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Aim: Knowledge of taxonomy and species distributions in highly diverse lineages of invertebrates remains too incomplete for the study of biogeographical patterns at the global scale. This limits the understanding of processes leading to the formation and maintenance of boundaries between major biogeographical realms. Site‐based metagenomic approaches may provide an alternative source of data for inference of historical processes of in situ speciation and interchange among biogeographical regions. We applied the methodology to explore the historical biogeography of the Qinling Mountains at the boundary of the Oriental and Palaearctic regions. Location: The focal area in the Qinling Mountains; sites in Borneo, Panama, and Spain, representing the Oriental, Neotropical and Palaearctic faunas. Time Period: Contemporary. Major Taxa Studied: Chrysomelidae, a group of ~40,000 species with worldwide distribution. Methods: Mass‐trapped insects were subjected to deep Illumina DNA sequencing and mitochondrial genome assembly, followed by phylogenetic analysis and historical biogeographical inference on a dated tree. The methodology produced 622 mitogenomes (304 newly sequenced) each representing a morphologically distinct species. Results: Ancestral area reconstruction revealed that the Qinling fauna is a composite of distinct clades that, respectively, have Oriental or Palaearctic ancient origins, while in situ speciation and local clade formation were limited. The global diversity of Chrysomelidae consists of regionalised deep clades at the level of the major zoogeographic realms, which remain recognisable where these realms abut in the Qinling mountains. Yet, the Qinling fauna is clearly distinct from the source areas although local lineage ages are generally <20 Ma. Main Conclusions: The Qinling fauna is a composite of clades that have either Oriental or Palaearctic origin, indicating the important role of immigration at the realm boundary. Global site‐based phylogenetic analyses based on metagenomic sequencing can address previously intractable questions about the historical biogeography of poorly studied groups even without a fully developed taxonomy. [ABSTRACT FROM AUTHOR]

Introduction: Historic museum collections hold a wealth of biodiversity data that are essential to our understanding of the rapidly changing natural world. Novel curatorial practices are needed to extract and digitise these data, especially for the innumerable pinned insects whose collecting information is held on small labels. Methods: We piloted semi-automated specimen imaging and digitisation of specimen labels for a collection of ~29,000 pinned insects of ground beetles (Carabidae: Lebiinae) held at the Natural History Museum, London. Raw transcription data were curated against literature sources and non-digital collection records. The primary data were subjected to statistical analyses to infer trends in collection activities and descriptive taxonomy over the past two centuries. Results: This work produced research-ready digitised records for 2,546 species (40% of known species of Lebiinae). Label information was available on geography in 91% of identified specimens, and the time of collection in 39.8% of specimens and could be approximated for nearly all specimens. Label data revealed the great age of this collection (average age 91.4 years) and the peak period of specimen acquisition between 1880 and 1930, with little differences among continents. Specimen acquisition declined greatly after about 1950. Early detected species generally were present in numerous specimens but were missing records from recent decades, while more recently acquired species (after 1950) were represented mostly by singleton specimens only. The slowing collection growth was mirrored by the decreasing rate of species description, which was affected by huge time lags of several decades to formal description after the initial specimen acquisition. Discussion: Historic label information provides a unique resource for assessing the state of biodiversity backwards to pre-industrial times. Many species held in historical collections especially from tropical super-diverse areas may not be discovered ever again, and if they do, their recognition requires access to digital resources and more complete levels of species description. A final challenge is to link the historical specimens to contemporary collections that are mostly conducted with mechanical trapping of specimens and DNA-based species recognition. [ABSTRACT FROM AUTHOR]

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]

Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research. [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]

Background: MacArthur and Wilson's theory of island biogeography has been a foundation for obtaining testable predictions from models of community assembly and for developing models that integrate across scales and disciplines. Historically, however, these developments have focused on integration across ecological and macroevolutionary scales and on predicting patterns of species richness, abundance distributions, trait data and/or phylogenies. The distribution of genetic variation across species within a community is an emerging pattern that contains signatures of past population histories, which might provide an historical lens for the study of contemporary communities. As intraspecific genetic diversity data become increasingly available at the scale of entire communities, there is an opportunity to integrate microevolutionary processes into our models, moving towards development of a genetic theory of island biogeography. Motivation/goal: We aim to promote the development of process‐based biodiversity models that predict community genetic diversity patterns together with other community‐scale patterns. To this end, we review models of ecological, microevolutionary and macroevolutionary processes that are best suited to the creation of unified models, and the patterns that these predict. We then discuss ongoing and potential future efforts to unify models operating at different organizational levels, with the goal of predicting multidimensional community‐scale data including a genetic component. Main conclusions: Our review of the literature shows that despite recent efforts, further methodological developments are needed, not only to incorporate the genetic component into existing island biogeography models, but also to unify processes across scales of biological organization. To catalyse these developments, we outline two potential ways forward, adopting either a top‐down or a bottom‐up approach. Finally, we highlight key ecological and evolutionary questions that might be addressed by unified models including a genetic component and establish hypotheses about how processes across scales might impact patterns of community genetic diversity. [ABSTRACT FROM AUTHOR]

New methods are required for biomonitoring of poorly known tropical ecosystems, but biological assessments of environmental status are limited by insufficient information on taxonomy, composition and ecology of local communities. The current work applies DNA‐based assessment to establish the impact of various types of anthropogenic disturbances on the freshwater macroinvertebrates in an understudied biodiversity hotspot in South Asia, an area that attracts increasing attention for the loss of aquatic ecosystems.We sampled 16 river systems in the Chittagong Hill Tracts region of Bangladesh and characterised habitat intactness based on a set of 14 environmental parameters associated with habitat quality and human activities. Whole‐community metabarcoding was used to investigate the distribution of hypothetical species‐level clusters (Operational Taxonomic Units, OTUs) across sites of different impacts.We found >900 DNA clusters of insects, decapods and molluscs, dominated by Diptera, which revealed significant variation (p < 0.001) in richness across sites. The presumed sensitive Ephemeroptera‐Plecoptera–Trichoptera (EPT) represented 15.6% of total OTU richness. The type and strength of anthropogenic stressors varied greatly across streams but did not affect total OTU diversity. In contrast, EPT richness decreased by ~50% in response to habitat degradation. Partial‐network analysis revealed 26 OTUs that may serve as potential indicators for either good or poor ecological status. Overall, our results document high diversity, local endemicity and pronounced responses to disturbance in these largely unexplored but threatened habitats.Synthesis and applications. The proposed methodology combines local habitat surveys across sites of various degrees of disturbance with species‐level metabarcoding, as a model for biological evaluation of water bodies in poorly known and inaccessible places across the world. Implemented here for the Indo‐Burmese hotspot, the approach will have great value for applied conservation management as a step towards building a biomonitoring system in this region where currently little is known about the taxonomy, diversity and endemicity in both intact and disturbed ecosystems. [ABSTRACT FROM AUTHOR]

Metabarcoding of DNA extracted from community samples of whole organisms (whole organism community DNA, wocDNA) is increasingly being applied to terrestrial, marine and freshwater metazoan communities to provide rapid, accurate and high resolution data for novel molecular ecology research. The growth of this field has been accompanied by considerable development that builds on microbial metabarcoding methods to develop appropriate and efficient sampling and laboratory protocols for whole organism metazoan communities. However, considerably less attention has focused on ensuring bioinformatic methods are adapted and applied comprehensively in wocDNA metabarcoding. In this study we examined over 600 papers and identified 111 studies that performed COI metabarcoding of wocDNA. We then systematically reviewed the bioinformatic methods employed by these papers to identify the state‐of‐the‐art. Our results show that the increasing use of wocDNA COI metabarcoding for metazoan diversity is characterised by a clear absence of bioinformatic harmonisation, and the temporal trends show little change in this situation. The reviewed literature showed (i) high heterogeneity across pipelines, tasks and tools used, (ii) limited or no adaptation of bioinformatic procedures to the nature of the COI fragment, and (iii) a worrying underreporting of tasks, software and parameters. Based upon these findings we propose a set of recommendations that we think the metabarcoding community should consider to ensure that bioinformatic methods are appropriate, comprehensive and comparable. We believe that adhering to these recommendations will improve the long‐term integrative potential of wocDNA COI metabarcoding for biodiversity science. [ABSTRACT FROM AUTHOR]

Metazoan metabarcoding is emerging as an essential strategy for inventorying biodiversity, with diverse projects currently generating massive quantities of community-level data. The potential for integrating across such data sets offers new opportunities to better understand biodiversity and how it might respond to global change. However, large-scale syntheses may be compromised if metabarcoding workflows differ from each other. There are ongoing efforts to improve standardization for the reporting of inventory data. However, harmonization at the stage of generating metabarcode data has yet to be addressed. A modular framework for harmonized data generation offers a pathway to navigate the complex structure of terrestrial metazoan biodiversity. Here, through our collective expertise as practitioners, method developers, and researchers leading metabarcoding initiatives to inventory terrestrial biodiversity, we seek to initiate a harmonized framework for metabarcode data generation, with a terrestrial arthropod module. We develop an initial set of submodules covering the 5 main steps of metabarcode data generation: (i) sample acquisition; (ii) sample processing; (iii) DNA extraction; (iv) polymerase chain reaction amplification, library preparation, and sequencing; and (v) DNA sequence and metadata deposition, providing a backbone for a terrestrial arthropod module. To achieve this, we (i) identified key points for harmonization, (ii) reviewed the current state of the art, and (iii) distilled existing knowledge within submodules, thus promoting best practice by providing guidelines and recommendations to reduce the universe of methodological options. We advocate the adoption and further development of the terrestrial arthropod module. We further encourage the development of modules for other biodiversity fractions as an essential step toward large-scale biodiversity synthesis through harmonization. [ABSTRACT FROM AUTHOR]

Metabarcoding of Metazoa using mitochondrial genes may be confounded by both the accumulation of PCR and sequencing artefacts and the co‐amplification of nuclear mitochondrial pseudogenes (NUMTs). The application of read abundance thresholds and denoising methods is efficient in reducing noise accompanying authentic mitochondrial amplicon sequence variants (ASVs). However, these procedures do not fully account for the complex nature of concomitant sequences and the highly variable DNA contribution of specimens in a metabarcoding sample. We propose, as a complement to denoising, the metabarcoding Multidimensional Abundance Threshold Evaluation (metaMATE) framework, a novel approach that allows comprehensive examination of multiple dimensions of abundance filtering and the evaluation of the prevalence of unwanted concomitant sequences in denoised metabarcoding datasets. metaMATE requires a denoised set of ASVs as input, and designates a subset of ASVs as being either authentic (mitochondrial DNA haplotypes) or nonauthentic ASVs (NUMTs and erroneous sequences) by comparison to external reference data and by analysing nucleotide substitution patterns. metaMATE (i) facilitates the application of read abundance filtering strategies, which are structured with regard to sequence library and phylogeny and applied for a range of increasing abundance threshold values, and (ii) evaluates their performance by quantifying the prevalence of nonauthentic ASVs and the collateral effects on the removal of authentic ASVs. The output from metaMATE facilitates decision‐making about required filtering stringency and can be used to improve the reliability of intraspecific genetic information derived from metabarcode data. The framework is implemented in the metaMATE software (available at https://github.com/tjcreedy/metamate). see also the Perspective by Natalie R. Graham, Rosemary G. Gillespie and Henrik Krehenwinkel [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. [ABSTRACT FROM AUTHOR]

Improved taxonomic methods are needed to quantify declining populations of insect pollinators. This study devises a high‐throughput DNA barcoding protocol for a regional fauna (United Kingdom) of bees (Apiformes), consisting of reference library construction, a proof‐of‐concept monitoring scheme, and the deep barcoding of individuals to assess potential artefacts and organismal associations. A reference database of cytochrome oxidase c subunit 1 (cox1) sequences including 92.4% of 278 bee species known from the UK showed high congruence with morphological taxon concepts, but molecular species delimitations resulted in numerous split and (fewer) lumped entities within the Linnaean species. Double tagging permitted deep Illumina sequencing of 762 separate individuals of bees from a UK‐wide survey. Extracting the target barcode from the amplicon mix required a new protocol employing read abundance and phylogenetic position, which revealed 180 molecular entities of Apiformes identifiable to species. An additional 72 entities were ascribed to nuclear pseudogenes based on patterns of read abundance and phylogenetic relatedness to the reference set. Clustering of reads revealed a range of secondary operational taxonomic units (OTUs) in almost all samples, resulting from traces of insect species caught in the same traps, organisms associated with the insects including a known mite parasite of bees, and the common detection of human DNA, besides evidence for low‐level cross‐contamination in pan traps and laboratory procedures. Custom scripts were generated to conduct critical steps of the bioinformatics protocol. The resources built here will greatly aid DNA‐based monitoring to inform management and conservation policies for the protection of pollinators. [ABSTRACT FROM AUTHOR]

1. Metabarcoding of arthropod communities can be used for assessing species diversity in tropical forests but the methodology requires validation for accurate and repeatable species occurrences in complex mixtures. This study investigates how the composition of ecological samples affects the accuracy of species recovery. 2. Starting with field‐collected bulk samples from the tropical canopy, the recovery of specimens was tested for subsets of different body sizes and major taxa, by assembling these subsets into increasingly complex composite pools. After metabarcoding, we track whether richness, diversity, and most importantly composition of any size class or taxonomic subset are affected by the presence of other subsets in the mixture. 3. Operational taxonomic units (OTUs) greatly exceeded the number of morphospecies in most taxa, even under very stringent sequencing read filtering. There was no significant effect on the recovered OTU richness of small and medium‐sized arthropods when metabarcoded alongside larger arthropods, despite substantial biomass differences in the mixture. The recovery of taxonomic subsets was not generally influenced by the presence of other taxa, although with some exceptions likely due to primer mismatches. Considerable compositional variation within size and taxon‐based subcommunities was evident resulting in high beta‐diversity among samples from within a single tree canopy, but this beta‐diversity was not affected by experimental manipulation. 4. We conclude that OTU recovery in complex arthropod communities, with sufficient sequencing depth and within reasonable size ranges, is not skewed by variable biomass of the constituent species. This could remove the need for time‐intensive manual sorting prior to metabarcoding. However, there remains a chance of taxonomic bias, which may be primer‐dependent. There will never be a panacea primer; instead, metabarcoding studies should carefully consider whether the aim is broadscale turnover, in which case these biases may not be important, or species lists, in which case separate PCRs and sequencing might be necessary. OTU number inflation remains an issue in metabarcoding and requires bioinformatic development, particularly in read filtering and OTU clustering, and/or greater use of species‐identifying sequences generated outside of bulk sequencing. [ABSTRACT FROM AUTHOR]