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At least 595 records · Page 33Linked to original sources

USGS2006

Assessment of factors limiting Klamath River fall Chinook salmon production potential using historical flows and temperatures

We parameterized and applied a deterministic salmon production model to infer the degree to which river flows and temperatures may limit freshwater production potential of the Klamath River in California. Specific parameter requirements, data sources, and significant assumptions are discussed in detail. Model simulations covered a wide variety of historical hydrologic and meteorologic conditions for 40+ years of environmental data. The model was calibrated only qualitatively, appearing to perform well in predicted outmigrant timing, but overestimating growth. Egg-to-outmigrant survival was near that reported for other rivers north of the Klamath River. Predicted production potential appeared to be determined by multiple causes involving both regularly occurring habitat-related constraints and irregularly occurring exposure to high water temperatures. Simulated production was greatest in years of intermediate water availability and was constrained in both dry and wet years, but for different reasons. Reducing mortality associated with limitations to juvenile habitat, if possible, would be expected to have the highest payoff in increasing production. Water temperature was important in determining predicted production in some years but overall was not predicted to be as important as physical microhabitat. No single mortality cause acted as a true “bottleneck” on production. Model uncertainty is addressed through a sensitivity analysis. Predicted habitat area may be a large source of model uncertainty and sensitivity, but collectively, model parameters associated with timing of events (for example spawning, fry emergence, and emigration) or related triggers control much of the model sensitivity. Though model uncertainty remains, one can begin to explore potential alternatives to reduce production limitations. Specific recommendations are made regarding future study and reducing uncertainty.

California, Oregon↗

USGS2018

Contaminants in tropical island streams and their biota

Environmental contamination is problematic for tropical islands due to their typically dense human populations and competing land and water uses. The Caribbean island of Puerto Rico (USA) has a long history of anthropogenic chemical use, and its human population density is among the highest globally, providing a model environment to study contaminant impacts on tropical island stream ecosystems. Polycyclic Aromatic Hydrocarbons, historic-use chlorinated pesticides, current-use pesticides, Polychlorinated Biphenyls (PCBs), and metals (mercury, cadmium, copper, lead, nickel, zinc, and selenium) were quantified in the habitat and biota of Puerto Rico streams and assessed in relation to land-use patterns and toxicological thresholds. Water, sediment, and native fish and shrimp species were sampled in 13 rivers spanning broad watershed land-use characteristics during 2009–2010. Contrary to expectations, freshwater stream ecosystems in Puerto Rico were not severely polluted, likely due to frequent flushing flows and reduced deposition associated with recurring flood events. Notable exceptions of contamination were nickel in sediment within three agricultural watersheds (range 123–336 ppm dry weight) and organic contaminants (PCBs, organochlorine pesticides) and mercury in urban landscapes. At an urban site, PCBs i n several fish species (Mountain Mullet Agonostomus monticola [range 0.019–0.030 ppm wet weight] and American Eel Anguilla rostrata [0.019–0.031 ppm wet weight]) may pose human health hazards, with concentrations exceeding the U.S. Environmental Protection Agency (EPA) consumption limit for 1 meal/month. American Eel at the urban site also contained dieldrin (range < detection-0.024 ppm wet weight) that exceeded the EPA maximum allowable consumption limit. The Bigmouth Sleeper Gobiomorous dormitor , an important piscivorus sport fish, accumulated low levels of organic contaminants in edible muscle tissue (due to its low lipid c ontent) and may be most suitable for human consumption island-wide; only mercury at one site (an urban location) exceeded EPA's consumption limit of 3 meals/month for this species. These results comprise the first comprehensive island-wide contaminant assessment of Puerto Rico streams and biota and provide natural resource and public health agencies here and in similar tropical islands elsewhere with information needed to guide ecosystem and fisheries conservation and management and human health risk assessment.

Environmental Research↗

USGS2015

Resilience and risk: a demographic model to inform conservation planning for polar bears

Climate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear ( Ursus maritimus ) and other ice-dependent marine mammals under the U.S. Endangered Species Act (ESA). Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans. We developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes density-dependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex- and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93–0.96), recruitment (number of yearling cubs per adult female; 0.1–0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years. We also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, and risk tolerance. The historical standard 4.5-percent harvest rate for polar bears, at a 2:1 male-to-female ratio, is reasonable under many biological and management conditions, although lower or higher rates may be appropriate in some cases. Our modeling results suggest that harvest of polar bears is unlikely to accelerate population declines that result from declining carrying capacity caused by sea-ice loss, provided that several conditions are met: (1) the sustainable harvest rate reflects the population’s intrinsic growth rate, and the corresponding harvest level is obtained by applying this rate to an estimate of population size; (2) the sustainable harvest rate reflects the quality of population data (e.g., lower harvest when data are poor); and (3) the level of human-caused removals can be adjusted. Finally, our results suggest that stopgap measures (e.g., further reduction or cessation of harvest when the population size is less than a critical threshold) may be necessary to minimize the incremental risk associated with harvest, if environmental conditions are deteriorating rapidly. We suggest that the demographic model and approaches presented here can serve as a template for conservation planning for polar bears and other species facing similar challenges.

Open-File Report↗

USGS2021

Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival

Moose populations in the northeastern United States have declined over the past 15 years, primarily due to the impacts of winter ticks. Research efforts have focused on the effects of winter tick infestation on moose survival and reproduction, but stress and nutritional responses to ticks and other stressors remain understudied. We examined the influence of several environmental factors on moose calf stress hormone metabolite concentrations and nutritional restriction in Vermont, USA. We collected 407 fecal and 461 snow urine samples from 84 radio-collared moose calves in the winters of 2017–2019 (January–April) to measure fecal glucocorticoid metabolites (fGCM) concentrations and urea nitrogen:creatinine (UN:C) ratios. We used generalized mixed-effects models to evaluate the influence of individual condition, winter ticks, habitat, climate and human development on stress and nutrition in calf moose. We then used these physiological data to build generalized linear models to predict calf winter survival. Calf fGCM concentrations increased with nutritional restriction and snow depth during adult winter tick engorgement. Calf UN:C ratios increased in calves with lighter weights and higher tick loads in early winter. Calf UN:C ratios also increased in individuals with home ranges composed of little deciduous forests during adult winter tick engorgement. Our predictive models estimated that winter survival was negatively related to UN:C ratios and positively related to fGCM concentrations, particularly in early winter. By late March, as winter ticks are having their greatest toll and endogenous resources become depleted, we estimated a curvilinear relationship between fGCM concentrations and survival. Our results provide novel evidence linking moose calf stress and nutrition, a problematic parasite and challenging environment and winter survival. Our findings provide a baseline to support the development of non-invasive physiological monitoring for assessing environmental impacts on moose populations.

Vermont↗

USGS2018

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗

USGS2026

Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions

Our understanding of the impacts of climate change, sea-level rise (SLR), and freshwater management on the magnitude and variability of carbon fluxes in tidal forested wetlands remains limited. In this study, we applied a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool—DeNitrification-DeComposition (WCAT-DNDC) model to explore responses of carbon fluxes in tidal swamp forests to climate change-induced alterations in hydrologic conditions and to predict impacts of planned reintroduction of river flows. We selected twelve sites in three habitats (throughput, relict, degraded) inside the Lake Maurepas swamp forests (Louisiana, USA) to represent various hydrological and salinity regimes. Environmental scenarios included dry, average, and wet conditions, SLR (low and high), and a Mississippi River (MR) diversion. Simulation results showed that the responses of net ecosystem exchange (NEE), net primary productivity (NPP), ecosystem respiration (ER), methane (CH 4 ) and nitrous oxide (N 2 O) emissions in the Lake Maurepas swamp forests varied substantially among sites. However, the overall net carbon uptake capacity of the Lake Maurepas swamp forests was high (NEE: − 1143 to − 1650 g C m −2 yr −1 ), suggesting that Lake Maurepas swamp forests are large carbon sinks. The high net carbon uptake capacity could be significantly affected by climate change induced drought, flooding, and SLR with the bi-directional changes (increase or decrease) depending on the direction and magnitude of the hydrologic regime changes. The response of the net carbon uptake capacity to MR diversion is also bi-directional and site-specific, but enhancement of the capacity of NEE of up to − 1957 g C m 2 yr −1 is possible, implying that MR diversion into the swamp forests could be beneficial in the context of carbon cycling and carbon sequestration.

Louisiana↗

USGS2025

Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations

Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.

Environmental Data Science↗

USGS2014

Effects of fine sediment, hyporheic flow, and spawning site characteristics on survival and development of bull trout embryos

Successful spawning is imperative for the persistence of salmonid populations, but relatively little research has been conducted to evaluate factors affecting early life-stage survival for bull trout ( Salvelinus confluentus ), a threatened char. We conducted a field experiment to assess the relationship between site-specific environmental factors and bull trout embryo survival and fry emergence timing. Survival from egg to hatch was negatively related to percent fine sediment (<1 mm) in the redd and positively related to the strength of downwelling at spawning sites. Survival of eggs to fry emergence was also negatively related to fine sediment, and the best statistical models included additional variables that described the rate of downwelling and intragravel flow within the incubation environment. Fry emerged at an earlier stage in development from redds with high percentages of fine sediment. Increased hydraulic conductivity via redd construction and selection of spawning sites with strong downwelling appear to enhance hyporheic flow rates and bull trout egg survival, but early life-stage success may ultimately be limited by intrusion of fine sediment into the incubation environment.

Oregon↗

USGS2000

Hydrogeology and simulation of ground-water flow at the Gettysburg Elevator Plant Superfund Site, Adams County, Pennsylvania

Ground water in Triassic-age sedimentary fractured-rock aquifers in the area of Gettysburg, Pa., is used as drinking water and for industrial and commercial supply. In 1983, ground water at the Gettysburg Elevator Plant was found by the Pennsylvania Department of Environmental Resources to be contaminated with trichloroethene, 1,1,1-trichloroethane, and other synthetic organic compounds. As part of the U.S. Environmental Protection Agency?s Comprehensive Environmental Response, Compensation, and Liability Act, 1980 process, a Remedial Investigation was completed in July 1991, a method of site remediation was issued in the Record of Decision dated June 1992, and a Final Design Report was completed in May 1997. In cooperation with the U.S. Environmental Protection Agency in the hydrogeologic assessment of the site remediation, the U.S. Geological Survey began a study in 1997 to determine the effects of the onsite and offsite extraction wells on ground-water flow and contaminant migration from the Gettysburg Elevator Plant. This determination is based on hydrologic and geophysical data collected from 1991 to 1998 and on results of numerical model simulations of the local ground-water flow-system. The Gettysburg Elevator Site is underlain by red, green, gray, and black shales of the Heidlersburg Member of the Gettysburg Formation. Correlation of natural-gamma logs indicates the sedimentary rock strike about N. 23 degrees E. and dip about 23 degrees NW. Depth to bedrock onsite commonly is about 6 feet but offsite may be as deep as 40 feet. The ground-water system consists of two zones?a thin, shallow zone composed of soil, clay, and highly weathered bedrock and a thicker, nonweathered or fractured bedrock zone. The shallow zone overlies the bedrock zone and truncates the dipping beds parallel to land surface. Diabase dikes are barriers to ground-water flow in the bedrock zone. The ground-water system is generally confined or semi-confined, even at shallow depths. Depth to water can range from flowing at land surface to more than 71 feet below land surface. Potentiometric maps based on measured water levels at the Gettysburg Elevator Plant indicate ground water flows from west to east, towards Rock Creek. Multiple-well aquifer tests indicate the system is heterogeneous and flow is primarily in dipping beds that contain discrete secondary openings separated by less permeable beds. Water levels in wells open to the pumped bed, as projected along the dipping stratigraphy, are drawn down more than water levels in wells not open to the pumped bed. Ground-water flow was simulated for steady-state conditions prior to pumping and long-term average pumping conditions. The three-dimensional numerical flow model (MODFLOW) was calibrated by use of a parameter estimation program (MODFLOWP). Steady-state conditions were assumed for the calibration period of 1996. An effective areal recharge rate of 7 inches was used in model calibration. The calibrated flow model was used to evaluate the effectiveness of the current onsite and offsite extraction well system. The simulation results generally indicate that the extraction system effectively captures much of the ground-water recharge at the Gettysburg Elevator Plant and, hence, contaminated ground-water migrating from the site. Some of the extraction wells pump at low rates and have very small contributing areas. Results indicate some areal recharge onsite will move to offsite extraction wells.

Pennsylvania↗

USGS2009

Hydrogeology and Ground-Water Flow in the Opequon Creek Watershed area, Virginia and West Virginia

Due to increasing population and economic development in the northern Shenandoah Valley of Virginia and West Virginia, water availability has become a primary concern for water-resource managers in the region. To address these issues, the U.S. Geological Survey (USGS), in cooperation with the West Virginia Department of Health and Human Services and the West Virginia Department of Environmental Protection, developed a numerical steady-state simulation of ground-water flow for the 1,013-square-kilometer Opequon Creek watershed area. The model was based on data aggregated for several recently completed and ongoing USGS hydrogeologic investigations conducted in Jefferson, Berkeley, and Morgan Counties in West Virginia and Clarke, Frederick, and Warren Counties in Virginia. A previous detailed hydrogeologic assessment of the watershed area of Hopewell Run (tributary to the Opequon Creek), which includes the USGS Leetown Science Center in Jefferson County, West Virginia, provided key understanding of ground-water flow processes in the aquifer. The ground-water flow model developed for the Opequon Creek watershed area is a steady-state, three-layer representation of ground-water flow in the region. The primary objective of the simulation was to develop water budgets for average and drought hydrologic conditions. The simulation results can provide water managers with preliminary estimates on which water-resource decisions may be based. Results of the ground-water flow simulation of the Opequon Creek watershed area indicate that hydrogeologic concepts developed for the Hopewell Run watershed area can be extrapolated to the larger watershed model. Sensitivity analyses conducted as part of the current modeling effort and geographic information system analyses of spring location and yield reveal that thrust and cross-strike faults and low-permeability bedding, which provide structural and lithologic controls, respectively, on ground-water flow, must be incorporated into the model to develop a realistic simulation of ground-water flow in the larger Opequon Creek watershed area. In the model, recharge for average hydrologic conditions was 689 m3/d/km2 (cubic meters per day per square kilometer) over the entire Opequon Creek watershed area. Mean and median measured base flows at the streamflow-gaging station on the Opequon Creek near Martinsburg, West Virginia, were 604,384 and 349,907 m3/d (cubic meters per day), respectively. The simulated base flow of 432,834 m3/d fell between the mean and median measured stream base flows for the station. Simulated base-flow yields for subwatersheds during average conditions ranged from 0 to 2,643 m3/d/km2, and the median for the entire Opequon Creek watershed area was 557 m3/d/km2. A drought was simulated by reducing model recharge by 40 percent, a rate that approximates the recharge during the prolonged 16-month drought that affected the region from November 1998 to February 2000. Mean and median measured streamflows for the Opequon Creek watershed area at the Martinsburg, West Virginia, streamflow-gaging station during the 1999 drought were 341,098 and 216,551 m3/d, respectively. The simulated drought base flow at the station of 252,356 m3/d is within the range of flows measured during the 1999 drought. Recharge was 413 m3/d/km2 over the entire watershed during the simulated drought, and was 388 m3/d/km2 at the gaging station. Simulated base-flow yields for drought conditions ranged from 0 to 1,865 m3/d/km2 and averaged 327 m3/d/km2 over the entire Opequon Creek watershed. Water budgets developed from the simulation results indicate a substantial component of direct ground-water discharge to the Potomac River. This phenomenon had long been suspected but had not been quantified. During average conditions, approximately 564,176 m3/d of base flow discharges to the Potomac River. An additional 124,379 m3/d of ground water is also estimated to discharge directly to the Potomac River and rep

Scientific Investigations Report↗

USGS2005

The no-project alternative analysis: An early product of the Tahoe Decision Support System

We report on the development of a No-project alternative analysis (NPAA) or “business as usual” scenario with respect to a 20-year projection of 21 indicators of environmental and socioeconomic conditions in the Lake Tahoe Basin for the Tahoe Regional Planning Agency (TRPA). Our effort was inspired by earlier work that investigated the tradeoffs between an environmental and an economic objective. The NPAA study has implications for a longer term goal of building a Tahoe Decision Support System (TDSS) to assist the TRPA and other Basin agencies in assessing the outcomes of management strategies. The NPAA assumes no major deviations from current management practices or from recent environmental or societal trends and planned Environmental Improvement Program (EIP) projects. Quantitative “scenario generation” tools were constructed to simulate site-specific land uses, various population categories, and associated vehicle miles traveled. Projections of each indicator’s attainment status were made by building visual conceptual models of the relevant natural and social processes, extrapolating trends, and using available models, research, and expert opinion. We present results of the NPAA, projected indicator status, key factors affecting the indicators, indicator functionality, and knowledge gaps. One important result is that current management practices may slow the loss or degradation of environmental qualities but not halt or reverse it. Our analysis also predicts an increase in recreation and commuting into and within the basin, primarily in private vehicles. Private vehicles, which are a critical mechanism by which the Basin population affects the surrounding environment, are a key determinant of air-quality indicators, a source of particulate matter affecting Secchi depth, a source of noise, and a factor in recreational and scenic quality, largely owing to congestion. Key uncertainties in the NPAA include climate change, EIP project effectiveness, and external population, economic activity, and air pollution.

Lake Tahoe Basin↗

USGS2008

Coastal Louisiana ecosystem assessment and restoration program: The role of ecosystem forecasting in evaluating restoration planning in the Mississippi River Deltaic Plain

The development of ecosystem management plans to restore and rehabilitate natural resources requires an understanding of how specific ecological mechanisms regulate the structure and function of ecosystems. To achieve restoration goals, comprehensive plans and engineering designs must effectively change environmental drivers at the regional level to reduce stress conditions at the local environment that are responsible for ecosystem degradation. This document focuses on the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) ecosystem forecasting framework and how it can be used to support the analysis of Louisiana’s coastal restoration plans. Specifically, the framework is designed to (1) develop and incorporate conceptual ecological models that can be used to integrate ecological needs and opportunities with engineering designs, (2) utilize wetland loss rates to describe the most likely “future without” scenario for a variety of ecosystem attributes, (3) estimate broad ecosystem responses to restoration alternatives based on processes associated with succession of geomorphic and ecological systems, and (4) calculate ecological benefits for incorporation into decision support tools associated with large-scale geomorphic and hydrologic processes. This paper provides a brief overview of the spatial framework and modular design of the CLEAR ecosystem forecasting framework and describes in greater detail the evolution of the landscape change module, concepts for its refinement, and how it was utilized in evaluating a coastal restoration alternative proposed in the Coastal Protection and Restoration Authority Preliminary Draft Master Plan. Such projections by the CLEAR forecasting framework can evaluate processes and conditions that result in sustainable coastal ecosystems with habitat functions that support higher trophic levels.

Louisiana↗

USGS2015

Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

Conference Paper↗

USGS2015

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2 °C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery.

Wisconsin↗

USGS2015

Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline

Aim Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making. Location Oregon and Washington, USA. Methods We developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km 2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines. Results Forest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis ( Myotis thysanodes ), canyon bat ( Parastrellus hesperus ) and pallid bat ( Antrozous pallidus ) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience. Main conclusions Landscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.

Oregon, Washington↗

USGS2026

Groundwater source water assessment area delineation of public supply wells in the Treasure Valley, western Idaho

The Idaho Department of Environmental Quality (IDEQ) is responsible for assessing the source water for public water supply systems including the delineation of source water assessment areas for wells, which are defined as the subsurface areas contributing water to a well during a period of time. Part of the IDEQ assessment plan is to update source water assessments over time. The U.S. Geological Survey (USGS) developed a new groundwater-flow model for part of the western Snake River Plain aquifer in southwestern Idaho. This groundwater- flow model provided a new opportunity for IDEQ to update source water assessment for public water supply wells within the model boundary. The USGS, in cooperation with IDEQ, used the USGS Treasure Valley Groundwater Flow Model along with a MODPATH particle tracking post-processing program to reassess public-water supply source water assessment areas. The USGS created an automated script that requests a well location, depth, and pumpage rate, and then incorporates that information into the Treasure Valley Groundwater Flow Model combined with the MODPATH model to create 3-, 6-, and 10-year time of travel zones that are output to a geographic information system shapefile. The TVSWA_Delineator script provides a fast, transparent tool for IDEQ to reassess or create new public-water supply source water assessment area delineations based on new and updated information and is available as a Python script and a Windows executable with the compiled script and all necessary components. TVSWA_Delineator utilizes a quadtree approach to rediscretize the Treasure Valley Groundwater Flow Model grid around the pumping well location from 1-mile cell lengths telescoped down to 1/16 mile. This rediscretization increases the source water assessment area delineation resolution near the pumping well and minimizes the effect of weak sinks in the MODPATH model. The stress inputs for each month of the final 10 years (2006 to 2015) of the Treasure Valley Groundwater Flow model historical simulation were averaged for the particle tracking analysis. The MODPATH model used backwards tracking of particles released at each stress period to create the source water assessment area delineations. This report documents the creation of the TVSWA_Delineator Python script, including adaptations made to the Treasure Valley Groundwater Flow Model, creation of a companion MODPATH model, and post-processing results to provide source water assessment areas.

Idaho↗

USGS2025

Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks

Objective Although conserving fish biodiversity in lotic systems is challenging, protected areas can provide refuge from certain environmental stressors. In the Appalachian region, USA, the National Park Service manages Delaware Water Gap National Recreation Area (DEWA) and New River Gorge National Park & Preserve (NERI), which contain abundant and diverse freshwater resources. To assess the effectiveness of these protected areas in conserving stream fishes, we evaluated decadal changes and ecological drivers of species occupancy and detection. Methods Using fish assemblage data from backpack electrofishing surveys conducted in both parks during 2013–2014 and 2022–2023, we quantified temporal differences in species occupancy and detection probabilities using a Bayesian hierarchical multispecies occupancy modeling approach. For the 2022–2023 survey, we included habitat variables as predictors of occupancy and detection. Results Community composition and occupancy probabilities for species in both parks remained similar through time, with the most recent occupancy estimates ranging from 0.07 (90% CI = 0.02, 0.14) for Variegate Darter Etheostoma variatum and Rainbow Darter E. caeruleum to 0.73 (90% credible interval = 0.59, 0.85) for Blacknose Dace Rhinichthys atratulus . Changes in occupancy were more prominent at Delaware Water Gap National Recreation Area than New River Gorge National Park & Preserve, with Yellow Perch Perca flavescens having a posterior mean difference of −0.17 [90% credible interval = −0.35, −0.01] and American Eel Anguilla rostrata having a high posterior probability (>80%) of occupancy increasing by at least 1%. Habitat variables were related to community structure, but effects varied in significance, magnitude, and direction among species and parks. Conversely, species-specific detection probabilities were comparatively less affected by environmental and sampling effort predictors. Conclusions Between 2013 and 2023, occupancy estimates for 44 fish species across two protected, ecologically diverse landscapes remained relatively stable. Furthermore, we highlight the efficacy of national parks in maintaining freshwater fish biodiversity amidst rapid global change.

New Jersey, Pennsylvania, West Virginia↗

USGS2014

Human infrastructure and invasive plant occurrence across rangelands of southwestern Wyoming, U.S.A.

Although human influence across rural landscapes is often discussed, interactions between the native, natural systems and human activities are challenging to measure explicitly. We assessed the distribution of introduced, invasive species as related to anthropogenic infrastructure and environmental conditions across southwestern Wyoming. to discern direct correlations as well as covariate influences between land use, land cover, and abundance of invasive plants, and assess the supposition that these features affect surrounding rangeland conditions. Our sample units were 1 000 m long and extended outward from target features, which included roads, oil and gas well pads, pipelines, power lines, and featureless background sites. Sample sites were distributed across the region using a stratified, random design with a frame that represented features and land-use intensity. In addition to land-use gradients, we captured a representative, but limited, range of variability in climate, soils, geology, topography, and dominant vegetation. Several of these variables proved significant, in conjunction with distance from anthropogenic features, in regression models of invasive plant abundance. We used general linear models to demonstrate and compare associations between invasive plant frequency and Euclidian distance from features, natural logarithm transformed distances (log-linear), and environmental variables which were presented as potential covariates. We expected a steep curvilinear (log or exponential) decline trending towards an asymptote along the axis representing high abundance near features with rapid decrease beyond approximately 50–100 m. Some of the associations we document exhibit this pattern, but we also found some invasive plant distributions that extended beyond our expectations, suggesting a broader distribution than anticipated. Our results provide details that can inform local efforts for management and control of invasive species, and they provide evidence of the different associations between natural patterns and human land use exhibited by nonnative species in this rural setting, such as the indirect effects of humans beyond impact areas.

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