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At least 1,009 records · Page 56Linked to original sources
USGS2017

Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities

The U.S. Geological Survey (USGS), in cooperation with the U.S. Nuclear Regulatory Commission, has investigated statistical methods for probabilistic flood hazard assessment to provide guidance on very low annual exceedance probability (AEP) estimation of peak-streamflow frequency and the quantification of corresponding uncertainties using streamgage-specific data. The term “very low AEP” implies exceptionally rare events defined as those having AEPs less than about 0.001 (or 1 × 10 –3 in scientific notation or for brevity 10 –3 ). Such low AEPs are of great interest to those involved with peak-streamflow frequency analyses for critical infrastructure, such as nuclear power plants. Flood frequency analyses at streamgages are most commonly based on annual instantaneous peak streamflow data and a probability distribution fit to these data. The fitted distribution provides a means to extrapolate to very low AEPs. Within the United States, the Pearson type III probability distribution, when fit to the base-10 logarithms of streamflow, is widely used, but other distribution choices exist. The USGS-PeakFQ software, implementing the Pearson type III within the Federal agency guidelines of Bulletin 17B (method of moments) and updates to the expected moments algorithm (EMA), was specially adapted for an “Extended Output” user option to provide estimates at selected AEPs from 10 –3 to 10 –6 . Parameter estimation methods, in addition to product moments and EMA, include L-moments, maximum likelihood, and maximum product of spacings (maximum spacing estimation). This study comprehensively investigates multiple distributions and parameter estimation methods for two USGS streamgages (01400500 Raritan River at Manville, New Jersey, and 01638500 Potomac River at Point of Rocks, Maryland). The results of this study specifically involve the four methods for parameter estimation and up to nine probability distributions, including the generalized extreme value, generalized log-normal, generalized Pareto, and Weibull. Uncertainties in streamflow estimates for corresponding AEP are depicted and quantified as two primary forms: quantile (aleatoric [random sampling] uncertainty) and distribution-choice (epistemic [model] uncertainty). Sampling uncertainties of a given distribution are relatively straightforward to compute from analytical or Monte Carlo-based approaches. Distribution-choice uncertainty stems from choices of potentially applicable probability distributions for which divergence among the choices increases as AEP decreases. Conventional goodness-of-fit statistics, such as Cramér-von Mises, and L-moment ratio diagrams are demonstrated in order to hone distribution choice. The results generally show that distribution choice uncertainty is larger than sampling uncertainty for very low AEP values.

Scientific Investigations Report↗
USGS2017

On the reliability of N‐mixture models for count data

N‐mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p . They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture–recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the “constant p ” assumption) scientifically plausible alternative models in which N (or its expectation) is non‐identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N‐mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p .

Biometrics↗
USGS2012

Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona

This report details the findings of the Bureau of Land Management–U.S. Geological Survey Ecosystem Services Valuation Pilot Study. This project evaluated alternative methods and tools that quantify and value ecosystem services, and it assessed the tools’ readiness for use in the Bureau of Land Management decisionmaking process. We tested these tools on the San Pedro River watershed in northern Sonora, Mexico, and southeast Arizona. The study area includes the San Pedro Riparian National Conservation Area (managed by the Bureau of Land Management), which has been a focal point for conservation activities and scientific research in recent decades. We applied past site-specific primary valuation studies, value transfer, the Wildlife Habitat Benefits Estimation Toolkit, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Artificial Intelligence for Ecosystem Services (ARIES) models to value locally important ecosystem services for the San Pedro River watershed—water, carbon, biodiversity, and cultural values. We tested these approaches on a series of scenarios to evaluate ecosystem service changes and the ability of the tools to accommodate scenarios. A suite of additional tools were either at too early a stage of development to run, were proprietary, or were place-specific tools inappropriate for application to the San Pedro River watershed. We described the strengths and weaknesses of these additional ecosystem service tools against a series of evaluative criteria related to their usefulness for Bureau of Land Management decisionmaking. Using these tools, we quantified gains or losses of ecosystem services under three categories of scenarios: urban growth, mesquite management, and water augmentation. These results quantify tradeoffs and could be useful for decisionmaking within Bureau of Land Management district or field offices. Results are accompanied by a relatively high level of uncertainty associated with model outputs, valuation methods, and discount rates applied. Further guidance on representing uncertainty and applying uncertain results in decisionmaking would benefit both tool developers and those offices in using ecosystem services to compare management tradeoffs. Decisionmakers and Bureau of Land Management managers at the State-, district-, and field-office level would also benefit from continuing model improvements, training, and guidance on tool use that can be provided by the U.S. Geological Survey, the Bureau of Land Management, and the Department of the Interior. Tradeoffs were identified in the level of effort needed to parameterize and run tools and the amount and quality of information they provide to the decision process. We found the Wildlife Habitat Benefits Estimation Toolkit, Ecosystem Services Review, and United Nations Environment Programme–World Conservation Monitoring Centre Ecosystem Services Toolkit to be immediately feasible for application by the Bureau of Land Management, given proper guidance on their use. It is also feasible for the Bureau of Land Management to use the InVEST model, but in early 2012 the process of parameterizing the model required resources and expertise that are unlikely to be available in most Bureau of Land Management district or field offices. Application of past primary valuation is feasible, but developing new primary-valuation studies is too time consuming for regular application. Value transfer approaches (aside from the Wildlife Habitat Benefits Estimation Toolkit) are best applied carefully on the basis of guidelines described in this report, to reduce transfer error. The ARIES model can provide useful information in regions modeled in the past (Arizona, California, Colorado, and Washington), but it lacks some features that will improve its usability, such as a generalized model that could be applied anywhere in the United States. Eleven other tools described in this report could become useful as the tools more fully develop, in high-profile cases for which additional resources are available for tool application or in case-study regions where place-specific models have already been developed. To improve the value of these tools in decisionmaking, we suggest scientific needs that agencies such as U.S. Geological Survey can help meet—for instance, development and support of data archives. Such archives could greatly reduce resource needs and improve the reliability and consistency of results. Given the rapid state of evolution in the field, periodic follow-up studies on ecosystem services tools would help to ensure that the Bureau of Land Management and other public land management agencies are kept up to date on new tools and features that bring ecosystem services closer to readiness for use in regular decisionmaking.

Arizona;Sonora↗
USGS2024

Using local monitoring results to inform the Chesapeake Bay Program’s Watershed Model

The Chesapeake Bay Program’s Watershed Model (CBWM) has been used as an accounting tool for the Chesapeake Bay Total Maximum Daily Load (TMDL). However, some of the fundamental parameters that underpin the watershed model may not represent local watershed characteristics at all scales. Significant investments have been made by state and local governments, and other local stakeholders, who are interested in validating loads and progress in implementing measures to achieve the pollutant reductions called for in the TMDL through local monitoring data. For the purposes of this STAC workshop, local monitoring is considered any relevant data collected by a local, regional, state, or federal organization that has not been used previously in the development, calibration, or validation of the CBWM. Some of these local monitoring efforts have been collecting data over the past 5-10 years, with some datasets extending back over more than two decades. However, the data and the CBWM are often not directly comparable due to differences in temporal and spatial scales or because the water quality parameters being monitored are not those estimated by the model. Therefore, a Scientific and Technical Advisory Committee (STAC) workshop was convened to bring together Chesapeake Bay Program (CBP) modelers, local and state government stakeholders, and scientists who are monitoring and analyzing local water quality data to recommend ways in which local monitoring data can be used to inform the CBWM, identify gaps between modeled and monitored data, and validate model predictions at the local scale. The workshop, “Using Local Monitoring Results to Inform the Chesapeake Bay Program’s Watershed Model”, was held in March 2023 to provide insight on the scope of local water quality monitoring efforts within and outside of the Bay watershed that could be used to inform the CBWM. Scientists and managers developed recommendations that could be used by modelers for either calibration or knowledge generation to inform the Phase 7 version of the CBWM currently under development for a 2027 decision by the CBP, recommendations for how local monitoring efforts could be designed or altered to better inform the CBWM, and recommendations for how monitored trends could be used in management. The preliminary presentations for the workshop provided essential background information on the CBWM and data used to parameterize it. This information was the foundation for discussions on existing data gaps, the importance of current local monitoring networks, and best practices for developing future monitoring networks. More information on this STAC-funded effort including workshop presentation slides and recordings can be accessed on the workshop webpage. Confidence in the loading estimates of the CBWM is critical because of its role as the accounting mechanism for measuring progress toward the Bay TMDL’s nutrient and sediment reduction goals. Those who are being asked or required to pay for these reductions, from state and local government managers to farmers, property owners and developers, must have confidence in the scientific validity of the CBWM’s loading estimates or trust in the restoration effort will dissipate. Toward that end, several local entities have invested in extensive urban, suburban, and agricultural monitoring programs to characterize nutrient and sediment loading (among other water quality parameters) at a relatively fine scale (from a few acres to 5 square miles). Monitoring networks outside of the Bay watershed were also included as their relevance and similarities to Bay watershed landscapes, hydrology, and climate conditions can help build the body of knowledge necessary for better parameterization of the CBWM. Local monitoring results could be analyzed for loads and trends for calibration of Phase 7, comparison against trends, informing the structure and parameterization of the model, and potentially in policy evaluation. The effectiveness of management practices at the small watershed scale is a primary question of watershed managers that could be addressed by local monitoring, but to do so study design and statistical techniques may need to be altered if these datasets are intended to inform parameterization of the Bay modeling tools. The partnership would benefit from the redesign of some existing monitoring programs so that they are hypothesis-driven, with fully described inputs, outputs, and practices. New statistical tools could be applied to evaluate the relative importance of various drivers affecting water quality and influenced by hydrogeologic setting and watershed condition.

Chesapeake Bay watershed↗
USGS2022

Water-quality trends in the Delaware River Basin calculated using multisource data and two methods for trend periods ending in 2018

Many organizations in the Delaware River Basin (DRB) monitor surface-water quality for regulatory, scientific, and decision-making purposes. In support of these purposes, over 260,000 water-quality records provided by 8 different organizations were compiled, screened, and used to generate water-quality trends in the DRB. These trends, for periods of record that end in 2018, were generated for 124 sites and up to 16 constituents using 2 trend methods: the Seasonal Kendall Test and the Weighted Regressions on Time, Discharge, and Season model. Seasonal Kendall Tests were performed on all water-quality records to detect monotonic trends in concentration over the period of record and for as many as four additional trend periods (1978–2018, 1998–2018, 2003–18, and 2008–18). The Weighted Regressions on Time, Discharge, and Season model was applied to water-quality records that passed more stringent screening criteria and was used to detect monontonic and nonmonotonic trends, account for variations in streamflow, and estimate annual concentrations. These two trend methods produced different trend directions less than 1 percent of the time, illustrating general agreement between the methods despite the different approaches and data input requirements. Overall, the changes in concentration for salinity constituents (specific conductance and total dissolved solids), chloride, and sodium were increases; those increases were some of the largest changes observed in the basin, and they occurred at faster rates over time. Total dissolved solids concentration trends at 4 of the 60 sites increased from below to above the level of concern threshold (a secondary drinking water threshold) over the period of record, indicating potentially meaningful degradation in water quality. Nutrient constituent (ammonia, nitrate, orthophosphate, total nitrogen, and total phosphorus) concentrations tended to decrease over the period of record, although fewer sites had significant trends and the changes in concentration were smaller compared to the salinity constituents. Total nitrogen and total phosphorus were the only nutrient constituents to have decreasing concentration trends that crossed from above to below the level of concern threshold, U.S. Environmental Protection Agency (EPA) ecoregional nutrient criteria, (EPA, undated c). This finding indicates water-quality improvement at sites with these trends (nine sites with total nitrogen trends and one site with a total phosphorus trend), although many sites were still in exceedance of the level of concern. Trends for total suspended solids and some major ions (calcium, magnesium, potassium) were largely nonsignificant or variable between sites, with no prevalent patterns across the DRB; however, sulfate concentrations decreased at most sites. Cumulative land-surface change within each watershed had a strong positive relation with changes in water-quality concentrations for the salinity constituents and most major ions, but not for the other constituents, indicating that land-surface changes are related to the sources and transport of these constituents. Investigating long-term trends (a decade or longer) in water quality can help the DRB water management community quantify the success of management practices and identify potential threats to water availability.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2011

Thermal profiles for selected river reaches in the Stillaguamish River basin, Washington, August 2011

Datums Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83). Abstract Longitudinal profiles of near-streambed temperature were collected for eight river reaches in the Stillaguamish River basin, Washington, during August 2011, to provide information about areas of groundwater discharge to streams. During summer, groundwater discharge can be a source of cold water to streams that regulates warm stream temperatures creating cold-water thermal refugia for native stream biota including salmon and trout. To assess areas of groundwater discharge to streams, temperature was measured using a probe with an internal datalogger towed behind a watercraft moving downstream at ambient stream velocity. The data were referenced to location, concurrently surveyed with a Global Positioning System, during collection of the water temperature data. Data are presented as Microsoft Excel® files consisting of date and time, near-streambed water temperature, and latitude and longitude. Introduction Longitudinal profiles of near-streambed temperatures surveyed at ambient river velocity in a Lagrangian framework provide information about potential areas of groundwater discharge as well as salmonid habitat and thermal refugia (Vaccaro and Maloy, 2006). Longitudinal thermal profiles have previously been surveyed in several rivers in Washington, including the Yakima River and tributaries (Vaccaro and others, 2008) and the Nooksack River (Cox and others, 2005). This report presents eight thermal profiles within the Stillaguamish River basin including parts of the North Fork Stillaguamish River, South Fork Stillaguamish River, Jim Creek, and Pilchuck Creek (fig. 1). This data augments previous investigations of longitudinal temperature variations within the Stillaguamish River and tributaries by thermal infrared radar by the Washington State Department of Ecology (Watershed Sciences, 2002), and may be used as a tool to develop a better understanding of groundwater/surface-water interactions within the Stillaguamish River basin. Purpose and Scope The purpose of this report is to present longitudinal thermal profiles of stream temperature of streams within the Stillaguamish River basin including the North Fork Stillaguamish River, the South Fork Stillaguamish River, Pilchuck Creek, and Jim Creek. This data may be used to determine zones of groundwater discharge and improve understanding of the relation between the groundwater and surface water systems of the Stillaguamish River basin. Description of Study Area The Stillaguamish River basin is in northwestern Washington and is bounded to the east by the Cascade Mountains, to the west by Puget Sound, to the north by the Skagit River basin, and to the south by the Snohomish River basin (fig. 1). The Stillaguamish River basin is characterized by cool, wet winters and warm, dry summers. Mean annual discharge of the North Fork Stillaguamish River (North Fork Stillaguamish River near Arlington, Washington, USGS gaging station 12167000) for water years 1929-2010 is 1,898 ft 3 /s and mean annual discharge of the South Fork Stillaguamish River (South Fork Stillaguamish River near Granite Falls, Washington gaging station 12161000) for water years 1929-1980 is 1,071 ft 3 /s. Jim Creek is a tributary of the South Fork Stillaguamish River and Pilchuck Creek is a tributary of the mainstem Stillaguamish River. Thermal Profile Survey Continuous water temperature and Global Positioning System (GPS) data were collected at 3-second intervals while drifting downstream at ambient stream velocity in a Lagrangian framework following the method of Vaccaro and Maloy (2006) for Pilchuck Creek between river mile (RM) 0.0 and 3.7 (table 1); the North Fork Stillaguamish River between RM 0.0 and 34.2 (tables 2-5); South Fork Stillaguamish River between RM 17.7 and 33.4 (tables 6-7); and Jim Creek between RM 0.0 and 7.0 (table 8). Profiling at ambient stream velocity in a Lagrangian framework tracks a parcel of water as it moves downstream during the day; departures from the diurnal heating cycle may be due to groundwater input, surface-water inflows, or riparian shading. Continuous temperature was measured using a Solinst® Levelogger LT temperature probe verified by a National Institute of Standards and Technology (NIST) certified thermistor and position data was measured using a Garmin® GPSmap® 60Csx for the eight surveys during August 15-26, 2011. The temperature probe was towed behind a watercraft following the stream thalweg and dragged along the streambed except when in-stream obstacles prevented probe movement downstream. The location of each temperature measurement was determined by relating the time stamp of the GPS data to the temperature data. If a GPS location was not recorded at the same time as a temperature measurement, the location of the temperature measurement was determined by linear interpolation of the two GPS known locations that bracket the time of the temperature measurement. A 0.5-mi gap exists between the beginning of the North Fork Stillaguamish datasets collected on August 18 (table 4) and August 22 (table 5) because of inadequate equilibration of the temperature probe to ambient stream temperature during the initial 0.5 mi of the August 22 survey. Distribution of Information An Excel file of tables 1-8 that include the thermal-profile data for each longitudinal thermal profile is available at http://pubs.usgs.gov/ds/654/ds654_tables.xls. Table 1. Temperature and Global Positioning System location data for the Pilchuck Creek (RM 0.0-3.7), August 15, 2011. Table 2. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 30.0-34.2), August 16, 2011. Table 3. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 17.6-30.0), August 17, 2011. Table 4. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 9.5-17.6), August 18, 2011. Table 5. Temperature and Global Positioning System location data for the North Fork Stillaguamish River (RM 0.0-9.0), August 22, 2011. Table 6. Temperature and Global Positioning System location data for the South Fork Stillaguamish River (RM 25.9-33.4), August 24, 2011. Table 7. Temperature and Global Positioning System location data for the South Fork Stillaguamish River (RM 17.7-25.9), August 26, 2011. Table 8. Temperature and Global Positioning System location data for Jim Creek (RM 0.0-7.0), August 25, 2011. References Cited Cox, S.E., Simonds, F.W., Doremus, L., Huffman, R.L., and Defawe, R.M., 2005, Ground water/surface water interactions and quality of discharging ground water in streams of the lower Nooksack River Basin, Whatcom County, Washington: U.S. Geological Survey Scientific Investigations Report 2005-5255, 46 p Vaccaro, J.J., Keys, M.E., Julich, R.J., and Welch, W.B., 2008, Thermal profiles for selected river reaches in the Yakima River basin, Washington: U.S. Geological Survey Data Series 342 (Available at http://pubs.usgs.gov/ds/342/). Vaccaro, J.J., and Maloy, K.J., 2006, A thermal profile method to identify potential ground-water discharge areas and preferred salmonid habitats for long river reaches: U.S. Geological Survey Scientific Investigations Report 2006-5136, 16 p. Watershed Sciences, LLC, 2002, Aerial surveys in the Stillaguamish and Skagit River Basins-Thermal infrared and color videography: Corvallis, Oreg., Water Sciences, for Washington Department of Ecology, 28 p.

Data Series↗
USGS2009

Physical property data from the ICDP-USGS Eyreville cores A and B, Chesapeake Bay impact structure, Virginia, USA, acquired using a multisensor core logger

The International Continental Scientific Drilling Program (ICDP) and the U.S. Geological Survey (USGS) drilled three core holes to a composite depth of 1766 m within the moat of the Chesapeake Bay impact structure. Core recovery rates from the drilling were high (??90%), but problems with core hole collapse limited the geophysical downhole logging to natural-gamma and temperature logs. To supplement the downhole logs, ??5% of the Chesapeake Bay impact structure cores was processed through the USGS GeoTek multisensor core logger (MSCL) located in Menlo Park, California. The measured physical properties included core thickness (cm), density (g cm -3 ), P-wave velocity (m s -1 ), P-wave amplitude (%), magnetic susceptibility (cgs), and resistivity (ohm-m). Fractional porosity was a secondary calculated property. The MSCL data-sampling interval for all core sections was 1 cm longitudinally. Photos of each MSCL sampled core section were imbedded with the physical property data for direct comparison. These data have been used in seismic, geologic, thermal history, magnetic, and gravity models of the Chesapeake Bay impact structure. Each physical property curve has a unique signature when viewed over the full depth of the Chesapeake Bay impact structure core holes. Variations in the measured properties reflect differences in pre-impact target-rock lithologies and spatial variations in impact-related deformation during late-stage crater collapse and ocean resurge. ?? 2009 The Geological Society of America.

Special Paper of the Geological Society of America↗
USGS2012

User’s guide and metada for the PICES Nonindigenous Species Information System

Introduction Welcome to the PICES Nonindigenous Species Information System, a Microsoft Access database that displays the biogeographic distributions, invasion status, vectors, and key life history attributes of the approximately 740 reported nonindigenous species (NIS) in the estuarine and near-coastal habitats of the North Pacific and Hawaii. This database was developed by the U.S. Environmental Protection Agency and the U.S. Geological Survey under the auspices of Working Group 21 (Invasive Species) of the North Pacific Marine Science Organization (PCIES). The PICES database contains the data used to generate the “Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific” (Lee and Reusser, 2012; herein referred to as the “Atlas”). The User’s Guide provides instructions on how to use the PICES database as well as metadata for the database and the Atlas. We note that for most users, the Atlas provides a simpler approach to accessing key information on NIS in the PICES countries than the database, though the database does provide additional information on species and sources as well as allowing users to extract information on specific taxa and/or locations (see Section 4). The PICES database also includes species reported from the PICES Rapid Assessment Surveys (RAS). PICES sponsored four rapid assessment surveys with the objective of quickly characterizing the native, non-native, and cryptogenic species present in different locations. Surveys were sponsored in Dalian, China in 2008, Jeju, Korea in 2009, Newport, Oregon, USA in 2010, and Peter the Great Bay, near Vladivostok and Nakhodka, Russia in 2011 ( http://www.pices.int/publications/pices_press/volume19/v19_n1/pp_30-31_Kobe-WS_f.pdf , http://www.pices.int/publications/pices_press/volume20/v20_n1/pp_26-29_RAS-2011.pdf ). The PICES database contains the RAS species that were made available in time for inclusion. Thus, the database does not capture all the species found in these surveys. In addition, much of the information on the RAS species was provided by the experts conducting the survey, and their distributions, environmental requirements, and life history attributes were not evaluated to the same level of detail by the PICES authors as the North Pacific NIS. In lieu of the more extensive review as conduced with the Atlas species, the information on the RAS species needs to be considered preliminary. Additionally, it is important to use the “Map All Distributions” option (see Section 3.6.6) when mapping their distribution or conducting a query. The general reference for the RAS surveys in the PICES database is “PICES Working Group 21, YEAR SURVEY”. The overall goal of both the database and Atlas was to simplify and standardize the dissemination of distributional, habitat, and life history characteristics of near-coastal and estuarine nonindigenous species. This database provides a means of querying these data and displaying the information in a consistent format. The specific classes of information the database captures include: Regional and global ranges of native and nonindigenous near-coastal and estuarine species at different hierarchical spatial scales. Habitat and physiological requirements of near-coastal and estuarine species. Life history characteristics of near-coastal and estuarine species. Invasion history and vectors for nonindigenous species. This standardized and synthesized data in the database and the Atlas provide the basic information needed to address a number of managerial and scientific needs. Thus, users will be able to: Create a baseline on the extent of invasion by region in order to assess new invasions. Use existing geographical patterns of invasion to gain some insights into potential new invaders. Use existing geographical patters of invasion to gain some insights into mechanisms affecting relative invasibility of different areas. Use life history attributes and environmental requirements of the reported nonindigenous species to evaluate traits of invaders. Understand the potential spread of invaders based on their habitat and environmental requirements. Understand importance of different vectors of introduction of nonindigenous species by region. The data in the Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific (Lee and Reusser, 2012) are up-to-date as of June 2012. Updates to the PICES database were made in September 2012.

Report↗
USGS2016

ChemCam activities and discoveries during the nominal mission of the Mars Science Laboratory in Gale crater, Mars

At Gale crater, Mars, ChemCam acquired its first laser-induced breakdown spectroscopy (LIBS) target on Sol 13 of the landed portion of the mission (a Sol is a Mars day). Up to Sol 800, more than 188 000 LIBS spectra were acquired on more than 5800 points distributed over about 650 individual targets. We present a comprehensive review of ChemCam scientific accomplishments during that period, together with a focus on the lessons learned from the first use of LIBS in space. For data processing, we describe new tools that had to be developed to account for the uniqueness of Mars data. With regard to chemistry, we present a summary of the composition range measured on Mars for major-element oxides (SiO 2 , TiO 2 , Al 2 O 3 , FeO T , MgO, CaO, Na 2 O, K 2 O) based on various multivariate models, with associated precisions. ChemCam also observed H, and the non-metallic elements C, O, P, and S, which are usually difficult to quantify with LIBS. F and Cl are observed through their molecular lines. We discuss the most relevant LIBS lines for detection of minor and trace elements (Li, Rb, Sr, Ba, Cr, Mn, Ni, and Zn). These results were obtained thanks to comprehensive ground reference datasets, which are set to mimic the expected mineralogy and chemistry on Mars. With regard to the first use of LIBS in space, we analyze and quantify, often for the first time, each of the advantages of using stand-off LIBS in space: no sample preparation, analysis within its petrological context, dust removal, sub-millimeter scale investigation, multi-point analysis, the ability to carry out statistical surveys and whole-rock analyses, and rapid data acquisition. We conclude with a discussion of ChemCam performance to survey the geochemistry of Mars, and its valuable support of decisions about selecting where and whether to make observations with more time and resource-intensive tools in the rover's instrument suite. In the end, we present a bird's-eye view of the many scientific results: discovery of felsic Noachian crust, first observation of hydrated soil, discovery of manganese-rich coatings and fracture fills indicating strong oxidation potential in Mars' early atmosphere, characterization of soils by grain size, and wide scale mapping of sedimentary strata, conglomerates, and diagenetic materials.

Journal of Analytical Atomic Spectrometry↗
USGS2001

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

Hydrological Processes↗
USGS2015

Diel cycling of trace elements in streams draining mineralized areas: a review

Many trace elements exhibit persistent diel, or 24-h, concentration cycles in streams draining mineralized areas. These cycles can be caused by various physical and biogeochemical mechanisms including streamflow variation, photosynthesis and respiration, as well as reactions involving photochemistry, adsorption and desorption, mineral precipitation and dissolution, and plant assimilation. Iron is the primary trace element that exhibits diel cycling in acidic streams. In contrast, many cationic and anionic trace elements exhibit diel cycling in near-neutral and alkaline streams. Maximum reported changes in concentration for these diel cycles have been as much as a factor of 10 (988% change in Zn concentration over a 24-h period). Thus, monitoring and scientific studies must account for diel trace-element cycling to ensure that water-quality data collected in streams appropriately represent the conditions intended to be studied.

Applied Geochemistry↗
USGS2012

Enhanced visualization for the interpretation of Magellan radar data: Supplement to the Magellan special issue

The differences of radar data from more familiar photographic images, coupled with the unique geologic characteristics of Venus's surface, can make interpretation of the standard Magellan data products difficult for both planetary scientists and nonspecialists. We describe a set of digital processing techniques for transforming individual remote‐sensing datasets in order to make the information they contain more apparent, and for combining multiple datasets of diverse resolution and information content into synthetic images that allow the viewer to explore correlations among the data. The creation of derived data products by techniques like those we describe is becoming increasingly widespread and important, both for scientific research and for use in educational and media presentations. We apply our processing techniques to Magellan synthetic aperture radar images, altimetry, and microwave emissivity measurements of four areas that exemplify some of the most important styles of geologic activity on Venus.

Journal of Geophysical Research E: Planets↗
USGS2018

Stratifying ocean sampling globally and with depth to account for environmental variability

With increasing depth, the ocean is less sampled for physical, chemical and biological variables. Using the Global Marine Environmental Datasets (GMED) and Ecological Marine Units (EMUs) , we show that spatial variation in environmental variables decreases with depth. This is also the case over temporal scales because seasonal change, surface weather conditions, and biological activity are highest in shallow depths. A stratified sampling approach to ocean sampling is therefore proposed whereby deeper environments, both pelagic and benthic, would be sampled with relatively lower spatial and temporal resolutions. Sampling should combine measurements of physical and chemical parameters with biological species distributions, even though species identification is difficult to automate. Species distribution data are essential to infer ecosystem structure and function from environmental data. We conclude that a globally comprehensive, stratification-based ocean sampling program would be both scientifically justifiable and cost-effective.

Scientific Reports↗
USGS2020

Scenarios for valuing sample information in natural resources

Uncertainty is ubiquitous in natural resource systems, science and management. Sample data are obtained in order to reduce uncertainty, thereby increasing knowledge and improving resource management, but sampling always comes at a cost of some sort. Is that cost worthwhile? Analysis of the value of sample information ( VSI ) addresses this question. In this paper we develop the valuation of sample information in terms of five elements: (a) a system whose attributes are the focus of analysis; (b) a range of management actions that affect the system's status; (c) uncertainty about system status or structure, as characterized by initial (prior) probabilities of possible system states or structures; (d) an experiment or other information source that produces new data points and updated (posterior) probabilities; and (e) a value measure that is a function of the management action taken, conditional on either the system state or structure. We describe five scenarios for analysing the VSI under uncertainty about system structure and state. Scenarios 1–3 comprise analyses of conditional, expected and optimal expected values of sample information. They focus primarily on choice of management adaptations with new information. Scenarios 4 and 5 involve pre-selected management actions, and are useful for comparing designs of data collection rather than for choosing a management action. These last scenarios expand the framework for VSI to include actions that have been selected independently of the updating of uncertainty. We discuss other extensions of VSI analysis, which include spatial applications, hybrid scenarios, applications involving dynamic systems, and a focus on costs rather than net benefits. Value of sample information analysis holds promise in emerging areas of ecology such as ecological forecasting and the use of remote sensing in conservation, where potential new data from models and satellites can be evaluated in advance, thereby allowing more efficient prioritization of scientific efforts. More generally, VSI can contribute to better ecological understanding and more effective management in a wide range of ecological situations.

Methods in Ecology and Evolution↗
USGS2024

Perspectives on the future of host-microbe biology from the Council on Microbial Sciences of the American Society for Microbiology

Host-microbe biology (HMB) stands on the cusp of redefinition, challenging conventional paradigms to instead embrace a more holistic understanding of the microbial sciences. The American Society for Microbiology (ASM) Council on Microbial Sciences hosted a virtual retreat in 2023 to identify the future of the HMB field and innovations needed to advance the microbial sciences. The retreat presentations and discussions collectively emphasized the interconnectedness of microbes and their profound influence on humans, animals, and environmental health, as well as the need to broaden perspectives to fully embrace the complexity of these interactions. To advance HMB research, microbial scientists would benefit from enhancing interdisciplinary and transdisciplinary research to utilize expertise in diverse fields, integrate different disciplines, and promote equity and accessibility within HMB. Data integration will be pivotal in shaping the future of HMB research by bringing together varied scientific perspectives, new and innovative techniques, and ’omics approaches. ASM can empower under-resourced groups with the goal of ensuring that the benefits of cutting-edge research reach every corner of the scientific community. Thus, ASM will be poised to steer HMB toward a future that champions inclusivity, innovation, and accessible scientific progress.

mSphere↗
USGS2001

Petroleum systems and assessment of the South Florida Basin

This CD-ROM contains coverages that define and outline the geographic boundaries of petroleum systems and assessment units and text that describes the geology and reasoning to support the assessment of undiscovered oil and gas resources in the South Florida Basin for a forecast period of 30 years. This assessment was performed by using the best geological information and scientific theory available to the USGS; however, the USGS did not have access to seismic survey data for the South Florida Basin.

Florida↗
USGS1999

Monitoring the Water Quality of the Nation's Large Rivers: Mississippi River Basin NASQAN Program

The U.S. Geological Survey (USGS) has monitored water quality in the Mississippi River Basin as part of the National Stream Quality Accounting Network (NASQAN) since 1995, applying a basinwide perspective to understanding water quality on a regional scale (Hooper and others, 1997). The objectives of the Mississippi River Basin NASQAN Program are to provide an ongoing characterization of the concentrations and mass fluxes of sediment and chemicals at key locations in the basin, to determine regional source areas for these materials, and to assess the effect of human influences on observed concentrations and fluxes. NASQAN complements the ongoing USGS National Water-Quality Assessment (NAWQA) Program, which is performing a detailed assessment in 23 subbasins within the Mississippi River Basin (Hirsch and others, 1988). NASQAN monitors the large rivers in the Mississippi River Basin, downstream of NAWQA study units. NASQAN, in conjunction with NAWQA, can provide the data and information needed by other USGS programs, Federal and State agencies, other segments of the scientific community, and by the public to address the present and future status of water quality in the Mississippi River Basin.

Fact Sheet↗
USGS2004

The value of long-term monitoring in the development of ground-water-flow models

As environmental issues have come to the forefront of public concern, so has the awareness of the importance of ground water in the overall water cycle and as a source of the Nation’s drinking water. Heightened interest has spawned a host of scientific enterprises (Taylor and Alley, 2001). Some activities are directed toward collection of water-level data and related information to monitor the physical and chemical state of the resource. Other activities are directed at interpretive studies undertaken, for example, to optimize the location of new water-supply wells or to protect rivers and lakes fed by ground water. An important type of interpretive study is the computer ground-water-flow model that inte- grates field data in a mathematical framework. Long-term, systematic collection of hydro- logic data is crucial to the construction and testing of ground-water models so that they can reproduce the evolution of flow systems and forecast future conditions.

Wisconsin↗