Inferring the ecological and evolutionary determinants of community genetic diversity.

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.

The phylogeny and evolutionary ecology of hoverflies (Diptera: Syrphidae) inferred from mitochondrial genomes.

Hoverflies (Diptera: Syrphidae) are a diverse group of pollinators and a major research focus in ecology, but their phylogenetic relationships remain incompletely known. Using a genome skimming approach we generated mitochondrial genomes for 91 species, capturing a wide taxonomic diversity of the family. To reduce the required amount of input DNA and overall cost of the library construction, sequencing and assembly was conducted on mixtures of specimens, which raises the problem of chimera formation of mitogenomes. We present a novel chimera detection test based on gene tree incongruence, but identified only a single mitogenome of chimeric origin. Together with existing data for a final set of 127 taxa, phylogenetic analysis on nucleotide and amino acid sequences using Maximum Likelihood and Bayesian Inference revealed a basal split of Microdontinae from all other syrphids. The remainder consists of several deep clades assigned to the subfamily Eristalinae in the current classification, including a clade comprising the subfamily Syrphinae (plus Pipizinae). These findings call for a re-definition of subfamilies, but basal nodes had insufficient support to fully justify such action. Molecular-clock dating placed the origin of the Syrphidae crown group in the mid-Cretaceous while the Eristalinae-Syrphinae clade likely originated near the K/Pg boundary. Transformation of larval life history characters on the tree suggests that Syrphidae initially had sap feeding larvae, which diversified greatly in diet and habitat association during the Eocene and Oligocene, coinciding with the diversification of angiosperms and the evolution of various insect groups used as larval host, prey, or mimicry models. Mitogenomes proved to be a powerful phylogenetic marker for studies of Syrphidae at subfamily and tribe levels, allowing dense taxon sampling that provided insight into the great ecological diversity and rapid evolution of larval life history traits of the hoverflies.

Community metabarcoding reveals the relative role of environmental filtering and spatial processes in metacommunity dynamics of soil microarthropods across a mosaic of montane forests.

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 ß 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.

Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands.

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.

Climate change alters impacts of extreme climate events on a tropical perennial tree crop.

Anthropogenic climate change causes more frequent and intense fluctuations in the El Niño Southern Oscillation (ENSO). Understanding the effects of ENSO on agricultural systems is crucial for predicting and ameliorating impacts on lives and livelihoods, particularly in perennial tree crops, which may show both instantaneous and delayed responses. Using cocoa production in Ghana as a model system, we analyse the impact of ENSO on annual production and climate over the last 70 years. We report that in recent decades, El Niño years experience reductions in cocoa production followed by several years of increased production, and that this pattern has significantly shifted compared with prior to the 1980s. ENSO phase appears to affect the climate in Ghana, and over the same time period, we see corresponding significant shifts in the climatic conditions resulting from ENSO extremes, with increasing temperature and water stress. We attribute these changes to anthropogenic climate change, and our results illustrate the big data analyses necessary to improve understanding of perennial crop responses to climate change in general, and climate extremes in particular.

Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods.

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.

Coming of age for COI metabarcoding of whole organism community DNA: Towards bioinformatic harmonisation.

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.

Validated removal of nuclear pseudogenes and sequencing artefacts from mitochondrial metabarcode data.

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).

Connecting high-throughput biodiversity inventories: Opportunities for a site-based genomic framework for global integration and synthesis.

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.

A validated workflow for rapid taxonomic assignment and monitoring of a national fauna of bees (Apiformes) using high throughput DNA barcoding.

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.

Toward accurate species-level metabarcoding of arthropod communities from the tropical forest canopy.

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.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.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.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.

Forests and Their Canopies: Achievements and Horizons in Canopy Science.

Forest canopies are dynamic interfaces between organisms and atmosphere, providing buffered microclimates and complex microhabitats. Canopies form vertically stratified ecosystems interconnected with other strata. Some forest biodiversity patterns and food webs have been documented and measurements of ecophysiology and biogeochemical cycling have allowed analyses of large-scale transfer of CO2, water, and trace gases between forests and the atmosphere. However, many knowledge gaps remain. With global research networks and databases, and new technologies and infrastructure, we envisage rapid advances in our understanding of the mechanisms that drive the spatial and temporal dynamics of forests and their canopies. Such understanding is vital for the successful management and conservation of global forests and the ecosystem services they provide to the world.