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Biotic exchanges between Taiwan and Mainland China have shaped the biodiversity and ecosystems of both regions. Exchanges from Mainland China to Taiwan have received more attention, mainly studied in terrestrial vertebrates, while the reverse direction and invertebrates have largely been overlooked. Here, we explore the dispersal events between these two regions based on the moths of three species groups of Obeidia, including Taiwan taxa and its relatives from mainland. We conducted mixed methods and analysis, including reconstructing a phylogenetic tree, estimating associated divergence times and inferring ancestral areas and source regions, to explore the phylogeographical structure and genetic pattern of three groups based on eight genes. Our results revealed a structure of three clades and every clade included at least one Taiwanese taxa and its closest relatives of mainland of China, and also served Taiwan as an important source region of two mainland taxa. Our study revealed various origin pattern and dispersal models on the basis of three species groups of Obeidia. Bi‐directional biotic exchange via a land bridge were found: four Taiwanese taxa originated from mainland, and two of them migrated back to mainland. Both eastern Himalayas and south China are important origin areas for Taiwan biota, and the dominant source region may need multiple insect cases to confirm. Our study also provided evidences for disjunct distribution from the perspective of insecta molecular phylogeny. [ABSTRACT FROM AUTHOR]

The full potential for using DNA barcodes for profiling functional trait diversity has yet to be determined in plants and animals; thus, we outline a general framework for quantifying functional trait diversity of insect community DNA and propose and assess the accuracy of three methods for achieving this. We built a novel dataset of traits and DNA barcodes for wild bees in China. An informatics framework was developed for phylogeny‐based integration of these data and prediction of traits for any subject barcodes, which was compared with two distance‐based methods. For Phylogenetic Assignment, we additionally conducted a species‐level analysis of publically available bee trait data. Under the specimen‐level dataset, the rate of trait assignment was negatively correlated with distance between the query and the nearest trait‐known reference, for all methods. Phylogenetic Assignment was found to perform best under several criteria; particularly, it had the lowest false‐positive rate (rarely returning a state prediction where success was unlikely; where the distance from query to the nearest reference was high). For a wider range of compiled traits, conservative life‐history traits showed the highest rates of assignment; for example, sociality was predicted with confidence at 53%, parasitism at 44% and nest location at 33%. As outlined herein, automated trait assignment might be applied at scale to either barcodes or metabarcodes. With further compilation and databasing of DNA barcode and trait data, the rate and accuracy of trait assignment is expected to increase to the point of being a widely viable and informative approach. [ABSTRACT FROM AUTHOR]

Wild bees provide important pollination services, but they face numerous stressors that threaten them and their ecosystem services. Wild bees can be exposed to heavy metal pollution through the consumption of nectar, pollen, and water, which might cause bee decline. While some studies have measured heavy metal concentrations in honeybees, few studies have monitored heavy metal concentrations in wild bees or explored their potential effects on wild bee communities. To investigate the impact of heavy metal pollution on wild bee communities, heavy metal concentrations, including vanadium (V), chromium (Cr), nickel (Ni), cadmium (Cd), Zinc (Zn) and lead (Pb) in multiple wild bee species were measured. Multiple wild bee species, including: Xylocopa tranquabaroroum, Eucera floralia, Apis cerana , and small bee mixtures (representing multiple small wild bee species) were sampled from 18 sites in Quzhou, Zhejiang Province, China. The findings demonstrated that there were significant differences in heavy metal concentrations among different bee species. The concentrations of V, Zn, Cd, and Pb in X. tranquabaroroum , the largest bee species in this study, were lower than that in the other three sample groups. Furthermore, there were significant negative correlations between heavy metal pollution and wild bee diversity and species richness, but not with abundance. Particularly, there was no significant relationship between heavy metal pollution and the abundance of small bees. Given these worrying findings, monitoring multiple heavy metals in wild bees should be conducted for protecting wild bee diversity and securing their pollination services. • Heavy metal concentrations in wild bee bodies varied among different species. • Heavy metal pollution lowered wild bee species diversity. • Heavy metal pollution had no significant effect on wild bee abundance. • Wild bee conservation should consider the impact of heavy metal pollution. [ABSTRACT FROM AUTHOR]

The microbiomes associated with bee nests influence colony health through various mechanisms, although it is not yet clear how honeybee congeners differ in microbiome assembly processes, in particular the degrees to which floral visitations and the environment contribute to different aspects of diversity. We used DNA metabarcoding to sequence bacterial 16S rRNA from honey and stored pollen from nests of 4 honeybee species (Apis cerana, A. dorsata, A. florea, and A. laboriosa) sampled throughout Yunnan, China, a global biodiversity hotspot. We developed a computational pipeline integrating multiple databases for quantifying key facets of diversity, including compositional, taxonomic, phylogenetic, and functional ones. Further, we assessed candidate drivers of observed microbiome dissimilarity, particularly differences in floral visitations, habitat disturbance, and other key environmental variables. Analyses revealed that microbiome alpha diversity was broadly equivalent across the study sites and between bee species, apart from functional diversity which was very low in nests of the reclusive A. laboriosa. Turnover in microbiome composition across Yunnan was driven predominantly by pollen composition. Human disturbance negatively impacted both compositional and phylogenetic alpha diversity of nest microbiomes, but did not correlate with microbial turnover. We herein make progress in understanding microbiome diversity associated with key pollinators in a biodiversity hotspot, and provide a model for the use of a comprehensive informatics framework in assessing pattern and drivers of diversity, which enables the inclusion of explanatory variables both subtly and fundamentally different and enables elucidation of emergent or unexpected drivers., (© 2022 Institute of Zoology, Chinese Academy of Sciences.)