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At least 847 records · Page 47Linked to original sources

Cyanotoxin occurrence in the United States: A 20 year retrospective

Cyanobacterial blooms, and associated cyanotoxin occurrence, are a concern because of the potential harms posed to humans, wildlife, and aquatic ecosystem health. Evidence suggests the magnitude, frequency, and duration of cyanobacterial blooms are increasing, and these events represent a significant challenge to freshwaters and, increasingly, marine waters, worldwide. Cyanobacterial blooms routinely receive local and national attention because of occurrence in new locations, recreational closures, drinking-water impacts, animal illnesses and deaths, scientific advances, and novel management and mitigation strategies. Due to public information campaigns at local, state, and federal levels, the public is generally aware of what cyanobacterial blooms look like and potential risks posed to human and animal health. It is difficult now to imagine a time when cyanobacterial blooms were considered an occasional nuisance in lakes and reservoirs, well-known only by limnologists. When I began my career over twenty years ago, however, that was the status. Cyanobacteria were just beginning to capture attention, and they certainly captured mine.

Lakeline↗

Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the Lower Gunnison River Basin, Colorado, 2012–16

Dissolved selenium is a contaminant of concern in the lower Gunnison River Basin, Colorado. Selenium is naturally present in the Cretaceous Mancos Shale and is leached to groundwater and surface water by irrigation. The groundwater on the east side of the Uncompahgre River in Delta and Montrose Counties is one of the primary sources of selenium concentration and load to surface water in the lower Gunnison River Basin. Although little information about the contribution of groundwater to surface water has been historically available, groundwater has often been implicated as an appreciable source of selenium to surface water. From 2012 to 2016, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program, established a 30-well groundwater-monitoring network on irrigated land to characterize the hydrology and groundwater quality of the shallow groundwater system on the east side of the Uncompahgre River in the lower Gunnison River Basin. The installation of the 30-well network and the data collected allowed for the development of a conceptual model of selenium mobilization and transport in the shallow groundwater system. Monitoring wells were completed in surficial deposits and in weathered Mancos Shale, which generally exhibited unconfined and confined conditions, respectively. Groundwater-quality monitoring provides information on the distribution of selenium and the geochemical processes controlling selenium concentrations in shallow groundwater. Monitoring wells were sampled between August 2013 and March 2015 to understand groundwater quality, seasonality, sources of recharge, and groundwater age. Concentrations of dissolved selenium ranged from below the limit of detection to 4,100 micrograms per liter (µg/L), with a median concentration of 14 µg/L. Concentrations showed a high degree of spatial variability and no seasonal difference. Similarly, no seasonal pattern was observed in specific conductance values of groundwater despite the considerably lower specific conductance value of irrigation water. Reduction-oxidation processes are important controls on selenium mobility. Nitrate derived from geologic material was a primary control on reduction-oxidation conditions in groundwater and inhibited selenium reduction to less mobile forms. Nitrate was reduced by denitrification in groundwater, but it was not reduced to the extent necessary to allow for selenium reduction. Groundwater ages were determined for groundwater samples from eight wells and ranged from 6 to 20 years old. Isotopic data indicate groundwater was recharged by irrigation water; no information collected supported an older, deeper source of recharge to the shallow groundwater system. Data on water level in all wells showed response to irrigation practices, but the response was delayed in some wells, which may be an indication of distance from recharge source.

Colorado↗

Assessment of general health of fishes collected at selected sites in the Great Lakes Basin In 2012

During the past decade, there has been a substantive increase in the detection of “emerging contaminants”, defined as a new substance, chemical, or metabolite in the environment; or a legacy substance with a newly expanded distribution, altered release, or a newly recognized effect (such as endocrine disruption). Emerging contaminants include substances such as biogenic hormones (human and animal), brominated flame retardants, pharmaceuticals, personal care products, plasticizers, current use pesticides, detergents, and nanoparticles. These contaminants are frequently not regulated or inadequately regulated by state or Federal water quality programs. Information about the toxicity of these substances to fish and wildlife resources is generally limited, compared to more highly regulated contaminants, and some classes have been shown to cause affects (for example feminization of male fish, immunomodulation) that are not evaluated via traditional toxicity testing protocols. As a result, these compounds may pose a substantial, but currently poorly documented threat to aquatic ecosystems. Failure to identify and understand the impacts of these emerging contaminants on fish and wildlife resources may result in deleterious impacts to Great Lakes resources that can result in adverse ecological, economic and recreational consequences. The U. S. Fish and Wildlife Service received funding through the Great Lakes Restoration Initiative (GLRI) for an Early Warning Program to detect and identify emerging contaminants and to evaluate the effects of these contaminants on fish and wildlife. The U.S. Geological Survey (WV Cooperative Fish and Wildlife Research Unit and National Fish Health Research Laboratory, Leetown Science Center) developed and implemented a biological effects monitoring protocol to assist in this program. Fish collections and measurements of biomarkers of exposure in Fall 2010 and Spring 2011 occurred at individual sites within select Areas of Concern (AOCs). They provided an assessment of the utility of the suite of biomarkers and also identified sites for more in-depth analyses. Selected areas are characterized as areas with known emerging contaminants, sensitive or listed species, areas downstream from municipal wastewater discharges or receiving waters for industrial facilities, and/or areas susceptible to agricultural or urban contamination, or harbors or ports. The results of the 2010- 2011 studies were summarized in Blazer et al. 2014 a, b, c; Braham et al. in review and Blazer et al. in review.

Great Lakes↗

Regional Water-Resources Studies in Nevada

Introduction: Water-resources information for the State of Nevada should be readily accessible to community planners and the general public in a user-friendly web environment and should be actively managed and maintained with accurate historic and current hydrologic data. The USGS, in cooperation with State of Nevada and local government agencies, has established a data framework that provides critical hydrologic information to meet the challenges of water resources planning for Nevada.

Fact Sheet↗

Predictability and behavior of water transfers across basin boundaries

Inter-basin water transfers (IBTs) are important components of water balances of basins, and they can have substantial impact on regional water availability. Flow information is often not available at locations with known IBTs, which is a drawback in several published IBT databases. Few, if any, studies examine whether IBT flow behavior can be generalized, and if these behaviors can be predicted at undocumented locations or known IBT locations with no flow information. In this study, we employ a clustering method based on image matching to identify similar classes of flow behavior of IBTs. Machine learning models are used to assess how well IBT flow characteristics (e.g., average flow) associated with these behaviors can be predicted. These evaluations of IBTs are done for two regions in the United States. Three primary classes of IBTs (seasonal, nonseasonal/not mixed, and seasonal/mixed) are identified across the two regions analyzed. The IBT flow characteristics are accurately predicted in the northeast region. In the Colorado region, however, only the flow characteristics related to timing were accurately predicted. These results indicate that the proposed modeling framework can be used to identify generalizable IBT flow characteristics. This framework is shown to predict flow characteristics with a reasonable amount of accuracy to undocumented locations and improves previously published IBT databases by backfilling flow information to locations with a known IBT presence.

Arizona, Colorado, Delaware, Kansas, Maryland, Mas↗

Estimating the magnitude and frequency of floods in rural basins of North Carolina— Revised

A statewide study was conducted to develop two methods for estimating the magnitude and frequency of floods in rural ungaged basins in North Carolina. Flood-frequency estimates for gaged sites in North Carolina were computed by fitting the annual peak flows for each site to a log-Pearson Type III distribution. As part of the computation of flood-frequency estimates for gaged sites, new values for generalized skew coefficients were developed. Basin characteristics for these gaged sites were computed by using a geographic information system and automated computer algorithms. Flood-frequency estimates and basin characteristics for 317 gaged sites were combined to form the data base that was used for this analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont, Coastal Plain, and Sand Hills hydrologic areas. The predictive equations are all functions of drainage area. Average errors of prediction for these regression equations range from 36 to 65 percent. A region-of-influence method also was developed that interactively estimates recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont and Coastal Plain hydrologic areas of North Carolina. Regression techniques are used to develop a unique relation between flood discharge and basin characteristics for a subset of gaged sites with similar basin characteristics. This, then, can be used to estimate flood discharges at ungaged sites. Because the computations required for this method are somewhat complex, a computer application was developed that performs the computations and compares the predictive errors for this method. The computer application also includes the option of using the regression equations to compute estimated flood discharges and errors of prediction specific to each ungaged site. Root mean square errors, computed for each recurrence interval and hydrologic area, are generally only slightly lower for the region-of-influence method than for the regression equations and do not provide sufficient basis for recommending one method over the other. In addition, the region-of-influence method is a new method that is still being improved. As a result, the regional regression equations are considered to be the primary method for computing flood-frequency estimates at ungaged sites.

North Carolina↗

Estimating the magnitude and frequency of floods in rural basins of North Carolina

A statewide study was conducted to develop two methods for estimating the magnitude and frequency of floods in rural ungaged basins in North Carolina. Flood-frequency estimates for gaged sites in North Carolina were computed by fitting the annual peak flows for each site to a log-Pearson Type III distribution. As part of the computation of flood-frequency estimates for gaged sites, new values for generalized skew coefficients were developed. Basin characteristics for these gaged sites were computed by using a geographic information system and automated computer algorithms. Flood-frequency estimates and basin characteristics for 317 gaged sites were combined to form the data base that was used for this analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont, Coastal Plain, and Sand Hills hydrologic areas. The predictive equations are all functions of drainage area. Average errors of prediction for these regression equations range from 36 to 65 percent. A region-of-influence method also was developed that interactively estimates recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont and Coastal Plain hydrologic areas of North Carolina. Regression techniques are used to develop a unique relation between flood discharge and basin characteristics for a subset of gaged sites with similar basin characteristics. This, then, can be used to estimate flood discharges at ungaged sites. Because the computations required for this method are somewhat complex, a computer application was developed that performs the computations and compares the predictive errors for this method. The computer application also includes the option of using the regression equations to compute estimated flood discharges and errors of prediction specific to each ungaged site. Root mean square errors, computed for each recurrence interval and hydrologic area, are generally only slightly lower for the region-of-influence method than for the regression equations and do not provide sufficient basis for recommending one method over the other. In addition, the region-of-influence method is a new method that is still being improved. As a result, the regional regression equations are considered to be the primary method for computing flood-frequency estimates at ungaged sites.

North Carolina↗

Estimating state-transition probabilities for unobservable states using capture-recapture/resighting data

Temporary emigration was identified some time ago as causing potential problems in capture-recapture studies, and in the last five years approaches have been developed for dealing with special cases of this general problem. Temporary emigration can be viewed more generally as involving transitions to and from an unobservable state, and frequently the state itself is one of biological interest (e.g., 'nonbreeder'). Development of models that permit estimation of relevant parameters in the presence of an unobservable state requires either extra information (e.g., as supplied by Pollock's robust design) or the following classes of model constraints: reducing the order of Markovian transition probabilities, imposing a degree of determinism on transition probabilities, removing state specificity of survival probabilities, and imposing temporal constancy of parameters. The objective of the work described in this paper is to investigate estimability of model parameters under a variety of models that include an unobservable state. Beginning with a very general model and no extra information, we used numerical methods to systematically investigate the use of ancillary information and constraints to yield models that are useful for estimation. The result is a catalog of models for which estimation is possible. An example analysis of sea turtle capture-recapture data under two different models showed similar point estimates but increased precision for the model that incorporated ancillary data (the robust design) when compared to the model with deterministic transitions only. This comparison and the results of our numerical investigation of model structures lead to design suggestions for capture-recapture studies in the presence of an unobservable state.

Long Island↗

Preliminary assessment of a water-quality monitoring program for total maximum daily loads in Johnson County, Kansas, January 2015 through June 2016

Municipalities in Johnson County in northeastern Kansas are required to implement stormwater management programs to reduce pollutant discharges, protect water quality, and comply with applicable water-quality regulations in accordance with National Pollutant Discharge Elimination System permits for stormwater discharge. To this end, municipalities collect grab samples at streams entering and leaving their jurisdiction to determine levels of excessive nutrients, sediment, and fecal bacteria to characterize pollutants and understand the factors affecting them. In 2014, the U.S. Geological Survey and the Johnson County Stormwater Management Program, with input from the Kansas Department of Health and Environment, initiated a 5-year monitoring program to satisfy minimum sampling requirements for each municipality as described by new stormwater permits issued to Johnson County municipalities. The purpose of this report is to provide a preliminary assessment of the monitoring program. The monitoring program is described, a preliminary assessment of the monitoring program design is provided using water-quality data collected during the first 2 years of the program, and the ability of the current monitoring network and sampling plan to provide data sufficient to quantify improvements in water quality resulting from implemented and planned best management practices is evaluated. The information in this initial report may be used to evaluate changes in data collection methods while data collection is still ongoing that may lead to improved data utility. Discrete water-quality samples were collected at 27 sites and analyzed for nutrients, Escherichia coli ( E. coli ) bacteria, total suspended solids, and suspended-sediment concentration. In addition, continuous water-quality data (water temperature, pH, dissolved oxygen, specific conductance, turbidity, and nitrate plus nitrite) were collected at one site to characterize variability and provide a basis for comparison to discrete data. Base flow samples indicated that point sources are likely affecting nutrient concentrations and E. coli bacteria densities at several sites. Concentrations of all analytes in storm runoff samples were characterized by substantial variability among sites and samples. About one-half of the sites, representing different watersheds, had storm runoff samples with nitrogen concentrations greater than 10 milligrams per liter. About one-third of the sites, representing different watersheds, had storm runoff samples with total phosphorus concentrations greater than 3 milligrams per liter. Six sites had samples with E. coli densities greater than 100,000 colonies per 100 milliliters of water. Total suspended solids concentrations of about 12,000 milligrams per liter or greater occurred in samples from three sites. Data collected for this monitoring program may be useful for some general assessment purposes but may also be limited in potential to fully inform stormwater management activities. Valuable attributes of the monitoring program design included incorporating many sites across the county for comparisons among watersheds and municipalities, using fixed-stage samplers to collect multiple samples during single events, collection of base flow samples in addition to storm samples to isolate possible point sources from stormwater sources, and use of continuous monitors to characterize variability. Limiting attributes of the monitoring program design included location of monitoring sites along municipal boundaries to satisfy permit requirements rather than using watershed-based criteria such as locations of tributaries, potential pollutant sources, and implemented management practices. Additional limiting attributes include having a large number of widespread sampling locations, which presented logistical challenges for predicting localized rainfall and collecting and analyzing samples during short timeframes associated with storms, and collecting storm samples at fixed-stage elevations only during the rising limb of storms, which does not characterize conditions over the storm hydrograph. The small number of samples collected per site resulted in a sample size too small to be representative of site conditions, including seasonal and hydrologic variability, and insufficient for meaningful statistical analysis or site-specific modeling. Several measures could be taken to improve data utility and include redesigning the monitoring network according to watershed characteristics, incorporating a nested design in which data are collected at different scales (watershed, subwatershed, and best management practices), increasing sampling frequency, and combining different methods to allow for flexibility to focus on areas and conditions of particular interest. A monitoring design that would facilitate most of these improvements would be to focus efforts on a limited number of watersheds for several years, then cycle to the next set of watersheds for several years, eventually returning to previously monitored watersheds to document changes. Redesign of the water-quality monitoring program requires considerable effort and commitment from municipalities of Johnson County. However, the long-term benefit likely is a monitoring program that results in improved stream conditions and more effective management practices and efficient expenditure of resources.

Kansas↗

Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.

Environmental Research Letters↗

1995 annual report on Alaska's mineral resources

Section 1011 of the Alaska National Interest Lands Conservation Act (ANILCA) of 1980, as amended, requires that "On or before October 1, 1982, and annually thereafter, the President shall transmit to the Congress all pertinent public information relating to minerals in Alaska gathered by the United States Geological Surveys, United States Bureau of Mines, and any other Federal agency." This report has been prepared in response to that requirement. This circular is the fourteenth in the series of annual mineral reports mandated by the ANILCA. The report provides information about current Alaskan mineral projects and events during 1994; the emphasis is on Federal activity. The report addresses both onshore and offshore areas of Alaska. The U.S. Geological Survey (USGS), U.S. Bureau of Mines (USBM), and Minerals Management Service (MMS) are the principal Federal agencies that publish information about energy and mineral resources in Alaska. Their reports and data form the basis for decisions by other Federal agencies regarding land use, access, environmental impacts, and mining claim evaluation. The time required for sample analysis, data synthesis, and publication is lengthy; as a result, scientific reports are generally issued a year or more after initial sample and data collection. Other sources of information for this report include additional Federal and State publications, trade and professional journals, presentations at public meetings and hearings, and press releases. Information is provided for two broad categories of minerals: energy resources and nonfuel-mineral resources.

Circular↗

Guidelines for use of fishes in research

The 2004 and 2014 Guidelines were developed to provide a structure that advances appropriate attention toward valid experimental designs and procedures with aquatic animals while ensuring humane treatment of the experimental subjects. At a practical level, the Guidelines are intended to provide general recommendations on field and laboratory endeavors, such as sampling, holding, and handling fishes; to offer information on administrative matters, including regulations and permits; and to address typical ethical concerns, such as perceptions of pain or discomfort experienced by experimental subjects. These Guidelines must be recognized as guidelines . They are not intended to provide detailed instructions but rather to alert investigators to a broad array of topics and concerns to consider prior to initiating study. At a comprehensive level, the principles upon which these Guidelines are based are broadly applicable, and many of the described practices and approaches can be adapted to situations involving other aquatic animal species and conditions. Understanding the differences between fishes and other vertebrates, especially mammals, is critically important to conducting scientifically sound research with fishes. Disparities in life histories and mortality rates in fishes versus other vertebrates are critical in designing sustainable sampling levels in fish populations. The UFR Committee points out that (1) compared to mammalian populations, adult populations of many fish species persist despite very high natural mortality rates in juvenile stages by virtue of the fact that most species lay thousands or tens of thousands of eggs; (2) because of these mortality patterns, research on fishes, especially field research or research on early life stages, can involve, and often requires, much larger numbers of research subjects than does research on mammals; and (3) the animal handling and husbandry requirements for fishes are fundamentally different from those for mammals and other vertebrates, in general. Policies, regulations, and recommendations developed for research on mammals, birds, reptiles, or even amphibians are frequently inappropriate for research with fishes. The Guidelines also address some of the ethical concerns that motivate guidelines used for research with other vertebrates, while being mindful of the unique physiology and general nature of fishes. The Guidelines were developed for general use by investigators within the United States; therefore, the roles, responsibilities, and informational needs of Institutional Animal Care and Use Committees (IACUCs) were given specific attention. All United States institutions that use vertebrate animals for research, teaching, research training, and biological testing are required to create an IACUC to oversee and evaluate all aspects of the institution’s animal care and use program. Investigators from other nations who read this document may disregard specific references to U.S. state and federal laws and regulations, as their institutional infrastructure and processes may differ from those of an internal committee such as IACUCs. The principles described herein, however, are applicable to research on fishes regardless of geographic location. Investigators in other nations may benefit by modifying any of the specific provisions pertaining to the United States, thereby adopting guidelines consistent with the laws and regulations of their own government. The UFR Committee urges that the Guidelines be endorsed and adopted (adapted, where necessary) by those state and federal authorities with regulatory responsibilities for fishes, offices with federal oversight (e.g., National Institutes of Health, Office of Laboratory Animal Welfare; http://grants.nih.gov/grants/olaw/olaw.htm ) as well as by universities and other institutions and authorities using fishes and aquatic animals within their research and teaching programs.

Report↗

Incorporation of Fine-Grained Sediment Erodibility Measurements into Sediment Transport Modeling, Capitol Lake, Washington

Capitol Lake was created in 1951 with the construction of a concrete dam and control gate that prevented salt-water intrusion into the newly formed lake and regulated flow of the Deschutes River into southern Puget Sound. Physical processes associated with the former tidally dominated estuary were altered, and the dam structure itself likely caused an increase in retention of sediment flowing into the lake from the Deschutes River. Several efforts to manage sediment accumulation in the lake, including dredging and the construction of sediment traps upriver, failed to stop the lake from filling with sediment. The Deschutes Estuary Feasibility Study (DEFS) was carried out to evaluate the possibility of removing the dam and restoring estuarine processes as an alternative ongoing lake management. An important component of DEFS was the creation of a hydrodynamic and sediment transport model of the restored Deschutes Estuary. Results from model simulations indicated that estuarine processes would be restored under each of four restoration alternatives, and that over time, the restored estuary would have morphological features similar to the predam estuary. The model also predicted that after dam-removal, a large portion of the sediment eroded from the lake bottom would be deposited near the Port of Olympia and a marina located in lower Budd Inlet seaward of the present dam. The volume of sediment transported downstream was a critical piece of information that managers needed to estimate the total cost of the proposed restoration project. However, the ability of the model to predict the magnitude of sediment transport in general and, in particular, the volume of sediment deposition in the port and marina was limited by a lack of information on the erodibility of fine-grained sediments in Capitol Lake. Cores at several sites throughout Capitol Lake were collected between October 31 and November 1, 2007. The erodibility of sediments in the cores was later determined in the lab with Sedflume, an apparatus for measuring sediment erosion-parameters. In this report, we present results of the characterization of fine-grained sediment erodibility within Capitol Lake. The erodibility data were incorporated into the previously developed hydrodynamic and sediment transport model. Model simulations using the measured erodibility parameters were conducted to provide more robust estimates of the overall magnitudes and spatial patterns of sediment transport resulting from restoration of the Deschutes Estuary.

Open-File Report↗

A methodology for the assessment of unconventional (continuous) resources with an application to the Greater Natural Buttes gas field, Utah

The Greater Natural Buttes tight natural gas field is an unconventional (continuous) accumulation in the Uinta Basin, Utah, that began production in the early 1950s from the Upper Cretaceous Mesaverde Group. Three years later, production was extended to the Eocene Wasatch Formation. With the exclusion of 1100 non-productive (“dry”) wells, we estimate that the final recovery from the 2500 producing wells existing in 2007 will be about 1.7 trillion standard cubic feet (TSCF) (48.2 billion cubic meters (BCM)). The use of estimated ultimate recovery (EUR) per well is common in assessments of unconventional resources, and it is one of the main sources of information to forecast undiscovered resources. Each calculated recovery value has an associated drainage area that generally varies from well to well and that can be mathematically subdivided into elemental subareas of constant size and shape called cells. Recovery per 5-acre cells at Greater Natural Buttes shows spatial correlation; hence, statistical approaches that ignore this correlation when inferring EUR values for untested cells do not take full advantage of all the information contained in the data. More critically, resulting models do not match the style of spatial EUR fluctuations observed in nature. This study takes a new approach by applying spatial statistics to model geographical variation of cell EUR taking into account spatial correlation and the influence of fractures. We applied sequential indicator simulation to model non-productive cells, while spatial mapping of cell EUR was obtained by applying sequential Gaussian simulation to provide multiple versions of reality (realizations) having equal chances of being the correct model. For each realization, summation of EUR in cells not drained by the existing wells allowed preparation of a stochastic prediction of undiscovered resources, which range between 2.6 and 3.4 TSCF (73.6 and 96.3 BCM) with a mean of 2.9 TSCF (82.1 BCM) for Greater Natural Buttes. A second approach illustrates the application of multiple-point simulation to assess a hypothetical frontier area for which there is no production information but which is regarded as being similar to Greater Natural Buttes.

Utah↗

Short Course Introduction to Quantitative Mineral Resource Assessments

This is an abbreviated text supplementing the content of three sets of slides used in a short course that has been presented by the author at several workshops. The slides should be viewed in the order of (1) Introduction and models, (2) Delineation and estimation, and (3) Combining estimates and summary. References cited in the slides are listed at the end of this text. The purpose of the three-part form of mineral resource assessments discussed in the accompanying slides is to make unbiased quantitative assessments in a format needed in decision-support systems so that consequences of alternative courses of action can be examined. The three-part form of mineral resource assessments was developed to assist policy makers evaluate the consequences of alternative courses of action with respect to land use and mineral-resource development. The audience for three-part assessments is a governmental or industrial policy maker, a manager of exploration, a planner of regional development, or similar decision-maker. Some of the tools and models presented here will be useful for selection of exploration sites, but that is a side benefit, not the goal. To provide unbiased information, we recommend the three-part form of mineral resource assessments where general locations of undiscovered deposits are delineated from a deposit type's geologic setting, frequency distributions of tonnages and grades of well-explored deposits serve as models of grades and tonnages of undiscovered deposits, and number of undiscovered deposits are estimated probabilistically by type. The internally consistent descriptive, grade and tonnage, deposit density, and economic models used in the design of the three-part form of assessments reduce the chances of biased estimates of the undiscovered resources. What and why quantitative resource assessments: The kind of assessment recommended here is founded in decision analysis in order to provide a framework for making decisions concerning mineral resources under conditions of uncertainty. What this means is that we start with the question of what kinds of questions is the decision maker trying to resolve and what forms of information would aid in resolving these questions. Some applications of mineral resource assessments: To plan and guide exploration programs, to assist in land use planning, to plan the location of infrastructure, to estimate mineral endowment, and to identify deposits that present special environmental challenges. Why not just rank prospects / areas? Need for financial analysis, need for comparison with other land uses, need for comparison with distant tracts of land, need to know how uncertain the estimates are, need for consideration of economic and environmental consequences of possible development. Our goal is to provide unbiased information useful to decision-makers.

Open-File Report↗

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised ( n = 6), semi-supervised ( n = 1), and unsupervised ( n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors ( Gymnogyps californianus ). Unsupervised K-means and EM (expectation–maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: −0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

Ecology and Evolution↗

Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales

Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.

Limnology and Oceanography↗

Adjacent and downstream effects of forest harvest on the distribution and abundance of larval headwater stream amphibians in the Oregon Coast Range

Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs ( Ascaphus truei ), coastal giant salamanders ( Dicamptodon tenebrosus ), and Columbia torrent salamanders ( Rhyacotriton kezeri ) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri . Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.

Oregon↗