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At least 1,081 records · Page 60Linked to original sources
USGS2014

The 3D Elevation Program: Summary for South Dakota

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of South Dakota, elevation data are critical for agriculture and precision farming, natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

South Dakota↗
USGS2016

The 3D Elevation Program: summary for Puerto Rico

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, scientific research, national security, recreation, and many others. For the Commonwealth of Puerto Rico, elevation data are critical for flood risk management, landslide mitigation, natural resources conservation, sea level rise and subsidence, coastal zone management, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, U.S. territorial, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States, Hawaii, and selected U.S. territories, and quality level 5 interferometric synthetic aperture radar (IfSAR) data for Alaska, all with a 6- to 10-year acquisition cycle, provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A‒16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other three-dimensional (3D) representations of the Nation’s natural and constructed features.

Puerto Rico↗
USGS2014

The 3D Elevation Program: summary for Tennessee

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Tennessee, elevation data are critical for agriculture and precision farming, flood risk management, natural resources conservation, infrastructure and construction management, forest resources management, aviation navigation and safety, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Tennessee↗
USGS2013

The 3D Elevation Program: summary for Washington

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Washington, elevation data are critical for natural resources conservation, agriculture and precision farming, infrastructure and construction management, flood risk management, geologic resource assessment and hazards mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Washington↗
USGS2015

The 3D Elevation Program: summary for Pennsylvania

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Pennsylvania, elevation data are critical for natural resources conservation (including the effects of drilling for oil and natural gas), agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to replace data that are older and of lower quality. A joint goal of Commonwealth and Federal partners is to provide a temporal and density refresh of the current statewide coverage in order to support existing and emerging applications enabled by improved lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Pennsylvania↗
USGS2014

The 3D Elevation Program: summary for Louisiana

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Louisiana, elevation data are critical for flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Louisiana↗
USGS2014

The 3D Elevation Program: summary for Oklahoma

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Oklahoma, elevation data are critical for flood risk management, infrastructure and construction management, agriculture and precision farming, natural resources conservation, wildlife and habitat management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of local, State, and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Oklahoma↗
USGS2000

Selected hydrologic data, through water year 1998, Black Hills Hydrology Study, South Dakota

This report presents water-level and water-quality data that have been collected or compiled, through water year 1998, for the Black Hills Hydrology Study. This study is a long-term cooperative effort between the U.S. Geological Survey, the South Dakota Department of Environment and Natural Resources, and the West Dakota Water Development District (which represents various local and county cooperators). This report is the third in a series of project data reports produced for the study. Daily water-level data are presented for 71 observation wells and 2 cave sites in the Black Hills area of western South Dakota. The wells include a network of observation wells that are maintained in cooperation with the South Dakota Department of Environment and Natural Resources and are completed in various bedrock formations that are utilized as aquifers in the Black Hills area of western South Dakota. Both cave sites are located within outcrops of the Madison Limestone. Data presented include site descriptions, hydrographs, and tables of daily water levels. Annual measurements of water levels collected during water years 1995-98 from a net-work of 18 additional, miscellaneous wells are presented. These wells are part of a statewide network of wells completed in bedrock aquifers that was operated from 1959 through 1989 in cooperation with the South Dakota Department of Environment and Natural Resources. Site descriptions and hydrographs for the entire period of record for each site also are presented. Water-quality data are presented for 9 surface-water sites, 19 ground-water sites, and 30 sites that have been classified as areas of surface- and ground-water interaction in the Black Hills area. The surface- and ground-water interaction sites are further divided into three categories that include 11 loss zone sites, 8 headwater spring sites, and 11 downgradient spring sites.

South Dakota↗
USGS2014

The 3D Elevation Program: summary for Maine

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Maine, elevation data are critical for natural resources conservation, flood risk management, forest resources management, agriculture and precision farming, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Maine↗
USGS2014

The 3D Elevation Program: summary for New York

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of New York, elevation data are critical for coastal zone management, natural resources conservation, agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

New York↗
USGS2014

The 3D Elevation Program: summary for North Dakota

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of North Dakota, elevation data are critical for agriculture and precision farming, natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

North Dakota↗
USGS2012

Presence of selected chemicals of emerging concern in water and bottom sediment from the St. Louis River, St. Louis Bay, and Superior Bay, Minnesota and Wisconsin, 2010

The St. Louis Bay of Lake Superior receives substantial urban runoff, wastewater treatment plant effluent, and industrial effluent. In 1987, the International Joint Commission designated the St. Louis Bay portion of the lower St. Louis River as one of the Great Lakes Areas of Concern. Concerns exist about the potential effects of chemicals of emerging concern on aquatic biota because many of these chemicals, including endocrine active chemicals, have been shown to affect the endocrine systems of fish. To determine the occurrence of chemicals of emerging concern in the St. Louis River, the St. Louis Bay, and Superior Bay, the U.S. Geological Survey in cooperation with the Minnesota Pollution Control Agency and the Wisconsin Department of Natural Resources collected water and bottom-sediment samples from 40 sites from August through October 2010. The objectives of this study were to (1) identify the extent to which chemicals of emerging concern, including pharmaceuticals, hormones, and other organic chemicals, occur in the St. Louis River, St. Louis Bay, and Superior Bay, and (2) identify the extent to which the chemicals may have accumulated in bottom sediment of the study area. Samples were analyzed for selected wastewater indicators, hormones, sterols, bisphenol A , and human-health pharmaceuticals. During this study, 33 of 89 chemicals of emerging concern were detected among all water samples collected and 56 of 104 chemicals of emerging concern were detected in bottom-sediment samples. The chemical N,N -diethyl- meta -toluamide (DEET) was the most commonly detected chemical in water samples and 2,6-dimethylnaphthalene was the most commonly detected chemical in bottom-sediment samples. In general, chemicals of emerging concern were detected at a higher frequency in bottom-sediment samples than in water samples. Estrone (a steroid hormone) and hexahydrohexamethyl cyclopentabensopyran (a synthetic fragrance) were the most commonly detected endocrine active chemicals in water samples; beta -sitosterol (a plant sterol), estrone, and 4- tert -octylphenol (an alkylphenol) were the most commonly detected endocrine active chemicals in bottom-sediment samples. The greater detection frequency of chemicals in bottom-sediment samples compared to the detection frequency in water samples indicates that bottom sediment is an important sink for chemicals of emerging concern. At least one polycyclic aromatic hydrocarbon was detected in every sample; and in most samples, all nine polycyclic aromatic hydrocarbons included in analyses were detected. Bottom sediment collected from Superior Bay had the most polycyclic aromatic hydrocarbon detections of the sediment sampling locations.

Minnesota;Wisconsin↗
USGS2011

Suspended material availability and filtration-biodeposition processes performed by a native and invasive bivalve species in streams

Unionid mussels are among the most threatened group of freshwater organisms globally. They are known for their ability to filter food particles from flowing and standing waters. However, invasive bivalve species, such as the Asian clam ( Corbicula fluminea ) in North America, have the potential to overlap in feeding and potentially out-compete the native species. Yet, the feeding preferences of unionid mussels and C. fluminea are incompletely understood. We hypothesized that Elliptio crassidens (native) and C. fluminea (invasive) would select for specific organic components present within seston. We examined changes in seston (dry mass and ash-free dry mass) resulting from bivalve feeding activity for three size classes of material that were isolated using gravimetric filtration. The treatments were also sub-sampled for flow cytometry (FC) which separated the suspended materials in the stream water into five categories: detritus, heterotrophic bacteria, picoautotrophs, nanoautotrophs, and heterotrophic nanoeukaryotes. Our results indicated that both species of bivalve showed preferences for organic and living materials. E. crassidens preferentially filtered nanoeukaryotes, whose decreases were associated with an increase in bacteria. In contrast, C. fluminea preferred smaller materials through selective filtration of picoautotrophs. In addition, both species increased the concentration of large materials toward the end of the experiment because of the suspension of their pseudofeces biodeposits. To our knowledge, this study is the first to examine grazing by bivalve species on natural stream particulate matter using FC. Our results suggest that native and non-native mussels have different functional roles, which has important implications for organic matter processing and food webs in streams.

Georgia↗
USGS2016

Feline immunodeficiency virus cross-species transmission: Implications for emergence of new lentiviral infections

Owing to a complex history of host-parasite coevolution, lentiviruses exhibit a high degree of species specificity. Given the well-documented viral archeology of HIV emergence following human exposures to SIV, understanding processes that promote successful cross-species lentiviral transmissions is highly relevant. We have previously reported natural cross-species transmission of a subtype of feline immunodeficiency virus, puma lentivirus A (PLVA), between bobcats ( Lynx rufus ) and mountain lions ( Puma concolor ) in a small number of animals in California and Florida. In this study we investigate host-specific selection pressures, within-host viral fitness, and inter- vs. intra-species transmission patterns among a larger collection of PLV isolates from free-ranging bobcats and mountain lions. Analysis of proviral and viral RNA levels demonstrates that PLVA fitness is severely restricted in mountain lions compared to bobcats. We document evidence of diversifying selection in three of six PLVA genomes from mountain lions, but did not detect selection among twenty PLVA isolates from bobcats. These findings support that PLVA is a bobcat-adapted virus, which is less fit in mountain lions and under intense selection pressure in the novel host. Ancestral reconstruction of transmission events reveals intraspecific PLVA transmission has occurred among panthers ( Puma concolor coryi ) in Florida following initial cross-species infection from bobcats. In contrast, interspecific transmission from bobcats to mountain lions predominates in California. These findings document outcomes of cross-species lentiviral transmission events among felids that compare to emergence of HIV from nonhuman primates. IMPORTANCE Cross-species transmission episodes can be singular, dead-end events or can result in viral replication and spread in the new species. The factors that determine which outcome will occur are complex, and the risk of new virus emergence is therefore difficult to predict. Here we use molecular techniques to evaluate transmission, fitness, and adaptation of puma lentivirus A (PLVA) between bobcats and mountain lions in two geographic regions. Our findings illustrate that mountain lion exposure to PLVA is relatively common, but does not routinely result in infections communicable in the new host. This is attributed to efficient species barriers that largely prevent lentiviral adaptation. However, the evolutionary capacity for lentiviruses to adapt to novel environments may ultimately overcome host restriction mechanisms over time and under certain ecological circumstances. This phenomenon provides a unique opportunity to examine cross-species transmission events leading to new lentiviral emergence.

California, Florida↗
USGS1989

Enhanced detection of infectious hematopoietic necrosis virus by pretreatment of cell monolayers with polyethylene glycol

To improve quantification of very low levels of infectious hematopoietic necrosis virus (IHNV) in samples of tissue, ovarian fluid, or natural water supplies, we tested the ability of polyethylene glycol (PEG) to enhance the sensitivity and speed of the plaque assay system. We compared 4, 7, and 10% solutions of PEG of molecular weight 6,000, 8,000, or 20,000 applied at selected volumes and for various durations. When cell monolayers of epithelioma papulosum cyprini (EPC), fathead minnow (FHM), chinook salmon embryo (CHSE-214), and bluegill fry (BF2) were pretreated with 7% PEG-20,000, they produced 4-17-fold increases in plaque assay titers of IHNV. The plaque assay titers of viral hemorrhagic septicemia virus, chum salmon reovirus, and chinook salmon paramyxovirus were also enhanced by exposure of CHSE-214 cells to PEG, but the titers of infectious pancreatic necrosis virus and Oncorhynchus masou virus were not substantially changed. Plaques formed by IHNV on PEG-treated EPC cells incubated at 15°C had a larger mean diameter at 6 d than those on control cells at 8 d; this suggests the assay could be shortened by use of PEG. Pretreatment of EPC cell monolayers with PEG enabled detection of IHNV in some samples that appeared negative with untreated cells. For example, when ovarian fluid samples from chinook salmon Oncorhynchus tshawytscha were inoculated onto untreated monolayers of EPC cells, IHNV was detected in only 11 of 51 samples; 17 of the samples were positive when PEG-treated EPC cells were used. PDF

Journal of Aquatic Animal Health↗
USGS2014

Area- and depth- weighted averages of selected SSURGO variables for the conterminous United States and District of Columbia

This digital data release consists of seven data files of soil attributes for the United States and the District of Columbia. The files are derived from National Resources Conservations Service’s (NRCS) Soil Survey Geographic database (SSURGO). The data files can be linked to the raster datasets of soil mapping unit identifiers (MUKEY) available through the NRCS’s Gridded Soil Survey Geographic (gSSURGO) database ( http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628 ). The associated files, named DRAINAGECLASS, HYDRATING, HYDGRP, HYDRICCONDITION, LAYER, TEXT, and WTDEP are area- and depth-weighted average values for selected soil characteristics from the SSURGO database for the conterminous United States and the District of Columbia. The SSURGO tables were acquired from the NRCS on March 5, 2014. The soil characteristics in the DRAINAGE table are drainage class (DRNCLASS), which identifies the natural drainage conditions of the soil and refers to the frequency and duration of wet periods. The soil characteristics in the HYDRATING table are hydric rating (HYDRATE), a yes/no field that indicates whether or not a map unit component is classified as a "hydric soil". The soil characteristics in the HYDGRP table are the percentages for each hydrologic group per MUKEY. The soil characteristics in the HYDRICCONDITION table are hydric condition (HYDCON), which describes the natural condition of the soil component. The soil characteristics in the LAYER table are available water capacity (AVG_AWC), bulk density (AVG_BD), saturated hydraulic conductivity (AVG_KSAT), vertical saturated hydraulic conductivity (AVG_KV), soil erodibility factor (AVG_KFACT), porosity (AVG_POR), field capacity (AVG_FC), the soil fraction passing a number 4 sieve (AVG_NO4), the soil fraction passing a number 10 sieve (AVG_NO10), the soil fraction passing a number 200 sieve (AVG_NO200), and organic matter (AVG_OM). The soil characteristics in the TEXT table are percent sand, silt, and clay (AVG_SAND, AVG_SILT, and AVG_CLAY). The soil characteristics in the WTDEP table are the annual minimum water table depth (WTDEP_MIN), available water storage in the 0-25 cm soil horizon (AWS025), the minimum water table depth for the months April, May and June (WTDEPAMJ), the available water storage in the first 25 centimeters of the soil horizon (AWS25), the dominant drainage class (DRCLSD), the wettest drainage class (DRCLSWET), and the hydric classification (HYDCLASS), which is an indication of the proportion of the map unit, expressed as a class, that is "hydric", based on the hydric classification of a given MUKEY. (See Entity_Description for more detail). The tables were created with a set of arc macro language (aml) and awk (awk was created at Bell Labsin the 1970s and its name is derived from the first letters of the last names of its authors – Alfred Aho, Peter Weinberger, and Brian Kernighan) scripts. Send an email to mewieczo@usgs.gov to obtain copies of the computer code (See Process_Description.) The methods used are outlined in NRCS's "SSURGO Data Packaging and Use" (NRCS, 2011). The tables can be related or joined to the gSSURGO rasters of MUKEYs by the item 'MUKEY.' Joining or relating the tables to a MUKEY grid allows the creation of grids of area- and depth-weighted soil characteristics. A 90-meter raster of MUKEYs is provided which can be used to produce rasters of soil attributes. More detailed resolution rasters are available through NRCS via the link above.

Data Series↗
USGS2016

Climate Change Science Activities of the U.S. Geological Survey in New England

The U.S. Geological Survey (USGS) has actively pursued research in the effects of climate change on the hydrology of New England. Ongoing focus areas of climate change science activities of the USGS in New England include the following: • Hydrologic climate-response data (initiating or expanding long-term hydrologic climate-response data collection networks to detect and monitor climate-related changes in hydrology) • Relations between historical climatic and hydrologic variation (investigating historic relations between long-term climatic variation and hydrologic variation and connecting these relations to future conditions as forecasted by the Interagency Panel on Climate Change (Nakićenović and others, 2000) • Hydrologic change on natural and human (incorporating climate change scenarios into assessments of how flows in streams or water levels in aquifers may change) • Relations between climatic and hydrologic variation (characterizing impacts of climate change on floods and droughts, the long-term availability of water supplies for societal and natural uses in response to climate changes) • Developing tools to forecast ecosystem change and water resources management (developing regionally consistent tools for forecasting ecosystem change and resource management) This fact sheet presents recent climate change investigations of the USGS in New England using selected recent publications. These publications highlight the broad spectrum of expertise and commitment to understanding the relations of climate change and water resources in New England.

New England↗
USGS2003

Dimension stone

Dimension stone can be defined as natural rock material quarried to obtain blocks or slabs that meet specifications as to size (width, length and thickness) and shape for architectural or engineering purposes. Color, grain texture and pattern, and surface finish of the stone are also normal requirements. Other important selection criteria are durability (based on mineral composition, hardness and past performance), strength and the ability of the stone to take a polish.

Mining Engineering↗