An improved method for utilizing high‐throughput amplicon sequencing to determine the diets of insectivorous animals

DNA analysis of predator faeces using high‐throughput amplicon sequencing (HTS) enhances our understanding of predator–prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (COI). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair “ZBJ” to results using the novel primer pair “ANML.” To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single‐copy (cloned) COI sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre‐ and post‐PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%), whereas ZBJ amplified 24–40 of 59 taxa (41%–68%). Furthermore, in an HTS comparison of field‐collected samples, the ANML primers detected nearly fourfold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.     

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.     

Environmental DNA metabarcoding of wild flowers reveals diverse communities of terrestrial arthropods

Terrestrial arthropods comprise the most species‐rich communities on Earth, and grassland flowers provide resources for hundreds of thousands of arthropod species. Diverse grassland ecosystems worldwide are threatened by various types of environmental change, which has led to decline in arthropod diversity. At the same time, monitoring grassland arthropod diversity is time‐consuming and strictly dependent on declining taxonomic expertise. Environmental DNA (eDNA) metabarcoding of complex samples has demonstrated that information on species compositions can be efficiently and non‐invasively obtained. Here, we test the potential of wild flowers as a novel source of arthropod eDNA. We performed eDNA metabarcoding of flowers from several different plant species using two sets of generic primers, targeting the mitochondrial genes 16S rRNA and COI. Our results show that terrestrial arthropod species leave traces of DNA on the flowers that they interact with. We obtained eDNA from at least 135 arthropod species in 67 families and 14 orders, together representing diverse ecological groups including pollinators, parasitoids, gall inducers, predators, and phytophagous species. Arthropod communities clustered together according to plant species. Our data also indicate that this experiment was not exhaustive, and that an even higher arthropod richness could be obtained using this eDNA approach. Overall, our results demonstrate that it is possible to obtain information on diverse communities of insects and other terrestrial arthropods from eDNA metabarcoding of wild flowers. This novel source of eDNA represents a vast potential for addressing fundamental research questions in ecology, obtaining data on cryptic and unknown species of plant‐associated arthropods, as well as applied research on pest management or conservation of endangered species such as wild pollinators.     

Disparities in second‐generation DNA metabarcoding results exposed with accessible and repeatable workflows

Different second‐generation sequencing technologies may have taxon‐specific biases when DNA metabarcoding prey in predator faeces. Our major objective was to examine differences in prey recovery from bat guano across two different sequencing workflows using the same faecal DNA extracts. We compared results between the Ion Torrent PGM and the Illumina MiSeq with similar library preparations and the same analysis pipeline. We focus on repeatability and provide an R Notebook in an effort towards transparency for future methodological improvements. Full documentation of each step enhances the accessibility of our analysis pipeline. We tagged DNA from insectivorous bat faecal samples, targeted the arthropod cytochrome c oxidase I minibarcode region and sequenced the product on both second‐generation sequencing platforms. We developed an analysis pipeline with a high operational taxonomic unit (OTU) clustering threshold (i.e., ≥98.5%) followed by copy number filtering to avoid merging rare but genetically similar prey into the same OTUs. With this workflow, we detected 297 unique prey taxa, of which 74% were identified at the species level. Of these, 104 (35%) prey OTUs were detected by both platforms, 176 (59%) OTUs were detected by the Illumina MiSeq system only, and 17 (6%) OTUs were detected using the Ion Torrent system only. Costs were similar between platforms but the Illumina MiSeq recovered six times more reads and four additional insect orders than did Ion Torrent. The considerations we outline are particularly important for long‐term ecological monitoring; a more standardized approach will facilitate comparisons between studies and allow faster recognition of changes within ecological communities.     

Using faecal metabarcoding to examine consumption of crop pests and beneficial arthropods in communities of generalist avian insectivores

Generalist insectivorous birds can provide ecosystem services in agricultural landscapes by consuming arthropod pests, or they can provide disservices when they consume beneficial arthropods. To examine bird impacts on arthropod communities, including pest control services, we need to know which arthropods birds commonly consume. Faecal metabarcoding is an emerging technique that can be used to identify prey from faecal samples, often to the species level. We used faecal metabarcoding to study diets of birds inhabiting the ecotone between soybean fields and adjacent grasslands in a largely agricultural landscape in Illinois, USA, during the summer of 2017. Whereas previous studies have used faecal metabarcoding to compare bird diets among species or among capture sites, we analysed samples from multiple species within a community at replicate sites. We collected and sequenced DNA from 132 faecal samples from 25 bird species captured at six sites. We found that birds consumed an extremely large and varied diet that differed among both species and sites, suggesting that birds were consuming prey opportunistically as available at each site. Of the nine most commonly detected prey species, three are known pests of soybeans. Bird diets also contained significantly more species of herbivorous prey than natural enemies. Finally, we discovered that American Goldfinches Spinus tristis, a highly granivorous species, may consume arthropods more frequently than expected and thus may provide ecosystem services in agricultural landscapes. Our study demonstrates that birds within this system consume a large variety of prey, suggesting that they may be able to respond quickly to pest outbreaks and contribute to agricultural resiliency.     

Toward an ecoregion scale evaluation of eDNA metabarcoding primers: A case study for the freshwater fish biodiversity of the Murray–Darling Basin (Australia)

High‐throughput sequencing of environmental DNA (i.e., eDNA metabarcoding) has become an increasingly popular method for monitoring aquatic biodiversity. At present, such analyses require target‐specific primers to amplify DNA barcodes from co‐occurring species, and this initial amplification can introduce biases. Understanding the performance of different primers is thus recommended prior to undertaking any metabarcoding initiative. While multiple software programs are available to evaluate metabarcoding primers, all programs have their own strengths and weaknesses. Therefore, a robust in silico workflow for the evaluation of metabarcoding primers will benefit from the use of multiple programs. Furthermore, geographic differences in species biodiversity are likely to influence the performance of metabarcoding primers and further complicate the evaluation process. Here, an in silico workflow is presented that can be used to evaluate the performance of metabarcoding primers on an ecoregion scale. This workflow was used to evaluate the performance of published and newly developed eDNA metabarcoding primers for the freshwater fish biodiversity of the Murray–Darling Basin (Australia). To validate the in silico workflow, a subset of the primers, including one newly designed primer pair, were used in metabarcoding analyses of an artificial DNA community and eDNA samples. The results show that the in silico workflow allows for a robust evaluation of metabarcoding primers and can reveal important trade‐offs that need to be considered when selecting the most suitable primer. Additionally, a new primer pair was described and validated that allows for more robust taxonomic assignments and is less influenced by primer biases compared to commonly used fish metabarcoding primers.     

eDNA metabarcoding of avocado flowers: ‘Hass’ it got potential to survey arthropods in food production systems?

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (Persea americana—‘Hass’ avocado), with two conventional survey techniques: digital video recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 h of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Environmental DNA metabarcoding from flowers revealed potential arthropod pollinators, as well as plant pests and parasites. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. eDNA metabarcoding of flowers has the potential to revolutionize the way arthropod communities are monitored in natural and agro-ecosystems, potentially detecting the response of pollinators and pests to climate change, diseases, habitat loss and other disturbances.     

Metabarcoding for the parallel identification of several hundred predators and their prey: Application to bat species diet analysis

Assessing diet variability is of main importance to better understand the biology of bats and design conservation strategies. Although the advent of metabarcoding has facilitated such analyses, this approach does not come without challenges. Biases may occur throughout the whole experiment, from fieldwork to biostatistics, resulting in the detection of false negatives, false positives or low taxonomic resolution. We detail a rigorous metabarcoding approach based on a short COI minibarcode and two‐step PCR protocol enabling the “all at once” taxonomic identification of bats and their arthropod prey for several hundreds of samples. Our study includes faecal pellets collected in France from 357 bats representing 16 species, as well as insect mock communities that mimic bat meals of known composition, negative and positive controls. All samples were analysed using three replicates. We compare the efficiency of DNA extraction methods, and we evaluate the effectiveness of our protocol using identification success, taxonomic resolution, sensitivity and amplification biases. Our parallel identification strategy of predators and prey reduces the risk of mis‐assigning prey to wrong predators and decreases the number of molecular steps. Controls and replicates enable to filter the data and limit the risk of false positives, hence guaranteeing high confidence results for both prey occurrence and bat species identification. We validate 551 COI variants from arthropod including 18 orders, 117 family, 282 genus and 290 species. Our method therefore provides a rapid, resolutive and cost‐effective screening tool for addressing evolutionary ecological issues or developing “chirosurveillance” and conservation strategies.     

Agriculture shapes the trophic niche of a bat preying on multiple pest arthropods across Europe: Evidence from DNA metabarcoding

The interaction between agricultural production and wildlife can shape, and even condition, the functioning of both systems. In this study, we i) explored the degree to which a widespread European bat, namely the common bent‐wing bat Miniopterus schreibersii, consumes crop‐damaging insects at a continental scale, and ii) tested whether its dietary niche is shaped by the extension and type of agricultural fields. We employed a dual‐primer DNA metabarcoding approach to characterize arthropod 16S and COI DNA sequences within bat faecal pellets collected across 16 Southern European localities, to first characterize the bat species’ dietary niche, second measure the incidence of agricultural pests across their ranges and third assess whether geographical dietary variation responds to climatic, landscape diversity, agriculture type and vegetation productivity factors. We detected 12 arthropod orders, among which lepidopterans were predominant. We identified >200 species, 44 of which are known to cause agricultural damage. Pest species were detected at all but one sampling site and in 94% of the analysed samples. Furthermore, the dietary diversity of M. schreibersii exhibited a negative linear relation with the area of intensive agricultural fields, thus suggesting crops restrict the dietary niche of bats to prey taxa associated with agricultural production within their foraging range. Overall, our results imply that M. schreibersii might be a valuable asset for biological pest suppression in a variety of agricultural productions and highlight the dynamic interplay between wildlife and agricultural systems.     

Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

Environmental DNA studies targeting multiple taxa using metabarcoding provide remarkable insights into levels of species diversity in any habitat. The main drawbacks are the presence of primer bias and difficulty in identifying rare species. We tested a DNA sequence‐capture method in parallel with the metabarcoding approach to reveal possible advantages of one method over the other. Both approaches were performed using the same eDNA samples and the same 18S and COI regions, followed by high throughput sequencing. Metabarcoded eDNA libraries were PCR amplified with one primer pair from 18S and COI genes. DNA sequence‐capture libraries were enriched with 3,639 baits targeting the same gene regions. We tested amplicon sequence variants (ASVs) and operational taxonomic units (OTUs) in silico approaches for both markers and methods, using for this purpose the metabarcoding data set. ASVs methods uncovered more species for the COI gene, whereas the opposite occurred for the 18S gene, suggesting that clustering reads into OTUs could bias diversity richness especially using 18S with relaxed thresholds. Additionally, metabarcoding and DNA sequence‐capture recovered 80%–90% of the control sample species. DNA sequence‐capture was 8x more expensive, nonetheless it identified 1.5x more species for COI and 13x more genera for 18S than metabarcoding. Both approaches offer reliable results, sharing ca. 40% species and 72% families and retrieve more taxa when nuclear and mitochondrial markers are combined. eDNA metabarcoding is quite well established and low‐cost, whereas DNA‐sequence capture for biodiversity assessment is still in its infancy, is more time‐consuming but provides more taxonomic assignments.     

Needle in a haystack? A comparison of eDNA metabarcoding and targeted qPCR for detection of the great crested newt (Triturus cristatus)

Environmental DNA (eDNA) analysis is a rapid, cost‐effective, non‐invasive biodiversity monitoring tool which utilises DNA left behind in the environment by organisms for species detection. The method is used as a species‐specific survey tool for rare or invasive species across a broad range of ecosystems. Recently, eDNA and “metabarcoding” have been combined to describe whole communities rather than focusing on single target species. However, whether metabarcoding is as sensitive as targeted approaches for rare species detection remains to be evaluated. The great crested newt Triturus cristatus is a flagship pond species of international conservation concern and the first UK species to be routinely monitored using eDNA. We evaluate whether eDNA metabarcoding has comparable sensitivity to targeted real‐time quantitative PCR (qPCR) for T. cristatus detection. Extracted eDNA samples (N = 532) were screened for T. cristatus by qPCR and analysed for all vertebrate species using high‐throughput sequencing technology. With qPCR and a detection threshold of 1 of 12 positive qPCR replicates, newts were detected in 50% of ponds. Detection decreased to 32% when the threshold was increased to 4 of 12 positive qPCR replicates. With metabarcoding, newts were detected in 34% of ponds without a detection threshold, and in 28% of ponds when a threshold (0.028%) was applied. Therefore, qPCR provided greater detection than metabarcoding but metabarcoding detection with no threshold was equivalent to qPCR with a stringent detection threshold. The proportion of T. cristatus sequences in each sample was positively associated with the number of positive qPCR replicates (qPCR score) suggesting eDNA metabarcoding may be indicative of eDNA concentration. eDNA metabarcoding holds enormous potential for holistic biodiversity assessment and routine freshwater monitoring. We advocate this community approach to freshwater monitoring to guide management and conservation, whereby entire communities can be initially surveyed to best inform use of funding and time for species‐specific surveys.     

An appetite for pests: Synanthropic insectivorous bats exploit cotton pest irruptions and consume various deleterious arthropods

Conservation biological control (CBC) seeks to minimize the deleterious effects of agricultural pests by enhancing the efficiency of natural enemies. Despite the documented potential of insectivorous bats to consume pests, many synanthropic bat species are still underappreciated as beneficial species. We investigated the diet of Kuhl's pipistrelle (Pipistrellus kuhlii), a common synanthropic insectivorous bat that forages in urban and agricultural areas, to determine whether it may function as a natural enemy in CBC. Faecal samples of P. kuhlii were collected throughout the cotton‐growing season from five roost sites near cotton fields located in a Mediterranean agroecosystem, Israel, and analyzed using DNA metabarcoding. Additionally, data on estimated abundance of major cotton pests were collected. We found that the diet of P. kuhlii significantly varied according to sites and dates and comprised 27 species of agricultural pests that were found in 77.2% of the samples, including pests of key economic concern. The dominant prey was the widespread cotton pest, the pink bollworm, Pectinophora gossypiella, found in 31% of the samples and in all the roosts. Pink bollworm abundance was positively correlated with its occurrence in the bat diet. Furthermore, the bats’ dietary breadth narrowed, while temporal dietary overlap increased, in relation to increasing frequencies of pink bollworms in the diet. This suggests that P. kuhlii exploits pink bollworm irruptions by opportunistic feeding. We suggest that synanthropic bats provide important pest suppression services, may function as CBC agents of cotton pests and potentially contribute to suppress additional deleterious arthropods found in their diet in high frequencies.     

Environmental DNA metabarcoding primers for freshwater fish detection and quantification: In silico and in tanks

Environmental DNA (eDNA) techniques refer to utilizing the organisms’ DNA extracted from environment samples to genetically identify target species without capturing actual organisms. eDNA metabarcoding via high‐throughput sequencing can simultaneously detect multiple fish species from a single water sample, which is a powerful tool for the qualitative detection and quantitative estimates of multiple fish species. However, sequence counts obtained from eDNA metabarcoding may be influenced by many factors, of which primer bias is one of the foremost causes of methodological error. The performance of 18 primer pairs for COI, cytb, 12S rRNA, and 16S rRNA mitochondrial genes, which are all frequently used in fish eDNA metabarcoding, were evaluated in the current study. The ribosomal gene markers performed better than the protein‐coding gene markers during in silico screening, resulting in higher taxonomic coverage and appropriate barcode lengths. Four primer pairs—AcMDB07, MiFish‐U, Ve16S1, and Ve16S3—designed for various regions of the 12S and 16S rRNA genes were screened for tank metabarcoding in a case study targeting six freshwater fish species. The four primer pairs were able to accurately detect all six species in different tanks, while only MiFish‐U, Ve16S1, and Ve16S3 revealed a significant positive relationship between species biomass and read count for the pooled tank data. The positive relationship could not be found in all species within the tanks. Additionally, primer efficiency differed depending on the species while primer preferential species varied in different fish assemblages. This case study supports the potential for eDNA metabarcoding to assess species diversity in natural ecosystems and provides an alternative strategy to evaluate the performance of candidate primers before application of eDNA metabarcoding in natural ecosystems.     

Next‐generation monitoring of aquatic biodiversity using environmental DNA metabarcoding

Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present in the environment. In this study, we tested whether an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90–0.99) vs. 0.58 (CI = 0.50–0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA‐based approach has the potential to become the next‐generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.     

Using DNA metabarcoding for simultaneous inference of common vampire bat diet and population structure

Metabarcoding diet analysis has become a valuable tool in animal ecology; however, co‐amplified predator sequences are not generally used for anything other than to validate predator identity. Exemplified by the common vampire bat, we demonstrate the use of metabarcoding to infer predator population structure alongside diet assessments. Growing populations of common vampire bats impact human, livestock and wildlife health in Latin America through transmission of pathogens, such as lethal rabies viruses. Techniques to determine large‐scale variation in vampire bat diet and bat population structure would empower locality‐ and species‐specific projections of disease transmission risks. However, previously used methods are not cost‐effective and efficient for large‐scale applications. Using bloodmeal and faecal samples from common vampire bats from coastal, Andean and Amazonian regions of Peru, we showcase metabarcoding as a scalable tool to assess vampire bat population structure and feeding preferences. Dietary metabarcoding was highly effective, detecting vertebrate prey in 93.2% of the samples. Bats predominantly preyed on domestic animals, but fed on tapirs at one Amazonian site. In addition, we identified arthropods in 9.3% of samples, likely reflecting consumption of ectoparasites. Using the same data, we document mitochondrial geographic population structure in the common vampire bat in Peru. Such simultaneous inference of vampire bat diet and population structure can enable new insights into the interplay between vampire bat ecology and disease transmission risks. Importantly, the methodology can be incorporated into metabarcoding diet studies of other animals to couple information on diet and population structure.     

Assessing niche partitioning of co‐occurring sibling bat species by DNA metabarcoding

Niche partitioning through foraging is a mechanism likely involved in facilitating the coexistence of ecologically similar and co‐occurring animal species by separating their use of resources. Yet, this mechanism is not well understood in flying insectivorous animals. This is particularly true of bats, where many ecologically similar or cryptic species coexist. The detailed analysis of the foraging niche in sympatric, cryptic sibling species provides an excellent framework to disentangle the role of specific niche factors likely involved in facilitating coexistence. We used DNA metabarcoding to determine the prey species consumed by a population of sympatric sibling Rhinolophus euryale and Rhinolophus mehelyi whose use of habitat in both sympatric and allopatric ranges has been well established through radio tracking. Although some subtle dietary differences exist in prey species composition, the diet of both bats greatly overlapped (O_jk = 0.83) due to the consumption of the same common and widespread moths. Those dietary differences we did detect might be related to divergences in prey availabilities among foraging habitats, which prior radio tracking on the same population showed are differentially used and selected when both species co‐occur. This minor dietary segregation in sympatry may be the result of foraging on the same prey‐types and could contribute to reduce potential competitive interactions (e.g., for prey, acoustic space). Our results highlight the need to evaluate the spatial niche dimension in mediating the co‐occurrence of similar insectivorous bat species, a niche factor likely involved in processes of bat species coexistence.     

Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries

The extraction and characterization of DNA from aquatic environmental samples offers an alternative, noninvasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next‐generation sequencing (“metabarcoding”), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom‐designed group‐specific primer set and next‐generation sequencing for the detection of three species at risk (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada: the Grand River and the Sydenham River. Of 82 fish species detected in both rivers using capture‐based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co‐occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture‐based methods, for improved mapping of species distribution patterns.     

Dung‐associated arthropods influence foraging ecology and habitat selection in Black‐necked Cranes (Grus nigricollis) on the Qinghai–Tibet Plateau

Variation in grassland vegetation structure influences the habitat selection of insectivorous birds. This variation presents a trade‐off for insectivorous predators: Arthropod abundance increases with vegetation height and heterogeneity, but access to arthropod prey items decreases. In contrast, grazing by large herbivores reduces and homogenizes vegetation, decreasing total arthropod abundance and diversity. However, the presence of livestock dung may help counteract the overall reduction in invertebrates by increasing arthropods associated with dung. It is unclear, however, how the presence of arthropod prey in dung contributes to overall habitat selection for insectivorous birds or how dung‐associated arthropods affect trade‐offs between vegetation structure, arthropod abundance, and access to prey. To explore these relationships, we studied habitat selection of the Black‐necked Crane (Grus nigricollis), a large omnivorous bird that breeds on the Qinghai–Tibet Plateau. We assessed the relationships between habitat selection of cranes and vegetation structure, arthropod abundance, and the presence of yak dung. We found that Black‐necked Cranes disproportionately foraged in grassland patches with short sward height, low sward height heterogeneity, and high numbers of dry yak dung, despite these habitats having lower total arthropod abundance. Although total arthropod abundance is lower, these habitats are supplemented with dry yak dung, which are associated with coleopteran larvae, making dung pats an indicator of food resources for breeding Black‐necked Cranes. Coleopteran adults and larvae in yak dung appear to be an important factor influencing the habitat selection of Black‐necked Cranes and should be considered when assessing grassland foraging trade‐offs of insectivorous birds. This research provides new insights into the role of livestock dung in defining foraging habitats and resources for insectivorous predators.     

Taxon-specific PCR for DNA barcoding arthropod prey in bat faeces

The application of DNA barcoding to dietary studies allows prey taxa to be identified in the absence of morphological evidence and permits a greater resolution of prey identity than is possible through direct examination of faecal material. For insectivorous bats, which typically eat a great diversity of prey and which chew and digest their prey thoroughly, DNA-based approaches to diet analysis may provide the only means of assessing the range and diversity of prey within faeces. Here, we investigated the effectiveness of DNA barcoding in determining the diets of bat species that specialize in eating different taxa of arthropod prey. We designed and tested a novel taxon-specific primer set and examined the performance of short barcode sequences in resolving prey species. We recovered prey DNA from all faecal samples and subsequent cloning and sequencing of PCR products, followed by a comparison of sequences to a reference database, provided species-level identifications for 149/207 (72%) clones. We detected a phylogenetically broad range of prey while completely avoiding detection of nontarget groups. In total, 37 unique prey taxa were identified from 15 faecal samples. A comparison of DNA data with parallel morphological analyses revealed a close correlation between the two methods. However, the sensitivity and taxonomic resolution of the DNA method were far superior. The methodology developed here provides new opportunities for the study of bat diets and will be of great benefit to the conservation of these ecologically important predators.     

One‐locus‐several‐primers: A strategy to improve the taxonomic and haplotypic coverage in diet metabarcoding studies

In diet metabarcoding analyses, insufficient taxonomic coverage of PCR primer sets generates false negatives that may dramatically distort biodiversity estimates. In this paper, we investigated the taxonomic coverage and complementarity of three cytochrome c oxidase subunit I gene (COI) primer sets based on in silico analyses and we conducted an in vivo evaluation using fecal and spider web samples from different invertivores, environments, and geographic locations. Our results underline the lack of predictability of both the coverage and complementarity of individual primer sets: (a) sharp discrepancies exist observed between in silico and in vivo analyses (to the detriment of in silico analyses); (b) both coverage and complementarity depend greatly on the predator and on the taxonomic level at which preys are considered; (c) primer sets’ complementarity is the greatest at fine taxonomic levels (molecular operational taxonomic units [MOTUs] and variants). We then formalized the “one‐locus‐several‐primer‐sets” (OLSP) strategy, that is, the use of several primer sets that target the same locus (here the first part of the COI gene) and the same group of taxa (here invertebrates). The proximal aim of the OLSP strategy is to minimize false negatives by increasing total coverage through multiple primer sets. We illustrate that the OLSP strategy is especially relevant from this perspective since distinct variants within the same MOTUs were not equally detected across all primer sets. Furthermore, the OLSP strategy produces largely overlapping and comparable sequences, which cannot be achieved when targeting different loci. This facilitates the use of haplotypic diversity information contained within metabarcoding datasets, for example, for phylogeography and finer analyses of prey–predator interactions.