Skip to main content
Ecology and Evolution logoLink to Ecology and Evolution
. 2019 Aug 5;9(17):9827–9840. doi: 10.1002/ece3.5524

Evolution and losses of spines in slug caterpillars (Lepidoptera: Limacodidae)

Yu‐Chi Lin 1, Rung‐Juen Lin 1, Michael F Braby 2,3, Yu‐Feng Hsu 1,
PMCID: PMC6745677  PMID: 31534697

Abstract

Larvae of the cosmopolitan family Limacodidae, commonly known as “slug” caterpillars, are well known because of the widespread occurrence of spines with urticating properties, a morpho‐chemical adaptive trait that has been demonstrated to protect the larvae from natural enemies. However, while most species are armed with rows of spines (“nettle” caterpillars), slug caterpillars are morphologically diverse with some species lacking spines and thus are nonstinging. It has been demonstrated that the evolution of spines in slug caterpillars may have a single origin and that this trait is possibly derived from nonstinging slug caterpillars, but these conclusions were based on limited sampling of mainly New World taxa; thus, the evolution of spines and other traits within the family remains unresolved. Here, we analyze morphological variation in slug caterpillars within an evolutionary framework to determine character evolution of spines with samples from Asia, Australia, North America, and South America. The phylogeny of the Limacodidae was reconstructed based on a multigene dataset comprising five molecular markers (5.6 Kbp: COI, 28S, 18S, EF‐1α, and wingless) representing 45 species from 40 genera and eight outgroups. Based on this phylogeny, we infer that limacodids evolved from a common ancestor in which the larval type possessed spines, and then slug caterpillars without spines evolved independently multiple times in different continents. While larvae with spines are well adapted to avoiding generalist predators, our results imply that larvae without spines may be suited to different ecological niches. Systematic relationships of our dataset indicate six major lineages, several of which have not previously been identified.

Keywords: character evolution, molecular phylogeny, morpho‐chemical defense, Zygaenoidea

1. INTRODUCTION

When similar phenotypes occur in a broadly distributed taxonomic clade, it may result from one or more processes, including inheritance from a common ancestor (homology), adaptation to similar local environments, shared constraints, and random genetic drift (homoplasy) (Jacobs et al., 2013; Losos, 2011; Stewart, 2007). Homoplasy, the phenotypic similarity resulting from independent evolution, is an important and common phenomenon, and it may arise in three different ways (Brooks, 1996; Hall, 2007; Lankester, 1870; Losos, 2011; McGhee, 2011; Meyer, 1999; Stayton, 2008; Wake, 1996). Firstly, it may reveal that natural selection produces optimal solutions to repeated problems posed by similar environments (Gordon & Notar, 2015; Larson & Losos, 1996; Losos, 2011; McGhee, 2011; Wake, Wake, & Specht, 2011). For example, mimicry is a form of homoplasy in which one species (the mimic) independently evolves a similar phenotype to a harmful or distasteful species (the model) to avoid predation (McGhee, 2011; Rettenmeyer, 1970; Sherratt, 2008; Symula, Schulte, & Summers, 2001). Secondly, homoplasy may reveal that genetic or developmental constraints limit the generation of phenotypic variations (Brakefield, 2006; Losos, 2011; McGhee, 2011; McKitrick, 1993; Powell, 2007; Uller, Moczek, Watson, Brakefield, & Laland, 2018; Wake, 1991; Wake et al., 2011). For example, digit loss in amphibians has occurred repeatedly during their evolutionary history, but the adaptive significance is not clear and it may simply represent developmental constraints (Alberch & Gale, 1985; Amundson, 2001; Autumn et al., 2002; Lamb & Beamer, 2012; Reeve & Sherman, 1993; Wake, 1991). Thirdly, homoplasy may result from random genetic drift (Jacobs et al., 2013; Jacobs, Mutumi, Maluleke, & Webala, 2016; Stayton, 2008). For example, homoplasy of morphology and echolocation frequency in the bats, Rhinolophus darling and R. damarensis, may be the result of random genetic drift, after excluding adaptation to similar local environments and shared constraints (Jacobs et al., 2013, 2016). In order to recognize homoplasy, it is critical to distinguish synapomorphic traits from convergent traits, which can be achieved using a phylogenetic systematics approach (Eldredge & Cracraft, 1980; Gordon & Notar, 2015; Larson & Losos, 1996; Losos, 2011; McGhee, 2011; Wake et al., 2011).

Antipredator strategies occur in every biome of the world, implying that predation is a potent selective force and thus of immense ecological and evolutionary significance (Grimaldi & Engel, 2005; Murphy, Leahy, Williams, & Lill, 2010; Ruxton, Sherratt, & Speed, 2004). Spines are one kind of obvious antipredator strategy to avoid predation (Inbar & Lev‐Yadun, 2005), such as the spines on inflated pufferfish (Brainerd, 1994), sticklebacks (Gross, 1978; Hoogland, Morris, & Tinbergen, 1956; Reimchen, 1983), slug caterpillars of the moth family Limacodidae (Murphy et al., 2010) and those on spiny plants (Gowda, 1996; Hanley, Lamont, Fairbanks, & Rafferty, 2007; Lev‐Yadun, 2001). Spines are a common defense mechanism that have evolved independently (homoplasy) in aquatic and terrestrial ecosystems, indicating that the reappearance of this phenotype is highly adaptive. However, antipredator strategies may be secondarily lost due to various  factors, for example, due to the loss of predators or limited nutrients (Bell, Francis, & Havens, 1985; Giles, 1983; Larson, 1976; McNab, 1994; Whitwell et al., 2012). Thus, it may be difficult to distinguish whether similar phenotypes present in a broadly distributed taxonomic clade is due to gains or losses. Hence, integrating phenotypic variation and reconstructing the probable ancestral states within a phylogenetic framework can enhance our knowledge of how traits evolve and may provide insights into the evolutionary processes and selective pressures involved.

Caterpillars play a major role in herbivory, but while feeding they are susceptible to attack from natural enemies (Reed, Grotan, Jenouvrier, Sather, & Visser, 2013). To protect themselves from predators and parasitoids, caterpillars have evolved a diverse array of antipredator strategies, including chemical, physiological, morphological, and behavioral responses (Greeney, Dyer, & Smilanich, 2012). Spines and setae in caterpillars are one kind of morphological–chemical adaptive response to avoid predation. At least 13 families of Lepidoptera, including the Limacodidae, have been recorded in which the caterpillars possess stinging (urticating) properties via spines and setae (Battisti, Holm, Fagrell, & Larsson, 2011; Hossler, 2010; Kano, 1977; Kawamoto & Kumada, 1984; Mullen, 2009). Spines and setae may injure predators or impose a cost in terms of increased handling time (Murphy et al., 2010; Petrucco Toffolo et al., 2014; Sugiura & Yamazaki, 2014). The Limacodidae, containing more than 1,650 species (Nieukerken et al., 2011), occur in all zoogeographic regions of the world (Cock, Godfray, & Holloway, 1987; Epstein, Geertsema, Naumann, & Tarmann, 1999), and their slug caterpillars are morphologically diverse (Figure 1) (Cock et al., 1987; Murphy, Lill, & Epstein, 2011). Three main types of slug caterpillars have been distinguished among late instars: (a) larvae armed with rows of spines (“nettle” caterpillars); (b) larvae with no spines on a relatively smooth surface (“gelatine” caterpillars); and (c) larvae with many fine setae on tubercles that can be detached (“monkey” slug caterpillars) (Cock et al., 1987; Dyar, 1896, 1907; Zaspel, Weller, & Epstein, 2016). Nettle caterpillars and gelatine caterpillars are almost distributed globally, whereas monkey slugs are rare, occurring in low abundance and being geographically restricted to Asia and the New World. The majority of limacodid larvae are nettle caterpillars, which are armed with spines that are well known to inflict stings (Hossler, 2010; Kawamoto, 1978; Murphy et al., 2010; Walker, 2018; Zaspel et al., 2016).

Figure 1.

Figure 1

Different larval types of slug caterpillars in the Limacodidae with respect to the presence of spines: (a–c) first, early, and late instar of Parasa consocia (character state A: spines present after second instar); (d) late instar of Microleon longipalpis (character state A); (e–f) first and late instar larva of Cania heppneri (character state A); (g) spines on the late instar of Cania heppneri; (h) spines on the late instar of Microleon longipalpis; (i) first instar of Demonarosa rufotessellata subrosea (character state B: spines present after second instar but reduced in late instars); (j) second instar of Demonarosa rufotessellata subrosea with spines on the segments (character state B); (k) late instar of Demonarosa rufotessellata subrosea with almost all spines lost (character state B); (l) first instar of Phrixolepia inouei (character state D: spines absent but numerous setae present after second instar); (m) first instar of Caiella pygmy (character state B); (n) early instar of Caiella pygmy with spines (character state B); (o) late instar of Caiella pygmy with almost all spines reduced (character state B); (p) late instar of Phrixolepia inouei with numerous setae (character state D); (q) first instar of Pseudanapaea transvestita (character state B); (r) second instar of Pseudanapaea transvestita with spines (character state B); (s) late instar of Pseudanapaea transvestita with almost all spines reduced (character state B); (t) late instar larva of Nagodopsis shirakiana (character state C: spines absent in all instars); (u) early instar of Ecnomoctena brachyopa with spines (character state B); (v) late instar of Ecnomoctena brachyopa with almost all spines reduced (character state B); (w, x) first and late instar of Altha melanopsis (character state C)

Murphy et al. (2010) presented evidence that spines do indeed protect slug caterpillars from generalist predators. Cock et al. (1987) presented a hypothesis that nonstinging types of slug caterpillars evolved from nettle caterpillars. However, the first detailed phylogenetic study of Limacodidae by Zaspel et al. (2016) suggested that (a) nettle caterpillars are a monophyletic group; (b) gelatine caterpillars are a monophyletic group; and (c) nettle caterpillars are derived from gelatine caterpillars. Because the study of Zaspel et al. (2016) was based on mainly New World taxa, the results may be derived from in situ diversification or independent colonization. Thus, it is uncertain if the evolutionary pattern of slug caterpillars is the same after including samples from different zoogeographic regions of the world. It is also unclear whether the existence or loss of spines in slug caterpillars has evolved once or has evolved repeatedly and independently in different lineages and/or in different continents.

When spines are present, they may be derived from a common ancestor or the result of homoplasy. Furthermore, because antipredator features may be secondarily lost, nettle, and gelatine caterpillars may be the result of multiple gains or losses of spines. Hence, our objectives were as follows: (a) to reconstruct a well‐supported phylogeny of the Limacodidae using a multigene dataset and (b) to trace the evolution of spines by optimizing character states of slug caterpillars with and without spines on this phylogenetic framework. We also comment on the systematic relationships of the Limacodidae. Most of the taxa included in this study were reared from samples collected from Asia, but we also include material from Australia, North America, and South America.

2. MATERIALS AND METHODS

2.1. Phylogenetic reconstruction

2.1.1. Taxon sampling

A total of 53 samples representing 45 ingroup species and 40 genera of the Limacodidae from Asia, Australia, North America, and South America were included for DNA extraction and phylogenetic analysis. We used eight outgroup species, including exemplars from Dalceridae, Lacturidae, Megalopygidae, Phaudidae, and Zygaenidae belonging to the superfamily Zygaenoidea. Among the five outgroup families, Dalceridae and Phaudidae are the most closely related families to the Limacodidae according to previous higher‐level phylogenetic studies (Epstein, 1996; Niehuis, Naumann, & Mishof, 2006; Regier et al., 2013). Most of the samples were collected and reared by the authors. Specimens were identified by DNA barcoding with BOLD Systems (Ratnasingham & Hebert, 2007) (http://www.barcodinglife.org/) or BLAST (Johnson et al., 2008) (http://www.ncbi.nlm.nih.gov/BLAST), and by morphological traits on Catalogue of Life in Taiwan (Biodiversity Research Center, 2018) and CSIRO‐Australian Moths Online (CSIRO, 2018). All exemplar species for this study are listed in Table 1.

Table 1.

List of species used in the phylogenetic analysis for this study, their broad geographical distribution, larval character states A–D (A = spines present after second instar; B = spines present after second instar but reduced in late instars; C = spines and setae absent in all instars; D = spines absent but numerous setae present after second instar), and GenBank accession numbers

Taxon Geographical region Character state GenBank accession number
COI 28S 18S EF‐1α Wingless
Ingroup
Limacodidae
Altha melanopsis Asia C MK128255 MK128153 MK128204 MK128308 MK128360
Anaxidia lozogramma Australia A MK128292 MK128190 MK128241 MK128345 MK128397
Apoda y‐inversa North America B MK128294 MK128192 MK128243 MK128347 MK128399
Belippa horrida Asia C MK128259 MK128157 MK128208 MK128312 MK128364
Birthamoides plagioscia Australia Unknown MK128287 MK128185 MK128236 MK128340 MK128392
Birthamula rufa Asia A MK128261 MK128159 MK128210 MK128314 MK128366
Caiella pygmy Asia B MK128278 MK128176 MK128227 MK128331 MK128383
Calcarifera ordinata Australia A MK128285 MK128183 MK128234 MK128338 MK128390
Cania heppneri Asia A MK128263 MK128161 MK128212 MK128316 MK128368
Ceratonema apodina Asia B MK128262 MK128160 MK128211 MK128315 MK128367
Chalcocelis albiguttatus Australia C MK128288 MK128186 MK128237 MK128341 MK128393
Chalcoscelides castaneipars Asia C MK128257 MK128155 MK128206 MK128310 MK128362
Demonarosa rufotessellata subrosea Asia B MK128271 MK128169 MK128220 MK128324 MK128376
Doratifera quadriguttata Australia A MK128286 MK128184 MK128235 MK128339 MK128391
Doratifera vulnerans Australia A MK128290 MK128188 MK128239 MK128343 MK128395
Ecnomoctena brachyopa Australia A MK128289 MK128187 MK128238 MK128342 MK128394
Flavinarosa obscura Asia A MK128272 MK128170 MK128221 MK128325 MK128377
Griseothosea fasciata Asia A MK128253 MK128151 MK128202 MK128306 MK128358
Hampsonella arizana Asia B MK128254 MK128152 MK128203 MK128307 MK128359
Isa textula North America A MK128296 KR068974 KR068941 MK128349 MK128401
Isochaetes sp. South America D MK128303 MK128199 MK128250 MK128355 MK128408
Microleon longipalpis Asia A MK128277 MK128175 MK128226 MK128330 MK128382
Monema rubriceps Asia A MK128266 MK128164 MK128215 MK128319 MK128371
Nagodopsis shirakiana Asia C MK128276 MK128174 MK128225 MK128329 MK128381
Narosa nigrisigna Asia B MK128265 MK128163 MK128214 MK128318 MK128370
Natada nasoni North America A MK128295 KR068981 KR068948 MK128348 MK128400
Orthocraspeda furva Asia A MK128267 MK128165 MK128216 MK128320 MK128372
Parasa consocia Asia A MK128258 MK128156 MK128207 MK128311 MK128363
Parasa pastoralis Asia A MK128281 MK128179 MK128230 MK128334 MK128386
Parasa shirakii Asia A MK128269 MK128167 MK128218 MK128322 MK128374
Parasa sinica Asia A MK128279 MK128177 MK128228 MK128332 MK128384
Phlossa conjuncta Asia A MK128256 MK128154 MK128205 MK128309 MK128361
Phrixolepia inouei Asia D MK128274 MK128172 MK128223 MK128327 MK128379
Pseudanapaea transvestita Australia B MK128291 MK128189 MK128240 MK128344 MK128396
Quasinarosa corusca Asia B MK128273 MK128171 MK128222 MK128326 MK128378
Sansarea formosana Asia B MK128268 MK128166 MK128217 MK128321 MK128373
Scopelodes contractus Asia A MK128252 MK128150 MK128201 MK128305 MK128357
Setora baibarana Asia A MK128284 MK128182 MK128233 MK128337 MK128389
Setora postornata Asia A MK128260 MK128158 MK128209 MK128313 MK128365
Spatulifimbria castaneiceps opprimata Asia A MK128280 MK128178 MK128229 MK128333 MK128385
Thosea sinensis Asia B MK128264 MK128162 MK128213 MK128317 MK128369
Trichogyia limacodiformis Asia A MK128283 MK128181 MK128232 MK128336 MK128388
Vanlangia castanea Asia A MK128275 MK128173 MK128224 MK128328 MK128380
Unplaced genus sp. 1 Asia A MK128282 MK128180 MK128231 MK128335 MK128387
Unplaced genus sp. 2 Asia D MK128293 MK128191 MK128242 MK128346 MK128398
Outgroup
Dalceridae
Acraga melinda South America Unknown MK128301 MK128197 MK128248 MK128353 MK128406
Lacturidae
Eustixis sapotearum Australia B or C MK128300 MK128196 MK128247   MK128405
Megalopygidae
Megalopyge opercularis North America A MK128297 MK128193 MK128244 MK128350 MK128402
Norape ovina North America A MK128299 MK128195 MK128246 MK128352 MK128404
Phaudidae
Phauda mimica Asia C MK128270 MK128168 MK128219 MK128323 MK128375
Phauda sp. Asia C MK128302 MK128198 MK128249 MK128354 MK128407
Zygaenidae
Clelea formosana Asia Unknown MK128298 MK128194 MK128245 MK128351 MK128403
Erasmia pulchella hobsoni Asia A MK128251 MK128149 MK128200 MK128304 MK128356

Taxa are listed alphabetically.

2.1.2. Molecular data

Total genomic DNA was extracted from 1 to 3 legs of each specimen using a commercial DNA extraction kit (Gentra Puregene Tissue kit, Qiagen) following the manufacturer's protocol. The polymerase chain reaction (PCR) was used to amplify the following five gene fragments: cytochrome oxidase subunit I (COI), D2 region of the 28S ribosomal sequence, 18S ribosomal sequence, elongation factor‐1 alpha (EF‐1α), and partial sequences of the wingless gene. The first mentioned fragment is encoded in the mitochondrial genome, whereas the remaining four markers are part of the nuclear genome. These genetic markers are phylogenetically informative and commonly used for resolving the systematics of the Lepidoptera (Chalwatzis, Baur, Stetzer, Kinzelbach, & Zimmermann, 1995; Lee & Brown, 2008; Lo et al., 2015; Mutanen, Wahlberg, & Kaila, 2010; Niehuis et al., 2006; Regier et al., 2013, 2009; Simon et al., 1994; Wahlberg & Wheat, 2008; Zaspel et al., 2016). A list of primers used for generating sequence data from the targeted loci is given in Table 2. Most of the primers have been published in previous studies, but several new primers for 18S ribosomal sequence and wingless were designed for this study. In addition, four sequences (18S and 28S for both Apoda y‐inversa and Natada nasoni) were downloaded from GenBank NCBI (https://www.ncbi.nlm.nih.gov/genbank/).

Table 2.

List of primers used for generating sequence data for the five genetic markers

Marker Primer Name Primer sequence Reference
COI Pat TCC AAT GCA CTA ATC TGC CAT ATT A Simon et al. (1994)
Jerry CAA CAT TTA TTT TGA TTT TTT GG Simon et al. (1994)
Ron GGA TCA CCT GAT ATA GCA TTC CC Simon et al. (1994)
Nancy CCC GGT AAA ATT AAA ATA TAA ACT TC Simon et al. (1994)
K698 TAC AAT TTA TCG CCT AAA CTT CAG CC Simon et al. (1994)
K808 TGG AGG GTA TAC TGT TCA ACC Simon et al. (1994)
28S 28S‐f1 GAG TAC GTG AAA CCG TTC AG Lee and Brown (2008)
28S‐r1 CTG ACC AGG CAT AGT TCA C Lee and Brown (2008)
18S 18S‐f1 TAC CTG GTG GAT CCT GCC AGT Chalwatzis et al. (1995)
18S‐f2 GAT ACG GGA CTC TTA CGA GG Niehuis et al. (2006)
18S‐f3 GGT GTT TTC ATC AAT CAA G Niehuis et al. (2006)
18S‐f4 TCC GAT AAC GAA CGA GAC TC Niehuis et al. (2006)
18S‐r1 TAA CCG CAA CAA CTT TAA T DeSalle, Gatesy, Wheeler, and Grimaldi (1992)
18S‐r2 GCT AGA TGA CAT TTT TAC GG Niehuis et al. (2006)
18S‐r3 CGC CGG TCC CTC TAA GAA G Niehuis et al. (2006)
18S‐r4 TAA TGA TCC TTC TGC AGG TTC Chalwatzis et al. (1995)
18S‐80F AAG GCG ATA CCG CGA ATG GCT This study
18S‐858R CAG CAT TTT GAG CCC GCT TTG This study
EF‐1α Starsky CAC ATY AAC ATT GTC GTS ATY GG Cho et al. (1995)
Luke CAT RTT GTC KCC GTG CCA KCC Cho et al. (1995)
Cho GTC ACC ATC ATY GAC GC Reed and Sperling (1999)
Verdi GAT ACC AGT CTC AAC TCT TCC Nazari, Zakharov, and Sperling (2007)
EF51.9 CAR GAC GTA TAC AAA ATC GG Cho et al. (1995)
EFrcM4 ACA GCV ACK GTY TGY CTC ATR TC Cho et al. (1995)
Wingless LepWg1 GAR TGY AAR TGY CAY GGY ATG TCT GG Brower and DeSalle (1998)
LepWg2 ACT ICG CAR CAC CAR TGG AAT GTR CA Brower and DeSalle (1998)
wg‐lim2F GTG AAG ACY TGC TGG ATG AGG CT This study
wg‐lim425R CCA ATG GAA TGT RCA GTT GCA This study

The following PCR settings were adopted: 4 min at 94°C, followed by 40 cycles of 30 s at 94°C, 30 s at 60°C, and 40–60 s at 72°C. The final elongation step was continued for 10 min at 72°C and stopped at 4°C. If the above conditions failed, we amplified the fragments using a touchdown method: 4 min at 94°C, followed by 10 cycles of 30 s at 94°C, 30 s at 62°C decreasing 1°C each cycle, 40–60 s at 72°C and then followed by 35 cycles of 30 s at 94°C, 30 s at 52°C, and 40–60 s at 72°C. The final elongation step was continued for 10 min at 72°C and stopped at 4°C. The PCR products were conducted on agarose gel electrophoresis to verify successful amplification. Purified PCR products were sequenced with dye‐labeled terminators, and the dye‐labeled DNA fragments were read on ABI 3730XL Analyzer (Applied Biosystems).

2.1.3. Phylogenetic analyses

The DNA sequences were checked and assembled with Sequencher 4.8 (GENCODE). The resulting multiple sequence alignments were achieved by MUSCLE (Edgar, 2004) implemented in MEGA (version 6) (Tamura, Stecher, Peterson, Filipski, & Kumar, 2013) and then adjusted manually by eye. Phylogenetic analyses were performed on the combined dataset of the five concatenated gene sequences. The combined dataset was allocated to 11 subsets with respect to the five gene fragments and to codon positions of protein‐coding genes; the best‐fit substitution model and subset partitions were then evaluated by PartitionFinder (version 1.1.1) (Lanfear, Calcott, Ho, & Guindon, 2012). Maximum likelihood (ML) and partitioned Bayesian Inference (BI) analyses were implemented separately by RAxML‐HPC BlackBox (version 8.2.9) (Stamatakis, 2014) and MrBayes XSEDE (version 3.2.6) (Ronquist & Huelsenbeck, 2003) on CIPRES (http://www.phylo.org/portal2/) (Miller, Pfeiffer, & Schwartz, 2010).

2.2. Character evolution

2.2.1. Larval morphology

We collected eggs and larvae for most species to record larval character states. Some eggs were obtained from females collected from light traps, while other eggs and larvae were collected directly from the field. Eggs and larvae were brought back to the laboratory and assigned rearing records, adopting the system used by Powell and De Benedictis (1995). Each collection was labeled according to the collecting year and month, for example, 05G2 refers the second collection in July 2005 (this system employs alphabetical letters to represent months, e.g., G = July). Larvae were reared in plastic containers (150 mm × 80 mm × 45 mm). Vouchers are deposited in the Department of Life Sciences, National Taiwan Normal University (NTNU), Taipei.

2.2.2. Coding of spines

Spines are composed of multiple cells; they involve poison‐secreting cells and neural cells (Battisti et al., 2011; Hossler, 2010; Kano, 1977). Spines cause urtication because the poison contents can be released into the skin from the broken tip of the spine (Battisti et al., 2011; Hossler, 2010; Kano, 1977; Kawamoto & Kumada, 1984; Mullen, 2009).

Based on previous studies (Battisti et al., 2011; Epstein, 1996; Murphy et al., 2011; Zaspel et al., 2016) and extensive rearing by the authors in the present study, spines of limacodid larvae usually form on protuberances (Figure 1g,h), which change in size on different segments, different instars, and among different species. For example, in Parasa consocia (Figure 1b,c) some protuberances are longer in early instars than in late instars. Thus, we focused mainly on the presence or absence of spines in the larval developmental stages. For the three main types of limacodid larvae, we recognized four character states based on the presence or absence of spines and setae throughout the entire larval developmental stage, as follows:

  • State A: Spines present after the second instar (Figure 1b–d,f); a few setae are present on pairs of protuberances on each segment in the first instar (Figure 1a,e).

  • State B: Spines present after the second instar (Figure 1j,n,r,u), but almost all spines are lost or reduced in late instars (Figure 1k,o,s,v); when the spines are reduced, they are tiny and vestigial (Figure 1v). A few setae are present on pairs of protuberances on each segment in the first instar (Figure 1i,m,q).

  • State C: Spines absent in all instars (Figure 1t,w,x). Further, the setae in the first instar are also vestigial, such as Belippa horrida (Epstein, 1996).

  • State D: Spines absent; numerous setae are present on tubercles, which can be pulled off after the second instar (Figure 1p); a few setae are present on pairs of protuberances on each segment in the first instar (Figure 1l).

2.2.3. Character evolution analyses

The character evolution of larval spine variation was reconstructed on the maximum clade credibility tree using the Mk1 evolutionary model as implemented in Mesquite (version 3.2) (Maddison & Maddison, 2017).

3. RESULTS

3.1. Phylogenetic patterns

The aligned sequences consisted of a total of 5,648 bp from 53 taxa, corresponding to the combinations of 1,510 bp COI, 674 bp 28S rRNA, 1865 bp 18S rRNA, 1,230 bp EF‐1α, and 369 bp wingless. The optimal topologies reconstructed by partitioned ML and Bayesian (BI) analyses were identical (Figure 2). Both ML and BI analyses strongly supported the monophyly of Limacodidae (ML bootstrap = 100%; Posterior probability = 1).

Figure 2.

Figure 2

Phylogenetic trees of the Limacodidae based on the combined dataset constructed with: (a) partitioned Bayesian Inference; (b) partitioned Maximum Likelihood using the GTR + Γ+I substitution model. Branch lengths are proportional to inferred nucleotide substitutions, with values above nodes representing posterior probabilities (a) and ML bootstraps (b). Optimal topologies recovered by BI and ML were congruent. Six major lineages were recovered, which are indicated by different colors. Zoogeographic regions are represented in different colors on terminals, as per legend

Within the inferred phylogenetic tree of the Limacodidae, six major clades (lineages 1–6) were identified with strong support (ML bootstrap = 100%; Posterior probability = 1 for lineages 2–6) and typically long basal branches (stems) (Figure 2). These clades fell into two reciprocally monophyletic groups, with lineages 1–3 sister to lineages 4–6. Lineage 1 with good support (ML bootstrap = 80%; Posterior probability = 0.98) included only nettle caterpillars from Asia. Lineage 2 included all hairy slug caterpillars from Asia and South America. The hairy slug caterpillars of lineage 2 were sister to lineage 3, which comprised gelatine caterpillars from Asia, North America, and Australia. Lineage 4 included nettle caterpillars from Asia, whereas lineage 5 included nettle caterpillars from both Asia and North America. Lineage 6 included mostly nettle caterpillars from Asia and Australia, but also three taxa in which spines were reduced: Caiella pygmy from Asia, and Ecnomoctena brachyopa and Pseudanapaea transvestita from Australia.

3.2. Character evolution of spines

The evolutionary reconstruction of spines in limacodid caterpillars indicated that the ancestral state was most likely larvae with spines present from second instar to final instar (character state A) (Figure 3, Node 1: proportional likelihood of character state A = 0.999). There were four separate transitions from this ancestral character state to spines lost or reduced in late instars (character state B), which evolved independently three times in lineage 6 and once in lineage 3 (Figure 3, Node 2: proportional likelihood of character state B = 0.987). There was a further transition from spines lost or reduced in late instars to spines absent in all instars (character state C) in lineage 3 (Figure 3, Node 3: proportional likelihood of character state C = 0.963). There was another transition from spines present after second instar (character state A) to spines absent but numerous setae present after second instar (character state D) in lineage 2 (Figure 3, Node 4: proportional likelihood of character state D = 0.958).

Figure 3.

Figure 3

Phylogenetic tree of the Limacodidae constructed using partitioned Maximum Likelihood, with bootstrap values below branches and posterior probabilities above. Character state reconstruction for spines was carried out using Maximum Likelihood (Mesquite). The proportional likelihoods of the different character states in the ancestral reconstructions are indicated by the area red/yellow/white/blue in each pie diagram (A = red for spines present after second instar; B = yellow for spines present after second instar but reduced in late instars; C = white for spines and setae absent in all instars; D = blue for spines absent but numerous setae present after second instar). Node 1: proportional likelihood of character state A = 0.999. Node 2: proportional likelihood of character state B = 0.987. Node 3: proportional likelihood of character state C = 0.964. Node 4: proportional likelihood of character state D = 0.958. Node 5: proportional likelihood of character state A = 0.999

4. DISCUSSION

Our molecular study provides a robust phylogeny of the Limacodidae. The well‐supported phylogenetic framework allows us to reliably reconstruct the character evolution of spines throughout the entire larval stage, to test previous hypotheses regarding the evolution of slug caterpillars, and to infer the potential mechanisms of homoplasy in limacodids.

4.1. Character evolution and morphological homoplasy

According to the phylogeny reconstructed in this study, limacodids evolved from a common ancestor in which the larval type possessed spines from second instar to final instar (character state A), and then, spines were evolutionary lost or reduced in late instars (character state B) multiple times—at least on four occasions (Figure 3). Of the four independent transitions from the presence of spines to the absence or reduction of spines in late instars, two were in Asia (ancestor of lineage 3 and Caiella pygmy in lineage 6), and two were in Australia (Ecnomoctena brachyopa and Pseudanapaea transvestita in lineage 6). Thus, we infer that loss or reduction in spines is the result of homoplasy in these zoogeographic regions. Moreover, spines absent in all instars (character state C) evolved once from a common ancestor in which spines were lost or reduced in late instars (character state B), indicating a clear evolutionary progression in the loss of poisonous spines from nettle caterpillars to gelatine caterpillars. This pattern is consistent with Cock's (1987) hypothesis that nonstinging types of slug caterpillars evolved from nettle caterpillars. Although the pattern contrasts with the larval character evolution of Zaspel et al. (2016), it must be emphasized that branch support for many of the basal nodes in that phylogenetic study was low and hence ancestral reconstructions were at best preliminary.

Spines in the Limacodidae are considered to be an adaptive response to predation (Murphy et al., 2010). Our phylogeny indicates that this defense strategy evolved early in the origin of the family, and the trait is widespread across lineages 1 and 4–6 (Figure 3). Therefore, the independent losses of poisonous spines (homoplasy) raise the interesting question as to why have some larvae evolutionary lost their toxic antipredator mechanism? Gelatine caterpillars avoid predation through crypsis or masquerade, but it remains to be determined what mechanism may have driven this type of defense strategy. Here, we propose several potential mechanisms (hypotheses) for spine reduction in slug caterpillars.

The first hypothesis is that spines get lost or reduced because they confer no advantage below a certain size threshold. It has been demonstrated that defensive characters such as warning coloration are more effective when displayed in insects with large bodies (Forsman & Merilaita, 1999; Hossie, Skelhorn, Breinholt, Kawahara, & Sherratt, 2015). For example, defensive eyespots are effective in big caterpillars, but costly in small caterpillars, because they enhance detectability without providing a protective advantage in small caterpillars (Hossie et al., 2015). In tree‐feeding insects, avian predation risk increased with larger prey body size (Remmel, Davison, & Tammaru, 2011; Remmel & Tammaru, 2009). Therefore, slug caterpillars with small body size (e.g., Quasinarosa corusca) may be hard to detect, so that the cost of producing spines and toxins may be higher than the benefit of avoiding predation in smaller taxa.

The second hypothesis is that there has been a change in predator pressure. Predators (e.g., insectivorous birds) eat aposematic prey in a selective manner according to their levels of hunger and the presence of alternative prey (Cott, 1940; Ruxton et al., 2004). When limacodids expand their range or enter new adaptive zones, such as in low diversity biomes (e.g., high mountain or desert habitats), with potentially higher levels of predator pressure and less alternative prey, nettle caterpillars may be too obvious to survive and cryptic larvae without spines may be selected for.

The third hypothesis is that slug caterpillars without spines may be physiologically more suited to dry environments, such as deserts, seasonal savannas, and alpine woodlands (Leuschner, 2000). According to previous studies (Battisti et al., 2011; Cock et al., 1987; Epstein et al., 1999; Hossler, 2010; Kano, 1977; Kawamoto & Kumada, 1984), spines on nettle caterpillars consist of multiple cells, and spines are usually arranged on tubercles. Slug caterpillars with spines on tubercles have higher surface area to volume ratios than slug caterpillars without spines and tubercles. Surface area to volume ratios may influence water balance in ectotherms (Ashton, 2002; Bidau & Marti, 2008). For example, the tropical rain frog, Eleutherodactylus coqui, reduces water loss by adjusting posture and activity to control the exposed surface area (Pough, Taigen, Stewart, & Brussard, 1983; Vitt & Caldwell, 2013). By analogy, slug caterpillars without spines with lower surface area to volume ratios may be more suited to dry environments. In a previous study, it has been observed that nettle caterpillars are distributed more in tropical areas and gelatine caterpillars are distributed more in temperate areas (Zaspel et al., 2016).

In addition to adaptation to similar local environments, because genetic or developmental constraints limit the generation of phenotypic variations (Brakefield, 2006; Hall, 2007; Wake et al., 2011), the reappearance of similar features in organisms may result from different selective pressures (Hall, 2007). For example, pelvic reduction in stickleback populations, which are sympatric with various fish and bird predators, may be triggered by low calcium ion concentration (Giles, 1983); in Paxton Lake with a high calcium ion level and in some Alaskan Lakes with lack of native predatory fishes, stickleback populations have similar pelvic vestiges (Bell et al., 1985; Larson, 1976). Therefore, homoplasy of pelvic reduction in sticklebacks is more likely to be caused by different selective pressures, low calcium ion concentration and lack of native predatory fishes, in different lakes (Bell, 1987). Furthermore, homoplasy is common with reduced characters especially for complex characters, which may have low probability of origin but can be lost or reduced by the action of a few genes (Culver & Pipan, 2016; Cunningham, Omland, & Oakley, 1998; Maddison, 1994; Sackton et al., 2019). In this study, the larvae of Caiella pygmy occur in montane areas (above 2500 m) in winter and spring, whereas those of Ecnomoctena brachyopa and Pseudanapaea transvestita are distributed in relatively dry areas of Australia. Thus, loss of spine may be evolved to response to different environments because of genetic constraints.

Finally, spine loss in slug caterpillars may be just fixed by random genetic drift, especially at the ancestral state in lineage 3, because most of these species with spine loss in late instars (character state B) are sympatric with most species from Asia in lineage 4‐6 in which spines are present in late instars (character state A). Hence, homoplasy of spine loss in the Limacodidae may be the result of one or more processes, including adaptation to similar local environments, shared constraints, and random genetic drift.

4.2. Systematic considerations

In the inferred phylogenetic tree of the Limacodidae, we identified six lineages (Figure 2). Lineage 1 contains Trichogyia limacodiformis, Microleon longipalpis and sp. 1, a clade which had not been identified in previous phylogenetic studies of the Limacodidae. Interestingly, this clade was recovered relatively deep in our phylogeny, being sister to lineages 2 and 3. Lineage 1 shares several morphological characters, such as small body size (forewing length <10 mm) and character state A. The structure of the spine in lineage 1 is the same as that in lineages 4–6, which is formed by trichogen cells that line up with the epidermal cells (Kawamoto & Kumada, 1984), although the numbers of spines on each segment (Figure 1d,h) are fewer than those in lineages 4–6 (Figure 1b,c,f,g).

In lineage 2, three taxa comprise a monophyletic group that is characterized by hairy monkey slug caterpillars (character state D). The clade includes Isochaetes sp. and Phrixolepia inouei, which emerged as sister taxa. The geographical distribution of Isochaetes is in eastern North America, Central America, and northern South America, whereas the distribution of Phrixolepia is mainly in eastern Asia (Ratnasingham & Hebert, 2007). The disjunction between North America and eastern Asia has been reported for many animal and plant taxa (Espeland et al.2015; Nordlander, Liu, & Ronquist, 1996; Peña, Nylin, Freitas, & Wahlberg, 2010; Tiffney, 1985; Wen, 1999). Thus, Isochaetes and Phrixolepia may provide another example of dispersal (and extinction) through the Bering land bridge that formerly connected North America with Eurasia.

The large clade including lineages 4–6 containing most of the nettle caterpillars with spines present after second instar is phylogenetically equivalent to the “nettle” clade identified by Zaspel et al. (2016). In both clades, most, if not all, species fast in the first instar, which is that the first instars do not feed on the host plant and then they quickly molt to the second instar. Interestingly, in our study this clade included Caiella pygmy, Pseudanapaea transvestita, and Ecnomoctena brachyopa in lineage 6 in which there were transitions from late instars with spines to late instars with spines lost or reduced. From the rearing experience, Caiella pygmy and Pseudanapaea transvestita still retain the fasting behavior in the first instar. However, we do not know if fasting in the first instar applies to Ecnomoctena brachyopa.

Within lineage 6, we found that the genus Parasa is not monophyletic because of inclusion of the species Caiella pygmy. Solovyev (2010) originally described the species pygmy in the genus Parasa. Later, Solovyev (2014) revised Parasa and transferred P. pygmy to his newly described genus Caiella based on adult forewing pattern and the reduced scoli in mature larvae. However, our phylogenetic results indicate that Caiella pygmy renders Parasa paraphyletic. Further, the character reconstruction in this study revealed that reduced scoli in late instar larvae is the result of homoplasy and should not be regarded as an autapomorphy to diagnose the genus. Hence, either the genus Caiella needs to be synonymized with Parasa or many of the subgroups within Parasa need to be elevated to monophyletic genera. Since Parasa currently comprises about 240 species, we suggest the monophyly of the genus needs further investigation until any taxonomic change is made.

With the exception of Chalcocelis albiguttatus, all other taxa from Australia (seven species representing six genera) comprised a monophyletic group within lineage 6 (Figure 3: Node 5). Although the clade was not strongly supported, it may be improved by greater taxon sampling of the fauna of the continent. The topology and relative branch lengths indicate that most limacodids in Australia evolved relatively recently. Moreover, the Australian lineage is nested within a set of predominantly Asia lineages (lineages 4–6), which suggests that the origin of these limacodids is not in Australia. Further taxon sampling of the family and divergence times using a molecular clock are needed to estimate deeper biogeographic patterns to test this hypothesis.

CONFLICT OF INTEREST

None declared.

ACKNOWLEDGMENTS

We appreciate David Wagner's and an anonymous reviewer for their careful review and insightful suggestions. We thank Shou‐Hsien Li, Wei‐Jen Chen, Shen‐Horn Yen, Si‐Min Lin, Ren‐Chung Cheng, and Yi‐Shuo Liang for helpful comments and technical discussions. We thank David Rentz, Oliverio Velástegui, Chang‐Chin Chen, Chia‐Lung Huang, Tomotaka Doi, Fukashi Isiwata, Yu‐Tang Wang, Wei‐Ting Liu, and all students in or graduated from Yu‐Feng Hsu's laboratory of NTNU for helping us to collect limacodid samples. We also thank Derek Smith (Australian Museum), Susan Wright (Queensland Museum), Chunsheng Wu (Institute of Zoology Chinese Academy of Science), You Ning Su (Australian National Insect Collection), and Jing‐Fu Tsai (National Museum of Natural Science) for access to collections under their care or for helping with the identification of samples. This study was supported by grants provided by Yangmingshan National Park Headquarters (1050721) and Taroko National Park Headquarters (1079007).

Lin Y‐C, Lin R‐J, Braby MF, Hsu Y‐F. Evolution and losses of spines in slug caterpillars (Lepidoptera: Limacodidae). Ecol Evol. 2019;9:9827–9840. 10.1002/ece3.5524

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in GenBank at https://www.ncbi.nlm.nih.gov/genbank/, accession numbers in Table 1.

REFERENCES

  1. Alberch, P. , & Gale, E. A. (1985). A developmental analysis of an evolutionary trend: Digital reduction in amphibians. Evolution, 39(1), 8–23. 10.1111/j.1558-5646.1985.tb04076.x [DOI] [PubMed] [Google Scholar]
  2. Amundson, R. (2001). Adaptation, development, and the quest for common ground In Orzack S. H., & Sober E. (Eds.), Adaptation and optimality (pp. 303–334). Cambridge, UK: Cambridge University Press. [Google Scholar]
  3. Ashton, K. G. (2002). Do amphibians follow Bergmann's rule? Canadian Journal of Zoology, 80(4), 708–716. 10.1139/z02-049 [DOI] [Google Scholar]
  4. Autumn, K. , Sitti, M. , Liang, Y. A. , Peattie, A. M. , Hansen, W. R. , Sponberg, S. , … Full, R. J. (2002). Evidence for van der Waals adhesion in gecko setae. Proceedings of the National Academy of Sciences, 99(19), 12252–12256. 10.1073/pnas.192252799 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Battisti, A. , Holm, G. , Fagrell, G. , & Larsson, S. (2011). Urticating hairs in arthropods: Their nature and medical significance. Annual Review of Entomology, 56, 203–220. 10.1146/annurev-ento-120709-144844 [DOI] [PubMed] [Google Scholar]
  6. Bell, M. A. (1987). Interacting evolutionary constraints in pelvic reduction of threespine sticklebacks, Gasterosteus aculeatus (Pisces, Gasterosteidae). Biological Journal of the Linnean Society, 31(4), 347–382. 10.1111/j.1095-8312.1987.tb01998.x [DOI] [Google Scholar]
  7. Bell, M. A. , Francis, R. C. , & Havens, A. C. (1985). Pelvic reduction and its directional asymmetry in threespine sticklebacks from the Cook Inlet region, Alaska. Copeia, 1985(2), 437–444. 10.2307/1444855 [DOI] [Google Scholar]
  8. Bidau, C. J. , & Marti, D. A. (2008). A test of Allen's rule in ectotherms: The case of two South American Melanopline grasshoppers (Orthoptera: Acrididae) with partially overlapping geographic ranges. Neotropical Entomology, 37(4), 370–380. 10.1590/S1519-566X2008000400004 [DOI] [PubMed] [Google Scholar]
  9. Biodiversity Research Center (Academia Sinica of Taiwan) (2018). Catalogue of life in Taiwan. Retrieved from http://taibnet.sinica.edu.tw/ [Google Scholar]
  10. Brainerd, E. L. (1994). Pufferfish inflation: Functional morphology of postcranial structures in Diodon holocanthus (Tetraodontiformes). Journal of Morphology, 220(3), 243–261. 10.1002/jmor.1052200304 [DOI] [PubMed] [Google Scholar]
  11. Brakefield, P. M. (2006). Evo‐devo and constraints on selection. Trends in Ecology & Evolution, 21(7), 362–368. 10.1016/j.tree.2006.05.001 [DOI] [PubMed] [Google Scholar]
  12. Brooks, D. R. (1996). Explanation of homoplasy at different level of biological organization In Sanderson M. J., & Hufford L. (Eds), Homoplasy: The recurrence of similarity in evolution (pp. 3–36). San Diego, CA: Academic Press. [Google Scholar]
  13. Brower, A. V. Z. , & DeSalle, R. (1998). Patterns of mitochondrial versus nuclear DNA sequence divergence among nymphalid butterflies: The utility of wingless as a source of characters for phylogenetic inference. Insect Molecular Biology, 7(1), 73–82. 10.1046/j.1365-2583.1998.71052.x [DOI] [PubMed] [Google Scholar]
  14. Chalwatzis, N. , Baur, A. , Stetzer, E. , Kinzelbach, R. , & Zimmermann, F. K. (1995). Strongly expanded 18S rRNA genes correlated with a peculiar morphology in the insect order of Strepsiptera. Zoology, 98(2), 115–126. [Google Scholar]
  15. Cho, S. , Mitchell, A. , Regier, J. C. , Mitter, C. , Poole, R. W. , Friedlander, T. P. , & Zhao, S. (1995). A highly conserved nuclear gene for low‐level phylogenetics: Elongation factor‐1α recovers morphology‐based tree for Heliothine moths. Molecular Biology and Evolution, 12(4), 650–656. 10.1093/oxfordjournals.molbev.a040244 [DOI] [PubMed] [Google Scholar]
  16. Cock, M. J. W. , Godfray, H. C. J. , & Holloway, J. D. (1987). Slug and nettle caterpillars. The biology, taxonomy and control of the Limacodidae of economic importance on palms in South‐east Asia. Wallingford, UK: CAB International. [Google Scholar]
  17. Commonwealth Scientific and Industrial Research Organisation (CSIRO) (2018). Australian moths online. Retrieved from http://www1.ala.org.au/ [Google Scholar]
  18. Cott, H. B. (1940). Adaptive coloration in animals. London, UK: Methuen. [Google Scholar]
  19. Culver, D. , & Pipan, T. (2016). Shifting paradigms of the evolution of cave life. Acta Carsologica, 44(3), 415–425. 10.3986/ac.v44i3.1688 [DOI] [Google Scholar]
  20. Cunningham, C. W. , Omland, K. E. , & Oakley, T. H. (1998). Reconstructing ancestral character states: A critical reappraisal. Trends in Ecology & Evolution, 13(9), 361–366. 10.1016/S0169-5347(98)01382-2 [DOI] [PubMed] [Google Scholar]
  21. DeSalle, R. , Gatesy, J. , Wheeler, W. , & Grimaldi, D. (1992). DNA sequences from a fossil termite in Oligo‐Miocene amber and their phylogenetic implications. Science, 257(5078), 1933–1936. 10.1126/science.1411508 [DOI] [PubMed] [Google Scholar]
  22. Dyar, H. G. (1896). The life histories of the New York slug caterpillars. III‐VI. Journal of the New York Entomological Society, 4(4), 167–190. [Google Scholar]
  23. Dyar, H. G. (1907). The life histories of the New York slug caterpillars. XIX. Journal of the New York Entomological Society, 15(4), 219–226. [Google Scholar]
  24. Edgar, R. C. (2004). MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32(5), 1792–1797. 10.1093/nar/gkh340 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Eldredge, N. , & Cracraft, J. (1980). Phylogenetic patterns and the evolutionary process. New York, NY: Columbia University Press. [Google Scholar]
  26. Epstein, M. E. (1996). Revision and phylogeny of the Limacodid‐group families, with evolutionary studies on slug caterpillars (Lepidoptera: Zygaenoidea). Smithsonian Contributions to Zoology, 582, 1–102. 10.5479/si.00810282.582 [DOI] [Google Scholar]
  27. Epstein, M. E. , Geertsema, H. , Naumann, C. M. , & Tarmann, G. M. (1999). The Zygaenoidea In Kristensen N. P. (Ed.), Lepidoptera, moths and butterflies. Volume 1: Evolution, systematics, and biogeography (pp. 159–180). New York, NY: Walter de Gruyter. [Google Scholar]
  28. Espeland, M. , Hall, J. P. W. , DeVries, P. J. , Lees, D. C. , Cornwall, M. , Hsu, Y.-F. , … & Pierce, N.E. (2015). Ancient Neotropical origin and recent recolonisation: phylogeny and biogeography of the Riodinidae (Lepidoptera: Papilionoidea). Molecular Phylogenetics and Evolution, 93, 296–306. [DOI] [PubMed] [Google Scholar]
  29. Forsman, A. , & Merilaita, S. (1999). Fearful symmetry: Pattern size and asymmetry affects aposematic signal efficacy. Evolutionary Ecology, 13(2), 131–140. 10.1023/A:1006630911975 [DOI] [Google Scholar]
  30. Giles, N. (1983). The possible role of environmental calcium levels during the evolution of phenotypic diversity in Outer Hebridean populations of the Three‐spined stickleback, Gasterosteus aculeatus . Journal of Zoology, 199(4), 535–544. 10.1111/j.1469-7998.1983.tb05104.x [DOI] [Google Scholar]
  31. Gordon, M. S. , & Notar, J. C. (2015). Can systems biology help to separate evolutionary analogies (convergent homoplasies) from homologies? Progress in Biophysics and Molecular Biology, 117(1), 19–29. 10.1016/j.pbiomolbio.2015.01.005 [DOI] [PubMed] [Google Scholar]
  32. Gowda, J. H. (1996). Spines of Acacia tortilis: What do they defend and how? Oikos, 77(2), 279–284. 10.2307/3546066 [DOI] [Google Scholar]
  33. Greeney, H. F. , Dyer, L. A. , & Smilanich, A. M. (2012). Feeding by lepidopteran larvae is dangerous: A review of caterpillars' chemical, physiological, morphological, and behavioral defenses against natural enemies. Invertebrate Survival Journal, 9(1), 7–34. [Google Scholar]
  34. Grimaldi, D. , & Engel, M. S. (2005). Evolution of the Insects. Cambridge, UK and New York, NY: Cambridge University Press. [Google Scholar]
  35. Gross, H. P. (1978). Natural selection by predators on the defensive apparatus of the three‐spined stickleback, Gasterosteus aculeatus L. Canadian Journal of Zoology, 56(3), 398–413. 10.1139/z78-058 [DOI] [Google Scholar]
  36. Hall, B. K. (2007). Homoplasy and homology: Dichotomy or continuum? Journal of Human Evolution, 52(5), 473–479. 10.1016/j.jhevol.2006.11.010 [DOI] [PubMed] [Google Scholar]
  37. Hanley, M. E. , Lamont, B. B. , Fairbanks, M. M. , & Rafferty, C. M. (2007). Plant structural traits and their role in anti‐herbivore defence. Perspectives in Plant Ecology, Evolution and Systematics, 8(4), 157–178. 10.1016/j.ppees.2007.01.001 [DOI] [Google Scholar]
  38. Hoogland, R. , Morris, D. , & Tinbergen, N. (1956). The spines of sticklebacks (Gasterosteus and Pygosteus) as means of defence against predators (Perca and Esox). Behaviour, 10(3/4), 205–236. 10.1163/156853956X00156 [DOI] [Google Scholar]
  39. Hossie, T. J. , Skelhorn, J. , Breinholt, J. W. , Kawahara, A. Y. , & Sherratt, T. N. (2015). Body size affects the evolution of eyespots in caterpillars. Proceedings of the National Academy of Sciences, 112(21), 6664–6669. 10.1073/pnas.1415121112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Hossler, E. W. (2010). Caterpillars and moths: Part I. Dermatologic manifestations of encounters with Lepidoptera. Journal of the American Academy of Dermatology, 62(1), 1–10. 10.1016/j.jaad.2009.08.060 [DOI] [PubMed] [Google Scholar]
  41. Inbar, M. , & Lev‐Yadun, S. (2005). Conspicuous and aposematic spines in the animal kingdom. Naturwissenschaften, 92(4), 170–172. 10.1007/s00114-005-0608-2 [DOI] [PubMed] [Google Scholar]
  42. Jacobs, D. S. , Babiker, H. , Bastian, A. , Kearney, T. , van Eeden, R. , & Bishop, J. M. (2013). Phenotypic convergence in genetically distinct lineages of a Rhinolophus species complex (Mammalia, Chiroptera). PLoS ONE, 8(12), e82614 10.1371/journal.pone.0082614 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Jacobs, D. S. , Mutumi, G. L. , Maluleke, T. , & Webala, P. W. (2016). Convergence as an evolutionary trade‐off in the evolution of acoustic signals: Echolocation in horseshoe bats as a case study In Pontarotti P. (Ed.), Evolutionary biology (pp. 89–103). Cham, Switzerland: Springer; 10.1007/978-3-319-41324-2_6 [DOI] [Google Scholar]
  44. Johnson, M. , Zaretskaya, I. , Raytselis, Y. , Merezhuk, Y. , McGinnis, S. , & Madden, T. L. (2008). NCBI BLAST: A better web interface. Nucleic Acids Research, 36, W5–W9. 10.1093/nar/gkn201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Kano, R. (1977). Lepidoptera (butterflies and moths) In Sasa M., Takahashi H., Kano R., & Tanaka H. (Eds.), Animals of medical importance in the Nansei Islands in Japan (pp. 117–119). Tokyo, Japan: Shinjuku Shobo. [Google Scholar]
  46. Kawamoto, F. (1978). Studies on the venomous spicules and spines of moth caterpillars III. Scanning electron microscopic examination of spines and spicules of the slug moth caterpillar, Parasa consocia, and some properties of pain‐producing substances in venoms. Japanese Journal of Medical Science and Biology, 31(3), 291–299. 10.7883/yoken1952.31.291 [DOI] [PubMed] [Google Scholar]
  47. Kawamoto, F. , & Kumada, N. (1984). Biology and venoms of Lepidoptera In Tu A. T. (Ed.), Handbook of natural toxins. Vol. 2. Insect poisons, allergens, and other invertebrate venoms (pp. 291–330). New York, NY and Basel, Switzerland: Marcel Dekker Inc. [Google Scholar]
  48. Lamb, T. , & Beamer, D. A. (2012). Digits lost or gained? Evidence for pedal evolution in the dwarf salamander complex (Eurycea, Plethodontidae). PLoS ONE, 7(5), e37544 10.1371/journal.pone.0037544 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Lanfear, R. , Calcott, B. , Ho, S. Y. W. , & Guindon, S. (2012). PartitionFinder: Combined selection of partitioning schemes and substitution models for phylogenetic analyses. Molecular Biology and Evolution, 29(6), 1695–1701. 10.1093/molbev/mss020 [DOI] [PubMed] [Google Scholar]
  50. Lankester, E. R. (1870). On the use of the term homology in modern zoology, and the distinction between homogenetic and homoplastic agreements. Annals and Magazine of Natural History, 6(31), 34–43. 10.1080/00222937008696201 [DOI] [Google Scholar]
  51. Larson, A. , & Losos, J. B. (1996). Phylogenetic systematics of adaptation In Rose M., & Lauder G. (Eds.), Adaptation (pp. 187–220). San Diego, CA: Academic Press. [Google Scholar]
  52. Larson, G. L. (1976). Social behavior and feeding ability of two phenotypes of Gasterosteus aculeatus in relation to their spatial and trophic segregation in a temperate lake. Canadian Journal of Zoology, 54(2), 107–121. [Google Scholar]
  53. Lee, S. , & Brown, R. L. (2008). Phylogenetic relationships of Holarctic Teleiodini (Lepidoptera: Gelechiidae) based on analysis of morphological and molecular data. Systematic Entomology, 33(4), 595–612. 10.1111/j.1365-3113.2008.00430.x [DOI] [Google Scholar]
  54. Leuschner, C. (2000). Are high elevations in tropical mountains arid environments for plants? Ecology, 81(5), 1425–1436. 10.1890/0012-9658(2000)081[1425:AHEITM]2.0.CO;2 [DOI] [Google Scholar]
  55. Lev‐Yadun, S. (2001). Aposematic (warning) coloration associated with thorns in higher plants. Journal of Theoretical Biology, 210(3), 385–388. 10.1006/jtbi.2001.2315 [DOI] [PubMed] [Google Scholar]
  56. Lo, P. C. , Liu, S. H. , Chao, N. L. , Nunoo, F. K. E. , Mok, H. K. , & Chen, W. J. (2015). A multi‐gene dataset reveals a tropical New World origin and early Miocene diversification of croakers (Perciformes: Sciaenidae). Molecular Phylogenetics and Evolution, 88, 132–143. 10.1016/j.ympev.2015.03.025 [DOI] [PubMed] [Google Scholar]
  57. Losos, J. B. (2011). Convergence, adaptation, and constraint. Evolution, 65(7), 1827–1840. 10.1111/j.1558-5646.2011.01289.x [DOI] [PubMed] [Google Scholar]
  58. Maddison, D. R. (1994). Phylogenetic methods for inferring the evolutionary history and processes of change in discretely valued characters. Annual Review of Entomology, 39(1), 267–292. 10.1146/annurev.en.39.010194.001411 [DOI] [Google Scholar]
  59. Maddison, W. P. , & Maddison, D. R. (2017). Mesquite: A modular system for evolutionary analysis. Version 3.2. Retrieved from http://mesquiteproject.org [Google Scholar]
  60. McGhee, G. R. (2011). Convergent evolution: Limited forms most beautiful. Cambridge, MA and London, UK: The MIT Press. [Google Scholar]
  61. McKitrick, M. C. (1993). Phylogenetic constraint in evolutionary theory: Has it any explanatory power? Annual Review of Ecology and Systematics, 24(1), 307–330. 10.1146/annurev.es.24.110193.001515 [DOI] [Google Scholar]
  62. McNab, B. K. (1994). Energy conservation and the evolution of flightlessness in birds. American Naturalist, 144(4), 628–642. 10.1086/285697 [DOI] [Google Scholar]
  63. Meyer, A. (1999). Homology and homoplasy: The retention of genetic programmes. Novartis Foundation Symposium, 222, 141–153. 10.1002/9780470515655.ch10 [DOI] [PubMed] [Google Scholar]
  64. Miller, M. A. , Pfeiffer, W. , & Schwartz, T. (2010). Creating the CIPRES science gateway for inference of large phylogenetic trees. In 2010 Gateway Computing Environments Workshop (GCE). New Orleans, 14 November 2010. New York: LEEE; 10.1109/GCE.2010.5676129 [DOI] [Google Scholar]
  65. Mullen, G. R. (2009). Moths and butterflies (Lepidoptera) In Mullen G. R., & Durden L. A. (Eds.), Medical and veterinary entomology (pp. 363–370). Amsterdam, the Netherlands: Elsevier. [Google Scholar]
  66. Murphy, S. M. , Leahy, S. M. , Williams, L. S. , & Lill, J. T. (2010). Stinging spines protect slug caterpillars (Limacodidae) from multiple generalist predators. Behavioral Ecology, 21(1), 153–160. 10.1093/beheco/arp166 [DOI] [Google Scholar]
  67. Murphy, S. M. , Lill, J. T. , & Epstein, M. E. (2011). Natural history of Limacodid moth (Zygaenoidea) in the Environs of Washington, DC. Journal of the Lepidopterists' Society, 65(3), 137–153. [Google Scholar]
  68. Mutanen, M. , Wahlberg, N. , & Kaila, L. (2010). Comprehensive gene and taxon coverage elucidates radiation patterns in moths and butterflies. Proceedings of the Royal Society B: Biological Sciences, 277(1695), 2839–2848. 10.1098/rspb.2010.0392 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Nazari, V. , Zakharov, E. , & Sperling, F. A. H. (2007). Phylogeny, historical biogeography, and taxonomic ranking of Parnassinae (Lepidoptera, Papilionidae) based on morphology and seven genes. Molecular Phylogenetics and Evolution, 42(1), 131–156. 10.1016/j.ympev.2006.06.022 [DOI] [PubMed] [Google Scholar]
  70. Niehuis, O. , Naumann, C. M. , & Mishof, B. (2006). Phylogenetic analysis of Zygaenoidea small‐subunit rRNA structural variation implies initial oligophagy on cyanogenic host plants in larvae of the moth genus Zygaena (Insecta: Lepidoptera). Zoological Journal of the Linnean Society, 147(3), 367–381. 10.1111/j.1096-3642.2006.00222.x [DOI] [Google Scholar]
  71. Nieukerken, E. J. , Kaila, L. , Kitching, I. J. , Kristensen, N. P. , Lees, D. C. , Minet, J. , … Zwick, A. (2011). Order Lepidoptera Linnaeus, 1758 In Zhang Z.‐Q. (Ed.). Animal biodiversity: An outline of higher‐level classification and survey of taxonomic richness. Zootaxa (vol. 3148, pp. 212–221). Retrieved from https://www.mapress.com/zootaxa/2011/f/zt03148p221.pdf [Google Scholar]
  72. Nordlander, G. , Liu, Z. , & Ronquist, F. (1996). Phylogeny and historical biogeography of the cynipoid wasp family Ibaliidae (Hymenoptera). Systematic Entomology, 21(2), 151–166. 10.1046/j.1365-3113.1996.d01-4.x [DOI] [Google Scholar]
  73. Peña, C. , Nylin, S. , Freitas, A. V. , & Wahlberg, N. (2010). Biogeographic history of the butterfly subtribe Euptychiina (Lepidoptera, Nymphalidae, Satyrinae). Zoologica Scripta, 39(3), 243–258. 10.1111/j.1463-6409.2010.00421.x [DOI] [Google Scholar]
  74. Petrucco Toffolo, E. , Zovi, D. , Perin, C. , Paolucci, P. , Roques, A. , Battisti, A. , & Horvath, H. (2014). Size and dispersion of urticating setae in three species of processionary moths. Integrative Zoology, 9(3), 320–327. 10.1111/1749-4877.12031 [DOI] [PubMed] [Google Scholar]
  75. Pough, F. H. , Taigen, T. L. , Stewart, M. M. , & Brussard, P. F. (1983). Behavioral modification of evaporative water loss by a Puerto Rican frog. Ecology, 64(2), 244–252. 10.2307/1937072 [DOI] [Google Scholar]
  76. Powell, J. A. , & De Benedictis, J. A. (1995). Biological relationships: Host tree preferences and isolation by pheromones among allopatric and sympatric populations of western Choristoneura. University of California Publications in Entomology, 115, 21–68. [Google Scholar]
  77. Powell, R. (2007). Is convergence more than an analogy? Homoplasy and its implications for macroevolutionary predictability. Biology & Philosophy, 22(4), 565–578. 10.1007/s10539-006-9057-3 [DOI] [Google Scholar]
  78. Ratnasingham, S. , & Hebert, P. D. N. (2007). BOLD: The barcode of life data system. Molecular Ecology Notes, 7, 355–364. 10.1111/j.1471-8286.2007.01678.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Reed, R. D. , & Sperling, F. A. H. (1999). Interaction of process partitions in phylogenetic analysis: An example from the swallowtail butterfly genus Papilio . Molecular Biology and Evolution, 16(2), 286–297. 10.1093/oxfordjournals.molbev.a026110 [DOI] [PubMed] [Google Scholar]
  80. Reed, T. E. , Grotan, V. , Jenouvrier, S. , Sather, B. , & Visser, M. E. (2013). Population growth in a wild bird is buffered against phenological mismatch. Science, 340(6131), 488–491. 10.1126/science.1232870 [DOI] [PubMed] [Google Scholar]
  81. Reeve, H. K. , & Sherman, P. W. (1993). Adaptation and the goals of evolutionary research. Quarterly Review of Biology, 68(1), 1–32. 10.1086/417909 [DOI] [Google Scholar]
  82. Regier, J. C. , Mitter, C. , Zwick, A. , Bazinet, A. L. , Cummings, M. P. , Kawahara, A. Y. , … Mitter, K. T. (2013). A large‐scale, higher‐level, molecular phylogenetic study of the insect order Lepidoptera (moths and butterflies). PLoS ONE, 8(3), e58568 10.1371/journal.pone.0058568 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Regier, J. C. , Zwick, A. , Cummings, M. P. , Kawahara, A. Y. , Cho, S. , Weller, S. , … Mitter, C. (2009). Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): An initial molecular study. BMC Evolutionary Biology, 9(1), 280 10.1186/1471-2148-9-280 [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Reimchen, T. E. (1983). Structural relationships between spines and lateral plates in threespine stickleback (Gasterosteus aculeatus). Evolution, 37(5), 931–946. 10.1111/j.1558-5646.1983.tb05622.x [DOI] [PubMed] [Google Scholar]
  85. Remmel, T. , Davison, J. , & Tammaru, T. (2011). Quantifying predation on folivorous insect larvae: The perspective of life‐history evolution. Biological Journal of the Linnean Society, 104(1), 1–18. 10.1111/j.1095-8312.2011.01721.x [DOI] [Google Scholar]
  86. Remmel, T. , & Tammaru, T. (2009). Size‐dependent predation risk in tree‐feeding insects with different colouration strategies: A field experiment. Journal of Animal Ecology, 78(5), 973–980. 10.1111/j.1365-2656.2009.01566.x [DOI] [PubMed] [Google Scholar]
  87. Rettenmeyer, C. W. (1970). Insect mimicry. Annual Review of Entomology, 15(1), 43–74. 10.1146/annurev.en.15.010170.000355 [DOI] [Google Scholar]
  88. Ronquist, F. , & Huelsenbeck, J. P. (2003). MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19(12), 1572–1574. 10.1093/bioinformatics/btg180 [DOI] [PubMed] [Google Scholar]
  89. Ruxton, G. D. , Sherratt, T. N. , & Speed, M. P. (2004). Avoiding attack: The evolutionary ecology of crypsis, warning wignals and mimicry. Oxford, UK: Oxford University Press. [Google Scholar]
  90. Sackton, T. B. , Grayson, P. , Cloutier, A. , Hu, Z. , Liu, J. S. , Wheeler, N. E. , … Edwards, S. V. (2019). Convergent regulatory evolution and loss of flight in paleognathous birds. Science, 364(6435), 74–78. 10.1126/science.aat7244 [DOI] [PubMed] [Google Scholar]
  91. Sherratt, T. N. (2008). The evolution of Müllerian mimicry. Naturwissenschaften, 95(8), 681 10.1007/s00114-008-0403-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Simon, C. , Frati, F. , Beckenbach, A. , Crespi, B. , Liu, H. , & Flook, P. (1994). Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Annals of the Entomological Society of America, 87(6), 651–701. 10.1093/aesa/87.6.651 [DOI] [Google Scholar]
  93. Solovyev, A. V. (2010). New species of the genus Parasa (Lepidoptera, Limacodidae) in south‐east Asia. Zoologicheskiĭ Zhurnal, 89(11), 1354–1360. [Google Scholar]
  94. Solovyev, A. V. (2014). Parasa Moore auct.: phylogenetic review of the complex from the Palaearctic and Indomalayan regions (Lepidoptera, Limacodidae). Munich and Vilnius: Museum Witt and Nature Research Center. [Google Scholar]
  95. Stamatakis, A. (2014). RAxML version 8: A tool for phylogenetic analysis and post‐analysis of large phylogenies. Bioinformatics, 30(9), 1312–1313. 10.1093/bioinformatics/btu033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Stayton, C. T. (2008). Is convergence surprising? An examination of the frequency of convergence in simulated datasets. Journal of Theoretical Biology, 252(1), 1–14. 10.1016/j.jtbi.2008.01.008 [DOI] [PubMed] [Google Scholar]
  97. Stewart, C.‐B. (2007). Evolution: Convergent and parallel evolution In Encyclopedia of life sciences. Chichester, UK: John Wiley & Sons, Ltd. [Google Scholar]
  98. Sugiura, S. , & Yamazaki, K. (2014). Caterpillar hair as a physical barrier against invertebrate predators. Behavioral Ecology, 25(4), 975–983. 10.1093/beheco/aru080 [DOI] [Google Scholar]
  99. Symula, R. , Schulte, R. , & Summers, K. (2001). Molecular phylogenetic evidence for a mimetic radiation in Peruvian poison frogs supports a Müllerian mimicry hypothesis. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268(1484), 2415–2421. 10.1098/rspb.2001.1812 [DOI] [PMC free article] [PubMed] [Google Scholar]
  100. Tamura, K. , Stecher, G. , Peterson, D. , Filipski, A. , & Kumar, S. (2013). MEGA6: Molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution, 30(12), 2725–2729. 10.1093/molbev/mst197 [DOI] [PMC free article] [PubMed] [Google Scholar]
  101. Tiffney, B. H. (1985). The Eocene North Atlantic land bridge: Its importance in Tertiary and modern phytogeography of the Northern Hemisphere. Journal of the Arnold Arboretum, 66(2), 243–273. 10.5962/bhl.part.13183 [DOI] [Google Scholar]
  102. Uller, T. , Moczek, A. P. , Watson, R. A. , Brakefield, P. M. , & Laland, K. N. (2018). Developmental bias and evolution: A regulatory network perspective. Genetics, 209(4), 949–966. 10.1534/genetics.118.300995 [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Vitt, L. J. , & Caldwell, J. P. (2013). Herpetology: An introductory biology of amphibians and reptiles (4th ed.). San Diego, CA: Academic Press. [Google Scholar]
  104. Wahlberg, N. , & Wheat, C. W. (2008). Genomic outposts serve the phylogenomic pioneers: Designing novel nuclear markers for genomic DNA extractions of Lepidoptera. Systematic Biology, 57(2), 231–242. 10.1080/10635150802033006 [DOI] [PubMed] [Google Scholar]
  105. Wake, D. B. (1991). Homoplasy: The result of natural selection or evidence of design limitations? American Naturalist, 138(3), 543–567. 10.1086/285234 [DOI] [Google Scholar]
  106. Wake, D. B. (1996). Introduction In Sanderson M. J., & Hufford L. (Eds.), Homoplasy: Recurrence of similarity in evolution (pp. xvii–xxv). San Diego, CA: Academic Press. [Google Scholar]
  107. Wake, D. B. , Wake, M. H. , & Specht, C. D. (2011). Homoplasy: From detecting pattern to determining process and mechanism of evolution. Science, 331(6020), 1032–1035. 10.1126/science.1188545 [DOI] [PubMed] [Google Scholar]
  108. Walker, A. (2018). Exploring the world of insect venoms. Entomological Society of Queensland, 46(2), 24–29. [Google Scholar]
  109. Wen, J. (1999). Evolution of eastern Asian and eastern North American disjunct distributions in flowering plants. Annual Review of Ecology and Systematics, 30(1), 421–455. 10.1146/annurev.ecolsys.30.1.421 [DOI] [Google Scholar]
  110. Whitwell, S. M. , Amiot, C. , Mclean, I. G. , Lovegrove, T. G. , Armstrong, D. P. , Brunton, D. H. , & Ji, W. (2012). Losing anti‐predatory behaviour: A cost of translocation. Austral Ecology, 37(4), 413–418. 10.1111/j.1442-9993.2011.02293.x [DOI] [Google Scholar]
  111. Zaspel, J. M. , Weller, S. J. , & Epstein, M. E. (2016). Origin of the hungry caterpillar: Evolution of fasting in slug moths (Insecta: Lepidoptera: Limacodidae). Molecular Phylogenetics and Evolution, 94, 827–832. 10.1016/j.ympev.2015.09.017 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are openly available in GenBank at https://www.ncbi.nlm.nih.gov/genbank/, accession numbers in Table 1.


Articles from Ecology and Evolution are provided here courtesy of Wiley

RESOURCES