A Best Practices Case Study for Scientific Collaboration between Researchers and Managers.

Effective engagement among scientists, government agency staff, and policymakers is necessary for solving fisheries challenges, but remains challenging for a variety of reasons. We present seven practices learned from a collaborative project focused on invasive species in the Great Lakes region (USA-CAN). These practices were based on a researcher-manager model composed of a research team, a management advisory board, and a bridging organization. We suggest this type of system functions well when (1) the management advisory board is provided compelling rationale for engagement; (2) the process uses key individuals as communicators; (3) the research team thoughtfully selects organizations and individuals involved; (4) the funding entity provides logistical support and allows for (5) a flexible structure that prioritizes management needs; (6) a bridging organization sustains communication between in-person meetings; and (7) the project team determines and enacts a project endpoint. We predict these approaches apply equally effectively to other challenges at the research-management-policy interface, including reductions of water pollution, transitions to renewable energy, increasing food security, and addressing climate change.

Early detection monitoring for aquatic non-indigenous species: Optimizing surveillance, incorporating advanced technologies, and identifying research needs.

Following decades of ecologic and economic impacts from a growing list of nonindigenous and invasive species, government and management entities are committing to systematic early- detection monitoring (EDM). This has reinvigorated investment in the science underpinning such monitoring, as well as the need to convey that science in practical terms to those tasked with EDM implementation. Using the context of nonindigenous species in the North American Great Lakes, this article summarizes the current scientific tools and knowledge - including limitations, research needs, and likely future developments - relevant to various aspects of planning and conducting comprehensive EDM. We begin with the scope of the effort, contrasting target-species with broad-spectrum monitoring, reviewing information to support prioritization based on species and locations, and exploring the challenge of moving beyond individual surveys towards a coordinated monitoring network. Next, we discuss survey design, including effort to expend and its allocation over space and time. A section on sample collection and analysis overviews the merits of collecting actual organisms versus shed DNA, reviews the capabilities and limitations of identification by morphology, DNA target markers, or DNA barcoding, and examines best practices for sample handling and data verification. We end with a section addressing the analysis of monitoring data, including methods to evaluate survey performance and characterize and communicate uncertainty. Although the body of science supporting EDM implementation is already substantial, research and information needs (many already actively being addressed) include: better data to support risk assessments that guide choice of taxa and locations to monitor; improved understanding of spatiotemporal scales for sample collection; further development of DNA target markers, reference barcodes, genomic workflows, and synergies between DNA-based and morphology-based taxonomy; and tools and information management systems for better evaluating and communicating survey outcomes and uncertainty.

Joint analysis of stressors and ecosystem services to enhance restoration effectiveness.

With increasing pressure placed on natural systems by growing human populations, both scientists and resource managers need a better understanding of the relationships between cumulative stress from human activities and valued ecosystem services. Societies often seek to mitigate threats to these services through large-scale, costly restoration projects, such as the over one billion dollar Great Lakes Restoration Initiative currently underway. To help inform these efforts, we merged high-resolution spatial analyses of environmental stressors with mapping of ecosystem services for all five Great Lakes. Cumulative ecosystem stress is highest in near-shore habitats, but also extends offshore in Lakes Erie, Ontario, and Michigan. Variation in cumulative stress is driven largely by spatial concordance among multiple stressors, indicating the importance of considering all stressors when planning restoration activities. In addition, highly stressed areas reflect numerous different combinations of stressors rather than a single suite of problems, suggesting that a detailed understanding of the stressors needing alleviation could improve restoration planning. We also find that many important areas for fisheries and recreation are subject to high stress, indicating that ecosystem degradation could be threatening key services. Current restoration efforts have targeted high-stress sites almost exclusively, but generally without knowledge of the full range of stressors affecting these locations or differences among sites in service provisioning. Our results demonstrate that joint spatial analysis of stressors and ecosystem services can provide a critical foundation for maximizing social and ecological benefits from restoration investments.

Environmental conditions influence eDNA persistence in aquatic systems.

Environmental DNA (eDNA) surveillance holds great promise for improving species conservation and management. However, few studies have investigated eDNA dynamics under natural conditions, and interpretations of eDNA surveillance results are clouded by uncertainties about eDNA degradation. We conducted a literature review to assess current understanding of eDNA degradation in aquatic systems and an experiment exploring how environmental conditions can influence eDNA degradation. Previous studies have reported macrobial eDNA persistence ranging from less than 1 day to over 2 weeks, with no attempts to quantify factors affecting degradation. Using a SYBR Green quantitative PCR assay to observe Common Carp ( Cyprinus carpio ) eDNA degradation in laboratory mesocosms, our rate of Common Carp eDNA detection decreased over time. Common Carp eDNA concentration followed a pattern of exponential decay, and observed decay rates exceeded previously published values for aquatic macrobial eDNA. Contrary to our expectations, eDNA degradation rate declined as biochemical oxygen demand, chlorophyll, and total eDNA (i.e., from any organism) concentration increased. Our results help explain the widely divergent, previously published estimates for eDNA degradation. Measurements of local environmental conditions, consideration of environmental influence on eDNA detection, and quantification of local eDNA degradation rates will help interpret future eDNA surveillance results.

Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas.

At least 65 aquatic plant species have been identified as part of a surveillance list of non-native species that pose a threat to biodiversity and ecosystem services in the Laurentian Great Lakes. Early detection of these potentially invasive aquatic plants (IAP) could minimize impacts of novel incursions and facilitate successful eradication. We developed, implemented, and then adaptively refined a probabilistic boat-based sampling design that aimed to maximize the likelihood of detecting novel IAP incursions in large (400+ hectares) Great Lakes coastal areas. Surveys were conducted from 2017 to 2019 at five Great Lakes locations - St Joseph River (MI), Saginaw River (MI), Milwaukee (WI), Cleveland (OH), and the Detroit River (MI). Aquatic plant communities were characterized across the five sites, with a total of 61 aquatic plant species detected. One-fifth of the species detected in our surveys were non-native to the Great Lakes basin. Sample-based species rarefaction curves, constructed from detection data from all surveys combined at each location, show that the estimated sample effort required for high confidence (> 95%) detection of all aquatic plants at a site, including potentially invasive species, varies (< 100 sample units for Detroit River; > 300 sample units for Milwaukee, roughly equivalent to 6 to 18 days sampling effort, respectively). At least 70% of the estimated species pool was detected at each site during initial 3-day surveys. Leveraging information on detection patterns from initial surveys, including depth and species richness strata, improved survey efficiency and completeness at some sites, with detection of at least 80% of the estimated species pool during subsequent surveys. Based on a forest-based classification and regression method, a combination of just five variables explained 70% or more of the variation in observed richness at all sites (depth, fetch, percent littoral, distance to boat ramps and distance to marinas). We discuss how the model outcomes can be used to inform survey design for other Great Lakes coastal areas. The survey design we describe provides a useful template that could be adaptively improved for early detection of IAP in the Great Lakes.

A Framework for Aquatic Invasive Species Surveillance Site Selection and Prioritization in the US waters of the Laurentian Great Lakes.

Risk-based prioritization for early detection monitoring is of utmost importance to prevent and mitigate invasive species impacts. The Great Lakes Water Quality Agreement, a binational commitment between the United States and Canada to restore and protect the waters of the Laurentian Great Lakes, identifies aquatic invasive species (AIS) as one of ten priority issues (annexes) that must be addressed to ensure the chemical, physical, and biological integrity of the Great Lakes. The Agreement calls out the need for a comprehensive strategy for detecting and tracking new and potentially invasive species. Yet, with a surface water area of 95, 000 square miles (246, 049 square km) and shoreline length of 10, 210 miles (16, 431 km), the Great Lakes represent a daunting challenge for prioritizing where AIS surveillance activities should occur. Our goal was to develop a spatially-explicit and quantitative approach for identifying the highest risk sites for AIS introduction into the US waters of the Great Lakes based on the cumulative risk of new introductions (including range expansions) from a range of pathways and associated taxa. We estimate "invasion risk" scores for nearly 6,000 sites (9 km x 9 km) across the Great Lakes basin using proxy measures for propagule pressure weighted by the proportion of taxa associated with each proxy variable. Proxy variables include human population, number of ship visits, marina size, number of ponds, and number of natural or artificial aquatic connections. In total, we identify more than 1,800 sites with invasion risk scores >0. A small subset of these 1,800+ sites accounts for a majority of predicted propagule pressure and are therefore logical targets for future surveillance and AIS prevention efforts. Many of the highest risk sites are located in western Lake Erie, southern Lake Michigan, and the St. Clair-Detroit River System.

A spatial modeling approach to predicting the secondary spread of invasive species due to ballast water discharge.

Ballast water in ships is an important contributor to the secondary spread of invasive species in the Laurentian Great Lakes. Here, we use a model previously created to determine the role ballast water management has played in the secondary spread of viral hemorrhagic septicemia virus (VHSV) to identify the future spread of one current and two potential invasive species in the Great Lakes, the Eurasian Ruffe (Gymnocephalus cernuus), killer shrimp (Dikerogammarus villosus), and golden mussel (Limnoperna fortunei), respectively. Model predictions for Eurasian Ruffe have been used to direct surveillance efforts within the Great Lakes and DNA evidence of ruffe presence was recently reported from one of three high risk port localities identified by our model. Predictions made for killer shrimp and golden mussel suggest that these two species have the potential to become rapidly widespread if introduced to the Great Lakes, reinforcing the need for proactive ballast water management. The model used here is flexible enough to be applied to any species capable of being spread by ballast water in marine or freshwater ecosystems.

Geographic selection bias of occurrence data influences transferability of invasive Hydrilla verticillata distribution models.

Due to socioeconomic differences, the accuracy and extent of reporting on the occurrence of native species differs among countries, which can impact the performance of species distribution models. We assessed the importance of geographical biases in occurrence data on model performance using Hydrilla verticillata as a case study. We used Maxent to predict potential North American distribution of the aquatic invasive macrophyte based upon training data from its native range. We produced a model using all available native range occurrence data, then explored the change in model performance produced by omitting subsets of training data based on political boundaries. We also compared those results with models trained on data from which a random sample of occurrence data was omitted from across the native range. Although most models accurately predicted the occurrence of H. verticillata in North America (AUC > 0.7600), data omissions influenced model predictions. Omitting data based on political boundaries resulted in larger shifts in model accuracy than omitting randomly selected occurrence data. For well-documented species like H. verticillata, missing records from single countries or ecoregions may minimally influence model predictions, but for species with fewer documented occurrences or poorly understood ranges, geographic biases could misguide predictions. Regardless of focal species, we recommend that future species distribution modeling efforts begin with a reflection on potential spatial biases of available occurrence data. Improved biodiversity surveillance and reporting will provide benefit not only in invaded ranges but also within under-reported and unexplored native ranges.

Validation of eDNA surveillance sensitivity for detection of Asian carps in controlled and field experiments.

In many North American rivers, populations of multiple species of non-native cyprinid fishes are present, including black carp (Mylpharyngodon piceus), grass carp (Ctenopharyngodon idella), bighead carp (Hypophthalmichthys nobilis), silver carp (Hypophthalmichthys molitrix), common carp (Cyprinus carpio), and goldfish (Carassius auratus). All six of these species are found in the Mississippi River basin and tracking their invasion has proven difficult, particularly where abundance is low. Knowledge of the location of the invasion front is valuable to natural resource managers because future ecological and economic damages can be most effectively prevented when populations are low. To test the accuracy of environmental DNA (eDNA) as an early indicator of species occurrence and relative abundance, we applied eDNA technology to the six non-native cyprinid species putatively present in a 2.6 river mile stretch of the Chicago (IL, USA) canal system that was subsequently treated with piscicide. The proportion of water samples yielding positive detections increased with relative abundance of the six species, as indicated by the number of carcasses recovered after poisoning. New markers for black carp, grass carp, and a common carp/goldfish are reported and details of the marker testing to ensure specificity are provided.

Weed risk assessment for aquatic plants: modification of a New Zealand system for the United States.

We tested the accuracy of an invasive aquatic plant risk assessment system in the United States that we modified from a system originally developed by New Zealand's Biosecurity Program. The US system is comprised of 38 questions that address biological, historical, and environmental tolerance traits. Values associated with each response are summed to produce a total score for each species that indicates its risk of invasion. To calibrate and test this risk assessment, we identified 39 aquatic plant species that are major invaders in the continental US, 31 species that have naturalized but have no documented impacts (minor invaders), and 60 that have been introduced but have not established. These species represent 55 families and span all aquatic plant growth forms. We found sufficient information to assess all but three of these species. When the results are compared to the known invasiveness of the species, major invaders are distinguished from minor and non-invaders with 91% accuracy. Using this approach, the US aquatic weed risk assessment correctly identifies major invaders 85%, and non-invaders 98%, of the time. Model validation using an additional 10 non-invaders and 10 invaders resulted in 100% accuracy for the former, and 80% accuracy for the latter group. Accuracy was further improved to an average of 91% for all groups when the 17% of species with scores of 31-39 required further evaluation prior to risk classification. The high accuracy with which we can distinguish non-invaders from harmful invaders suggests that this tool provides a feasible, pro-active system for pre-import screening of aquatic plants in the US, and may have additional utility for prioritizing management efforts of established species.