Material and methods
Material examinednext section
A total of 400 Chrysotoxum specimens were examined. They were collected in Austria, Bosnia & Herzegovina, Croatia, Finland, FYR Macedonia, Germany, Greece, Italy, Kyrgyzstan, Montenegro, Poland, Serbia and Turkey, by various collectors, from 1860 to 2013. The following abbreviations are used for where specimens are deposited: FSUNS, Department of Biology and Ecology, Faculty of Sciences, University of Novi Sad, Serbia; MZH, Zoological Museum, Finnish Museum of Natural History, Helsinki, Finland; NHMW, Naturhistorisches Museum, Wien, Austria; ZMHB, Zoologishes Museum of the Humbolt University, Berlin, Germany; RMNH, Naturalis Biodiversity Center, Leiden, The Netherlands; DD, Dieter Doczkal’s and AS, Axel Ssymank’s private collection, Germany. In addition, type material was also examined in the collection at Zoologishes Museum of the Humbolt University, Berlin (ZMHB) and Museo Zoologico La Specola, Firenze, Italy (LSF). Material examined is detailed in Table S1 (Supplementary information). Only type material is detailed in the text.
To describe and diagnose species, characters were studied using a Ceti® binocular microscope. Colour characters always refer to dry specimens. Body size was measured as the length (‘L’) from the tip of the frontal prominence (excluding antenna) to the tip of the abdomen. Proportional length of the antennal segments is given as a ratio (‘r’) of x: y: z (‘x’, scape; ‘y’, pedicel; ‘z’, basoflagellomere). Measurements were made using an eye-piece micrometer. Morphological terms follow Thompson (1999).
Two or three legs of each specimen were used for total genomic DNA extraction from 25 Chrysotoxum dry specimens (Table S2), following Chen et al. (2010). Material analysed included 22 specimens of the C. vernale A, two specimens of the C. vernale B and one of third Chrysotoxum species. DNA voucher specimens are deposited in FSUNS.
The 5’ region of cytochrome c oxidase I gene (COI) was amplified using forward primer LCO (5’-GCTCAACAAATCATAAAGATATTGG-3’) and reverse primer HCO (5’-TAAACTTCAGGGTGACCAAAA AATCA-3’) (Folmer et al., 1994). The universally conserved primers were used for amplifying and sequencing the 3’ region of COI: forward primer C1-J-2183 (5’-CAACATTTATTTTGATTTTTTGG-3’) (alias JERRY) and reverse primer TL2-N-3014 (5’-TCCAATGCACTAATCTGCCATATTA-3’) (alias PAT) (Simon et al., 1994).
PCR reactions were carried out in 25 µl reactions containing: approx. 50 ng of DNA, 2 pmoles of each primer, 0.2 µl of DNA polymerase (5U/ µl), 2.5 mM MgCl2 , 2.5 µl 10× Taq Buffer, 0.1 mM of each nucleotide and ultra-pure water. Thermocycler conditions were initial denaturing at 95ºC for 2 min, 29 cycles of 30 s denaturing at 94ºC, 30 s annealing at 49ºC, 2 min extension at 72ºC, followed by a final extension of 8 min at 72ºC.
Expected size of amplification products was confirmed with a standard 1.5% agarose gel electrophoresis. The remaining product was purified using Exonuclease I and Shrimp Alkaline Phosphatase enzymes following the manufacturer’s instructions (Thermo Scientific, USA). All sequencing reactions were performed using the Big Dye Terminator Kit v3.1. (Applied Biosystems, USA) following the manufacturer’s protocol; sequences were generated on ABI 3730xl DNA Analyzer and deposited in GenBank (accession numbers: KR019039-KR019063).
Sequences were aligned using the ClustalW algorithm (Thompson et al., 1994) as implemented in BioEdit 18.104.22.168 (Hall, 1999), with final adjustments performed manually. The data set containing 5’ region COI sequences had final length 542bp, and the final length of dataset containing 3’ region COI sequences was 625bp. The final dataset with 25 mtDNA COI sequences was created by merging sequence information of 3’ and 5’ COI regions. Phylogenetic analysis for all species was performed using Maximum Likelihood (ML) method, and a tree was created in MEGA 6.0 (Tamura et al., 2013). The Maximum Likelihood method applied is based on the Tamura-3 parameter model (T92+γ; γ=0.05) of nucleotide substitution as defined in MEGA 6.0 (Tamura et al., 2013). Statistical support of internal nodes was calculated with 1000 bootstrap repetitions. Eumerus flavitarsis Zetterstedt, 1843 (AY212782) was used as an outgroup taxon. Median-joining (MJ) network (Bandelt et al., 1999) was constructed using the software Network 22.214.171.124 (available at http://www.fluxus-engineering.com/sharenet.htm). The network was constructed using equal weights for all the mutations and setting parameter ε to zero in order to restrict the choice of feasible links in final network.
Morphometric analyses were used to characterise all taxa. High-resolution pictures of wings and surstyli were made using a Leica DFC320 video camera attached to a Leica MZ16 stereomicroscope. A video camera was connected to a PC computer in which the software to make pictures was installed. Landmarks (wings) and semi-landmarks (surstyli) were drawn on every picture using TpsDig 2.05 software (Rohlf, 2006). One-way analysis of variance (ANOVA) and Tukey’s post hoc test were used to test differences in wing centroid size between sexes and taxa. Wing centroid size is the square root of the sum of the squared distances between the centre of the wing and each landmark (Zelditch et al., 2004). Multivariate analysis of variance (MANOVA), canonical variate analysis (CVA) and discriminant function analysis (DA) were used to test differences in wing and surstylus shape between sexes and taxa. Statistical analyses were made using Statistica® for Windows (StatSoft, 2012). For males and females of morphotypes A and B analyses were carried out separately.
Variation of wing size and shape was studied in 249 specimens of all three taxa following Bookstein (1991). The right wing of each specimen was taken off by means of micro-scissors and then mounted in Hoyer’s medium (Anderson, 1954) on a microscopic slide. Wings are archived and labelled using unique codes shown in Table S1 (Supplementary information). Sixteen homologous landmarks were chosen at vein intersections and terminations throughout the wing; landmarks were selected in positions of the wing that could be easily recognisable at any time (Fig. 1). To reduce the statistical errors due to the low number of specimens (Arnqvist and Mårtensson, 1998) wings of Chrysotoxum orthostylum Vujić sp. nov., were digitized 10 times. Generalised least squares Procrustes superimposition (GLS) was used to minimise non-shape variations in location, scale and orientation of wings, and also to superimpose the wings in a common coordinate system (Rohlf and Slice, 1990; Zelditch et al., 2004). GLS, wing centroid size and partial-warp scores were computed using CoordGen7.14 and CVAgen7.14a, which are part of IMP package (Sheets, 2012). MorphoJ v2.0 was used to visualize the thin-plate spline deformation (Klingenberg, 2011).
For surstyli, outline shape was studied. Surstyli of 51 Chrysotoxum males were analyzed: 21 of morphotype A and 30 of morphotype B. The right surstylus was taken off using pins. Surstyli were mounted in Hoyer’s medium on a microscopic slide and immobilized with a cover slip. In the absence of clearly-identifiable, homologous, anatomical loci, 30 semi-landmarks were generated (Fig. 2). For each specimen semi-landmarks were drawn twice to reduce statistical error. To superimpose semi-landmarks, CoordGen7.14 and an integrated Semiland module were used following a distance-minimising protocol to minimize the shape differences due to the arbitrary nature of semi-landmark positions along the curve (Bookstein, 1997; Zelditch et al., 2004).
Fig. 2. Location of the 30 analysed semi-landmarks on the right surstylus of the male genitalia in the Chrysotoxum vernale.
This analysis was carried out for 183 specimens of morphotype A and 121 of morphotype B from Croatia, Finland, FYR Macedonia, Germany, Greece, Montenegro, Poland and Serbia. Localities with geographic coordinates were used without modification. Records with only locality names were assigned coordinates using Google Earth (Google Inc, 2013), which was also used to confirm the validity of the localities with coordinates. All localities were represented in DivaGis (v7.5) (Hijmans et al., 2012). A total of 19 Bioclim variables plus altitude (2.5 arc-minutes resolution) were generated for each locality on the basis of the WoldClim data set (Hijmans et al., 2005). Climatic profiles obtained for the two morphotypes were analysed using Principal Component Analysis (PCA). PCA was carried out applying a normal varimax rotation of factor loadings. Only factors with an eigenvalue greater than one were considered significant. Variables with a factor loading greater than 0.8 were interpreted as significantly correlated with the correspondent factor. ANOVA and Fisher LSD post hoc test were carried out to compare the derived factor scores between the two morphotypes. A scatter plot of PCA score values was used to graphically display position of these morphotypes in environmental space.