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At least 1,171 records · Page 65Linked to original sources
USGS2024

Variability in weather and site properties affect fuel and fire behavior following fuel treatments in semiarid sagebrush-steppe.

Fuel-treatments targeting shrubs and fire-prone exotic annual grasses (EAGs) are increasingly used to mitigate increased wildfire risks in arid and semiarid environments, and understanding their response to natural factors is needed for effective landscape management. Using field-data collected over four years from fuel-break treatments in semiarid sagebrush-steppe, we asked 1) how the outcomes of EAG and sagebrush fuel treatments varied with site biophysical properties, climate, and weather, and 2) how predictions of fire behavior using the Fuel Characteristic Classification System fire model related to land-management objectives of maintaining fire behavior expected of low-load, dry-climate grasslands. Generalized linear mixed effect modeling with build-up model selection was used to determine best-fit models, and marginal effects plots to assess responses for each fuel type. EAG cover decreased as antecedent-fall precipitation increased and increased as antecedent-spring temperatures and surface soil clay contents increased. Herbicides targeting EAGs were less effective where pre-treatment EAG cover was >40 % and antecedent spring temperatures were >9.5 °C. Sagebrush cover was inversely related to soil clay content, especially where clay contents were >17 %. Predicted fire behavior exceeded management objectives under 1) average fire weather conditions when EAG or sagebrush cover was >50 % or >26 %, respectively, or 2) extreme fire weather conditions when EAG or sagebrush cover was >10 % or >8 %, respectively. Consideration of the strong effects of natural variability in site properties and antecedent weather can help in justifying, planning and implementing fuel-treatments.

Idaho, Oregon↗
USGS2022

Predictive models of selective cattle use of large, burned landscapes in semiarid sagebrush-steppe

The fire-exotic annual grass cycle is a severe threat to shrub-steppe rangelands, and a greater understanding of how livestock grazing relates to the problem is needed to guide effective management interventions. Grazing effects vary throughout shrub-steppe rangelands because livestock are selective in their use within pastures. Thus, knowing where cattle are located and concentrate their use in a postfire landscape is important for enhancing plant community resiliency to disturbance and resistance to exotic annual grass invasion. We asked how the distribution and intensity of cattle use varied across 113 000 ha of recently burned, environmentally varied shrub-steppe. Generalized linear mixed effects models were used to determine the relationship of cattle dung (presence/absence and counts), which was recorded during the third to fifth postfire year (after grazing deferment) on 1166 (531-m 2 ) plots, to water sources, burn severity, grass cover, and topographic predictors. Our distribution and intensity of use models revealed similar relationships between cattle use and landscape predictors. Cattle use was greater in areas that were flatter and closer to water and that had moderate burn severity and less heat load and ruggedness. Slope had the strongest effect on cattle use of the predictors. The probability of cattle being present decreased by 10% for every 5° increase in slope until slope exceeded 15°, and then the effect of slope weakened. Despite moderate slopes χ ¯ "> χ¯ = 14°), cattle use was greater in areas of moderate burn severity, presumably because these areas provided greater perennial grass production. While there was much unexplained variation, these models suggest that cooler climate, water access, topographic factors, and burn severity affect maneuverability to create greater livestock use of certain areas within grazing pastures. Restoration investment planning or assessments and expectations of restoration success could be improved by considering that these livestock hotspots may recover differently from the surrounding landscape.

Rangeland Ecology and Management↗
USGS2019

Geological and geophysical data for a three-dimensional view—Inside the San Juan and Silverton Calderas, Southern Rocky Mountains Volcanic Field, Silverton, Colorado

Introduction The San Juan-Silverton caldera complex located near Silverton, Colorado, in the Southern Rocky Mountains volcanic field is an ideal natural laboratory for furthering the understanding of shallow-to-deep volcanic-related mineral systems. Recent advances in geophysical data processing and three-dimensional (3D) model construction will help to characterize shallow properties important for understanding surface water and groundwater quality issues and will also improve knowledge of deep geological structures that may have been conduits for hydrothermal fluids that formed mineral deposits. The study has general applications to mineral resource assessments in other areas of the world and to identifying possible groundwater flow paths and associated geochemistry important in abandoned mine lands cleanup. Silverton, Colorado, is the site of a spectacular succession of igneous rocks that formed beginning about 35 million years ago (Ma). Base metals (copper, lead, and zinc) and precious metals (silver and gold) mined from the late 1870s to 1991 owe their existence to a 25-million-year cycle of igneous activity. The presence of economic, base, and precious metal deposits within a complex geological setting were largely responsible for stimulating studies by the U.S. Geological Survey (USGS) conducted during the early 20th century. The focus of investigations in the late 20th and 21st centuries have broadened in scope to include abandoned mine lands (AML) investigations. The legacy of hard rock mining in headwater catchment areas caused environmental challenges for local communities and downstream water resource users. The Gold King Mine, located a few kilometers north of Silverton, illustrates the potential environmental effects of abandoned mines. On August 5, 2015, during reclamation efforts at the Gold King Mine, a breach of collapsed workings sent approximately 3 million gallons of acidic and metal-rich mine water into the upper Animas River, a tributary to the Colorado River Basin. Mining-related sources of metals and acidity add to geological sources of metals in surface water and groundwater. Weathering processes of altered and mineralized rock have been a source of acid rock drainage that have been ongoing for millennia.

Colorado↗
USGS2005

Water-quality assessment of part of the Upper Mississippi River Basin, Minnesota and Wisconsin — Ground-water quality along a flow system in the Twin Cities metropolitan area, Minnesota, 1997-98

As part of a national analysis of the effects of land use on ground-water quality for the National Water-Quality Assessment Program, the U.S. Geological Survey sampled wells along a flow system in surficial glacial aquifers in the northwestern part of the Twin Cities metropolitan area during 1997 and 1998. In addition, a reconnaissance steady-state ground-water model was developed to estimate flowpaths and dates of ground-water recharge using a particle-tracking routine. Sediment samples collected during drilling had high horizontal hydraulic conductivities (ranging from about 3.1 to about 190 feet per day, based on sediment-size analysis of well cuttings), small organic carbon concentrations (ranging from less than 0.2 to 160 grams per kilogram), and pH values that were mostly alkaline (ranging from 4.9 to 8.2). Water samples were analyzed for physical properties, major ions, iron, manganese, nutrients, organic carbon, radon, pesticides, volatile organic compounds (VOCs), chlorofluorocarbons, tritium, and isotopes of nitrogen, hydrogen, and oxygen. Most of the water samples had small dissolved-oxygen concentrations (less than 1 milligram per liter). Calcium, magnesium, sodium, bicarbonate, sulfate, and chloride were the primary dissolved constituents in water samples. Nitrite plus nitrate as nitrogen (nitrate) concentrations were less than the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level of 10 mg/L. Nitrogen isotope ratios indicated that the sources of nitrate primarily were soils, animal waste, or denitrification that increased nitrogen isotope ratios in nitrate. Small concentrations of pesticides were detected in the shallow parts of the aquifer. The herbicide prometon was the most frequently detected pesticide. Herbicides applied to control grasses and weeds in corn (atrazine, simazine, and metolachlor) also were frequently detected in water samples. All pesticide and VOCs detected were below USEPA Maximum Contaminant Levels or Health Advisory Limits. Chlorofluorocarbon compounds and tritium concentrations were used to estimate dates of recharge of ground-water samples. In general, shallower ground-water samples were more recently recharged although most water sampled from the aquifer was recharged after 1955. Although land use had substantial effects on ground-water quality, the distribution of contaminants in the aquifer also is affected by complex combinations of factors and processes that include sources of natural and anthropogenic contaminants, three-dimensional advective flow, physical and hydrologic settings, age and evolution of ground water, and transformation of chemical compounds along the flow system. Compounds such as nitrate and dissolved oxygen were greatest in water samples from the upgradient end of the flow system and near the water table. Specific conductance and dissolved solids increased along the flow system and with depth due to increase in residence time in the flow system and dissolution of aquifer materials.

Minnesota↗
USGS2017

Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds

Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point. Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased slightly high and some biased slightly low compared to the recursive digital filter. There were notable differences between the days at base flow estimated by the different methods, with the recursive digital filter having a smaller range of values. This was attributed to how the different methods determine cessation of quickflow (the part of streamflow which is not base flow). For 109 Chesapeake Bay watershed sites with available specific conductance data, the parameters of the filter were optimized using a chemical-mass-balance constraint and two different models for the time-dependence of base-flow specific conductance. Sixty-seven models were deemed acceptable and the results compared well with non-optimized results. There are a number of limitations to the optimal hydrograph-separation approach resulting from the assumptions implicit in the conceptual model, the mathematical model, and the approach taken to impose chemical mass balance (including tracer choice). These limitations may be evidenced by poor model results; conversely, poor model fit may provide an indication that two-component separation does not adequately describe the hydrologic system’s runoff response. The results of this study may be used to address a number of questions regarding the role of groundwater in understanding past changes in stream-water quality and forecasting possible future changes, such as the timing and magnitude of land-use and management practice effects on stream and groundwater quality. Ongoing and future modeling efforts may benefit from the estimates of base flow as calibration targets or as a means to filter chemical data to model base-flow loads and trends. Ultimately, base-flow estimation might provide the basis for future work aimed at improving the ability to quantify groundwater discharge, not only at the scale of a gaged watershed, but at the scale of individual reaches as well.

Scientific Investigations Report↗
USGS2021

Grand challenges of hydrologic modeling for food-energy-water nexus security in high mountain Asia

Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution ( in-situ ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.

Frontiers in Water↗
USGS2022

Assessing the accuracy and potential for improvement of the national land cover database’s tree canopy cover dataset in urban areas of the conterminous United States

The National Land Cover Database (NLCD) provides time-series data characterizing the land surface for the United States, including land cover and tree canopy cover (NLCD-TC). NLCD-TC was first published for 2001, followed by versions for 2011 (released in 2016) and 2011 and 2016 (released in 2019). As the only nationwide tree canopy layer, there is value in assessing NLCD-TC accuracy, given the need for cross-city comparisons of urban forest characteristics. Accuracy assessments have only been conducted for the 2001 data and suggest substantial inaccuracies for that dataset in cities. For the most recent NLCD-TC version, we used various datasets that characterize the built environment, weather, and climate to assess their accuracy in different contexts within 27 cities. Overall, NLCD underestimates tree canopy in urban areas by 9.9% when compared to estimates derived from those high-resolution datasets. Underestimation is greater in higher-density urban areas (13.9%) than in suburban areas (11.0%) and undeveloped areas (6.4%). To evaluate how NLCD-TC error in cities could be reduced, we developed a decision tree model that uses various remotely sensed and built-environment datasets such as building footprints, urban morphology types, NDVI (Normalized Difference Vegetation Index), and surface temperature as explanatory variables. This predictive model removes bias and improves the accuracy of NLCD-TC by about 3%. Finally, we show the potential applications of improved urban tree cover data through the examples of ecosystem accounting in Seattle, WA, and Denver, CO. The outputs of rainfall interception and urban heat mitigation models were highly sensitive to the choice of tree cover input data. Corrected data brought results closer to those from high-resolution model runs in all cases, with some variation by city, model, and ecosystem type. This suggests paths forward for improving the quality of urban environmental models that require tree canopy data as a key model input.

Remote Sensing↗
USGS1993

Ground water discharge and the related nutrient and trace metal fluxes into Quincy bay, Massachusetts

Measurement of the rate and direction of ground water flow beneath Wollaston Beach, Quincy, Massachusetts by use of a heat-pulsing flowmeter shows a mean velocity in the bulk sediment of 40 cm d −1 . The estimated total discharge of ground water into Quincy Bay during October 1990 was 1324–2177 m 3 d −1 , a relatively low ground water discharge rate. The tides have only a moderate effect on the rate and direction of this flow. Other important controls on the rate and volume of ground water flow are the limited thickness, geographic extent, and permeability of the aquifer. Comparisons of published streamflow data and estimates of ground water discharge indicate that ground water makes up between 7.4–12.1% of the gaged freshwater input into Quincy Bay. The data from this study suggest the ground water discharge is a less important recharge component to Quincy Bay than predicted by National Urban Runoff Program (NURP) models. The high nitrate and low nitrite and ammonia concentrations in the ground water at the backshore well sites and low nitrate and high nitrite and ammonia concentrations in the water flowing from the foreshore suggests that denitrification is active in the sediments. The low ground water flow rates and low nitrate concentrations in the foreshore samples suggest that little or no nitrate is surviving the denitrification process to affect the planktonic community. Similarly, oxidizing conditions in the aquifer and low trace metal concentrations in the ground water samples suggest that the metals may be precipitating and binding to sedimentary phases before impacting the bay.

Massachusetts↗
USGS2018

Concentrations of environmental DNA (eDNA) reflect spawning salmon abundance at fine spatial and temporal scales

Developing fast, cost-effective assessments of wild animal abundance is an important goal for many researchers, and environmental DNA (eDNA) holds much promise for this purpose. However, the quantitative relationship between species abundance and the amount of DNA present in the environment is likely to vary substantially among taxa and with ecological context. Here, we report a strong quantitative relationship between eDNA concentration and the abundance of spawning sockeye salmon in a small stream in Alaska, USA, where we took temporally- and spatially-replicated samples during the spawning period. This high-resolution dataset suggests that (1) eDNA concentrations vary significantly day-to-day, and likely within hours, in the context of the dynamic biological event of a salmon spawning season; (2) eDNA, as detected by species-specific quantitative PCR probes, seems to be conserved over short distances (tens of meters) in running water, but degrade quickly over larger scales (ca. 1.5 km); and (3) factors other than the mere presence of live, individual fish — such as location within the stream, live/dead ratio, and water temperature — can affect the eDNA-biomass correlation in space or time. A multivariate model incorporating both biotic and abiotic variables accounted for over 75% of the eDNA variance observed, suggesting that where a system is well-characterized, it may be possible to predict species' abundance from eDNA surveys, although we underscore that species- and system-specific variables are likely to limit the generality of any given quantitative model. Nevertheless, these findings provide an important step toward quantitative applications of eDNA in conservation and management.

Alaska↗
USGS2024

Movement behavior in a dominant ungulate underlies successful adjustment to a rapidly changing landscape following megafire

Background Movement plays a key role in allowing animal species to adapt to sudden environmental shifts. Anthropogenic climate and land use change have accelerated the frequency of some of these extreme disturbances, including megafire. These megafires dramatically alter ecosystems and challenge the capacity of several species to adjust to a rapidly changing landscape. Ungulates and their movement behaviors play a central role in the ecosystem functions of fire-prone ecosystems around the world. Previous work has shown behavioral plasticity is an important mechanism underlying whether large ungulates are able to adjust to recent changes in their environments effectively. Ungulates may respond to the immediate effects of megafire by adjusting their movement and behavior, but how these responses persist or change over time following disturbance is poorly understood. Methods We examined how an ecologically dominant ungulate with strong site fidelity, Columbian black-tailed deer ( Odocoileus hemionus columbianus ), adjusted its movement and behavior in response to an altered landscape following a megafire. To do so, we collected GPS data from 21 individual female deer over the course of a year to compare changes in home range size over time and used resource selection functions (RSFs) and hidden Markov movement models (HMMs) to assess changes in behavior and habitat selection. Results We found compelling evidence of adaptive capacity across individual deer in response to megafire. Deer avoided exposed and severely burned areas that lack forage and could be riskier for predation immediately following megafire, but they later altered these behaviors to select areas that burned at higher severities, potentially to take advantage of enhanced forage. Conclusions These results suggest that despite their high site fidelity, deer can navigate altered landscapes to track rapid shifts in encounter risk with predators and resource availability. This successful adjustment of movement and behavior following extreme disturbance could help facilitate resilience at broader ecological scales.

California↗
USGS2018

Demographic characteristics of an avian predator, Louisiana Waterthrush (Parkesia motacilla), in response to its aquatic prey in a Central Appalachian USA watershed impacted by shale gas development

We related Louisiana Waterthrush ( Parkesia motacilla ) demographic response and nest survival to benthic macroinvertebrate aquatic prey and to shale gas development parameters using models that accounted for both spatial and non-spatial sources of variability in a Central Appalachian USA watershed. In 2013, aquatic prey density and pollution intolerant genera (i.e., pollution tolerance value <4) decreased statistically with increased waterthrush territory length but not in 2014 when territory densities were lower. In general, most demographic responses to aquatic prey were variable and negatively related to aquatic prey in 2013 but positively related in 2014. Competing aquatic prey covariate models to explain nest survival were not statistically significant but differed annually and in general reversed from negative to positive influence on daily survival rate. Potential hydraulic fracturing runoff decreased nest survival both years and was statistically significant in 2014. The EPA Rapid Bioassessment protocol (EPA) and Habitat Suitability Index (HSI) designed for assessing suitability requirements for waterthrush were positively linked to aquatic prey where higher scores increased aquatic prey metrics, but EPA was more strongly linked than HSI and varied annually. While potential hydraulic fracturing runoff in 2013 may have increased Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, in 2014 shale gas territory disturbance decreased EPT richness. In 2014, intolerant genera decreased at the territory and nest level with increased shale gas disturbance suggesting the potential for localized negative effects on waterthrush. Loss of food resources does not seem directly or solely responsible for demographic declines where waterthrush likely were able to meet their foraging needs. However collective evidence suggests there may be a shale gas disturbance threshold at which waterthrush respond negatively to aquatic prey community changes. Density-dependent regulation of their ability to adapt to environmental change through acquisition of additional resources may also alter demographic response.

West Virginia↗
USGS2025

The 3D Elevation Program—Supporting Vermont's economy

Introduction The geographic information system (GIS) community in Vermont has a long history of interdisciplinary and cooperative projects that have facilitated the leveraging of geospatial technology on myriad data acquisitions across the State. High-resolution elevation data are proving to be a resource of great economic value in dealing with many important issues in Vermont. Vermont attained statewide coverage of quality level 2 coverage of topographic light detection and ranging (lidar) data in 2019. Having access to elevation data that are exponentially more accurate than what was previously available is enabling GIS professionals to better support and empower decision makers in economically important efforts such as environmental protection, public safety, watershed management and water quality, geology, transportation planning, forest and wildlife management, local planning, and flood plain management. In addition, developing a consistent and seamless statewide topographic framework supplants the traditionally time consuming and costly approach of extensive field data collection by requiring less time and money, therefore adding economic benefits. Critical applications that meet the State’s management needs depend on lidar data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Vermont. The status of available and in-progress 3DEP baseline lidar data in Vermont is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.64 million in new benefits annually to the State. The top eight Vermont business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Vermont↗
USGS2014

Health status of Largescale Sucker ( Catostomus macrocheilus ) collected along an organic contaminant gradient in the lower Columbia River, Oregon and Washington, USA

The health of Largescale Sucker ( Catostomus macrocheilus ) in the lower Columbia River (USA) was evaluated using morphometric and histopathological approaches, and its association with organic contaminants accumulated in liver was evaluated in males. Fish were sampled from three sites along a contaminant gradient In 2009, body length and mass, condition factor, gonadosomatic index, and hematocrit were measured in males and females; liver and gonad tissue were collected from males for histological analyses; and organ composites were analyzed for contaminant content in males. In 2010, additional data were collected for males and females, including external fish condition assessment, histopathologies of spleen, kidney and gill and, for males, liver contaminant content. Multivariate analysis of variance indicated that biological traits in males, but not females, differed among sites in 2009 and 2010. Discriminant function analysis indicated that site-related differences among male populations were relatively small in 2009, but in 2010, when more variables were analyzed, males differed among sites in regards to kidney, spleen, and liver histopathologies and gill parasites. Kidney tubular hyperplasia, liver and spleen macrophage aggregations, and gill parasites were generally more severe in the downstream sites compared to the reference location. The contaminant content of male livers was also generally higher downstream, and the legacy pesticide hexachlorobenzene and flame retardants BDE-47 and BDE-154 were the primary drivers for site discrimination. However, bivariate correlations between biological variables and liver contaminants retained in the discriminant models failed to reveal associations between the two variable sets. In conclusion, whereas certain non-reproductive biological traits and liver contaminant contents of male Largescale Sucker differed according to an upstream-downstream gradient in the lower Columbia River, results from this study did not reveal the specific environmental factors responsible for the differences in health status among fish populations.

Science of the Total Environment↗
USGS2024

Environmental drivers and spatial patterns of antibiotic-resistant, enteric coliforms across a forest–urban riverscape

Antibiotic resistant bacteria are prevalent environmental contaminants in freshwaters, and antibiotic resistance genes circulate throughout the urban water cycle. The increase of antibiotic resistant pathogens threatens public health through direct and indirect exposure, and natural resource managers need information on the spatial patterns of antibiotic resistant bacteria and environmental factors associated with their distribution to improve water quality monitoring and to better assess human, animal, and environmental health risks. We collected water and epilithic biofilm samples and measured physicochemical environmental variables at 29 sites distributed longitudinally in the Green-Duwamish River basin, Washington, USA. We characterized catchment-wide patterns of gram-negative fecal indicator bacteria and hypothesized that the presence of antibiotic resistance would be associated with environmental heterogeneity, bacterial primary ecology, stream compartment, and stream type. Antibiotic resistance was determined by microbial growth on selective media supplemented with 3 different antibiotics (ampicillin, chloramphenicol, or tetracycline). Phenotypic antibiotic resistance was positively associated with disturbance, but resistance to at least 1 antibiotic was also detected in undeveloped river segments, with an 83% overall detection rate (i.e., 24 out of 29 sites, 17 in the mainstem and 7 in tributaries). The most probable number of Escherichia coli was associated with higher levels of antibiotic resistance of non- E. coli coliforms across the basin (ρ = 0.38, p < 0.01) but was not associated with antibiotic resistance of E. coli . Phenotypic resistance was highest among non- E. coli coliforms in the water column of tributaries draining moderately to extensively developed subcatchments. Generalized linear mixed-effects model results showed that 18% of the variance in presence of antibiotic resistance was explained by the fixed effects (summed CV across environmental variables, stream type, primary ecology, and stream compartment), and when a spatial random effect was included, the model explained 27% of the variance. Our study provides new evidence that environmental factors and bacterial primary ecology are important underlying factors associated with spatial patterns of antibiotic resistant enteric coliforms. We used macroecological concepts and a riverscape approach to characterize the distribution of antibiotic resistance with methods applicable to municipalities.

Freshwater Science↗
USGS2004

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2019

Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics

A previously developed CE–QUAL–W2 model for Madison Lake, Minnesota, simulated the algal community dynamics, water quality, and fish habitat suitability of Madison Lake under recent (2014) meteorological conditions. Additionally, this previously developed model simulated the complex interplay between external nutrient loading, internal nutrient loading from sediment release of phosphorus, and the organic matter decomposition of the algal biomass. However, the partitioning of Cyanophyta within the modeling framework was simplified to one group and did not account for how different Cyanophyta populations are affected by light conditions, use of nitrogen, temperature growth ranges, and differences in settling rates. Properly capturing Cyanophyta dynamics is important given the potential risks posed by potential large algal blooms. For example, when Cyanophyta form large blooms, recreational activities can become restricted in certain areas because of thick algal scums or algal mats, in addition to the possible production of a class of toxins, known as cyanotoxins, capable of threatening human health, domestic animals, and wildlife. Therefore, we updated the model to partition the Cyanophyta into a group that fixed nitrogen and a second, more buoyant Cyanophyta group that did not independently fix nitrogen. The U.S. Geological Survey, in cooperation with the St. Croix Watershed Research Station (Science Museum of Minnesota) with support from the Environmental and Natural Resources Trust Fund of Minnesota (Legislative-Citizen Commission on Minnesota Resources), updated the Madison Lake CE–QUAL–W2 model to address the shortcomings of simulating Cyanophyta in the previously developed model and better characterize Cyanophyta into two groups. In addition to updating the Cyanophyta group differentiation, the part of the model that handles the simulation of algal community dynamics was updated while preserving model predictive capabilities for nutrients, water temperature, and dissolved oxygen. The calibration and validation of the model was done under recent meteorological conditions with large and persistent Cyanophyta blooms (2014 and 2016). Overall, the model simulations predicted the persistently large total phosphorus concentrations in the hypolimnion of Madison Lake and key differences in nutrient concentrations between 2014 and 2016. The Cyanophyta bloom persistence throughout the summer was also simulated by the model in 2014 and 2016, a critical goal of the model update. Finally, monthly total phosphorus budgets were calculated for the updated Madison Lake model for 2014 and 2016.

Minnesota↗
USGS2018

Current research in land, water, and agroecosystems: ASABE journals 2017 year in review

This article highlights current research into land and water resources, agroecosystems, and agricultural production systems published by the Natural Resources and Environmental Systems (NRES) community of ASABE journals (Transactions of the ASABE and Applied Engineering in Agriculture) in 2017. This article reviews the context, scope, and key results of the published articles and perhaps more importantly recommends areas for increased research attention. Experimental and modeling advances were described in hydrology, agroecosystems, climate-change effects, soil erosion, irrigation, drainage, forest resources, livestock systems, natural treatment systems, international water issues, and water quality topic areas. Three special collections were published (International Watershed Technology, Crop Modeling to Optimize Water Use, and Advances in Drainage). Other focal areas included 14 articles relating to livestock waste management, 13 concerning irrigated agricultural systems, 8 addressing climate change effects on land and water resources, and 16 on various aspects of soil erosion measurement and modeling. Building on the articles reviewed from 2017 and toward a vision of future agroecosystems research, the NRES community of ASABE journals strives to grow its role in making new knowledge accessible to sustain agricultural and natural systems in a changing world. In this vane, recommendations for future research direction are discussed with an emphasis on increased application of remote sensing data to agroecosystems research, improved assessment of agroecosystem resiliency and vulnerability to land and climate change, development of integrated models of agroecosystem services, meeting stubborn water management challenges in agricultural production systems, and focusing on publishing fully reproducible model results.

Transactions of the ASABE↗
USGS2015

Web based visualization of large climate data sets

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Environmental Modelling and Software↗