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At least 1,315 records · Page 73Linked to original sources

USGS1998

Choosing indicators of natural resource condition: A case study in Arches National Park, Utah, USA

Heavy visitor use in many areas of the world have necessitated development of ways to assess visitation impacts. Arches National Park recently completed a Visitor Experience and Resource Protection (VERP) plan. Integral to this plan was developing a method to identify biological indicators that would both measure visitor impacts and response to management actions. The process used in Arches for indicator selection is outlined here as a model applicable to many areas facing similar challenges. The steps were: (1) Vegetation types most used by visitors were identified. Impacted and unimpacted areas in these types were sampled, comparing vegetation and soil factors. (2) Variables found to differ significantly between compared sites were used as potential indicators. (3) Site-specific criteria for indicators were developed, and potential indicators evaluated using these criteria. (4) Chosen indicators were further researched for ecological relevancy. (5) Final indicators were chosen, field tested, and monitoring sites designated. In Arches, indicators were chosen for monitoring annually (soil crust index, soil compaction, number of used social trails and soil aggregate stability) and every five years (vegetation cover and frequency; ground cover; soil chemistry; and plant tissue chemistry).

Environmental Management↗

USGS2005

Mass balance assessment for mercury in Lake Champlain

A mass balance model for mercury in Lake Champlain was developed in an effort to understand the sources, inventories, concentrations, and effects of mercury (Hg) contamination in the lake ecosystem. To construct the mass balance model, air, water, and sediment were sampled as a part of this project and other research/monitoring projects in the Lake Champlain Basin. This project produced a STELLA-based computer model and quantitative apportionments of the principal input and output pathways of Hg for each of 13 segments in the lake. The model Hg concentrations in the lake were consistent with measured concentrations. Specifically, the modeling identified surface water inflows as the largest direct contributor of Hg into the lake. Direct wet deposition to the lake was the second largest source of Hg followed by direct dry deposition. Volatilization and sedimentation losses were identified as the two major removal mechanisms. This study significantly improves previous estimates of the relative importance of Hg input pathways and of wet and dry deposition fluxes of Hg into Lake Champlain. It also provides new estimates of volatilization fluxes across different lake segments and sedimentation loss in the lake. ?? 2006 American Chemical Society.

Environmental Science & Technology↗

USGS2020

Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities

Streambed sediment is commonly analyzed to assess occurrence of hydrophobic pesticides and risks to aquatic communities. However, stream biofilms also have the potential to accumulate pesticides and may be consumed by aquatic organisms. To better characterize risks to aquatic life, the U.S. Geological Survey Regional Stream Quality Assessment measured 93 current-use and 3 legacy pesticides in bed sediment and biofilm from 54 small streams in California across a range of land-use settings. On average, 4 times as many current-use pesticides were detected in biofilm at a site (median of 2) as in sediment (median of 0.5). Of 31 current-use pesticides detected, 20 were detected more frequently in biofilm than sediment and 10 equally frequently. Pyrethroids as a class were the most potentially toxic to benthic invertebrates, and of the nine pyrethroids detected, seven occurred more frequently in biofilm than sediment. We constructive General Additive Models to investigate relations between pesticides and six metrics of benthic community structure. Pesticides in biofilm improved fit in four of the six models, and pesticides in sediment improved fit in two. The results indicate that sampling of stream biofilms can complement bed-sediment sampling by identifying more current-use pesticides present and better estimating ecological risks.

California↗

USGS2023

Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands

Mercury (Hg) is a widespread element and persistent pollutant, harmful to fish, wildlife, and humans in its organic, methylated form. The risk of Hg contamination is driven by factors that regulate Hg loading, methylation, bioaccumulation, and biomagnification. In remote locations, with infrequent access and limited data, understanding the relative importance of these factors can pose a challenge. Here, we assessed Hg concentrations in an apex predator fish species, lake trout (Salvelinus namaycush), collected from 14 lakes spanning two National Parks in southwest Alaska, U.S.A. We then examined factors associated with the variation in fish Hg concentrations using a Bayesian hierarchical model. We found that total Hg concentrations in water were consistently low among lakes (0.11–0.50 ng L− 1). Conversely, total Hg concentrations in lake trout spanned a thirty-fold range (101–3046 ng g− 1 dry weight), with median values at 7 lakes exceeding Alaska’s human consumption threshold. Model results showed that fish age and, to a lesser extent, body condition best explained variation in Hg concentration among fish within a lake, with Hg elevated in older, thinner lake trout. Other factors, including plankton methyl Hg content, fish species richness, volcano proximity, and glacier loss, best explained variation in lake trout Hg concentration among lakes. Collectively, these results provide evidence that multiple, hierarchically nested factors control fish Hg levels in these lakes.

Alaska↗

USGS2024

Assessing the population consequences of disturbance and climate change for the Pacific walrus

Climate change and anthropogenic disturbance are increasingly affecting wildlife at a global scale. Predicting how varying types and degrees of disturbance may interact to influence population dynamics is a key management challenge. Population consequences of disturbance (PCoD) models provide a framework to link effects of anthropogenic disturbance on an individual’s behavior and physiology to population-level changes. In the present study, we develop a Pacific walrus ( Odobenus rosmarus divergens ) PCoD model to encompass the population-level effects of both anthropogenic disturbance and climate change. As the Arctic becomes increasingly ice-free, walruses spend more time at coastal (vs. ice-based) haulouts, from which they must expend more energy to reach foraging areas and where they have an elevated risk of mortality. Concurrently, sea ice loss is increasing the anthropogenic footprint in the Arctic (e.g. fisheries, shipping, energy exploration), which creates additional disturbance. We applied the PCoD model to 4 scenarios (ranging from optimistic to pessimistic) which incorporate different global sea ice model projections along with varying degrees of anthropogenic disturbance. All scenarios indicated a decline in Pacific walrus vital rates by the end of the 21st century, but our results demonstrated that the intensity of that decline could be mitigated by global efforts to reduce carbon emissions, along with local management and conservation efforts to protect important coastal haulouts and foraging grounds. In summary, we introduce a flexible PCoD modeling framework in a novel context which will prove useful to researchers studying species threatened by rapid environmental change.

Marine Ecology Progress Series↗

USGS2003

Occurrence and transport of cadmium, lead, and zinc in the Spokane River basin, Idaho and Washington, water years 1999-2001

A water-quality investigation of the Clark Fork-Pend Oreille and Spokane River Basins began in 1997 as part of the U.S. Geological Survey National Water-Quality Assessment Program. As part of the investigation, selected streams in the Spokane River Basin were sampled for trace metals during water years 1999–2001. These data, combined with data collected as part of a U.S. Environmental Protection Agency Remedial Investigation/ Feasibility Study, were used to assess the occurrence, loads, and transport of cadmium, lead, and zinc at 21 streamflow-gaging stations in the Spokane River Basin. Concentrations of dissolved and total cadmium, lead, and zinc varied widely both at and among stations. At most stations, dissolved cadmium and zinc composed most of the total concentrations; dissolved lead generally composed less than 10 percent of the total lead concentration. From the South Fork Coeur d’Alene River near Mullan downstream to the South Fork Coeur d’Alene River near Pinehurst, concentrations of trace metals increased 2 to 4 orders of magnitude. The mean flow-weighted concentrations of total cadmium, lead, and zinc near Pinehurst for water years 1999–2001 were 5.7, 80, and 810 micrograms per liter ( µg/L), respectively. On the Coeur d’Alene River near Harrison, downstream from the confluence of the metal-enriched South Fork and the relatively dilute North Fork Coeur d’Alene River, the mean flow-weighted concentrations of total cadmium, lead, and zinc were 1.6, 88, and 240 µg/L, respectively. Trace-metal concentrations were smaller in the Spokane River than in the Coeur d’Alene River because of dilution and retention in Coeur d’Alene Lake. The mean flowweighted concentrations of total cadmium, lead, and zinc in the Spokane River near Post Falls were 0.32, 3.1, and 71 µg/L, respectively. Regression models relating the mass transport, or load, of trace metals to changes in stream discharge and time were successful in simulating the variability in trace-metal concentrations and loads. The median coefficient of determination for the load models for the 21 stations was largest for total lead (92 percent) and smallest for dissolved and total cadmium (82 percent). Whereas most of the cadmium and zinc loads in the Spokane River Basin were derived from the South Fork Coeur d’Alene River, most of the lead load was derived from the Coeur d’Alene River downstream from the confluence of the North and South Forks. Major tributary sources of trace metals to the South Fork Coeur d’Alene River were Canyon Creek, Ninemile Creek, and Government Gulch. These three tributaries contributed about 3,000 pounds of cadmium, 23,000 pounds of lead, and 310,000 pounds of zinc annually to the South Fork Coeur d’Alene River. Erosion and transport of sediment-bound lead in the Coeur d’Alene River was the primary source of total lead, accounting for almost 400,000 pounds annually during water years 1999–2000. Ground-water discharge in the area of the Bunker Hill Superfund site was a major source of zinc in the South Fork Coeur d’Alene River, contributing more than 250,000 pounds per year. During water years 1999–2000, the average annual loads of cadmium, lead, and zinc transported from the Coeur d’Alene, St. Joe, and St. Maries Rivers to Coeur d’Alene Lake were 8,900, 500,000, and 1.4 million pounds, respectively. The Coeur d’Alene River accounted for more than 99 percent of the total load of each of these three metals entering the lake. About 4,600 pounds of cadmium, 44,000 pounds of lead, and 980,000 pounds of zinc were transported from Coeur d’Alene Lake into the Spokane River. Between the Spokane River near Post Falls, Idaho, and the Spokane River at Long Lake, Washington, there was an annual net loss of about 2,600, 20,000, and 250,000 pounds of cadmium, lead, and zinc, respectively. About 2,000 pounds of cadmium, 24,000 pounds of lead, and 730,000 pounds of zinc were transported annually downstream from Long Lake toward the Columbia River.

Idaho;Washington↗

USGS2021

Habitat suitability index model improvement recommendations

As part of the model improvement effort for the 2023 Coastal Master Plan, the Habitat Suitability Index (HSI) models used during previous master plans were reevaluated to assess how the model relationships could be improved, and to determine what species should be included in the master plan analyses. This process considered the technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plans. Reviews were then conducted to determine the availability of data and information that could be used to make model improvements. As a result of this effort, a recommended list of relevant species to model is provided, and HSI model improvements are recommended that are categorized by whether the suitability index (SI) relationship to be improved is statistical-based or literature-based. The species recommended to be included in the 2023 Coastal Master Plan analyses are: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. These species were selected because they represent a range of taxonomies, life histories, trophic levels, and habitats, and most are commercially- or recreationally-important in coastal Louisiana. Most of these species were also included in the 2017 Coastal Master Plan analyses, and the models used during that effort should be further improved. Seaside sparrow and bald eagle are new for the master plan, and new models should be developed for the analyses. The 2017 fish, shrimp, and blue crab HSI models included a water quality SI that was based on statistical analyses of species catch and environmental data collected by the Louisiana Department of Wildlife and Fisheries. As suggested during the 2017 Coastal Master Plan, the modeling approach used to develop the water quality SI was revisited and alternate modeling approaches were explored. Using literature and an evaluation of the general steps of model development, three components for HSI model improvement were identified, including 1) selecting alternative modeling approach(es); 2) detecting and resolving statistical issues; and 3) improving model fit and evaluation. Multiple options for each component were explored, which resulted in a proposed multi-step phased approach for model improvement. This proposed approach entails improving the generalized linear models used for the 2017 water quality SIs and then, if desired, comparing them to alternative model approaches (e.g., generalized additive models) to explore model performance and select the best approach to use for the 2023 Coastal Master Plan HSI models. All of the existing master plan HSI models include literature-based SIs, which use information from published studies of species-habitat associations to derive suitability relationships. Similar to previous master plans, these literature-based SIs should be updated and improved for the 2023 Coastal Master Plan using recent literature and new ecological knowledge. Preliminary reviews were conducted and recent information was found that could be used to improve the eastern oyster, crayfish, and potentially brown pelican HSI models; but no appropriate recent literature was located for improvement of the American alligator, gadwall, and mottled duck HSI models. However, it is recommended that the literature reviews and information searches be continued. In addition to the statistical-based water quality SI, the 2017 fish, shrimp, and blue crab HSI models also included a structural habitat SI that was based on literature showing high densities of these species in fragmented marsh. The relationship used for this SI, however, did not account for the effects of other estuarine habitats, such as submerged aquatic vegetation and oyster reefs, which are also important to these species. Therefore, a meta-analysis approach is proposed that would estimate the relative importance of these habitats for each species, and the results of this analysis could be used to calculate a new structural habitat SI for the 2023 Coastal Master Plan.

Report↗

USGS2024

Using climate-fire analog mapping to inform climate change adaptation strategies for wildland fire in protected areas of the conterminous US

Potential changes in wildland fire regimes due to anthropogenic climate change can be projected using data from climate models, but directly applying these meteorological variables to long-term planning and adaptive management activities may be difficult for decision makers. Analog mapping, in contrast, creates more intuitive assessments of changing fire regimes that also recognize the complex, multivariate, and multi-scalar nature of ecosystems. Here, we use data from 20 downscaled climate models under two climate forcing scenarios, Representative Concentration Pathways (RCP 4.5 and 8.5), to identify and map future climate-fire analogs for 655 protected areas in the conterminous U.S. based on annual temperature, cumulative precipitation amount and seasonality, and fire regime potentials derived from a simple process-based fire frequency model. Patterns of analogs were heavily influenced by gradients in latitude and topography, with longer time frames (end-of-century conditions) and the more extreme climate forcing scenario resulting in greater analog distances and more ensemble entropy (i.e., less consensus among climate models regarding the closest analog for a given management unit). Finer scale analyses for three protected areas (Yellowstone and Great Smoky Mountains National Parks, White Mountain National Forest) illustrate how climate-fire analog mapping can improve insight into the types of ecosystem responses that might occur under similar management conditions. Federally protected areas such as national parks, forests, and wildlife refuges have long served as reference sites for the study of fire regimes, a role that is likely to continue because many of these units are managed to allow at least some ecosystem processes to operate independently. The results suggest that analog mapping approaches are well-suited as part of qualitative assessments within climate- and fire-aware adaptive management processes. The use of analogs to depict relatable, real-world depictions of possible ecosystem changes in a given place, can help managers make more strategic choices about when and where to resist, accept, or direct climate change-driven ecological change.

Global Environmental Change Advances↗

USGS2012

Fluvial transport and surface enrichment of arsenic in semi-arid mining regions: examples from the Mojave Desert, California

As a result of extensive gold and silver mining in the Mojave Desert, southern California, mine wastes and tailings containing highly elevated arsenic (As) concentrations remain exposed at a number of former mining sites. Decades of weathering and erosion have contributed to the mobilization of As-enriched tailings, which now contaminate surrounding communities. Fluvial transport plays an intermittent yet important and relatively undocumented role in the migration and dispersal of As-contaminated mine wastes in semi-arid climates. Assessing the contribution of fluvial systems to tailings mobilization is critical in order to assess the distribution and long-term exposure potential of tailings in a mining-impacted environment. Extensive sampling, chemical analysis, and geospatial mapping of dry streambed (wash) sediments, tailings piles, alluvial fans, and rainwater runoff at multiple mine sites have aided the development of a conceptual model to explain the fluvial migration of mine wastes in semi-arid climates. Intense and episodic precipitation events mobilize mine wastes downstream and downslope as a series of discrete pulses, causing dispersion both down and lateral to washes with exponential decay behavior as distance from the source increases. Accordingly a quantitative model of arsenic concentrations in wash sediments, represented as a series of overlapping exponential power-law decay curves, results in the acceptable reproducibility of observed arsenic concentration patterns. Such a model can be transferable to other abandoned mine lands as a predictive tool for monitoring the fate and transport of arsenic and related contaminants in similar settings. Effective remediation of contaminated mine wastes in a semi-arid environment requires addressing concurrent changes in the amounts of potential tailings released through fluvial processes and the transport capacity of a wash.

California↗

USGS2022

Using piecewise regression to identify biological phenomena in biotelemetry datasets

1. Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal’s location, movement characteristics, external environmental conditions, and internal physiological status. 2. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. 3. We provide six example applications highlighting a variety of taxonomic species, data streams, timescales and biological phenomena. These examples include a short-term behavioural response (flee and return) by a trumpeter swan Cygnus buccinator following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose Alces alces ; a physiological response (spike in heart-rate) in a black bear Ursus americanus to a stressful stimulus(presence of a drone); a mortality event of a trumpeter swan signalled by changes in collar temperature and overall dynamic body acceleration; an unsupervised method for identifying the onset, return, duration and staging use of sandhill crane Antigone canadensis migration; and estimation of the transition between incubation and brood-rearing (i.e. hatching) for a breeding trumpeter swan. 4. We implement analyses using the MCP package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criteria and cross-validation measures.

Journal of Animal Ecology↗

USGS2022

Assessment of well yield, dominant fractures, and groundwater recharge in Wake County, North Carolina

A cooperative study led by the U.S. Geological Survey and Wake County Environmental Services was initiated to characterize the fractured-rock aquifer system and assess the sustainability of groundwater resources in and around Wake County. This report contributes to the development of a comprehensive groundwater budget for the study area, thereby helping to enable resource managers to make sound and sustainable water-supply and water-use decisions. Construction information was used to analyze the well depth, casing depth, and reported well yield of more than 7,500 inventoried wells. The median well depth and casing depth were 265 feet (ft) below land surface (bls) and 68 ft bls, respectively, and the median well yield was 10 gallons per minute. Generally, well yield increased with depth to around 200 ft bls and then began to decrease with depth within the fractured-rock aquifer. Borehole geophysical logging methods were used to characterize the fractured-rock aquifer by mapping the orientation of geologic structures within the subsurface. Structure measurements were made on resulting log data and mapped to observed general spatial trends within the regional groundwater system and more distinct hydrogeologic units. Many of the fractures observed within the borehole logs are steeply dipping across Wake County, although open fractures with shallow dip angles were also observed in most rock classes. Regional geologic structural trends were observed in proximity to the Jonesboro Fault. Potential groundwater recharge in the study area was estimated using a Soil-Water-Balance (SWB) model, as well as using base flow hydrograph separation. The SWB model calculated net infiltration below the root zone for 1981 through 2019 for a 5,402-square-mile area that extends to the counties surrounding Wake County. The mean annual net infiltration rate for the 39-year period was about 8.6 inches per year for the study area. The mean annual net infiltration results from the SWB model were comparable to annual base flow estimates using the PART hydrograph-separation method at six U.S. Geological Survey streamgages within the study area. Mean annual base flow for all six drainage basins was near 7.5 inches per year and estimates ranged from 2.9 to 8.9 inches. Comparisons of mean annual potential recharge from the SWB model and base flow estimates were generally within 2 inches, except during high flows for most of the drainage basins in the study area.

North Carolina↗

USGS2013

Intra- and inter-basin mercury comparisons: Importance of basin scale and time-weighted methylmercury estimates

To assess inter-comparability of fluvial mercury (Hg) observations at substantially different scales, Hg concentrations, yields, and bivariate-relations were evaluated at nested-basin locations in the Edisto River, South Carolina and Hudson River, New York. Differences between scales were observed for filtered methylmercury (FMeHg) in the Edisto (attributed to wetland coverage differences) but not in the Hudson. Total mercury (THg) concentrations and bivariate-relationships did not vary substantially with scale in either basin. Combining results of this and a previously published multi-basin study, fish Hg correlated strongly with sampled water FMeHg concentration ( p = 0.78; p = 0.003) and annual FMeHg basin yield ( p = 0.66; p = 0.026). Improved correlation ( p = 0.88; p < 0.0001) was achieved with time-weighted mean annual FMeHg concentrations estimated from basin-specific LOADEST models and daily streamflow. Results suggest reasonable scalability and inter-comparability for different basin sizes if wetland area or related MeHg-source-area metrics are considered.

Environmental Pollution↗

USGS2008

Methane hydrates

Gas hydrate is a solid, naturally occurring substance consisting predominantly of methane gas and water. Recent scientific drilling programs in Japan, Canada, the United States, Korea and India have demonstrated that gas hydrate occurs broadly and in a variety of forms in shallow sediments of the outer continental shelves and in Arctic regions. Field, laboratory and numerical modelling studies conducted to date indicate that gas can be extracted from gas hydrates with existing production technologies, particularly for those deposits in which the gas hydrate exists as pore-filling grains at high saturation in sand-rich reservoirs. A series of regional resource assessments indicate that substantial volumes of gas hydrate likely exist in sand-rich deposits. Recent field programs in Japan, Canada and in the United States have demonstrated the technical viability of methane extraction from gas-hydrate-bearing sand reservoirs and have investigated a range of potential production scenarios. At present, basic reservoir depressurisation shows the greatest promise and can be conducted using primarily standard industry equipment and procedures. Depressurisation is expected to be the foundation of future production systems; additional processes, such as thermal stimulation, mechanical stimulation and chemical injection, will likely also be integrated as dictated by local geological and other conditions. An innovative carbon dioxide and methane swapping technology is also being studied as a method to produce gas from select gas hydrate deposits. In addition, substantial additional volumes of gas hydrate have been found in dense arrays of grain-displacing veins and nodules in fine-grained, clay-dominated sediments; however, to date, no field tests, and very limited numerical modelling, have been conducted with regard to the production potential of such accumulations. Work remains to further refine: (1) the marine resource volumes within potential accumulations that can be produced through exploratory drilling programs; (2) the tools for gas hydrate detection and characterisation from remote sensing data; (3) the details of gas hydrate reservoir production behaviour through additional, well-monitored and longer duration field tests and (4) the understanding of the potential environmental impacts of gas hydrate resource development. The results of future production tests, in the context of varying market and energy supply conditions around the globe, will be the key to determine the ultimate timing and scale of the commercial production of natural gas from gas hydrates.

Book chapter↗

USGS2017

The practice of prediction: What can ecologists learn from applied, ecology-related fields?

The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.

Ecological Complexity↗

USGS2026

Lost in translation: Reconciling different streamflow permanence data products

The objective of this study is to provide a framework to reconcile streamflow permanence products that provide information on whether a stream is perennial or nonperennial. Accurate classification of streams as perennial or nonperennial is important for a variety of land and water resource management decisions. However, resource managers are challenged with how to reconcile different streamflow permanence information to determine if it is sufficient to avoid field verification, which can be prohibitively costly and time consuming. The study evaluates two datasets for the Pacific Northwest Region, U.S., the National Hydrography Dataset Plus High Resolution (NHDPlus HR) hydrographic classification and the PRObability of Streamflow PERmanence (PROSPER) model output, which differ in structure, output type, and temporal and spatial resolution. The framework includes a two-level evaluation that involves assessing agreement between the two datasets and evaluating the reliability of the two datasets. Summarized at a regional scale, the two datasets agree for 68% of flowlines with higher agreement for nonperennial streams. PROSPER nonperennial stream classifications may be considered generally reliable in arid regions relative to other ecoregions within the Pacific Northwest study area but less reliable for high elevation mountain regions and larger streams and rivers. More than 75% of NHDPlusHR classifications may be considered reliable when evaluating reliability based on approximate climate conditions associated with the year that the NHDPlus HR classification was assigned. The decision procedure is reproducible, flexible to varying criteria of end user applications, and is intended to help provide cost saving opportunities for land managers by providing information for more strategic field verification of streamflow class determination based on available yet imperfect data sources.

California, Idaho, Montana, Nevada, Utah, Washingt↗

USGS2023

Evolving radon diffusion through earthen barriers at uranium waste disposal sites

Field measurements of Rn-222 fluxes from the tops and bottoms of compacted clay radon barriers were used to calculate effective Rn diffusion coefficients (D Rn ) at four uranium waste disposal sites in the western United States to assess cover performance after more than 20 years of service. Values of D Rn ranged from 7.4 × 10 −7 to 6.0 × 10 −9 m 2 /s, averaging 1.42 × 10 −7 . Water saturation (S W ) from soil cores indicated that there was relatively little control of D Rn by S W , especially at higher moisture levels, in contrast to estimates from most steady-state diffusion models. This is attributed to preferential pathways intrinsic to construction of the barriers or to natural process that have developed over time including desiccation cracks, root channels, and insect burrows in the engineered earthen barriers. A modification to some models in which fast and slow pathway D Rn values are partitioned appears to give a good representation of the data; 4% of the fast pathway was needed to fit the data regression. For locations with high S w and highest D Rn (and fluxes) at each site, the proportion of fast pathway ranged from 1.7% to 34%, but for many locations with lower fluxes, little if any fast pathway was needed.

Journal of Environmental Radioactivity↗

USGS2006

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment

We developed a process-based model to predict the probability of arsenic exceeding 5 ??g/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors. ?? 2006 American Chemical Society.

Environmental Science & Technology↗

USGS2002

An ecosystem report on the Panama Canal: Monitoring the status of the forest communities and the watershed

In 1996, the Smithsonian Tropical Research Institute and the Republic of Panama's Environmental Authority, with support from the United States Agency for International Development, undertook a comprehensive program to monitor the ecosystem of the Panama Canal watershed. The goals were to establish baseline indicators for the integrity of forest communities and rivers. Based on satellite image classification and ground surveys, the 2790 km2 watershed had 1570 km2 of forest in 1997, 1080 km2 of which was in national parks and nature monuments. Most of the 490 km2 of forest not currently in protected areas lies along the west bank of the Canal, and its management status after the year 2000 turnover of the Canal from the U.S. to Panama remains uncertain. In forest plots designed to monitor forest diversity and change, a total of 963 woody plant species were identified and mapped. We estimate there are a total of 850-1000 woody species in forests of the Canal corridor. Forests of the wetter upper reaches of the watershed are distinct in species composition from the Canal corridor, and have considerably higher diversity and many unknown species. These remote areas are extensively forested, poorly explored, and harbor an estimated 1400-2200 woody species. Vertebrate monitoring programs were also initiated, focusing on species threatened by hunting and forest fragmentation. Large mammals are heavily hunted in most forests of Canal corridor, and there was clear evidence that mammal density is greatly reduced in hunted areas and that this affects seed predation and dispersal. The human population of the watershed was 113 000 in 1990, and grew by nearly 4% per year from 1980 to 1990. Much of this growth was in a small region of the watershed on the outskirts of Panama City, but even rural areas, including villages near and within national parks, grew by 2% per year. There is no sewage treatment in the watershed, and many towns have no trash collection, thus streams near large towns are heavily polluted. Analyses of sediment loads in rivers throughout the watershed did not indicate that erosion has been increasing as a result of deforestation, rather, erosion seems to be driven largely by total rainfall and heavy rainfall events that cause landslides. Still, models suggest that large-scale deforestation would increase landslide frequency, and failure to detect increases in erosion could be due to the gradual deforestation rate and the short time period over which data are available. A study of runoff showed deforestation increased the amount of water from rainfall that passed directly into streams. As a result, dry season flow was reduced in a deforested catchment relative to a forested one. Currently, the Panama Canal watershed has extensive forest areas and streams relatively unaffected by humans. But impacts of hunting and pollution near towns are clear, and the burgeoning population will exacerbate these impacts in the next few decades. Changes in policies regarding forest protection and pollution control are necessary.

Environmental Monitoring and Assessment↗