DOI: 10.5061/dryad.ttdz08kw6
title: Variation in plant leaf traits affects transmission and detectability of herbivore vibrational cues

description: 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.
description: Animal rearing The beet armyworm <i>S.
 exigua</i> (Hübner; Lepidoptera, Noctuidae) is a polyphagous insect
 pest with a worldwide distribution, and is considered a serious pest of
 vegetables, field, and flower crops. <i>S. exigua</i> 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 <i>S. exigua </i>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 <i>H.
 annuus</i>, cabbage <i>B.oleracea var. Capitata</i>,
 beetroot <i>B. vulgaris</i>, and corn <i>Z.
 mays</i>. 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
 (cm<sup>2</sup>), 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 (cm<sup>2</sup>/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 (&lt; 100 Hz), biasing the
 playback to the frequencies &gt; 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: <i>RMS</i><i>
 </i><i>amp</i><i>
 (</i><i>mm</i><i>s</i><i>)=
 </i><i>RMS</i><i>measurement</i><i>RMS</i><i>(</i><i>reference</i><i>)</i><i>*</i><i>2.80</i><i>*</i><i>LDV</i><i> </i><i>vel</i><i> </i><i>scaling</i><i> </i><i>setting</i> 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: <i><sub>20Log10</sub></i><sub>=</sub><i><sub>RMS(measurement)</sub></i><i><sub>RMS(reference)</sub></i> 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.
description: 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.