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The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview of current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By reanalysing published data sets, we demonstrate that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, a finding that is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared to the ITS2 subregion. Finally, we show that specific methods for compositional data analyses provide more reliable estimates of shifts in community structure. We conclude that metabarcoding analyses of fungi are especially promising for integrating fungi into the full microbiome and broader ecosystem functioning context, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

Ocean color remote sensing offers two decades-long time series of information on phytoplankton abundance. However, determining the structure of the phytoplankton community from this signal is not straightforward, and many uncertainties remain to be evaluated, despite multiple intercomparison efforts of the different available algorithms. Here, we use remote sensing and machine learning to infer the abundance of seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. Our dataset is to our knowledge the most comprehensive and complete, available to describe phytoplankton community structure at a global scale using a molecular marker that defines relative abundances of all phytoplankton groups simultaneously. The methodology shows satisfying performances to provide robust estimates of phytoplankton groups using satellite data, with few limitations regarding the global generalization of the method. Furthermore, this new satellite-based methodology allows a valuable global intercomparison with the pigment-based approach used in in-situ and satellite data to identify phytoplankton groups. Nevertheless, these datasets show different, yet coherent information on the phytoplankton, valuable for the understanding of community structure. This makes remote sensing observations excellent tools to collect Essential Biodiversity Variables and provide a foundation for developing marine biodiversity forecasts.

Monitoring biodiversity is essential to protect, preserve and restore ecosystems, particularly in the context of current challenges such as climate change, habitat destruction and globalization (Baird & Hajibabaei, 2012). Biomonitoring is needed for developing biotic indices for assessing ecological status, measuring impacts of anthropogenic activities in natural ecosystems, evaluating biodiversity loss, surveying nonindigenous species, conservation, and identifying cryptic species (Balvanera et al., 2006; Fišer et al., 2018). Thus, spatially and temporally structured biomonitoring activities provide a powerful tool for the implementation of regional, national and international regulations, directives and policies for nature conservation. However substantial impediments exist including access to remote locations, limited specialist taxonomic knowledge, cost, slow pace of human-driven data analyses, and typically low sensitivity for detection of rare and elusive species (Zinger et al., 2020). These drawbacks are often translated into expensive monitoring activities with limited spatial, temporal and taxonomic coverage. In this context, new approaches for biomonitoring are being explored, among which advanced DNA-based technologies are emerging (Kissling et al., 2018). The field of biodiversity monitoring through the analysis of the pool of DNA isolated from environmental samples, referred to as environmental DNA or eDNA (Pawlowski et al., 2020; Taberlet et al., 2012), is rapidly growing. This growth is being driven through improved approaches for sampling, data generation and analyses, and with recent advances on how eDNA should be interpreted for biodiversity assessments (Bohmann et al., 2014). The success of eDNA-based biomonitoring is reflected in exponential growth of publications within this area and increasing submissions to Molecular Ecology Resources in particular (Figure 1). Molecular Ecology Resources aims to publish high quality eDNA studies that serve as broad resources, including innovative methodologies for DNA sampling, enhanced laboratory protocols for data generation, or new computer programs and statistical advances for data analyses. Thus, the aim of this editorial is to contribute to producing good quality DNA data-derived essential biodiversity variables (EBVs) (Kissling et al., 2018) by providing guidance to the community submitting articles on the subject. For that purpose, we have summarized best practices established in published literature related to the different phases involved in the process, namely sampling, laboratory work, bioinformatic analyses and data interpretation (Figure 2).

DNA metabarcoding is becoming the tool of choice for biodiversity studies across taxa and large-scale environmental gradients. Yet, the artefacts present in metabarcoding datasets often preclude a proper interpretation of ecological patterns. Bioinformatic pipelines removing experimental noise have been designed to address this issue. However, these often only partially target produced artefacts, or are marker specific. In addition, assessments of data curation quality and the appropriateness of filtering thresholds are seldom available in existing pipelines, partly due to the lack of appropriate visualisation tools. Here, we present metabaR, an R package that provides a comprehensive suite of tools to effectively curate DNA metabarcoding data after basic bioinformatic analyses. In particular, metabaR uses experimental negative or positive controls to identify different types of artefactual sequences, i.e. reagent contaminants and tag-jumps. It also flags potentially dysfunctional PCRs based on PCR replicate similarities when those are available. Finally, metabaR provides tools to visualise DNA metabarcoding data characteristics in their experimental context as well as their distribution, and facilitate assessment of the appropriateness of data curation filtering thresholds. metabaR is applicable to any DNA metabarcoding experimental design but is most powerful when the design includes experimental controls and replicates. More generally, the simplicity and flexibility of the package makes it applicable any DNA marker, and data generated with any sequencing platform, and pre-analysed with any bioinformatic pipeline. Its outputs are easily usable for downstream analyses with any ecological R package. metabaR complements existing bioinformatics pipelines by providing scientists with a variety of functions with customisable methods that will allow the user to effectively clean DNA metabarcoding data and avoid serious misinterpretations. It thus offers a promising platform for automatised data quality assessments of DNA metabarcoding data for environmental research and biomonitoring.

The peer review history for this article is available at https://publons.com/publon/10.1111/1365-2745.13986.Raw data have been deposited in the Sequence Read Archive (SRA) under the BioProject accession no. PRJNA692353.; International audience; In soils, plants and fungi can form complex mycorrhizal networks allowing nutrient transfers between plant individuals and species. It is less clear, however, whether such networks exist on the bark of trees where epiphytic plant communities thrive in rainforests. Previous work showed that tropical epiphytic orchids especially, harbour symbiotic fungi in their roots, but the structure and determinants of the resulting networks remain unknown at the tree scale.We tested the hypothesis that epiphytic orchids rooted in the same area on the bark share mycorrhizal fungi, regardless of their species (i.e. spatial determinant). For this purpose, we selected the trunk of six trees of two common species in a rainforest and sampled orchid roots, protocorms and surrounding bark. We identified mycorrhizal fungi including Tulasnellaceae using high-throughput sequencing of the ITS2 marker, and reconstructed orchid-fungus bipartite networks for each tree to analyse their structure and the spatial turnover of this symbiosis.We found that epiphytic orchid communities form antinested and highly modular networks with mycorrhizal fungi spread on the bark. As expected, modules of interactions are explained by their spatial structure, with nearby roots sharing fungi, but also by the orchid species involved. These results reveal the presence of shared mycelial networks in epiphytic habitats, whose roles in the resilience and facilitation of epiphytic plant communities need to be assessed.Synthesis. Tropical tree barks are densely colonized by certain mycorrhizal fungi that can form symbioses in nearby adult and young orchids simultaneously. These mycorrhizal networks may allow water and nutrient transfers to alleviate the stressful conditions of the epiphytic habitats.

International audience; Aim: Although soil biodiversity is extremely rich and spatially variable, both in terms of species and trophic groups, we still know little about its main drivers. Here, we contrast four long-standing hypotheses to explain the spatial variation of soil multi-trophic diversity: energy, physiological tolerance, habitat heterogeneity and resource heterogeneity.Location: French Alps.Methods: We built on a large-scale observatory across the French Alps (Orchamp) made of seventeen elevational gradients (similar to 90 plots) ranging from low to very high altitude (280-3,160 m), and encompassing large variations in climate, vegetation and pedological conditions. Biodiversity measurements of 36 soil trophic groups were obtained through environmental DNA metabarcoding. Using a machine learning approach, we assessed (1) the relative importance of predictors linked to different ecological hypotheses in explaining overall multi-trophic soil biodiversity and (2) the consistency of the response curves across trophic groups.Results: We showed that predictors associated with the four hypotheses had a statistically significant influence on soil multi-trophic diversity, with the strongest support for the energy and physiological tolerance hypotheses. Physiological tolerance explained spatial variation in soil diversity consistently across trophic groups, and was an especially strong predictor for bacteria, protists and microfauna. The effect of energy was more group-specific, with energy input through soil organic matter strongly affecting groups related to the detritus channel. Habitat and resource heterogeneity had overall weaker and more specific impacts on biodiversity with habitat heterogeneity affecting mostly autotrophs, and resource heterogeneity affecting bacterivores, phytophagous insects, enchytraeids and saprotrophic fungi.Main Conclusions: Despite the variability of responses to the environmental drivers found across soil trophic groups, major commonalities on the ecological processes structuring soil biodiversity emerged. We conclude that among the major ecological hypotheses traditionally applied to aboveground organisms, some are particularly relevant to predict the spatial variation in soil biodiversity across the major soil trophic groups.

The increasing severity and frequency of natural disturbances requires a better understanding of their effects on all compartments of biodiversity. In Northern Fennoscandia, recent large-scale moth outbreaks have led to an abrupt change in plant communities from birch forests dominated by dwarf shrubs to grass-dominated systems. However, the indirect effects on the belowground compartment remained unclear. Here, we combined eDNA survey of multiple trophic groups with network analyses to demonstrate that moth defoliation has far-reaching consequences on soil food webs. Following this disturbance, diversity and relative abundance of certain trophic groups declined (e.g. ectomycorrhizal fungi) while many others profited (e.g. bacterivores, omnivores) making soil food webs more diverse and structurally different. Overall, the direct and indirect consequences of moth outbreaks increased belowground diversity at different trophic levels. Our results highlight that a holistic view of ecosystems improves our understanding of cascading effects of major disturbances on soil food webs.

Phytoplankton account for >45% of primary production on Earth, and hence have an enormous impact on aquatic food webs and on the entire Earth System. Their members are found across many of the major clades of the tree of life, including prokaryotes (cyanobacteria) and multiple eukaryotic lineages. Phytoplankton communities are generally studied by PCR amplification of rRNA marker genes from the DNA extracted from environmental samples and high-throughput sequencing of the amplicons. However, our appreciation of phytoplankton abundance or biomass is limited by PCR-amplification biases, rRNA gene copy number variations across taxa and the fact that rRNA do not provide insights into metabolic traits such as photosynthesis (i.e., it is sometimes difficult to distinguish an rRNA sequence of a phytoplanktonic species from a phylogenetically close non-photosynthetic species). In addition, rRNA marker genes fail to capture both cyanobacteria and photosynthetic eukaryotes simultaneously, thus hampering assessment of the entire phytoplankton community. Here, we propose to use the core single-copy photosynthetic gene psbO extracted from metagenomes to circumvent these limitations: the method is PCR-free, and the gene is present in both prokaryotes and eukaryotes, mainly in one copy per genome. We applied and validated this new strategy with the Tara Oceans datasets, and showed in most cases improved correlations with flow cytometry and microscopy than when based on rRNA genes. Furthermore, we revealed unexpected features of the ecology of these organisms, such as the high abundance of picocyanobacterial aggregates and symbionts in the ocean, and the decrease in relative abundance of phototrophs towards the larger size classes of marine communities of dinoflagellates. To facilitate the incorporation of psbO in future molecular-based surveys, we released a curated database including >20,000 unique sequences. Overall, psbO appears to be a promising new gene marker for improving molecular-based evaluations of phytoplankton communities.

International audience; Soil trophic networks are key to biogeochemical cycles, in particular decomposition. However, few studies have yet quantified how microbial decomposition activity along environmental gradients is jointly driven by bacteria, fungi, and their respective consumers. Here, we quantified these direct and indirect effects on decomposition and contrasted them between forests and open habitats using multiple elevational gradients in the French Alps.While environmental control on microbial decomposition activity was comparable in the two habitats, the pathways and strengths of biotic predictors strongly differed. The fungal channel composition played a moderate role in forests, while the bacterial channel composition was critical in open habitats. Importantly, we found trophic regulation by consumers to be a key modulator of the direct environmental effects on decomposition in open habitats. These results highlight the need to integrate trophic regulation when predicting future ecosystem functioning.

Metazoan metabarcoding is emerging as an essential strategy for inventorying biodiversity,with diverse projects currently generating massive quantities of community-level data. The potential for integrating across such data sets offers new opportunities to better understand biodiversity and how it might respond to global change. However, large-scale synthesesmay be compromised if metabarcoding workflows differ from each other. There are ongoing efforts to improve standardization for the reporting of inventory data. However, harmonization at the stage of generating metabarcode data has yet to be addressed. A modular framework for harmonized data generation offers a pathway to navigate the complex structure of terrestrial metazoan biodiversity. Here, through our collective expertise as practitioners,method developers, and researchers leading metabarcoding initiatives to inventory terrestrial biodiversity, we seek to initiate a harmonized framework for metabarcode data generation, with a terrestrial arthropod module. We develop an initial set of submodules covering the 5 main steps of metabarcode data generation: (i) sample acquisition; (ii) sample processing; (iii) DNA extraction; (iv) polymerase chain reaction amplification, library preparation, and sequencing; and (v) DNA sequence and metadata deposition, providing a backbone for a terrestrial arthropod module. To achieve this, we (i) identified key points for harmonization, (ii) reviewed the current state of the art, and (iii) distilled existing knowledge within submodules, thus promoting best practice by providing guidelines and recommendations to reduce the universe of methodological options.We advocate the adoption and further development of the terrestrial arthropodmodule.We further encourage the development of modules for other biodiversity fractions as an essential step toward large-scale biodiversity synthesis through harmonization., The working group “Toward Harmonisation for the Generation of Metabarcoding Data: Soil Biodiversity and Terrestrial Arthropod modules” held in November 2020 (online) was organized by the iBioGen project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 810729. P.A. was funded through a Junior Leader Fellowship (LCF/BQ/PR21/11840006) by “la Caixa” Foundation (ID 100010434) and the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 847648.

Altres ajuts: acords transformatius de la UAB Understanding the mechanisms that drive the change of biotic assemblages over space and time is the main quest of community ecology. Assessing the relative importance of dispersal and environmental species selection in a range of organismic sizes and motilities has been a fruitful strategy. A consensus for whether spatial and environmental distances operate similarly across spatial scales and taxa, however, has yet to emerge. We used censuses of four major groups of organisms (soil bacteria, fungi, ground insects, and trees) at two observation scales (1-m sampling point vs. 2,500-m plots) in a topographically standardized sampling design replicated in two tropical rainforests with contrasting relationships between spatial distance and nutrient availability. We modeled the decay of assemblage similarity for each taxon set and site to assess the relative contributions of spatial distance and nutrient availability distance. Then, we evaluated the potentially structuring effect of tree composition over all other taxa. The similarity of nutrient content in the litter and topsoil had a stronger and more consistent selective effect than did dispersal limitation, particularly for bacteria, fungi, and trees at the plot level. Ground insects, the only group assessed with the capacity of active dispersal, had the highest species turnover and the flattest nonsignificant distance−decay relationship, suggesting that neither dispersal limitation nor nutrient availability were fundamental drivers of their community assembly at this scale of analysis. Only the fungal communities at one of our study sites were clearly coordinated with tree composition. The spatial distance at the smallest scale was more important than nutrient selection for the bacteria, fungi, and insects. The lower initial similarity and the moderate variation in composition identified by these distance-decay models, however, suggested that the effects of stochastic sampling were important at this smaller spatial scale. Our results highlight the importance of nutrients as one of the main environmental drivers of rainforest communities irrespective of organismic or propagule size and how the overriding effect of the analytical scale influences the interpretation, leading to the perception of greater importance of dispersal limitation and ecological drift over selection associated with environmental niches at decreasing observation scales.

The most remarkable feature of our planet is the diversity of its life forms, ranging from viruses and nanobacteria to blue whales and giant sequoias to satanic leaf‐tailed geckos and leafy seadragons (look them up!). Life is found in essentially all environments on earth, and the number of species living on our planet is many times greater than we could have imagined a century ago. A well‐regarded estimate pegs the number of eukaryotic species on earth at 8.7 million (±1.3 million), of which fewer than 15% are currently described (Mora et al., 2011). The diversity of prokaryotes is less clear (and highly controversial), but an analysis of 1.6 billion 16S ribosomal RNA sequences estimated that 0.8–1.6 million prokaryotic operational taxonomic units exist globally (Louca et al., 2019). While we do not know how many species are currently extant, or have existed in the past, we do know that this biodiversity is valuable, providing food, fibre and medicine, furnishing ecosystem services such as water and air purification, nutrient cycling, pollination and carbon uptake, and contributing to technological innovations ranging from biotechnology to robotics to material science. Moreover, biodiversity underlies the cultural identity of human populations and is important to human health and well‐being. Geographically, species richness increases from the Polar Regions to the tropics in terrestrial and surface marine ecosystems. Thus, some countries, especially those in tropical and subtropical regions, are endowed with much greater biodiversity than others. Unfortunately, benefits arising from the access and utilization of this biodiversity have been unequally shared, with (paradoxically) biodiversity‐poor countries often accruing the lion's share of economic gains. There can be imbalances within countries as well, wherein some segments of the population obtain greater economic benefits from biodiversity and associated traditional knowledge than indigenous peoples. The “Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization,” which came into force in 2014, is an international agreement designed to ensure that the benefits arising from biodiversity are shared equitably (https://www.cbd.int/abs/). However, few scientific journals require compliance with the Nagoya Protocol or the reporting of benefits from biodiversity research. In this editorial, we (the editors of Molecular Ecology and Molecular Ecology Resources) express support for the Nagoya Protocol and the principle of benefit sharing. We believe that scientific journals publishing research on biodiversity can play an important role in implementing the Nagoya Protocol and in reporting on benefits generated from such research. Below, we provide background on the Nagoya Protocol, discuss the kinds of benefits that may arise from biodiversity research, describe the rationale for reporting on these benefits and introduce changes to the journals’ Data Accessibility Statements to incorporate the requirements and goals of the Nagoya Protocol.

DNA metabarcoding is becoming the tool of choice for biodiversity studies across taxa and large-scale environmental gradients. Yet, the artefacts present in metabarcoding datasets often preclude a proper interpretation of ecological patterns. Bioinformatic pipelines removing experimental noise have been designed to address this issue. However, these often only partially target produced artefacts, or are marker specific. In addition, assessments of data curation quality and the appropriateness of filtering thresholds are seldom available in existing pipelines, partly due to the lack of appropriate visualisation tools.Here, we present metabaR, an R package that provides a comprehensive suite of tools to effectively curate DNA metabarcoding data after basic bioinformatic analyses. In particular, metabaR uses experimental negative or positive controls to identify different types of artefactual sequences, i.e. reagent contaminants and tag-jumps. It also flags potentially dysfunctional PCRs based on PCR replicate similarities when those are available. Finally, metabaR provides tools to visualise DNA metabarcoding data characteristics in their experimental context as well as their distribution, and facilitate assessment of the appropriateness of data curation filtering thresholds.metabaR is applicable to any DNA metabarcoding experimental design but is most powerful when the design includes experimental controls and replicates. More generally, the simplicity and flexibility of the package makes it applicable any DNA marker, and data generated with any sequencing platform, and pre-analysed with any bioinformatic pipeline. Its outputs are easily usable for downstream analyses with any ecological R package.metabaR complements existing bioinformatics pipelines by providing scientists with a variety of functions with customisable methods that will allow the user to effectively clean DNA metabarcoding data and avoid serious misinterpretations. It thus offers a promising platform for automatised data quality assessments of DNA metabarcoding data for environmental research and biomonitoring.

The role of the Arctic Ocean ecosystem in climate regulation may depend on the responses of marine microorganisms to environmental change. We applied genome-resolved metagenomics to 41 Arctic seawater samples, collected at various depths in different seasons during the Tara Oceans Polar Circle expedition, to evaluate the ecology, metabolic potential and activity of resident bacteria and archaea. We assembled 530 metagenome-assembled genomes (MAGs) to form the Arctic MAGs catalogue comprising 526 species. A total of 441 MAGs belonged to species that have not previously been reported and 299 genomes showed an exclusively polar distribution. Most Arctic MAGs have large genomes and the potential for fast generation times, both of which may enable adaptation to a copiotrophic lifestyle in nutrient-rich waters. We identified 38 habitat generalists and 111 specialists in the Arctic Ocean. We also found a general prevalence of 14 mixotrophs, while chemolithoautotrophs were mostly present in the mesopelagic layer during spring and autumn. We revealed 62 MAGs classified as key Arctic species, found only in the Arctic Ocean, showing the highest gene expression values and predicted to have habitat-specific traits. The Artic MAGs catalogue will inform our understanding of polar microorganisms that drive global biogeochemical cycles.

Bacteria living on the cuticle of ants are generally studied for their protective role against pathogens, especially in the clade of fungus-growing ants. However, little is known regarding the diversity of cuticular bacteria in other ant host species, as well as the mechanisms leading to the composition of these communities. Here, we used 16S rRNA gene amplicon sequencing to study the influence of host species, species interactions and the pool of bacteria from the environment on the assembly of cuticular bacterial communities on two phylogenetically distant Amazonian ant species that frequently nest together inside the roots system of epiphytic plants, Camponotus femoratus and Crematogaster levior. Our results show that (a) the vast majority of the bacterial community on the cuticle is shared with the nest, suggesting that most bacteria on the cuticle are acquired through environmental acquisition, (b) 5.2% and 2.0% of operational taxonomic units (OTUs) are respectively specific to Ca. femoratus and Cr. levior, probably representing their respective core cuticular bacterial community, and (c) 3.6% of OTUs are shared between the two ant species. Additionally, mass spectrometry metabolomics analysis of metabolites on the cuticle of ants, which excludes the detection of cuticular hydrocarbons produced by the host, were conducted to evaluate correlations among bacterial OTUs and m/z ion mass. Although some positive and negative correlations are found, the cuticular chemical composition was weakly species-specific, suggesting that cuticular bacterial communities are prominently environmentally acquired. Overall, our results suggest the environment is the dominant source of bacteria found on the cuticle of ants.

International audience

International audience; The rainforests of the Neotropics shelter a vast diversity of plant, animal and microscopic species that provide critical ecosystem goods and services for both local and worldwide populations. These environments face a major crisis due to increased deforestation, pollution, and climate change, emphasizing the need for more effective conservation efforts. The adequate monitoring of these ecosystems has proven a complex and time consuming endeavour, which depends on ever dwindling taxonomic expertise. To date, many species remain undiscovered, let alone described, with otherwise limited information regarding known species population distributions and densities. Overcoming these knowledge shortfalls and practical limitations is becoming increasingly possible through techniques based on environmental DNA (eDNA), i.e., DNA that can be obtained from environmental samples (e.g. tissues, soil, sediment, water, etc.). When coupled with high-throughput sequencing, these techniques now enable realistic, cost-effective, and standardisable biodiversity assessments. This opens up enormous opportunities for advancing our understanding of complex and species-rich tropical communities, but also in facilitating large-scale biomonitoring programs in the neotropics. In this review, we provide a brief introduction to eDNA methods, and an overview of their current and potential uses in both terrestrial and aquatic ecosystems of neotropical rainforests. We also discuss the limits and challenges of these methods for our understanding and monitoring of biodiversity, as well as future research and applied perspectives of these techniques in neotropical rainforests, and beyond.

International audience; High-throughput sequencing of amplicons from environmental DNA samples permits rapid, standardized and comprehensive biodiversity assessments. However, retriev-ing and interpreting the structure of such data sets requires efficient methods for di-mensionality reduction. Latent Dirichlet Allocation (LDA) can be used to decompose environmental DNA samples into overlapping assemblages of co-occurring taxa. It is a flexible model-based method adapted to uneven sample sizes and to large and sparse data sets. Here, we compare LDA performance on abundance and occurrence data, and we quantify the robustness of the LDA decomposition by measuring its stability with respect to the algorithm's initialization. We then apply LDA to a survey of 1,131 soil DNA samples that were collected in a 12-ha plot of primary tropical for-est and amplified using standard primers for bacteria, protists, fungi and metazoans. The analysis reveals that bacteria, protists and fungi exhibit a strong spatial structure, which matches the topographical features of the plot, while metazoans do not, con-firming that microbial diversity is primarily controlled by environmental variation at the studied scale. We conclude that LDA is a sensitive, robust and computationally efficient method to detect and interpret the structure of large DNA-based biodiver-sity data sets. We finally discuss the possible future applications of this approach for the study of biodiversity.

Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β‐diversity) along ecological gradients. Here, we characterize soil microbial β‐diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β‐diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β‐diversities with respect to plant β‐diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β‐diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β‐diversities were mostly related to plant β‐diversity, while bacterial β‐diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β‐diversities with plant β‐diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β‐diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early‐evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today's microbial community structure. ISSN:0906-7590 ISSN:1600-0587

Much effort has been devoted to better understanding the effects of environment and biodiversity on ecosystem functioning. However, few studies have moved beyond measuring biodiversity as species richness of a single group and/or focusing on a single ecosystem function. While there is a growing recognition that along environmental gradients, the compositional turnover of multiple trophic groups influences not only productivity but multiple ecosystem functions, we do not know yet which components of multi‐trophic β‐diversity influence which ecosystem functions. Here, we captured the biodiversity found in soils using environmental DNA to study total soil multi‐trophic β‐diversity (between all taxa regardless of their trophic group association), horizontal β‐diversities (β‐diversities within trophic groups) and vertical β‐diversity (β‐diversity across trophic groups) along a 1,000 m elevational gradient in the French Alps. Using path analyses, we quantified how these β‐diversity components mediate the effects of environmental turnover on the turnover of multiple ecosystem functions (i.e. productivity, N‐cycling, N‐leaching) and overall multifunctionality. While we found a strong direct effect of soil properties on the turnover of multiple ecosystem functions, we also found an indirect effect of climate and soil properties through multi‐trophic β‐diversity. More specifically, only total multi‐trophic β‐diversity and the horizontal β‐diversity of saprophytic fungi were strongly related to the turnover of multifunctionality and, to a lower extent, the turnover of productivity and N‐cycling. Our results suggest that decomposition processes and resulting nutrient availability are key to understand how ecosystem functions change along soil properties and climatic gradients in alpine ecosystems. By demonstrating how saprophytic fungi and their associated trophic groups can offset the direct responses of multiple ecosystem functions to environmental change, our study highlights the paramount importance of multi‐trophic diversity for better understanding ecosystem multifunctionality in a changing world. A free Plain Language Summary can be found within the Supporting Information of this article.

The phylogenetic depth at which arbuscular mycorrhizal (AM) fungi harbor a coherent ecological niche is unknown, which has consequences for operational taxonomic unit (OTU) delineation from sequence data and the study of their biogeography. We tested how changes in AM fungi community composition across habitats (beta diversity) vary with OTU phylogenetic resolution. We inferred exact sequence variants (ESVs) to resolve phylotypes at resolutions finer than provided by traditional sequence clustering and analyzed beta diversity profiles up to order-level sequence clusters. At the ESV level, we detected the environmental predictors revealed with traditional OTUs or at higher genetic distances. However, the correlation between environmental predictors and community turnover steeply increased at a genetic distance of c. 0.03 substitutions per site. Furthermore, we observed a turnover of either closely or distantly related taxa (respectively at or above 0.03 substitutions per site) along different environmental gradients. This study suggests that different axes of AM fungal ecological niche are conserved at different phylogenetic depths. Delineating AM fungal phylotypes using DNA sequences should screen different phylogenetic resolutions to better elucidate the factors that shape communities and predict the fate of AM symbioses in a changing environment.

International audience

DNA metabarcoding on soil samples is increasingly used for large-scale and multi-taxa biodiversity studies. However, DNA extraction may be a major bottleneck for such wide uses. It should be cost/time effective and allow dealing with large sample volumes so as to maximise the representativeness of both micro- and macro-organisms diversity. Here, we compared the performances of a fast and cheap extracellular DNA extraction protocol with a total DNA extraction method in retrieving bacterial, eukaryotic and plant diversity from tropical soil samples of ca. 10 g. The total DNA extraction protocol yielded more high-quality DNA. Yet, the extracellular DNA protocol provided similar diversity assessments although it presented some differences in clades relative abundance and undersampling biases. We argue that extracellular DNA is a good compromise between cost, labor, and accuracy for high-throughput DNA metabarcoding studies of soil biodiversity.

International audience; Tropical forests shelter an unparalleled biological diversity. The relative influence of environmental selection (i.e., abiotic conditions, biotic interactions) and stochastic-distance-dependent neutral processes (i.e., demography, dispersal) in shaping communities has been extensively studied for various organisms, but has rarely been explored across a large range of body sizes, in particular in soil environments. We built a detailed census of the whole soil biota in a 12-ha tropical forest plot using soil DNA metabarcoding. We show that the distribution of 19 taxonomic groups (ranging from microbes to mesofauna) is primarily stochastic, suggesting that neutral processes are prominent drivers of the assembly of these communities at this scale. We also identify aluminium, topography and plant species identity as weak, yet significant drivers of soil richness and community composition of bacteria, protists and to a lesser extent fungi. Finally, we show that body size, which determines the scale at which an organism perceives its environment, predicted the community assembly across taxonomic groups, with soil mesofauna assemblages being more stochastic than microbial ones. These results suggest that the relative contribution of neutral processes and environmental selection to community assembly directly depends on body size. Body size is hence an important determinant of community assembly rules at the scale of the ecological community in tropical soils and should be accounted for in spatial models of tropical soil food webs. K E Y W O R D S DNA metabarcoding, eDNA, French Guiana, multitaxa, neutral assembly, niche determinism, propagule size, soil diversity

International audience; 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.

The DNA barcoding concept (Woese et al. ; Hebert et al. ) has considerably boosted taxonomy research by facilitating the identification of specimens and discovery of new species. Used alone or in combination with DNA metabarcoding on environmental samples (Taberlet et al. ), the approach is becoming a standard for basic and applied research in ecology, evolution and conservation across taxa, communities and ecosystems (Scheffers et al. ; Kress et al. ). However, DNA barcoding suffers from several shortcomings that still remain overlooked, especially when it comes to species delineation (Collins & Cruickshank ). In this issue of Molecular Ecology, Barley & Thomson () demonstrate that the choice of models of sequence evolution has substantial impacts on inferred genetic distances, with a propensity of the widely used Kimura 2-parameter model to lead to underestimated species richness. While DNA barcoding has been and will continue to be a powerful tool for specimen identification and preliminary taxonomic sorting, this work calls for a systematic assessment of substitution models fit on barcoding data used for species delineation and reopens the debate on the limitation of this approach.

Chapter 5 “DNA extraction” focuses on the particularities and practical constraints associated with the isolation of eDNA from environmental samples. The extraction protocol is indeed crucial in eDNA studies, as it will determine whether extracellular, intracellular, or total DNA is targeted. Chapter 5 describes the main advantages and limitations of the most popular extraction kits aimed at obtaining DNA from soil, sediment, litter, feces, or water. It provides a detailed protocol for DNA extraction from soil samples using a saturated phosphate buffer. This protocol has been optimized for an easy implementation in the field using a mobile laboratory, so the material and consumables necessary are also listed.

DNA metabarcoding generates huge amounts of data containing noise introduced by molecular methods. Chapter 8 “DNA metabarcoding data analysis” discusses the analytic steps and available software to curate and evaluate DNA metabarcoding data prior to final ecological analyses. It provides command lines to perform primary analyses of Illumina sequencing data with the OBITools, ranging from read assignment to samples to the formation of molecular operational taxonomic units (MOTUs) and their assignment to a taxon through comparison against reference databases. Chapter 8 also develops several methods to further curate sequencing data from contaminants or dysfunctional PCRs by using DNA extraction, PCR, and sequencing blank controls as well as PCR/biological replicates. It also presents several classical analyses to ensure that the diversity of the sample or the study site is appropriately covered. Finally, this chapter considers what conclusions on biodiversity and ecological processes can be really drawn from metabarcoding data.

Chapter 11 entitled “Some early landmark studies” revisits several seminal articles that paved the way for the field of eDNA research. It first evokes the paper that first coined the expression “environmental DNA” in the late 1980s. Then, it describes how eDNA was first exploited in the early 1990s to reveal an unsuspected microbial diversity that morphology- or cultivation-based methods had failed to reach. In the late 1990s, microbiologists began to explore in several pioneer papers the functional insight provided by “metagenomes” (i.e., the collective genomes found in eDNA samples). In the 2000s, eDNA analysis was finally extended to macroorganisms. Chapter 11 reports such a use in two very different contexts (i.e., the detection of a contemporary invasive species, the bullfrog, and the reconstruction of past plant and animal communities from sediment and permafrost samples).

Environmental DNA (eDNA), i.e. DNA released in the environment by any living form, represents a formidable opportunity to gather high-throughput and standard information on the distribution or feeding habits of species. It has therefore great potential for applications in ecology and biodiversity management. However, this research field is fast-moving, involves different areas of expertise and currently lacks standard approaches, which calls for an up-to-date and comprehensive synthesis. Environmental DNA for biodiversity research and monitoring covers current methods based on eDNA, with a particular focus on “eDNA metabarcoding”. Intended for scientists and managers, it provides the background information to allow the design of sound experiments. It revisits all steps necessary to produce high-quality metabarcoding data such as sampling, metabarcode design, optimization of PCR and sequencing protocols, as well as analysis of large sequencing datasets. All these different steps are presented by discussing the potential and current challenges of eDNA-based approaches to infer parameters on biodiversity or ecological processes. The last chapters of this book review how DNA metabarcoding has been used so far to unravel novel patterns of diversity in space and time, to detect particular species, and to answer new ecological questions in various ecosystems and for various organisms. Environmental DNA for biodiversity research and monitoring constitutes an essential reading for all graduate students, researchers and practitioners who do not have a strong background in molecular genetics and who are willing to use eDNA approaches in ecology and biomonitoring.

DNA-based approaches have enabled the multifaceted role of microbes for the fitness and performance of their host to be revealed. The increasing recognition of the crucial role of microorganisms for the fitness and performance of plants and animals has led to the concepts of holobiont (i.e., a host and its microbiota), and hologenome (i.e., the collective genomes of a holobiont). Here a brief review is provided of the advances that have been made in this field by using DNA-based approaches. Chapter 16 “Host-associated microbiota” summarizes this area of research by presenting past and recent major findings, as well as new research avenues for unraveling host-microbiota interactions in non-model animals and plants.

Chapter 9 “Single-species detection” deals with the practical aspects of detecting a single and predefined taxon with eDNA, with a particular focus on the use of quantitative PCR (qPCR) for this purpose. After presenting how single-species detection has been implemented in a few seminal studies, it details the principles underlying qPCR. More specifically, it describes the typical qPCR amplification curve and the different systems (SYBR green and TaqMan probe assays) available to record amplicon accumulation in real time via fluorescence measurements. Chapter 9 also explains how the initial number of target sequences can be estimated with the Ct method, and addresses the design and test of reliable qPCR barcodes and probes targeting a single species. Finally, several important experimental considerations are highlighted, including the particular concerns of contamination and inhibition in qPCR.

One of the most fascinating facets of eDNA lies in the possibility of exploiting it to reconstruct past environments in paleoecology and in archaeology. Chapter 15, entitled “Paleoenvironments,” reviews different pioneer studies that scrutinized ancient eDNA extracted from different substrates (e.g., lake sediments, permafrost, or archaeological midden material), to address a wide range of questions. These include, for example, the taxonomic identification of archaeological fish bones in Madagascar from bulk samples, the reconstruction of past plant communities based on the large-scale analysis of permafrost samples, or the assessment of past human diet in Greenland based on midden material. Midden material from archaeological sites represents a valuable source of information for tracking food habits of ancient human communities. It also provides information about the surrounding biodiversity, using humans as biodiversity samplers, which is also explored here.

Chapter 17 “Diet analysis” focuses on the specificities of DNA metabarcoding in the context of diet analyses. It presents the proof-of-concept study, which examined the diet of several herbivore species using next-generation sequencing for the first time. Chapter 17 reports how DNA-based analysis of bison diet helped evaluate the effect of conservation policies in a protected area. The different strategies aiming at disentangling predator and prey sequences in carnivorous diets are reviewed, including the use of a blocking oligonucleotide. Using bear diet as a study case, the issues associated with omnivorous diets are discussed, particularly that of integrating several diet components. Finally, Chapter 17 develops several important methodological and experimental factors to consider in eDNA-based diet analyses. These comprise the source of eDNA, the quantitative aspects, and the use of diet as a proxy of surrounding biodiversity (e.g., as in the case of invertebrate samplers).

Chapter 12 “Freshwater ecosystems” focuses on the study of freshwater organisms via eDNA analysis. It addresses the particularities of the production, persistence, transport, and detectability of eDNA in surface waters. Biomonitoring freshwater ecosystems is imposed by law in more and more countries (e.g., European Council 2000) and the potential of eDNA for this purpose has been identified relatively early. This chapter revisits several studies dealing with eDNA-based analysis of macroinvertebrates (e.g., to track seasonal variation in the ecosystem scale), diatoms (for water quality assessment purposes), aquatic plants (e.g., for invasive species detection), fish, amphibians, and other vertebrates (for species inventories and biomass estimation). Finally, Chapter 12 discusses whether rivers can be good conveyor belts of the biodiversity at the scale of an entire catchment.

DNA references databases are a prerequisite to identify sequences obtained from a metabarcoding experiments. Chapter 3 “Reference databases” gives a brief description of the content and structure of existing generalistic resources and proposes guidelines to construct reference databases specific to the metabarcode of interest, when no specific databases are available. The method presented consists in capturing all sequences corresponding to the metabarcode in generalistic international repositories by using the program ecoPCR. Second, existing resources specific to rRNAs or classical barcodes are presented. Finally, this chapter develops strategies relying on either on polymerase chain reaction (PCR), or on genome skimming, to enrich existing databases with new species from fresh specimens or collections in museums. This chapter does not deal with taxonomic assignment per se, which is discussed in Chapter 8.

The emergence of eDNA analysis is tightly linked to the development of next-generation sequencing. Chapter 7 “DNA sequencing” gives an overview of the characteristics and limitations of the main next-generation sequencing platforms. It focuses particularly on the Illumina platform, which is the only technology currently suitable for large-scale analysis with hundreds to thousands of samples. More specifically, Chapter 7 describes the Illumina library preparation process, the generation of sequencing clusters by bridge PCR on the flow cell, and the sequencing reaction itself, based on sequencing by synthesis. Finally, detailed information is provided on the meaning and coding of quality scores of the sequencing reads.

Chapter 10 “Environmental DNA for functional diversity” discusses the potential of environmental DNA to assess functional diversity. It first focuses on DNA metabarcoding and discusses the extent to which this approach can be used and/or optimized to retrieve meaningful information on the functions of the target community. This knowledge usually involves coarsely defined functional groups (e.g., woody, leguminous, graminoid plants; shredders or decomposer soil organisms; pathogenicity or decomposition role of certain microorganisms). Chapter 10 then introduces metagenomics and metatranscriptomics approaches, their advantages, but also the challenges and solutions to appropriately sampling, sequencing these complex DNA/RNA populations. Chapter 10 finally presents several strategies and software to analyze metagenomes/metatranscriptomes, and discusses their pros and cons.

Chapter 18 “Analysis of bulk samples” deals with the particular case of biodiversity surveys based on bulk samples. A bulk sample is an environmental sample containing mainly organisms from the taxonomic group under study, such as insect samples obtained from a Malaise trap, or eukaryote-enriched samples obtained from filtered or size-fractionated water samples. One important characteristic of bulk samples is that they usually provide good-quality DNA in high amounts. Chapter 18 presents several seminal studies based on bulk samples that aimed at monitoring arthropod, nematode, or marine metazoan diversity. The advantages and limitations of the classical barcoding COI marker versus metabarcoding markers for bulk sample analysis are also discussed. Finally, Chapter 18 reviews two alternative strategies to limit the taxonomic biases associated with the use of the COI marker (i.e., mitochondrial enrichment via differential centrifugation or capture, followed by extraction and shotgun sequencing).

After a brief reminder of the principles underlying the polymerase chain reaction (PCR), Chapter 6 “DNA amplification and multiplexing” discusses the choice of a DNA polymerase for the PCR. In particular, it warns against the use of proofreading polymerases, that can lead to a substantial loss of PCR specificity. Chapter 6 insists on the benefits of including different types of controls in the PCR (e.g., PCR negatives and positives, tagging system controls, etc.). The most common causes of PCR failures and their solutions are addressed, as well as the precautions to take to avoid and monitor contaminations. Chapter 6 also deals with the particular case of blocking oligonucleotides, which aim at reducing the amplification of undesired sequences. It gives some valuable guidelines to design such oligonucleotides and use them efficiently. Finally, Chapter 6 presents different strategies for tagging individual samples during the amplification, to allow subsequent multiplexing during the sequencing step.