Unravelling the Molecular Identity of Bulgarian Jumping Plant Lice of the Family Aphalaridae (Hemiptera: Psylloidea)

Abstract

Simple Summary

Correct taxonomic identification is essential for conducting successful biological research, especially with regard to economically important insects, such as jumping plant lice or psyllids. In the present study, we identify and diagnose the morphologically characterised aphalarid species from Bulgaria using two molecular markers, cytochrome c oxidase I and cytochrome b. A total of 80 sequences of 25 Aphalaridae species were obtained and included in the BOLD and GenBank databases. This should enable even non-experts to identify these species quickly and accurately. The results of the current study show that two barcode genes are sufficient to distinguish most aphalarid species.

Abstract

Psyllids (Hemiptera: Psylloidea) are plant sap-sucking insects whose identification is often difficult for non-experts. Despite the rapid development of DNA barcoding techniques and their widespread use, only a limited number of sequences of psyllids are available in the public databases, and those that are available are often misidentified. Here, we provide 80 sequences of two mitochondrial genes, cytochrome c oxidase I (COI) and cytochrome b (Cytb), for 25 species of Aphalaridae, mainly from Bulgaria. The DNA barcodes for 15 of these species are published for the first time. In cases where standard primers failed to amplify the target gene fragment, we designed new primers that can be used in future studies. The distance-based thresholds for the analysed species were between 0.0015 and 0.3415 for COI and 0.0771 and 0.4721 for Cytb, indicating that the Cytb gene has a higher interspecific divergence, compared to COI, and therefore allows for more accurate species identification. The species delimitation based on DNA barcodes is largely consistent with the differences resulting from morphological and host plant data, demonstrating that the use of DNA barcodes is suitable for successful identification of most aphalarid species studied. The phylogenetic reconstruction based on maximum likelihood and Bayesian inference analyses, while showing similar results at high taxonomic levels to previously published phylogenies, provides additional information on the placement of aphalarids at the species level. The following five species represent new records for Bulgaria: Agonoscena targionii, Aphalara affinis, Colposcenia aliena, Co. bidentata, and Craspedolepta malachitica. Craspedolepta conspersa is reported for the first time from the Czech Republic, while Agonoscena cisti is reported for the first time from Albania.

1. Introduction

The accurate identification of species is key to successful biological research. Over the last three decades, molecular methods have become increasingly popular, often replacing taxonomic expertise founded in morphology [1]. DNA barcoding is expected to provide a rapid and reliable method for species identification, especially for specimens lacking conspicuous morphological features (e.g., immature insects, cryptic species) or species exhibiting seasonal or sexual dimorphism [2,3]. Consequently, molecular identification is now widely used for the detection of quarantine species and plant pests [4,5,6]. However, the use of DNA barcoding for reliable species identification is only possible if the gene sequences of correctly identified individuals are available in reference databases such as BOLD or GenBank [7]. Unfortunately, these databases are quite incomplete for many groups and are plagued by misidentifications [8] as they lack a quality control mechanism.

Jumping plant lice or psyllids (Hemiptera: Psylloidea) constitute a group of Sternorrhyncha. Some psyllid species are serious pests of crops or ornamental plants, while others are used as biological control agents [9,10,11,12]. Psyllids are small (1–10 mm body length, including the wings when folded over the body), sap-sucking, generally host-specific insects that are predominantly associated with eudicots and magnoliids and only exceptionally with monocots or conifers [13,14]. Slightly more than 4000 species have been described from all biogeographical regions, except Antarctica, but at least as many are still undescribed [14]. From Europe, a comparatively well-studied region, about 400 species are known, representing six (Aphalaridae, Calophyidae, Carsidaridae, Liviidae, Psyllidae, and Triozidae) of the seven currently recognised psyllid families [15]. The molecular data available in GenBank “https://www.ncbi.nlm.nih.gov/genbank/ (accessed on 12 November 2023)” and BOLD “http://boldsystems.org (accessed on 12 November 2023)” mostly concern pest psyllids such as Bactericera cockerelli (Šulc), pear psyllids of the genus Cacopsylla Ossiannilsson, and Diaphorina citri Kuwayama, while information on non-pest psyllids is often limited [6,16].

Aphalaridae are the third largest family of Psylloidea, with 770 described species [15]. Their phylogeny is still controversial as to whether they are monophyletic or paraphyletic [16,17]. Wang et al. [18], however, provided evidence in favour of the monophyly of the family. Burckhardt et al. [14] recognised seven subfamilies worldwide, of which only Aphalarinae and Rhinocolinae are native to Europe and Bulgaria, while several introduced pests of Eucalyptus sp. from Spondyliaspidinae also occur in Europe [19,20,21,22]. The monophyly of Aphalarinae and Rhinocolinae is strongly supported by molecular and morphological data ([14] and the literature cited therein). The phylogenetic relationships within the two subfamilies have been analysed at the generic level using morphological data [23,24,25] and for a limited set of taxa using molecular data [16,17].

In Bulgaria, Aphalaridae are represented by 20 species of Aphalarinae [26,27,28,29,30,31,32,33,34,35,36] and four species of Rhinocolinae [23,28]. Aphalara Foerster and Craspedolepta Enderlein are two species-rich genera of Aphalarinae with a predominantly Holarctic distribution. In the past, both genera were divided into two or more genera or subgenera, which led to artificial groupings, as shown by Burckhardt and Lauterer [32], who defined the genera as putatively monophyletic.

Due to minor morphological differences and overlapping host ranges between some species, the identification of Aphalaridae, especially Aphalara, Craspedolepta, and Agonoscena Enderlein, may prove difficult for non-experts. Here, we evaluate the accuracy and efficiency of DNA barcoding of the two protein-coding mitochondrial gene fragments COI and Cytb for the identification of 25 species of Aphalaridae (23 spp. from Bulgaria, 1 sp. from the Czech Republic, 1 sp. from Albania). We also use the newly obtained molecular data to shed more light on the phylogenetic relationships within Aphalaridae.

2. Materials and Methods

2.1. Material

A total of 75 specimens of 25 Aphalaridae species were collected from 27 localities in Bulgaria (23 spp.), Albania (1 sp.), and the Czech Republic (1 sp.) (Table 1 and Figure 1). The specimens were collected during faunistic surveys in different types of vegetation using a sweep net and an aspirator. The host plants were identified in the field and are listed in Table 1. Specimens collected after 2016 were preserved in 70% or 96% ethanol, while specimens collected before 2016 were mounted dry. The material was primarily identified on the basis of morphological characters of the adults according to the identification keys and taxonomic descriptions of Ossiannilsson [37] and Burckhardt and Lauterer [32] for Aphalara spp., Loginova [38] and Burckhardt [39] for Colposcenia Enderlein, Ossiannilsson [37], Loginova [40,41], Dobreanu and Manolache [42], Conci and Tamanini [43], and Burckhardt and Lauterer [44] for Craspedolepta, Conci and Tamanini [45] and Burckhardt [46] for Rhodochlanis Loginova, and Burckhardt and Lauterer [23] for Rhinocolinae. The nomenclature and classification follow the Psyl’list database [15]. The voucher specimens are deposited in the Zoological Collection of the University of Sofia.

2.2. DNA Extraction, Amplification, Sequencing and Alignment

DNA extraction, amplification, and sequencing of the COI gene fragment of 21 species were performed by the Canadian Centre for DNA Barcoding (CCDB) using non-destructive DNA extraction from the whole specimen. The non-destructive method was chosen to preserve the morphological integrity of these specimens for future analysis. Later, nineteen samples of 18 species were destructively extracted with DNeasy Blood and Tissue (QIAGEN) in the molecular laboratory of the Free University of Bozen-Bolzano according to the manufacturer’s protocol. The fragments of the two mitochondrial genes COI and Cytb were amplified there with DreamTaq DNA Polymerase (Thermo Fisher, Waltham, MA, USA). We chose these two genes because of their utility in species identification and phylogeographic studies, with COI being widely used for DNA barcoding and Cytb often used as an additional marker [2,4,8,47,48]. We designed new primers and developed protocols for the amplification of Cytb when the universal primer pairs Cytbf/Cytbr [16,49] failed to amplify the targeted gene fragment. The newly developed primers were designed manually using the conserved gene regions. Their suitability and the compatibility of the forward and reverse primer pairs were assessed using the PCR Primer Stats tools “https://www.bioinformatics.org/sms2/pcr_primer_stats.html (accessed on 15 December 2023)”. All primer sequences and PCR conditions are listed in Table 2. PCR products were purified and Sanger sequenced by Eurofins Genomics (Ebersberg, Germany). For the following seven species, Agonoscena pistaciae, Aphalara freji, Aph. polygoni, Craspedolepta bulgarica, Cr. conspersa, Cr. innoxia, and Cr. omissa, only the COI gene fragment was sequenced as no additional DNA was available.

The PCR products were sequenced in both directions. The sequences were aligned and trimmed using Geneious v.8.1.9 (Dotmatics, Boston, MA, USA) [50]. The alignment of the sequences was performed manually with MEGA v.11 [51]. The gene sequences were concatenated with SEAVIEW v.5.0.5 [52].

Table 1

Collecting data for the specimens of Aphalaridae associated with DNA barcodes or included in the phylogenetic analyses, with references to BOLD and GenBank databases. Abbreviations used in the table: M: male, F: female. The accession numbers of the sequences that were sequenced for the first time, are printed in bold. Psyllid species that represent new records for Bulgaria, Albania, or the Czech Republic are marked with an asterisk (*). For some voucher entries, only limited information about the locality is available in GenBank.

Subfamily	Species	Locality	Host Plant	Latitude	Longitude	Altitude (m)	Collection Date	Sex	Sofia University Catalog Number	Process ID (BOLD)	Barcode Index Number (BIN)	Accession N (GenBank)	Reference	Figure
Aphalarinae	* Aphalara affinis (Zetterstedt, 1828)	Bulgaria, Western Rhodopi Mts., Smolyanski ezera lakes	-	41.6203	24.6771	1520	15 September 2021	M	BFUS-I-IG026770	PSYBG001-23	BOLD:AFM2800	PQ109732	This study	Figure 1j
		Bulgaria, Western Rhodopi Mts., Smolyanski ezera lakes	-	41.6203	24.6771	1520	15 September 2021	M	BFUS-I-IG026975	PSYBG100-24	-	PQ100053	This study	Figure 1j
Aphalarinae	Aphalara itadori (Shinji, 1938)	Japan	-	-	-	-	-	-	-	-	-	KP113670	[53]	-
		United Kingdom	-	-	-	-	-	-	-	-	-	MG988914	[16]; Percy, pers. comm.	-
Aphalarinae	Aphalara avicularis Ossiannilsson, 1981	Bulgaria, Western Stara Planina Mts., Churek	Polygonum aviculare L.	42.7767	23.7157	796	27 August 2023	M	BFUS-I-IG026773	PSYBG004-23	BOLD:ACY0265	PQ109737	This study	Figure 1k
		Bulgaria, Western Stara Planina Mts., Churek		42.7767	23.7157	796	27 August 2023	F	BFUS-I-IG026977	PSYBG115-24	-	PQ100054	This study	Figure 1k
Aphalarinae	Aphalara freji Burckhardt & Lauterer, 1997	Bulgaria, Eastern Stara Planina Mts., Bardarevo	-	42.8983	27.6219	72	27 July 2011	M	BFUS-I-IG005891	PSYBG062-23	BOLD:ACY0265	PQ109739	This study	-
Aphalarinae	Aphalara maculipennis Löw, 1886	Bulgaria, Western Stara Planina Mts., Aldomivsko lake	-	42.8848	22.9998	660	13 May 2022	F	BFUS-I-IG026960	PSYBG096-24	BOLD:AFT1810	PQ109740 PQ100055	This study	Figure 1l
Aphalarinae	Aphalara nigrimaculosa Gegechkori, 1981	Bulgaria, Western Rhodopi Mts., Pamporovo, Snezhanka peak	Rumex acetosella L.	41.6370	24.6835	1850	16 September 2021	M	BFUS-I-IG026982	PSYBG097-24	BOLD:AFT1810	PQ109742 PQ100056	This study	Figure 1m
Aphalarinae	Aphalara polygoni Foerster, 1848	Bulgaria, Western Rhodopi Mts., Cigov chark	-	41.9318	24.1292	1380	18 June 2016	F	BFUS-I-IG005903	PSYBG063-23	BOLD:AFL6229	PQ109743	This study	-
Aphalarinae	* Colposcenia aliena (Löw, 1881)	Bulgaria, East Danube plain, Poveljanovo district	Tamarix sp.	43.2122	27.6480	74	6 July 2023	M	BFUS-I-IG026791	PSYBG016-23	BOLD:AFN1581	PQ109745	This study	Figure 1d
		Bulgaria, East Danube plain, Poveljanovo district		43.2122	27.6480	74	6 July 2023	M	BFUS-I-IG027010	PSYBG102-24	-	PQ100058	This study	Figure 1d
Aphalarinae	* Colposcenia bidentata Burckhardt, 1988	Bulgaria, Eastern Rhodopi Mts., Meden buk	Tamarix sp.	41.3696	26.0545	110	6 July 2012		BFUS-I-IG020788	PSYBG066-23	BOLD:AFN1583	PQ109747	This study	-
		Bulgaria, Eastern Rila-Rhodopi Massif, near Arda river		41.6514	25.8687	140	27 August 2022	F	BFUS-I-IG027009	PSYBG103-24	-	PQ100059	This study	Figure 1e
Aphalarinae	Colposcenia osmanica Vondráček, 1953	Bulgaria, Vlahina Planina Mts., Simitli	Tamarix sp.	41.8945	23.1184	290	8 May 2022	M	BFUS-I-IG026785	PSYBG019-23	BOLD:AFN1582	PQ109749	This study	-
		Bulgaria, Krumovgrad		41.5044	25.3948	255	10 October 2023	M	BFUS-I-IG027006	PSYBG104-24	-	PQ100060	This study	-
Aphalarinae	Colposcenia traciana (Klimaszewski, 1970)	Bulgaria, Strandzha Mts., Tsarevo	Tamarix sp.	42.1363	27.7992	142	12 July 2023	M	BFUS-I-IG026788	PSYBG022-23	BOLD:AFL7588	PQ109752	This study	Figure 1g
		Bulgaria, Strandzha Mts., Tsarevo		42.1363	27.7992	142	12 July 2023	M	BFUS-I-IG027003	PSYBG105-24	-	PQ100061	This study	Figure 1g
Aphalarinae	Colposcenia sp.	Bulgaria, Meden buk	-	41.3696	26.0545	110	6 July 2012	-	-	-	-	MG989005MG988706	[16]; Percy, pers. comm.	-
Aphalarinae	Craspedolepta anomola (Crawford, 1914)	Canada	-	-	-	-	-	-	-	-	-	MG989006MG988707	[16]; Percy, pers. comm.	-
Aphalarinae	Craspedolepta bulgarica Klimaszewski, 1961	Bulgaria, Western Stara planina Mts., Buhovo	Achillea sp.	42.7703	23.5663	743	10 June 2023	M	BFUS-I-IG026794	PSYBG025-23	BOLD:AFM9464	PQ109753	This study	Figure 1n
Aphalarinae	* Craspedolepta conspersa (Löw, 1888)	Czech Republic, South Moravia, Sedlec	Artemisia vulgaris L.	48.7746	16.6998	178	25 June 2023	F	BFUS-I-IG026829	PSYBG026-23	BOLD:AFM9463	PQ109754	This study	-
Aphalarinae	Craspedolepta innoxia (Foerster, 1848)	Bulgaria, Western Stara planina Mts., Buhovo	-	42.7703	23.5663	743	10 June 2023	F	BFUS-I-IG026795	PSYBG027-23	BOLD:AFM9464	PQ109756	This study	-
Aphalarinae	* Craspedolepta malachitica (Dahlbom, 1851)	Bulgaria, Western Stara Planina Mts., Negovan, lake	Artemisia absinthium L.	42.7660	23.4007	513	14 July 2022	F	BFUS-I-IG026799	PSYBG030-23	BOLD:AFL5094	PQ109759	This study	-
		Bulgaria, Western Stara Planina Mts., Negovan, lake		42.7660	23.4007	513	14 July 2022	F	BFUS-I-IG026992	PSYBG106-24	-	PQ100062	This study	-
Aphalarinae	Craspedolepta nebulosa (Zetterstedt, 1828)	Bulgaria, Rila-Rhodopi Massif, Rila Mts., Maljovitsa	Chamaenerion angustifolium (L.) Scop.	42.2083	23.3889	1750	23 July 2021	F	BFUS-I-IG026801	PSYBG032-23	BOLD:AFM9466	PQ109760	This study	-
		Bulgaria, Rila Mts, Maljovitsa hut		42.1880	23.3736	2010	15 June 2019	M	BFUS-I-IG026998	PSYBG107-24	-	PQ100063	This study	-
Aphalarinae	Craspedolepta nervosa (Foerster, 1848)	Bulgaria, Western Stara planina Mts., Buhovo	Achillea sp.	42.7703	23.5663	743	10 June 2023	F	BFUS-I-IG026796	PSYBG036-23	BOLD:ACY1733	PQ109765	This study	-
		Bulgaria, Western Stara planina Mts., Buhovo		42.7703	23.5663	743	10 June 2023	F	BFUS-I-IG026987	PSYBG108-24	-	PQ100064	This study	-
Aphalarinae	Craspedolepta omissa Wagner, 1944	Bulgaria, Rila-Rhodopi Massif, Rila Mts., Kartala district	Artemisia vulgaris L.	42.04232	23.36638	1464	2 August 2020	M	BFUS-I-IG026806	PSYBG038-23	BOLD:AFM9465	PQ109768	This study	-
Aphalarinae	Craspedolepta pontica Dobreanu & Manolache, 1962	Bulgaria, Maleshevska Planina Mts., Stara Kresna, tourist shelter	Achillea clypeolata Sibth. & Sm.	41.7691	23.1758	560	7 May 2022	M	BFUS-I-IG026808	PSYBG040-23	BOLD:AFM1102	PQ109770	This study	-
		Bulgaria, Maleshevska Planina Mts., road to Stara Kresna		41.7656	23.1659	350	30 April 2023	F	BFUS-I-IG026985	PSYBG109-24	-	PQ100065	This study	Figure 1r
Aphalarinae	Craspedolepta subpunctata (Foerster, 1848)	Bulgaria, Rila Mts, Alen mak hotel	Chamaenerion angustifolium (L.) Scop.	42.2121	23.3870	1712	14 June 2019	M	BFUS-I-IG026811	PSYBG043-23	BOLD:AAV0240	PQ109771	This study	-
		Bulgaria, Rila Mts., Alen mak hotel		42.2121	23.3870	1712	14 June 2019	M	BFUS-I-IG026989	PSYBG114-24	-	PQ100066	This study	-
Aphalarinae	Lanthanaphalara mira Tuthill, 1959	Peru	-	-	-	-	-	-	-	-	-	NC038111	[16]; Percy, pers. comm.	-
Aphalarinae	Limataphalara lautereri Burckhardt & Queiroz, 2013	Brazil	-	-	-	-	-	-	-	-	-	MG988785MG989094	[16]; Percy, pers. comm.	-
Aphalarinae	Neaphalara fortunae Brown & Hodkinson, 1988	Costa Rica	-	-	-	-	-	-	-	-	-	MG988801MG989115	[16]; Percy, pers. comm.	-
Aphalarinae	Rhodochlanis bicolor (Scott, 1880)	Bulgaria, Black Sea coast, Pomorie, salt lake	Salicornia europaea (Moss) Lambinon & Vanderp.	42.5998	27.6261	16	23 July 2022	M	BFUS-I-IG026956	PSYBG099-24	BOLD:AFT3392	PQ109781 PQ100069	This study	Figure 1h
Rhinocolinae	Agonoscena atlantica Bastin, Burckhardt & Ouvrard, 2023	Canary Islands	-	-	-	-	-	-	-	-	-	OR027209OR067180	[54]	-
Rhinocolinae	* Agonoscena cisti (Puton, 1882)	Albania, Memoraq	Pistacia lentiscus L.	39.8522	20.1470	190	10 June 2022	F	BFUS-I-IG027025	PSYBG098-24	BOLD:AEB2674	PQ109723 PQ100051	This study	-
Rhinocolinae	Agonoscena pistaciae Burckhardt & Lauterer, 1989	Bulgaria, Eastern Rila-Rhodopi Massif, Gaberovo, Gjurgena	Pistacia terebinthus L.	41.6206	25.8851	280	27 August 2022	F	BFUS-I-IG026831	PSYBG067-23	BOLD:AFM5846	PQ109726	This study	-
Rhinocolinae	Agonoscena sinuata Bastin, Burckhardt & Ouvrard 2023	Canary Islands	-	-	-	-	-	-	-	-	-	OR027214OR067162	[54,55]	-
Rhinocolinae	* Agonoscena targionii (Lichtenstein, 1874)	Bulgaria, Maleshevska Planina Mts., Kresna, Peyo Yavorov station	Pistacia terebinthus L.	41.7482	23.1615	217	13 August 2022	M	BFUS-I-IG026813	PSYBG111-24	BOLD:AFL7612	PQ109729 PQ100052	This study	Figure 1a
Rhinocolinae	Apsylla cistellata (Buckton, 1896)	Madagascar	-	-	-	-	-	-	-	-	-	MG988642MG988918	[16]; Percy, pers. comm.	-
Rhinocolinae	Lisronia echidna Loginova, 1976	Canary Islands	-	-	-	-	-	-	-	-	-	OR864739OR067189	[55]
Rhinocolinae	Megagonoscena gallicola Burckhardt & Lauterer, 1989	Bulgaria, Maleshevska Planina Mts., Stara Kresna	Pistacia terebinthus L.	41.7650	23.1662	360	7 May 2022	M	BFUS-I-IG026820	PSYBG051-23	BOLD:AFN1666	PQ109777	This study	Figure 1c
		Bulgaria, Maleshevska Planina Mts., Stara Kresna		41.7650	23.1662	360	7 May 2022	F	BFUS-I-IG027016	PSYBG112-24	-	PQ100067	This study	Figure 1c
Rhinocolinae	Rhinocola aceris (Linnaeus, 1758)	Bulgaria, Western Stara Planina Mts., Churek	Acer sp.	42.7805	23.7137	817	21 May 2022	M	BFUS-I-IG026822	PSYBG055-23	BOLD:ACK6660	PQ109778	This study	-
		Bulgaria, Transitional region, Lozenska Mts., Lozen		42.5944	23.5081	768	27 July 2022	M	BFUS-I-IG026979	PSYBG113-24	-	PQ100068	This study	Figure 1i
Phacopteroninae	Pseudophacopteron sp.	Australia	-	-	-	-	-	-	-	-	-	MG989234	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Anoeconeossa unicornuta Taylor, 1987	Australia	-	-	-	-	-	-	-	-	-	NC_038108	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Australopsylla sp.	Australia	-	-	-	-	-	-	-	-	-	MG988646MG988933	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Blastopsylla occidentalis Taylor, 1985	Australia	-	-	-	-	-	-	-	-	-	NC_038147	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Boreioglycaspis melaleucae Moore, 1964	Australia	-	-	-	-	-	-	-	-	-	MG988659MG988952	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Cardiaspina retator Taylor, 1962	Australia	-	-	-	-	-	-	-	-	-	MG988694MG988991	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Creiis sp.	Australia	-	-	-	-	-	-	-	-	-	MG988715MG989015	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Ctenarytaina eucalypti (Maskell, 1890)	Canary Islands	-	-	-	-	-	-	-	-	-	OR068450OR067182	[55]	-
Spondyliaspidinae	Glycaspis brimblecombei Moore, 1964	Canary Islands	-	-	-	-	-	-	-	-	-	OR068451OR067183	[55]	-
Spondyliaspidinae	Lasiopsylla rotundipennis Froggatt, 1900	Australia	-	-	-	-	-	-	-	-	-	MG988781MG989090	[16]; Percy, pers. comm.	-
Spondyliaspidinae	Platyobria sp.	Australia	-	-	-	-	-	-	-	-	-	MG988812MG989131	[16]; Percy, pers. comm.	-
Liviidae, Euphyllurinae	Psyllospsis fraxini (Linnaeus, 1758)	United Kingdom	-	-	-	-	-	-	-	-	-	MG988820MG989139	[16]; Percy, pers. comm.	-
Psyllidae, Psyllinae	Cacopsylla melanoneura (Foerster, 1848)	Italy	-	-	-	-	-	-	-	-	-	OQ304120	[56]	-
		Czech Republic	-	-	-	-	-	-	-	-	-	OR346833	[57]	-

Figure 1

Habitus of the studied species of Aphalaridae from Bulgaria. (a) Agonoscena targionii; (b) A. pistaciae; (c) Megagonoscena gallicola; (d) Colposcenia aliena; (e) Co. bidentata; (f) Co. osmanica; (g) Co. traciana; (h) Rhodochlanis bicolor; (i) Rhinocola aceris; (j) Aphalara affinis; (k) Aph. avicularis; (l) Aph. maculipennis; (m) Aph. nigrimaculosa; (n) Craspedolepta bulgarica; (o) Cr. conspersa, specimen from Austria, photo credit to T. Oswald; (p) Cr. innoxia; (q) Cr. nervosa; (r) Cr. pontica.

[Figure omitted. See PDF]

Table 2

PCR primers and conditions.

Gene	Primer Set	Primer Sequence′ (5′–3′)	Amplicon Size (bp)	PCR Conditions	Primer References
COI	LCOP-F	AGAACWAAYCATAAAAYWATTGG	654	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 50 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	[54]
	HCO2198R	TAAACTTCAGGGTGACCAAAAAATCA
	C_LepFolF	ATTCAACCAATCATAAAGATATTGG	658	94 °C for 1 min, 5 cycles of 94 °C for 30 s, 45–50 °C for 40 s, 72 °C for 1 min, 30–35 cycles of 94 °C for 30 s, 51–54 °C for 40 s and 72 °C for 1 min, 72 °C for 10 min	[58]
	C_LepFolR	TAAACTTCTGGATGTCCAAAAAATCA
	LCO1490F	GGTCAACAAATCATAAAGATATTGG	654	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 51 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	[58]
	HCO2198R	TAAACTTCAGGGTGACCAAAAAATCA
	VpmCOIF2	TACCTYTGAATTTGCAATTC	646	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 46 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	[59]
	VpmCOIR4	AATAARTGTTGGTATAARATAGG
Cytb	Cytbf	TGAGGNCAAATATCHTTYTGA	393	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 53 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	[16,49]
	Cytbr	GCAAATARRAARTATCATTCDG
	CytbnewF2	TGATTATGRGGAGGDTTYGC	330	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 53 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	This study
	CytbnewR	GTTGAATATGDATDGGDGTWAC
	CytbnewF1	TATGAGGAGGDTTYGCWGTTG	248	95 °C for 3 min; 35 cycles of 95 °C for 30 s, 53 °C 30 s and 72 °C for 1 min; 72 °C for 10 min	This study
	CytbnewR	GTTGAATATGDATDGGDGTWAC

2.3. Species Delimitation Based on Molecular Data

In order to verify the identification of the aphalarids, several species delimitation methods were applied to the molecular data. The Barcode Index Number (BIN) system was used to assign unique identifiers (BINs), corresponding to operational taxonomic units (OTUs), after the COI sequences were subjected to Refined Single Linkage (RESL) analysis in the BOLD system [60]. In addition, to evaluate the genetic distances and compare our results with those of other studies that did not use the BIN system, the Kimura 2-parameter (K2P) model was calculated for each COI and Cytb using MEGA v.11 [51]. The threshold of 3% K2P distance was used to delimit OTUs as an alternative to RESL analysis for Cytb data. Subsequently, Assemble Species by Automatic Partitioning (ASAP) and Automatic Barcode Gap Discovery (ABGD) methods were performed using K2P distances for each COI and Cytb [61,62]. Finally, ultrametric trees were generated using the K2P model in BEAST v. 10.5.0 [63] with 10 million replicates, followed by a 10% burn-in via TreeAnnotator. The resulting trees were saved in NEXUS format using FigTree v. 1.4.4 “http://tree.bio.ed.ac.uk/software/figtree (accessed on 8 January 2024)”, and the trees were tested with the Bayesian implementation of the Poisson Tree Processes (bPTP) [64] (implemented in the web server http://species.h-its.org/ptp/, accessed on 26 August 2024) and the multi-rate Poisson Tree Processes (mPTP) [65] (implemented in the web server http://mptp.h-its.org/#/tree, accessed on 26 August 2024).

2.4. Phylogenetic Analyses

In addition to the 25 aphalarid species sequenced in the current study, a further 21 species from the subfamilies Aphalarinae (6), Phacopteroninae (1), Rhinocolinae (4) and Spondyliaspidinae (10) were included in the phylogenetic analyses. Psyllopsis fraxini (Liviidae) and Cacopsylla melanoneura (Psyllidae), which are representatives of two psyllid families distantly related to Aphalaridae, were selected as outgroups.

All sequences not from this study were obtained from GenBank (Table 1). COI and Cytb sequences were extracted from the whole mitochondrial genome for the following species: Anoeconeossa unicornuta, Blastopsylla occidentalis, Lanthanaphalara mira, and Pseudophacopteron sp., while all other representatives were selected based on the availability of their COI and Cytb sequences in GenBank. Most of the sequence data are from Percy et al. [16], Bastin et al. [54,55], and Corretto et al. [56]. We consider their identifications to be reliable.

Prior to the phylogenetic analyses, the best partitioning scheme was determined using PartitionFinder2 [66], and the concatenated dataset was divided into four partitions according to gene regions and codon position. Setting of codon position for protein-coding gene fragments was performed with MESQUITE v.3.61 [67].

Maximum likelihood (ML) analysis was performed with IQ-TREE v.1.6.12. [68]. Nodal support was obtained through a standard non-parametric bootstrap with 1000 replicates. A suitable substitution model for each partition was calculated by IQ-TREE. Bayesian inference (BI) analysis was run using MrBayes v.3.2.7a [69] on the CIPRES platform [70]. The best substitution model for each gene was estimated using jModelTest v.2.1.10 [71] and a comparison of scores from Akaike information criterion (AIC) and Bayesian information criterion (BIC) (Table S2). For the BI analysis, two independent runs were performed, each with four Metropolis-coupled Markov chains for 15 million generations, sampling every 1000th generation. The priors for tree topology and speciation rates were set to uniform, the gamma distribution category number was set to 4, and the probability distribution for branch lengths was set to exponential. A Dirichlet prior was used to cover the substitution rates of the evolutionary models and the stationary nucleotide frequencies. The priors for all other parameters were left at the default values. Nodal support was assessed using posterior probabilities after discarding 30% of the samples as burn-in. The convergence of the MCMC chains was assessed with the average standard deviation of split frequencies (ASDSF). The ML and BI trees were visualised using iTOL v.5 [72] and FigTree v.1.4.4 “http://tree.bio.ed.ac.uk/software/figtree (accessed on 20 January 2024)”. Nodal support for ML analysis was assessed by the frequency of clade occurrence across the resampled datasets and is expressed as bootstrap values in %, while nodal support for BI analysis was expressed as posterior probability (PP), which indicates the probability that a given clade is correct based on the observed data and the specified model and ranges from 0 to 1. We considered significantly high nodal support for bootstrap values (BS) > 90% and for posterior probabilities (PP) > 0.95, and moderately good support for BS > 70–90% and for PP > 0.90–0.94 [73].

3. Results

3.1. Molecular Identification of the Bulgarian Aphalarids

We sequenced 25 species (1–6 specimens per species) of Aphalaridae, belonging to the two subfamilies Aphalarinae and Rhinocolinae with four and three genera, respectively, which were identified morphologically. The DNA of most analysed species was successfully amplified using the applied protocols. The COI gene fragment was amplified in 25 species, while Cytb was only successfully amplified in 18 species.

DNA barcodes were generated for the first time for the following 15 species: Aphalara affinis, Aph. freji, Aph. nigrimaculosa, Colposcenia aliena, Co. bidentata, Co. osmanica, Co. traciana, Craspedolepta bulgarica, Cr. conspersa, Cr. innoxia, Cr. malachitica, Cr. omissa, Cr. pontica, Megagonoscena gallicola, and Rhodochlanis bicolor.

All sequences of COI generated in the present study are available in BOLD (generic address), and the sequences of COI and Cytb of the analysed species are available in GenBank “https://www.ncbi.nlm.nih.gov/genbank/ (accessed on 30 July 2024)” (see also Data Availability Statement).

The Barcode Index Number (BIN) implemented in the BOLD system showed that our 61 COI sequences from 25 species are grouped in 22 BINs. Unique new BINs were generated for 15 species, and eight species were assigned to eight non-unique, pre-existing BINs. The majority of COI sequences generated were over 500 bp in length. Within Aphalarinae, the newly generated BIN BOLD:AFM9464 contained the 658 bp sequences of Aphalara maculipennis and Aph. nigrimaculosa, respectively. In addition, one of the pre-existing BINs (BOLD:ACY0265) contained the following three species: Aph. avicularis, Aph. freji, and Aph. polygoni. Aphalara polygoni from the current study was assigned to a separate, newly generated BIN (BOLD:AFL6229). In Colposcenia, Co. aliena (BOLD:AFN1581), Co. bidentata (BOLD:AFN1583), and Co. traciana (BOLD:AFL7588) were assigned new unique BINs, while C. osmanica was assigned to a pre-existing BIN (BOLD:AFN1582). In fact, as a result of our study we can identify the species assigned to the latter as Cr. osmanica. In Craspedolepta, all species received separate BINs, with the sole exception of Cr. bulgarica and Cr. innoxia, which were grouped together in the same BIN (BOLD:AFM9464). In Agonoscena (Rhinocolinae), A. pistaciae received two BINs. One of the sequences was assigned to a newly generated BIN (BOLD:AFL7611), while the other sequences were assigned to an already existing BIN (BOLD:AFM5846).

In addition to the BIN (RESL) analysis, we performed analyses of K2P genetic distance for both COI and Cytb gene fragments separately (Table S1). In Aphalarinae, rather high genetic distances for COI were observed between Aphalara affinis and Aph. maculipennis (0.1644), while a very low distance-based threshold was observed between Aph. avicularis and Aph. freji (0.0026). In Colposcenia, the interspecific distance for COI ranged from 0.1622 to 0.2365. Within the Craspedolepta species analysed, there were comparatively high genetic distances between Cr. conspersa and Cr. nervosa (0.1823), in contrast to the threshold between Cr. bulgarica and Cr. innoxia (0.0015), with the lowest genetic distance observed in our study. Within Agonoscena (Rhinocolinae), the genetic distance for COI was highest between A. pistaciae and A. targionii (0.2430), while the lowest genetic distance was found between A. cisti and A. pistaciae (0.1736).

In addition, the species boundaries based on the COI marker were tested with ASAP, ABGD, bPTP, and mPTP analyses (Figure 2). All analyses consistently combined Aphalara avicularis with Aph. freji, Aph. maculipennis with Aph. nigrimaculosa, and Craspedolepta bulgarica with Cr. innoxia, indicating that the COI gene is unsuitable for the delimitation of these species. Similar to the results of the BIN (RESL) analysis, almost all delimitation analyses separated A. pistaciae into two distinct species groups, highlighting the need for a more thorough molecular and morphological investigation of Agonoscena spp. in future studies. The only analysis that clustered A. pistaciae sequences together was ABGD. However, the same analysis suggested the separation of Aph. avicularis into two species. In total, only 17 OTUs could then be delimited using the COI marker.

With respect to Cytb, the interspecific divergence within the genera analysed was usually somewhat higher than that observed for COI. The maximum genetic distance within Aphalara was 0.1681 between Aph. avicularis and Aph. nigrimaculosa, while the distance between Aph. affinis and Aph. avicularis was the smallest (0.0771) of the species pairs that could be compared. In Colposcenia and Craspedolepta, the interspecific divergence ranged from 0.2571 to 0.3243 and from 0.1108 to 0.2803, respectively (however, Cytb data were available only for some Craspedolepta spp.). In Agonoscena, the interspecific distance between Agonoscena cisti and A. pistaciae was 0.2598. In most cases, the Cytb gene fragments gave comparable or better results for the separation of Aphalaridae species than the COI gene fragments. Using the 3% genetic distance threshold (as an alternative to RESL analysis for COI), ASAP, and bPTP, all 18 species analysed were successfully delimited. However, ABGD produced slightly different results and merged Aphalara affinis and Aph. avicularis into a single cluster, while mPTP was less effective and failed to delimit the taxa to species level, with the exception of Aph. nigrimaculosa, and instead grouped them into five clusters at the subfamily or genus level (Figure 3).

3.2. Phylogeny of Aphalaridae

In addition to the 25 aphalarid species sequenced in the current study, 21 species from the subfamilies Aphalarinae, Phacopteroninae, Rhinocolinae, and Spondyliaspidinae were included in the phylogenetic analyses. The final sequence alignment of 46 species of Aphalaridae and two outgroups contained 1043 characters. As both Bayesian inference (BI) and maximum likelihood (ML) analysis yielded very similar results, only the phylogenetic tree from the BI is shown in Figure 4 in the main text, while the ML tree is included as a Supplementary File (Figure S1).

In both analyses, support for monophyly of Aphalaridae was weak or virtually absent (0.52 PP, 24% BS). The subfamily Aphalarinae was strongly supported in both BI and ML analyses (1.00 PP, 95% BS). Aphalara was recovered as paraphyletic (0.89 PP, 66% BS), with Aph. itadori forming the sister taxon to the remaining Aphalara and Craspedolepta. The internal relationships of Aphalara were well supported in BI (0.94–1.00 PP) and ML analyses (92–99% BS), with the exception of Aph. itadori (66% BS) and Aph. maculipennis (74% BS). Craspedolepta was a strongly supported clade in both BI and ML analyses (1.00 PP, 96% BS). Four clades were strongly supported within the genus: Cr. omissa + (Cr. nervosa + Cr. pontica) (1.00 PP, 97% BS); Cr. nervosa + Cr. pontica (1.00 PP, 98% BS); Cr. nebulosa + Cr. subpunctata (1.00 PP, 96% BS); and Cr. bulgarica + Cr. innoxia (1.00 PP, 100% BS).

The support for monophyly of Rhinocolinae was weak in the ML analysis (72% BS) but strong in the BI (0.97 PP). Agonoscena was strongly supported in both analyses (1.00 PP, 90% BS), while support for the other genera was moderate to weak.

A sister group relationship between Phacopteroninae, represented only by Pseudophacopteron sp., and Aphalarinae was moderately supported (0.93 PP, 85% BS). The phylogenies of the two analyses also shared the same topology in terms of the strongly supported Spondyliaspidinae (1.00 PP, 97% BS) with a strongly supported clade Blastopsylla occidentalis Taylor, 1985 + Platyobria sp. (1.00 PP, 96% BS). The other nodes of the clade Spondyliaspidinae were weakly to moderately supported in the ML analysis. In the BI, Anoeconeossa unicornuta was strongly supported (0.99 PP) as a sister species to the clade Boreioglycaspis melaleucae + Glycaspis brimblecombei (1.00 PP). Lasiopsylla rotundipennis, Australopsylla sp., and Creiis sp. together constituted, with strong support (0.98 PP), the sister clade to Cardiaspina retator.

3.3. Faunistic Data

The following five species represent new records for Bulgaria: Agonoscena targionii, Aphalara affinis, Colposcenia aliena, Co. bidentata and Craspedolepta malachitica. Craspedolepta conspersa is reported for the first time from the Czech Republic, while Agonoscena cisti is reported for the first time from Albania (Table 1).

4. Discussion

4.1. Molecular Identification of Species

The highest species diversity among the psyllids is probably found in tropical and southern temperate regions [14], but there are also some characteristic northern temperate genera, such as Psylla Geoffroy and Spanioneura Foerster (Psyllidae) [14] or the species-rich Aphalara and Craspedolepta [32] (Aphalaridae). The latter family comprises about 60 described species in Europe, about half of which also occur in Bulgaria [15]. Aphalara and Craspedolepta are particularly diverse in Bulgaria, with seven and eleven species, respectively. The taxonomic knowledge of the two genera, based on morphology, is good for Europe [37], fair for the rest of the Palaearctic (e.g., [32,40,41]), but poor for the Nearctic [74]. Some species groups are morphologically homogeneous, which makes species identification difficult for non-experts. Here, we show that most of the 25 studied aphalarid species from seven genera, including Aphalara and Craspedolepta, differ significantly in molecular barcodes (COI and Cytb), which can be used to identify species that are difficult to separate morphologically. The DNA barcodes for 15 species are published here for the first time.

In other similar studies on psyllids, a distance-based threshold of 3% for mitochondrial markers was suggested as appropriate for distinguishing species of psyllids in New Zealand [2] or Cacopsylla species developing on pear in the Palaearctic [8]. We found a good correlation between molecular, morphological, and biological evidence for species delimitation, with a relatively high genetic divergence for most species supporting the 3% threshold. We suggest here that the COI and Cytb barcoding genes are useful for the molecular identification of most aphalarid species. However, the COI gene fragment alone was not sufficient to clearly separate six morphologically supported species of Aphalara and Craspedolepta in our study. Some other studies, e.g., on grasshoppers and fungus gnats, comparing morphological and molecular species identification [75,76] also showed contradictory results, with morphologically distinct taxa being indistinguishable in a single gene fragment.

The observed small interspecific difference in the COI between Aphalara avicularis and Aph. freji (0.0026), which could be due to genuine genetic proximity or limitations in the resolution of the COI gene, is also reflected in the morphological similarities between these two species [32,37]. Within Aphalara, there are several morphologically homogeneous species groups whose species differ in the distribution of surface spinules on the forewings and often subtle details of the terminalia [32]. These differences are paralleled by the host ranges. Aphalara avicularis and Aph. freji develop on the Polygonum aviculare aggregate and Persicaria spp., respectively, and differ from each other by the shape of the distal segment of the aedeagus and, to a certain extent, in the spacing of the surface spinules on the forewings. In the morphologically similar and closely related Aph. polygoni, which develops on Rumex spp., the surface spinules of the forewings are arranged in transverse rows. Two congeneric but morphologically different species, Craspedolepta bulgarica and Cr. innoxia, also showed only a slight genetic divergence. In morphology and host plant association [77], Cr. bulgarica is more similar to Cr. nervosa and Cr. pontica, which all develop on Achillea spp., than Cr. innoxia, which is associated with Daucus carota and Seseli leucospermum [78]. On the other hand, the interspecific genetic distances based on the COI for Agonoscena were significantly higher in our study than those found by Lashkari, et al. [47] for a different set of species in Iran (A. bimaculata, A. pegani, and A. pistaciae). Further studies on the genus are needed to clarify whether these discrepancies are due to differences in methodology, sample selection, or actual genetic divergence between species. All species delimitation methods based on COI yielded similar results and recognised 17 of 25 aphalarid species. However, the ABGD analysis yielded some contradictory results, suggesting cryptic lineages within Aphalara avicularis. This interpretation seems unlikely, as all other species delimitation methods and morphological observations consistently supported the conclusion that the Aph. avicularis specimens belong to a single species. On the other hand, the ABGD was the only method that recognised Agonoscena pistaciae specimens as a single species, which is consistent with morphological evidence.

In contrast to the COI delimitation results, where a maximum of 68% of the species were recognised, the Cytb gene allowed the correct assignment of all 100% of the species analysed using the 3% genetic distance threshold, ASAP, and bPTP, suggesting that this gene is an efficient marker for the recognition of aphalarid species, which was already suggested for Agonoscena by Lashkari et al. [47]. As we did not sequence Cytb for all species in this study, the comparison of the two genes remains preliminary.

4.2. Phylogenetic Relationships within Aphalaridae

The phylogenetic results of our study on Aphalaridae are similar to other phylogenetic analyses based on genomic or multilocus DNA sequence data [16,17]. The phylogenetic reconstruction inferred by the BI and ML analyses resulted in a similar tree topology, albeit with some differences (Figure 4 and Figure S1). In both analyses we performed, Aphalaridae were recovered as monophyletic, albeit with very low or virtually absent clade support. In their comprehensive amino-acid-based analysis, Wang et al. [18] found Aphalaridae to be monophyletic, in contrast to Percy et al. [16] and Cho et al. [17], who considered the family as paraphyletic.

In several studies [16,17,23,24,25], the monophyly of Aphalarinae and Rhinocolinae was well supported. Similarly, both subfamilies were strongly supported in our BI analysis. In contrast, the ML analysis in our study showed strong support for Aphalarinae, while Rhinocolinae was only weakly supported. Our analyses strongly supported the sister-group relationship between the Spondyliaspidinae and the moderately supported clade Aphalarinae + Phacopteroninae. Representatives of the three small subfamilies of Aphalaridae (Cecidopsyllinae, Microphyllurinae, and Togepsyllinae) were not included in our analyses, which may partly explain deviations from the previously published tree topologies [14,16,17,18].

Within Aphalarinae, our results are generally consistent with these from the previous studies [16,25,32]. There are two important differences in our analyses. Aphalara was recovered as paraphyletic with respect to Craspedolepta, as Aph. itadori formed a sister group to the remaining Aphalara + Craspedolepta. Craspedolepta bulgarica formed a strongly supported clade together with Cr. innoxia. Based on the morphological and host plant data [32,77], both groupings are highly unlikely and could result from the use of the limited number of exclusively mitochondrial gene markers.

Within Rhinocolinae, our results are in agreement with other studies [23,24]. Agonoscena was strongly supported as monophyletic, and its internal relationships are consistent with those proposed by Burckhardt and Lauterer [23] based on morphology and by Bastin et al. [79] based on molecular data.

The phylogenetic results of our study, especially the higher-level relationships, must be interpreted with caution, as only two short mitochondrial gene fragments were analysed here. For a more accurate investigation of the phylogenetic relationships within the group, additional nuclear markers should be used in future studies.

4.3. New Data on the Distribution of Aphalarid Species

The psyllid fauna of Bulgaria has been treated in a number of works (e.g., [23,26,27,28,29,30,31,32,33,34,80]), in which less than a hundred species were reported [15,35]. The revision of existing museum collections and more intensive faunistic research in recent years have revealed additional species [35,36,81]. Here we report five species for the first time from Bulgaria. Aphalara affinis is a species with a boreomontane distribution in northern Europe and Siberia as well as in the mountains of Central and Eastern Europe; it is associated with Stellaria graminea (Caryophyllaceae) in grasslands and forest clearings [15,37,82]. In Bulgaria, Aph. affinis was found in the Western Rhodopi Mountains. Colposcenia aliena and Co. bidentata are both associated with Tamarix spp. (Tamaricaceae), which in Bulgaria usually grow on sandy or stony substrates along rivers and the Black Sea coast. Colposcenia aliena is widespread in southern Europe, North Africa, the Middle East, and Central Asia [15,38,83]. Colposcenia bidentata is so far only known from Turkey [39,84]. Craspedolepta malachitica is widespread in Europe and temperate Asia on Artemisia absinthium and A. maritima (Asteraceae) in open habitats, such as disturbed dry grassland or salty sites [15,37,44]. Finally, Agonoscena targionii is widespread in its native range in the Mediterranean Basin and was introduced to Britain and Saint Helena; it is associated with Pistacia spp. (P. lentiscus, P. terebinthus, and P. vera; Anacardiaceae) [23,85].

The psyllid fauna of the Czech Republic is quite well known, with a rather long history of investigation and a total number of over 130 recorded species [86,87,88]. Here we report for the first time on Craspedolepta conspersa from the Czech Republic. The species was collected on its known host plant, Artemisia vulgaris (Asteraceae), in a ruderal habitat in southern Moravia, the warmest part of the country. Craspedolepta conspersa is known from southern parts of Central and Eastern Europe [43,44] and was recently reported for the first time from neighbouring Austria [89]. The Czech record is located at the northern limit of the species’ currently known range.

Compared to Bulgaria and the Czech Republic, Albania has only been very sparsely studied for Psylloidea. Agonoscena cisti, which is newly recorded here from Albania, is, similar to A. targionii, widely distributed in the Mediterranean region on Pistacia lentiscus and P. palaestina [23,90]. Given the presence of the species in neighbouring countries, its occurrence in Albania is not surprising.

5. Conclusions

Our study investigated the suitability of two barcoding genes, COI and Cytb, for the identification of species from the subfamilies Aphalarinae and Rhinocolinae (Aphalaridae). We provide the DNA barcodes for 25 species collected mainly in Bulgaria, of which 15 species were barcoded for the first time. The use of correctly identified barcodes will help to improve the dubious quality of repositories, such as GenBank and BOLD in the future. We have designed new primers for Cytb that can be used in future studies. In our study, the Cytb gene fragment showed better results by correctly delimiting 100% of the analysed species, compared to COI (68%), and thus could be a useful tool for efficient and accurate identification of aphalarid species. Overall, we believe that molecular data are a valuable tool, providing new insights for the diagnosis of aphalarid species, especially when combined with reliable morphological characters. We found good agreement between the resulting species definitions based on molecular, morphological and ecological (e.g., host plant) data. However, the low genetic divergence between some aphalarid species found in our study also demonstrates the importance of using an integrative taxonomic approach [2,48,91], including the study of psyllid morphology, ecological data and multilocus molecular data, for accurate species identification.

Author Contributions

Conceptualisation, M.P., L.Š.S. and D.B.; methodology, M.P., L.Š.S., D.B. and I.G.; validation, L.Š.S., I.M. and D.B.; formal analysis, M.P. and L.Š.S.; investigation, M.P. and L.Š.S.; resources, M.P., I.G. and H.S.; data curation, M.P. and I.G.; writing—original draft preparation, M.P. and L.Š.S.; writing—review and editing, I.M. and D.B.; visualisation, M.P.; supervision, L.Š.S., I.M. and D.B.; project administration, M.P. and I.G.; funding acquisition, M.P. and H.S. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

All DNA sequences can be accessed in BOLD under the project name “PSYBG” (Process ID: PSYBG001-23–PSYBG067-23, PSYBG096-24–PSYBG116-24), available also in GenBank (COI accession numbers: PQ109723–PQ109782, Cytb accession numbers: PQ100051–PQ100069).

Acknowledgments

M.P. is grateful to the Sofia University Student Council for funding her stay at the Free University of Bozen-Bolzano. We thank D. Percy (University of British Columbia, Canada) for providing detailed locality data for the published sequences and T. Oswald (Karl-Franzens-Universität, Graz, Austria) for the photograph of Cr. conspersa. We are grateful to two anonymous reviewers for their critical comments, which significantly improved the quality of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 2. Results of species delimitation methods based on the cytochrome c oxidase subunit I (COI) gene. Each vertical colour bar represents different delimitation schemes obtained with ASAP, ABGD, RESL, bPTP, and mPTP methods, with the corresponding number of specimens. The tree is based on ASAP analysis, with nodes colour coded depending on their p-value (black: p [less than] 0.001, red: p [less than] 0.05, orange: p [less than] 0.1, yellow: p [greater than] 0.1, grey: not applicable).

Figure 3. Results of species delimitation methods based on the cytochrome b (Cytb) gene. Each vertical colour bar represents different delimitation schemes obtained with ASAP, ABGD, bPTP and mPTP methods, with the corresponding number of specimens. Grouping based on a threshold of 3% using the Kimura 2-parameter pairwise distance (PDK2P) is presented as an alternative to RESL analysis of COI data. The tree is based on ASAP analysis, with nodes colour coded depending on their p-values (yellow: p [greater than] 0.1, grey: not applicable).

Figure 4. Phylogenetic tree based on Bayesian inference (BI) analysis of concatenated COI and Cytb gene fragments of representatives of the family Aphalaridae. Nodal support is given as posterior probability values.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/insects15090683/s1, Figure S1: Phylogenetic tree based on the maximum likelihood analysis of concatenated COI and Cytb gene fragments of representatives of the family Aphalaridae. Nodal support is assessed by bootstrap values; Table S1: Interspecific K2P distances (COI and Cytb gene fragments) of the analysed species of Aphalaridae; Table S2: Gene partitions with estimated nucleotide substitution models used in Bayesian inference (BI) analysis based on a comparison of scores from Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in JModeltest.

References

1. Löbl, I.; Klausnitzer, B.; Hartmann, M.; Krell, F.-T. The Silent Extinction of Species and Taxonomists—An Appeal to Science Policymakers and Legislators. Diversity; 2023; 15, 1053. [DOI: https://dx.doi.org/10.3390/d15101053]

2. Martoni, F.; Bulman, S.; Pitman, A.; Taylor, G.; Armstrong, K. DNA Barcoding Highlights Cryptic Diversity in the New Zealand Psylloidea (Hemiptera: Sternorrhyncha). Diversity; 2018; 10, 50. [DOI: https://dx.doi.org/10.3390/d10030050]

3. Yin, Y.; Yao, L.F.; Hu, Y.; Shao, Z.K.; Hong, X.Y.; Hebert, P.D.N.; Xue, X.F. DNA Barcoding Uncovers Cryptic Diversity in Minute Herbivorous Mites (Acari, Eriophyoidea). Mol. Ecol. Resour.; 2022; 22, pp. 1986-1998. [DOI: https://dx.doi.org/10.1111/1755-0998.13599]

4. Hebert, P.D.; Cywinska, A.; Ball, S.L.; DeWaard, J.R. Biological Identifications through DNA Barcodes. Proc. R. Soc. B Biol. Sci.; 2003; 270, pp. 313-321. [DOI: https://dx.doi.org/10.1098/rspb.2002.2218]

5. Suh, S.-J.; Choi, D.-S. Using DNA Barcoding for Identification of Some Psyllids (Hemiptera: Psylloidea) Intercepted at South Korea Ports-of-Entry. Insecta Mundi; 2020; 816, pp. 1-10. [DOI: https://dx.doi.org/10.5281/zenodo.4565519]

6. Sumner-Kalkun, J.; Sjölund, M.; Arnsdorf, Y.; Carnegie, M.; Highet, F.; Ouvrard, D.; Greenslade, A.; Bell, J.; Sigvald, R.; Kenyon, D. A Diagnostic Real-Time PCR Assay for the Rapid Identification of the Tomato-Potato Psyllid, Bactericera cockerelli (Šulc, 1909) and Development of a Psyllid Barcoding Database. PLoS ONE; 2020; 15, e0230741. [DOI: https://dx.doi.org/10.1371/journal.pone.0230741]

7. Moesges, Z.; Brandis, D.; Ewers, C. Detailed Integrative Taxonomic Analysis Reveals Large-Scale Species Misidentification of Barnacles Based on DNA Barcoding Data. Zool. J. Linn. Soc.; 2023; 201, zlad145. [DOI: https://dx.doi.org/10.1093/zoolinnean/zlad145]

8. Cho, G.; Malenovský, I.; Burckhardt, D.; Inoue, H.; Lee, S. DNA Barcoding of Pear Psyllids (Hemiptera: Psylloidea: Psyllidae), a Tale of Continued Misidentifications. Bull. Entomol. Res.; 2020; 110, pp. 521-534. [DOI: https://dx.doi.org/10.1017/S0007485320000012] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32037992]

9. Burckhardt, D. Psylloid Pests of Temperate and Subtropical Crop and Ornamental Plants (Hemiptera, Psylloidea): A Review. Trends Agric. Sci. Entomol.; 1994; 2, pp. 173-186.

10. De Morais, E.G.F.; Picanço, M.C.; Barreto, R.W.; Silva, N.R.; Campos, M.R. Biological Performance of Diclidophlebia smithi (Hemiptera: Psyllidae), a Potential Biocontrol Agent for the Invasive Weed Miconia calvescens. Biocontrol Sci. Technol.; 2010; 20, pp. 107-116. [DOI: https://dx.doi.org/10.1080/09583150903428711]

11. Munyaneza, J.E. Psyllids as Vectors of Emerging Bacterial Diseases of Annual Crops. Southwest. Entomol.; 2010; 35, pp. 471-477. [DOI: https://dx.doi.org/10.3958/059.035.0335]

12. Moreno, A.; Miranda, M.P.; Fereres, A. Psyllids as Major Vectors of Plant Pathogens. Entomol. Gen.; 2021; 41, pp. 419-438. [DOI: https://dx.doi.org/10.1127/entomologia/2021/1289]

13. Burckhardt, D.; Ouvrard, D.; Queiroz, D.L.; Percy, D.M. Psyllid Host-Plants (Hemiptera: Psylloidea): Resolving a Semantic Problem. Fla. Entomol.; 2014; 97, pp. 242-246. [DOI: https://dx.doi.org/10.1653/024.097.0132]

14. Burckhardt, D.; Ouvrard, D.; Percy, D.M.M. An Updated Classification of the Jumping Plant-Lice (Hemiptera: Psylloidea) Using Molecular and Morphological Evidence. Eur. J. Taxon.; 2021; 736, pp. 137-182. [DOI: https://dx.doi.org/10.5852/ejt.2021.736.1257]

15. Ouvrard, D. Psyl’list—The World Psylloidea Database. Available online: http://psyllist.hemiptera.infosyslab.fr/psyllist/ (accessed on 20 June 2024).

16. Percy, D.M.; Crampton-Platt, A.; Sveinsson, S.; Lemmon, A.R.; Lemmon, E.M.; Ouvrard, D.; Burckhardt, D. Resolving the Psyllid Tree of Life: Phylogenomic Analyses of the Superfamily Psylloidea (Hemiptera). Syst. Entomol.; 2018; 43, pp. 762-776. [DOI: https://dx.doi.org/10.1111/syen.12302]

17. Cho, G.; Malenovský, I.; Lee, S. Higher-level Molecular Phylogeny of Jumping Plant Lice (Hemiptera: Sternorrhyncha: Psylloidea). Syst. Entomol.; 2019; 44, pp. 638-651. [DOI: https://dx.doi.org/10.1111/syen.12345]

18. Wang, W.; Dong, Z.; Du, Z.; Wu, P. Genome-Scale Approach to Reconstructing the Phylogenetic Tree of Psyllids (Superfamily Psylloidea) with Account of Systematic Bias. Mol. Phylogenet. Evol.; 2023; 189, 107924. [DOI: https://dx.doi.org/10.1016/j.ympev.2023.107924]

19. Burckhardt, D. Ctenarytaina eucalypti (Maskell) (Hemiptera, Psylloidea) Neu Für Mitteleuropa Mit Bemerkungen Zur Blattflohfauna von Eucalyptus. Mitt. Ent. Ges.; 1998; 48, pp. 59-67.

20. Valente, C.; Manta, A.; Vaz, A. First Record of the Australian Psyllid Ctenarytaina spatulata Taylor (Homoptera: Psyllidae) in Europe. J. Appl. Entomol.; 2004; 128, pp. 369-370. [DOI: https://dx.doi.org/10.1111/j.1439-0418.2004.00860.x]

21. Valente, C.; Hodkinson, I. First Record of the Red Gum Lerp Psyllid, Glycaspis brimblecombei Moore (Hemiptera: Psyllidae), in Europe. J. Appl. Entomol.; 2008; 133, pp. 315-317. [DOI: https://dx.doi.org/10.1111/j.1439-0418.2008.01324.x]

22. Mifsud, D. The Jumping Plant-Lice (Hemiptera: Pysilloidea) of the Maltese Islands. Bull. Entomol. Soc.; 2020; 11, pp. 103-117. [DOI: https://dx.doi.org/10.17387/bullentsocmalta.2020.18]

23. Burckhardt, D.; Lauterer, P. Systematics and Biology of the Rhinocolinae (Homoptera: Psylloidea). J. Nat. Hist.; 1989; 23, pp. 643-712. [DOI: https://dx.doi.org/10.1080/00222938900770371]

24. Burckhardt, D.; Basset, Y. The Jumping Plant-Lice (Hemiptera, Psylloidea) Associated with Schinus (Anacardiaceae): Systematics, Biogeography and Host Plant Relationships. J. Nat. Hist.; 2000; 34, pp. 57-155. [DOI: https://dx.doi.org/10.1080/002229300299688]

25. Burckhardt, D.; Queiroz, D.L. Phylogenetic Relationships within the Subfamily Aphalarinae Including a Revision of Limataphalara (Hemiptera: Psylloidea: Aphalaridae). Acta Musei Morav. Sci. Biol.; 2013; 98, pp. 35-56.

26. Joakimov, D. Po Faunata Na Hemiptera va Balgaria (On the Fauna of Hemiptera of Bulgaria). Nar. Umotvor. Nauk. Knizhnina.; 1909; 25, pp. 1-34.

27. Klimaszewski, S. Psyllidologische Notizen XII–XIV (Homoptera). Ann. Zool.; 1965; 23, pp. 195-209.

28. Harizanov, A.; Lauterer, P. Beitrag Zur Fauna Der Blattflöhe (Homoptera-Psylloidea) in Bulgarien. Landwirtsch. Hochsch. Wassil Kolar.; 1968; 17, pp. 139-145.

29. Klimaszewski, S. Psyllidologische Notizen XVIII—XX (Homoptera). Ann. Zool.; 1970; 27, pp. 417-428.

30. Głowacka, E.; Harizanov, A. The Jumping Plant Lice (Homoptera, Psylloidea) from Western Rodope Mountains (Bulgaria). Acta Biol.; 1983; 12, pp. 62-69.

31. Głowacka, E. Jumpin Plant-Lice (Homaptera: Psylloidea) of the Pirin Mountains (Bulgaria). Acta Biol.; 1989; 13, pp. 14-19.

32. Burckhardt, D.; Lauterer, P. Systematics and Biology of the Aphalara exilis (Weber & Mohr) Species Assemblage (Hemiptera: Psyllidae). Entomol. Scand.; 1997; 28, pp. 271-305. [DOI: https://dx.doi.org/10.1163/187631297X00088]

33. Lauterer, P.; Malenovský, I. New Distributional and Biological Data on European Psylloidea (Hemiptera, Sternorrhyncha), with Special Reference to the Fauna of the Czech Republic and Slovakia. Entomol. Basiliensia; 2002; 24, pp. 161-177.

34. Labina, E.S. The Jumping-Lice (Homoptera, Psyllinea) Fauna of the Republic of Altai. Entomol. Rev.; 2008; 88, pp. 277-285. [DOI: https://dx.doi.org/10.1134/S0013873808030032]

35. Pramatarova, M.; Malenovský, I.; Gjonov, I. Notes on Jumping Plant-Lice (Hemiptera, Psylloidea) from the Sarnena Gora Mountains. Fauna of Sarnena Sredna Gora Mts, Part 2 ZooNotes, Supplement 10; Georgiev, D.; Bechev, D.; Yancheva, V. Plovdiv University Press “Paisii Hilendarski”: Plovdiv, Bulgaria, 2021; pp. 28-37. [DOI: https://dx.doi.org/10.5281/zenodo.5806004]

36. Pramatarova, M.; Malenovský, I.; Gjonov, I. Psyllids (Hemiptera: Psylloidea) in the Entomological Collection of the National Museum of Natural History, Bulgarian Academy of Sciences. Hist. Nat. Bulg.; 2023; 45, pp. 261-269. [DOI: https://dx.doi.org/10.48027/hnb.45.102]

37. Ossiannilsson, F. The Psylloidea (Homoptera) of Fennoscandia and Denmark. Fauna Entomol. Scand.; 1992; 26, pp. 1-347.

38. Loginova, M. Jumping Plant Lice of the Tribe Stigmaphalarini Vondr. (Psylloidea, Aphalaridae) from Arid Regions of Palaearctic. Rev. Entomoogie URSS; 1974; LIII, pp. 150-170.

39. Burckhardt, D. Angaben Zur Psyllidenfauna Der Nordosttürkei (Homoptera: Psylloidea). Mitteilungen Entomol. Gesellschafi; 1988; 38, pp. 31-44.

40. Loginova, M.M. A Revision of the Species of the Genera Aphalara Frst. and Craspedolepta Enderl. (Homoptera, Psylloidea) in the Fauna of the USSR. I. Rev. Entomoogie URSS; 1961; XL, pp. 602-623.

41. Loginova, M. Revision of the Species of the Genera Aphalara Frsr. and Craspedolepta Enderl. (Homoptera, Psylloidea) in the Fauna of the USSR. II. Rev. Entomoogie URSS; 1963; XLII, pp. 621-648.

42. Dobreanu, E.; Manolache, C. Insecta, Homoptera, Psylloidea. Fauna Republicii Populare Romane; Botnariuc, N. Academia Română: Bucharest, Romania, 1962; pp. 1-376.

43. Conci, C.; Tamanini, L. Craspedolepta conspersa, Nuova per l’Italia, Da Artemisia vulgaris (Insecta: Homoptera: Psylloidea). Stud. Trentini Sci. Nat. Acta Biol.; 1983; 60, pp. 77-85.

44. Burckhardt, D.; Lauterer, P. Faunistic and Taxonomic Notes on Jumping Plant-Lice from the Alps (Hemiptera: Psylloidea: Aphalarinae). Contrib. Nat. Hist.; 2009; 12, pp. 341-348. [DOI: https://dx.doi.org/10.5169/seals-786971]

45. Conci, C.; Tamanini, L. Rhodochlanis salicorniae Klim. Nuovo per l’Italia, R. Hodkinsoni n. Sp. Di Puglia, Da Suaeda vera e Considerazioni Sul Genere. Atti Soc. Ital. Sci. Nat. Mus. Civ. Stor. Nat.; 1984; 125, pp. 61-80.

46. Burckhardt, D. Les Psylles (Insecta, Homoptera, Psylloidea) de l’Algerie. Arch. Sci.; 1989; 42, pp. 367-424. [DOI: https://dx.doi.org/10.5169/seals-740086]

47. Lashkari, M.; Burckhardt, D.; Gushki, R.S. Molecular and Morphometric Identification of Pistachio Psyllids with Niche Modeling of Agonoscena pistaciae (Hemiptera: Aphalaridae). Bull. Entomol. Res.; 2019; 110, pp. 1-11. [DOI: https://dx.doi.org/10.1017/S0007485319000555]

48. Percy, D.M. Making the Most of Your Host: The Metrosideros-Feeding Psyllids (Hemiptera, Psylloidea) of the Hawaiian Islands. Zookeys; 2017; 649, pp. 1-163. [DOI: https://dx.doi.org/10.3897/zookeys.649.10213]

49. Timmermans, M.J.T.N.; Dodsworth, S.; Culverwell, C.L.; Bocak, L.; Ahrens, D.; Littlewood, D.T.J.; Pons, J.; Vogler, A.P. Why Barcode? High-Throughput Multiplex Sequencing of Mitochondrial Genomes for Molecular Systematics. Nucleic Acids Res.; 2010; 38, e197. [DOI: https://dx.doi.org/10.1093/nar/gkq807]

50. Kearse, M.; Moir, R.; Wilson, A.; Stones-Havas, S.; Cheung, M.; Sturrock, S.; Buxton, S.; Cooper, A.; Markowitz, S.; Duran, C. et al. Geneious Basic: An Integrated and Extendable Desktop Software Platform for the Organization and Analysis of Sequence Data. Bioinformatics; 2012; 28, pp. 1647-1649. [DOI: https://dx.doi.org/10.1093/bioinformatics/bts199]

51. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol. Biol. Evol.; 2021; 38, pp. 3022-3027. [DOI: https://dx.doi.org/10.1093/molbev/msab120]

52. Gouy, M.; Guindon, S.; Gascuel, O. SeaView Version 4: A Multiplatform Graphical User Interface for Sequence Alignment and Phylogenetic Tree Building. Mol. Biol. Evol.; 2010; 27, pp. 221-224. [DOI: https://dx.doi.org/10.1093/molbev/msp259]

53. Andersen, J.C.; Bourchier, R.S.; Grevstad, F.S.; Van Driesche, R.; Mills, N.J. Development and Verification of SNP Arrays to Monitor Hybridization between Two Host-Associated Strains of Knotweed Psyllid, Aphalara itadori. Biol. Control.; 2016; 93, pp. 49-55. [DOI: https://dx.doi.org/10.1016/j.biocontrol.2015.11.007]

54. Bastin, S.; Percy, D.M.; Siverio, F. Establishing Reliable DNA Barcoding Primers for Jumping Plant Lice (Psylloidea, Hemiptera). BMC Res. Notes; 2023; 16, 322. [DOI: https://dx.doi.org/10.1186/s13104-023-06585-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37941051]

55. Bastin, S.; Reyes-Betancort, J.A.; Siverio, F.; Percy, D.M. Origins of the Central Macaronesian Psyllid Lineages (Hemiptera; Psylloidea) with Characterization of a New Island Radiation on Endemic Convolvulus floridus (Convolvulaceae) in the Canary Islands. PLoS ONE; 2024; 19, e0297062. [DOI: https://dx.doi.org/10.1371/journal.pone.0297062] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38277393]

56. Corretto, E.; Trenti, M.; Serbina, L.; Howie, J.; Dittmer, J.; Kerschbamer, C.; Candian, V.; Tedeschi, R.; Janik, K.; Schuler, H. Multiple Factors Driving the Acquisition Efficiency of Apple Proliferation Phytoplasma in Cacopsylla melanoneura. J. Pest Sci.; 2023; 97, pp. 1299-1314. [DOI: https://dx.doi.org/10.1007/s10340-023-01699-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/39188925]

57. Šafářová, D.; Zrníková, E.; Holušová, K.; Ouředníčková, J.; Starý, M.; Navrátil, M. Molecular Characterization of Mitogenome of Cacopsylla picta and Cacopsylla melanoneura, Two Vector Species of ‘Candidatus Phytoplasma Mali’. Agronomy; 2023; 13, 2210. [DOI: https://dx.doi.org/10.3390/agronomy13092210]

58. Folmer, O.; Black, M.; Hoeh, W.; Lutz, R. DNA Primers for Amplification of Mitochondrial Cytochrome c Oxidase Subunit I from Diverse Metazoan Invertebrates. Mol. Mar. Biol. Biotechnol.; 1994; 3, pp. 294-299. [DOI: https://dx.doi.org/10.1071/ZO9660275]

59. Oettl, S.; Schlink, K. Molecular Identification of Two Vector Species, Cacopsylla melanoneura and Cacopsylla picta (Hemiptera: Psyllidae), of Apple Proliferation Disease and Further Common Psyllids of Northern Italy. J. Econ. Entomol.; 2015; 108, pp. 2174-2183. [DOI: https://dx.doi.org/10.1093/jee/tov204]

60. Ratnasingham, S.; Hebert, P.D.N. A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System. PLoS ONE; 2013; 8, e66213. [DOI: https://dx.doi.org/10.1371/journal.pone.0066213]

61. Puillandre, N.; Lambert, A.; Brouillet, S.; Achaz, G. ABGD, Automatic Barcode Gap Discovery for Primary Species Delimitation. Mol. Ecol.; 2012; 21, pp. 1864-1877. [DOI: https://dx.doi.org/10.1111/j.1365-294X.2011.05239.x]

62. Puillandre, N.; Brouillet, S.; Achaz, G. ASAP: Assemble Species by Automatic Partitioning. Mol. Ecol. Resour.; 2021; 21, pp. 609-620. [DOI: https://dx.doi.org/10.1111/1755-0998.13281]

63. Suchard, M.A.; Lemey, P.; Baele, G.; Ayres, D.L.; Drummond, A.J.; Rambaut, A. Bayesian Phylogenetic and Phylodynamic Data Integration Using BEAST 1.10. Virus Evol.; 2018; 4, vey016. [DOI: https://dx.doi.org/10.1093/ve/vey016]

64. Zhang, J.; Kapli, P.; Pavlidis, P.; Stamatakis, A. A General Species Delimitation Method with Applications to Phylogenetic Placements. Bioinformatics; 2013; 29, pp. 2869-2876. [DOI: https://dx.doi.org/10.1093/bioinformatics/btt499] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23990417]

65. Kapli, P.; Lutteropp, S.; Zhang, J.; Kobert, K.; Pavlidis, P.; Stamatakis, A.; Flouri, T. Multi-Rate Poisson Tree Processes for Single-Locus Species Delimitation under Maximum Likelihood and Markov Chain Monte Carlo. Bioinformatics; 2017; 33, pp. 1630-1638. [DOI: https://dx.doi.org/10.1093/bioinformatics/btx025] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28108445]

66. Lanfear, R.; Frandsen, P.; Wright, A.; Senfeld, T.; Calcott, B. Partitionfinder 2: New Methods for Selecting Partitioned Models of Evolution for Molecular and Morphological Phylogenetic Analyses. Mol. Biol. Evol.; 2016; 34, pp. 772-773. [DOI: https://dx.doi.org/10.1093/molbev/msw260] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28013191]

67. Maddison, W.; Maddison, D. Mesquite: A Modular System for Evolutionary Analysis. Version 3.81. 2023; Available online: http://www.mesquiteproject.org (accessed on 19 January 2024).

68. Trifinopoulos, J.; Nguyen, L.; Haeseler, A.; Minh, B. W-IQ-TREE: A fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res.; 2016; 44, pp. W232-W235. [DOI: https://dx.doi.org/10.1093/nar/gkw256] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27084950]

69. Ronquist, F.; Teslenko, M.; Van Der Mark, P.; Ayres, D.; Darling, A.; Höhna, S.; Larget, B.; Liu, L.; Suchard, M.; Huelsenbeck, J. Mrbayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice across a Large Model Space. Syst. Biol.; 2012; 61, pp. 539-542. [DOI: https://dx.doi.org/10.1093/sysbio/sys029]

70. Miller, M.; Pfeiffer, W.; Schwartz, T. Creating the CIPRES Science Gateway for inference of large phylogenetic trees. Proceedings of the 2010 Gateway Computing Environments Workshop (GCE); New Orleans, LA, USA, 14 November 2010; pp. 1-8.

71. Darriba, D.; Taboada, G.; Doallo, R.; Posada, D. JModelTest 2: More Models, New Heuristics and Parallel Computing. Nat. Methods; 2012; 9, 772. [DOI: https://dx.doi.org/10.1038/nmeth.2109]

72. Letunic, I.; Bork, P. Interactive Tree of Life (ITOL) v5: An Online Tool for Phylogenetic Tree Display and Annota-tion. Nucleic Acids Res.; 2021; 49, pp. W293-W296. [DOI: https://dx.doi.org/10.1093/nar/gkab301]

73. Burckhardt, D.; Serbina, L.; Malenovský, I.; De Queiroz, D.L.; Aléné, D.C.; Cho, G.; Percy, D.M. Phylogeny and Classification of Jumping Plant Lice of the Subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) Based on Molecular and Morphological Data. Zool. J. Linn. Soc.; 2023; 201, pp. 387-421. [DOI: https://dx.doi.org/10.1093/zoolinnean/zlad128]

74. Halbert, S.E.; Burckhardt, D. The Psyllids (Hemiptera: Psylloidea) of Florida: Newly Established and Rarely Collected Taxa and Checklist. Insecta Mundi; 2020; 788, pp. 1-88. [DOI: https://dx.doi.org/10.5281/zenodo.4564694]

75. Dowle, E.J.; Morgan-Richards, M.; Trewick, S.A. Morphological Differentiation despite Gene Flow in an Endangered Grasshopper. BMC Evol. Biol.; 2014; 14, pp. 19-23. [DOI: https://dx.doi.org/10.1186/s12862-014-0216-x]

76. Kurina, O.; Õunap, E.; Põldmaa, K. Two New Neuratelia rondani (Diptera, Mycetophilidae) Species from Western Palaearctic: A Case of Limited Congruence between Morphology and DNA Sequence Data. Zookeys; 2015; 129, pp. 105-129. [DOI: https://dx.doi.org/10.3897/zookeys.496.9315] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25931957]

77. Lauterer, P. A Contribution to the Knowledge of the Psyllid Fauna of Czechoslovakia II. Acta Musei Morav. Sci. Biol.; 1965; 50, pp. 171-190.

78. Burckhardt, D. Vorläufiges Verzeichnis Der Blattflöhe Mitteleuropas Mit Wirtspflanzenangaben (Insecta, Hemiptera, Psylloidea). Beiträge Zikadenkd.; 2002; 5, pp. 1-9.

79. Bastin, S.; Burckhardt, D.; Reyes-Betancort, J.A.; Hernández-Suárez, E.; Ouvrard, D. A Review of the Jumping Plant-Lice (Hemiptera: Psylloidea) of the Canary Islands, with Descriptions of Two New Genera and Sixteen New Species. Zootaxa; 2023; 5313, pp. 1-98. [DOI: https://dx.doi.org/10.11646/zootaxa.5313.1.1]

80. Percy, D.M.; Cronk, Q. Salix Transect of Europe: Patterns in the Distribution of Willow-Feeding Psyllids (Hemiptera: Psylloidea) from Greece to Arctic Norway. Biodivers. Data J.; 2020; 8, e53788. [DOI: https://dx.doi.org/10.3897/BDJ.8.e53788]

81. Pramatarova, M. Taxonomic, Faunistic, and Ecological Studies of the Superfamily Psylloidea in Bulgaria. Master’s Thesis; Sofia University “St. Kliment Ohridski”: Sofia, Bulgaria, 2021.

82. Malenovský, I.; Kment, P.; Sychra, J. True Bugs, Leafhoppers, Planthoppers and Psyllids (Hemiptera: Heteroptera, Auchenorrhyncha, Psylloidea) of the Environs of Přebuz in the Krušné Hory Mountains (Czech Republic). Klapalekiana; 2014; 50, pp. 181-234.

83. Malenovský, I.; Lauterer, P.; Burckhardt, D.; Labina, E.S.; Burckhardt, D. Jumping Plant-Lice (Hemiptera: Psylloidea) of Afghanistan. Acta Entomol. Musei Natl. Pragae; 2012; 52, pp. 1-22.

84. Burckhardt, D.; Önuçar, A. A Review of Turkish Jumping Plant-Lice (Homoptera, Psylloidea). Rev. Suisse Zool.; 1993; 100, pp. 547-574. [DOI: https://dx.doi.org/10.5962/bhl.part.79887]

85. Luker, S. A Pistachio Psyllid Agonoscene targionii (Hemiptera: Aphalaridae) New to Britain. Bull. Nat. Hist. Mus. Entomol.; 2015; 28, pp. 1-5.

86. Vondráček, K. Mery-Psylloidea [Jumping Plant Lice—Psylloidea]. Fauna ČSR, Svazek 9. [Fauna of Czechoslovakia, Vol. 9]; Československá akademie věd: Praha, Czech Republic, 1957; pp. 1-430.

87. Lauterer, P. Psyllodea. Psylloidea. In Enumeratio Insectorum Bohemoslovakiae. Check List Tschechoslowakische Insektenfauna; Dlabola, J., Ed. Acta Faun. Entomol. Mus. Natl. Pragae; 1977; 15, (Suppl. 4), pp. 97-100.

88. Malenovský, I.; Lauterer, P. Psylloidea (Mery). In Red List of Threatened Species of the Czech Republic. Invertebrates; Hejda, R., Farkač, J., Chobot, K., Eds. Příroda; 2017; 36, pp. 161-165.

89. Oswald, T. Erstfunde von Bactericera perrisii Puton, 1876 Und Craspedolepta conspersa (Löw, 1888) Aus Österreich (Hemiptera: Psylloidea). Cicadina; 2024; 23, pp. 23-27. [DOI: https://dx.doi.org/10.25673/116290]

90. Pramatarova, M.; Mifsud, D.; Gjonov, I. First Record of the Pistachio Psyllid Agonoscena cisti (Puton, 1882) (Hemiptera, Psylloidea) in the Maltese Islands (Central Mediterranean). Check List; 2024; 20, pp. 991-995. [DOI: https://dx.doi.org/10.15560/20.4.991]

91. Masonick, P.; Weirauch, C. Integrative Species Delimitation in Nearctic Ambush Bugs (Heteroptera: Reduviidae: Phymatinae): Insights from Molecules, Geometric Morphometrics and Ecological Associations. Syst. Entomol.; 2020; 45, pp. 205-223. [DOI: https://dx.doi.org/10.1111/syen.12388]