10.5061/DRYAD.R2280GB8J
Molleman, Freerk
0000-0002-6551-266X
Adam Mickiewicz University in Poznań
Javoiš, Juhan
University of Tartu
Davis, Robert
University of Tartu
Whitaker, Melissa
Harvard University
Tammaru, Toomas
University of Tartu
Prinzing, Andreas
University of Rennes 1
Õunap, Erki
University of Tartu
Wahlberg, Niklas
Lund University
Kodandaramaiah, Ullasa
Indian Institute of Science Education and Research, Thiruvananthapuram
Aduse-Poku, Kwaku
University of Richmond
Kaasik, Ants
University of Tartu
Carey, James
University of California, Davis
Quantifying the effects of species traits on predation risk in nature: a
comparative study of butterfly wing damage
Dryad
dataset
2020
crypsis
flight speed
symmetrical damage
restricted maximum likelihood
capture mark recapture
butterfly
National Institute on Aging
https://ror.org/049v75w11
PO1 AG022500-01
National Institute on Aging
https://ror.org/049v75w11
PO1 AG608761-10
Bixby International Travel Grant
National Science Foundation
https://ror.org/021nxhr62
1309425
Estonian Science Foundation
9215
Estonian Science Foundation
IUT20-33
European Commission
https://ror.org/00k4n6c32
FIBIR
Regional Council of Brittany
https://ror.org/05510z802
SAD
Regional Council of Brittany
https://ror.org/05510z802
ACOMB
French National Centre for Scientific Research
https://ror.org/02feahw73
ATIP
French National Centre for Scientific Research
https://ror.org/02feahw73
ATIP
Department of Science and Technology, Government of India
DST/INSPIRE/04/2013/000476
2020-10-31T00:00:00Z
2020-10-31T00:00:00Z
en
2050583 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1) Evading predators is a fundamental aspect of the ecology and evolution
of all prey animals. In studying the influence of prey traits on predation
risk, previous researchers have shown that crypsis reduces attack rates on
resting prey, predation risk increases with increased prey activity, and
rapid locomotion reduces attack rates and increases chances of surviving
predator attacks. However, evidence for these conclusions is nearly always
based on observations of selected species under artificial conditions. In
nature, it remains unclear how defensive traits such as crypsis, activity
levels, and speed influence realized predation risk across species in a
community. Whereas direct observations of predator-prey interactions in
nature are rare, insight can be gained by quantifying bodily damage caused
by failed predator attacks. 2) We quantified how butterfly species traits
affect predation risk in nature by determining how defensive traits
correlate with wing damage caused by failed predation attempts, thereby
providing the first robust multi-species comparative analysis of
predator-induced bodily damage in wild animals. 3) For 34 species of
fruit-feeding butterflies in an African forest, we recorded wing damage
and quantified crypsis, activity levels, and flight speed. We then tested
for correlations between damage parameters and species traits using
comparative methods that account for measurement error. 4) We detected
considerable differences in the extent, location, and symmetry of wing
surface loss among species, with smaller differences between sexes. We
found that males (but not females) of species that flew faster had
substantially less wing surface loss. However, we found no correlation
between cryptic colouration and symmetrical wing surface loss across
species. In species in which males appeared to be more active than
females, males had a lower proportion of symmetrical wing surface loss
than females. 5) Our results provide evidence that activity greatly
influences the probability of attacks and that flying rapidly is effective
for escaping pursuing predators in the wild, but we did not find evidence
that cryptic species are less likely to be attacked while at rest.
15-Oct-2019
This study was conducted near the Makerere University Biological Field
Station in Kibale National Park, Western Uganda. Butterflies were captured
in fruit-baited traps in two areas with selectively logged sub-montane
tropical forest (Lowercamp and K31) and a forest regeneration site
(Mikana). We used 22 trap locations in Lowercamp (Molleman et al. 2006),
and 40 trap locations in the understory of forest compartment K31, and six
in the Mikana area. In K31, traps were baited once each a week from
January 2006 until February 2007, and butterflies were scored, marked, and
released on four consecutive days between 10:00 and 16:00, replacing bait
only when it was lost. In Lowercamp and Mikana, trapping was performed
once every 4 weeks from May 2006 to June 2012. Since the traps accumulated
butterflies over 24-hour time periods, any differences in diurnal activity
could not bias trap catches. In forest compartment K31, 34 species of
fruit-feeding butterflies were included to capture as much diversity in
terms of phylogeny and putative defensive tactics, as possible. In
Lowercamp and Mikana, we focused on three butterfly species: Euphaedra
medon (L.), E. alacris Hecq and Charaxes fulvescens Aurivillius in order
to obtain large sample sizes for selected species. We focused on medium to
large bodied species that are less likely damaged by handling. All
included species hold their wings closed over their back while at rest and
are thus expected to show symmetrical wing damage if they were attacked
while at rest, although the Adoliadini and Cymothoe species hold their
wings open during sun basking and can open their wings during feeding (FM
pers. sobs.). Scoring damage Focal species were carefully removed from
baited traps by hand. To avoid pseudo-replication, butterflies were marked
with a unique number before release. Most individuals were captured only
once (the proportion of captures that were recaptured is given in Table B3
and the frequency of recaptures in Table B4 of Appendix B). We visually
estimated the proportion of wing surface missing on each wing as well as
the percentage of scale loss of all wings taken together. Any entire
number could be noted, albeit obviously a difference of 1% would not be
interpretable. We compared estimates of wing surface loss with detailed
drawings of the wing surfaces of 538 of the included specimens and
corrected systematic biases accordingly (e.g. overestimation of minor
damage, underestimation of severe damage: Online Appendix B). We also
counted the number of tears (ripped wings without surface loss) in the
wings (Fig. 1). To gauge the realized repeatability of estimates of
butterfly wing damage in this study, we took data from individual
butterflies that were captured and recaptured at most one day apart
(estimates often made by different observers), and determined the
correlation between the two estimates of wing damage. Since the
butterflies could have incurred new wing damage during this one day, it is
likely that we slightly underestimate repeatability. Across 1100 instances
of individuals that were captured on two consecutive days, the correlation
coefficient of wing surface loss was 0.74 on average, wing tears 0.53 and
scale loss 0.98. We note that stronger correlation, i.e. reproducibility,
did not correspond to stronger statistical signal in the later tests of
our hypotheses (Tab. 1). We calculated the degree to which wing surface
loss was biased toward forewings as the damage to forewings minus that in
hindwings, divided by the total wing surface loss; such that this variable
had positive values when wing surface loss was biased towards forewings,
and negative values when biased towards hindwings. For each pair of wings,
we scored whether any of the surface missing was symmetrical (i.e. the
surface loss on left and right wings represented a mirror image of each
other). Even when some of the wing surface loss had a symmetrical shape
across wing pairs, the extent of wing surface loss of wings in a wing-pair
often differed between the two wings, because there was additional
non-symmetrical wing surface loss. We attempted to avoid damage due to
handling by focusing on species of large body size (forewing length over
2.8 cm.), and by working with local field assistants with several years of
experience in handling butterflies. Fingerprints on butterfly wings are
readily recognizable and were ignored when scoring butterflies. We noted
if a specimen was damaged during handling, and excluded any subsequent
recaptures of these individuals from the analyses. Wing length Forewing
measurements were made using callipers at the study site for the 34
species, represented by 12,271 live individuals that were not included in
the study of damage (separate data set). Flight speed Flight speed was
measured in a 3 m long tunnel. A house at the field station was darkened
except for one exterior door that was left open, and the doorframe was
covered with white mesh, providing a light target to butterflies.
Butterflies were taken from baited traps in the morning during a
four-month period, provided water and mashed banana and used during the
afternoon between 13:00 and 16:00 of the same day for flight speed
measurements. Therefore, the ambient temperature was roughly the same for
all trials, ranging between 20.5 and 25 ̊C. Butterflies were individually
released 1 m from the floor and 4 m from the open door, oriented towards
the open door. Butterfly flight away from a human experimenter is likely
escape behaviour, thus we presume that butterflies were displaying escape
flight tactics and were ostensibly maximizing their speed. The time they
took to reach the mesh covering the open door was recorded, and flights
that were not straight towards the target door were excluded from
analyses.