Sucking while swimming: evaluating the effects of ram speed on suction generation in bluegill sunfish Lepomis macrochirus using digital particle image velocimetry
Section of Evolution and Ecology, University of California, One Shields Avenue, Davis, CA 95616, USA
* Author for correspondence (e-mail: tehigham{at}ucdavis.edu)
Accepted 11 May 2005
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Summary |
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Key words: DPIV, suction feeding, ram feeding, Centrarchidae, sunfish, Lepomis macrochirus, locomotion, swimming
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Introduction |
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One important issue about the combined use of ram and suction concerns how
the two behaviors may hydrodynamically combine
(Weihs, 1980;
Muller et al., 1982
;
Muller and Osse, 1984
). How
does the attack velocity of the predator influence the spatial pattern of
fluid flow entering the mouth? The influence of ram speed on the water
ingested during suction feeding was estimated by Weihs
(1980
) using a hydrodynamic
sink model. In this model, the ingested volume of water became focused in
front of the mouth as ram speed increased. The shape of the ingested volume of
water appears to be related to the ratio of ram speed to fluid speed, such
that higher values will result in the capture of narrower and more elongated
parcels of water (Weihs,
1980
).
One metric of suction performance is the maximum fluid speed moving towards
the mouth of the fish. While it may be possible that ram and suction work in
concert to increase overall prey capture performance
(Wainwright et al., 2001), it
has also been suggested that swimming can decrease suction performance
(Nyberg, 1971
). The idea is
that fluid flow is determined by the rate of buccal expansion, and if swimming
speed approaches that of the suction-induced flow, net flow in the absolute
reference frame could be negligible because most of the water flow into the
mouth will be passive (Nyberg,
1971
; van Leeuwen,
1984
). Additionally, a swimming fish produces water movement in
front of it, termed a bow wave, and it is possible that this could negatively
influence the suction flow (Nyberg,
1971
; Lauder and Clark,
1984
; Muller and Osse,
1984
; Van Damme and Aerts,
1997
; Summers et al.,
1998
; Ferry-Graham et al.,
2003
).
In the present study we visualized the flows generated by suction-feeding
bluegill sunfish using digital particle image velocimetry (DPIV;
Fig. 1; e.g. Drucker and
Lauder, 2002,
2003
), and we measured the
effect of bluegill swimming speed on aspects of the induced suction flows.
Depending on the question, we measured fluid speed FS in either the
earth-bound, or absolute, frame of reference (AFS) or the fish's
frame of reference (FFS). We focused on the following three
questions: First, does ram speed affect the maximum fluid speed entering the
mouth during suction feeding, as measured in the absolute frame of reference?
We hypothesize that, if the fish is stationary, fluid speed in the absolute
frame of reference (AFSstationary) will result exclusively
from buccal cavity expansion. However, if the fish is swimming at a ram speed
RS, then fluid speed at the mouth aperture in the absolute frame of
reference (AFSswimming) will equal the predicted fluid
speed if the fish were not moving (AFSstationary) minus
the magnitude of RS. This is because when the buccal cavity expands,
water will enter the mouth passively at a speed equal to the swimming speed of
the fish. We therefore expected that increases in ram speed would result in
decreasing fluid speed as long as buccal expansion rate is identical.
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Lastly, does ram speed affect the shape of the ingested volume of water, as
measured in the absolute frame of reference? If water flow into the mouth
becomes more focused with increasing ram speed, this should influence the
dimensions of the parcel of water that is captured during a suction feeding
event. Modeling studies (Drost et al.,
1988; Weihs, 1980
)
and limited empirical work (van Leeuwen,
1984
) have indicated that this will be the case, with higher ram
speeds resulting in the ingested parcel of water becoming elongate in the
direction of swimming and reaching farther away from the mouth aperture.
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Materials and methods |
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Experimental protocol
Each bluegill was placed in the experimental tank and trained to feed in
the laser sheet (see below). At the onset of experiments, the individual was
kept at one end of the tank and restrained behind a door
(Fig. 1). A tubifex worm
(1.0 cm) or a ghost shrimp (Palaemonetes sp., about 2 cm), was
then dropped through a 0.3 cm diameter plastic tubing or attached to a thin
wire, held within the laser light sheet and within the camera field of view,
and the door was lifted. Varying locomotor speeds were elicited by introducing
the prey items at one of three distances from the fish
(Fig. 1AC). Previous
work indicates that bluegill will capture prey with relatively high ram speeds
when traversing distances within the range used in this set-up (T. E. Higham,
B. Malas, B. C. Jayne and G. V. Lauder, manuscript submitted for publication).
Each individual was fed at every location and the order of locations for each
fish was arbitrarily chosen.
Digital Particle Image Velocimetry (DPIV)
We used DPIV to quantify a number of parameters describing the flow of
water into the mouth during suction feeding. Willert and Gharib
(1991) provide a detailed
description of this technique for measuring fluid flow. An Innova-90 5 W
argonion continuous wave laser (Coherent, Inc., Santa Clara, CA, USA) was used
in combination with a set of focusing lenses and mirrors to produce a vertical
laser sheet that was approximately 10 cm wide and 1 mm thick in the aquarium
(Fig. 1). Theaquarium was
seeded with silver coated, neutrally buoyant glass spheres (12 µm) in order
to visualize the flow of water. Mirrors above and below the tank were used to
illuminate both above and below the head of the fish during feeding
(Fig. 1). Lateral-view video
sequences were recorded using a NAC Memrecam ci digital system (Tokyo, Japan)
operating at 500 images s1
(Fig. 1) with a field of view
of 5.1 x6.7 cm. Additionally, a Sony CCD camcorder (Tokyo, Japan),
operating at 30 images s1, was used to capture anterior view
images for each sequence in order to determine the orientation and position of
the fish relative to the laser sheet. While we only analyzed sequences
recorded in lateral view in this study, we have found that the flow pattern
generated by bluegill is radially symmetrical about the long axis of the fish
(Day et al., 2005
).
An adaptive mesh cross correlation algorithm created by Scarano and
Riethmuller (1999) was used to
calculate velocities from image pairs. The distance that particles traveled
between image pairs (2 ms interval) was determined within interrogation
windows with dimensions of 0.9 x0.9 mm, with 50% overlap between
interrogation windows. The algorithm then returned a two-dimensional grid of
two components of measured velocity for each image pair that was processed.
Two-dimensional (x and y) velocity vector profiles were
visualized using Tecplot version 10 (Amtec Engineering, Inc., Bellevue,
Washington, USA).
In order to determine the validity of the vector measurements, a two-step validation scheme was implemented. Only vectors with a signal-to-noise ratio (SNR) of 2 or greater were included in the analyses, and no smoothing was applied to the final velocity field. Some spurious measurements passed the SNR validation criterion, and the second part of the validation scheme accounted for these measurements. Measurements both directly on the transect (i,j) and at two grid points above (i,j+2) and two grid points below (i,j2) were considered at each horizontal position along the transect. Measurements located two grid points away from the primary measurement location were used, because these do not overlap the primary measurement region. If at least two of the three measurements considered had not been removed, based on the SNR criterion (step one of the validation scheme), then the mean of the remaining measurements was used as the value of speed for that position along the transect. Finally, for several sequences we confirmed that measurements with an SNR of 2 were accurate by tracking particles manually for several sequences using IMAGE J version 1.33 (NIH, Washington, DC, USA).
A transect extending forward from the center of the fish's mouth was studied to measure the speed of the fluid as a function of distance from the mouth. The closest position to the mouth where accurate measurements of velocity vectors were made in 100% of the sequences was at a distance equal to one half of the peak gape diameter (PG) of the fish for the feeding sequence. The accuracy at this position was validated in every trial. All vector velocities reported in this paper are at this distance and the term `AFS1/2 PG' refers to the speed of the fluid at this position.
Data analysis
The statistical analyses were performed only on those feedings that met the
following criteria: (1) successful prey capture occurred, (2) the laser sheet
intersected the mid-sagittal plane of the fish (verified with the anterior
view camera), (3) the fish was centered on the filming screen in lateral view,
and (4) maximum gape followed prey capture. The last point is important
because the prey item can interfere with the DPIV measurements, which were
made at maximum gape.
Using IMAGE J, the x and y coordinates of the tip of the
upper and lower jaw were digitized for each image (2 msintervals) starting
before the onset of mouth opening and ending after the mouth was closed. These
points were used to quantify changes in gape and to calculate maximum gape for
every feeding sequence. Time to peak gape (TTPG) was measured as the
time from 20% to 95% of maximum gape. This method for measuring TTPG
reduced errors that are related to a variable rate of early mouth opening and
the difficulty in clearly identifying the point where the peak value is
achieved in an asymptotic relationship. TTPG was measured as an
indication of the rate of buccal expansion that is used by the fish to
generate suction (Sanford and Wainwright,
2002). The x and y coordinates of the anterior
margin of the eye were digitized and used to quantify ram speed throughout the
strikes. Although ram speed usually varied during the course of the strike,
`ram speeds' reported in this study were measured at the time of 95% of
maximum gape, the same time that flow speed was measured.
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To determine the degree of focusing (DF) of water flow that was directed towards the mouth, the streamlines in the fish's frame of reference were visualized using Tecplot, and we determined the most dorsal and ventral streamlines that entered the fish's mouth. At a distance anterior to the fish equal to the fish's maximum gape, we measured the maximum vertical distance between these outermost streamlines (Fig. 2) and then scaled this value by the maximum gape of the fish. The reciprocal of this value is defined as DF such that larger values of DF indicate a smaller vertical distance between streamlines and a flow pattern that is more focused in front of the fish.
To determine the shape of the ingested volume of water, we visually tracked particles going into the mouth using IMAGE J and drew a boundary around the outer limit of particles that entered the mouth (Fig. 3). We measured the maximum height and the length of this boundary and converted the measurements to a ratio that described the aspect ratio of the ingested volume in lateral view.
We used SYSTAT version 9 (SPSS Inc., Chicago, IL, USA) for all statistical
analyses. All variables were first log10 transformed to normalize
variances, and in each case this allowed the variables to meet the assumptions
of the parametric procedures. We performed mixed-model multiple regressions
with individual (categorical, random), TTPG (continuous), and ram
speed (continuous) as the independent variables and all two-way and the
three-way interaction terms, with the following dependent variables: (1)
maximum fluid speed (AFS1/2 PG), (2) the degree of
focusing (DF) of the water moving towards the mouth of the fish, and (3) the
height-to-length ratio of the ingested volume of water. TTPG was
included as a variable in the analyses because it strongly affects the suction
speed in bluegill sunfish (Day et al.,
2005). Each complete multiple regression model was first run and
all variables with P>0.5 were removed from the model, and the
reduced models were re-run in a final analysis. All P values from
this second analysis are presented in Table
1. Unless stated otherwise, all results are presented as mean
± S.E.M.
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Results |
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As ram speed increased, the height-to-length ratio of the ingested volume of water decreased significantly, indicating that a more elongated volume of fluid was captured (Table 1, Figs 3, 7). While we only quantified the dimensions of the water parcel that entered the mouth during the strike, water outside this boundary was also moved by the suction.
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Discussion |
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Swimming and suction performance
In contrast to our expectation, bluegill sunfish did not forfeit suction
fluid speed when using forward swimming during feeding. Overall body closing
speed was therefore enhanced by incorporating both suction and ram. For a
bluegill using relatively high amounts of suction, the effect of moderate
increases in ram speed is additive and results in increasing closing speed of
the predator. This insensitivity of suction speed to moderate amounts of ram
has not previously been recognized or predicted
(Muller and Osse, 1984;
van Leeuwen, 1984
), and we
suggest that it may be biologically significant for suction feeding predators,
like bluegill and many other species, that feed on prey that have some
capacity to escape suction flows. Thus, there was no apparent hydrodynamic
trade-off between ram and peak fluid speed over the range of values observed
in this study.
In feeding bluegill the fluid speed generated during suction decays rapidly
with distance from the mouth aperture such that AFS1/2 PG
is approximately 25% of that at the mouth aperture
(AFSaperture) (Fig.
8; Day et al.,
2005). Using this proportionality, we can estimate
AFSaperture using our measurements of AFS1/2
PG. We find that the ram speeds were approximately 020% of
maximum AFSaperture. For a hypothetical
AFSaperture of 100 cm s1, a ram speed of
20 cm s1 would reduce AFSaperture to 80
cm s1 in the absolute frame of reference. This 20% decrement
in fluid speed should then apply to all positions from the fish's mouth
because the scaled shape of the relationship between flow speed and distance
is uniform across the range of fluid speeds and ram speeds observed in our
study (Day et al., 2005
). If
AFS1/2 PG is 25% of AFSaperture, a ram
speed of 20 cm s1 would reduce AFS1/2 PG
by 5 cm s1. However, body closing speed, or the speed that
the predator and prey are moving towards each other, would actually be
predicted to increase from 25 cm s1 (only suction) to 40 cm
s1 (20 cm s1 of ram + AFS1/2
PG of 20 cm s1). Since the ratio
RS/AFSaperture was commonly less than 10% (27 of
41), the expected decrease (<3 cm s1) in
AFS1/2 PG is not as great as subtracting the complete ram
speed. Thus, like fluid speed, the effect of ram speed decays rapidly with
distance away from the mouth. Nevertheless, we did not see any tendency for
ram speed to reduce suction speed (Fig.
5).
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Bluegill sunfish exhibit fine temporal control of their velocity prior to, and during, prey capture (T. E. Higham, B. Malas, B. C. Jayne and G. V. Lauder, manuscript submitted for publication). For example, in a laboratory setting bluegill decelerate to approximately 30% of their maximum approach speed at the time of prey capture, and then maximally decelerate until stopping (T. E. Higham, B. Malas, B. C. Jayne and G. V. Lauder, manuscript submitted for publication). One benefit of decelerating to 30% of the maximum approach speed could be to lower the ram speed-to-fluid speed ratio (RS/AFSaperture) to between 020%, since it is possible that larger ratios have a negative effect on suction performance. Two potential strategies that high performance suction feeders can employ to achieve a low RS/AFSaperture include decelerating prior to prey capture or maintaining a low ram speed throughout the predatorprey interaction. The question of whether predators that rely predominantly on suction always exhibit a low RS/AFSaperture ratio requires further investigation.
Degree of focusing
In our study, the degree of focusing (DF) during suction feeding increased
with an increase in ram speed (Figs
2,
6). Focusing the flow of water
enables the predator to draw water from in front of its mouth where the prey
is positioned rather than drawing water from a wider space around the fish's
head. The largest gain in DF seems to occur when values of
RS/AFSaperture are between 2 and 10%, whereas
there is less of an increase in DF for values between 10 and 20%. At very high
values of RS/AFSaperture, the degree of focusing
would approach 1, where the distance between streamlines is equal to the
diameter of the mouth at maximum gape. Thus, increases in DF might become
increasingly subtle as ram speed approaches suction speed.
By increasing DF, the accuracy required to capture a prey item also
increases. Thus, swimming slowly, or slowing down prior to feeding, might
enable the fish to maintain accuracy (more time for steering and positioning)
and not forfeit suction performance. Decelerating prior to prey capture has
been suggested as a way to increase accuracy during feeding (T. E. Higham, B.
Malas, B. C. Jayne and G. V. Lauder, manuscript submitted for publication;
Lauder and Drucker, 2004), but
our observations provide a hydrodynamic basis for how braking can increase
accuracy.
Shape of ingested water volume
When bluegill sunfish attacked the prey item at a high velocity, they
ingested a more elongated volume of water
(Fig. 3). In the example shown
in Fig. 3, the length of the
ingested water along the x-axis is 50% greater in the case with high
ram (17.5 cm s1) than in the case with no ram (0 cm
s1). The shape of the ingested fluid volume is likely to be
an important factor in determining whether a prey item is captured. For
example, by extending the distance from the mouth that water is ingested, a
predator might be able to limit the ability of the prey to escape.
With an increase in ram speed, the more elongate parcel of ingested water
enables the bluegill to capture more fluid from the space in front of the
mouth, corroborating several modeling studies
(Weihs, 1980;
van Leeuwen, 1984
;
de Jong et al., 1987
;
Drost et al., 1988
). Drost et
al. (1988
) used a model to
predict the shape of the ingested volume of water by suction-feeding carp
larva swimming at 3.5 cm s1. Although all of the water drawn
into the mouth originated from in front of the carp larva, the shape of the
ingested volume of water is notably different from that of bluegill. For
example, the maximum vertical height of the ingested volume in bluegill is
typically centered (Fig. 3)
while the volume ingested by the carp was predicted to be `trumpet' shaped
with the maximum vertical height occurring distally to the central axis (fig.
5 in Drost et al., 1988
). We
never observed this shape in bluegill feeding events. In another modeling
study, de Jong et al. (1987
)
determined that the shape of the ingested volume of water would become more
elongated as swimming speed increased, and our results confirm this.
Additionally, the overall shape of the ingested volume of water predicted in
the study by de Jong et al.
(1987
) more closely resembled
the shapes that we observed.
Weihs (1980) developed a
term that was the ratio of ingestion distance directly forward to that in the
orthogonal direction, and predicted that it would increase with greater ram
speed, and our results support this. Weihs
(1980
) also suggests that with
increased swimming speed, a fish can minimize the amount of wasted ingested
volume and thus maximize their efficiency. Another implication of narrowing
and elongating the ingested volume of water is that the predator must increase
attack accuracy as the region of influence in front of the predator will
become more focused (Drost et al.,
1988
). Thus, it is likely that a trade-off exists between accuracy
and efficiency in high-performance suction-feeding fish.
The hydrodynamic interactions between suction and ram are complex and it seems that, depending on their morphology and ecology, fish can modulate their ram speed in order to achieve a balance between the several interrelated factors that result from changes in ram speed. For example, bluegill sunfish have relatively small mouths and thus accuracy may be a relatively important factor. Moderate to low ram speeds increase their closing speed without forfeiting peak fluid speed, but a relatively low ram speed allows them to maintain accuracy (lower degree of focusing). Additionally, their efficiency increases with a moderate amount of ram speed by ingesting a narrower volume of water where the prey is located.
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Acknowledgments |
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References |
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