10.5061/DRYAD.TTDZ08KW6
Velilla, Estefania
0000-0002-7678-2390
Vrije Universiteit Amsterdam
Polajnar, Jernej
0000-0002-4212-0567
National Institute of Biology
Virant-Doberlet, Meta
National Institute of Biology
Commandeur, Daniel
Vrije Universiteit Amsterdam
Simon, Ralph
Vrije Universiteit Amsterdam
Ellers, Jacintha
Vrije Universiteit Amsterdam
Halfwerk, Wouter
Vrije Universiteit Amsterdam
Variation in plant leaf traits affects transmission and detectability of
herbivore vibrational cues
Dryad
dataset
2020
FOS: Biological sciences
Spodoptera exigua
Helianthus annuus
Zea mays
Beta vulgaris
Brassica oleracea var. capitata
laser vibrometry
playback experiment
vibrational signals
Slovenian Research Agency
https://ror.org/059bp8k51
Research core funding No. P1-0255, project No. J1-8142
2021-09-11T00:00:00Z
2021-09-11T00:00:00Z
en
451996 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Many insects use plant-borne vibrations to obtain important information
about their environment, such as where to find a mate or a prey, or when
to avoid a predator. Plant species can differ in the way they vibrate,
possibly affecting the reliability of information, and ultimately the
decisions that are made by animals based on this information. We examined
whether the production, transmission and possible perception of
plant-borne vibrational cues is affected by variation in leaf traits. We
recorded vibrations of 69 Spodoptera exigua caterpillars foraging on four
plant species that differed widely in their leaf-traits (cabbage,
beetroot, sunflower and corn). We carried out a transmission and an
airborne noise absorption experiment to assess whether leaf traits
influence amplitude and frequency characteristics, and background noise
levels of vibrational-chewing cues. Our results reveal that
species-specific leaf traits can influence transmission and potentially
perception of herbivore-induced chewing vibrations. Experimentally-induced
vibrations attenuated stronger on plants with thicker leaves. Amplitude
and frequency characteristics of chewing vibrations measured near a
chewing caterpillar were, however, not affected by leaf traits.
Furthermore, we found a significant effect of leaf area, water content and
leaf thickness - important plant traits against herbivory, on the
vibrations induced by airborne noise. On larger leaves higher amplitude
vibrations were induced, whereas on thicker leaves containing more water
airborne noise induced higher peak frequencies. Our findings indicate that
variation in leaf traits can be important for the transmission and
possibly detection of vibrational cues.
Animal rearing The beet armyworm S. exigua (Hübner; Lepidoptera,
Noctuidae) is a polyphagous insect pest with a worldwide distribution, and
is considered a serious pest of vegetables, field, and flower crops. S.
exigua was reared at 26°C ± 1°C and 80% relative humidity on a 12:12 h
(L:D) photoperiod. Larvae were fed with a corn-based artificial diet, and
adults were given 10% sucrose solution. Mating was facilitated by placing
a male and a female moth in a plastic round container with a mesh cloth
sealing the top. The mesh cloth was used as a surface on which eggs were
laid. Eggs were collected by removing the cloth and cutting and placing
the sections of the cloth containing eggs on diet-filled petri dishes. As
eggs hatched, larvae developed on these diet-filled petri dishes. The life
cycle of S. exigua under our rearing conditions was completed between
25-30 days and included 5 instars. Each instar transition took between
three and five days. Plant rearing and measuring of plant leaf traits Four
plant species were used for this experiment: sunflower H. annuus, cabbage
B.oleracea var. Capitata, beetroot B. vulgaris, and corn Z. mays. Seeds
were bought from commercial companies: Seedo and 123Zaden. Plants were
reared in growing chambers at 20˚C - 25˚C with an 8:16 h (L:D) photoperiod
and with 70% relative humidity. Quartz sand was used instead of potting
soil to control for any variation in soil quality that could influence
plant traits. A fixed amount of 50% Hoagland’s solution was provided every
second day. The amount changed gradually with the growth of the plants
(~10-100ml). Plants that were between six- and eight-weeks post
germination were used in the experiments. We measured four leaf traits in
the lab: Leaf area (cm2), leaf mass (g), leaf thickness (mm), and punch
force (N) following the handbook for standardized measurement of plant
functional traits (Pérez-Harguindeguy et al., 2013). Leaf area was
measured by scanning the leaves, and subsequently measuring the area with
the program ImageJ. The dry weight was calculated by first drying the
harvested leaves for at least 48 hours in a 70 °C oven, and then weighing
them. Dry weight and leaf area were used to calculate the specific leaf
area SLA (cm2/g) (one-sided area of a fresh leaf, divided by its dry
weight). Leaf thickness was measured with a manual calliper on nine
locations on the leaf, seven for corn (Fig. 1). Punch force was measured
as the maximum (i.e. pulse) force needed for a 1 mm diameter blunt needle
to puncture the leaf, which was clamped tightly on either side of the
puncturing spot using a Mecmesin Ultratest Newton meter with Force Gauge
AFG 1000-N (Mecmesin, Broadbridge UK). These measurements were done on the
same nine locations within eudicot leaves and in, the same seven locations
for corn. The measuring points one, two, and three covered the main vein,
and the points four, five, six, seven, eight, nine the soft tissue (Fig.
1). The fresh weight and dry weight were used to calculate the fresh
weight to dry weight ratio, which we interpreted as the water content. We
measured leaf traits of two sets of plants. The first set (n= 101)
consisted of plants paired up with the plants used in the recordings of
caterpillar chewing vibrations (chewing experiment). This paired design
allowed us to measure leaf traits in plants undamaged by chewing while
being representative of the leaf traits of chewed plants, but relied on
the assumption that paired plants used to measure traits represent the
leaf trait variation of the plants on which chewing measurements were
done. Although this assumption may not have been met for all pairs, it
still seems reasonable compared to the alternative design which would
involve measuring leaf traits and vibrations on the same leaf, given that
chewing behaviour could be affected by prior measuring of the traits (e.g.
damage by punch force tests could have elicited secondary metabolites),
and trait measurement could have been affected by foraging (e.g. loss of
mass or strength after herbivory attack). The second set of plants (n=40)
corresponds to the transmission experiment, described in a section below.
In this case, there was no confounding effect of herbivory, and we
therefore used the same plants to measure vibrations and leaf traits.
Recordings of caterpillar chewing vibrations The purpose of these
recordings was to investigate the effect of variation in leaf traits on
the production of caterpillar chewing vibrational cues. We first made
recordings of caterpillars chewing on different plant species and we then
related the amplitude and frequency characteristics of those recordings to
variation in leaf traits. A custom-built wooden box (90cm x 60 cm x 60 cm)
with a Plexiglas top was used to reduce airborne noise during recording of
the chewing vibrations. The box was lined with noise absorbing foam and
was placed on a vibration reduction marble table with passive suspenders
to minimize substrate-borne noise of the building. The airborne noise
amplitude inside the box at the location of the plant, was approximately
35 dB (A) measured with an Extech SDL600 sound level meter set to (set to
fast and max). Caterpillar chewing was recorded using a Laser-Doppler
Vibrometer (LDV; Polytec PDV-100, set to 5 or 20 mm/s/V, sampling rate 22
kHz). The output of the laser was acquired using a TASCAM DR-60D MKII
audio recorder (44,1 kHz, 16-bit resolution). The recording level of the
Tascam was set so that there would not be overload of the signal. A
reference signal using the same recording level was made against the
vibration-isolation table after each recording to allow calculation of
absolute amplitude. A reference signal can be made by generating a
sinusoidal test signal of 2.80 V (RMS) with a frequency of approximately 1
kHz by setting the laser service mode to Output = Full (Polytec PDV-100
user manual, section 5). We recorded this test signal on the table on
which we placed our plants with caterpillars and we recorded it with the
TASCAM with the exact same recording settings used per recording of
caterpillar chewing vibrations. A single plant was placed inside the
noise-isolation box, and a free-moving caterpillar was placed on a leaf of
the plant. The caterpillar was always dropped on the middle of the leaf,
but it foraged freely and therefore the foraging position changed per
trial. A piece of reflective tape placed central on the measuring side of
the leaf was used to enhance reflection of the laser beam. Recordings
started always around the same time of day (~13:00). A recording started
when a caterpillar started eating, and the recording lasted 30 seconds.
The distance from feeding site to the measurement site (reflective tape)
was noted. The distances ranged from 0.50 to 33.3 mm, with a mean ± sd
distance of 12 ± 8.7 mm. Individual plants and caterpillars were used only
once for each recording. Recordings were done throughout three larval
stages of the animals (L2-L4/5). Before the recordings, caterpillars were
weighed and allowed to acclimatize to the experimental chamber. We had 19
replicates for cabbage, 24 for beetroot, 18 for sunflower, and 16 for
corn. However, eight recordings were too low in amplitude and the chewing
vibrations were not distinguishable from the background noise levels.
Therefore, our total sample size was reduced to 69 caterpillar – plant
combinations. Transmission experiment To test which leaf-traits affected
the transmission of caterpillar chewing cues among plant species, we
conducted a vibrational playback experiment. The purpose of this
experiment was to measure the transmission of a synthetic vibratory signal
throughout the leaves of the different plant species we used during the
chewing vibrations recordings. We then related these transmission
measurements to the different leaf traits. Using a Brüel & Kjær
mini-shaker Type 4810, we played back a two-minute frequency sweep
starting at 20 Hz and ending at 2 kHz. The playback was corrected for the
frequency response of the shaker to ensure constant velocity at all
frequencies, and adjusted to the RMS amplitude level of chewing vibrations
recorded in caterpillar trials. This adjustment was necessary because the
frequency response of the mini shaker is highly non-linear in the low
frequencies (< 100 Hz), biasing the playback to the frequencies
> 100 Hz in a non-corrected format. Therefore, by correcting our
playback file to the frequency response of the shaker, we made sure all
frequencies were equally represented. We used two LDVs, one to register
vibrations next to the source (Fig. 1) and the other on the nine different
points on the leaf, seven for corn (Fig. 1). These points were the same
points that were used for measuring leaf thickness and punch force (Fig.
1). Furthermore, we recorded the sweep on the adjacent leaf to test
relative energy loss during transmission. Vibrations were transferred via
a rod mounted on the shaker and attached with Blue Tack adhesive to the
underside of the leaf on a point in the centre of the soft tissue, not
touching the main vein, between points five and eight (Fig. 1). The
distance between each point and the stimulus was noted. The distances
ranged from 1 to 20 mm. We tested five plants per species.
Airborne-noise exposure experiment To test whether amplitude of vibrations
induced by airborne noise was affected by leaf traits, we did an acoustic
noise playback experiment with white noise (0.1 – 20kHz) (Rebar et al.
2012). Using a Behringer MPA40BT speaker positioned 60 cm from the plant,
we played back 10 seconds of white noise at 70 dB (A) measured at the
position of the leaf with an Extech SDL600 sound level meter (set to fast
and max) and recorded with the LDV on three points (points 1:3, Fig. 1).
Using an LDV we recorded the vibrations induced by the airborne noise
playback. We tested five plants per species. Analysis of vibratory
measurements Chewing recordings were first filtered with a 100 Hz high
pass filter in R version 3.3.1 (R Core Team 2016), run in the RStudio
interface (RStudio Team 2015) with the function “fir” from the Seewave
package version 2.1.4 (Sueur, 2008). Recordings were filtered to remove
high amplitude, low-frequency background building noise. Using Raven Pro
1.5 software (Cornell Lab of Ornithology 2017), we selected ten chewing
events per recording (see Fig. A1 in Appendix 1 for an example). We
measured root mean square (RMS) amplitude from the waveform, and first and
third quartiles. Peak frequency was taken from the spectrum (sampling
frequency: 44100, window type: “Hanning”, window size: 1024, overlap: 50).
All measurements were done on the filtered recordings. Reference
recordings were filtered in the same way as chewing recordings. RMS
measurements from the reference recordings were used to calculate absolute
RMS amplitude (mm/s) of chewing events. To calculate absolute RMS
amplitude, we used the following formula: RMS amp (mms)=
RMSmeasurementRMS(reference)*2.80*LDV vel scaling setting The value of
2.80 represents the RMS amplitude (in Volts) output of the LDV, and the
LDV velocity scaling setting was either 5 or 20 mm/s/V (Polytec PDV-100
user manual, section 5). Analysis of vibratory sweep and acoustic noise
playbacks The sweep recordings were high-pass filtered in the same way as
the chewing recordings. The main frequency range of chewing recordings was
determined by plotting frequency spectrum of a representative recording
per plant species (Fig. 2). We determined RMS amplitude of reference
recordings in Raven Pro, which were made for every recorded point,
including the ones on the adjacent leaves. Attenuation (dB) was calculated
for every measurement point of every individual plant using the following
formula: 20Log10=RMS(measurement)RMS(reference) We also calculated peak
frequency from the spectrum (sampling frequency: 44100, window type:
“Hanning”, window size: 1024, overlap: 50). Because we did not measure
transmission on the stem, we decided to use the midvein points and the
adjacent leaf as a proxy for transmission. Hence, our statistical analyses
not only explore differences in the average amplitude change (dB) and mean
peak frequency (Hz) measurements across all points on the same leaf, but
also of the midvein points, as well as transmission via the stem to the
nearest leaf. Noise recordings were also high-pass filtered and RMS
amplitude (dB) and peak frequency (Hz) measurements obtained with Raven
Pro. All recordings were normalized in R by dividing them by the maximum
amplitude of the loudest recording.
In the dataset called "plant.traits_transmission
experiment_2017" (Excel file) used during the transmission
experiment, the variables LT1, LT2...LT9 (leaf thickness) are expressed in
a different unit than in the datasets from the caterpillar chewing
experiments, called "plant.traits" and
"plant.traits.complete". In those datasets leaf thickness is
expressed in mm. Therefore, in the R script
"transmission.experiment", I divide the leaf trait values by 100
to convert leaf thickness to mm. In the dataset "PT_whole"
(Excel file), the variables "dry.weight" and
"fresh.weight" are also in the wrong units (mg). Therefore, in
the R script "substrate_effects_on_chewing_cues" I divide them
by 1000 to properly calculate water content and SLA. The dataset
"plant.traits.complete" (Excel file) contains the corrected
units of measurement for all variables.