Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

A set of nematode rRNA cistron databases and a primer assessment tool to enable more flexible and comprehensive metabarcoding

The ITS-2-rRNA has been particularly useful for nematode metabarcoding but does not resolve all phylogenetic relationships, and reference sequences are not available for many nematode species. This is a particular issue when metabarcoding complex communities such as wildlife parasites or terrestrial and aquatic free-living nematode communities. We have used markerDB to produce four databases of distinct regions of the rRNA cistron: the 18S rRNA gene, the 28S rRNA gene, the ITS-1 intergenic spacer and the region spanning ITS-1_5.8S_ITS-2. These databases comprise 2645, 254, 13,461 and 10,107 unique full-length sequences representing 1391, 204, 1837 and 1322 nematode species, respectively. The comparative analysis illustrates the complementary value but also reveals a better representation of Clade III, IV and V than Clade I and Clade II nematodes in each case. Although the ITS-1 database includes the largest number of unique full-length sequences, the 18S rRNA database provides the widest taxonomic coverage. We also developed PrimerTC, a tool to assess primer sequence conservation across any reference sequence database, and have applied it to evaluate a large number of previously published rRNA cistron primers. We identified sets of primers that currently provide the broadest taxonomic coverage for each rRNA marker across the nematode phylum. These new resources will facilitate more comprehensive metabarcoding of nematode communities using either short-read or long-read sequencing platforms. Further, PrimerTC is available as a simple WebApp to guide or assess PCR primer design for any genetic marker and/or taxonomic group beyond the nematode phylum.

eDNA Metabarcoding Reveals the Species-Area Relationship of Amphibians on the Zhoushan Archipelago

The species-area relationship is important for understanding species diversity patterns at spatial scales, but few studies have examined the relationship using environmental DNA (eDNA) techniques. We investigated amphibian diversity on 21 islands of the Zhoushan Archipelago and nearby mainland areas in China using the combination of eDNA metabarcoding and the traditional line transect method (TLTM) and identified the species-area relationship for amphibians on the islands. The mean detection probability of eDNA is 0.54, while the mean detection probability of TLTM is 0.24. The eDNA metabarcoding detected eight amphibian species on the islands and nine species in the mainland areas, compared with seven species on the islands and nine species in the mainland areas that were identified by TLTM. Amphibian richness on the islands increased with island area and habitat diversity. The species-area relationship for amphibians in the archipelago was formulated as the power function (S = 0.47A0.21) or exponential function (S = 2.59 + 2.41 (logA)). Our results suggested that eDNA metabarcoding is more sensitive for the detection of amphibian species. The combined use of eDNA metabarcoding and the traditional line transect method may optimize the survey results for amphibians.

Mt. Apo Biotic Index (MABI): a macroinvertebrate-based multimetric index for assessing stream biotic integrity of wadeable streams within a geothermal production field in Mindanao, Philippines

Monitoring the ecological integrity of streams is a challenge, especially in the tropics, which experience high rates of degradation. Multimetric scoring systems have been widely used in other countries in evaluating current stream conditions; however, it has never been done in the Philippines. This study focuses on the development of a benthic macroinvertebrate-based multimetric index for the overall assessment of streams in Mt. Apo, Mindanao, Philippines. The index was used to develop existing physicochemical and biological data obtained during 2010 to 2015 surveys from 15 monitoring sites within the Mt. Apo Geothermal Project (MAGP). Metrics related to benthic macroinvertebrate abundance, richness, composition, functional habit groups, functional feeding groups, and pollution tolerance were screened for their range, temporal stability, sensitivity, discrimination efficiency (DE), redundancy, and responsiveness to anthropogenic impacts. The resulting multimetric index, the Mt. Apo Biotic Index (MABI), is computed as the sum of the individual metric scores after metric transformation using the discrete scoring method DRQ1 (D = discrete, R = reference, Q1 = 25th percentile) of the six core metrics: (1) number of Coleoptera individuals (abundance), (2) number of taxa (richness); (3) [%] Coleoptera taxa (composition), (4) number of sprawler individuals (functional habit group), (5) [%] collector-filterer taxa (functional feeding group), and (6) the Biological Monitoring Working Party Thai version (BMWP-Thai; pollution tolerance). MABI scores were classified into five condition ratings of stream biotic integrity: very poor (6 to 10), poor (11 to 15), fair (16 to 20), good (21 to 25), and excellent (26 to 30). The study demonstrated that the resulting pilot index may provide useful information that will benefit policymakers and resource managers in formulating more comprehensive stream management approaches and conservation plans for priority sites in the region.

Current Status of Omics in Biological Quality Elements for Freshwater Biomonitoring

Freshwater ecosystems have been experiencing various forms of threats, mainly since the last century. The severity of this adverse scenario presents unprecedented challenges to human health, water supply, agriculture, forestry, ecological systems, and biodiversity, among other areas. Despite the progress made in various biomonitoring techniques tailored to specific countries and biotic communities, significant constraints exist, particularly in assessing and quantifying biodiversity and its interplay with detrimental factors. Incorporating modern techniques into biomonitoring methodologies presents a challenging topic with multiple perspectives and assertions. This review aims to present a comprehensive overview of the contemporary advancements in freshwater biomonitoring, specifically by utilizing omics methodologies such as genomics, metagenomics, transcriptomics, proteomics, metabolomics, and multi-omics. The present study aims to elucidate the rationale behind the imperative need for modernization in this field. This will be achieved by presenting case studies, examining the diverse range of organisms that have been studied, and evaluating the potential benefits and drawbacks associated with the utilization of these methodologies. The utilization of advanced high-throughput bioinformatics techniques represents a sophisticated approach that necessitates a significant departure from the conventional practices of contemporary freshwater biomonitoring. The significant contributions of omics techniques in the context of biological quality elements (BQEs) and their interpretations in ecological problems are crucial for biomonitoring programs. Such contributions are primarily attributed to the previously overlooked identification of interactions between different levels of biological organization and their responses, isolated and combined, to specific critical conditions.

Interrogating 1000 insect genomes for NUMTs: A risk assessment for estimates of species richness

The nuclear genomes of most animal species include NUMTs, segments of the mitogenome incorporated into their chromosomes. Although NUMT counts are known to vary greatly among species, there has been no comprehensive study of their frequency/attributes in the most diverse group of terrestrial organisms, insects. This study examines NUMTs derived from a 658 bp 5' segment of the cytochrome c oxidase I (COI) gene, the barcode region for the animal kingdom. This assessment is important because unrecognized NUMTs can elevate estimates of species richness obtained through DNA barcoding and derived approaches (eDNA, metabarcoding). This investigation detected nearly 10,000 COI NUMTs ≥ 100 bp in the genomes of 1,002 insect species (range = 0-443). Variation in nuclear genome size explained 56% of the mitogenome-wide variation in NUMT counts. Although insect orders with the largest genome sizes possessed the highest NUMT counts, there was considerable variation among their component lineages. Two thirds of COI NUMTs possessed an IPSC (indel and/or premature stop codon) allowing their recognition and exclusion from downstream analyses. The remainder can elevate species richness as they showed 10.1% mean divergence from their mitochondrial homologue. The extent of exposure to "ghost species" is strongly impacted by the target amplicon's length. NUMTs can raise apparent species richness by up to 22% when a 658 bp COI amplicon is examined versus a doubling of apparent richness when 150 bp amplicons are targeted. Given these impacts, metabarcoding and eDNA studies should target the longest possible amplicons while also avoiding use of 12S/16S rDNA as they triple NUMT exposure because IPSC screens cannot be employed.

All boreal forest successional stages needed to maintain the full suite of soil biodiversity, community composition, and function following wildfire

Wildfire is a natural disturbance in boreal forest systems that has been predicted to increase in frequency, intensity, and extent due to climate change. Most studies tend to assess the recovery of one component of the community at a time but here we use DNA metabarcoding to simultaneously monitor soil bacteria, fungi, and arthropods along an 85-year chronosequence following wildfire in jack pine-dominated ecosites. We describe soil successional and community assembly processes to better inform sustainable forest management practices. Soil taxa showed different recovery trajectories following wildfire. Bacteria shared a large core community across stand development stages (~ 95-97% of their unique sequences) and appeared to recover relatively quickly by crown closure. By comparison fungi and arthropods shared smaller core communities (64-77% and 68-69%, respectively) and each stage appeared to support unique biodiversity. We show the importance of maintaining a mosaic ecosystem that represents each stand development stage to maintain the full suite of biodiversity in soils following wildfire, especially for fungi and arthropods. These results will provide a useful baseline for comparison when assessing the effects of human disturbance such as harvest or for assessing the effects of more frequent wildfire events due to climate change.

Zeta diversity patterns in metabarcoded lotic algal assemblages as a tool for bioassessment

Assessments of the ecological health of algal assemblages in streams typically focus on measures of their local diversity and classify individuals by morphotaxonomy. Such assemblages are often connected through various ecological processes, such as dispersal, and may be more accurately assessed as components of regional-, rather than local-scale assemblages. With recent declines in the costs of sequencing and computation, it has also become increasingly feasible to use metabarcoding to more accurately classify algal species and perform regional-scale bioassessments. Recently, zeta diversity has been explored as a novel method of constructing regional bioassessments for groups of streams. Here, we model the use of zeta diversity to investigate whether stream health can be determined by the landscape diversity of algal assemblages. We also compare the use of DNA metabarcoding and morphotaxonomy classifications in these zeta diversity-based bioassessments of regional stream health. From 96 stream samples in California, we used various orders of zeta diversity to construct models of biotic integrity for multiple assemblages of diatoms, as well as hybrid assemblages of diatoms in combination with soft-bodied algae, using taxonomy data generated with both DNA sequencing as well as traditional morphotaxonomic approaches. We compared our ability to evaluate the ecological health of streams with the performance of multiple algal indices of biological condition. Our zeta diversity-based models of regional biotic integrity were more strongly correlated with existing indices for algal assemblages classified using metabarcoding compared to morphotaxonomy. Metabarcoding for diatoms and hybrid algal assemblages involved rbcL and 18S V9 primers, respectively. Importantly, we also found that these algal assemblages, independent of the classification method, are more likely to be assembled under a process of niche differentiation rather than stochastically. Taken together, these results suggest the potential for zeta diversity patterns of algal assemblages classified using metabarcoding to inform stream bioassessments.

Comparative analysis of fish environmental DNA reveals higher sensitivity achieved through targeted sequence-based metabarcoding

Environmental DNA (eDNA)-based methods of species detection are enabling various applications in ecology and conservation including large-scale biomonitoring efforts. qPCR is widely used as the standard approach for species-specific detection, often targeting a fish species of interest from aquatic eDNA. However, DNA metabarcoding has the potential to displace qPCR in certain eDNA applications. In this study, we compare the sensitivity of the latest Illumina NovaSeq 6000 NGS platform to qPCR TaqMan assays by measuring limits of detection and by analysing eDNA from water samples collected from Churchill River and Lake Melville, NL, Canada. Species-specific, targeted next generation sequencing (NGS) assays had significantly higher sensitivity than qPCR, with limits of detection 14- to 29-fold lower. For example, when analysing eDNA, qPCR detected Gadus ogac (Greenland cod) in 21% of samples, but targeted NGS detected this species in 29% of samples. General NGS assays were as sensitive as qPCR, while simultaneously detecting 15 fish species from eDNA samples. With over 34,000 fish species on the planet, parallel and sensitive methods such as NGS will be required to support effective biomonitoring at both regional and global scales.

Progress in understanding the vulnerability of freshwater ecosystems

The ability to collect and synthesize long-term environmental monitoring data is essential for the effective management of freshwater ecosystems. Progress has been made in assessment and monitoring approaches that have integrated routine monitoring programs into more holistic watershed-scale vulnerability assessments. While the concept of vulnerability assessment is well-defined for ecosystems, complementary and sometimes competing concepts of adaptive management, ecological integrity, and ecological condition complicate the communication of results to a broader audience. Here, we identify progress in freshwater assessments that can contribute to the identification and communication of freshwater vulnerability. We review novel methods that address common challenges associated with: 1) a lack of baseline information, 2) variability associated with a spatial context, and 3) the taxonomic sufficiency of biological indicators used to make inferences about ecological conditions. Innovation in methods and communication are discussed as a means to highlight meaningful cost-effective results that target policy towards heuristic ecosystem-management.

Benthic invertebrates in Svalbard fjords-when metabarcoding does not outperform traditional biodiversity assessment

To protect and restore ecosystems and biodiversity is one of the 10 challenges identified by the United Nations's Decade of the Ocean Science. In this study we used eDNA from sediments collected in two fjords of the Svalbard archipelago and compared the taxonomic composition with traditional methods through metabarcoding, targeting mitochondrial CO1, to survey benthos. Clustering of 21.6 mill sequence reads with a d value of 13 in swarm, returned about 25 K OTU reads. An identification search with the BOLD database returned 12,000 taxonomy annotated sequences spanning a similarity range of 50% to 100%. Using an acceptance filter of minimum 90% similarity to the CO1 reference sequence, we found that 74% of the ca 100 taxon identified sequence reads were Polychaeta and 22% Nematoda. Relatively few other benthic invertebrate species were detected. Many of the identified sequence reads were extra-organismal DNA from terrestrial, planktonic, and photic zone sources. For the species rich Polychaeta, we found that, on average, only 20.6% of the species identified from morphology were also detected with DNA. This discrepancy was not due to missing reference sequences in the search database, because 90-100% (mean 96.7%) of the visually identified species at each station were represented with barcodes in Boldsystems. The volume of DNA samples is small compared with the volume searched in visual sorting, and the replicate DNA-samples in sum covered only about 2% of the surface area of a grab. This may considerably reduce the detection rate of species that are not uniformly distributed in the sediments. Along with PCR amplification bias and primer mismatch, this may be an important reason for the limited congruence of species identified with the two approaches. However, metabarcoding also identified 69 additional species that are usually overlooked in visual sample sorting, demonstrating how metabarcoding can complement traditional methodology by detecting additional, less conspicuous groups of organisms.

Fast-tracking bespoke DNA reference database generation from museum collections for biomonitoring and conservation

Despite recent advances in high-throughput DNA sequencing technologies, a lack of locally relevant DNA reference databases limits the potential for DNA-based monitoring of biodiversity for conservation and biosecurity applications. Museums and national collections represent a compelling source of authoritatively identified genetic material for DNA database development, yet obtaining DNA barcodes from long-stored specimens may be difficult due to sample degradation. Here we demonstrate a sensitive and efficient laboratory and bioinformatic process for generating DNA barcodes from hundreds of invertebrate specimens simultaneously via the Illumina MiSeq system. Using this process, we recovered full-length (334) or partial (105) COI barcodes from 439 of 450 (98%) national collection-held invertebrate specimens. This included full-length barcodes from 146 specimens which produced low-yield DNA and no visible PCR bands, and which produced as little as a single sequence per specimen, demonstrating high sensitivity of the process. In many cases, the identity of the most abundant sequences per specimen were not the correct barcodes, necessitating the development of a taxonomy-informed process for identifying correct sequences among the sequencing output. The recovery of only partial barcodes for some taxa indicates a need to refine certain PCR primers. Nonetheless, our approach represents a highly sensitive, accurate and efficient method for targeted reference database generation, providing a foundation for DNA-based assessments and monitoring of biodiversity.

Fine-scale differences in eukaryotic communities inside and outside salmon aquaculture cages revealed by eDNA metabarcoding

Aquaculture impacts on marine benthic ecosystems are widely recognized and monitored. However, little is known about the community changes occurring in the water masses surrounding aquaculture sites. In the present study, we studied the eukaryotic communities inside and outside salmonid aquaculture cages through time to assess the community changes in the neighbouring waters of the farm. Water samples were taken biweekly over five months during the production phase from inside the cages and from nearby points located North and South of the salmon farm. Eukaryotic communities were analyzed by eDNA metabarcoding of the partial COI Leray-XT fragment. The results showed that eukaryotic communities inside the cages were significantly different from those in the outside environment, with communities inside the cages having higher diversity values and more indicator species associated with them. This is likely explained by the appearance of fouling species that colonize the artificial structures, but also by other species that are attracted to the cages by other means. Moreover, these effects were highly localized inside the cages, as the communities identified outside the cages, both North and South, had very similar eukaryotic composition at each point in time. Overall, the eukaryotic communities, both inside and outside the cages, showed similar temporal fluctuations through the summer months, with diversity peaks occurring at the end of July, beginning of September, and in the beginning of November, with the latter showing the highest Shannon diversity and richness values. Hence, our study suggests that seasonality, together with salmonid aquaculture, are the main drivers of eukaryotic community structure in surface waters surrounding the farm.

Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria

Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 μg TP/L with the greatest changes occurring from 110 to 195 μg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 μg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

Comparison of traditional and DNA metabarcoding samples for monitoring tropical soil arthropods (Formicidae, Collembola and Isoptera)

The soil fauna of the tropics remains one of the least known components of the biosphere. Long-term monitoring of this fauna is hampered by the lack of taxonomic expertise and funding. These obstacles may potentially be lifted with DNA metabarcoding. To validate this approach, we studied the ants, springtails and termites of 100 paired soil samples from Barro Colorado Island, Panama. The fauna was extracted with Berlese-Tullgren funnels and then either sorted with traditional taxonomy and known, individual DNA barcodes ("traditional samples") or processed with metabarcoding ("metabarcoding samples"). We detected 49 ant, 37 springtail and 34 termite species with 3.46 million reads of the COI gene, at a mean sequence length of 233 bp. Traditional identification yielded 80, 111 and 15 species of ants, springtails and termites, respectively; 98%, 37% and 100% of these species had a Barcode Index Number (BIN) allowing for direct comparison with metabarcoding. Ants were best surveyed through traditional methods, termites were better detected by metabarcoding, and springtails were equally well detected by both techniques. Species richness was underestimated, and faunal composition was different in metabarcoding samples, mostly because 37% of ant species were not detected. The prevalence of species in metabarcoding samples increased with their abundance in traditional samples, and seasonal shifts in species prevalence and faunal composition were similar between traditional and metabarcoding samples. Probable false positive and negative species records were reasonably low (13-18% of common species). We conclude that metabarcoding of samples extracted with Berlese-Tullgren funnels appear suitable for the long-term monitoring of termites and springtails in tropical rainforests. For ants, metabarcoding schemes should be complemented by additional samples of alates from Malaise or light traps.

Multi-marker DNA metabarcoding detects suites of environmental gradients from an urban harbour

There is increasing need for biodiversity monitoring, especially in places where potential anthropogenic disturbance may significantly impact ecosystem health. We employed a combination of traditional morphological and bulk macroinvertebrate metabarcoding analyses to benthic samples collected from Toronto Harbour (Ontario, Canada) to compare taxonomic and functional diversity of macroinvertebrates and their responses to environmental gradients. At the species rank, sites assessed using COI metabarcoding showed more variation than sites assessed using morphological methods. Depending on the assessment method, we detected gradients in magnesium (morphological taxa), ammonia (morphological taxa, COI sequence variants), pH (18S sequence variants) as well as gradients in contaminants such as metals (COI & 18S sequence variants) and organochlorines (COI sequence variants). Observed responses to contaminants such as aromatic hydrocarbons and metals align with known patchy distributions in harbour sediments. We determined that the morphological approach may limit the detection of macroinvertebrate responses to lake environmental conditions due to the effort needed to obtain fine level taxonomic assignments necessary to investigate responses. DNA metabarcoding, however, need not be limited to macroinvertebrates, can be automated, and taxonomic assignments are associated with a certain level of accuracy from sequence variants to named taxonomic groups. The capacity to detect change using a scalable approach such as metabarcoding is critical for addressing challenges associated with biodiversity monitoring and ecological investigations.

Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers

For DNA metabarcoding to attain its potential as a community assessment tool, we need to better understand its performance versus traditional morphological identification and work to address any remaining performance gaps in incorporating DNA metabarcoding into community assessments. Using fragments of the 18S nuclear and 16S mitochondrial rRNA genes and two fragments of the mitochondrial COI marker, we examined the use of DNA metabarcoding and traditional morphological identification for understanding the diversity and composition of crustacean zooplankton at 42 sites across western Lake Superior. We identified 51 zooplankton taxa (genus or species, depending on the finest resolution of the taxon across all identification methods), of which 17 were identified using only morphological traits, 13 using only DNA and 21 using both methods. The taxa found using only DNA metabarcoding included four species and one genus-level identification not previously known to occur in Lake Superior, the presence of which still needs to be confirmed. A substantial portion of taxa that were identified to genus or species by morphological identification, but not identified using DNA metabarcoding, had zero ("no record") or ≤ 2 ("underrepresented records") reference barcodes in the BOLD or NCBI databases (63% for COI, 80% for 16S, 74% for 18S). The two COI marker fragments identified the most genus- and species-level taxa, whereas 18S was the only marker whose family-level percent sequence abundance patterns showed high correlation to composition patterns from morphological identification, based on a NMDS analysis of Bray-Curtis similarities. Multiple replicates were collected at a subset of sites and an occupancy analysis was performed, which indicated that rare taxa were more likely to be detected using DNA metabarcoding than traditional morphology. Our results support that DNA metabarcoding can augment morphological identification for estimating zooplankton diversity and composition of zooplankton over space and time, but may require use of multiple markers. Further addition of taxa to reference DNA databases will improve our ability to use DNA metabarcoding to identify zooplankton and other invertebrates in aquatic surveys.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Profile hidden Markov model sequence analysis can help remove putative pseudogenes from DNA barcoding and metabarcoding datasets

BACKGROUND

Pseudogenes are non-functional copies of protein coding genes that typically follow a different molecular evolutionary path as compared to functional genes. The inclusion of pseudogene sequences in DNA barcoding and metabarcoding analysis can lead to misleading results. None of the most widely used bioinformatic pipelines used to process marker gene (metabarcode) high throughput sequencing data specifically accounts for the presence of pseudogenes in protein-coding marker genes. The purpose of this study is to develop a method to screen for nuclear mitochondrial DNA segments (nuMTs) in large COI datasets. We do this by: (1) describing gene and nuMT characteristics from an artificial COI barcode dataset, (2) show the impact of two different pseudogene removal methods on perturbed community datasets with simulated nuMTs, and (3) incorporate a pseudogene filtering step in a bioinformatic pipeline that can be used to process Illumina paired-end COI metabarcode sequences. Open reading frame length and sequence bit scores from hidden Markov model (HMM) profile analysis were used to detect pseudogenes.

RESULTS

Our simulations showed that it was more difficult to identify nuMTs from shorter amplicon sequences such as those typically used in metabarcoding compared with full length DNA barcodes that are used in the construction of barcode libraries. It was also more difficult to identify nuMTs in datasets where there is a high percentage of nuMTs. Existing bioinformatic pipelines used to process metabarcode sequences already remove some nuMTs, especially in the rare sequence removal step, but the addition of a pseudogene filtering step can remove up to 5% of sequences even when other filtering steps are in place.

CONCLUSIONS

Open reading frame length filtering alone or combined with hidden Markov model profile analysis can be used to effectively screen out apparent pseudogenes from large datasets. There is more to learn from COI nuMTs such as their frequency in DNA barcoding and metabarcoding studies, their taxonomic distribution, and evolution. Thus, we encourage the submission of verified COI nuMTs to public databases to facilitate future studies.

The efficacy of DNA barcoding in the classification, genetic differentiation, and biodiversity assessment of benthic macroinvertebrates

Macroinvertebrates have been recognized as key ecological indicators of aquatic environment and are the most commonly used approaches for water quality assessment. However, species identification of macroinvertebrates (especially of aquatic insects) proves to be very difficult due to the lack of taxonomic expertise in some regions and can become time-consuming. In this study, we evaluated the feasibility of DNA barcoding for the classification of benthic macroinvertebrates and investigated the genetic differentiation in seven orders (Insecta: Ephemeroptera, Plecoptera, Trichoptera, Diptera, Hemiptera, Coleoptera, and Odonata) from four large transboundary rivers of northwest China and further explored its potential application to biodiversity assessment. A total of 1,144 COI sequences, belonging to 176 species, 112 genera, and 53 families were obtained and analyzed. The barcoding gap analysis showed that COI gene fragment yielded significant intra- and interspecific divergences and obvious barcoding gaps. NJ phylogenetic trees showed that all species group into monophyletic species clusters whether from the same population or not, except two species (Polypedilum. laetum and Polypedilum. bullum). The distance-based (ABGD) and tree-based (PTP and MPTP) methods were utilized for grouping specimens into Operational Taxonomic Units (OTUs) and delimiting species. The ABGD, PTP, and MPTP analysis were divided into 177 (p = .0599), 197, and 195 OTUs, respectively. The BIN analysis generated 186 different BINs. Overall, our study showed that DNA barcoding offers an effective framework for macroinvertebrate species identification and sheds new light on the biodiversity assessment of local macroinvertebrates. Also, the construction of DNA barcode reference library of benthic macroinvertebrates in Eurasian transboundary rivers provides a solid backup for bioassessment studies of freshwater habitats using modern high-throughput technologies in the near future.

Biotic signals associated with benthic impacts of salmon farms from eDNA metabarcoding of sediments

Environmental DNA (eDNA) metabarcoding can rapidly characterize the composition and diversity of benthic communities, thus it has high potential utility for routine assessments of benthic impacts of marine finfish farming. In this study, 126 sediment grab samples from 42 stations were collected at six salmon farms in British Columbia, Canada. Benthic community changes were assessed by both eDNA metabarcoding of metazoans and macrofaunal polychaete surveys. The latter was done by analysing 11,466 individuals using a combination of morphology-based taxonomy and DNA barcoding. Study objectives were to: (i) compare biotic signals associated with benthic impacts of salmon farming in the two data sources, and (ii) identify potential eDNA indicators to facilitate monitoring in Canada. Alpha diversity parameters were consistently reduced near fish cage edge and negatively correlated with pore-water sulphide concentration, with coefficients ranging from -0.62 to -0.48. Although Polychaeta are a common indicator group, the negative correlation with pore-water sulphide concentration was much stronger for Nematoda OTU richness (correlation coefficient: -0.86) than for Polychaeta (correlation coefficient: -0.38). Presence/absence of Capitella generally agreed well between the two methods despite that they differed in the volume of sediments sampled and the molecular marker used. Multiple approaches were used to identify OTUs related to organic enrichment statuses. We demonstrate that eDNA metabarcoding generates biotic signals that could be leveraged for environmental assessment of benthic impacts of fish farms in multiple ways: both alpha diversity and Nematoda OTU richness could be used to assess the spatial extent of impact, and OTUs related to organic enrichment could be used to develop local biotic indices.

Integration of DNA-Based Approaches in Aquatic Ecological Assessment Using Benthic Macroinvertebrates

Benthic macroinvertebrates are among the most used biological quality elements for assessing the condition of all types of aquatic ecosystems worldwide (i.e., fresh water, transitional, and marine). Current morphology-based assessments have several limitations that may be circumvented by using DNA-based approaches. Here, we present a comprehensive review of 90 publications on the use of DNA metabarcoding of benthic macroinvertebrates in aquatic ecosystems bioassessments. Metabarcoding of bulk macrozoobenthos has been preferentially used in fresh waters, whereas in marine waters, environmental DNA (eDNA) from sediment and bulk communities from deployed artificial structures has been favored. DNA extraction has been done predominantly through commercial kits, and cytochrome c oxidase subunit I (COI) has been, by far, the most used marker, occasionally combined with others, namely, the 18S rRNA gene. Current limitations include the lack of standardized protocols and broad-coverage primers, the incompleteness of reference libraries, and the inability to reliably extrapolate abundance data. In addition, morphology versus DNA benchmarking of ecological status and biotic indexes are required to allow general worldwide implementation and higher end-user confidence. The increased sensitivity, high throughput, and faster execution of DNA metabarcoding can provide much higher spatial and temporal data resolution on aquatic ecological status, thereby being more responsive to immediate management needs.

Comparison of Larval Fish Detections Using Morphology-Based Taxonomy versus High-Throughput Sequencing for Invasive Species Early Detection

When first introduced, invasive species typically evade detection; DNA barcoding coupled with high-throughput sequencing (HTS) may be more sensitive and accurate than morphology-based taxonomy, and thereby improve invasive (or rare) species detection. We quantified the relative error of species detection between morphology-based and HTS-based taxonomic identification of ichthyoplankton collections from the Port of Duluth, Minnesota, an aquatic non-native species introduction 'hot-spot' in the Laurentian Great Lakes. We found HTS-based taxonomy identified 28 species and morphology-based taxonomy 30 species, of which 27 were common to both. Among samples, 76% of family-level taxonomic assignments agreed; however, only 42% of species assignments agreed. Most errors were attributed to morphology-based taxonomy, whereas HTS-based taxonomy error was low. For this study system, for most non-native fishes, the detection probability by randomized survey for larvae was similar to that by a survey that is optimized for non-native species early detection of juveniles and adults. We conclude that classifying taxonomic errors by comparing HTS results against morphology-based taxonomy is an important step toward incorporating HTS-based taxonomy into biodiversity surveys.

Methodological considerations for monitoring soil/litter arthropods in tropical rainforests using DNA metabarcoding, with a special emphasis on ants, springtails and termites

Robust data to refute or support claims of global insect decline are currently lacking, particularly for the soil fauna in the tropics. DNA metabarcoding represents a powerful approach for rigorous spatial and temporal monitoring of the taxonomically challenging soil fauna. Here, we provide a detailed field protocol, which was successfully applied in Barro Colorado Island (BCI) in Panama, to collect soil samples and arthropods in a tropical rainforest, to be later processed with metabarcoding. We also estimate the proportion of soil/litter ant, springtail and termite species from the local fauna that can be detected by metabarcoding samples obtained either from Berlese-Tullgren (soil samples), Malaise or light traps. Each collecting method detected a rather distinct fauna. Soil and Malaise trap samples detected 213 species (73%) of all target species. Malaise trap samples detected many ant species, whereas soil samples were more efficient at detecting springtail and termite species. With respect to long-term monitoring of soil-dwelling and common species (more amenable to statistical trends), the best combination of two methods were soil and light trap samples, detecting 94% of the total of common species. A protocol including 100 soil, 40 Malaise and 80 light trap samples annually processed by metabarcoding would allow the long-term monitoring of at least 11%, 18% and 16% of species of soil/litter ants, springtails and termites, respectively, present on BCI, and a high proportion of the total abundance (up to 80% of all individuals) represented by these taxa.

Metabarcoding From Microbes to Mammals: Comprehensive Bioassessment on a Global Scale

Global biodiversity loss is unprecedented, and threats to existing biodiversity are growing. Given pervasive global change, a major challenge facing resource managers is a lack of scalable tools to rapidly and consistently measure Earth's biodiversity. Environmental genomic tools provide some hope in the face of this crisis, and DNA metabarcoding, in particular, is a powerful approach for biodiversity assessment at large spatial scales. However, metabarcoding studies are variable in their taxonomic, temporal, or spatial scope, investigating individual species, specific taxonomic groups, or targeted communities at local or regional scales. With the advent of modern, ultra-high throughput sequencing platforms, conducting deep sequencing metabarcoding surveys with multiple DNA markers will enhance the breadth of biodiversity coverage, enabling comprehensive, rapid bioassessment of all the organisms in a sample. Here, we report on a systematic literature review of 1,563 articles published about DNA metabarcoding and summarize how this approach is rapidly revolutionizing global bioassessment efforts. Specifically, we quantify the stakeholders using DNA metabarcoding, the dominant applications of this technology, and the taxonomic groups assessed in these studies. We show that while DNA metabarcoding has reached global coverage, few studies deliver on its promise of near-comprehensive biodiversity assessment. We then outline how DNA metabarcoding can help us move toward real-time, global bioassessment, illustrating how different stakeholders could benefit from DNA metabarcoding. Next, we address barriers to widespread adoption of DNA metabarcoding, highlighting the need for standardized sampling protocols, experts and computational resources to handle the deluge of genomic data, and standardized, open-source bioinformatic pipelines. Finally, we explore how technological and scientific advances will realize the promise of total biodiversity assessment in a sample—from microbes to mammals—and unlock the rich information genomics exposes, opening new possibilities for merging whole-system DNA metabarcoding with (1) abundance and biomass quantification, (2) advanced modeling, such as species occupancy models, to improve species detection, (3) population genetics, (4) phylogenetics, and (5) food web and functional gene analysis. While many challenges need to be addressed to facilitate widespread adoption of environmental genomic approaches, concurrent scientific and technological advances will usher in methods to supplement existing bioassessment tools reliant on morphological and abiotic data. This expanded toolbox will help ensure that the best tool is used for the job and enable exciting integrative techniques that capitalize on multiple tools. Collectively, these new approaches will aid in addressing the global biodiversity crisis we now face.

Morphological vs. DNA metabarcoding approaches for the evaluation of stream ecological status with benthic invertebrates: Testing different combinations of markers and strategies of data filtering

Macroinvertebrate assemblages are the most common bioindicators used for stream biomonitoring, yet the standard approach exhibits several time-consuming steps, including the sorting and identification of organisms based on morphological criteria. In this study, we examined if DNA metabarcoding could be used as an efficient molecular-based alternative to the morphology-based monitoring of streams using macroinvertebrates. We compared results achieved with the standard morphological identification of organisms sampled in 18 sites located on 15 French wadeable streams to results obtained with the DNA metabarcoding identification of sorted bulk material of the same macroinvertebrate samples, using read numbers (expressed as relative frequencies) as a proxy for abundances. In particular, we evaluated how combining and filtering metabarcoding data obtained from three different markers (COI: BF1-BR2, 18S: Euka02 and 16S: Inse01) could improve the efficiency of bioassessment. In total, 140 taxa were identified based on morphological criteria, and 127 were identified based on DNA metabarcoding using the three markers, with an overlap of 99 taxa. The threshold values used for sequence filtering based on the "best identity" criterion and the number of reads had an effect on the assessment efficiency of data obtained with each marker. Compared to single marker results, combining data from different markers allowed us to improve the match between biotic index values obtained with the bulk DNA versus morphology-based approaches. Both approaches assigned the same ecological quality class to a majority (86%) of the site sampling events, highlighting both the efficiency of metabarcoding as a biomonitoring tool but also the need for further research to improve this efficiency.

Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, multi-substrate periphyton collection, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional multi-substrate microhabitat periphyton collections and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton collection and kick-net methodologies or site status, but there was significant difference between diatom communities depending on site (P = 0.042). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms as well as macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes that currently only use the kick-net technique to sample macroinvertebrates.

Harnessing the power of eDNA metabarcoding for the detection of deep-sea fishes

The deep ocean is the largest biome on Earth and faces increasing anthropogenic pressures from climate change and commercial fisheries. Our ability to sustainably manage this expansive habitat is impeded by our poor understanding of its inhabitants and by the difficulties in surveying and monitoring these areas. Environmental DNA (eDNA) metabarcoding has great potential to improve our understanding of this region and to facilitate monitoring across a broad range of taxa. Here, we evaluate two eDNA sampling protocols and seven primer sets for elucidating fish diversity from deep sea water samples. We found that deep sea water samples (> 1400 m depth) had significantly lower DNA concentrations than surface or mid-depth samples necessitating a refined protocol with a larger sampling volume. We recovered significantly more DNA in large volume water samples (1.5 L) filtered at sea compared to small volume samples (250 mL) held for lab filtration. Furthermore, the number of unique sequences (exact sequence variants; ESVs) recovered per sample was higher in large volume samples. Since the number of ESVs recovered from large volume samples was less variable and consistently high, we recommend the larger volumes when sampling water from the deep ocean. We also identified three primer sets which detected the most fish taxa but recommend using multiple markers due the variability in detection probabilities and taxonomic resolution among fishes for each primer set. Overall, fish diversity results obtained from metabarcoding were comparable to conventional survey methods. While eDNA sampling and processing need be optimized for this unique environment, the results of this study demonstrate that eDNA metabarcoding can facilitate biodiversity surveys in the deep ocean, require less dedicated survey effort per unit identification, and are capable of simultaneously providing valuable information on other taxonomic groups.

Drivers of tropical soil invertebrate community composition and richness across tropical secondary forests using DNA metasystematics

Tropical forests are fundamental ecosystems, essential for providing terrestrial primary productivity, global nutrient cycling, and biodiversity. Despite their importance, tropical forests are currently threatened by deforestation and associated activities. Moreover, tropical regions are now mostly represented by secondary forest regrowth, with half of the remaining tropical forests as secondary forest. Soil invertebrates are an important component to the functioning and biodiversity of these soil ecosystems. However, it remains unclear how these past land-use activities and subsequent secondary forest developments have altered the soil invertebrate communities and any potential ecological consequences associated with this. DNA metabarcoding offers an effective approach to rapidly monitor soil invertebrate communities under different land-use practices and within secondary forests. In this study, we used DNA metabarcoding to detect community-based patterns of soil invertebrate composition across a primary forest, a 23-year-old secondary forest, and a 33-year-old secondary forest and the associated soil environmental drivers of the soil invertebrate community structure in the Maquenque National Wildlife Refuge of Costa Rica (MNWR). We also used a species contribution analysis (SIMPER) to determine which soil invertebrate groups may be an indication of these soils reaching a pre-disturbed state such as a primary forest. We found that the soil invertebrate community composition at class, order, family, and ESV level were mostly significantly different across that habitats. We also found that the primary forest had a greater richness of soil invertebrates compared to the 23-year-old and 33-year-old secondary forest. Moreover, a redundancy analysis indicated that soil moisture influenced soil invertebrate community structure and explained up to 22% of the total variation observed in the community composition across the habitats; whereas soil invertebrate richness was structured by soil microbial biomass carbon (C) (Cmic) and explained up to 52% of the invertebrate richness across the primary and secondary forests. Lastly, the SIMPER analysis revealed that Naididae, Entomobryidae, and Elateridae could be important indicators of soil and forest recuperation in the MNWR. This study adds to the increasing evidence that soil invertebrates are intimately linked with the soil microbial biomass carbon (Cmic) and that even after 33 years of natural regrowth of a forest, these land use activities can still have persisting effects on the overall composition and richness of the soil invertebrate communities.

First DNA sequence reference library for mammals and plants of the Eastern Mediterranean Region

The Mediterranean region is identified as one of the world's 36 biodiversity hotspots, with the Earth's most biologically rich yet threatened areas. Lebanon is a hub for Eastern Mediterranean Region (EMR) biodiversity with 9116 characterized plant and animal species (4486 fauna and 4630 flora). Using DNA barcoding as a tool has become crucial in the accurate identification of species in multiple contexts. It can also complement species morphological descriptions, which will add to our understanding of the biodiversity and richness of ecosystems and benefit conservation projects for endangered and endemic species. In this study, we create the first reference library of standard DNA markers for mammals and plants in the EMR, with a focus on endemic and endangered species. Plant leaves were collected from different nature reserves in Mount Lebanon, and mammal samples were obtained from taxidermized museum specimens or road kills. We generated the 12S rRNA sequences of 18 mammal species from 6 orders and 13 different families. We also obtained the trnL and rbcL barcode sequences of 52 plant species from 24 different families. Twenty-five plant species and two mammal species included in this study were sequenced for the first time using these markers.

Assessment of stream macroinvertebrate communities with eDNA is not congruent with tissue-based metabarcoding

Freshwater biomonitoring programmes routinely sample aquatic macroinvertebrates. These samples are time-consuming to collect, as well as challenging and costly to identify reliably genus or species. Environmental DNA (eDNA) metabarcoding has emerged as a surrogate to traditional collection techniques and has been used in whole-community approaches across several taxa and ecosystems. However, the usefulness of eDNA-based detection of freshwater macroinvertebrates has not been extensively explored. Few studies have directly compared bulk sample and eDNA metabarcoding at a local scale to assess how effective each method is at characterizing aquatic macroinvertebrate communities. Here, we collected both eDNA and kicknet samples at the same sample transect locations across nine different streams in southern Ontario, Canada. We observed minimal overlap in community composition between these paired samples. Bulk tissue metabarcoding resulted in a greater proportion of sequences belonging to metazoan taxa (over 99%) than eDNA (12%) and had higher OTU richness for macroinvertebrate taxa. We suggest that degenerate primers are not effective for eDNA metabarcoding due to the high degree of nontarget amplification and subsequently low yield of target DNA. While both bulk sample and eDNA metabarcoding had the power to detect differences between stream communities, eDNA did not represent local communities. Bulk tissue metabarcoding thus provides a more accurate representation of local stream macroinvertebrate communities and is the preferred method if smaller-scale spatial resolution is an important factor in data analyses.

Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams

Taxonomic sufficiency represents the level of taxonomic detail needed to detect ecological patterns to a level that match the requirement of a study. Most bioassessments apply the taxonomic sufficiency concept and assign specimens to the family or genus level given time constraints and the difficulty to correctly identify species. This holds particularly true for stream invertebrates because small and morphologically similar larvae are hard to distinguish. Low taxonomic resolution may hinder detecting true community dynamics, which thus leads to incorrect inferences about community assembly processes. DNA metabarcoding is a new, affordable and cost-effective tool for the identification of multiple species from bulk samples of organisms. As it provides high taxonomic resolution, it can be used to compare results obtained from different identification levels. Measuring the effect of taxonomic resolution on the detection of community dynamics is especially interesting in extreme ecosystems like intermittent streams to test if species at intermittent sites are subsets of those from perennial sources or if independently recruiting taxa exist. Here we aimed to compare the performance of morphological identification and metabarcoding to detect macroinvertebrate community dynamics in the Trebbia River (Italy). Macroinvertebrates were collected from four perennial and two intermittent sites two months after flow resumption and before the next dry phase. The identification level ranged from family to haplotype. Metabarcoding and morphological identifications found similar alpha diversity patterns when looking at family and mixed taxonomic levels. Increasing taxonomic resolution with metabarcoding revealed a strong partitioning of beta diversity in nestedness and turnover components. At flow resumption, beta diversity at intermittent sites was dominated by nestedness when family-level information was employed, while turnover was evidenced as the most important component when using Operational Taxonomic Units (OTUs) or haplotypes. The increased taxonomic resolution with metabarcoding allowed us to detect species adapted to deal with intermittency, like the chironomid Cricotopus bicinctus and the ephemeropteran Cloeon dipterum. Our study thus shows that family and mixed taxonomic level are not sufficient to detect all aspects of macroinvertebrate community dynamics. High taxonomic resolution is especially important for intermittent streams where accurate information about species-specific habitat preference is needed to interpret diversity patterns induced by drying and the nestedness/turnover components of beta diversity are of interest to understand community assembly processes.

Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks

Current approaches to ecological assessment are limited by the traditional morpho-taxonomic methods presently employed and the inability to meet increasing demands for rapid assessments. Advancements in high throughput sequencing now enable rapid high-resolution ecological assessment using environmental DNA (eDNA). Here we test the ability of using eDNA-based ecological assessment methods against traditional assessment of two key indicator groups (diatoms and macroinvertebrates) and show how eDNA across multiple gene regions (COI, rbcL, 12S and 18S) can be used to infer interactive networks that link to ecological assessment criteria. We compared results between taxonomic and eDNA based assessments and found significant positive associations between macroinvertebrate (p < 0.001 R² = 0.645) and diatom (p = 0.015, R² = 0.222) assessment metrics. We further assessed the ability of eDNA based assessment to identify environmentally sensitive genera and found an order of magnitude greater potential for 18S, versus COI or rbcL, to determine environmental filtering of ecologically assessed communities. Lastly, we compared the ability of traditional metrics against co-occurrence network properties of our combined 18S, COI and rbcL indicator genera to infer habitat quality measures currently used by managers. We found that transitivity (network connectivity), linkage density and cohesion were significantly associated with habitat modification scores (HMS), whereas network properties were inconsistent with linking to the habitat quality score (HQS) metric. The incorporation of multi-marker eDNA network assessment opens up a means for finer scale ecological assessment, currently limited using traditional methods. While utilization of eDNA-based assessment is recommended, direct comparisons with traditional approaches are difficult as the methods are intrinsically different and should be treated as such with regards to future research. Overall, our findings show that eDNA can be used for effective ecological assessment while offering a wider range of scope and application compared to traditional assessment methods.

Application of deep learning in aquatic bioassessment: Towards automated identification of non-biting midges

Morphological species identification is often a difficult, expensive, and time-consuming process which hinders the ability for reliable biomonitoring of aquatic ecosystems. An alternative approach is to automate the whole process, accelerating the identification process. Here, we demonstrate an automatic machine-based identification approach for non-biting midges (Diptera: Chironomidae) using Convolutional Neural Networks (CNNs) as a means of increasing taxonomic resolution of biomonitoring data at a minimal cost. Chironomidae were used to build the automatic identifier, as a family of insects that are abundant and ecologically important, yet difficult and time-consuming to accurately identify. The approach was tested with 10 morphologically very similar species from the same genus or subfamilies, comprising 1846 specimens from the South Morava river basin, Serbia. Three CNN models were built utilizing either species, genus, or subfamily data. After training the artificial neural network, images that the network had not seen during the training phase achieved an accuracy of 99.5% for species-level identification, while at the genus and subfamily level all images were correctly assigned (100% accuracy). Gradient-weighted Class Activation Mapping (Grad-CAM) visualized the mentum, ventromental plates, mandibles, submentum, and postoccipital margin to be morphologically important features for CNN classification. Thus, the CNN approach was a highly accurate solution for chironomid identification of aquatic macroinvertebrates opening a new avenue for implementation of artificial intelligence and deep learning methodology in the biomonitoring world. This approach also provides a means to overcome the gap in bioassessment for developing countries where widespread use techniques for routine monitoring are currently limited.

DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness

The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large scales. The Peace-Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification and DNA metabarcoding. By using multispecies occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera and quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were nearly random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

The Ecobiomics project: Advancing metagenomics assessment of soil health and freshwater quality in Canada

Transformative advances in metagenomics are providing an unprecedented ability to characterize the enormous diversity of microorganisms and invertebrates sustaining soil health and water quality. These advances are enabling a better recognition of the ecological linkages between soil and water, and the biodiversity exchanges between these two reservoirs. They are also providing new perspectives for understanding microorganisms and invertebrates as part of interacting communities (i.e. microbiomes and zoobiomes), and considering plants, animals, and humans as holobionts comprised of their own cells as well as diverse microorganisms and invertebrates often acquired from soil and water. The Government of Canada's Genomics Research and Development Initiative (GRDI) launched the Ecobiomics Project to coordinate metagenomics capacity building across federal departments, and to apply metagenomics to better characterize microbial and invertebrate biodiversity for advancing environmental assessment, monitoring, and remediation activities. The Project has adopted standard methods for soil, water, and invertebrate sampling, collection and provenance of metadata, and nucleic acid extraction. High-throughput sequencing is located at a centralized sequencing facility. A centralized Bioinformatics Platform was established to enable a novel government-wide approach to harmonize metagenomics data collection, storage and bioinformatics analyses. Sixteen research projects were initiated under Soil Microbiome, Aquatic Microbiome, and Invertebrate Zoobiome Themes. Genomic observatories were established at long-term environmental monitoring sites for providing more comprehensive biodiversity reference points to assess environmental change.

Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

Towards conserving natural diversity: A biotic inventory by observations, specimens, DNA barcoding and high-throughput sequencing methods

The Kenai National Wildlife Refuge has been given a broad conservation mandate to conserve natural diversity. A prerequisite for fulfilling this purpose is to be able to identify the species and communities that make up that biodiversity. We tested a set of varied methods for inventory and monitoring of plants, birds and terrestrial invertebrates on a grid of 40 sites in a 938 ha study area in the Slikok Creek watershed, Kenai Peninsula, Alaska. We sampled plants and lichens through observation and specimen-based methods. We surveyed birds using bird call surveys on variable circular plots. We sampled terrestrial arthropods by sweep net sampling, processing samples with High Throughput Sequencing methods. We surveyed for earthworms, using the hot mustard extraction method and identified worm specimens by morphology and DNA barcoding. We examined community membership using clustering methods and Nonmetric Multidimensional Scaling. We documented a total of 4,764 occurrences of 984 species and molecular operational taxonomic units: 87 vascular plants, 51 mosses, 12 liverworts, 111 lichens, 43 vertebrates, 663 arthropods, 9 molluscs and 8 annelid worms. Amongst these records, 102 of the arthropod species appeared to be new records for Alaska. We found three non-native species: Deroceras agreste (Linnaeus, 1758) (Stylommatophora: Agriolimacidae), Dendrobaena octaedra (Savigny, 1826) (Crassiclitellata: Lumbricidae) and Heterarthrus nemoratus (Fallén, 1808) (Hymenoptera: Tenthredinidae). Both D. octaedra and H. nemoratus were found at sites distant from obvious human disturbance. The 40 sites were grouped into five community groups: upland mixed forest, black spruce forest, open deciduous forest, shrub-sedge bog and willow. We demonstrated that, at least for a subset of species that could be detected using these methods, we were able to document current species distributions and assemblages in a way that could be efficiently repeated for the purposes of biomonitoring. While our methods could be improved and additional methods and groups could be added, our combination of techniques yielded a substantial portion of the data necessary for fulfilling Kenai National Wildlife Refuge's broad conservation purposes.

Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics

Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of Drosophila included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.

Increased performance of DNA metabarcoding of macroinvertebrates by taxonomic sorting

DNA-based identification through the use of metabarcoding has been proposed as the next step in the monitoring of biological communities, such as those assessed under the Water Framework Directive (WFD). Advances have been made in the field of metabarcoding, but challenges remain when using complex samples. Uneven biomass distributions, preferential amplification and reference database deficiencies can all lead to discrepancies between morphological and DNA-based taxa lists. The effects of different taxonomic groups on these issues remain understudied. By metabarcoding WFD monitoring samples, we analyzed six different taxonomic groups of freshwater organisms, both separately and combined. Identifications based on metabarcoding data were compared directly to morphological assessments performed under the WFD. The diversity of taxa for both morphological and DNA-based assessments was similar, although large differences were observed in some samples. The overlap between the two taxon lists was 56.8% on average across all taxa, and was highest for Crustacea, Heteroptera, and Coleoptera, and lowest for Annelida and Mollusca. Taxonomic sorting in six basic groups before DNA extraction and amplification improved taxon recovery by 46.5%. The impact on ecological quality ratio (EQR) scoring was considerable when replacing morphology with DNA-based identifications, but there was a high correlation when only replacing a single taxonomic group with molecular data. Different taxonomic groups provide their own challenges and benefits. Some groups might benefit from a more consistent and robust method of identification. Others present difficulties in molecular processing, due to uneven biomass distributions, large genetic diversity or shortcomings of the reference database. Sorting samples into basic taxonomic groups that require little taxonomic knowledge greatly improves the recovery of taxa with metabarcoding. Current standards for EQR monitoring may not be easily replaced completely with molecular strategies, but the effectiveness of molecular methods opens up the way for a paradigm shift in biomonitoring.

Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples

Biomonitoring programs have evolved beyond the sole use of morphological identification to determine the composition of invertebrate species assemblages in an array of ecosystems. The application of DNA metabarcoding in freshwater systems for assessing benthic invertebrate communities is now being employed to generate biological information for environmental monitoring and assessment. A possible shift from the extraction of DNA from net-collected bulk benthic samples to its extraction directly from water samples for metabarcoding has generated considerable interest based on the assumption that taxon detectability is comparable when using either method. To test this, we studied paired water and benthos samples from a taxon-rich wetland complex, to investigate differences in the detection of arthropod taxa from each sample type. We demonstrate that metabarcoding of DNA extracted directly from water samples is a poor surrogate for DNA extracted from bulk benthic samples, focusing on key bioindicator groups. Our results continue to support the use of bulk benthic samples as a basis for metabarcoding-based biomonitoring, with nearly three times greater total richness in benthic samples compared to water samples. We also demonstrated that few arthropod taxa are shared between collection methods, with a notable lack of key bioindicator EPTO taxa in the water samples. Although species coverage in water could likely be improved through increased sample replication and/or increased sequencing depth, benthic samples remain the most representative, cost-effective method of generating aquatic compositional information via metabarcoding.

Validation of COI metabarcoding primers for terrestrial arthropods

Metabarcoding can rapidly determine the species composition of bulk samples and thus aids biodiversity and ecosystem assessment. However, it is essential to use primer sets that minimize amplification bias among taxa to maximize species recovery. Despite this fact, the performance of primer sets employed for metabarcoding terrestrial arthropods has not been sufficiently evaluated. This study tests the performance of 36 primer sets on a mock community containing 374 insect species. Amplification success was assessed with gradient PCRs and the 21 most promising primer sets selected for metabarcoding. These 21 primer sets were also tested by metabarcoding a Malaise trap sample. We identified eight primer sets, mainly those including inosine and/or high degeneracy, that recovered more than 95% of the species in the mock community. Results from the Malaise trap sample were congruent with the mock community, but primer sets generating short amplicons produced potential false positives. Taxon recovery from both mock community and Malaise trap sample metabarcoding were used to select four primer sets for additional evaluation at different annealing temperatures (40-60 °C) using the mock community. The effect of temperature varied by primer pair but overall it only had a minor effect on taxon recovery. This study reveals the weak performance of some primer sets employed in past studies. It also demonstrates that certain primer sets can recover most taxa in a diverse species assemblage. Thus, based our experimental set up, there is no need to employ several primer sets targeting the same gene region. We identify several suitable primer sets for arthropod metabarcoding, and specifically recommend BF3 + BR2, as it is not affected by primer slippage and provides maximal taxonomic resolution. The fwhF2 + fwhR2n primer set amplifies a shorter fragment and is therefore ideal when targeting degraded DNA (e.g., from gut contents).

Establishing arthropod community composition using metabarcoding: Surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches

DNA metabarcoding allows the analysis of insect communities faster and more efficiently than ever before. However, metabarcoding can be conducted through several approaches, and the consistency of results across methods has rarely been studied. We compare the results obtained by DNA metabarcoding of the same communities using two different markers – COI and 16S – and three different sampling methods: (a) homogenized Malaise trap samples (homogenate), (b) preservative ethanol from the same samples, and (c) soil samples. Our results indicate that COI and 16S offer partly complementary information on Malaise trap samples, with each marker detecting a significant number of species not detected by the other. Different sampling methods offer highly divergent estimates of community composition. The community recovered from preservative ethanol of Malaise trap samples is significantly different from that recovered from homogenate. Small and weakly sclerotized insects tend to be overrepresented in ethanol while strong and large taxa are overrepresented in homogenate. For soil samples, highly degenerate COI primers pick up large amounts of nontarget DNA and only 16S provides adequate analyses of insect diversity. However, even with 16S, very little overlap in molecular operational taxonomic unit (MOTU) content was found between the trap and the soil samples. Our results demonstrate that none of the tested sampling approaches is satisfactory on its own. For instance, DNA extraction from preservative ethanol is not a valid replacement for destructive bulk extraction but a complement. In future metabarcoding studies, both should ideally be used together to achieve comprehensive representation of the target community.