Journal of Plankton Research Vol.19 no.10 pp.1537-1552, 1997
Individual swimming behavior of Daphnia: effects of food, light
and container size in four clones
Stanley I.Dodson, Shanna Ryan, Ralph Tollrian1 and Winfried Lampert2
Department of Zoology - Birge Hall, University of Wisconsin, 430 Lincoln Drive,
Madison, XVI53706, USA, 'Ludwig Maximilians University, Zoological Institute,
Karlstrasse 25, D-80333 Munchen and 2Max Planck Institut fur Limnologie,
Postfach 165, D-23402 Plon, FRG
Abstract. Different species of Daphnia show differences in their swimming behavior under different
environmental conditions. We measured the three-dimensional swimming behavior of individual
adult female Daphnia in the mesocosm-scale Plon plankton towers (6400 1) and in small (183 ml)
observation chambers. Speed, sinking rate and turning angle were chosen as optimal variables for
describing the free-swimming animals of four species. Speed, sinking rate and turning angle show uniformity of variance among treatments, and they are relatively independent. Light level and food level
strongly affected swimming behavior. Light and food effects tended to be independent, although there
were two instances of synergism (out of 12 possible interactions). Each of the four species (one clone
per species) showed a unique response to food and light, which may reflect the diverse environmental
origin of each clone. Swimming behavior was consistently different between the small-scale (183 ml)
observation chamber and the mesocosm-scale (6400 1) plankton tower, suggesting that container size
affects swimming behavior: in the smaller chamber, Daphnia, regardless of species, swam slower, sank
slower and tended to move in straighter paths.
Introduction
Individual zooplankton swimming behavior is potentially a critical component of
zooplankton ecology (Ware, 1973; Larsson and Dodson, 1993; Dodson, 1996).
There are four major areas in which individual swimming behavior is an important mechanism, (i) Individual swimming behavior is the underlying mechanism
for population-level behavior such as horizontal and vertical migration, (ii) Individual behavior affects the outcome of predator-prey interactions, especially in
the pelagic environment, where prey movement is important both as a cue to
predators (Brewer and Coughlin, 1995) and a determinant of encounter rate
(Gerritsen and Strickler, 1977). (iii) Individual feeding rate may be linked to
swimming behavior; in most zooplankton, some of the same appendages are used
for the two behaviors, (iv) Toxic chemicals (whether natural, such as cyanobacterial toxins, or anthropogenic, such as pesticides and plasticizers) can have
indirect effects on the whole pelagic community via effects on individual swimming behavior (Dodson et aL, 1995).
The study of individual zooplankton behavior has old roots (e.g. Jurine, 1820)
that are growing into a vigorous research field as appropriate video and computer
technology becomes available. Quantitative techniques were first developed for
two dimensions (e.g. Buchanan et aL, 1982; Buskey et ai, 1983), then for three
dimensions (e.g. Young and Getty, 1987; Price, 1988; Dodson and Ramcharan,
1991; Ramcharan and Sprules, 1991; Bundy et aL, 1993; Hamner and Hamner,
© Oxford University Press
1537
SJ.Dodson el at
1993; Van Duren and Videler, 1995; Dodson, 19%). In the study of individual
swimming behavior, there are still questions about what variables to measure to
quantify swimming behavior efficiently. Baseline knowledge about the effect of
environmental factors on swimming behavior is crucial for intelligent experimental design and for comparison of results among experiments and laboratories.
Our study of zooplankton swimming behavior is focused on Daphnia (Crustacea: Branchiopoda). Daphnia are ecologically important, common, and easily
cultured in the laboratory. However, it is clear that studies of other zooplankton,
such as copepods and rotifers, also contribute to the general understanding of the
role of individual behavior in zooplankton ecology.
Zooplankton swimming behavior is affected by a large number of environmental variables, at the within-species level. For example, in copepods, swimming
speed is influenced by changes in light and light intensity and quality (Strickler,
1970; Tiselius and Jonsson, 1990), food concentration (Buskey, 1984; Bundy etal,
1993; Van Duren and Videler, 1995), food patches (Williamson, 1981; Price,
1988), predators (Ramcharan and Sprules, 1991; Van Duren and Videler, 1996),
turbulence (Saiz and Alcaraz, 1992; Buskey et al, 1996) and the presence of
potential mates (Strickler, 1975; Maly et al, 1994). Daphnia swimming speed is
affected by changes in light and light intensity and light quality (reviewed in
Ringelberg, 1987), food concentration (Porter et al, 1982; Young and Getty,
1987), presence of predators (Young and Taylor, 1990), body size (Dodson and
Ramcharan, 1991) and pesticides (Dodson et al, 1995).
Swimming speed and turning frequency are the variables most commonly used
to describe swimming behavior. However, a comparison of a number of variables
is needed to make sure we are using the best variables to describe swimming
behavior. For this study, we initially chose the six behavioral variables (recommended in Dodson et al, 1995) to describe swimming behavior. These are: hop
rate, speed, turning angle, vertical variance, and the up and down angles. In
addition, we measured sinking rate during swimming [as in Dodson and Ramcharan (1991) and in Gorski and Dodson (1995)]. We measured these seven variables for individuals of four Daphnia species, under conditions of high and low
food and light.
It is worth noting that the variables investigated in this study are scale dependent. That is, the variable will have different values depending on the scale at
which it is measured. For example, Daphnia swimming speed is typically 2-4
times greater when measured at 30 Hz compared to measurements at 1 Hz. We
chose to make all measurements at 30 Hz. For a more complete treatment of scale
dependence of swimming behavior variables, see Brewer (1996).
Our goal in this study was to screen the behavioral variables to find out which
of them were least variable within an environmental treatment and the most variable among different environmental treatments. Behavioral variables meeting
these criteria are most likely to be useful in describing Daphnia swimming
behavior. For environmental treatments, we chose two levels of food and two
levels of light. We also looked for differences in swimming behavior, under the
same conditions, in (i) a mesocosm system large enough to simulate the lake
pelagic zone (the Max Planck Institute for Limnology plankton towers; Lampert
1538
Individual swimming behavior of Daphnia
and Loose, 1992) and (ii) small (183 ml) observation chambers (described in
Dodsone/a/,,1995).
Using the several variables descriptive of swimming behavior, we can ask the
question: 'Do different species of Daphnia show the same or different responses
to environmental variables?'. To answer this question, we tested five hypotheses
concerning individual swimming behavior. Each hypothesis is based on a question about Daphnia swimming.
(i) Does light level affect swimming behavior? It is clear that changes in light
intensity have a strong effect on initiating changes in behavior (Ringelberg, 1987).
However, do constant light levels affect swimming behavior? The answer to this
question is relevant to predator-prey studies. For example, if fish (which use
vision to find prey) are an important predator, to which Daphnia behavior is
adapted, then it is reasonable to expect Daphnia to swim more slowly in brighter
light, all other things being equal. On the other hand, many invertebrate predators do not use visual cues. If these invertebrates are the important predator, then
we would expect no light effect on the basis of predation alone. This reasoning
suggests that Daphnia from lakes, where fish are abundant, will show different
swimming behaviors under different light levels, but Daphnia from fishless ponds
will swim the same in all light levels.
(ii) Does food level affect swimming behavior of Daphnia? Smith and Baylor
(1953) proposed that Daphnia swim more slowly and turn more frequently in
patches of dense food, compared to food-poor water. Porter et al. (1982) found
no effect of food concentration in response to algal patches. However, they did
find that mandibular and thoracic leg movements increased at higher food concentrations. Young and Getty (1987) reported that Daphnia magna swam more
slowly and in straighter lines at higher concentrations of yeast particles, and
Larsson and Kleiven (1996) reported sustained differences in swimming speed at
different concentrations of algae. Daphnia phototactic reactions and patterns of
diel vertical migration are modulated by food level (Flik and Ringelberg, 1993;
Van Gool and Ringelberg, 1995) and depend on the specific genotype (De
Meester and Dumont, 1989; De Meester, 1993; Spaak and Hoekstra, 1993; Young
and Watt, 1994; De Meester et al., 1995; King and Miracle, 1995). These previous
studies introduce the possibility that food level may influence Daphnia swimming
behavior when light is constant, at least for some genotypes.
(iii) Are the effects offood and light levels additive or synergisticl Environmental
conditions may, in certain combinations, have greater than additive effects on
organisms. For example, predator 'smell', low oxygen concentration and low
levels of pesticides all decrease Daphnia growth rate, fecundity and morphology.
In combination, these three factors have a greater than predicted effect on
Daphnia life history parameters and morphological development (Hanazato and
Dodson, 1995). The possibility exists that Daphnia are adapted to display different swimming behaviors for different environmental conditions; differences that
1539
S-I.Dodson et al
would not be predicted from a knowledge of the effects of different levels of food
or light alone.
(iv) Do different kinds of Daphnia have the same swimming behavior responses
to different levels of light and food? It is at least possible that different Daphnia
populations are adapted to behave differently, based on local (within-lake)
predation conditions (a possibility suggested in Parejko and Dodson, 1991). We
studied four species. In each case, we used a single clone to represent that species.
Two clones (D.hyalina and D.pulicaria) were from stratified lakes with both fish
and invertebrates, one (D.magna) was from an unstratified lake with bothfishand
invertebrate predators, and one clone (of D.pulex) was from a pond with predominantly invertebrate predators. Because the clones are from ponds or lakes
with different predator regimes, and because predation affects zooplankton
swimming behavior at the population scale (e.g. De Meester et al., 1995), we
expected to see differences in individual swimming behavior among the four
clones.
Daphnia of different size have slightly different swimming behavior (Dodson
and Ramcharan, 1991). Within a single clone, the larger adults swim faster than
neonates. This implies that larger species will swim faster than smaller species.
To look for an effect of body size, we observed the swimming behavior of a large
species, two intermediate species, and one small species.
(v) Do Daphnia swim in the same way in a very large container as they do in a
small observation chamber? Container effects are a major experimental design
concern of behavioral studies. Previous studies of three-dimensional swimming
behavior have been carried out in the laboratory in small containers of a few
hundred milliliters (e.g. Dodson etai, 1995). Peters and Downing (1984) reported
a small negative container size effect on cladoceran filtering rate in a survey of
hundreds of reports in which container sizes ranged from a few to a few hundred
milliliters. Container effects are also implicated in predator-prey studies (Sarnelle, 1997; W.G.Sprules, personal communication). Very small containers, in
which Daphnia often swim within a few millimeters of the container walls, will
affect swimming behavior through constraints due to simple fluid dynamics
(Zaret, 1980). In small containers, Daphnia spend much of their time either swimming along the walls (hugging the walls) or escaping from walls (Fischer and
Moore, 1993). In addition, the current and turbulence regimes (caused by, for
example, convection due to evaporative cooling at the surface) may depend on
container size as well. Because of this concern, our intention was to compare
observations on the same clones, under similar conditions, in small containers and
in the much larger plankton towers.
Method
Source of clones
The four Daphnia clones used in this study are in culture at the Max Planck Institut fllr Limnologie, Pl&n, Germany. Each clone is the descendant of a single
female, and each clone came from a distinct limnological habitat.
1540
Indhrkraal swimming behavior of Daphnia
The D.magna clone (Lampert, 1994) is from Grosser Binnensee, a shallow
unstratified hypereutrophic lake. The lake is located in northern Germany
(Schleswig-Holstein), near the Baltic Sea. Small plankton-eating cyprinid fish are
abundant and Baltic herring feed in the lake in spring (Lampert, 1991). These
large Daphnia may spend most of their time near or on the bottom of the lake,
in near darkness created by the dense algae and inorganic turbidity.
The D.pulicaria clone was collected from Lake Mendota, a deep stratified
eutrophic lake in southern Wisconsin, USA. Yellow perch and several other
species of plankton-eating fish are abundant. The female was taken from the
upper hypolimnion on 3 September 1993 at noon. Lake Mendota is a large lake
with several species of plankton-eating fish. This clone may be either non-migrating (diel vertical migration) or migrating. In any case, it spent its days deep in the
lake, in near darkness.
The D.pulex clone SBL (Dodson and Havel, 1988) is from a-Gardner pond, a
small and shallow (<1 m deep) dystrophic pond in the University of Wisconsin
Arboretum, Madison, in southern Wisconsin. The pond lacks fish in most years,
has dried up once in the last 10 years, and has high densities of invertebrate predators, especially Chaoborus americanus larvae. The pond is probably dark near the
bottom. The water is colored with humic acid and shaded by surrounding vegetation.
The D.hyalina clone is from Lake Constance (Stich and Lampert, 1984), a large
deep lake shared by Austria, Switzerland and southern Germany. The lake supports several species of plankton-eating fish, including whitefish and perch (Stich
and Lampert, 1981). These are small Daphnia that reproduce at -1.6 mm, compared to -2.0 mm for D.pulex and D.pulicaria, and -2.5 mm for D.magna.
Daphnia hyalina from Lake Constance show a pronounced diel vertical migration
(up to 35 m). Because of their daily migrations, they spend their lives at low light
levels.
In Plon, large numbers of individuals were produced by growing each clone
separately to high densities in 150 1 plastic rain barrels. Cultures were fed from a
chemostat producing the green alga Scenedesrnus acutus (growth rate 0.8 day 1 ).
Daphnia cultures were sieved and animals larger than -1 mm were added to a
plankton tower filled with -6400 1 of Schdhsee lake water. Daphnia density was
adjusted to -2-6 animals H, so that an average of -1 animal would be in view in
the 0.25 1 observation volume at any one time. Daphnia tended to concentrate in
the top meter, probably in response to the light arrangement. The same clones
were also raised in Madison, Wisconsin, where they were fed Chlamydomonas
and Selenastrum.
Physical considerations
The plankton towers are described in Lampert and Loose (1992). The towers
were filled with water pumped from Schdhsee through a fine plankton net. Water
was allowed to stand for at least 2 days before addition of Daphnia. During this
time, the temperature stabilized and excess gas bubbled out. The temperature
1541
S.LDodson et al
was maintained at room temperature in the upper part of the tower, or ~20.5°C.
At the end of an experiment, the towers were drained into the Schohsee.
In Madison, clones were observed at 21°C in 183 ml observation chambers. One
animal was put into an observation chamber at a time.
Light levels
The high light level was produced by an incandescent light bulb suspended over
the center of the tower (or Madison observation chamber). The light level was
adjusted to -60 uE s"1 m~2 at the water surface. The low light level in the towers,
-3 uE s"1 m~2, was produced by a small flashlight (torch) shone through a 1-mlong plastic tube whose end at the water surface was covered with a sheet of white
paper. Note that lake surface light intensity at noon on a sunny day is -2000 uE
s"1 nr 2 . The light level was measured with a spherical PAR photometer.
In the towers, a black background created contrast with bright white Daphnia
images at the high light level. For the low light level, a dark image was silhouetted against a bright (infrared) background. Each infrared spotlight had a flat
round (13 cm diameter) face of opaque white plastic and contained 16 infrared
diodes with a maximum output at -880 nm. The lights were held at right angles
on a frame, each light was -15 cm behind the center of the tower. The Madison
lighting system was set up as in Dodson et al. (1995).
Food levels
Daphnia in the towers were fed batch cultures of S.acutus. Food was sampled at
the depth of observation. Food concentration was determined and adjusted by
use of a particle counter (CASY, SchSrfe Systems) and a calibration curve for
transferring particle volumes into carbon values. The high food level was
0.45-0.50 mg C H; the low food was 0.15-0.20 mg C H. The incipient limiting
food level for Daphnia is probably between these two levels (Lampert, 1987).
Video techniques
The plankton towers werefittedwith a pair of video cameras aimed into the tower
through two glass window portholes positioned at right angles. We used the pair
of portholes at the top of the tower, pointing the cameras toward a volume of
water 17 cm below the water surface. In the plankton towers, the two infraredsensitive video cameras were focused on a 0.25 1 volume (10 cm high X 5 cm X 5
cm) in the center of the tower. Cameras were at right angles, to get three-dimensional swimming behavior. We used a wire cage, which could be lowered into the
center of the tower, to ensure proper positioning, focus and magnification of the
two images. Camera output was combined using a video image splitter and
recorded at 30 frames s"1. The video images were then digitized as in Dodson et
al. (1995).
1542
Individual swimming behavior of Daphnia
Animals and food were added to the tower the day before taping began.
Animals were acclimated to light conditions at least 2 h before taping. All taping
for a treatment was done in a single day. In order to guard against possible
circadian rhythms (Loose, 1993; Ringelberg and Van Gool, 1995) or innate diel
activity patterns (Lampert, 1987) of the Daphnia, we recorded swimming
behavior between 09:00 and 16:00 h.
Treatments were always taped in the same sequence: low food, high light (fL
treatment); low food, low light (fl); high food, high light (FL); high food, low light
(Fl). Our intention was to have 20 tracks for each treatment. However, this did
not always happen (Table I). Video records were digitized after the taping was
finished and, in a few cases, there were simply not 20 complete records. This was
especially true of the high-food, low-light treatment, in which the relatively dense
algae created a nebulous fog that reduced contrast between the Daphnia and the
dark background.
In Madison, the video system was set up as described in Dodson et al. (1995).
The observation chamber was 5 cm square and 7.3 cm tall. Thus, the volume
observed in the small chamber was similar to that observed in the Plon towers.
The major difference was that animals in the small observation chamber were
Table L Average values (and SDs) of speed and sinking rate measurements of hopping behavior in
four clones of Daphnia. In the treatments, f = low food; F = high food; 1 = low light; L = high light. Data
are tested for homogeneity of variances among treatments within each clone, using the Levene ratio
of variances. The 0.05 critical value for the Levene ratio (four treatments, 20 individuals per treatment)
is 3.29
Species
Treatment
No.
Body length Speed
(mm)
(rams" 1 )
Sinking rate
(mm s~')
Turning angle
(radians)
Daphnia magna
fL
fl
FL
Fl
Levene ratio
20
20
20
9
2.65 (0.31)
2.02 (0.23)
1.99 (0.25)
2.09 (0.17)
-3.22 (1.03)
-3.13 (0.52)
-3.22 (0.88)
-4.22 (1.30)
2.101
1.49
1.56
1.81
1.43
3.18
Daphnia pulicaria fL
fl
FL
Fl
Levene ratio
20
20
20
20
2.02 (0.27)
2.03 (0.01)
1.88 (0.19)
1.98 (0.18)
6.31
7.79
6.60
7.51
3.19
(0.62)
(1.32)
(0.57)
(0.87)
-3.04
-3.22
-3.56
-4.30
3.06
(0.63)
(1.16)
(0.64)
(1.00)
1.47 (0.16)
1.52 (0.24)
1.36 (0.18)
1.45 (0.19)
2.81
Daphnia pulex
fL
fl
FL
Fl
Levene ratio
17
19
20
20
2.01 (0.27)
2.11 (0.29)
2.00 (0.29)
2.03 (0.24)
4.38 (0.65)
7.58 (0.74)
6.41 (0.62)
8.16 (0.93)
2.41
-1.80
-3.25
-3.06
-3.89
3.44
(0.54)
(1.01)
(0.82)
(0.66)
1.48(0.18)
1.48 (027)
1.60 (0.13)
1.68 (0.13)
3.20
Daphnia hyalina
fL
fl
FL
Fl
Levene ratio
20
20
20
14
1.70
1.62
1.60
1.64
4.73 (1.08)
7.72 (0.92)
536 (1.39)
8.57 (1.06)
2.17
-1.84 (0.58)
-2.44(1.19)
-2.43 (1.21)
-3.05 (0.59)
2.88b
(0.15)
(0.19)
(0.19)
(0.22)
13.12 (1.90)
8.04 (0.86)
17.99 (2.49)
10.79 (1.37)
2.79*
1.30
1.70
138
1.69
(0.19)
(0.17)
(0.19)
(024)
(025)
(0.16)
(024)
(0.14)
•Levene ratio after data were log transformed.
b
Levene ratio after data were square root transformed.
1543
SJ.Dodson el al
always within 2.5 cm of a wall, while in the tower they were swimming -40 cm
from a wall. For the small observation chamber, we used individual infrared
diodes and a large collimating lens to create bright field illumination.
In the towers, animals were recorded as they came into view. They were not
removed after recording, so it is conceivable that we taped some animals twice.
However, since there were as many as 3000 animals in the tower, double records
of the same animal were unlikely. In Madison, animals were taped separately: one
animal in the observation chamber at a time.
Analysis of the video records followed Dodson et al. (1995), except for sinking
rate (see Dodson and Ramcharan, 1991). We used 3 s tracks, to accommodate the
dimensions of the observed volume and observed swimming speeds. We chose
the track duration to minimize loss of data caused by Daphnia swimming out of
the field of view.
Daphnia body length for each swimming track was measured on a 35 cm
monitor. We measured the video image length by laying a ruler on the monitor
screen, and then converted the measurement to actual body length.
The time scale for our variables was based on the 30 Hz recording rate. For
each 3 s track, the average speed, sinking rate and turning angle were calculated
using rates of movement or turning between each video frame (recorded at 30
Hz). It is worth mentioning that measurements of swimming behavior are
extremely sensitive to scale in the region of 30 Hz (M.C.Brewer, personal communication). For example, Daphnia speed measured at 30 Hz can be as much as
five times as great as that measured at 1 Hz.
Time constraints did not allow for replication within Daphnia clones. We performed only one set of observations on the four food and light levels for each
clone. We optimized our resources by replicating within treatments and among
clones.
Statistics
Outliers were removed from the data set if speed was more than 3 SDs from the
average speed for a treatment. No outliers were removed for D.hyalina or D.pulicaria. Two outliers were removed from the D.magna data set (one from each of
the fL and Fl treatments) and one from D.pulex (Fl treatment). The outliers were
fast swimmers that appeared to be showing 'escape behavior' of fast directional
swimming with no sinking seen between power strokes. Using the criterion of 3
SDs, we felt comfortable distinguishing between 'normal' swimming behavior
and the occasional 'escape' behavior.
Our goal was to identify measurements of swimming behavior that were
optimal for statistical analysis. For example, a desirable characteristic of the
measurements is similarity of variability ('homoscedasticity') in different experiments. The seven swimming behavior variables [recommended in Dodson et al.
(1995) plus sinking rate] were tested for homoscedasticity among treatments,
using the Levene test (Milliken and Johnson, 1992). If a variable did not test as
homoscedastic, the data were log and square root transformed, and re-tested
(Table I).
1544
Indhridnal swimming behavior ol Daphnia
For the homoscedastic variables, squares of pair-wise Pearson correlation
coefficients (Sokal and Rohlf, 1981) were used as an indication of the amount of
information gained by using more than one variable. That is, if two variables are
completely correlated (r2 = 1.0), then it is only necessary to use one variable to
describe swimming behavior and nothing is gained by using the second variable.
If the two variables are completely independent (uncorrelated, r2 = 0.0), then
both contribute information to a description of swimming behavior.
Effects of food and light on swimming behavior variables were tested for significance using a Model I two-way ANOVA (in some cases, with unequal sample
sizes; see Table I) (Sokal and Rohlf, 1981).
A synergism is a non-additive effect of two or more independent variables. If
the effects of two factors, such as light and food level, are additive, then the
ANOVA interaction term will not be significant. A significant interaction term
was taken as evidence of synergism.
Swimming behavior was compared between the Plbn and Madison sites, using
a /-test, for three of the four species: D.magna, D.pulex and D.pulicaria. Comparisons were made for the high-light, high-food conditions, using three measures
of swimming behavior (swimming speed, sinking rate and turning angle).
Results
Behavioral variables
Results of the light and food experiments in Plon were given a preliminary analysis, in order to determine which of the seven descriptors of swimming behavior
were optimal for further statistical analysis. The two criteria used to choose variables were the variance pattern among treatments and correlation among variables. Criteria for optimal variables were: (i) small amount of variance within a
treatment and similar (not statistically different) amount of variance among the
treatments; (ii) minimum amount of correlation between variables.
Three variables had similar variances among treatments within a clone: average
swimming speed within a 3 s track ('speed'), average sinking rate within the track
('sinking rate') and average turning angle within the track ('turning angle') as
indicated by the Levene ratios in Table I.
Pair-wise correlations among the three homoscedastic variables are given in
Table II. While there is statistically significant correlation, the values of r2 are
small. The values of r2 are mostly <0.1, indicating that <10% of the variance in
Table O. Squares of pair-wise correlation coefficients (r) among speed, sinking rate and turning angle
for four clones of Daphnia, each comparison has 79 degrees of freedom, the 5% level of significance
is r = 0.217 (r2 = 0.0471)
Species
Daphnia
Daphnia
Daphnia
Daphnia
magna
pulicaria
pulex
hyalina
Speed versus
sinking rate
Speed versus
turning angle
Sinking rate versus
turning angle
0.000025
0.0567
0.449
0.162
0.106
0.00032
0.057
0.081
0.047
0.212
0.00036
0.00241
1545
S-LDodson el al
one variable is explained by variation in the other. Thus, each variable contributes additional information about swimming behavior.
The three variables (swimming speed, sinking rate and average turning angle)
were used in subsequent tests of the effect of light and food on Daphnia swimming behavior.
Light and food effects
Results of the two-way Model I ANOVA show strong evidence for effects of both
light and food levels on Daphnia swimming behavior (Table III). The arrows in
the table indicate the change in a variable with an increase in an environmental
factor. For example, D.magna showed significantly higher swimming speed at the
high food level.
Comparisons among clones
The clones are similar in that they all showed significant light and food effects.
Different clones react in a similar, but not identical, way to the same light and
food levels (Table III). In general, a higher food level was associated with faster
swimming and sinking, higher light was associated with slower swimming and
sinking, and turning angle was either not affected by light or food, or showed variable results, depending on the clone.
Table ID. Results of two-way ANOVAs for four clones, showing the effect of food and light on
swimming speed and sinking rate, with body length as a covariate. An upward-pointing triangle
indicates that the behavioral variable increased at the higher level of the environmental variable. The
treatment that was significantly different from the other three combinations of food and light is
indicated for significant interaction terms
Daphnia magna
Log speed
Log sinking rate
Turning angle
Daphnia pulicaria
Speed
Sinking rate
Turning angle
Food
Light
*«A
''••A
Food x light
Body length
**• LF = highest
**»A
•*T
.**•
*>T
'' •
Daphnia hyalina
Speed
Sinking rate
Log turning angle
••A
•A
'»**T
'» •
>•••
Daphnia pulex
Speed
Square root sinking rate (?)
**»4
<>***T
Turning angle
•••A
*
*•
*
***LF = lowest
*P < 0.05; ••/> < 0.01; ••*/» < 0.001.
1546
***
Individual swimming behavior of Daphnia
Despite the similarities, no two clones responded in exactly the same way to
the food and light levels (Table III). Thus, genotype has a significant effect on
swimming behavior.
Synergism within clones
Where there was a significant interaction between light and food, we identified
the one treatment that was different from the other three (Table III). For
example, for D.magna, turning angle was the same for all treatments, except for
the high-light, high-food (LF) treatment, which was significantly larger than the
others. In general, food and light effects are independent and additive: there were
two instances of synergism, out of a possible 12 (Table III).
Container size
There were consistent differences between swimming behaviors observed in the
small chambers (in Madison) and the mesocosm (in Pldn). Averages and SDs,
and the results of /-tests, show significant differences in swimming (Table IV).
Discussion
Behavioral variables
The past several years have seen a sifting and winnowing of variables used to
describe Daphnia swimming behavior in three-dimensional video systems. Swimming speed has been the favorite variable, but a number of other measures of
swimming behavior have also been proposed (Brewer, 1996). Dodson and
Ramcharan (1991) proposed six possible variables to measure swimming
behavior. Dodson et al. (1995) measured nine variables, but not all the same as
in the previous study. They found six of the nine variables to be useful in statistical
analysis of the effects of predator smell and a pesticide on the swimming behavior
of a single clone of D.pulex. In our current study of four Daphnia clones, we have
Table IV. Comparison of mean values for high-food, high-light treatments in Pldn plankton towers
(64001) and Madison observation chamber (183 ml). Significant differences between treatments (size
of container) within a clone and for a specific swimming behavior are indicated by bold type ((-test, on
transformed data where appropriate to produce homoscedasticity). Data are presented as means with
SDs of the mean in parentheses.
Site
Species
No.
Length
Speed
Sinking
rate
Turning
angle
Plon
Madison
D.magna
20
12
1.99(0.26)
1.89(0.16)
17.99 (155)
6.03 (0.97)
-3.22 (0.90)
-2.96 (0.46)
1.81(0.20)
1.23 (0.18)
Plon
Madison
D.pulex
20
12
2.00 (0.27)
1.80 (0.01)
M l (0.62)
5.19 (0.62)
-3.06 (0.82)
-2.72 (0.44)
L60 (0.13)
136 (0.13)
PlOn
Madison
D.pulicaria
20
12
1.88(0.19)
1.92(0.19)
6^0(059)
5.70 (0.59)
-3.56 (0.66)
-3.03 (0.71)
L36 (0.19)
L33 (0.11)
1547
S.LDodson et aL
narrowed the field of useful quantitative variables to three. Speed, sinking rate
and turning angle were homoscedastic and were relatively independent. We recommend that these three variables be included in future studies of zooplankton
swimming behavior.
The averages given in Table I should not be taken as being characteristic of
each of the four Daphnia species because each species is represented by only one
clone. There is strong evidence for intra-clonal variation within a species in
morphological development (Parejko and Dodson, 1991) and large-scale
behavior (De Meester and Dumont, 1989; Young and Watt, 1994; De Meester et
aL, 1995). Therefore, it is reasonable to expect intra-clonal variation in small-scale
behavior as well. For example, the results of a study of the effect of food on the
speed of a D.pulicaria clone from Oneida Lake show significantly faster swimming speed at high food than at low food, the opposite of our results for the Lake
Mendota clone of D.pulicaria (T.O'Keefe, personal communication). Also, we
have two clones of D.pulex, both from temporary ponds in Ontario. One clone
swims slowly, hopping up and down in place, while the other swims fast, using
rapid antennal flicks instead of hop-and-sink behavior.
Measurements summarized in Table I indicate some variability in body size.
Variability in body size was small because we deliberately chose animals similar
in size. Results in Table III show that in some but not all tests, there is a correlation between a swimming behavior variable and body length. There is no clear
pattern of the length effects. Depending on the clone, body length was significantly correlated with one or two of the three swimming behavior variables. In
any case, the existence of significant correlations suggests two strategies for carrying out swimming behavior experiments with zooplankton: (i) use animals of one
size or (ii) as in our analysis, minimize variation in body size and treat body size
as a covariate.
Light and food effects
Our results suggest that both food and light levels have a strong effect on swimming behavior. These effects are displayed for animals that are equilibrated to
their environment, not to a change in food level.
Comparisons among clones
In our study, the overall pattern of reactions to food and light levels is unique for
each clone (Table III). In general, higher food tends to be associated with higher
speed, higher sinking rate, and shows no consistent effect on turning angle.
Higher light tends to be associated with lower speed and lower sinking rate, and
with a smaller turning angle. However, there are some strong exceptions. For
example, in our experiments, D.magna swam fastest when in conditions of high
food and high light. This phenomenally high sustained speed (17.99 mm s~' or ~9
body lengths s"1) was also observed by Larsson and Kleiven (1996). In our study,
three of the four clones swam faster at the higher food level. Food level had no
effect on D.pulicaria swimming speed, just as Porter et aL (1982) found no effect
1548
Individual swimming behavior of Daphnia
of algal concentration on D.magna swimming speed. Young and Getty (1987)
reported slower swimming with denser yeast particles, the opposite of what we
found. The variety of swimming behaviors observed in our study and reported in
the literature may be due in part to differences in environmental conditions (for
example, the type of food, interactions of light and food effects, and the different
experimental set-ups), but the range of variation may also be due to genetic
differences among clones.
Synergism within clones
Two of the clones (D.magna and D.pulex) showed synergistic reactions to food
and light. These strong linear (independent) and non-linear (synergistic) effects
of food and light indicate the importance of both food and light levels in swimming behavior experiments.
Among-clone differences in food and light effects may be the result of natural
selection. Each clone came from a different habitat characterized by a specific
combination of light levels, vertebrate and invertebrate predation intensity, and
average food levels distributed in different ways in time and space.
Complex environments can lead to complex patterns of local adaptation.
Revealing the adaptive significance of Daphnia swimming behavior will require
the exploration of far more than four habitats.
Container size
The results of this study suggest that container size affects the results of swimming behavior studies. The Madison chamber, 5 x 5 cm, was small enough to
affect swimming behavior significantly. Other studies of Daphnia swimming
behavior have used similar small observation chambers. For example, Buchanan
et al. (1982) observed Daphnia in a 10 cm diameter chamber. It is probably best
to use an observation chamber that is large enough so animals are swimming at
least 10 cm from any wall when they are recorded.
Suggestions for experimental design
Results of this study provide guidelines for designing experiments for exploring
Daphnia swimming behavior. In comparative studies, or when carrying out
studies at different times, it is important to use the same clone, the same light
levels and the same food concentration. In addition, the container size matters.
It is probably not necessary to use observation chambers as large as the Pl6n
towers, but small chambers, with the walls near the field of view, will affect the
results.
Future research opportunities
Unanswered opportunities presented by this study include understanding swimming behavior variability and the adaptive significance of swimming behavior.
1549
S-LDodson el al
One reason for using clones in our observations was the desire to minimize variance within a treatment. However, the variation, at least of speed, appears to be
just as high as that for a population of mixed genotypes. The coefficient of variation
(CV, denned as the standard deviation divided by the average) is a measure of variability. For two-dimensional data, Buchanan et al. (1982) reported swimming
speeds for D.magna, presumably for a mixed culture containing more than one
clone. Swimming speed in this population had CV values between 15 and 77%. In
the two-dimensional study of Porter et al. (1982), the CV for swimming speed
ranged from 25 to 33%. Copepods only reproduce sexually, and CV values from
copepod studies are in the range of 30-60% (Ramcharan and Sprules, 1991; Van
Duren and Videler, 1995). Swimming speeds observed for the genetically identical
Daphnia in our study had CV values between 36 and 63%, well within the range of
the non-clonal Daphnia and copepod CV values. We conclude that swimming
behavior measured for a clone is as variable as swimming behavior measured for a
sexual population or a population of a mixed group of clones from a single location.
One explanation for the variability seen in swimming behavior among Daphnia
clones is that the different clones are adapted to specific food and predator
regimes in nature. For example, faster swimming individuals may be able to feed
more efficiently, but may also be more vulnerable to predators. If this is the case,
then different clones (even of the same species) could potentially be adapted to
swimming to maximize feeding in a low-predator environment, such as a temporary pond, while other clones are adapted to maximizing survival in a high-predator environment, at the cost of feeding rate.
Acknowledgements
Thanks to Petter Larsson, Eric von Elert, Matt Brewer and Tom O'Keefe for their
contributions to this paper. Thanks also to H.Hansen (Plon electrician), Russ
Attoe and K.Olesen (Madison electricians), F.W. Scholer (chief in Plon workshop), F.Nerhoff von Holderberg (Plon workshop), R.Gange (chief in Madison
workshop), L.SchSler (Plon algae cultures), H.J.Krambeck (Plan computer
department), D.Leland (Madison accountant and shipping expediter) and to the
departmental managers G.Hinz (Plon) and W.Holthaus (Madison).
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Received on February 26,1997; accepted on June 13,1997
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