
Ser. 223: 61–71.
ECKMANN, R., AND R. RÖSCH. 1998. Lake Constance fisheries and
fish ecology. Arch. Hydrobiol. Spec. Issues Adv. Limnol. 53:
285–301.
EGGERS, D. M. 1976. Theoretical effect of schooling by
planktivorous fish predators on rate of prey consumption. J.
Fish. Res. Board Can. 33: 1964–1971.
FIETZ, S., G. KOBANOVA, L. IZMESTEVA, AND A. NICKLISCH. 2005.
Regional, vertical and seasonal distribution of phytoplankton
and photosynthetic pigments in Lake Baikal. J. Plankton Res.
27: 793–810.
FOLT, C. L., AND C. W. BURNS. 1999. Biological drivers of
zooplankton patchiness. Trends Ecol. Evol. 14: 300–305.
GAEDKE, U. 1998. Functional and taxonomical properties of the
phytoplankton community of large and deep Lake Constance:
Interannual variability and response to re-oligotrophication
(1979–1993). Arch. Hydrobiol. Spec. Issues Adv. Limnol. 53:
119–141.
GEORGE, D. G., AND S. I. HEANEY. 1978. Factors influencing the
spatial distribution of phytoplankton in a small productive
lake. J. Ecol. 66: 133–155.
———, AND I. J. WINFIELD. 2000. Factors influencing the spatial
distribution of zooplankton and fish in Loch Ness, UK.
Freshw. Biol. 43: 557–570.
GÜDE, H., H. ROSSKNECHT, AND G. WAGNER. 1998. Anthropogenic
impacts on the trophic state of Lake Constance during the
20th century. Arch. Hydrobiol. Spec. Issues Adv. Limnol. 53:
85–108.
HANSKI, I. 1981. Coexistence of competitors in patchy environment with and without predation. Oikos 37: 306–312.
HASTINGS, A. 1988. Food web theory and stability. Ecology 69:
1665–1668.
———. 2001. Transient dynamics and persistence of ecological
systems. Ecol. Lett. 4: 215–220.
———. 2004. Transients: The key to long-term ecological
understanding? Trends Ecol. Evol. 19: 39–45.
Limnology limn-54-04-41.3d 4/5/09 15:23:33
1321
Cust # 08-241
1321
HEDGER, R., N. OLSEN, D. GEORGE, T. MALTHUS, AND P.
ATKINSON. 2004. Modelling spatial distributions of Ceratium
hirundnella and Microcystis in a small productive British lake.
Hydrobiologia 528: 217–227.
JONES, R. I., A. S. FULCHER, J. K. U. JAYAKODY, J. LAYBOURNPARRY, A. J. SHINE, M. C. WALTON, AND J. M. YOUNG. 1995.
The horizontal distribution of plankton in a deep, oligotrophic lake —Loch Ness, Scotland. Freshw. Biol. 33: 161–170.
KESSLER, K. 2004. Distribution of Daphnia in a trade-off between
food and temperature: Individual habitat choice and time
allocation. Freshw. Biol. 49: 1220–1229.
LACROIX, G., AND F. LESCHER-MOUTOUÉ. 1995. Spatial patterns of
planktonic microcrustaceans in a small shallow lake. Hydrobiologia 300/301: 205–217.
LAMPERT, W., E. MCCAULEY, AND B. F. J. MANLY. 2003. Tradeoffs in the vertical distribution of zooplankton: Ideal free
distribution with costs? Proc. R. Soc. Lond. B Biol. Sci. 270:
765–773.
LORKE, A., D. F. MCGINNIS, P. SPAAK, AND A. WUEST. 2004.
Acoustic observations of zooplankton in lakes using a
Doppler current profiler. Freshw. Biol. 49: 1280–1292.
MARCE, R., C. FEIJOO, E. NAVARRO, J. ORDONEZ, J. GOMA, AND J.
ARMENGOL. 2007. Interaction between wind-induced seiches
and convective cooling governs algal distribution in a canyonshaped reservoir. Freshw. Biol. 52: 1336–1352.
MASSON, S., N. ANGELI, J. GUILLARD, AND B. PINEL-ALLOUL. 2001.
Diel vertical and horizontal distribution of crustacean
zooplankton and young of the year fish in a sub-alpine lake:
An approach based on high frequency sampling. J. Plankton
Res. 23: 1041–1060.
MCMANUS, M. A., AND oTHERS. 2003. Characteristics, distribution
and persistence of thin layers over a 48 hour period. Mar.
Ecol. Prog. Ser. 261: 1–19.
PATALAS, K., AND A. SALKI. 1992. Crustacean plankton in Lake
Winnipeg—variation in space and time as a function of lake
morphology, geology, and climate. Can. J. Fish. Aquat. Sci.
49: 1035–1059.
PEETERS, F., D. STRAILE, A. LORKE, AND D. OLLINGER. 2007.
Turbulent mixing and phytoplankton spring bloom development in a deep lake. Limnol. Oceanogr. 52: 286–298.
PINEL-ALLOUL, B., AND A. GHADOUANI. 2007. Spatial heterogeneity
of planktonic microorganisms in aquatic systems, p. 203–310.
In R. B. Franklin and A. L. Mills [eds.], The spatial
distribution of microbes in the environment. Springer.
———, C. GUAY, N. ANGELI, P. LEGENDRE, P. DUTILLEUL, G.
BALVAY, D. GERDEAUX, AND J. GUILLARD. 1999. Large-scale
spatial heterogeneity of macrozooplankton in Lake of
Geneva. Can. J. Fish. Aquat. Sci. 56: 1437–1451.
PINEL-ALLOUL, P. 1995. Spatial heterogeneity as a multiscale
characteristic of zooplankton community. Hydrobiologia
300–301: 17–42.
POTHOVEN, S. A., G. L. FAHNENSTIEL, AND H. A. VANDERPLOEG.
2004. Spatial distribution, biomass and population dynamics
of Mysis relicta in Lake Michigan. Hydrobiologia 522:
291–299.
R DEVELOPMENT CORE TEAM. 2008. R: A language and environment for statistical computing [Internet]. R Foundation for
Statistical Computing [accessed 2008 November 12]. Available from http://www.r-project.org.
REYNOLDS, C. S. 1990. Temporal scales of variability in pelagic
environments and the response of phytoplankton. Freshw.
Biol. 23: 25–53.
RINKE, K., AND T. PETZOLDT. 2003. Modelling the effects of
temperature and food on individual growth and reproduction
of Daphnia and their consequences on the population level.
Limnologica 33: 293–304.
1322
Rinke et al.
———, AND oTHERS. 2007. How internal waves influence the
vertical distribution of zooplankton. Freshw. Biol. 52:
137–144.
ROBSON, B. J., AND D. P. HAMILTON. 2004. Three-dimensional
modelling of a Microcystis bloom event in the Swan River
estuary, Western Australia. Ecol. Model. 174: 203–222.
ROJO, C., AND M. ALVAREZ-COBELAS. 2001. Phytoplankton
structure and dynamics at a daily temporal scale: Response
to the thermal overturn. Arch. Hydrobiol. 151: 549–569.
ROVINSKY, A. B., H. ADIWIDJAJA, V. Z. YAKHNIN, AND M.
MENZINGER. 1997. Patchiness and enhancement of productivity in plankton ecosystems due to the differential advection of
predator and prey. Oikos 78: 101–106.
SERRA, T., J. VIDAL, X. CASAMITJANA, M. SOLER, AND J. COLOMER.
2007. The role of surface vertical mixing in phytoplankton
distribution in a stratified reservoir. Limnol. Oceanogr. 52:
620–634.
SIMMONDS, J., AND D. N. MACLENNAN. 2005. Fisheries acoustics—
theory and practice, 2nd ed. Blackwell.
STICH, H. B. 1989. Seasonal changes of diel vertical migrations of
crustacean plankton in Lake Constance. Arch. Hydrobiol.
Suppl. 83: 355–405.
———, AND A. BRINKER. 2005. Less is better: Uncorrected versus
pheopigment-corrected photometric chlorophyll-a estimation.
Arch. Hydrobiol. 162: 111–120.
Limnology limn-54-04-41.3d 4/5/09 15:23:34
1322
STRAILE, D., AND W. GELLER. 1998. Crustacean zooplankton in
Lake Constance from 1920 to 1995: Response to eutrophication and re-oligotrophication. Arch. Hydrobiol. Spec. Issues
Adv. Limnol. 53: 255–274.
THACKERAY, S. J., D. G. GEORGE, R. I. JONES, AND I. J. WINFIELD.
2004. Quantitative analysis of the importance of windinduced circulation for the spatial structuring of planktonic
populations. Freshw. Biol. 49: 1091–1102.
TURING, A. M. 1952. The chemical basis of morphogenesis. Philos.
Trans. R. Soc. Lond. B Biol. Sci. 237: 37–72.
WANG, N., AND A. APPENZELLER. 1998. Abundance, depth
distribution, diet composition and growth of perch (Perca
fluviatilis) and burbot (Lota lota) larvae and juveniles in the
pelagic zone of Lake Constance. Ecol. Freshw. Fish 7:
176–183.
WEBSTER, I. T., AND P. A. HUTCHINSON. 1994. Effect of wind on
the distribution of phytoplankton cells in lakes revisited.
Limnol. Oceanogr. 39: 365–373.
Cust # 08-241
Associate editor: Edward McCauley
Received: 24 June 2008
Accepted: 06 March 2009
Amended: 17 March 2009