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USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

Authorea↗
USGS2017

Challenges and solutions for applying the travel cost demand model to geographically remote visitor destinations: A case study of bear viewing at Katmai National Park and Preserve

Remote and unique destinations present difficulties when attempting to construct traditional travel cost models to value recreation demand. The biggest limitation comes from the lack of variation in the dependent variable, defined as the number of trips taken over a set time frame. There are various approaches that can be used for overcoming limitations of the traditional travel cost model in the context of remote destinations. This study applies an adaptation of the standard model to estimate recreation benefits of bear viewing at Katmai National Park and Preserve in Alaska, which represents a once-in-a-lifetime experience for many visitors. Results demonstrate that visitors to this park’s Brooks Camp area are willing to pay an average of US$287 per day of bear viewing. Implications of these findings for valuing recreation at other remote destinations are discussed.

Alaska↗
USGS2009

EAARL Coastal Topography-Assateague Island National Seashore, 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for pre-survey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗
USGS2009

EAARL Coastal Topography-Assateague Island National Seashore, 2008: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for pre-survey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗
USGS2003

Geographic analysis and monitoring at the United States Geological Survey

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

Cartography and Geographic Information Science↗
USGS2014

Geochronology of plutonic rocks and their tectonic terranes in Glacier Bay National Park and Preserve, southeast Alaska

We have identified six major belts and two nonbelt occurrences of plutonic rocks in Glacier Bay National Park and Preserve and characterized them on the basis of geologic mapping, igneous petrology, geochemistry, and isotopic dating. The six plutonic belts and two other occurrences are, from oldest to youngest: (1) Jurassic (201.6–145.5 Ma) diorite and gabbro of the Lituya belt; (2) Late Jurassic (161.0–145.5 Ma) leucotonalite in Johns Hopkins Inlet; (3) Early Cretaceous (145.5–99.6 Ma) granodiorite and tonalite of the Muir-Chichagof belt; (4) Paleocene tonalite in Johns Hopkins Inlet (65.5–55.8 Ma); (5) Eocene granodiorite of the Sanak-Baranof belt; (6) Eocene and Oligocene (55.8–23.0 Ma) granodiorite, quartz diorite, and granite of the Muir-Fairweather felsic-intermediate belt; (7) Eocene and Oligocene (55.8–23.0 Ma) layered gabbros of the Crillon-La Perouse mafic belt; and (8) Oligocene (33.9–23.0 Ma) quartz monzonite and quartz syenite of the Tkope belt. The rocks are further classified into 17 different combination age-compositional units; some younger belts are superimposed on older ones. Almost all these plutonic rocks are related to Cretaceous and Tertiary subduction events. The six major plutonic belts intrude the three southeast Alaska geographic subregions in Glacier Bay National Park and Preserve, from west to east: (1) the Coastal Islands, (2) the Tarr Inlet Suture Zone (which contains the Border Ranges Fault Zone), and (3) the Central Alexander Archipelago. Each subregion includes rocks assigned to one or more tectonic terranes. The various plutonic belts intrude different terranes in different subregions. In general, the Early Cretaceous plutons intrude rocks of the Alexander and Wrangellia terranes in the Central Alexander Archipelago subregion, and the Paleogene plutons intrude rocks of the Chugach, Alexander, and Wrangellia terranes in the Coastal Islands, Tarr Inlet Suture Zone, and Central Alexander Archipelago subregions.

Alaska↗
USGS2019

A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns

Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r 2 ) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.

Applied Sciences↗
USGS2011

LANDFIRE 2001 and 2008 Refresh Geographic Area Report--Pacific Southwest

The LANDFIRE National project (LF_1.0.0) was successfully completed in 2009. The goal of LANDFIRE National was to generate consistent 2001 vintage 30 meter spatial data sets for all 50 states for fire and other natural resource applications. This report highlights results from the continuation of LANDFIRE as a program to update the spatial data layers through 2008. The focus of this phase of the program was to improve the data products and account for vegetation change across the landscape caused by wildland fire, fuel and vegetation treatments, and (or) management. In addition, changes caused by insects and disease, storms, invasive plants, and other natural or anthropogenic events were incorporated when appropriate data were available. This report describes the LANDFIRE 2001/2008 Refresh effort to update existing map layers to reflect more current conditions, focusing primarily on vegetation changes. The effort incorporated user feedback and new data, producing two comprehensive Refresh data product sets: 1. LANDFIRE 2001 Refresh (LF_1.0.5) enhanced LANDFIRE map layers by incorporating user feedback and additional data to provide a foundation to update data to 2008. It was also designed to provide users with a data set to help facilitate comparisons between 2001 and 2008 (i.e. Refresh LF_1.1.0) data sets. 2. LANDFIRE 2008 Refresh (LF_1.1.0) updated map layers to reflect vegetation changes and disturbances that occurred between 1999 and 2008. In this report, we (1) address the background and provide details pertaining to why there are two Refresh data sets, (2) explain the requirements, planning, and procedures behind the completion and delivery of the updated products for each of the data product sets, (3) show and describe results, and (4) provide case studies illustrating the performance of LANDFIRE National, LANDFIRE 2001 Refresh and LANDFIRE 2008 Refresh (LF_1.1.0) data products on some example wildland fires.

Report↗
USGS1978

Hydrologic Unit Map-1978, state of South Dakota

This map and accompanying table show Hydrologic Unites that are basically hydrographic in nature. The Cataloging Unites shown supplant the Cataloging Units previously depicted n the 1974 State Hydrologic Unit Map. The boundaries as shown have been adapted from the 1974 State Hydrologic Unit Map, "The Catalog of Information on Water Data" (1972), "Water Resources Regions and Subregions for the National Assessment of Water and Related Land Resources" by the U.S. Water Resources Council (1970), "River Basin of the United States" by the U.S. Soil Conservation Service (1963, 1970), "River Basin Maps Showing Hydrologic Stations" by the Inter-Agency Committee on Water Resources, Subcommittee on Hydrology (1961), and State planning maps. The Political Subdivision has been adopted from "Counties and County Equivalents of the States if the United States" presented in Federal Information Processing Standards Publication 6-2, issued by the National Bureau of Standards (1973) in which each county or county equivalent is identified by a 2-character State code and a 3-character county code. The Regions, Subregions and Accounting Units are aggregates of the Cataloging Unites. The Regions and Sub regions are currently (1978) used by the U.S> Water Resources Council for comprehensive planning, including the National Assessment, and as a standard geographical framework for more detailed water and related land-resources planning. The Accounting Units are those currently (1978) in use by the U.S. Geological Survey for managing the National Water Data Network. This map was revised to include a boundary realinement between Cataloging Units 10140103 and 10160009.

South Dakota↗
USGS2010

EAARL coastal topography and imagery-Fire Island National Seashore, New York, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired on July 9 and August 3, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral CIR camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2020

Water quality and ecological risk assessment of intermittent streamflow through mining and urban areas of San Marcos River sub-basin, Mexico

Intermittent rivers are becoming more ecologically stressed worldwide. Flow cessation occurs naturally and spatiotemporally in these systems and anthropogenic activities such as wastewater discharges can have considerable impacts. Public entities mostly monitor water quality in permanent streams, leading to insufficient monitoring of intermittent streams and consequently to their potentially inadequate management.. This study analyzed spatiotemporal patterns of water quality and associated ecological risk through the quantification of physicochemical and microbiological pollutants in the intermittent river system of El Novillo and San Marcos in Northeast Mexico. Results showed that water quality varied geographically and seasonally. Based on national and international criteria, annual averages of water quality parameters analyzed suggested that streamflow in these river systems is of poor quality and poses high ecological risk to aquatic life. In the urban area, annual mean concentrations of Cd and Pb (0.14 and 0.4 mg/L) were 77- and 10-fold higher than their respective water quality criteria (<0.0018 and 0.04 mg/L). Statistically significant (q < 0.05) correlations were identified in concentrations of cyanide, Cd, Cu and Pb between wastewater seeping into the river and streamflow within the urban area. These observations highlight the unique sensitivity of intermittent urban streams to anthropogenic activities and may provide useful information to enhance current water management plans for the El Novillo-San Marcos River system for the protection of ecosystem integrity and human health.

El Novillo Canyon↗
USGS2013

Comparing bacterial community composition between healthy and white plague-like disease states in Orbicella annularis using PhyloChip™ G3 microarrays

Coral disease is a global problem. Diseases are typically named or described based on macroscopic changes, but broad signs of coral distress such as tissue loss or discoloration are unlikely to be specific to a particular pathogen. For example, there appear to be multiple diseases that manifest the rapid tissue loss that characterizes &lsquo;white plague.&rsquo; PhyloChip&trade; G3 microarrays were used to compare the bacterial community composition of both healthy and white plague-like diseased corals. Samples of lobed star coral ( Orbicella annularis , formerly of the genus Montastraea [1] ) were collected from two geographically distinct areas, Dry Tortugas National Park and Virgin Islands National Park, to determine if there were biogeographic differences between the diseases. In fact, all diseased samples clustered together, however there was no consistent link to Aurantimonas coralicida , which has been described as the causative agent of white plague type II. The microarrays revealed a large amount of bacterial heterogeneity within the healthy corals and less diversity in the diseased corals. Gram-positive bacterial groups (Actinobacteria, Firmicutes) comprised a greater proportion of the operational taxonomic units (OTUs) unique to healthy samples. Diseased samples were enriched in OTUs from the families Corynebacteriaceae, Lachnospiraceae, Rhodobacteraceae, and Streptococcaceae. Much previous coral disease work has used clone libraries, which seem to be methodologically biased toward recovery of Gram-negative bacterial sequences and may therefore have missed the importance of Gram-positive groups. The PhyloChip&trade; data presented here provide a broader characterization of the bacterial community changes that occur within Orbicella annularis during the shift from a healthy to diseased state.

Dry Tortugas National Park, St. John, Virgin Islan↗
USGS2012

Occurrence of pesticides in water and sediment collected from amphibian habitats located throughout the United States, 2009-10

Water and bed-sediment samples were collected by the U.S. Geological Survey (USGS) in 2009 and 2010 from 11 sites within California and 18 sites total in Colorado, Georgia, Idaho, Louisiana, Maine, and Oregon, and were analyzed for a suite of pesticides by the USGS. Water samples and bed-sediment samples were collected from perennial or seasonal ponds located in amphibian habitats in conjunction with research conducted by the USGS Amphibian Research and Monitoring Initiative and the USGS Toxic Substances Hydrology Program. Sites selected for this study in three of the states (California, Colorado, and Orgeon) have no direct pesticide application and are considered undeveloped and remote. Sites selected in Georgia, Idaho, Louisiana, and Maine were in close proximity to either agricultural or suburban areas. Water and sediment samples were collected once in 2009 during amphibian breeding seasons. In 2010, water samples were collected twice. The first sampling event coincided with the beginning of the frog breeding season for the species of interest, and the second event occurred 10-12 weeks later when pesticides were being applied to the surrounding areas. Additionally, water was collected during each sampling event to measure dissolved organic carbon, nutrients, and the fungus, Batrachochytrium dendrobatidis , which has been linked to amphibian declines worldwide. Bed-sediment samples were collected once during the beginning of the frog breeding season, when the amphibians are thought to be most at risk to pesticides. Results of this study are reported for the following two geographic scales: (1) for a national scale, by using data from the 29 sites that were sampled from seven states, and (2) for California, by using data from the 11 sampled sites in that state. Water samples were analyzed for 96 pesticides by using gas chromatography/mass spectrometry. A total of 24 pesticides were detected in one or more of the 54 water samples, including 7 fungicides, 10 herbicides, 4 insecticides, 1 synergist, and 2 pesticide degradates. On a national scale, aminomethylphosphonic acid (AMPA), the primary degradate of the herbicide glyphosate, which is the active ingredient in Roundup&reg;, was the most frequently detected pesticide in water (16 of 54 samples) followed by glyphosate (8 of 54 samples). The maximum number of pesticides observed at a single site was nine compounds in a water sample from a site in Louisiana. The maximum concentration of a pesticide or degradate observed in water was 2,880 nanograms per liter of clomazone (a herbicide) at a site in Louisiana. In California, a total of eight pesticides were detected among all of the low and high elevation sites; AMPA was the most frequently detected pesticide, but glyphosate was detected at the highest concentrations (1.1 micrograms per liter). Bed-sediment samples were analyzed for 94 pesticides by using accelerated solvent extraction, gel permeation chromatography for sulfur removal, and carbon/alumina stacked solid-phase extraction cartridges to remove interfering sediment matrices. In bed sediment, 22 pesticides were detected in one or more of the samples, including 9 fungicides, 3 pyrethroid insecticides, p,p' -dichlorodiphenyltrichloroethane ( p,p' -DDT) and its major degradates, as well as several herbicides. Pyraclostrobin, a strobilurin fungicide, and bifenthrin, a pyrethroid insecticide, were detected most frequently. Maximum pesticide concentrations ranged from less than their respective method detection limits to 1,380 micrograms per kilogram (tebuconazole in California). The number of pesticides detected in samples from each site ranged from zero to six compounds. The sites with the greatest number of pesticides were in Maine and Oregon with six pesticides detected in one sample from each state, followed by Georgia with four pesticides in one sample. For California, a total of 10 pesticides were detected among all sites, and 4 pesticides were detected at both low and high elevation sites; tebuconazole and pyraclostrobin were the two most frequently detected pesticides in California. For the other six selected states, the most frequently detected pesticides in bed sediment were pyraclostrobin (detected in 17 of 42 samples), bifenthrin (detected in 14 of 42 samples), and tebuconazole (detected in 10 of 42 samples). The fungus, Batrachochytrium dendrobatidis (Bd), was detected in water samples in sites from four of the seven states during 2009 and 2010, and the number of zoospore equivalents per liter of water in samples where Bd was detected ranged from 1.6 to 343. Bd was not detected in water samples from sites in Georgia, Louisiana, and Oregon.

Data Series↗
USGS2003

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

Open-File Report↗
USGS2008

Using logistic regression to predict a probability of debris flows in areas burned by wildfires, southern California, 2003-2006

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

California↗
USGS2009

A topographic feature taxonomy for a U.S. national topographic mapping ontology

Using legacy feature lists from the U.S. National Topographic Mapping Program of the twentieth century, a taxonomy of features is presented for purposes of developing a national topographic feature ontology for geographic mapping and analysis. After reviewing published taxonomic classifications, six basic classes are suggested; terrain, surface water, ecological regimes, built-up areas, divisions, and events. Aspects of ontology development are suggested as the taxonomy is described.

Book↗
USGS2012

Methods to characterize environmental settings of stream and groundwater sampling sites for National Water-Quality Assessment

Characterization of natural and anthropogenic features that define the environmental settings of sampling sites for streams and groundwater, including drainage basins and groundwater study areas, is an essential component of water-quality and ecological investigations being conducted as part of the U.S. Geological Survey's National Water-Quality Assessment program. Quantitative characterization of environmental settings, combined with physical, chemical, and biological data collected at sampling sites, contributes to understanding the status of, and influences on, water-quality and ecological conditions. To support studies for the National Water-Quality Assessment program, a geographic information system (GIS) was used to develop a standard set of methods to consistently characterize the sites, drainage basins, and groundwater study areas across the nation. This report describes three methods used for characterization-simple overlay, area-weighted areal interpolation, and land-cover-weighted areal interpolation-and their appropriate applications to geographic analyses that have different objectives and data constraints. In addition, this document records the GIS thematic datasets that are used for the Program's national design and data analyses.

Scientific Investigations Report↗