Dung beetles as samplers of mammals in Malaysian Borneo-a test of high throughput metabarcoding of iDNA

Testing and optimizing metabarcoding of iDNA from dung beetles to sample mammals in the hyperdiverse Neotropics

Over the past few years, insects have been used as samplers of vertebrate diversity by assessing the ingested-derived DNA (iDNA), and dung beetles have been shown to be a good mammal sampler given their broad feeding preference, wide distribution and easy sampling. Here, we tested and optimized the use of iDNA from dung beetles to assess the mammal community by evaluating if some biological and methodological aspects affect the use of dung beetles as mammal species samplers. We collected 403 dung beetles from 60 pitfall traps. iDNA from each dung beetle was sequenced by metabarcoding using two mini-barcodes (12SrRNA and 16SrRNA). We assessed whether dung beetles with different traits related to feeding, nesting and body size differed in the number of mammal species found in their iDNA. We also tested differences among four killing solutions in preserving the iDNA and compared the effectiveness of each mini barcode to recover mammals. We identified a total of 50 mammal OTUs (operational taxonomic unit), including terrestrial and arboreal species from 10 different orders. We found that at least one mammal-matching sequence was obtained from 70% of the dung beetle specimens. The number of mammal OTUs obtained did not vary with dung beetle traits as well as between the killing solutions. The 16SrRNA mini-barcode recovered a higher number of mammal OTUs than 12SrRNA, although both sets were partly non-overlapping. Thus, the complete mammal diversity may not be achieved by using only one of them. This study refines the methodology for routine assessment of tropical mammal communities via dung beetle 'samplers' and its universal applicability independently of the species traits of local beetle communities.

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects

Holistic insect monitoring needs scalable techniques to overcome taxon biases, determine species abundances, and gather functional traits for all species. This requires that we address taxonomic impediments and the paucity of data on abundance, biomass and functional traits. We here outline how these data deficiencies could be addressed at scale. The workflow starts with large-scale barcoding (megabarcoding) of all specimens from mass samples obtained at biomonitoring sites. The barcodes are then used to group the specimens into molecular operational taxonomic units that are subsequently tested/validated as species with a second data source (e.g. morphology). New species are described using barcodes, images and short diagnoses, and abundance data are collected for both new and described species. The specimen images used for species discovery then become the raw material for training artificial intelligence identification algorithms and collecting trait data such as body size, biomass and feeding modes. Additional trait data can be obtained from vouchers by using genomic tools developed by molecular ecologists. Applying this pipeline to a few samples per site will lead to greatly improved insect monitoring regardless of whether the species composition of a sample is determined with images, metabarcoding or megabarcoding. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Dietary metabarcoding reveals the simplification of bird-pest interaction networks across a gradient of agricultural cover

Agriculture is vital for supporting human populations, but its intensification often leads to landscape homogenization and a decline in non-provisioning ecosystem services. Ecological intensification and multifunctional landscapes are suggested as nature-based alternatives to intensive agriculture, using ecological processes like natural pest regulation to maximize food production. Birds are recognized for their role in increasing crop yields by consuming invertebrate pests in several agroecosystems. However, the understanding of how bird species, their traits and agricultural land cover influence the structure of bird-pest interactions remains limited. We sampled bird-pest interactions monthly for 1 year, at four sites within a multifunctional landscape, following a gradient of increasing agricultural land cover. We analysed 2583 droppings of 55 bird species with DNA metabarcoding and detected 225 pest species in 1139 samples of 42 bird species. As expected, bird-pest interactions were highly variable across bird species. Dietary pest richness was lower in the fully agricultural site, while predation frequency remained consistent across the agricultural land cover gradient. Network analysis revealed a reduction in the complexity of bird-pest interactions as agricultural coverage increased. Bird species abundance affected the bird's contribution to the network structure more than any of the bird traits analysed (weight, phenology, invertebrate frequency in diet and foraging strata), with more common birds being more important to network structure. Overall, our results show that increasing agricultural land cover increases the homogenization of bird-pest interactions. This shows the importance of maintaining natural patches within agricultural landscapes for biodiversity conservation and enhanced biocontrol.

Analysing the effects of distance, taxon and biomass on vertebrate detections using bulk-collected carrion fly iDNA

Invertebrate-derived DNA (iDNA) metabarcoding from carrion flies is a powerful, non-invasive tool that has value for assessing vertebrate diversity. However, unknowns exist around the factors that influence vertebrate detections, such as spatial limits to iDNA signals or if detections are influenced by taxonomic class or estimated biomass of the vertebrates of interest. Using a bulk-collection method, we captured flies from within a zoo and along transects extending 4 km away from this location. From 920 flies, we detected 28 vertebrate species. Of the 28 detected species, we identified 9 species kept at the zoo, 8 mammals and 1 bird, but no reptiles. iDNA detections were highly geographically localized, and only a few zoo animals were detected outside the zoo setting. However, due to the low number of detections in our dataset, we found no influence of the taxonomic group or the estimated biomass of animals on their detectability. Our data suggest that iDNA detections from bulk-collected carrion flies, at least in urban settings in Australia, are predominantly determined by geographic proximity to the sampling location. This study presents an important step in understanding how iDNA techniques can be used in biodiversity monitoring.

Mammal dung-dung beetle trophic networks: an improved method based on gut-content DNA

Background

Dung beetles provide many important ecosystem services, including dung decomposition, pathogen control, soil aeration, and secondary seed dispersal. Yet, the biology of most dung beetles remains unknown. Natural diets are poorly studied, partly because previous research has focused on choice or attraction experiments using few, easily accessible dung types from zoo animals, farm animals, or humans. This way, many links within natural food webs have certainly been missed. In this work, we aimed to establish a protocol to analyze the natural diets of dung beetles using DNA gut barcoding.

Methods

First, the feasibility of gut-content DNA extraction and amplification of 12s rDNA from six different mammal dung types was tested in the laboratory. We then applied the method to beetles caught in pitfall traps in Ecuador and Germany by using 12s rDNA primers. For a subset of the dung beetles caught in the Ecuador sampling, we also used 16s rDNA primers to see if these would improve the number of species we could identify. We predicted the likelihood of amplifying DNA using gut fullness, DNA concentration, PCR primer, collection method, and beetle species as predictor variables in a dominance analysis. Based on the gut barcodes, we generated a dung beetle-mammal network for both field sites (Ecuador and Germany) and analyzed the levels of network specificity.

Results

We successfully amplified mammal DNA from dung beetle gut contents for 128 specimens, which included such prominent species as Panthera onca (jaguar) and Puma concolor (puma). The overall success rate of DNA amplification was 53%. The best predictors for amplification success were gut fullness and DNA concentration, suggesting the success rate can be increased by focusing on beetles with a full gut. The mammal dung-dung beetle networks differed from purely random network models and showed a moderate degree of network specialization (H2': Ecuador = 0.49; Germany = 0.41).

Conclusion

We here present a reliable method of extracting and amplifying gut-content DNA from dung beetles. Identifying mammal dung via DNA reference libraries, we created mammal dung-dung beetle trophic networks. This has benefits over previous methods because we inventoried the natural mammal dung resources of dung beetles instead of using artificial mammal baits. Our results revealed higher levels of specialization than expected and more rodent DNA than expected in Germany, suggesting that the presented method provides more detailed insights into mammal dung-dung beetle networks. In addition, the method could have applications for mammal monitoring in many ecosystems.

DNA metabarcoding, diversity partitioning and null models reveal mechanisms of seasonal trophic specialization in a Mediterranean warbler

Optimal Foraging Theory (OFT) predicts that a population's trophic niche expansion should occur in periods of food scarcity as individuals begin to opportunistically exploit sub-optimal food items. However, the Niche Variation Hypothesis (NVH) posits that niche widening may result from increased among-individual differentiation due to food partitioning to avoid competition. We tested these hypotheses through a DNA metabarcoding study of the Sardinian Warbler (Curruca melanocephala) diet over a year. We used null models and the decomposition of beta diversity on among-individual dietary differentiation to infer the mechanisms driving the population's niche variation. Warblers fed frequently on berries, with a peak in late summer and, to a lesser extent, in autumn. Their diet also included a wide range of arthropods, with their prevalence varying among seasons. Consistent with OFT, the population's niche width was narrower in spring/summer when the population was strongly specialized in berries. In winter, the population's niche expanded, possibly reflecting seasonal declines in food abundance. As predicted by NVH, among-individual differentiation tended to be higher in winter, but this was mainly due to increased differences in dietary richness rather than to the partitioning of resources. Overall, our results suggest that within-individual niche does not increase in lean periods, and instead, individuals adopt either a more opportunistic or more specialized foraging strategy. Increased competition in periods of scarcity may help explain such patterns, but instead of showing increased food partitioning as expected from NVH, it may reflect OFT mechanisms on individuals with differential competitive ability to access better food resources.

Network analysis with either Illumina or MinION reveals that detecting vertebrate species requires metabarcoding of iDNA from a diverse fly community

DNA obtained from invertebrates (iDNA) can be metabarcoded in order to survey vertebrate communities. However, little attention has been paid to the interaction between the invertebrate and vertebrate species. Here, we tested for specialization by sampling the dung and carrion fly community of a swamp forest remnant along a disturbance gradient (10 sites: 80-310 m from a road). Approximately, 60% of the baited 407 flies yielded 294 vertebrate identifications based on two COI fragments and 16S. A bipartite network analysis found no statistically significant specialization in the interactions between fly and vertebrate species, but uncommon fly species can carry the signal for vertebrate species that are otherwise difficult to detect with iDNA. A spatial analysis revealed that most of the 20 vertebrate species reported in this study could be detected within 150 m of the road (18 spp.) and that the fly community sourced for iDNA was unexpectedly rich (24 species, 3 families). They carried DNA for rare and common species inhabiting different layers of the forest (ground-dwelling: wild boar, Sunda pangolin, skinks, rats; arboreal: long-tailed macaque, Raffles' banded langur; flying: pin-striped tit-babbler, olive-winged bulbul). All our results were obtained with a new, greatly simplified iDNA protocol that eliminates DNA extraction by obtaining template directly through dissolving fly faeces and regurgitates with water. Lastly, we show that MinION- and Illumina-based metabarcoding yield similar results. We conclude by urging more studies that use different baits and involve experiments that are capable of revealing the dispersal capabilities of the flies carrying the iDNA.

Amplicon metagenomics of dung beetles (Coleoptera, Scarabaeidae, Scarabaeinae) as a proxy for lemur (Primates, Lemuroidea) studies in Madagascar

Dung beetles (Scarabaeidae, Scarabaeinae) are among the most cost-effective and informative biodiversity indicator groups, conveying rich information about the status of habitats and faunas of an area. Yet their use for monitoring the mammal species, that are the main providers of the food for the dung beetles, has only recently been recognized. In the present work, we studied the diet of four endemic Madagascan dung beetles (Helictopleurusfissicollis (Fairmaire), H.giganteus (Harold), Nanosagaboides (Boucomont), and Epilissussplendidus Fairmaire) using high-throughput sequencing and amplicon metagenomics. For all beetle species, the ⅔-¾ of reads belonged to humans, suggesting that human feces are the main source of food for the beetles in the examined areas. The second most abundant were the reads of the cattle (Bostaurus Linnaeus). We also found lower but significant number of reads of six lemur species belonging to three genera. Our sampling localities agree well with the known ranges of these lemur species. The amplicon metagenomics method proved a promising tool for the lemur inventories in Madagascar.

The predator problem and PCR primers in molecular dietary analysis: swamped or silenced; depth or breadth?

Dietary metabarcoding has vastly improved our ability to analyse the diets of animals, but it is hampered by a plethora of technical limitations including potentially reduced data output due to the disproportionate amplification of the DNA of the focal predator, here termed 'the predator problem'. We review the various methods commonly used to overcome this problem, from deeper sequencing to exclusion of predator DNA during PCR, and how they may interfere with increasingly common multi-predator-taxon studies. We suggest that multi-primer approaches with an emphasis on achieving both depth and breadth of prey detections may overcome the issue to some extent, although multi-taxon studies require further consideration, as highlighted by an empirical example. We also review several alternative methods for reducing the prevalence of predator DNA that are conceptually promising but require additional empirical examination. The predator problem is a key constraint on molecular dietary analyses but, through this synthesis, we hope to guide researchers in overcoming this in an effective and pragmatic way.