A Complete Time-Calibrated Multi-Gene Phylogeny of the European Butterflies

ZooKeys 938: 97–124 (2020) A peer-reviewed open-access journal doi: 10.3897/zookeys.938.50878 Data Paper https://zookeys.pensoft.net Launched to accelerate biodiversity research

A complete time-calibrated multi-gene phylogeny of the European butterflies

Martin Wiemers1,2, Nicolas Chazot3,4,5, Christopher W. Wheat6, Oliver Schweiger2, Niklas Wahlberg3

1 Senckenberg Deutsches Entomologisches Institut, Eberswalder Straße 90, 15374, Müncheberg, Germany 2 UFZ – Helmholtz Centre for Environmental Research, Department of Community Ecology, Theodor-Lieser- Str. 4, 06120, Halle, Germany 3 Department of Biology, Lund University, 22362, Lund, Sweden 4 Depart- ment of Biological and Environmental Sciences, University of Gothenburg, Box 461, 405 30, Gothenburg, Sweden 5 Gothenburg Global Biodiversity Centre, Box 461, 405 30, Gothenburg, Sweden 6 Department of Zoology, Stockholm University, 10691, Stockholm, Sweden

Corresponding author: Martin Wiemers ([email protected])

Academic editor: R. Rougerie | Received 6 February 2020 | Accepted 3 April 2020 | Published 4 June 2020

http://zoobank.org/DA70320D-851B-49A6-84F8-E9E87F88ED92

Citation: Wiemers M, Chazot N, Wheat CW, Schweiger O, Wahlberg N (2020) A complete time-calibrated multi- gene phylogeny of the European butterflies. ZooKeys 938: 97–124.https://doi.org/10.3897/zookeys.938.50878

Abstract With the aim of supporting ecological analyses in butterflies, the third most species-rich superfamily of Lepidoptera, this paper presents the first time-calibrated phylogeny of all 496 extant butterfly species in Europe, including 18 very localised endemics for which no public DNA sequences had been available previously. It is based on a concatenated alignment of the mitochondrial gene COI and up to eleven nuclear gene fragments, using Bayesian inferences of phylogeny. To avoid analytical biases that could result from our region-focussed sampling, our European tree was grafted upon a global genus-level backbone butterfly phylogeny for analyses. In addition to a consensus tree, the posterior distribution of trees and the fully concatenated alignment are provided for future analyses. Altogether a complete phylogenetic framework of European butterflies for use by the ecological and evolutionary communities is presented.

Keywords Butterflies of Europe, divergence times, macroecology, phylogeny, time tree

Copyright Martin Wiemers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 98 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Introduction

The incorporation of phylogenetic information in ecological theory and research has led to significant advancements by facilitating the connection of large-scale and long- term macro-evolutionary processes with ecological processes in the analysis of species interactions with their abiotic and biotic environments (Webb et al. 2002; Mouquet et al. 2012). Phylogenies are increasingly used across diverse areas of macroecological research (Roquet et al. 2013), such as studies on large-scale diversity patterns (De Palma et al. 2017), disentangling historical and contemporary processes (Mazel et al. 2017), latitudinal diversity gradients (Economo et al. 2018) or improving species area relationships (Mazel et al. 2015). Phylogenetic information has also improved studies on assembly rules of local communities (Cavender-Bares et al. 2009; Gerhold et al. 2015; D’Amen et al. 2018), including spatiotemporal community dynamics (Monnet et al. 2014) and multi-spatial and -temporal context-dependencies (Ovaskainen et al. 2017). Additionally, phylogenetic information has provided insights into the mechanisms and consequences of biological invasions (Knapp et al. 2008; Winter et al. 2009; Li et al. 2015; Gallien et al. 2017). They also contribute to assessments of ecosystem functioning and service provisioning (Díaz et al. 2013; Davies et al. 2016), though phylogenetic relationships cannot simply be taken as a one-to-one proxy for ecosystem functioning (Winter et al. 2013; Mazel et al. 2018). However, they are of great value for studies of species traits and niche characteristics by quantifying the amount of phylogenetic conservatism (Wiens and Graham 2005) and ensuring statistical inde- pendence (Kühn et al. 2009) in multi-species studies. Using an ever increasing toolkit of phylogenetic metrics (Schweiger et al. 2008; Tucker et al. 2017), and a growing body of phylogenetic insights, the afore mentioned advances across diverse research fields document how integrating evolutionary and ecological information can enhance assessments of future impacts of global change on biodiversity (Thuiller et al. 2011; Lavergne et al. 2013; Morales-Castilla et al. 2017) and consequently inform conservation efforts (Thuiller et al. 2015; but see also Winter et al. 2013). Although the amount of molecular data has increased exponentially during the last decades, most available phylogenetic studies are either restricted to a selected subset of species, higher taxa, or to small geographic areas. Complete and dated species-level phylogenetic hypotheses for species-rich taxa of larger regions have been restricted to vascular plants (Durka and Michalski 2012) or vertebrates, such as global birds (Jetz et al. 2012) or European tetrapods (Roquet et al. 2014), or the analyses are based on molecular data from a small subset of species (e.g., 5% in ants; Economo et al. 2018). Regionally complete phylogenetic hypotheses are rare for insects, although they com- prise the majority of multicellular life on Earth (Stork 2018), have enormous impacts on ecosystem functioning, provide a multitude of ecosystem services (Noriega et al. 2018), and have long been used as biodiversity indicators (McGeoch 2007). Here, we present the first comprehensive time-calibrated molecular phylogeny of all 496 extant European butterfly species (Lepidoptera: Papilionoidea), based on one mitochondrial and up to eleven nuclear genes, and the most recent systematic list Phylogeny of European butterflies 99 of European butterflies (Wiemers et al. 2018). European butterflies are well-studied, ranging from population level analyses (Settele et al. 2009) to large-scale impacts of global change (Devictor et al. 2012). There is also good knowledge of species traits and environmental niche characteristics (Bartonova et al. 2014; Schweiger et al. 2014), population trends (van Swaay et al. 2006; van Swaay et al. 2010) and large-scale distributions (Settele et al. 2008; Kudrna et al. 2011). Butterflies are thus well placed for studies in the emerging field of ecophylogenetics (Mouquet et al. 2012). Compared to other groups of insects, the phylogenetic relationships of butterflies are reasonably well-known, with robust backbone molecular phylogenies at the subfamily (Wahlberg et al. 2005a; Heikkilä et al. 2012; Espeland et al. 2018) and genus- level (Chazot et al. 2019). In addition, molecular phylogenies also exist for most butterfly families (Campbell et al. 2000; Caterino et al. 2001; Wahlberg et al. 2003; Braby et al. 2006; Warren et al. 2008; Wahlberg et al. 2009; Wahlberg et al. 2014; Espeland et al. 2015; Sahoo et al. 2016; Seraphim et al. 2018; Toussaint et al. 2018; Allio et al. 2020) as well as major subgroups (Wahlberg et al. 2005b; Peña et al. 2006; Nylin and Wahlberg 2008; Peña and Wahlberg 2008; Wiemers et al. 2010; Talavera et al. 2013; Peña et al. 2015; Condamine et al. 2018) and comprehensive COI data at the species level are available from DNA barcoding studies (Wiemers and Fiedler 2007; Dincă et al. 2011; Hausmann et al. 2011; Dincă et al. 2015; Huemer and Wiesmair 2017; Litman et al. 2018). Some ecological studies on butterflies have already incorporated phylogenetic information, e.g., on the impact of climate change on abundance trends (Bowler et al. 2015; Bowler et al. 2017), the sensitivity of butterflies to invasive species (Gallien et al. 2017; Schleuning et al. 2016) or the ecological determinants of butterfly vulnerability (Essens et al. 2017). However, the phylogenetic hypotheses used in these studies had incomplete taxon coverage and were not made available for reuse by other researchers. A first complete phylogeny of European butterflies was published by Dapporto et al. (2019) but this tree was not based on a global backbone phylogeny and therefore was also not time-calibrated. To fill these gaps in the literature, and to facilitate the growing field of ecophylogenetics, here we present the first complete and time-calibrated species-level phylogeny of a speciose higher invertebrate taxon above the family level for an entire continent. Importantly, we provide this continent-wide fully resolved phylogeny in standard analysis formats for further advancements in theo- retical and applied ecology.

Materials and methods Taxonomic, spatial, and temporal coverage

We analyse a dataset comprising all extant European species of butterflies (Papilio- noidea), including the families Papilionidae, Hesperiidae, Pieridae, Lycaenidae, Riodi- nidae, and Nymphalidae. We base our species concepts, as well as the area defined as Europe, on the latest checklist of European butterflies (Wiemers et al. 2018). 100 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Acquisition of sequence data

The data were mainly collated from published sources and downloaded from NCBI GenBank (Suppl. material 1). One mitochondrial gene, cytochrome c oxidase subunit I (COI, 1464 bp), was available for all species in the data matrix, in particular the 5’ half of the gene (658 bp, also known as the DNA barcode). Eleven nuclear genes were included when available: elongation factor-1α (EF-1α, 1240 bp), carbamoyl-phosphate synthase domain protein (CAD, 850 bp), cytosolic malate dehydrogenase (MDH, 733 bp), isocitrate dehydrogenase (IDH, 711 bp), glyceraldehyde-3-phosphate dehydrogenase (GAPDH, 691 bp), ribosomal protein S5 (RpS5, 617 bp), arginine kinase (ArgK, 596 bp), wingless (412 bp), ribosomal protein S2 (RpS2, 411 bp), DOPA decarboxy- lase (DDC, 373 bp), and histone 3 (H3, 329 bp). H3 has been sequenced almost exclusively for the family Lycaenidae, while the other gene regions have been sampled widely also in the other butterfly families. For each gene, the longest available sequence was used. However, in the case of several available sequences of similar length, those of European origin were preferentially used. Sequences were aligned manually to main- tain protein reading frame, and were curated and managed using VoSeq (Peña and Malm 2012). In many cases, new sequences were generated for this study. For these specimens, protocols followed Wahlberg and Wheat (2008) or Wiemers and Fiedler (2007). These include several species that did not have any available published sequences, many of which are island endemics (Table 1). The 239 new sequences have been sub- mitted to GenBank (accessions KC462784–KC462854, MN752702–MN752850, MN829460–MN829496). Almost all genera are represented by multiple genes, except Borbo, Gegenes, Lae- osopis, Callophrys, and Cyclyrius (the latter recently synonymised with Leptotes; Fric et al. 2019) which are represented only by the COI gene. Species represented by only the DNA barcode tend to be closely related to species with more genes sequenced (Suppl. material 1), minimising the potential bias these samples could have in our analyses.

Phylogenetic tree reconstructions

A biogeographically restricted tree of a given taxon is inherently very asymmetrically sampled. To avoid potentially strong biases when estimating topology and divergence times we chose to build upon the recent genus-level tree of butterflies (Chazot et al. 2019), which provides a well-supported time-calibrated backbone and is congruent with a recent phylogenomic analysis of Lepidoptera (Kawahara et al. 2019). This backbone tree contains 994 taxa, each taxon representing a genus across all Papilionoidea. The tree was time-calibrated using a set of 14 fossil calibration points, which provided mini- mum ages and ten calibration points based on ages of host plant clades taken from the literature, which provided maximum ages. Importantly, Chazot et al. (2019) tested the robustness of their results to a wide range of alternative assumptions made in the time- calibration analysis, and showed that the estimated times of divergences were robust. Phylogeny of European butterflies 101

Table 1. Newly sequenced species for which no published sequences had previously been available.

Taxon Origin COI EF-1α GAPDH Wingless Coenonympha orientalis Greece MN829478 MN829462 Glaucopsyche paphos Cyprus MN829481 MN829463 Gonepteryx maderensis Portugal: Madeira MN829482 MN829464 Hipparchia azorina Portugal: Azores MN829483 MN829465 Hipparchia bacchus Spain: Canary Islands MN829484 MN829466 Hipparchia cretica Greece: Crete MN752718 MN829467 MN752786 MN752837 Hipparchia gomera Spain: Canary Islands MN829485 MN829468 Hipparchia maderensis Portugal: Madeira MN829486 Hipparchia mersina Greece: Samos MN752720 MN829469 MN752785 MN752836 Hipparchia miguelensis Portugal: Madeira MN829487 Hipparchia sbordonii Italy: Pontine Islands MN752723 Hipparchia tamadabae Spain: Canary Islands MN829488 Hipparchia tilosi Spain: Canary Islands MN829489 Hipparchia wyssii Spain: Canary Islands MN829490 MN829470 Lycaena bleusei Spain MN829492 Pieris balcana North Macedonia KC462788 Pieris wollastoni Portugal: Madeira KC462820 Thymelicus christi Spain: Canary Islands MN829496

Analysis overview

To estimate a time-calibrated tree of European butterflies, we first identified the posi- tion of the European lineages and designed a grafting procedure accordingly. We split the European butterflies that needed to be added to the tree into 12 subclades. For each of these subclades we combined the DNA sequences of the taxa already included in the backbone to the DNA sequences of the European taxa to assemble an aligned molecular matrix. After identifying the best partitioning scheme, we performed a tree reconstruction without time-calibration (i.e., only estimating branch lengths propor- tional to relative time). The subclade trees were then rescaled using the ages estimated in the backbone and were subsequently grafted. This procedure was repeated using 1000 trees from BEAST posterior distributions of the backbone and subclade trees in order to obtain a posterior distribution of grafted trees. The details of these procedures are described below.

Backbone and subclades

The time-calibrated backbone tree provided by Chazot et al. (2019) contained about 55% of all butterfly genera, including 79% of the genera occurring in Europe. A fixed topology was obtained using RAxML (Stamatakis 2014) and node ages where estimated with BEAST v.1.8.3. (Suchard et al. 2018). We used this fixed topology from Chazot et al. (2019) to identify at which nodes European clades should be grafted. We partitioned the analysis into 12 subclades. For each subclade, the DNA sequences of all taxa already included in the global backbone (including also non-European taxa) were combined with the DNA sequences of all the new European taxa that were added. In addition to the focal taxa, we added between two and four outgroups. We 102 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020) note that the relationships of the 12 subclades were fixed according to Chazot et al. (2019), while the relationships of species within the 12 subclades were estimated with the new data. The subclades, sorted by families, were defined as follows:

Papilionidae – All Papilionidae were placed into one subclade. Hesperiidae – We identified two main clades to graft within the Hesperiidae: Hesperii- nae and Pyrginae. The Hesperiinae subclade was extended to also encompass the subfamilies Heteropterinae and Trapezitinae. The genus Muschampia, not available in the backbone, was included in the Pyrginae subclade. Pieridae – All Pieridae were considered as a single clade. Lycaenidae – All Lycaenidae were considered as a single clade. Riodinidae – The only European Riodinidae species, Hamearis lucina, was already available in the backbone tree. Nymphalidae – European Nymphalidae were divided into seven subclades. (i) A subclade for the Apaturinae. (ii) In order to add Danaus chrysippus we generated a tree of Danainae. (iii) We combined the sister clades Heliconiinae and Limenitidinae into a single subclade. (iv) Nymphalinae was treated as a single subclade. (v) A first clade of Satyrinae contained the generaKirinia , Pararge, Lasiommata, Tatinga, Chonala and Lopinga. (vi) A second Satyrinae clade contained the genera Calisto, Euptychia, Callerebia, Proterebia, Gyrocheilus, Strabena, Ypthima, Ypthimomorpha, Stygionympha, Cassionympha, Neocoenyra, Pseudonympha, Erebia, Boerebia, Hypone- phele, Cercyonis, Maniola, Aphantopus, Pyronia, Faunula, Grumia, Paralasa, Mela- nargia, Hipparchia, Berberia, Oeneis, Neominois, Karanasa, Brintesia, Arethusana, Satyrus, Pseudochazara, and Chazara. (vii) A third Satyrinae clade was created for the genus Coenonympha. Charaxinae were not treated separately from the backbone. Charaxes jasius is the only Charaxinae occurring in Europe and Charaxes castor (which is very closely related to C. jasius; Aduse-Poku et al. 2009) was already included in the backbone tree from Chazot et al. (2019). Hence, we used the posi- tion of Charaxes castor for Charaxes jasius.

Partitioning the dataset

For each subclade we ran PartitionFinder 2.1.1 (Lanfear et al. 2016) in order to select the best partitioning strategy and corresponding substitution models. The dataset was initially partitioned into genes and codon positions. Branch lengths were set to linked and the comparison between partitioning strategies was made using the greedy algo- rithm and BIC score (Lanfear et al. 2012).

Phylogenetic reconstruction

For each subclade, the dataset was imported in BEAUTi 1.8.3 (Drummond et al. 2012) and partitioned according to the partitioning strategy identified by Partition- Finder. We enforced the monophyly of the clade to be grafted (i.e., excluding the Phylogeny of European butterflies 103 outgroups). All other relationships were estimated by BEAST 1.8.3. (Suchard et al. 2018). We used an uncorrelated relaxed clock with lognormal distribution. By default, we started by setting one molecular clock per partition. If convergence or good mixing could not be obtained after running BEAST we reduced the number of molecular clocks (see details for each dataset further below). We did not add any time-calibration and therefore only estimated the relative timing of divergence. We performed at least two independent runs with BEAST for each subclade. We checked for convergence and mixing of the MCMC using Tracer 1.7.1 (Rambaut et al. 2018) and in the case of full convergence of the runs, the posterior distribution of trees from different runs were combined after removing the burn-in fraction.

Grafting procedure

Subclades were grafted on the backbone as follows. One backbone was sampled from the posterior distribution of time-calibrated trees from Chazot et al. (2019). For each subclade, one subclade tree was sampled from the posterior distribution of trees, the outgroups removed, and the tree was rescaled based on the crown age of the subclade extracted from the backbone tree. Finally, the rescaled subclade tree was grafted on the backbone after removing all lineages belonging to this subclade in the backbone (i.e., only keeping the stem branch). We repeated this procedure for 1000 backbone trees and 1000 subclade trees, and we thus obtained a posterior distribution of 1000 grafted trees. The topology of the backbone was fixed (see Chazot et al. 2019) but the topologies of the subclades were free. Hence the posterior distribution of grafted trees includes a posterior distribution of topologies and node ages. We describe below the details of the phylogenetic tree reconstruction for each subclade.

1. Papilionidae

Dataset – The dataset for the Papilionidae consisted of 36 taxa to which three outgroups were added: Macrosoma tipulata (Hedylidae), Achlyodes busiris (Hesperii- dae), Pieris rapae (Pieridae). We concatenated 11 gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless). PartitionFinder – PartitionFinder identified 12 subsets (Suppl. material 2: Table S1). BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform prior ranging between 0 and 10 for the following cases: subset5.at, subset5.cg, subset7.cg, subset7.gt, subset12.cg, sub- set12.gt. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed three runs of 40 million generations, sampling trees and parameters every 4000 generations. Grafting – For grafting, the outgroups were removed, as well as Baronia brevicornis, the first Papilionidae to diverge and endemic to Mexico (Allio et al. 2020), i.e., we grafted at the most recent common ancestor (MRCA) of all Papilionidae but Baronia brevicornis. 104 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

2. Hesperiidae: Hesperiinae

Dataset – The dataset for the Hesperiinae consisted of 169 taxa to which two outgroups were added: Typhedanus ampyx (Hesperiidae: Eudaminae), Mylon pelopidas (Hesperiidae: Pyrginae). We concatenated 10 gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified 17 subsets (Suppl. material 2: Table S2). BEAST analysis – Preliminary analyses showed problems with the subset 3 (ArgKin_ pos3) which was therefore removed from the analyses. In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following case: subset17.cg. The substitution model for the subset 14 was also changed into HKY+I after preliminary analyses. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 150 million generations, sampling trees and parameters every 15000 generations. Grafting – For grafting, the outgroups were removed and the subclade grafted at the MRCA of Hesperiinae.

3. Hesperiidae: Pyrginae

Dataset – The dataset for the Pyrginae consisted of 77 taxa to which three outgroups were added: Typhedanus ampyx (Hesperiidae: Eudaminae), Pyrrhopyge zenodorus (Hesperiidae: Pyrginae), and Hasora khoda (Hesperiidae: Coeliadinae). We concatenated ten gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified 14 subsets (Suppl. material 2: Table S3). BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following cases: subset7.ac, subset7.gt, subset14.cg, subset3.cg. Preliminary analyses showed problems when using a separate molecular clock for each subset identified by PartitionFinder. We restricted the analysis to one molecular clock. We used a birth-death tree prior. We performed two runs of 100 million generations, sampling trees and parameters every 10000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Pyrginae.

4. Pieridae

Dataset – The dataset for the Pieridae consisted of 126 taxa to which three outgroups were added: Bicyclus anynana (Nymphalidae), Achlyodes busiris (Hesperiidae), and Papilio glaucus (Papilionidae). We concatenated eleven gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless). PartitionFinder – PartitionFinder identified 17 subsets (Suppl. material 2: Table S4). Phylogeny of European butterflies 105

BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following case: subset7.cg. The substitution model for the subset 7 was also changed into GTR+G after preliminary analyses. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 100 million generations, sampling trees and parameters every 10000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Pieridae.

5. Lycaenidae

Dataset – The dataset for the Lycaenidae consisted of 187 taxa to which three outgroups were added: Bicyclus anynana (Nymphalidae), Pieris rapae (Pieridae) and Hamearis lucina (Riodinidae). We concatenated 12 gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless and H3). PartitionFinder – PartitionFinder identified 12 subsets (Suppl. material 2: Table S5). BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following cases: subset3.cg, subset6.ag, subset6.at, subset11.gt_subst7.cg. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 150 million generations, sampling trees and parameters every 15000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Lycaenidae.

6. Nymphalidae: Danainae

Dataset – The dataset for the Danainae consisted of 7 taxa to which two outgroups were added: Euploea camaralzeman (Nymphalidae: Danainae) and Lycorea halia (Nymphalidae: Danainae). We concatenated 9 gene fragments (COI, CAD, EF- 1α, GAPDH, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified eight subsets (Suppl. material 2: Table S6). BEAST analysis – We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 20 million generations, sampling trees and parameters every 2000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Danainae.

7. Nymphalidae: Apaturinae

Dataset – The dataset for the Apaturinae consisted of nine taxa to which two outgroups were added: Timelaea albescens (Nymphalidae: Apaturinae) and Biblis hyperia 106 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

(Nymphalidae: Biblidinae). We concatenated ten gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified seven subsets (Suppl. material 2: Table S7). BEAST analysis – We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 20 million generations, sampling trees and parameters every 2000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Danainae.

8. Nymphalidae: Heliconiinae + Limenitidinae

Dataset – The dataset combined the sister clades Heliconiinae and Limenitidinae and consisted of 92 taxa to which three outgroups were added: Amnosia decora (Nym- phalidae: Pseudoergolinae), Apatura iris (Nymphalidae: Apaturinae) and Libythea celtis (Nymphalidae: Libytheinae). We concatenated eleven gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless). PartitionFinder – PartitionFinder identified 14 subsets (Suppl. material 2: Table S8). BEAST analysis – Preliminary analyses showed problems with the subset 14 (RpS2_ pos2) which was therefore removed from the analyses. In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following case: subset7.cg. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 100 million generations, sampling trees and parameters every 10000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the split between Limenitidinae and Heliconiinae.

9. Nymphalidae: Nymphalinae

Dataset – The dataset of Nymphalinae consisted of 83 taxa to which two outgroups were added: Historis odius (Nymphalidae: Nymphalinae) and Pycina zamba (Nym- phalidae: Nymphalinae). We concatenated eleven gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless). PartitionFinder – PartitionFinder identified 12 subsets (Suppl. material 2: Table S9). BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform priors ranging between 0 and 10 for the following case: subset5.cg. Preliminary analyses revealed problems when using one molecular clock per subset identified by Partition Finder. We restricted the analysis to one molecular clock for the mitochondrial gene fragments and one molecular clock for the nuclear gene fragments. We used a birth-death tree prior. We performed two runs of 100 million generations, sampling trees and parameters every 10000 generations. Phylogeny of European butterflies 107

Grafting – For grafting, the outgroups were removed, and the subclade grafted at the MRCA of Nymphalinae.

10. Nymphalidae: Satyrinae 1

Dataset – The first Satyrinae dataset consisted of 13 taxa, belonging to the genera Kirinia, Pararge, Lasiommata, Tatinga, Chonala, and Lopinga, to which three outgroups were added: Bicyclus anynana (Nymphalidae: Satyrinae), Acrophtalmia leuce (Nymphalidae: Satyrinae), and Ragadia makuta (Nymphalidae: Satyrinae). We concatenated 5 gene fragments (COI, EF-1α, GAPDH, RpS5, wingless). PartitionFinder – PartitionFinder identified six subsets (Suppl. material 2: Table S10). BEAST analysis – We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 20 million generations, sampling trees and parameters every 2000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the crown of the clade after removing the outgroups.

11. Nymphalidae: Satyrinae 2

Dataset – The second Satyrinae dataset consisted of 161 taxa, belonging to the genera Cal- isto, Euptychia, Callerebia, Proterebia, Gyrocheilus, Strabena, Ypthima, Ypthimomorpha, Stygionympha, Cassionympha, Neocoenyra, Pseudonympha, Erebia, Boerebia, Hypone- phele, Cercyonis, Maniola, Aphantopus, Pyronia, Faunula, Grumia, Paralasa, Melanar- gia, Hipparchia, Berberia, Oeneis, Neominois, Karanasa, Brintesia, Arethusana, Satyrus, Pseudochazara, and Chazara, to which three outgroups were added: Coenonympha pamphilus (Nymphalidae: Satyrinae), Taygetis virgilia (Nymphalidae: Satyrinae), and Pronophila thelebe (Nymphalidae: Satyrinae). We concatenated ten gene fragments (COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified eleven subsets (Suppl. material 2: Table S11). BEAST analysis – In order to improve the quality of our runs we replaced the default priors for rates of substitutions by uniform prior ranging between 0 and 10 for the following cases: subset5.ac, subset5.ag, subset5.at, subset5.cg, subset5.gt. We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 100 million generations, sampling trees and parameters every 10000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the crown of the clade after removing the outgroups.

12. Nymphalidae: Satyrinae 3

Dataset – The third Satyrinae dataset consisted of 15 taxa all belonging to the genus Coenonympha, to which two outgroups were added: Sinonympha amoena (Nym- 108 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

phalidae: Satyrinae) and Oressinoma sorata (Nymphalidae: Satyrinae). We concatenated nine gene fragments (COI, CAD, EF-1α, GAPDH, IDH, MDH, RpS2, RpS5, wingless). PartitionFinder – PartitionFinder identified six subsets (Suppl. material 2: Table S12). BEAST analysis – We used one molecular clock per subset identified by PartitionFinder and obtained good mixing and convergence. We used a birth-death tree prior. We performed two runs of 20 million generations, sampling trees and parameters every 2000 generations. Grafting – For grafting, the outgroups were removed, and the subclade grafted at the crown of Coenonympha.

Quality control

Species identities of the chosen sequences for the dataset were validated by blasting the DNA barcode sequences against the Barcode Of Life Database (http://www.boldsys- tems.org/), which has a good representation of European butterfly species due to a number of barcoding projects implemented in different countries (e.g., Wiemers and Fiedler 2007; Dincă et al. 2011; Hausmann et al. 2011; Dincă et al. 2015; Huemer and Wiesmair 2017; Litman et al. 2018). In almost all cases, the sequences came from the same voucher specimen itself. In 17% of cases (Suppl. material 1), the sequences used were from different individuals. In these cases special care was taken to use sequences from reliable sources, preferably those with voucher photographs. We estimated our time-calibration from a recent re-evaluation of the timing of divergence of higher-level Papilionoidea. We used the topology inferred by Chazot et al. (2019) as a backbone in our grafting procedure. This topology was fixed in Chazot et al. (2019), hence only node ages were estimated. However, within each subclade we grafted, we let BEAST estimate the topology in addition to node ages. Several sections of the European butterfly tree remain poorly supported. This most likely arises from the lack of molecular information as well as recent and rapid diversification events within Polyommatus, Hipparchia, or Pseudochazara for example. Further more detailed work is needed in these groups, building on preliminary studies (e.g., Wiemers and Fiedler 2007; Vila et al. 2010; Wiemers et al. 2010; Verovnik and Wiemers 2016; Vishnevskaya et al. 2016), which might show that some of the taxa need to be synonymised (as e.g., Erebia polaris with E. medusa; see Aarvik et al. 2017). Most of the higher relationships among genera are well supported, however. Exceptions with low support values are the relationships among the genera Anthocharis, Euchloe, and Zegris (Pieridae: Pierinae), among Agriades, Cyaniris, Eumedonia, Kretania and Plebejidea (Lycaenidae: Polyommatinae), some relationships among the Theclinae (Lycaenidae) and between Aphantopus and Py- ronia (Nymphalidae: Satyrinae). This also means that the apparent non-monophyly of the genera Euchloe, Kretania, Satyrium, and Pyronia in our tree needs to be confirmed by further studies. The only subfamily relationship with low support is Phylogeny of European butterflies 109 the sister relationship of Aphnaeinae with Lycaeninae. In Dapporto et al. (2019) Aphnaeinae turned out as sister to the remaining Lycaenidae, a result in line with Espeland et al. (2018), although with low support in the latter study. In most of these cases, the low support values are due to insufficient molecular information for those groups of taxa. We show here a synthetic tree summarising the posterior distribution of topologies and node ages, but the posterior distribution of grafted trees can be found in the Supporting Information, providing a distribution of alternative topologies and node ages estimated by BEAST. We strongly advise any researcher using these phylogenetic trees to repeat any analyses on at least 100 trees randomly sampled from this posterior distribution in order to account for topology and node age uncertainties. This tree can also help to identify the sections of the tree lacking molecular information and therefore points at the sections that should be targeted in the future when generating new molecular data.

Dataset descriptions

The analysed dataset (a concatenated alignment of the genes COI, CAD, EF-1α, GAPDH, ArgK, IDH, MDH, RpS2, RpS5, DDC, wingless, and H3) is available in NEXUS format and the posterior distribution of ML trees and the consensus tree in NEWICK format at DOI: https://dx.doi.org/10.5281/zenodo.3531555.

Conclusions We have generated a robust phylogenetic hypothesis for all European species of butterflies with estimations of divergence times (Fig. 1, Suppl. material 3: Fig. S1) as well as subtrees of major sections (Suppl. material 4: Fig. S2, Suppl. material 5: Fig. S3, Suppl. material 6: Fig. S4, Suppl. material 7: Fig. S5), a tree with posterior probabilities (Fig. 2, Suppl. material 8: Fig. S6) and gene coverage (Fig. 3). Our purpose is to provide a complete phylogenetic framework for use by the ecological and evolutionary communities. The demand for such phylogenetic information is high and various proxies have been used that are not ideal, starting already in 2005 (Päivinen et al. 2005). Although the topology of major clades in our consensus tree is largely congruent with the one by Dapporto et al. (2019), differences can be found e.g., in the monophyly of Papilioninae which appeared as a paraphylum in the trees of Dap- porto et al. (2019) and Espeland et al. (2018). Our tree also confirms the monophyly of most of the European butterfly genera in the recent checklist of Wiemers et al. (2018). An exception is the genus Carcharodus which turned out to be a paraphylum. This result is in line with the tree in Dapporto et al. (2019) and a recent study by Zhang et al. (2020), that revises the taxonomy of Carcharodina accordingly, lead- ing to a change of several names (Table 2). We provide a posterior distribution of 110 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

n n

y ii a o l s s

s s o o m a u

iu c e i

r o bu m l dr a r he li v s l l

e s l n na ca n i o i p a u o a oe thamel o n u na a a s

no t a d i p p i n c or m is i as a h m i o s a yxe ph sy p t m ss s a ll i c x c p m u s fe s s e r l d s a u o ol

e a r l ca ru u l x o u e s s a o u s p p au io i i us c a i r i s i n n a c h ni a m e u h il a t r

es s a s a c h ra i r st t a a o i a p d s i s i

o s a h o i m s o p nu id a c e r i i e i n li h t i bo o lv i th i t e a l a h l t l l ax a t h e l e ass e r um h i t i n h c o t m cl c n n h p c i n t s v a n n c n pi t p sy yr l r h n o r a r o h po y n a s eo e yn n bo y i c ry r co h ap y s c a r s p a ro r y s r p n Er r y er e s s lc s e id i t I Iphi r Pa i Pa e P t e Er P e s P e t Pa e n u a Ar r p ia cu s um Ze bo ne s d e l m eb Er Z er e rt d r i Er Z e l c s l l Er eb Er Z r o i u s n s u Ze a l o l cu l Z g e i e H l e c mi l Er eb o ge du u p u r is eb ia eb Ca e p e i cu i eb C e h l o a Er ia B e el i o d a r b P l r i al eb pilion c m e r o o r o t ae ia Pa in G ae ym ia mo ia es e hl t e r sse t er ia Parn G y r e c f Er eb ne ass O h m r e i Er ia iina ym a h a e er s styx e H h m ha f t ro en Er za H T y t s i i Er stir e h h u i eb ia le or nt te T c a p se ia p cc th eb ro h r i o b a r rh Papil pt T c l a r p i or a ic eb eb fe pa ionida er hy r i r o e Er id an e ina T a a l a l ia pr ia e T i i o p ia f et d ia od a l a av ia bvre as H C i i p l u eb ia te a es p a l a am m us s me on p Ca i ae op er S a l h a ba ii pi s ta Er ia mn scip ri na Sp a am od du Er oe e pi i thiope en i S h o Er Er eb la p ar r du us s s Er eb go S usc sch o s yi estr s S h a r eb eb ia si io u sc od du e i eb E ia rg M c h a r g lo s Er s M c o r m r ia ia ar r h a r a a e e e Er e oe on a Mu c t a d a eb ia eu ll a r h a a b er a C c s m h d eb li me e h i d t oi me ia ryal ge H C c r v e ia ip e Ca ar r n is a ia Er s n me Er Er m hy a p C a s si ca al lv e ae su la er y nn o a Er flav eb eb a e ii C r u s m r i re s eb mp le 20 d y g d l u de n a E r r u s ma ae eb ia e g n Er ia of ia to E y ca au ul an tica us P gu eb ia a go pl y P yr r us s a ca nt at ic Er st rg P g e r pa sci ut i y r u s c or e eb ia he rg n P g a Er o ae y r m r Er ae nd nn at e P y gu us r a Er eb ia s sera i e i is eb a P yr g in i eb me thiopsro yo r s c s na rd Er ia P y gu u ir li ns Er ia se P r s c o Er ia p du y ar p ne ri eb a P rg s o e i Er eb tr ol y gu c n e i eb ia lb ar sa P s rr u el eb ia er ia yr rgu o a q h ia pa ri is P y s l s Er ia da ga us rgu u w u u nc me la P y g fo e i eb je ba na P us v po e Er ni ol ri yr g s al rs ica eb ia ne ca P r u du rn se an y rg s a e s Er ia or nsis P y e mo v pi i ie s rgu d a u e ep ie nsis P i e na le Er Er bi nt Py pt d a j li mn eb a p ip ti e si a bu eb a Le a ea rh sa Er hr lis ep id r eo o a Er eb Er ia ia ha on 40 D L pt de x l tr s eb ch is i ea ry c rin eb ia cl rt m Le pt e a pa nsi ia ia au rist e id t yx f e Er ca o Le pt p er leo er ar ne di i rp e ne yx Er eb ve ssio na h L pt er x c ad le i ne y m la eb ia rn id us in Go pt er el tynd a ne yx or s Er ia en es e Go o pt er fl si Er ca si G ne n e eb ar s o pt lia e ie m eb ia lcar G ne si al ar e Er ia us o p c th eb ni iu G to hy a o hi vali s lf a E Er ia sp Ca lias a rys n r eb o s h ri one Er eb ro an s C lia c ro eb i ia nd ia o s om a call ou C lia au ic ia ot C h ep to ia i o Co lias p e Er m s l s at a a isty a ia Co lia er ce Er Er e n ro ne eb eb bi gn a d Co lias c casic o ia a d e in s id ia is a Co ia cau Er Er cyc em a 60 e ol yrm eb eb lo bl C lias la o ia pi a s m ec n Er di ia r us Co lia ae eb scoi oss o s h al ia C lia e i Er fasci da ii Co as p eg Ma li li ych ta ce eb s Co as t ra i niol ia at li c rid Ma a m ed a Co ria lo ce ni da o ch lidi Ma ol eg Ap tia al a n al on c a Ma Ma ni ur a P tia us ice Ma ni ol ag P on ed lid ni ni ol a chi i P ia e ol ol a j e nt dap a a h a t ur a r el tina i Po ia assic ni Ma alicar me d ont br i ni ssi e a P is lasto th ol na a e er ol n a ssu a Pi w ira Py cyp in is e ri Ap ro s r er ch e ha Pyro ni rico y Pi p a c t ris ue ntop ni la 80 ie kr e us a t ecili a P is pa Pyro itho a S ier ra ii hype P is nn Hy ni ra nu er po a b n s Pi is ma ne Hy ne at tus er rga e p phel hs Pi s e ia Hypo one e eba ieri ryon n ph lyca P is b ep ele l on ier api Hipp hele up P s n na Hi ar hu in eri alca e pp chia eb a Pi s b or Hi ar s ne P ri vag pp chia bo ri Pie e s ar cypr rd i tis gi chi onii e lo ta ia a c ie r Co oe rlon Hi h nsi i hl ha pp riste s n Euc e c Hi arch ns a hlo ae pp ia en e uc az s arch cret i E loe b ia ide Hipp ia pe ica ch pen heno arch llucid Eu loe up es Hi ia a ch aris e amin ppar leig 100 Eu och ard Hipp chia hebi th ris c ne arch se An a mo H ia me nthoch ris da ippar volg le A cha uneri Hip chi ensi tho is gr parc a bla s An char e hia n chier ntho em Hipp eapo i A euph archi litana egris thoe Hi a ari Z pyro pparc stae gris rsi is Hipp hia s us Ze eve riens archia enth chloe ana mad es Eu granc Hipp eren chloe ridum H archi sis Eu hespe ippar a azo loe chia m rina Euch elemia igu N e b Hipp elens Million chlo ia archia m is e Eu auson Hip ers m chloe a parchia ina Eu mploni e si Hi hermio years chloe pp ne o u s archia a E insulari b e Hi utono Euchlo i ppa e i er rch R i cram ia syriaca n uchloe i E Hi a na ppar o is l uci chia e ear fa d am Hipparch gi H mas ia n i A is aca eomiris n Cigarit Hi p pha pparc i imor hia d a d gomera h Lycaen a Hipparc n a phlaeas hi e n a f a H idia Lycae ipp e i archia bacc aena bleuse hus i Lyc Hipp n irgaureae archia tilosi a Lycaena v Hi e ana pparchia wyssii Lycaena ottom Hip parchia tamadabae Lycaena tityrus Hipparc L ena h elle hia fatua y Lyca Hipparch c a alciphron ia statilinus a Lycaen Pseudochazara merc e Lycaena dispar urius n

Pseudochazara williamsi n Lycaena thetis a

Pseudochazara euxina e Lycaenathersamon Pseudochazara tisiphone Lycaena hippothoe Pseudochazara orestes Lycaena c andens Lae Pseudochazara cingovskii osopis roboris ea Thecla b Pseudochazara amalth etulae thelea Favonius qu Pseudochazara a n ercus amymone Tomares ballu Pseudochazara s a graeca Tomares noge

hazar T lii

Pseudoc To h m

azara geyeri ares c allima ch e ch Pseudo ri Callop us

zara prieu c hrys avis Cha l

i Ca e n llo

ersephon phrys rub a i Chazara p is Callo

brise e phrys Chazara Ca suaveola virbius llophrys Satyrus N chalybei ctaea eolycaen tincta atyrus a S a rhym S erula atyrium nus atyrus f Sa pruni S circe tyrium rintesia Sa w-albu B ryas tyrium a m inois d Sa caci M husa tyriu ae aret S m spin usana ialis atyrium i Areth s glac S led Oenei nes atyriu ereri olixe S m ili neis p rna atyr cis Oe is no Az ium e Oene gna anu sculi s m a A s jes enei utta zanu ous O is j Z s ub

Oene issa e izee aldu l a ri s

s m e Zi a kn

ei on d ze ys en m i eri na

O is am l Ta a ka re a r rs

ene bo ucu and O s h s nei ia Tar theo ra

Oe rpe p ucu ph

s ta a Ce s b ras i m a t

ne athe last lkan us l y C rin i

Oe a ga sis acy a a cus e N r argi ch La reus giol elan ia l a mp ma us M rg larissa P ide rs ana a iae hen s b halli Mel argi ss Ph ga oet elan a r u es e ris a icus M gi a in P nga lco anar rgi sa he ris n Mel ana eru P nga ario el h ica he ris n M gia p an S ng tel ar it ge col aris eiu lan occ ar Pr ita na s Me gia ia e a nti us nar arg rop I ep des ith ela lan te a ola hilo o ous M Me s e I na te rio ma a eg lis olan io s a n thi a ph ta a las nth Yp ebi ien ia Gla de rac ter or n G uc bi ias ro ha rca ta lau opsyc lita P mp a a et G co ta ny ph rd er la p he no ym ga d T uc syc me oe on a an o ur op h C n ph a le her P an syc e a lano oe m a a s an h le ps C ny mph ph nn P eu a e xis no y m ori s s do ta pa Coe on ny ru Ps eu ph yg ph en o ha c do is do il et o Co en p a s Ps eu p ote ica s Co ym ph en is do hil s n m op ll P eu ph ote ba

no ny d ary a s d il s b vi o L op u

oe no rh m ulli P eu ote a s

C e a s y se d hi s a r a u P l b c o

Co ph ha a t il L u p ot ag o b

m p ph ph is a ep do hi es en iae e

y m l lot

n y ym m rs y C tot p p c

a n h e an er

o on on p hy on o yc es ilo s

n i o r

m To a

e en en ha a t eri s d lyr p te ba pt g

o a n i s to e u

Co C Co p ph yc pu m C g u iri s s

e e u e s th vi n m gl ip a

nym y a d n C p ia w ou cr

o e y t id e a h a i u f b s ma

on n

en o hr n C p o isch b p a i

o oen ymp ha la e up id ar an C n p a e n e Cu o g e u C ph ox e ido d ia ri s no ym m r im e Cu p ec d oe on y ia cl hin id al ol es C n a ria Cu p o c or e on irin ni ac C id o e a en K iri a ge es h L p o s tas tu Co o K ae id a u id m iris s C ng o ia r Fr th o i pi ge hi h a a r l ni Lo ip ip er x P ey od or m ar g a in le e e qu u ar e x e x e er P be r s i s P g rg m a a le ia g ni ar ra na e P b ju t a i a ta eg ta ia D le e s a ro lb ar P a m li m a P b ju c a P m ra o a a n le e s i r hy m op id er a Pl b ju g l o pa tr e a s i L e e s d us us si e d iu n i Eu b ju b a a a p m s a b e s el s L at a ta ta a us e y K m ji m t a j th re e d a lie a s pp us e K t d e rg r om m ma e i p s i K re an o a y i mm x ys ip lti n t n l ro si m io om ra x e is a Kr re a ia e ia o g io s i a hr e c rt e t n e n La s a as h c l a ia Kr e a ia e wi o L L s p a l ta n ur u i m La C u s e m a C e ia h y m th to th ta n e p o na au i ssa e A y ia tr s i e n a by r u g a n a p lu d an b a a ion s K n ia s pp e s o D Li a ad ria ir e r n D e ae l de a Ag ret i p p ic it e de i i d s y h i a a l ar ia A a es s la i it e no v l g ria ni e ru el a c ea e ia A m o M e ta he r r a g ri de a o n s M a li rt ea u n A r a p ia lit e te i g i d s ps t a s ia A r a e il rg M pa lit a a a m x e A g i d s o y e u Me e ia n r a e rb lo t a a i a N G gr i d s d e s ea Me it e d c eb y a e a i ri a l a o at ie m A la ia d s p r tu ta lit e it a h n r p ri es y d l l ea e h A br d zu re a u e M e ae p na a r c es s ita t or ia l A ic i o a n M M l li a th in a in r a c lli n u e e e iv a A i i q a ea e r ci a m u gl u c s M ta a du tr a Ar ic l h ic Me a r ym n A a a or u a il i u li it a d ia i i s n o e l e A r ci a c n do s e ea di tur a i r t ro cy M a a a ed n N r c a n am er M it e ta a ia i i n n li u a L eo c a a ic o e a el ta ea m rm d i L ys ia n i e th n ii m rt ia er s n l ta e n s L ys l a e M e M i t s i ri i a ys a s si l as n yn u a Ly ys o xe a s y i a a p s a n g n M au L an e ry nt p s an nd d t rx Me dr s c i iop la L ys s e as d s o t P a r y is e os m ys a dr t n e y y ya a n P a nd d r is s r y sf m o a b a s ph dr h a m or a Po o a n r i p r e bu lyo a el s o hl l e P l n d ra c c yd d s m s bu a A P yo o hy y li a l g p o l d r c la o Eu h s d th e a P yo m a r p Eu a yc a o tu o l r c o y e p a na n l us i r P o yo m a rg ph au a in Po l ma h a ri d l u h a c- n ca t a olyo yo m e v a e s e Po l i el do u Eu im po ti i a yo m m sp on s E l n i s P s Eu a ni P ly m m l es t o mp s x is a a n o a t bi i ydry i s ich ur l l si ui P mm m n iu na ni o a o l u a p li a P l yo om ma a t ca h al a d i P o m u s t y al o s l yo a n s Ny a is i t lca r il is P ol t is p Ag en s l yo us s a H h lyg a a an s Po ol yo m ma t e u ph la P o u n s p yg v et ri H yo m m at tu ph l ni ca a i a elic e P t sc s im si i o a P yo m E gl r n in ly m s h a ea s ii id o nae enit P a Po le l im o l m u L P ma m m n s at s m s gi n o yo t e Ag A a vu a e Po l o m m d h y tu c ni P o yomm a us es m a Po a P l m s ir i a u j a o yo ma r n P l u i a e Nym ia a re r t e r i i e l yo m t c s N v ur i e o m a

e ra l a o l yo m a us Ny ss i t s r

t d o l yo m a p i l p e s

n a a l u t i

n o yo t ce n

essa i m r

e e sy r or i a l mm a e at s yo a h

tu is u r

l l m u yo m

ga ha r tu n o

f g is i a gs

A t a a du a a s a e ob yo m a

n h n r u

a i s

o i n

l ia t i e

e e

r a il

o m

a c sca i a at s do

a s

t r s p i

g c e a u

a mm l

r r es t tu

V a an a ph m a s v i s c

a i o i mm i n

e s n

schn n p n

Ap an o l r mm ma a n s

i p t n o i s

r a u s d

m i m

a m

o ia h a e ce ma u p essa or i ul a t o V l

V a e

r s h

l f al l e

a o ia na p h s r

Ap r l i o o a t u i a

r e p

c d a

p p o i p sc a r a v t us s l y e d

o m a

r t p

g s o g h ia o o p i m g l i p d t u s niobe

a i ad m

a r

a e hi l lo d u t a

an o ri n sa t Ar i s u

o i il a as a a odi

u ne

l a u

re t ap

n B o B l sk i at u s en a a

r h

a g a h t n u a a u r or t

V a i s m

a g o s c

u i t t

lo s e s r us s

i ia d s da i

n i

or r i u me o i B s la a p e tu s

Bo r r u v

l t en n

l n i n s q t ph

ol a e a a

a n f s

Bo i o

s p

i o i i a t s

Bo a s a ri i or a f

o a a s u

o l i i

o i a pt

i i

e o

r a l p d a r r n mo e s

B Bo l lo a is c

i n

h hu

i r r e r l

s i

o n n o t

t e l o e o

B o o i br g le B a ic a t

o o r a e e u

lo a l

l th y t

i o o ic m i

Br n

e r

i n h B i i l e i

ri nn

Bo r r N

o B B N mf p u t s c

r s m s o e s n lo o e

b y

i a ip e

L n

b im

s m s

r s h

lo en

B p r e

Bo B ss

i an

a g e

lo I

I e y s

gy r L ta a r i

o b

S B Bo L cu

o F da g i

F B s ei a

B Ar i m Ar B en to

F s Ar s en

s ae s

i o s s

Figure 1. Time-calibrated tree of European butterflies (Lepidoptera: Papilionoidea) with time scale and taxonomic assignment to subfamilies and families.

Table 2. Proposal for changes in the current taxonomic checklist by Wiemers et al. (2018) according to the recent revision of Carcharodina by Zhang et al. (2020).

Current name (Wiemers et al. 2018) Proposed name (Zhang et al. 2020) Muschampia cribrellum (Eversmann, 1841) Favria cribrellum (Eversmann, 1841) Carcharodus lavatherae (Esper, 1783) Muschampia (Reverdinus) lavatherae (Esper, 1783) Carcharodus orientalis Reverdin, 1913 Muschampia (Reverdinus) orientalis (Reverdin, 1913) Carcharodus floccifera(Zeller, 1847) Muschampia (Reverdinus) floccifera(Zeller, 1847) Carcharodus stauderi Reverdin, 1913 Muschampia (Reverdinus) stauderi (Reverdin, 1913) Carcharodus baeticus (Rambur, 1839) Muschampia (Reverdinus) baeticus (Rambur, 1840) Phylogeny of European butterflies 111

e s

m a

r a

a l

E r a n Erebia lefebvre n

h Ere Erebia zapateri a a t o r o o

e d t s n ic i a a i s Erebia pronoe

b o

Erebia albergan a E p h y

e b Erebia dabanensis Erebia stiria i apollo f p a x E c Erebia styx s Erebia rebiapolari medusaE is Erebia triariu ia montana

Erebia palarica e Erebia meolan a rebia melas s o s l Erebia sthenny rebia scipi n E cassandr h Erebia pandros e e a e polyxen aluspalaemon m cretic rebia flavofasciat i d o d a i a i o o ax l l i i o r s r l l i

i i l s i c c i i d

i i

E p x Erebia pluto p a p a pterusmorpheus nu h Er h teon a i a rebia aethiop a a ol s o p arnassius p arnassius phoebus arnassius r I I e P Erebia euryale i P e e Erebia melampusErebia eri P Parnassius mnemosyne Parnassius P P erynthi e comm pol bia gorg o apollinusArchon i a Erebia lige Zerynthiarumina t Zerynthia Zerynthia s Z Erebia mant s Zerynthia ErebiaErebia orientalis sudetic a Zerynthiacer Zerynthiacaucas s tr m He alce E s Carteroceph Carterocephalussilvicol u e Erebia rhodopensirebia epiphro o Borboborbonica e Pelopidasth n s Gegenesnostrodamu od u m e e Gegenespumilio r ri Erebia christ phyle a Hesperia o a Erebia pharte Ochlodessylvanus a o Erebia aethiopella s hymelicus ac r s Erebia mnestr a Thymelicus christ e ot ellu T s ali a Erebia jeniseiensis Thymelicus hyr rch fe t hymelicus sylvestr E o Thymelicus lin es fer T t s rebia gorgon Ca u i a orbi a r Erebia cassioid Carcharodus s lavatherorien tic Spialia phlomidis a locci n Spialia therap f Erebia oeme pialia rosa Erebia arvernensis i Spialia sert Erebia nivalis S hampi odus Erebia neleus s Spiali i a Muschampiauschampia cribrellusc pr e Erebia tyndarus s a M loy Erebia calcariu e Mu r e E Carcharodu a e taure eda rebia hispani e Carchar m n E s Carcharodus s rebia rondoui calia i Erebia otto Carcharodusarcharodus bae staude ce E C nni e s Erebia claudinrebia callia Erynnis tage a Erebia epistygne Ery oide yrgus v e e s s P al a Pyrgus ca tula m m i Erebia cyclopiu Pyrgus androm s ErebiaErebia dis an s Pyrgus sid rgu serra i a Pyrgus cartham r is a Py yrgus malva ErebiaErebia discoidalisErebia fascia rossembla P a Pyrgus foulquie e Pyrgus armoricanus a i ManiolaErebia jurtina s Pyrgus onopord M rgu inar ii e i Pyrgus alveus c a aniola megal ta i Py s gu i M edda Pyrgusr warrenensus cirs e a ManiolaManiola telmessianiola chia g Maniola halicarnassu Py r rnic Maniola cypricola Py is a mors e a Pyrgus carline nura eptidea duponchel i i Aphantopus hyperant L n Pyronia cecilia g Leptid cleobul sa is Pyronia Leptidea juve rham o s a eryx x rin Leptidea sinapt ry fa ra HyponephelePyronia baths lycaon aderen tit s Leptideaonep real ryx m H honu G e leopat Hyponepheleyponephele hue lupina onepte eryx c lla s G onept t ryx Hipparchia sbordoni us G nep te s Hipparchia christense eba o ilia flore si G onep le ien e G r Hipparchia cypriens hyafaca bner Catops al Coliasas e Hipparchia cretic i Coli aurorina Hipparchia semel i omon Hipparchia vo n Colias chrysothemphic i Coliass ate H is er a e ipparchia blachieri Colia s e Hipparchia pe a a Hipparchia aristalgensise Colia myrmidonsic Hipparchia neapolitan Colias croc ca cau a llucid Coliasas H Coli e ipparchia l a ch Hipparchia s eus Colias hecl i Hipparchia made olias ty g eigheb C tae ce Hipparchia a Colias palaeno cra ridi enthesi ice Hipparchia azorina Aporiatia chlo miguelensisrensis Pon a Hipparchia mersina ontia callid ice P tia edus Hipparchia syriac Pon ri Pontia daplid ae HipparchiaHipparchia hermion fa s kruepec Pieri nthi a Hipparchia au Pieris brassi cheirastoni Hipparchia neomirisgi ieris P is wolla tonoee Pier e H ii Hipparchiaipparchia bacchus tilosi Pieris rapa eris mannne Hipparchia tamadaba Pi erga e Pieriss bryoniaa Hipparchia wyssii Pieri Hipparchia e Pieris balcannapi gomera ieris e Hipparchia fidia P tis evagor H Colo tagis ipparchia fatu hloe a Hipparchia statilinus Euc charloni Pseudoc a ae hazara tisiphon Euchloe baz Pseudochazara oreste Euchloe a s P peni seudochazara cingovskiie Euchloe euphenoidees Pseudochazara williamsis damin Anthocharis e Pseudochaz Anthocharis car i Pseudochaara mercurius Anthocharis damon zara Anthocharis grunere Pseudochazara euxina amalthea pyrotho Pseudochazara anthel Zegris e Zegris euphemi Pseudochazara ea Euchloe evers s Pseudochazara graeca amymone Euchloe grancanariensiia Pseudochazara geyer Euchloe belemum Cha i Euchloe hesperid zara persephone is Chazara prieur Euchloe insular i Euchloe crameri Chazara briseis Satyrus virbiu Euchloe simplonia s uchloe ausonia Satyrus acta E ea Hamearis lucina Satyrus ferula Cigaritis acamas Arethusana arethusa Lycaena dimorpha Brintesia circe Lycaena helle Minois dryas Lycaena phlaeas Oeneis polixenes Lycaena ottomana Oeneis glacialis Lycaena virgaureae Oeneis norna Lycaena tityrus Oeneis magna Lycaena bleusei Oeneis jutta Lycaena alciphron Oeneis melissa Lycaena dispar n L Oeneis ammo ycaena thersamon Oeneis bore Lycaena thetis Lycaena hippot Oeneis tarpeia ho Lycaena candee Melanargia galatheas Laeosopis roborns Melanargia lachesi Thecla betulais Melanargia larissae Favonius quercue Melanargia russiaa Tomares ballus elanargia pherusa s M Tomares call Melanargia occitanicge Tomares noimachus Melanargia ar Callophrysgeli avi Melanargia inesa Callophrys is Proterebia phege Calloph suaveola rys Ypthima asteropea Callophrysrubi Sat chalybeitincta Coenonympha arcani yrium prun Neolycaena irh r Coenonympha orientalis Satyr ymnu S ium w-albu s Coenonympha gardetta atyriu Coenonympha leandea Satyriumm esculi ilic m Coenonympha heros Satyrium ledereis Coenonympha corinn Satyrium Satyriums piniacaciri Coenonympha amarylli Azanus jeso a CoenonymphaCoenonympha rhodopensis tullias Azanus ubalduse Zizeeria us oenonympha pamphiluss Zizeeria kn C ysn Coenonympha thyrsine Tarucu karsandra Coenonympha glycerionus Tarucuss balkanic theophrastu Coenonympha doru e Celastrina argiolua us Coenonympha phry a Lampides boetic Kirinia climen Cacyreus marshall s Coenonympha oedipp achines Phengaris alco s Kirinia roxelane u opingaiphioid a Phenga s L x P arge hen ris ario i ar a Phengarisgaris nausithon P Pararge aegerir n ararge xiphia Turanana P a Ps teleius Pseudophiloteseudophilotes tayg barbagbaviuus paramegaeraia Lasiommata mege a Pseu e tica us Pseudophilotesdophilotes abencerragpanopt Pse Lasiommata us s s Pseudophiu LasiommataLasiommata petropolitan deidam u dophil LasiommataCharaxes maer jasi is Scolitantides ori iae Praephil otes lotes bavicra Danaus plexipp ia Iolana debilitat t e us ter Iolana iola on s DanausLibythea chrysipp celt ot as G es o m a la an n a Melitaeataea aurelia a G u thracia eli la cop s M s Glaucopsycheuc sy alexia Le op c s elitaea vari sa syc he M e Cyclyriuspt webbian m n ot he elanop Melitaea parthenoideselitaea athali a Tongeia esfischer paph M p ia Cupido osir iri x Cupido minim tho os s in a s Melitaeaelitaea britomarti celadus c Cupido lorquin us M Melitaea deio C taea upido elitaea diamin C is i us M Meli a upido decolorat elitaea ornat a Cupid Luthrodes galb argiade u M ym ia s d a Freyeria otrochylu Melitaea phoebe di n al ii elitaea aetherie a Plebe c s M i Plebejus id e a tas P j Melitaeaelitaea arduinns matur a lebejus usbellie us M Melitaeaa triv a Plebejus argyrognomo y nthi Plebejidea loewargu a ydr Eumedonia eumedo h ainii a s p t Kr s s hydryas idun a Eu p fon s Kr e s K e tani Eu s re t ri de o Kr ania a Euphydryas intermed s m Kr e tania Euphydryas cy u t eurypilu thomela Cyaniriset ania semiargu hespe i Euphydryas aurini K i a ania trap xan s Agriadesretania or psylorit n aualb e Agriades optilet s ymphalis antiop v o ephirus r s N a c-album i Agriades pyren p p ica n EuphydryaHypolimnas misippus i ia Agriades darda y i ichnu a laon s t i Agriades glais n u Agriades aqui s olygonPolygonia egea A i Agriades Nymphalis ymphalis tala a G b NymphalisN polychlorP Aglai a Aglais urtica Ariciala cramer itul s an s Aricia antero a v s b u le i Ar r ir s A o zullic e s meti a i c aic a Ariciaricia montensici glando Vanessa vulcan a Ar ul nu s a u VanessaVanessa card hnia patura ilia ur A u h t s Neolysandrai coelestin m s cya l s s A ricia cagesti nicias o i sc a tani e Lysandra bellarguia a n a Lysandra corydoni o a Lysandra corido a rr Ap L a n Ar Apatura a rt onen s n Vanessa virginiens a Lysandraysandra albicans ca e Lysandra a e e Polyommatus amand Polyommatus escher x s Poly er i s P si Boloria ti i Polyommatus celin s x Boloria charicle Polyommatusolyommatus ero thers Boloria angarensi Boloria seleni s Polyommatus icarus e s s oloria oscaru Polyomma Boloria di P om s a Polyommatus dorylas B Boloria freij i Polyommatus damo a Polyommatus damon olyomma e Po e P a Polyommatus admetu h oloria frigg Polyommatus riparti e e Polyommatus nephohip P m Polyommatus dol olyommatus damocle a P i P P P span lest e P oloria euphrosy B c P oloria improb napaea o l elis i Boloria thor olyommatus violetae yommat a s a l a o a o i s o B o o o a l o n B i t l tus daphni Boloria selen u l i in n r l l h y l u l dor l y y i c

y ss iaalaskens y a p o

e a p o o s an n o u l Boloria tritonia o o a Boloria polar oloriapales m g o m m p m im his t m

u ci d m m B i a t us

u p Boloria oloriagraeca paphias a us

i v e c m m m nt i s hecate s a m e s r m i m

B r s Bolor i nivesce s a u golgu a s a i t a s

i a

i i a t i s a t u t s iphigenia r i i t t s Fabr t

u u i t t i

Bre t i Boloriaeunom n u t

p Boloria aquilonari aglaj Speyeria u a te s o n u u s s s enth n Fabriciananiob p s e e s s

s e s s

e e h f s

Fabricianaadipp f Argynnislaodi lathonia ssoria a Argynn Br I N a

o u I m s Brenthis daphn Brenthis t u m i

N i b i m r l r m n i m Argynnis pa Argynnis g o n L p r u L s L e e a

h f s e e

r s n n

i i d i

c s s s s i s

e a

u t e

n s

s i t

s a ameno s

e i

Figure 2. Majority rule consensus tree topology of a set of 1000 trees from the posterior distribution of time-calibrated trees of European butterflies. Circles3.0 at the nodes display clade support with a colour gradient from 50% (red) via 75% (yellow) to 100% (green). topologies and node ages for researchers to be able to take phylogenetic and node age uncertainty into account in the analyses. The tree files are provided in standard Newick format as output from BEAST. Since there are easily applied methods to prune the phylogeny to the species pool of a particular study, e.g., the ape package (Paradis et al. 2004) in R (R Core Team 2018), our tree is readily applicable to a large variety of ecological analyses ranging from the very local and regional scales, where the species pool only represents a subset of the European species, to the European scale. Since butterflies are an important indicator taxon for biodiversity studies, this time-calibrated phylogeny will provide a solid basis to advance our understanding of large-scale biodiversity patterns and underlying mechanisms by allowing the incorpo- 112 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

s i

s Callophrys

Lyca s e L

T Lycaena hipp Lycaena al e a y a ides n o L a c

Laeosopis robori e h i s i e o Favonius quercus s i Ca r ri L Neolycaena rhymnu mar ycaena canden a

Ly p a a ni e n a

e a m u r e Lycaena thetis y L e

s e o

Tomar na thers in Papilionidae a Thec o n T c llophrys suaveola caena dispar y n m u a hen c l plo da

a g m Call o c es ca a ularis

a e m Satyrium w-albu Call r ru p

l h i sonia

e i amer a a ia mares ballu s

c m hoe ar r g lu Satyrium ac o

i eme

b v p d d n t chalybeitincta e n

a c

c eu e t versi Satyrium prun Saty is la betula a ia n in

op t

a a e a a grancanarien lo ciphro r a s s ophrys rubi o e is T ris e s r

a i e r

n n n l n i z t S t a a limachus m e hesperidum i oe en a Hesperiidae s nogelii i r a

h oe s e a e

amon t e e oe au Satyrium esculi e a e Z lo o h r e rucu atyriu o euph ari Satyrium ili y loe belemi a p n Azanus ub r l

a o

a Tarucus a hl r a b izee Azanus jesous a h thoe e ys avis a l h agis ia r Ziz i h h m h ch t

n e c

c c ch um ledereri c Celastr u c e i l i Cacyreus marsha g c e ca n

l i c

y y o n y l a y uc e e uc s thi n ch o ni hocha o lo e evagor pi o Lam s eeria k u h a e

L L L lo L uchloe C t s Ha r E u h s E t lo a e e Euchl m sp Euchl t s to ia Euc b ry ga P t s E th i an E n c Pr heophras aciae E ch anni s Zegris pyro ch hlo b r Pieridae hengari Zegris n P An er karsandra An c ot is s di pides boet An u l la i ae Pheng A r i s rueper l a Glaucop Phengarish i b s Eu rapae ssica na m Scolitantides E o ri is k enga a i i Euch ie er dice philotes nysnaldus ni Eu i chei i lkanicu cis C s wo ra e P ie i dus o argi P b n Pseudoph P is e taegi o Gla G Pier er is s i r a dapl call he Riodinidae Pseudop a r Pieris m er i d i laucopsyche nausithous is alcon t a Pieris e ris c a Pseudo Iolana r o us P a chloridice laen ucopsychesyche melanops is tele Pi m e l a r asica Pseudophi T i us Pi ont ty p c one uranana Iolanaan io cu s Pie nti s ea s a l P ntia rion l Pontia oria cra s hecl a si th s i o au oc hem ilotes Po p lia ia c r in t n Pseud h debilitata r o ius P l as s my ate com e a Lycaenidae Pseud p acia A a iensis i rion c hi or r loteshi Co li er er Co o ella lotes bavius 10 genes Coli ias r ad le l abencer t pap alex las s C o o ot aygeti Colias liasas p m eopanosatr u Cy ph op barbagi ri b Le e Col oli ias aur o ni cl hi s hos Co e m Nymphalidae p ilot is C ol yx cl a y lote pano silia eryxfl x fa to ca C t ri es vicrama Coliasolias chrysolia alfacas hyalp e y x cl Cu Tongeius webbianute ragus o y i a Cupido s s a C r ic p ba p e Co at epterpter e ryx rh i pir te C e realnapisrn i heli do de on pt te e e c Cupido alcetaa fischeirithous ton s Gonep e p rs G on n e o on Cupido minim a G n ea si juv p i s C c rgiade 5 genes Go a m si u o e a du Cupido loratus s Go eptidea d eus FreyLeria pido L ti de lv uthrode p ti ea enenrdi s Leptide id a r Plebe osiris L ep s ar e P L pt u w a l lorquini s e rg nopoin us ebe t L gus foulquiero i ju Pl Pleb rocs u Py r us s g s rg u Eu s a ebeju jus alba Py y g arae m Plebejrgyrogneomon hy i P r cirsiin ulae ju a lu Py c K edonia eume s s idrgus s rrat ae K ret i b Pyrgusyrgus carl e retania dea ellie as P us armorican an Pyrgusg ia l ri s Kr Kr e oewi Pyr ae de u Pyrgus sus cacaliaelv oi eta et hespericry d g v Cya K n ani p on i Pyrgus centaureae ma retaniaia a ilus Pyr us ni se trappi Pyrgusrg andromede yi i A ri a o r Kr griadess se opti ph Py s e p ir Pyrgusgu sma carthaml i ae Agri tania psylm yla us staudeticu r Agr ades orbituluiarguson Pyr nis marl tagesus Agriadesi pyrenaic Pyrgus sida fera ades da l rynnnis et E lavathoccie Agri or e Ery l r ita charodus bae m Agri ad da Carcharodr s orientalisto Ag es zul n s Ca arodus f m Glabroculusr ades cyane aquilo us archarodush rodu essellu iades gl us C arc ha t Aricia lich C rc hampiaia pro cribrellu i Ca amp morronensiandon Musc r Aric uschchampia e M s a orbife us Ariciaia cramera an Mu osa ori te s Spialialia r Arici Aricia ros pi lia sertrapne A a S the us Neol ricia artaxerxe niciass Spia a phlomidis alceaen m Spiali s ysandraAricia coel oagesnten pialia us tripolia Lysandra S rod Lysandra c sis Carcharodua estinatis rch bellargus Ca rax Ly Lysandrorydon Thymelicus lineol on sandra ca Thymelicuselicus sylvestris hy i a c ius Lysandraelestiss hispanorido Thym Lysandra albi n Thymelicus acte Polyommatus ima ria comma Thymelicus christo Polyommatus thersitescan a Hespe mus Polyommatus aman eschers Ochlodes sylvanus nostroda Polyommatus dap i Gegenes pumilirax Gegenes Poly du ica laemon om s Pelopidas th a Polyommatus icarushnis Borbo borbon Polyommatusmatus cel ero Carterocephalusrocephalus pasilvicolpheus Polyommatus nivescenss Carte Polyommatu ina Heteropterusaucasica mor Polyommatuss dorylgolgus Zerynthia c as Zerynthia cerisya Polyommatus ena Pol Zerynthia creticpolyx yommatus damon Zerynthia ssandra Polyommatus damocliphigeniea Zerynthia ca Polyommatus s Zerynthia ruminaus Polyommatus adm hon apollin nephohip etus Arc s phoebus Polyommatustamenos Parnassiu o ripartii Parnassius apoll Polyommatus da assius mnemosyne Polyommatus violmonee Parn tae Papilio machaon Polyommatus fulgens Papilio hospiton Polyommatus fabressei Papilio alexanor Polyommatus dolus Iphiclides podalirius Polyommatus humedasae Iphiclides feisthamelii Polyommatus orphicus Erebia styx Polyommatus aroaniensis Erebia stiria Polyommatus timfristos Erebia montana Neptis rivularis Erebia neoridas Neptis sappho Erebia zapateri Limenitis populi Erebia lefebvrei ducta Erebia prono Limenitis re Erebia e tis camilla melas Limeni eugenia Erebia scipi Issoria Erebia rhodopeo a lathonia Issori ate Erebia nsis this hec Erebia mnestra Bren daphne aethiopella Brenthis o Erebia nthis in gorgon Bre ndora Erebia oe e nnis pa Erebi me Argy s paphia Ere a ligea Argynni odice bia eurya nnis la a Ereb le Argy a aglaj Er ia erip peyeri ippe ebia ma hyle S na ad Ere n bricia elisa bia me to Fa na be Ereb lam Fabricia a nio Ere ia su pus cian mia bia detica Fabri euno ca Ereb pluto loria Ere ia go Bo loria grae s bia f rge Bo ria paleea Erebia stlavofasc Bolo napa s Ere h ria nari Erebiabia ae p ennyoiata Bolo uilo sis an n s Ere dros ia aqlaske Er bia thiop e Bolor a polariia ebia me s loria loria ton Erebia dus Bo Bo tri gga polar a loria fri Erebia triariusis Bo oria E Bol improbane rebia paalbe ia e Er rga olor sel ore Er eb l na B loria ia e ia me aric Bo oria thia d Erebiabia da ol a Bol or Erebia an Bol ia freija je banens or syne Ere nis Bol hro Ere bia or eiensisis p b e ient ia eu oscarus a Er ia pip ali s lor a ni Erebiebia ch phr hro s Bo E art n Bolori ria titaricleais re a e Bolorialo selenisa s s E bia claudiist Bo ch en ri Erebirebi n i ria gar ra i s a el na olo an a Er casseus B ia i E ebi a ar Apatuura meti a rebia ac vernensisio Bolor at an Ereb tyn ide lev dui E d s Ap Apatura il r sis Ererebiaia hi ni a aru lcariuss hnias a ca Ere b va es giniencaniata E ia s li ir l n rebbia cr panis Arascan v vu la s io Erebia ep on V sa a ta i Ere ia al d a a icae ot l oui nes Agla sa E ias nu E rebbia tom Va Vanesnessas gea rebi i a ch e m Er ia di st an V s i Ereeb emblsa ygn a Aglais urtia albu a cyclopi lbumos Er biaia di e Aglai a c- lor E e ro a olygoin las a Manir bi ss P vaua p s eb a lych tio Ma i fa s ii us ygon Ma a coi po ippu niolol eddasci Pol phalisis nthomes an tainiiia Ma a dalis a li is n ia Ma niola m a x m on ri h ni a ta is t Man o nur egal Nym n ia Manioln l ymphal mpha s aucy duna a P io a c a N phaly desf i ed i la j hia g a m N rya rn Pyroniyr a ola te ur yas ma A o tin Ny ypolimnasryas ryasr erm Pyrop nia a ha lm yd hyd nt h cy a H up i matu e H a li e ph phydhyd a trivia a Hy ypone nt c pri c s u E u p as uinna t Hy n ti e arnasisa E y d be pone ia o t c co E Eu taea didy na ia Hipp p ho il i ar r e H p b u ia la o Hi onephe ph s hypenu sus a ho inx ippa at phydryasphydrMel Melitae p c a H p a p hseba s u u e mina a Hi i rc helee lupi E E ta a H pp pa l ea sterirelia s ppar rchiah cy e li a H ippa elitaeae aetheriaea de Hip archrich ia lyc ran Melitaea i ip le M M Hipparchi s huebn a lia Hi p i t aea ea vanori s pa archiarchichia a bord on us MelitMelitalitaea di e a Hippa a c n h H ppar chrispr lita th t H rch a litaea au H ipparc a leighe onii Me Melite e ea deionea i p reti ien ar Hippaippapparch e eri M M p a a ius ra H c i t it a H rc a vo seme l c ensesn e s ipparch hia nea bl lu a a Hi a is e ta ja mi H ip h c a H hia sei a Mel rysippus a pp p rc a ari id t tana ia H ipp rchi lgensi maed er H i a a b a es i h a H ippa p hia i le i Meli g e arch a mad c i x p H i p rc a hieri taeaLibythea britomarti celtis poli i e H i ppar a Meli Melitaea celadussa ra H ip p arch r hi a s poli n e H ipp ia a n taeus eli Hipp p ch ro e H i p m s aus ch t i p ar r a m z th amegaer us s Ps p c ia aut M mmata i Ps p arc ia s orin t Danaus plexippus P ip ar ch hia h igu erensei ana Cha s s P p c ia fag Pseudocha archia er s xiphioides P seudochazaraeu p a er clim s Pse s h Dan Ps eudoc a c i P r h a s el a P s eudo ar ia fi yri m Ps rchi hia tilosi C ch ia n in a Ch eu dochazar o ycerion Chaz se e ommata de Sa s g Lasio l a Saty Pararge x S e ch eo i B noe Mi ac Arethus h o a roxelana O a ns O a O eudocha u om i s g e eudo i b e ud d nder a d a ne a rint a u

a pha phryn a n ni a a a d i a ic e a miri e t e a t w ia is opensis n ty o a statilin a hero e y z do

s o n c rdetta t z hazara tam Lasi arargeParargeLopinga aegeri achin ntalis oc f cch n Kirinia m arge n n o er o rus ara c yssi h s

rus ar ha g u ru ara at Lasiommata me i P e e esia e j ch lea m Kiri arcani l i h mpha thyr a corinna terope ch a s

a s h itan a ines i c i a i a a ua h e s ussia s pheg s s z s a u c m az

i virbiu haz a za d

Lasiommata pe m p feru zara a a i a prie s a a da

a ana arethusa g rgi m p n e br za rya Lasiommata par za r a mpha pamphilus s c er z ra l circ o o

n a ti

i m s a s taea ara graec euxina b oenony i ise ra will y i ara us l r r a galath e e r mpha c i s rebi i u a er ae e n s C e x a

gia lachesis l or n y i a e c s e g O ri a Oeneis bore a on n a e e a enonymp n s Coenonympha tullia i i

thima as e i iphon c Coenony s p a oenonympha onymph n e ams l e m n o e gey ur i n Coenonympha oedipp ho m Melanargia Oeneis tarpei s st en n onympha ga O g C nympha rhod e Melana th Coenonympha doruC O a O oenonympha amarylli e Yp o i Prot s y e u lthe ne lanar e v lanargia oc mone i Co C Coenonymp eri s s Melanargia larissa s Melanargia r e le e Co Melanargia pherusa a kii Coenon Melanar Coen oenonympha orie a a Me M Coeno C

Figure 3. Time-calibrated tree of European butterflies. Grey bars indicate gene coverage per taxon. ration of macro-evolutionary processes into biodiversity analyses at macroecological, landscape and local community scales and by combining trait- and phylogeny-based assessments of species assembly processes.

Acknowledgements We thank Fabien L. Condamine (CNRS Montpellier) for his comments on a previ- ous version of this manuscript which helped to improve the paper. MW thanks Bri- gitte Gottsberger (University of Vienna) for assistance in the lab and the following colleagues for specimen samples or sequences: Benedicto Acosta-Fernandez (Spain), Bernard Turlin (France), Dirk Gerber (Germany), Eddie John (UK), John Coutsis (Greece), Javier García (Spain), Karen van Dorp (Netherlands), Klaus Schurian (Ger- Phylogeny of European butterflies 113 many), Pedro Oromí (Spain), Peter Russell (UK), Roger Vila (Spain), Vlad Dinca (Finland), Xavier Merit (France), Zdenek Fric (Czech Republic), and Zdravko Kolev (Bulgaria). We thank Pascal Wiemers of Selam-X (http://www.selam-x.com/studio) for the help in producing Figure 1. NW acknowledges funding from the Department of Biology, Lund University, the Swedish Research Council (grant number 2015-04441). NC acknowledges funding from BECC (Biodiversity and Ecosystem services in a Changing Climate). CWW acknowledges funding from the Swedish Research Council (grant number 2017-04386). The study was also supported by iDiv through the sDiv working group sECURE (https://www.idiv.de/secure).

References

Aarvik L, Bengtsson BÅ, Elven H, Ivinskis P, Jürivete U, Karsholt O, Mutanen M, Savenkov N (2017) Nordic-Baltic Checklist of Lepidoptera. Norwegian Journal of Entomology Sup- plement 3: 1–237. Aduse-Poku K, Vingerhoedt E, Wahlberg N (2009) Out-of-Africa again: a phylogenetic hypothesis of the genus Charaxes (Lepidoptera: Nymphalidae) based on five gene regions. Molecular Phylogenetics and Evolution 53: 463–478. https://doi.org/10.1016/j. ympev.2009.06.021 Allio R, Scornavacca C, Benoit N, Clamens AL, Sperling FAH, Condamine FL (2020) Whole genome shotgun phylogenomics resolves the pattern and timing of swallowtail butterfly evolution. Systematic Biology 69: 38–60. https://doi.org/10.1093/sysbio/syz030 Bartonova A, Benes J, Konvicka M (2014) Generalist-specialist continuum and life history traits of Central European butterflies (Lepidoptera) – are we missing a part of the picture? European Journal of Entomology 111: 543–553. https://doi.org/10.14411/eje.2014.060 Bowler DE, Haase P, Kroncke I, Tackenberg O, Bauer HG, Brendel C, Brooker RW, Ger- isch M, Henle K, Hickler T, Hof C, Klotz S, Kuhn I, Matesanz S, O’Hara R, Russell D, Schweiger O, Valladares F, Welk E, Wiemers M, Bohning-Gaese K (2015) A cross-taxon analysis of the impact of climate change on abundance trends in central Europe. Biological Conservation 187: 41–50. https://doi.org/10.1016/j.biocon.2015.03.034 Bowler DE, Hof C, Haase P, Kroncke I, Schweiger O, Adrian R, Baert L, Bauer HG, Blick T, Brooker RW, Dekoninck W, Domisch S, Eckmann R, Hendrickx F, Hickler T, Klotz S, Kra- berg A, Kuhn I, Matesanz S, Meschede A, Neumann H, O’Hara R, Russell DJ, Sell AF, Son- newald M, Stoll S, Sundermann A, Tackenberg O, Turkay M, Valladares F, van Herk K, van Klink R, Vermeulen R, Voigtlander K, Wagner R, Welk E, Wiemers M, Wiltshire KH, Bohn- ing-Gaese K (2017) Cross-realm assessment of climate change impacts on species’ abundance trends. Nature Ecology & Evolution 1: 0067. https://doi.org/10.1038/s41559-016-0067 Braby MF, Vila R, Pierce NE (2006) Molecular phylogeny and systematics of the Pieridae (Lepidoptera: Papilionoidea): higher classification and biogeography. Zoological Journal of the Linnean Society 147: 239–275. https://doi.org/10.1111/j.1096-3642.2006.00264.x Campbell DL, Brower AV, Pierce NE (2000) Molecular evolution of the wingless gene and its implications for the phylogenetic placement of the butterfly family Riodinidae (Lepi- 114 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

doptera: Papilionoidea). Molecular Biology and Evolution 17: 684–696. https://doi. org/10.1093/oxfordjournals.molbev.a026347 Caterino MS, Reed RD, Kuo MM, Sperling FAH (2001) A Partitioned Likelihood Analysis of Swallowtail Phylogeny (Lepidoptera: Papilionidae). Systematic Biology 50: 106–127. https://doi.org/10.1080/106351501750107530 Cavender-Bares J, Kozak KH, Fine PVA, Kembel SW (2009) The merging of community ecology and phylogenetic biology. Ecology letters 12: 693–715. https://doi.org/10.1111/ j.1461-0248.2009.01314.x Chazot N, Wahlberg N, Freitas AVL, Mitter C, Labandeira C, Sohn J-C, Sahoo RK, Seraphim N, de Jong R, Heikkilä M (2019) Priors and Posteriors in Bayesian Timing of Divergence Analyses: the Age of Butterflies Revisited. Systematic Biology 68: 797–813. https://doi. org/10.1093/sysbio/syz002 Condamine FL, Rolland J, Höhna S, Sperling FAH, Sanmartín I (2018) Testing the Role of the Red Queen and Court Jester as Drivers of the Macroevolution of Apollo Butterflies. Systematic Biology 67: 940–964. https://doi.org/10.1093/sysbio/syy009 D’Amen M, Mateo RG, Pottier J, Thuiller W, Maiorano L, Pellissier L, Ndiribe C, Salamin N, Guisan A (2018) Improving spatial predictions of taxonomic, functional and phylogenetic diversity. Journal of Ecology 106: 76–86. https://doi.org/10.1111/1365-2745.12801 Dapporto L, Cini A, Voda R, Dinca V, Wiemers M, Menchetti M, Magini G, Talavera G, Shreeve T, Bonelli S, Casacci LP, Balletto E, Scalercio S, Vila R (2019) Integrating three comprehensive data sets shows that mitochondrial DNA variation is linked to species traits and paleogeographic events in European butterflies. Molecular Ecology Resources 19: 1623–1636. https://doi.org/10.1111/1755-0998.13059 Davies TJ, Urban MC, Rayfield B, Cadotte MW, Peres-Neto PR (2016) Deconstructing the relationships between phylogenetic diversity and ecology: a case study on ecosystem functioning. Ecology 97: 2212–2222. https://doi.org/10.1002/ecy.1507 De Palma A, Kuhlmann M, Bugter R, Ferrier S, Hoskins AJ, Potts SG, Roberts SPM, Sch- weiger O, Purvis A (2017) Dimensions of biodiversity loss: Spatial mismatch in land-use impacts on species, functional and phylogenetic diversity of European bees. Diversity and Distributions 23: 1435–1446. https://doi.org/10.1111/ddi.12638 Devictor V, Van Swaay C, Brereton T, Brotons L, Chamberlain D, Heliölä J, Herrando S, Jul- liard R, Kuussaari M, Lindström A, Reif J, Roy DB, Schweiger O, Settele J, Stefanescu C, Van Strien A, Van Turnhout C, Vermouzek S, Wallis De Vries MF, Wynhoff I, Jiguet F (2012) Differences in the climatic debts of birds and butterflies at a continental scale. Nature Climate Change 2: 121–124. https://doi.org/10.1038/nclimate1347 Díaz S, Purvis A, Cornelissen JHC, Mace GM, Donoghue MJ, Ewers RM, Jordano P, Pearse WD (2013) Functional traits, the phylogeny of function, and ecosystem service vulnerability. Ecology and Evolution 3: 2958–2975. https://doi.org/10.1002/ece3.601 Dincă V, Montagud S, Talavera G, Hernández-Roldán J, Munguira ML, García-Barros E, He- bert PDN, Vila R (2015) DNA barcode reference library for Iberian butterflies enables a continental-scale preview of potential cryptic diversity. Scientific Reports 5: 12395. https://doi.org/10.1038/srep12395 Phylogeny of European butterflies 115

Dincă V, Zakharov E, Hebert PD, Vila R (2011) Complete DNA barcode reference library for a country’s butterfly fauna reveals high performance for temperate Europe. Proceedings of the Royal Society B 278: 347–355. https://doi.org/10.1098/rspb.2010.1089 Drummond AJ, Suchard MA, Xie D, Rambaut A (2012) Bayesian Phylogenetics with BEAU- ti and the BEAST 1.7. Molecular Biology and Evolution 29: 1969–1973. https://doi. org/10.1093/molbev/mss075 Durka W, Michalski SG (2012) Daphne: a dated phylogeny of a large European flora for phyloge- netically informed ecological analyses. Ecology 93: 2297. https://doi.org/10.1890/12-0743.1 Economo EP, Narula N, Friedman NR, Weiser MD, Guénard B (2018) Macroecology and macroevolution of the latitudinal diversity gradient in ants. Nature Communications 9: 1778. https://doi.org/10.1038/s41467-018-04218-4 Espeland M, Breinholt J, Willmott KR, Warren AD, Vila R, Toussaint EFA, Maunsell SC, Aduse-Poku K, Talavera G, Eastwood R, Jarzyna MA, Guralnick R, Lohman DJ, Pierce NE, Kawahara AY (2018) A Comprehensive and Dated Phylogenomic Analysis of Butter- flies. Current Biology 28: 770–778. https://doi.org/10.1016/j.cub.2018.01.061 Espeland M, Hall JPW, DeVries PJ, Lees DC, Cornwall M, Hsu YF, Wu LW, Campbell DL, Talavera G, Vila R, Salzman S, Ruehr S, Lohman DJ, Pierce NE (2015) Ancient Neo- tropical origin and recent recolonisation: Phylogeny, biogeography and diversification of the Riodinidae (Lepidoptera: Papilionoidea). Molecular Phylogenetics and Evolution 93: 296–306. https://doi.org/10.1016/j.ympev.2015.08.006 Essens T, van Langevelde F, Vos RA, Van Swaay CAM, Wallis De Vries MF (2017) Ecological determinants of butterfly vulnerability across the European continent. Journal of Insect Conservation 21: 439–450. https://doi.org/10.1007/s10841-017-9972-4 Fric ZF, Maresova J, Kadlec T, Tropek R, Pyrcz TW, Wiemers M (2019) World travellers: phylogeny and biogeography of the butterfly genus Leptotes (Lepidoptera: Lycaenidae). Systematic Entomology 44: 652–665. https://doi.org/10.1111/syen.12349 Gallien L, Altermatt F, Wiemers M, Schweiger O, Zimmermann NE (2017) Invasive plants threaten the least mobile butterflies in Switzerland. Diversity and Distributions 23: 185– 195. https://doi.org/10.1111/ddi.12513 Gerhold P, Cahill JF, Winter M, Bartish IV, Prinzing A (2015) Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). Functional Ecology 29: 600–614. https://doi.org/10.1111/1365-2435.12425 Hausmann A, Haszprunar G, Segerer AH, Speidel W, Behounek G, Hebert PDN (2011) Now DNA-barcoded: the butterflies and larger moths of Germany. Spixiana 34: 47–58. Heikkilä M, Kaila L, Mutanen M, Peña C, Wahlberg N (2012) Cretaceous origin and repeated tertiary diversification of the redefined butterflies. Proceedings of the Royal Society B- Biological Sciences 279: 1093–1099. https://doi.org/10.1098/rspb.2011.1430 Huemer P, Wiesmair B (2017) DNA-Barcoding der Tagfalter (Lepidoptera, Papilionoidea) Ös- terreichs. Unbekannte genetische Vielfalt im Zentrum Europas. Wissenschaftliches Jahr- buch der Tiroler Landesmuseen 2017. StudienVerlag, Innsbruck, Wien, Bozen, 8–33. Jetz W, Thomas GH, Joy JB, Hartmann K, Mooers AO (2012) The global diversity of birds in space and time. Nature 491: 444–448. https://doi.org/10.1038/nature11631 116 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Kawahara AY, Plotkin D, Espeland M, Meusemann K, Toussaint EFA, Donath A, Gimnich F, Frandsen PB, Zwick A, Dos Reis M, Barber JR, Peters RS, Liu S, Zhou X, Mayer C, Podsiadlowski L, Storer C, Yack JE, Misof B, Breinholt JW (2019) Phylogenomics reveals the evolutionary timing and pattern of butterflies and moths. Proceedings of the National Academy of Sciences of the Unated States of America 116(45): 22657–22663. https://doi. org/10.1073/pnas.1907847116 Knapp S, Kühn I, Schweiger O, Klotz S (2008) Challenging urban species diversity: contrast- ing phylogenetic patterns across plant functional groups in Germany. Ecology letters 11: 1054–1064. https://doi.org/10.1111/j.1461-0248.2008.01217.x Kudrna O, Harpke A, Lux K, Pennerstorfer J, Schweiger O, Settele J, Wiemers M (2011) Distribution Atlas of Butterflies in Europe. Gesellschaft für Schmetterlingsschutz, Halle, Germany, 576 pp. Kühn I, Nobis MP, Durka W (2009) Combining spatial and phylogenetic eigenvector filtering in trait analysis. Global Ecology and Biogeography 18: 745–758. https://doi.org/10.1111/ j.1466-8238.2009.00481.x Lanfear R, Calcott B, Ho SYW, Guindon S (2012) PartitionFinder: Combined Selection of Partitioning Schemes and Substitution Models for Phylogenetic Analyses. Molecular Biol- ogy and Evolution 29: 1695–1701. https://doi.org/10.1093/molbev/mss020 Lanfear R, Hua X, Warren DL (2016) Estimating the Effective Sample Size of Tree Topolo- gies from Bayesian Phylogenetic Analyses. Genome Biology and Evolution 8: 2319–2332. https://doi.org/10.1093/gbe/evw171 Lavergne S, Evans MEK, Burfield IJ, Jiguet F, Thuiller W (2013) Are species’ responses to global change predicted by past niche evolution? Philosophical Transactions of the Royal Society B-Biological Sciences 368: 20120091. https://doi.org/10.1098/rstb.2012.0091 Li S-P, Cadotte MW, Meiners SJ, Hua Z-S, Shu H-Y, Li J-T, Shu W-S (2015) The effects of phylogenetic relatedness on invasion success and impact: deconstructing Darwin’s natu- ralisation conundrum. Ecology letters 18: 1285–1292. https://doi.org/10.1111/ele.12522 Litman J, Chittaro Y, Birrer S, Praz C, Wermeille E, Fluri M, Stalling T, Schmid S, Wyler S, Gonseth Y (2018) A DNA barcode reference library for Swiss butterflies and forester moths as a tool for species identification, systematics and conservation. PLoS ONE 13(12): e0208639. https://doi.org/10.1371/journal.pone.0208639 Mazel F, Pennell MW, Cadotte MW, Diaz S, Dalla Riva GV, Grenyer R, Leprieur F, Moo- ers AO, Mouillot D, Tucker CM, Pearse WD (2018) Prioritizing phylogenetic diversity captures functional diversity unreliably. Nature Communications 9: 2888. https://doi. org/10.1038/s41467-018-05126-3 Mazel F, Renaud J, Guilhaumon F, Mouillot D, Gravel D, Thuiller W (2015) Mammalian phylogenetic diversity-area relationships at a continental scale. Ecology 96: 2814–2822. https://doi.org/10.1890/14-1858.1 Mazel F, Wüest RO, Lessard J-P, Renaud J, Ficetola GF, Lavergne S, Thuiller W (2017) Global patterns of β-diversity along the phylogenetic time-scale: The role of climate and plate tecton- ics. Global Ecology and Biogeography 26: 1211–1221. https://doi.org/10.1111/geb.12632 McGeoch MA (2007) Insects and bioindication: theory and progress. In: Stewart AJA, New TR, Lewis OT (Eds) Conservation Biology. CABI Publishing, Oxfordshire, 144–174. https://doi.org/10.1079/9781845932541.0144 Phylogeny of European butterflies 117

Monnet AC, Jiguet F, Meynard CN, Mouillot D, Mouquet N, Thuiller W, Devictor V (2014) Asynchrony of taxonomic, functional and phylogenetic diversity in birds. Global Ecology and Biogeography 23: 780–788. https://doi.org/10.1111/geb.12179 Morales-Castilla I, Davies TJ, Pearse WD, Peres-Neto P (2017) Combining phylogeny and co-occurrence to improve single species distribution models. Global Ecology and Biogeog- raphy 26: 740–752. https://doi.org/10.1111/geb.12580 Mouquet N, Devictor V, Meynard CN, Munoz F, Bersier LF, Chave J, Couteron P, Dalecky A, Fontaine C, Gravel D, Hardy OJ, Jabot F, Lavergne S, Leibold M, Mouillot D, Munke- muller T, Pavoine S, Prinzing A, Rodrigues ASL, Rohr RP, Thebault E, Thuiller W (2012) Ecophylogenetics: advances and perspectives. Biological Reviews 87: 769–785. https://doi. org/10.1111/j.1469-185X.2012.00224.x Noriega JA, Hortal J, Azcárate FM, Berg MP, Bonada N, Briones MJI, Del Toro I, Goulson D, Ibanez S, Landis DA, Moretti M, Potts SG, Slade EM, Stout JC, Ulyshen MD, Wackers FL, Woodcock BA, Santos AMC (2018) Research trends in ecosystem services provided by insects. Basic and Applied Ecology 26: 8–23. https://doi.org/10.1016/j.baae.2017.09.006 Nylin S, Wahlberg N (2008) Does plasticity drive speciation? Host-plant shifts and diversification in nymphaline butterflies (Lepidoptera: Nymphalidae) during the tertiary. Biological Journal of the Linnean Society 94: 115–130. https://doi.org/10.1111/j.1095- 8312.2008.00964.x Ovaskainen O, Tikhonov G, Norberg A, Guillaume Blanchet F, Duan L, Dunson D, Roslin T, Abrego N (2017) How to make more out of community data? A conceptual framework and its implementation as models and software. Ecology Letters 20: 561–576. https://doi. org/10.1111/ele.12757 Päivinen J, Grapputo A, Kaitala V, Komonen A, Kotiaho JS, Saarinen K, Wahlberg N (2005) Negative density-distribution relationship in butterflies. BMC Biology 3: e5. https://doi. org/10.1186/1741-7007-3-5 Paradis E, Claude J, Strimmer K (2004) APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics 20: 289–290. https://doi.org/10.1093/bioinformatics/btg412 Peña C, Malm T (2012) VoSeq: A Voucher and DNA Sequence Web Application. PLoS ONE 7(6): e39071. https://doi.org/10.1371/journal.pone.0039071 Peña C, Wahlberg N (2008) Prehistorical climate change increased diversification of a group of butterflies. Biology Letters 4: 274–278. https://doi.org/10.1098/rsbl.2008.0062 Peña C, Wahlberg N, Weingartner E, Kodandaramaiah U, Nylin S, Freitas AVL, Brower AVZ (2006) Higher level phylogeny of Satyrinae butterflies (Lepidoptera: Nymphalidae) based on DNA sequence data. Molecular Phylogenetics and Evolution 40: 29–49. https://doi. org/10.1016/j.ympev.2006.02.007 Peña C, Witthauer H, Klečková I, Fric Z, Wahlberg N (2015) Adaptive radiations in butterflies: evolutionary history of the genus Erebia (Nymphalidae: Satyrinae). Biological Journal of the Linnean Society 116: 449–467. https://doi.org/10.1111/bij.12597 R Core Team (2018) R: A language and environment for statistical computing. https://www.R- project.org/ R Foundation for Statistical Computing, Vienna. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA (2018) Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7. Systematic Biology 67: 901–904. https://doi. org/10.1093/sysbio/syy032 118 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Roquet C, Lavergne S, Thuiller W (2014) One tree to link them all: a phylogenetic dataset for the European tetrapoda. PLoS Currents Tree of Life. 2014 Aug 8 . Edition 1. https://doi. org/10.1371/currents.tol.5102670fff8aa5c918e78f5592790e48 Roquet C, Thuiller W, Lavergne S (2013) Building megaphylogenies for macroecology: taking up the challenge. Ecography 36: 13–26. https://doi.org/10.1111/j.1600-0587.2012.07773.x Sahoo RK, Warren AD, Wahlberg N, Brower AVZ, Lukhtanov VA, Kodandaramaiah U (2016) Ten genes and two topologies: an exploration of higher relationships in skipper butterflies (Hesperiidae). PeerJ 4: e2653. https://doi.org/10.7717/peerj.2653 Schleuning M, Fründ J, Schweiger O, Welk E, Albrecht J, Albrecht M, Beil M, Benadi G, Blüth- gen N, Bruelheide H, Böhning-Gaese K, Dehling DM, Dormann CF, Exeler N, Farwig N, Harpke A, Hickler T, Kratochwil A, Kuhlmann M, Kühn I, Michez D, Mudri-Stojnić S, Plein M, Rasmont P, Schwabe A, Settele J, Vujić A, Weiner CN, Wiemers M, Hof C (2016) Ecological networks are more sensitive to plant than to animal extinction under climate change. Nature Communications 7: 13965. https://doi.org/10.1038/ncomms13965 Schweiger O, Harpke A, Wiemers M, Settele J (2014) CLIMBER: Climatic niche characteristics of the butterflies in Europe. ZooKeys 367: 65–84. https://doi.org/10.3897/zookeys.367.6185 Schweiger O, Klotz S, Durka W, Kühn I (2008) A comparative test of phylogenetic diversity indices. Oecologia 157: 485–495. https://doi.org/10.1007/s00442-008-1082-2 Seraphim N, Kaminski LA, Devries PJ, Penz C, Callaghan C, Wahlberg N, Silva-Brandão KL, Freitas AVL (2018) Molecular phylogeny and higher systematics of the metalmark butterflies (Lepidoptera: Riodinidae). Systematic Entomology 43: 407–425. https://doi. org/10.1111/syen.12282 Settele J, Kudrna O, Harpke A, Kühn I, van Swaay C, Verovnik R, Warren M, Wiemers M, Hanspach J, Hickler T, Kühn E, van Halder I, Veling K, Vleigenhart A, Wynhoff I, Sch- weiger O (2008) Climatic risk atlas of European butterflies. BioRisk 1: 1–710. https://doi. org/10.3897/biorisk.1 Settele J, Shreeve TG, Konvicka M, van Dyck H [Eds] (2009) Ecology of Butterflies in Europe. Cambridge University Press, Cambridge, 513 pp. Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30: 1312–1313. https://doi.org/10.1093/bioinformatics/btu033 Stork NE (2018) How Many Species of Insects and Other Terrestrial Arthropods Are There on Earth? Annual review of entomology 63: 31–45. https://doi.org/10.1146/annurev- ento-020117-043348 Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A (2018) Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evolution 4: vey016. https://doi.org/10.1093/ve/vey016 Talavera G, Lukhtanov VA, Pierce NE, Vila R (2013) Establishing criteria for higher-level classification using molecular data: the systematics of Polyommatus blue butterflies (Lepidoptera, Lycaenidae). Cladistics 29: 166–192. https://doi.org/10.1111/j.1096-0031.2012.00421.x Thuiller W, Lavergne S, Roquet C, Boulangeat I, Lafourcade B, Araujo MB (2011) Conse- quences of climate change on the tree of life in Europe. Nature 470: 531–534. https://doi. org/10.1038/nature09705 Phylogeny of European butterflies 119

Thuiller W, Maiorano L, Mazel F, Guilhaumon F, Ficetola GF, Lavergne S, Renaud J, Roquet C, Mouillot D (2015) Conserving the functional and phylogenetic trees of life of Euro- pean tetrapods. Philosophical Transactions of the Royal Society B: Biological Sciences 370: 20140005. https://doi.org/10.1098/rstb.2014.0005 Toussaint EFA, Breinholt JW, Earl C, Warren AD, Brower AVZ, Yago M, Dexter KM, Espe- land M, Pierce NE, Lohman DJ, Kawahara AY (2018) Anchored phylogenomics illumi- nates the skipper butterfly tree of life. BMC Evolutionary Biology 18: 101. https://doi. org/10.1186/s12862-018-1216-z Tucker CM, Cadotte MW, Carvalho SB, Davies TJ, Ferrier S, Fritz SA, Grenyer R, Helmus MR, Jin LS, Mooers AO, Pavoine S, Purschke O, Redding DW, Rosauer DF, Winter M, Mazel F (2017) A guide to phylogenetic metrics for conservation, community ecology and macroecology. Biological Reviews 92: 698–715. ttps://doi.org/10.1111/brv.12252 van Swaay C, Cuttelod A, Collins S, Maes D, López Munguira ML, Šašić M, Settele J, Verovnik R, Verstrael T, Warren M, Wiemers M, Wynhoff I (2010) European Red List of Butterflies. Publications Office of the European Union, Luxembourg, 46 pp. van Swaay C, Warren M, Lois G (2006) Biotope use and trends of European butterflies. Journal of Insect Conservation 10: 305–306. https://doi.org/10.1007/s10841-006-8361-1 Verovnik R, Wiemers M (2016) Species delimitation in the Grayling genus Pseudochazara (Lep- idoptera, Nymphalidae, Satyrinae) supported by DNA barcodes. ZooKeys 600: 131–154. https://doi.org/10.3897/zookeys.600.7798 Vila R, Lukhtanov VA, Talavera G, Gil-TF, Pierce NE (2010) How common are dot-like distributions? Taxonomical oversplitting in western European Agrodiaetus (Lepidoptera: Lycae- nidae) revealed by chromosomal and molecular markers. Biological Journal of the Linnean Society 101: 130–154. https://doi.org/10.1111/j.1095-8312.2010.01481.x Vishnevskaya MS, Saifitdinova AF, Lukhtanov VA (2016) Karyosystematics and molecular taxonomy of the anomalous blue butterflies (Lepidoptera, Lycaenidae) from the Balkan Peninsula. Comparative Cytogenetics 10: 1–85. https://doi.org/10.3897/CompCytogen.v10i5.10944 Wahlberg N, Braby MF, Brower AVZ, de Jong R, Lee MM, Nylin S, Pierce NE, Sperling FAH, Vila R, Warren AD, Zakharov E (2005a) Synergistic effects of combining morphological and molecular data in resolving the phylogeny of butterflies and skippers. Proceedings of the Roy- al Society B-Biological Sciences 272: 1577–1586. https://doi.org/10.1098/rspb.2005.3124 Wahlberg N, Brower AVZ, Nylin S (2005b) Phylogenetic relationships and historical biogeography of tribes and genera in the subfamily Nymphalinae (Lepidoptera: Nymphalidae). Biological Journal of the Linnean Society 86: 227–251. https://doi.org/10.1111/j.1095- 8312.2005.00531.x Wahlberg N, Leneveu J, Kodandaramaiah U, Peña C, Nylin S, Freitas AVL, Brower AVZ (2009) Nymphalid butterflies diversify following near demise at the Cretaceous/Tertiary bound- ary. Proceedings of the Royal Society B-Biological Sciences 276: 4295–4302. https://doi. org/10.1098/rspb.2009.1303 Wahlberg N, Rota J, Braby MF, Pierce NE, Wheat CW (2014) Revised systematics and higher classification of pierid butterflies (Lepidoptera: Pieridae) based on molecular data. Zoo- logica Scripta 43: 641–650. https://doi.org/10.1111/zsc.12075 120 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Wahlberg N, Weingartner E, Nylin S (2003) Towards a better understanding of the higher systematics of Nymphalidae (Lepidoptera: Papilionoidea). Molecular Phylogenetics and Evolution 28: 473–484. https://doi.org/10.1016/S1055-7903(03)00052-6 Wahlberg N, Wheat CW (2008) Genomic outposts serve the phylogenomic pioneers: Design- ing novel nuclear markers for genomic DNA extractions of lepidoptera. Systematic Biology 57: 231–242. https://doi.org/10.1080/10635150802033006 Warren AD, Ogawa JR, Brower AVZ (2008) Phylogenetic relationships of subfamilies and circumscription of tribes in the family Hesperiidae (Lepidoptera : Hesperioidea). Cladistics 24: 642–676. https://doi.org/10.1111/j.1096-0031.2008.00218.x Webb CO, Ackerly DD, McPeek MA, Donoghue MJ (2002) Phylogenies and community ecology. Annual Review of Ecology and Systematics 33: 475–505. https://doi.org/10.1146/annurev.ecolsys.33.010802.150448 Wiemers M, Balletto E, Dinca V, Faltynek Fric Z, Gerardo L, Lukhtanov V, Munguira ML, Chris AMvS, Vila R, Vliegenthart A, Wahlberg N, Verovnik R (2018) An updated checklist of the European Butterflies (Lepidoptera, Papilionoidea). ZooKeys 811: 9–45. https:// doi.org/10.3897/zookeys.811.28712 Wiemers M, Fiedler K (2007) Does the DNA barcoding gap exist? - a case study in blue butterflies (Lepidoptera: Lycaenidae). Frontiers in Zoology 4: 8. https://doi.org/10.1186/1742- 9994-4-8 Wiemers M, Stradomsky BV, Vodolazhsky DI (2010) A molecular phylogeny of Polyommatus s. str. and Plebicula based on mitochondrial COI and nuclear ITS2 sequences (Lepidoptera: Lycaenidae). European Journal of Entomology 107: 325–336. https://doi.org/10.14411/ eje.2010.041 Wiens JJ, Graham CH (2005) Niche Conservatism: Integrating Evolution, Ecology, and Con- servation Biology. Annual Review of Ecology, Evolution, and Systematics 36: 519–539. https://doi.org/10.1146/annurev.ecolsys.36.102803.095431 Winter M, Devictor V, Schweiger O (2013) Phylogenetic diversity and nature conservation: where are we? Trends in Ecology & Evolution 28: 199–204. https://doi.org/10.1016/j. tree.2012.10.015 Winter M, Schweiger O, Klotz S, Nentwig W, Andriopoulos P, Arianoutsou M, Basnou C, Delipetrou P, Didziulis V, Hejda M, Hulme PE, Lambdon PW, Pergl J, Pyšek P, Roy DB, Kühn I (2009) Plant extinctions and introductions lead to phylogenetic and taxonomic homogenization of the European flora. Proceedings of the National Academy of Sciences of the United States of America 106: 21721–21725. https://doi.org/10.1073/ pnas.0907088106 Zhang J, Brockmann E, Cong Q, Shen J, Grishin NV (2020) A genomic perspective on the taxonomy of the subtribe Carcharodina (Lepidoptera: Hesperiidae: Carcharodini). Zootaxa 4748: 182–194. https://doi.org/10.11646/zootaxa.4748.1.10 Phylogeny of European butterflies 121

Supplementary material 1

Table listing of European butterfly species with higher taxonomy, voucher codes and accession numbers for the sequences used to build the phylogeny. Authors: Martin Wiemers, Niklas Wahlberg Data type: List of taxa with accession numbers Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl1

Supplementary material 2 Table S1–S12 Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: PartitionFinder results Explanation note: Table S1. PartitionFinder results for dataset 1 (Papilionidae). Table S2. PartitionFinder results for dataset 2 (Hesperiidae: Hesperiinae). Table S3. Par- titionFinder results for dataset 3 (Hesperiidae: Pyrginae). Table S4. PartitionFinder results for dataset 4 (Pieridae). Table S5. Partitionfinder results for dataset 5 (Lycae- nidae). Table S6. PartitionFinder results for dataset 6 (Nymphalidae: Danainae). Table S7. PartitionFinder results for dataset 7 (Nymphalidae: Apaturinae). Table S8. PartitionFinder results for dataset 8 (Nymphalidae: Heliconiinae + Limenitidi- nae). Table S9. PartitionFinder results for dataset 9 (Nymphalidae: Nymphalinae). Table S10. PartitionFinder results for dataset 10 (Nymphalidae: Satyrinae 1). Ta- ble S11. PartitionFinder results for dataset 11 (Nymphalidae: Satyrinae 2). Table S12. PartitionFinder results for dataset 12 (Nymphalidae: Satyrinae 3). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl2 122 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Supplementary material 3

Figure S1. Time-calibrated tree of European butterflies Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Unlabelled terminal branches (with monophyletic entities col- lapsed) represent non-European taxa which were included in the global backbone tree. Age estimates are indicated at the nodes (Ma). Node bars represent the 95% credibility intervals. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl3

Supplementary material 4 Figure S2. Time-calibrated tree of European butterflies Section I: Papilionidae, Hesperiidae & Pieridae Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Age estimates are indicated at the nodes (Ma). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl4 Phylogeny of European butterflies 123

Supplementary material 5

Figure S3. Time-calibrated tree of European butterflies Section II. Riodinidae & Lycaenidae. Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Age estimates are indicated at the nodes (Ma). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl5

Supplementary material 6 Figure S4. Time-calibrated tree of European butterflies Section III: Nymphalidae Part I: Subfamilies Limenitidinae, Heliconiinae, Apaturinae & Nymphalinae Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Age estimates are indicated at the nodes (Ma). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl6 124 Martin Wiemers et al. / ZooKeys 938: 97–124 (2020)

Supplementary material 7

Figure S5. Time-calibrated tree of European butterflies Section IV: Nymphalidae Part II: Subfamilies Libytheinae, Danainae & Satyrinae Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Age estimates are indicated at the nodes (Ma). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl7

Supplementary material 8 Figure S6. Time-calibrated tree of European butterflies Authors: Martin Wiemers, Nicolas Chazot, Christopher W. Wheat, Oliver Schweiger, Niklas Wahlberg Data type: Phylogenetic dendrogram Explanation note: Unlabelled terminal branches (with monophyletic entities col- lapsed) represent non-European taxa which were included in the global backbone tree. Posterior probabilities are indicated at the nodes (Ma). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.938.50878.suppl8