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.

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.

Complex genetic patterns and distribution limits mediated by native congeners of the worldwide invasive red-eared slider turtle.

Non-native (invasive) species offer a unique opportunity to study the geographical distribution and range limits of species, wherein the evolutionary change driven by interspecific interactions between native and non-native closely related species is a key component. The red-eared slider turtle, Trachemys scripta elegans (TSE), has been introduced and successfully established worldwide. It can coexist with its native congeners T. cataspila, T. venusta and T. taylori in Mexico. We performed comprehensive fieldwork, executed a battery of genetic analyses and applied a novel species distribution modelling approach to evaluate their historical lineage relationships and contemporary population genetic patterns. Our findings support the historical common ancestry between native TSE and non-native (TSEalien ), while also highlighting the genetic differentiation of the exotic lineage. Genetic patterns are associated with their range size/endemism gradient; the microendemic T. taylori showed significant reduced genetic diversity and high differentiation, whereas TSEalien showed the highest diversity and signals of population size expansion. Counter to our expectations, lower naturally occurring distribution overlap and little admixture patterns were found between TSE and its congeners, exhibiting reduced gene flow and clear genetic separation across neighbouring species despite having zones of contact. We demonstrate that these native Trachemys species have distinct climatic niche suitability, probably preventing establishment of and displacement by the TSEalien . Moreover, we found major niche overlap between TSEalien and native species worldwide, supporting our prediction that sites with closer ecological optima to the invasive species have higher establishment risk than those that are closer to the niche-centre of the native species.

ipyrad: Interactive assembly and analysis of RADseq datasets.

SUMMARY: ipyrad is a free and open source tool for assembling and analyzing restriction site-associated DNA sequence datasets using de novo and/or reference-based approaches. It is designed to be massively scalable to hundreds of taxa and thousands of samples, and can be efficiently parallelized on high performance computing clusters. It is available both as a command line interface and as a Python package with an application programming interface, the latter of which can be used interactively to write complex, reproducible scripts and implement a suite of downstream analysis tools. AVAILABILITY AND IMPLEMENTATION: ipyrad is a free and open source program written in Python. Source code is available from the GitHub repository (https://github.com/dereneaton/ipyrad/), and Linux and MacOS installs are distributed through the conda package manager. Complete documentation, including numerous tutorials, and Jupyter notebooks demonstrating example assemblies and applications of downstream analysis tools are available online: https://ipyrad.readthedocs.io/.

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.

High-throughput sequencing for community analysis: the promise of DNA barcoding to uncover diversity, relatedness, abundances and interactions in spider communities.

Large-scale studies on community ecology are highly desirable but often difficult to accomplish due to the considerable investment of time, labor and, money required to characterize richness, abundance, relatedness, and interactions. Nonetheless, such large-scale perspectives are necessary for understanding the composition, dynamics, and resilience of biological communities. Small invertebrates play a central role in ecosystems, occupying critical positions in the food web and performing a broad variety of ecological functions. However, it has been particularly difficult to adequately characterize communities of these animals because of their exceptionally high diversity and abundance. Spiders in particular fulfill key roles as both predator and prey in terrestrial food webs and are hence an important focus of ecological studies. In recent years, large-scale community analyses have benefitted tremendously from advances in DNA barcoding technology. High-throughput sequencing (HTS), particularly DNA metabarcoding, enables community-wide analyses of diversity and interactions at unprecedented scales and at a fraction of the cost that was previously possible. Here, we review the current state of the application of these technologies to the analysis of spider communities. We discuss amplicon-based DNA barcoding and metabarcoding for the analysis of community diversity and molecular gut content analysis for assessing predator-prey relationships. We also highlight applications of the third generation sequencing technology for long read and portable DNA barcoding. We then address the development of theoretical frameworks for community-level studies, and finally highlight critical gaps and future directions for DNA analysis of spider communities.

Asymmetrical gene flow in five co-distributed syngnathids explained by ocean currents and rafting propensity.

Ocean circulation driving macro-algal rafting is believed to serve as an important mode of dispersal for many marine organisms, leading to predictions on population-level genetic connectivity and the directionality of effective dispersal. Here, we use genome-wide single nucleotide polymorphism data to investigate whether gene flow directionality in two seahorses (Hippocampus) and three pipefishes (Syngnathus) follows the predominant ocean circulation patterns in the Gulf of Mexico and northwestern Atlantic. In addition, we explore whether gene flow magnitudes are predicted by traits related to active dispersal ability and habitat preference. We inferred demographic histories of these co-distributed syngnathid species, and coalescent model-based estimates indicate that gene flow directionality is in agreement with ocean circulation data that predicts eastward and northward macro-algal transport. However, the magnitude to which ocean currents influence this pattern appears strongly dependent on the species-specific traits related to rafting propensity and habitat preferences. Higher levels of gene flow and stronger directionality are observed in Hippocampus erectus, Syngnathus floridae and Syngnathus louisianae, which closely associated with the pelagic macro-algae Sargassum spp., compared to Hippocampus zosterae and the Syngnathus scovelli/Syngnathus fuscus sister-species pair, which prefer near shore habitats and are weakly associated with pelagic Sargassum. This study highlights how the combination of population genomic inference together with ocean circulation data can help explain patterns of population structure and diversity in marine ecosystems.

Strategies for improving approximate Bayesian computation tests for synchronous diversification.

BACKGROUND: Estimating the variability in isolation times across co-distributed taxon pairs that may have experienced the same allopatric isolating mechanism is a core goal of comparative phylogeography. The use of hierarchical Approximate Bayesian Computation (ABC) and coalescent models to infer temporal dynamics of lineage co-diversification has been a contentious topic in recent years. Key issues that remain unresolved include the choice of an appropriate prior on the number of co-divergence events (Ψ), as well as the optimal strategies for data summarization. METHODS: Through simulation-based cross validation we explore the impact of the strategy for sorting summary statistics and the choice of prior on Ψ on the estimation of co-divergence variability. We also introduce a new setting (ß) that can potentially improve estimation of Ψ by enforcing a minimal temporal difference between pulses of co-divergence. We apply this new method to three empirical datasets: one dataset each of co-distributed taxon pairs of Panamanian frogs and freshwater fishes, and a large set of Neotropical butterfly sister-taxon pairs. RESULTS: We demonstrate that the choice of prior on Ψ has little impact on inference, but that sorting summary statistics yields substantially more reliable estimates of co-divergence variability despite violations of assumptions about exchangeability. We find the implementation of ß improves estimation of Ψ, with improvement being most dramatic given larger numbers of taxon pairs. We find equivocal support for synchronous co-divergence for both of the Panamanian groups, but we find considerable support for asynchronous divergence among the Neotropical butterflies. CONCLUSIONS: Our simulation experiments demonstrate that using sorted summary statistics results in improved estimates of the variability in divergence times, whereas the choice of hyperprior on Ψ has negligible effect. Additionally, we demonstrate that estimating the number of pulses of co-divergence across co-distributed taxon-pairs is improved by applying a flexible buffering regime over divergence times. This improves the correlation between Ψ and the true variability in isolation times and allows for more meaningful interpretation of this hyperparameter. This will allow for more accurate identification of the number of temporally distinct pulses of co-divergence that generated the diversification pattern of a given regional assemblage of sister-taxon-pairs.

Isolation with asymmetric gene flow during the nonsynchronous divergence of dry forest birds.

Dry forest bird communities in South America are often fragmented by intervening mountains and rainforests, generating high local endemism. The historical assembly of dry forest communities likely results from dynamic processes linked to numerous population histories among codistributed species. Nevertheless, species may diversify in the same way through time if landscape and environmental features, or species ecologies, similarly structure populations. Here we tested whether six co-distributed taxon pairs that occur in the dry forests of the Tumbes and Marañón Valley of northwestern South America show concordant patterns and modes of diversification. We employed a genome reduction technique, double-digest restriction site-associated DNA sequencing, and obtained 4407-7186 genomewide SNPs. We estimated demographic history in each taxon pair and inferred that all pairs had the same best-fit demographic model: isolation with asymmetric gene flow from the Tumbes into the Marañón Valley, suggesting a common diversification mode. Overall, we also observed congruence in effective population size (Ne ) patterns where ancestral Ne were 2.9-11.0× larger than present-day Marañón Valley populations and 0.3-2.0× larger than Tumbesian populations. Present-day Marañón Valley Ne was smaller than Tumbes. In contrast, we found simultaneous population isolation due to a single event to be unlikely as taxon pairs diverged over an extended period of time (0.1-2.9 Ma) with multiple nonoverlapping divergence periods. Our results show that even when populations of codistributed species asynchronously diverge, the mode of their differentiation can remain conserved over millions of years. Divergence by allopatric isolation due to barrier formation does not explain the mode of differentiation between these two bird assemblages; rather, migration of individuals occurred before and after geographic isolation.

Behavioural response to song and genetic divergence in two subspecies of white-crowned sparrows (Zonotrichia leucophrys).

Divergence in sexual signals may drive reproductive isolation between lineages, but behavioural barriers can weaken in contact zones. Here, we investigate the role of song as a behavioural and genetic barrier in a contact zone between two subspecies of white-crowned sparrows (Zonotrichia leucophrys). We employed a reduced genomic data set to assess population structure and infer the history underlying divergence, gene flow and hybridization. We also measured divergence in song and tested behavioural responses to song using playback experiments within and outside the contact zone. We found that the subspecies form distinct genetic clusters, and demographic inference supported a model of secondary contact. Song phenotype, particularly length of the first note (a whistle), was a significant predictor of genetic subspecies identity and genetic distance along the hybrid zone, suggesting a close link between song and genetic divergence in this system. Individuals from both parental and admixed localities responded significantly more strongly to their own song than to the other subspecies song, supporting song as a behavioural barrier. Putative parental and admixed individuals were not significantly different in their strength of discrimination between own and other songs; however, individuals from admixed localities tended to discriminate less strongly, and this difference in discrimination strength was explained by song dissimilarity as well as genetic distance. Therefore, we find that song acts as a reproductive isolating mechanism that is potentially weakening in a contact zone between the subspecies. Our findings also support the hypothesis that intraspecific song variation can reduce gene flow between populations.

Detecting the ecological footprint of selection.

The structure of communities is influenced by many ecological and evolutionary processes, but the way these manifest in classic biodiversity patterns often remains unclear. Here we aim to distinguish the ecological footprint of selection-through competition or environmental filtering-from that of neutral processes that are invariant to species identity. We build on existing Massive Eco-evolutionary Synthesis Simulations (MESS), which uses information from three biodiversity axes-species abundances, genetic diversity, and trait variation-to distinguish between mechanistic processes. To correctly detect and characterise competition, we add a new and more realistic form of competition that explicitly compares the traits of each pair of individuals. Our results are qualitatively different to those of previous work in which competition is based on the distance of each individual's trait to the community mean. We find that our new form of competition is easier to identify in empirical data compared to the alternatives. This is especially true when trait data are available and used in the inference procedure. Our findings hint that signatures in empirical data previously attributed to neutrality may in fact be the result of pairwise-acting selective forces. We conclude that gathering more different types of data, together with more advanced mechanistic models and inference as done here, could be the key to unravelling the mechanisms of community assembly and question the relative roles of neutral and selective processes.

Global determinants of insect mitochondrial genetic diversity.

Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth's biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.

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.

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.

A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.

Digest: An emerging model system for understanding ecomorphological convergence.

Morales et al. test predictions of adaptive radiation theory and phenotypic convergence in Myotis bats using genomic target capture and a morphological dataset that represents 80% of the species described for this genus. The authors demonstrate that ecomorphological convergence has occurred multiple times throughout the history of Myotis, despite finding no diversification rate shifts associated with phenotypic adaptation. These patterns provide evidence that parallel adaptive radiations can be the result of nonadaptive lineage diversification followed by repetitive exploitation of ecomorphological solutions.

RADseq as a valuable tool for plants with large genomes-A case study in cycads.

Full genome sequencing of organisms with large and complex genomes is intractable and cost ineffective under most research budgets. Cycads (Cycadales) represent one of the oldest lineages of the extant seed plants and, partly due to their age, have incredibly large genomes up to ~60 Gbp. Restriction site-associated DNA sequencing (RADseq) offers an approach to find genome-wide informative markers and has proven to be effective with both model and nonmodel organisms. We tested the application of RADseq using ezRAD across all 10 genera of the Cycadales including an example data set of Cycas calcicola representing 72 samples from natural populations. Using previously available plastid and mitochondrial genomes as references, reads were mapped recovering plastid and mitochondrial genome regions and nuclear markers for all of the genera. De novo assembly generated up to 138,407 high-depth clusters and up to 1,705 phylogenetically informative loci for the genera, and 4,421 loci for the example assembly of C. calcicola. The number of loci recovered by de novo assembly was lower than previous RADseq studies, yet still sufficient for downstream analysis. However, the number of markers could be increased by relaxing our assembly parameters, especially for the C. calcicola data set. Our results demonstrate the successful application of RADseq across the Cycadales to generate a large number of markers for all genomic compartments, despite the large number of plastids present in a typical plant cell. Our modified protocol was adapted to be applied to cycads and other organisms with large genomes to yield many informative genome-wide markers.