Abstract Protists play important roles in food chains and symbioses in soil and aquatic environments, displaying an enormous morphological and functional diversity 1,2 . While most commonly found protist species are well known to science, our global-scale environmental DNA survey across soil, water, and sediments reveals dozens of novel, phylum-level phylogenetic lineages that remain to be characterized for basic morphology and function. A vast majority of these undescribed taxa occur in marine water and sediments, but some are common in soil. Most of these novel taxa have distinct substrate and habitat preferences and biogeographic patterns. To accord these lineages scientific agency and enable unambiguous scientific communication, we propose formal names for 150 species to phylum-level taxa from 25 deep lineages based on eDNA and rRNA gene long-read sequence information.

Although the first data on Estonian oribatid mites date back to 1859 with the work of A. E. Grube, the fauna has never been systematically revised since then. Data from all previous literature sources contain reliable records of 128 species, to which are added 172 new species records, based on 456 samples from different microhabitats from all parts of Estonia. The Estonian oribatid mite fauna has thus records of 300 species, which is a comparable number with the neighboring countries. Three new combinations and three new synonyms are proposed: Cymbaeremaeus venosus (Grube, 1859) comb. nov. et syn. nov. = Cymbaeremaeus cymba (Nicolet, 1855), Cepheus tricuspidatus (Grube, 1859) comb. nov. et syn. nov. = Cepheus latus (C. L. Koch, 1835), Oribatella quadricuspis (Grube, 1859) comb. nov. and Kaszabobates helveticus Mahunka & Mahunka-Papp, 2000 = Kaszabobates olbiopolitanus Sergienko, 1980 = syn. nov.

The mechanisms of soil carbon (C) cycling depend on belowground trophic interactions that regulate microbial organic matter processing, yet the role of soil fauna in controlling microbial carbon use efficiency (CUE) and carbon fluxes under field conditions remains unknown. Here, we combined an in-situ mesh-based faunal exclusion experiment with root manipulation (living vs. severed) in a boreal forest to disentangle the root–microbe–fauna controls on soil C cycling. We found that soil CO₂ efflux tended to decline across manipulated plots relative to undisturbed field control representing an intact root–microbe–fauna system, but a significant 26% decline was observed only when root severing was combined with restricted faunal access. This decline likely reflects both the loss of root-derived respiration and reduced fauna-mediated stimulation of microbial processes. However, microbial functioning was more sensitive than bulk soil C fluxes to disturbance of the belowground continuum. Active microbial biomass, and microbial biomass C declined following root severing, while CUE decreased by up to 28% and became significantly lower relative to the undisturbed control only when the soil food web was further disturbed by restricting the access of soil macro- and/or mesofauna. Leucine aminopeptidase activity also declined following root severing, indicating altered microbial nutrient acquisition. These responses were accompanied by shifts in microbial nutrient pools, whereas soil organic C and total nitrogen stocks remained unchanged during the one-year experiment. Our results demonstrate that integrity of root–microbe–fauna continuum, sustained by plant-derived labile C inputs and soil fauna-mediated processes, results in the most efficient microbial CUE. Hence, disruption of these trophic interactions suppresses microbial C processing, with important implications for predicting soil C–climate feedbacks.

Metabarcoding is a powerful tool for biodiversity comparisons, where standard-size DNA barcodes (> 500 bases) offer better taxonomic resolution than shorter ones. Still, the choice of sequencing platforms and bioinformatics pipelines may strongly affect inferred diversity due to various technical biases. We assessed the relative performance of Illumina MiSeq i100 (2 × 500 paired-end), PacBio Revio and Oxford Nanopore MinION sequencing and bioinformatics pipelines, using full-length ITS amplicon sequencing datasets from a 103-species mock community and 45 composite soil samples. Despite numerous low-quality reads, PacBio yielded the lowest overall error rate and highest number of taxa. Illumina revealed the highest proportion of chimeric and index-switched reads, along with a strong bias towards shorter amplicons. MinION data analysed using PRONAME and Minovar-a bioinformatics pipeline presented here-had the largest proportion of low-quality data, and rare taxa were lost during data filtering and read polishing steps. Although Minovar enabled amplicon sequence variant (ASV) level precision for common taxa, we recommend clustering ASVs into OTUs. For PacBio, standard filtering approaches outperformed the ASV approach because they retained rare taxa. For Illumina, a stringent ASV approach or removal of rare OTUs would limit artefacts. Across all platforms, excess PCR cycles promoted chimeric and low-quality reads and lost quantitativity in biodiversity assessments. With moderate differences in effect sizes, all analytical approaches supported the conclusion that sampling design determines how we see soil biodiversity responses to land use. For biodiversity surveys based on the full-length ITS metabarcoding, we recommend using PacBio sequencing with standard, non-ASV pipelines.

Given the sheer scale of faunal life present in soils, the remains of these organisms in their afterlife represent an important pool of soil organic matter (SOM). Recently, Lejoly et al. (2026) highlighted the importance of faunal contributions in SOM, including inputs from this “faunal necromass”, and calls for explicit measurement of this carbon pool. While we agree with this call, however, we raise the issue that no methods have been developed to explicitly quantify it. This oversight not only limits the measurement of this carbon pool, but also biases estimates of fungal necromass. That is, the widely used chitin-derived glucosamine as a fungal necromass biomarker is found in both fungal and faunal dead tissues. This “chitin conundrum” creates a major limitation for estimating of necromass-derived soil carbon pools dynamics. Integrating compound-specific isotope analysis, metaproteomics, high-resolution mass spectrometry and faunal-specific molecular markers with experimental soil food-web approaches could resolve this limitation and reveal the true role of soil fauna in carbon cycling dynamics.

Abstract Ecological roles are treated as discrete, bounded units of biological organization, even as evidence shows that many taxa are versatile, performing more than one of them. Each record of versatility represents a boundary crossing, yet current categorical paradigms prevent this cumulative evidence from reshaping the roles themselves. We solve this by introducing the ecological multiverse, a self-correcting framework that turns boundary crossings into a network of role connectivity. Applied to Fungi, the multiverse recasts the major form of plant pathogenicity from an isolated disease role into a central hub linking much of fungal functional space, especially benign plant symbioses and decomposition. By exposing this topology, the multiverse transforms categorical views of ecological function into a dynamic map, revealing pathways of role change as organisms and knowledge evolve.

African soils host a diverse but largely underexplored fungal community, but its poorly understood nature impedes the management and understanding of vital species that provide essential ecological services. As a result, the diversity and distribution of soil fungi in Africa remain largely unknown and inadequately documented compared to the global north, with countless species and presumably higher-level taxonomic groups awaiting discovery and description. Ongoing threats such as habitat degradation, climate change, and intensified land use highlight the urgent need to understand and conserve these vital microbial communities. To address this knowledge gap, we generated eDNA metabarcoding data from 467 topsoil samples across various terrestrial ecosystems in 32 African countries. Our analyses revealed significant spatial heterogeneity, with diversity hotspots in savannas, temperate mixed forests, and dry tropical forest ecosystems and low-diversity zones (coldspots) in arid shrublands and deserts. Precipitation and latitudinal distance emerged as the strongest predictors of fungal alpha diversity. Meanwhile, the drivers of beta diversity were mainly temperature, precipitation, and soil chemical properties. To integrate African soil fungi into the principles of continental biodiversity distribution, we present a detailed continent-wide (including islands) map of fungal richness for all fungi and mycorrhizal fungi, highlighting fine-scale spatial patterns across various ecosystems. This study presents the most comprehensive spatial analysis of soil fungal diversity in Africa to date, acting as a vital reference for advancing ecological research, biodiversity monitoring, and conservation planning across the continent. We emphasize here that more effort should be made to conserve soil fungi, particularly mycorrhizal fungi in Africa, especially in regions with low fungal diversity.

Of the two otariid species endemic to the Galapagos Islands, the Galapagos fur seal (GFS, Arctocephalus galapagoensis) remains the least studied due to its remote distribution restricted to the western islands of the archipelago, a region uniquely influenced by the cold, productive Equatorial Undercurrent (EUC). This study presents the first two complete GFS mitogenomes, assembled from scat samples collected at the Cabo Douglas rookery on Fernandina Island, to contribute to elucidating the evolutionary history of this endangered species. Time-calibrated phylogenies indicate most Arctocephalus species form a monophyletic group.​ These also show GFS as sister to South American and New Zealand fur seals, diverging 1.91–1.68 MYA (million years ago). This divergence coincides with the early Pleistocene cooling (Gelasian–Calabrian transition), when colder oceans favored otariid dispersal, thus suggesting the time of arrival of fur seals to the Galapagos Islands. The Galapagos region, maintained by the EUC, likely served as a climate refugium enabling fur seal persistence in tropical waters despite later interglacial warming. This study underscores the utility of non-invasive genetic sampling and highlights the role of the Galapagos marine ecosystem as a climate refugia for biodiversity in the face of oceanic warming.

The diversity and biogeographic patterns of ectomycorrhizal fungi (EcMF) remain underexplored in many parts of the world, particularly in southern temperate ecosystems. Here, we present the first molecular characterization of EcMF communities associated with North African populations of Alnus glutinosa (L.) Gaertn., commonly known as black alder. Root samples over multiple sampling periods were collected from three sites in and around El Kala Biosphere Reserve, northeastern Algeria, and analysed using high-throughput sequencing targeting the full ITS region. We identified 101 EcMF operational taxonomic units (OTUs), representing two phyla, two classes, seven orders, 15 families, and 18 genera—predominantly Basidiomycota (98.6%). The genera Lactarius, Tomentella, and Inocybe consistently dominated across all sites. Community richness and diversity varied significantly among sites. Organic matter content and site identity significantly influenced EcMF community composition, whereas seasonality and other edaphic parameters showed no detectable effects. Comparative phylogenetic analysis revealed minimal overlap with EcMF communities from European, Asian, or American Alnus populations. These findings demonstrate that southern marginal populations of A. glutinosa harbour exceptionally rich and potentially unique EcMF assemblages, likely shaped by relative aridity, geographic isolation, and host lineage divergence. Our study highlights the critical importance of incorporating biogeographically peripheral ecosystems into global fungal diversity assessments, particularly in historically and environmentally distinctive regions.

Soil eukaryotes, including fungi, protists, plants, and animals, are central to biosphere functioning and resilience. The Global Standardised Soil Eukaryome Dataset (GloSED) is the first dataset encompassing the entire spectrum of soil eukaryotes, covering 4,063 sampling sites in 121 countries on all continents, revealing nearly one million operational taxonomic units. All samples were collected and analysed using a standardised protocol minimizing technical biases. Long-read sequencing of full-length ITS and 18S-V9 regions provide broad taxonomic coverage and high-resolution identification supported by specialist curation of "dark taxa". A rigorous bioinformatic processing ensures against homopolymer errors, PCR-mediated chimeras, and index switching providing high data quality. The dataset is supported by raw sequences and an open-source containerised workflow for reproducible analyses. The samples are accompanied by land-cover description and directly measured soil pH, δ13C, δ15N, as well as P, K, Ca, Mg, and total C and N contents. GloSED is the first database that enables ecological and biogeographic studies of entire soil eukaryotic communities from local to global scales.

Abstract Aquatic ecosystems have changed dramatically, but the relative roles of external forcings and internal atmospheric variability remain unclear. Here, using Tibetan lake ecological reconstructions and Earth system simulations, we reveal how shared external forcings shaped Tibetan Plateau limnoecology over the past millennium through two distinct pathways. In the temperature-centric pathway, cooling episodes driven by volcanic activity and internal variability likely regulated preindustrial lake conditions. This baseline was disrupted as recent forced warming has shortened lake ice-cover and increased meltwater input, altering lake resources and triggering unprecedented diatom shifts. In the freshening-centric pathway, salinity-tolerant diatoms tracked monsoon-driven precipitation changes and lake freshening, both governed by shifts in the intertropical convergence zone. Preindustrial shifts likely reflected hemispherically asymmetric orbital and volcanic forcings, whereas modern changes have been altered remarkably by Northern Hemisphere industrial aerosol fluctuations and warming-induced meltwater. As multifaceted stressors intensify, Tibetan lake ecosystems may continue diverging from their natural variability.

Although the Galápagos islands represent a unique ecosystem—with generally well-studied biota—research on its macroalgal flora remains relatively scant compared to other groups, particularly terrestrial fauna. Furthermore, while a few recent studies have applied molecular techniques, taxonomic identification of the archipelago’s macroalgae has mostly relied on morphology alone, which presents numerous challenges. In this study, we developed a DNA barcoding approach to identify macroalgal specimens collected opportunistically across the foraging grounds of endemic marine iguanas (Amblyrhynchus cristatus Bell 1825), which feed almost exclusively on macroalgae in coastal zones. We optimized primers for short DNA fragments of two genes and generated a reference dataset of macroalgal DNA sequences to facilitate future metabarcoding studies on marine iguana diet. Our approach—amplifying 110 bp of the nuclear small subunit (18S) ribosomal gene—proved effective for identifying red, green, and brown macroalgae at higher taxonomic ranks, specifically at ordinal rank, while 184 bp of the ribulose-1,5-bisphosphate carboxy-lase/oxygenase (rbcL) gene enabled genus-rank identification in red macroalgae. We present the first compendium of macroalgal DNA sequences from marine iguana foraging areas, comprising 181 algal specimens: 136 red algae, 32 green algae, and 13 brown algae. We confirm taxa previously reported for the Galápagos and report eight new species of red macroalgae for this region. Our short barcodes provide a dataset of reference sequences to further research on marine iguana dietary habits. We also updated the Galápagos species checklists for Rhodophyta, Chlorophyta, and Ochrophyta by incorporating our newly generated molecular data alongside previously available macroalgal DNA sequences.

Afforestation is increasingly recognized as a critical strategy to restore ecosystems and enhance biodiversity on post-agricultural landscapes. However, agricultural legacies, such as altered soil structure, nutrient imbalances, and depleted microbial diversity, can slow down forest establishment or cause ecosystems to deviate from expected successional trajectories. In this opinion paper, we explore the potential of soil inoculations as a tool to overcome these challenges by introducing beneficial microbial communities that can accelerate ecosystem recovery and forest development. Restoring soil biodiversity is a crucial aspect of this process that drives broader ecosystem functionality and resilience. We highlight the need to carefully consider the type and timing of inoculations and to ensure compatibility between the inoculum and recipient site characteristics to optimize the establishment of introduced species. While tree productivity is often a central focus of afforestation efforts, the restoration of soil biodiversity, which will also contribute to increased ecosystem-level functions, should also be a priority for long-term forest resilience. Agricultural legacies add complexities to the restoration process, creating unique challenges that need to be addressed in restoration planning. Thus, successful inoculation strategies require a thorough understanding of both donor and recipient site characteristics, also in relation to potential mismatches related to soil physiochemical properties to avoid unintended consequences such as the non-establishment of introduced species. Additionally, we call for the re-evaluation of afforestation targets and the development of standardized monitoring protocols that track the success of inoculation efforts, particularly regarding soil health, microbial community establishment, and biodiversity recovery. By integrating inoculation practices within a broader restoration framework, we can enhance the resilience, biodiversity, and ecosystem functionality of newly afforested landscapes. Ultimately, this approach may play a critical role in ensuring the success of large-scale afforestation projects.

The characterization of soil mite (Acari) communities traditionally follows morphological identifications of specimens extracted from soil, which is a highly laborious and time-consuming process. Metabarcoding has become an increasingly utilized approach for species identification from environmental DNA (eDNA) samples, but whether the metabarcoding approaches align with the morphological identification data on soil mites has rarely been addressed. Here, we examine the congruence of soil mite communities between morphological and metabarcoding datasets. The morphological dataset was generated by extracting mite specimens from the soil samples, whereas molecular datasets represent two types of cytochrome c oxidase subunit I (COI) amplicons produced directly from soil eDNA (from 0.2 g and 2 g soil samples) and sequenced with Illumina (313 base pairs amplicons) and PacBio (658 base pairs amplicons) platforms. We found that specimen extraction from soil samples, followed by morphological identification, yielded the highest number of mite species. Despite significantly lower mite richness in the metabarcoding datasets, PacBio datasets provided more reliable community profiles that aligned strongly with the morphological data. This indicates that soil sample quantities generally used for microbial analyses are also informative in studying soil faunal communities. Furthermore, our results indicate that methodological choices (herein PacBio vs. Illumina) have a greater influence on mite community detection than the amount of input soil used for DNA extraction. Interestingly, the patterns of the entire metazoan community in the metabarcoding datasets strongly mirrored those of the morphologically identified mite communities alone, indicating that soil mites serve as a powerful ecological indicator group.

Integration of soil biodiversity restoration into reforestation strategies is important to accelerate the restoration process given the interplay between belowground and plant community dynamics. Research on the mechanisms underlying the temporal changes that occur in soil communities has been limited, and this is especially true for eukaryotes. Understanding these processes can help us to manipulate soil communities in a way that promotes recovery and stability. Here, we test the importance of selection, dispersal, and drift in structuring community composition of taxonomic and functional groups of soil eukaryotes in croplands and planted forests, and their relationships with successional time. We observed a link between functional/taxonomic groups of soil eukaryotes, the importance of ecological processes in their community compositional patterns, and successional time. To optimize the effectiveness of soil restoration, we suggest implementing additional measures that target specific groups of soil organisms, account for the key ecological processes structuring their communities, and address how these processes correlate with successional time. Our findings advance both theoretical understanding and practical guidelines for restoring soil biodiversity.

Long-read amplicon sequencing has enabled us to return to full-length DNA barcodes, which benefit from the higher taxonomic resolution in metabarcoding-based biodiversity studies. However, chimeric sequences (artificial constructs formed when incomplete amplicons fuse during polymerase chain reaction (PCR)) remain challenging, potentially skewing diversity estimates and ecological inferences. Here, we benchmark three de novo chimera detection algorithms, uchime_denovo, removeBimeraDenovo, and chimeras_denovo, on simulated and empirical eukaryotic full-ITS (rRNA ITS1-5.8S-ITS2) datasets to evaluate their precision, sensitivity, and effects on the final OTUs composition/community structure. Upon simulated data, uchime_denovo achieved the highest precision even with default settings, whereas other algorithms displayed high false-positive chimera rates without setting adjustments. Similarly, the tests upon empirical data showed that uchime_denovo had lower false positive rates, whereas about half of the sequences in the putative chimeric batch were false positives when using chimeras_denovo and removeBimeraDenovo. We found that most of the false-negative chimeras contained multiple 5.8S regions, indicating PacBio library preparation artifacts rather than PCR artifacts. However, OTU-level comparisons indicated that overall richness and community-ordination patterns remain largely consistent across different chimera-filtering approaches with or without accounting for false positives and negatives.

Across the world, human (anthropophonic) sounds add to sounds of biological (biophonic) and geophysical (geophonic) origin, with human contributions including both speech and technophony (sounds of technological devices). To characterize society's contribution to the global soundscapes, we used passive acoustic recorders at 139 sites across 6 continents, sampling both urban green spaces and nearby pristine sites continuously for 3 years in a paired design. Recordings were characterized by bird species richness and by 14 complementary acoustic indices. By relating each index to seasonal, diurnal, climatic and anthropogenic factors, we show here that latitude, time of day and day of year each predict a substantial proportion of variation in key metrics of biophony-whereas anthropophony (speech and traffic) show less predictable patterns. Compared to pristine sites, the soundscape of urban green spaces is more dominated by technophony and less diverse in terms of acoustic energy across frequencies and time steps, with less instances of quiet. We conclude that the global soundscape is formed from a highly predictable rhythm in biophony, with added noise from geophony and anthropophony. At urban sites, animals experience an increasingly noisy background of sound, which poses challenges to efficient communication.

DNA-based biodiversity surveys result in massive-scale data, including up to millions of species-of which, most are rare. Making the most of such data for inference and prediction requires modeling approaches that can relate species occurrences to environmental and spatial predictors, while incorporating information about their taxonomic or phylogenetic placement. Even if the scalability of joint species distribution models to large communities has greatly advanced, incorporating hundreds of thousands of species has not been feasible to date, leading to compromised analyses. Here we present a 'common to rare transfer learning' (CORAL) approach, based on borrowing information from the common species to enable statistically and computationally efficient modeling of both common and rare species. We illustrate that CORAL leads to much improved prediction and inference in the context of DNA metabarcoding data from Madagascar, comprising 255,188 arthropod species detected in 2,874 samples.

Soil communities are essential to ecosystem functioning, yet the impact of reducing soil biota on root-associated communities, tree performance, and greenhouse gas (GHG) fluxes remains unclear. This study examines how different size fractions of soil biota from young and mature forests influence Alnus glutinosa performance, rootassociated community composition, and GHG fluxes. We conducted a mesocosm experiment using soil community fractions (wet sieving through 250, 20, 11, and 3 mu m) from young and mature forest developmental stages as inocula. The results indicate that the root-associated community composition was shaped by forest developmental stage but not by the size of the community fractions. Inoculation with the largest size fraction from mature forests negatively affected tree growth, likely due to increased competition between the plants and soil biota. In addition, GHG fluxes were not significantly impacted by either size fraction or forest developmental stage despite the different community composition supplied. Overall, our research indicates that A. glutinosa strongly selects the composition of the root-associated community, despite differences in the initial inoculum, and this composition varies depending on the stage of ecosystem development, impacting the performance of the trees but not GHG fluxes.

To turn environmentally derived metabarcoding data into community matrices for ecological analysis, sequences must first be clustered into operational taxonomic units (OTUs). This task is particularly complex for data including large numbers of taxa with incomplete reference libraries. OptimOTU offers a taxonomically aware approach to OTU clustering. It uses a set of taxonomically identified reference sequences to choose optimal genetic distance thresholds for grouping each ancestor taxon into clusters which most closely match its descendant taxa. Then, query sequences are clustered according to preliminary taxonomic identifications and the optimized thresholds for their ancestor taxon. The process follows the taxonomic hierarchy, resulting in a full taxonomic classification of all the query sequences into named taxonomic groups as well as placeholder "pseudotaxa" which accommodate the sequences that could not be classified to a named taxon at the corresponding rank. The OptimOTU clustering algorithm is implemented as an R package, with computationally intensive steps implemented in C++ for speed, and incorporating open-source libraries for pairwise sequence alignment. Distances may also be calculated externally, and may be read from a UNIX pipe, allowing clustering of large datasets where the full distance matrix would be inconveniently large to store in memory. The OptimOTU bioinformatics pipeline includes a full workflow for paired-end Illumina sequencing data that incorporates quality filtering, denoising, artifact removal, taxonomic classification, and OTU clustering with OptimOTU. The OptimOTU pipeline is developed for use on high performance computing clusters, and scales to datasets with millions of reads per sample, and tens of thousands of samples.