Developing robust methods for amplifying and analysing highly-polymorphic nuclear genetic markers from environmental samples could assist in the reliable and scalable long term monitoring of elusive, threatened or invasive species that are otherwise challenging to observe. In this study, we used zebrafish in controlled aquaria to apply forensic science approaches and demonstrate that microhaplotypes, which are short segments of nuclear DNA (100 to 300bp) containing two or more single nucleotide polymorphisms (SNPs), can be amplified from trace DNA in water samples to accurately estimate population genetic diversity and species abundance. We successfully amplified a panel of 17 microhaplotypes that comprised 69 SNPs which could reliably estimate population-level allele frequencies and genetic diversity estimates from water DNA. The panel of microhaplotypes amplified from water samples from replicate tanks strongly matched allele frequency estimates from corresponding tissue samples, and could also be used for estimating number of contributors from multi-individual samples. Our research demonstrates the effectiveness and potential of amplifying microhaplotype panels from eDNA as a non-invasive and scalable tool for population genetic studies of aquatic species. ### Competing Interest Statement The authors have declared no competing interest.

The global marine ecosystem is changing rapidly as the result of biogeochemical cycles and ecosystem structure being altered by industrial civilization. Invasive marine species (IMS) are one of the most damaging regional consequences of human activity, and one of the most easily attributable to specific processes. This makes IMS introduction one of most tractable threats for management by appropriate policies. Once established, a different set of policies are required either to restrict IMS spread, or to attempt local eradication. The key ecosystem management tool for IMS damage mitigation is rapid, widely deployable IMS detection. Environmental Nucleic Acids (eNA), combining environmental DNA (eDNA) and environmental RNA (eRNA) analyses, have emerged as valuable tools for sensitive, cost-effective and readily deployable detection of IMS. Methods for IMS detection by eNA are still being developed through a widespread and active research community, so identifying the limitations of current processes will help prioritise eNA-based IMS detection research. We analysed and synthesised the opinions of expert marine ecosystem managers and researchers in Australia and New Zealand about the knowledge gaps and research needs for eNA-based IMS detection. This synthesis was placed in context with current research literature on what eNA technologies are currently providing as an IMS management tool; what problems exist with the current technology; and what could be done to improve this general approach. Our analyses produced a list of priorities that chart a path towards the best possible systems for IMS detection by eNA.

Global biodiversity is declining at an ever-increasing rate. Yet effective policies to mitigate or reverse these declines require ecosystem condition data that are rarely available. Morphology-based bioassessment methods are difficult to scale, limited in scope, suffer prohibitive costs, require skilled taxonomists, and can be applied inconsistently between practitioners. Environmental DNA (eDNA) metabarcoding offers a powerful, reproducible and scalable solution that can survey across the tree-of-life with relatively low cost and minimal expertise for sample collection. However, there remains a need to condense the complex, multidimensional community information into simple, interpretable metrics of ecological health for environmental management purposes. We developed a riverine taxon-independent community index (TICI) that objectively assigns indicator values to amplicon sequence variants (ASVs), and significantly improves the statistical power and utility of eDNA-based bioassessments. The TICI model training step uses the Chessman iterative learning algorithm to assign health indicator scores to a large number of ASVs that are commonly encountered across a wide geographic range. New sites can then be evaluated for ecological health by averaging the indicator value of the ASVs present at the site. We trained a TICI model on an eDNA dataset from 53 well-studied riverine monitoring sites across New Zealand, each sampled with a high level of biological replication (n = 16). Eight short-amplicon metabarcoding assays were used to generate data from a broad taxonomic range, including bacteria, microeukaryotes, fungi, plants, and animals. Site-specific TICI scores were strongly correlated with historical stream condition scores from macroinvertebrate assessments (macroinvertebrate community index or MCI; R2 = 0.82), and TICI variation between sample replicates was minimal (CV = 0.013). Taken together, this demonstrates the potential for taxon-independent eDNA analysis to provide a reliable, robust and low-cost assessment of ecological health that is accessible to environmental managers, decision makers, and the wider community.

Abstract Age at sexual maturity is a key life history trait that can be used to predict population growth rates and develop life history models. In many wild animal species, the age at sexual maturity is not accurately quantified. This results in a reduced ability to accurately model demography of wild populations. Recent studies have indicated the potential for CpG density within gene promoters to be predictive of other life history traits, specifically maximum lifespan. Here, we have developed a machine learning model using gene promoter CpG density to predict the mean age at sexual maturity in mammalian species. In total, 91 genomes were used to identify 101 unique gene promoters predictive of age at sexual maturity across males and females. We found these gene promoters to be most predictive of age at sexual maturity in females (R2 = 0.881) compared to males (R2 = 0.758). The median absolute error rate was also found to be lower in females (0.427 years) compared to males (0.785 years). This model provides a novel method for species‐level age at sexual maturity prediction without the need for long‐term monitoring. This study also highlights a potential epigenetic mechanism for the onset of sexual maturity, indicating the possibility of using epigenetic biomarkers for this important life history trait.

Environmental DNA (eDNA) analyses of species present in marine environments is the most effective biological diversity measurement tool currently available. eDNA sampling methods are an intrinsically important part of the eDNA biodiversity analysis process. Identification and development of eDNA sampling methods that are as rapid, affordable, versatile and practical as possible will improve rates of detection of marine species. Optimal outcomes of eDNA biodiversity surveys come from studies employing high levels of sampling replication, so any methods that make sampling faster and cheaper will improve scientific outcomes. eDNA sampling methods that can be applied more widely will also enable sampling from a greater range of marine surface micro-habitats, resulting in detection of a wider range of organisms. In this study, we compared diversity detection by several methods for sampling eDNA from submerged marine surfaces: polyurethane foam, nylon swabs, microfibre paint rollers, and sediment scoops. All of the methods produced a diverse range of species identifications, with >250 multicellular species represented by eDNA at the study site. We found that widely-available small paint rollers were an effective, readily available and affordable method for sampling eDNA from underwater marine surfaces. This approach enables the sampling of marine eDNA using extended poles, or potentially by remotely operated vehicles, where surface sampling by hand is impractical.

AbstractConservation translocations require robust post‐release monitoring to evaluate their success, which can be challenging to implement and maintain. Monitoring techniques that can account for the dispersal and cryptic nature of translocated animals are necessary to provide critical information on persistence and distribution. In this study, we developed a highly sensitive environmental DNA (eDNA) assay specific to the critically endangered western swamp turtle (Pseudemydura umbrina), a species currently undergoing trials of assisted colonization. Actively filtering sufficient volumes of water in lentic systems is difficult due to high concentrations of clogging particulates, therefore we assessed the viability of passive sampling in a controlled environment by submerging filter membranes and directly extracting DNA. Active sampling detected P. umbrina with a 97.6% detection rate, whereas passive sampling resulted in an 8.3% detection rate. We then used a fine‐scale eDNA sampling design and radio‐tracked translocated P. umbrina at the assisted colonization wetland to investigate eDNA dispersal and spatial monitoring resolution. We detected P. umbrina at 42% (7/17) of eDNA sample sites, and the probability of a positive eDNA detection was negatively associated with the distance of P. umbrina from the sampling site, indicating limited eDNA dispersal from the source. Systems with low natural mixing and limited eDNA dispersal provide an opportunity for high‐resolution spatial and temporal monitoring via targeted eDNA approaches. This is beneficial for monitoring rare species in these systems, as such high‐resolution results can provide insights into species presence, distribution, and microhabitat use.

ABSTRACT There is an increasing interest in environmental DNA (eDNA) as a method to survey marine biota, enhancing traditional survey methods, and a need to ground truth eDNA‐based interpretations with visual surveys to understand biases in both the eDNA and visual datasets. We designed and tested a rapidly deployable, robust method pairing water sampling for eDNA collection and stereo‐video imagery, comparing inferred fish assemblages with interspersed baited remote underwater video (stereo‐BRUV) samples. The system is capable of rapidly collecting simultaneous wide‐field stereo‐video imagery, oceanographic measurements and multiple water samples across a range of habitats and depths (up to 600 m). A platform demonstration was conducted in a no‐take National Park Zone of the Ningaloo Marine Park, Western Australia, with samples being collected whilst the system is resting on the seafloor. Combining simultaneous visual survey data with eDNA species estimates increased the total diversity of the fish assemblage by ca. 6.5% over eDNA estimates alone, whilst the analysis of the assemblage composition sampled by each method revealed significant differences. The platform demonstration highlights the biases of each sampling method and their complementarity to one another. We suggest that these biases will be better understood by advancements that allow eDNA metabarcoding to discriminate the abundance and life stage of marine biota. Furthermore, investigation of the relationship between eDNA metabarcoding data and concomitant imagery‐derived length, age and habitat data is needed.

Animal age at maturity can be used as a universal and simple predictor of species extinction risk. At present, methods to estimate age at maturity are typically species-specific, limiting comparisons among species, or are infeasible due to practical constraints. To overcome this, here we develop a universal predictor of species-level age at maturity for vertebrates. We show that modelling the frequency of ‘CG’ sequences (CpG sites) in gene promoter regions yields rapid predictions of vertebrate age at maturity. Our models predict age at maturity with remarkable accuracy and generalisability, with median error rates of 30% (less than 1 year) and are robust to genome assemblies of varying quality. We generate predictions for 1912 vertebrate species for which age at maturity estimates were previously absent from public databases. The predictions can be used to help to inform management decisions for the many species for which more detailed population information is currently unavailable. A universal model to predict vertebrate species’ age at maturity using gene promoter CpG density provides critical data for conservation efforts, with predictions for 1912 species previously lacking this information.

Age is a fundamental feature of individual and population ecology. Many species do not have morphological characters that allow their age to be determined. For those that do, measurement often requires capture of the animal or dissection of deceased animals. Many of these methods are impractical to apply in species that are not being killed for harvest or management purposes. Genomic methods enable age estimation with tissue samples from live animals. We describe current methods for developing 'epigenetic clocks', which predict age based on the degree of methylation at specific CpG sites. Epigenetic clock development depends on samples of known age animals to calibrate the clock, which should be from the same tissue type that will be collected for age analysis in the wild population. The clock development process involves choosing a genomic method to identify highly age-related CpG sites from amongst all those in the genome of that species. A lower-cost genomic method for measuring CpG methylation in test samples should also be chosen. We discuss the process of developing epigenetic clocks for a new target animal species. The range of genomic methods for implementing epigenetic clocks has increased recently, and there is evidence is emerging that epigenetic clocks may be useful in animal clades other than vertebrates.

In understanding the impact of commercial whaling, it is important to estimate the mixing of low latitude breeding populations on Antarctic feeding grounds, particularly the endangered humpback whale populations of Oceania. This paper estimates the degree of genetic differentiation among the putative populations of Oceania (New Caledonia, Tonga, the Cook Islands and French Polynesia) and Australia (western Australia and eastern Australia) using ten microsatellite loci and mtDNA, assesses the power of the data for a mixed-stock analysis, determines ways to improve statistical power for future studies and estimates the population composition of Antarctic samples collected in 2010 south of New Zealand and eastern Australia. A large proportion of individuals could not be assigned to a population of origin (> 52%) using a posterior probability threshold of > 0.90. The mixed-stock analysis simulations however, produced accurate results with humpback whales reapportioned to their population of origin above the 90% threshold for western Australia, New Caledonia and Oceania grouped using a combined mtDNA and microsatellite dataset. Removing the Cook Islands, considered a transient region for humpback whales, from the simulation analysis increased the ability to reapportion Tonga from 86% to 89% and French Polynesia from 89% to 92%. Breeding ground sample size was found to be a factor influencing the accuracy of population reapportionment whereas increasing the mixture or feeding ground sample size improved the precision of results. The mixed-stock analysis of our Antarctic samples revealed substantial contributions from both eastern Australia (53.2%, 6.8% SE) and New Caledonia (43.7%, 5.5% SE) [with Oceania contributing 46.8% (5.9% SE)] but not western Australia. Despite the need for more samples to improve estimates of population allocation, our study strengthens the emerging genetic and non-genetic evidence that Antarctic waters south of New Zealand and eastern Australia are used by humpback whales from both eastern Australia and the more vulnerable breeding population of New Caledonia, representing Oceania.

DNA collected from the environment (eDNA) can provide valuable understanding of ecological patterns and processes. eDNA is highly physically heterogeneous, but this has not been well-characterized, so most eDNA sampling strategies do not target any particular physical fraction. Consequently, we have limited evidence to understand and interpret the physical behavior of eDNA, to improve the efficiency of sampling, nor to target components of the eDNA spectrum for taxonomic and molecular attributes. We perform the first detailed characterization of the components of a marine eDNA sample using serial filtering from an 80 to <0.22 mu m particle size gradient, a tree of life metabarcoding approach using taxon-specific and universal assays, coupled with scanning electron microscopy and fluorescent confocal microscopy. We confirm that eDNA is manifest in a broad spectrum of physical states, ranging from extracellular DNA fragments to whole cells, tissue fragments, and whole organisms. The largest of these fractions of eDNA were embedded in microbial biofilms, rather than particulate. We show that the choice of filter size and types can target components of this spectrum, can affect the detectable species richness, and notably, also enrich samples for specific taxonomic groups. Our results imply that there is considerable scope to improve the efficiency of eDNA collection from aquatic environments, and its informativeness.

Coral reefs are biodiversity hotspots, places of high endemicity and provide essential services to billions of people globally. With increasing threats to these reefs worldwide, there is a need to implement faster, more efficient ways to monitor spatial and temporal patterns of biodiversity. Environmental DNA (eDNA) metabarcoding offers a promising tool to address this issue, as it has revolutionized our ability to monitor biodiversity from complex environmental samples such as seawater. However, the capacity for eDNA to resolve fine scale shifts in community composition across habitats in seascapes is yet to be fully explored. Here, we applied eDNA metabarcoding using the rRNA 18S Universal eukaryote assay to explore differences in community profiles between samples collected from the lagoon and reef slope habitats across more than 170 km of the Ningaloo Coast World Heritage Area in Western Australia. We recovered 2061 amplicon sequence variants that comprised of 401 taxa spanning 14 different metazoan phyla such as cnidarians, poriferans, molluscs, algae, worms, and echinoderms. Our results revealed strong clustering of samples by habitat type across the length of the reef. Community dissimilarity (beta diversity) between samples collected from the reef slope and lagoon habitats was high and was driven largely by a strong rate of spatial turnover, indicating a distinct set of taxa representing each reef zone community. We also detected a strong pattern of isolation by distance within our slope samples, suggesting that communities are spatially stratified across the length of the reef. Despite high connectivity due to regular flushing of the lagoon environment, our results demonstrate that metabarcoding of seawater eDNA from different habitats can resolve fine scale community structure. By generating multi-trophic biodiversity data, our study also provided baseline data for Ningaloo from which future changes can be assessed.

Animal age data are valuable for management of wildlife populations. Yet, for most species, there is no practical method for determining the age of unknown individuals. However, epigenetic clocks, a molecular-based method, are capable of age prediction by sampling specific tissue types and measuring DNA methylation levels at specific loci. Developing an epigenetic clock requires a large number of samples from animals of known ages. For most species, there are no individuals whose exact ages are known, making epigenetic clock calibration inaccurate or impossible. For many epigenetic clocks, calibration samples with inaccurate age estimates introduce a degree of error to epigenetic clock calibration. In this study, we investigated how much error in the training data set of an epigenetic clock can be tolerated before it resulted in an unacceptable increase in error for age prediction. Using four publicly available data sets, we artificially increased the training data age error by iterations of 1% and then tested the model against an independent set of known ages. A small effect size increase (Cohen's d >0.2) was detected when the error in age was higher than 22%. The effect size increased linearly with age error. This threshold was independent of sample size. Downstream applications for age data may have a more important role in deciding how much error can be tolerated for age prediction. If highly precise age estimates are required, then it may be futile to embark on the development of an epigenetic clock when there is no accurately aged calibration population to work with. However, for other problems, such as determining the relative age order of pairs of individuals, a lower-quality calibration data set may be adequate.

Aim: To use a long-term collection of bulk plankton samples to test the capacity of DNA metabarcoding to characterize the spatial and seasonal patterns found within a range of zooplankton communities, and investigate links with concurrent abiotic data collected as part of Australia's Integrated Marine Observing System (IMOS) programme. Location: Samples were sourced seasonally for 3 years from nine Pan-Australian marine sites (n = 90). Methods: Here, we apply a multi--assay metabarcoding approach to environmental DNA extracted from bulk plankton samples. Six assays (targeting 16SrRNA and COI genes) were used to target, amplify and sequence the zooplankton diversity found within each sample. The data generated from each assay were filtered and clustered into OTUs prior to analysis. Abiotic IMOS data collected contemporaneously enabled us to explore the physical and chemical drivers of community composition. Results: From over 25 million sequences, we identified in excess of 500 distinct taxa and detected clear spatial differences. We found that site and sea surface temperature are the most consistent predictors of differences between zooplankton communities. We detected endangered and invasive species such as the bryozoan Membranipora membranacea and the mollusc Maoricolpus roseus, and seasonal occurrences of species such as humpback whales (Megaptera novaeangliae). We also estimated the number of samples required to detect any significant seasonal changes. For OTU richness, this was found to be assay dependent and for OTU assemblage, a minimum of nine samples per season would be required. Main Conclusion: Our results demonstrate the ability of DNA to capture and map zooplankton community changes in response to seasonal and spatial stressors and provide vital evidence to environmental stakeholders. We confirm that a metabarcoding method offers a practical opportunity for an ecosystem-wide approach to long-term biomonitoring and understanding marine biomes where morphological analysis is not feasible.

Antarctic krill (Euphausia superba) is Earth’s most abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research.

Lifespan is a key attribute of a species' life cycle and varies extensively among major lineages of animals. In fish, lifespan varies by several orders of magnitude, with reported values ranging from less than 1 year to approximately 400 years. Lifespan information is particularly useful for species management, as it can be used to estimate invasion potential, extinction risk and sustainable harvest rates. Despite its utility, lifespan is unknown for most fish species. This is due to the difficulties associated with accurately identifying the oldest individual(s) of a given species, and/or deriving lifespan estimates that are representative for an entire species. Recently it has been shown that CpG density in gene promoter regions can be used to predict lifespan in mammals and other vertebrates, with variable accuracy across taxa. To improve accuracy of lifespan prediction in a non-mammalian vertebrate group, here we develop a fish-specific genomic lifespan predictor. Our new model includes more than eight times the number of fish species included in the previous vertebrate model (n = 442) and uses fish-specific gene promoters as reference sequences. The model predicts fish lifespan from genomic CpG density alone (measured as CpG observed/expected ratio), explaining 64% of the variance between known and predicted lifespans. The predictions are highly robust to variation in genome quality and are applicable to all classes of fish; a taxonomically diverse and speciose group. The results demonstrate the value of promoter CpG density as a universal predictor of fish lifespan that can applied where empirical data are unavailable, or impracticable to obtain.

Population genetic data can provide valuable information on the demography of a species. For rare and elusive marine megafauna, samples for generating the data are traditionally obtained from tissue biopsies, which can be logistically difficult and expensive to collect and require invasive sampling techniques. Analysis of environmental DNA (eDNA) offers an alternative, minimally invasive approach to provide important genetic information. Although eDNA approaches have been studied extensively for species detection and biodiversity monitoring in metabarcoding studies, the potential for the technique to address population-level questions remains largely unexplored. Here, we applied "eDNA haplotyping" to obtain estimates of the intraspecific genetic diversity of a whale shark (Rhincodon typus) aggregation at Ningaloo reef, Australia. Over 2 weeks, we collected seawater samples directly behind individual sharks prior to taking a tissue biopsy sample from the same animal. Our data showed a 100% match between mtDNA sequences recovered in the eDNA and tissue sample for all 28 individuals sampled. In the seawater samples, >97% of all reads were assigned to six dominant haplotypes, and a clear dominant signal (similar to 99% of sample reads) was recovered in each sample. Our study demonstrates accurate individual-level haplotyping from seawater eDNA. When DNA from one individual clearly dominates each eDNA sample, it provides many of the same opportunities for population genetic analyses as a tissue sample, potentially removing the need for tissue sampling. Our results show that eDNA approaches for population-level analyses have the potential to supply critical demographic data for the conservation and management of marine megafauna.

Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long-lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known-age green turtles (Chelonia mydas) from two captive populations, and mark-recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.

Passive collection is an emerging sampling method for environmental DNA (eDNA) in aquatic systems. Passive eDNA collection is inexpensive, efficient, and requires minimal equipment, making it suited to high density sampling and remote deployment. Here, we compare the effectiveness of nine membrane materials for passively collecting fish eDNA from a 3 million litre marine mesocosm. We submerged materials (cellulose, cellulose with 1% and 3% chitosan, cellulose overlayed with electrospun nanofibers and 1% chitosan, cotton fibres, hemp fibres and sponge with either zeolite or active carbon) for intervals between five and 1080 minutes. We show that for most materials, with as little as five minutes submersion, mitochondrial fish eDNA measured with qPCR, and fish species richness measured with metabarcoding, was comparable to that collected by conventional filtering. Furthermore, PCR template DNA concentrations and species richness were generally not improved significantly by longer submersion. Species richness detected for all materials ranged between 11 to 37 species, with a median of 27, which was comparable to the range for filtered eDNA (19-32). Using scanning electron microscopy, we visualised biological matter adhered to the surface of materials, rather than entrapped, with images also revealing a diversity in size and structure of putative eDNA particles. Environmental DNA can be collected rapidly from seawater with a passive approach and using a variety of materials. This will suit cost and time-sensitive biological surveys, and where access to equipment is limited.

Reptile populations are in decline globally, with total reptile abundance halving in the past half century, and approximately a fifth of species currently threatened with extinction. Research on reptile distributions, population trends, and trophic interactions can greatly improve the accuracy of conservation listings and planning for species recovery, but data deficiency is an impediment for many species. Environmental DNA (eDNA) can detect species and measure community diversity at diverse spatio-temporal scales, and is especially useful for detection of elusive, cryptic, or rare species, making it potentially very valuable in herpetology. We aim to summarize the utility of eDNA as a tool for informing reptile conservation and management and discuss the benefits and limitations of this approach. A literature review was conducted to collect all studies that used eDNA and focus on reptile ecology, conservation, or management. Results of the literature search are summarized into key discussion points, and the review also draws on eDNA studies from other taxa to highlight methodological challenges and to identify future research directions. eDNA has had limited application to reptiles, relative to other vertebrate groups, and little use in regions with high species richness. eDNA techniques have been more successfully applied to aquatic reptiles than to terrestrial reptiles, and most (64%) of studies focused on aquatic habitats. Two of the four reptilian orders dominate the existing eDNA studies (56% Testudines, 49% Squamata, 5% Crocodilia, 0% Rhynchocephalia). Our review provides direction for the application of eDNA as an emerging tool in reptile ecology and conservation, especially when it can be paired with traditional monitoring approaches. Technologies associated with eDNA are rapidly advancing, and as techniques become more sensitive and accessible, we expect eDNA will be increasingly valuable for addressing key knowledge gaps for reptiles.