Facing the infinity: tackling large samples of challenging Chironomidae (Diptera) with an integrative approach

The first record of Chironomusnuditarsis Keyl, 1961 from Sevan Lake (Armenia) confirmed by morphology, karyotype and COI gene sequence

Chironomusnuditarsis Keyl, 1961 is recorded from Sevan Lake for the first time. This species is widespread in Europe, the Caucasus, and Siberia. For species identification, we used a comprehensive approach that included morphological, cytogenetic and molecular genetic analyses. Morphological analysis showed a high similarity with the description. Nine chromosome banding sequences ndtA1, ndtA2, ndtB2, ndtC1, ndtD1, ndtE1, ndtF1, ndtG1, and ndtG2 were found. The banding sequences ndtA1, ndtA2, ndtG1, and ndtG2 are species-specific for C.nuditarsis and allow us to accurately distinguish it from the sibling species Ch.curabilis Belyanina, Sigareva et Loginova, 1990. Molecular-genetic analysis of the COI gene sequences has shown low genetic distances of 0.38-0.95% in the sibling species Ch.nuditarsis and Ch.curabilis complex and the insufficiency of using a single COI as a molecular marker for their separation.

Image-based recognition of parasitoid wasps using advanced neural networks

Hymenoptera has some of the highest diversity and number of individuals among insects. Many of these species potentially play key roles as food sources, pest controllers and pollinators. However, little is known about the diversity and biology and ~80% of the species have not yet been described. Classical taxonomy based on morphology is a rather slow process but DNA barcoding has already brought considerable progress in identification. Innovative methods such as image-based identification and automation can further speed up the process. We present a proof of concept for image data recognition of a parasitic wasp family, the Diapriidae (Hymenoptera), obtained as part of the GBOL III project. These tiny (1.2-4.5mm) wasps were photographed and identified using DNA barcoding to provide a solid ground truth for training a neural network. Taxonomic identification was used down to the genus level. Subsequently, three different neural network architectures were trained, evaluated and optimised. As a result, 11 different genera of diaprids and one mixed group of 'other Hymenoptera' can be classified with an average accuracy of 96%. Additionally, the sex of the specimen can be classified automatically with an accuracy of >97%.

The InBIO Barcoding Initiative Database: DNA barcodes of Orthoptera from Portugal

Background

The InBIO Barcoding Initiative (IBI) Orthoptera dataset contains records of 420 specimens covering all the eleven Orthoptera families occurring in Portugal. Specimens were collected in continental Portugal from 2005 to 2021 and were morphologically identified to species level by taxonomists. A total of 119 species were identified corresponding to about 77% of all the orthopteran species known from continental Portugal.

New information

DNA barcodes of 54 taxa were made public for the first time at the Barcode of Life Data System (BOLD). Furthermore, the submitted sequences were found to cluster in 129 BINs (Barcode Index Numbers), 35 of which were new additions to the Barcode of Life Data System (BOLD). All specimens have their DNA barcodes publicly accessible through BOLD online database. Stenobothruslineatus is recorded for the first time for continental Portugal. This dataset greatly increases the knowledge on the DNA barcodes and distribution of Orthoptera from Portugal. All DNA extractions and most specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources.

How non-target chironomid communities respond to mosquito control: Integrating DNA metabarcoding and joint species distribution modelling

The conservation and management of riparian ecosystems rely on understanding the ecological consequences of anthropogenic stressors that impact natural communities. In this context, studies investigating the effects of anthropogenic stressors require reliable methods capable of mapping the relationships between taxa occurrence or abundance and environmental predictors within a spatio-temporal framework. Here, we present an integrative approach using DNA metabarcoding and Hierarchical Modelling of Species Communities (HMSC) to unravel the intricate dynamics and resilience of chironomid communities exposed to Bacillus thuringiensis var. israelensis (Bti). Chironomid emergence was sampled from a total of 12 floodplain pond mesocosms, half of which received Bti treatment, during a 16-week period spanning spring and summer of 2020. Subsequently, we determined the community compositions of chironomids and examined their genus-specific responses to the Bti treatment, considering their phylogenetic affiliations and ecological traits of the larvae. Additionally, we investigated the impact of the Bti treatment on the body size distribution of emerging chironomids. Our study revealed consistent responses to Bti among different chironomid genera, indicating that neither phylogenetic affiliations nor larval feeding strategies significantly contributed to the observed patterns. Both taxonomic and genetic diversity were positively correlated with the number of emerged individuals. Furthermore, our findings demonstrated Bti-related effects on chironomid body size distribution, which could have relevant implications for size-selective terrestrial predators. Hence, our study highlights the value of employing a combination of DNA metabarcoding and HMSC to unravel the complex dynamics of Bti-related non-target effects on chironomid communities. The insights gained from this integrated framework contribute to our understanding of the ecological consequences of anthropogenic stressors and provide a foundation for informed decision-making regarding the conservation and management of riparian ecosystems.

Abundant, diverse, unknown: Extreme species richness and turnover despite drastic undersampling in two closely placed tropical Malaise traps

Arthropods account for a large proportion of animal biomass and diversity in terrestrial systems, making them crucial organisms in our environments. However, still too little is known about the highly abundant and megadiverse groups that often make up the bulk of collected samples, especially in the tropics. With molecular identification techniques ever more evolving, analysis of arthropod communities has accelerated. In our study, which was conducted within the Global Malaise trap Program (GMP) framework, we operated two closely placed Malaise traps in Padang, Sumatra, for three months. We analyzed the samples by DNA barcoding and sequenced a total of more than 70,000 insect specimens. For sequence clustering, we applied three different delimitation techniques, namely RESL, ASAP, and SpeciesIdentifier, which gave similar results. Despite our (very) limited sampling in time and space, our efforts recovered more than 10,000 BINs, of which the majority are associated with "dark taxa". Further analysis indicates a drastic undersampling of both sampling sites, meaning that the true arthropod diversity at our sampling sites is even higher. Regardless of the close proximity of both Malaise traps (< 360 m), we discovered significantly distinct communities.