DOI: 10.5061/dryad.t1g1jwt5d
title: Onthophagus babirussa sexual size dimporphism and male sexual trait files and R codes

description: Sexual size dimorphism (SSD) arises when natural selection and sexual
 selection act differently on males and females. Male-biased SSD is rare in
 insects and usually indicates strong selection pressure on a population or
 species. Patterns of SSD can also vary between populations of species that
 are exposed to different environmental conditions, such as differing
 resource availability and diversity. Here, we investigate intra-specific
 variation in SSD as well as relative investment in precopulatory (horn
 length) and postcopulatory traits (sperm length and testes weight) in a
 tropical rainforest dung beetle Onthophagus babirussa across Singapore and
 Peninsular Malaysia. Overall, three out of four populations displayed
 significant male-biased SSD and SSD was greater in populations with
 smaller overall body size. Average male body size was similar across all
 populations while female body size was significantly smaller in Singapore,
 suggesting that the pronounced SSD may also be due to stronger sexual
 selection on male body size in Singapore populations. All populations
 showed significant investment in horns as a weapon used in precopulatory
 competition, while postcopulatory traits showed no clear scaling
 relationship with body size, suggesting a higher priority on precopulatory
 sexual traits in the mating system of this species.
description: 2.1.1 Study
 Sites Dung beetles examined in this study were sampled
 in SG and MY. Figure 1 depicts a map of all sampling sites, and a full
 list of coordinates are appended in a supplement to the main manuscript
 (Appendix 1: Table S1). Sampling in SG spanned over fifteen months from
 August 2018 to February 2018 and May 2019 to December 2019. Specimens from
 MY were sampled across four sites, Perak, Gombak, Kenyir and Langkawi,
 from August to November 2016, as well as in July 2019. Beetles from sites
 A, B, C and D were pooled because these sites were part of a continuous
 stretch of forest in the central region of SG. Pulau Ubin is an island
 separate from mainland SG and was treated as a population on its own.
 Sites G, H and I were pooled as they were all mainland MY sites with
 connected forests. Langkawi is an island separate from mainland MY and was
 also treated as its own population. Thus, for all analyses, specimens were
 separated into four populations – Central Catchment Nature Reserve on
 mainland SG (Central Catchment SG), Pulau Ubin (Pulau Ubin Island SG),
 central MY (Central Peninsular MY), and Langkawi (Langkawi Island MY).
 Literature search was conducted to compile a checklist of non-volant
 mammal species present in each of the four study sites with species body
 size and consumer type, and these are presented and summarised in the
 appendix (Appendix 1: Tables S2 and S3). 
  2.1.2 Sampling and sorting
 protocol Dung beetle sampling was conducted using baited
 pitfall traps and baited funnel pitfall traps with human dung as the bait
 because it is widely accepted to be the best bait to attract a wide
 variety dung beetles (Howden & Nealis, 1975; Kudavidanage et al.,
 2012; Larsen & Forsyth, 2005). Exact details of trap materials and
 construction are appended (Appendix 1, Figure S1). Traps were retrieved
 after 24 to 48 hours, and captured beetles were brought back to the
 laboratory for morphological identification and sorting using an Olympus
 SZX10 microscope. Onthophagus babirussa were separated from other species via
 sorting by morphological characters (see Appendix 2, Figures S2 &
 S3) and DNA barcoding. Specimens used for DNA barcoding were killed and
 preserved in 70% molecular grade ethanol. DNA was extracted from 739
 specimens from Singapore populations (CCNR=129 and Pulau Ubin=167) and
 Malaysian populations (Central Peninsular MY=109 and Langkawi=334). For
 these specimens, the right mid femur was dissected into 7 μl of
 QuickExtract solution and the DNA was extracted by following the
 manufacturer’s protocol (Lucigen, 2018). Then, 313bp fragments of the COI
 gene were amplified via PCR (see Appendix 2 for detailed protocol), sent
 for Next Generation sequencing (NGS) and used for DNA barcoding.
 Sequence analysis was then
 conducted with reference to the analysis pipeline detailed
 by (Meier et al., 2016),
 and a well-established 3%
 threshold for uncorrected pairwise distances was used to delimit different
 species (Hebert et al., 2003; Meiklejohn, Wallman, & Dowton, 2011;
 Srivathsan & Meier, 2012). All specimens examined in this study
 fell within the same molecular cluster under this 3% threshold, and a
 cluster fusion diagram with representatives from each population is
 appended in Appendix 2 (Figure S4), along with the full protocol for
 morphological and molecular sorting. The molecular barcodes were congruent
 with our morphological sorting and general consensus with the geographical
 sampling. 2.3. Documenting reproductive trait
 variation 2.3.1 Precopulatory trait measurements
 To
 investigate the sexual size dimorphism in the four populations of O.
 babirussa, maximum pronotum width (Figure 2) of males and females were
 measured as a proxy for body size with the eyepiece reticle on the Olympus
 SZX10 microscope. This is widely used proxy for body size because the
 pronotum width does not change in adulthood and has been found to be the
 most appropriate measure for body size in dung
 beetles (Emlen, 1997;
 Knapp & Knappová, 2013).  Horn lengths of
 male O. babirussa (Figure 2) were measured to document variation in this
 precopulatory trait. Images were taken of the anterior habitus. Heads of
 the beetles were separated and suspended with Durex KY Jelly, with horns
 aligned parallel to the lens of the camera. Images were captured using the
 EOS 800D and 6D camera body with the Canon MP-E 65mm f/2.8 1-5x lens
 at 5x optical zoom. The camera was suspended on the Dun, Inc. P-51 and
 the Camlift controller V2.9.3.0 software was used to take multiple
 images at different heights for focus stacking.  EOS Utility Launcher
 software was used to access the images and stack them using
 the Zerene Stacker V. 1.04. software. Stacked images were imported to
 Adobe Photoshop CS5 V. 12.0 x64 and a 1mm scale bar was added to each
 image. Next, processed images were imported to ImageJ V. 1.51 and the
 horns were measured from the tip to the bottom of the outer edge of each
 horn, following previous studies (Moczek & Emlen,
 1999). 2.3.2 Postcopulatory trait measurements of male
 specimens Abdomens of male O. babirussa specimens were
 dissected into 1x phosphate-buffered solution (PBS) to measure the
 following postcopulatory traits: testes weight and sperm length (Figure
 2). Testes were isolated and transferred onto pre-weighed aluminium sheets
 and dried in a Memmert Gravity Basic Digital Oven D overnight. Then, total
 weight was measured on the Mettler Toledo ML104 Newclassic ml Analytical
 Balance. Weight of the testes were calculated by subtracting the weight of
 the aluminium sheet from the total weight. 
 To measure the sperm length,
 seminal vesicles containing the mature sperm were first isolated and
 transferred onto a drop of PBS on a frosted slide. Then, sperms were
 teased out from the vesicles using an insect pin. Slides were dried in the
 oven and sperms were fixed onto the slides with a solution of three parts
 methanol and one part acetic acid for two minutes. Next, the slides were
 washed in 1x PBS for one minute and the sperms were stained for five
 minutes in the dark with 4′,6-diamidino-2-phenylindolev (DAPI),
 which binds to DNA to form a fluorescent complex to allow for
 visualisation of sperm heads under a fluorescent microscope. Following
 that, the slides were washed in 1x PBS and placed in the dark to dry. When
 the slides were dried completely, one to two drops of glycerol were added
 on the stained regions, coverslips were placed, and the edges were sealed
 with clear nail polish and left to dry in the dark. The sperms were
 visualized using an Olympus BX50 fluorescence microscope and measured
 using μManager and ImageJ V. 1.51 software. Based on previous studies,
 five to ten sperms were measured per specimen (García-González & Simmons, 2007;
 Simmons & Kotiaho, 2002; Werner & Simmons,
 2011).
 2.4.
 Statistical analyses Box plots of average pronotum width were
 constructed with confidence intervals using the R packages ggplot2
 (Wickham,
 2016), dplyr
 (Wickham et al.,
 2020) and plotrix
 (Lemon,
 2006) and
 tested for significance in body size difference between the
 sexes within each population using ANOVA, checking the residuals for
 normality after. To test if SSD varied between populations, we ran linear
 models testing for significant sex by location interaction. Post-hoc analyses using Dunn test were also
 conducted to determine which populations differ from the other for male
 and female body size.  In addition, the sexual dimorphism index (SDI) was
 calculated for each population following the formulation by Gibbons and
 Lovich (1990), where the mean size of the larger sex is divided by the
 mean size of the smaller sex. A negative sign is arbitrarily added to the
 SDI as the males are larger (Gibbons and Lovich,
 1990).  To determine whether populations differed with
 respect to relative investments in precopulatory and
 postcopulatory traits, the static allometries were calculated
 by first constructing log-log scatterplots of trait size against pronotum
 width. As the log-log scatter plot of horn length against pronotum width
 displayed a clear non-linear relationship, we followed the recommendations
 by Knell
 (2009) and Parrett et al.
 (2021) and fitted (1)
 linear model, (2) quadratic model, (3) cubic model and (4) breakpoint
 model using the R package segmented (Muggeo, 2008) to the pooled data with all
 four populations to characterise the trait size-body size
 relationship Figure 3). Model selection was then conducted with the Akaike
 information criterion (AIC). The breakpoint model had
 the lowest AIC score for horn length (Table 1), indicating that this model
 is the best model for explaining the relationship between the variables
 (Knell,
 2009). Following this,
 allometries were also calculated for the overall data separated by 1)
 population, and 2) minor or major morphs as determined by the breakpoint
 models applied to each population (see Appendix 3, Figure
 S5).
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