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At least 1,369 records · Page 76Linked to original sources
USGS2020

Flow‐ecology modelling to inform reservoir releases for riparian restoration and management

Linked hydrologic, hydraulic, and ecological models can facilitate planning and implementing water releases from reservoirs to achieve ecological objectives along rivers. We applied a flow‐ecology model, the Ecosystem Functions Model (HEC‐EFM), to the Bill Williams River in southwestern USA to estimate areas suitable for recruitment of riparian tree seedlings in the context of managing flow releases from a large dam for riparian restoration. Ecological variables in the model included timing of seed dispersal, tolerable rates of flow recession, and tolerable duration of inundation following germination and early seedling establishment for native Fremont cottonwood and Goodding's willow, and non‐native tamarisk. Hydrological variables included peak flow timing, rate of flow recession following the peak, and duration of inundation. A one‐dimensional hydraulic model was applied to estimate stage‐discharge relationships along ~58 river kilometres. We then used HEC‐EFM to apply relationships between seedling ecology and streamflow to link hydrological dynamics with ecological response. We developed and validated HEC‐EFM based on an examination of seedling recruitment following an experimental flow release from Alamo Dam in spring 2006. The model predicted the largest area of potential recruitment for cottonwood (280–481 ha), with smaller areas predicted for willow (174–188 ha) and tamarisk (59–60 ha). Correlations between observed and predicted patches with successful seedling recruitment for areas within 40 m of the main channel ranged from 0.66 to 0.94. Finally, we examined arrays of hydrographs to identify which are most conducive to seedling recruitment along the river, given different combinations of peak flow, recession rate, and water volume released. Similar application of this model could be useful for informing reservoir management in the context of riparian restoration along other rivers facing similar challenges.

Arizona↗
USGS2021

Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins

Basin-centric long short-term memory (LSTM) network models have recently been shown to be an exceptionally powerful tool for stream temperature (T s ) temporal prediction (training in one period and predicting in another period at the same sites). However, spatial extrapolation is a well-known challenge to modelling T s and it is uncertain how an LSTM-based daily T s model will perform in unmonitored or dammed basins. Here we compiled a new benchmark dataset consisting of >400 basins across the contiguous United States in different data availability groups (DAG, meaning the daily sampling frequency) with and without major dams, and studied how to assemble suitable training datasets for predictions in basins with or without temperature monitoring. For prediction in unmonitored basins (PUB), LSTM produced a root-mean-square error (RMSE) of 1.129°C and an R 2 of 0.983. While these metrics declined from LSTM's temporal prediction performance, they far surpassed traditional models' PUB values, and were competitive with traditional models' temporal prediction on calibrated sites. Even for unmonitored basins with major reservoirs, we obtained a median RMSE of 1.202°C and an R 2 of 0.984. For temporal prediction, the most suitable training set was the matching DAG that the basin could be grouped into (for example, the 60% DAG was most suitable for a basin with 61% data availability). However, for PUB, a training dataset including all basins with data was consistently preferred. An input-selection ensemble moderately mitigated attribute overfitting. Our results indicate there are influential latent processes not sufficiently described by the inputs (e.g., geology, wetland covers), but temporal fluctuations can still be predicted well, and LSTM appears to be a highly accurate T s modelling tool even for spatial extrapolation.

Hydrological Processes↗
USGS2022

Using machine learning to improve predictions and provide insight into fluvial sediment transport

A thorough understanding of fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. Fluvial sediment samples are integral for addressing these environmental concerns but cannot be collected at every river and time of interest. Therefore, to gain a better understanding for rivers where direct measurements have not been made, extreme gradient boosting machine learning (ML) models were developed and trained to predict suspended sediment and bedload from sampling data collected in Minnesota, United States (U.S.), by the U.S. Geological Survey. Approximately 400 watershed (full upstream area), catchment (nearby landscape), near-channel, channel, and streamflow features were retrieved or developed from multiple sources, reduced to approximately 30 uncorrelated features, and used in the final ML models. The results indicate suspended sediment and bedload ML models explain approximately 70% of the variance in the datasets. Important features used in the models were interpreted with Shapley additive explanation (SHAP) plots, which provided insight into sediment transport processes. The most important features in the models were developed to normalize streamflow by the 2-year recurrence interval and quantify the rate of change in streamflow (slope), which helped account for sediment hysteresis. Generally, this study also showed a combination of mostly watershed and catchment geospatial features were important in ML models that predict sediment transport from physical samples. This study is a promising step forward in making fluvial sediment transport predictions using machine learning models trained by physically collected samples. The approach developed here can be used wherever similar datasets exists and will be useful for landscape and water management.

Minnesota↗
USGS2023

Identifying hydrologic signatures associated with streamflow depletion caused by groundwater pumping

Groundwater pumping can reduce streamflow in nearby waterways (‘streamflow depletion’), a process which must be accounted for in integrated management of surface and groundwater resources. However, causal identification of streamflow depletion from hydrographs alone is challenging because pumping impacts are masked by other drivers of hydrologic variability. To identify potential indicators of streamflow depletion, we used synthetic hydrographs and an analytical streamflow depletion model to assess potential pumping impacts on specific hydrograph characteristics (‘hydrologic signatures’) for 215 streamgages spanning the conterminous United States (CONUS). We found that streamflow depletion commonly impacts signatures associated with seasonal and annual low flows and low flow recessions. The largest impacts occurred during dry years, suggesting streamflow depletion may be evident in dry years even where impacts are unmeasurable in wet years. Random forest models indicated that streamflow depletion could significantly impact Annual, Summer, and Fall signatures in most streams. Our finding that multiple hydrologic signatures are consistently responsive to streamflow depletion across CONUS suggests that the underlying hydrological processes linking pumping to streamflow reductions are consistent across diverse settings, information that will aid in identifying indicators of streamflow depletion from streamflow hydrographs.

Hydrological Processes↗
USGS2024

Solute export patterns across the contiguous USA

Understanding controls on solute export to streams is challenging because heterogeneous catchments can respond uniquely to drivers of environmental change. To understand general solute export patterns, we used a large-scale inductive approach to evaluate concentration–discharge (C–Q) metrics across catchments spanning a broad range of catchment attributes and hydroclimatic drivers. We leveraged paired C–Q data for 11 solutes from CAMELS-Chem, a database built upon an existing dataset of catchment and hydroclimatic attributes from relatively undisturbed catchments across the contiguous USA. Because C–Q relationships with Q thresholds reflect a shift in solute export dynamics and are poorly characterized across solutes and diverse catchments, we analysed C–Q relationships using Bayesian segmented regression to quantify Q thresholds in the C–Q relationship. Threshold responses were rare, representing only 12% of C–Q relationships, 56% of which occurred for solutes predominantly sourced from bedrock. Further, solutes were dominated by one or two C–Q patterns that reflected vertical solute–source distributions. Specifically, solutes predominantly sourced from bedrock had diluting C–Q responses in 43%–70% of catchments, and solutes predominantly sourced from soils had more enrichment responses in 35%–51% of catchments. We also linked C–Q relationships to catchment and hydroclimatic attributes to understand controls on export patterns. The relationships were generally weak despite the diversity of solutes and attribute types considered. However, catchment and hydroclimatic attributes in the central USA typically drove the most divergent export behaviour for solutes. Further, we illustrate how our inductive approach generated new hypotheses that can be tested at discrete, representative catchments using deductive approaches to better understand the processes underlying solute export patterns. Finally, given these long-term C–Q relationships are from minimally disturbed catchments, our findings can be used as benchmarks for change in more disturbed catchments.

contiguous United States↗
USGS2004

Are big basins just the sum of small catchments?

Many challenges remain in extending our understanding of how hydrologic processes within small catchments scale to larger river basins. In this study we examine how low-flow runoff varies as a function of basin scale at 11 catchments, many of which are nested, in the 176 km2 Neversink River watershed in the Catskill Mountains of New York. Topography, vegetation, soil and bedrock structure are similar across this river basin, and previous research has demonstrated the importance of deep groundwater springs for maintaining low-flow stream discharge at small scales in the basin. Therefore, we hypothesized that deep groundwater would contribute an increasing amount to low-flow discharge as basin scale increased, resulting in increased runoff. Instead, we find that, above a critical basin size of 8 to 21 km2, low-flow runoff is similar within the Neversink watershed. These findings are broadly consistent with those of a previous study that examined stream chemistry as a function of basin scale for this watershed. However, we find physical evidence of self-similarity among basins greater than 8 km2, whereas the previous study found gradual changes in stream chemistry among basins greater than 3 km 2. We believe that a better understanding of self-similarity and the subsurface flow processes that affect stream runoff will be attained through simultaneous consideration of both chemical and physical evidence. We also suggest that similar analyses of stream runoff in other basins that represent a range of spatial scales, geomorphologies and climate conditions will further elucidate the issue of scaling of hydrologic processes. Copyright ?? 2004 John Wiley & Sons, Ltd.

Hydrological Processes↗
USGS2007

Factors controlling nitrogen release from two forested catchments with contrasting hydrochemical responses

Quantifying biogeochemical cycles of nitrogen (N) and the associated fluxes to surface waters remains challenging, given the need to deal with spatial and temporal variability and to characterize complex and heterogeneous landscapes. We focused our study on catchments S14 and S15 located in the Adirondack Mountains of New York, USA, which have similar topographic and hydrologic characteristics but contrasting stream nitrate ($\hbox{NO}_{3}^{-}$) concentrations. We characterized the mechanisms by which $\hbox{NO}_{3}^{-}$ reaches the streams during hydrological events in these catchments, aiming to reconcile our field data with our conceptual model of factors that regulate nutrient exports from forested catchments. Combined hydrometric, chemical and isotopic (δ$\hbox{NO}_{3}^{-}$) data showed that the relative contributions of both soil and ground water sources were similar between the two catchments. Temporal patterns of stream chemistry were markedly different between S14 and S15, however, because the water sources in the two catchments have different solute concentrations. During late summer/fall, the largest source of $\hbox{NO}_{3}^{-}$ in S14 was till groundwater, whereas shallow soil was the largest $\hbox{NO}_{3}^{-}$ source in S15. $\hbox{NO}_{3}^{-}$ concentrations in surface water decreased in S14, whereas they increased in S15 because an increasing proportion of stream flow was derived from shallow soil sources. During snowmelt, the largest sources of $\hbox{NO}_{3}^{-}$were in the near‐surface soil in both catchments. Concentrations of $\hbox{NO}_{3}^{-}$ increased as stream discharge increased and usually peaked before peak discharge, when shallow soil water sources made the largest contribution to stream discharge. The timing of peaks in stream $\hbox{NO}_{3}^{-}$concentrations was affected by antecedent moisture conditions. By elucidating the factors that affect sources and transport of N, including differences in the soil nutrient cycling and hydrological characteristics of S14 and S15, this study contributes to the overall conceptualization of $\hbox{NO}_{3}^{-}$ release from temperate forested catchments.

Hydrological Processes↗
USGS2008

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

Hydrological Processes↗
USGS2024

An intercomparison of DOC estimated from fDOM sensors in wildfire affected streams of the western United States

Wildfires in the western United States (US) have been demonstrated to affect water quality, including dissolved organic carbon (DOC), in streams. Elevated post-wildfire DOC concentration poses a potential risk to drinking water treatment systems. In-stream measurements of fluorescent dissolved organic matter (fDOM), a proxy for DOC, have shown potential to detect dynamic changes in DOC. High frequency monitoring of water temperature, turbidity, and fDOM was used in conjunction with discrete sampling during targeted storm events and at fixed intervals to estimate DOC in five western US streams following wildfires in 2020 and 2021 with the objective to characterise and compare responses to wildfire among sites. The elevated turbidity conditions typical after wildfire presented a challenge to fDOM measurements and there was a need to identify appropriate turbidity corrections at burned sites. A combination of established and novel methods corrected fDOM concentrations for turbidity effects up to 800 Formazin nephelometric units (FNU). Pre-wildfire high frequency water quality data in adjacent burned and unburned watersheds allowed for separation of climate effects on DOC at one of the sites. Hydrology, climate and landcover were more important drivers of post-wildfire DOC yield than wildfire characteristics. Seasonal patterns of DOC were unchanged by wildfire in snowmelt-driven watersheds. Large, transient spikes in DOC concentration following frontal and convective storms were observed post-wildfire at all burned sites, but not at the unburned site. These spikes often exceeded operational thresholds for drinking water treatment. This study highlights the ability to develop high frequency DOC estimates in surface waters up to 800 FNU using fDOM sensors and targeted storm sampling and emphasises the value of high frequency pre-wildfire data in adjacent burned and unburned watersheds for separating climate and wildfire effects.

California, Colorado, Montana, Oregon↗
USGS2025

Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management

Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.

Hydrological Processes↗
USGS2010

Gypsies in the palace: Experimentalist's view on the use of 3-D physics-based simulation of hillslope hydrological response

As a fundamental unit of the landscape, hillslopes are studied for their retention and release of water and nutrients across a wide range of ecosystems. The understanding of these near-surface processes is relevant to issues of runoff generation, groundwater-surface water interactions, catchment export of nutrients, dissolved organic carbon, contaminants (e.g. mercury) and ultimately surface water health. We develop a 3-D physics-based representation of the Panola Mountain Research Watershed experimental hillslope using the TOUGH2 sub-surface flow and transport simulator. A recent investigation of sub-surface flow within this experimental hillslope has generated important knowledge of threshold rainfall-runoff response and its relation to patterns of transient water table development. This work has identified components of the 3-D sub-surface, such as bedrock topography, that contribute to changing connectivity in saturated zones and the generation of sub-surface stormflow. Here, we test the ability of a 3-D hillslope model (both calibrated and uncalibrated) to simulate forested hillslope rainfall-runoff response and internal transient sub-surface stormflow dynamics. We also provide a transparent illustration of physics-based model development, issues of parameterization, examples of model rejection and usefulness of data types (e.g. runoff, mean soil moisture and transient water table depth) to the model enterprise. Our simulations show the inability of an uncalibrated model based on laboratory and field characterization of soil properties and topography to successfully simulate the integrated hydrological response or the distributed water table within the soil profile. Although not an uncommon result, the failure of the field-based characterized model to represent system behaviour is an important challenge that continues to vex scientists at many scales. We focus our attention particularly on examining the influence of bedrock permeability, soil anisotropy and drainable porosity on the development of patterns of transient groundwater and sub-surface flow. Internal dynamics of transient water table development prove to be essential in determining appropriate model parameterization. ?? 2010 John Wiley & Sons, Ltd.

Hydrological Processes↗
USGS2011

Investigating the spatial distribution of water levels in the Mackenzie Delta using airborne LiDAR

Airborne light detection and ranging (LiDAR) data were used to map water level (WL) and hydraulic gradients (δH/δx) in the Mackenzie Delta. The LiDAR WL data were validated against eight independent hydrometric gauge measurements and demonstrated mean offsets from − 0·22 to + 0·04 m (σ< 0·11). LiDAR‐based WL gradients could be estimated with confidence over channel lengths exceeding 5–10 km where the WL change exceeded local noise levels in the LiDAR data. For the entire Delta, the LiDAR sample coverage indicated a rate of change in longitudinal gradient (δ 2 H/δx) of 5·5 × 10 −10 m m −2 ; therefore offering a potential means to estimate average flood stage hydraulic gradient for areas of the Delta not sampled or monitored. In the Outer Delta, within‐channel and terrain gradient measurements all returned a consistent estimate of − 1 × 10 −5 m m −1 , suggesting that this is a typical hydraulic gradient for the downstream end of the Delta. For short reaches (<10 km) of the Peel and Middle Channels in the middle of the Delta, significant and consistent hydraulic gradient estimates of − 5 × 10 −5 m m −1 were observed. Evidence that hydraulic gradients can vary over short distances, however, was observed in the Peel Channel immediately upstream of Aklavik. A positive elevation anomaly (bulge) of > 0·1 m was observed at a channel constriction entering a meander bend, suggesting a localized modification of the channel hydraulics. Furthermore, water levels in the anabranch channels of the Peel River were almost 1 m higher than in Middle Channel of the Mackenzie River. This suggests: (i) the channels are elevated and have shallower bank heights in this part of the delta, leading to increased cross‐delta and along‐channel hydraulic gradients; and/or (ii) a proportion of the Peel River flow is lost to Middle Channel due to drainage across the delta through anastamosing channels. This study has demonstrated that airborne LiDAR data contain valuable information describing Arctic river delta water surface and hydraulic attributes that would be challenging to acquire by other means.

Mackenzie Delta↗
USGS2016

Restoration of impaired ecosystems: An ounce of prevention or a pound of cure? introduction, overview, and key messages from a SETAC-SER workshop

A workshop on Restoration of Impaired Ecosystems was held in Jackson, Wyoming, in June 2014. Experts from Australia, Canada, Mexico, the United Kingdom, and the United States in ecotoxicology, restoration, and related fields from both the Society of Environmental Toxicology and Chemistry and the Society for Ecological Restoration convened to advance the practice of restoring ecosystems that have been contaminated or impaired from industrial activities. The overall goal of this workshop was to provide a forum for ecotoxicologists and restoration ecologists to define the best scientific practices to achieve ecological restoration while addressing contaminant concerns. To meet this goal, participants addressed 5 areas: 1) links between ecological risk assessment and ecological restoration, 2) restoration goals, 3) restoration design, 4) monitoring for restoration effectiveness and 5) recognizing opportunities and challenges. Definitions are provided to establish a common language across the varied disciplines. The current practice for addressing restoration of impaired ecosystems tends to be done sequentially to remediate contaminants, then to restore ecological structure and function. A better approach would anticipate or plan for restoration throughout the process. By bringing goals to the forefront, we may avoid intrusive remediation activities that close off options for the desired restoration. Participants realized that perceived limitations in the site assessment process hinder consideration of restoration goals; contaminant presence will influence restoration goal choices; social, economic, and cultural concerns can factor into goal setting; restoration options and design should be considered early during site assessment and management; restoration of both structure and function is encouraged; creative solutions can overcome limitations; a regional focus is imperative; monitoring must occur throughout the restoration process; and reciprocal transfer of knowledge is needed among theorists, practitioners, and stakeholders and among varied disciplines.

Integrated Environmental Assessment and Management↗
USGS2019

Scientific integrity issues in environmental toxicology and chemistry: Improving research transparency, reproducibility, and credibility

High‐profile reports of detrimental scientific practices leading to retractions in the scientific literature contribute to lack of trust in scientific experts. Although the bulk of these have been in the literature of other disciplines, environmental toxicology and chemistry are not free from problems. While we believe that egregious misconduct such as fraud, fabrication of data, or plagiarism is rare, scientific integrity is much broader than the absence of misconduct. We are more concerned with more commonly encountered and nuanced issues such as poor reliability and bias. We review a range of topics including conflicts of interests, competing interests, some particularly challenging situations, reproducibility, bias, and other attributes of ecotoxicological studies that enhance or detract from scientific credibility. Our vision of scientific integrity encourages a self‐correcting culture that promotes scientific rigor, relevant reproducible research, transparency in competing interests, methods and results, and education.

Integrated Environmental Assessment and Management↗
USGS2022

Integrative monitoring strategy for marine and freshwater harmful algal blooms and toxins across the freshwater-to-marine continuum

Many coastal states throughout the USA have observed negative effects in marine and estuarine environments caused by cyanotoxins produced in inland waterbodies that were transported downstream or produced in the estuaries. Estuaries and other downstream receiving waters now face the dual risk of impacts from harmful algal blooms (HABs) that occur in the coastal ocean as well as those originating in inland watersheds. Despite this risk, most HAB monitoring efforts do not account for hydrological connections in their monitoring strategies and designs. Monitoring efforts in California have revealed the persistent detection of cyanotoxins across the freshwater-to-marine continuum. These studies underscore the importance of inland waters as conduits for the transfer of cyanotoxins to the marine environment and highlight the importance of approaches that can monitor across hydrologically connected waterbodies. A HAB monitoring strategy is presented for the freshwater-to-marine continuum to inform HAB management and mitigation efforts and address the physical and hydrologic challenges encountered when monitoring in these systems. Three main recommendations are presented based on published studies, new datasets, and existing monitoring programs. First, HAB monitoring would benefit from coordinated and cohesive efforts across hydrologically interconnected waterbodies and across organizational and political boundaries and jurisdictions. Second, a combination of sampling modalities would provide the most effective monitoring for HAB toxin dynamics and transport across hydrologically connected waterbodies, from headwater sources to downstream receiving waterbodies. Third, routine monitoring is needed for toxin mixtures at the land–sea interface including algal toxins of marine origins as well as cyanotoxins that are sourced from inland freshwater or produced in estuaries. Case studies from California are presented to illustrate the implementation of these recommendations, but these recommendations can also be applied to inland states or regions where the downstream receiving waterbody is a freshwater lake, reservoir, or river.

California, Oregon↗
USGS2022

A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI)

Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here, we describe a weight-of-evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96-h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017–2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data-limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[ a ]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data sufficient and flagged as candidates for further effects-based monitoring studies. Twenty-one compounds were identified as high or medium priority and data limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2-methylnaphthalene) displayed no data limitations and was flagged as a definitively low-priority chemical. The remaining chemicals displayed some data limitations and were considered lower-priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening-level (non-definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. Integr Environ Assess Manag 2023;00:1–21. © 2022 SETAC

Wisconsin↗
USGS2023

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects

Despite advances in toxicity testing and development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole animal toxicity tests are central to hazard assessment, non-standard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically-based risk assessments to enhance the “eco” component of ERAs. Regulatory and logistical challenges often relegate such non-standard endpoints and indirect effects to post-registration evaluations of pesticides and industrial chemicals, and contaminated site evaluations. While NAMs are being developed, to date their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole animal data and simple hazard ratios.

Integrated Environmental Assessment and Management↗
USGS2024

Survey effort and targeted landbird community metrics at Indiana lowland forest restoration sites

Many sampling and analytical methods can estimate the abundance, distributions, and diversity of birds and other wildlife. However, challenges with sample size and analytical capacity can make these methods difficult to implement for resource-limited monitoring programs. To apprise efficient and attainable sampling designs for landbird monitoring programs with limited observational data, we used breeding season bird point survey data collected in 2016 at four forest restoration sites in Indiana, USA. We evaluated three subsets of observed species richness, total possibly breeding landbirds, Partners in Flight Regional Conservation Concern (PIF RCC) landbirds, and interior forest specialists (IFSs). Simulated surveys based on field data were used to conduct Bayesian Michaelis–Menten curve analyses estimating observed species as a function of sampling effort. On comparing simulated survey sets with multiple habitat types versus those with one habitat, we found that those with multiple habitat types had estimated 39%–83% greater observed PIF RCC species richness and required 41%–55% fewer visits per point to observe an equivalent proportion of PIF RCC species. Even with multiple habitats in a survey set, the number of visits per point required to detect 50% of observable species was 30% higher for PIF RCC species than for total breeding landbird species. Low detection rates of IFS species at two field sites made precise estimation of required effort to observe these species difficult. However, qualitatively, we found that only sites containing mature forest fragments had detections of several bird species designated as high-confidence IFS species. Our results suggest that deriving specialized species diversity metrics from point survey data can add value when interpreting those data. Additionally, designing studies to collect these metrics may require explicitly planning to visit multiple habitat types at a monitoring site and increasing the number of visits per survey point.

Indiana↗