Invasive European green crab (Carcinus maenas) predation in a Washington State estuary revealed with DNA metabarcoding.

Predation by invasive species can threaten local ecosystems and economies. The European green crab (Carcinus maenas), one of the most widespread marine invasive species, is an effective predator associated with clam and crab population declines outside of its native range. In the U.S. Pacific Northwest, green crab has recently increased in abundance and expanded its distribution, generating concern for estuarine ecosystems and associated aquaculture production. However, regionally-specific information on the trophic impacts of invasive green crab is very limited. We compared the stomach contents of green crabs collected on clam aquaculture beds versus intertidal sloughs in Willapa Bay, Washington, to provide the first in-depth description of European green crab diet at a particularly crucial time for regional management. We first identified putative prey items using DNA metabarcoding of stomach content samples. We compared diet composition across sites using prey presence/absence and an index of species-specific relative abundance. For eight prey species, we also calibrated metabarcoding data to quantitatively compare DNA abundance between prey taxa, and to describe an 'average' green crab diet at an intertidal slough versus a clam aquaculture bed. From the stomach contents of 61 green crabs, we identified 54 unique taxa belonging to nine phyla. The stomach contents of crabs collected from clam aquaculture beds were significantly different from the stomach contents of crabs collected at intertidal sloughs. Across all sites, arthropods were the most frequently detected prey, with the native hairy shore crab (Hemigrapsus oregonensis) the single most common prey item. Of the eight species calibrated with a quantitative model, two ecologically-important native species-the sand shrimp (Crangon franciscorum) and the Pacific staghorn sculpin (Leptocottus armatus)-had the highest average DNA abundance when detected in a stomach content sample. In addition to providing timely information on green crab diet, our research demonstrates the novel application of a recently developed model for more quantitative DNA metabarcoding. This represents another step in the ongoing evolution of DNA-based diet analysis towards producing the quantitative data necessary for modeling invasive species impacts.

Modeling ocean distributions and abundances of natural- and hatchery-origin Chinook salmon stocks with integrated genetic and tagging data.

Background: Considerable resources are spent to track fish movement in marine environments, often with the intent of estimating behavior, distribution, and abundance. Resulting data from these monitoring efforts, including tagging studies and genetic sampling, often can be siloed. For Pacific salmon in the Northeast Pacific Ocean, predominant data sources for fish monitoring are coded wire tags (CWTs) and genetic stock identification (GSI). Despite their complementary strengths and weaknesses in coverage and information content, the two data streams rarely have been integrated to inform Pacific salmon biology and management. Joint, or integrated, models can combine and contextualize multiple data sources in a single statistical framework to produce more robust estimates of fish populations. Methods: We introduce and fit a comprehensive joint model that integrates data from CWT recoveries and GSI sampling to inform the marine life history of Chinook salmon stocks at spatial and temporal scales relevant to ongoing fisheries management efforts. In a departure from similar models based primarily on CWT recoveries, modeled stocks in the new framework encompass both hatchery- and natural-origin fish. We specifically model the spatial distribution and marine abundance of four distinct stocks with spawning locations in California and southern Oregon, one of which is listed under the U.S. Endangered Species Act. Results: Using the joint model, we generated the most comprehensive estimates of marine distribution to date for all modeled Chinook salmon stocks, including historically data poor and low abundance stocks. Estimated marine distributions from the joint model were broadly similar to estimates from a simpler, CWT-only model but did suggest some differences in distribution in select seasons. Model output also included novel stock-, year-, and season-specific estimates of marine abundance. We observed and partially addressed several challenges in model convergence with the use of supplemental data sources and model constraints; similar difficulties are not unexpected with integrated modeling. We identify several options for improved data collection that could address issues in convergence and increase confidence in model estimates of abundance. We expect these model advances and results provide management-relevant biological insights, with the potential to inform future mixed-stock fisheries management efforts, as well as a foundation for more expansive and comprehensive analyses to follow.

Environmental DNA reveals patterns of biological invasion in an inland sea.

Non-native species have the potential to cause ecological and economic harm to coastal and estuarine ecosystems. Understanding which habitat types are most vulnerable to biological invasions, where invasions originate, and the vectors by which they arrive can help direct limited resources to prevent or mitigate ecological and socio-economic harm. Information about the occurrence of non-native species can help guide interventions at all stages of invasion, from first introduction, to naturalization and invasion. However, monitoring at relevant scales requires considerable investment of time, resources, and taxonomic expertise. Environmental DNA (eDNA) metabarcoding methods sample coastal ecosystems at broad spatial and temporal scales to augment established monitoring methods. We use COI mtDNA eDNA sampling to survey a diverse assemblage of species across distinct habitats in the Salish Sea in Washington State, USA, and classify each as non-native, native, or indeterminate in origin. The non-native species detected include both well-documented invaders and species not previously reported within the Salish Sea. We find a non-native assemblage dominated by shellfish and algae with native ranges in the temperate western Pacific, and find more-retentive estuarine habitats to be invaded at far higher levels than better-flushed rocky shores. Furthermore, we find an increase in invasion level with higher water temperatures in spring and summer across habitat types. This analysis contributes to a growing understanding of the biotic and abiotic factors that influence invasion level, and underscores the utility of eDNA surveys to monitor biological invasions and to better understand the factors that drive these invasions.

Quantifying impacts of an environmental intervention using environmental DNA.

Environmental laws around the world require some version of an environmental-impact assessment surrounding construction projects and other discrete instances of human development. Information requirements for these assessments vary by jurisdiction, but nearly all require an analysis of the biological elements of ecosystems. Amplicon-sequencing-also called metabarcoding-of environmental DNA (eDNA) has made it possible to sample and amplify the genetic material of many species present in those environments, providing a tractable, powerful, and increasingly common way of doing environmental-impact analysis for development projects. Here, we analyze an 18-month time series of water samples taken before, during, and after two culvert removals in a salmonid-bearing freshwater stream. We also sampled multiple control streams to develop a robust background expectation against which to evaluate the impact of this discrete environmental intervention in the treatment stream. We generate calibrated, quantitative metabarcoding data from amplifying the 12s MiFish mtDNA locus and complementary species-specific quantitative PCR data to yield multispecies estimates of absolute eDNA concentrations across time, creeks, and sampling stations. We then use a linear mixed effects model to reveal patterns of eDNA concentrations over time, and to estimate the effects of the culvert removal on salmonids in the treatment creek. We focus our analysis on four common salmonid species: cutthroat trout (Oncorhynchus clarkii), coho salmon (Oncorhynchus kisutch), rainbow trout (Oncorhynchus mykiss), and sockeye salmon (Oncorhynchus nerka). We find that one culvert in the treatment creek seemed to have no impact while the second culvert had a large impact on fish passage. The construction itself seemed to have only transient effects on salmonid species during the two construction events. In the context of billions of dollars of court-mandated road culvert replacements taking place in Washington State, USA, our results suggest that culvert replacement can be conducted with only minimal impact of construction to key species of management concern. Furthermore, eDNA methods can be an effective and efficient approach for monitoring hundreds of culverts to prioritize culverts that are required to be replaced. More broadly, we demonstrate a rigorous, quantitative method for environmental-impact reporting using eDNA that is widely applicable in environments worldwide.

XFEL Microcrystallography of Self-Assembling Silver n-Alkanethiolates.

New synthetic hybrid materials and their increasing complexity have placed growing demands on crystal growth for single-crystal X-ray diffraction analysis. Unfortunately, not all chemical systems are conducive to the isolation of single crystals for traditional characterization. Here, small-molecule serial femtosecond crystallography (smSFX) at atomic resolution (0.833 Å) is employed to characterize microcrystalline silver n-alkanethiolates with various alkyl chain lengths at X-ray free electron laser facilities, resolving long-standing controversies regarding the atomic connectivity and odd-even effects of layer stacking. smSFX provides high-quality crystal structures directly from the powder of the true unknowns, a capability that is particularly useful for systems having notoriously small or defective crystals. We present crystal structures of silver n-butanethiolate (C4), silver n-hexanethiolate (C6), and silver n-nonanethiolate (C9). We show that an odd-even effect originates from the orientation of the terminal methyl group and its role in packing efficiency. We also propose a secondary odd-even effect involving multiple mosaic blocks in the crystals containing even-numbered chains, identified by selected-area electron diffraction measurements. We conclude with a discussion of the merits of the synthetic preparation for the preparation of microdiffraction specimens and compare the long-range order in these crystals to that of self-assembled monolayers.

Signal and noise in metabarcoding data.

Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to thousands of species from a single sample, underpinning microbiome and environmental DNA (eDNA) methods. Deriving quantitative estimates of underlying biological communities from metabarcoding is critical for enhancing the utility of such approaches for health and conservation. Recent work has demonstrated that correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data stems from non-detections across technical PCR replicates where one replicate fails to detect a species observed in other replicates. Such non-detections are a special case of variability among technical replicates in metabarcoding data. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) suggest how non-detections may arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show with both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing-both of which we can model-but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

Toward quantitative metabarcoding.

Amplicon-sequence data from environmental DNA (eDNA) and microbiome studies provide important information for ecology, conservation, management, and health. At present, amplicon-sequencing studies-known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture-struggle to link genetic observations to the underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology, it becomes more important to develop ways to make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying polymerase chain reaction mechanism explains the observed patterns of amplicon data in a general way. By modeling the process through which amplicon-sequence data arise, rather than transforming the data post hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.

Introducing zoid: A mixture model and R package for modeling proportional data with zeros and ones in ecology.

Many ecological data sets are proportional, representing mixtures of constituent elements such as species, populations, or strains. Analyses of proportional data are challenged by categories with zero observations (zeros), all observations (ones), and overdispersion. In lieu of ad hoc data adjustments, we describe and evaluate a zero-and-one inflated Dirichlet regression model, with its corresponding R package (zoid), capable of handling observed data x $$ x $$ consisting of three possible categories: zeros, proportions, or ones. Instead of fitting the model to observations of single biological units (e.g., individual organisms) within a sample, we sum proportional contributions across units and estimate mixture proportions using one aggregated observation per sample. Optional estimation of overdispersion and covariate influences expand model applications. We evaluate model performance, as implemented in Stan, using simulations and two ecological case studies. We show that zoid successfully estimates mixture proportions using simulated data with varying sample sizes and is robust to overdispersion and covariate structure. In empirical case studies, we estimate the composition of a mixed-stock Chinook salmon (Oncorhynchus tshawytscha) fishery and analyze the stomach contents of Atlantic cod (Gadus morhua). Our implementation of the model as an R package facilitates its application to varied ecological data sets composed of proportional observations.

Environmental DNA provides quantitative estimates of Pacific hake abundance and distribution in the open ocean.

All species inevitably leave genetic traces in their environments, and the resulting environmental DNA (eDNA) reflects the species present in a given habitat. It remains unclear whether eDNA signals can provide quantitative metrics of abundance on which human livelihoods or conservation successes depend. Here, we report the results of a large eDNA ocean survey (spanning 86 000 km2 to depths of 500 m) to understand the abundance and distribution of Pacific hake (Merluccius productus), the target of the largest finfish fishery along the west coast of the USA. We sampled eDNA in parallel with a traditional acoustic-trawl survey to assess the value of eDNA surveys at a scale relevant to fisheries management. Despite local differences, the two methods yield comparable information about the broad-scale spatial distribution and abundance. Furthermore, we find depth and spatial patterns of eDNA closely correspond to acoustic-trawl estimates for hake. We demonstrate the power and efficacy of eDNA sampling for estimating abundance and distribution and move the analysis eDNA data beyond sample-to-sample comparisons to management relevant scales. We posit that eDNA methods are capable of providing general quantitative applications that will prove especially valuable in data- or resource-limited contexts.

Tracking an invasion front with environmental DNA.

Data from environmental DNA (eDNA) may revolutionize environmental monitoring and management, providing increased detection sensitivity at reduced cost and survey effort. However, eDNA data are rarely used in decision-making contexts, mainly due to uncertainty around (1) data interpretation and (2) whether and how molecular tools dovetail with existing management efforts. We address these challenges by jointly modeling eDNA detection via qPCR and traditional trap data to estimate the density of invasive European green crab (Carcinus maenas), a species for which, historically, baited traps have been used for both detection and control. Our analytical framework simultaneously quantifies uncertainty in both detection methods and provides a robust way of integrating different data streams into management processes. Moreover, the joint model makes clear the marginal information benefit of adding eDNA (or any other) additional data type to an existing monitoring program, offering a path to optimizing sampling efforts for species of management interest. Here, we document green crab eDNA beyond the previously known invasion front and find that the value of eDNA data dramatically increases with low population densities and low traditional sampling effort, as is often the case at leading-edge locations. We also highlight the detection limits of the molecular assay used in this study, as well as scenarios under which eDNA sampling is unlikely to improve existing management efforts.

Chemical crystallography by serial femtosecond X-ray diffraction.

Inorganic-organic hybrid materials represent a large share of newly reported structures, owing to their simple synthetic routes and customizable properties1. This proliferation has led to a characterization bottleneck: many hybrid materials are obligate microcrystals with low symmetry and severe radiation sensitivity, interfering with the standard techniques of single-crystal X-ray diffraction2,3 and electron microdiffraction4-11. Here we demonstrate small-molecule serial femtosecond X-ray crystallography (smSFX) for the determination of material crystal structures from microcrystals. We subjected microcrystalline suspensions to X-ray free-electron laser radiation12,13 and obtained thousands of randomly oriented diffraction patterns. We determined unit cells by aggregating spot-finding results into high-resolution powder diffractograms. After indexing the sparse serial patterns by a graph theory approach14, the resulting datasets can be solved and refined using standard tools for single-crystal diffraction data15-17. We describe the ab initio structure solutions of mithrene (AgSePh)18-20, thiorene (AgSPh) and tethrene (AgTePh), of which the latter two were previously unknown structures. In thiorene, we identify a geometric change in the silver-silver bonding network that is linked to its divergent optoelectronic properties20. We demonstrate that smSFX can be applied as a general technique for structure determination of beam-sensitive microcrystalline materials at near-ambient temperature and pressure.

Investigation of Nucleation and Growth at a Liquid-Liquid Interface by Solvent Exchange and Synchrotron Small-Angle X-Ray Scattering.

Hybrid nanomaterials possess complex architectures that are driven by a self-assembly process between an inorganic element and an organic ligand. The properties of these materials can often be tuned by organic ligand variation, or by swapping the inorganic element. This enables the flexible fabrication of tailored hybrid materials with a rich variety of properties for technological applications. Liquid-liquid interfaces are useful for synthesizing these compounds as precursors can be segregated and allowed to interact only at the interface. Although procedurally straightforward, this is a complex reaction in an environment that is not easy to probe. Here, we explore the interfacial crystallization of mithrene, a supramolecular multi-quantum well. This material sandwiches a well-defined silver-chalcogenide layer between layers of organic ligands. Controlling mithrene crystal size and morphology to be useful for applications requires understanding details of its crystal growth, but the specific mechanism for this reaction remain only lightly investigated. We performed a study of mithrene crystallization at an oil-water interfaces to elucidate how the interfacial free energy affects nucleation and growth. We exchanged the oil solvent on the basis of solvent viscosity and surface tension, modifying the dynamic contact angle and interfacial free energy. We isolated and characterized the reaction byproducts via scanning electron microscopy (SEM). We also developed a high-throughput small angle X-ray scattering (SAXS) technique to measure crystallization at short reaction timescales (minutes). Our results showed that modifying interfacial surface energy affects both the reaction kinetics and product size homogeneity and yield. Our SAXS measurements reveal the onset of crystallinity after only 15 min. These results provide a template for exploring directed synthesis of complex materials via experimental methods.

Environmental DNA metabarcoding reveals winners and losers of global change in coastal waters.

Studies of the ecological effects of global change often focus on one or a few species at a time. Consequently, we know relatively little about the changes underway at real-world scales of biological communities, which typically have hundreds or thousands of interacting species. Here, we use COI mtDNA amplicons from monthly samples of environmental DNA to survey 221 planktonic taxa along a gradient of temperature, salinity, dissolved oxygen and carbonate chemistry in nearshore marine habitat. The result is a high-resolution picture of changes in ecological communities using a technique replicable across a wide variety of ecosystems. We estimate community-level differences associated with time, space and environmental variables, and use these results to forecast near-term community changes due to warming and ocean acidification. We find distinct communities in warmer and more acidified conditions, with overall reduced richness in diatom assemblages and increased richness in dinoflagellates. Individual taxa finding more suitable habitat in near-future waters are more taxonomically varied and include the ubiquitous coccolithophore Emiliania huxleyi and the harmful dinoflagellate Alexandrium sp. These results suggest foundational changes for nearshore food webs under near-future conditions.

A halo of reduced dinoflagellate abundances in and around eelgrass beds.

Seagrass beds provide a variety of ecosystem services, both within and outside the bounds of the habitat itself. Here we use environmental DNA (eDNA) amplicons to analyze a broad cross-section of taxa from ecological communities in and immediately surrounding eelgrass (Zostera marina). Sampling seawater along transects extending alongshore outward from eelgrass beds, we demonstrate that eDNA provides meter-scale resolution of communities in the field. We evaluate eDNA abundance indices for 13 major phylogenetic groups of marine and estuarine taxa along these transects, finding highly local changes linked with proximity to Z. marina for a diverse group of dinoflagellates, and for no other group of taxa. Eelgrass habitat is consistently associated with dramatic reductions in dinoflagellate abundance both within the contiguous beds and for at least 15 m outside, relative to nearby sites without eelgrass. These results are consistent with the hypothesis that eelgrass-associated communities have allelopathic effects on dinoflagellates, and that these effects can extend in a halo beyond the bounds of the contiguous beds. Because many dinoflagellates are capable of forming harmful algal blooms (HABs) toxic to humans and other animal species, the apparent salutary effect of eelgrass habitat on neighboring waters has important implications for public health as well as shellfish aquaculture and harvesting.

Environmental DNA reveals seasonal shifts and potential interactions in a marine community.

Environmental DNA (eDNA) analysis allows the simultaneous examination of organisms across multiple trophic levels and domains of life, providing critical information about the complex biotic interactions related to ecosystem change. Here we used multilocus amplicon sequencing of eDNA to survey biodiversity from an eighteen-month (2015-2016) time-series of seawater samples from Monterey Bay, California. The resulting dataset encompasses 663 taxonomic groups (at Family or higher taxonomic rank) ranging from microorganisms to mammals. We inferred changes in the composition of communities, revealing putative interactions among taxa and identifying correlations between these communities and environmental properties over time. Community network analysis provided evidence of expected predator-prey relationships, trophic linkages, and seasonal shifts across all domains of life. We conclude that eDNA-based analyses can provide detailed information about marine ecosystem dynamics and identify sensitive biological indicators that can suggest ecosystem changes and inform conservation strategies.

Understanding PCR Processes to Draw Meaningful Conclusions from Environmental DNA Studies.

As environmental DNA (eDNA) studies have grown in popularity for use in ecological applications, it has become clear that their results differ in significant ways from those of traditional, non-PCR-based surveys. In general, eDNA studies that rely on amplicon sequencing may detect hundreds of species present in a sampled environment, but the resulting species composition can be idiosyncratic, reflecting species' true biomass abundances poorly or not at all. Here, we use a set of simulations to develop a mechanistic understanding of the processes leading to the kinds of results common in mixed-template PCR-based (metabarcoding) studies. In particular, we focus on the effects of PCR cycle number and primer amplification efficiency on the results of diversity metrics in sequencing studies. We then show that proportional indices of amplicon reads capture trends in taxon biomass with high accuracy, particularly where amplification efficiency is high (median correlation up to 0.97). Our results explain much of the observed behavior of PCR-based studies, and lead to recommendations for best practices in the field.

Low-load resistance exercise during inactivity is associated with greater fibre area and satellite cell expression in older skeletal muscle.

BACKGROUND: Age-related sarcopenia is accelerated by physical inactivity. Low-load resistance exercise (LLRE) counters inactivity-induced muscle atrophy in older adults, but changes in muscle fibre morphology are unstudied. We aimed to determine the impact of LLRE during short-term inactivity (step-reduction) on muscle fibre size and capillarity as well as satellite cell (SC) content in older skeletal muscle. METHODS: Fourteen older (~71 years) male adults underwent 14 days of step reduction (<1500 steps/day) while performing six sessions of LLRE (~30% maximal strength) with one leg (SR + EX) while the contralateral leg served as an untrained control (SR). Seven healthy ambulatory age-matched male adults (~69 years) served as a comparator group (COM). Muscle biopsies were taken from the vastus lateralis after 14 days, and immunohistochemical analysis was performed to determine muscle fibre cross-sectional area (CSA), myonuclear content, SC content (PAX7+ cells), and total (C:F) and fibre type-specific (C:Fi) capillary-to-fibre ratios. RESULTS: Type I and II fibre CSA was greater in SR + EX compared with SR. Whereas there were no differences across fibre types between SR + EX and CON, type II fibre CSA was significantly lower in SR compared with COM. Type II myonuclear domain was greater in SR + EX compared with COM and SR. Pax7+ cells associated with type I and II fibres were lower in SR compared with SR + EX. Type II PAX7+ cells were also lower in SR compared with COM with a similar trend for type I fibres. There were trends for a lower C:Fi in SR compared with SR + EX for both fibre types with no differences for each compared with COM. CONCLUSIONS: Minimal LLRE during a period of decreased physical activity is associated with greater muscle fibre CSA, SC content, and capillarization. These results support the use of LLRE as an effective countermeasure to inactivity-induced alterations in muscle morphology with age.

Quantifying the effectiveness of shoreline armoring removal on coastal biota of Puget Sound.

Shoreline armoring is prevalent around the world with unprecedented human population growth and urbanization along coastal habitats. Armoring structures, such as riprap and bulkheads, that are built to prevent beach erosion and protect coastal infrastructure from storms and flooding can cause deterioration of habitats for migratory fish species, disrupt aquatic-terrestrial connectivity, and reduce overall coastal ecosystem health. Relative to armored shorelines, natural shorelines retain valuable habitats for macroinvertebrates and other coastal biota. One question is whether the impacts of armoring are reversible, allowing restoration via armoring removal and related actions of sediment nourishment and replanting of native riparian vegetation. Armoring removal is targeted as a viable option for restoring some habitat functions, but few assessments of coastal biota response exist. Here, we use opportunistic sampling of pre- and post-restoration data for five biotic measures (wrack % cover, saltmarsh % cover, number of logs, and macroinvertebrate abundance and richness) from a set of six restored sites in Puget Sound, WA, USA. This broad suite of ecosystem metrics responded strongly and positively to armor removal, and these results were evident after less than one year. Restoration responses remained positive and statistically significant across different shoreline elevations and temporal trajectories. This analysis shows that removing shoreline armoring is effective for restoration projects aimed at improving the health and productivity of coastal ecosystems, and these results may be widely applicable.

The effect of tides on nearshore environmental DNA.

We can recover genetic information from organisms of all kinds using environmental sampling. In recent years, sequencing this environmental DNA (eDNA) has become a tractable means of surveying many species using water, air, or soil samples. The technique is beginning to become a core tool for ecologists, environmental scientists, and biologists of many kinds, but the temporal resolution of eDNA sampling is often unclear, limiting the ecological interpretations of the resulting datasets. Here, in a temporally and spatially replicated field study using ca. 313 bp of eukaryotic COI mtDNA as a marker, we find that nearshore organismal communities are largely consistent across tides. Our findings suggest that nearshore eDNA from both benthic and planktonic taxa tends to be endogenous to the site and water mass sampled, rather than changing with each tidal cycle. However, where physiochemical water mass characteristics change, we find that the relative contributions of a broad range of organisms to eDNA communities shift in concert.