Scale and scope matter when explaining varying patterns ofcommunity diversity in riverine metacommunities

Large-scale species and genetic metacommunity patterns are influenced by variation in environmental factors and distancebetween communities, according to previous studies. However, these studies often used different measures to assess patternsof metacommunity diversity, distances between communities and grain sizes at which environmental variables are measured.This hinders interpretations and generalizations of the underlying process that drive metacommunity diversity. We applied asynthetic and multi-analytical approach to identify general factors structuring the diversity of a large riverine metacommunity.Using complementing approaches we analyzed how distance, measured as Euclidean or topological distance, and environmentalfactors, assessed at different grain sizes, influenced different measures of metacommunity diversity (species richness, functionalrichness and phylogenetic diversity) of mayfly, stonefly and caddisfly species in a large river network (river Rhine, Switzerland).We found the amount of explained variation in species diversity was generally unaffected by grain size, but improved with the useof topological distance, compared to Euclidean distance. Variation in functional diversity was best explained by environmentalfactors at small grain sizes and topological distance. Variation in phylogenetic diversity was best explained when environmentalvariables were assessed at larger grain sizes and Euclidean distance was used. Overall, our results indicate that processesstructuring metacommunity diversity may differ at the species, functional or phylogenetic level of the community, as recentlypostulated in the metacommunity–phylogenetics approach. While such differences may hinder comparisons across studiesusing different methodologies, it offers opportunities to disentangle the structuring factors within metacommunities by applyingmultiple analytical approaches to the same dataset

A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers

Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared three different approaches in order to better understand assessments of aquatic macroinvertebrate diversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species richness model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species richness model, that is, a generalized linear model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the kicknet and eDNA approaches, particularly at a local scale. We found the EPT-specific primer set fwhF2/EPTDr2n, detected a greater number of targeted EPT species compared to the more general primer set mlCOIintF/HCO2198. Moreover, we found that the species richness measured by eDNA from either primer set was poorly correlated to the richness measured by kicknet sampling (Pearson correlation = 0.27) and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the species richness model (Pearson correlation = 0.30 and 0.44, respectively). The weak relationships between the traditional kicknet sampling and eDNA with this model indicates inherent limitations in upscaling species richness estimates, and possibly a limited ability of the model to meet real world expectations. It is also possible that the number of replicates was not sufficient to detect ambiguous correlations. Future challenges include improving the accuracy and sensitivity of each approach individually, yet also acknowledging their respective limitations, in order to best meet stakeholder demands and address the biodiversity crisis we are facing

Introduction to special issue: Advancing disease ecology through eDNA monitoring of infectious agents

This special issue focuses on the applications of environmental DNA (eDNA) sequencing for the detection and monitoring of disease‐causing agents, including viruses, bacteria, protozoans, myxozoans, fungi, trematodes, and arthropods. We explore the impact of eDNA technologies, such as metabarcoding and qPCR, in understanding the dynamics of pathogens in various environments as well as their implications for conservation, biosecurity, and veterinary and agricultural health under the “One Health” framework. This issue addresses how molecular sequencing provides innovative solutions to the challenges faced by conventional parasite and pathogen detection methods, enabling a more comprehensive understanding of the spatiotemporal dynamics of disease agents. Finally, we discuss the challenges in eDNA applications, such as primer development and taxonomic resolution, and the opportunities for future research in advancing eDNA methodologies for infectious disease studies. This issue highlights the growing importance of eDNA surveillance in understanding and managing the health of ecosystems and at‐risk species

The effects of parameter choice on defining molecular operational taxonomic units and resulting ecological analyses of metabarcoding data

Copyright remains with the author(s) or their institution(s). Permission for reuse (free in most cases) can be obtained from RightsLink.This work was supported by a NSERC CREATE grant to M.E.C. and an Institutional Links grant 172726351 to E.L.C. under the Newton-Ungku Omar Fund, through the British Council in the UK and the Malaysian Industry-Government Group for High Technology in Malaysia. The Newton Fund is Overseas Development Assistance administered through the UK Department for Business Innovation and Skills (BIS). For further information, please visitwww.newtonfund.ac.uk

Environmental DNA metabarcoding:Transforming how we survey animal and plant communities

The genomic revolution has fundamentally changed how we survey biodiversity on earth. High-throughput sequencing (?HTS?) platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed ?environmental DNA? or ?eDNA?). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called ?eDNA metabarcoding? and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity educationpublishersversionPeer reviewe

An integrated spatio-temporal view of riverine biodiversity using environmental DNA metabarcoding 2

Anthropogenically forced changes in global freshwater biodiversity demands better monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the accurate spatiotemporal resolution at which robust biodiversity information can be detected remains ambiguous. Here, using intensive, annual spatiotemporal eDNA sampling across space (five rivers in the USA and Europe, with an upper range of 20-35 km between samples), time (19 timepoints across 2017 to 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of abiotic factors were taxon-specific, reflecting habitat filtering of communities rather than environmental effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatiotemporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river ecology during an epoch of environmental change

肥満糖尿病ラットにおける胃バイパス後の選択的腸管刺激による糖代謝への影響

研究科: 医学薬学府学位:千大院医薬博甲第医1000号要約博士(医学)千葉大

Trade-Offs Between Reducing Complex Terminology and Producing Accurate Interpretations from Environmental DNA: Comment on “Environmental DNA: What\u27s behind the term?” by Pawlowski et al., (2020)

In a recent paper, “Environmental DNA: What\u27s behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring,” Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. This terminology is based on categories that are often difficult to assign and uninformative, and it overlooks a fundamental distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived