Animals, protists and bacteria share marine biogeographic patterns

Community organization and network complexity and stability: contrasting strategies of prokaryotic versus eukaryotic microbiomes in the Bohai Sea and Yellow Sea

Unraveling the effects of spatial gradients on microbiome assembly and association is a challenging topic that remains understudied in the coastal ecosystem. Here, we aimed to investigate the effects of spatial variation on the network complexity and stability of plankton microbiomes in the Bohai Sea and Yellow Sea. These seas serve as spawning and nursery grounds for economically important fisheries valued at billions of dollars annually. Environmental heterogeneity structures microbial communities into distinct spatial patterns, leading to complex direct/indirect relationships and broader ecological niches of bacterioplankton compared to microeukaryotic communities. Interestingly, salinity gradients positively influenced the richness of rare subgroups of bacterioplankton, while the rare microeukaryotic subgroups showed an opposite trend. Abundant subgroups of prokaryotic/eukaryotic microbiomes exhibited greater environmental niche breadth and lower phylogenetic distance compared to the rare subgroups. Stochastic processes contributed greatly to microbiome dynamics, and deterministic processes governed the bacterioplankton organization with a lower phylogenetic turnover rate. Compared to microeukaryotes, bacterioplankton exhibit higher network modularity, complexity, and robustness and lower fragmentation, and vulnerability. These observations offer vital insights into the anti-interference ability and resistance of plankton microbiomes in response to environmental gradients in terms of organization and survival strategy as well as their adaptability to environmental disturbances.IMPORTANCEAn in-depth understanding of community organization and stability of coastal microbiomes is crucial to determining the sustainability of marine ecosystems, such as the Bohai Sea and Yellow Sea. Distinct responses between prokaryotic and eukaryotic microbiomes to spatial heterogeneity were observed in terms of geographical distribution, phylogenetic distance, niche breadth, and community assembly process. Environmental variations are significantly correlated with the dynamics of rare eukaryotic plankton subcommunities compared to prokaryotic plankton subcommunities. Deterministic processes shaped prokaryotic plankton community organization with a lower phylogenic turnover rate. Rare subgroups had noticeably higher phylogenetic distance and lower niche breadth than the corresponding abundant subgroups. Prokaryotic microbiomes had higher molecular network complexity and stability compared to microeukaryotes. Results presented here show how environmental gradients alter both the geographical characteristics of the microbial organization in coastal seas and also their co-occurrence network complexity and stability and thus have critical implications for nutrient and energy cycling.

Biodiversity of multi-trophic biological communities within riverine sediments impacted by PAHs contamination and land use changes

River ecosystems currently face a significant threat of degradation and loss of biodiversity resulting from continuous emissions of persistent organic pollutants and human activities. In this study, multi-trophic communities were assessed using DNA metabarcoding in a relatively stable riverine sediment compartment to investigate the biodiversity dynamics in the Beiluo River, followed by an evaluation of their response to polycyclic aromatic hydrocarbons (PAHs) and land use changes. A total of 48 bacterial phyla, 4 fungal phyla, 4 protist phyla, 9 algal phyla, 31 metazoan phyla, and 12 orders of fish were identified. The total concentration of PAHs in the Beiluo River sediments ranged from 25.95 to 1141.35 ng/g, with low molecular weight PAHs constituting the highest proportion (68.67%), followed by medium (22.19%) and high (9.14%) molecular weight PAHs. Notably, in contrast to lower trophic level aquatic communities such as bacteria, algae, and metazoans, PAHs exhibited a significant inhibitory effect on fish. Furthermore, the diversity of aquatic communities displayed obvious heterogeneity across distinct land use groups. A high proportion of cultivated land reduced the biodiversity of fish communities but increased that of metazoans. Conversely, an elevated proportion of built-up land reduced metazoan biodiversity, while simultaneously enhancing that of fungi and bacteria. Generally, land use changes exert both indirect and direct effects on aquatic communities. The direct effects primarily influence the abundance of aquatic communities rather than their diversity. Nevertheless, PAHs pollution may have limited potential to disrupt community structures through complex species interactions, as the hub species identified in the co-occurrence network did not align with those significantly affected by PAHs. This study indicates the potential of PAHs and land use changes to cause biodiversity losses. However, it also highlights the possibility of mitigating these negative effects in riverine sediments through optimal land use management and the promotion of enhanced species interactions.

Distance-decay equations of antibiotic resistance genes across freshwater reservoirs

Distance-decay (DD) equations can discern the biogeographical pattern of organisms and genes in a better way with advanced statistical methods. Here, we developed a data Compilation, Arrangement, and Statistics framework to advance quantile regression (QR) into the generation of DD equations for antibiotic resistance genes (ARGs) across various spatial scales using freshwater reservoirs as an illustration. We found that QR is superior at explaining dissemination potential of ARGs to the traditionally used least squares regression (LSR). This is because our model is based on the 'law of limiting factors', which reduces influence of unmeasured factors that reduce the efficacy of the LSR method. DD equations generated from the 99th QR model for ARGs were 'Sall = 90.03e-0.01Dall' in water and 'Sall = 92.31e-0.011Dall' in sediment. The 99th QR model was less impacted by uneven sample sizes, resulting in a better quantification of ARGs dissemination. Within an individual reservoir, the 99th QR model demonstrated that there is no dispersal limitation of ARGs at this smaller spatial scale. The QR method not only allows for construction of robust DD equations that better display dissemination of organisms and genes across ecosystems, but also provides new insights into the biogeography exhibited by key parameters, as well as the interactions between organisms and environment.

An integrated spatio-temporal view of riverine biodiversity using environmental DNA metabarcoding

Anthropogenically forced changes in global freshwater biodiversity demand more efficient monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the appropriate spatio-temporal resolution of robust biodiversity assessment remains ambiguous. Here, using intensive, spatio-temporal eDNA sampling across space (five rivers in Europe and North America, with an upper range of 20-35 km between samples), time (19 timepoints between 2017 and 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers using eDNA. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of environmental conditions were taxon-specific, reflecting habitat filtering of communities rather than effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatio-temporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river community ecology during a time of environmental change.

Large-scale environmental signals in seagrass blue carbon stocks are hidden by high variability at local scales

Increasing focus on nature-based climate change mitigation and adaptation strategies has led to the recognition of seagrasses as globally significant organic carbon (Corg) stocks. However, estimates of carbon stocks have been generally confined to a few regions, with few African studies represented in global datasets. In addition, the extent to which biogeographical and environmental variation shape carbon stocks in marine vegetated environments remains uncertain. For South Africa, Zostera capensis is the dominant seagrass species with limited mapping and quantification of its Corg stocks. Here, we measured Z. capensis Corg stocks at six South African estuaries spanning ∼1800 km of the cool-temperate to subtropical marine environmental gradient. Targeting the intertidal zone of the upper and lower estuary reaches, we collected Z. capensis sediments to a depth of 50 cm and measured the Corg, with the median Corg stock estimated at 24.11 Mg C ha-1 (40.4 ± 53.02; mean ± SD). While this is lower than the global average, these data demonstrate that Z. capensis ecosystems are important contributors to blue carbon stocks in the region. Measured Corg stocks showed significant differences between sampling sites for estuaries; however, we did not detect significant differences between estuaries due to high intra-estuarine Corg variability. Examination of biogeographical regions, terrestrial and marine environmental variables as drivers of Corg variability revealed that annual mean sea surface temperature may explain variation in Corg stocks. Furthermore, we found evidence of signals of biogeographical regions and precipitation driving some of the variability in Corg stocks; however, this requires further investigation. Overall, our estimates for Z. capensis add to ongoing national and global efforts to quantify seagrass Corg stocks across environmental and biogeographic gradients to better determine their contributions as nature-based solutions to climate change.

Nuclear environmental DNA resolves fine-scale population genetic structure in an aquatic habitat

There is considerable potential for nuclear genomic material in environmental DNA (eDNA) to inform us of population genetic structure within aquatic species. We tested if nuclear allelic composition data sourced from eDNA can resolve fine scale spatial genetic structure of the cichlid fish Astatotilapia calliptera in Lake Masoko, Tanzania. In this ∼35 m deep crater lake the species is diverging into two genetically distinguishable ecomorphs, separated by a thermo-oxycline at ∼15 m that divides biologically distinct water masses. We quantified population genetic structure along a depth transect using single nucleotide polymorphisms (SNPs) derived from genome sequencing of 530 individuals. This population genetic structure was reflected in a focal set of SNPs that were also reliably amplified from eDNA - with allele frequencies derived from eDNA reflecting those of fish within each depth zone. Thus, by targeting known genetic variation between populations within aquatic eDNA, we measured genetic structure within the focal species.

Community assembly patterns and processes of bacteria in a field-scale aquaculture wastewater treatment system

Microbial communities are responsible for the biological treatment of wastewater, however, our comprehension of their diversity, assembly patterns, and functions remains limited. In this study, we analyzed bacterial communities in both water and sediment samples. These samples were gathered from a novel field-scale aquaculture wastewater treatment system (FAWTS), which employs a multi-stage purification process to eliminate nutrients from pond culture wastewater. Significant variations were observed in bacterial diversity and composition across various ponds within the system and at different stages of the culture. Notably, the bacterial community in the FAWTS displayed a distinct species abundance distribution. The influence of dispersal-driven processes on shaping FAWTS communities was found to be relatively weak. The utilization of neutral and null models unveiled that the assembly of microbial communities was primarily governed by stochastic processes. Moreover, environmental factors variables such as total nitrogen (TN), dissolved oxygen (DO), and temperature were found to be associated with both the composition and assembly of bacterial communities, influencing the relative significance of stochastic processes. Furthermore, we discovered a close relationship between that bacterial community composition and system functionality. These findings hold significant implications for microbial ecologists and environmental engineers, as they can collaboratively refine operational strategies while preserving biodiversity. This, in turn, promotes the stability and efficiency of the FAWTS. In summary, our study contributes to an enhanced mechanistic understanding of microbial community diversity, assembly patterns, and functionality within the FAWTS, offering valuable insights into both microbial ecology and wastewater treatment processes.

Response mechanism of meiofaunal communities to multi-type of artificial reef habitats from the perspective of high-throughput sequencing technology

Multiple types of artificial reefs have been widely deployed in the coast of northern Yellow Sea, which can enhance fishery resources, restore coastal habitats and improve the marine environment. Meiofauna plays important ecological roles in marine ecosystem, but the response mechanism of meiofaunal community to different types of artificial reef is still poorly understood. In this study, we characterized the meiofaunal communities of concrete artificial reef habitat (CAR), rocky artificial reef habitat (RAR), ship artificial reef habitat (SAR) and adjacent natural habitat (NH) using 18S rRNA gene high-throughput sequencing technology, and explored the relationship of community-environment. The results showed that the diversity and community structure of meiofauna differed significantly on both spatial and temporal scales. Spatial differences were mainly contributed to the flow field effects and biological effects generated by artificial habitats, while temporal differences were driven by temperature (T) and dissolved oxygen (DO). The dominant taxa of meiofauna included arthropods, annelids, platyhelminths and nematodes. Platyhelminths were mainly positively influenced by artificial habitats but annelids were the opposite. Co-occurrence network analysis revealed that NH was more sensitive to environmental change than artificial habitat, while the performance of CAR and SAR were more stable. These results indicated that meiofauna can respond accordingly to different types of artificial habitats, and could be superimposed over the normal seasonal effects. The current study could provide fundamental data for understanding the response mechanism of meiofaunal community to different types of artificial habitats and a reference for assessments of the impact of artificial reefs on the marine environment.

Community assembly patterns and processes of microbiome responses to habitats and Mytilopsis sallei invasion in the tidal zones of the Pearl River Estuary

The sustainability of estuarine ecosystem functions depends on the stabilization of microbial ecological processes. However, due to the unique and variable habitat characteristics of estuarine areas, in-depth studies on ecological processes such as the spatial distribution and assembly patterns of microbial community structure are lacking. As methods to elucidate this structure, we used 16S rDNA, 18S rDNA and ITS sequencing technologies to study the composition, diversity, spatial pattern and aggregation mechanism of the bacterial, protist and fungal communities in the tidal zones of the Pearl River Estuary (PRETZ). The abundance of bacterial communities was much higher than that of protists and fungi, and the spatial pattern was obvious in PRETZ. The application of neutral and null models revealed the assembly process of three microbial communities dominated by stochastic processes. Among the stochastic processes, undominated processes (64.03 %, 62.45 %, and 59.29 %) were the most critical processes in the assembly of bacterial, fungal and protist communities. Meanwhile, environmental variables, geographic locations, and biological factors were associated with the composition and assembly of bacterial, protist, and fungal communities. Among the environmental variables, dissolved oxygen and salinity were the main predictors that jointly affected the differences in the community structure of the three microorganisms, and geographic location was the second predictor affecting the community structure of the three microorganisms and had a more pronounced effect on the diversity and network structure of the bacterial and fungal communities. However, biological factors exerted a weaker effect on the microbial community structure than spatial factors and only affected bacteria and protists; the invasive species Mytilopsis sallei only affected the process of protist community assembly. In addition, environmental variables affected the relative importance of stochastic processes. In summary, the formation of microbial communities in the PRETZ was affected by random processes, environmental variables, geographic location, and invasive species.

Metabarcoding reveals high diversity of benthic foraminifera linked to water masses circulation at coastal Svalbard

Arctic marine biodiversity is undergoing rapid changes due to global warming and modifications of oceanic water masses circulation. These changes have been demonstrated in the case of mega- and macrofauna, but much less is known about their impact on the biodiversity of smaller size organisms, such as foraminifera that represent a main component of meiofauna in the Arctic. Several studies analyzed the distribution and diversity of Arctic foraminifera. However, all these studies are based exclusively on the morphological identification of specimens sorted from sediment samples. Here, we present the first assessment of Arctic foraminifera diversity based on metabarcoding of sediment DNA samples collected in fjords and open sea areas in the Svalbard Archipelago. We obtained a total of 5,968,786 reads that represented 1384 amplicon sequence variants (ASVs). More than half of the ASVs (51.7%) could not be assigned to any group in the reference database suggesting a high genetic novelty of Svalbard foraminifera. The sieved and unsieved samples resolved comparable communities, sharing 1023 ASVs, comprising over 97% of reads. Our analyses show that the foraminiferal assemblage differs between the localities, with communities distinctly separated between fjord and open sea stations. Each locality was characterized by a specific assemblage, with only a small overlap in the case of open sea areas. Our study demonstrates a clear pattern of the influence of water masses on the structure of foraminiferal communities. The stations situated on the western coast of Svalbard that are strongly influenced by warm and salty Atlantic water (AW) are characterized by much higher diversity than stations in the northern and eastern part, where the impact of AW is less pronounced. This high diversity and specificity of Svalbard foraminifera associated with water mass distribution indicate that the foraminiferal metabarcoding data can be very useful for inferring present and past environmental conditions in the Arctic.

A manager's guide to using eDNA metabarcoding in marine ecosystems

Environmental DNA (eDNA) metabarcoding is a powerful tool that can enhance marine ecosystem/biodiversity monitoring programs. Here we outline five important steps managers and researchers should consider when developing eDNA monitoring program: (1) select genes and primers to target taxa; (2) assemble or develop comprehensive barcode reference databases; (3) apply rigorous site occupancy based decontamination pipelines; (4) conduct pilot studies to define spatial and temporal variance of eDNA; and (5) archive samples, extracts, and raw sequence data. We demonstrate the importance of each of these considerations using a case study of eDNA metabarcoding in the Ports of Los Angeles and Long Beach. eDNA metabarcoding approaches detected 94.1% (16/17) of species observed in paired trawl surveys while identifying an additional 55 native fishes, providing more comprehensive biodiversity inventories. Rigorous benchmarking of eDNA metabarcoding results improved ecological interpretation and confidence in species detections while providing archived genetic resources for future analyses. Well designed and validated eDNA metabarcoding approaches are ideally suited for biomonitoring applications that rely on the detection of species, including mapping invasive species fronts and endangered species habitats as well as tracking range shifts in response to climate change. Incorporating these considerations will enhance the utility and efficacy of eDNA metabarcoding for routine biomonitoring applications.

Detection of community-wide impacts of bottom trawl fishing on deep-sea assemblages using environmental DNA metabarcoding

Although considerable research progress on the effects of anthropogenic disturbance in the deep sea has been made in recent years, our understanding of these impacts at community level remains limited. Here, we studied deep-sea assemblages of Sicily (Mediterranean Sea) subject to different intensities of benthic trawling using environmental DNA (eDNA) metabarcoding and taxonomic identification of meiofauna communities. Firstly, eDNA metabarcoding data did not detect trawling impacts using alpha diversity whereas meiofauna data detected a significant effect of trawling. Secondly, both eDNA and meiofauna data detected significantly different communities across distinct levels of trawling intensity when we examined beta diversity. Taxonomic assignment of the eDNA data revealed that Bryozoa was present only at untrawled sites, highlighting their vulnerability to trawling. Our results provide evidence for community-wide impacts of trawling, with different trawling intensities leading to distinct deep-sea communities. Finally, we highlight the need for further studies to unravel understudied deep-sea biodiversity.

Different Responses of Bacteria and Microeukaryote to Assembly Processes and Co-occurrence Pattern in the Coastal Upwelling

Upwelling may generate unique hydrological and environmental heterogeneity, leading to enhanced diffusion to reshape microbial communities. However, it remains largely unknown how different microbial taxa respond to highly complex and dynamic upwelling systems. In the present study, geographic patterns and co-occurrence network of different microbial communities in response to upwelling were examined. Our results showed that coastal upwelling shaped prokaryotic and eukaryotic microbial community and decreased their diversity. In addition, bacteria and microeukaryote had similar biogeographical patterns with distinct assembly mechanisms. The impact of stochastic processes on bacteria was significantly stronger compared with microeukaryote in upwelling. Lower network complexity but more frequent interaction was found in upwelling microbial co-occurrence. However, the upwelling environment increased the robustness and modularity of bacterial network, while eukaryotic network was just the opposite. Co-occurrence networks of bacteria and microeukaryote showed significant distance-decay patterns, while the bacterial network had a stronger spatial variation. Temperature and salinity were the strongest environmental factors affecting microbial coexistence, whereas the topological characteristics of bacterial and eukaryotic networks had different responses to the upwelling environment. These findings expanded our understanding of biogeographic patterns of microbial community and ecological network and the underlying mechanisms of different microbial taxa in upwelling.

Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA.

Managing human-mediated range shifts: understanding spatial, temporal and genetic variation in marine non-native species

The use of molecular tools to manage natural resources is increasingly common. However, DNA-based methods are seldom used to understand the spatial and temporal dynamics of species' range shifts. This is important when managing range shifting species such as non-native species (NNS), which can have negative impacts on biotic communities. Here, we investigated the ascidian NNS Ciona robusta, Clavelina lepadiformis, Microcosmus squamiger and Styela plicata using a combined methodological approach. We first conducted non-molecular biodiversity surveys for these NNS along the South African coastline, and compared the results with historical surveys. We detected no consistent change in range size across species, with some displaying range stability and others showing range shifts. We then sequenced a section of cytochrome c oxidase subunit I (COI) from tissue samples and found genetic differences along the coastline but no change over recent times. Finally, we found that environmental DNA metabarcoding data showed broad congruence with both the biodiversity survey and the COI datasets, but failed to capture the complete incidence of all NNS. Overall, we demonstrated how a combined methodological approach can effectively detect spatial and temporal variation in genetic composition and range size, which is key for managing both thriving NNS and threatened species.

This article is part of the theme issue ‘Species’ ranges in the face of changing environments (part I)’.

Eutrophication causes microbial community homogenization via modulating generalist species

Eutrophication substantially influences the community structure of aquatic organisms and has become a major threat to biodiversity. However, whether eutrophication is linked to homogenization of microbial communities and the possible underlying mechanisms are poorly understood. Here, we studied bacterial and fungal communities from water and sediments of 40 shallow lakes in the Yangtze-Huaihe River basin, a representative area characterized by intensifying eutrophication in China, and further examined the beta diversity patterns and underlying mechanisms under eutrophication conditions. Our results indicate that eutrophication generally caused biotic homogenization of bacterial and fungal communities in both habitats showing decreased community variations for the sites with a higher trophic state index (TSI). In the two habitats, community dissimilarities were positively correlated with TSI changes for both taxonomic groups, while the local contribution to beta diversity (LCBD) remarkably declined with increasing TSI for the fungal community. These phenomena were consistent with the pivotal importance of the TSI in statistically accounting for beta diversity of bacterial and fungal communities in both habitats. In addition, we found that physicochemical factors such as water temperature and pH were also important for bacterial and fungal communities in water, while heavy metal elements were important for the communities in sediments. Interestingly, generalist species, rather than specialist species, were revealed to more dominantly affect the variations in beta diversity along the trophic gradient, which were quantified by Bray-Curtis dissimilarity and LCBD. Collectively, our findings reveal the importance of generalist species in contributing to the change of beta diversity of microbial communities along trophic gradients, which have profound implications for a comprehensive understanding of the effects of eutrophication on microbial community.

Land-use type temporarily affects active pond community structure but not gene expression patterns

Changes in land use and agricultural intensification threaten biodiversity and ecosystem functioning of small water bodies. We studied 67 kettle holes (KH) in an agricultural landscape in northeastern Germany using landscape-scale metatranscriptomics, to understand the responses of active bacterial, archaeal, and eukaryotic communities, to land-use type. These KH are proxies of the millions of small standing water bodies of glacial origin spread across the northern hemisphere. Like other landscapes in Europe, the study area has been used for intensive agriculture since the 1950s. In contrast to a parallel eDNA study which revealed the homogenization of biodiversity across KH conceivably resulting from long-lasting intensive agriculture, land-use type affected the structure of the active KH communities during spring crop fertilization, but not a month later. This effect was more pronounced in eukaryotes than in bacteria. In contrast, gene expression patterns did not differ between months or across land-use type, suggesting a high degree of functional redundancy across the KH communities. Variability in gene expression was best explained by active bacterial and eukaryotic community structures, suggesting that these changes in functioning are primarily driven by interactions between organisms. Our results show that influences of the surrounding landscape result in temporary changes in the activity of different community members. Thus, even in KH where biodiversity has been homogenized, communities continue to respond to land management. This needs to be considered when developing sustainable management options for restoration purposes and for successful mitigation of further biodiversity loss in agricultural landscapes.

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one another. As a result, non-saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false-negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA.