Odor Plumes and How Blue Crabs Use Them in Finding Prey

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Orientation of animals using chemical cues often takes place in flows, where the stimulus properties of odorants are affected by the characteristics of fluid motion. Kinematic analysis of movement patterns by animals responding to odor plumes has been used to provide insight into the behavioral and physiological aspects of olfactory-mediated orientation, particularly in terrestrial insects. We have used this approach in analyzing predatory searching by blue crabs in response to plumes of attractant metabolites released from the siphons of live clams in controlled hydrodynamic environments. Crabs proceed directly upstream towards clams in smooth-turbulent flows and show high locomotory velocities and few periods of motionlessness. Crabs assume more indirect trajectories and display slower locomotion and more stopping in rough-turbulent flows. This degradation of foraging performance is most pronounced as flow shifts from a smooth- to a rough-turbulent regime, where the change in hydraulic properties is associated with contraction of the viscous sublayer region of the boundary layer. Because flow in this region is quasilaminar, the viscous sublayer may be a particularly effective vehicle for chemical stimulus transmission, such that orientation is severely compromised when it is reduced or removed. Our results also suggest that rheotactic and chemical information are both necessary for successful orientation. Perception of chemical cues acts to bias locomotion upcurrent, and feedback from odorant stimulus distributions appears directly to regulate subsequent stopping and turning en route to prey. Although the mechanisms of orientation to odorant plumes displayed by insects and blue crabs are largely similar, blue crabs appear to rely more heavily on spatial and/or temporal aspects of chemical stimulus distributions than has been suggested for insect systems.
J. exp. Biol. 197, 349–375 (1994)
Printed in Great Britain © The Company of Biologists Limited 1994
Department of Biology, Georgia State University, PO Box 1040, Atlanta,
GA 30302-4010, USA
Department of Biology, Marine Science Program, and Belle W. Baruch Institute for
Marine Biology and Coastal Research, University of South Carolina, Columbia,
SC 29208, USA
Accepted 29 July 1994
Orientation of animals using chemical cues often takes place in flows, where the
stimulus properties of odorants are affected by the characteristics of fluid motion.
Kinematic analysis of movement patterns by animals responding to odor plumes has been
used to provide insight into the behavioral and physiological aspects of olfactory-mediated
orientation, particularly in terrestrial insects. We have used this approach in analyzing
predatory searching by blue crabs in response to plumes of attractant metabolites released
from the siphons of live clams in controlled hydrodynamic environments. Crabs proceed
directly upstream towards clams in smooth-turbulent flows and show high locomotory
velocities and few periods of motionlessness. Crabs assume more indirect trajectories and
display slower locomotion and more stopping in rough-turbulent flows. This degradation
of foraging performance is most pronounced as flow shifts from a smooth- to a rough-
turbulent regime, where the change in hydraulic properties is associated with contraction
of the viscous sublayer region of the boundary layer. Because flow in this region is quasi-
laminar, the viscous sublayer may be a particularly effective vehicle for chemical stimulus
transmission, such that orientation is severely compromised when it is reduced or
removed. Our results also suggest that rheotactic and chemical information are both
necessary for successful orientation. Perception of chemical cues acts to bias locomotion
upcurrent, and feedback from odorant stimulus distributions appears directly to regulate
subsequent stopping and turning en route to prey. Although the mechanisms of orientation
to odorant plumes displayed by insects and blue crabs are largely similar, blue crabs
appear to rely more heavily on spatial and/or temporal aspects of chemical stimulus
distributions than has been suggested for insect systems.
A large variety of aquatic and terrestrial animals are directed to resources by olfactory
Key words: advection, boundary layer, chemoreception, eddy diffusion, hydrodynamics, kinematics,
orientation, rheotaxis, turbulence, blue crab, Callinectes sapidus.
cues (see reviews in Bell and Cardé, 1984; Atema et al. 1988), often navigating through
moving fluid. Consequently, distance and directional information on the location of odor
sources is frequently encoded by chemical stimulus distributions in odor plumes
transported by flow. In these cases, the spatial and temporal aspects of odor plume
structure depend on transport dynamics occurring within the carrier fluid, and this may
cause interactions between animal orientation ability and the flow environment.
Surprisingly, studies explicitly examining the influence of fluid dynamics on qualities of
odor plumes and orientation abilities are rare in both marine and terrestrial systems.
Substantial advances in understanding the mechanics of orientation in terrestrial animals,
notably insects (i.e. Baker and Haynes, 1989; Willis and Arbas, 1991), occurred only
after considering the effects of flow on odor plume microstructure (e.g.Mikstad and
Kittredge, 1979; Murlis and Jones, 1981). In aquatic systems, previous work has not
stressed the control of the fluid environment, or the production of flows mimicking the
natural habitats of the experimental organism (see review by Zimmer-Faust, 1989).
Although studies have firmly established the chemosensory basis of orientation in aquatic
organisms, particularly crustaceans (see review by Ache, 1988), it is currently difficult to
come to firm conclusions regarding the connections between hydrodynamic forces,
chemosensory abilities and locomotory performance.
Experimental verification of the interaction between hydrodynamics and olfaction is a
necessary first step in determining the mechanisms of orientation in flow. Weissburg and
Zimmer-Faust (1993) recently assayed the ability of blue crabs, Callinectes sapidus
(Rathbun), to locate live prey (actively pumping clams) using chemosensation. These
experiments took place under measured and controlled hydrodynamic conditions
naturally experienced by crabs in estuaries along the Gulf of Mexico and south Atlantic
coasts of the United States. Actively pumping bivalves liberate metabolic by-products,
such as small peptides (Rittschof et al. 1984), which appear to act as olfactory cues
guiding animals to the location of potential prey. The interaction between hydrodynamics
and the success of olfactory-mediated behavior was addressed by measuring the
properties of boundary layer flows, specifically boundary shear velocity and roughness
Reynolds number. Shear velocity is proportional to the magnitude of turbulent mixing,
while roughness Reynolds number increases as turbulent eddies penetrate closer to the
substratum. This investigation revealed that the degree of boundary layer turbulence,
rather than flow speed or sea bed topography per se, largely determines the ability of
crabs to locate potential prey. Flows characterized by higher shear velocity and roughness
Reynolds number diminish the capacity of crabs to track clam scents.
Documenting the effects of explicitly characterized fluid flows on orientation behavior
in blue crabs raises further issues concerning the mechanisms of orientation. Theoretical
treatments of odor transport indicate that changes in turbulence magnitude are principally
expressed as alterations in the frequency and duration of discrete pulses of odorants
within a plume, as well as by changes in odorant concentration (Murlis et al. 1991).
Investigators have proposed several orientation mechanisms that are potentially sensitive
to these changes in the distribution of odorants and which could explain the correlation
between orientation success and hydrodynamic conditions observed in Callinectes. These
mechanisms focus on the use of purely chemical cues to establish the distance and
direction to sources of odor emission. Investigators have hypothesized that some
crustaceans encode information by determining differences in odorant intensity
simultaneously at bilaterally paired chemosensory organs (Reeder and Ache, 1980;
Devine and Atema, 1982), or possibly by successive assessment of the frequency of
detectable odor pulses or the onset slope of an odor pulse (Moore and Atema, 1991).
However, given the lack of detailed information on movement patterns of animals in
hydrodynamically defined flows, it is difficult to substantiate whether orientation is
purely chemotactic, much less to distinguish among proposed orientation strategies.
Kinematic analysis of locomotory behavior has been invaluable in understanding
orientation mechanisms in other animals that function in flows, particularly insects
navigating in pheromone plumes (e.g. Baker and Haynes, 1989; Willis and Arbas, 1991).
Patterns of insect behavior have frequently suggested mechanisms amenable to further
study in more controlled stimulus environments or suggested fruitful neurophysiological
approaches. Consequently, we have attempted a detailed analysis of the search
kinematics of blue crabs as they attempt to locate prey in controlled flows. As in our
earlier work, explicit hydrodynamic measurements have been coupled with
determinations of the locomotory performance of individuals in differing flow regimes.
Not surprisingly, turbulence is found to have major effects on the kinematics of olfactory-
mediated prey search. Crabs search more effectively at slower speeds and assume more
indirect routes as boundary layer flows become more turbulent. Degradation of
orientation performance is most pronounced as flow shifts from a smooth-turbulent to a
rough-turbulent regime. This shift is associated with contraction of the viscous sublayer,
a region of quasi-laminar flow adjacent to the sea bed that is apparently conducive to
uninterrupted, effective transmission of chemical signals.
Materials and methods
Overview of flume design and hydrodynamic methodology
The flume
Experiments were conducted in steady flows and in fully developed boundary layers
within a single-channel recirculating flume (10 m length 0.75 m width 0.15 m water
depth) constructed from Plexiglas. The working section was a fixed drop-box (100 cm
length 45 cm width 15 cm depth) placed 7.5 m downstream of the entry section and
1.5 m upstream of the exit weir. The drop box was filled with sand taken from local
habitats and sieved to <1 mm to remove large particles (mean particle diameter
m, S.D.; N=100). The entire flume bed was carefully layered to a uniform depth
of 0.5 cm with this material.
Hydrodynamic methods
Benthic boundary layer flows can be defined by a variety of fluid dynamic variables. In
unidirectional flows, frictional or shear velocity (u*) and roughness Reynolds number
(Re*) are measures of boundary layer flows that are generally comprehensive enough to
provide a means of establishing the dynamic similarity of various flow regimes (Nowell
and Jumars, 1984). For an organism moving within the boundary layer region, such as a
351Blue crabs use odor plumes to find prey
macroscopic crustacean crawling along the seafloor, these measures roughly indicate the
hydrodynamic forces acting upon the animal. Shear velocity and roughness Reynolds
number were calculated by determining the velocity gradient through the log-layer region
of boundary layer. Neutrally buoyant styrene/divinylbenene beads (350
m diameter,
specific gravity 1.03; Bangs Laboratories, Carmel, IN) were injected into the flow at
known heights above the substratum. Path trajectories were recorded on video tape, and
bead velocity was determined using computer-aided video motion analysis with a Motion
Analysis system (model VP-110; Motion Analysis Corp., Marin, CA). Given the
relationship between velocity and log height above the substratum, boundary shear
velocity (u*) was calculated using the ‘law of the wall’:
U(z) = (u*/k)ln(z/zo) , (1)
where U(z) is the mean velocity at height zabove the substratum, kis von Karman’s
constant and zois the roughness height, determined as the y-intercept of the equation
regressing logzagainst measured flow speed (Schlicting, 1979). Roughness Reynolds
numbers (Re*) were calculated as:
Re*= u*D/v, (2)
where Dis the bed roughness scale (the mean value of the sediment grain size) and vis the
kinematic viscosity of sea water. Finally, we estimated the thickness of the viscous
sublayer by reworking equation 2 and solving for D, setting Re*=6. The onset of
turbulence in outer boundary layer regions occurs at an Re* of approximately 6
(Schlicting, 1979); thus, when Re* is set to this value, Destimates the thickness of the
region of quasi-laminar flow. Explicit details pertaining to the flume design, the
calculation of hydrodynamic variables and the methods used to determine log-layer
velocity gradients are found in Weissburg and Zimmer-Faust (1993).
Animal capture and holding methods
Adult blue crabs Callinectes sapidus (Rathbun) were captured by seine or by baited
trap at local marshes and maintained in one of the holding tanks associated with the
flume. Lighting was provided by standard fluorescent fixtures, with the photoperiod set at
12 h:12 h (L:D). All animals were allowed to acclimate to laboratory conditions for 4–5
days prior to experimentation and were fed an ad libitum diet of bivalves and fish. Crabs
were starved for 48 h prior to experiments, in order to standardize their hunger level.
Water in both the holding tanks and flowing through the flume during behavioral trials
passed through a 5
m particle filter, an activated-charcoal bed and an ultraviolet
sterilization unit before being returned to the system. We periodically monitored the
levels of organic chemicals (ammonium and dissolved organic carbon) in the seawater
system. Levels of these organic chemicals never exceeded concentrations typically found
in estuarine environments.
Hard clams (Mercenaria mercenaria) were obtained from a commercial supplier,
housed in holding tanks without blue crabs and fed every other day on a mixed diet of the
flagellates Isochrysis galbana and Pavlova lutheri in logarithmic growth phase at a cell
density of approximately 4104cells ml1.
Behavioral assays
Behavioral trials consisted of challenging crabs to locate actively pumping Mercenaria
merceneria under a variety of flow regimes in the flume. Trials were performed at four
different current speeds (free-stream velocity, U=0, 1.0, 3.8 and 14.4 cm s1), with prey
located either 1.0 or 0.5 m away from the crab’s initial starting position (hereafter referred
to as ‘far’ and ‘close’ starting sites, respectively). Trials were also performed at each
current speed without prey (no-clam controls) at the close starting site.
All behavioral trials were started at least 1 h after sunset, since Callinectes generally
exhibits peak foraging activity during nocturnal periods (e.g. Sponaugle and Lawton,
1990). Crabs were individually isolated, fitted with a monofilament tether and then
allowed to remain undisturbed under natural illumination until used in behavioral trials. A
trial commenced by placing a tethered crab into the flume containing a 0.25 m2patch of
Mercenaria, at a density of 40 clams m2. This density is well within the range reported
for natural populations of Mercenaria (Walker, 1989). Crabs often gravitated to the flume
edge during the acclimation period; 30–45 min after introducing the crab (and only when
the crab was at least 15 cm away from the walls), the tether was gently cut and the crab
was allowed to forage for the clams for 30 min. Crab foraging behavior was filmed with a
SONY CCD camera, equipped with a 1.8 mm wide-angle video lens, video tape recorder
and viewing monitor. Filming was accomplished with infrared light (>820 nm), since
previous work has shown that brachyuran crabs cannot detect light emissions at these
longer wavelengths (Cronin, 1986). Only intermolt crabs between 75–125 mm in
carapace width were used in trials, and both sexes were equally represented. Individuals
were tested once, and then released several kilometers from their initial capture location.
Locomotory and orientation behavior were determined using computer-aided motion
analysis of the crab movement trajectories. A path began when the crab first exhibited
movement and ended when the animal either began to dig for a clam (‘successful
search’), or left the camera’s field of view without locating the clam (‘unsuccessful
search’). Paths were analyzed at a rate of 2 frames s1; thus, data from each set of
consecutive frames represent values averaged over a 0.5 s interval. We determined the
distribution of angular bearings (0–360 ˚) of movement for all crabs relative to the
direction of flow (0 ˚); that is, the angle of the vector defined by the animal’s translational
movement from the starting frame to the following frame. We also determined the
average velocity of each path and the distribution of velocities for each path on a frame-
by-frame basis. Lastly, the net-to-gross displacement ratio (NGDR) was determined for
each path. The NGDR is the ratio of the shortest linear distance between the start- and
endpoints of the path divided by the total travel distance. This indicator of path circuity
has a maximum value of 1 (when paths are completely straight) and a minimum of zero
(when paths are circular and the start- and endpoints occur at the same spatial
Experiments separating the effects of advection (bulk transport) from eddy diffusion
The results of experiments with live clams indicated that increasing the free-stream
353Blue crabs use odor plumes to find prey
flow velocity substantially altered the search behavior of crabs (see Results). At the
macroscopic scale of a blue crab, transport of odor molecules occurs principally by eddy
diffusion and advection. Both of these transport mechanisms increased with free-stream
velocity in our experiments with live clams; advection and diffusion thus covaried.
Benthic boundary layer turbulence increases with the hydraulic roughness length of the
bed (i.e. sediment grain size; equation 2); we therefore elected to manipulate the bed
substratum size to increase turbulence, and hence eddy diffusion, without increasing free-
stream advection.
Behavioral assays were repeated at U=1.0 and 3.8 cm s1, and additional trials were
performed at U=1.0 cm s1, where the sand substratum was replaced with a
commercially available fine gravel (particle diameter 1.93±0.65 mm S.D.; N=100). At
U=1.0 cm s1flowing over the gravel substratum, u* and Re* increased relative to their
values at the same velocity flowing over sand, effectively decoupling advection from
eddy diffusion (see Results).
To provide more control over the stimulus environment, these experiments utilized
prey extracts emanating from model clams as the odor source. Prey extract was prepared
from hard clam tissue homogenized in artificial seawater medium (ASW, Forty Fathoms
Marine Mix) prepared using HPLC grade deionized water and reagent grade salts
(16.5 g wet tissue mass l1). The extract was prepared as a single batch, stored at 87 ˚C,
then diluted to a final concentration of 1:50 with ASW immediately prior to use.
To recreate the physical conditions of odor dispersal experienced by crabs foraging for
live clams, the homogenate was introduced into the flow through the excurrent siphon of
a model clam. Excurrent and incurrent siphons of a living clam were simulated using a
pair of Tygon tubes, placed contiguously with their lips and extending 3 mm above the
substratum. The excurrent flow was supplied from a small constant-head tank while the
incurrent flow was taken by a gravity feed from the flume. To ensure equality of the
incurrent and excurrent flow rates, we continuously monitored these flows with two
separate in-line rotameters. The scale of our model bivalve (physical size and pumping
rate) corresponded to a Mercenaria mercenaria of 15–20 mm length. On the basis of the
measurements of pumping clams (Weissburg and Zimmer-Faust, 1993), behavioral trials
were performed with a flow rate of 10 ml min1through a siphon pair with an excurrent
diameter of 3.7 mm and an incurrent diameter of 4.7 mm.
Behavioral assays were conducted, and analyzed, using the protocol described above.
Because paths were generally rather short and with high locomotory velocity, motion
analysis was performed using a video sampling rate of 5 frames s1. Animals were tested
only at an initial starting site of 0.5 m. A successful search was defined as one in which a
crab located the siphon of the model clam and began to grasp or unbury the siphon tubes.
A full treatment of the methods used in performing behavioral assays is presented in
Weissburg and Zimmer-Faust (1993).
Statistical methods
For experiments involving live prey, we employed multiway analyses of covariance
(ANCOVA) (Statistical Analysis Systems GLM procedure; SAS Institute, Carey, NC;
SAS, 1988) to determine the effects of flow speed, starting site and search result
(successful, unsuccessful and control) on mean velocity and NGDR of crabs during
searching. In this analysis, flow speed was the regression variable, and starting site and
search result were classification criteria. Paths of individual crabs were replicates in the
statistical analysis.
To investigate the mechanics of prey search adequately, it is also necessary to perform
a more detailed analysis of crab behavior by examining the distributions of locomotor
velocities and angular bearings during searching. However, statistical analysis of
kinematic data is quite difficult, and there is no completely adequate method. Circular
statistics (e.g. Batschelet, 1981) are generally only useful for examining a mean angle
over the entire path; that is, the angle of the vector from the initial to the final position of
the animal. In our experiments, the mean angle will be 0 ˚ for crabs moving directly
upstream to find prey, so analysis using mean angles reveals little regarding the actual
movement during searching. Calculating the mean angle for each path by averaging the
bearing of the animals across all frames will also result in values near zero. Furthermore,
this analysis suffers from a lack of independence, and paths with more frames are
weighted unequally. The last option is to compute a time budget for each path, by
expressing the proportion of travel time across various angular intervals, which become a
treatment effect in an analysis of variance (ANOVA). However, because these time
budgets must sum to one, the levels of the angular interval treatment of the ANOVA
analysis are not independent. Given these difficulties, investigations of search kinematics
typically present and analyze data using frame-wise measurements (i.e.Buskey, 1984;
Butman et al. 1988; Willis and Arbus, 1991).
In order to examine search kinematics more explicitly, we therefore employed
multiway contingency table analysis to determine the effects of flow speed and search
result on the distribution of velocities and angular bearings. The raw frequency data (from
the analysis of video frames) from all animals within a particular experimental treatment
were pooled to give aggregate distributions of velocities and angular bearings. For
multiway tables, Cohran–Mantel–Haenszel (CMH) general association statistics were
used to examine the general significance of each main effect while holding the other
effects constant. G-tests were employed in analysis of two-way tables extracted from the
full data matrix.
Hydrodynamic conditions
Hydrodynamic conditions during behavioral trials varied with current speed in
experiments with live clams and were functions of current speed and substratum type in
experiments using artificial clams (Table 1). In experiments with live clams, the
measurements of Re* indicate that boundary layer flows were smooth-turbulent at free-
stream velocities of 1.0 and 3.8 cm s1and that flow was transitional between smooth-
and rough-turbulence at 14.4 cms1. In experiments using artificial clams, measurements
of u* and Re* indicated greater turbulence, with eddies penetrating closer to the
substratum, at a velocity of 1.0 cms1over gravel than at that same velocity flowing over
sand. On the basis of calculated measures of boundary-layer structure, and visual
355Blue crabs use odor plumes to find prey
observation of Fluorescein dye ejected through the clam mimic (Weissburg and Zimmer-
Faust, 1993), plumes generated at 1.0 cm s1over gravel were more similar to those at a
current speed of 3.8 cm s1over sand than to plumes at a speed of 1.0 cm s1over sand.
Experiments with live clams
Analysis of locomotory speed
Mean speeds were complicated functions of flow velocity, starting site and search
result (Fig. 1A; Table 2). The large number of significant interaction effects indicates that
movement patterns were often determined jointly by two or more variables, although the
main effects themselves were generally significant.
Locomotory speeds of animals discovering prey (successful searchers) were
significantly faster than those of animals that either failed to uncover prey (unsuccessful
searchers) or were not presented with a prey item (no-clam controls; Fig. 1A; Table 2).
Ryan’s multiple range test (
=0.05) revealed that the speeds of successful searchers were
greater than the speeds of both unsuccessful searchers and animals in no-clam controls,
Table 1. Summary of hydrodynamic variables for flow treatments used in crab
behavioral trials
Uu* Viscous sublayer
(cm s1) (cm s1)Re* thickness (mm)
0.0 −−
1.0 0.07 0.4 8.0
1.0 (gravel) 0.14 2.7 1.1
3.8 0.3 1.6 1.8
14.4 1.2 6.3 0.5
U, free-stream velocity; u*, boundary shear velocity; Re*, roughness Reynolds number.
Substratum is sand except where otherwise noted.
Table 2. Summary ANCOVA table for analysis of mean locomotory speed in experiments
with live clams
Effect SS d.f. MS F
Flow speed 1.25 1 1.25 3.11
Site 6.88 1 6.88 17.11***
Result 35.66 2 17.83 44.37***
Flow speed ×site 0.16 1 0.16 0.39
Site ×result 3.03 1 3.03 7.54**
Flow speed ×result 2.90 2 1.45 3.61*
Flow speed ×site ×result 0.007 1 0.007 0.02
Error 64.69 161 0.402
In this analysis, flow speed is the regression variable, and site (close or far) and result (successful,
unsuccessful, no clam control) are class variables.
*P<0.05; **P<0.01; ***P<0.001.
and also that the locomotory speeds of the latter two groups were statistically
indistinguishable. Free-stream velocity and starting site affected locomotory speed only
for crabs that found prey; Ryan’s multiple range test indicated that all animals failing to
357Blue crabs use odor plumes to find prey
Fig. 1. Mean motion statistics for crabs in experiments with live clams. Mean ±1 S.E.M.
Found-C, crabs starting from the close site and finding clams. Found-F, crabs starting from the
far site and finding clams. Not found, crabs not finding clams, with data pooled across both
starting sites. No clam, crabs in no-clam controls, which always started at the close site. For
successful searchers starting at close positions, the numbers of crabs were 2, 9, 6, and 3 at 0,
1.0, 3.8 and 14.4 cms1respectively. For successful searchers starting at far positions, the
numbers of crabs were 6, 4 and 2 at 1.0, 3.8 and 14.4 cms1respectively. For unsuccessful
searchers starting at close positions, the numbers of crabs were 17, 9, 13 and 12 at 0, 1.0, 3.8
and 14.4 cms1respectively. For unsuccessful searchers starting at far positions, the numbers
of crabs were 17, 11, 13 and 13 at 0, 1.0, 3.8 and 14.4 cms1respectively. For no-clam
controls, the numbers of crabs were 10, 10, 9 and 9 at 0, 1.0, 3.8 and 14.4 cms1respectively.
(A) Mean locomotory speed versus free-stream flow velocity. No crabs found clams at
1at the far starting site. (B) Mean net-to-gross displacement ratio (NGDR) versus free-
stream flow velocity.
locate clams or in the control group displayed similar movement speeds regardless of
initial distance or free-stream velocity. This accounts for the interactions when ‘result’ is
paired with the other main effects (Table 2). In general, successful searchers moved faster
at slow current speeds and when initiating search closer to prey (Fig. 1A).
Analysis of the distributions of walking speed provides some insight into the patterns
of mean velocity. Animals that did not find clams, or where no prey was present, showed
a similar distribution of velocities regardless of current velocity or starting site (Fig. 2).
The distributions of walking speeds are unimodal, with a large peak in the zero velocity
bin (speed <0.25 cm s1) and steadily decreasing frequencies at higher locomotory
speeds. By comparison, crabs finding clams had speed distributions lacking a strong peak
in the zero velocity bin, but with an appreciable frequency of observations at higher
locomotory velocities (Fig. 3).
Animals finding clams (at either site) exhibited a lower frequency of observations in
the zero velocity class and more observations at high speeds than animals either not
finding clams or in the control group. Search result significantly affected the overall
distribution of speeds when controlling for current velocity (Table 3). Pairwise
Fig. 2. Frequency distribution of locomotory speeds at each flow velocity for crabs that were
not presented with clam prey or did not locate clam prey. No clam, no-clam control; NF-
Close, crabs starting from the close site and not finding clams; NF-Far, crabs starting from the
far site and not finding clams. (A) 0 cms1, N=2801, 3042 and 10137 frames for no-clam
controls, close and far starting sites, respectively. (B) 1.0 cms1, N=3528, 5388 and 1496
respectively. (C) 3.8 cms1, N=2273, 8175 and 1478 respectively. (D) 14.4cms1, N=2684,
1758 and 1552 respectively. Numbers of crabs in each treatment are given in the legend of
Fig. 1.
comparisons of successful versus unsuccessful searchers at each flow rate indicate a
significant effect of search result on the overall distribution of locomotory speeds at close
and far sites at U=1.0 cm s1(CMH>158.18, d.f.=9, P<0.001, for all comparisons). In
spite of the lack of an effect on the entire distribution of walking speeds at the remaining
far sites (U=14.4, 3.8 cm s1), animals that find clams show a lower frequency of
observations in the zero velocity bin than do their counterparts that fail to locate clams
(G>20.50, d.f.=1, P<0.001, for both comparisons).
359Blue crabs use odor plumes to find prey
Fig. 3. Frequency distribution of locomotory speeds at each flow velocity for crabs that found
clam prey at either the close or far starting site. (A) 0 cm s1, N=306 frames for the close site.
No crabs found clams starting from the far site. (B) 1.0 cm s1, N=228 and 332 frames for the
close and far sites, respectively. (C) 3.8 cms1, N=268 and 189 respectively. (D) 14.4 cms1,
N=122 and 483 respectively. Numbers of crabs in each treatment are given in legend of Fig. 1.
Table 3. Summary of analysis of distribution of locomotory speeds in experiments with
live clams
Test statistic Value d.f.
Search result
Close sites CMH11381.2*** 9
Far sites CMH 338.01*** 9
Flow speed2CMH 246.40*** 27
Site2CMH 184.94*** 9
1Cochran–Mantel–Haenzel general association statistic.
2Analysis includes only crabs successfully finding clams.
When considering only animals that search successfully, the velocity distributions of
animals in low flows were right-shifted, so the modes occurred at higher velocity classes.
Furthermore, crabs remained motionless less often at low flows and when initiating
search closer to prey (Fig. 3). The duration and number of bouts of motionlessness are
given in Table 4. Although there is considerable variability, regression analysis indicated
a general association between the duration of motionless periods and flow velocity
(F=4.44 d.f.=1,79, P<0.05).
The mean speed for each crab finding prey was subsequently recalculated after
removing all observations in the zero velocity class, yielding average locomotory speed
of crabs during the time animals were actually walking. These ‘true’ locomotory speeds
were then analyzed with ANCOVA, again using flow speed as the regression variable and
initial site as the classification variable. Crabs still moved significantly faster when
initially closer to clam prey, and there was a strong, but only marginally insignificant,
tendency for crabs to move faster at lower flow velocities (P<0.10; Table 5).
Analysis of NGDR and angular bearings
The analysis of NGDR reveals a more complicated interaction among the variables
Table 4. Summary of characteristics of motionless periods as a function of flow speed for
crabs in experiments with live clams
Flow speed (cm s1)
0 1.0 3.8 14.4
Mean ± S.E.M. 2.3±0.5 3.9±1.1 5.5±1.1 7.5±1.7
N12 16 19 34
Mean duration of motionless period (number of video frames) is given ±1 standard error, with number
of periods.
Video frame rate is 2 framess1.
Table 5. Summary ANCOVA statistics for analysis of mean true locomotory speed of
crabs successfully locating clam prey
Effect SS d.f. MS F
Flow speed 1.88 1 1.88 3.37†
Site 2.05 1 2.05 4.34*
Flow speed ×site 0.51 1 0.51 0.92
Error 11.76 21 0.559
In this analysis, mean locomotory speeds have been recalculated after removing all observations in
which velocity equals 0.
P<0.1; *P<0.05.
For crabs starting close to prey, average locomotory speed was 2.8, 2.8, 1.9 and 1.5 cm s1at flow
velocities of 0, 1.0, 3.8 and 14.4 cm s1respectively. For crabs starting far from prey, average
locomotory speed was 1.8, 2.0 and 1.3 cm s1at flow velocities of 1.0, 3.8 and 14.4 cm s1(no crabs
found clams at the far site in no flow).
than that occurring in the analysis of locomotory speed (Fig. 1B; Table 6). There was a
significant interaction among all three variables. In five of the six possible comparisons in
which there is flow, animals that find prey show lower NGDRs at high current speeds and
higher NGDRs at low current speeds. This trend is violated by crabs in zero flow, an
observation having important implications for hypotheses on orientation mechanisms
(see Discussion). Animals that do not find clams or animals in the no-clam control group
show the reverse pattern, displaying lower NGDRs at low current speeds and higher
NGDRs at high current speeds.
Analysis of movement direction provides explanations for the patterns of NGDR
observed across the various experimental treatments (Figs 4, 5). For animals that do not
find clams or are not presented with prey, the distribution of angular bearings indicates
that as flow increases movement becomes increasingly aligned with the axis parallel to
the current. In these treatment groups, flow velocity exerts a significant effect on the
distribution of angular bearings (CMH>947.0, d.f.=21, P<0.001, for all comparisons). As
flow velocity increases, animals move in a straight line parallel to the flow direction and
proceed either directly up- or downstream. At low velocities, crabs take headings oblique
to the flow axis and execute numerous turns while travelling either up- or downstream
across the working section. There appears to be no detectable pattern with respect to
frequency of movement up- versus downstream for crabs not finding clams. On the basis
of confidence limits for percentages (data shown in Fig. 4), animals in five treatments
(0 cm s1no clam; 0 cm s1close; 1 cm s1close and far; 14.4 cm s1close) moved
predominantly downstream, animals in four treatments (1.0, 3.8 and 14.4 cms1no clam;
14.4 cm s1far) moved mainly upstream, and up- versus downstream movement was
equal in the remaining treatments (0 cm s1far; 3.8 cm s1close and far). Pooled across
all trials, movement was random with respect to flow direction.
In contrast, the relationship between movement direction and flow rate in successful
predators was exactly the opposite of that found in either of the other groups (Fig. 5).
Typical search paths displayed by successful predators are shown in Fig. 6. As in the
361Blue crabs use odor plumes to find prey
Table 6. Summary ANCOVA statistics for analysis of mean NGDR in experiments with
live clams
Effect SS d.f. MS F
Flow speed 0.024 1 0.024 0.59
Site 0.058 1 0.058 1.41
Result 0.052 2 0.026 0.63
Flow speed ×site 0.263 1 0.263 6.36**
Flow speed ×result 0.476 2 0.238 5.75**
Site ×result 0.087 1 0.087 2.11
Flow speed ×site ×result 0.193 1 0.193 4.66*
Error 6.830 161 0.042
In this analysis, flow speed is the regression variable, and site and result are class variables.
Net-to-gross displacement ratio, NGDR, has been arcsine-transformed to meet normality criteria.
*P<0.05; **P<0.01.
previous analysis, there was a significant association between movement direction and
flow velocity for crabs finding prey (CMH=302.0, d.f.=21; CMH=162.2, d.f.=14, for
close and far sites, respectively, P<0.001 for both comparisons; d.f. differs because no
crabs found clams at 0 cm s1at the far site). When crabs found prey, paths were most
aligned to the current direction at U=1.0 cm s1, whereas crabs frequently moved
obliquely to the current direction at higher flow speeds. Crabs that successfully searched
for prey at U=1.0 cm s1appeared to move directly upstream towards the prey, while
successful searchers at higher current speeds always tacked across stream at least once,
and often several times, while en route to the prey item. Crabs in the absence of flow
exhibited highly chaotic path trajectories apparently devoid of any pattern of preferential
movement relative to the nominal flow axis.
Crabs that found clams also exhibited movement that was apparently polarized in the
upcurrent direction. Animals moved predominantly upstream in all treatments in which
Fig. 4. Frequency distribution of angular headings at each flow velocity for crabs that were not
presented with clam prey or did not locate clam prey. No clam, no-clam control; NF-Close,
crabs starting from the close site and not finding clams; NF-Far, crabs starting from the far site
and not finding clams. (A) 0 cm s1, N=1311, 2968 and 2372 frames for no-clam controls,
close and far starting sites, respectively. (B) 1.0 cm s1, N=1655, 1635 and 343 respectively.
(C) 3.8 cm s1, N=288, 465 and 840 respectively. (D) 14.4 cm s1, N=1766, 1153 and 1107
respectively. Sample sizes are different from those given in Fig. 2 because frames during
which crabs remained motionless had no angular headings. Numbers of crabs in each
treatment are given in the legend of Fig. 1. Clam prey is located at 0˚, and ±180 ˚ points
downstream directly away from prey.
they located prey (based on confidence limits for percentages; data from Fig. 5). Crabs in
the absence of flow were a notable exception to the above pattern, showing extensive
movement down-flume, i.e. away from clam prey.
The differences in behavior between crabs finding prey and the other two groups were
consistent and profound. Overall, crabs finding prey showed a significantly different
distribution of angular bearings compared with animals either not finding or not searching
for prey, at all current speeds (CMH>184.1, d.f.=7, P<0.001, for all comparisons).
Further, pairwise comparisons at each current speed/position combination indicate that
successful predators showed significantly different distributions of angular bearings from
either unsuccessful predators or crabs in the control group (G>61.1, d.f.=7, P<0.001, over
all comparisons). In summary, crabs finding prey in low flows exhibited movement
aligned to the direction of flow and polarized upstream, whereas crabs not finding prey or
in the absence of prey, moved obliquely to the flow direction without any upstream bias.
In swift flows, crabs finding clams exhibited a greater tendency to move across-stream
towards prey (i.e. upstream) and crabs in the other two groups moved parallel to the
direction of the flow either up- or downstream.
363Blue crabs use odor plumes to find prey
Fig. 5. Frequency distribution of angular headings for crabs that found clams at either the
close or the far starting site. The coordinate system is the same as that given in Fig. 4.
(A) 0 cm s1, N=279 frames for close site. No crabs starting from far site found clams.
(B) 1.0 cm s1, N=206 and 303 frames for close and far sites, respectively. (C) 3.8 cm s1,
N=226 and 158 respectively. (D) 14.4 cms1, N=99 and 361 respectively. Sample sizes differ
from those given in Fig. 3 because frames during which crabs remained motionless had no
angular headings. Number of crabs in each treatment are given in the legend of Fig. 1.
Experiments separating the effects of advection from those of eddy-diffusion
The measurements of boundary layer structure (Table 1) indicate that the use of
substrata of different hydraulic roughness alters boundary layer turbulence and the degree
of eddy penetrance, irrespective of changes in flow speed. Thus, treatments at the same
flow velocity, but where gravel was substituted for smaller-diameter sand, displayed
increased u* and Re*. The effects of turbulence (eddy diffusion) were magnified without
concomitant increases in flow speed (advection).
Single-classification ANOVA indicates that the boundary layer structures generated
using particular substratum/flow current speed conditions appear to be responsible for
effects on crab locomotory behavior during prey search (Table 7; Figs 7, 8). For both
locomotory speed and NGDR, Ryan’s multiple range test (
=0.05) indicates that the
behavior of crabs in the low u*/low Re* treatment (U=1.0 cm s1over sand) is
significantly different from that of crabs in either of the other two high u*/high Re*
treatments (U=1.0 cm s1over gravel, and U=3.8 cm s1over sand). Furthermore, the
behavior patterns of animals in these latter two treatments are statistically
indistinguishable from each other.
Fig. 6. Typical search paths for crabs successfully finding clams. Dashed lines are for crabs
that started from the close site, solid lines are for crabs starting from the far site. Paths begin at
the cross and end when the clam (denoted by a star) is located. Paths have occasionally been
shifted along the x-axis to avoid overlap and to increase clarity. Flow proceeds from the top to
the bottom of the figure.
365Blue crabs use odor plumes to find prey
Table 7. Summary ANOVA statistics for experiments separating advection from eddy
Effect SS d.f. MS F
Mean locomotory speed
Flow treatment 20.26 2 10.13 8.06**
Error 27.66 22 1.26
Mean net-to-gross displacement ratio
Flow treatment 0.338 2 0.169 10.39***
Error 0.357 22 0.016
NGDR has been arcsine-transformed to meet normality criteria.
**P<0.01; ***P<0.001.
Fig. 7. Mean movement statistics for crabs successfully finding clam mimic in experiments
separating advection from eddy-diffusion. Means +1 S.E.M. Crab symbols mark groups not
significantly different using a Ryan’s Q-test,
=0.05. (A) Mean locomotory speed versus flow
speed/substratum combination. (B) Mean NGDR versus flow speed/substratum combination.
Numbers of crabs successfully finding a clam mimic were six at 1.0 cms1over gravel, nine at
1.0 cm s1over sand and nine at 3.8 cms1over sand.
Analysis of the frequency data of crab walking speeds (Fig. 8) indicates that the
boundary layer structure also has a significant effect on the distribution of movement
velocities (CMH=9.4, d.f.=1, P<0.001). The frequency of observations in which crabs
remained motionless follows the ranking of Re* across treatments, and pairwise
comparisons indicated that all treatments are significantly different from each other
(G>22.1, d.f.=9, P<0.01, over all comparisons). When locomotory speeds are
recomputed after removing the zero velocity class, animals still travel more quickly in the
low u*/low Re* treatment (F=9.2, d.f.=2,22, P<0.001), and a Ryan’s multiple range test
indicates that this behavior is different from that of a group consisting of the other two
Increased hydraulic roughness of the bed also affects angular bearings in a way similar
to the effects of increased flow speed, again indicating that boundary layer structure, not
flow speed per se, is responsible for modulating behavior. Animals in both the high
u*/high Re* trials move more obliquely relative to the direction of flow (Fig. 9), with a
significant overall effect of treatment on the distribution of angular bearings (CMH=65.9,
d.f.=14, P<0.001). Pairwise comparisons indicate similar distributions of angular
bearings in the two high u*/high Re* conditions (G=13.4, d.f.=14, P>0.05), while the
behavior of the lowest u* and Re* treatment group is significantly different from that of
either of the remaining two groups (G>45.9, d.f.=14, P<0.001 for both comparisons).
Fig. 8. Frequency distribution of locomotory speed for the three flow speed/substratum
combinations in experiments separating advection from eddy diffusion. N=809 frames for
3.8 cm s1over sand, 234 frames for 1.0 cm s1over gravel and 260 frames for 1.0 cm s1
over sand. Numbers of crabs in each treatment group are given in the legend of Fig. 7.
Our observations on blue crabs in controlled flow conditions show that locomotory
behavior is a complex function of both the hydrodynamic properties of the flow and the
presence or absence of olfactory stimulants. Locomotory speed and travel direction are
affected by the flow and stimulus treatments. When crabs either fail to detect odorants
(unsuccessful predators) or move in flows without odorants (no-clam controls),
locomotory speeds are slow and bear no relationship to flow velocity. Movement of crabs
becomes progressively more aligned to the flow axis as U(free-stream velocity)
increases, although movement up- versus downstream occurs with equal probability.
Because the behavior of unsuccessful predators is strikingly similar to the patterns
displayed by crabs in the no-clam trials, it appears that unsuccessful predators have not
detected odorants or, perhaps, are not responding to odorants that they do indeed detect.
Crabs responding to prey odors (successful predators) display behavior patterns very
different from the movements of the two groups mentioned above. The general kinematic
properties of locomotory tracks are summarized for each group in Table 8. In flowing
367Blue crabs use odor plumes to find prey
Fig. 9. Frequency distribution of angular headings for the three flow speed/substratum
combinations used in experiments separating advection from eddy diffusion. N=452 frames
for 3.8 cms1over sand, 185 frames for 1.0 cms1over gravel and 191 frames for 1.0 cms1
over sand. Sample sizes differ from those listed in Fig. 8 because frames in which animals
remained motionless had no angular headings. The coordinate system is the same as that given
in Fig. 4. Numbers of crabs in these treatment groups are given in the legend of Fig. 7.
water, locomotory speeds of successful predators decrease with elevations in U.
Movement paths become less parallel to the flow axis with increasing Uas crabs tack
across stream in search of prey, yet always move steadily upstream. The zero velocity
treatment represents a special case. Animals display the high locomotory speeds
characteristic of behavior in low flow, yet move along chaotic trajectories. Paths in no
flow show extensive movement across the nominal flow axis and display lower NGDRs
than in any other treatment.
Altering substratum roughness and flow velocity separates the effects of free-stream
velocity (advection) from those of turbulence (eddy diffusion). These manipulations
produced a set of treatments with similar degrees of advection, but different levels of two
variables, u* and Re*, that describe the magnitude of turbulent flow near the sediment
bed. For crabs responding to prey odors, decreased u* and Re* leads to greater sustained
rates of locomotory speed, decreases in the extent to which animals remain at rest, and
paths that are oriented more directly upstream towards potential prey. In these
experiments, the changes in crab behavior mimic the effects seen in trials with live clams,
suggesting that increases in current velocity and substratum hydraulic roughness both
mediate behavioral changes by altering turbulence structure within the boundary layer.
Odorant transport is profoundly influenced by the physical environment of the
prevailing fluid flow. It is clear that, in blue crabs, predatory search behavior is heavily
influenced by the flow environment in which these olfactory activities take place. Crabs
successfully locating prey behave quite differently from crabs that fail to find prey items.
Crab predators successfully accomplished their task in darkness under infrared light,
where chemical cues emanating from the partially exposed siphon of an otherwise buried
clam were required to indicate the presence of prey. Thus, changes in the behavior of
successful predators may at least partially be ascribed to alterations in the temporal and
spatial properties of the chemical stimulus environment. These changes in odor plume
structure are mainly a result of changes in boundary layer turbulence, as shown by similar
responses of crabs in swift flows and of crabs in slower flows where u* and Re* are
increased by manipulations of the substratum. Flow velocity itself influences some
aspects of the locomotory behavior in the absence of odorants, particularly the degree of
across-stream movement. This may have important consequences for determining the
probability of encountering an odor plume, but has little bearing on orientation within a
Table 8. Summary of behavioral responses to increased flow speed
Walking speed NGDR Angular bearing
Successful searchers Decreases Decreases* More oblique*
Unsuccessful searchers No relationship Increases More aligned
No-clam controls No relationship Increases More aligned
The relationship of walking speed, NGDR and angular bearings relative to the flow axis are given for
crabs that are either successful or unsuccessful in locating clam prey, or are not presented with prey
items (no-clam controls).
*Except crabs at 0 cm s1, which exhibit low NGDR and frequently move across the nominal flow
plume. In any case, the net result is that crabs in more turbulent flows locate prey less
often than crabs foraging in more benign hydrodynamic conditions (Weissburg and
Zimmer-Faust, 1993).
Although flow-induced turbulence is detrimental to orientation ability in a plume,
this argument cannot be taken to its extreme conclusion; namely, that flow itself is
undesirable. When deprived of flow in an environment where molecular diffusion is the
only odorant transport mechanism, crabs rarely locate prey (Weissburg and Zimmer-
Faust, 1993) and display long convoluted search paths. Odorants in stagnant conditions
diffuse slowly, and odorant concentrations decrease exponentially with distance from
the source to establish a well-defined gradient in odorant strength (Okubo, 1980). Dye
visualization studies conducted in our flume are consistent with these theoretical
expectations of diffusion models. Clearly, crabs are not guided to odor sources by
following this simple gradient up-flume to the odor source, ruling out an orientation
mechanism based solely on changes in odorant intensity. The general orientation
towards prey is mediated by the perception of flow direction, and the presence of flow
acts to polarize olfactory-guided locomotion in the up-current direction. Animals as
diverse as snails, flatworms, insects and sharks also appear to require flow in order to
locate odor sources (Hodgson and Mathewson, 1971; Bell and Tobin, 1982; Brown and
Rittschof, 1984; Baker, 1986). In other crustaceans, workers have not demonstrated
convincingly that flow is either required or unnecessary for successful location of an
odor source. McLeese (1973) reported that the lobster Homarus americanus could
detect an odorant trail in the absence of flow, but not that animals could successfully
use a chemical concentration gradient to find an odor source in stagnant water. In other
investigations of lobster orientation, stimulus delivery involved the use of a carrier
flow, and the authors concede that flow may be acting as a cue during orientation
(Reeder and Ache, 1980; Devine and Atema, 1982; P. A. Moore, personal
It remains to be seen whether increasing flow rate is beneficial when divorced from the
effects of increasing turbulence magnitude. Swifter flows can provide greater stimulation
of mechanosensory hairs, which must be deflected from a stationary position to encode a
mechanical stimulus. As long as the flow remains sufficiently smooth so that chemical
signal properties are not adversely affected, increasing flow velocity may allow animals
to sense current more accurately and to take more direct routes to the odor source. In any
case, our data demonstrate the existence of a minimum flow velocity (<1 cm s1) below
which orientation responses of blue crabs are compromised.
Crabs maneuvering within the odor plume are responding to a chemical signal with
spatial/temporal properties produced, in part, by the hydraulic properties of the flow.
Changes in the kinematics of search as a function of flow may therefore reveal much
about the relevant chemical signal properties, since it is possible to relate fluid dynamic
variables to potential changes in odor plume structure. First, increased turbulence will
result in greater eddy diffusion, dispersing odorants more widely and reducing time-
averaged odorant concentration in the plume (Schlicting, 1979; Okubo, 1980). Second,
since turbulence is essentially the degree to which correlated fluctuations in velocity (or
eddies) are present in the fluid, variance in odor concentration also increases in more
369Blue crabs use odor plumes to find prey
turbulent flows. A fixed location may therefore experience odorant levels considerably
above or below the time-averaged concentration.
Separate experiments recently conducted in our laboratory using similar flow speeds
and substratum types to those used here verify these anticipated effects of increased
turbulence on dynamics of odor transport (Moore et al. 1992, 1994). In these two studies,
tracer molecules (dopamine) were introduced via the same model clam and at the same
flow rates as were used in the trials with blue crabs reported here. The parallel
methodology ensures similarity of odorant transport dynamics in each of these
investigations. At a stationary sensor (sampling at 10 Hz), odorant concentrations above
background occurred in discrete bursts that last several seconds. Between these bursts,
odorant concentrations fell to zero. Within a burst, odorant concentrations could be further
resolved into a series of brief peaks termed odor pulses. As turbulence was increased, the
time between bursts lengthened, but the total number of odor pulses within a burst
increased. Concentration variance at both short (500–1000 ms) and long (>1 s) temporal
scales was positively associated with turbulence intensity. Additionally, the time-averaged
odorant level within these odor pulses fell with increased turbulence, reflecting greater
overall dilution of odorants transported downstream within the plume. These findings are
in qualitative agreement with observations of transport dynamics occurring within air-
borne odor plumes (Murlis and Jones, 1981; Murlis, 1986; Murlis et al. 1991).
The behavior of blue crabs foraging in more turbulent flows seems to reflect at least
some of the predicted changes in plume structure. Average locomotory velocities, with or
without the inclusion of periods of motionlessness, are lower in more turbulent flows.
Similarly, modes in the frequency distributions are shifted towards lower velocities in
more turbulent flows. Walking speeds presumably decrease because lower odorant
concentrations in turbulent plumes induce a less vigorous locomotory response.
Extensive study of crustacean olfactory receptors indicates a positive relationship
between neural output and the concentration of stimulatory substances (Fuzessery et al.
1978; Ache, 1982; Derby and Atema, 1988). For known behavioral stimulants,
observations on neural output correlate well with evidence on searching or locomotory
responses to applied dose in a variety of crustacean taxa. Studies indicate that rates of
searching movements (Zimmer-Faust and Case, 1982; Harpaz and Steiner, 1990) and of
antennule flicking (Price and Ache, 1977; Harpaz and Steiner, 1990; Daniel and Derby,
1991) and locomotory velocity (Buskey, 1984; Weissburg and Zimmer-Faust, 1991) may
all increase with stimulant concentration.
Crabs also stop more frequently in more turbulent flows. The most parsimonious
explanation is that these bouts of motionlessness simply reflect long periods during which
odorant concentration falls below detectable limits. As animals reach the edge of the
plume, odorant concentration is low, or not above background levels. Individuals then
cease walking until a burst of odorant is carried past the animal, initiating movement back
towards the odor source. It is worth noting that an average of 3–4 clams, generally
separated by 10–15 cm, were observed pumping during behavioral trials. We conclude
from dye visualization using model clams that crabs were probably reacting to plumes
from isolated clams, rather than perceiving the entire clam patch as a solid corridor of
Our data on the duration of motionless periods and on the angular bearings of the
animals during searching suggest that locomotion stops when crabs lose contact with the
plume. Upstream tack angles show an average difference of 76±57 ˚(S.D.) in the directions
taken by animals before and after stationary periods. Both the number and duration of
motionless periods increase as a function of increased flow speed (Table 4). Plume
meandering will be more extensive in more turbulent conditions (Murlis and Jones, 1981;
Elkinton and Cardé, 1984) and, hence, at faster flows. Thus, animals in a swift flow find
themselves at an edge with increasing probability, so the incidence of turning and
stopping will increase. This is consistent with the gross movement patterns (NGDR) and
the distributions of angular headings for the animals in our high versus low turbulence
treatments. Insects that walk to odor sources, or intersperse flying with bouts of walking,
also appear to stop when they have lost contact with the plume, resuming motion when
contact has been re-established (Hawkes and Croaker, 1979; Didonis and Miller, 1980;
Bursell, 1984). Insects flying in wind currents cannot stop to re-establish contact,
although the ‘casting’ behavior observed following loss of contact with a plume fulfils the
same function; that is, animals can remain in a holding pattern by sweeping back and
forth across the wind direction until the plume edge is relocated (David et al. 1983;
Baker, 1986; Willis and Arbas, 1991). Although tentative, and under further study, our
conclusion is that large-scale variation induced by plume meandering, not microscale
structure within the plume, is affecting the stopping and subsequent turning maneuvers of
blue crabs orienting to prey.
The turning behavior described here also illustrates the lack of a regular pattern of
changes in course trajectory (Fig. 6), which has implications for determining the neural
mechanisms underlying olfactory orientation. It is frequently observed that when insects
follow pheromone plumes, they display consistent turning angles that alternate regularly
between left- and right-hand turns, thus continually tacking towards the center of the
plume. This phenomenon, called counter-turning, has often been interpreted as being the
result of an internally guided motor program (Willis and Cardé, 1990; Willis and Arbas,
1991; but see also Preiss and Kramer, 1986). In this scenario, the alternation of turning is
triggered by chemical cues, but chemical information does not provide feedback control
of the actual turning angles. Rather, it is speculated that counter-turns are produced by an
endogenous oscillator, possibly interneurons that act to bias motor output alternately
from one side to the other (Olberg, 1983). The lack of both consistent turning angles and
an alternating turning pattern argues against an internal motor program in foraging blue
crabs. Furthermore, course trajectories taken by insects utilizing counter-turning behavior
appear to be largely unaffected by changes in flow (wind) speed (Willis and Cardé, 1990;
Willis and Arbas, 1991), whereas blue crabs clearly change their search behavior in
response to flow (Figs 4, 6, 9). It appears that at least one other benthic crustacean, the
American lobster Homarus americanus, also fails to display evidence for internally
guided motor programs (Moore et al. 1992).
In the absence of an endogenous counter-turning motor program, crabs might remain
in the center of the plume by using direct feedback from temporal and/or spatial
comparisons of odorant concentration. Lobsters have been reported to use both
simultaneous bilateral comparisons (tropotaxis; Frankel and Gunn, 1961) and sequential
371Blue crabs use odor plumes to find prey
comparisons (klinotaxis; Frankel and Gunn, 1961) during orientation to odor sources
(McLeese, 1973; Reeder and Ache, 1980; Devine and Atema, 1982). These reports
stress the importance of chemo-orientation but, as discussed above, cannot rule out the
influence of flow in producing successful orientation. Orderly gradients of odorant
concentration do not exist in naturally turbulent water flows (Zimmer-Faust et al. 1988;
Moore et al. 1994), making tropo- or klinotactic methods of chemical gradient detection
ineffective search strategies for most macroscopic bottom-dwelling aquatic animals. In
many estuarine environments, flow is tidally driven and, hence, unidirectional over long
periods. Under these conditions, flow provides a reliable cue for orientation towards the
odor source. On the basis of our results, we suggest that chemotactic and rheotactic
mechanisms together produce successful orientation. Upon perception of a chemical
cue, crabs determine the direction of flow, producing an upstream bias in locomotion.
Subsequently, features of the odorant distribution are then used by the animals to orient
themselves within the plume and to mediate turning behavior if the searcher loses
contact with the plume. The reliance on multi-modal cues is similar to models of insect
orientation. However, in contrast to our view of orientation in Callinectes sapidus,
insects are generally thought not to rely as heavily on direct feedback from chemical
information during upwind flight (Arbas et al. 1993). Rather, locomotory patterns in
flying insects probably result from the interaction between stimulus-induced
endogenous counter-turning and optomotor guided amenotaxis (Mafra-Neto and Cardé,
1994). Continued examination of the olfactory-mediated orientation of crustaceans in
realistic benthic boundary layer flows, and with carefully controlled stimulus properties,
is clearly necessary to substantiate these differences between marine and terrestrial
Our data on the kinematics of orientation implicate boundary layer structure as a
crucial element in establishing patterns of locomotory performance, through effects on
the spatial and temporal properties of odorant concentration. Since the hydraulic
environment mediates a number of different aspects of odorant transport, the resulting
aggregate properties of odorant plumes are likely to be quite complex. Determining
strategies of animal navigation through turbulent odor plumes may subsequently appear
daunting. However, our studies are currently aimed at examining the role of individual
signal features in determining orientation patterns. These studies, in turn, may suggest the
environmental features that alter the properties of odor plume structure most relevant to
the ability of animals to perceive odor cues accurately. Further investigations establishing
a comparative approach to olfactory-mediated orientation may help to provide linkages
between animal navigational performance and the hydraulic properties of fluid
environments. Most available information originates from a few well-studied insects.
However, the scant information on the behavior and physiology of marine organisms
suggests important differences between marine and terrestrial arthropods that are
consistent with the differences in the fluid mechanical properties that characterize the
environments occupied by each group. A strong comparative approach may allow
predictions about the mechanisms used by various animals in searching for distant odor
sources, depending on properties such as animal size and mobility, fluid viscosity and
transport mechanics of odorants in fluid flows.
The authors express their thanks for the extremely capable assistance of M. Tamburri,
T. Thibault and M. Williams in collecting and tethering crabs during the many
experiments, P. Moore for helpful comments on the arcana of terminology relating to
orientation mechanisms and C. Derby for thoughtful comments on earlier drafts. This
work was partially supported by an NIH-NIMH grant 1-F32-MH10030 to M.J.W., an
NSF grant IBN-9222225 to R.Z.F. and the University of South Carolina Research and
Productive Scholarship Fund.
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375Blue crabs use odor plumes to find prey
  • ... Therefore there was less variation in crawling speed response. Weissburg and Zimmer-Faust (1994) who studied feeding response of blue crab (Callinectes sapidus), found that the crab showed directional responses toward the odour source in less turbulent flow and showed a more indirect trajectory in turbulent flow resulting in smooth and rough odour plumes, respectively. The narrow and straight plume resulting from slow current velocity may cause the tip of the leading arm to move in a limited arc, resulting in a straighter trajectory. ...
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    INSTISARI Penelitian tentang respon hewan bintang laut Pasifik Utara telah dilakukan di Tasmania Aquaculture and Fisheries Institute (TAFI) Taroona Hobart Tasmania. Tujuan penelitian ini untuk mengetahui respon Asterias amurensis terhadap stimulan (asam amino Betaine) dan ambang konsentrasi yang direspon serta orientasi pemangsaan (NGDR dan kecepatan merayap). Tujuh konsentrasi (Molar) larutan Betaine yang ditandai pewarna rhodamin digunakan dalam penelitian ini yaitu 0 M (kontrol), M. Kecepatan arus yang digunakan adalah 1,1 cm/dt. Respon direkam dengan kamera video dan dianalisa dengan program MOCHA. Hasil analisa statistik menunjukkan bahwa respon maksimum ditunjukkan pada konsentrasi 10-5 M (P: 0,05, IDF= 3,843). Kosentrasi ambang diduga antara 10-7 M dan 10-8 M. Hasil penelitian juga menunjukkan bahwa tidak ada perbedaan respon bintang laut kecil dengan yang besar. Hasil analisa statistik juga menunjukkan bahwa NGDR dan kecepatan merayap tidak ada perbedaan diantara konsentrasi Betaine. ABSTRACT A study on the response of North Pacific Sea star was undertaken at Tasmania Aquaculture and Fisheries Institute (TAFI) Taroona Hobart Tasmania. The objectives of the observation were to observe response of Asterias amurensis to various of feeding attractant (Betaine-amino acid) concentration, the threshold concentration to which A. amurensis respond; feeding orientation (NGDR) and crawling spped. Seven molars concentration of feeding attractant dyed with rhodamine were applied i.e. 0 M (control), M. The experiment was carried out in a simulation tank with undirectional flow i.e. 1,1 cm/s. Feeding response was recorded with video camera and quantitatively analyzed by means of image analysis software i.e. MOCHA. The statistical analysis results indicate that the maximum response was shown at 10-5 M (P: 0,05), IDF= 3,843) and the threshold concentration was thought at between 10-7 M and 10-8. It was also shown that there was not significant difference on the response of small and large size individuals, except at 10-1 M concentration. The were no significant difference on both NGDR and crawling speed.
  • ... The velocities we observed are similar to movement velocities of crabs walking seaward during the spawning migration [13] . They are considerably faster than average 0.3m/min speeds observed in a flume walking up current in response of chemical stimulation [44] . ...
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    In their ranges on east and south coasts of the Americas as well as their established invasions in the Adriatic and Baltic, blue crabs, Callinectis sapidus, inhabit estuaries, sounds and coastal oceans and are commercially and ecologically important. How crabs move in response to physical variables is important to management. We monitored life stages at canal control structures, assessed gender ratios with recreational crabbing, learned from crabbers, and studied movements of tagged crabs in a canal connecting Lake Mattamuskeet to the Pamlico sound. Juveniles enter the lake through two of 4 canals connecting to the sounds. Females migrate out through one canal. The lake standing population is about 70% male. Movements of 240 crabs in August 2012 and 102 crabs in October 2014 were quantified using RFID tags with co-located meteorological and oceanographic devices. Non-spawning females and males are nomadic. Crabs released in the canal move in response to changes in water depth and go with the flow, toward the Pamlico Sound (summer 76% and fall 78%). What crabbers describe as a fall migration appears to be concentration of crabs in warmer deeper canals and then southern movement with flow generated by strong north winds. To be effective, management strategies like migratory corridors require understanding of crab movements.
  • ... A relatively unexplored characteristic of a gas distribution map for source localization is the concentration intermittency [45]. The concentration intermittency, defined by Celani et al. [46] as the fraction of time the concentration is nonzero, is a key directional cue for animal chemo-orientation in turbulent plumes [45,[47][48][49]. Mapping the concentration intermittency with a CSG would be very interesting. ...
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    The difficulty to obtain ground truth (i.e. empirical evidence) about how a gas disperses in an environment is one of the major hurdles in the field of mobile robotic olfaction (MRO), impairing our ability to develop efficient gas source localization strategies and to validate gas distribution maps produced by autonomous mobile robots. Previous ground truth measurements of gas dispersion have been mostly based on expensive tracer optical methods or 2D chemical sensor grids deployed only at ground level. With the ever-increasing trend towards gas-sensitive aerial robots, 3D measurements of gas dispersion become necessary to characterize the environment these platforms can explore. This paper presents ten different experiments performed with a 3D grid of 27 metal oxide semiconductor (MOX) sensors to visualize the temporal evolution of gas distribution produced by an evaporating ethanol source placed at different locations in an office room, including variations in height, release rate and air flow. We also studied which features of the MOX sensor signals are optimal for predicting the source location, considering different lengths of the measurement window. We found strongly time-varying and counter-intuitive gas distribution patterns that disprove some assumptions commonly held in the MRO field, such as that heavy gases disperse along ground level. Correspondingly, ground-level gas distributions were rarely useful for localizing the gas source and elevated measurements were much more informative. We make the dataset and the code publicly available to enable the community to develop, validate, and compare new approaches related to gas sensing in complex environments.
  • ... Crab behaviour in separate trials was recorded using GoPro V R Hero 4 cameras ($5 h footage). To minimize alterations in behaviour associated with bright light (Weissburg and Zimmer-Faust, 1994) these cameras were fitted with lenses without infrared filtration and infrared illuminators (Extreme CCTV Moonlight-IR) provided illumination. ...
    A unique strain of the red alga Irish moss (Chondrus crispus) is found solely amongst clumps of blue mussels (Mytilus edulis) in a coastal lagoon in Atlantic Canada. Since about 2000, its bed area has shrunk by >99.9%, coinciding with the arrival of the non-indigenous green crab (Carcinus maenas). This study tested two mechanisms by which green crabs may harm the Irish moss. The hypothesis that green crabs directly consume the alga was tested by exposing fronds and clumps to crabs. Crab interaction with the clumps caused limited fragmentation, consumption was very small, and the condition (visible grazing damage) of fronds did not change significantly. A second hypothesis, that during predation and handling of mussels green crabs indirectly displace the seaweed and remove its attachment substrate, was addressed by placing crabs with Irish moss-mussel clumps containing either large or small mussels. Green crabs removed and ate up to 100% of the small mussels but did not consume or displace large mussels. This study concludes that direct consumption is not a plausible mechanism for green crabs to harm this strain. Instead, green crabs harm could be mediated by mussels, whose removal deprives the giant Irish moss of positional stability.
  • ... Turbidity can alter predation success by reducing the distance and angle at which visual predators like cormorants can detect prey ( Figure 1A; Strod et al., 2008). Hydrodynamics can influence the availability of predator cues and thus information about predation risk (Weissburg and Zimmer-Faust, 1994;Smee and Weissburg, 2006;Large et al., 2011). Altered water chemistry associated with future ocean acidification can impair the ability of snails and larval fish to respond to predator cues, which makes them exhibit riskier behavior and, in turn, increases mortality rates (Munday et al., 2010;Jellison et al., 2016). ...
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    Human-caused environmental change will have significant non-lethal and indirect impacts on organisms due to altered sensory pathways, with consequences for ecological interactions. While a growing body of work addresses how global ocean change can impair the way organisms obtain and use information to direct their behavior, these efforts have typically focused on one step of the pathway (e.g., reception of a cue/signal), one sensory modality (e.g., visual), or one environmental factor (e.g., temperature). An integrated view of how aspects of environmental change will impact multiple sensory pathways and related ecological processes is needed to better anticipate broader consequences for marine ecosystems. Here, we present a conceptual synthesis of effects of global change on marine sensory ecology, based on a literature review. Our review supports several predictions for how particular sensory pathway steps – production, transmission, and reception/processing of cues/signals – are affected by environmental change. First, the production and reception/processing of multiple modalities of cues/signals are vulnerable to multiple global change stressors, indicating that there are generalizable mechanisms by which environmental change impairs these pathways steps, leading to altered sensory pathway outcomes. Factors that enhance organismal stress as a whole may amplify impacts to these sensory pathways. Second, global change factors tend to affect specific modalities of cue/signal transmission. Consequently, local impacts on ecological processes linked with cue/signal transmission will vary depending on environmental stressor(s) present and the corresponding sensory modality. Finally, because many ecological and evolutionary interactions rely on sensory processing, impairment of sensory pathways may frequently underpin impacts of global ocean change on marine ecosystems. Effects on individual sensory processes will integrate to shape processes like mating, predation, and habitat selection, and we highlight new insights on impacts to ecological interactions by employing our mechanistic conceptual framework.
  • ... Environmental context affects predator-prey dynamics by modulating the ability of predator and prey to detect one another. For example, in marine systems the fluid environmental context (e.g., bulk flow and turbulence) can reduce consumptive effects by interfering with the ability of predators to find prey using chemical signals (Weissburg and Zimmerfaust, 1994). Fluid motion also can increase non-consumptive effects by enhancing the ability of prey to remotely detect predators via predator scent (Leonard et al., 1998;Shears et al., 2008;Smee et al., 2010;Pruett and Weissburg, 2018). ...
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    Ecosystems are shaped by complex interactions between species and their environment. However, humans are rapidly changing the environment through increased carbon dioxide (CO2) emissions, creating global warming and elevated CO2 levels that affect ecological communities through multiple processes. Understanding community responses to climate change requires examining the consequences of changing behavioral interactions between species, such as those affecting predator and prey. Understanding the underlying sensory process that govern these interactions and how they may be affected by climate change provides a predictive framework, but many studies examine behavioral outcomes only. This review summarizes the current knowledge of global warming and elevated CO2 impacts on predator-prey interactions with respect to the relevant aspects of sensory ecology, and we discuss the potential consequences of these effects. Our specific questions concern how climate change affects the ability of predators and prey to collect information and how this affects predator-prey interactions. We develop a framework for understanding how warming and elevated CO2 can alter behavioral interactions by examining how the processes (steps) of sensory cue (or signal) production, transmission and reception may change. This includes both direct effects on cue production and reception resulting from changes in organismal physiology, but also effects on cue transmission resulting from modulation of the physical environment via physical and biotic changes. We suggest that some modalities may be particularly prone to disruption, and that aquatic environments may suffer more serious disruptions as a result of elevated CO2 and warming that collectively affect all steps of the signaling process. Temperature by itself may primarily operate on aspects of cue generation and transmission, implying that sensory-mediated disruptions in terrestrial environments may be less severe. However, significant biases in the literature in terms of modalities (chemosensation), taxa (fish), and stressors (elevated CO2) examined currently prevents accurate generalizations. Significant issues such as multimodal compensation and altered transmission or other environmental effects remain largely unaddressed. Future studies should strive to fill these knowledge gaps in order to better understand and predict shifts in predator-prey interactions in a changing climate.
  • ... Certainly, prolonged exposure of predators to C. gigas as an available prey source may alter these predation patterns, however we show that biotic resistance to initial invasions is unlikely. Chemical cues are understood to play several roles in predator-prey dynamics (Weissburg and Zimmer-Faust, 1994;Leonard et al., 1999;Griffiths and Richardson, 2006) and are commonplace in the aquatic environment. Invasive alien species have been shown to produce chemical cues which may facilitate their invasion by inducing behavioural displacement of native species (Raw et al., 2013). ...
    Full-text available
    Invasive alien species continue to proliferate and cause severe ecological impacts. Functional responses (FRs) have shown excellent utility in predicting invasive predator success, however, their use in predicting invasive prey success is limited. Here, we assessed invader success by quantifying FRs and prey switching patterns of two native predators, the common sea star, Asterias rubens, and the green crab, Carcinus maenas, towards native blue mussels, Mytilus edulis, and invasive Pacific oysters, Crassostrea gigas. Asterias displayed destabilising type II FRs, whereas Carcinus displayed stabilising type III FRs towards both prey species. Both predators exhibited greater search efficiencies and maximum feeding rates towards native compared to invasive prey. Both predators disproportionately consumed native mussels over invasive oysters when presented simultaneously, even when native mussels were rare in the environment, therefore indicating negligible prey switching. We demonstrate that invasion success may be mediated through differential levels of biotic resistance exerted by native predators.
  • Presentation
    Full-text available
    Keynote Speech Title:� Plume Tracking Missions And Obstacles In Robotic World
  • Chapter
    This chapter addresses the key issues of chemical plume mapping and tracing via swarm robots. First, the authors present the models of turbulent odor plumes with both non-buoyant and buoyant features, which can efficiently evaluate strategies for tracing plumes, identifying their sources in two or three-dimensions. Second, the authors use the Monte Carlo technique to optimize moth-inspired plume tracing via swarm robots under formation control, which includes a leader to perform plume tracing maneuvers and non-leaders to follow the leader during plume tracing missions. Third, the authors introduce a variety of robot-based plume tracers, including ground-based robots, autonomous underwater vehicles, or unmanned aerial vehicles. Finally, the authors prospect the further research in this area, e.g., applying swarm robots to detect oil or gas leak, or to investigate subsea chemical pollution and greenhouse gases.
  • Chapter
    Previous chapters in this volume have considered the molecular nature and distribution of chemical signals in aquatic environments (Chap. 1), the behavior of aquatic invertebrates associated with stimulus acquisition (Chap. 2), and the structure (Chap. 11) and functional organization of chemoreceptors in aquatic invertebrates (Chap. 14). The present chapter continues this logical progression from stimulus to response by considering the fate of the information the chemoreceptor cells of aquatic invertebrates send to the CNS. This is a bittersweet topic, in that our understanding of chemosensory processing in invertebrates is just beginning, even though numerous species of invertebrates have served as important animal models in neurobiology and their motor organization is well understood. In fact, the best-characterized motor networks typically underlie behaviors such as feeding that are naturally triggered by chemical stimuli. Understanding chemosensory processing in these organisms would be a major step towards deciphering the “black box” in which sensory input is coupled to motor output, and ultimately to behavior.
  • Chapter
    The sensory capabilities of any animal are determined by a sequential set of physical and biological filters that regulate which environmental disturbances will stimulate the receptive surface of the animal. The environment itself is the first filter as it transmits physical or chemical disturbances from one or another source. The animal’s sense organs contain additional physical filters that select—each with its own degree of specificity—which part of the disturbances will have best access to the receptor membrane. Subsequent filtering occurs at the level of receptor cells and at each next level of the CNS. Environmental disturbances that alter the activity of receptor cells are called stimuli: they include disturbances that trigger molecular mechanisms, such as adaptation in the cell without necessarily causing it to fire nerve impulses or other means of information coding. Subsequent interneuronal steps of information processing are all based on neural signals that code certain aspects of the original stimuli.
  • Article
    The transfer of chemical information from an emitting to a receiving organism can occur directly by way of contact chemoreception or by dispersion through a transport medium. In this chapter we focus on transport of odor signals in the air. The various mathematical models discussed here have been used to describe the dispersion of pheromones in still air (Bossert and Wilson, 1963; Mankin et al., 1980a) or moving air (Wright, 1958; Bossert and Wilson, 1963; Aylor et al., 1976; Miksad and Kittredge, 1979; Fares et al., 1980). They can be applied to the dispersion of any airborne odor such as plant volatiles inducing host finding. An understanding of odor dispersion is requisite for an accurate interpretation of odor-induced behaviors. (See Bell, Chapter 4, and Cardé, Chapter 5).
  • Article
    Predatory muricid gastropods,Urosalpinx cinerea, respond to specific chemical stimuli by creeping upcurrent. Attractant substances originate from living barnacles. Newly hatched snails have no prior predatory experience but respond strongly to attractants. We report here methods for rapidly extracting and desalting attractants from seawater. Attractants from living barnacles are relatively large, at least partially proteinaceous, heat-stable molecules (> 1000 but < 10000 dallons) that adsorb onto Amberlite XAD-7, a polyacrylate water purification resin, at neutral pH. Attractants remain adsorbed to the resin during a wash with deionized water and can be eluted in a small volume with 100% methanol. Attractant substances are effective in the bioassay in μg/liter concentrations (octa- to nanomolar range). Potency is destroyed by nonspecific proteases (carboxy-peptidase and pronase) but not by trypsin. Attractant is not sequestered within barnacles.