The rapid evolution of environmental (e)DNA methods has resulted in knowledge gaps in smaller, yet critical details like proper use of negative controls to detect contamination. Detecting contamination is vital for confident use of eDNA results in decision-making. We conducted two literature reviews to summarize (a) the types of quality assurance measures taken to detect contamination of eDNA samples from aquatic environments, (b) the occurrence, frequency and attribution (i.e., putative sources) of unexpected amplification in these quality assurance samples, and (c) how results were interpreted when contamination occurred. In the first literature review, we reviewed 156 papers and found that 91% of targeted and 73% of metabarcoding eDNA studies reported inclusion of negative controls within their workflows. However, a large percentage of targeted (49%) and metabarcoding (80%) studies only reported negative controls for laboratory procedures, so results were potentially blind to field contamination. Many of the 156 studies did not provide critical methodological information and amplification results of negative controls. In our second literature review, we reviewed 695 papers and found that 30 targeted and 32 metabarcoding eDNA studies reported amplification of negative controls. This amplification occurred at similar proportions for field and lab workflow steps in targeted and metabarcoding studies. These studies most frequently used amplified negative controls to delimit a detection threshold above which is considered significant or provided rationale for why the unexpected amplifications did not affect results. In summary, we found that there has been minimal convergence over time on negative control implementation, methods, and interpretation, which suggests that increased rigor in these smaller, yet critical details remains an outstanding need. We conclude our review by highlighting several studies that have developed especially effective quality assurance, control and mitigation methods.

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The costs of invasive species in the United States alone are estimated to exceed US$100 billion per year, so a critical tactic in minimizing the costs of invasive species is the development of effective, early-detection systems. To this end, we evaluated the efficacy of adding environmental (e)DNA surveillance to the U.S. Geological Survey (USGS) streamgage network, which consists of >8200 streamgages nationwide systemically visited by USGS hydrologic technicians. Incorporating strategic eDNA sample collection during routine streamgage visits could provide early-detection surveillance of aquatic invasive species with minimal additional cost. For this evaluation, USGS hydrologic technicians collected monthly eDNA water samples, May-September 2018, from streamgages downstream of reservoirs in the Columbia River Basin thought to be vulnerable to invasive dreissenid mussel (Dreissenidae spp.) establishment. We tested water samples for dreissenid mussel DNA and also for kokanee (Oncorhynchus nerka) and yellow perch (Perca flavescens) DNA; the two fishes were used to assess if streamgages are adequately located to provide early-detection eDNA surveillance of taxa known to be present in upstream reservoirs. No Columbia River Basin streamgage samples met our criteria for being scored as positive for dreissenid DNA. We did detect kokanee and yellow perch DNA at all streamgages downstream of reservoirs where these species are known to occur. Field collection, laboratory analyses, and personnel time required for collection of four eDNA samples at a streamgage site cost US$500-US$600 (net). Given these results, incorporating eDNA biosurveillance into routine streamgage visits might decrease costs associated with an invasion since early detection maximizes the potential for eradication, containment, and mitigation.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Proliferative kidney disease (PKD) is an emerging disease that recently resulted in a large mortality event of salmonids in the Yellowstone River (Montana, USA). Total PKD fish mortalities in the Yellowstone River were estimated in the tens of thousands, which resulted in a multi-week river closure and an estimated economic loss of US$500,000. This event shocked scientists, managers, and the public, as this was the first occurrence of the disease in the Yellowstone River, the only reported occurrence of the disease in Montana in the past 25 yr, and arguably the largest wild PKD fish kill in the world. To understand why the Yellowstone River fish kill occurred, we used molecular and historical data to evaluate evidence for several hypotheses: Was the causative parasite Tetracapsuloides bryosalmonae a novel invader, was the fish kill associated with a unique parasite strain, and/or was the outbreak caused by unprecedented environmental conditions? We found that T. bryosalmonae is widely distributed in Montana and have documented occurrence of this parasite in archived fish collected in the Yellowstone River prior to the fish kill. T. bryosalmonae had minimal phylogeographic population structure, as the DNA of parasites sampled from the Yellowstone River and distant water bodies were very similar. These results suggest that T. bryosalmonae could be endemic in Montana. Due to data limitations, we could not reject the hypothesis that the fish kill was caused by a novel and more virulent genetic strain of the parasite. Finally, we found that single-year environmental conditions are insufficient to explain the cause of the 2016 Yellowstone River PKD outbreak. Other regional rivers where we documented T. bryosalmonae had similar or even more extreme conditions than the Yellowstone River and similar or more extreme conditions have occurred in the Yellowstone River in the recent past, yet mass PKD mortalities have not been documented in either instance. We conclude by placing these results and unresolved hypotheses into the broader context of international research on T. bryosalmonae and PKD, which strongly suggests that a better understanding of bryozoans, the primary host of T. bryosalmonae, is required for better ecosystem understanding.

Management of invasive species, whether prevention, population reduction, or eradication, requires assessment of the invasive species' population status and an assessment of the probability of success of management options. Perceptions of a species' permanence in an environment or lack thereof frequently drives how limited time, financial, and personnel resources are allocated to such efforts. Language we use to describe a non-native species' status largely defines these perceptions and sets boundaries, real or perceived, to potential management actions. Here we discuss the use of a particular term-"established"when confronting management decisions for invasive species. Our objective is to contribute to bridging the gap between the realms of conceptual development and management with respect to use of the term "established". We find that although there are benefits of polysemy and synonymy to conceptual development they present an additional challenge to managers who must weigh the costs, benefits, and potential for success of particular management actions. We also examine how existing conceptual frameworks might be augmented to bridge the theoretical-practical gap, such as more precisely defining potential management actions and explicitly including assessment of risk.

The conventional view of bacterial adaptation emphasizes the importance of rapidly evolved changes that are highly repeatable in response to similar environments and subject to loss in the absence of selection. Consequently, genetic variation is not expected to persist over long time scales for these organisms. Here, we show that a geographically widespread gene content polymorphism has surprisingly been maintained for tens of millions of years of diversification of the multicellular cyanobacterium Fischerella thermalis. The polymorphism affects gas permeability of the heterocyst-the oxygen-sensitive, nitrogen-fixing cell produced by these bacteria-and spatial variation in temperature favours alternative alleles due to thermodynamic effects on both heterocyst function and organism fitness at physiological temperature extremes. Whether or not ancient balancing selection plays a generally important role in the maintenance of microbial diversity remains to be investigated.

Autonomous, robotic environmental (e)DNA samplers now make it possible for biological observations to match the scale and quality of abiotic measurements collected by automated sensor networks. Merging these automated data streams may allow for improved insight into biotic responses to environmental change and stressors. Here, we merged eDNA data collected by robotic samplers installed at three U.S. Geological Survey (USGS) streamgages with gridded daily weather data, and daily water quality and quantity data into a cloud-hosted database. The eDNA targets were a rare fish parasite and a more common salmonid fish. We then used computationally expedient Bayesian hierarchical occupancy models to evaluate associations between abiotic conditions and eDNA detections and to simulate how uncertainty in result interpretation changes with the frequency of autonomous robotic eDNA sample collection. We developed scripts to automate data merging, cleaning and analysis steps into a chained-step, workflow. We found that inclusion of abiotic covariates only provided improved insight for the more common salmonid fish since its DNA was more frequently detected. Rare fish parasite DNA was infrequently detected, which caused occupancy parameter estimates and covariate associations to have high uncertainty. Our simulations found that collecting samples at least once per day resulted in more detections and less parameter uncertainty than less frequent sampling. Our occupancy and simulation results together demonstrate the advantages of robotic eDNA samplers and how these samples can be combined with easy to acquire, publicly available data to foster real-time biosurveillance and forecasting.