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First published online June 13, 2008
Journal of Experimental Biology 211, 2066-2070 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.017038
Scallops visually respond to the size and speed of virtual particles
Biology Department, Duke University, Durham, NC 27708, USA
* Author for correspondence (e-mail: dis4{at}duke.edu)
Accepted 16 April 2008
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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;
Barber et al., 1966;
Morton, 2000). Light reflected
off the mirror is thought to form a focused image on the distal retina
(Land, 1965), which appears to
be well-suited for the detection of movement
(Land, 1966).
Because scallops close their valves in the presence of large moving
objects, it has been argued that their eyes primarily act as predator
detectors (Nilsson, 1994;
Morton, 2000). Although
predator detection is almost certainly one task of the mantle eyes, evidence
suggests that other scallop behaviors are also visually influenced. For
example, scallops have been observed extending their tentacles in response to
visual stimuli (von Buddenbrock and
Moller-Racke, 1953; Wilkens,
2006) and visually navigating toward a preferred habitat
(von Buddenbrock and Moller-Racke,
1953; Hamilton and Koch,
1996).
Measurements of optical resolution also imply that predator detection may
be only one of several functions performed by scallop eyes. Behavioral
(von Buddenbrock and Moller-Racke,
1953), morphological (Land,
1965) and physiological (Land,
1966) studies all conclude that scallop eyes have an angular
resolution of around 2°. In comparison, the predator-detecting eyes of
other bivalves have angular resolutions ranging from 13° to 40°
(Nilsson, 1994;
Land, 2003). Although coarse,
an angular resolution within this range would still probably allow scallops to
spot major predators, such as crabs, gastropods, rays and starfish
(Brand, 2006;
Myers et al., 2007), at
ecologically relevant distances. Therefore, while predator detection may
explain some aspects of scallop vision, it does not account for these
bivalves' diverse visual behaviors or why they see so relatively well.
We have tested the hypothesis that scallops visually detect the presence
and speed of moving particles when assessing feeding conditions. Scallops
actively feed on suspended organic particles and can open their valves to see
without opening their mantle gape. Thus, the visual detection of particle
presence and speed may let these animals monitor feeding conditions without
exposing the vulnerable structures of their mantle cavity. We placed specimens
of A. irradians in a flow tank, showed them simulated particles of
different sizes moving at a range of different speeds, and recorded and
analyzed their responses. We worked with A. irradians because it
lives in bright, shallow water and has been used in previous studies of
scallop vision (e.g. Hamilton and Koch,
1996).
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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(Instant Ocean sea salt, Aquarium Systems, Inc., Mentor, OH, USA). Animals
collected in 2007 were immediately transported to the Duke University Marine
Laboratory (Beaufort, NC, USA), where they were kept in sea tables with
continually flowing filtered sea water. At both sites, animals remained in
apparent good health for over a month. Experiments were conducted on animals
1–3 weeks after they were collected.
Experimental apparatus
The experimental set-up included a computer monitor, laptop computer, small
flow tank, video camera, and recorder (Fig.
1). The flow-tank was a Plexiglas box (64 cmx14 cmx18
cm, LxWxH) attached at each end to a curved length of 6 cm
diameter PVC pipe. A 1200 l h–1-rated submersible pump
(Penguin 1140, Marineland Aquarium Products, Moorpark, CA, USA) and a 13
cm-long baffle made of plastic drinking straws created a laminar flow of
5–10 cm s–1 within the tank, well within the normal
range of flow rates encountered by scallops in nature
(MacDonald et al., 2006). Flow
was used because scallops, in preliminary trials, rarely opened their valves
in still water.
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The flow-tank was placed in front of a 46 cm monitor attached to a laptop computer that ran the particle simulation program. The behavior of A. irradians was recorded with a video camera attached to a time-lapse VHS video recorder. Video camera output was displayed on a second monitor so that proper aperture and focus could be maintained from trial to trial. In both 2006 and 2007, trials were conducted in light-tight rooms. The only illumination in these rooms was provided by the two monitors.
Experimental procedure
The flow tank was rinsed and filled to a depth of 14 cm with newly mixed
artificial sea water on each day that trials were run. Trials were conducted
during daylight hours and with one animal at a time. To prevent scallops from
swimming during trials, while allowing a full range of valve motion, specimens
of A. irradians were glued, right valve down, to a short length of
PVC pipe that was then attached to a mount at the bottom of the flow-tank.
Specimens were mounted so that the anterior (inhalant) opening faced the video
camera and was downstream with regards to flow. The flow-tank was positioned
so that the computer monitor was, at most, 2.5 cm from the nearest point on a
test animal.
In our experiment, we observed the behavior of scallops shown moving, simulated particles of different sizes and speeds. The particle simulation program was written in JavaScript (Ecma International, Geneva, Switzerland) and run as an HTML file. In our first set of trials, particles in the no particle treatment were grey (grey value=80 out of 255) and invisible against the grey background (grey value=80 out of 255) and particles in the 0.6x0.6 mm (1.4° angular size) and 1.5x1.5 mm (3.4° angular size) particle treatments were black (grey value=0 out of 255). All particles in our first set of trials moved at 2.5 cm s–1. In our second set of trials, black virtual particles were 1.5x1.5 mm in size and moved at 2.5, 5, or 10 cm s–1 against the grey background. In all treatments, particles appeared at random positions on the left edge of the screen at a rate of ten per second and moved left to right, the same direction as the flow in the tank. Flow speed was not altered between trials. Monitor refresh rate was 50 Hz and irradiances at the scallop (integrated from 400 to 700 nm) were nearly identical between trials, with readings of 1.20x1014 photons cm–2 s–1 and 1.21x1014 photons cm–2 s–1 for the no particle and particle treatments, respectively. Furthermore, no observed scallop behaviors differed significantly when the monitor background was changed from white (grey value=255; N=23) to grey (grey value=80; N=23) to black (grey value=0; N=24) in an independent set of trials. The irradiance values at the scallop for the white, grey and black backgrounds were 6.61x1014, 1.20x1014 and 5.11x1011 photons cm–2 s–1, respectively. No virtual particles were displayed in these treatments. The results from this set of trials suggest that the slight differences in irradiance values between the virtual particle treatments did not influence scallop behavior.
Trials for the no particle and 1.5x1.5 mm, 2.5 cm s–1 virtual particle treatments were conducted in 2006 and trials for the 0.6x0.6 mm, 2.5 cm s–1 and the 1.5x1.5 mm, 5 and 10 cm s–1 treatments were conducted in 2007. Different animals were used for each trial within a given treatment. Because some animals were used in both the 0.6x0.6 mm, 2.5 cm s–1 and the 1.5x1.5 mm, 5 cm s–1 treatments, these two conditions were not compared in our analysis. Trials for the black, grey and white background conditions were conducted in 2006 and 2007, different animals were used for each trial within a treatment, and no animals were used in more than one treatment.
Data collection and analysis
The particle simulation program was initiated and behavioral recording
begun immediately after scallops were placed in the flow tank. All trials
lasted 10 min, measured from the onset of recording. For our recordings of
each trial, scallop mantle gapes were scored as open or closed and tentacles
were scored as extended or not extended at 24 s intervals. Mantle gapes were
scored as open if there was a gap in the anterior mantle folds and the gills
were exposed (Fig. 2A). Mantle
gapes were scored as closed if no gap was visible between the anterior mantle
folds and the gills were not exposed (Fig.
2B). We also counted the number of times that each scallop clapped
its valves during a trial. Scallops can see as long as their valves are open,
but it is unlikely that they are able to see when their valves are closed.
Therefore, we only analyzed trial data recorded after a scallop first opened
its valves. This resulted in a variable number of observations per trial.
However, the total number of observations varied little between treatments
(Table 1).
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We calculated the proportion of observations in each trial in which a scallop's mantle gape was open or its tentacles were extended (Table 1). These proportions were arcsine square-root transformed for analysis and comparisons between treatments were made using one-way ANOVAs and Bonferroni pairwise multiple comparison t-tests. The numbers of valve claps per trial were not consistent with a normal distribution, so Kruskal–Wallis one way ANOVAs on rank order were used to compare valve claps between treatments.
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RESULTS |
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Tentacle extension and valve claps
Scallops had extended tentacles in 53±14% to 69±12% of the
observations per trial for the different particle treatments
(Table 1). Particles of
different size (F2, 70=1.031, P=0.362; one way
ANOVA) or speed (F3,94=1.091, P=0.357; one way
ANOVA) did not have an influence on scallop tentacle extension. Scallops also
clapped their valves between 1.4±0.7 and 1.9±0.8 times per trial
(Table 1). Kruskal–Wallis
ANOVAs revealed that the number of valve claps per trial did not vary
significantly between treatments when particle size
(H2=3.330; P=0.189) or particle speed
(H3=2.032; P=0.566) varied.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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), and
other bivalves, such as mussels, have been found to increase their mantle gape
in response to the presence of feeding cues
(Riisgård et al., 2003).
It is likely, therefore, that the scallops in our study responded to the size
and speed of virtual particles with a feeding-related behavior. Scallops must
also regularly open their mantle gape to respire
(MacDonald et al., 2006),
which may account for why open mantle gapes were observed during trials in
which no particles, or any other feeding cues, were present. Respiratory
conditions were identical between trials, so it is unlikely that respiration
accounted for the differences observed between treatments.
Scallop behaviors other than mantle gape position, including tentacle extension and valve clapping, varied little between treatments (Table 1). Scallops extended their tentacles within the first 2 min of most trials, indicating that this behavior may be a general response to new environmental conditions. Valve clapping, however, did not display a temporal pattern and may have represented behavior related to respiration, swimming attempts or pseudo-feces expulsion. These findings support our hypothesis that A. irradians responded to different virtual particle sizes and speeds with specific behaviors consistent with increased or decreased levels of feeding activity.
The response of A. irradians to virtual particle size was
consistent with the estimated 2° inter-receptor angle of its eyes
(Speiser and Johnsen, in
press). An angular resolution of 2° would probably have let
A. irradians see the 1.5x1.5 mm particles, which had angular
sizes of 3.4°. However, it is less likely that scallops were able to
detect the 0.6x0.6 mm particles, which had angular sizes of 1.4°.
This strongly implies that the differences in scallop behavior we observed
between treatments were due to the detection of the virtual particles by
visual means.
Scallops may respond to the presence of virtual particles with
feeding-related behavior because they visually monitor feeding conditions.
Scallops feed on suspended organic particles ranging from 5 to 950 µm in
diameter (Mikulich and Tsikhon-Lukanina,
1981; Shumway et al.,
1987). Objects in the upper half of this range would be visible to
scallops at a distance of a few millimeters, provided that scallop eyes are
capable of focusing at such short distances. Alternately, scallops may detect
larger, inorganic particles and use this information as a proxy for the
presence of smaller, organic particles.
Coastal scallops, such as A. irradians, encounter highly variable
feeding conditions (Fegley et al.,
1992). For example, re-suspensions of bottom sediment by tide or
wind (Grant et al., 1997) and
changes in phytoplankton abundance
(Fréchette and Bourget,
1987) may cause food particle concentrations to fluctuate.
Previous studies have clearly established that scallops track these
fluctuations using tactile and chemosensory cues
(MacDonald et al., 2006).
However, we hypothesize that the visual detection of suspended particles may
be a safe and efficient method for scallops to initially assess new feeding
conditions. For example, although scallops may be able to continually test for
the presence of food particles by opening their mantle gapes and sampling
water with their gills, this action may increase their vulnerability to mantle
cavity parasites such as pinnotherid crabs
(Kruczynski, 1972) and
odostomid gastropods (Leibovitz et al.,
1984). Because scallops can see even when their mantle gape is
closed, visually monitoring for food particles may allow them to avoid these
risks. Furthermore, the detection of food particles on the gills may, like
feeding in most bivalves (Widdows and
Hawkins, 1989), incur a metabolic cost in scallops. This cost may
be avoided if scallops are able to visually detect food particles.
A. irradians responded not only to differences in particle size,
but to differences in particle speed as well. We found that A.
irradians had open anterior mantle gapes significantly more often when
they were shown virtual particles moving at 2.5 or 5 cm s–1
than when they were shown particles moving at 10 cm s–1.
Laboratory experiments suggest that scallop feeding may be inhibited by flow
rates over 10–15 cm s–1
(Kirby-Smith, 1972; Wildish
and Saulnier, 1993). Therefore, our findings suggest that A.
irradians exhibited higher rates of feeding-related behavior when they
were shown simulations that indicated favorable feeding conditions. This
implies that scallops may visually monitor aspects of their environment
related to feeding efficiency, such as particle speed, not just food
availability.
Scallops process visual information in the lateral lobes of their
visceroparietal ganglion (VPG), an organ that innervates the adductor muscle
and probably controls mantle gape position
(Wilkens, 2006). Processing
may be simplified if visual input is filtered at the level of the scallop eye.
For example, scallops may optimally respond to a range of environmental
conditions if they simply close their mantle gape when they are unable to
visually detect suspended particles. Electroretinograms (ERGs) indicate that
scallop eyes have an integration time of around 200 ms [for Amusium
japonicum (Kanmizutaru,
2005)]. Moving at a speed of 10 cm s–1 and at a
distance of 2.5 cm, the 1.5x15 mm particles in our study probably
traveled the entire distance across A. irradians retinas in less than
a single visual cycle. It is unlikely, therefore, that the scallops in our
study were able to detect the virtual 10 cm s–1 particles
that they were shown. As previously mentioned, flow rates over 10–15 cm
s–1 may inhibit scallop feeding
(Kirby-Smith, 1972; Wildish
and Saulnier, 1993), so an inability to distinguish between rapidly moving and
non-existent particles may help scallops link a single behavioral output,
mantle gape position, to a wide range of visual conditions. This sort of
visual system, which filters information at the level of the eye, may be a
common feature in animals that lack the neural complexity to process large
amounts of visual input (Wehner,
1987; Nilsson et al.,
2005).
The position in which scallops were mounted in the flow tank may have
influenced our results. Evidence suggests that high flow rates strongly
inhibit scallop growth when posterior (exhalant) openings face oncoming flow,
as they did in our study, and that juvenile A. irradians actively
turn their anterior (inhalant) opening to face oncoming flow when flow speeds
exceed 9 cm s–1 (Eckman et
al., 1989). This suggests that we may not have observed a decrease
in feeding-related behavior at virtual flow speeds of 10 cm
s–1 if A. irradians had been positioned in the flow
tank in their preferred anterior-to-flow orientation. However, given that
scallops are probably unable to detect objects moving faster than 10 cm
s–1 (Kanmizutaru,
2005), it is doubtful that the observed visual response of A.
irradians to virtual particle speed was influenced by flow direction.
Future experiments will explore whether scallops use vision to help assess
flow direction, as well as other environmental conditions relevant to feeding,
such as turbidity levels, and whether these responses may be interpreted
through a `matched filters' model of information processing.
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Acknowledgments |
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References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
Barber, V. C., Evans, E. M. and Land, M. F. (1966). The fine structure of the eye of the mollusc Pecten maximus. Cell Tissue Res. 76,295 -312.
Brand, A. R. (2006). Scallop ecology: distributions and behaviour. In Scallops: Biology, Ecology, and Aquaculture (ed. S. E. Shumway and G. J. Parsons), pp.651 -744. New York: Elsevier.
Dakin, W. J. (1928). The eyes of Pecten, Spondylus, Amussium and allied lamellibranchs with a short discussion on their evolution. Proc. R. Soc. Lond. B Biol. Sci. 103,355 -365.
Eckman, J. E., Peterson, C. H. and Cahalan, J. A. (1989). Effects of flow speed, turbulence,and orientation on growth of juvenile bay scallops Argopecten irradians concentricus (Say). J. Exp. Mar. Biol. Ecol. 132,123 -140.[CrossRef]
Fegley, S. R., MacDonald, B. A. and Jacobsen, T. R. (1992). Short-term variation in the quantity and quality of seston available to benthic suspension feeders. Estuar. Coast. Shelf Sci. 34,393 -412.[CrossRef]
Fréchette, M. and Bourget, E. (1987). Significance of small-scale spatio-temporal heterogeneity in phytoplankton abundance for energy flow in Mytilus edulis. Mar. Biol. 94,231 -240.[CrossRef]
Grant, J., Cranford, P. J. and Emerson, C. W. (1997). Sediment resuspension rates, organic matter quality, and its utilization by sea scallops (Placopecten magellanicus) on Georges Bank. J. Mar. Res. 55,965 -994.[CrossRef]
Hamilton, P. V. and Koch, K. M. (1996). Orientation toward natural and artificial grassbeds by swimming Bay scallops, Argopecten irradians (Lamarck, 1819). J. Exp. Mar. Biol. Ecol. 199,79 -88.[CrossRef]
Kanmizutaru, T. (2005). Light perception capability of the pallial eyes in the Japanese moon scallop Amusium japonicum as determined by electroretinogram. Nippon Suisan Gakkai Shi 71,928 -934.[CrossRef]
Kirby-Smith, W. W. (1972). Growth of the bay scallop: the influence of experimental water currents. J. Exp. Mar. Biol. Ecol. 8,7 -18.[CrossRef]
Kruczynski, W. L. (1972). The effect of the pea crab, Pinnotheres maculates Say, on the growth of the bay scallop, Argopecten irradians concentricus Say. Chesapeake Sci. 13,218 -220.[CrossRef]
Land, M. F. (1965). Image formation by a concave reflector in the eye of the scallop, Pecten maximus. J. Phys. 179,138 -153.
Land, M. F. (1966). Activity in the optic nerve
of Pecten maximus in response to changes in light intensity and to
pattern and movement in the optical environment. J. Exp.
Biol. 45,83
-99.
Land, M. F. (2003). The spatial resolution of the pinhole eyes of giant clams (Tridacna maxima). Proc. R. Soc. Lond. B Biol. Sci. 270,185 -188.[Medline]
Leibovitz, L., Schott, E. F. and Karney, R. C. (1984). Diseases of wild, captive, and cultured scallops. J. World Maricult. Soc. 15,269 -283.
MacDonald, B. A., Bricelj, V. M. and Shumway, S. E. (2006). Physiology: energy acquisition and utilization. In Scallops: Biology, Ecology, and Aquaculture (ed. S. E. Shumway and G. J. Parsons), pp. 417-492. New York: Elsevier.
Mikulich, L. V. and Tsikhon-Lukanina, E. A. (1981). Food composition of the yesso scallop. Oceanology 21,633 -635.
Morton, B. (2000). The function of pallial eyes within the Pectinidae, with a description of those present in Patinopecten yessoensis. In The Evolutionary Biology of the Bivalvia. Vol. 177 (ed. E. M. Harper, J. D. Taylor and J. A. Crame), pp. 247-255. London: The Geological Society.
Myers, R. A., Baum, J. K., Shepherd, T. D., Powers, S. P. and
Peterson, C. H. (2007). Cascading effects of the loss of apex
predatory sharks from a coastal ocean. Science
315,1846
-1850.
Nilsson, D.-E. (1994). Eyes as optical alarm systems in fan worms and ark clams. Philos. Trans. R. Soc. Lond. B Biol. Sci. 346,195 -212.[CrossRef]
Nilsson, D.-E., Gislén, L., Coates, M. M., Skogh, C. and Garm, A. (2005). Advanced optics in a jellyfish eye. Nature 435,201 -205.[CrossRef][Medline]
Riisgård, H. U., Kittner, C. and Seerup, D. F. (2003). Regulation of opening state and filtration rate in filter-feeding bivalves (Cardium edule, Mytilus edulis, Mya arenaria) in response to low algal concentration. J. Exp. Mar. Biol. Ecol. 284,105 -127.[CrossRef]
Shumway, S. E., Selvin, R. and Shick, D. F. (1987). Food resources related to habitat in the scallop Placopecten magellanicus (Gmelin, 1791): a quantitative study. J. Shellfish Res. 6,89 -95.
Speiser, D. I. and Johnsen, S. (2009). Comparative morphology of the concave mirror eyes of scallops (Pectinoidea). Am. Malacol. Bull. 26 (in press).
von Buddenbrock, W. and Moller-Racke, I. (1953). Uber den lichtsinn von Pecten. Pubbl. Staz. Zool. Napoli 24,217 -245.
Wehner, R. (1987). `Matched filters'-neural models of the external world. J. Comp. Physiol. 161,511 -531.[CrossRef]
Widdows, J. and Hawkins, A. J. S. (1989). Partitioning of rate of heat dissipation by Mytilus edulis into maintenance, feeding, and growth components. Physiol. Zool. 62,764 -784.
Wildish, D. J. and Saulnier, A. M. (1982). The effect of velocity and flow direction on the growth of juvenile and adult giant scallops. J. Exp. Mar. Biol. Ecol. 155,161 -168.[CrossRef]
Wilkens, L. A. (2006). Neurobiology and behaviour of the scallop. In Scallops: Biology, Ecology, and Aquaculture (ed. S. E. Shumway and G. J. Parsons), pp.317 -356. New York: Elsevier.
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