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Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human‐modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco‐evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation‐based machine learning approach we show that neutral and non‐neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community‐scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high‐elevation and isolated habitats act as an abiotic filter generating non‐neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community‐scale, biodiversity using community‐scale genetic data. [ABSTRACT FROM AUTHOR]

Disentangling the relative role of environmental filtering and spatial processes in driving metacommunity structure across mountainous regions remains challenging, as the way we quantify spatial connectivity in topographically and environmentally heterogeneous landscapes can influence our perception of which process predominates. More empirical data sets are required to account for taxon‐ and context‐dependency, but relevant research in understudied areas is often compromised by the taxonomic impediment. Here we used haplotype‐level community DNA metabarcoding, enabled by stringent filtering of amplicon sequence variants (ASVs), to characterize metacommunity structure of soil microarthropod assemblages across a mosaic of five forest habitats on the Troodos mountain range in Cyprus. We found similar β diversity patterns at ASV and species (OTU, operational taxonomic unit) levels, which pointed to a primary role of habitat filtering resulting in the existence of largely distinct metacommunities linked to different forest types. Within‐habitat turnover was correlated to topoclimatic heterogeneity, again emphasizing the role of environmental filtering. However, when integrating landscape matrix information for the highly fragmented Quercus alnifolia habitat, we also detected a major role of spatial isolation determined by patch connectivity, indicating that stochastic and niche‐based processes synergistically govern community assembly. Alpha diversity patterns varied between ASV and OTU levels, with OTU richness decreasing with elevation and ASV richness following a longitudinal gradient, potentially reflecting a decline of genetic diversity eastwards due to historical pressures. Our study demonstrates the utility of haplotype‐level community metabarcoding for characterizing metacommunity structure of complex assemblages and improving our understanding of biodiversity dynamics across mountainous landscapes worldwide. [ABSTRACT FROM AUTHOR]

Complex bulk samples of insects from biodiversity surveys present a challenge for taxonomic identification, which could be overcome by high‐throughput imaging combined with machine learning for rapid classification of specimens. These procedures require that taxonomic labels from an existing source data set are used for model training and prediction of an unknown target sample. However, such transfer learning may be problematic for the study of new samples not previously encountered in an image set, for example, from unexplored ecosystems, and require methods of domain adaptation that reduce the differences in the feature distribution of the source and target domains (training and test sets). We assessed the efficiency of domain adaptation for family‐level classification of bulk samples of Coleoptera, as a critical first step in the characterization of biodiversity samples. Neural network models trained with images from a global database of Coleoptera were applied to a biodiversity sample from understudied forests in Cyprus as the target. Within‐dataset classification accuracy reached 98% and depended on the number and quality of training images, and on dataset complexity. The accuracy of between‐datasets predictions (across disparate source–target pairs that do not share any species or genera) was at most 82% and depended greatly on the standardization of the imaging procedure. An algorithm for domain adaptation, domain adversarial training of neural networks (DANN), significantly improved the prediction performance of models trained by non‐standardized, low‐quality images. Our findings demonstrate that existing databases can be used to train models and successfully classify images from unexplored biota, but the imaging conditions and classification algorithms need careful consideration. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence suggests that vitamin D might be implicated in asthma pathophysiology. This study aims to compare Vitamin D mean serum levels and status between asthmatic and non-asthmatic adolescents and investigate the association of vitamin D with asthma severity. Methods: In a cohort of adolescents aged 16-17 years, those reporting wheezing in the past 12 months and Ever asthma on the ISAAC questionnaire were invited to participate and formed the Active Asthmatics group. Controls were selected amongst Never Wheezers/Never Asthmatics (NWNA). Differences in mean 25(OH)D serum levels and vitamin D status between AA and NWNA were examined in multivariate linear and logistic regression models respectively, adjusting for potential confounders. Within AA, differences in vitamin D levels were assessed across asthma severity indicators. Results: A total of 69 AA and 671 NWNA participated in the study. Unadjusted mean 25(OH)D serum levels were 22.90 (SD 6.41), and 21.15 (SD 5.59) ng/mL in NWNA and AA respectively (p = 0.03). In adjusted models, mean 25(OH)D levels remained significantly lower amongst AA compared to NWNA (adjusted beta coefficient -1.68, 95% CI -3.24, -0.13). Severe (<12 ng/mL), moderate (<25 ng/mL) or insufficient (<30 ng/mL) vitamin D status was more prevalent among AA who were 1.6 times (95% CI 1.01, 2.53) more likely to belong to a lower vitamin D category compared to NWNA. Within AA, there was a negative trend between vitamin D levels and the number of reported asthma severity indicators. Conclusions: Levels of vitamin D tend to be lower among asthmatic compared to non-asthmatic children and in those with severe asthma independent of important confounders. [ABSTRACT FROM AUTHOR]

Two new species of the tribe Helopini (Coleoptera: Tenebrionidae) are described from Turkey: Nalassus (Nalassus) becvari sp. nov. (Elazığ Province) and Hedyphanes (Hedyphanes) kmenti sp. nov. (Artvin Province). The fi rst species is characterized by strongly thickened antennomeres 2-8 and differs from all Turkish Nalassus s. str. Mulsant, 1854 in the ventral aspect of eye, which bears a weak posterior ventral impression (rather than a distinct groove of other species). The second species belongs to the species group with asperate punctation of the prothoracic hypomera and differs from all Hedyphanes Fischer von Waldheim, 1820 in the presence of suberect pubescence on both sides of elytral base. Distribution of some Helopini (the Helops genus-group, subtribe Helopina) from Anatolia and Cyprus is updated with new data. Hedyphanes mannerheimi Faldermann, 1837 is recorded for Turkey (Iğdır Province) for the fi rst time. Helops caeruleus caeruleus Linnaeus, 1758 from Pervolia is a new record for Cyprus and the occurrence is probably a result of anthropogenic introduction. [ABSTRACT FROM AUTHOR]

High-throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site-based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled "Next Generation Biodiversity Monitoring" was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3-day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS-based strategy to collectively build an integrative framework for site-based biodiversity data generation., (© 2021 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

Objective: To assess vitamin D status among Cypriot adolescents and investigate potential determinants including BMI and body fat percentage (BF%)., Design: Participants had cross-sectional assessments of serum vitamin D, physical activity, dietary vitamin D intake and sun exposure. Linear and logistic regression models were used to explore the associations of vitamin D with potential predictors., Setting: Hospitals, Cyprus, November 2007-May 2008., Subjects: Adolescents (n 671) aged 16-18 years., Results: Mean serum vitamin D was 22·90 (sd 6·41) ng/ml. Only one in ten children had sufficient levels of vitamin D (≥30 ng/ml), while the prevalence of vitamin D deficiency (12-20 ng/ml) and severe deficiency (<12 ng/ml) was 31·7 % and 4·0 %, respectively. Lower vitamin D was associated with winter and spring season, female gender, reduced sun exposure in winter and darker skin. Participants with highest BMI and BF% when compared with a middle reference group had increased adjusted odds of vitamin D insufficiency (OR = 3·00; 95 % CI 1·21, 7·45 and OR = 5·02; 95 % CI 1·80, 13·97, respectively). A similar pattern, although not as strong, was shown for vitamin D deficiency with BF% (OR = 1·81; 95 % CI 1·04, 3·16) and BMI (OR = 1·51; 95 % CI 0·85, 2·67). Participants in the lowest BMI and BF% groups also displayed compromised vitamin D status, suggesting a U-shaped association., Conclusions: Vitamin D deficiency in adolescence is very prevalent in sunny Cyprus, particularly among females, those with darker skin and those with reduced sun exposure in winter. Furthermore, vitamin D status appears to have a U-shaped association with adiposity measures.