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Copepod foraging and predation
risk within the surface layer during
night-time feeding forays
ANDREW W. LEISING1*, JAMES J. PIERSON2, SCOTT CARY2 AND BRUCE W. FROST2
1
NOAA, ENVIRONMENTAL RESEARCH DIVISION, SOUTHWEST FISHERIES SCIENCE CENTER, 1352 LIGHTHOUSE AVENUE, PACIFIC GROVE, CA 93950, USA AND
2
SCHOOL OF OCEANOGRAPHY, UNIVERSITY OF WASHINGTON, SEATTLE, WA
*CORRESPONDING AUTHOR:
98150, USA
[email protected]
Received June 21, 2005; accepted in principle July 26, 2005; accepted for publication October 7, 2005; published online November 22, 2005
Communicating editor: R.P. Harris
Vertical distribution data seem to indicate that certain species of diel vertical migrating copepods
avoid the surface high chlorophyll (Chl) region within coastal and estuarine environments, even
during the night. Copepods may avoid this layer to reduce predation mortality, avoid advective loss
or to avoid consuming too much toxic algae. We hypothesize that copepods make several
intermittent feeding ‘forays’ into shallow surface layers during the night, returning to intermediate
depths between forays. Using an individual-based model (IBM) of Calanus pacificus, we
examined the implications of this behavior on feeding success and mortality risk, and tested
whether a practical field-sampling scheme would be able to detect foray-like behavior. In some
cases, mortality of the foray-foraging copepods was up to 50% less than that of randomly
behaving controls, for a given amount of food ingested. The trapping scheme devised should be
able to detect the occurrence of foray behavior (FB) in the field and should show differences in the
gut contents of copepods entering and leaving the uppermost food-rich layer. The presence or
absence of foray-like behavior significantly altered the relative concentration of copepods within
various surface strata and thus could influence the temporal availability of copepods as prey for
the larvae and juveniles of several important managed fish species.
INTRODUCTION
Copepods exhibit a wide array of foraging behaviors
across many spatial scales. The largest scale (for the
copepod) includes well-studied behaviors such as diel
vertical migration, whereby a copepod typically resides
at depth during the day and may swim hundreds of
meters to the surface to feed during the night. The
adaptive value of this behavior is generally considered
to be avoidance of mortality caused by visual predators
that are highly abundant in surface layers and are
thought to feed during the daytime (Zaret and Suffern,
1976; Ohman, 1990; Lampert, 1993). Such predators
primarily include vertebrates such as small planktivorous
fish and the larvae or juveniles of certain fish species.
At the smallest scale relevant to a copepod’s foraging
behavior (e.g. the microscale; mm and s), copepods
exhibit moderately complex behaviors that vary by
copepod species and prey type. Such behaviors have
been documented through various laboratory studies
utilizing high-speed cinematography (Alcaraz et al., 1980;
Paffenhöfer et al., 1982) and other video-based observation
systems (Landry and Fagerness, 1988; Tiselius and
Jonsson, 1990). At more intermediate scales (e.g. the
fine scale; 10s of m and h), much less is known about
the foraging behavior of copepods, since it is currently
impossible to track individual copepods in situ over time
periods greater than a few seconds and technically
difficult if not impossible to set-up and track individuals
within tanks simulating water columns of sufficient size
to allow unrestricted travel. Because of this, little is
known about how individual copepods forage on these
scales, particularly for species that undergo diel vertical
migration and feed within the surface layers during the
night.
What field data there are at these intermediate scales
suggest complex and temporally varying interactions
between copepods and their food. For example, once
This paper is one of six on the subject of the role of zooplankton predator–prey interactions in structuring plankton communities.
doi:10.1093/plankt/fbi084, available online at www.plankt.oxfordjournals.org
Published by Oxford University Press 2005.
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vertically migrating copepods reach the surface, they are
typically not distributed evenly throughout the upper
layers. Copepods may sometimes be found associated
with subsurface chlorophyll (Chl) maxima (Sameoto,
1984; Townsend et al., 1984; Harris, 1988; Napp et al.,
1988; Castro et al., 1991), which increases ingestion and
subsequently growth or reproduction rates. However,
numerous other studies have found copepods at higher
abundances below the layer of maximum Chl concentration (Mullin and Brooks, 1976; Sameoto, 1984;
Simard et al., 1985; Napp et al., 1988; Bjørnsen and
Nielsen, 1991; Bollens et al., 1993; Tarling et al., 2002).
Why would a copepod avoid the region with maximum
food availability? Three obvious possibilities are that
(i) such behavior would minimize time within high food
regions if those regions also expose the copepod to higher
predation risk, (ii) surface layers may be highly advective
relative to deeper strata and displace the copepod to a
less favorable region (Peterson et al., 1979, Peterson,
1998) and (iii) high-phytoplankton regions may contain
toxic diatoms or other harmful algae (Ban et al., 1997;
Miralto et al., 1999; Ianora et al., 2004; Pierson et al.,
2005a). There is significant evidence supporting the first
hypothesis, particularly when considering copepods that
undertake diel vertical migrations. Whereas the surfacemost layer may often contain high food levels, this layer
may also contain the highest number of predators, visual
or otherwise. Although fish have traditionally been
thought of as primarily daytime feeders, since they
depend on visual means to locate prey, many larval and
juvenile fish can feed quite readily under low-light
conditions typical of night-time levels (Neilsen and
Perry, 1990, and references therein). Indeed, the larvae
of many fish species also undergo diel vertical migrations,
swimming to depth during the day, and returning to the
surface during the night, to avoid even larger piscivorous
visual predators. Thus, they may be adapted to feed at
night under low light levels (Nielsen and Perry, 1990;
Macy et al., 1998; Schabetsberger et al., 2000; Sørnes
and Aksnes, 2004). Since the feeding rates of these larvae
are typically correlated with light intensity, however,
predation rates on copepods will increase nearer the
surface, particularly during the night when light may
preclude the ability of these fish to feed at intermediate
depths. Yet copepods may still need to risk feeding within
this higher risk upper surface layer in order to obtain an
adequate daily ration.
We hypothesize a relatively generic foraging behavior
that should allow a copepod to achieve a dynamic balance
between the time it needs to feed within the surface layer,
and risk aversion through avoidance of this layer during
non-feeding periods. We propose that copepods might
make short intermittent ‘forays’ into the surface, high-
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concentration high-mortality-risk layer to feed, returning
to intermediate depths between these forays, during which
they reduce their feeding activity while they digest (Fig. 1).
Such behavior of plankton has been suggested before
(Gauld, 1953; Pearre, 1973; Mackas and Bohrer, 1976;
Pearre, 1979) and has been termed the ‘hunger/satiation
hypothesis’, as used to explain ‘midnight sinking.’
Evidence supports the contention that copepods do not
continuously feed, even during the night (Mackas and
Bohrer, 1976; Mackas and Burns, 1986; Rodriguez and
Durbin, 1992; Kleppel et al., 1988). In these cases, a
copepod may fill its gut rather rapidly, on the scale of
minutes to an hour, and then require a similar period of
time, or longer, to digest before beginning to feed again.
This ‘refractory’ period, during which the copepod may
also need time to rebuild its enzyme pool (Head et al.,
1984; Mackas and Burns, 1986; Hassett and BladesEckelbarger, 1995), could serve as a natural time during
which a copepod might leave the more dangerous or
harmful surface region. Beyond the reasons listed above
for avoiding the surface layer, there may also be other
physiological or energetic reasons that make it advantageous to sink out of the surface layer between feeding
events (as reviewed in Pearre, 2003).
Here, we examine whether such a proposed foraging
behavior could confer an advantage of increased feeding
and/or reduced mortality for copepods. We used an
individual-based model (IBM) of adult female Calanus
pacificus, feeding within a water column characterized
similarly to natural conditions found during the spring
bloom within Dabob Bay, WA. Because many of the
parameters controlling the foray behavior (FB) are
poorly constrained, we further conducted a detailed
sensitivity analysis of the effects of our parameter choices
on both copepod fitness and the ability to detect
FB through a simulated field-sampling scheme. Lastly,
we also investigated how foray versus non- FB s could
0
High
chlorophyll
Feeding
15
Depth (m)
JOURNAL OF PLANKTON RESEARCH
Low
chlorophyll
50
Digesting
100
Sunset
Time
Sunrise
Fig. 1. Conceptual diagram of the foray behavior (FB). Copepods
swim into the upper, high-food, high-mortality layer to rapidly feed,
then sink to the lower, low-food, low-mortality layer during a refractory
digestive period, returning to the surface multiple times during the
night to feed. Shading of copepod body represents relative gut fullness.
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differentially affect the prey field and feeding success of
copepod predators, which includes the larvae of several
important managed fisheries species, such as hake, herring, northern anchovy and salmon (Bollens and Frost,
1989). This particular ecosystem was chosen to test this
hypothesized behavior for several reasons: C. pacificus is
known to undertake diel vertical migrations to avoid
surface visual predators (Osgood and Frost, 1994),
some of which are still active at night (Bollens and
Frost, 1989); the surface mixed layer within Dabob
Bay typically flows out of the bay and is where the
highest concentration of phytoplankton is found during
the spring (Osgood and Frost, 1996; Dagg et al.,
1997); the surface spring bloom often contains diatoms
known to have harmful effects on the reproduction of
C. pacificus (Pierson et al., 2005a). Thus all three of our
hypothetical criteria that should favor FB are present
within this system. Lastly, C. pacificus has been observed
to have relatively long (1–3 h) low activity, non-feeding
periods between active feeding bouts (Mackas and
Burns, 1986), which would facilitate sinking out of the
upper surface layer, as in our proposed foraging
mechanism.
METHODS
Overview
One thousand copepods were placed within a simulated
200 m deep water column, with 20 mg Chl L1 within
the surface 0–15 m layer, and 1 mg Chl L1 within a
15–50 m intermediate layer, similar to situations previously observed within Dabob Bay (Frost, 1988; Dagg
et al., 1997; Pierson et al., 2005b). Copepods were given
swimming and feeding behaviors based on our foray
hypothesis (described in detail below). Mortality probability was arbitrarily set to 10% and 1% per night
within the upper and lower layers, respectively. We
consider mortality to be higher within the upper layer
due to (i) visual predation, which is light dependent and
greater near the surface even during the night, and
(ii) advective loss of the surface layer, due to estuarine
flow. Although we do not have direct estimates of the
absolute value of copepod mortality from Dabob Bay, the
critical point here is to examine the effects of the relative
mortality between layers; our sensitivity analysis below
investigates changes in the ratio of mortality between the
layers.
A simulated zooplankton trap was placed at 17 m
depth, just below the high concentration surface layer.
So as not to alter the overall concentration of copepods
within the simulation, the trap does not stop the copepods as they swim between layers, but simply notes their
direction of passing. The total number of copepods that
swam up or down past the trap over 45-min intervals
was thus recorded. The gut contents (measured in units
of ng Chl) of all copepods which passed by the ‘trap’
were also recorded at the end of the 45-min interval. To
more realistically simulate this trapping process for gut
contents, at the exact moment when a copepod swam
past the ‘trap’, an identical duplicate of that copepod
was created and held at the trap depth for the remainder
of the 45-min period, during which it was not allowed
to feed but continued to digest its stomach contents.
At the end of the 45-min interval, the gut contents of
these duplicate copepods were then recorded, and these
duplicate copepods were then discarded from the simulation. This directional-trapping scheme was chosen as it
reflects a fairly simple and practical method that could
theoretically be used in the field to measure the flux of
copepods between surface layers, even though it is not a
regularly used method. Also at 45-min intervals, we
simulated sampling the water column as would be done
using opening-and-closing vertical net tows, sampling the
surface, intermediate, and deepest layer, in order to
obtain the relative abundance of copepods within each
layer over the course of the night. The simulation starts
(t = 0 h) at the point when copepods would first migrate
up from their daytime depth (some point near local
sunset), and ends12 h later (t = 12 h), just after local
sunrise. The model time step was 10 s.
Model equations and parameters
The model can be broken down into five major behavioral
components:
(i) Initial vertical migration to shallow layers from
depth
(ii) Spatial foraging control within the upper layers
(iii) Ingestion and gut filling
(iv) Refractory period and sinking
(v) Termination of foraging behavior and migration
to depth
Initial vertical migration
All copepods started the simulation at a depth of 195 m.
The timing of surface ascent for each copepod was
chosen randomly from a normal probability distribution
function, with a mean value of 1 h after the start of the
simulation, and a standard deviation of 30 min for the
standard runs. This formulation led to 68% of the
population starting its migration toward the surface
within a window from 30 to 90 min after the start of
the simulation (68% is the integrated area within 1
stdev of the mean of a Gaussian curve). Migration speed
of the copepods was set to 100 m h1 and was kept
constant for all runs. Each copepod migrated up at this
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speed until it reached a depth somewhere between 0 and
50 m that was randomly predetermined for each copepod,
at which point the copepod began to forage and feed.
Spatial foraging
Copepods foraged within the simulated water column
using a vertical random walk. For an unbiased random
walk, the copepod has a 50/50 chance of swimming
either up or down at each time step (10 s for this
model), with a step size set by, Sstep. However, to simulate the FB, which calls for the copepods to swim upward
into the high-concentration layers while feeding, the
distance of upward motions was set to 20% greater
than Sstep, and the distance of downward motions was
20% less than Sstep. For the standard run, Sstep was set
such that the average swimming speed was 2.5 cm s1,
similar to the maximum swimming speeds seen for
C. pacificus (Landry and Fagerness, 1988).
Ingestion and gut filling
Ingestion rate as a function of food concentration was
modeled following a Michaelis-Menton type-II curve,
where the ingestion rate, I was
I ¼Imax
C
ðks þC Þ
ð1Þ
where Imax is the maximum ingestion rate (ng Chl h1),
C is the concentration of phytoplankton at the location
of the copepod (mg Chl L1) and ks is the half-saturation
constant (mg Chl L1). Imax was set to 100 ng Chl h1
and ks was set to 5 mg Chl L1 (Frost, 1972, 1985). Imax
was chosen so that, when combined with the digestion
and refractory periods (described below), average ingestion over longer periods would be similar to observations
(referenced below).
Gut content, G, at any instant in time, was modeled as
the combination of the ingestion rate, minus the gut
clearance rate such that
dG
¼I GR
dt
ð2Þ
where R is the instantaneous gut clearance rate coefficient (h1), and I and C are as above. Each copepod was
given a unique value of R for the duration of each model
run, drawn from a uniform random distribution of 25%
of the standard value of R, which was set at 2 h1, based
on data from laboratory experiments (Mackas and Burns,
1986; Dagg et al., 1989). This variability was added to
reflect the possibility that within a population, copepods
will have slightly different physiological states, based on
their individual history, and may also have different body
weights (copepod weight was not explicitly modeled).
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Copepod gut content was allowed to increase to a maximum of Gmax, which was set to the equivalent of 30 ng
Chl, based on levels of average individual gut content
measured in both field and laboratory experiments
(Mackas and Burns, 1986; Dagg et al., 1989, 1997).
Refractory period and sinking
Once a copepod’s gut content, G, reached Gmax, the
copepod was considered to enter a ‘refractory’ period,
during which feeding ceased, yet digestion continued.
During this period, gut contents decreased according to
dG
¼ GR
dt
ð3Þ
until G reaches H, the hunger threshold (ng Chl) at
which feeding recommences. H was set to 5 ng Chl,
based on field and laboratory measurements of minimum gut contents (Mackas and Burns, 1986; Dagg
et al., 1989, 1997). During this refractory period, the
FB copepods ‘sink’ at a fixed speed of 1 cm s1. This
speed is 4 higher than measured sinking speeds for
C. pacificus (2.5 mm s1; Landry and Fagerness, 1988)
but is meant to be consistent with our view that downward movement may consist of both sinking and periods
of active swimming. Using a novel plankton wheel apparatus, Hardy and Bainbridge (Hardy and Bainbridge,
1954) observed sustained periods of downward swimming for Calanus finmarchicus, with average speeds ranging
from 2.9 cm s1 over a 2-min interval to 1.3 cm s1 over
a 60-min interval. As there are no published data like
this for C. pacificus, our analysis below includes an examination of the sensitivity of the model to decreasing the
sinking speed from this value. Upon G reaching H, the
copepods ‘awaken’ and continue to feed and swim again
with the bias random walk described above.
Given the above parameters for ingestion and gut
clearance, average time to maximum gut fullness
(assumed to be 30 ng Chl), within the high-concentration
layer (20 mg Chl L1) was 36 min. Average ingestion rate
over a 6 h period, including the non-feeding digestive
periods, was 33 ng Chl h1, and average time for the gut
to empty from a full stomach down to the hunger threshold was 45 min [these rates and parameters are similar
to those previously found for C. pacificus from Dabob Bay
(Frost, 1985; Dagg et al., 1989, 1997)].
Migration to depth
At a fixed time after the start of the simulation (t = 9.5
h), all copepods were forced to migrate back to 195 m at
the previously used migration speed of 100 m h1,
regardless of their condition or location within the surface layers. Copepods did not feed during this downward
migration.
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Standard run
Given the above parameterizations, we ran a standard
scenario where we compared the hypothesized FB to a
random ‘control’ behavior. For the random control (RC)
behavior, all parameters were the same as the FB; however, the copepods have no upward bias in their random
walk (equal upward and downward step sizes). These
control copepods cease feeding during the refractory
period, just as in the FB; however, the control copepods
do not sink during this time and continue to swim
randomly up and down.
Sensitivity analysis
As many of the parameters controlling the various
aspects of the copepods’ physiology and foraging behavior are not well constrained, a sensitivity analysis of the
effect of altering these parameters was conducted. For
each parameter set to be tested (summarized in Table I),
the model was run six times: twice (once with FB and
once with the RC behavior) at the standard parameter
set, twice (foray and control) at a higher value of a single
parameter and twice (foray and control) at a lower value
of the parameter. Both biological and environmental
parameters were considered. The biological parameters
investigated were the gut clearance rate, R, the maximum ingestion rate, Imax, the hunger threshold, H, the
swimming speed (step size), Sstep, and the ‘sinking’
speed. All biological parameters were varied 25%
from their standard value, except the hunger threshold,
H, which was varied by 50%. The ‘environmental’
parameters investigated were the relative height of the
layers, the relative concentration of the layers and the
relative mortality rates between the layers. Lastly, we
examined the effect of altering the length of the trap
interval on our ability to detect FB, as a more practical
consideration.
For each simulation with a changed parameter
value, we calculated the percentage change in average
gut contents of both upward- and downward-caught
copepods versus their paired run using the standard
parameter value. Average gut content was calculated
as the average of all copepods trapped in samples
taken from t = 3 to t = 9 h (n = 9). The initial and
final samples were not used, as they contained copepods which had either just migrated up from depth at
the start of the simulation or were forced to descend
at the end of the simulation, regardless of their
physiological state. Therefore, the motion of these
copepods past the traps was not foraging-behavior
dependent and not relevant to the comparison.
Within each run, to test for differences in gut contents
between upward- and downward-traveling copepods,
we calculated an analysis of variance (ANOVA),
comparing the four treatments: FB copepods caught
swimming up, FB copepods caught swimming down,
control behavior copepods caught swimming up and
control behavior copepods caught swimming down.
In all cases except for altering the concentration of
food within the lower layer, the ANOVA revealed a
significant difference between at least two of the treatments. We then conducted post-hoc paired t-tests,
pairing the samples by time, comparing the upwardversus downward-caught copepods for either FB or the
control behavior, using only those samples from t = 3 to
t = 9 h (thus n = 9 for these t-tests).
Table I: Standard parameter values
Parameter
Value
Description
Units
Imax
100 (75,125)
Maximum ingestion rate
ng Chl h1
ks
5
Ingestion half-saturation constant
mg Chl L1
H
5 (2.5, 7.5)
Hunger threshold
ng Chl
R
2 (1.5, 2.5)
Gut clearance rate
h1
Sstep
0.025 (.018, .031)
Average step size
m
Gmax
30
Maximum stomach content
ng Chl
Sink
0.01 (.0075, .0125)
‘Sink’ speed
m s1
Cu
20
Upper layer Chl concentration
mg Chl L1
Cl
1 (5, 10)
Lower layer Chl concentration
mg Chl L1
Mu
10
Mortality in the upper layer
Individual probability (%)
Ml
1 (5, 7.5)
Mortality in the lower layer
Individual probability (%)
Lu:Ll
15:35 (20:30, 25:25)
Relative layer vertical size, upper : lower
m
Deltat
10
Time step of model
s
Numbers in parentheses indicate the altered value of the parameter used for the sensitivity analysis. Chl, chlorophyll.
991
To compare differences in copepod success among the
different parameter sets, two metrics were calculated:
copepod fitness (the ratio of food ingested to probability
of mortality) and feeding success (total amount of food
ingested per night). Only those copepods that ate a
certain minimum ration were used for the calculation
of average copepod fitness, with the minimum ration
defined as the mean amount of food eaten per night by
the individuals from a particular run. The comparison
was limited in this fashion, because many of the copepods using the RC behavior never fed within the highfood, high-mortality layer. Thus, they had low mortality
probabilities but also very low nightly ingestion.
Although we did not model it explicitly, copepods
require a certain minimum daily ration in order to
meet their daily metabolic requirements, and in the
case of the current model, they also need to meet the
energetic demands associated with their diel vertical
migration. Without knowing exactly what this minimum
daily ration was for our simulated copepods, we therefore used the average minimum ration defined above as
a conservative means for eliminating copepods that may
not have met their metabolic requirements from the
comparison. The fitness and feeding success metrics for
the FB copepods were then compared with the values for
their paired RC. This was done as a percent anomaly,
calculated as the difference between the average value of
the metric for the foray copepods and the paired RC, all
divided by the average value of the metric for the control
copepods. We also compared the fitness metric between
the foray and control behaviors for each paired run set
using a two-sample t-test with unequal variance. To assess
effects of this behavior on the feeding success of potential
copepod predators, in a similar manner we also calculated
the anomaly of copepod abundance within the surface
and intermediate layer, comparing each foray-behavior
run with its paired random-behavior control.
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pycnocline (maximum was 36 mg L1 at 6 m depth) and
a sharp decrease to <1 mg L1 below 12 m. To mimic
this situation in the model, the upper layer depth was set
to 0–10 m, with the lower layer set to 10–50 m, with Chl
values within these layers set to 16 and 1 mg L1,
respectively. The standard parameter values were used
to control the simulated copepods, with no additional
‘tuning.’ To compare the model data with the fieldcollected data, simulated vertical net tows were taken
at similar intervals during the model run, sampling the
same depth bins as the field data. Because there was
some advection in the field, and some variability in
total numbers from sample to sample, all data was scaled
within a particular cast by the maximum number of
copepods collected so that the samples could be more
readily compared over time.
RESULTS
Standard scenario
On the basis of the simulated data for our zooplankton
trapping approach, it is clearly possible to differentiate
between the ‘foray’ and ‘RC’ foraging strategies (Fig. 2).
In both cases, there was a large upward flux of copepods
in the early evening, and a large downward flux in
the early morning, simply due to the overall vertical
migration behavior. However, for the FB, there are
several pulses of upward and then downward exchanges
of copepods between the high-food layer and the
low-food layer, as can be seen in the upward- versus
Caught up
Comparison with field data
600
500
400
300
200
100
0
Foray behavior
0
Average gut content
Field data were collected from Dabob Bay, WA (47
46.0770 N, 122 50.2320 W), 9 and 10 April, 2003.
Zooplankton samples were collected with a vertically
hauled Puget Sound net (1 m diameter, 209-mm mesh)
deployed at 1–2 h intervals throughout the night from
9:00 pm to 1:00 pm the next day. During each interval,
samples were collected from four depth strata: 100–50
m, 50–25 m, 25–10 m and 10 m-surface. Upon retrieval,
contents of the cod ends were placed in 500-mL glass
jars and preserved in 10% formalin seawater solution.
Calanus pacificus females were enumerated under a dissecting microscope. On these dates, a relatively strong
pycnocline was located between 10 and 12 m, with an
average Chl concentration of about 16 mg L1 above the
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12
10
8
6
4
2
0
2
4
6
8 10 12 0
Foray behavior
0
2
4 6 8 10 12 0
Time (h)
Caught down
Random behavior
2
4
6
8 10 12
Random behavior
2
4 6 8 10 12
Time (h)
Fig. 2. Results of the standard foray behavior (FB) case versus the
controls. Upper panels show number of copepods trapped per 45-min
interval, going either up or down. Lower panels show the average and
standard deviation of the gut contents of all individuals in the traps.
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Individual probability of
mortality
downward-caught trap data over time. From these data,
it is possible to conclude that copepods probably made at
least 2 if not 3 forays into the upper layer during the time
of the simulation. The actual average number of times
that the copepods filled their guts within the surface layer
(a measure of the number of forays conducted) was 2.48
(a value that could not be measured with traps but was
tracked within the model). For the RC behavior, there
was exchange between the two layers during the night,
but it was of much lower magnitude than the FB, and
there were no detectable coordinated pulses, as there were
within the FB case.
There was also a larger difference between the average
gut contents of upward- versus downward-caught copepods for the FB than for the RC (Fig. 2, lower panels).
In the field, if such samples were taken rather than
determining the individual gut fluorescence for each copepod (as has essentially been done to produce the data for
Fig. 2, lower panels), the average gut content would be
determined from replicates of batches of copepods, e.g.
five batches of 10 copepods each from within each net
might be analysed for their average gut fluorescence and
then the mean and variance of these five samples from
each net could be compared for statistical differences.
Simulating this more realistic procedure, t-tests were performed on the 10 pairs of samples taken during hours 3–9
of the simulation, comparing upward- and downwardcaught copepods from the FB runs, and separately
comparing upward- and downward-caught copepods
from the RC runs (alpha was set to 0.005 for each t-test,
under the Bonferroni correction criteria; the total alpha
for the ten pairs of samples = 0.05). Based on this analysis,
mean copepod gut content of FB was significantly greater
for downward- than upward-caught copepods for all
4.0%
10:1%
3.5%
3.0%
sample times except for t = 5.25 h. For the RC, there
was no significant difference between the mean gut
content of upward versus downward copepods for five
out of these 10 sample times. Thus, based on a procedure
more similar to what might be conducted with real samples, the FB would result in samples where differences in
gut contents between upward- and downward-caught
copepods could be detected.
Although it could not be estimated using trap samples
similar to those that might be deployed in the field, the
IBM model allowed tracking of the total ingestion and
probability of mortality of each individual copepod
throughout the simulation. For the standard run, mortality rates were set to 10% per night within the upper
layer and 1% per night within the deeper layer. Thus,
the total nightly probability of any individual copepod
dying was a function of the time it spent within each
layer, given the mortality probability within that layer.
Under the standard setting, copepods with FB had a
much lower individual probability of mortality than
the RC copepods, for a given amount of food ingested
(Fig. 3). The calculated fitness metric—food ingested
divided by probability of mortality—was also significantly higher for the foray copepods than the RCs
under the standard parameter set (two sample t-test,
unequal variance; P < 0.001). As the mortality rate of
the lower layer increased, the relative mortality difference between the foray and random behavior copepods
decreased; the fitness metric was significantly greater for
the foray copepods than the controls when the lower
layer mortality was raised to 5% night1 (two sample
t-test, unequal variance; P < 0.01) but not significantly
different than the controls at 7.5% night1 (two sample
t-test, unequal variance; P > 0.05). However, no matter
10:7.5%
10:5%
2.5%
2.0%
1.5%
1.0%
0.5%
Random
Foray
0.0%
0
100 200 300 400 0
100 200 300 400 0
100 200 300 400
Total ingestion (ng copepod–1)
Fig. 3. Comparison of predicted individual morality probability versus total food ingested per copepod per night, for the foray behavior (FB)
versus the random swimming control, versus three different levels of relative mortality pressure within the lower layer. Mortality rate within the
upper layer was held constant at 10% per night. Mortality within the lower layer was set to 1% (left), 5% (middle) and 7.5% (right) per night.
Upper layer food concentration was 20 the lower layer.
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what the mortality rates were, each copepod from
within the foray simulations always obtained at least a
certain minimum nightly ration (in these cases, >100 ng
copepod1), whereas there were a large number of individuals from within the random behavior simulation that
had low relative nightly ingestion (Fig. 3).
Sensitivity analysis
Decreasing the maximum ingestion rate, Imax, led to a
lower flux of individuals between the two surface layers
(Fig. 4, top left panel), as indicated by the lower number
of individuals caught within the virtual traps, as compared to the standard case (Fig. 4, top center panel).
Increasing the value of Imax did not greatly increase the
flux of individuals between the layers (Fig. 4, top right
panel). Evidence of forays was detectable via the trap
data regardless of the value of Imax, as shown by the
relative timing of peaks for upward- versus downwardcaught copepods. There was little change in the average
gut content of copepods caught in the traps, for either
the FB or RC simulations, with a change in Imax (Fig. 4,
middle panels), although gut contents of downward
traveling copepods increased slightly for both as Imax
Fig. 4. The effects of altering the maximum ingestion rate, Imax,
versus number of copepods caught in the virtual traps (top panels),
gut levels (middle panel) and ingestion versus mortality (bottom panels).
Top panels show number caught per trap, going up or down, from the
foray-based simulations only, with ingestion rate increasing (gut filling
time decreasing) from left to right. Middle panel shows gut contents of
all individuals averaged from all traps taken from t = 3 to t = 9 h, for
both the foray-based behaviors and for the random swimming controls.
Error bars show 1SD of all samples taken from t = 3 to t = 9 h.
Bottom panels show predicted individual mortality probability versus
total food ingested.
27
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increased. Regardless of the value of Imax used, there
was always a larger difference between the downwardand upward-caught copepods for the FB case than for
the RC; for both cases, gut contents of downwardtrapped copepods was significantly greater than upward
trapped copepods, although the significance level was an
order of magnitude greater for the foray case (Table II).
The relative difference in individual probability of mortality for a given amount of food ingested for FB versus
RC increased with an increase in Imax, while counter
intuitively, the maximum amount of food ingested per
night decreased as Imax increased (Fig. 4, bottom panels).
This is due to the rules used to control the ‘refractory’
period between feeding bouts. At a high value of Imax,
the gut is filled more quickly to Gmax, at which point the
copepods stop feeding and enter the refractory phase
(and sink if they are using the FB). Thus a copepod
with a high value of Imax would spend more time within
the refractory, non-feeding phase, sink out of the upper
layer more often and subsequently achieve a lower total
nightly ingestion. This may seem suboptimal, although
these same copepods had a much lower mortality risk,
than those that remained within the surface layer longer.
Changing the gut clearance rate, R (which also has a
direct effect on the time spent within the refractory, nonfeeding phase), had a large effect on the amplitude of the
variability of copepods caught going up versus down
over time (Fig. 5, top panels). Decreasing R led to larger
differences between the gut contents of trapped copepods caught up versus down for FB, whereas increasing
the gut clearance rate constant decreased the difference
in gut contents of the copepods between the FB and RC
(Fig. 5, middle panel), making gut contents alone a less
useful criteria for detecting forays, although differences
in gut contents were significant for all cases (Table II).
Relative difference between foray and control copepod
mortality for a given amount of food ingested, decreased
with an increase in the gut clearance rate constant; foray
copepods with a higher gut clearance rate spend more
time within the surface layer (less time within the refractory phase where they sink into the lower layer) and thus
have a mortality more similar to the random behavior
controls. For the highest gut clearance rate constant
used, there were a number of individuals for both the
control and FB copepods that reached very high nightly
ingestion levels (Fig. 5, bottom right panel). This was
because the value of 2.25 h1 was the average gut
clearance rate used, whereas, as described above, individuals were randomly given a range of clearance rates
up to 25% greater than this average value. Given the
standard value of Imax, and the maximum food concentration within the upper layer, copepods with gut clearance rates >2.7 h1 could never completely fill their guts
994
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COPEPOD FEEDING FORAYS
Table II: Results of the sensitivity analysis on average gut content of trapped copepods
Parameter
Change in
% change average gut content
Paired t-test P value,
parameter
Imax
H
R
Sstep
Sink
Control up
Control down
Foray up
25%
24
12
17
+25%
19
6
28
50%
4
4
2
Lu : Ll
Trap interval
Foray down
Control
Foray
2
.004
.0005
21
.01
.0001
0.8
.008
.0003
.0005
+50%
6
3
5
3
.006
25%
39
34
45
46
.014
.00004
+25%
28
16
24
27
.0074
.0067
25%
1
12
14
.014
.0001
+25%
5
16
0.2
1.6
.002
.0002
25%
2.2
4.6
4.4
.005
.0035
+25%
Cl
up versus down
7.9
5
175
10
7
1.5
0.3
22
.003
.00007
104
184
22
.36
.58
226
22
.38
.19
154
89
+55%
1
5
+133%
4
2
3
25%
38
17
+25%
28
27
0.7
2.9
7.2
.003
.0001
3
.005
.0009
36
28
2.6 106
1.5 1011
20
24
.009
.007
For all t-tests, n = 9.
Fig. 5. The effects of altering the gut clearance rate, R, on the trap
catch (top), gut content (middle) and ingestion versus mortality (bottom). From left to right, the gut clearance rate constant increases from
1.5 h1 to 2 and to 2.5 h1, which changes the time between forays
from 1 to 0.9 and to 0.8 h.
to Gmax and therefore never left the upper layer. In all
three cases, however, copepods using the FB had significantly higher values of the fitness metric than the
controls (two-sample t-test, unequal variance; P < 0.01).
Changing the hunger threshold, H, had little or no
effect on the gut contents of copepods caught within the
traps, or the mortality of the copepods for a given
amount of food ingested (Fig. 6, middle and bottom
panels), although it had a large effect on the flux of
copepods between layers (Fig. 6, top panel). Increasing
the threshold and thereby decreasing the time spent
within the refractory, non-feeding (and sinking for the
FB) period, resulted in an increase in the number of
individuals swimming between the two layers. Conversely, decreasing the hunger threshold (meaning that
copepods must digest more of their stomach contents
before ‘reviving’) led to lower exchange between layers
and therefore fewer forays per individual per night
(Fig. 6, left top panel). At higher threshold levels, copepods spent less time in the refractory phase, and more
time feeding, and thus nightly ingestion reached higher
maximum values for some copepods (Fig. 6, bottom
right panel). As for ingestion rate, in all three cases,
copepods using the FB had significantly higher values
of the fitness metric than the controls (two-sample t-test,
unequal variance; P < 0.01).
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Fig. 6. Effect of altering the hunger threshold, H, on the trap catch
(top), gut content (middle) and ingestion versus mortality (bottom).
Hunger threshold increases from left to right from 2.5 to 5 and to 7.5 ng
per copepod.
Table II summarizes the results of the remaining
sensitivity analyses on the gut contents of the trapped
copepods. Compared to the physiological parameters,
swimming speed, Sstep, had less of an effect on the gut
content of the trapped copepods. The difference in gut
contents between upward- and downward-caught
copepods was highly significant for the foray copepods
(P < 0.005) regardless of whether swimming speed was
increased or decreased. Sinking rate also had little effect
on the model outcome for average gut content, with the
greatest change for downward-caught FB copepods with
a 25% reduction in sinking rate (a decrease of 22%).
Even with this decrease in gut content, the difference
in gut content between upward- and downwardcaught copepods was still highly significant (P < 0.005).
Changing the vertical extent of the layers led to little or
no change in the model results for either gut content
(Table II) or numbers caught within the traps (data not
shown).
Increasing the concentration of food within the lower
layer to 5 mg Chl L1, led to large changes in the gut
contents of foray and control copepods (Table II), with
the difference between upward- and downward-caught
copepods being indistinguishable (P > 0.05), although
forays were still detectable by examining the number of
copepods caught swimming up or down versus time
(data not shown). At 10 mg Chl L1, not only were gut
contents no different between controls and FB but also
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were forays not detected from the vertical flux data. This
is because many of the copepods filled their guts completely within the lower layer, and initiated sinking from
within that layer, since this food concentration was well
above the half-saturation constant of their feeding
response (which was set to 5 mg Chl L1). As a result,
there was no significant difference between upward- and
downward-trapped copepods for either the foray or control cases under these higher lower-layer food levels
(Table II).
The last parameter examined was the time interval
between trapping the copepods. As would be expected,
numbers of copepods caught per trap increased as trap
interval increased (data not shown), which would make
detection of FB easier. Differences between the gut contents of upward- versus downward-caught FB copepods
increased as trap interval decreased, (Table II), as seen
by the highly significant P values for a decreased trap
interval, although the difference was still significant for
the longer trap interval.
To summarize the effects of varying these different
parameters on the copepods and their potential predators, as described above we also calculated an anomaly
of copepod fitness measured in two different ways: the
ratio of ingestion to mortality (relative fitness) and total
nightly ingestion (feeding success; Fig. 7), along with the
anomaly in copepod abundance within the surface
(upper) and intermediate (lower) layers (Fig. 8). For the
best-guess parameter set, copepod concentration within
the surface layer was nearly 40% higher for the FB
simulation versus the RC behavior simulation (Fig. 8).
Relative fitness of the FB copepods was nearly 45%
higher than RCs (Fig. 7). Growth potential (total amount
eaten) was also higher for the FB, although the individual variability was very high (as denoted by the large
error bars). The largest increases in copepod abundance
within the upper surface layer occurred when any parameter was changed such that the time to fill the gut was
increased, e.g. lowering Imax or raising the gut clearance
rate. Under these parameter choices, copepod fitness did
not increase relative to the controls, although copepod
growth potential was on average higher but with higher
individual variability. Conversely, highest copepod
fitness was achieved when parameters were set to minimize the time taken to fill the gut, e.g. increasing Imax or
decreasing the gut clearance rate. These cases also led to
no increase in growth potential versus the controls.
Comparison with field data
We also ran our model in such a way as to simulate the
conditions present on 9 April, 2003, from within Dabob
Bay, WA, and compared it to field samples of copepod
vertical distribution from that same time period (Fig. 9).
996
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225%
Ingestion/mortality
175%
Total ingestion
125%
75%
25%
–25%
–75%
te
ra
te
th
r
H
es
ig
ho
Eq h t
ld
ua hr
es
lho
si
ld
H zed
ig
la
co h
y
nc low er
Lo en er s
w tra la
sw tio ye
n r
Lo im
sp
w
e
si
nk ed
sp
ee
d
Lo
w
ra
ea
cl
t
h
gu
gu
H
ig
w
Lo
nc
e
ce
an
ig
ea
r
H
cl
t
St
ra
ax
ax
h
w
Lo
d
an
da
r
Im
Im
ra
y
–125%
fo
Average individual fitness anomaly
(relative to control)
A. W. LEISING ETAL.
Parameter set
Fig. 7. Average relative fitness (ingestion/mortality) and feeding success (total ingestion) of all copepods from each simulation. Error bars show
1SD of the fitness metric for all individuals (n = 1000) from within each simulation. From left to right, categories represent (i) the standard ‘bestguess’ foray behavior (FB) case, (ii) FB with the value of Imax lowered by 25% from the standard case, (iii) FB with Imax raised by 25%, (iv) FB with
gut clearance rate, R, decreased by 25%, (v) FB with R increased by 25%, (vi) FB with the hunger threshold, H, decreased by 50%, (vii) FB with H
increased by 50%, (viii) FB with the vertical extent of the layers changed from upper = 0–15 m, lower = 15–50 m, to upper = 0–25 m, lower = 25–50 m,
(ix) FB with the concentration of food in the lower layer raised from 1 m chlorophyll (Chl) L1, to 10 mg Chl L1, (x) FB with a lower swim speed
of 1.875 cm s1 and (xi) FB with a lower sink speed of 0.75 cm s1.
Upper layer
150%
Lower layer
100%
50%
0%
–50%
Im
Lo
w
gu
t
ig
w
Lo
H
fo
rd
St
an
da
H
ig ax
h
cl
Im
e
h
ar
gu
an ax
t
ce
cl
ea
ra
ra
te
nc
Lo
e
ra
w
te
th
r
H
es
ig
ho
Eq h t
ld
hr
ua
es
lho
si
H
ze
ld
ig
d
h
co
la
l
o
nc w ye
e e
r
Lo ntr r l s
a
a
w
t y
sw ion er
i
m
Lo
w
s
si pe
nk ed
sp
ee
d
–100%
ra
y
Copepod abundance anomaly
(relative to control)
200%
Parameter set
Fig. 8. Average abundance anomaly of foray copepods versus their paired random behavior control, within either the surface (upper) layer or the
intermediate (lower) layer, from simulated vertical net tows taken every 45 min over a 6-h period (from t = 3 to t = 9 of the simulation). Categories
(horizontal axis) as described for Fig. 7. Error bars show 1SD of the average abundance from the 9 ‘net tows’.
To compare between profiles over time, for each profile
(model or field) the data has been scaled by the maximum copepod concentration from within that profile.
Whereas there is not a clear match at all time points
between the model and field data, the general trends of
the field data do not preclude the model results; albeit,
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Fig. 9. Comparison of vertical distribution data taken from the model standard run (black bars, right hand side) versus field-collected data for
Calanus pacificus females (grey bars, left hand side), taken on 9 and 10 April 2003 from Dabob Bay. Numbers across the top indicate the time of the
tow in decimal hours. For comparison between the model and field data, the abundance values (originally as number of copepods m3) at each
time point are scaled by the maximum abundance for that vertical series. Time points with no bars indicate no field data was taken during that
time point.
there may be other behaviors which could have led to
such distributions. A random behavior, however, would
not have led to the distribution shown, as random
swimming results in a nearly exact equal abundance of
copepods within the two surface layers during most of
the night; this was not observed. Instead, the field data
seems to be more consistent with the idea that the
copepods could have undergone at least two forays
during the early morning, one near 2:30 am (t = 2.5)
and one near 4:45 am (t = 4.75). Our model also has the
copepods leaving the surface waters too soon to begin
the normal downward leg of their daily vertical migration. Unfortunately, the temporal resolution of the field
sampling was not detailed enough to evaluate the success
of the model, and it is unclear whether the copepods
from the field may have undergone an initial migration
into the surface waters upon their initial ascent from
depth, as there are no samples from this time.
DISCUSSION
If FB is used by C. pacificus, then our model results
indicate that in most cases this behavior confers a large
advantage to feeding success and a considerable reduction in mortality, relative to copepods that just swim and
feed at random throughout the upper water column. As
might be expected, the mortality benefit decreases as the
mortality rate within the lower layer approaches the
mortality rate of the surface layer. However, no matter
what the relative mortality rates are, if grazing rates are
food limited within the lower layer, then the FB always
confers a feeding advantage to the copepods, since it
enables them to spend most of their feeding time within
the high-food region, and most of their digestive/refractory time within the low-food region. Under the random
behavior scenario, a few individuals had higher nightly
total ingestion than any of the FB copepods. However,
all of the FB copepods typically received a minimum
daily ration much higher than a large proportion of the
randomly behaving copepods. Thus random behavior
may confer an advantage to a few individuals, whereas
the FB ensures a certain level of success for all individuals, although these few random foragers also had the
highest probability of mortality.
Field evidence supports the existence of foray-like
behaviors in certain cases. Simard et al. (Simard et al.,
1985) found that C. finmarchicus within the St. Lawrence
estuary, where Chl was mainly found only above 30 m
within the fresh, warm surface layer, were rapidly filling
their guts upon their initial migration into the surface
and then quickly descending below this layer. The copepods would then ascend again before dawn to feed a
second time. Simard et al. (Simard et al., 1985) point out
that the copepods gained an additional benefit from
ascending into the surface layer to feed, since these
waters were significantly warmer than deeper layers,
thus enabling a much more rapid filling of the gut.
Durbin et al. (Durbin et al., 1995) also observed similar
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behavior for C. finmarchicus within the Gulf of Maine.
Tarling et al. (Tarling et al., 2002) observed that
C. finmarchicus within the Clyde Sea abandoned the
high-food surface layer fairly rapidly upon the arrival
of high numbers of krill within this layer. However,
Tarling et al. (Tarling et al., 2003) also concluded that
such synchronized departure from the surface occurred
regardless of the hunger state of the copepods, yet
acknowledged that there still could be satiation responses
leading to exchange of individual between the surface
and deeper layers. Our modeling results suggest that
even with relatively asynchronous initial upward migration and with a relatively high level of variability in
individual physiology (approximately, our gut clearance
rates varied by 25% between individuals), synchronous
sinking and re-ascent can occur through most of the
night. Within Dabob Bay, numerous studies have
shown that concentrations of C. pacificus are typically
higher below the surface, high-food layer, than within
(Frost, 1988, references therein; Dagg et al., 1989, 1997,
1998; Bollens et al., 1993; Pierson et al., 2005b). Yet
from measurements of gut contents (Dagg et al., 1989,
1997) and egg production (Pierson et al., 2005a), it is
clear that individuals must be feeding within the surface
layer, at least for some portion of the night. There is also
evidence that predation on C. pacificus is high within this
surface layer, and that there are seasonal correlations
between the extent of vertical migration behavior and
potential predator abundance (Bollens and Frost, 1989).
Further, although the data are limited, the correspondence between our model results and the only set of field
data amenable to comparison seems to rule out random
foraging behavior, at the very least, and certainly does
not preclude the existence of foray-like behavior.
From another point of view, it is equally important to
consider what effect the existence of FB might have on
the feeding success of copepod predators. Figures 7 and
8 show a summary of the results of the sensitivity analyses in terms of both copepod success and changes in
copepod abundance within the two upper layers. If a
predator is limited only to the surface-most layer, then
changes in the abundance of copepods within that layer
caused by different copepod behaviors should affect the
feeding of the predator when the prey is limiting. Under
the standard case scenario of FB, the average nightly
abundance of copepods within the upper surface layer
increased by nearly 35% (Fig. 8) compared to copepods
that swam randomly. As might be expected, the greatest
increases in average night-time surface copepod abundance occurred whenever the physiological parameters
led to longer gut-filling times (and thus higher surfacelayer residency times), such as when the maximum
ingestion rate was lowered, or when the gut clearance
rate was raised (Fig. 8). However, for these cases the fitness
of the foray copepods was no different than for randomly
behaving copepods. For both the standard foray parameter set, and the ‘high threshold’ sensitivity run, the
abundance of copepods within the surface increased, and
the fitness of the copepods increased. As counterintuitive
as this may seem, it therefore appears that there are
conditions that increase the success of both the predator
and the prey. It is possible that such an increase in surface
abundance of copepods may not always increase the
success of the predators. For instance, the FB may lead
to somewhat bimodal surface copepod densities over
time, due to the semi-synchronous nature of the forays
set up by the initial upward migration after sunset. If
these surface copepod density vary between very low
and very high values, then the predators may go from a
situation of severe prey limitation, to a situation where
their ingestion response is saturated. In this case, although
the nightly average surface abundance of copepods
might be higher when the copepods use FB, the end result
may actually be a poorer feeding environment for the
predators.
Under what conditions were forays detectable by our
trapping scheme? This is a critical question, for although
our model results suggest advantages of the FB, its
existence in natural settings may remain unknown unless
it is possible to detect it via practical sampling schemes.
Here, we proposed a scheme that could be carried out
using vertically towed, opening and closing nets to sample distributions, along with upward and downward
facing traps (the technical details of which seem surmountable), which could collect upward and downward
swimming copepods over time. These samples could
then be assayed for gut fluorescence to detect differences
in feeding state. Other markers besides gut Chl concentrations could be used equally as well [such as high
performance liquid chromatography (HPLC) or highmagnification digital imagery of gut contents, or more
advanced assays; see Pearre, 2003] or might complement the gut Chl measurements. Given these conditions,
and under our ‘best-guess’ scenario for the parameters
controlling the swimming and feeding of C. pacificus, it
seems probable that our simulated field-sampling
scheme would be able to detect the use of FBs by the
copepods. However, there were also cases where our
simulated sampling scheme would not be able to detect
forays, or rather, certain elements of the sampling would
reveal little about the copepods behavior. First, copepod
gut fluorescence alone became less useful in detecting
forays when the gut clearance rate was increased (Fig. 5).
Gut clearance rate may vary with temperature (Dam
and Peterson, 1988), feeding history (Kiørboe and Tiselius,
1987), and possibly food concentration (Mullin et al.,
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1975; Pasternak, 1994), and could therefore increase to
levels making gut fluorescence a poor indicator of FB.
Potentially, measurements of gut clearance rates under
ambient conditions might be necessary to augment the
field sampling described above. Decreased sinking or
rather downward displacement speeds also decreased
the utility of gut fluorescence as a marker of FB. In
this case, there may be other markers, such as lipid
content, or Chl to phaeopigment ratios, which might
be better markers of recent feeding history. Even if
physiological markers fail to differentiate FB, directional trap sampling may still be used in most cases
to infer the use of FB. Of course, trapping may be
susceptible to problems of high variability typical of
such net sampling, or worse due to the nature of the
proposed upward- and downward-facing traps. Our
analysis showed that closer spaced temporal sampling
could increase the ability to resolve the peaks and
troughs of the semi-synchronous forays, yet decreasing
the sample interval decreases the number of copepods
caught per trap, and may also push the limits inherent
in physically deploying such traps. Although not
shown here, the addition of both multiple upward–
downward facing traps at the same depth, yet at a
different location, along with more traps spaced at
different depths, would increase the ability of such a
system to detect FB, and reduce interpretive problems
due to sample variability.
Although there may be other, possibly more complex behaviors which could lead to the distributions
and observations supporting the hunger/satiation
foraging hypothesis, our modeling results suggest that
a relatively simple behavior like that proposed here
could lead to such observations. Whether the behavior
is as simple as we suggest, or more complicated, the
implications of such behaviors are significant for both
the population dynamics of the copepods and the
feeding environment for their predators (Pearre,
2003). Specifically, our results suggest not only that
a foray-like behavior could greatly enhance the feeding success of the copepods while reducing their individual probability of mortality, but that there could be
periods of increased copepod abundance within particular strata which would in turn enhance the prey
field for planktivores. Further, our proposed sampling
scheme seems technically feasible and should be able
to detect the existence of foray-like behaviors under
most cases. In conclusion, given the broad global
distribution and trophic importance of Calanus species,
both as grazers on phytoplankton and food for commercially important fish species, conducting further
field and laboratory studies to determine the nature
and existence of such behaviors is warranted.
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ACKNOWLEDGEMENTS
A.W.L. thanks the staff at the Pacific Fisheries Environmental Laboratory for many comments and helpful discussions during the course of the development of this
model. This article is dedicated to G.A. Paffenhöfer,
whose work on copepods has pioneered aspects of copepod feeding behavior on multiple scales and stimulated
many of the questions leading up to this study. The
comments from two anonymous reviewers significantly
helped this work. As always, the crew of the C.A. Barnes
were invaluable in obtaining the copepod distribution
data. J. Pierson and S. Cary were supported by the NSF
through contract OCE-0118044 to B. Frost.
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