Vibration-guided mate searching in treehoppers ...Vibration-guided mate searching in treehoppers: directional accuracy and sampling strategies in a complex sensory environment Jeremy

RESEARCH ARTICLE

Vibration-guided mate searching in treehoppers directionalaccuracy and sampling strategies in a complex sensoryenvironmentJeremy S GibsonDagger and Reginald B Cocroft

ABSTRACTAnimal movement decisions involve an actionndashperception cycle inwhich sensory flow influences motor output Key aspects of theactionndashperception cycle involved in movement decisions can beidentified by integrating path information with measurement ofenvironmental cues We studied mate searching in insects forwhich the primary sensory cues are mechanical vibrations travelingthrough the tissues of living plants We mapped search paths of malethornbug treehoppers locating stationary females through anexchange of vibrational signals At each of the malesrsquo samplinglocations we used two-dimensional laser vibrometry to measurestem motion produced by female vibrational signals We relatedproperties of the vibrational signals to the malesrsquomovement directioninter-sample distance and accuracy Males experienced gradients insignal amplitude and in the whirling motion of the plant stem andthese gradients were influenced to varying degrees by sourcedistance and local stem properties Males changed their samplingbehavior during the search making longer inter-sample movementsfarther from the source where uncertainty is higher The primarydirectional cue used by searching males was the direction of wavepropagation and males made more accurate decisions when signalamplitude was higher when time delays were longer between thefront and back legs and when female responses were short induration The whirling motion of plant stems including both theeccentricity and the major axes of motion is a fundamental feature ofvibrational environments on living plants and we show for the firsttime that it has important influences on the decisions of vibrationallyhoming insects

KEY WORDS Movement ecology Directional sensing

INTRODUCTIONAlthough understanding the causes and consequences of animalmovement is a major goal of ecological research (Nathan et al2008 Sutherland et al 2013) for most species we lack anunderstanding of the perceptual cues used in movement decisionsMovement decisions involve an integrated process in which sensoryflow influences motor output which in turn determines the nature ofthe sensory flow (Hofmann et al 2013) This actionndashperceptioncycle and the ways in which it changes with context are well

understood for some organisms including echolocating bats(Ulanovsky and Moss 2008 Yovel et al 2010) odor-trackingmoths and fruit flies (Gaudry et al 2012 Murlis et al 1992)visually tracking insects (Srinivasan 2011) chemotactic micro-organisms (Berg 2000) and electroreceptive fish (Hofmann et al2013) For the majority of species for which the sensory system ispoorly known and movement decisions are not well understood keyinsights into the cues that predict movement decisions come fromcombining path information with measurements of environmentalvariables (eg Smolka et al 2011 Dodge et al 2013) Recentadvances including small sensors and global positioning systemtechnologies have made tracking some animals a much easier task(Kays et al 2015) These technologies allow researchers to not onlytrack movement paths for individuals in real time but also gatherother data streams simultaneously such as acceleration (Nathan et al2012 Resheff et al 2014 Spiegel et al 2017) environmentalfeatures (Kays et al 2015) and physiological states (Signer et al2010) With the continued miniaturization of these technologies alarger range of animals can be tracked but small animals such asinsects still pose tracking challenges In such cases directobservations can be especially powerful when the organismrsquosmovements and sampling behavior can be observed in sufficientdetail to reveal the points where reorientation decisions are made asthese are the key points at which to measure environmentalinformation (Gomez-Marin et al 2011 Smolka et al 2011) Herewe used this approach to understand movement decisions in anenvironment used by the majority of terrestrial animal species basedon one of the most widespread but least studied information streamsmechanical vibrations traveling through the tissues of living plants

Many of the social and ecological interactions within thearthropod community on plants depend on the production andperception of plant-borne vibrations These vibrations are used bysome 200000 insect species to communicate with mates mutualistsor group members (Cocroft and Rodriacuteguez 2005) and by manymore insects and other arthropods to locate prey or avoid predators(Barbosa and Castellanos 2005 Barth 1998 Casas and Magal2006) Plant-borne vibrations are also important in the social andecological interactions of some arboreal vertebrates (Barnett et al1999 Caldwell 2014 Christensen et al 2012 Warkentin 2005)

Many of the vibration-mediated interactions among plant-dwelling animals involve homing in on a vibration source(Cocroft and Rodriacuteguez 2005) Searches based on plant-bornevibrations are well suited for studying the actionndashperception cyclethat underlies movement decisions Searches usually occur overdistances of less than a meter (Virant-Doberlet and Cokl 2004) Inmany cases mechanical vibrations are the only available search cueand where other cues such as light are involved they can beexperimentally manipulated (Hunt and Nault 1991) Becausevibration-guided searches are typically based on intermittentReceived 28 November 2017 Accepted 16 January 2018

Division of Biological Sciences University of Missouri Columbia MO 65211 USAPresent address Department of Electronic and Electrical Engineering Universityof Strathclyde 99 George Street Glasgow G1 1RD UK

DaggerAuthor for correspondence ( jeremysgibsongmailcom)

JSG 0000-0002-5761-0710 RBC 0000-0002-6991-5757

1

copy 2018 Published by The Company of Biologists Ltd | Journal of Experimental Biology (2018) 221 jeb175083 doi101242jeb175083

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locomotion (Kramer and Mclaughlin 2001) with clearly definedsampling points (Legendre et al 2012) the key locations formeasuring vibrational cues can be identified The accuracy andefficiency of searching (and likewise the efficacy of signals Endler1992) can be quantified precisely because the available movementpaths are constrained by the structure of the plant and the targetlocation is known However although some likely cues for vibrationlocalization have been experimentally tested (reviewed in Hager andKirchner 2014 Virant-Doberlet et al 2006) some search pathsquantified (Legendre et al 2012) and some vibration gradientsexamined for their effect on male behavior (Polajnar et al 2014) nostudies have integrated entire search paths with measurement of theavailable vibrational cues at each sampling location to relate sensoryinput to motor outputWe studied movement decisions during mate searching in the

thornbug treehopper [Hemiptera Membracidae Umboniacrassicornis (Amyot amp Serville 1843)] Mate localization inthornbugs occurs through a back-and-forth exchange of plant-borne vibrational signals or duet between a searching male and astationary female Search efficiency is important for male matingsuccess thornbugs occur at high densities (Wood and Dowell1985) and female thornbugs mate only once with the first male toarrive during their narrow window of receptivity (Cocroft andMcNett 2006) Male movement decisions are one-dimensional(forward or back along a stem) and are based on identifiablesampling locations searching males walk along plant stemsperiodically stop to signal and elicit a female reply then continueforward or turn around Source localization through duetting thuscombines features of both echolocation and beacon-guided searchas with echolocation males obtain information about the target byproducing a signal however rather than relying on physicalreflections the lsquoreflectionrsquo is a signal produced by a stationaryreceiver Duetting is thus an active sensing strategy in which thesensory flow ndash transmitted signals from the source ndash is shaped by thepositions at which males decide to stop the number of signals theyproduce there and the signaling decisions of the femaleWe analyzed the movement decisions of male thornbugs in three

stages We first characterized their search paths asking howmovement decisions and accuracy changed over the course of thesearch We then investigated the vibrational cues correlated withmovement decisions and asked how variation in those cuesinfluenced sampling behavior and accuracy Finally we combinedthe information from all of the searches to obtain an overview of thevibrational gradients encountered by the searching insects

MATERIALS AND METHODSStudy systemThornbug treehoppers are sap-feeding insects that use vibrationalcommunication throughout their lives (Cocroft 1999 De Luca andCocroft 2008 Hamel and Cocroft 2012 Ramaswamy and Cocroft2009) Their host plants are woody shrubs and trees in theMimosaceae Most individuals grow to adulthood in a siblingaggregation of 50ndash100 individuals (Cocroft 2002) and whenfemales oviposit near other females the communal aggregationsmay be much larger Some females mate before dispersing from thenatal aggregation whereas others mate after dispersing (De Lucaand Cocroft 2008) Males disperse before females and either locateand remain with a pre-dispersal aggregation of females or search fordispersed unmated females Searching males use a call-fly strategyto locate a host plant with a receptive female and vibrationalduetting to locate the female within the plantWe studied thewithin-plant phase of mate searching

Animal careWe drew the study animals from a greenhouse colony at theUniversity of Missouri (Columbia MO USA) which weestablished with collections from in and around Miami FL USA(USDA APHIS permit P526P-10-03348) Thornbugs have three tofour generations per year in the greenhouse we maintained anoutbred colony by mating individuals with non-siblings and byintroducing new individuals from the field every three generationsFamily groups collected from the field contained late-instar nymphsandor teneral adults Each family was maintained on its ownpotted host plant (Mimosaceae Albizia julibrissin or Lysilomalatisiliquum) which was covered with a screen cage Approximately1 week after the adult molt the sexes were separated to preventsibling mating The colony was maintained on a 14 h10 h lightdarkcycle with a temperature range of 27ndash32degC (day) and 21ndash24degC(night) at 60ndash70 humidity

Experimental designOur goal was to obtain path data for searching males duettingwith stationary females then annotate the path by obtainingenvironmental information at each of the malesrsquo sampling points(Fig 1) Obtaining the necessary vibration measurements requiredseveral minutes for each point on the plant (see below) so it was notpossible to make those measurements in real time during a malersquossearch For each pair of insects then our characterization of searchpaths proceeded in two phases First after introducing the insectsonto a plant we plotted the malersquos sampling locations on a map ofthe plant and videorecorded the entire search while recording theduetting signals of the pair using a single stationary transducerSecond we removed the male before it reached the female or after15 min then used two lasers to measure stem vibration at each pointsampled by the male during the search Female signals were evokedas needed by playing back male vibrational signals Theexperimental data thus consisted of (1) variables measured fromthe original duet signaling behavior (timing duration) and malemovement information (location versus time) and (2) variables thatwere a proxy for vibrational signals experienced by the male duringits search signal amplitude spectral content and two-dimensionalmotion of the stem To ensure that the proxy measurements were asclose as possible to the signals experienced by the searching malewe only used trials in which the female was stationary during theentire search and post-search recording period This criterionensured that the signal transmission path was virtually identicalbetween the original search and the post-search recordings

We conducted n=16 trials each with a unique pair of unrelatedindividuals drawn from 10 family groups We selected experimentalindividuals haphazardly from their family group and did notuse individuals more than once We chose two sim1 m tall pottedL latisiliquum plants (woody hosts with multiple side branches seeResults and Fig S1 for branching structure) on which to observesearches Using only two hosts allowed us to estimate the effect ofplant differences while obtaining a detailed map of the structure ofthe individual plants We conducted eight trials on each plant fourwith the female on a stem near the top of the plant and four with thefemale on a stem near the bottom of the plant (see Results andFig S1 for female locations) Each male was placed at the samestarting location on a given plant sim40 cm from the female(measured along the stem) on a side stem roughly equidistantfrom both female positions Males began signaling either at theirinitial location or after walking a few centimeters along the stem

Treehoppers are not known to use chemical cues during within-plant searches and playback studies have shown that localization

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RESEARCH ARTICLE Journal of Experimental Biology (2018) 221 jeb175083 doi101242jeb175083

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readily occurs when only vibrational cues are available (egCocroft 2005) However to reduce the influence of potentialchemical cues that might have been left on the plant by previousindividuals we conducted trials with the female in the same position(apical or basal) on the same plant at intervals of 1ndash7 daysalternating with searches for females in the opposite position Anytrials conducted within the same day were separated by at least125 hWe know little about the role of vision in movement decisions of

thornbugs but visual cues appear to be important within 10 cm onthe same plant stem Females defending offspring walk directlytoward a moving predator in their line of sight (Wood 1976Cocroft 2002) but do not do so if their compound eyes are covered(Wood 1976) Searching males sometimes climb onto and court avibration actuator playing back female signals but males may alsowalk past a stationary female that is on the same stem and clearly intheir line of sight (authorsrsquo personal observations) In this study weminimized the potential influence of close-range visual homing byending the trial when the male was within 5 cm of the femaleHowever future studies should address the contribution of visualcues to movement decisions (see Verdeny-Vilalta et al 2015)ideally in combination with vibrational cuesFor each trial we placed a receptive female at the assigned

location waited 5 min and then introduced a male at the startinglocation If the male did not begin producing advertisement signalswithin 2 min we elicited signaling by playing back a signalexchange from a pre-recorded malendashfemale duet The trial startedwhen the male began signaling and initiated a duet with the femaleThe trial ended when the male approached within 5 cm of the femaleor after 15 min whichever came first During the trial the male wasvideorecorded using a stationary video camera (Exilim EX-F1Casio Dover NJ USA) and the duet was recorded using a piezo

film sensor attached near the base of the plant (12Prime piezo film taband General Purpose Amplifier model 1007214 MeasurementSpecialties Hampton VA USA) We ended the searches byremoving each male from the plant when it came within 5 cm of thefemale

We identified the sampling locations visually during each searchusing a map of the plant yielding a precision of plusmn05 cm asdetermined by comparison with the video recordings We then usedvibrational playback of male signals to induce the female tocontinue signaling from her original location and measured thesignals at each location where the male stopped signaled andreceived a reply from the female

Evoking female signals for measurementTo evoke continued female signals for measurement we used apiezoelectric stack actuator (ThorLabs AE0505D18F Newton NJUSA) mounted on a positioning arm and contacting the plant 5 cmabove the base with the contact secured using accelerometer waxThe actuator was driven by an open loop controller (ThorLabsMDT694A) custom DC-offset box Dell computer and Audacity(version 13) software

Vibration recording and analysisWe measured stem motion using two laser Doppler vibrometers(CLV 1000 lasers CLV M030 decoder modules Polytec IncAuburn MA USA) oriented perpendicularly to the long axis of thestem and to each other (see McNett et al 2006) We attached twosim1 mm2 pieces of reflective tape at the recording locations toincrease laser reflectance The laser output was high-pass filtered at30 Hz which is below the frequencies in the female signals (Filtermodel 3202 Krohn-Hite Corp Brockton MA USA) and digitizedusing a data acquisition system (CA-1000 board National

Annotatedsearch

ActionPerception

Direction

Distance tonext signalexchange

Signalexchanges

Female signal features

DurationRMS amplitude

1

1

10140

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1

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1

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loci

ty (m

sndash1

)Fr

eque

ncy

(kH

z)(m

m s

ndash1)

Amplitudeversus frequency

Axis of stemmotion

Eccentricityof stem motion

Wavepropagationvelocity

42 s

Fig 1 Study overview We first annotated male searches mapping each decision point (circles top left panel) where the searching male ( ) stopped andexchanged signals with the stationary female ( ) We used two-dimensional laser vibrometry to measure the femalersquos vibrational signals at each of the malersquosdecision points We then extracted multiple features of the signals including traditional features such as signal amplitude and duration as well as previouslyunmeasured features including the major axis and the eccentricity of stem motion at each frequency in the signal (signal shown is from the search in the top leftpanel) Finally we used a general linear mixed model to relate sensory input to subsequent action to infer how the searching males perceived and weightedfemale signal features when making movement decisions Blue boxes represent the lsquoknownsrsquo at each decision point and the red box represents the lsquounknownrsquoestimated by the statistical model

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Instruments Austin TX USA) with a Dell PC computer runningLabView software v 51 (National Instruments)The two simultaneous laser signals were analyzed using custom-

written scripts in MATLAB (version 10 MathWorks Natick MAUSA) based on equations from McNett et al (2006) Because stemmotion can occur along any axis within a plane perpendicular to thelong axis of the stem measuring motion along a single axis (as withuse of a single laser or accelerometer) will typically result inunderestimation of the signal amplitude (McNett et al 2006)Furthermore when a vibration is transmitted along a plant stem anypoint on the stem will move in an ellipse whose shape can vary fromlinear to circular and this motion cannot be captured with a singletransducer (McNett et al 2006) Use of two orthogonal transducersallows measurement of the amplitude of the major axis of stemmotion (Fig 2A) the relative amplitude of the major and minor axesof motion (Fig 2A) and the angle of rotation of the major axis ofmotion with respect to a reference axis (the malersquos dorsoventral axisat the time the female signal was produced Fig 2B) Each of theseproperties of motion can vary between different frequencies in thesame signal (Fig 1) Because we could not precisely score themalersquos orientation when it was hidden from the camera by the plantstem we characterized the malersquos orientation around the stem to thenearest 90 deg We thus had four possible reference axes dependingon the malersquos position 0 deg when the malersquos dorsoventral axis wasvisible and aligned with the video camera lens 180 deg when it wason the opposite side of the stem and 90 or 270 deg when the malersquosdorsoventral axis was perpendicular to the 0 deg axisThe information contained in two-sensor measurements of the

signal is distributed across three spectra (Fig 1) an amplitudespectrum (representing the major axis of stem motion at eachfrequency) an eccentricity spectrum (a unitless ratio of theamplitudes of the minor axismajor axis at each frequency) and arotation spectrum (the angle of rotation of the major axis at eachfrequency relative to the searching malersquos dorsoventral axis)

Wave propagation velocityPlant-borne vibrations are transmitted in the form of bending wavesunder most conditions (Casas et al 2007 Hill and Wessel 2016Miles 2016) including those experienced by the insects in thisstudy Variation in the propagation speed of bending waves is animportant feature of the sensory world of insects on plantsPropagation speed is faster at higher frequencies and on stems witha greater diameter and stiffness (Cremer et al 2005) To estimatethe wave propagation velocity at each location on the plants used inthis study we played back broadband noise using a piezo actuatoras above and recorded the noise simultaneously using two lasers

oriented in parallel and focused on two points 5 cm apart and 3ndash5 cm from the actuator (see Cocroft et al 2000) We made thesemeasurements at 12 locations spanning the range of variation instem diameter within a plant Frequencyndashvelocity curves have theform k times the square root of frequency where k is a constant thatvaries among substrates We estimated this constant for eachmeasured location by curve-fitting and found a strong positiverelationship between the velocity constant and stem diameter (FigS2) The expected relationship between diameter and velocitycannot be predicted precisely without also measuring stemproperties including the mass per unit volume and the elasticmodulus (Michelsen et al 1982) whose relationship to stemdiameter can vary along the length of the stem (Niklas 1992)Although we investigated only one type of wave (bending waves)other wave types are possible in plants including surface waves(Casas et al 2007 Michelsen 2014) whose propagation velocitydepends neither on diameter nor frequency and longitudinal waveswhose role in plant-borne vibrational communication has not beeninvestigated but which might be generated at junctions (Michelsen2014) In this study however we encountered only waves whosedispersive propagation is consistent with bending waves and we didnot attempt to measure longitudinal waves

To estimate the propagation velocity at each location sampled bymales we measured stem diameter throughout the plantinterpolated the value of the constant based on the curve obtainedabove and calculated the propagation velocity at an arbitraryfrequency in the signal (200 Hz the frequency with the highestamplitude is usually between 150 and 200 Hz) For statisticalanalysis we converted this measure into an estimate of the timedelay between front and back legs which on a male thornbug areseparated by sim5 mm

Note that we did not similarly estimate differences in amplitudebetween front and back legs For insects obtaining a 5 mm spatialsample along a vibrating stem the amplitude difference is near zero(Virant-Doberlet et al 2006) Furthermore for thornbugtreehoppers any differences in the amplitude of stem motionbetween front and back legs will be far smaller than the amplitudedifferences (up to 20 dB) generated between the front and back ofthe body by the mechanical response of the insectsrsquo body to time-of-arrival differences between the front and back legs (Cocroft et al2000)

Statistical analysis of movement decisionsWe analyzed the data with SAS v 94 (SAS Institute Cary NCUSA) We used PROC GLIMMIX unless otherwise noted thismodule supports general linear mixed models with response

A B

1

1 0 1

0

1

Maj

or a

xis

Minor axis

Stem

Stem

0 deg

45 deg

Fig 2 Two features of the two-dimensional motion of a plant stemduring transmission of vibrational signals (A) Eccentricity (minoraxismajor axis in this case eccentricity=05) magnitude of motion isexaggerated for illustration (B) Angle of rotation (in this case 45 degthe black dashed line at 0 deg represents the malersquos dorsoventral axisand the red dashed line the major axis of stem motion)

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variables that have non-normal distributions as was the case withmost of the variables we measured

Vibration gradientsTo further understand the insectsrsquo sensory environment and theiruse of vibrational cues we examined the effect of distance-to-sourceon four signal features (amplitude spectral shape eccentricity ofstem motion and variation among frequencies in the major axis ofstem motion) that could provide directional information throughcomparisons of sequential samples along a gradient Furthermorebecause plants are highly heterogeneous substrates for signalpropagation some gradients may occur as a consequence of plantstructure rather than source distance per se Consequently welooked at variation in these signal features not only in relation tosource distance but also in relation to a local property of the plantsubstrate stem diameter

AmplitudeThe response signals of the female thornbugs measured in this studyconsisted primarily of a harmonic series without amplitudemodulation and we characterized amplitude by averaging the rootmean square (RMS) amplitude over the entire signal Female signalscan also contain broadband clicks under some circumstances butthere were few or no clicks in most of the female signals in ourrecordings Measurements based on the waveform obtained by asingle laser would on average underestimate the signal amplitudeas explained above Accordingly we used the two-laser recordingsto calculate the amplitude spectrum of the major axis of vibration ateach frequency then used an inverse fast Fourier transform (FFT) toconstruct a new signal waveform with this amplitude spectrum Thiswaveform does not by itself represent the lsquotruersquo signal (ie the oneexperienced by the insect) but rather the maximum amplitude ofstem motion for each frequency in the signal regardless of the axisalong which the stem was vibrating There is additional signalenergy along the minor axis of stem motion and in principle theenergy in the major and minor axes could be summed here weaccounted for energy along the minor axis in a separate variable theeccentricity of the elliptical path of stem motion (see Eccentricitybelow)

Spectral shapeBecause attenuation of bending waves is greater at higherfrequencies (Markl 1983 Aicher et al 1983 Barth et al 1988)as a signal propagates farther from the source (other things beingequal) there should be increasing differences between theamplitudes of lower and higher frequencies As an index ofspectral content we calculated the ratio of energy in higherlowerfrequencies using a cut-off frequency of 300 Hz an approximatemid-point of the bandwidth for most female signals To make thismeasure comparable to our measure of overall signal amplitude weused the lsquomajor-axisrsquo waveform described in the previousparagraph To calculate the RMS energy in higher versus lowerfrequencies in the signal we filtered out the frequencies above orbelow the cut-off frequency generated the respective higher andlower frequency waveforms using an inverse FFT and obtained theratio of the average RMS in higher frequencies to that of lowerfrequencies (Fig S3)

EccentricityStems move with a whirling motion during propagation of bendingwaves (McNett et al 2006) and this motion varies from nearlylinear to circular As an index of the shape of the ellipse through

which the stem travels at each frequency in a signal we used theratio of the amplitudes of the two axes of the ellipse (minor axismajor axis) To exclude values from frequencies with little energywe used the amplitude spectrogram of the signal as a mask andaveraged only those frequencies with amplitudes within 20 dB ofthe maximum amplitude in the signal (Fig S4) To avoid assuminga priori that the eccentricity of motion at a given frequency wouldremain constant during the signal ndash and thus to account for potentialvariation in eccentricity as a function of not only frequency but alsotime ndash we averaged values from the masked spectrogram (a timeseries of spectra)

Angle of rotationA description of the whirling motion of the stem at a given signalfrequency includes not only the shape of the elliptical path (theeccentricity) but also the orientation of the major axis of motionrelative to a reference axis We used the searching malersquosdorsoventral axis at the location where it received the femalersquossignal as a reference axis (an angle of rotation of 0 deg is alignedwith this axis whereas an angle of 90 deg is perpendicular to thisaxis) Because the major axis of stem motion can vary amongdifferent frequencies in the signal we estimated an average angleof rotation As with eccentricity we first generated a rotationspectrogram (Fig 1) used the corresponding amplitudespectrogram as a mask and included only frequencies withamplitudes within 20 dB of the maximum amplitude Because themeasurements are angles we used circular statistics to estimate theaverage angle and the vector length which is a measure of howcorrelated the axis is among frequencies in the signal where a vectorlength of 1 would indicate that all the frequencies in the signal sharethe same major axis of stem motion

RESULTSSearch behaviorMales began their search on the stem on which they were placedBefore leaving this stem they made one to seven samples where alsquosamplersquo involved stopping signaling and receiving femalevibrational responses Males then walked onto the main stem ofthe plant where approximately one-third (516) made their firstsample while oriented across the stem (ie with the malersquos long axisperpendicular to the long axis of the stem virtually all of the othersamples we observed were made with the malersquos long axis parallelto the stem on which it was standing) Most of the males (1316)walked upward after first encountering the main stem

Males then continued to duet with the stationary female stoppingto make another sample every 52plusmn502 cm (meanplusmnsd range 1ndash34 cm) Males sampled side stems by walking a few centimetersonto them and signaling they did not sample branching points bysimultaneously touching both branches at a branching point as seenin some other insects during vibrational homing (Cokl et al 1999)Time versus distance-to-source plots for all of the searches areprovided in the supplementary material (Figs S5 and S6)

Males stayed at a sampling location for 13ndash142 s depending onthe number of signals they exchanged with the female (grandmean=32plusmn074 s N=16 pairs 236 samples) Stationary samplesconstituted on average approximately 25 of the total search time(range 11ndash39)

Most males located the female within 2ndash3 min (range 54 s to9 min 33 s) but one male failed to locate the female within 15 minMales located females in both locations (apical location eight out ofeight males basal location seven out of eight males) but malestook significantly less time and made more accurate directional

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decisions when the female was in the apical location (Fig 3AB)The average movement efficiency (minimum distance betweenmale and female along the plant surfacetotal distance traveled)when the female was in the apical location was 80 and four of theeight males traveled the minimum possible distance In contrast theaverage movement efficiency when the female was in the basallocation was 43 (including only the seven males that located thefemale within 15 min) In the lsquobasal positionrsquo searches only onemale traveled on a direct path between the starting position and thefemale whereas others searched more of the plant eg of two malesthat started 39 cm from the female one walked 15 m beforelocating the female and the other walked over 3 m in 15 minwithout locating the female

Distance-to-source and the accuracyofmovement decisionsThe directional accuracy of the malesrsquo movement decisions (iewhether the movement was toward or away from the female) waslower when males were farther from the female (Fig 3C) Most ofthe inaccurate decisions occurred when males searched for femalesthat were near the base of the plant and errors typically occurred inruns (see the time versus distance-to-source plots in Figs S4 and S5)Of the 10 searches in which males made at least two directionalerrors four searches had significantly more erroneous decisions in arow than expected by chance [runs tests all Plt005 after adjustingfor multiple comparisons using the false discovery rate procedure(Benjamini and Hochberg 1995)] During such runs whichoccurred both on the main stem and on side stems malescontinued to walk forward through two to six samples movingfarther from the female each time before finally reversing directionMales also sampled differently at different distances from the

female The farther males were from the female the greater distancetheymoved between samples (GLMM df=1219F=1383Plt0001)

Observations and video analysis revealed an additionalpreviously unrecognized sampling behavior which we havetermed lsquocryptic samplesrsquo After leaving a stationary samplingpoint males sometimes continued to signal while walking makingbrief (lt1 s) interruptions in their forwardmotion during the femalersquosreply Males often made two to four cryptic samples in successionapproximately 15 cm apart before making another stationarysample These brief samples constituted approximately 30(plusmn11 se) of all sampling points The time and location of allcryptic samples were mapped from the videos (see Figs S4 and S5)however female signals were only recorded from 12 cryptic samplesthat were obvious enough to be detectable in real time The accuracyof directional decisions did not differ between stationary samplesand cryptic samples (GLMM df=1324 F=028 P=059)

Vibrational cues and movement decisionsBecause there was substantial variation in directional accuracy andsampling behavior within and among searches we next asked whichvibrational cues were correlated with accuracy forwardreversedecisions and the distance moved between samples In theseanalyses we included only the lsquostationaryrsquo samples and not the 12cryptic samples for which we obtained signal data

Forwardreverse decisionsThe main predictor of turning decisions was the direction of wavepropagation Males were more likely to walk forward if thepropagating waves came from in front of them and to turn aroundif the waves came from behind them (Fig 4A) Among thepotential gradients (ie differences between successive samplingpoints in the amplitude or two-dimensional properties of thesignal) the only variable correlated with male decisions was theaverage angle of rotation of the signal relative to the malersquosdorsoventral axis Males were more likely to reverse direction if

A B

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0ndash20 20ndash40Distance to female (cm)

40ndash60

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porti

on c

orre

ct

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Tim

e to

loca

te fe

mal

e (m

in)

Apical BasalFemale position

100

075

050

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porti

on c

orre

ct

025

0

Fig 3 The influence of female location onmale search time and accuracyMale thornbugs (A) located females more quickly and (B) made fewer directionalerrors when the female was in the apical location on the plant (16 malendashfemale pairs) (C) Males mademore accurate decisions when closer to the female (grandmeans 16 males 360 directional decisions) Plt005 Error bars represent sem

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they first sampled a signal whose average angle of rotation wasclosely aligned with their dorsoventral axis and at the next sampleencountered a signal whose average angle of rotation was morenearly perpendicular to the malersquos dorsoventral axis (side-to-side

with respect to the male Fig 4B) Between-sample differences insignal amplitude eccentricity ratio of high and low frequenciesand female signal duration did not significantly predict turningdecisions (Table 1)

10

075

025

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-40 0 40∆ Angle of rotation between samples

(negative values axis in second sample is more alignedwith malersquos dorsoventral axis) 10

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D

E

Fig 4 Relationship between sensory input andmotor output for male thornbugsMales were more likely to walk forward rather than turn around when (A) thepropagatingwave arrived from in front rather than frombehind and (B) when themale experienced a between-sample change in the axis of stemmotion such that thestemmotion during the second signal wasmore closelyalignedwith themalersquos dorsoventral axis During their searchmalesmademore accurate decisionswhen thefemale response signal at the current sampling location (C) was greater in amplitude (D) had a lower propagation speed and correspondingly greater time-of-arrivaldifference between vibration sensors in front and back legs and (E) was shorter in duration Gray shading indicates the 95 confidence intervals

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Directional accuracyMales made more accurate decisions (ie they were more likely tomove in the direction of the female after a sample) when signalamplitude was higher (Fig 4C Table 2) which occurred closer tothe source (Fig 5A) Males also mademore accurate decisions whenthey experienced a longer time delay between front and back legsie when signal propagation speed was slower (Fig 4D) Thisproperty of signal transmission varied with stem diameter (Fig 5B)and during a search males sometimes experienced very differentsignal propagation speeds between one sample and the next Theduration of the femalersquos reply signal was also correlated with maledirectional accuracy males made more accurate decisions when thefemalersquos reply was shorter (Fig 4E)

Distance moved between samplesTwo aspects of the whirling motion of the stem were correlated withhow far males moved between samples Males moved farther aftersampling a signal for which (1) the axis of stem motion was highlyvariable among frequencies and (2) the average path of stemmotionwas more linear (Table 3)

Vibration gradientsAmplitudeSignal amplitude decreased with distance from the source on bothplants and in both apical and basal female locations (Fig 6Table 4) However amplitude gradients were local with amplitudedecreasing consistently only within 10ndash20 cm of the signal source(Fig 5A)Amplitude is also strongly dependent on stem diameter for a

given signal smaller stems vibrate at a higher amplitude than largerstems The influences of diameter and source distance on amplitudewere independent of each other (Fig 6 Table 4)

EccentricitySignal eccentricity was not reliably correlated with distance fromthe source (Fig 6 Table 4) Instead there was a three-wayinteraction between diameter female location and distance to the

female overall eccentricity increased toward the top of the plantand the outer stems in both female location treatments

Angle of rotationWithin-signal variability in the angle of rotation increased withdistance from the female (Fig 6 Table 4)

Spectral shapeThe relative amplitude of higher and lower frequencies changed as afunction of distance from the source with higher frequenciesbecoming increasingly attenuated as predicted In addition to thisgradient however the relative amplitude of higher and lowerfrequencies was also influenced by the stem diameter (Fig 6Table 4)

DISCUSSIONPlant-dwelling insects make up a large fraction of terrestrialbiodiversity perhaps 40 of animal species (Bush and Butlin2004) and many of their social and ecological interactions aremediated by plant-borne vibrations (Cocroft and Rodriacuteguez 2005)In this study we have gained insights into both the nature ofvibrational environments on living plants and the search strategiesof male thornbugs that allow them to navigate a complexenvironment using highly variable and often uncertain sensoryinformation Vibration transmission in living plants presentschallenges for localization waves travel at very different speedson different parts of the plant and at different frequencies adding tothat complexity at any given location the stem moves in a whirlingpath whose properties also vary among different frequencies in thesignal These difficulties are especially great for small insects whosevibration sensors are separated by only a few millimetersNonetheless nearly all of the male thornbugs in this study locatedthe stationary signaling female Because the insectsrsquo directionaldecisions are made at identifiable sampling locations we were ableto compare behavioral output with sensory input to identify cuesthat are important in movement decisions This study is the first toannotate complete within-plant searches based on plant-bornevibrations by measuring the motion of the substrate at samplinglocations and the first study to investigate the influence of the two-dimensional motion of the substrate on behavior The whirlingmotion of plant stems is a fundamental feature of the vibrationalworld of insects on plants and differences in this motion have animportant influence on behavior

We identified two mechanisms by which males can determine thedirection of the signal source The most important cue was thedirection of wave propagation with higher accuracy at lowertransmission speeds and correspondingly higher time-of-arrivaldifferences at front and back legs Desert scorpions and termites alsouse time-of-arrival differences between spatially separated legs toassess direction and likewise lost directional accuracy at hightransmission speeds (Brownell and Farley 1979 Hager andKirchner 2014) Although the vibration receptors in the legs ofmale thornbugs are separated by 5 mm or less the mechanicalresonance of the thornbugrsquos body (Cocroft et al 2000) convertssmall time delays into large amplitude differences at the front andback of the body potentially providing an additional source ofinformation about wave propagation direction Importantly therewas no evidence of the standing waves that can occur duringvibration transmission on plants (Michelsen et al 1982 Polajnaret al 2012) standing waves provide no information about sourcedirection Instead vibration transmission on these woody plants wasdominated by one-way transient wave propagation Males also

Table 2 Signal features that influence the accuracy of movementdecisions by searching male thornbugs

EffectsNumerator dfdenominator df F P

Amplitude RMS 1199 874 00035Mean eccentricity 1199 000 09956Mean angle of rotation 1199 205 01541Estimated time delay 1199 965 00022Ratio of high to low frequencies 1199 062 04336Female response duration 1199 628 00130

Random effects (controlling for differences among malendashfemale pairs) are notincluded in tables

Table 1 Signal features that influence the forwardreverse decisions ofsearching male thornbugs


Wave propagation direction 1139 1533 00001ΔAmplitude RMS 1139 028 05989ΔAngle of rotation 1139 463 00332ΔMean eccentricity 1139 145 02299ΔRatio of high to low frequencies 1139 005 08209ΔFemale response duration 1139 185 01763

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compared signals between sequential samples males were morelikely to walk forward if the axis of stem motion became moreclosely aligned with their own dorsoventral axis and more likely toturn around if the axis became less closely aligned with theirdorsoventral axis In honeybees substrate motion along the longaxis of the leg stimulated higher output from the subgenual organ(the principal vibration receptor in the legs of many insects) than didmotion in a direction perpendicular to the leg This difference in theaxis of motion was equivalent to an amplitude difference of 10 dB(Kilpinen and Storm 1997) If the same is true for male thornbugsthe axis of substrate motion relative to a searching male maytranslate into a substantial difference in perceived amplitude suchthat males perceived an increase in amplitude between samplesWe identified a previously unnoticed type of sampling behavior

in thornbugs which we termed lsquocryptic samplingrsquo In contrast tostationary samples that typically last 3ndash4 s cryptic samples takeonly a fraction of a second They occur when males continue tosignal while walking but pause briefly during the female replyMales evidently gained information from cryptic samples theproportion of reversals of direction and the influence of distancefrom the female on accuracy and step length did not differ betweensample typesWe hypothesize that cryptic samples are a competitive

strategy used by males to reduce search time In this study there wasonly one male on the plant at a time but playback of a malendashfemaleduet to initiate signaling may have causedmales to behave as thougha competitor were present Thornbugs often occur at high densitiesbecause females mate only once and will duet with more than onemale at a time (JSG personal observation) there is likely sexualselection for rapid localization Males spent about a quarter of theirsearch time in stationary sampling so individuals may be able toreduce their sampling time through these short samples Althoughdata from this study did not reveal a speed versus accuracy trade-offin sampling behavior study of search behavior in other contexts(such as the presence of other males) may reveal why males usuallyengaged in the more time-consuming stationary samples Thediscovery that males can obtain brief samples while moving fromone stationary sample to another is relevant to studies of otherspecies with intermittent locomotion closer examination mayreveal that individuals are obtaining information not just during thestationary phase but also during the movement phase

Thornbugs often experience substantial uncertainty about sourcelocation Accuracy can be unambiguously quantified during thesesearches because both the target location and the decision points areknown (see Legendre et al 2012 Polajnar et al 2014) The

Apical Basal

Plant 2

Am

plitu

de (d

B re

1 m

m s

ndash1)

Prop

agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

minus5

minus10

minus15

minus20

minus25

minus30

minus35

minus40

minus45

70

65

60

55

50

45

40

35

30

25

Fig 5 Within-plant spatial variation invibrational signal propertiesencountered by searching malethornbugs silhouettes representfemale ( ) location and male ( )starting location (A) Amplitude gradientsfor both female positions within each plantheat maps represent measurements at alllocations sampled by males for that femaleposition on that plant plus interpolatedvalues (B) Wave propagation speed at200 Hz for all locations on each plantestimated from the measured relationshipbetween stem diameter and propagationspeed One search path is superimposedon each heat map to illustrate the changingvibrational environment encountered bysearching males circles show decisionpoints where males stopped andexchanged signals with stationaryfemales Closed circles correct decisionsopen circles incorrect decisions largercircles longer stationary samples smallercircles brief cryptic samples

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accuracy of movement decisions was lower when males were fartherfrom the signaling female Errors occurred in runs with malesmaking several incorrect decisions in a row before correctingcourse shorter runs of errors were also seen during vibrationalhoming in a leafhopper (Polajnar et al 2014) Note that we onlyconsidered a decision to be inaccurate if the male turned in theincorrect direction after a sample we did not consider it an error ifthe male took the wrong turn at a branching point without stoppingto sample The relationship between distance to the source andaccuracy was mirrored by a relationship between distance andsampling behavior The distance males moved between samplesbecame successively smaller as males approached the female Thelonger inter-sample movements made at greater distances may allowindividuals to leave areas in which source direction was difficult toassess (Bartumeus 2009 Hein and McKinley 2012)The observation that the sampling behavior of searching males

changed predictably with distance from the source indicates thatmales experienced some form of distance-dependent vibrationalgradient We examined four potential vibrational gradientsincluding overall signal amplitude the relative amplitude ofhigher and lower frequencies and within-signal variation in boththe axis of motion and the elliptical shape of stemmotion at differentfrequencies We investigated how each of these gradients wasinfluenced by both distance to the source and the stem diameter atthe malesrsquo locationThe searching males in this study encountered amplitude

gradients within 10ndash20 cm of the source signal amplitudeincreased reliably as males approached the source whereas at

greater distances there was no relationship between amplitude anddistance from the source (see Fig 5A) These short-range gradientsoccurred only on the side stem on which the femalewas located Thesteep increase in amplitude close to the source may be due at least inpart to vibrational near-field effects (Miles 2016) The existence ofa local amplitude gradient on side stems where females were locatedprovides reliable information about whether to explore a side stemon the lsquocorrectrsquo side stem the amplitude will increase relative to themain stem whereas on the lsquoincorrectrsquo side stems the amplitude willdecrease or stay the same relative to the main stem Similarlysearching leafhoppers (Polajnar et al 2014) make rapid correctionsafter walking from the stem onto the petioles of leaves notcontaining the female The leafhopper males encountered amplitudeincreases once they walked onto the leaf from which the stationaryfemale was signaling (Mazzoni et al 2014) and the amplitudeincreases were correlated with changes in the searching malersquosbehavior

At any one frequency produced by a vibration source on a plantthere is unlikely to be a gradient of monotonically decreasingamplitude with distance from the source (Mazzoni et al 2014Michelsen 2014 Michelsen et al 1982 Mortimer 2017 Virant-Doberlet et al 2006) this is because of changes in the properties ofthe transmission channel or because of reflections that createstanding waves with local minima and maxima (Polajnar et al2012) However signal amplitude must decrease with distanceowing to frictional loss during transmission (Mortimer 2017) andfor signals with a broad band of frequencies the amplitude does falloff reliably with distance (present study Polajnar et al 2014)Michelsen et al (1982) point out that in their measurements ofsignal propagation along plant stems there were monotonicdecreases in signal amplitude with distance for frequencies above2 kHz Furthermore in that study the average amplitude across theentire spectrum measured [based on area under the curve fromimage analysis in ImageJ (Schindelin et al 2015)] also decreasedmonotonically at 3 7 and 17 cm from the source the averageamplitude was approximately minus2 minus5 and minus12 dB relative to theamplitude at the source respectively Amplitude gradients thusappear to provide a reliable cue for insects homing in on signals witha wide frequency range such as insect songs with broadbandcomponents (Polajnar et al 2014) or herbivore feeding vibrations(Pfannenstiel et al 1995)

The signal amplitude perceived by a searching insect will also beinfluenced by changes in the two-dimensional nature of stemmotion We already mentioned the influence of the major axis ofstem motion and its degree of alignment with the axis of greatestsensitivity of the vibration receptors in the legs This effect may befurther modified by the eccentricity of stem motion For a givenamplitude of stem motion there is twice as much energy in thesignal if the stem moves in a circular path than if it moves in a linearpath (ie there is an equal amplitude of motion along two orthogonalaxes) Furthermore if there is considerable energy in the minor axisof the elliptical path of stem motion this may compensate for amisalignment of the major axis of stem motion with the axis ofgreatest sensitivity of the leg vibration sensors Searching malethornbugs provide behavioral evidence that both aspects of stemmotion are important Males in situations of high uncertainty (suchas when far from the female) tended to walk farther betweensamples The signal traits correlated with these longer inter-sampledistances were the signal eccentricity (males walked farther whenmotion was more linear) and the axis of stem motion (males walkedfarther when there was greater variation in the axis of stem motionamong different frequencies in the signal)

Table 3 Signal features that influence the distance that searching malethornbugs walked between sampling locations


Amplitude RMS 1192 176 01862Mean eccentricity 1192 912 00029Mean angle of rotation 1192 034 05629Variation in angle of rotation 1192 980 00020Estimated time delay 1192 005 08206Ratio of high to low frequencies 1192 042 05184Female response duration 1192 364 00579

Distance to female Stem diameter

RMS amplitude

Ratio of high to lowfrequencies

Variation in angle ofrotation ns

Mean eccentricityapical

Mean eccentricitybasal

L + H

L

Fig 6 The relationship between vibrational signal properties anddistance along the plant structure from the signaling female and thestem diameter at the sampled location Solid lines indicate the slope ofsignificant relationships based on linear regression

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Signal amplitude is influenced not only by the transmission pathbut also by the local properties at the sampling location in particularthe stem diameter Whether the insects make use of the stronginverse relationship between amplitude and stem diameter isunknown but there are at least two ways in which thisrelationship could shape communicative interactions Firstbecause distance and diameter have independent effects on signalamplitude there will be a steeper amplitude gradient relative to asignal source at the narrow end of a tapering stem than at the widerend Depending on whether the fitness of the vibration-producingindividual is increased by being located (as with a signaling female)or decreased (as with a feeding herbivore) it may be an advantage tobe at the narrower or wider end of a tapering stem Second detectionof low-amplitude signals may be enhanced when insects lsquolistenrsquo onsmall-diameter stemsIn addition to amplitude gradients searching male thornbugs also

experienced distance-to-source gradients in the nature of stemmotion In particular there was a distance-to-source gradient in themajor axis of stem motion with distance the axes of motion withinthe signal became increasingly uncorrelated among differentfrequencies in the signal In contrast for the plants in this studythe eccentricity of stem motion was primarily a function of plantstructure rather than source distance increasing toward the lessanchored parts of the plant including the top of the plant and theouter parts of the side stems Accordingly eccentricity gradientswere unreliable indicators of source direction instead there was acoincidental increase or decrease in eccentricity with distancedepending on whether the signaler was near the bottom or the top ofthe plant This finding does not support the hypothesis proposed byVirant-Doberlet et al (2006) that changes from more linear to morecircular motion provide a cue of source distance The two studiesthat support the lsquoeccentricity gradientrsquo hypothesis were limited inscope ndash one was based on single-sensor measurements around thestem of a sedge vibrated with an actuator at two distances from thesource (Virant-Doberlet et al 2006) and the other was based ontwo-sensor measurements as in this study at three distances fromsignaling male thornbugs on a woody plant (McNett et al 2006) ndashand cannot separate out the effects of distance from those of plantstructure or the possible anchoring effect of a vibration actuatorFrequency-dependent attenuation of bending waves has also been

proposed as a ranging mechanism for vibrational signals on plants(Aicher et al 1983 Barth et al 1988) because higher frequencieshave shorter wavelengths and thus lose more energy to friction perunit distance than lower frequencies (Mortimer 2017) In thepresent study there was indeed a distance-dependent change in thespectral shape of female signals with the predicted loss of higherfrequencies at greater distances however therewas no evidence thatmales used this vibrational gradient Polajnar et al (2014) looked foran influence of such attenuation on the behavior of searching maleleafhoppers but in that study there was no consistent relationship

between spectral shape of the female reply signals and eitherdistance from the female or male behavior

The picture emerging from consideration of these threegradients ndash amplitude whirling motion of the stem and spectralshape ndash is that as a male travels farther from the signaling femalethe plant stems move in an increasingly complex and disorderedfashion This increasing disorder of the signal is associated withthe malesrsquo decisions to travel farther before stopping to obtainanother sample In thornbugs then the actionndashperception cycleresponds to the quality of the available cues of source locationThese properties of stem motion ndash the axes along which the stemmoves the eccentricity of its elliptical path and the variation ofthese features among different frequencies in the signal ndash shouldbe taken into account in future studies of vibration-guidedsearching

The behavior of the stationary female may provide another sourceof directional information in addition to the transmission-dependent changes in vibrational signals In many insect duettingsystems there is mutual behavioral adjustment between signalers(Rodriacuteguez and Barbosa 2014) Both individuals may be able toassess the distance between them and if the interaction iscooperative the stationary individual could in principle changeits signaling behavior to provide the searcher with additionalinformation In this study females varied the duration of theirsignals and male search accuracy was lower when the femalesignals were longer The cause and effect relationship here isunclear and the most we can say is that the behavior of the searchingand stationary individuals were correlated such that not only malesbut also females were altering their behavior in predictable waysover the course of the search It would be useful to examine therelationship between sensory input and behavioral output infemales for example by measuring signals at the femalersquoslocation and relating properties of male signals to femalesignaling behavior

The efficacy of female signals ie their transmission anddetectability (Endler 1992 Endler and Basolo 1998) wasmaximized when females were near the top of the plant Althoughmalendashfemale distance was the same at the start of all trials thetransmission path between female and male consisted of larger-diameter stems when the female was at the bottom of the plant Asstem diameter increases signal amplitude decreases and wavepropagation speed increases thus as males search on larger-diameter stems they will encounter lower signal amplitudes andsmaller time delays between sensors in the front and back legs andboth of these features will reduce accuracy Furthermore stemproperties such as xylem vessel size stiffness and mass per unitvolume also differ at different locations on a plant furtherinfluencing vibration propagation (Niklas 1992) A femalersquoschoice of a signaling site within a plant will therefore have a largeeffect on signal efficacy

Table 4 The relationship between signal features distance to the signal source and stem diameter


Numerator dfdenominator df F P


Amplitude RMS 1230 6509 lt00001 1230 5994 lt00001Ratio of high to low frequencies 1226 2137 lt00001 1226 2114 lt00001Variation in angle of rotation 1230 7230 lt00001 1230 107 03016Mean eccentricity 1226 702 00086 1226 199 01602

Non-significant interaction terms were removed from models Significant three-way interaction between distance to female diameter and female position (seeTable S1 for details)

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Further studies will likely reveal additional adaptations that allowinsects to navigate such a complex environment and will beespecially fruitful when combined with experimental tests of thehierarchy of cues used by searching insects Furthermore laboratoryconditions such as those in this study represent an ideal case forsearch efficiency In nature vibrational environments are noisywith plant tissues set into vibration by wind rain airborne soundand movement or signaling by multiple species on the same plant(Cocroft and Rodriacuteguez 2005 McNett et al 2010 Tishechkin2007 Virant-Doberlet et al 2014) Sociality will also influencebiotic noise levels male thornbugs are most likely to encounterrelatively low-noise conditions such as those in this study whensearching for solitary dispersed females In contrast other mate-finding mechanisms may be required when searching for femalesstill in the natal aggregation where other signaling males aretypically present and there may be dozens of females in closeproximity most of which are non-receptive (De Luca and Cocroft2011) In any case search efficiency is likely to be under strongselection especially during competitive mate searching (Legendreet al 2012) or during recruitment to a feeding site (Cocroft 2005)The strategies used by insects during vibrational homing on plantsare thus an excellent model system for understanding how searchstrategies evolve to exploit uncertain sensory cues in a complexenvironment (Giuggioli and Bartumeus 2010)

AcknowledgementsThis research represents a portion of a dissertation submitted as part of therequirements for a PhD at the University of Missouri We thank Manuel Leal JeromeCasas and an anonymous reviewer for comments on the manuscript and SarahBush Mark Flinn Carl Gerhardt Scott Holan and Chris Wikle for their assistance atvarious stages of this project We thank Lada Micheas of the University of MissouriStatistics department for statistical consulting We also thank Flavia Barbosa ShiloBender Anne Lohrey Jennifer Hamel Rhett Hartman Rico Holdo Kelly HouglandPeter Marting Maria Rodenas Bosque and Lucas Rodenas Gibson for help andadvice

Competing interestsThe authors declare no competing or financial interests

Author contributionsConceptualization JSG RBC Methodology JSG Formal analysis JSGRBC Investigation JSG Writing - original draft JSG Writing - review ampediting RBC Visualization JSG Supervision RBC Funding acquisitionRBC

FundingSupport for this project was provided by the National Science Foundation Division ofIntegrative Biology and Neuroscience grant 0820533

Supplementary informationSupplementary information available online athttpjebbiologistsorglookupdoi101242jeb175083supplemental

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Barbosa P and Castellanos I (2005) Ecology of Predator-Prey InteractionsOxford Oxford University Press

Barnett K E Cocroft R B and Fleishman L J (1999) Possible communicationby substrate vibration in a chameleon Copeia 1999 225-228

Barth F G (1998) The vibrational sense of spiders In Comparative HearingInsects (ed R R Hoy A N Popper and R R Fay) pp 228-278 New YorkSpringer

Barth F G Bleckmann H Bohnenberger J and Seyfarth E A (1988)Spiders of the genus Cupiennius Simon 1891 (Araneae Ctenidae) - II On thevibratory environment of a wandering spider Oecologia 77 194-201

Bartumeus F (2009) Behavioral intermittence Levy patterns and randomness inanimal movement Oikos 118 488-494

Benjamini Y and Hochberg Y (1995) Controlling the false discovery rate apractical and powerful approach to multiple testing J R Stat Soc Ser B 57289-300

Berg H C (2000) Motile behavior of bacteria Phys Today 53 24-30Brownell P and Farley R D (1979) Detection of vibrations in sand by tarsal

sense organs of the nocturnal scorpion Paruroctonus mesaensis J CompPhysiol A 131 23-30

Bush G L and Butlin R K (2004) Sympatric speciation in insects In AdaptiveSpeciation (ed U Dieckmann M Doebeli J Metz and D Tautz) pp 229-248Cambridge Cambridge University Press

Caldwell M S (2014) Interactions between airborne sound and substrate vibrationin animal communication In Studying Vibrational Communication ed (R BCocroft M Gogala P S M Hill and A Wessel) pp 65-92 Heidelberg Springer

Casas J andMagal C (2006) Mutual eavesdropping through vibrations in a host-parasitoid interaction from plant biomechanics to behavioural ecology In InsectSounds and Communication (ed S Drosopoulos and M F Claridge)pp 263-271 Boca Raton FL CRC Press

Casas J Magal C and Sueur J (2007) Dispersive and non-dispersive wavesthrough plants implications for arthropod vibratory communicationProc Biol Sci274 1087-1092

Christensen C B Christensen-Dalsgaard J Brandt C and Madsen P T(2012) Hearing with an atympanic ear good vibration and poor sound-pressuredetection in the royal python Python regius J Exp Biol 215 331-342

Cocroft R B (1999) Offspring-parent communication in a subsocial treehopper(Hemiptera Membracidae Umbonia crassicornis) Behaviour 136 1-21

Cocroft R B (2002) Antipredator defense as a limited resource unequal predationrisk in broods of an insect with maternal care Behav Ecol 13 125-133

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Cocroft R B and McNett G D (2006) Vibratory communication in treehoppers(Hemiptera Membracidae) In Insect Sounds and Communication PhysiologyBehaviour Ecology and Evolution (ed S Drosopoulos and M F Claridge) pp305-318 Boca Raton FL Taylor and Francis Group

Cocroft R B and Rodrıguez R L (2005) The behavioral ecology of insectvibrational communication Bioscience 55 323-334

Cocroft R B Tieu T D Hoy R R and Miles R N (2000) Directionality in themechanical response to substrate vibration in a treehopper (HemipteraMembracidae Umbonia crassicornis) J Comp Physiol A 186 695-705

Cokl A Virant-Doberlet M and McDowell A (1999) Vibrational directionality inthe southern green stink bug Nezara viridula (L) is mediated by female songAnim Behav 58 1277-1283

Cremer L Heckl M and Petersson B A T (2005) Structure-Borne SoundStructural Vibrations and Sound Radiation at Audio Frequencies 3rd edn BerlinHeidelberg Springer-Verlag

De Luca P A and Cocroft R B (2008) The effects of age and relatedness onmating patterns in thornbug treehoppers inbreeding avoidance or inbreedingtolerance Behav Ecol Sociobiol 62 1869-1875

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Dodge S Bohrer G Weinzierl R Davidson S C Kays R Douglas DCruz S Han J Brandes D andWikelski M (2013) The environmental-dataautomated track annotation (Env-DATA) system linking animal tracks withenvironmental data Mov Ecol 1 3

Endler J A (1992) Signals signal conditions and the direction of evolution AmNat 139 S125-S153

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Gaudry Q Nagel K I and Wilson R I (2012) Smelling on the fly sensory cuesand strategies for olfactory navigation in Drosophila Curr Opin Neurobiol 22216-222

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Hager F A and Kirchner W H (2014) Directional vibration sensing in the termiteMacrotermes natalensis J Exp Biol 217 2526-2530

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and Engelmann J (2013) Sensory flow shaped by active sensing sensorimotorstrategies in electric fish J Exp Biol 216 2487-2500

Hunt R E and Nault L R (1991) Roles of interplant movement acousticcommunication and phototaxis in mate-location behavior of the leafhopperGraminella nigrifrons Behav Ecol Sociobiol 28 315-320

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Legendre F Marting P R and Cocroft R B (2012) Competitive masking ofvibrational signals during mate searching in a treehopper Anim Behav 83361-368

Markl H (1983) Vibrational communication In Neuroethology and BehavioralPhysiology (ed F Huber and H Markl) pp 332-353 Berlin Heidelberg Springer

Mazzoni V Eriksson A Anfora G Lucchi A and Virant-Doberlet M (2014)Active space and the role of amplitude in plant-borne vibrational communicationIn Studying Vibrational Communication (ed RB Cocroft M Gogala P S M Hilland A Wessel) pp 125-145 Berlin Heidelberg Springer

McNett G D Miles R N Homentcovschi D and Cocroft R B (2006) Amethod for two-dimensional characterization of animal vibrational signalstransmitted along plant stems J Comp Physiol A 192 1245-1251

McNett G D Luan L H and Cocroft R B (2010) Wind-induced noise alterssignaler and receiver behavior in vibrational communication Behav EcolSociobiol 64 2043-2051

Michelsen A (2014) Physical aspects of vibrational communication In StudyingVibrational Communication (ed R B Cocroft M Gogala P S M Hill and AWessel) pp 199-213 Berlin Heidelberg Springer

Michelsen A Fink F Gogala M and Traue D (1982) Plants as transmissionchannels for insect vibrational songs Behav Ecol Sociobiol 11 269-281

Miles R N (2016) An analytical model for the propagation of bending waves on aplant stem due to vibration of an attached insect Heliyon 2 e00086

Mortimer B (2017) Biotremology do physical constraints limit the propagation ofvibrational information Anim Behav 130 165-174

Murlis J Elkinton J S and Carde R (1992) Odor plumes and how insects usethem Annu Rev Entomol 37 505-532

Nathan R Getz W M Revilla E Holyoak M Kadmon R Saltz D andSmouse P E (2008) A movement ecology paradigm for unifying organismalmovement research Proc Natl Acad Sci USA 105 19052-19059

Nathan R Spiegel O Fortmann-Roe S Harel R Wikelski M and GetzW M (2012) Using tri-axial acceleration data to identify behavioral modes of free-ranging animals general concepts and tools illustrated for griffon vultures J ExpBiol 215 986-996

Niklas K J (1992) Plant Biomechanics An Engineering Approach to Plant Formand Function Chicago IL University of Chicago Press

Pfannenstiel R S Hunt R E and Yeargan K V (1995) Orientation of ahemipteran predator to vibrations produced by feeding caterpillars J InsectBehav 8 1-9

Polajnar J Svensek D and Cokl A (2012) Resonance in herbaceous plantstems as a factor in vibrational communication of pentatomid bugs (HeteropteraPentatomidae) J R Soc Interface 9 1898-1907

Polajnar J Eriksson A Rossi Stacconi M V Lucchi A Anfora G Virant-doberlet M and Mazzoni V (2014) The process of pair formation mediated bysubstrate-borne vibrations in a small insect Behav Processes 107 68-78

Ramaswamy K and Cocroft R B (2009) Collective signals in treehopper broodsprovide predator localization cues to the defending mother Anim Behav 78697-704

Resheff Y S Rotics S Harel R Spiegel O and Nathan R (2014)AcceleRater a web application for supervised learning of behavioral modes fromacceleration measurements Mov Ecol 2 27

Rodrıguez R L and Barbosa F (2014) Mutual behavioral adjustment invibrational duetting In Studying Vibrational Communication (ed R B Cocroft MGogala P S M Hill and A Wessel) pp 147-169 Berlin Heidelberg Springer

Schindelin J Rueden C T Hiner M C and Eliceiri K W (2015) The ImageJecosystem an open platform for biomedical image analysis Mol Reprod Dev82 518-529

Signer C Ruf T Schober F Fluch G Paumann T and Arnold W (2010) Aversatile telemetry system for continuous measurement of heart rate bodytemperature and locomotor activity in free-ranging ruminantsMethods Ecol Evol1 75-85

Smolka J Zeil J and Hemmi J M (2011) Natural visual cues eliciting predatoravoidance in fiddler crabs Proc R Soc B Biol Sci 278 3584-3592

Spiegel O Leu S T Bull C M and Sih A (2017) Whatrsquos your moveMovement as a link between personality and spatial dynamics in animalpopulations Ecol Lett 20 3-18

Srinivasan M V (2011) Honeybees as a model for the study of visually guidedflight navigation and biologically inspired robotics Physiol Rev 91 413-460

SutherlandW J Freckleton R P Godfray H C J Beissinger S R BentonT Cameron D D Carmel Y Coomes D A Coulson T Emmerson M Cet al (2013) Identification of 100 fundamental ecological questions J Ecol 10158-67

Tishechkin D Y (2007) Newdata on vibratory communication in jumping plant liceof the families Aphalaridae and Triozidae (Homoptera Psyllinea) Entomol Rev87 394-400

Ulanovsky N Moss C F (2008) What the batrsquos voice tells the batrsquos brain ProcNatl Acad Sci USA 105 8491-8498

Verdeny-Vilalta O Aluja M and Casas J (2015) Relative roles of resourcestimulus and vegetation architecture on the paths of flies foraging for fruit Oikos124 337-346

Virant-Doberlet M and Cokl A (2004) Vibrational communication in insectsNeotrop Entomol 33 121-134

Virant-Doberlet M Cokl A and Zorovic M (2006) Use of substrate vibrationsfor orientation from behaviour to physiology In Insect Sounds andCommunication Physiology Behaviour Ecology and Evolution (ed SDrosopoulos and M F Claridge) pp 81-98 Boca Raton FL Taylor andFrancis Group

Virant-Doberlet M Mazzoni V de Groot M Polajnar J Lucchi ASymondson W O C and Cokl A (2014) Vibrational communicationnetworks eavesdropping and biotic noise In Studying VibrationalCommunication (ed R B Cocroft M Gogala P S M Hill and A Wessel) pp93-123 Berlin Heidelberg Springer

Warkentin K M (2005) Howdo embryos assess risk Vibrational cues in predator-induced hatching of red-eyed treefrogs Anim Behav 70 59-71

Wood T K (1976) Alarm behavior of brooding female Umbonia crassicornis(Homoptera Membracidae) Ann Entomol Soc Am 69 340-344

Wood T K and Dowell R (1985) Reproductive behavior and dispersal inUmbonia crassicornis (Homoptera Membracidae) Florida Entomol 68 151-158

Yovel Y Falk B Moss C F Ulanovsky N and Ulanovsky N (2010) Optimallocalization by pointing off axis Science 327 701-704

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locomotion (Kramer and Mclaughlin 2001) with clearly definedsampling points (Legendre et al 2012) the key locations formeasuring vibrational cues can be identified The accuracy andefficiency of searching (and likewise the efficacy of signals Endler1992) can be quantified precisely because the available movementpaths are constrained by the structure of the plant and the targetlocation is known However although some likely cues for vibrationlocalization have been experimentally tested (reviewed in Hager andKirchner 2014 Virant-Doberlet et al 2006) some search pathsquantified (Legendre et al 2012) and some vibration gradientsexamined for their effect on male behavior (Polajnar et al 2014) nostudies have integrated entire search paths with measurement of theavailable vibrational cues at each sampling location to relate sensoryinput to motor outputWe studied movement decisions during mate searching in the

thornbug treehopper [Hemiptera Membracidae Umboniacrassicornis (Amyot amp Serville 1843)] Mate localization inthornbugs occurs through a back-and-forth exchange of plant-borne vibrational signals or duet between a searching male and astationary female Search efficiency is important for male matingsuccess thornbugs occur at high densities (Wood and Dowell1985) and female thornbugs mate only once with the first male toarrive during their narrow window of receptivity (Cocroft andMcNett 2006) Male movement decisions are one-dimensional(forward or back along a stem) and are based on identifiablesampling locations searching males walk along plant stemsperiodically stop to signal and elicit a female reply then continueforward or turn around Source localization through duetting thuscombines features of both echolocation and beacon-guided searchas with echolocation males obtain information about the target byproducing a signal however rather than relying on physicalreflections the lsquoreflectionrsquo is a signal produced by a stationaryreceiver Duetting is thus an active sensing strategy in which thesensory flow ndash transmitted signals from the source ndash is shaped by thepositions at which males decide to stop the number of signals theyproduce there and the signaling decisions of the femaleWe analyzed the movement decisions of male thornbugs in three

stages We first characterized their search paths asking howmovement decisions and accuracy changed over the course of thesearch We then investigated the vibrational cues correlated withmovement decisions and asked how variation in those cuesinfluenced sampling behavior and accuracy Finally we combinedthe information from all of the searches to obtain an overview of thevibrational gradients encountered by the searching insects

MATERIALS AND METHODSStudy systemThornbug treehoppers are sap-feeding insects that use vibrationalcommunication throughout their lives (Cocroft 1999 De Luca andCocroft 2008 Hamel and Cocroft 2012 Ramaswamy and Cocroft2009) Their host plants are woody shrubs and trees in theMimosaceae Most individuals grow to adulthood in a siblingaggregation of 50ndash100 individuals (Cocroft 2002) and whenfemales oviposit near other females the communal aggregationsmay be much larger Some females mate before dispersing from thenatal aggregation whereas others mate after dispersing (De Lucaand Cocroft 2008) Males disperse before females and either locateand remain with a pre-dispersal aggregation of females or search fordispersed unmated females Searching males use a call-fly strategyto locate a host plant with a receptive female and vibrationalduetting to locate the female within the plantWe studied thewithin-plant phase of mate searching

Animal careWe drew the study animals from a greenhouse colony at theUniversity of Missouri (Columbia MO USA) which weestablished with collections from in and around Miami FL USA(USDA APHIS permit P526P-10-03348) Thornbugs have three tofour generations per year in the greenhouse we maintained anoutbred colony by mating individuals with non-siblings and byintroducing new individuals from the field every three generationsFamily groups collected from the field contained late-instar nymphsandor teneral adults Each family was maintained on its ownpotted host plant (Mimosaceae Albizia julibrissin or Lysilomalatisiliquum) which was covered with a screen cage Approximately1 week after the adult molt the sexes were separated to preventsibling mating The colony was maintained on a 14 h10 h lightdarkcycle with a temperature range of 27ndash32degC (day) and 21ndash24degC(night) at 60ndash70 humidity

Experimental designOur goal was to obtain path data for searching males duettingwith stationary females then annotate the path by obtainingenvironmental information at each of the malesrsquo sampling points(Fig 1) Obtaining the necessary vibration measurements requiredseveral minutes for each point on the plant (see below) so it was notpossible to make those measurements in real time during a malersquossearch For each pair of insects then our characterization of searchpaths proceeded in two phases First after introducing the insectsonto a plant we plotted the malersquos sampling locations on a map ofthe plant and videorecorded the entire search while recording theduetting signals of the pair using a single stationary transducerSecond we removed the male before it reached the female or after15 min then used two lasers to measure stem vibration at each pointsampled by the male during the search Female signals were evokedas needed by playing back male vibrational signals Theexperimental data thus consisted of (1) variables measured fromthe original duet signaling behavior (timing duration) and malemovement information (location versus time) and (2) variables thatwere a proxy for vibrational signals experienced by the male duringits search signal amplitude spectral content and two-dimensionalmotion of the stem To ensure that the proxy measurements were asclose as possible to the signals experienced by the searching malewe only used trials in which the female was stationary during theentire search and post-search recording period This criterionensured that the signal transmission path was virtually identicalbetween the original search and the post-search recordings

We conducted n=16 trials each with a unique pair of unrelatedindividuals drawn from 10 family groups We selected experimentalindividuals haphazardly from their family group and did notuse individuals more than once We chose two sim1 m tall pottedL latisiliquum plants (woody hosts with multiple side branches seeResults and Fig S1 for branching structure) on which to observesearches Using only two hosts allowed us to estimate the effect ofplant differences while obtaining a detailed map of the structure ofthe individual plants We conducted eight trials on each plant fourwith the female on a stem near the top of the plant and four with thefemale on a stem near the bottom of the plant (see Results andFig S1 for female locations) Each male was placed at the samestarting location on a given plant sim40 cm from the female(measured along the stem) on a side stem roughly equidistantfrom both female positions Males began signaling either at theirinitial location or after walking a few centimeters along the stem

Treehoppers are not known to use chemical cues during within-plant searches and playback studies have shown that localization

2


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Annotatedsearch

ActionPerception

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Signalexchanges



1

1

10140

0

1

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1

0

1

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25

kHz

Time (s)

Time (s)

Time (s)

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10Frequency (kHz)Ve

loci

ty (m

sndash1

)Fr

eque

ncy

(kH

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m s

ndash1)


Axis of stemmotion



42 s


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A B

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4


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40ndash60

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075

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porti

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orre

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5

4

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Tim

e to

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e (m

in)


100

075

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A

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D

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7


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Apical Basal

Plant 2

Am

plitu

de (d

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1 m

m s

ndash1)

Prop

agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

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Annotatedsearch

ActionPerception

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Signalexchanges



1

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0

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Time (s)

Time (s)

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loci

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(kH

z)(m

m s

ndash1)


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42 s


3


Journal

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A B

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Stem

Stem

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4


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5


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A B

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40ndash60

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porti

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Tim

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100

075

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10

075

025

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0-30 -20 -10-40


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A

B

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D

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7


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m s

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agat

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velo

city

(m s

ndash1)

Plant 1

A B

minus5

minus10

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70

65

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4


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5


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A B

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100

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porti

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5

4

3

2

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Tim

e to

loca

te fe

mal

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in)


100

075

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on c

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025

0


6


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025

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ecis

ion

10

075

025

05

0-30 -20 -10-40


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dict

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bilit

y g

oing

forw

ard

A

B

C

D

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7


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ofEx

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8


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Apical Basal

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de (d

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1 m

m s

ndash1)

Prop

agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

minus5

minus10

minus15

minus20

minus25

minus30

minus35

minus40

minus45

70

65

60

55

50

45

40

35

30

25


9


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B

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7


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8


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Apical Basal

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1 m

m s

ndash1)

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agat

ion

velo

city

(m s

ndash1)

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A B

minus5

minus10

minus15

minus20

minus25

minus30

minus35

minus40

minus45

70

65

60

55

50

45

40

35

30

25


9


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4

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2

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Tim

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075

025

05

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dict

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bilit

y g

oing

forw

ard

A

B

C

D

E


7


Journal

ofEx

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entalB

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8


Journal

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Apical Basal

Plant 2

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1 m

m s

ndash1)

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agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

minus5

minus10

minus15

minus20

minus25

minus30

minus35

minus40

minus45

70

65

60

55

50

45

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35

30

25


9


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11


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12


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13


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10

075

025

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dict

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ion

10

075

025

05

0-30 -20 -10-40


Pre

dict

ed p

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bilit

y g

oing

forw

ard

A

B

C

D

E


7


Journal

ofEx

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entalB

iology


















8


Journal

ofEx

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iology





Apical Basal

Plant 2

Am

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de (d

B re

1 m

m s

ndash1)

Prop

agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

minus5

minus10

minus15

minus20

minus25

minus30

minus35

minus40

minus45

70

65

60

55

50

45

40

35

30

25


9


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ofEx

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10


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11


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12


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13


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8


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Apical Basal

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de (d

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1 m

m s

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Prop

agat

ion

velo

city

(m s

ndash1)

Plant 1

A B

minus5

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Apical Basal

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Prop

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city

(m s

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Documents

Vibration-guided mate searching in treehoppers ...Vibration-guided mate searching in treehoppers: directional accuracy and sampling strategies in a complex sensory environment Jeremy