Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material

The metabarcoding of Grubs: Traditional herbal medicine of Scarabaeidae larvae

Grubs, called Qicao in China, have a long tradition as herbal medicine in East Asia. These larvae belong to the diverse family Scarabaeidae and are typically harvested from the wild during their immature stage based on morphological characteristics. However, rapid and accurate identification becomes challenging when relying solely on external morphological features, as the lack of clarity on biological sources raises safety concerns for clinical applications. The application of DNA metabarcoding provides a solution by enabling the determination of the biological source of a large sample. In the current study, we collected 19 batches of Grubs, consisting of 11,539 individuals, from the market and analyzed their biological composition through metabarcoding. We identified 49 Amplicon Sequence Variants (ASVs), 21 of which were Grubs. The 21 ASVs were classified into seven Molecular Operational Taxonomic Units (MOTUs) through species delimitation, which revealed that commercially available Grubs are predominantly sourced from Protaetia brevitarsis seulensis, while species of Rutelinae, Anomala, and Holotrichia were also abundant in some commercial batches. Among the identified ASVs, 28 belonged to non-Grub species and indicated adulteration from different animal families; high abundances of these ASVs were detected for Bombycidae, Tabanidae, and Viviparidae. Our findings underscore the complexity of Grubs' species composition and advocate for a deeper understanding of the wildlife sources contributing to herbal products. This research contributes valuable insights into the molecular identification of Grubs, paving the way for enhanced quality assurance in traditional medicine applications to provide safe and effective medicines for humanity.

Seasonal shifts in pronghorn antelope (Antilocapra americana) diets under a new lens: Examining diet composition using a molecular technique

Foraging is one of the most fundamental activities contributing to the maximization of an animal's fitness, and thus herbivores must optimize their diet selection and intake to meet their nutrient demands for survival, growth, and reproduction. Using plant DNA barcoding, we determined diet composition of five subpopulations of adult female pronghorn antelope (Antilocapra americana) grazing rangelands in southern and southeastern Idaho, USA. Fecal samples were collected for two years (2018-2019), and across metabolically-important adult female life history stages (late gestation, early lactation, breeding season). Plant DNA barcoding yielded 137 detected species within pronghorn diets across subpopulations and sampling periods with forbs being the most abundant. Pronghorn dietary functional group composition ranged from 52.2-60.3% from forbs followed by shrubs (22.6-28.2%), graminoids (8.7-15.7%), and legumes (5.5-9.6%). Dietary protein intake was also highest from forbs and ranged from 32.4-62.4% followed by graminoids (1.2-43.1%), shrubs (18.7-21.3%), and legumes (2.6-7.4%). We found significant intra- and interannual differences in the mean number of genera-based plant detections in pronghorn diets. Dietary protein intake of cultivated legumes (e.g., alfalfa [Medicago sativa] and sainfoin [Onobrychis viciifolia]) was lower than expected, ranging from <1.0-30.8%, suggesting that even within an agricultural-dominated landscape, factors other than plant nutritional composition contributed to pronghorn diets. Although the plant DNA barcoding technique exhibits limitations, it demonstrated potential for elucidating pronghorn dietary species richness, particularly for plants consumed in small proportions, as well as for observing temporal fluctuations in functional group composition and dietary protein intake explained through the interplay between environmental factors, plant chemical composition, and the animals' physiological needs.

Monitoring mosquito richness in an understudied area: can environmental DNA metabarcoding be a complementary approach to adult trapping?

Mosquito surveillance programmes are essential to assess the risks of local vector-borne disease outbreaks as well as for early detection of mosquito invasion events. Surveys are usually performed with traditional sampling tools (i.e., ovitraps and dipping method for immature stages or light or decoy traps for adults). Over the past decade, numerous studies have highlighted that environmental DNA (eDNA) sampling can enhance invertebrate species detection and provide community composition metrics. However, the usefulness of eDNA for detection of mosquito species has, to date, been largely neglected. Here, we sampled water from potential larval breeding sites along a gradient of anthropogenic perturbations, from the core of an oil palm plantation to the rainforest on São Tomé Island (Gulf of Guinea, Africa). We showed that (i) species of mosquitoes could be detected via metabarcoding mostly when larvae were visible, (ii) larvae species richness was greater using eDNA than visual identification and (iii) new mosquito species were also detected by the eDNA approach. We provide a critical discussion of the pros and cons of eDNA metabarcoding for monitoring mosquito species diversity and recommendations for future research directions that could facilitate the adoption of eDNA as a tool for assessing insect vector communities.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

DNA metabarcoding highlights cyanobacteria as the main source of primary production in a pelagic food web model

Models that estimate rates of energy flow in complex food webs often fail to account for species-specific prey selectivity of diverse consumer guilds. While DNA metabarcoding is increasingly used for dietary studies, methodological biases have limited its application for food web modeling. Here, we used data from dietary metabarcoding studies of zooplankton to calculate prey selectivity indices and assess energy fluxes in a pelagic resource-consumer network. We show that food web dynamics are influenced by prey selectivity and temporal match-mismatch in growth cycles and that cyanobacteria are the main source of primary production in the investigated coastal pelagic food web. The latter challenges the common assumption that cyanobacteria are not supporting food web productivity, a result that is increasingly relevant as global warming promotes cyanobacteria dominance. While this study provides a method for how DNA metabarcoding can be used to quantify energy fluxes in a marine food web, the approach presented here can easily be extended to other ecosystems.

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.

Toward quantitative metabarcoding

Amplicon-sequence data from environmental DNA (eDNA) and microbiome studies provide important information for ecology, conservation, management, and health. At present, amplicon-sequencing studies-known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture-struggle to link genetic observations to the underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology, it becomes more important to develop ways to make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying polymerase chain reaction mechanism explains the observed patterns of amplicon data in a general way. By modeling the process through which amplicon-sequence data arise, rather than transforming the data post hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.

Combining vertebrate mitochondrial 12S rRNA gene sequencing and shotgun metagenomic sequencing to investigate the diet of the leopard cat (Prionailurus bengalensis) in Korea

The leopard cat (Prionailurus bengalensis), an endangered species in South Korea, is a small feline widely distributed in Asia. Here, we investigated the diet of leopard cats in the inland areas of Korea by examining their fecal contents using vertebrate mitochondrial 12S rRNA gene sequencing and shotgun metagenomic sequencing. Shotgun metagenomic sequencing revealed that the feces were rich in DNA not only of vertebrates but also of arthropods and plants, but care should be taken when using shotgun metagenomic sequencing to identify vertebrates at low taxonomic levels (e.g., genus level), as it was often erroneous. Meanwhile, vertebrate mitochondrial 12S rRNA gene sequencing was found to be accurate in the genus-level identification, as the genera identified were consistent with the Korean fauna. We found that small mammals such as murids were their main prey. By using these two sequencing methods in combination, this study demonstrated that accurate information about the overall dietary content and vertebrate prey of leopard cats could be obtained. We expect that the continued community efforts to expand the genome database of wildlife, including vertebrates, will alleviate the problem of erroneous identification of prey at low taxonomic levels by shotgun metagenomic sequencing in the near future.

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.

Diet preferences based on sequence read count: the role of species interaction in tissue bias correction

High-throughput sequencing and metabarcoding techniques provide a unique opportunity to study predator-prey relationships. However, in animal dietary preference studies, how to properly correct tissue bias within the sequence read count and the role of interactions between co-occurring species in metabarcoding mixtures remain largely unknown. In this study, we proposed two categories of tissue bias correction indices: sequence read count number per unit tissue (SCN) and its ratio form (SCN ratio). By constructing plant mock communities with different numbers of co-occurring species in metabarcoding mixtures and conducting feeding trails on captive sika deer (Cervus nippon), we demonstrated the features of the SCN and SCN ratio, evaluated their correction effects, and assessed the role of species interactions during tissue bias correction. Tissue differences between species are defined as the differential ability in generating sequence counts. Our study suggests that pure tissue differences among species without species interaction is not an optimal correction index for many biomes with limited tissue differences among species. Species interactions in mixtures may amplify tissue differences, which is beneficial for tissue bias correction. However, caution must be taken because varied species interaction among communities may increase the risk of worse correction. Correction effects based on the SCN and SCN ratio are comparable, while the SCN is less influenced by control species than the SCN ratio. According to our study, several suggestions were provided for future animal diet studies or other high-throughput sequencing studies containing tissue bias.

Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias

Plankton metabarcoding is increasingly implemented in marine ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on microscopy (morphological). 18S rRNA gene is the most widely used marker for groups’ and species’ detection and classification within marine eukaryotic microorganisms. These datasets have commonly relied on the acquisition of organismal abundances directly from the number of DNA sequences (i.e. reads). Besides the inherent technical biases in metabarcoding, the largely varying 18S rRNA gene copy numbers (GCN) among marine protists (ranging from tens to thousands) is one of the most important biological biases for species quantification. In this work, we present a gene copy number correction factor (CF) for four marine planktonic groups: Bacillariophyta, Dinoflagellata, Ciliophora miscellaneous and flagellated cells. On the basis of the theoretical assumption that ‘1 read’ is equivalent to ‘1 GCN’, we used the GCN median values per plankton group to calculate the corrected cell number and biomass relative abundances. The species-specific absolute GCN per cell were obtained from various studies published in the literature. We contributed to the development of a species-specific 18S rRNA GCN database proposed by previous authors. To assess the efficiency of the correction factor we compared the metabarcoding, morphological and corrected relative abundances (in cell number and biomass) of 15 surface water samples collected in the Belgian Coastal Zone. Results showed that the application of the correction factor over metabarcoding results enables us to significantly improve the estimates of cell abundances for Dinoflagellata, Ciliophora and flagellated cells, but not for Bacillariophyta. This is likely to due to large biovolume plasticity in diatoms not corresponding to genome size and gene copy numbers. C-biomass relative abundance estimations directly from amplicon reads were only improved for Dinoflagellata and Ciliophora. The method is still facing biases related to the low number of species GCN assessed. Nevertheless, the increase of species in the GCN database may lead to the refinement of the proposed correction factor.

Using DNA metabarcoding and a novel canid-specific blocking oligonucleotide to investigate the composition of animal diets of raccoon dogs (Nyctereutes procyonoides) inhabiting the waterside area in Korea

The raccoon dog (Nyctereutes procyonoides) is known to be an opportunistic generalist who feeds on a wide variety of foods. Historically, their diet has been investigated by morphological observation of undigested remains in feces, requiring specialized knowledge such as osteology, zoology, and phytology. Here, we used DNA metabarcoding of vertebrate 12S rRNA gene and invertebrate 16S rRNA gene to investigate their fecal contents. Additionally, we developed a blocking oligonucleotide that specifically inhibits the amplification of the canid 12S rRNA gene. We confirmed that the blocking oligonucleotide selectively inhibit the amplification of raccoon dog’s DNA without significantly changing the composition of the preys’ DNA. We found that the main foods of raccoon dogs in our study area, the waterside of paddy fields in Korea, were fishes such as Cyprinidae and insects such as mole crickets, which makes sense given the Korean fauna and their well-known opportunistic feeding behaviors. As a method to conveniently and objectively investigate feeding habits of raccoon dogs, this study provided baseline information on DNA metabarcoding. By using DNA metabarcoding, it is expected that the diet habits and ecology of raccoon dogs will be better understood by future research.

DNA metabarcoding quantifies the relative biomass of arthropod taxa in songbird diets: Validation with camera‐recorded diets

Ecological research is often hampered by the inability to quantify animal diets. Diet composition can be tracked through DNA metabarcoding of fecal samples, but whether (complex) diets can be quantitatively determined with metabarcoding is still debated and needs validation using free‐living animals. This study validates that DNA metabarcoding of feces can retrieve actual ingested taxa, and most importantly, that read numbers retrieved from sequencing can also be used to quantify the relative biomass of dietary taxa. Validation was done with the hole‐nesting insectivorous Pied Flycatcher whose diet was quantified using camera footage. Size‐adjusted counts of food items delivered to nestlings were used as a proxy for provided biomass of prey orders and families, and subsequently, nestling feces were assessed through DNA metabarcoding. To explore potential effects of digestion, gizzard and lower intestine samples of freshly collected birds were subjected to DNA metabarcoding. For metabarcoding with Cytochrome Oxidase subunit I (COI), we modified published invertebrate COI primers LCO1490 and HCO1777, which reduced host reads to 0.03%, and amplified Arachnida DNA without significant changing the recovery of other arthropod taxa. DNA metabarcoding retrieved all commonly camera‐recorded taxa. Overall, and in each replicate year (N = 3), the relative scaled biomass of prey taxa and COI read numbers correlated at R = .85 (95CI:0.68–0.94) at order level and at R = .75 (CI:0.67–0.82) at family level. Similarity in arthropod community composition between gizzard and intestines suggested limited digestive bias. This DNA metabarcoding validation demonstrates that quantitative analyses of arthropod diet is possible. We discuss the ecological applications for insectivorous birds.

DNA metabarcoding uncovers the diet of subterranean rodents in China

OBJECTIVE

A type of rodent called a zokor causes great harm to agriculture and forestry production due to its large and sophisticated diet. As this rodent lives subterrane for most of its life, researchers know little about its dietary habits. Further understanding of its diet is important for developing green and sustainable control strategies for the zokor.

METHODS

Chloroplast trnL gene and internal transcription spacer 1 primers were selected for high-throughput sequencing of stomach contents of captured zokor by DNA metabarcoding.

RESULTS

A total of 25 zokors were selected, the food list of 32 families, 80 genera, and 154 species was obtained. At the family level, it was found that zokors mainly fed on Asteraceae, Poaceae, Rosaceae, Pinaceae, Brassicaceae, and Apiaceae. At the genus level, zokors mainly fed on Echinops, Littledalea, Artemisia, Picea, Cirsium, and Elymus. The diet alpha diversity of Eospalax cansus was slightly higher than that of Eospalax cansus (P>0.05). The zokor's diet is highly phconsistent with the resources of its habitat. Most food choices tend to be the same between the two zokors. They fed primarily on Calamagrostis, Cirsium, Echinops, Medicago, Sanguisorba, and Taraxacum. Zokors mainly fed on the roots of perennial herbs, which are important source of energy.

CONCLUSION

High-throughput sequencing-based DNA metabarcoding technology has effectively revealed the diet of zokors and indicated that zokors are food generalists.

Message in a Bottle-Metabarcoding enables biodiversity comparisons across ecoregions

Background

Traditional biomonitoring approaches have delivered a basic understanding of biodiversity, but they cannot support the large-scale assessments required to manage and protect entire ecosystems. This study used DNA metabarcoding to assess spatial and temporal variation in species richness and diversity in arthropod communities from 52 protected areas spanning 3 Canadian ecoregions.

Results

This study revealed the presence of 26,263 arthropod species in the 3 ecoregions and indicated that at least another 3,000–5,000 await detection. Results further demonstrate that communities are more similar within than between ecoregions, even after controlling for geographical distance. Overall α-diversity declined from east to west, reflecting a gradient in habitat disturbance. Shifts in species composition were high at every site, with turnover greater than nestedness, suggesting the presence of many transient species.

Conclusions

Differences in species composition among their arthropod communities confirm that ecoregions are a useful synoptic for biogeographic patterns and for structuring conservation efforts. The present results also demonstrate that metabarcoding enables large-scale monitoring of shifts in species composition, making it possible to move beyond the biomass measurements that have been the key metric used in prior efforts to track change in arthropod communities.

Feces DNA analyses track the rehabilitation of a free-ranging beluga whale

Following the sudden appearance, and subsequent efforts to support the survival of a beluga whale (Delphinapterus leucas) speculated to have been previously trained off the coast of Norway, we investigate the animal's ability to readapt to life in the wild. Dietary DNA (dDNA) analysis was used to assess diet throughout this rehabilitation process, and during a return to unassisted foraging and self-feeding. Metabarcoding of feces collected throughout this process, confirmed the diversification of the beluga whale's diet to local prey. These findings are indicative of improved foraging behavior, and the ability of this individual to resume wild foraging following a period of dependency in managed care. New insight of digestion rates, and the time window during which prey detection through dDNA analysis is appropriate was also obtained. Beyond the case study presented here, we demonstrate the power of dDNA analysis as a non-intrusive tool to assess the diet of large mammals and track progress adapting to life in the wild following release from captivity and rehabilitation programs.

Metabarcoding versus mapping unassembled shotgun reads for identification of prey consumed by arthropod epigeal predators

Background

A central challenge of DNA gut content analysis is to identify prey in a highly degraded DNA community. In this study, we evaluated prey detection using metabarcoding and a method of mapping unassembled shotgun reads (Lazaro).

Results

In a mock prey community, metabarcoding did not detect any prey, probably owing to primer choice and/or preferential predator DNA amplification, while Lazaro detected prey with accuracy 43–71%. Gut content analysis of field-collected arthropod epigeal predators (3 ants, 1 dermapteran, and 1 carabid) from agricultural habitats in Brazil (27 samples, 46–273 individuals per sample) revealed that 64% of the prey species detections by either method were not confirmed by melting curve analysis and 87% of the true prey were detected in common. We hypothesized that Lazaro would detect fewer true- and false-positive and more false-negative prey with greater taxonomic resolution than metabarcoding but found that the methods were similar in sensitivity, specificity, false discovery rate, false omission rate, and accuracy. There was a positive correlation between the relative prey DNA concentration in the samples and the number of prey reads detected by Lazaro, while this was inconsistent for metabarcoding.

Conclusions

Metabarcoding and Lazaro had similar, but partially complementary, detection of prey in arthropod predator guts. However, while Lazaro was almost 2× more expensive, the number of reads was related to the amount of prey DNA, suggesting that Lazaro may provide quantitative prey information while metabarcoding did not.

Data on the diets of Salish Sea harbour seals from DNA metabarcoding

Marine trophic ecology data are in high demand as natural resource agencies increasingly adopt ecosystem-based management strategies that account for complex species interactions. Harbour seal (Phoca vitulina) diet data are of particular interest because the species is an abundant predator in the northeast Pacific Ocean and Salish Sea ecosystem that consumes Pacific salmon (Oncorhynchus spp.). A multi-agency effort was therefore undertaken to produce harbour seal diet data on an ecosystem scale using, 1) a standardized set of scat collection and analysis methods, and 2) a newly developed DNA metabarcoding diet analysis technique designed to identify prey species and quantify their relative proportions in seal diets. The DNA-based dataset described herein contains records from 4,625 harbour seal scats representing 52 haulout sites, 7 years, 12 calendar months, and a total of 11,641 prey identifications. Prey morphological hard parts analyses were conducted alongside, resulting in corresponding hard parts data for 92% of the scat DNA samples. A custom-built prey DNA sequence database containing 201 species (192 fishes, 9 cephalopods) is also provided.

The precautionary principle and dietary DNA metabarcoding: Commonly used abundance thresholds change ecological interpretation

Dietary DNA metabarcoding enables researchers to identify and characterize trophic interactions with a high degree of taxonomic precision. It is also sensitive to sources of bias and contamination in the field and laboratory. One of the earliest and most common strategies for dealing with such sensitivities has been to remove all low-abundance sequences and conduct ecological analyses based on the presence or absence of food taxa. Although this step is now often perceived to be necessary, evidence of its sufficiency is lacking and more attention to the risk of introducing other errors is needed. Using computer simulations, we demonstrate that common strategies to remove low-abundance sequences can erroneously eliminate true dietary sequences in ways that impact downstream inferences. Using real data from well-studied wildlife populations in Yellowstone National Park, we further show how these strategies can markedly alter the composition of dietary profiles in ways that scale-up to obscure ecological interpretations about dietary generalism, specialism, and composition. Although the practice of removing low-abundance sequences may continue to be a useful strategy to address research questions that focus on a subset of relatively abundant foods, its continued widespread use risks generating misleading perceptions about the structure of trophic networks. Researchers working with dietary DNA metabarcoding data-or similar data such as environmental DNA, microbiomes, or pathobiomes-should be aware of drawbacks and consider alternative bioinformatic, experimental, and statistical solutions.

Disentangling bias for non-destructive insect metabarcoding

A fast and reliable method for obtaining a species-level identification is a fundamental requirement for a wide range of activities, from plant protection and invasive species management to biodiversity assessments and ecological studies. For insects, novel molecular techniques such as DNA metabarcoding have emerged as a rapid alternative to traditional morphological identification, reducing the dependence on limited taxonomic experts. Until recently, molecular techniques have required a destructive DNA extraction, precluding the possibility of preserving voucher specimens for future studies, or species descriptions. Here we paired insect metabarcoding with two recent non-destructive DNA extraction protocols, to obtain a rapid and high-throughput taxonomic identification of diverse insect taxa while retaining a physical voucher specimen. The aim of this work was to explore how non-destructive extraction protocols impact the semi-quantitative nature of metabarcoding, which alongside species presence/absence also provides a quantitative, but biased, representation of their relative abundances. By using a series of mock communities representing each stage of a typical metabarcoding workflow we were able to determine how different morphological (i.e., insect biomass and exoskeleton hardness) and molecular traits (i.e., primer mismatch and amplicon GC%), interact with different protocol steps to introduce quantitative bias into non-destructive metabarcoding results. We discuss the relevance of taxonomic bias to metabarcoding identification of insects and potential approaches to account for it.

Ichthyoplankton DNA metabarcoding: challenges and perspectives

DNA metabarcoding has been widely used to access and monitor species. However, several challenges remain open for its mainstream application in ecological studies, particularly when dealing with a quantitative approach. In a from the Cover article in this issue of Molecular Ecology, Mariac et al. (2021) report species-level ichthyoplankton dynamics for 97 fish species from two Amazon river basins using a clever quantitative metabarcoding approach employing a probe capture method. They clearly show that most species spawned during the floods, although ~20% also spawned mainly during the receding period and some other year-round, but interestingly, species from the same genus reproduced in distinct periods (i.e., inverse phenology). Opportunistically, Mariac et al. (2021) reported that during an intense hydrological anomaly, several species had a sharp reduction in spawning activity, demonstrating a quick response to environmental cues. This is an interesting result since the speed at which fish species can react to environmental changes, during the spawning period, is largely unknown. Thus, this study brings remarkable insights into basic life history information that is imperative for proposing strategies that could lead to a realistic framework for sustainable fisheries management practices and conservation, fundamental for an under-studied and threatened realm, such as the Amazon River basin.

Assessing changes in stream macroinvertebrate communities across ecological gradients using morphological versus DNA metabarcoding approaches

Freshwater macroinvertebrates provide valuable indicators for biomonitoring ecosystem change in relation to natural and anthropogenic drivers. DNA metabarcoding is an efficient approach for estimating such indicators, but its results may differ from morphotaxonomic approaches traditionally used in biomonitoring. Here we test the hypothesis that despite differences in the number and identity of taxa recorded, both approaches may retrieve comparable patterns of community change, and detect similar ecological gradients influencing such changes. We compared results obtained with morphological identification at family level of macroinvertebrates collected at 80 streams under a Water Framework Directive biomonitoring program in Portugal, with results obtained with metabarcoding from the ethanol preserving the bulk samples, using either single (COI-M19BR2, 16S-Inse01, 18S-Euka02) or multiple markers. Metabarcoding recorded less families and different communities compared to morphotaxonomy, but community sensitivities to disturbance estimated with the IASPT index were more similar across approaches. Spatial variation in local community metrics and the factors influencing such variation were significantly correlated between morphotaxonomy and metabarcoding. After reducing random noise in the dissimilarity matrices, the spatial variation in community composition was also significantly correlated across methods. A dominant gradient of community change was consistently retrieved, and all methods identified a largely similar set of anthropogenic stressors strongly influencing such gradient. Overall, results confirm our initial hypothesis, suggesting that morphotaxonomy and metabarcoding can estimate consistent spatial patterns of community variation and their main drivers. These results are encouraging for macroinvertebrate biomonitoring using metabarcoding approaches, suggesting that they can be intercalibrated with morphotaxonomic approaches to recover equivalent spatial and temporal gradients of ecological change.

Issues of under-representation in quantitative DNA metabarcoding weaken the inference about diet of the tundra vole Microtus oeconomus

During the last decade, methods based on high-throughput sequencing such as DNA metabarcoding have opened up for a range of new questions in animal dietary studies. One of the major advantages of dietary metabarcoding resides in the potential to infer a quantitative relationship between sequence read proportions and biomass of ingested food. However, this relationship's robustness is highly dependent on the system under study, calling for case-specific assessments. Herbivorous small rodents often play important roles in the ecosystem, and the use of DNA metabarcoding for analyses of rodent diets is increasing. However, there has been no direct validation of the quantitative reliability of DNA metabarcoding for small rodents. Therefore, we used an experimental approach to assess the relationship between input plant biomass and sequence reads proportions from DNA metabarcoding in the tundra vole Microtus oeconomus. We found a weakly positive relationship between the number of high-throughput DNA sequences and the expected biomass proportions of food plants. The weak relationship was possibly caused by a systematic under-amplification of one of the three plant taxa fed. Generally, our results add to the growing evidence that case-specific validation studies are required to reliably make use of sequence read abundance as a proxy of relative food proportions in the diet.

Relative species abundance estimation in artificial mixtures of insects using mito-metagenomics and a correction factor for the mitochondrial DNA copy number

Mito-metagenomics (MMG) is becoming an alternative to amplicon metabarcoding for the assessment of biodiversity in complex biological samples using high-throughput sequencing. Whereas MMG overcomes the biases introduced by the PCR step in the generation of amplicons, it is not yet a technique free of shortcomings. First, as the reads are obtained from shotgun sequencing, a very low proportion of reads map into the mitogenomes, so a high sequencing effort is needed. Second, as the number of mitogenomes per cell can vary among species, the relative species abundance (RSA) in a mixture could be wrongly estimated. Here, we challenge the MMG method to estimate the RSA using artificial libraries of 17 insect species whose complete genomes are available on public repositories. With fresh specimens of these species, we created single-species libraries to calibrate the bioinformatic pipeline and mixed-species libraries to estimate the RSA. Our results showed that the MMG approach confidently recovers the species list of the mixtures, even when they contain congeneric species. The method was also able to estimate the abundance of a species across different samples (within-species estimation) but failed to estimate the RSA within a single sample (across-species estimation) unless a correction factor accounting for the variable number of mitogenomes per cell was used. To estimate this correction factor, we used the proportion of reads mapping into mitogenomes in the single-species libraries and the lengths of the whole genomes and mitogenomes.

Biases in bulk: DNA metabarcoding of marine communities and the methodology involved

With the growing anthropogenic pressure on marine ecosystems, the need for efficient monitoring of biodiversity grows stronger. DNA metabarcoding of bulk samples is increasingly being implemented in ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on morphology. However, before raw sequences are obtained from bulk samples, a profound number of methodological choices must be made. Here, we critically review the recent methods used for metabarcoding of marine bulk samples (including benthic, plankton and diet samples) and indicate how potential biases can be introduced throughout sampling, preprocessing, DNA extraction, marker and primer selection, PCR amplification and sequencing. From a total of 64 studies evaluated, our recommendations for best practices include to (a) consider DESS as a fixative instead of ethanol, (b) use the DNeasy PowerSoil kit for any samples containing traces of sediment, (c) not limit the marker selection to COI only, but preferably include multiple markers for higher taxonomic resolution, (d) avoid touchdown PCR profiles, (e) use a fixed annealing temperature for each primer pair when comparing across studies or institutes, (f) use a minimum of three PCR replicates, and (g) include both negative and positive controls. Although the implementation of DNA metabarcoding still faces several technical complexities, we foresee wide-ranging advances in the near future, including improved bioinformatics for taxonomic assignment, sequencing of longer fragments and the use of whole-genome information. Despite the bulk of biases involved in metabarcoding of bulk samples, if appropriate controls are included along the data generation process, it is clear that DNA metabarcoding provides a valuable tool in ecosystem assessments.

All together now: Limitations and recommendations for the simultaneous analysis of all eukaryotic soil sequences

The soil environment contains a large, but historically underexplored, reservoir of biodiversity. Sequencing prokaryotic marker genes has become commonplace for the discovery and characterization of soil bacteria and archaea. Increasingly, this approach is also applied to eukaryotic marker genes to characterize the diversity and distribution of soil eukaryotes. However, understanding the properties and limitations of eukaryotic marker sequences is essential for correctly analysing, interpreting, and synthesizing the resulting data. Here, we illustrate several biases from sequencing data that affect measurements of biodiversity that arise from variation in morphology, taxonomy and phylogeny between organisms, as well as from sampling designs. We recommend analytical approaches to overcome these limitations, and outline how the benchmarking and standardization of sequencing protocols may improve the comparability of the data.

Developing a non-destructive metabarcoding protocol for detection of pest insects in bulk trap catches

Metabarcoding has the potential to revolutionise insect surveillance by providing high-throughput and cost-effective species identification of all specimens within mixed trap catches. Nevertheless, incorporation of metabarcoding into insect diagnostic laboratories will first require the development and evaluation of protocols that adhere to the specialised regulatory requirements of invasive species surveillance. In this study, we develop a multi-locus non-destructive metabarcoding protocol that allows sensitive detection of agricultural pests, and subsequent confirmation using traditional diagnostic techniques. We validate this protocol for the detection of tomato potato psyllid (Bactericera cockerelli) and Russian wheat aphid (Diuraphis noxia) within mock communities and field survey traps. We find that metabarcoding can reliably detect target insects within mixed community samples, including specimens that morphological identification did not initially detect, but sensitivity appears inversely related to community size and is impacted by primer biases, target loci, and sample indexing strategy. While our multi-locus approach allowed independent validation of target detection, lack of reference sequences for 18S and 12S restricted its usefulness for estimating diversity in field samples. The non-destructive DNA extraction proved invaluable for resolving inconsistencies between morphological and metabarcoding identification results, and post-extraction specimens were suitable for both morphological re-examination and DNA re-extraction for confirmatory barcoding.

The problem of omnivory: A synthesis on omnivory and DNA metabarcoding

Dietary analysis using DNA metabarcoding is a powerful tool that is increasingly being used to further our knowledge of trophic interactions in highly complex food webs but is not without limitations. Omnivores, the most generalist of consumers, pose unique challenges when using such methods. Here, we provide the rationale to understand the problems associated with analysing the complex diets of omnivores. By reviewing existing metabarcoding studies of omnivorous diet, and constructing hypothetical scenarios arising from each, we outline that great caution is required when interpreting sequencing data in such cases. In essence, the problems of accidental consumption and secondary ingestion are significant sources of error when investigating omnivorous diets. The integration of multiple high throughput sequencing markers increases the taxonomic breadth of taxa detected but we reveal how some detections may be misleading. Disentangling which taxa have been deliberately or accidentally consumed by the focal omnivore is challenging and can falsely emphasise those that were not intentionally consumed, obscuring biologically meaningful interactions. Although we suggest ways to disentangle these issues, we urge that the results of such analyses should be interpreted with caution and all possible scenarios for the presence of biota within omnivores given due consideration.

Quantitative assessment of fish larvae community composition in spawning areas using metabarcoding of bulk samples

Accurate assessment of larval community composition in spawning areas is essential for fisheries management and conservation but is often hampered by the cryptic nature of many larvae, which renders them difficult to identify morphologically. Metabarcoding is a rapid and cost-effective method to monitor early life stages for management and environmental impact assessment purposes but its quantitative capability is under discussion. We compared metabarcoding with traditional morphological identification to evaluate taxonomic precision and reliability of abundance estimates, using 332 fish larvae from multinet hauls (0-50 m depth) collected at 14 offshore sampling sites in the Irish and Celtic seas. To improve quantification accuracy (relative abundance estimates), the amount of tissue for each specimen was standardized and mitochondrial primers (12S gene) with conserved binding sites were used. Relative family abundance estimated from metabarcoding reads and morphological assessment were positively correlated, as well as taxon richness (R_S  = 0.81, P = 0.007) and diversity (R_S  = 0.90, P = 0.002). Spatial patterns of community composition did not differ significantly between metabarcoding and morphological assessments. Our results show that DNA metabarcoding of bulk tissue samples can be used to monitor changes in fish larvae abundance and community composition. This represents a feasible, efficient, and faster alternative to morphological methods that can be applied to terrestrial and aquatic habitats.

Isotope analysis combined with DNA barcoding provide new insights into the dietary niche of khulan in the Mongolian Gobi

With increasing livestock numbers, competition and avoidance are increasingly shaping resource availability for wild ungulates. Shifts in the dietary niche of wild ungulates are likely and can be expected to negatively affect their fitness. The Mongolian Gobi constitutes the largest remaining refuge for several threatened ungulates, but unprecedentedly high livestock numbers are sparking growing concerns over rangeland health and impacts on threatened ungulates like the Asiatic wild ass (khulan). Previous stable isotope analysis of khulan tail hair from the Dzungarian Gobi suggested that they graze in summer but switch to a poorer mixed C3 grass / C4 shrub diet in winter, most likely in reaction to local herders and their livestock. Here we attempt to validate these findings with a different methodology, DNA metabarcoding. Further, we extend the scope of the original study to the South Gobi Region, where we expect higher proportions of low-quality browse in the khulan winter diet due to a higher human and livestock presence. Barcoding confirmed the assumptions behind the seasonal diet change observed in the Dzungarian Gobi isotope data, and new isotope analysis revealed a strong seasonal pattern and higher C4 plant intake in the South Gobi Region, in line with our expectations. However, DNA barcoding revealed C4 domination of winter diet was due to C4 grasses (rather than shrubs) for the South Gobi Region. Slight climatic differences result in regional shifts in the occurrence of C3 and C4 grasses and shrubs, which do not allow for an isotopic separation along the grazer-browser continuum over the entire Gobi. Our findings do not allow us to confirm human impacts upon dietary preferences in khulan as we lack seasonal samples from the South Gobi Region. However, these data provide novel insight into khulan diet, raise new questions about plant availability versus preference, and provide a cautionary tale about indirect analysis methods if used in isolation or extrapolated to the landscape level. Good concordance between relative read abundance of C4 genera from barcoding and proportion of C4 plants from isotope analysis adds to a growing body of evidence that barcoding is a promising quantitative tool to understand resource partitioning in ungulates.

DNA metabarcoding of zooplankton communities: species diversity and seasonal variation revealed by 18S rRNA and COI

Background

Zooplankton is an important component of aquatic organisms and has important biological and economical significance in freshwater ecosystems. However, traditional methods that rely on morphology to classify zooplankton require expert taxonomic skills. Moreover, traditional classification methods are time-consuming and labor-intensive, which is not practical for the design of conservation measures and ecological management tools based on zooplankton diversity assessment.

Methods

We used DNA metabarcoding technology with two different markers: the nuclear small subunit ribosomal RNA (18S rRNA) and mitochondrial cytochrome c oxidase (COI), to analyze 72 zooplankton samples collected in 4 seasons and 9 locations from the Sanmenxia Reservoir. We investigated seasonal changes in the zooplankton community and their relationship with water environmental factors.

Results

A total of 190 species of zooplankton were found, belonging to 12 phyla, 24 classes, 61 orders, 111 families, and 174 genera. Protozoa, especially ciliates, were the most diverse taxa. Richness and relative abundance of zooplankton showed significant seasonal changes. Both alpha and beta diversity showed seasonal trends: the diversity in summer and autumn was higher than that in winter and spring. The zooplankton diversity was most similar in winter and spring. By correlating metabarcoding data and water environmental factors, we proved that water temperature, chemical oxygen demand, total nitrogen and ammoniacal nitrogen were the main environmental factors driving the seasonal changes in zooplankton in the Sanmenxia Reservoir. Water temperature, followed by total nitrogen, were the most influential factors. This study highlights the advantages and some limitations of zooplankton molecular biodiversity assessment using two molecular markers.

Resolving Food-Web Structure

Food webs are a major focus and organizing theme of ecology, but the data used to assemble them are deficient. Early debates over food-web data focused on taxonomic resolution and completeness, lack of which had produced spurious inferences. Recent data are widely believed to be much better and are used extensively in theoretical and meta-analytic research on network ecology. Confidence in these data rests on the assumptions ( a) that empiricists correctly identified consumers and their foods and ( b) that sampling methods were adequate to detect a near-comprehensive fraction of the trophic interactions between species. Abundant evidence indicates that these assumptions are often invalid, suggesting that most topological food-web data may remain unreliable for inferences about network structure and underlying ecological and evolutionary processes. Morphologically cryptic species are ubiquitous across taxa and regions, and many trophic interactions routinely evade detection by conventional methods. Molecular methods have diagnosed the severity of these problems and are a necessary part of the cure.

NGS-based barcoding with mini-COI gene target is useful for pet food market surveys aimed at mislabelling detection

Pet food industry has grown considerably in the last few years and it is expected to continue with this rate. Despite the economic impact of this sector and the consumer concerns for the increasing number of food and feed adulteration cases, few studies have been published on mislabelling in pet foods. We therefore investigated the capability of a next generation sequencing-based mini-barcoding approach to identify animal species in pet food products. In a preliminary analysis, a 127 bp fragment of the COI gene was tested on both individual specimens and ad hoc mixed fresh samples used as testers, to evaluate its discrimination power and primers effectiveness. Eighteen pet food products of different price categories and forms available on the market (i.e. kibbles, bites, pâté and strips) were analysed through an NGS approach in biological replicates. At least one of the species listed in the ingredients was not detected in half of the products, while seven products showed supplementary species in addition to those stated on the label. Due to the accuracy, sensitivity and specificity demonstrated, this method can be proposed as food genetic traceability system to evaluate both the feed and food quality timely along the supply chain.

A trophic latitudinal gradient revealed in anchovy and sardine from the Western Mediterranean Sea using a multi-proxy approach

This work combines state-of-the-art methods (DNA metabarcoding) with classic approaches (visual stomach content characterization and stable isotope analyses of nitrogen (δ¹⁵N) and carbon (δ¹³C)) to investigate the trophic ecology of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) at high taxonomic and spatial resolution in the Western Mediterranean Sea. Gut contents observed are in accordance with the dietary plasticity generally described for anchovy and sardine, suggesting a diet related to the opportunistic ingestion of available prey in a certain area and/or time. Genetic tools also showed modest inter-specific differences regarding ingested species. However, inter-specific and intra-specific differences in ingested prey frequencies and prey biomass reflected a latitudinal signal that could indicate a more effective predation on large prey like krill by anchovy versus sardine, as well as a generalized higher large prey ingestion by both species southwards. In fact, both species presented lower δ¹⁵N in the northernmost area. This latitudinal gradient indicates changes in the trophic ecology of anchovy and sardine that coincide with previously described better biological conditions for fish in the southern part of the study area as well as higher landings of both species in recent years.

Large-scale molecular barcoding of prey DNA reveals predictors of intrapopulation feeding diversity in a marine predator

Predator-prey interactions are critical in understanding how communities function. However, we need to describe intraspecific variation in diet to accurately depict those interactions. Harbor seals (Phoca vitulina) are an abundant marine predator that prey on species of conservation concern. We estimated intrapopulation feeding diversity (variation in feeding habits between individuals of the same species) of harbor seals in the Salish Sea. Estimates of feeding diversity were examined relative to sex, month, and location using a novel approach that combined molecular techniques, repeated cross-sectional sampling of scat, and a specialization metric (within-individual consistency in diet measured by the Proportional Similarity Index ( P S i )). Based on 1,083 scat samples collected from five haul-out sites during four nonsequential years, we quantified diet using metabarcoding techniques and determined the sex of the scat depositor using a molecular assay. Results suggest that intrapopulation feeding diversity was present. Specialization was high over short periods (24-48 hr, P S i  = 0.392, 95% CI = 0.013, R = 100,000) and variable in time and space. Females showed more specialization than males, particularly during summer and fall. Additionally, demersal and benthic prey species were correlated with more specialized diets. The latter finding suggests that this type of prey likely requires specific foraging strategies and that there are trade-offs between pelagic and benthic foraging styles for harbor seals. This differential feeding on prey species, as well as between sexes of harbor seals, indicates that predator-prey interactions in harbor seals are complex and that each sex may have a different impact on species of conservation concern. As such, describing intrapopulation feeding diversity may unravel hitherto unknown complex predator-prey interactions in the community.

A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton

The past 30 years have seen both a surge of interest in assessing ecological interactions using tools borrowed from network theory and an explosion of data on the occurrence of microbial symbionts thanks to next-generation sequencing. Given that classic network methods cannot currently measure the respective effects of different environmental and biological drivers on network structure, we here present two methods to elucidate the determinants of bipartite interaction networks. The first method is based on classifications and compares communities within networks to the grouping of nodes by treatment or similar controlling groups. The second method assesses the link between multivariate explanatory variables and network structure using redundancy analyses after singular value decomposition. In both methods, the significance of effects can be gauged through two randomizations. Our methods were applied to experimental data on Daphnia magna and its interactions with gut microbiota and bacterioplankton. The whole network was affected by Daphnia's diet (algae and/or cyanobacteria) and sample type, but not by Daphnia genotype. At coarse grains, bacterioplankton and gut microbiota communities were different. At this scale, the structure of the gut microbiota-based network was not linked to any explanatory factors, while the bacterioplankton-based network was related to both Daphnia's diet and genotype. At finer grains, Daphnia's diet and genotype affected both microbial networks, but the effect of diet on gut microbiota network structure was mediated solely by differences in microbial richness. While no reciprocal effect between the microbial communities could be found, fine-grained analyses presented a more nuanced picture, with bacterioplankton likely affecting the composition of the gut microbiota. Our methods are widely applicable to bipartite networks, can elucidate both controlled and environmental effects in experimental setting using a large amount of sequencing data and can tease apart reciprocal effects of networks on one another. The twofold approach we propose has the advantage of being able to tease apart effects at different scales of network structure, thus allowing for detailed assessment of reciprocal effects of linked networks on one another. As such, our network methods can help ecologists understand huge datasets reporting microbial co-occurrences within different hosts.

Combining a COI Mini-Barcode with Next-Generation Sequencing for Animal Origin Ingredients Identification in Processed Meat Product

For revealing animal species in complex or adulterated processed meat product, we presented a method combining a novel cytochrome oxidase I (COI) mini-barcode with next-generation sequencing (NGS), which identifies various animal species (swine, bovine, Caprinae, and some of fish, shrimp, and poultry) accurately and efficiently in processed meat products. We designed a universal primer based on 140 sequences from 51 edible animal species. A mixture of 12 species raw meat samples were identified with the clone sequencing and also with a mini-barcode- (136 bp) combined NGS method, respectively. The mini-barcode of these 12 species was 100% identical to the target species sequence by Sanger sequencing. Compared to the clone sequencing method, the NGS method is superior in accuracy, sensitivity, and detection efficiency. Various edible animal species were identified in the species level both in the mixed samples and the 7 heavily processed food products. Moreover, some unlabeled species and dubious contamination were detected as well.

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

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

Point-of-care diagnostic (POCD) method for detecting Bursaphelenchus xylophilus in pinewood using recombinase polymerase amplification (RPA) with the portable optical isothermal device (POID)

The pinewood nematode (PWN), Bursaphelenchus xylophilus, is a causative agent of pine wilt disease (PWD). To date, although several molecular diagnostic methods have been developed, rapid on-site diagnostic tools for detecting PWN in pinewood are limited. In this study, a point of care diagnostic (POCD) method for detecting PWN in pinewood using recombinase polymerase amplification (RPA) assay was developed. This method comprises quick gDNA extraction buffer (DAP buffer) for the direct extraction of gDNA of PWN from pinewood and a battery-mounted portable optical isothermal device (POID) for the detection of PWD in the field. The RPA assay can distinguish between the PWN and its conspecies which exist in pinewood and can complete diagnostic procedures within 25 min in the field. Moreover, the RPA assay can detect PWN in old wood samples in both natural and stored conditions. The POCD-RPA assay to detect PWN will be useful for epidemiological investigations in the field as well as for quarantine processes in the wood trade.

Species in the faeces: DNA metabarcoding as a method to determine the diet of the endangered yellow-eyed penguin

Abstract Context. Diet variability is a significant driver of seabird decline; however, data on seabird diet composition and trends have been affected by changes in precision and resolution owing to the evolution of different sampling methods over time. We investigated the effectiveness of applying a passive molecular diet method using faeces obtained from the endangered yellow-eyed penguin. Aims. To assess the feasibility of applying DNA metabarcoding methods to yellow-eyed penguin faeces to evaluate diet, and to compare the reliability of diet results derived from adults and chicks, and from latrine versus fresh faecal samples. Methods. We collected 313 faecal samples from yellow-eyed penguins resident on the Otago coast of New Zealand from October 2016 to August 2017. We used polymerase chain reaction (PCR) with mitochondrial 16S cephalopod and chordate primers to amplify prey DNA present in the faecal samples, and tested the completeness of our assembled reference databases based on previous diet research. Amplified prey DNA sequences were then assigned to taxa from our reference databases by using QIIME2. Key results. Mitochondrial 16S chordate PCR primers were effective at identifying 29 fish taxa, with 98.3% of amplified sequences being identified to species or genus level in 193 samples (61.7% collected). There was no significant difference in the number, occurrence or proportion of ray-finned fish prey DNA sequences derived from fresh samples or latrines. Mitochondrial 16S cephalopod PCR primers classified 1.98% of amplified DNA sequences as targets, with 96.5% of these target sequences being identified to species or genus level in 48 samples (15.3% collected), and five taxa identified. Conclusions. We recommend the collection of latrine samples to enable long-term monitoring of the diet of yellow-eyed penguins, which will optimise the trade-off between wildlife disturbance and dietary resolution. Further refinement is needed to identify cephalopod dietary components for yellow-eyed penguins, because our cephalopod primers were not as specific as those used for ray-finned fishes, amplifying a large number (&gt;98%) of non-cephalopod species. Implications. DNA metabarcoding offers a robust and comprehensive alternative to other, more intrusive, seabird diet-assessment methods, but still requires parallel studies to provide critical information on prey size, true diet composition and diet quality.

Insectivorous bats selectively source moths and eat mostly pest insects on dryland and irrigated cotton farms

Insectivorous bats are efficient predators of pest arthropods in agroecosystems. This pest control service has been estimated to be worth billions of dollars to agriculture globally. However, few studies have explicitly investigated the composition and abundance of dietary prey items consumed or assessed the ratio of pest and beneficial arthropods, making it difficult to evaluate the quality of the pest control service provided. In this study, we used metabarcoding to identify the prey items eaten by insectivorous bats over the cotton-growing season in an intensive cropping region in northern New South Wales, Australia. We found that seven species of insectivorous bat (n = 58) consumed 728 prey species, 13 of which represented around 50% of total prey abundance consumed. Importantly, the identified prey items included major arthropod pests, comprising 65% of prey relative abundance and 13% of prey species recorded. Significant cotton pests such as Helicoverpa punctigera (Australian bollworm) and Achyra affinitalis (cotton webspinner) were detected in at least 76% of bat fecal samples, with Teleogryllus oceanicus (field crickets), Helicoverpa armigera (cotton bollworm), and Crocidosema plebejana (cotton tipworm) detected in 55% of bat fecal samples. Our results indicate that insectivorous bats are selective predators that exploit a narrow selection of preferred pest taxa and potentially play an important role in controlling lepidopteran pests on cotton farms. Our study provides crucial information for farmers to determine the service or disservice provided by insectivorous bats in relation to crops, for on-farm decision making.