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USGS2018

Fish misidentification and potential implications to monitoring within the San Francisco Estuary, California

Fish monitoring programs often rely on the collection, species identification, and counting of individual fish over time to inform natural resource management decisions. Thus, the utility of the data used to inform these decisions can be negatively affected by species misidentification. Fish species misidentification bias can be minimized by confirming identification using genetic techniques, training observers, or adjusting monitoring data using estimates of incomplete detection and false-positive misidentification. Despite the existence of well-established fish identification training and quality control programs, there is considerable uncertainty about fish species false-positive misidentification rates and the effectiveness of fish identification training programs within the San Francisco Estuary. We evaluated the misidentification of fish species among Delta Juvenile Fish Monitoring Program observers by conducting five fish identification exams under controlled conditions at the Lodi Fish and Wildlife Office in Lodi, California, between 2012 and 2014. To assess the variability in false-positive misidentification, we fitted data to species and observer characteristics using hierarchical logistic regression. We found that fish species misidentification was fairly common, averaging 17% among 155 test specimens and 32 observers. False-positive misidentification varied considerably among species and was negatively related to fish size, the abundance of the species within monitoring samples, and observer experience. In addition, observers who were not formally trained or used as full-time observers were, on average, 6.0 times more likely to falsely identify a species. However, false-positive misidentification rates among observers and specimens still varied considerably after controlling for observer experience and training, and species and size, respectively. Our results could be used to improve fish identification training and testing, increase the accuracy of fish occupancy or abundance estimation, and justify the allocation of resources to continually use and formally train full-time observers within long-term monitoring programs operating in the system.

California↗

USGS2012

Evaluation of Bayesian estimation of a hidden continuous-time Markov chain model with application to threshold violation in water-quality indicators

Natural resource managers require information concerning the frequency, duration, and long-term probability of occurrence of water-quality indicator (WQI) violations of defined thresholds. The timing of these threshold crossings often is hidden from the observer, who is restricted to relatively infrequent observations. Here, a model for the hidden process is linked with a model for the observations, and the parameters describing duration, return period, and long-term probability of occurrence are estimated using Bayesian methods. A simulation experiment is performed to evaluate the approach under scenarios based on the equivalent of a total monitoring period of 5-30 years and an observation frequency of 1-50 observations per year. Given constant threshold crossing rate, accuracy and precision of parameter estimates increased with longer total monitoring period and more-frequent observations. Given fixed monitoring period and observation frequency, accuracy and precision of parameter estimates increased with longer times between threshold crossings. For most cases where the long-term probability of being in violation is greater than 0.10, it was determined that at least 600 observations are needed to achieve precise estimates. An application of the approach is presented using 22 years of quasi-weekly observations of acid-neutralizing capacity from Deep Run, a stream in Shenandoah National Park, Virginia. The time series also was sub-sampled to simulate monthly and semi-monthly sampling protocols. Estimates of the long-term probability of violation were unbiased despite sampling frequency; however, the expected duration and return period were over-estimated using the sub-sampled time series with respect to the full quasi-weekly time series.

Journal of Environmental Informatics↗

USGS2018

Featured collection introduction: Connectivity of streams and wetlands to downstream waters

Connectivity is a fundamental but highly dynamic property of watersheds. Variability in the types and degrees of aquatic ecosystem connectivity presents challenges for researchers and managers seeking to accurately quantify its effects on critical hydrologic, biogeochemical, and biological processes. However, protecting natural gradients of connectivity is key to protecting the range of ecosystem services that aquatic ecosystems provide. In this featured collection, we review the available evidence on connections and functions by which streams and wetlands affect the integrity of downstream waters such as large rivers, lakes, reservoirs, and estuaries. The reviews in this collection focus on the types of waters whose protections under the U.S. Clean Water Act have been called into question by U.S. Supreme Court cases. We synthesize 40+ years of research on longitudinal, lateral, and vertical fluxes of energy, material, and biota between aquatic ecosystems included within the Act's frame of reference. Many questions about the roles of streams and wetlands in sustaining downstream water integrity can be answered from currently available literature, and emerging research is rapidly closing data gaps with exciting new insights into aquatic connectivity and function at local, watershed, and regional scales. Synthesis of foundational and emerging research is needed to support science‐based efforts to provide safe, reliable sources of fresh water for present and future generations.

Journal of the American Water Resources Associatio↗

USGS2011

Trap style influences wild pig behavior and trapping success

Despite the efforts of many natural resource professionals, wild pig ( Sus scrofa ) populations are expanding in many areas of the world. Although many creative techniques for controlling pig populations are being explored, trapping has been and still is the most commonly used method of population control for many public and private land managers. We conducted an observational study to examine the efficiency of 2 frequently used trap styles: a small, portable box‐style trap and a larger, semi‐permanent, corral‐style trap. We used game cameras to examine patterns of trap entry by wild pigs around each style of trap, and we conducted a trapping session to compare trapping success between trap styles. Adult female and juvenile wild pigs entered both styles of trap more readily than did adult males, and adult males seemed particularly averse to entering box traps. Less than 10% of adult male visits to box traps resulted in entries, easily the least percentage of any class at any style of trap. Adult females entered corral traps approximately 2.2 times more often per visit than box traps and re‐entered corral traps >2 times more frequently. Juveniles entered and re‐entered both box and corral traps at similar rates. Overall (all‐class) entry‐per‐visit rates at corral traps (0.71) were nearly double that of box traps (0.37). Subsequent trapping data supported these preliminary entry data; the capture rate for corral traps was >4 times that of box traps. Our data suggest that corral traps are temporally and economically superior to box traps with respect to efficiency; that is, corral traps effectively trap more pigs per trap night at a lower cost per pig than do box traps

Georgia↗

USGS2021

Seasonal diet and habitat use of large, introduced Rainbow Trout in an Ozark Highland stream

Stocking of Rainbow Trout Oncorhynchus mykiss commonly provides seasonal or mitigation fisheries; however, these fish are usually small and ecosystem effects are spatially or temporally limited. Yet agencies receive requests to stock Rainbow Trout in relatively natural settings (i.e., not tailwater or mitigation fisheries), where introductions may have greater ecosystem consequences. The size of introduced fish is an important factor in determining biotic interactions with native species; therefore, our objectives were to assess the seasonal feeding ecology and microhabitat use of large (265–530 mm TL) nonnative Emmerson strain Rainbow Trout in a relatively unaltered, groundwater-influenced, warmwater stream of the Ozark Highlands. Rainbow Trout consumed a variety of prey; however, diets differed between cool (winter and spring) and warm (summer) seasons. Cool-season Rainbow Trout exhibited a mixed feeding strategy, with individual specialization on crayfishes and fishes and generalist feeding on Ephemeroptera and Diptera, but Gastropoda were the dominant prey. Feeding strategy in the warm season switched to individual specialization on numerous prey types. Overall, larger prey resources were important components of Rainbow Trout diets. Piscivory was relatively high in both seasons, and crayfishes were one of the most important prey types across seasons. Selection of coarse substrates and deeper-water microhabitats (>0.95 m) was similar between seasons. Rainbow Trout selected the lowest-velocity microhabitats available during the warm season and moderate velocities in the cool season. Rainbow Trout were five times more likely to be associated with cover in the warm season. Due to their higher temperature tolerance, Emmerson strain Rainbow Trout may persist in Ozark Highland streams, where they disrupt local food webs and occupy habitat otherwise selected by native fish, such as Neosho Smallmouth Bass Micropterus dolomieu velox . If native species conservation is a priority for agencies, then caution regarding Rainbow Trout stockings may be warranted.

Arkansas, Oklahoma↗

USGS2013

Fens as whole-ecosystem gauges of groundwater recharge under climate change

Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (T min ) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in T min occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.

Journal of Hydrology↗

USGS2011

Selectivity evaluation for two experimental gill-net configurations used to sample Lake Erie walleyes

We used length frequencies of captured walleyes Sander vitreus to indirectly estimate and compare selectivity between two experimental gill-net configurations used to sample fish in Lake Erie: (1) a multifilament configuration currently used by the Ohio Department of Natural Resources (ODNR) with stretched-measure mesh sizes ranging from 51 to 127 mm and a constant filament diameter (0.37 mm); and (2) a monofilament configuration with mesh sizes ranging from 38 to 178 mm and varying filament diameter (range = 0.20–0.33 mm). Paired sampling with the two configurations revealed that the catch of walleyes smaller than 250 mm and larger than 600 mm was greater in the monofilament configuration than in the multifilament configuration, but the catch of 250–600-mm fish was greater in the multifilament configuration. Binormal selectivity functions yielded the best fit to observed walleye catches for both gill-net configurations based on model deviances. Incorporation of deviation terms in the binormal selectivity functions (i.e., to relax the assumption of geometric similarity) further improved the fit to observed catches. The final fitted selectivity functions produced results similar to those from the length-based catch comparisons: the monofilament configuration had greater selectivity for small and large walleyes and the multifilament configuration had greater selectivity for mid-sized walleyes. Computer simulations that incorporated the fitted binormal selectivity functions indicated that both nets were likely to result in some bias in age composition estimates and that the degree of bias would ultimately be determined by the underlying condition, mortality rate, and growth rate of the Lake Erie walleye population. Before the ODNR switches its survey gear, additional comparisons of the different gill-net configurations, such as fishing the net pairs across a greater range of depths and at more locations in the lake, should be conducted to maintain congruence in the fishery-independent survey time series.

North American Journal of Fisheries Management↗

USGS2016

Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk ( Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Journal of Visualized Experiments↗

USGS2017

Movements of four native Hawaiian birds across a naturally fragmented landscape

Animals often increase their fitness by moving across space in response to temporal variation in habitat quality and resource availability, and as a result of intra and inter-specific interactions. The long-term persistence of populations and even whole species depends on the collective patterns of individual movements, yet animal movements have been poorly studied at the landscape level. We quantified movement behavior within four native species of Hawaiian forest birds in a complex lava-fragmented landscape: Hawai‛i ‘amakihi Chlorodrepanis virens , ‘oma‘o Myadestes obscurus , ‘apapane Himatione sanguinea , and ‘i‘iwi Drepanis coccinea . We evaluated the relative importance of six potential intrinsic and extrinsic drivers of movement behavior and patch fidelity: 1) forest fragment size, 2) the presence or absence of invasive rats ( Rattus sp.), 3) season, 4) species, 5) age, and 6) sex. The study was conducted across a landscape of 34 forest fragments varying in size from 0.07 to 12.37 ha, of which 16 had rats removed using a treatment-control design. We found the largest movements in the nectivorous ‘apapane and ‘i‘iwi, intermediate levels in the generalist Hawai‛i ‘amakihi, and shortest average movement for the ‘oma‘o, a frugivore. We found evidence for larger patch sizes increasing patch fidelity only in the ‘oma‘o, and an effect of rat-removal increasing patch fidelity of Hawai‛i ‘amakihi only after two years of rat-removal. Greater movement during the non-breeding season was observed in all species, and season was an important factor in explaining higher patch fidelity in the breeding season for ‘apapane and ‘i‘iwi. Sex was important in explaining patch fidelity in ‘oma‘o only, with males showing higher patch fidelity. Our results provide new insights into how these native Hawaiian species will respond to a changing environment, including habitat fragmentation and changing distribution of threats from climate change.

Journal of Avian Biology↗

USGS2021

Aerial strip-transect surveys: Indexing autumn–winter waterbird abundance and distribution in South Carolina

Aerial surveys integrating probability-based sample designs have been implemented successfully to estimate relative abundance of wintering ducks in Arkansas, Louisiana, Mississippi, and Missouri, but these approaches have not been evaluated in the Atlantic Flyway except for American black ducks ( Anas rubripes ) along the Atlantic coast. Furthermore, these surveys have not been used to index abundance of other nonbreeding waterbirds. Given elimination or reduction of resources allocated to the Midwinter Waterfowl Survey in the Atlantic Flyway and elsewhere, the South Carolina Department of Natural Resources (SCDNR) expressed a need for reliable surveys to monitor waterfowl and other waterbirds during autumn through winter. We designed stratified aerial strip-transect surveys to estimate population indices for migrating and wintering dabbling ducks (Anatini), diving ducks (Aythini, Mergini, Oxyurini), pelagic and piscivorous waterbirds (Anhingidae, Laridae, Pelicanidae, Phalacrocoracidae), and wading birds (Ardeidae, Ciconiidae, Threskiornithidae) in coastal and inland regions of South Carolina during autumn-winter 2017–2019. We used unequal probability random sampling to estimate population indices with deemed adequate precision (i.e., coefficient of variation [CV] ≤ 20%) and estimated theoretical survey efforts needed to achieve desired precision for future aerial surveys. Indices met our goal for precision in September and January 2018 for wading birds, in February and November 2018 for pelagic waterbirds, and in February 2018 for diving ducks, but never for other ducks during South Carolina waterfowl hunting season. We detected peak abundance of dabbling and diving ducks in January and wading birds and wood storks ( Mycteria americana ) in September. We estimated ~2.5 times greater survey effort was needed across waterbird taxa than was expended to achieve a CV=20%. We also used survey data to depict spatiotemporal variation in waterbird distributions across the study area. Our surveys are applicable for the SCDNR and other agencies seeking to monitor autumn-winter waterbird populations. Although survey refinements are necessary to increase precision in South Carolina, our waterbird indices are useful to assess population trends through time, guide habitat management and restoration efforts, refine local harvest regulations, inform law enforcement to detected illicit activities (e.g., baiting), and monitor possible shifting waterbird distributions in response to land-use and climate change.

South Carolina↗

USGS2010

Influence of environmental factors on biotic responses to nutrient enrichment in agricultural streams

The influence of environmental factors on biotic responses to nutrients was examined in three diverse agricultural regions of the United States. Seventy wadeable sites were selected along an agricultural land use gradient while minimizing natural variation within each region. Nutrients, habitat, algae, macroinvertebrates, and macrophyte cover were sampled during a single summer low-flow period in 2006 or 2007. Continuous stream stage and water temperature were collected at each site for 30 days prior to sampling. Wide ranges of concentrations were found for total nitrogen (TN) (0.07-9.61 mg/l) and total phosphorus (TP) (<0.004-0.361 mg/l), but biotic responses including periphytic and sestonic chlorophyll a (RCHL and SCHL, respectively), and percent of stream bed with aquatic macrophyte (AQM) growth were not strongly related to concentrations of TN or TP. Pearson's coefficient of determination ( R 2 ) for nutrients and biotic measures across all sites ranged from 0.08 to 0.32 and generally were not higher within each region. The biotic measures (RCHL, SCHL, and AQM) were combined in an index to evaluate eutrophic status across sites that could have different biotic responses to nutrient enrichment. Stepwise multiple regression identified TN, percent canopy, median riffle depth, and daily percent change in stage as significant factors for the eutrophic index ( R 2 = 0.50, p < 0.001). A TN threshold of 0.48 mg/l was identified where eutrophic index scores became less responsive to increasing TN concentrations, for all sites. Multiple plant growth indicators should be used when evaluating eutrophication, especially when streams contain an abundance of macrophytes.

Arkansas;Idaho;Minnesota;Missouri;Nevada;Oklahoma;↗

USGS2026

Estimating the power of a standardized monitoring program for sportfish in Georgia, USA

Objective Biological monitoring is a major component of management decisions and operating budgets of many natural resource management agencies. Given the scientific and financial commitments to monitoring, it is critical to estimate the ability to detect trends through time (i.e., power). Methods The Georgia Department of Natural Resources has monitored reservoir sport fish populations since the 1980s. We estimated the power to detect simulated long-term (≥10 years) changes in relative abundance (CPUE) for Largemouth Bass (some of which are a potential genetic admixture of the recently described species Micropterus nigricans [now known as Largemouth Bass] and M. salmoides [now known as Florida Bass)] and Black Crappie Pomoxis nigromaculatus sampled with electrofishing and gill nets, respectively, across multiple reservoirs ( n = 21). Reservoir-specific simulations were parameterized using 13 years (∼2010–2022) of monitoring data. Power was calculated as the proportion of simulations ( n = 1,000) resulting in significant ( P ≤ 0.1) temporal trends across a 10-year period. We considered power ≥0.8 (i.e., 80% of simulations with significant trends) as the threshold for sufficient power across reservoirs. For both species, we estimated power under three scenarios: (1) declining CPUE, (2) increasing CPUE, and (3) reduction to biennial sampling effort with a 50% decline in CPUE. Results Most reservoirs had sufficient power to detect either a 50% decline or a 100% increase in CPUE of Largemouth Bass across a 10-year period. Switching from annual to biennial sampling for Largemouth Bass reduced the number of reservoirs with sufficient power by half. Power was generally lower for Black Crappie until larger declines (75%) or increases (400%) were imposed. Conclusions We found that Largemouth Bass monitoring was generally near or beyond our reference threshold, but post hoc correlation analyses suggested that the power of Black Crappie data could be increased with more within-reservoir station replication. Overall, using data simulation to estimate power proved a valuable tool in assessing the potential ability of common monitoring approaches to detect change.

Georgia↗

USGS2015

An evaluation of the efficiency of minnow traps for estimating the abundance of minnows in desert spring systems

Desert springs are sensitive aquatic ecosystems that pose unique challenges to natural resource managers and researchers. Among the most important of these is the need to accurately quantify population parameters for resident fish, particularly when the species are of special conservation concern. We evaluated the efficiency of baited minnow traps for estimating the abundance of two at-risk species, Foskett Speckled Dace Rhinichthys osculus ssp. and Borax Lake Chub Gila boraxobius , in desert spring systems in southeastern Oregon. We evaluated alternative sample designs using simulation and found that capture–recapture designs with four capture occasions would maximize the accuracy of estimates and minimize fish handling. We implemented the design and estimated capture and recapture probabilities using the Huggins closed-capture estimator. Trap capture probabilities averaged 23% and 26% for Foskett Speckled Dace and Borax Lake Chub, respectively, but differed substantially among sample locations, through time, and nonlinearly with fish body size. Recapture probabilities for Foskett Speckled Dace were, on average, 1.6 times greater than (first) capture probabilities, suggesting “trap-happy” behavior. Comparison of population estimates from the Huggins model with the commonly used Lincoln–Petersen estimator indicated that the latter underestimated Foskett Speckled Dace and Borax Lake Chub population size by 48% and by 20%, respectively. These biases were due to variability in capture and recapture probabilities. Simulation of fish monitoring that included the range of capture and recapture probabilities observed indicated that variability in capture and recapture probabilities in time negatively affected the ability to detect annual decreases by up to 20% in fish population size. Failure to account for variability in capture and recapture probabilities can lead to poor quality data and study inferences. Therefore, we recommend that fishery researchers and managers employ sample designs and estimators that can account for this variability.

Oregon↗

USGS2017

Predicted pH at the domestic and public supply drinking water depths, Central Valley, California

This scientific investigations map is a product of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project modeling and mapping team. The prediction grids depicted in this map are of continuous pH and are intended to provide an understanding of groundwater-quality conditions at the domestic and public supply drinking water zones in the groundwater of the Central Valley of California. The chemical quality of groundwater and the fate of many contaminants is often influenced by pH in all aquifers. These grids are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to pH. In this work, the median well depth categorized as domestic supply was 30 meters below land surface, and the median well depth categorized as public supply is 100 meters below land surface. Prediction grids were created using prediction modeling methods, specifically boosted regression trees (BRT) with a Gaussian error distribution within a statistical learning framework within the computing framework of R ( http://www.r-project.org/ ). The statistical learning framework seeks to maximize the predictive performance of machine learning methods through model tuning by cross validation. The response variable was measured pH from 1,337 wells and was compiled from two sources: USGS National Water Information System (NWIS) database (all data are publicly available from the USGS: http://waterdata.usgs.gov/ca/nwis/nwis ) and the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW) database (water quality data are publicly available from the SWRCB: http://www.waterboards.ca.gov/gama/geotracker_gama.shtml ). Only wells with measured pH and well depth data were selected, and for wells with multiple records, only the most recent sample in the period 1993–2014 was used. A total of 1,003 wells (training dataset) were used to train the BRT model, and 334 wells (hold-out dataset) were used to validate the prediction model. The training r-squared was 0.70, and the root-mean-square error (RMSE) in standard pH units was 0.26. The hold-out r-squared was 0.43, and RMSE in standard pH units was 0.37. Predictor variables consisting of more than 60 variables from 7 sources were assembled to develop a model that incorporates regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrology. Previously developed Central Valley model outputs of textures (Central Valley Textural Model, CVTM; Faunt and others, 2010) and MODFLOW-simulated vertical water fluxes and predicted depth to water table (Central Valley Hydrologic Model, CVHM; Faunt, 2009) were used to represent aquifer textures and groundwater hydraulics, respectively. In this work, wells were attributed to predictor variable values in ArcGIS using a 500-meter buffer. Faunt, C.C., ed., 2009, Groundwater availability in the Central Valley aquifer, California: U.S. Geological Survey Professional Paper 1776, 225 p., accessed at https://pubs.usgs.gov/pp/1766/ . Faunt, C.C., Belitz, K., and Hanson, R.T., 2010, Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA: Hydrogeology Journal, v. 18, no. 3, p. 625–649, https://doi.org/10.1007/s10040-009-0539-7 .

California↗

USGS2009

The influence of use-related, environmental, and managerial factors on soil loss from recreational trails

Recreational uses of unsurfaced trails inevitably result in their degradation, with the type and extent of resource impact influenced by factors such as soil texture, topography, climate, trail design and maintenance, and type and amount of use. Of particular concern, the loss of soil through erosion is generally considered a significant and irreversible form of trail impact. This research investigated the influence of several use-related, environmental, and managerial factors on soil loss on recreational trails and roads at Big South Fork National River and Recreation Area, a unit of the U.S. National Park Service. Regression modeling revealed that trail position, trail slope alignment angle, grade, water drainage, and type of use are significant determinants of soil loss. The introduction of individual and groups of variables into a series of regression models provides improved understanding and insights regarding the relative influence of these variables, informing the selection of more effective trail management actions. Study results suggest that trail erosion can be minimized by avoiding “fall-line” alignments, steep grades, and valley-bottom alignments near streams, installing and maintaining adequate densities of tread drainage features, applying gravel to harden treads, and reducing horse and all-terrain vehicle use or restricting them to more resistant routes. This research also sought to develop a more efficient Variable Cross-Sectional Area method for assessing soil loss on trails. This method permitted incorporation of CSA measures in a representative sampling scheme applied to a large (24%) sample of the park's 526 km trail system. The variety of soil loss measures derived from the Variable CSA method, including extrapolated trail-wide soil loss estimates, permit an objective quantification of soil erosion on recreational trails and roads. Such data support relational analyses to increase understanding of trail degradation, and long-term monitoring of the natural and recreational integrity of the trail system infrastructure.

Journal of Environmental Management↗

USGS2010

Source and fate of inorganic solutes in the Gibbon River, Yellowstone National Park, Wyoming, USA: I. Low-flow discharge and major solute chemistry

The Gibbon River in Yellowstone National Park (YNP) is an important natural resource and habitat for fisheries and wildlife. However, the Gibbon River differs from most other mountain rivers because its chemistry is affected by several geothermal sources including Norris Geyser Basin, Chocolate Pots, Gibbon Geyser Basin, Beryl Spring, and Terrace Spring. Norris Geyser Basin is one of the most dynamic geothermal areas in YNP, and the water discharging from Norris is much more acidic (pH 3) than other geothermal basins in the upper-Madison drainage (Gibbon and Firehole Rivers). Water samples and discharge data were obtained from the Gibbon River and its major tributaries near Norris Geyser Basin under the low-flow conditions of September 2006. Surface inflows from Norris Geyser Basin were sampled to identify point sources and to quantify solute loading to the Gibbon River. The source and fate of the major solutes (Ca, Mg, Na, K, SiO 2 , Cl, F, HCO 3 , SO 4 , NO 3 , and NH 4 ) in the Gibbon River were determined in this study and these results may provide an important link in understanding the health of the ecosystem and the behavior of many trace solutes. Norris Geyser Basin is the primary source of Na, K, Cl, SO 4 , and N loads (35–58%) in the Gibbon River. The largest source of HCO 3 and F is in the lower Gibbon River reach. Most of the Ca and Mg originate in the Gibbon River upstream from Norris Geyser Basin. All the major solutes behave conservatively except for NH 4 , which decreased substantially downstream from Gibbon Geyser Basin, and SiO 2 , small amounts of which precipitated on mixing of thermal drainage with the river. As much as 9–14% of the river discharge at the gage is from thermal flows during this period.

Wyoming↗

USGS2023

Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA

The mining industry, in most cases, targets a specific valuable commodity that is present in small quantities within large volumes of extracted material. After milling and processing, most of the extracted material and the effluents are stored as waste (tailings) in impoundments, such as dams or waste dumps, or are backfilled into underground mines. In time, tailing materials may become an issue of environmental and health concern due to the hazardous elements, ions, and oxides contained within the waste material. In addition, handling and storage of such waste in dams may pose the risk of dam failure with catastrophic consequences to nature and nearby communities. On the other hand, tailings may offer potential as secondary sources of critical elements (CEs), including rare earth elements (REEs), which may have been overlooked during primary production and processing. Therefore, treating mine tailings as a resource has economic and environmental benefits by reducing the waste from new and historical mine sites through remining. One of the critical steps for taking advantage of these benefits is to spatially quantify the resources and the pollutants, which require the application of adequate data analysis and modeling methods, often to compositional geochemical data. Utilizing adequate methods is especially important for correctly quantifying resource potential, as the quantities will often be at low concentrations. This work presents quantification of resource potential (Au, Ag, Cu, Zn, Pb) and elements of environmental concern (Hg and As) from the tailings of a historic mine site, Katherine Mine, AZ, USA. Data reported by the U.S. Bureau of Mines (USBM) after extensive field campaigns in the 1990s, including sampling from tailing impoundment and surrounding areas for geochemical characterization and geophysical surveys, were used. First, compositional data (CoDa) analysis was employed to explore associations of sampling locations, geochemical parts, and the clustering of samples. Next, sequential Gaussian simulation (SGSIM) was applied to samples that showed a genetic link to tailing material after isometric log-ratio transformation (ilr) and mix/max autocorrelation factor (MAF) transformation for spatial modeling and uncertainty evaluation. Geostatistical results revealed spatial variability of concentrations within the tailing area. Uncertainty evaluation based on realizations indicated that Cu (14.27–20.01 t), Zn (44.23–76.23 t), and Pb (22.56–38.28 t) are the most abundant elements within a 5 %–95 % interval, followed by Ag and Au (~5.3 and 0.18 t, at 50th percentile), respectively. Of the elements of health concern, As was found to be ~4.8 t (50th percentile) in the tailing area. The work also showed that ~0.51 t As, 0.005 t Hg, 0.020 t of Au, and 0.62 t of Ag were carried to Lake Mohave by an ephemeral stream called Katherine Wash, which transects the tailings.

Arizona↗

USGS1990

Modern aerial gamma-ray spectrometry and regional potassium map of the conterminous United States

Aerial gamma-ray surveys of the natural environment measure the flux of gamma rays produced by the radioactive decay of 40 K, 214 Bi, and 208 Tl in the upper 10–20 cm of surface materials. 40 K is a radioactive potassium isotope which can be used to estimate the total amount of potassium in the soils and rocks. 214 Bi is a decay product of the 238 U radioactive decay series and is used to estimate the uranium concentrations, and 208 Tl, a decay product of the 232 Th radioactive decay series, is used to estimate thorium concentrations. Aerial gamma-ray data covering the 48 contiguous states of the United States have been compiled to produce maps showing the distributions of equivalent uranium, equivalent thorium, and potassium. This compilation involved processing the aerial survey data from about 470 1° × 2° quadrangle maps. The aerial gamma-ray data were obtained as part of the National Uranium Resource Evaluation (NURE) Program sponsored by the U.S. Department of Energy during the period 1975-1983. References for the Open-File Reports that describe the surveys and data collection can be found in Bendix Field Engineering Corp. (1983). The aerial surveys were flown by contractors using fixed-wing and helicopter systems with 33-50 L (liters) of thallium-activated sodium iodide (NaI (TI)) crystals. The nominal survey altitude used is 122 m. The survey lines were generally east-west with line spacings of 1.6-10 km. Tie lines were flown perpendicular to the flight lines at intervals of 16- 30 km. The data were corrected for background from aircraft contamination and cosmic rays, altitude variations, airborne 214Bi, and Compton scattering. The gamma-ray systems were calibrated using the calibrations pads at Grand Junction, Colorado (Ward, 1978 ) and the dynamic test strip at Lake Mead, Arizona (Geodata International, Inc., 1977).

Journal of Geochemical Exploration↗