DOI: 10.5061/dryad.sf7m0cgdr
title: Data from: Male-female chemical interactions in a facultatively parthenogenetic stick insect

description: Facultative parthenogenesis is a form of reproduction in which females can
 either lay unfertilised eggs that typically develop into female offspring
 only, or mate and lay fertilised eggs that develop into male and female
 offspring. Facultative parthenogens often occur in mixed-sex
 populations where reproduction is mostly sexual, and all-female
 populations where reproduction is asexual. How all-female populations
 avoid invasion by males remains unknown. Here, we
 investigated the role of volatile and non-volatile (cuticular
 hydrocarbons, CHCs) pheromones in the persistence of all-female
 populations in the facultatively parthenogenetic stick
 insect, Megacrania batesii. We found that M. batesii exhibits
 slight sexual dimorphism in antenna morphology, and
 behavioural assays provided little evidence that males could
 locate females solely by volatile pheromones. However, CHC profiles
 differed substantially between different types of
 females. Analysis of CHC structure and
 abundance indicated a clear genetic difference between females
 from all-female versus mixed-sex populations, as well as a maternal
 effect of female parthenogenesis versus sexual development.
 Together, our results suggest that males might rely more
 on close-range chemical cues to differentiate females, and chemical
 communication could play a role in the persistence of
 all-female populations.
description: <em>Animal maintenance</em>
 Individuals for all experiments were offspring derived from
 hatchlings or eggs collected from mixed-sex and all-female populations in
 northern Queensland between 2019 and 2022. All males and females from
 mixed-sex populations were collected from populations of the northern
 genotype, whilst females from all-female populations were collected from
 populations of the southern genotype. Hatchlings were first group-reared
 with up to four siblings on a live <em>Pandanus
 tectorius</em> host plant, then housed separately in a cylindrical
 plastic container (height = 39.5 cm, radius = 10 cm) covered with a mesh
 lid. The insects were all kept at approximately 27°C, with humidity of
 around 40%, and they were sprayed with reverse-osmosis water
 daily. Individuals housed without live plants were fed cut
 <em>Pandanus</em> leaves, which were replaced three times a
 week. All individuals used in experiments were reproductively mature
 adults. The paternity of individuals were manipulated by the control of
 mating status of their mothers. <em>Antenna
 morphology</em> To test for sexual dimorphism in
 antennal morphology, antenna static allometry and sensilla density were
 quantified in the two sexes. Antenna static allometry was quantified by
 measuring antenna and body size on digital photos of paternate northern
 males and females (40 individuals of each sex). Static allometry refers to
 the scaling relationship between a log-transformed trait (i.e., antenna)
 size and body size. Thorax length (measured from the anterior margin of
 the prothorax to the posterior margin of the mesonotum) was measured as a
 proxy for body size. Length of the entire antennae (from the first to the
 last antennomere) was measured in each individual. We included only one
 antenna per individual in the analyses: using only intact antennae, and
 selecting the longer of the two when both antennae were intact.
 To compare sensilla density between paternate northern males and
 females, we removed one intact antenna from each individual (20 males and
 20 females, which were all euthanised and kept in a -80°C freezer until
 the investigation). We used intact antennae only, selecting the longest of
 the two when both antennae of a specimen were intact. We took photos of
 the last antennomere using a camera (Leica, Flexacam C1) mounted on a
 stereo-microscope (Leica, MZ 16 A) at a magnification of 90x. Sensilla
 density was observed to increase from the base to the tip of the antenna,
 so we assumed that the last (i.e., most distal) antennomere had the
 highest density of sensilla. We used the densest part of the antenna
 because it effectively indicates olfactory sensitivity. We counted the
 number of sensilla (visible as bumps on the antenna surface) inside a
 randomly selected rectangular area (size approximately from 0.025 to 0.03
 mm<sup>2)</sup> on each antenna, and we divided the number of
 sensilla by the area of the rectangle to estimate sensilla density. We
 also measured the length of the last 20 antennomeres of these antennae to
 test for potential covariation of antenna length with sensilla density.
 All image measurements were performed in imageJ.
 <em>Volatile p</em><em>heromone behavioural
 experiment</em> To test whether males respond to
 olfactory cues from females, we placed males in an open arena with hidden
 females and measured their activity levels and attraction to females. We
 ran two types of trials: North-South trials (impaternate northern females
 versus impaternate southern females) to test for genetic effects, and
 paternate-impaternate trials (impaternate northern females versus
 paternare northern females) to test for maternal effects. The equilateral
 triangular arena comprised four areas, including three smaller triangles
 at the corners (hereafter referred to as zones). Each zone contained a
 black mesh opaque hood (height = 49 cm, radius = 15.3 cm, mesh size = 0.15
 mm<sup>2</sup>) with a smaller mesh container (height = 39.5
 cm, radius = 10 cm, mesh size = 1.8 mm<sup>2</sup>) inside. In
 each trial, one of the three containers was empty (control), and the other
 two contained one female each. The black mesh hoods were used to prevent
 the use of visual cues by males but allow female volatiles to disseminate
 throughout the arena. The position of the containers was randomised for
 every trial to control for the effect of position. Each trial commenced
 when a focal male was placed on top of a plastic cylinder in the middle of
 the arena. The arena was continuously video-recorded
 using tablets (Samsung T580) for 12 hours under red ceiling lights, during
 the night. We ran the trials at night because this is when these insects
 are most active. We put sackcloth on the arena floor to mimic rough
 topsoil and to make it easier for males to walk between zones, and we
 watered the arena, hoods and containers before every trial to increase
 humidity. Two trials (one of each type) were performed simultaneously in
 two identical controlled-temperature rooms (27°C) four nights per week,
 over seven weeks, alternating which trial type (North-South trials and
 paternate-impaternate trials) was in which room. The arenas had constant
 air-flow through vents on the ceiling (six air changes per hour) so that
 there was air movement for the focal males to follow pheromone plumes. The
 floor area of each room was 12 m<sup>2</sup>. All individuals
 were well fed on the day before the trial. No
 <em>Pandanus</em> leaves were placed in the arenas to avoid
 males reacting to the smell of the leaves or the sound of
 feeding females, rather than to the smell of the females.
 We measured the total time spent by the focal male in each zone,
 the time from the start of a trial until the male first reached each
 container (latency), and the total number of visits to all zones in one
 trial. We performed 30 trials for each trial type, using 16 paternate
 northern females, 17 impaternate northern females, 17 impaternate southern
 females, and 31 males in total. 29 of the males were used in both trial
 types, and each of the two remaining males was only used in one of the
 trial types. Individuals were reused in a subsequent trial after a minimum
 of three days from the previous trial. We randomised which trial type each
 male underwent first. Most paternate northern and impaternate southern
 females were used twice, whilst most impaternate northern females were
 used a total of four times (twice in each trial type). We were not able to
 standardise the mating status of all individuals used in this experiment,
 so we compared mated females to mated females, and unmated females to
 unmated females in each North-South trial to eliminate the effect of
 mating status. However, in paternate-impaternate trials, mated paternate
 northern females were compared with unmated impaternate southern females
 in 21 out of 30 trials. Our experiment might have therefore underestimated
 male preference for paternate females if males also preferred unmated
 females. <em>CHC
 </em><em>extraction</em> After all
 behavioural assays had been completed, four females from each type were
 frozen at -80°C. Males used in the CHC assay were euthanised by freezing
 at the same time as females but were not involved in the behavioural
 assays described above. All individuals had mated at least once and were
 stored in a -80°C freezer until CHC extraction. Prior to immersion for CHC
 extraction, all individuals were thawed for 10 minutes at room
 temperature. Whole insect immersion in hexane is the most common way to
 extract pheromones from small insect species, but given the relatively
 large size of <em>M. batesii</em>, a custom procedure was used
 to extract their CHCs. Each individual was placed in a cylindrical flask,
 covered with aluminium foil and gently swirled for ten minutes in 5 mL of
 n-hexane (Sigma-Aldrich, Castle Hill, NSW, Australia, product no.
 650552) to ensure the hexane washed over the whole insect. The hexane
 was spiked with 10 micrograms/mL of hexacosane (Sigma-Aldrich,
 product no.241687) as an internal standard. Water was removed from each
 extraction by filtering it through a glass Pasteur pipette packed with
 silane-treated glass wool (Alltech, Australia) and a small amount of
 anhydrous sodium sulphate (AjaxFinechem,
 Seven Hills, NSW, Australia, product no.503-500). Extracts were then
 transferred into 2 mL autosampler vials (Agilent Technologies, Mulgrave,
 VIC, Australia) and stored in a -20°C freezer until chemical
 analysis.  <em>Data analyses</em>
 All data analyses were carried out in R 4.1.3. To examine antenna
 length static allometry and relative antenna length, we built an ordinary
 least-squares (OLS) model using the lme4 package and, for comparison, a
 standardised major axis (SMA) linear model using the smatr package. SMA
 models assume equal error in the measurement of antenna length
 (y-variable) and thorax length (x-variable), so the true allometric slopes
 would not be underestimated, and there would not be bias that could
 produce misleading results when comparing male and female slopes. By
 contrast, an OLS model attributes all error to the y-variable, which could
 be more appropriate if the measurement error in curved antennae exceeds
 the measurement error in straight thoraxes. We conducted an analysis of
 covariance (ANCOVA) for OLS models and a likelihood ratio test for SMA
 models to compare the allometric slopes of the two sexes. The thorax
 length and antenna length were log-transformed, as the trait size-body
 size relationship is assumed to be exponential and log-transformation
 allows the exponent to be estimated as the slope from a linear model. A
 Welch’s t-test was performed to compare sensilla density between the
 sexes, and an ANCOVA was used to identify the relationship between
 sensilla density and antenna length of each sex. Data
 from the pheromone behavioural experiment was analysed using generalised
 linear mixed models with a Gaussian distribution to test for the effect of
 female type on male responses (i.e., time spent in and latency to reach
 each zone) in each trial type separately, using the glmmTMB package. Zone
 type (i.e., the two female types and control) was modelled as the fixed
 effect, male identity as the random effect, and time spent in each zone
 and latency to each zone by focal males as response variables in separate
 models. The amount of time spent in each zone was log-transformed and
 latencies to each zone were square root-transformed to improve the
 distribution of residuals. We excluded 12 North-South trials and eight
 paterante-impaternate trials where the male did not visit any of the zones
 in these analyses. Likelihood ratio tests were performed by comparing each
 full model to the corresponding null model, where the fixed effect was
 removed. A near-significant effect was found for the paternate-impaternate
 trials. We therefore used a post-hoc (Tukey) test to compare the time
 spent in each zone using the emmeans package. Because focal females varied
 in age, which can affect female attractiveness, we also investigated the
 effect of female age (number of days since the adult moult) on male
 response in both trial types, by building generalised linear mixed models
 where female age was modelled as a fixed effect together with zone type.
 Female age and female type (i.e. zone type, excluding the control zone)
 were modelled as the fixed effects. Male identity was modelled as the
 random effect, and male response (i.e. either amount of time spent in
 zones or latency to zones) was the response variable. Amount of time spent
 in each zone and latencies were log-transformed, except for the latencies
 in North-South trials, to improve model fit (based on inspection of model
 residuals). Female age was standardised within female types to remove the
 correlation between female age and female type. All trials were included
 in analyses involving fixed effects of both zone type and female
 age. In addition, we built another generalised linear
 mixed model as an exploratory analysis to investigate the effect of trial
 type on overall male activity (total number of visits to zones). This
 model was fitted with a Poisson distribution and a log link. Trial type
 was modelled as the fixed effect, male identity as the random effect, and
 the total number of visits as the response variable. We included trials
 where the male did not visit any of the zones in this analysis, but
 excluded two outliers, in which the two males made many more zone visits,
 to improve the distribution of residuals. The effect of
 sex and female type on CHC profile was investigated by performing a
 principal component analysis (PCA) of centred log-ratio (CLR) coefficients
 of the proportional peak areas to identify covariation patterns of CHC
 profiles by insect type. CLR transformation was applied to make these
 compositional data suitable for analysis by standard multivariate
 techniques. CHC data is compositional, and different components can
 potentially act synergistically, making it more meaningful to analyse the
 entire profile instead of single components. The peak area of each
 component was first divided by the peak area of the internal standard of
 the corresponding sample to control for differences between sample runs on
 the GCMS. This relative peak area was further divided by the total
 relative peak area of the corresponding sample to avoid confounding body
 size with total CHC amount. CLRs were then calculated by dividing the
 proportional peak area by the geometric mean of the detected peaks in the
 corresponding sample. 10<sup>-17</sup> was added to all
 proportion peak areas before CLR transformation to avoid zero
 values because some peaks were present in only one type of
 insect.
description: # Data from: Male-female chemical interactions in a facultatively
 parthenogenetic stick insect
 [https://doi.org/10.5061/dryad.sf7m0cgdr](https://doi.org/10.5061/dryad.sf7m0cgdr) There are 10 .csv files in total, including "antenna_length.csv", "antennae_sensilla.csv", "pheromone_imp_pat.csv", "pheromone_n_s.csv", "pheromone_ip_wide_zero.csv", "pheromone_ns_wide_zero.csv", "chcs_pca.csv", "chc_pca_cor.csv "chc_clr_pca.csv", and "clr_pca_score.csv". "antenna_length.csv" is the data for investigating the degree of sexual dimorphism in antenna length static allometry. "antennae_sensilla.csv" is the data for investigating the degree of sexual dimorphism in antenna sensilla density. "pheromone_imp_pat.csv" is the data for comparing male responses in paternate-impaternate trials of the volatile pheromone behavioural experiment, and the effect of female age on male response. "pheromone_n_s.csv" is the data for comparing male responses in North-South trials of the volatile pheromone behavioural experiment, and the effect of female age on male response. "pheromone_ip_wide_zero.csv" and "pheromone_ns_wide_zero.csv" are the data for comparing male activity levels across paternate-impaternate trials and North-South trials in the volatile pheromone behavioural experiment. "chcs_pca.csv", "chc_pca_cor.csv", and "chc_clr_pca.csv" are the data for CHC analysis. "clr_pca_score.csv" is the data derived from analysis using "chc_clr_pca.csv", used for visualsing the data. ## Description of the data and file structure In "antenna_length.csv", each row represents one replicate, and each column represents one variable. "individuals_id" is the identity of an individual insect. "throax_cm" is the length of an individual's thorax in cm, measured using imageJ. "left_antenna_cm" is the length of an individual's left antenna in cm. "right_antenna_cm" is the length of an individual's right antenna in cm. "left_antenna_cm" and "right_antenna_cm" were left blank when the corresponding anntenae were not intact. "sex" is the sex of the individual, "F" refers to female, and "M" refers to male. "longest antenna" is the longer of the two antennae. "log.thorax_cm" is the log-transformed thorax length. "log.longest_antenna" is the log_transformed length of the longer of antenna. "proportion" is the proportion of the longer antenna length to thorax length, calculated by "longest_antenna"/"thorax_cm". In "antennae_sensilla.csv", each row represents one replicate, and each column represents one variable. "individual_id" is the identity of an individual insect. "sex" is the sex of the individual, "M" represent male, and "F" represents female. "no_of_segments" is the number of segments (antennomere) in the antenna, from the base segment to the tip segment. "no_of_bristle" is the number of bristle (where a sensilla sticks out) in a drawn window, using imageJ. "antenna_length_mm" is the length of the antenna in mm. "area_mm2" is the area of the drawn window on a segment using imageJ. "density" is the sensilla density of the antenna, calculated by dividing no_of_bristle by area_mm2. In "pheromone_imp_pat.csv" and "pheromone_n_s", each trial has three rows, where one row represents one zone type. Each column represents one variable. "trialtype" is the trialtype, "IP" represents paternate-impatrernate trial, and "NS" represents North-South trials . "trial" is the trial identity within paternate-impaternate trials. "trial_unique" is the unique trial identity across paternate-impaternate trials and North-South trials. "male-id" is the identity of the focal male in a trial. "treatment" is the zone type. "female_id" is the identity of the focal female, left blank in the rows of control zone because there were no females in the control zones. "total_stay" is the total time spent in the zone, left blank when total_stay = 0 to avoid zero inflation in data analysis. "latency" is the time from the start of a trial until the male first reached the zone (i.e., latency). "male_adult_date" is the day the focal male had his adult molt. "female_adult_date" is the day the focal female had her adult molt, left blank for control zones. "male_mating_status" is the mating status of the male. "female_mating_status" is the mating status of the focal female. "trial_date" is the day the trial commenced. "male_age" is the age of the focal male, calculated by "trial_date" minus "male_adult_date". "female_age" is the age of the focal female, calculated by "trial_date" minus "female_adult_age". "no_of_visits" is the number of visits made by the focal male to the zone. "f_visit_yn" and "visit_yn" are whether the focal male visited a female zone (excluding the control zone) and whether the focal male visited any of the zone (including the control zone) respectively. In "pheromone_ip_wide_zero.csv" and "pheromone_ns_wide_zero.csv", each row represents one trial, and each column represents one variable. They have the same information as "pheromone_imp_pat.csv" and "pheromone_n_s", but "pheromone_ip_wide_zero.csv" and "pheromone_ns_wide_zero.csv" are short-formed datasets for comparisons across trials, whilst "pheromone_n_s", but "pheromone_ip_wide_zero.csv" are long-formed datasers for comparisons within trials. "trialtype" is the trialtype, "IP" represents paternate-impatrernate trial, and "NS" represents North-South trials . "trial" is the trial identity within paternate-impaternate trials. "trial_unique" is the unique trial identity across paternate-impaternate trials and North-South trials. "visit_yn" and "female_visit_yn" are whether the focal male visited any of the zone (including the control zone) and whether the focal male visited a female zone (excluding the control zone) respectively. "Y" means that the focal male visited, "N" means that the focal male did not visit. "total_visits" is the total number of visits to all zones in a trial made by the focal male. "male_id" is the identity of the focal male. "male_age" is the number of days from the day the focal male had his adult molt to the day where the trial commenced. In "chcs_pca.csv", "chc_pca_cor.csv", and "chc_clr_pca.csv", each row represents one CHC sample, extracted from one individual. Each column represents an identified peak. "type" is the insect type of the sample: "patn" = paternate northern female, "impn" = impaternate northern female", "imps" = impaternate southern female, "male" = paternate northern male, and "gyn" = putative gynandromorph. In "chcs_pca.csv", "p1" to "p18" are the peak areas of peak 1 to peak 18. In "chc_pca_cor.csv", "p1" to "p18" are the relative peak areas of peak to peak 18, calculated by dividing each peak area by the peak area of the internal standard of the corresponding sample. In "chc_clr_pca.csv", "p1" to "p18" are the centred log-ratio-transformed relative peak areas of peak 1 to peak 18. "clr_pca_score.csv" is derived from the PCA analysis of "chc_clr_pca.csv", each column represents the PCA score of an identified peak, for data visualisation. ## Code/Software We used R for all statistical analysis in the study. There are 5 R scripts in total, including "antenna static length allometry.R", "sensilla density.R", "pheromone behavioural experiment.R", "pheromone female age effect.R", and "CHC analysis.R". "antenna static length allometry.R" is the R script for the investigation of antenna static allometry, by building an ordinary least-squares (OLS) model using the lme4 package and a standardised major axis (SMA) linear model using the smatr package. "sensilla density.R" is the R script for the investigation of antenna sensilla density, by doing a Welch's T test and an ANCOVA. "pheromone behavioural experiment.R" is the R script for the comparison of male responses within trials and across trial types, by doing generalised mixed-model analyses using the glmmTMB package. "pheromone female age effect.R" is the R script for the investigation of an female age effect on male responses in the pheromone behavioural experiments, also by doing generalised mixed-model analyses using the glmmTMB package. "CHC analysis.R" is the R script for investigating the effect of sex and female type on CHC profiles, by performing a principal component analysis (PCA).