Environmental DNA

Environmental DNA (eDNA) methods offer a powerful tool for monitoring aquatic species, yet field applications remain challenged by uncertainty in DNA transport, mixing, and detection, particularly in flowing or tidally influenced systems. One approach to improve confidence in eDNA surveys is the use of controlled DNA sources (positive controls), but questions remain regarding how the biological condition of the source influences eDNA release and detectability. This study evaluated differences in eDNA concentrations emitted from live versus dead fish in a controlled, shallow, well-mixed channel. Using a fixed point-sampling design, we measured eDNA concentrations over time and modeled the effects of treatment, sampling time, temperature, and water velocity. Dead fish consistently released significantly higher concentrations of eDNA than live fish, while eDNA concentrations declined over time in both treatments. Water temperature and velocity did not significantly influence detection, and the rate of eDNA decline was similar between live and dead treatments. These findings highlight the importance of source condition and site-specific mixing dynamics when interpreting positive control experiments and underscore the value of site characterization when designing eDNA sampling protocols.

Environmental DNA (eDNA) provides a powerful tool for biodiversity monitoring in large river ecosystems. However, current studies often rely on subjective site selection and lack systematic sampling designs. This can limit the ability to capture the full spectrum of environmental conditions that species depend on, thereby compromising sampling efficiency. To address this challenge, we propose utilizing remote sensing-based clustering for environmental stratification of sampling designs, thereby enhancing detection capabilities and increasing the objectivity of eDNA sampling. Using GBIF-based fish species distribution models and simulated distributions along the Danube, we demonstrate that this approach enhances detection efficiency compared to conventional random and regular sampling methods. To facilitate practical implementation, we developed a tool to help fieldwork planners of river sampling campaigns automatically apply this method and select stratified sampling sites without the need for extensive data processing. Finally, we demonstrate that eDNA detection occurred most frequently within the range of 0-20km downstream of the expected modeled distribution of species, suggesting that the diffusion of the signal should be further considered in the sampling design process. Our findings highlight the potential of remote sensing-based stratification to create more efficient and objective sampling designs but suggest that sampling design should be further combined with hydrological information to optimize cost-efficient sampling. The development of standard and robust sampling protocols will help advance more cost-effective eDNA-based biodiversity monitoring in riverine ecosystems.

Airborne environmental DNA (eDNA) is a promising tool for detecting a wide range of taxa including threatened and invasive species, yet its application in management is constrained by a limited understanding of its temporal persistence, particularly in nature. We investigated the temporal persistence of airborne eDNA in a natural outdoor setting, using Bennetts wallaby Notamacropus rufogriseus as a case study. We captured airborne eDNA from a single Bennetts wallaby carcass, deployed in an area where wallabies are otherwise not present. A total of 180 samples were collected, spanning the period before deploying the carcass, the 11 days it was on site, and for 32 days after its removal, at distances of 1, 10, and 100 metres using both active (fan-assisted) and passive (no fan) collection methods. Although overall detection rates were low, wallaby DNA was detectable up to 100 metres shortly after the wallaby was introduced to the site and for up to three days after its removal. These findings indicate that airborne eDNA persists only briefly. Actively sampling air using battery-powered fans significantly improved detection rates relative to passive sampling. We demonstrate that airborne eDNA can detect individual organisms in outdoor environments, but reliable detection requires robust sampling and replication to capture rare, transient signals. By revealing how these signals persist over time, our findings provide a framework for optimizing field deployment and for distinguishing remnant DNA from new incursions.

Leaf litter ecosystems and their fauna are largely understudied, despite their critical ecological roles. Here, we investigate challenges associated with estimating biodiversity in terrestrial leaf litter. Current methodologies for biodiversity assessment are fraught with limitations, amongst the most significant is a decline in taxonomic expertise, complicating the process of species identification and the significant costs associated with species-level morphological identifications. DNA barcoding employs the mitochondrial gene cytochrome c oxidase I (COI) to identify animal species, and DNA metabarcoding facilitates the identification of multiple species without necessitating taxonomic expertise. Recent studies indicate that environmental DNA (eDNA) may exhibit greater sensitivity compared to traditional methods. To test whether these methods work in a real-world application, we sampled leaf litter across a temperate forest/field ecotone. Leaf litter was dried, ground and processed to extract environmental DNA. We evaluated the DNA extraction protocols to test their relative efficacy. We found that the Qiagen Blood and Tissue Kit was the most effective at recovering invertebrate diversity and that there were notable differences in biodiversity between forest and field habitats. Temperature emerged as a significant factor influencing the composition of the communities observed. Our methodology is applicable across various environments for efficient biodiversity assessment and might be particularly beneficial for monitoring pests and invasive species. Our approach offers a cost-effective and timely alternative to conventional biodiversity assessment methods and underscores the significance of accurate assessment methodologies for leaf litter communities.

Effective monitoring of the critically endangered European eel (Anguilla anguilla) is essential for conservation planning and regulatory decision-making, particularly in heavily fragmented rivers. Environmental DNA (eDNA) methods offer sensitive alternatives to traditional surveys, but there is uncertainty around whether targeted assays or community-wide approaches are better suited to achieve monitoring objectives. We compared eDNA metabarcoding and species-specific quantitative PCR (qPCR) for detecting A. anguilla across 145 pumped catchments in the Fens, East Anglia, England. All sites were sampled once initially, and sites negative for A. anguilla were re-sampled based on metabarcoding results. This allowed comparison of detection rates from a single water sample and site-level retrospective identification of sites where qPCR could have identified A. anguilla in earlier samples. The findings were also set in the context of the wider biodiversity information generated by metabarcoding. From the initial (single) water sample, qPCR detected A. anguilla at seven more sites than metabarcoding (17 versus 10). With repeated sampling, metabarcoding detected A. anguilla at 43 sites, including all but one of the sites where qPCR detected A. anguilla, and ten sites where qPCR did not detect A. anguilla within the same number of samples. Indeed, the additional sampling effort required to detect A. anguilla with metabarcoding at sites also positive with qPCR was small relative to the overall sampling effort. Furthermore, metabarcoding additionally detected 28 non-target fish species alongside fish, amphibian and mammal species of conservation concern. Our results highlight trade-offs between target-species sensitivity and the broader ecological information provided by each method, and support metabarcoding as an effective tool for a holistic conservation approach, with the additional community data outweighing the marginally increased sensitivity of qPCR.

O_LIEnvironmental DNA (eDNA) metabarcoding is an emerging tool for biodiversity assessment in freshwater systems, offering high-resolution insights into community composition. Here, we apply eDNA metabarcoding to evaluate the ecological impacts of Eurasian beaver (Castor fiber) activity within a seminatural enclosure in the Scottish Highlands. C_LIO_LIWe collected seasonal water samples from nine sites, six influenced by beaver dams and three control sites with no evidence of beaver engineering, across a 40-hectare enclosure. Samples were analysed for vertebrate and macroinvertebrate diversity using established 12S and COI markers. C_LIO_LIVertebrate alpha diversity did not differ significantly between beaver and control sites, likely reflecting the small spatial scale and low species richness of upland Scottish streams. However, community composition differed significantly between treatments, especially for fish (PERMANOVA, R2 = 0.55, P < 0.001), with beaver-influenced sites dominated by three-spined stickleback and control sites by brown trout. Macroinvertebrate communities showed a 78% increase in gamma diversity in beaver-modified habitats relative to controls. Species composition varied strongly with beaver presence (PERMANOVA, R2 = 0.29, P < 0.001), likely due to the creation of lentic-lotic mosaics and associated microhabitat diversity. Seasonal variation was significant in both taxonomic groups, with the lowest species richness and highest community dispersion observed in summer, probably reflecting hydrological and temperature-driven dynamics in eDNA production and transport. C_LIO_LIOur findings reinforce previous evidence that beaver dam-building activity enhances beta diversity in headwater systems. Additionally, we demonstrate that eDNA metabarcoding is a sensitive method for detecting spatial patterns in freshwater biodiversity associated with these activities at scales ranging from tens to hundreds of meters. These approaches could inform future monitoring strategies aligned with landscape-scale beaver management and reintroductions. C_LI

Vertebrates play vital roles in maintaining ecosystem processes and services and serve as valuable indicators of environmental health, making them an important target for monitoring and conservation efforts. Within the environmental DNA (eDNA) toolbox, airborne environmental DNA has recently emerged as a novel approach for vertebrate monitoring. In this study, we evaluated on-site airborne eDNA for terrestrial vertebrate monitoring in the Luangwa Valley savanna in Zambia, which represents a major biodiversity stronghold of largely intact wilderness and with high levels of vertebrate diversity and endemism. Six air samplers were deployed over four days alongside camera traps for validation, and samples were processed using a mobile molecular laboratory. In total, 120 terrestrial vertebrate taxa were detected with airborne eDNA, including 16 of the 17 taxa recorded by camera traps, demonstrating high sensitivity. Notably, 72.5% of taxa were detected on the first day, and a single sampler recovered 61.7% of all taxa; the taxonomic richness incrementally increased with extended sampling efforts, but the magnitude of these increases declined progressively. The detected taxa spanned the four terrestrial vertebrate classes and encompassed a wide range of ecological traits. These results show that airborne eDNA can quickly recover a substantial and representative fraction of local vertebrate diversity within a short sampling window, while extended sampling can improve detection of less common taxa. Despite existing limitations, our findings support the use of airborne eDNA as an efficient and scalable complementary tool for community-level biodiversity assessments in terrestrial ecosystems such as Zambezian savannas.

Terrestrial environmental DNA (eDNA) approaches are rapidly expanding, yet robust, field-ready substrates for detecting insect DNA remain limited in forest ecosystems. Tree sap is a localized microhabitat that attracts diverse insects and may provide a useful substrate for surface eDNA sampling, but its potential for insect monitoring has rarely been evaluated. Here, we present a pilot proof-of-concept study testing naturally exuding tree sap and sap-mimicking traps as terrestrial eDNA substrates. We collected swab samples from sap and trap surfaces at two forest sites in Japan (Fujisawa and Minamisanriku) and performed metabarcoding using COI and an arthropod-focused 16S marker (gInsect). Reads were processed into amplicon sequence variants and assigned by BLAST top hits against NCBI nt, with high-confidence detections defined at identity [&ge;]98%. Across sites, sap and trap swabs yielded multiple high-confidence insect detections spanning several orders, including sap-associated stag beetles (Dorcus spp.). Overlap with contemporaneous conventional monitoring was limited, suggesting that sap-surface eDNA and conventional surveys capture partly different components of sap-associated insect assemblages. In a targeted 2024 spot survey, actively fermenting sap yielded multiple insect eDNA detections, whereas inactive, non-fermented sap yielded no high-confidence insect detections. Although limited by small sample size and the absence of dedicated process controls, these findings support the feasibility of tree sap as a localized terrestrial eDNA substrate and provide a basis for future replicated studies of sap-associated insect monitoring.

O_LIEnvironmental DNA (eDNA) metabarcoding of water samples is increasingly used to detect fish species in streams. Several studies have concluded that it can outperform traditional inventory methods and recommend using it at large scales for fish-based ecological assessments. However, there is no standard protocol that can guarantee sufficient detection rates and repeatability, despite companies offering an extensive range of analyses. C_LIO_LIWe compared eDNA metabarcoding performed by four companies. Following their guidelines, samples were collected in a small tropical stream in the Maroni River (French Guiana) that hosts a species-rich fish community. We compared their inventories to each other and to a list of species captured during an extensive fish inventory performed immediately after sampling eDNA, as well as to current data on the species distributions. C_LIO_LIThe number of species detected by eDNA metabarcoding ranged from 5 to 48 among the companies, but these inventories contained many inaccuracies. All companies combined, 63 species were detected, of which 10 (16%) had never been reported in the Maroni River. The extensive inventory identified 50 species in the local fish community, of which 16-46 were not detected by eDNA metabarcoding (i.e. false negative detection rate of 32%-92% among the companies). C_LIO_LIReanalysis of raw sequencing data decreased differences among companies greatly, highlighting the importance of using a comprehensive and accurate DNA barcode database to assign species. Dissimilarity indices, calculated to compare the local fish community (based on presence/absence or fish catches) to eDNA detection, revealed large differences regardless of the company. C_LIO_LISummary and applications. The large percentage of species not detected by eDNA metabarcoding of water samples could strongly bias fish-diversity inventories in streams that host species-rich communities. This issue is not well documented in the literature, and we recommend that similar studies in the future focus on other stream contexts. The large differences between commercial eDNA inventories and the local fish community challenge the use of eDNA metabarcoding for fish-based ecological assessments of streams. The variable performance of eDNA companies indicates the need for a standard protocol and access to a comprehensive DNA database before beginning large-scale eDNA programmes. C_LI Highlights- eDNA metabarcoding of water samples is widely used to detect species in streams - Detection performances of 4 private companies were compared to an exhaustive fish inventory - The number of undetected species varies from 32 to 92% depending on the company - Such discrepancies challenge the use of eDNA for fish-based ecological assessments

Evidence supporting the use of airborne eDNA for biodiversity studies and ecosystem monitoring is growing. The promise of wide-area population dynamics data for downstream applications in targeted monitoring of pests and pathogens for agriculture and rare species for conservation is appealing; however, several technical challenges persist. Here, we focused on the development of a comprehensive dataset to facilitate assay development and accelerate the use of aerial sampling for species detection. Year-round metabarcoding data was generated using bacterial, fungal, plant, and arthropod primer sets and resulted in relative abundance estimates for 4,960 amplicon sequence variants (ASVs), 1,748 ASVs of which were assigned to a minimum taxonomic level of genus (bacteria, fungi, plants) or class (arthropods). Sequence diversity assessments and seasonal clustering based on presence/absence detection patterns were performed for individual ASVs, while discerning quantitative changes in seasonal abundance required grouping ASVs to at least the genus level. Examination of the technical aspects of metabarcoding suggested that the use of subsampling allows for consistent detection of genera with relative abundance values above 2 %, even when samples have varying sequencing depths. Sequencing depth was the primary determinate for detecting sporadic and/or rare ASVs. Sampler comparisons, common sources of variation, and the benefits of barcoding regional species to supplement the existing taxonomic databases were discussed. Insufficient knowledge of sampler coverage area for the different organism types was identified as a limitation to the deployment of aerial monitoring networks. Considerations for further aerial metabarcoding efforts are suggested based on our experimental findings. ImportanceOur study deals directly with the generation, analysis and limitations of airborne eDNA metabarcoding data for re-use by the broader environmental research community. This includes timing of seasonal detection for possible genera of interest across multiple kingdoms, including bacteria, fungi, plants and animals (specifically arthropods), and support for the generation of local databases to assess the current limitations of universal primers for species/genus taxonomic resolution. With regards to methodology, it continues to build upon established best practices for airborne eDNA collection in areas such as sub-sampling and sampling replicates, sampler type and sequencing depth. To accelerate possible uptake and application of the data, we provide the identified ASVs and their seasonal relative abundances as a resource.

Pollen is a robust and widespread substance that captures a historical snapshot of a specific time and place, and it can be used to track movements through space by examining the pollen deposited on various objects. Palynology, the study of pollen, is used across fields such as conservation, natural history, and forensics, where it is particularly useful for tracing the origin and movement of objects. However, pollen has remained underutilized due to the difficulty of distinguishing many pollen taxa beyond the family level and limited pollen reference material to support location predictions. With recent developments in pollen DNA metabarcoding these issues have been rectified, but much of the available pollen data are primarily from wind-pollinated species, which are widespread and less informative of specific sample locations. Bee-collected pollen presents an untapped resource in training predictive models to geolocate sample origin. Here we compiled bee-collected pollen DNA sequence relative abundance data from three projects in the western U.S. and assessed the accuracy of supervised machine learning models to predict the location of sample origin based solely on pollen assemblage, without the need of incorporating additional data. Random Forest and k-Nearest Neighbors models yielded high accuracy across all projects. We also found that models trained on taxonomically clustered pollen assigned sequence variants (ASVs) performed slightly better than those trained on raw sequence data, but the difference was minor, indicating that models trained on raw sequence data can reliably predict location and avoid the time-consuming taxonomic assignment process. Our results demonstrate the utility of repurposing bee-collected pollen for geolocation and provide a framework for employing supervised machine learning in future geolocation efforts. HighlightsO_LIBee-collected pollen metabarcoding data was used to accurately predict sample origin C_LIO_LIRandom Forest and k-Nearest Neighbors algorithms were most accurate with lowest error C_LIO_LITaxonomically-classified and raw DNA sequence data training sets performed comparably C_LI

Early detection and monitoring of non-indigenous species (NIS) is crucial to prevent their establishment and to reduce ecological and economic impacts in coastal ecosystems. Traditional monitoring approaches, which rely largely on morphological identification of collected organisms, are often time-consuming and may fail to detect species that occur at low abundance, are morphologically cryptic, or are present in the form of inconspicuous life stages. DNA-based approaches, particularly those resorting to environmental DNA, have demonstrated high aptitude for biodiversity monitoring and biosecurity surveillance. By examining the genetic material from bulk community samples or released into the environment, DNA-based approaches enable the detection of species without the need for direct observation, thereby increasing detection sensitivity and expanding the scope of monitoring programs. Despite the rapid growth of its employment in marine monitoring, a global synthesis of the status and trends of DNA-based approaches for detecting NIS in this environment has been lacking. Here, we present such synthesis, based on 146 published studies employing DNA for NIS detections in coastal environments. Two main methodological approaches were used across the reviewed studies, namely DNA metabarcoding which was applied in 49% of studies, closely followed by targeted single-species PCR assays, used in 42% of the studies. A smaller proportion of studies (10%) combined both approaches, integrating broad community screening with targeted detection to improve surveillance efficiency. Globally, 752 NIS were detected across disparate taxonomic groups, with metazoans representing the largest proportion of detections (464 species), followed by Chromista (210 species) and Plantae (77 species). Among these, the most frequently detected taxonomic groups included Dinophyceae (Dinoflagellata), Teleostei (Chordata), Florideophyceae (Rodophyta), Polychaeta (Annelida), Copepoda and Malacostraca (Arthropoda), and Ascidiacea (Chordata). At the species level, several well-known marine invaders were recurrently reported, including Bugula neritina (Linnaeus, 1758), Styela plicata (Lesueur, 1823), Acartia (Acanthacartia) tonsa Dana, 1849-1852, and Botryllus schlosseri (Pallas, 1766), highlighting the ability of DNA approaches to detect widespread and established invaders across different regions. The mitochondrial cytochrome c oxidase subunit I (COI) gene was the most widely used genetic marker, reflecting its broad taxonomic coverage and extensive representation in reference databases, particularly for targeting Metazoa. Ribosomal RNA genes, particularly 18S and 16S rRNA gene markers, were also frequently employed to target a wider range of eukaryotic taxa. Regarding sampled substrates, water was by far the most analyzed substrate, followed by zooplankton and biofouling communities collected from man-made structures. Notably, approximately 31% of all NIS detections reported in the reviewed studies constituted new regional records. These results highlight the potential of eDNA for coastal monitoring but also underline important limitations. Persistent geographical, taxonomic, and methodological biases can affect detection outcomes, and reliance on single sample types or markers may increase false negatives - particularly critical for NIS early detection. Therefore, multi-marker and multi-substrate approaches are essential to improve detection reliability and support effective biosecurity strategies. As reference databases continue to expand and methodological protocols become increasingly standardized, DNA-based monitoring is likely to play a central role in future management and surveillance of biological invasions in coastal ecosystems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/722998v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@17948b1org.highwire.dtl.DTLVardef@193832dorg.highwire.dtl.DTLVardef@189033dorg.highwire.dtl.DTLVardef@33cddf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Understanding the dietary patterns of introduced predators is essential for assessing their impacts on freshwater ecosystems. Here, we investigated the feeding ecology of the invasive Korean perch (Coreoperca herzi) introduced to the Oyodo River system, Japan, by integrating gut content DNA metabarcoding and environmental DNA (eDNA) metabarcoding. Fifty specimens were collected, and prey taxa were identified using metabarcoding targeting fish, aquatic insects, and crustaceans. In parallel, eDNA metabarcoding of habitat water samples was used to assess prey availability and selectivity. The results revealed that the Korean perch prey extensively on aquatic insects and fish. Aquatic insect prey were dominated by epilithic clinger taxa inhabiting stone surfaces, particularly mayflies, suggesting visual-mediated prey selection. Fish predation was frequently detected even in small individuals (<100 mm SL), in contrast to previous studies based on conventional methods, indicating that piscivory begins early and ontogenetic dietary shifts are not pronounced. Furthermore, quantitative fish eDNA analysis showed a positive relationship between eDNA concentrations of prey species and predation frequency, indicating opportunistic feeding on abundant, size-accessible prey. By applying two metabarcoding approaches, this study provides an integrated assessment of prey utilisation and environmental context, highlighting ecological risks posed by the Korean perch to freshwater communities in Japan.

Understanding risks of biological invasions associated with ballast water (BW) requires full understanding of the biodiversity transported in ballast tanks. Here we characterize the remarkable level of diversity that can be carried in the BW of a single vessel. To maximize our ability to capture BW diversity we: 1) utilized DNA-based methods to describe biodiversity, including both native and non-native taxa; 2) exploited multiple primer sets targeting multiple genomic loci with different expectations for taxonomic coverage; 3) assessed multiple tanks on a single vessel to capture different communities present in different tanks; and 4) sampled those tanks with far higher-than-usual replication both to improve representation of the diversity present and to enable statistical estimation of total richness. Using this approach, we found extraordinarily high diversity associated with a single vessel. Across all loci, we estimate a total of 272 taxa that can be assigned species names; looking more broadly at unnamed molecular operational taxonomic units, our estimates are between 425 and 742 individual taxa, depending on the locus. We confirm that only a fraction of this diversity would be captured with typical sampling efforts. We found that different loci capture different snapshots of biodiversity and that our ability to detect taxa of interest (e.g., non-native species) depends on sampling effort and genomic locus. Our results expand upon previous studies describing highly diverse BW communities and add to a growing literature that demonstrates the value of molecular methods for characterizing those communities and assessing the associated risk of non-native species introduction.

Environmental DNA metabarcoding is a powerful monitoring tool for assessing aquatic biodiversity, as well as the sustainability and impacts of fisheries and aquaculture. However, conventional laboratory workflows remain time-consuming and dependent on dedicated infrastructures. Here, we present a field trial of a fully portable, off-grid eDNA metabarcoding pipeline that enables end-to-end analysis within a few days using compact equipment, including a BentoLab workstation and an Oxford Nanopore Technologies (ONT) MinION sequencer. The workflow was implemented during two international training courses in Norway and Brazil, where students and early career researchers collected environmental samples, extracted and amplified DNA, prepared DNA libraries, and sequenced on-site before performing bioinformatics and statistical analyses. In the case study detailed here, seven eDNA samples collected and analysed on-site in the Oslofjord allowed detection of 16 fish and elasmobranch species. Although overall diversity was lower than in earlier studies using Illumina-based sequencing, our protocol reliably detected key species and demonstrates that portable eDNA metabarcoding is feasible for rapid ecological assessment, surveillance of high-risk regions and/or deployment in remote or resourcelZllimited settings.

DNA metabarcoding is a central tool in biodiversity research and monitoring, producing detailed taxa lists with comparatively little time and effort. One of its limitations, however, is the lack of quantitative data on biomass or abundance. This limitation has two main reasons: 1) template copy number variation and 2) primer-induced amplification bias. Many metabarcoding markers are mitochondrial and mitochondrial copy numbers vary in animal tissues, potentially decoupling sequence counts from biomass. Additionally, primer mismatches can lead to taxon-specific amplification biases, for which PCR cycle calibration has been proposed as a solution. To mechanistically study both effects, we constructed mock communities of different arthropod species. We combined digital droplet PCR and COI metabarcoding to quantify relationships between biomass, mitochondrial copy number and metabarcoding reads. Mitochondrial DNA copy numbers per biomass varied strongly within and among the different taxa. Metabarcoding reads did not reflect input mitochondrial DNA copies without a correction. Attempts to correct for amplification bias via PCR cycle calibration failed as read proportions remained stable across cycles. We therefore mathematically derived an approach to estimate relative amplification bias and initial mitochondrial DNA copy numbers in a sample based on a non-exponential amplification bias model and demonstrate its applicability. Still, the detected high variation in mitochondrial copy numbers and derived prerequisites necessary to calculate amplification efficiencies and mitochondrial copy numbers limit the practical application. Our study highlights fundamental constraints of quantitative metabarcoding and underscores the need for additional methodological approaches for quantitative insights while delivering essential conceptual insights.

Biodiversity patterns in tropical freshwater ecosystems remain unevenly understood, particularly in high-integrity regions such as Indigenous territories. In this study, we assessed taxonomic and functional beta diversity of Ephemeroptera, Plecoptera, and Trichoptera (EPT) in Amazonian streams located within the Panara Indigenous Territory, Brazil. We evaluated the relative contributions of local environmental variables, spatial processes, and landscape context to beta-diversity patterns. We disentangled the roles of replacement and richness differences across taxonomic and functional dimensions. EPT larvae were sampled in 31 streams during the dry season. Beta diversity was quantified using Sorensen-based dissimilarity indices, and functional dissimilarity was calculated from seven ecological traits using Gower distances. Taxonomic beta diversity was dominated by genus replacement and was jointly structured by local habitat variables and spatial components, indicating the combined influence of environmental filtering and dispersal limitation. In contrast, functional beta diversity was higher than taxonomic beta diversity and was predominantly structured by richness differences, with significant effects of local environmental variables but no detectable influence of spatial processes. This pattern indicates a decoupling between taxonomic and functional dimensions, suggesting high levels of functional redundancy among EPT genera across streams. Our findings demonstrate that Amazonian streams within Indigenous territories provide key systems for understanding community assembly processes under low levels of direct anthropogenic disturbance. By revealing contrasting mechanisms underlying taxonomic and functional beta diversity, this study underscores the importance of integrating multiple facets of biodiversity and reinforces the role of Indigenous territories as strategic landscapes for safeguarding Amazonian freshwater biodiversity.

BackgroundUnderstanding ecosystem dynamics is essential for assessing ecosystem health, yet remains challenging due to complex biotic and abiotic interactions. Microbial communities are valuable indicators of environmental change, but the high dimensionality of microbiome data requires advanced analytical methods. This study explores the use of topic modeling (TM), an unsupervised machine learning approach initially designed for text analysis, to analyze microbiome data from the dynamic Warnow Estuary on the southern Baltic Sea coast. ResultsWe applied TM to estuarine microbiome data and compared its performance to traditional dimensionality reduction methods, Principal Component Analysis (PCA) and Principal Coordinate Analysis (PCoA). Quantitative results indicate that TM performs comparably to conventional approaches in preserving ecological and functional information, and in certain aspects even superior. In addition, we show qualitatively that NNMF, a TM method, captures latent patterns in the data providing an interpretable perspective on the microbiome. In this exploratory framework, NNMF suggested five distinct sub-communities within the estuary that appear to follow a seasonal succession influenced by freshwater inflow. These sub-communities were associated with specific ranges of salinity and temperature and showed distinct taxonomic profiles, with shared characteristics across the estuarine system. ConclusionsOur findings suggest that TM is a useful tool for exploring complex environmental microbiome datasets, offering a complementary perspective that can provide additional ecological insights. TMs ability to highlight coherent microbial community patterns indicates its promise for supporting environmental monitoring and informing targeted ecosystem management in dynamic habitats, though further studies are needed to fully assess its applicability.

Amazon streams are increasingly threatened by land-use change, yet Indigenous Territories represent some of the most effective areas for maintaining habitat integrity and ecological processes in these systems. Understanding how local environmental conditions, landscape context, and spatial structure interact to shape biodiversity within these territories is essential for advancing conservation strategies. Here, we evaluated the relative influence of local habitat, landscape, and spatial predictors on Odonata diversity and identified species-specific ecological thresholds within an Indigenous Territory in the southern Brazilian Amazon. Adult Odonata were sampled in 31 first- to third-order forested streams in the Panara Indigenous Territory, Xingu River basin. Local habitat variables were the main drivers of Odonata community structure, indicating that local habitat integrity and physical stream characteristics strongly influence assemblage composition. In contrast, Zygoptera suborder were primarily structured by spatial predictors, suggesting stronger dispersal limitations and fine-scale spatial processes. Anisoptera suborder showed no significant community-level associations with the predictors, reflecting their broader ecological tolerance and higher dispersal capacity. Our results demonstrate that even within highly conserved Indigenous Territories, subtle environmental gradients and spatial structure shape Odonata assemblages and define ecological thresholds. By integrating community-level and species-specific approaches, this study provides robust evidence of the role of Indigenous lands in sustaining freshwater biodiversity and highlights the value of Odonata as indicators for monitoring ecological integrity in Amazonian streams.

Invasive round goby Neogobius melanostomus have advanced eastward through the state of New York and provinces of Ontario and Quebec over the past two decades and are approaching Lake Champlain, one of the largest lakes in North America. This manuscript describes international efforts to monitor round goby populations during 2021-2025 on (a) the southern approach to Lake Champlain via the Hudson River and Champlain Canal, and (b) the northern approach to Lake Champlain via the Saint Lawrence River and Richelieu River. Monitoring utilized environmental DNA (eDNA), backpack electrofishing, beach seining, benthic trawling, and viral hemorrhagic septicemia virus (VHSV) testing. In the Champlain Canal, round goby were captured as far north as the downstream side of the C1 dam (97 kilometers [km] from Lake Champlain) while eDNA detections occurred as far north as the upstream side of the C2 dam (90 km from Lake Champlain). In the Richelieu River, round goby were captured as far south as Saint-Marc-sur-Richelieu (82 km from Lake Champlain) while the southern-most eDNA detections occurred near the Canadian side of the international border (4 km from Lake Champlain). Water temperature influenced habitat usage of round goby in the Champlain Canal, with catch rates in near-shore areas declining at < 10 {degrees}C. All VHSV test results were non-detections at the mouth of the Richelieu River, while one positive and two inconclusive results occurred along the Champlain Canal. Together, these data have informed multiple mitigation measures and have implications for management of aquatic invasive species across North America.