DOI: 10.5061/dryad.4qrfj6q7c
title: The evolution of startle displays: a case study in praying mantises

description: Anti-predator defences are typically regarded as static signals that
 conceal prey or advertise their unprofitability. However, startle displays
 are performed by prey when attacked and can include a spectacular array of
 movements, colours, and sounds. Here we present the first
 phylogenetically-controlled comparative analyses of startle displays
 including behaviour, using praying mantises as a test case. For 58
 species, with a dated phylogeny, we estimate the strength of phylogenetic
 signal in the presence and ‘complexity’ (number of display components) of
 displays and their components and test hypotheses on their evolutionary
 correlates including primary defence and body size. We report strong
 phylogenetic signal in display presence and complexity, and strong
 lability in behavioural, but not morphological, components. Body size
 correlates with display presence and complexity independently of
 phylogeny, but not in phylogenetically-controlled analyses. Finally,
 species in species-rich clades are more likely to have a display, and a
 more complex one, suggesting support for ecological displacement via
 behavioural traits. To further elucidate the conditions under which
 startle display evolve, future work should include quantitative
 descriptions of display components, habitat type, and predator
 communities. Understanding the evolution of startle displays enriches our
 overall understanding of predator-prey dynamics and provides scaffolding
 for the development of new theory.
description: Startle display and primary defense data
 Studies on mantis displays can be found in publications from
 several decades (Varley, 1939; Crane, 1952; Maldonado, 1970; Edmunds,
 1972, 1976; Pita, 1972; Loxton, 1979; Grandcolas &
 Desutter-Grandcolas, 1998; O’Hanlon <i>et al.</i>, 2018).To
 generate our dataset, we searched Web of Science and Google Scholar for
 all published descriptions of praying mantis startle displays. Search
 terms were: defensive display, deimatic, startle, antipredator,
 frightening attitude, praying mantis, praying mantid, and Mantodea. Six
 papers and the observations of scientists therein provided sufficiently
 detailed accounts of the displays or lack thereof. Nine species were
 scored based on personal observations of scientists currently working in
 the field of praying mantis behaviour (G. Holwell, K. Barry and J.
 O’Hanlon). In total, we gathered behavioural descriptions for 58 praying
 mantis species, with each species representing a different genus across
 the Mantodea. Our data therefore represent approximately 13% of mantis
 diversity at the generic level. We scored the description of the species’
 primary defense, i.e. camouflage, as crypsis or masquerade, based on the
 descriptions of ‘general resemblance’ and ‘special resemblance’
 respectively by Edmunds (Edmunds, 1972, 1976) and the overall shape of the
 mantis (e.g. ‘mantis shaped’, ‘dead leaf shaped’, etc.) in accordance with
 the conceptual framework outlined by Skelhorn et al (2010b).
 We scored the presence of a display as whether the display
 behaviour had been witnessed first-hand by a scientist and/or a
 description published. We scored absence of display if the species had
 been explicitly reported to lack a display despite being exposed to the
 same stimuli as those reported to have a display (Edmunds, 1972,
 1976). For species with a display (N = 31), we scored
 the presence and absence of seven components, four behaviours and three
 colour patterns: (1) wings display – wings raised during the display, (2)
 arms display – arms raised during the display, (3) mouth display – if the
 mouth is opened during the display, (4) sound – display includes sound
 (e.g. rustling wings not related solely to raising the wings), (5) wing
 colours – wings have contrasting colour markings or ‘eyespots’ that are
 revealed or highlighted during the display, (6) arm colours – raptorial
 forelimbs have conspicuous colours or ‘eyespots’ that are revealed or
 highlighted during the display, (7) abdomen colours – part of the abdomen
 revealed during the display has a contrasting colour. Display complexity
 was the unweighted sum of these traits with a maximum possible complexity
 score of seven. Body size and shape data
 To compile the dataset of mantis body size, we took size data
 from seven publications and in addition, directly measured 294 specimens
 from 49 species kept in the collections of the Cleveland Museum of Natural
 History and the National Museum of Natural History (Smithsonian
 Institution). We took three measurements of body size in both males and
 females for each species in the data set where specimens were available:
 body length, pronotum length, and forewing length (Supplementary Figure
 1). We took an average for each measurement from a variety of sample
 numbers per species. From these measures we created four further
 variables: ‘flight capacity’ (forewing length divided by body length,
 larger values indicate larger wings relative to body length and thus
 greater likelihood of flight), ‘size dimorphism’ (female body length minus
 male body length, positive values indicate females larger than males), and
 ‘flight dimorphism’ (male flight capacity minus females flight capacity,
 positive values indicate male have larger wings per unit body size than
 females). Mantis phylogeny and timetree
 estimation A total of 94 praying mantis taxa were
 selected (Supplementary Table 1) from tree topologies recovered in prior
 studies [1–8]. Four outgroup taxa were selected from Blattodea [3]. The
 selected taxa provided broad taxonomic and clade specific representation
 that also allowed collection of attribute data used to test the hypotheses
 of this study. A total of 10 gene fragments were included, all of which
 have proven to be phylogenetically informative at multiple levels of the
 Mantodea phylogeny [1–8]. These genes are 12S rRNA, 16S rRNA, 18S rRNA,
 28S rRNA, Cytochrome Oxidase I (COI), Cytochrome Oxidase II (COII), NADH
 dehydrogenase subunit 4 (ND4), Histone 2A (H2A), Histone 3 (H3), and
 Wingless (wnt-1) (see Supplementary Table 1 for GenBank accession
 numbers). For all included taxa, but one with newly
 sampled data, sequences were downloaded from GenBank (NCBI) and imported
 into Geneious v7.1.4 for 10 loci (Supplementary Table 1). The new sequence
 data (<i>Negromantis</i> sp.) was generated in the Cleveland
 Museum of Natural History DNA Laboratory. Thoracic and coxal muscle tissue
 was excised from specimens and extracted using the Qiagen DNeasy protocol
 for animal tissue. Specimen and DNA vouchers and template are deposited in
 the Department of Invertebrate Zoology at the Cleveland Museum of Natural
 History (CMNH). New sequence data from four gene loci were generated
 previously, but not published until this study (GenBank accession numbers
 in Supplementary Table 1), using well-established protocols for
 amplification, gel verification, amplicon purification, and sequencing
 [2,3,7]. Gene regions were sequenced with complements and sufficient
 overlap with adjacent regions to ensure the accuracy of sequence
 data. Gene fragments were aligned in Geneious v7.1.4
 using MAFFT v7 [9] and reading frame was determined for coding genes. We
 used SequenceMatrix v1.7.8 [10] to concatenate the matrix for a dataset
 including 10207 characters. We used PartitionFinder v2.1.1 [11,12] to
 determine partitioning strategy and models. A total of 22 partitions were
 input based on gene and codon position with the BIC and greedy settings
 for model selection and search strategy, respectively. Four partitions
 were recovered, each using the GTR+I+G model: 1) 12S, 16S, ND4_pos1,
 ND4_pos3, 2) 18S, 28S, H2A_pos1, H2A_pos2, H2A_pos3, H3_pos1, H3_pos2,
 H3_pos3, wnt_pos1, wnt_pos2, wnt_pos3, 3) COII_pos3, COI_pos3, and 4)
 COII_pos1, COII_pos2, COI_pos1, COI_pos2, ND4_pos2. We
 conducted a mixed-model maximum likelihood (ML) analysis using RAxML v8
 [13] with partitions corresponding to PartitionFinder results. One
 thousand non-parametric bootstrap (BS) pseudoreplicates were performed
 under a GTRGAMMA. We also conducted a mixed-model MrBayes v3.2.3 [14]
 analysis using PartitionFinder results by implementing four independent
 runs (four chains each) for 40 million generations. Each Bayesian run was
 started from a random tree and subsequently monitored for convergence
 using the program Tracer v1.7.1 [15]. Specifically, the plots for each run
 for sampled generations (every 1000) were compared using mean likelihoods,
 standard deviations, and distribution plots to ensure they converged on
 the same distribution after the burn-in. Bayesian analyses were performed
 on the Cyberinfrastructure for Phylogenetic Research (CIPRES) Science
 Gateway[16]Sampled trees were used to calculate a 50% majority rule tree
 to determine posterior probabilities (PP) [17]. FigTree v1.4.4 [18] was
 used to visualize topologies and produce figures for both ML and Bayesian
 analyses. We used the Bayesian output tree as a start
 tree to estimate divergence times using a lognormal uncorrelated
 relaxed-clock model of among-lineage rate variation in BEAST v1.8.3 [19].
 Like the Bayesian analysis, we utilized the CIPRES Science Gateway to run
 BEAST. We applied an exact root height with the mean set at 197 and the
 standard deviation set to 20 based on root dates recovered consistently in
 prior studies, which used significantly expanded taxon sampling or
 datasets along with multiple fossil calibrations [3,20,21]. We chose this
 method of calibration because of the lack of an adequate fossil record
 capable of calibrating later diverging nodes in the phylogeny [22–24] and
 it simply recovered a consistent phylogenetic tree scaled to time
 (timetree) that can address our evolutionary questions rather than
 addressing fundamental questions about the temporal origins of lineages
 [8]. Based on PartitionFinder results, we assigned all four partitions the
 GTR+I+G model. We executed two independent runs using the Yule process
 [25] for the tree prior. Trees were sampled every 1,000 generations over
 10 million generations. Tracer was used to monitor convergence across
 runs. We used LogCombiner v1.8.3 to process log and tree files.
 TreeAnnotator v1.8.3 was used to produce a maximum clade credibility tree
 (25% burn-in) with median node heights with upper and lower
 confidence-interval (CI) values.