The classification of the hyperdiverse true bug family Miridae is far from settled, and is particularly contentious for the cosmopolitan subfamily Bryocorinae. The morphological diversity within the subfamily is pronounced, and a lack of explicit character formulation hampers stability in the classification. Molecular partitions are few and only a handful of taxa have been sequenced. In this study the phylogeny of the subfamily Bryocorinae has been analysed based on morphological data alone, with an emphasis on evaluating the tribe Dicyphina sensu Schuh, 1976, within which distinct groups of taxa exist. A broad sample of taxa was examined from each of the bryocorine tribes. A broad range of outgroup taxa from most of the other mirid subfamilies was also examined to test for bryocorine monophyly, ingroup relationships and to determine character polarity. In total a matrix comprising 44 ingroup, 15 outgroup taxa and 111 morphological characters was constructed. The phylogenetic analysis resulted in a monophyletic subfamily Bryocorinae sensu Schuh (1976, 1995), except for the genus Palaucoris, which is nested within Cylapinae. The tribe Dicyphini sensu Schuh (1976, 1995) has been rejected. The subtribe Odoniellina is synonymized with the subtribe Monaloniina and the subtribes Dicyphina, Monaloniina and Eccritotarsina are now elevated to tribal level, with the Dicyphini now restricted in composition and definition. The genus Felisacus is highly autapomorphic and a new tribe -the Felisacini -is erected for the included taxa. This phylogeny of the tribes of the Bryocorinae comprises the following sister-group relationships: Dicyphini ((Bryocorini + Eccritotarsini)(Felisicini + Monaloniini)).

The phylogenetic relationships among major lineages of the planthopper family Issidae were explored by analyzing a molecular dataset of nine fragments (COI, CytB, 12S, H3, 16S, 18SII, 18SIII, 28S D3–D5, 28S D6–D7) and 48 terminal taxa. Bayesian and Maximum likelihood analyses yielded similar and mostly well-resolved trees with moderate to high support for most branches. The obtained results suggest subdivision of the family Issidae Spinola into two subfamilies, Issinae Spinola, 1839 (= Thioniinae Melichar, 1906, = Hemisphaeriinae Melichar, 1906) and Hysteropterinae Melichar, 1906. The Issinae was clustered into the tribes Issini Spinola, 1839, with the subtribes Issina Spinola, 1839 and Thioniina Melichar, 1906, Sarimini Wang, Zhang et Bourgoin, 2016, Parahiraciini Cheng et Yang, 1991, Hemisphaeriini Melichar, 1906, and Kodaianellini Wang, Zhang et Bourgoin, 2016. The Hysteropterinae incorporates the rest of Western Palaearctic taxa except Issina. Chimetopini Gnezdilov, 2017, stat. nov. is elevated to tribe from the subtribal level. Most well-supported clades showed clear geographical pattering. Newly obtained data contradicts the scenario of an early split of American Thioniinae from other Issidae and possible origin of the family in the New World, while the combination of Palaearctic Issus Fabricius and Latissus Dlabola with Oriental and American taxa in one well supported clade may serve as an evidence for a common ancestor for extant Oriental, American, and Palaearctic issids.

The higher classification of the mirid subfamily Bryocorinae has received comparatively little attention. It is not highly species-rich in comparison with other mirid subfamilies but does exhibit extraordinary morphological heterogeneity. In this work we provide a synthesis of the subfamily on a global basis, providing a new key and updated diagnoses of supraspecific taxa. Five tribes are recognised: Bryocorini, Dicyphini, Eccritotarsini, Felisacini and Monaloniini. The genus Campyloneura Fieber is transferred from the tribe Dicyphini to the Eccritotarsini. Analysis of distributional patterns and a survey of host plant associations are provided. Available data on distribution of the main bryocorine lineages are summarised in tabular form and evaluated using UPGMA methods, and geographically structured patterns were detected. The synthesis will enable users to identify bryocorines to tribal level with confidence and provides a classificatory framework for future revisionary and phylogenetic studies.

The Palaearctic genus Orthocephalus Fieber, 1858 is revised. The generic names Anapomella Putshkov, 1961 and Oraniella Reuter, 1894 are synonymized with Orthocephalus Fieber, 1858; providing for three comb. nov. — O. arnoldii (Putshkov, 1961), O. tibialis (Reuter, 1894), and O. tristis (Reuter, 1894). The following new species-level synonymies are established: O. niger Reuter, 1879 = O. bivittatus Fieber, 1864, O. parvulus Reuter, 1891 = O. saltator (Hahn, 1835), and O. beresovskii Reuter, 1906 with all its varieties = O. funestus Jakovlev, 1881. Piezocanum medvedevi Putshkov, 1961 is transferred to Orthocephalus and the replacement name O. putshkovi nom. nov. is proposed to remove the homonymy with O. medvedevi Kiritshenko, 1951. Keys to males and females, and data on distribution and host plants are given for all 23 species of the genus, including Orthocephalus turkmenicus sp. n. (Azerbaijan, Iran, and Turkmenistan). Color digital habitus images and genitalic illustrations are provided of female specimens for all species and males for most of the species. Scanning electron micrographs are used to illustrate characteristic features for Orthocephalus and related groups. A phylogenetic analysis, including 33 taxa and 35 characters, is presented. The main results of this study are support for a sister-group relationship between Orthocephalus and Pachytomella, the monophyly of Orthocephalus as here diagnosed, and the relatively apical position of the clade containing Anapomella arnoldii and Oraniella tibialis within Orthocephalus.

A cladistic analysis of the tribe Bryocorini based on 68 morphological characters is conducted. Bryocorini are supported as a monophyletic group with Eccritotarsini as their sister taxon. Based on the phylogenetic analysis, we redefine the tribe Bryocorini to contain the following seven genera: Bryocorella Carvalho, 1956, Bryocoris Fallén, 1829, Bryophilocapsus Yasunaga, 2000, Cobalorrhynchus Reuter, 1906 gen. dist., Diplazicoris gen. nov., Hekista Kirkaldy, 1902, and Monalocoris Dahlbom, 1851. The genus Bryocorella is transferred to Bryocorini from the tribe Eccritotarsini. The subgenus Cobalorrhynchus is treated as a separate genus. Diplazicoris is described as monotypic to accommodate Diplazicoris lombokianus sp. nov. An updated diagnosis of the tribe, a key to genera, and a diagnosis of each recognized genus are presented. Selected photomicrographs, scanning micrographs, and illustrations of the pretarsus, metepisternal scent efferent system, metafemoral trichobothria, and morphology of head, pronotum, and male and female genitalia are provided. Mapping of the host data on the revealed tree shows that Bryocorini represent one of the very few currently known examples of the adaptive radiation of a fairly large insect group on ferns.

A revised diagnosis and description of the genus Ethelastia Reuter is given. Descriptions, illustrations of selected characters, data on distribution and host plants are provided for species of Ethelastia, including E. lonicerae sp.n. (Kazakhstan).

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Deep learning algorithms and particularly convolutional neural networks are very successful in pattern recognition from images and are increasingly employed in biology. The development of automated systems for rapid and reliable species identification is vital for insect systematics and may revolutionize this field soon. In this study, we demonstrate the ability of a convolutional neural network to identify species based on habitus photographs with expert‐level accuracy in a taxonomically challenging group where a human‐based identification would require notorious genitalia dissections. Using the economically important and polymorphic plant bug genus Adelphocoris Reuter (Heteroptera: Miridae) as a model group, we explore the variability in the performance of 11 convolutional neural models most commonly used for image classification, test the role of class‐imbalance on the model performance assessment and visualize areas of interest using three interpretation algorithms. Classification performance in our experiments with collection‐based habitus photographs is high enough to identify very similar species from a large group with an expert‐level accuracy. The accuracy is getting lower only in the experiments with an additional dataset of Adelphocoris and other live plant bugs photographs taken from the Web. Our article demonstrates the importance of comprehensive institutional insect collections for bringing deep learning algorithms into service for systematic entomology using affordable equipment and methods.