Ultra-Conserved Elements and morphology reciprocally illuminate conflicting phylogenetic hypotheses in Chalcididae (Hymenoptera, Chalcidoidea).

Recent technical advances combined with novel computational approaches have promised the acceleration of our understanding of the tree of life. However, when it comes to hyperdiverse and poorly known groups of invertebrates, studies are still scarce. As published phylogenies will be rarely challenged by future taxonomists, careful attention must be paid to potential analytical bias. We present the first molecular phylogenetic hypothesis for the family Chalcididae, a group of parasitoid wasps, with a representative sampling (144 ingroups and seven outgroups) that covers all described subfamilies and tribes, and 82% of the known genera. Analyses of 538 Ultra-Conserved Elements (UCEs) with supermatrix (RAxML and IQTREE) and gene tree reconciliation approaches (ASTRAL, ASTRID) resulted in highly supported topologies in overall agreement with morphology but reveal conflicting topologies for some of the deepest nodes. To resolve these conflicts, we explored the phylogenetic tree space with clustering and gene genealogy interrogation methods, analyzed marker and taxon properties that could bias inferences and performed a thorough morphological analysis (130 characters encoded for 40 taxa representative of the diversity). This joint analysis reveals that UCEs enable attainment of resolution between ancestry and convergent/divergent evolution when morphology is not informative enough, but also shows that a systematic exploration of bias with different analytical methods and a careful analysis of morphological features is required to prevent publication of artifactual results. We highlight a GC content bias for maximum-likelihood approaches, an artifactual mid-point rooting of the ASTRAL tree and a deleterious effect of high percentage of missing data (>85% missing UCEs) on gene tree reconciliation methods. Based on the results we propose a new classification of the family into eight subfamilies and ten tribes that lay the foundation for future studies on the evolutionary history of Chalcididae.

coil: an R package for cytochrome c oxidase I (COI) DNA barcode data cleaning, translation, and error evaluation.

Biological conclusions based on DNA barcoding and metabarcoding analyses can be strongly influenced by the methods utilized for data generation and curation, leading to varying levels of success in the separation of biological variation from experimental error. The 5' region of cytochrome c oxidase subunit I (COI-5P) is the most common barcode gene for animals, with conserved structure and function that allows for biologically informed error identification. Here, we present coil ( https://CRAN.R-project.org/package=coil ), an R package for the pre-processing and frameshift error assessment of COI-5P animal barcode and metabarcode sequence data. The package contains functions for placement of barcodes into a common reading frame, accurate translation of sequences to amino acids, and highlighting insertion and deletion errors. The analysis of 10 000 barcode sequences of varying quality demonstrated how coil can place barcode sequences in reading frame and distinguish sequences containing indel errors from error-free sequences with greater than 97.5% accuracy. Package limitations were tested through the analysis of COI-5P sequences from the plant and fungal kingdoms as well as the analysis of potential contaminants: nuclear mitochondrial pseudogenes and Wolbachia COI-5P sequences. Results demonstrated that coil is a strong technical error identification method but is not reliable for detecting all biological contaminants.

Using DNA-barcoded Malaise trap samples to measure impact of a geothermal energy project on the biodiversity of a Costa Rican old-growth rain forest.

We report one year (2013-2014) of biomonitoring an insect community in a tropical old-growth rain forest, during construction of an industrial-level geothermal electricity project. This is the first-year reaction by the species-rich insect biodiversity; six subsequent years are being analyzed now. The site is on the margin of a UNESCO Natural World Heritage Site, Área de Conservación Guanacaste (ACG), in northwestern Costa Rica. This biomonitoring is part of Costa Rica's ongoing efforts to sustainably retain its wild biodiversity through biodevelopmental integration with its societies. Essential tools are geothermal engineering needs, entomological knowledge, insect species-rich forest, government-NGO integration, common sense, DNA barcoding for species-level identification, and Malaise traps. This research is tailored for integration with its society at the product level. We combine an academic view with on-site engineering decisions. This biomonitoring requires alpha-level DNA barcoding combined with centuries of morphology-based entomological taxonomy and ecology. Not all desired insect community analyses are performed; they are for data from subsequent years combined with this year. We provide enough analysis to be used by both guilds now. This biomonitoring has shown, for the first year, that the geothermal project impacts only the biodiversity within a zone less than 50 m from the project margin.

Expedited assessment of terrestrial arthropod diversity by coupling Malaise traps with DNA barcoding 1.

Monitoring changes in terrestrial arthropod communities over space and time requires a dramatic increase in the speed and accuracy of processing samples that cannot be achieved with morphological approaches. The combination of DNA barcoding and Malaise traps allows expedited, comprehensive inventories of species abundance whose cost will rapidly decline as high-throughput sequencing technologies advance. Aside from detailing protocols from specimen sorting to data release, this paper describes their use in a survey of arthropod diversity in a national park that examined 21 194 specimens representing 2255 species. These protocols can support arthropod monitoring programs at regional, national, and continental scales.

A Sequel to Sanger: amplicon sequencing that scales.

BACKGROUND: Although high-throughput sequencers (HTS) have largely displaced their Sanger counterparts, the short read lengths and high error rates of most platforms constrain their utility for amplicon sequencing. The present study tests the capacity of single molecule, real-time (SMRT) sequencing implemented on the SEQUEL platform to overcome these limitations, employing 658 bp amplicons of the mitochondrial cytochrome c oxidase I gene as a model system. RESULTS: By examining templates from more than 5000 species and 20,000 specimens, the performance of SMRT sequencing was tested with amplicons showing wide variation in GC composition and varied sequence attributes. SMRT and Sanger sequences were very similar, but SMRT sequencing provided more complete coverage, especially for amplicons with homopolymer tracts. Because it can characterize amplicon pools from 10,000 DNA extracts in a single run, the SEQUEL can reduce greatly reduce sequencing costs in comparison to first (Sanger) and second generation platforms (Illumina, Ion). CONCLUSIONS: SMRT analysis generates high-fidelity sequences from amplicons with varying GC content and is resilient to homopolymer tracts. Analytical costs are low, substantially less than those for first or second generation sequencers. When implemented on the SEQUEL platform, SMRT analysis enables massive amplicon characterization because each instrument can recover sequences from more than 5 million DNA extracts a year.

Species-Level Para- and Polyphyly in DNA Barcode Gene Trees: Strong Operational Bias in European Lepidoptera.

The proliferation of DNA data is revolutionizing all fields of systematic research. DNA barcode sequences, now available for millions of specimens and several hundred thousand species, are increasingly used in algorithmic species delimitations. This is complicated by occasional incongruences between species and gene genealogies, as indicated by situations where conspecific individuals do not form a monophyletic cluster in a gene tree. In two previous reviews, non-monophyly has been reported as being common in mitochondrial DNA gene trees. We developed a novel web service "Monophylizer" to detect non-monophyly in phylogenetic trees and used it to ascertain the incidence of species non-monophyly in COI (a.k.a. cox1) barcode sequence data from 4977 species and 41,583 specimens of European Lepidoptera, the largest data set of DNA barcodes analyzed from this regard. Particular attention was paid to accurate species identification to ensure data integrity. We investigated the effects of tree-building method, sampling effort, and other methodological issues, all of which can influence estimates of non-monophyly. We found a 12% incidence of non-monophyly, a value significantly lower than that observed in previous studies. Neighbor joining (NJ) and maximum likelihood (ML) methods yielded almost equal numbers of non-monophyletic species, but 24.1% of these cases of non-monophyly were only found by one of these methods. Non-monophyletic species tend to show either low genetic distances to their nearest neighbors or exceptionally high levels of intraspecific variability. Cases of polyphyly in COI trees arising as a result of deep intraspecific divergence are negligible, as the detected cases reflected misidentifications or methodological errors. Taking into consideration variation in sampling effort, we estimate that the true incidence of non-monophyly is ∼23%, but with operational factors still being included. Within the operational factors, we separately assessed the frequency of taxonomic limitations (presence of overlooked cryptic and oversplit species) and identification uncertainties. We observed that operational factors are potentially present in more than half (58.6%) of the detected cases of non-monophyly. Furthermore, we observed that in about 20% of non-monophyletic species and entangled species, the lineages involved are either allopatric or parapatric-conditions where species delimitation is inherently subjective and particularly dependent on the species concept that has been adopted. These observations suggest that species-level non-monophyly in COI gene trees is less common than previously supposed, with many cases reflecting misidentifications, the subjectivity of species delimitation or other operational factors.

International Barcode of Life: Focus on big biodiversity in South Africa.

Participants in the 7th International Barcode of Life Conference (Kruger National Park, South Africa, 20-24 November 2017) share the latest findings in DNA barcoding research and its increasingly diversified applications. Here, we review prevailing trends synthesized from among 429 invited and contributed abstracts, which are collated in this open-access special issue of Genome. Hosted for the first time on the African continent, the 7th Conference places special emphasis on the evolutionary origins, biogeography, and conservation of African flora and fauna. Within Africa and elsewhere, DNA barcoding and related techniques are being increasingly used for wildlife forensics and for the validation of commercial products, such as medicinal plants and seafood species. A striking trend of the conference is the dramatic rise of studies on environmental DNA (eDNA) and on diverse uses of high-throughput sequencing techniques. Emerging techniques in these areas are opening new avenues for environmental biomonitoring, managing species-at-risk and invasive species, and revealing species interaction networks in unprecedented detail. Contributors call for the development of validated community standards for high-throughput sequence data generation and analysis, to enable the full potential of these methods to be realized for understanding and managing biodiversity on a global scale.

PROTAX-GPU: a scalable probabilistic taxonomic classification system for DNA barcodes.

DNA-based identification is vital for classifying biological specimens, yet methods to quantify the uncertainty of sequence-based taxonomic assignments are scarce. Challenges arise from noisy reference databases, including mislabelled entries and missing taxa. PROTAX addresses these issues with a probabilistic approach to taxonomic classification, advancing on methods that rely solely on sequence similarity. It provides calibrated probabilistic assignments to a partially populated taxonomic hierarchy, accounting for taxa that lack references and incorrect taxonomic annotation. While effective on smaller scales, global application of PROTAX necessitates substantially larger reference libraries, a goal previously hindered by computational barriers. We introduce PROTAX-GPU, a scalable algorithm capable of leveraging the global Barcode of Life Data System (>14 million specimens) as a reference database. Using graphics processing units (GPU) to accelerate similarity and nearest-neighbour operations and the JAX library for Python integration, we achieve over a 1000 × speedup compared with the central processing unit (CPU)-based implementation without compromising PROTAX's key benefits. PROTAX-GPU marks a significant stride towards real-time DNA barcoding, enabling quicker and more efficient species identification in environmental assessments. This capability opens up new avenues for real-time monitoring and analysis of biodiversity, advancing our ability to understand and respond to ecological dynamics. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

BOLD v4: A Centralized Bioinformatics Platform for DNA-Based Biodiversity Data.

BOLD, the Barcode of Life Data System, supports the acquisition, storage, validation, analysis, and publication of DNA barcodes, activities requiring the integration of molecular, morphological, and distributional data. Its pivotal role in curating the reference library of DNA barcodes, coupled with its data management and analysis capabilities, makes it a central resource for biodiversity science. It enables rapid, accurate identification of specimens and also reveals patterns of genetic diversity and evolutionary relationships among taxa.Launched in 2005, BOLD has become an increasingly powerful tool for advancing the understanding of planetary biodiversity. It currently hosts 17 million specimen records and 14 million barcodes that provide coverage for more than a million species from every continent and ocean. The platform has the long-term goal of providing a consistent, accurate system for identifying all species of eukaryotes.BOLD's integrated analytical tools, full data lifecycle support, and secure collaboration framework distinguish it from other biodiversity platforms. BOLD v4 brought enhanced data management and analysis capabilities as well as novel functionality for data dissemination and publication. Its next version will include features to strengthen its utility to the research community, governments, industry, and society-at-large.

Global arthropod beta-diversity is spatially and temporally structured by latitude.

Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

DNA barcodes reveal striking arthropod diversity and unveil seasonal patterns of variation in the southern Atlantic Forest.

The Atlantic Forest harbors 7% of global biodiversity and possesses high levels of endemism, but many of its component taxa remain unstudied. Due to the importance of tropical forests and the urgency to protect them, there is a compelling need to address this knowledge gap. To provide more information on its arthropod fauna, a Malaise trap was deployed for 12 months in a semi-degraded area of the southern Upper Paraná ecoregion of the Atlantic Forest. All specimens were DNA barcoded and the Barcode Index Number (BIN) system was employed to assign each specimen to a species proxy. DNA barcodes were obtained from 75,500 arthropods that included representatives of 8,651 BINs. Nearly 81% of these BINs were first records, highlighting the high rates of endemism and lack of study of arthropods from the Atlantic Forest. Diptera was the most abundant order, followed by Hemiptera, Lepidoptera and Hymenoptera. Diptera was also the most species-rich order, followed by Hymenoptera, Lepidoptera, and Coleoptera, a result consistent with studies in other biogeographic regions. Insects were most abundant in winter and most diverse in autumn and winter. This pattern, however, was caused mainly by the dynamics of dipteran diversity as other orders differed in their seasonal variation. The BIN composition of the insect community varied sharply through the year and also differed between the two consecutive summers included in the sampling period. The study of the 38 commonest BINs showed that seasonal patterns of abundance were not order-specific. Temperature had the strongest impact on seasonal abundance variation. Our results highlight the striking and understudied arthropod diversity of the highly fragmented Atlantic Forest, the predominance of dipterans, and the fact that abundance and richness in this insect community peak in the coolest months. Standardized studies like this generate fast and reliable biodiversity inventories and unveil ecological patterns, thus providing valuable information for conservation programs.

More discussion of minimalist species descriptions and clarifying some misconceptions contained in Meier et al. 2021.

This is a response to a preprint version of "A re-analysis of the data in Sharkey et al.'s (2021) minimalist revision reveals that BINs do not deserve names, but BOLD Systems needs a stronger commitment to open science", https://www.biorxiv.org/content/10.1101/2021.04.28.441626v2. Meier et al. strongly criticized Sharkey et al.'s publication in which 403 new species were deliberately minimally described, based primarily on COI barcode sequence data. Here we respond to these criticisms. The following points are made: 1) Sharkey et al. did not equate BINs with species, as demonstrated in several examples in which multiple species were found to be in single BINs. 2) We reiterate that BINs were used as a preliminary sorting tool, just as preliminary morphological identification commonly sorts specimens based on color and size into unit trays; despite BINs and species concepts matching well over 90% of species, this matching does not equate to equality. 3) Consensus barcodes were used only to provide a diagnosis to conform to the rules of the International Code of Zoological Nomenclature just as consensus morphological diagnoses are. The barcode of a holotype is definitive and simply part of its cellular morphology. 4) Minimalist revisions will facilitate and accelerate future taxonomic research, not hinder it. 5) We refute the claim that the BOLD sequences of Plesiocoelusvanachterbergi are pseudogenes and demonstrate that they simply represent a frameshift mutation. 6) We reassert our observation that morphological evidence alone is insufficient to recognize species within species-rich higher taxa and that its usefulness lies in character states that are congruent with molecular data. 7) We show that in the cases in which COI barcodes code for the same amino acids in different putative species, data from morphology, host specificity, and other ecological traits reaffirm their utility as indicators of genetically distinct lineages.

Molecular analysis of parasitoid linkages (MAPL): gut contents of adult parasitoid wasps reveal larval host.

Metamorphosing insects often have complex and poorly known life histories. In particular, what they feed on during their larval stages remains unknown for the vast majority of species, and its documentation only results from difficult and time-intensive field observations, rearing or dissections. Through the application of a DNA analysis of gut contents in adult parasitoid wasps, we were able to selectively sequence a diagnostic DNA marker that permitted the identification of the host used by these wasps during their larval stages. By reproducing these results in species with different life histories, we excluded other potential sources of host DNA, confirming that after ingestion by the parasitoid larva the host DNA can persist through metamorphosis in the abdominal contents of the adult wasp. Our discovery considerably extends the applicability of molecular analysis of gut contents by enabling the documentation of food used by insects during their larval stages and thus increasing the accuracy and precision of food web studies. The 24% success rate of our approach is surprisingly high considering the challenging context for host DNA preservation, and we discuss the factors possibly affecting this rate. We propose molecular analysis of parasitoid linkages (MAPL) as a new method to document host-parasitoid associations at a faster pace and with unrivalled precision. Because of the key regulatory role of parasitoid wasps in ecosystems, which makes them the most commonly used biological control agents, MAPL will have immediate applications in both basic and applied biological sciences.

Debar: A sequence-by-sequence denoiser for COI-5P DNA barcode data.

DNA barcoding and metabarcoding are now widely used to advance species discovery and biodiversity assessments. High-throughput sequencing (HTS) has expanded the volume and scope of these analyses, but elevated error rates introduce noise into sequence records that can inflate estimates of biodiversity. Denoising -the separation of biological signal from instrument (technical) noise-of barcode and metabarcode data currently employs abundance-based methods which do not capitalize on the highly conserved structure of the cytochrome c oxidase subunit I (COI) region employed as the animal barcode. This manuscript introduces debar, an R package that utilizes a profile hidden Markov model to denoise indel errors in COI sequences introduced by instrument error. In silico studies demonstrated that debar recognized 95% of artificially introduced indels in COI sequences. When applied to real-world data, debar reduced indel errors in circular consensus sequences obtained with the Sequel platform by 75%, and those generated on the Ion Torrent S5 by 94%. The false correction rate was less than 0.1%, indicating that debar is receptive to the majority of true COI variation in the animal kingdom. In conclusion, the debar package improves DNA barcode and metabarcode workflows by aiding the generation of more accurate sequences aiding the characterization of species diversity.

Torix Rickettsia are widespread in arthropods and reflect a neglected symbiosis.

BACKGROUND: Rickettsia are intracellular bacteria best known as the causative agents of human and animal diseases. Although these medically important Rickettsia are often transmitted via haematophagous arthropods, other Rickettsia, such as those in the Torix group, appear to reside exclusively in invertebrates and protists with no secondary vertebrate host. Importantly, little is known about the diversity or host range of Torix group Rickettsia. RESULTS: This study describes the serendipitous discovery of Rickettsia amplicons in the Barcode of Life Data System (BOLD), a sequence database specifically designed for the curation of mitochondrial DNA barcodes. Of 184,585 barcode sequences analysed, Rickettsia is observed in ∼0.41% of barcode submissions and is more likely to be found than Wolbachia (0.17%). The Torix group of Rickettsia are shown to account for 95% of all unintended amplifications from the genus. A further targeted PCR screen of 1,612 individuals from 169 terrestrial and aquatic invertebrate species identified mostly Torix strains and supports the "aquatic hot spot" hypothesis for Torix infection. Furthermore, the analysis of 1,341 SRA deposits indicates that Torix infections represent a significant proportion of all Rickettsia symbioses found in arthropod genome projects. CONCLUSIONS: This study supports a previous hypothesis that suggests that Torix Rickettsia are overrepresented in aquatic insects. In addition, multiple methods reveal further putative hot spots of Torix Rickettsia infection, including in phloem-feeding bugs, parasitoid wasps, spiders, and vectors of disease. The unknown host effects and transmission strategies of these endosymbionts make these newly discovered associations important to inform future directions of investigation involving the understudied Torix Rickettsia.

?Addendum to a minimalist revision of Costa Rican Braconidae: 28 new species and 23 host records.

Twenty-nine species are treated, most of which have host caterpillar and food plant records, and all but one are new to science. The first host record for the agathidine genus Amputoearinus is given. Gnathopleurajosequesadai Sharkey, sp. nov. is reported as a hyperparasitoid of fly larvae, the first such record for the genus. The following new species are diagnosed primarily using COI barcode data; Sharkey is the authority for all: Agathidinae: Aerophilusdavidwagneri, Aerophilusfundacionbandorum, Aerophilusnicklaphami, Lytopylusdavidstopaki, Lytopylusdavidschindeli; Alysiinae: Gnathopleurajosequesadai; Braconinae: Braconandreamezae, Braconfranklinpaniaguai, Braconrafagutierrezi, Braconguillermoblancoi, Braconoscarmasisi, Braconpauldimaurai, Braconshebadimaurae, Saciremakarendimaurae; Cheloninae: Chelonusminorzunigai; Homolobinae: Homolobusstevestroudi; Macrocentrinae: Macrocentrusmichaelstroudi; Orgilinae: Stantoniagilbertfuentesi; Rhysipolinae: Rhysipolisstevearonsoni; Rogadinae: Aleiodeskaydodgeae, Aleiodeskerrydresslerae, Aleiodesjosesolanoi, Aleiodesjuniorporrasi, Aleiodesrocioecheverri, Aleiodesronaldzunigai, Choreborogasjesseausubeli, Triraphisdoncombi, and Yeliconesmayrabonillae.

A DNA barcode library for the butterflies of North America.

Although the butterflies of North America have received considerable taxonomic attention, overlooked species and instances of hybridization continue to be revealed. The present study assembles a DNA barcode reference library for this fauna to identify groups whose patterns of sequence variation suggest the need for further taxonomic study. Based on 14,626 records from 814 species, DNA barcodes were obtained for 96% of the fauna. The maximum intraspecific distance averaged 1/4 the minimum distance to the nearest neighbor, producing a barcode gap in 76% of the species. Most species (80%) were monophyletic, the others were para- or polyphyletic. Although 15% of currently recognized species shared barcodes, the incidence of such taxa was far higher in regions exposed to Pleistocene glaciations than in those that were ice-free. Nearly 10% of species displayed high intraspecific variation (>2.5%), suggesting the need for further investigation to assess potential cryptic diversity. Aside from aiding the identification of all life stages of North American butterflies, the reference library has provided new perspectives on the incidence of both cryptic and potentially over-split species, setting the stage for future studies that can further explore the evolutionary dynamics of this group.

Minimalist revision and description of 403 new species in 11 subfamilies of Costa Rican braconid parasitoid wasps, including host records for 219 species.

Three new genera are described: Michener (Proteropinae), Bioalfa (Rogadinae), and Hermosomastax (Rogadinae). Keys are given for the New World genera of the following braconid subfamilies: Agathidinae, Braconinae, Cheloninae, Homolobinae, Hormiinae, Ichneutinae, Macrocentrinae, Orgilinae, Proteropinae, Rhysipolinae, and Rogadinae. In these subfamilies 416 species are described or redescribed. Most of the species have been reared and all but 13 are new to science. A consensus sequence of the COI barcodes possessed by each species is employed to diagnose the species, and this approach is justified in the introduction. Most descriptions consist of a lateral or dorsal image of the holotype, a diagnostic COI consensus barcode, the Barcode Index Number (BIN) code with a link to the Barcode of Life Database (BOLD), and the holotype specimen information required by the International Code of Zoological Nomenclature. The following species are treated and those lacking authorship are newly described here with authorship attributable to Sharkey except for the new species of Macrocentrinae which are by Sharkey & van Achterberg: AGATHIDINAE: Aerophiluspaulmarshi, Mesocoelusdavidsmithi, Neothlipsisbobkulai, Plesiocoelusvanachterbergi, Pneumagathiserythrogastra (Cameron, 1905), Therophilusbobwhartoni, T.donaldquickei, T.gracewoodae, T.maetoi, T.montywoodi, T.penteadodiasae, Zacremnopsbrianbrowni, Z.coatlicue Sharkey, 1990, Zacremnopscressoni (Cameron, 1887), Z.ekchuah Sharkey, 1990, Z.josefernandezi, Zelomorphasarahmeierottoae. BRACONINAE: Braconalejandromarini, B.alejandromasisi, B.alexamasisae, B.andresmarini, B.andrewwalshi, B.anniapicadoae, B.anniemoriceae, B.barryhammeli, B.bernardoespinozai, B.carlossanabriai, B.chanchini, B.christophervallei, B.erasmocoronadoi, B.eugeniephillipsae, B.federicomatarritai, B.frankjoycei, B.gerardovegai, B.germanvegai, B.isidrochaconi, B.jimlewisi, B.josejaramilloi, B.juanjoseoviedoi, B.juliodiazi, B.luzmariaromeroae, B.manuelzumbadoi, B.marialuisariasae, B.mariamartachavarriae, B.mariorivasi, B.melissaespinozae, B.nelsonzamorai, B.nicklaphami, B.ninamasisae, B.oliverwalshi, B.paulamarinae, B.rafamoralesi, B.robertofernandezi, B.rogerblancoi, B.ronaldzunigai, B.sigifredomarini, B.tihisiaboshartae, B.wilberthbrizuelai, Digonogastramontylloydi, D.montywoodi, D.motohasegawai, D.natwheelwrighti, D.nickgrishini. CHELONINAE: Adeliusadrianguadamuzi, A.gauldi Shimbori & Shaw, 2019, A.janzeni Shimbori & Shaw, 2019, Ascogastergloriasihezarae, A.grettelvegae, A.guillermopereirai, A.gustavoecheverrii, A.katyvandusenae, A.luisdiegogomezi, Chelonusalejandrozaldivari, C.gustavogutierrezi, C.gustavoinduni, C.harryramirezi, C.hartmanguidoi, C.hazelcambroneroae, C.iangauldi, C.isidrochaconi, C.janecheverriae, C.jeffmilleri, C.jennyphillipsae, C.jeremydewaardi, C.jessiehillae, C.jesusugaldei, C.jimlewisi, C.jimmilleri, C.jimwhitfieldi, C.johanvalerioi, C.johnburnsi, C.johnnoyesi, C.jorgebaltodanoi, C.jorgehernandezi, C.josealfredohernandezi, C.josefernandeztrianai, C.josehernandezcortesi, C.josemanuelperezi, C.josephinerodriguezae, C.juanmatai, C.junkoshimurae, C.kateperezae, C.luciariosae, C.luzmariaromeroae, C.manuelpereirai, C.manuelzumbadoi, C.marianopereirai, C.maribellealvarezae, C.markmetzi, C.markshawi, C.martajimenezae, C.mayrabonillae, C.meganmiltonae, C.melaniamunozae, C.michaelstroudi, C.michellevanderbankae, C.mingfangi, C.minorcarmonai, C.monikaspringerae, C.moniquegilbertae, C.motohasegawai, C.nataliaivanovae, C.nelsonzamorai, C.normwoodleyi, C.osvaldoespinozai, C.pamelacastilloae, C.paulgoldsteini, C.paulhansoni, C.paulheberti, C.petronariosae, C.ramyamanjunathae, C.randallgarciai, C.rebeccakittelae, C.robertoespinozai, C.robertofernandezi, C.rocioecheverriae, C.rodrigogamezi, C.ronaldzunigai, C.rosibelelizondoae, C.rostermoragai, C.ruthfrancoae, C.scottmilleri, C.scottshawi, C.sergioriosi, C.sigifredomarini, C.stevearonsoni, C.stevestroudi, C.sujeevanratnasinghami, C.sureshnaiki, C.torbjornekremi, C.yeimycedenoae, Leptodrepanaalexisae, L.erasmocoronadoi, L.felipechavarriai, L.freddyquesadai, L.gilbertfuentesi, L.manuelriosi, Phanerotomaalmasolisae, P.alvaroherrerai, P.anacordobae, P.anamariamongeae, P.andydeansi, P.angelagonzalezae, P.angelsolisi, P.barryhammeli, P.bernardoespinozai, P.calixtomoragai, P.carolinacanoae, P.christerhanssoni, P.christhompsoni, P.davesmithi, P.davidduthiei, P.dirksteinkei, P.donquickei, P.duniagarciae, P.duvalierbricenoi, P.eddysanchezi, P.eldarayae, P.eliethcantillanoae, P.jenopappi, Pseudophanerotomaalanflemingi, Ps.albanjimenezi, Ps.alejandromarini, Ps.alexsmithi, Ps.allisonbrownae, Ps.bobrobbinsi. HOMOLOBINAE: Exasticolusjennyphillipsae, E.randallgarciai, E.robertofernandezi, E.sigifredomarini, E.tomlewinsoni. HORMIINAE: Hormiusanamariamongeae, H.angelsolisi, H.anniapicadoae, H.arthurchapmani, H.barryhammeli, H.carmenretanae, H.carloswalkeri, H.cesarsuarezi, H.danbrooksi, H.eddysanchezi, H.erikframstadi, H.georgedavisi, H.grettelvegae, H.gustavoinduni, H.hartmanguidoi, H.hectoraritai, H.hesiquiobenitezi, H.irenecanasae, H.isidrochaconi, H.jaygallegosi, H.jimbeachi, H.jimlewisi, H.joelcracrafti, H.johanvalerioi, H.johnburleyi, H.joncoddingtoni, H.jorgecarvajali, H.juanmatai, H.manuelzumbadoi, H.mercedesfosterae, H.modonnellyae, H.nelsonzamorai, H.pamelacastilloae, H.raycypessi, H.ritacolwellae, H.robcolwelli, H.rogerblancosegurai, H.ronaldzunigai, H.russchapmani, H.virginiaferrisae, H.warrenbrighami, H.willsflowersi. ICHNEUTINAE: Oligoneuruskriskrishtalkai, O.jorgejimenezi, Paroligoneuruselainehoaglandae, P.julianhumphriesi, P.mikeiviei. MACROCENTRINAE: Austrozelejorgecampabadali, A.jorgesoberoni, Dolichozelegravitarsis (Muesebeck, 1938), D.josefernandeztrianai, D.josephinerodriguezae, Hymenochaoniakalevikulli, H.kateperezae, H.katherinebaillieae, H.katherineellisonae, H.katyvandusenae, H.kazumifukunagae, H.keithlangdoni, H.keithwillmotti, H.kenjinishidai, H.kimberleysheldonae, H.krisnorvigae, H.lilianamadrigalae, H.lizlangleyae, Macrocentrusfredsingeri, M.geoffbarnardi, M.gregburtoni, M.gretchendailyae, M.grettelvegae, M.gustavogutierrezi, M.hannahjamesae, M.harisridhari, M.hillaryrosnerae, M.hiroshikidonoi, M.iangauldi, M.jennyphillipsae, M.jesseausubeli, M.jessemaysharkae, M.jimwhitfieldi, M.johnbrowni, M.johnburnsi, M.jonathanfranzeni, M.jonathanrosenbergi, M.jorgebaltodanoi, M.lucianocapelli. ORGILINAE: Orgilusamyrossmanae, O.carrolyoonae, O.christhompsoni, O.christinemcmahonae, O.dianalipscombae, O.ebbenielsoni, O.elizabethpennisiae, O.evertlindquisti, O.genestoermeri, O.jamesriegeri, O.jeanmillerae, O.jeffmilleri, O.jerrypowelli, O.jimtiedjei, O.johnlundbergi, O.johnpipolyi, O.jorgellorentei, O.larryspearsi, O.marlinricei, O.mellissaespinozae, O.mikesmithi, O.normplatnicki, O.peterrauchi, O.richardprimacki, O.sandraberriosae, O.sarahmirandae, O.scottmilleri, O.scottmorii, Stantoniabillalleni, S.brookejarvisae, S.donwilsoni, S.erikabjorstromae, S.garywolfi, S.henrikekmani, S.luismirandai, S.miriamzunzae, S.quentinwheeleri, S.robinkazmierae, S.ruthtifferae. PROTEROPINAE: Hebichneutestricolor Sharkey & Wharton, 1994, Proteropsiangauldi, P.vickifunkae, Michenercharlesi. RHYSIPOLINAE: Pseudorhysipolisluisfonsecai, P. mailyngonzalezaeRhysipolisjulioquirosi. ROGADINAE: Aleiodesadrianaradulovae, A.adrianforsythi, A.agnespeelleae, A.alaneaglei, A.alanflemingi, A.alanhalevii, A.alejandromasisi, A.alessandracallejae, A.alexsmithi, A.alfonsopescadori, A.alisundermieri, A.almasolisae, A.alvarougaldei, A.alvaroumanai, A.angelsolisi, A.annhowdenae, A.bobandersoni, A.carolinagodoyae, A.charlieobrieni, A.davefurthi, A.donwhiteheadi, A.doylemckeyi, A.frankhovorei, A.henryhowdeni, A.inga Shimbori & Shaw, 2020, A.johnchemsaki, A.johnkingsolveri, A.gonodontovorus Shimbori & Shaw, 2020, A.manuelzumbadoi, A.mayrabonillae, A.michelledsouzae, A.mikeiviei, A.normwoodleyi, A.pammitchellae, A.pauljohnsoni, A.rosewarnerae, A.steveashei, A.terryerwini, A.willsflowersi, Bioalfapedroleoni, B.alvarougaldei, B.rodrigogamezi, Choreborogasandydeansi, C.eladiocastroi, C.felipechavarriai, C.frankjoycei, Clinocentrusandywarreni, Cl.angelsolisi, Cystomastaxalexhausmanni, Cy.angelagonzalezae, Cy.ayaigarashiae, Hermosomastaxclavifemorus Quicke sp. nov., Heterogamusdonstonei, Pseudoyeliconesbernsweeneyi, Stiropiusbencrairi, S.berndkerni, S.edgargutierrezi, S.edwilsoni, S.ehakernae, Triraphisbillfreelandi, T.billmclarneyi, T.billripplei, T.bobandersoni, T.bobrobbinsi, T.bradzlotnicki, T.brianbrowni, T.brianlaueri, T.briannestjacquesae, T.camilocamargoi, T.carlosherrerai, T.carolinepalmerae, T.charlesmorrisi, T.chigiybinellae, T.christerhanssoni, T.christhompsoni, T.conniebarlowae, T.craigsimonsi, T.defectus Valerio, 2015, T.danielhubi, T.davidduthiei, T.davidwahli, T.federicomatarritai, T.ferrisjabri, T.mariobozai, T.martindohrni, T.matssegnestami, T.mehrdadhajibabaei, T.ollieflinti, T.tildalauerae, Yeliconesdirksteinkei, Y.markmetzi, Y.monserrathvargasae, Y.tricolor Quicke, 1996. Y.woldai Quicke, 1996. The following new combinations are proposed: Neothlipsissmithi (Ashmead), new combination for Microdussmithi Ashmead, 1894; Neothlipsispygmaeus (Enderlein), new combination for Microduspygmaeus Enderlein, 1920; Neothlipsisunicinctus (Ashmead), new combination for Microdusunicinctus Ashmead, 1894; Therophilusanomalus (Bortoni and Penteado-Dias) new combination for Plesiocoelusanomalus Bortoni and Penteado-Dias, 2015; Aerophilusareolatus (Bortoni and Penteado-Dias) new combination for Plesiocoelusareolatus Bortoni and Penteado-Dias, 2015; Pneumagathiserythrogastra (Cameron) new combination for Agathiserythrogastra Cameron, 1905. Dolichozelecitreitarsis (Enderlein), new combination for Paniscozelecitreitarsis Enderlein, 1920. Dolichozelefuscivertex (Enderlein) new combination for Paniscozelefuscivertex Enderlein, 1920. Finally, Bassusbrooksi Sharkey, 1998 is synonymized with Agathiserythrogastra Cameron, 1905; Paniscozelegriseipes Enderlein, 1920 issynonymized with Dolichozelekoebelei Viereck, 1911; Paniscozelecarinifrons Enderlein, 1920 is synonymized with Dolichozelefuscivertex (Enderlein, 1920); and Paniscozelenigricauda Enderlein,1920 is synonymized with Dolichozelequaestor (Fabricius, 1804). (originally described as Ophionquaestor Fabricius, 1804).