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At least 1,585 records · Page 88Linked to original sources

USGS2020

Nutrient status of San Francisco Bay and its management implications

Nutrient enrichment has degraded many of the world’s estuaries by amplifying algal production, leading to hypoxia/anoxia, loss of vascular plants and fish/shellfish habitat, and expansion of harmful blooms (HABs). Policies to protect coastal waters from the effects of nutrient enrichment require information to determine if a water body is impaired by nutrients and if regulatory actions are required. We compiled information to inform these decisions for San Francisco Bay (SFB), an urban estuary where the best path toward nutrient management is not yet clear. Our results show that SFB has high nutrient loadings, primarily from municipal wastewater; there is potential for high algal production, but that production is not fully realized; and SFB is not impaired by hypoxia or recurrent HABs. However, our assessment includes reasons for concern: nitrogen and phosphorus concentrations higher than those in other estuaries impaired by nutrient pollution, chronic presences of multiple algal toxins, a recent increase of primary production, and projected future hydroclimatic conditions that could increase the magnitude and frequency of algal blooms. Policymakers thus face the challenge of determining the appropriate protective policy for SFB. We identify three crucial next steps for meeting this challenge: (1) new research to determine if algal toxins can be reduced through nutrient management, (2) establish management goals as numeric targets, and (3) determine the magnitude of nutrient load reduction required to meet those targets. Our case study illustrates how scientific information can be acquired and communicated to inform policymakers about the status of nutrient pollution, its risks, and strategies for minimizing those risks.

California↗

USGS2022

The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts

Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.

California, Illinois, Iowa, Missouri↗

USGS2022

Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs

Structure from motion (SfM) photogrammetry is an increasingly common technique for measuring landscape change over time by deriving 3D point clouds and surface models from overlapping photographs. Traditional change detection approaches require photos that are geotagged with a differential GPS (DGPS) location, which requires expensive equipment that can limit the ability of communities and researchers to perform frequent ( i.e. daily, weekly, and/or monthly) surveys. Crowd-sourced photos can lower the barrier to entry and substantially increase the frequency of surveys, although such photos often lack accurate location information and can vary in quality. This paper presents a SfM approach for monitoring environmental change in high relief coastal environments that does not require all photos have DGPS location information and does not require field survey data. A 1.5 km section of coastal bluffs near the Elwha River Delta (Washington state) is used to demonstrate the efficacy of this approach. Photos of the bluff were collected with a digital SLR camera or phone camera while either on foot along the beach or from a boat as part of monitoring following removal of two large dams along the Elwha River during 2011–2013. Only 33% of photos had DGPS location information, whereas most photos had no location information or locations that were accurate to a couple of meters. All photos were processed using 3D, 4D, and fixed-floating (FF) SfM alignment methods and the resulting dense point clouds are used to compare the different alignment approaches with crowd-sourced photo sets. Results demonstrate that 4D and FF approaches are more likely to reconstruct and are more accurate than the 3D approach. While the 4D and FF have comparable accuracies, the FF approach is several orders of magnitude more efficient, as this method can leverage camera location information from relatively few photos to improve the accuracy of all aligned and derived products. Effectively utilizing crowd-sourced photos in SfM change detection can improve the frequency of surveying a landscape in a more cost-effective approach that also has potential for citizen-science engagement and communication. This is especially important for data-poor environments such as high-relief coastal cliffs and bluffs, where near-nadir imagery and LIDAR may fail to accurately capture near-vertical cliffs or bluff faces. Based on the analysis of different photo alignment and filtering approaches, we present suggested best practices for engaging citizen scientists in coastal cliff and bluff monitoring efforts through collecting photos amenable for SfM reconstruction.

Washington↗

USGS2024

Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling

Foragers on patchy landscapes must efficiently balance time between searching for and consuming resources to meet their daily energetic requirements. Spatial aggregation foraging behaviors may improve foraging efficiency by sharing information on locations of resource hotspots. Wading birds are an example of patch foragers that form colonial aggregations during the breeding season to obtain sufficient prey energy to sustain themselves and their offspring each day. Here, we describe a spatially-explicit simulation model of wading bird optimal foraging that represents information sharing through visual cues. The overall purpose of the model is to describe how wading bird daily foraging and reproductive success may change with alternative water control management practices that determine spatial availability of prey for wading birds on the landscape, throughout their breeding seasons. Wading birds are simulated as individuals that operate independently, sampling and selecting among patches based on a prey density tolerance threshold, but also use information from other birds to inform their selection decisions. Foraging success is evaluated against the fundamental objectives of (a) fulfilling daily energetic demands and (b) minimizing predation exposure, by tracking individual daily energetic intake and time spent foraging. In this way, the model approximates population level dynamics of wading bird aggregations that emerge through collective decision making of birds simulated at the lower individual level. Key results of this study suggest that aggregation behaviors may improve population-level foraging success rates, and the optimal settling threshold may modulate when resources become more scarce or difficult to find. Thus, the model addresses ecological theory on the advantages of foraging in groups versus independently. This technique is appropriate for evaluating wading bird populations that forage on patchy landscapes, such as seasonally-pulsed wetlands, wherever sufficient information is available to describe (1) foraging behavior (e.g., feeding rate, flight speeds, patch selection decisions), (2) key landscape characteristics, (3) spatial distributions of prey densities among foraging patches, and (4) changes in prey densities through time. The model was designed to predict qualitative, testable spatial patterns of wading bird foraging movements which can be compared with empirical observations and empirically-derived habitat suitability models. These techniques can also be applied to other bird species, such as shorebirds, or more generally to any species that transits between discrete foraging patches.

Ecological Modelling↗

USGS2024

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast. The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.

Christchurch↗

USGS2017

Are coastal managers ready for climate change? A case study from estuaries along the Pacific coast of the United States

A key challenge for coastal resource managers is to plan and implement climate change adaptation strategies inlight of uncertainties and competing management priorities. In 2014, we held six workshops across estuaries along the Pacific coast of North America with over 150 participants to evaluate resource managers' perceived level of understanding of climate change science, where they obtain information, how they use this knowledge, and their preparedness for incorporating climate change into their management decisions. We found that most resource managers understood the types of climate change impacts likely to occur in their estuaries, but often lacked the scientific information to make decisions and plan effectively. Managers stated that time, money, and staff resources were the largest obstacles in their efforts. Managers identified that they learned most of their information from peers, scientific journals, and the Internet and indicated that sea-level rise was their greatest concern. There was, however, variation in managers' levels of readiness and perceived knowledge within and among workshop locations. The workshops revealed that some regions don't have the information they need or the planning capacity to effectively integrate climate change into their management, with eight out of fifteen site comparisons showing a significant difference between their level of preparedness (F 5,26 = 6.852; p = 0.0003), and their willingness to formally plan (F 5,26 = 12.84; p = 0.000002). We found that Urban estuaries were significantly different from Mixed Use and Rural estuaries, in having access to information and feeling more prepared to conduct climate change planning and implementation (F 2,29 = 17.34; p = 0.00001). To facilitate climate change preparedness more comprehensive integration of science into management decisions is essential.

Ocean and Coastal Management↗

USGS2025

Molluscan isotope sclerochronology in marine palaeoclimatology: Taxa, technique and timespan issues

Study of the accretionary biomineralised hardparts of organisms (sclerochronology) can make a useful contribution to palaeoclimatology. Ontogenetic sequences of isotopic data (δ 18 O and Δ 47 values) from the shells of marine molluscs are a source of information on seasonal sea-surface temperatures that can be used for detailed and rigorous evaluation of the outputs of numerical climate models. In situations where there is significant seasonality, and where shell preservation is adequate, accurate information about winter and summer surface temperature can be obtained from shallow-water benthic forms (bivalves and gastropods), in particular the early ontogeny of fast-growing species. Accurate information about winter surface temperature can also be obtained from individuals that lived at mid-shelf depths (20–40 m), but summer seafloor values from these need upward adjustment to derive a plausible surface temperature if thermal stratification of the water column occurs in this season. Ontogenetic δ 18 O profiles from planktonic pteropod gastropods are a potential source of insight into seasonal surface temperatures in the ocean basins; these organisms merit investigation for provision of information to complement shelf data. Temperature profiles constructed from shell δ 18 O require an estimate of the δ 18 O value of ambient seawater, which can be derived by back-calculation from the Δ 47 -temperature supplied by the same shell material. Alternatively, through appropriate sampling and data processing, seasonal temperatures can be obtained directly from Δ 47 profiles. Climate parameters are defined in terms of the mean state over a period of 30 consecutive years, a statistic (e.g., for seasonal temperatures) which can be derived from the long isotopic temperature records obtainable from bivalve species that live for many tens or hundreds of years. Efforts should be made to acquire such records, especially averaged data from crossdated shells, to specify climate parameters for precise times in the past. Information for precise times would be of particular value for icehouse intervals like the late Cenozoic, characterised by high frequency (high amplitude) climate fluctuation. Short records from non-crossdated shells can nevertheless provide useful insights into climate, particularly if a large dataset is obtained, supplying a reliable picture of the mean state and range of variation in climate parameters over the interval represented by the shells.

Quaternary Science Reviews↗

USGS2016

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

State-and-transition models (STMs) are useful tools for management, but they can be difficult to use and have limited content. STMs created for groups of related ecological sites could simplify and improve their utility. The amount of information linked to models can be increased using tables that communicate management interpretations and important within-group variability. We created a new web-based information system (the Ecosystem Dynamics Interpretive Tool) to house STMs, associated tabular information, and other ecological site data and descriptors. Fewer, more informative, better organized, and easily accessible STMs should increase the accessibility of science information.

Rangelands↗

USGS2025

Costs of land treatments on public lands in the western United States

Public land managers often conduct rehabilitation and restoration actions to achieve desired conditions or specific natural resource objectives. These “land treatments” include a variety of techniques, such as biomass removal or manipulation, seeding, and herbicide application. Limited information exists on the costs of conducting many common types of land treatments, but such information can be paired with treatment effectiveness data to prioritize application of limited resources where they may have the greatest benefit and improve efficiency. Here, we investigated cost information recorded in the Land Treatment Digital Library, a catalog of legacy land treatment information on public lands managed by the U.S. Department of the Interior's Bureau of Land Management. Based on 1,701 treatment records across eleven western U.S. states, we developed empirical per-acre cost estimates for representative land treatments in eight categories: three seeding categories (aerial seeding, drill seeding, and seedling planting), prescribed burning, soil disturbance, soil stabilization, vegetation disturbance, and weed control. We evaluated spatio-temporal factors that may be associated with variation in treatment costs and found strong evidence for nonlinear decreases in per-acre costs as treatment areas increased and that per-acre treatment costs have increased in real terms in recent decades. We also found evidence that per-acre costs for drill seeding, prescribed burns, and soil stabilization increased with the average slope of the terrain of a treated area and that per-acre costs for prescribed burns, seedling planting, and soil stabilization were influenced by distance to urban areas or major roads. These results can inform planning, prioritization, and assessment of common land treatments on public lands in the western United States, in particular supporting greater consideration of costs and cost effectiveness.

Rangeland Ecology & Management↗

USGS2003

Entropy and generalized least square methods in assessment of the regional value of streamgages

The Illinois State Water Survey performed a study to assess the streamgaging network in the State of Illinois. One of the important aspects of the study was to assess the regional value of each station through an assessment of the information transfer among gaging records for low, average, and high flow conditions. This analysis was performed for the main hydrologic regions in the State, and the stations were initially evaluated using a new approach based on entropy analysis. To determine the regional value of each station within a region, several information parameters, including total net information, were defined based on entropy. Stations were ranked based on the total net information. For comparison, the regional value of the same stations was assessed using the generalized least square regression (GLS) method, developed by the US Geological Survey. Finally, a hybrid combination of GLS and entropy was created by including a function of the negative net information as a penalty function in the GLS. The weights of the combined model were determined to maximize the average correlation with the results of GLS and entropy. The entropy and GLS methods were evaluated using the high-flow data from southern Illinois stations. The combined method was compared with the entropy and GLS approaches using the high-flow data from eastern Illinois stations. ?? 2003 Elsevier B.V. All rights reserved.

Journal of Hydrology↗

USGS2010

Multiobjective sampling design for parameter estimation and model discrimination in groundwater solute transport

Sampling design for site characterization studies of solute transport in porous media is formulated as a multiobjective problem. Optimal design of a sampling network is a sequential process in which the next phase of sampling is designed on the basis of all available physical knowledge of the system. Three objectives are considered: model discrimination, parameter estimation, and cost minimization. For the first two objectives, physically based measures of the value of information obtained from a set of observations are specified. In model discrimination, value of information of an observation point is measured in terms of the difference in solute concentration predicted by hypothesized models of transport. Points of greatest difference in predictions can contribute the most information to the discriminatory power of a sampling design. Sensitivity of solute concentration to a change in a parameter contributes information on the relative variance of a parameter estimate. Inclusion of points in a sampling design with high sensitivities to parameters tends to reduce variance in parameter estimates. Cost minimization accounts for both the capital cost of well installation and the operating costs of collection and analysis of field samples. Sensitivities, discrimination information, and well installation and sampling costs are used to form coefficients in the multiobjective problem in which the decision variables are binary (zero/one), each corresponding to the selection of an observation point in time and space. The solution to the multiobjective problem is a noninferior set of designs. To gain insight into effective design strategies, a one-dimensional solute transport problem is hypothesized. Then, an approximation of the noninferior set is found by enumerating 120 designs and evaluating objective functions for each of the designs. Trade-offs between pairs of objectives are demonstrated among the models. The value of an objective function for a given design is shown to correspond to the ability of a design to actually meet an objective.

Water Resources Research↗

USGS2022

Can non-invasive methods replace radiocollar-based winter counts in a 50-year wolf study? Lessons learned from a three-winter trial

Context: Monitoring low-density, elusive predators such as grey wolves ( Canis lupus ) has often been undertaken via live-capture and radio-collaring. Recent advances in non-invasive methods suggest live-captures may not be necessary for adequate monitoring. Further, non-invasive methods are considered best practice when possible. Aims: I evaluated whether a suite of non-invasive methods could replace aerial radiotelemetry to census resident pack wolves. Methods: I employed aerial snow-tracking, ground snow-tracking, camera-trapping, non-invasive genetic surveys, and community-scientist reports during three winters (2019–2021) in north-eastern Minnesota, USA to census pack wolves in a 2060 km 2 area. I attempted to enumerate individual pack sizes as has been historically undertaken to compile the census. Traditional aerial radiotelemetry methods were also conducted for comparison. Key results: Ground snow-tracking and camera-trapping provided the most similar information to radiotelemetry for determining pack counts and territory information, and, in some cases, documented higher pack counts than those obtained by aerial radiotelemetry. Radiotelemetry was the best method for determining pack territories, but was limited to radioed packs. A staggered application of both approaches resulted in increased precision and additional pack-level information without greatly increasing overall field effort. Non-invasive methods allowed trapping for radio-collaring to be reduced to every other year (a 50% reduction), but depending on trapping success, survival of animals, and radio-collar battery life, might even be reduced to every third year. Conclusions: In this 3-year trial, non-invasive methods were not sufficient to completely replace radio-collaring. Nevertheless, non-invasive methods allowed for a 50% reduction in trapping, increased the annual wolf-count precision, and increased community involvement. Anticipated technological improvements in non-invasive methods should reduce some issues encountered – but others will likely persist, in part, because of the fundamental nature of non-invasive methods. Implications: Less reliance on captures, enhanced pack information, and increased public involvement are all successful outcomes of this 3-year trial of non-invasive methods for monitoring wolf populations. Non-invasive methods continue to broaden and improve technologically, and information from trials such as this will help guide others as they increasingly implement non-invasive methods as partial or complete replacements for traditional capture-based methods.

Wildlife Research↗

USGS1996

Earthquake prediction: The interaction of public policy and science

Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake.

Conference Paper↗

USGS2022

Diatoms.org: Supporting taxonomists, connecting communities

Consistent identification of diatoms is a prerequisite for studying their ecology, biogeography, and successful application as environmental indicators. However, taxonomic consistency among observers has been difficult to achieve because taxonomic information is scattered across numerous literature sources, presenting challenges to the diatomist. Firstly, literature is often inaccessible because of cost or its location in journals that are not widely circulated. Secondly, taxonomic revisions of diatoms are taking place faster than floras can be updated. Finally, taxonomic information is often contradictory across literature sources. These issues can be addressed by developing a content creation community dedicated to making taxonomic, ecological, and image-based data freely available for diatom researchers. Diatoms.org represents such a content curation community, providing open, online access to a vast amount of recent and historical information on North American diatom taxonomy and ecology. The content curation community aggregates existing taxonomic information, creates new content, and provides feedback in the form of corrections and notices of literature with nomenclatural changes. The website not only addresses the needs of experienced diatom scientists for consistent identification but is also designed to meet users at their level of expertise, including engaging the lay public in the importance of diatom science. The website now contains over 1000 species pages contributed by over 100 content contributors, from students to established scientists. The project began with the intent to provide accurate information on diatom identification, ecology, and distribution using an approach that incorporates engaging design, user feedback, and advanced data access technology. In retrospect, the project that began as an ‘extended electronic book’ has emerged not only as a means to support taxonomists, but for practitioners to communicate and collaborate, expanding the size of and benefits to the content curation community. In this paper, we outline the development of diatoms.org , document key elements of the project, examine ongoing challenges and consider the unexpected emergent properties, including the value of diatoms.org as a source of data. Ultimately, if the field of diatom taxonomy, ecology, and biodiversity is to be relevant, a new generation of taxonomists needs to be trained and employed using new tools. We propose that diatoms.org is in a key position to serve as a hub of training and continuity for the study of diatom biodiversity and aquatic conditions.

Diatom Research↗

USGS1991

The measurement of mangrove characteristics in southwest Florida using spot multispectral data

An intensive in situ sampling program near Marco Island, Florida during 19–23 October 1988 collected information on mangrove type, maximum canopy height, and percent canopy closure. These data were correlated with selected vegetation index information derived from analysis of SPOT multispectral (XS) data obtained on 21 October 1988. The Normalized Difference (ND) vegetation index information was the most highly correlated index with percent canopy closure (r=0.91). Percent canopy closure information can be used as a surrogate for mangrove density which is of great value when predicting which parts of the mangrove ecosystem are at greatest risk after an oil spill occurs. Such information is very valuable when constructing oil spill Environmental Sensitivity Index (ESI) Maps for tropical regions of the world.

Florida↗

USGS2026

Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data

Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.

Michigan, Minnesota, Wisconson↗

USGS2015

A pheromone outweighs temperature in influencing migration of sea lamprey

Organisms continuously acquire and process information from surrounding cues. While some cues complement one another in delivering more reliable information, others may provide conflicting information. How organisms extract and use reliable information from a multitude of cues is largely unknown. We examined movement decisions of sea lampreys ( Petromyzon marinus L.) exposed to a conspecific and an environmental cue during pre-spawning migration. Specifically, we predicted that the mature male-released sex pheromone 3-keto petromyzonol sulfate (3kPZS) will outweigh the locomotor inhibiting effects of cold stream temperature (less than 15°C). Using large-scale stream bioassays, we found that 3kPZS elicits an increase (more than 40%) in upstream movement of pre-spawning lampreys when the water temperatures were below 15°C. Both warming temperatures and conspecific cues increase upstream movement when the water temperature rose above 15°C. These patterns define an interaction between abiotic and conspecific cues in modulating animal decision-making, providing an example of the hierarchy of contradictory information.

Royal Society Open Science↗

USGS2019

Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network

This study explores the feasibility and utility of integrating environmental DNA (eDNA) assessments of species occurrences into the United States (U.S.) Geological Survey’s national streamgage network. We used an existing network of five gages in southwest Idaho to explore the type of information that could be gained as well as the associated costs and limitations. Hydrologic technicians were trained in eDNA sampling protocols and they collected samples during routine monthly visits to streamgages over an entire water year (2016). We analyzed the eDNA in the filtered water samples to determine the presence of two fish species: bull trout and rainbow trout. We then modeled the spatiotemporal distribution of each species using discharge and temperature data. To assess the influence of the spatial distribution of the gages on the biological information obtained, we also collected eDNA samples from locations between the gages three times during the water year. We found eDNA monitoring at the five gages provided meaningful information about the distribution of both species, especially when detection probabilities accounted for variations in temperature and discharge. Sampling between the gages provided additional information about bull trout distribution — the rarer of the two species. Our study suggests the integration of eDNA sampling into a streamgage network is feasible and could provide a novel and powerful source of biological information for riverine ecosystems in the U.S.

Idaho, Nebraska↗