Is DNA barcoding actually cheaper and faster than traditional morphological methods: results from a survey of freshwater bioassessment efforts in the United States?

An analysis of morphological and genetic diversity of mango fruit flies in Pakistan

Fruit flies of genus Bactrocera are important insect pests of commercially cultivated mangos in Pakistan limiting its successful production in the country. Despite the economic risk, the genetic diversity and population dynamics of this pest have remained unexplored. This study aimed to morphologically identify Bactrocera species infesting Mango in major production areas of the country and to confirm the results with insect DNA barcode techniques. Infested mango fruits from the crop of 2022, were collected from 46 locations of 11major production districts of Punjab and Sindh provinces, and first-generation flies were obtained in the laboratory. All 10,653 first generation flies were morphologically identified as two species of Bactrocera; dorsalis and zonata showing geography-based relative abundance in the two provinces; Punjab and Sindh. Morphological identification was confirmed by mitochondrial cytochrome oxidase gene subunit I (mt-COI) based DNA barcoding. Genetic analysis of mtCOI gene region of 61 selected specimens by the presence of two definite clusters and reliable intraspecific distances validated the results of morphological identification. This study by morphological identification of a large number of fruit fly specimens from the fields across Pakistan validated by insect DNA barcode reports two species of Bactrocera infesting mango in the country.

Towards global insect biomonitoring with frugal methods

None of the global targets for protecting nature are currently met, although humanity is critically dependent on biodiversity. A significant issue is the lack of data for most biodiverse regions of the planet where the use of frugal methods for biomonitoring would be particularly important because the available funding for monitoring is insufficient, especially in low-income countries. We here discuss how three approaches to insect biomonitoring (computer vision, lidar, DNA sequences) could be made more frugal and urge that all biomonitoring techniques should be evaluated for global suitability before becoming the default in high-income countries. This requires that techniques popular in high-income countries should undergo a phase of 'innovation through simplification' before they are implemented more broadly. We predict that techniques that acquire raw data at low cost and are suitable for analysis with AI (e.g. images, lidar-signals) will be particularly suitable for global biomonitoring, while techniques that rely heavily on patented technologies may be less promising (e.g. DNA sequences). We conclude the opinion piece by pointing out that the widespread use of AI for data analysis will require a global strategy for providing the necessary computational resources and training. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Towards harmonized standards for freshwater biodiversity monitoring and biological assessment using benthic macroinvertebrates

Monitoring programs at sub-national and national scales lack coordination, harmonization, and systematic review and analysis at continental and global scales, and thus fail to adequately assess and evaluate drivers of biodiversity and ecosystem degradation and loss at large spatial scales. Here we review the state of the art, gaps and challenges in the freshwater assessment programs for both the biological condition (bioassessment) and biodiversity monitoring of freshwater ecosystems using the benthic macroinvertebrate community. To assess the existence of nationally- and regionally- (sub-nationally-) accepted freshwater benthic macroinvertebrate protocols that are put in practice/used in each country, we conducted a survey from November 2022 to May 2023. Responses from 110 respondents based in 67 countries were received. Although the responses varied in their consistency, the responses clearly demonstrated a lack of biodiversity monitoring being done at both national and sub-national levels for lakes, rivers and artificial waterbodies. Programs for bioassessment were more widespread, and in some cases even harmonized among several countries. We identified 20 gaps and challenges, which we classed into five major categories, these being (a) field sampling, (b) sample processing and identification, (c) metrics and indices, (d) assessment, and (e) other gaps and challenges. Above all, we identify the lack of harmonization as one of the most important gaps, hindering efficient collaboration and communication. We identify the IUCN SSC Global Freshwater Macroinvertebrate Sampling Protocols Task Force (GLOSAM) as a means to address the lack of globally-harmonized biodiversity monitoring and biological assessment protocols.

Assessing the relevance of DNA metabarcoding compared to morphological identification for lake phytoplankton monitoring

Phytoplankton is a key biological group used to assess the ecological status of lakes. The classical monitoring approach relies on microscopic identification and counting of phytoplankton species, which is time-consuming and requires high taxonomic expertise. High-throughput sequencing, combined with metabarcoding, has recently demonstrated its potential as an alternative approach for plankton surveys. Several studies have confirmed the relevance of the diatom metabarcoding approach to calculate biotic indices based on species ecology. However, phytoplankton communities have not yet benefited from such validation. Here, by comparing the results obtained with the two methods (molecular and microscopic counting), we evaluated the relevance of metabarcoding approach for phytoplankton monitoring by considering different metrics: alpha diversity, taxonomic composition, community structure and a phytoplankton biotic index used to assess the trophic level of lakes. For this purpose, 55 samples were collected in four large alpine lakes (Aiguebelette, Annecy, Bourget, Geneva) during the year 2021. For each sample, a metabarcoding analysis based on two genetic markers (16S and 23S rRNA) was performed, in addition to the microscopic count. Regarding the trophic level of lakes, significant differences were found between index values obtained with the two approaches. The main hypothesis to explain these differences comes from the incompleteness, particularly at the species level, of the barcode reference library for the two genetic markers. It is therefore necessary to complete reference libraries for using such species-based biotic indices with metabarcoding data. Besides this, species richness and diversity were higher in the molecular inventories than in the microscopic ones. Moreover, despite differences in taxonomic composition of the floristic lists obtained by the two approaches, their community structures were similar. These results support the possibility of using metabarcoding for phytoplankton monitoring but in a different way. We suggest exploring alternative approaches to index development, such as a taxonomy-free approach.

Metabarcoding is (usually) more cost effective than seining or qPCR for detecting tidewater gobies and other estuarine fishes

Many studies have shown that environmental DNA (eDNA) sampling can be more sensitive than traditional sampling. For instance, past studies found a specific qPCR probe of a water sample is better than a seine for detecting the endangered northern tidewater goby, Eucyclogobius newberryi. Furthermore, a metabarcoding sample often detects more fish species than a seine detects. Less consideration has been given to sampling costs. To help managers choose the best sampling method for their budget, I estimated detectability and costs per sample to compare the cost effectiveness of seining, qPCR and metabarcoding for detecting endangered tidewater gobies as well as the associated estuarine fish community in California. Five samples were enough for eDNA methods to confidently detect tidewater gobies, whereas seining took twice as many samples. Fixed program costs can be high for qPCR and seining, whereas metabarcoding had high per-sample costs, which led to changes in relative cost-effectiveness with the number of locations sampled. Under some circumstances (multiple locations visited or an already validated assay), qPCR was a bit more cost effective than metabarcoding for detecting tidewater gobies. Under all assumptions, seining was the least cost-effective method for detecting tidewater gobies or other fishes. Metabarcoding was the most cost-effective sampling method for multiple species detection. Despite its advantages, metabarcoding has gaps in sequence databases, can yield vague results for some species, and can lead novices to serious errors. Seining remains the only way to rapidly assess densities, size distributions, and fine-scale spatial distributions.

DNA barcoding for the assessment of marine and coastal fish diversity from the Coast of Mozambique

The ichthyological provinces of Mozambique are understudied hotspots of global fish diversity. In this study, we applied DNA barcoding to identify the composition of the fish fauna from the coast of Mozambique. A total of 143 species belonging to 104 genera, 59 families, and 30 orders were identified. The overall K2P distance of the COI sequences within species ranged from 0.00% to 1.51%, while interspecific distances ranged from 3.64% to 24.49%. Moreover, the study revealed 15 threatened species according to the IUCN Red List of Threatened Species, with elasmobranchs being the most represented group. Additionally, the study also uncovered four new species that were not previously recorded in this geographic area, including Boleophthalmus dussumieri, Maculabatis gerrardi, Hippocampus kelloggi, and Lethrinus miniatus. This study represents the first instance of utilizing molecular references to explore the fish fauna along the Mozambican coast. Our results indicate that DNA barcoding is a dependable technique for the identification and delineation of fish species in the waters of Mozambique. The DNA barcoding library established in this research will be an invaluable asset for advancing the understanding of fish diversity and guiding future conservation initiatives.

Identification of hybrids between the Japanese giant salamander (Andrias japonicus) and Chinese giant salamander (Andrias cf. davidianus) using deep learning and smartphone images

Human-mediated hybridization between native and non-native species is causing biodiversity loss worldwide. Hybridization has contributed to the extinction of many species through direct and indirect processes such as loss of reproductive opportunity and genetic introgression. Therefore, it is essential to manage hybrids to conserve biodiversity. However, specialized knowledge is required to identify the target species based on visual characteristics when two species have similar features. Although image recognition technology can be a powerful tool for identifying hybrids, studies have yet to utilize deep learning approaches. Hence, this study aimed to identify hybrids between the native Japanese giant salamander (Andrias japonicus) and the non-native Chinese giant salamander (Andrias cf. davidianus) using EfficientNetV2 and smartphone images. We used smartphone images of 11 individuals of native A. japonicus (five training and six test images) and 20 individuals of hybrids between A. japonicus and A. cf. davidianus (five training and 15 test images). In our experimental environment, an AI model constructed with EfficientNetV2 exhibited 100% accuracy in identifying hybrids. In addition, gradient-weighted class activation mapping revealed that the AI model was able to classify A. japonicus and hybrids between A. japonicus and A. cf. davidianus on the basis of the dorsal head spot patterning. Our approach thus enables the identification of hybrids against A. japonicus, which was previously considered difficult by non-experts. Furthermore, since this study achieved reliable identification using smartphone images, it is expected to be applied to a wide range of citizen science projects.

Diversity of eukaryotic and prokaryotic microbiota revealed by metabarcoding in Neotropical floodplain lakes

The diversity of eukaryotic and prokaryotic communities has been assessed by morphological and genetic approaches, which are used to characterize the microbiota in different environments. Here, planktonic prokaryotic and eukaryotic communities of the Araguaia River, located in the Central region of Brazil, were analyzed based on metabarcoding analysis of rRNA genes to evaluate the diversity of these groups in tropical floodplain lakes. Also, we tested their spatial concordance throughout the Araguaia river. Water samples were collected from 8 floodplain lakes in Araguaia River. The 16S and 18S rRNA genes were amplified and sequenced using Illumina MiSeq. For eukaryotes, 34,242 merged reads were obtained and 225 distinct OTUs were delineated, of which 106 OTUs were taxonomically classified. For prokaryotes, 26,426 sequences were obtained and 351 OTUs were detected. Of them, 231 were classified in at least one taxonomic category. The most representative eukaryotes belonged to Ciliophora, Chlorophyta and Charophyta. The prokaryotic phylum with the most OTUs classified were Proteobacteria, Actinobacteria and Bacteroidetes. The lakes did not show spatial concordance when comparing the similarity between their microbiota. The knowledge of freshwater biodiversity using DNA sequencing for important rivers, such as Araguaia River, can improve microbiota inventories of tropical biodiversity hotspots.

Haplotype-level metabarcoding of freshwater macroinvertebrate species: A prospective tool for population genetic analysis

Metabarcoding is a molecular-based tool capable of large quantity high-throughput species identification from bulk samples that is a faster and more cost-effective alternative to conventional DNA-sequencing approaches. Still, further exploration and assessment of the laboratory and bioinformatics strategies are required to unlock the potential of metabarcoding-based inference of haplotype information. In this study, we assessed the inference of freshwater macroinvertebrate haplotypes from metabarcoding data in a mock sample. We also examined the influence of DNA template concentration and PCR cycle on detecting true and spurious haplotypes. We tested this strategy on a mock sample containing twenty individuals from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. We recovered fourteen zero-radius operational taxonomic units (zOTUs) of 421-bp length, with twelve zOTUs having a 100% match with the Sanger haplotype sequences. High-quality reads relatively increased with increasing PCR cycles, and the relative abundance of each zOTU was consistent for each cycle. This suggests that increasing the PCR cycles from 24 to 64 did not affect the relative abundance of each zOTU. As metabarcoding becomes more established and laboratory protocols and bioinformatic pipelines are continuously being developed, our study demonstrated the method's ability to infer intraspecific variability while highlighting the challenges that must be addressed before its eventual application for population genetic studies.

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.

DNA High-Throughput Sequencing for Arthropod Gut Content Analysis to Evaluate Effectiveness and Safety of Biological Control Agents

The search for effective biological control agents without harmful non-target effects has been constrained by the use of impractical (field direct observation) or imprecise (cage experiments) methods. While advances in the DNA sequencing methods, more specifically the development of high-throughput sequencing (HTS), have been quickly incorporated in biodiversity surveys, they have been slow to be adopted to determine arthropod prey range, predation rate and food web structure, and critical information to evaluate the effectiveness and safety of a biological control agent candidate. The lack of knowledge on how HTS methods could be applied by ecological entomologists constitutes part of the problem, although the lack of expertise and the high cost of the analysis also are important limiting factors. In this review, we describe how the latest HTS methods of metabarcoding and Lazaro, a method to identify prey by mapping unassembled shotgun reads, can serve biological control research, showing both their power and limitations. We explain how they work to determine prey range and also how their data can be used to estimate predation rates and subsequently be translated into food webs of natural enemy and prey populations helping to elucidate their role in the community. We present a brief history of prey detection through molecular gut content analysis and also the attempts to develop a more precise formula to estimate predation rates, a problem that still remains. We focused on arthropods in agricultural ecosystems, but most of what is covered here can be applied to natural systems and non-arthropod biological control candidates as well.

Are genomic indices effective alternatives to morphology based benthic indices in biomonitoring studies? Perspectives from a major harbour and marine protected area

Ecological assessments are currently being conducted by traditional morpho-taxonomical identification techniques that are time-consuming and often inaccurate. Biomonitoring programs are increasingly being complemented by the more rapid and efficient DNA barcoding approach. We compared the congruency of morpho-taxonomic (AMBI - AZTI's Marine Biotic Index) and genomic (gAMBI) benthic indices in ecological quality status (EcoQS) assignation in Mumbai harbour and Malvan Marine Protected area (MPA). The study, first of its kind to adopt the gAMBI tool in the selected milieu, contributed substantial number of macrobenthic cytochrome c oxidase subunit I gene (COI) sequences that were previously unavailable in the reference library, adding sufficient genetic resources for establishing ecostatus. AMBI and gAMBI values based on presence/absence data related significantly with those derived from abundance data matrices. Taxonomic and genomic indices derived ecostatus corresponded sufficiently well despite minor discrepancies, underscoring the viability of gAMBI as a superior alternative to AMBI in monitoring studies.

Multilocus DNA metabarcoding diet analyses of small cetaceans: a case study on highly vulnerable humpback dolphins and finless porpoises from the Pearl River Estuary, China

Accurate diet identification of top predators is crucial to fully understand their ecological roles. Compared to terrestrial animals, gathering dietary information from cetaceans is notoriously difficult. Here, we applied a multilocus metabarcoding approach to investigate the diet of vulnerable Indo-Pacific humpback dolphins and Indo-Pacific finless porpoises from the Pearl River Estuary (PRE), China. Our analyses identified 21 prey fish species from the 42 humpback dolphin stomachs, as well as 10 species of fish and 1 species of cephalopod from the 13 finless porpoise stomachs. All of the taxa were assigned to the species level, highlighting that the multimarker approach could facilitate species identification. Most of the prey species were small- and medium-sized fishes that primarily fed on zooplankton. The calculated similarity index revealed a moderated dietary overlap between the 2 cetaceans, presumably due to the feeding of the 2 predators in association with fishing vessels in the PRE. A more diverse diet was observed in humpback dolphins in the closed fishing season compared to the fishing season, implying the influence on the dolphin diet due to the availability of commercial fishery resources. However, according to the results of species rarefaction curves, our findings on the feeding habits of the 2 cetaceans are still limited by insufficient sample size and therefore should be interpreted with caution. This study represents a first attempt to apply the multilocus DNA metabarcoding technique in the diet analysis of small cetaceans, although more efforts are needed to improve this type of analysis.

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.

Drivers of Spatiotemporal Eukaryote Plankton Distribution in a Trans-Basin Water Transfer Canal in China

Planktonic eukaryotes are important components of aquatic ecosystems, and analyses of the whole eukaryotic planktonic community composition and function have far-reaching significance for water resource management. We aimed to understand the spatiotemporal variation and drivers of eukaryotic plankton distribution in the Middle Route Project of the South-to-North Water Diversion in Henan Province, China. Specifically, we examined planktonic assemblages and water quality at five stations along the canal and another one located before the dam in March, June, September, and December 2019. High-throughput sequencing revealed that the eukaryotic plankton community was primarily composed of 53 phyla, 200 genera, and 277 species, with Cryptophyta, Ciliophora, and norank_k_Cryptophyta being the dominant phyla. Redundancy analysis of the eukaryotic community and environmental factors showed that five vital factors affecting eukaryotic plankton distribution were oxidation-reduction potential, nitrate nitrogen, pH, total phosphorus, and water flow velocity. Furthermore, the geographical distribution of eukaryotic communities was consistent with the distance decay model. Importantly, environmental selection dominantly shaped the geographical distribution of the eukaryotic community. In summary, our study elucidates the ecological response of planktonic eukaryotes by identifying the diversity and ecological distribution of planktonic eukaryotes in trans-basin diversion channels.

Lack of Statistical Rigor in DNA Barcoding Likely Invalidates the Presence of a True Species' Barcode Gap

DNA barcoding has been largely successful in satisfactorily exposing levels of standing genetic diversity for a wide range of taxonomic groups through the employment of only one or a few universal gene markers. However, sufficient coverage of geographically-broad intra-specific haplotype variation within genomic databases like the Barcode of Life Data Systems (BOLD) and GenBank remains relatively sparse. As reference sequence libraries continue to grow exponentially in size, there is now the need to identify novel ways of meaningfully analyzing vast amounts of available DNA barcode data. This is an important issue to address promptly for the routine tasks of specimen identification and species discovery, which have seen broad adoption in areas as diverse as regulatory forensics and resource conservation. Here, it is demonstrated that the interpretation of DNA barcoding data is lacking in statistical rigor. To highlight this, focus is set specifically on one key concept that has become a household name in the field: the DNA barcode gap. Arguments outlined herein specifically center on DNA barcoding in animal taxa and stem from three angles: (1) the improper allocation of specimen sampling effort necessary to capture adequate levels of within-species genetic variation, (2) failing to properly visualize intra-specific and interspecific genetic distances, and (3) the inconsistent, inappropriate use, or absence of statistical inferential procedures in DNA barcoding gap analyses. Furthermore, simple statistical solutions are outlined which can greatly propel the use of DNA barcoding as a tool to irrefutably match unknowns to knowns on the basis of the barcoding gap with a high degree of confidence. Proposed methods examined herein are illustrated through application to DNA barcode sequence data from Canadian Pacific fish species as a case study.

A comparison of genetically and morphometrically identified macroinvertebrate community index scores with implications for aquatic life use attainment

Measures of aquatic macroinvertebrate communities are often used to characterize water quality and indicate whether waterbodies are meeting management expectations. The accuracy of these measures depends on the skill and experience of the person identifying the macroinvertebrates, and obtaining these measures can be relatively expensive due to the time necessary for identification. Utilizing genetic identification of macroinvertebrate taxa has the potential to reduce the time of sample processing, identify a greater number of taxa, and increase the resolution of identification. We compared Colorado multi-metric index (MMI) scores from seven locations in the Big Thompson River, CO, based on genetic and morphometric identification and estimated the ability of MMI scores based on genetic identification to characterize aquatic life use attainment management thresholds. We found a significant linear relationship (p = 0.002, R² = 0.87) between MMI scores generated by genetic and morphological identification. MMIs support the following aquatic life use designations as defined by the Colorado Water Quality Control Commission: Impaired < 40, Attaining > 48, and Ambiguous 40-48. These values correspond to MMIs based on genetic identification as Impaired < 20, Attaining > 64, and Ambiguous = 21-63 based on the prediction interval of the regression equation. Our results suggest that using genetically identified macroinvertebrates to estimate MMI scores can provide some degree of certainty regarding aquatic life use designations, and while it may be inappropriate at the current time to entirely replace morphologically based biotic integrity measures with those based on molecular identification, there are opportunities in their use.

Hyperspectral data as a biodiversity screening tool can differentiate among diverse Neotropical fishes

Hyperspectral data encode information from electromagnetic radiation (i.e., color) of any object in the form of a spectral signature; these data can then be used to distinguish among materials or even map whole landscapes. Although hyperspectral data have been mostly used to study landscape ecology, floral diversity and many other applications in the natural sciences, we propose that spectral signatures can be used for rapid assessment of faunal biodiversity, akin to DNA barcoding and metabarcoding. We demonstrate that spectral signatures of individual, live fish specimens can accurately capture species and clade-level differences in fish coloration, specifically among piranhas and pacus (Family Serrasalmidae), fishes with a long history of taxonomic confusion. We analyzed 47 serrasalmid species and could distinguish spectra among different species and clades, with the method sensitive enough to document changes in fish coloration over ontogeny. Herbivorous pacu spectra were more like one another than they were to piranhas; however, our method also documented interspecific variation in pacus that corresponds to cryptic lineages. While spectra do not serve as an alternative to the collection of curated specimens, hyperspectral data of fishes in the field should help clarify which specimens might be unique or undescribed, complementing existing molecular and morphological techniques.

DNA barcodes enable higher taxonomic assignments in the Acari

Although mites (Acari) are abundant in many terrestrial and freshwater ecosystems, their diversity is poorly understood. Since most mite species can be distinguished by variation in the DNA barcode region of cytochrome c oxidase I, the Barcode Index Number (BIN) system provides a reliable species proxy that facilitates large-scale surveys. Such analysis reveals many new BINs that can only be identified as Acari until they are examined by a taxonomic specialist. This study demonstrates that the Barcode of Life Datasystem's identification engine (BOLD ID) generally delivers correct ordinal and family assignments from both full-length DNA barcodes and their truncated versions gathered in metabarcoding studies. This result was demonstrated by examining BOLD ID's capacity to assign 7021 mite BINs to their correct order (4) and family (189). Identification success improved with sequence length and taxon coverage but varied among orders indicating the need for lineage-specific thresholds. A strict sequence similarity threshold (86.6%) prevented all ordinal misassignments and allowed the identification of 78.6% of the 7021 BINs. However, higher thresholds were required to eliminate family misassignments for Sarcoptiformes (89.9%), and Trombidiformes (91.4%), consequently reducing the proportion of BINs identified to 68.6%. Lineages with low barcode coverage in the reference library should be prioritized for barcode library expansion to improve assignment success.

Barcoding pest species in a biodiversity hot-spot: the South African polyphagous broad-nosed weevils (Coleoptera, Curculionidae, Entiminae)

Polyphagous broad nosed weevils (Curculionidae: Entiminae) constitute a large and taxonomically challenging subfamily that contains economically significant agricultural pests worldwide. South Africa is a hot-spot for biodiversity and several species of indigenous and endemic genera of Entiminae have shifted on to cultivated plants, with some being phytosanitary pests. The sporadic pest status of many species (where the species has an occasional economic impact on the agricultural industry, but is not encountered often enough that is is readily recognisable by researchers and agricultural extension workers) and the presence of pest complexes and cryptic species represent an identification challenge to non-specialists. Furthermore, no comprehensive identification tools exist to identify immature stages that may be found in crops/soil. In this paper, a curated barcoding database with 70 COI sequences from 41 species (39 Entiminae, 2 Cyclominae) is initiated, to assist with the complexity of identification of species in this group.

Choosing an Effective PCR-Based Approach for Diet Analysis of Insect Herbivores: A Systematic Review

Identification of ingested plant species using polymerase chain reaction (PCR)-based methods is an increasingly useful yet challenging approach to accurately determine the diet composition of insect herbivores and thus their trophic interactions. A typical process of detection of DNA of ingested plants involves the choice of a DNA extraction method, a genomic target region, and/or the best approach for an accurate plant species identification. The wide range of available techniques makes the choice of the most appropriate method for an accurately and timely identification of ingested plants from insect guts difficult. In our study, we reviewed the commonly used PCR-based approaches in studies published from 1977 to 2019, to provide researchers with the information on the tools which have been shown to be effective for obtaining and identifying ingested plants. Our results showed that among five insect orders used in the retrieved studies Coleoptera and Hemiptera were prevalent (33 and 28% of all the records, respectively). In 79% of the studies a DNA barcoding approach was employed. In a substantial number of studies Qiagen DNA extraction kits and CTAB protocol were used (43 and 23%, respectively). Of all records, 65% used a single locus as a targeted plant DNA fragment; trnL, rbcL, and ITS regions were the most frequently used loci. Sequencing was the dominant type of among DNA verification approaches (70% of all records). This review provides important information on the availability of successfully used PCR-based approaches to identify ingested plant DNA in insect guts, and suggests potential directions for future studies on plant-insect trophic interactions.

Molecular diversity within the genus Laeonereis (Annelida, Nereididae) along the west Atlantic coast: paving the way for integrative taxonomy

The polychaete genus Laeonereis (Annelida, Nereididae) occurs over a broad geographic range and extends nearly across the entire Atlantic coast of America, from the USA to Uruguay. Despite the research efforts to clarify its diversity and systematics, mostly by morphological and ecological evidence, there is still uncertainty, mainly concerning the species Laeonereis culveri, which constitutes an old and notorious case of taxonomic ambiguity. Here, we revised the molecular diversity and distribution of Laeonereis species based on a multi-locus approach, including DNA sequence analyses of partial segments of the cytochrome c oxidase subunit I (COI), 16S rRNA, and 28S rRNA genes. We examined Laeonereis specimens collected from 26 sites along the American Atlantic coast from Massachusetts (USA) to Mar del Plata (Argentina). Although no comprehensive morphological examination was performed between different populations, the COI barcodes revealed seven highly divergent MOTUs, with a mean K2P genetic distance of 16.9% (from 6.8% to 21.9%), which was confirmed through four clustering algorithms. All MOTUs were geographically segregated, except for MOTUs 6 and 7 from southeastern Brazil, which presented partially overlapping ranges between Rio de Janeiro and São Paulo coast. Sequence data obtained from 16S rRNA and 28S rRNA markers supported the same MOTU delimitation and geographic segregation as those of COI, providing further evidence for the existence of seven deeply divergent lineages within the genus. The extent of genetic divergence between MOTUs observed in our study fits comfortably within the range reported for species of polychaetes, including Nereididae, thus providing a strong indication that they might constitute separate species. These results may therefore pave the way for integrative taxonomic studies, aiming to clarify the taxonomic status of the Laeonereis MOTUs herein reported.

Using near-infrared spectroscopy to discriminate closely related species: a case study of neotropical ferns

Identifying plant species requires considerable knowledge and can be difficult without complete specimens. Fourier-transform near-infrared spectroscopy (FT-NIR) is an effective technique for discriminating plant species, especially angiosperms. However, its efficacy has never been tested on ferns. Here we tested the accuracy of FT-NIR at discriminating species of the genus Microgramma. We obtained 16 spectral readings per individual from the adaxial and abaxial surfaces of 100 specimens belonging to 13 species. The analyses included all 1557 spectral variables. We tested different datasets (adaxial + abaxial, adaxial, and abaxial) to compare the correct identification of species through the construction of discriminant models (Linear discriminant analysis and partial least squares discriminant analysis) and cross-validation techniques (leave-one-out, K-fold). All analyses recovered an overall high percentage (> 90%) of correct predictions of specimen identifications for all datasets, regardless of the model or cross-validation used. On average, there was > 95% accuracy when using partial least squares discriminant analysis and both cross-validations. Our results show the high predictive power of FT-NIR at correctly discriminating fern species when using leaves of dried herbarium specimens. The technique is sensitive enough to reflect species delimitation problems and possible hybridization, and it has the potential of helping better delimit and identify fern species.

Technological Advances to Address Current Issues in Entomology: 2020 Student Debates

The 2020 Student Debates of the Entomological Society of America (ESA) were live-streamed during the Virtual Annual Meeting to debate current, prominent entomological issues of interest to members. The Student Debates Subcommittee of the National ESA Student Affairs Committee coordinated the student efforts throughout the year and hosted the live event. This year, four unbiased introductory speakers provided background for each debate topic while four multi-university teams were each assigned a debate topic under the theme 'Technological Advances to Address Current Issues in Entomology'. The two debate topics selected were as follows: 1) What is the best taxonomic approach to identify and classify insects? and 2) What is the best current technology to address the locust swarms worldwide? Unbiased introduction speakers and debate teams began preparing approximately six months before the live event. During the live event, teams shared their critical thinking and practiced communication skills by defending their positions on either taxonomical identification and classification of insects or managing the damaging outbreaks of locusts in crops.

Characterizing the elusive Vancouver Island wolverine, Gulo gulo vancouverensis, using historical DNA

The wolverine (Gulo gulo) is a Holarctic species found in North America primarily across the boreal forest, the subarctic, and along the Pacific coast, including Vancouver Island (VI), British Columbia. While wolverines on VI are rare and possibly extirpated, they have been previously described as a unique subspecies, G. g. vancouverensis, distinct from G. g. luscus from the mainland of North America. However, the validity of the VI subspecies is contentious, with conflicting results from studies of skull morphology. Here, we used molecular analyses to characterize the genetic diversity of the VI population and resolve this taxonomic debate to assist with conservation priorities. Historical DNA of VI wolverines was obtained from museum specimens, amplified at 16 nuclear microsatellite loci, and sequenced at the mitochondrial D-loop control region to compare with wolverines from mainland British Columbia. The VI population had lower allelic richness and was fixed for a single common mtDNA haplotype. Bayesian and non-Bayesian assignments using microsatellites generally revealed admixture across populations, implying allele frequencies between the VI and mainland populations were not significantly different. Hence, both types of genetic markers showed little evolutionary divergence between VI and the mainland population. Combined, these results do not provide evidence of significant genetic distinction for VI wolverines, nor support the subspecific classification. Immediate conservation efforts should focus on estimating population size, while future conservation planning can assume VI wolverines likely are not a unique genetic population and there remains the potential for natural recolonization of wolverines to VI.

Adding DNA barcoding to stream monitoring protocols - What's the additional value and congruence between morphological and molecular identification approaches?

Although aquatic macroinvertebrates and freshwater fishes are important indicators for freshwater quality assessments, the morphological identification to species-level is often impossible and thus especially in many invertebrate taxa not mandatory during Water Framework Directive monitoring, a pragmatism that potentially leads to information loss. Here, we focus on the freshwater fauna of the River Sieg (Germany) to test congruence and additional value in taxa detection and taxonomic resolution of DNA barcoding vs. morphology-based identification in monitoring routines. Prior generated morphological identifications of juvenile fishes and aquatic macroinvertebrates were directly compared to species assignments using the identification engine of the Barcode of Life Data System. In 18% of the invertebrates morphology allowed only assignments to higher systematic entities, but DNA barcoding lead to species-level assignment. Dissimilarities between the two approaches occurred in 7% of the invertebrates and in 1% of the fishes. The 18 fish species were assigned to 20 molecular barcode index numbers, the 104 aquatic invertebrate taxa to 113 molecular entities. Although the cost-benefit analysis of both methods showed that DNA barcoding is still more expensive (5.30–8.60€ per sample) and time consuming (12.5h), the results emphasize the potential to increase taxonomic resolution and gain a more complete profile of biodiversity, especially in invertebrates. The provided reference DNA barcodes help building the foundation for metabarcoding approaches, which provide faster sample processing and more cost-efficient ecological status determination.

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.

Translational Molecular Ecology in practice: Linking DNA-based methods to actionable marine environmental management

Molecular-based approaches can provide timely biodiversity assessments, showing an immense potential to facilitate decision-making in marine environmental management. However, the uptake of molecular data into environmental policy remains minimal. Here, we showcase a selection of local to global scale studies applying molecular-based methodologies for environmental management at various stages of implementation. Drawing upon lessons learned from these case-studies, we provide a roadmap to facilitate applications of DNA-based methods to marine policies and to overcome the existing challenges. The main impediment identified is the need for standardized protocols to guarantee data comparison across spatial and temporal scales. Adoption of Translational Molecular Ecology - the sustained collaboration between molecular ecologists and stakeholders, will enhance consensus with regards to the objectives, methods, and outcomes of environmental management projects. Establishing a sustained dialogue among stakeholders is key to accelerating the adoption of molecular-based approaches for marine monitoring and assessment.

Relationship of taxonomic error to frequency of observation

Biological nomenclature is the entry point to a wealth of information related to or associated with living entities. When applied accurately and consistently, communication between and among researchers and investigators is enhanced, leading to advancements in understanding and progress in research programs. Based on freshwater benthic macroinvertebrate taxonomic identifications, inter-laboratory comparisons of >900 samples taken from rivers, streams, and lakes across the U.S., including the Great Lakes, provided data on taxon-specific error rates. Using the error rates in combination with frequency of observation (FREQ; as a surrogate for rarity), six uncertainty/frequency classes (UFC) are proposed for approximately 1,000 taxa. The UFC, error rates, FREQ each are potentially useful for additional analyses related to interpreting biological assessment results and/or stressor response relationships, as weighting factors for various aspects of ecological condition or biodiversity analyses and helping set direction for taxonomic research and refining identification tools.

Continental-scale patterns of hyper-cryptic diversity within the freshwater model taxon Gammarus fossarum (Crustacea, Amphipoda)

Traditional morphological diagnoses of taxonomic status remain widely used while an increasing number of studies show that one morphospecies might hide cryptic diversity, i.e. lineages with unexpectedly high molecular divergence. This hidden diversity can reach even tens of lineages, i.e. hyper cryptic diversity. Even well-studied model-organisms may exhibit overlooked cryptic diversity. Such is the case of the freshwater crustacean amphipod model taxon Gammarus fossarum. It is extensively used in both applied and basic types of research, including biodiversity assessments, ecotoxicology and evolutionary ecology. Based on COI barcodes of 4926 individuals from 498 sampling sites in 19 European countries, the present paper shows (1) hyper cryptic diversity, ranging from 84 to 152 Molecular Operational Taxonomic Units, (2) ancient diversification starting already 26 Mya in the Oligocene, and (3) high level of lineage syntopy. Even if hyper cryptic diversity was already documented in G. fossarum, the present study increases its extent fourfold, providing a first continental-scale insight into its geographical distribution and establishes several diversification hotspots, notably south-eastern and central Europe. The challenges of recording hyper cryptic diversity in the future are also discussed.

Proteomic fingerprinting of Neotropical hard tick species (Acari: Ixodidae) using a self-curated mass spectra reference library

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used for proteomic fingerprinting and taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method to complement other well-established techniques for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens.

Next generation sequencing-aided comprehensive geographic coverage sheds light on the status of rare and extinct populations of Aporia butterflies (Lepidoptera: Pieridae)

The Black-veined White Aporia crataegi (Linnaeus, 1758), a common and widespread butterfly ranging from northwestern Africa to Europe and Asia, has been extinct in Britain since the 1920s and is on a steady decline in several other parts of its range. In order to investigate genetic diversity within A. crataegi and its correspondence with current subspecies-level taxonomy, we barcoded 173 specimens from across its range including, for the first time, extinct populations from Britain and Korea. Using next generation sequencing we also obtained a sequence for Aporia joubini, a peculiar taxon from China known only by its type specimen collected in the early twentieth century. Our phylogenetic analysis placed A. joubini sister to A. oberthuri, although further taxon sampling may reveal a different scheme. Within A. crataegi, we observed a shallow and weak mitogenomic structure with only a few distinct lineages in North Africa, Sicily, Iran, and Japan. Eurasian populations, including those extinct in Britain and Korea, clustered into a large set of closely allied lineages, consistent with a recent expansion during the Late Pleistocene glacial period. This study highlights the importance of museum collections and the unique opportunities they provide in documenting species diversity and helping conservation efforts.

A taxonomy-free approach based on machine learning to assess the quality of rivers with diatoms

Diatoms are a compulsory biological quality element in the ecological assessment of rivers according to the Water Framework Directive. The application of current official indices requires the identification of individuals to species or lower rank under a microscope based on the valve morphology. This is a highly time-consuming task, often susceptible of disagreements among analysts. In alternative, the use of DNA metabarcoding combined with High-Throughput Sequencing (HTS) has been proposed. The sequences obtained from environmental DNA are clustered into Operational Taxonomic Units (OTUs), which can be assigned to a taxon using reference databases, and from there calculate biotic indices. However, there is still a high percentage of unassigned OTUs to species due to the incompleteness of reference libraries. Alternatively, we tested a new taxonomy-free approach based on diatom community samples to assess rivers. A combination of three machine learning techniques is used to build models that predict diatom OTUs expected in test sites, under reference conditions, from environmental data. The Observed/Expected OTUs ratio indicates the deviation from reference condition and is converted into a quality class. This approach was never used with diatoms neither with OTUs data. To evaluate its efficiency, we built a model based on OTUs lists (HYDGEN) and another based on taxa lists from morphological identification (HYDMORPH), and also calculated a biotic index (IPS). The models were trained and tested with data from 81 sites (44 reference sites) from central Portugal. Both models were considered accurate (linear regression for Observed and Expected richness: R² ≈ 0.7, interception ≈ 0.8) and sensitive to global anthropogenic disturbance (Rs² > 0.30 p < 0.006 for global disturbance). Yet, the HYDGEN model based on molecular data was sensitive to more types of pressures (such as, changes in land use and habitat quality), which gives promising insights to its use for bioassessment of rivers.

Quantifying stream periphyton assemblage responses to nutrient amendments with a molecular approach

Nutrient (nitrogen [N] and phosphorus [P]) pollution is a pervasive water quality issue in the USA for small streams and rivers. The effect of nutrients on the biotic condition of streams is often evaluated with biological indicators such as macroinvertebrate assemblages or periphyton assemblages, particularly diatoms. Molecular approaches facilitate the use of periphyton assemblages as bioindicators because periphyton is diverse and its composition as a whole, rather than just diatoms, soft-bodied algae, or any single group, may convey additional information about responses to nutrients. To further develop the concept that a taxonomically-broad evaluation of periphyton assemblages could be useful for developing stream bioindicators, we examined microbial assemblage composition with both 16S and 18S rRNA genes, enabling us to evaluate composition in 3 domains. We measured otherwise unknown nutrient responses of different periphyton groups in situ with experiments that used glass fiber filters to allow diffusion of amended nutrients into a stream. We deployed these experimental setups in 2 streams that differ in the extent of agricultural land-use in their catchments in the southeastern USA. Experiments consisted of controls, N amendments, P amendments, and both N and P amendments. Periphyton assemblages that grew on the filters differed significantly by stream, date or season, and nutrient treatment. Assemblage differences across treatments were more consistent among Bacteria and Archaea than among eukaryotes. Effects of nutrient amendments were more pronounced in the stream with less agricultural land use and, therefore, lower nutrient loading than in the stream with more agricultural land use and higher nutrient loading. Combined N and P amendments decreased species richness and evenness for Bacteria and Archaea by ∼36 and ∼9%, respectively, compared with controls. Indicator species analysis revealed that specific clades varied in their response to treatments. Indicators based on the responses of these indicator clades were related to nutrient treatments across sites and seasons. Analyses that included all the taxa in a domain did not resolve differences in responses to N vs P. Instead, better resolution was achieved with an analysis focused on diatoms, which responded more strongly to P than N. Overall, our results showed that in situ nutrient-diffusing substrate experiments are a useful approach for describing assemblage responses to nutrients in streams. This type of molecular approach may be useful to environmental agencies and stakeholders responsible for assessing and managing stream water quality and biotic condition.

Stream Algal Biofilm Community Diversity Along An Acid Mine Drainage Recovery Gradient Using Multimarker Metabarcoding

In southeastern Ohio, active remediation of streams affected by Acid Mine Drainage (AMD) has proven to be successful for some streams, while others have not recovered based on macroinvertebrate assessment. In this study, biofilms were collected from three Moderately Impaired, three Recovered, and two Unimpaired streams. The biodiversity was characterized by metabarcoding using two universal barcode markers (16S and 18S) along with two algal specific markers (UPA and rbcL) and high-throughput amplicon sequencing. For each marker, the ordination of Bray-Curtis Index calculated from the total Amplicon Sequence Variants (ASVs) present in each stream showed the Unimpaired and Recovered streams clustered, while Moderately Impaired streams were more distant. Focusing on the algal ASVs, the Shannon index for the rbcL, and UPA markers showed significantly lower alpha diversity in Moderately Impaired streams compared to Unimpaired streams, but the Recovered streams were not significantly different from the other two stream categories. The two universal markers together captured all algal phyla providing an outline of the diversity, but the two algal specific markers produced a greater number of ASVs and taxonomic depth for algal taxa. Further examination of the UPA marker revealed a drastic decrease in relative abundance of diatoms in Moderately Impaired streams compared to Recovered and Unimpaired streams. Likewise, diatom genera identified in the rbcL data and indicative of stream water quality showed marked differences in relative abundance among stream categories. Although all markers were useful, the algal-specific UPA and rbcL contributed more insights into algal community differences among stream categories.

HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves

Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5-10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.

Taxonomic diversity of Biomphalaria (Planorbidae) in São Paulo state, Brazil

Abstract: Morphological and molecular identifications were carried out for Biomphalaria occidentalis, Biomphalaria oligoza, Biomphalaria peregrina, Biomphalaria schrammi, Biomphalaria straminea and Biomphalaria tenagophila collected from 55 sites located along the upper basin of Tietê River in the Southeast Region of Brazil. Morphological analysis considered aspects of the shell, mantle, excretory organs and reproductive system. Molecular data included 122 sequences of Cytochrome C Oxidase I gene (COI). Our results showed that some shell characters, as well as other characters related to the mantle and the reproductive system, are fundamental for the identification of the six Biomphalaria species included in this study. The use of DNA barcoding together with morphological taxonomy generated more reliable results, proving to be a very useful approach, even for malacological surveillance services.

Food from faeces: Evaluating the efficacy of scat DNA metabarcoding in dietary analyses

Scat DNA metabarcoding is increasingly being used to track the feeding ecology of elusive wildlife species. This approach has greatly increased the resolution and detection success of prey items contained in scats when compared with other classical methods. However, there have been few studies that have systematically tested the applicability and reliability of this approach to study the diet of large felids species in the wild. Here we assessed the effectiveness of this approach in the cheetah Acinonyx jubatus. We tested how scat degradation, meal size, prey species consumed and feeding day (the day a particular prey was consumed) influenced prey DNA detection success in captive cheetahs. We demonstrated that it is possible to obtain diet information from 60-day old scats using genetic approaches, but the efficiency decreased over time. Probability of species-identification was highest for food items consumed one day prior to scat collection and the probability of being able to identify the species consumed increased with the proportion of the prey consumed. Detection success varied among prey species but not by individual cheetah. Identification of prey species using DNA detection methods from a single consumption event worked for samples collected between 8 and 72 hours post-feeding. Our approach confirms the utility of genetic approaches to identify prey species in scats and highlight the need to account for the systematic bias in results to control for possible scat degradation, feeding day, meal size and prey species consumed especially in the wild-collected scats.

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.

Assessing pollution of aquatic environments with diatoms’ DNA metabarcoding: experience and developments from France water framework directive networks

Ecological status assessment of watercourses is based on the calculation of quality indices using pollution sensitivity of targeted biological groups, including diatoms. The determination and quantification of diatom species is generally based on microscopic morphological identification, which requires expertise and is time-consuming and costly. In Europe, this morphological approach is legally imposed by standards and regulatory decrees by the Water Framework Directive (WFD). Over the past decade, a DNA-based molecular biology approach has newly been developed to identify species based on genetic criteria rather than morphological ones (i.e. DNA metabarcoding). In combination with high throughput sequencing technologies, metabarcoding makes it possible both to identify all species present in an environmental sample and to process several hundred samples in parallel. This article presents the results of two recent studies carried out on the WFD networks of rivers of Mayotte (2013–2018) and metropolitan France (2016–2018). These studies aimed at testing the potential application of metabarcoding for biomonitoring in the context of the WFD. We discuss the various methodological developments and optimisations that have been made to make the taxonomic inventories of diatoms produced by metabarcoding more reliable, particularly in terms of species quantification. We present the results of the application of this DNA approach on more than 500 river sites, comparing them with those obtained using the standardised morphological method. Finally, we discuss the potential of metabarcoding for routine application, its limits of application and propose some recommendations for future implementation in WFD.

Selecting Comparator Sites for Ecological Causal Assessment Based on Expected Biological Similarity

Sites in poor ecological condition often require causal assessment to determine appropriate follow-up actions. Site-specific causal assessments can be time consuming. To streamline the process, we describe a quantitative method that expedites a key component of causal assessment: identifying a group of ecologically similar (comparator) sites that are used to compare and contrast biological condition and stressor exposure at the site of interest. A good set of comparator sites should: 1. Be capable of supporting similar biota to the impaired site in the absence of disturbance; 2. Comprise a gradient of biotic condition; and 3. Contain enough sites to assess variability. We used expected biological similarity to select good sets of comparator sites from a large pool of potential sites. Expected biological similarity was measured as Bray-Curtis dissimilarity values (BC) calculated from the expected benthic macroinvertebrate taxa lists produced by a predictive biotic index of stream health. Sets of comparator sites were created for 15 demonstration sites across Southern California in poor condition. We examined the stressor and biological data collected at the 15 sites and their comparators to assess the likelihood that four example stressors - total nitrogen, ammonia, specific conductivity, and bifenthrin - contribute to the poor biotic conditions that were observed. We were able to select more than 100 comparator sites for all but 1 of the 15 demonstration sites at a BC <0.1. These sets of comparator sites were then used to evaluate the four example stressors using two commonly used causal assessment types of evidence. Elevated conductivity was the most frequently supported likely cause among the demonstration sites, though total nitrogen and bifenthrin were also indicated at some sites. Though our specific approach was tailored for application in California's stream bioassessment framework, the concepts could be adapted for any bioassessment program with a large amount of sample data and an associated predictive index of biotic condition. Furthermore, this approach lays the groundwork for developing a novel approach to causal assessment that begins with a rapid, screening-level evaluation of stressors common in a region using these data-rich groups of comparator sites, which then informs follow-up management actions.

Molecular versus morphological data for benthic diatoms biomonitoring in Northern Europe freshwater and consequences for ecological status

Diatoms are known to be efficient bioindicators for water quality assessment because of their rapid response to environmental pressures and their omnipresence in water bodies. The identification of benthic diatoms communities in the biofilm, coupled with quality indices such as the Indice de polluosensibilité spécifique (IPS) can be used for biomonitoring purposes in freshwater. However, the morphological identification and counting of diatoms species under the microscope is time-consuming and requires extensive expertise to deal with a constantly evolving taxonomy. In response, a molecular-based and potentially more cost-effective method has been developed, coupling high-throughput sequencing and DNA metabarcoding. The method has already been tested for water quality assessment with diatoms in Central Europe. In this study, we applied both the traditional and molecular methods on 180 biofilms samples from Northern Europe (rivers and lakes of Fennoscandia and Iceland). The DNA metabarcoding data were obtained on two different DNA markers, the 18S-V4 and rbcL barcodes, with the NucleoSpin Soil kit for DNA extraction and sequenced on an Ion Torrent PGM platform. We assessed the ability of the molecular method to produce species inventories, IPS scores and ecological status class comparable to the ones generated by the traditional morphology-based approach. The two methods generated correlated but significantly different IPS scores and ecological status assessment. The observed deviations are explained by presence/absence and abundance discrepancies in the species inventories, mainly due to the incompleteness of the barcodes reference databases, primer bias and strictness of the bioinformatic pipeline. Abundance discrepancies are less common than presence/absence discrepancies but have a greater effect on the ecological assessment. Missing species in the reference databases are mostly acidophilic benthic diatoms species, typical of the low pH waters of Northern Europe. The two different DNA markers also generated significantly different ecological status assessments. The use of the 18S-V4 marker generates more species inventories discrepancies, but achieves an ecological assessment more similar to the traditional morphology-based method. Further development of the metabarcoding method is needed for its use in environmental assessment. For its application in Northern Europe, completion and curation of reference databases are necessary, as well as evaluation of the currently available bioinformatics pipelines. New indices, fitted for environmental biomonitoring, should also be developed directly from molecular data.

Application of matrix-assisted laser desorption/ionization mass spectrometry to identify species of Neotropical Anopheles vectors of malaria

Background

Malaria control in Panama is problematic due to the high diversity of morphologically similar Anopheles mosquito species, which makes identification of vectors of human Plasmodium challenging. Strategies by Panamanian health authorities to bring malaria under control targeting Anopheles vectors could be ineffective if they tackle a misidentified species.

Methods

A rapid mass spectrometry identification procedure was developed to accurately and timely sort out field-collected Neotropical Anopheles mosquitoes into vector and non-vector species. Matrix-assisted laser desorption/ionization (MALDI) mass spectra of highly-abundant proteins were generated from laboratory-reared mosquitoes using different extraction protocols, body parts, and sexes to minimize the amount of material from specimen vouchers needed and optimize the protocol for taxonomic identification. Subsequently, the mass spectra of field-collected Neotropical Anopheles mosquito species were classified using a combination of custom-made unsupervised (i.e., Principal component analysis—PCA) and supervised (i.e., Linear discriminant analysis—LDA) classification algorithms.

Results

Regardless of the protocol used or the mosquito species and sex, the legs contained the least intra-specific variability with enough well-preserved proteins to differentiate among distinct biological species, consistent with previous literature. After minimizing the amount of material needed from the voucher, one leg was enough to produce reliable spectra between specimens. Further, both PCA and LDA were able to classify up to 12 mosquito species, from different subgenera and seven geographically spread localities across Panama using mass spectra from one leg pair. LDA demonstrated high discriminatory power and consistency, with validation and cross-validation positive identification rates above 93% at the species level.

Conclusion

The selected sample processing procedure can be used to identify field-collected Anopheles species, including vectors of Plasmodium, in a short period of time, with a minimal amount of tissue and without the need of an expert mosquito taxonomist. This strategy to analyse protein spectra overcomes the drawbacks of working without a reference library to classify unknown samples. Finally, this MALDI approach can aid ongoing malaria eradication efforts in Panama and other countries with large number of mosquito’s species by improving vector surveillance in epidemic-prone sites such as indigenous Comarcas.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2723-0) contains supplementary material, which is available to authorized users.

Prediction of Lard in Palm Olein Oil Using Simple Linear Regression (SLR), Multiple Linear Regression (MLR), and Partial Least Squares Regression (PLSR) Based on Fourier-Transform Infrared (FTIR)

Fourier-transform infrared (FTIR) offers the advantages of rapid analysis with minimal sample preparation. FTIR in combination with multivariate approach, particularly partial least squares regression (PLSR), has been widely used for adulterant analysis. Limited study has been done to compare PLSR with other regression strategies. In this paper, we apply simple linear regression (SLR), multiple linear regression (MLR), and PLSR for prediction of lard in palm olein oil. Pure palm olein oil was adulterated with lard at different concentrations and subjected to analysis with FTIR. The marker bands distinguishing lard and palm olein oil were determined using Fisher’s weights. The marker regions were then subjected to regression analysis with the models verified based on 100 training/test sets. The prediction performance was measured based on the percentage root mean square error (%RMSE). The absorption bands at 3006 cm−1, 2852 cm−1, 1117 cm−1, 1236 cm−1, and 1159 cm−1 were identified as the marker bands. The bands at 3006 and 1117 cm−1 were found with satisfactory predictive ability, with PLSR demonstrating better prediction yielding %RMSE of 16.03 and 13.26%, respectively.

The influence of macroinvertebrate abundance on the assessment of freshwater quality in The Netherlands

The use of molecular tools for the detection and identification of invertebrate species enables the development of more easily standardisable inventories of biological elements for water quality assessments, as it circumvents human-based bias and errors in species identifications. Current Ecological Quality Ratio (EQR) assessments methods, however, often rely on abundance data. Translating metabarcoding sequence data into biomass or specimen abundances has proven difficult, as PCR amplification bias due to primer mismatching often provides skewed proportions of read abundances. While some potential solutions have been proposed in previous research, we instead looked at the necessity of abundance data in EQR assessments. In this study, we used historical monitoring data from natural (lakes, rivers and streams) and artificial (ditches and canals) water bodies to assess the impact of species abundances on the EQR scores for macroinvertebrates in the Water Framework Directive (WFD) monitoring programme of The Netherlands. By removing all the abundance data from the taxon observations, we simulated presence/absence-based monitoring, for which EQRs were calculated according to traditional methods. Our results showed a strong correlation between abundance-based and presence/absence-based EQRs. EQR scores were generally higher without abundances (75.8% of all samples), which resulted in 9.1% of samples being assigned to a higher quality class. The majority of the samples (89.7%) were assigned to the same quality class in both cases. These results are valuable for the incorporation of presence/absence metabarcoding data into water quality assessment methodology, potentially eliminating the need to translate metabarcoding data into biomass or absolute specimen counts for EQR assessments.

Ecological influence of sediment bypass tunnels on macroinvertebrates in dam-fragmented rivers by DNA metabarcoding

Sediment bypass tunnels (SBTs) are guiding structures used to reduce sediment accumulation in reservoirs during high flows by transporting sediments to downstream reaches during operation. Previous studies monitoring the ecological effects of SBT operations on downstream reaches suggest a positive influence of SBTs on riverbed sediment conditions and macroinvertebrate communities based on traditional morphology-based surveys. Morphology-based macroinvertebrate assessments are costly and time-consuming, and the large number of morphologically cryptic, small-sized and undescribed species usually results in coarse taxonomic identification. Here, we used DNA metabarcoding analysis to assess the influence of SBT operations on macroinvertebrates downstream of SBT outlets by estimating species diversity and pairwise community dissimilarity between upstream and downstream locations in dam-fragmented rivers with operational SBTs in comparison to dam-fragmented (i.e., no SBTs) and free-flowing rivers (i.e., no dam). We found that macroinvertebrate community dissimilarity decreases with increasing operation time and frequency of SBTs. These factors of SBT operation influence changes in riverbed features, e.g. sediment relations, that subsequently effect the recovery of downstream macroinvertebrate communities to their respective upstream communities. Macroinvertebrate abundance using morphologically-identified specimens was positively correlated to read abundance using metabarcoding. This supports and reinforces the use of quantitative estimates for diversity analysis with metabarcoding data.

Implementation options for DNA-based identification into ecological status assessment under the European Water Framework Directive

Assessment of ecological status for the European Water Framework Directive (WFD) is based on "Biological Quality Elements" (BQEs), namely phytoplankton, benthic flora, benthic invertebrates and fish. Morphological identification of these organisms is a time-consuming and expensive procedure. Here, we assess the options for complementing and, perhaps, replacing morphological identification with procedures using eDNA, metabarcoding or similar approaches. We rate the applicability of DNA-based identification for the individual BQEs and water categories (rivers, lakes, transitional and coastal waters) against eleven criteria, summarised under the headlines representativeness (for example suitability of current sampling methods for DNA-based identification, errors from DNA-based species detection), sensitivity (for example capability to detect sensitive taxa, unassigned reads), precision of DNA-based identification (knowledge about uncertainty), comparability with conventional approaches (for example sensitivity of metrics to differences in DNA-based identification), cost effectiveness and environmental impact. Overall, suitability of DNA-based identification is particularly high for fish, as eDNA is a well-suited sampling approach which can replace expensive and potentially harmful methods such as gill-netting, trawling or electrofishing. Furthermore, there are attempts to replace absolute by relative abundance in metric calculations. For invertebrates and phytobenthos, the main challenges include the modification of indices and completing barcode libraries. For phytoplankton, the barcode libraries are even more problematic, due to the high taxonomic diversity in plankton samples. If current assessment concepts are kept, DNA-based identification is least appropriate for macrophytes (rivers, lakes) and angiosperms/macroalgae (transitional and coastal waters), which are surveyed rather than sampled. We discuss general implications of implementing DNA-based identification into standard ecological assessment, in particular considering any adaptations to the WFD that may be required to facilitate the transition to molecular data.

Can non-destructive DNA extraction of bulk invertebrate samples be used for metabarcoding?

Background

High throughput DNA sequencing of bulk invertebrate samples or metabarcoding is becoming increasingly used to provide profiles of biological communities for environmental monitoring. As metabarcoding becomes more widely applied, new reference DNA barcodes linked to individual specimens identified by taxonomists are needed. This can be achieved through using DNA extraction methods that are not only suitable for metabarcoding but also for building reference DNA barcode libraries.

Methods

In this study, we test the suitability of a rapid non-destructive DNA extraction method for metabarcoding of freshwater invertebrate samples.

Results

This method resulted in detection of taxa from many taxonomic groups, comparable to results obtained with two other tissue-based extraction methods. Most taxa could also be successfully used for subsequent individual-based DNA barcoding and taxonomic identification. The method was successfully applied to field-collected invertebrate samples stored for taxonomic studies in 70% ethanol at room temperature, a commonly used storage method for freshwater samples.

Discussion

With further refinement and testing, non-destructive extraction has the potential to rapidly characterise species biodiversity in invertebrate samples, while preserving specimens for taxonomic investigation.

Re-evaluation of the discriminatory power of DNA barcoding on some specimens of African Cyprinidae (subfamilies Cyprininae and Danioninae)

Specimen identification in the absence of diagnostic morphological characters (e.g., larvae) can be problematic even for experts. The goal of the present study was to assess the performance of COI in discriminating specimens of the fish family Cyprinidae in Africa, and to explore whether COI-phylogeny can be reliably used for phylogenetic comparative analysis. The main objective was to analyse a matrix of COI sequences for 315 specimens from 15 genera of African Cyprinidae using various distance-based identification methods alongside multiple tests of DNA barcode efficacy (barcode gap, species monophyly on NJ tree). Some morphological and biological characters were also mapped on a COI-phylogeny reconstructed using Maximum Parsimony. First, the results indicated the existence of barcode gaps, a discriminatory power of COI ranging from 79 % to 92 %, and that most nodes form well-supported monophyletic clades on an NJ tree. Second, it was found that some morphological and biological characters are clustered on the COI-phylogeny, and this indicates the reliability of these characters for taxonomic discrimination within the family. Put together, our results provide not only an additional support for the COI as a good barcode marker for the African Cyprinidae but it also indicate the utility of COI-based phylogenies for a wide spectrum of ecological questions related to African Cyprinidae.