Environmental DNA

DNA based methods offer a rapid and cost-effective way for detecting species occurrence and monitoring biodiversity; among them bulk DNA metabarcoding is well-established, and recently developed environmental DNA (eDNA)-based methods offer a non-destructive alternative. With a goal to develop suitable methods for assessing insect biodiversity in ecosystems for which DNA reference libraries are not well developed and incomplete, such as remote islands, we compared established bulk DNA metabarcoding methods with eDNA across three replicated terrestrial ecosystem types (limestone forest, degraded forest, and grassland) in Guam. Using two mitochondrial COI primer pairs, we performed bulk DNA metabarcoding of standard entomological collection methods (malaise traps, pan traps, vegetation beating), and compared the assessment of biodiversity with that from different eDNA sources (flowers, spider webs, leaves, tree trunks). In our samples, eDNA and bulk DNA metabarcoding both detected a large proportion of overall taxa (OTUs, 86.6% and 60.3%, respectively). Although DNA metabarcoding detected significantly more taxa, eDNA proved to be a reasonable non-destructive alternative. As expected, because of limitations in existing reference databases for remote habitats, species-level identification was achieved for only a few OTUs. Overall, the sampling approach was the dominant driver of arthropod diversity, explaining [~]17% of the observed variation, while habitat type accounted for [~]4%. Thus, each sampling approach captured some unique diversity signals and contributed to the complementary effect of maximizing detection. For rapid insect biodiversity surveys of terrestrial arthropods, we recommend an integrated metabarcoding approach, and in sensitive habitats where insect capture is undesirable, eDNA offers a powerful alternative to monitor diversity and community change.

Robust methods to monitor species distributions are vital to ensuring successful conservation strategies, particularly in the case of conservation translocations. Environmental DNA (eDNA) from water samples is a cost-effective method to monitor species distributions without physical capture or disturbance. However, eDNA is vulnerable to long-distance transport depending on the hydrological and environmental characteristics which can lead to spatially false positives and ultimately inaccurate species distributions. Recently, the development of particle transport models has allowed researchers to integrate hydrological and environmental variables to predict how far eDNA will transport from a source point. Here, eDNA samples (n=218) were collected and quantified using digital PCR (dPCR) to study monthly changes in Eurasian beaver (Castor fiber) eDNA concentrations downstream of an enclosure which contained 4 - 5 beavers located in Scotland. The shortest eDNA transport distances (< 2 km) were observed in the summer which correlated with the lowest flows and highest temperatures. In contrast, throughout the winter eDNA was consistently detected up to 5.8 km downstream correlating with the highest discharge and lowest temperature. The eDNA transport model reliably reproduced the decrease in eDNA concentrations downstream of the enclosure, however there were challenges surrounding stream-specific decay rates following a confluence. To study localised species distributions, samples should be collected during summer low flow conditions. Conversely, to maximise species detections sampling should be conducted in winter which had the longest eDNA transport and highest detectability.

Despite the increasing use of different sequencing techniques in ecological applications, the mechanistic factors driving their quantitative performance remain poorly understood. Here, we assembled two types of mock communities: one using DNA extracted from pooled marine nematodes and one using the individual nematodes as input. The composition and relative abundances within those communities were then characterized using 18S and 28S rRNA metabarcoding and shotgun sequencing. A qualitatively similar {beta}-diversity was revealed by both methods. Shotgun read proportions generally tracked input DNA across well-represented genera, whereas metabarcoding performance depended on primer choice. Under the analytical frameworks applied, shotgun sequencing provided more consistent estimates of individual counts for nematode genera. However, although shotgun sequencing provided a more consistent estimation of taxon abundance than metabarcoding, particularly for nematodes represented by a high DNA input, neither method was able to accurately quantify nematodes with low input DNA or a small body size. The correlation analyses revealed that relative read abundances from both sequencing approaches were more strongly associated with DNA quantity than with individual counts. This suggests that variation in starting material can influence quantitative outcomes, and that differences in nematode body size across genera may significantly affect community composition assessment. Our findings show that metabarcoding and shotgun sequencing are equally effective in detecting structural changes at the community level as well as abundance shifts within individual taxa, but shotgun sequencing is more reliable for across-taxon comparisons. We provide a comprehensive assessment of how input material, primer choice, and sequencing approach influence the accuracy of nematode abundance quantification. Our study advances quantitative practices in the application of these methods for nematode-based bioindication and, more broadly environmental DNA biomonitoring.

Conservation planning for rare, threatened, and endangered species requires basic information for distribution and abundance. Often this information is lacking due to the nature of traditional survey methods which can be time and labor intensive and thus costly. Environmental DNA (eDNA) metabarcoding offers a promising approach for monitoring freshwater mussel assemblages, a taxonomic group that is both highly imperiled and difficult to survey using traditional methods. We evaluated the performance of eDNA metabarcoding across 30 km of Fish Creek, in Ohio and Indiana, U.S.. We compared results to visual surveys conducted at the same sites. eDNA detected 25 mussel species, including four species not observed alive visually, while visual surveys detected 22 live species. Both methods confirmed the presence of three federally protected species, and eDNA uniquely detected Simpsonaias ambigua, a species rarely encountered in conventional surveys. Incorporating detection repeatability improved congruence between methods: high-repeatability detections strongly aligned with visual presence, whereas moderate and low repeatability detections likely represented reach-scale occupancy. Overall, eDNA metabarcoding offers an efficient and sensitive tool for assessing mussel assemblages and can substantially enhance monitoring programs when integrated with species ecology and hydrological context.

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.

Environmental DNA (eDNA) provides a powerful non-invasive tool for monitoring freshwater mussel assemblages, yet detection probabilities can be influenced by reproductive behaviors, seasonal vertical migration, and hydrological conditions. This study assessed eDNA detection from April through October across two diverse mussel beds in Ohio, encompassing species with both tachytictic (short-term brooders) and bradytictic (long-term brooders) reproductive strategies. Mussel DNA was consistently detected across seasons, with detection patterns generally aligning with species observed through a visual tactile survey. Overall, the eDNA sequence abundance was positively correlated with tactile mussel counts, however congruence between the two surveys was strongest during low discharge and when the surveys occurred in close temporal proximity to one another. This study finds that eDNA sampling for freshwater mussels performs adequately within the currently prescribed survey window for visual surveys. However, seasonal factors such as endobenthic burial behavior and high discharge events may have reduced detection efficiency, particularly in Killbuck Creek, where species richness was lowest during periods of high flow in early spring. Therefore, decisions made regarding the timing of eDNA surveys should consider local environmental conditions (e.g., temperature and flow) to achieve optimal results.

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.

Tropical estuaries within the Brazilian Atlantic Forest are biodiversity hotspots facing escalating anthropogenic pressures, yet their ichthyofaunal assemblages remain incompletely documented. We evaluated the combined use of environmental DNA (eDNA) and environmental RNA (eRNA) metabarcoding to characterize fish communities in two estuaries with contrasting levels of urbanization (the Juqueriquere and Escuro rivers) on the northern coast of Sao Paulo, Brazil. Targeting the mitochondrial 12S rRNA (MiFish) fragment, we detected a diverse vertebrate assemblage totaling 93 species. eDNA identified 32 fish species across both systems, while eRNA detected 22 species in the preserved estuary, providing robust signals of metabolically active assemblages. The less impacted estuary exhibited significantly higher diversity indices and a more heterogeneous taxonomic composition. In contrast, the urbanized system displayed clear molecular signatures of anthropogenic influence, including the presence of invasive species (Oreochromis niloticus, O. aureus, and Clarias gariepinus) and domestic animals. This study constitutes the first application of fish eRNA metabarcoding in Brazil and demonstrates that integrating eDNA and eRNA refines ecological interpretation by coupling biodiversity detection with improved inference about contemporary community composition. Our findings highlight the potential of multi-molecule metabarcoding for routine, non-invasive biodiversity assessment in megadiverse and conservation-priority coastal ecosystems.

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

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

Unionid freshwater mussels exhibit a unique form of mitochondrial inheritance, termed doubly uniparental inheritance, in which a maternal and a paternal mitotype is transmitted uniparentally. The exclusive presence of a male mitotype in gonadal tissue and sperm cells suggests that environmental DNA (eDNA) could serve as a non-invasive method for monitoring freshwater mussel reproduction. Yet, the dynamics of male mitotype detection within the environment remain poorly understood. This study analyzed seasonal eDNA samples from two diverse mussel beds, detecting 24 mitochondrial operational taxonomic units (MOTUs) associated with the male mitotype. Peaks in male mitotype signal for mussels identifiable to the species level generally aligned with expected spawning periods based on female gravidity records (e.g., Pyganodon grandis, Lasmigona costata, Ortmaniana ligamentina). Additionally, male mitotype detection was often sporadic compared to the consistently detected female mitotype, indicating that male signals may be tied to behavioral or reproductive events rather than continuous shedding. While elevated male signals may reflect spawning, alternative sources such as tissue decay, mitotype leakage, glochidia release, or post-spawning gamete clearance complicate interpretation. A male-to-female mitotype ratio is proposed as a more reliable proxy for identifying sperm release events, given the high concentration of male mitotypes that occurs within spermatozeugmata. Limitations in male mitotype reference databases hindered species-level resolution for many MOTUs, underscoring the need for expanded genomic resources. Overall, this work demonstrates that male mitotype eDNA likely provides valuable insights into mussel reproductive ecology, while emphasizing the importance of long-term monitoring and integrated gametogenesis studies to refine its application in conservation.

Simpsonaias ambigua (Salamander Mussel), is a small and thin shelled freshwater mussel often found in difficult to survey habitats, such as beneath slab stones, in the crevices of rock walls, or buried within roots of emergent vegetation and in undercuts of banks. The use of environmental DNA (eDNA - genetic material released from urine, waste, mucus, or sloughed cells) sampling may improve detection and assessment of presence / absence for this rare mussel in comparison to visual tactile techniques. This study completed side by side comparisons of traditional mussel searches and eDNA for a direct assessment of mussel detection efficiencies. Surveying was conducted in several waterbodies of different habitat characteristics with varying abundances of S. ambigua. Additionally, a broad assessment of S. ambigua presence was conducted throughout the proposed critical habitat reach of the Blanchard River in northwest Ohio, to assess if the species remained extant. All eDNA samples were also assessed for the presence of Necturus maculosus (Mudpuppy), the obligate host species for S. ambigua. The eDNA sampling successfully detected S. ambigua from multiple sites and watersheds where it was found with visual surveys. In some cases, eDNA detections occurred in locations where over 16 hours of search yielded only a single individual or fresh dead shells, supporting the sensitivity of eDNA for detection of rare species. Furthermore, probability of detection analysis suggests eDNA sampling can provide high detection efficiency with relatively low effort in comparison to visual searches. The development and validation of an eDNA protocol for the simultaneous detection of S. ambigua and its host salamander increases survey efficiency, reduces field costs, and can support future conservation efforts for listing drainages of extant populations and monitoring conservation goals.

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.

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.

Freshwater biofilms host diverse microbial eukaryotic communities that are central to ecosystem functioning and serve as key indicators of water quality. Molecular biomonitoring approaches based on environmental DNA (eDNA) sequencing are increasingly used to characterise these communities, offering scalable alternatives to traditional microscopy-based assessments. Understanding how DNA sequencing methods influence the observed community composition and diversity is essential for ensuring accurate ecological interpretation. Here, we compared short-read Illumina and long-read Pacific Biosciences sequencing of the 18S rRNA gene, alongside a trimmed long-read dataset (restricted to the Illumina-primed region), to evaluate how read length and sequencing platform affect community profiling in river biofilms from seven English rivers sampled across three timepoints. Distinct community patterns were observed between the sequencing approaches, with PERMANOVA revealing significant differences in beta diversity (p = 0.001) and modest effect sizes (R2 = 3.8-8.3%). While the long and trimmed datasets produced nearly identical community structures, both diverged strongly from the short-read data, suggesting that short-read sequencing captures a systematically different subset of taxa than long-read sequencing. Long-read sequencing significantly improved taxonomic resolution of the 18S rRNA gene, particularly at the genus and species levels, enabling detection of lineages that were unresolvable in short-read data. However, comparisons of paired long- and trimmed-read ASVs indicated that trimming can increase taxonomic mismatches at finer ranks, likely due to reduced sequence length rather than sequencing platform bias. Collectively, our results demonstrate that sequencing strategy significantly influences inferred community composition and taxonomic precision. Long-read sequencing provides a more robust representation of community diversity, whereas trimmed analyses reveal how shorter amplicons may contribute to misidentification. These findings emphasise the importance of considering read length when interpreting eDNA-based assessments using the 18S rRNA gene and support the adoption of long-read sequencing for high-resolution biomonitoring applications.

Vascular plants are a major component of terrestrial diversity, yet they are overrepresented among the worlds threatened species. To effectively manage this biodiversity crisis, data with high spatiotemporal resolution are crucial, yet often lacking for plants. Environmental DNA analysis (eDNA) is capable of rapid detection of biodiversity by metabarcoding the collection of DNA molecules retrieved from environmental samples such as soil cores. The technology may soon support the generation of broad-scale longitudinal plant community data, yet much methodological work on sampling strategies and analytical choices remains if soil-based eDNA is to become a reliable tool for monitoring terrestrial plant communities. Therefore, this dual purpose study in seven Swedish semi-natural grasslands investigated if and when eDNA-generated community data can be used as a stand-alone information source 1) to inform on the presence of a rare, small-statured grassland specialist (Gentianella campestris) and 2) to simultaneously infer community compositional change. We demonstrate eDNA to be an effective means of finding a rare species in a highly taxonomically diverse habitat, uncovering G. campestris DNA in 31% of the core samples. Evidence suggests the eDNA signal reflects recent spatio-temporal population dynamics at fine spatial scales. Although the entire plant community was not uncovered, molecular community data proved a representative subset, effectively capturing changes in community diversity and composition at plot sizes commonly used for plant surveys. Choices surrounding typical RRA-filtering had significant bearing on eDNAs discriminating power: filtering may overly conservatively remove true observations of a rare species, while filtering highly localized plot noise led to more robust patterns emerging in species richness and plant composition turn-over. Given careful alignment of study goals and sampling strategies, soil-based eDNA may already provide a stand-alone tool for generating reliable, scalable and observer-independent longitudinal data for unveiling and monitoring changes in plant diversity in terrestrial habitats.

Environmental DNA (eDNA) metabarcoding is a key tool in biodiversity monitoring due to its high-throughput, non-destructive nature. While short-read (SR) sequencing platforms such as Illumina Miseq have been routinely used in environmental monitoring, their limited read lengths (less than 600 bp) constrain the depth of taxonomic assignment, particularly for complex microbial eukaryotes like protists. Conversely, long-read (LR) sequencing technologies like Oxford Nanopore Technologies (ONT) offer promising alternatives but remain underutilized for studying protist communities. We conducted a comparative study of SR versus LR metabarcoding of protist communities along a coastal-offshore gradient in the Belgian part of the North Sea. Using amplicons targeting the V4 region (SR; 577 bp) and the V4-V5 region (LR; 745 bp) of the 18S rRNA gene, we compared diversity patterns, taxonomic assignment, and community composition between approaches. We observed general congruence in community composition at higher taxonomic levels, but under the applied workflows, LR metabarcoding yielded a greater depth of taxonomic annotation at lower taxonomic ranks. Notably, dinoflagellates were less overrepresented in LR data, and a unique detection of potential nuisance taxa (e.g., Bellerochea), and ecologically important genera such as haptophytes (e.g., Gephyrocapsa) was achieved. These results highlight the potential of LR metabarcoding to complement SR approaches by providing increased taxonomic annotation depth and ecological insights. Although both methods targeted only partial regions of the 18S rRNA gene, LR metabarcoding yielded a greater depth of taxonomic assignment under the applied workflows. As next-generation sequencing technologies continue to evolve, our research provides valuable insights for selecting optimal strategies in routine plankton monitoring and biodiversity assessment programs.

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.

Foraminiferal environmental DNA (eDNA) assemblages have recently emerged as a robust and complementary proxy for relative sea level (RSL) reconstruction. However, unlike traditional morphological methods, eDNA assemblages are influenced by diverse DNA sources, including propagules and juveniles, whose effects on RSL reconstruction remain poorly understood. To assess how foraminiferal eDNA from different life stages vary in taxa composition and impact RSL reconstruction, we analyzed foraminiferal eDNA from bulk, 500-63 m and <63 m size fraction sediments from mangrove and mudflat environments in subtropical Hong Kong. The eDNA assemblages in size-fractioned sediments displayed distinct patterns from those in bulk sediment eDNA across different environments. The propagule and juvenile-derived eDNA <63 m fraction exhibited a similar community structure to bulk eDNA in mudflat environments but diverged in mangrove environments, indicating a greater contribution of propagule and juvenile eDNA to the total eDNA pool in the mudflat environment. We applied Bayesian transfer function modeling to estimate the elevation of samples using different size fractions. eDNA assemblages from the <63 m fraction systematically underpredicted elevation in mangrove environments, while elevations inferred from the 500-63 m fraction and bulk sediment eDNA were accurate. Conversely, all eDNA assemblages in the mudflat-mangrove transitional zone led to the overprediction of RSL. These findings confirm the reliability of bulk sediment eDNA for RSL reconstruction in mangrove environments, while highlighting the need for caution when reconstructing RSL in transitional zones.

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.