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At least 523 records · Page 29Linked to original sources
USGS2024

Assessing factors related to Walleye stocking success in the Midwestern United States

Objective The objective of this study was to evaluate stocking success of Walleye Sander vitreus in lakes and reservoirs across the Midwestern United States to inform stocking practices for state agencies. Demand for Walleye stocking may increase if climate change limits the potential for natural recruitment in lakes. Consequently, the strategic distribution of Walleye stocking may maximize fishing opportunities. Methods We synthesized data from 2226 Walleye fry and fingerling stocking events on 653 lakes in the Midwestern United States and used random forest algorithms and mixed-effects linear models to identify abiotic and biotic factors related to Walleye stocking success. Result Latitude and year explained relatively little variation in stocking success compared to within-lake variation. Relative abundance of Largemouth Bass Micropterus nigricans was an important indicator of Walleye stocking success for fry and fingerlings, with stocking success generally decreasing with increased bass abundance. There was an interaction between lake surface area and growing degree-days, as large lakes (>2500 ha) seemed to be more conducive to Walleye stocking success regardless of growing degree-days. The models that we developed did not accurately predict exact levels of Walleye stocking success but were 92–94% accurate in predicting whether the stocking success of both fry and fingerlings would be at or above the 50th percentile. Conclusion These findings may help to inform the management and stocking allocation of Walleye and suggest that future increases in Largemouth Bass abundance and growing degree-days could limit the effectiveness of stocking in some lakes.

Illinois, Indiana, Iowa, Michigan, Minnesota, Nebr↗
USGS2023

The Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

Accurate knowledge of the speed at which water moves along a river is essential for understanding ecohydraulic processes and managing natural resources. Measuring flow velocity via remote sensing can be more efficient than conventional field methods, and powerful computational techniques for inferring velocity fields from videos or image time series have been developed. The development of dedicated software tools for particle image velocimetry (PIV) could facilitate greater use of these methods by the river community. This paper introduces a standalone app designed for this exact purpose: the Toolbox for River Velocimetry using Images from Aircraft, or TRiVIA. The program provides a complete workflow for producing spatially distributed velocity vectors from a video or sequence of images, all within an accessible graphical user interface. TRiVIA includes modules for extracting and resampling frames, stabilization and geo-referencing images, defining a region of interest, enhancing images, performing PIV with an efficient ensemble correlation algorithm, visualizing results, assessing accuracy assessment, and exporting PIV output. We illustrate the software's capabilities using an example data set from a large river in Alaska. The initial release of the toolbox is now freely available. Augmenting TRiVIA to incorporate bathymetric information could enable discharge calculation functionality.

River Research and Applications↗
USGS2023

Scanning electron microscopic evaluation of broad ion beam milling effects to sedimentary organic matter: Sputter-induced artifacts or naturally occurring porosity?

Research examining organic-matter hosted porosity has significantly increased during the last decade due to greater focus on understanding hydrocarbon migration and storage in source-rock reservoirs, and technological advances in scanning electron microscopy (SEM) capabilities. The examination of nanometer-scale organic-matter hosted porosity by SEM requires the preparation of exceptionally flat geologic samples beyond the abilities of traditional mechanical polishing, which can deform or otherwise obscure organic surfaces. To meet this demand, broad ion beam (BIB) milling was introduced as a sample preparation technique for SEM petrographic analysis of geologic samples. As with any sample preparation technique, there can be unintended consequences. In this study, we examined the development of nanometer-scale sputter-induced voids caused by BIB milling of thermoset plastic binder material [poly(methyl methacrylate), PMMA] used for the mounting of geologic samples, and artifact sputter-induced voids in the organic matter of Green River Formation and Kimmeridge Clay Formation source rocks. Development of artifact sputter-induced voids was evaluated in relation to variations in the slope of the sample examination surface (0.0–4.9% slope), effectively varying the angle of ion incidence. The results indicate that only minor variations in the angle of ion incidence can generate sputter-induced voids in both PMMA (10.0–386.2 nm diameter sputter-induced voids) and sample sedimentary organic matter (solid bitumen; 12.2–103.6 nm diameter sputter-induced voids). Overall, average artifact pore diameters increased with increasing ion incidence angle within PMMA. Although sputter-induced voids within solid bitumen in the Green River Formation sample were only found in limited extent, the size of these void artifacts falls within the same size range as naturally occurring meso-macroporosity. That is, the pore-like artifacts could easily be misconstrued as naturally developed organic porosity, which is a major concern for SEM-based porosity evaluation methods. This study describes the factors that contribute to the creation of artifact sputter-induced voids, their distinguishing characteristics, and best practices for avoiding the creation of ion-induced artifacts.

International Journal of Coal Geology↗
USGS2021

Material failure and caldera collapse: Insights from the 2018 Kilauea eruption

The Failure Forecast Method (FFM) was introduced as an empirical model for forecasting catastrophic material failures related to natural hazards, such as landslides and volcanic eruptions, with mixed success. During the 2018 eruption of Kilauea volcano, Hawaii, the draining of the summit magma reservoir into the Lower East Rift Zone resulted in the formation of a new caldera at the summit. I tested the applicability of the FFM to caldera collapse by analyzing the cyclical earthquake swarms and ground deformation that occurred between 62 sudden major caldera collapse events. The progression of both the cumulative moment release of the cyclical earthquakes and the GNSS displacement show a major change in mid-June. In late May through early June, the progression of the parameters is consistent with strain localization or creep progression related to the development or activation of the ring fault system. From late June until the end of the eruption, parameter progression is roughly steady with initial accelerating increases in cumulative moment and displacement that shift to approximately linear progression. Analysis of repeating earthquake families in the cyclical swarms showed that the behavior of the repeaters was consistent with that of the cyclical swarms as a whole and suggested that each family undergoes its own progression of activation to termination. While the FFM analysis identified the system change in mid-June, it did not demonstrate an ability to forecast collapse events or the end of the eruption.

Hawaii↗
USGS2013

A comprehensive change detection method for updating the National Land Cover Database to circa 2011

The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.

Remote Sensing of Environment↗
USGS2020

The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes

The effect of nutrients on phytoplankton biomass in lakes continues to be a subject of debate by aquatic scientists. However, determining whether or not chlorophyll a (CHL) is limited by phosphorus (P) and/or nitrogen (N) is rarely considered using a probabilistic method in studies of hundreds of lakes across broad spatial extents. Several studies have applied a unified CHL-nutrient relationship to determine nutrient limitation, but pose a risk of ecological fallacy because they neglect spatial heterogeneity in ecological contexts. To examine whether or not CHL is limited by P, N, or both nutrients in hundreds of lakes and across diverse ecological settings, a probabilistic machine learning method, Bayesian Network, was applied. Spatial heterogeneity in ecological context was accommodated by the probabilistic nature of the results. We analyzed data from 1382 lakes in 17 US states to evaluate the cause-effect relationships between CHL and nutrients. Observations of CHL, total phosphorus (TP), and total nitrogen (TN) were discretized into three trophic states (oligo-mesotrophic, eutrophic, and hypereutrophic) to train the model. We found that although both nutrients were related to CHL trophic state, TP was more related to CHL than TN, especially under oligo-mesotrophic and eutrophic CHL conditions. However, when the CHL trophic state was hypereutrophic, both TP and TN were important. These results provide additional evidence that P-limitation is more likely under oligo-mesotrophic or eutrophic CHL conditions and that co-limitation of P and N occurs under hypereutrophic CHL conditions. We also found a decreasing pattern of the TN/TP ratio with increasing CHL concentrations, which might be a key driver for the role change of nutrients. Previous work performed at smaller scales support our findings, indicating potential for extension of our findings to other regions. Our findings enhance the understanding of nutrient limitation at macroscales and revealed that the current debate on the limiting nutrient might be caused by failure to consider CHL trophic state. Our findings also provide prior information for the site-specific eutrophication management of unsampled or data-limited lakes.

Water Research↗
USGS2018

Using the value of information to improve conservation decision making

Conservation decisions are challenging, not only because they often involve difficult conflicts among outcomes that people value, but because our understanding of the natural world and our effects on it is fraught with uncertainty. Value of Information (VoI) methods provide an approach for understanding and managing uncertainty from the standpoint of the decision maker. These methods are commonly used in other fields (e.g., economics, public health) and are increasingly used in biodiversity conservation. This decision analytical approach can identify the best management alternative to select where the effectiveness of interventions is uncertain, and can help to decide when to act and when to delay action until after further research. We review the use of VoI in the environmental domain, reflect on the need for greater uptake of VoI, particularly for strategic conservation planning, and suggest promising areas for new research. We also suggest common reporting standards as a means of increasing the leverage of this powerful tool. The environmental science, ecology and biodiversity categories of the Web of Knowledge were searched using the terms ‘Value of Information,’ ‘Expected Value of Perfect Information,’ and the abbreviation ‘EVPI.’ Google Scholar was searched with the same terms, and additionally the terms decision and biology, biodiversity conservation, fish, or ecology. We identified 1225 papers from these searches. Included studies were limited to those that show an application of VoI in biodiversity conservation rather than simply describing the method. All examples of use of VOI were summarised regarding the application of VoI, the management objectives, the uncertainties, models used, how the objectives were measured, and the type of VoI. While the use of VoI appears to be on the increase in biodiversity conservation, the reporting of results is highly variable, which can make it difficult to understand the decision context and which uncertainties were considered. Moreover, it was unclear if, and how, the papers informed management and policy interventions, which is why we suggest a range of reporting standards that would aid the use of VoI. The use of VoI in conservation settings is at an early stage. There are opportunities for broader applications, not only for species-focussed management problems, but also for setting local or global research priorities for biodiversity conservation, making funding decisions, or designing or improving protected area networks and management. The long-term benefits of applying VoI methods to biodiversity conservation include a more structured and decision-focused allocation of resources to research.

Biological Reviews↗
USGS2006

Multiscale patterns of movement in fragmented landscapes and consequences on demography of the snail kite in Florida

1. Habitat loss and fragmentation are major factors affecting vertebrate populations. A major effect of these habitat alterations is that they reduce movement of organisms. Despite the accepted importance of movement in driving the dynamics of many natural populations, movement of vertebrates in fragmented landscapes have seldom been estimated with robust statistical methods. 2. We estimated movement probabilities of snail kites Rosthramus sociabilis within the remaining wetlands in Florida. Using both radio-telemetry and banding information, we used a multistate modelling approach to estimate transition probabilities at two temporal scales (month; year) and multiple spatial scales. We examined kite movement among wetlands altered by three different levels of fragmentation: among wetlands separated by small physical barriers (e.g. road); among wetlands separated by moderate amount of matrix (< 5 km); and among wetlands separated by extensive matrix areas (> 15 km). 3. Kites moved extensively among contiguous wetlands (movement probability 0?29 per month), but significantly less among isolated wetlands (movement probability 0?10 per month). 4. Kites showed high levels of annual site fidelity to most isolated wetlands (probability ranged from 0?72 to 0?95 per year). 5. We tested the effects of patch size and interpatch distance on movement. Our modelling indicated an effect of both distance and patch size on juveniles' movement (but not adult) when examining movements among fragments. 6. Only a small proportion of kites escaped a regional drought by moving to refugia (wetlands less affected by drought). Many individuals died after the drought. During drought adult survival dropped by 16% while juvenile survival dropped by 86% (possibly because juveniles were less likely to reach refugia). 7. We hypothesize that fragmentation may decrease kite's resistance to drought by restricting exploratory behaviour.

Florida↗
USGS2010

Comparing scat detection dogs, cameras, and hair snares for surveying carnivores

Carnivores typically require large areas of habitat, exist at low natural densities, and exhibit elusive behavior - characteristics that render them difficult to study. Noninvasive survey methods increasingly provide means to collect extensive data on carnivore occupancy, distribution, and abundance. During the summers of 2003-2004, we compared the abilities of scat detection dogs, remote cameras, and hair snares to detect black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) at 168 sites throughout Vermont. All 3 methods detected black bears; neither fishers nor bobcats were detected by hair snares. Scat detection dogs yielded the highest raw detection rate and probability of detection (given presence) for each of the target species, as well as the greatest number of unique detections (i.e., occasions when only one method detected the target species). We estimated that the mean probability of detecting the target species during a single visit to a site with a detection dog was 0.87 for black bears, 0.84 for fishers, and 0.27 for bobcats. Although the cost of surveying with detection dogs was higher than that of remote cameras or hair snares, the efficiency of this method rendered it the most cost-effective survey method.

Journal of Wildlife Management↗
USGS2006

Relative Coastal Change-Potential Assessment of Glacier Bay National Park and Preserve

A change-potential index (CPI) was used to map the relative coastal change-potential of the shoreline to future sea-level fluctuation within Glacier Bay National Park and Preserve (GBNPP) in southeastern Alaska. The CPI ranks the following in terms of their physical contribution to coastal change: geomorphology, regional coastal slope, rate of relative sea-level change, historical shoreline change rates, mean tidal range and mean significant wave height. The rankings for each input variable were combined, and an index value calculated for 1-minute grid cells covering the park. The CPI highlights those regions where the physical effects of sea-level and coastal change might be the greatest. This approach combines the coastal system's potential for change with its natural ability to adapt to changing environmental conditions, yielding a quantitative, although relative, measure of the park's natural susceptibility to the effects of sea-level variation. The CPI provides an objective method for evaluation and long-term planning by scientists and park managers. The CPI was developed from a Coastal Vulnerability Index (CVI) typically applied to coastlines experiencing long-term sea-level rise. The CPI is modified from the CVI and applied to the emergent coast of GBNPP to understand the limits of applying this type of assessment method in a variety of sea level settings. GBNPP consists of sand and gravel beaches, rock cliffs, calving glaciers, mudflats, and alluvial fans. The areas within GBNPP that are likely to be most susceptible to coastal change as a result of sea-level change are tidewater glaciers and outer coast shorelines of unconsolidated sediment where wave energy is highest and the regional coastal slope is shallowest.

Open-File Report↗
USGS2018

Compilation and assessment of resource values and hazards to inform transportation planning and associated land-use planning

Land-use planning has an important role in local, regional, State, and Federal land management, and planning efforts can benefit from consistent, spatially explicit information that can help guide priorities and decisions. The credibility and relevance of information used to inform planning activities depends on the availability of consistent information about the resources and values of interest or concern within the planning area. To support long-range transportation planning and other regional land-use planning efforts, the U.S. Geological Survey gathered, processed, interpreted, and compiled spatial datasets representing a wide range of information on terrestrial and aquatic ecosystem condition and importance, cultural (historical) features and places, and natural hazards. This report describes the spatial data compiled to represent natural landscape conditions (including social, cultural, and natural attributes) to estimate the potential importance of lands for wildlife, wild habitats, recreation, and conservation based on abundance of species, habitats, land and water conditions, and conservation designations. Abundance of resources, including the potential number of species, presence of important habitats and protected areas, and proximity to particular features or habitats, indicates the potential sensitivity of the natural landscape to land use, especially transportation networks. The source data, derived indices, and the methods for processing these data are described in this final report. The datasets referenced in the report are available from the U.S. Geological Survey ( https://www.sciencebase.gov/catalog/ and https://doi.org/10.5066/F7MW2F8W ) or the Central Federal Lands Highway Division of the Office of Federal Lands Highway ( https://flh.fhwa.dot.gov ).

Scientific Investigations Report↗
USGS2013

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Hydrology and Earth System Sciences↗
USGS2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience↗
USGS2017

Climate change-driven cliff and beach evolution at decadal to centennial time scales

Here we develop a computationally efficient method that evolves cross-shore profiles of sand beaches with or without cliffs along natural and urban coastal environments and across expansive geographic areas at decadal to centennial time-scales driven by 21st century climate change projections. The model requires projected sea level rise rates, extrema of nearshore wave conditions, bluff recession and shoreline change rates, and cross-shore profiles representing present-day conditions. The model is applied to the ~470-km long coast of the Southern California Bight, USA, using recently available projected nearshore waves and bluff recession and shoreline change rates. The results indicate that eroded cliff material, from unarmored cliffs, contribute 11% to 26% to the total sediment budget. Historical beach nourishment rates will need to increase by more than 30% for a 0.25 m sea level rise (~2044) and by at least 75% by the year 2100 for a 1 m sea level rise, if evolution of the shoreline is to keep pace with rising sea levels.

Conference Paper↗
USGS2003

Genetic assessment of strain-specific sources of lake trout recruitment in the Great Lakes

Populations of wild lake trout Salvelinus namaycush have been extirpated from nearly all their historical habitats across the Great Lakes. Efforts to restore self-sustaining lake trout populations in U.S. waters have emphasized the stocking of coded-wire-tagged juveniles from six hatchery strains (Seneca Lake, Lewis Lake, Green Lake, Apostle Islands, Isle Royale, and Marquette) into vacant habitats. Strain-specific stocking success has historically been based on estimates of the survival and catch rates of coded-wire-tagged adults returning to spawning sites. However, traditional marking methods and estimates of relative strain abundance provide no means of assessing strain fitness (i.e., the realized contributions to natural recruitment) except by assuming that young-of-the-year production is proportional to adult spawner abundance. We used microsatellite genetic data collected from six hatchery strains with likelihood-based individual assignment tests (IA) and mixed-stock analysis (MSA) to identify the strain composition of young of the year recruited each year. We show that strain classifications based on IA and MSA were concordant and that the accuracy of both methods varied based on strain composition. Analyses of young-of-the-year lake trout samples from Little Traverse Bay (Lake Michigan) and Six Fathom Bank (Lake Huron) revealed that strain contributions differed significantly from estimates of the strain composition of adults returning to spawning reefs. The Seneca Lake strain contributed the majority of juveniles produced on Six Fathom Bank and more young of the year than expected within Little Traverse Bay. Microsatellite markers provided a method for accurately classifying the lake trout hatchery strains used for restoration efforts in the Great Lakes and for assessment of strain-specific reproductive success.

Transactions of the American Fisheries Society↗
USGS2017

Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.

Ecography↗
USGS1978

Models for calculating density and vapor pressure of geothermal brines

In a model for estimating density of a brine, the density of a natural brine at a known temperature, pressure, and composition can be calculated from the densities of the component salt solutions in the complex brine. A model for estimating vapor pressure requires two direct or indirect estimates of the vapor pressure and uses a published "reference-substance principle" to extrapolate,; these data 200° to 300° above the temperature of the highest observation. The methods can be used to estimate the partial molal volume and partial molal enthalpy of H 2 O in the natural brine and the partial molal volume change and partial molal heat change for the H2O component in the vaporization process. The equations for density and vapor pressure and the derived thermochemical properties will help in designing turbines for operation with geothermal and geopressured brines, in optimizing production conditions, and in physical and chemical modeling of a geothermal reservoir.

Journal of Research of the U.S. Geological Survey↗
USGS2023

Round goby detection in Lakes Huron and Michigan— An evaluation of eDNA and fish catches

Aquatic surveys for fish in large water bodies (e.g., Laurentian Great Lakes of North America) often require a flexible approach using multiple methods, surveying different depths, and sampling across seasons, especially when the target species is elusive in its natural habitat. The round goby ( Neogobius melanostomus ) is an invasive, bottom-dwelling fish inhabiting rocky areas of all five Great Lakes. While trawl surveys are typically used for abundance assessments, angling has been demonstrated as a means of supplementing surveys with additional data. Yet, round goby abundance and distribution is still not well described. Recently, with considerable success, scientists have explored sampling environmental DNA (eDNA) to complement traditional monitoring techniques for population abundance estimates, early detection of invasive species, and spawning or migration events. Therefore, we collected eDNA from water samples alongside bottom trawls and hook and line angling in Lakes Huron and Michigan to detect round goby. eDNA samples were analyzed by both droplet digital PCR (ddPCR) and quantitative PCR (qPCR) to maximize the likelihood of detection. Overall, round goby was captured in 23% of the trawls, but the eDNA based methods detected round goby in 74% and 66% of samples by ddPCR and qPCR, respectively, mostly in samples collected at <30 m depths, and mostly in the fall. More studies comparing eDNA based methods to traditional monitoring, especially trawls in large open waters, may contribute to a better understanding of using eDNA in population assessments.

Illinois, Indiana, Michigan↗