Quantitative analysis of individual trajectories in
moving flocks of fiddler crabs
Bianca S. Smith, Keiyana Hamlet, Anissa Kennedy, and Steven V. Viscido
Department of Life Sciences, Winston-Salem State University, Winston-Salem, NC, USA
INTRODUCTION
• Social aggregation is very common in the animal
world (Parrish and Edesltein-Keshet 1999).
(a) Parallel orientation
(b) Sharp edges
METHODS
RESULTS
Video capture
• The NGDR distribution changed significantly (Kruskal-Wallis Test, df=2, P < 0.001) throughout
the tidal cycle (Figure 6).
• We filmed fiddler crab flocks for 5-10 min periods throughout the
tidal cycle using Sony HDR-40 high-definition video cameras.
• Groups provide many benefits for members, such
as defense against predation and improved foraging
success.
• In the lab, video was converted to *.avi format and saved to the
computer’s hard drive.
• Groups display many complex, emergent properties
(Figure 1).
(c) Coordination
• These properties are not programmed; they arise
from combined individual interactions (Couzin et al.
2002).
• Videos were examined for lighting, camera shake, water
movement, and other confounding factors.
(d) Dense packing
• Five 15-second clips of video judged most amenable to motion
analysis were selected for each tidal period (FT, SLT, and RT).
• The velocity distribution did not change significantly (Kruskal-Wallis Test, df=2, P > 0.5) during
the tidal cycle (Figure 7).
• We rejected the null hypothesis that the mean ranks of NGDR and samples were the same.
• Therefore, we accepted the alternative hypothesis that NGDR depends on the tidal cycle.
• For velocity, the null hypothesis could not be rejected.
• Environmental factors can affect individual
movements, and can therefore alter group
behaviors (Krause 1993).
Figure 1: Examples of emergent group
properties: (a) parallel orientation, (b) sharp
edges, (c) coordination, and (d) dense
packing. Photos courtesy of Dr. Julia K.
Parrish.
• Goal: To test whether environmental factors such
as tidal periods can alter individual movement of
group members, and therefore can alter emergent
properties.
Calibration
• White golf balls glued to golf tees were sunk into the mud at
known positions in the shape of a 38-cm regular octagon.
• Ball position allowed us to calibrate the video and correct for
parallax distortion.
38 cm
• In the lab, a single frame of each video was captured, and the
motion analyst used a mouse cursor to click on the center of
each golf ball.
STUDY SITE AND ANIMAL
• The tidal cycle is a major factor in the lives of
intertidal marine animals.
• The tracking software (TrackerEF) used this information to
convert all video pixel coordinates to real-world two-dimensional
distances (in cm).
• We traveled to North Inlet, SC, to study the impact of
the tidal cycle on social marine invertebrates who live
in the intertidal zone (Figure 2).
• Our model organisms were sand fiddler crabs (Uca
pugilator), animals that form feeding aggregations
(Figure 3).
Figure 2: An overview of the
salt marsh and tidal creeks in
North Inlet, SC.
Background Subtraction
• These animals hide from the water during tidal
inundations, and are inactive at high tide.
• We used a modified version of the program Avidemux to
subtract the stationary background from the image.
• During low tides, the crabs emerge from their
burrows, form groups, and travel several meters to
the creek bottom to find food.
• Predators frequently attack during low tide, and food
is patchy, so groups improve both predation defense
and foraging success (Viscido and Wethey 2002).
• The video image was then thresholded to distinguish
crabs (white) from the background (black).
• A computer algorithm then located the centroid of each
individual.
Figure 3: A small group of
fiddler crabs feeding on the
muddy marsh bottom.
• The centroid positions were recorded to a data file.
HYPOTHESIS AND PREDICTIONS
• Because the tidal cycle is such a strong factor in
the lives of these crabs, their individual and
group behavior may be governed by it.
Automated Detection
• The overall hypothesis: movements of flock
members are governed, at least in part, by the
tidal cycle.
Figure 6: Frequency distributions of NGDR
during the falling tide (top), slack low tide
(middle), and rising tide (bottom). NGDR=1 for
straight paths and 0 for maximally curvy paths
(see Figure 5). NGDR was calculated along the
entire trajectory for each crab.
• The computer automatically “connected the
dots” through time to generate paths.
• We predicted that crab movements would
change as the tide went out (“falling tide”),
during slack low tide, and as the tide returned
(“rising tide,” Figure 4).
(A) POOR PATH DETECTION
• We defined tidal periods as follows:
• TrackerEF reported the total number of
crabs detected (red line) and the number
matched to a path (green line).
• Tracking parameters could result in either
poor (A) or good (B) path detection.
• Slack Low Tide: the 1 h period bracketing
the predicted low tide.
• Falling Tide: 30 - 90 min before predicted
low tide.
Figure 4: Graphical depiction of a 24-hour tidal
cycle at North Inlet from June 2010. Low tide
occurs every 12 h, 50 min. The water recedes
during the “falling tide” and returns during the
“rising tide.” Peak flock behavior occurs at slack
low tide. Tide data courtesy of N.O.A.A.
• Rising Tide: 30 - 90 minutes after
predicted low tide.
• The individual behaviors measured were
Velocity and path straightness (as estimated
NGDR, Figure 5).
(B) GOOD PATH DETECTION
• We adjusted parameters until the computer
was able to resolve most points into a good
path detection (B).
Path Reconstruction
B
Figure 5: How Net:Gross Displacement
Ratio (NGDR) is calculated. Net
displacement is the straight-line distance
between point A and B. Gross displacement
is the sum of all line segment lengths
between points A and B. The straighter a
path is, the closer NGDR is to 1.
• We then used the TrackerEF path editor to visualize
trajectories and manually correct errors.
A
ACKNOWLEDGMENTS
We thank the many individuals who assisted in the completion of this project. Crabs were filmed
at the University of South Carolina’s Belle W. Baruch Marine Field Station. Amanda Lee, Tiarra
Ogletree, Angel Watson, Asha Barnes, Bridgette Parks, and Dana Collins assisted with motion
analysis . Hawanatu Savage filmed crab behavior. Danny Grünbaum of the University of
Washington provided the original tracking code (Tracker3D) from which TrackerEF was
developed. Funding was provided by NSF grant IOS-1149302 to Dr. Steven Viscido.
Smoothing Spline
Figure 7: Frequency distributions of velocity in
cm/s during the falling tide (top), slack low tide
(middle), and rising tide (bottom). Velocity was
calculated as the mean speed along the entire
trajectory for each crab.
CONCLUSIONS
•
Our main finding is that environmental factors can affect the behaviors of individual
group members.
•
For flocking fiddler crabs, path straightness (as measured by NGDR) changed in response to the
tidal cycle, the most important environmental factor in their habitat (Figure 6).
• Trajectories were much straighter on the falling and slack tide than during the rising tide
(Figure 6).
•
However, the distribution of individual velocities did not appear to be affected by the tidal cycle
(Figure 7). Crabs moved at about the same speed throughout the tidal period.
•
Therefore, although the tidal cycle is an important contributing factor to individual crab
behaviors, not all behaviors responded equally to this environmental factor.
•
Because individual movements control group characteristics such as shape and density, we
predict that the environment will also affect these characteristics.
•
Our study demonstrates the importance environmental factors in determining animal group
behavior, but also demonstrates that different aspects of behavior may respond unequally to
external stimuli.
REFERENCES
• After we corrected errors, we applied a smoothing spline
to the data to remove video artifacts.
• Couzin, I. D., Krause, J., James, R., Ruxton, G. D., and Franks, N. R. 2002. Collective
memory and spatial sorting in animal groups. Journal of Theoretical Biology 218:1-11
• We tested individual velocity and NGDR distributions in
the three tidal periods against the null hypothesis that
mean ranks of samples were the same using a KruskalWallis test (Sokal and Rohlf, 1995).
• Krause, J. 1993. The effect of 'schreckstoff' on the shoaling behavior of the minnow: a
test of hamilton's selfish herd theory. Animal Behaviour 45:1019-1024.
• Parrish, J. K. and Edelstein-Keshet, L. 1999. Complexity, pattern, and evolutionary tradeoffs in animal aggregation. Science 284:99-101.
• Sokal, R. R. and Rohlf, J. F. 1995. Biometry, 3rd edition. W. H. Freeman.
• Viscido, S. V. and Wethey, D. S. 2002. Quantitative analysis of fiddler crab flock
movement: evidence for "selfish herd" behaivour. Animal Behaviour 63:735-741.