USGS Science⌕ Search

SEARCH · USGS Science

Results for “Information Services and Use”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76Linked to original sources
USGS1990

Hydrogeology of the Pictured Cliffs Sandstone in the San Juan structural basin, New Mexico, Colorado, Arizona, and Utah

This report is one in a series resulting from the U.S. Geological Survey's Regional Aquifer System Analysis (RASA) study of the San Juan structural basin that began in October 1984. The purposes of the study (Welder, 1986) are to: (1) Define and evaluate the aquifer system; (2) assess the effects of past, present, and potential ground-water use on aquifers and streams, and (3) determine the availability and quality of ground water. Previous reports in this series describe the hydrogeology of the Dakota Sandstone (Craigg and others, 1989), Gallup Sandstone (Kernodle and others, 1989), Morrison Formation (Dam and others, 1990), Point Lookout Sandstone (Craigg and others, 1990), Kirtland Shale and Fruitland Formation (Kernodle and others, 1990), Menefee Formation (Levings and others, 1990), Cliff House Sandstone (Thorn and others, 1990), and Ojo Alamo Sandstone (Thorn and others, 1990) in the San Juan structural basin. This report summarizes information on the geology and the occurrence and quality of water in the Pictured Cliffs Sandstone, one of the primary water-bearing units in the regional aquifer system. Data used in this report were collected during the RASA study or derived from existing records in the U.S. Geological Survey's computerized National Water Information System (NWIS) data base, the Petroleum Information Corporation's data base, and the Dwight's ENERGYDATA Inc. BRIN database. Although all data available for the Pictured Cliffs Sandstone were considered in formulating the discussions in the text, not all those data could be plotted on the illustrations. The San Juan structural basin in New Mexico, Colorado, Arizona, and Utah has an area of about 21,600 square miles (fig. 1). The structural basin is about 140 miles wide and about 200 miles long. The study area is that part of the structural basin that contains rocks of Triassic and younger age; therefore, the study area is less extensive than the structural basin. Triassic through Tertiary sedimentary rocks are emphasized in this study because these units are the major aquifers in the basin. The study area is about 140 miles wide (about the same as the structural basin), 180 miles long, and has an area of about 19,400 square miles. Altitudes in the study area range from about 4,500 feet in southeastern Utah, to about 11,000 feet in the southeastern part of the basin. The area-weighted mean altitude is about 6,700 feet. Annual precipitation in the high mountainous areas along the north and east margins of the basin is as much as 45 inches, whereas annual precipitation in the lower altitude, central basin is generally less than 8 inches. Mean annual precipitation is about 12 inches. Data obtained from documents published by the U.S. Bureau of the Census (1980 and 1985) were used to calculate the population of the study area. The population in 1970 was calculated to be about 134,000. The population increased to about 194,000 in 1980,212,000 in 1982,221,000 in 1984, and then declined to about 210,000 in 1985. The economy of the basin is supported by exploration and development of natural gas, petroleum, coal, and uranium resources; urban enterprise; farming and ranching tourism, and recreation. The rise and fall in population were related to changes in the economic strength of the minerals, oil, and gas industries, and support services. Uranium-mining and -milling activities underwent rapid growth until the late 1970's when most uranium-mining activity came to an abrupt end. Likewise, the oil and gas industry prospered until about 1983 and then declined rapidly.

Hydrologic Atlas↗
USGS1990

Hydrogeology of the Cliff House Sandstone in the San Juan structural basin, New Mexico, Colorado, Arizona, and Utah

This report is one in a series resulting from the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) study of the San Juan structural basin that began in October 1984. Previous reports in the series describe the hydrogeology of the Dakota Sandstone (Craigg and others, 1989), Point Lookout Sandstone (Craigg and others, 1990), Morrison Formation (Dam and others, 1990), Gallup Sandstone (Kernodle and others, 1989), and Menefee Formation (Levings and others, 1990) in the San Juan structural basin. The purposes of the RASA (Welder, 1986) are to: (1) Define and evaluate the aquifer system; (2) assess the effects of past, present, and potential ground-water use on aquifers and streams; and (3) determine the availability and quality of ground water. This report summarizes information on the geology and the occurrence and quality of water in the Cliff House Sandstone, one of the primary water-bearing units in the regional aquifer system. Data used in this report were collected during the study or were derived from existing records in the U.S. Geological Survey's computerized National Water Information System (NWIS) data base, the Petroleum Information Corporation's data base, and the Dwight's ENERGYDATA Inc. BRIN data base. Although all data available for the Cliff House Sandstone were considered in formulating the discussions in the text, not all those data could be plotted on the illustrations. The San Juan structural basin is in New Mexico, Colorado, Arizona, and Utah and has an area of about 21,600 square miles (fig. 1). The structural basin is about 140 miles wide and about 200 miles long. The study area is that part of the structural basin that contains rocks of Triassic or younger age and, therefore, is less extensive than the structural basin. Triassic through Tertiary sedimentary rocks are emphasized in this study because the major aquifers in the basin are present in these rocks. The study area is about 140 miles wide (about the same as the structural basin), 180 miles long, and has an area of about 19,400 square miles. Altitudes in the study area range from about 4,500 feet in San Juan County, Utah, to about 11,000 feet in Cibola County, New Mexico. Annual precipitation in the high mountainous areas along the north and east margins of the basin is as much as 45 inches, whereas annual precipitation in the lower altitude, central basin is generally less than 8 inches. Mean annual precipitation in the study area is about 12 inches. Data obtained from documents published by the U.S. Bureau of the Census, 1980 and 1985, were used to estimate the population of the study area. The population of the study area in 1970 was estimated to be about 134,000. The population rose to about 194,000 in 1980, 212,000 in 1982, 221,000 in 1984, and then fell to about 210,000 in 1985. The economy of the basin is supported by exploration and development of petroleum, natural gas, coal, and uranium resources; urban enterprise, farming and ranching; tourism; and recreation. The rise and fall in population were related to changes in the economic strength of the mining, petroleum, and natural-gas industries, and support services. Uranium mining and milling activities grew rapidly until the late 1970's when most uranium-mining activity ended in the study area. Likewise, the oil and gas industry prospered until about 1983 and then declined rapidly, also affecting many jobs in support industries.

Arizona, Colorado, New Mexico, Utah↗
USGS1990

Hydrogeology of the Point Lookout Sandstone in the San Juan structural basin, New Mexico, Colorado, Arizona, and Utah

This report is one in a series resulting from the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) study of the San Juan structural basin that began in October 1984. Previous reports in the series describe the hydrogeology of the Dakota Sandstone (Craigg and others, 1989), Morrison Formation (Dam and others, 1990), Gallup Sandstone (Kernodle and others, 1989), Menefee Formation (Levings and others, 1990), and Cliff House Sandstone (Thorn and others, 1990), in the San Juan structural basin. The purposes of the RASA (Welder, 1986) are to: (1) Define and evaluate the aquifer system; (2) assess the effects of past, present, and potential ground-water use on aquifers and streams; and (3) determine the availability and quality of ground water. This report summarizes information on the geology and the occurrence and quality of water in the Point Lookout Sandstone, one of the primary water-bearing units in the regional aquifer system. Data used in this report were collected during the study or were derived from existing records in the U.S. Geological Survey's computerized National Water Information System (NWIS) data base, the Petroleum Information Corporation's database, and the Dwight's ENERGYDATA Inc. BRIN data base. Although all data available for the Point Lookout Sandstone were considered in formulating the discussions in the text, not all those data could be plotted on the illustrations. The San Juan structural basin is in New Mexico, Colorado, Arizona, and Utah and has an area of about 21,600 square miles (fig. 1). The structural basin is about 140 miles wide and about 200 miles long. The study area is that part of the structural basin that contains rocks of Triassic or younger age and, therefore, is less areally extensive than the structural basin. Triassic through Tertiary sedimentary rocks are emphasized in this study because the major aquifers in the basin are present in these rocks. The study area is about 140 miles wide (about the same as the structural basin), 180 miles long, and has an area of about 19,400 square miles. Altitudes in the study area range from about 4,500 feet in San Juan County, Utah, to about 11,000 feet in Cibola County, New Mexico. Annual precipitation in the high mountainous areas along the north and east margins of the basin is as much as 45 inches, whereas annual precipitation in the lower altitude, central basin is generally less than 8 inches. Mean annual precipitation in the study area is about 12 inches. Data obtained from documents published by the U.S. Bureau of the Census, 1980 and 1985, were used to estimate the population of the study area. The population of the study area in 1970 was estimated to be about 134,000. The population rose to about 194,000 in 1980, 212,000 in 1982, 221,000 in 1984, and then fell to about 210,000 in 1985. The economy of the basin is supported by exploration and development of petroleum, natural gas, coal, and uranium resources; urban enterprise, farming "and ranching; tourism; and recreation. The rise and fall in population were related to changes in the economic strength of the mining, petroleum, and natural-gas industries, and support services. Uranium mining and milling activities grew rapidly until the late 1970's when most uranium-mining activity ended in the study area. Likewise, the oil and gas industry prospered until about 1983 and then declined rapidly, also affecting many jobs in support industries.

Arizona, Colorado, New Mexico, Utah↗
USGS1996

Instream investigations in the Beaver Creek Watershed in West Tennessee, 1991-95

The U.S. Geological Survey (USGS), in cooperation with the Tennessee Department of Agriculture, began a long-term scientific investigation in 1989 to evaluate the effect of agricultural activities on water quality and the effectiveness of agricultural best management practices in the Beaver Creek watershed, West Tennessee. In 1993 as a part of this study, the USGS, in cooperation with the Natural Resources Conservation Service, Shelby County Soil Conservation District, and the Tennessee Soybean Promotion Board, began an evaluation of the physical, chemical, biological and hydrological factors that affect water quality in streams and wetlands, and instream resource-management systems to treat agricultural nonpoint-source runoff and improve water quality. The purpose of this report is to present the results of three studies of stream and wetland investigations and a study on the transport of aldicarb from an agricultural field in the Beaver Creek watershed. A natural bottomland hardwood wetland and an artificially constructed wetland were evaluated as instream resource-management systems. These two studies showed that wetlands are an effective way to improve the quality of agricultural nonpoint-source runoff. The wetlands reduced concentrations and loads of suspended sediments, nutrients, and pesticides in the streams. A third paper documents the influence of riparian vegetation on the biological structure and water quality of a small stream draining an agricultural field. A comparison of the upper reach lined with herbaceous plants and the lower reach with mature woody vegetation showed a more stable biological community structure and Water- quality characteristics in the woody reach than in the herbaceous reach. The water-quality characteristics monitored were pH, temperature, dissolved oxygen, and specific conductance. The herbaceous reach had a greater diversity and abundance of organisms during spring and early summer, but the abundance dropped by approximately 85 percent during late summer. A fourth study describes the transport of aldicarb and its metabolites--aldicarb sulfoxide and aldicarb sulfone-in runoff at a small stream draining a cotton field. During 1991 to 1995, aldicarb and its metabolites were detected in runoff events. The highest concentrations occurred when aldicarb was applied to the field just hours before a rain storm. Aldicarb was not detectable in runoff a few weeks after application. The metabolites of aldicarb were detectable for 76 days after application. These studies demonstrate streambank vegetation and wetlands have a significant influence on stream water quality. The importance of weather conditions to herbicide application and runoff also is evident. This information can be used by resource managers to sustain and improve our Nation's streams for future generations.

Water-Resources Investigations Report↗
USGS1984

A workshop model simulating fate and effect of drilling muds and cuttings on benthic communities

Oil and gas exploration and production at marine sites has generated concern over potential environmental impacts resulting from the discharge of spent drilling muds and cuttings. This concern has led to a broad array of publicly and privately sponsored research. This report described a cooperative modeling effort designed to focus information resulting from this research through construction of explicit equations that simulate the potential impacts of discharge drilling fluids (muds) and cuttings on marine communities. The model is the result of collaboration among more than 30 scientists. The principal cooperating organizations were the E.S. Environmental Protection Agency, the U.S. Minerals Management Service, the Offshore Operators Committee, and the Alaska Oil and Gas Association. The overall simulation model can be conceptualized as three connected submodels: Discharge and Plume Fate, Sediment Redistribution, and Benthic Community Effects. On each day of simulation, these submodels are executed in sequence, with flows of information between submodels. The Benthic Community Effects submodel can be further divided into sections that calculate mortality due to burial, mortality due to toxicity, mortality due to resuspension disturbance, and growth of the community. The model represents a series of seven discrete 1-m 2 plots at specified distances along a transect in one direction away from a discharge point. It consists of coupled difference equations for which parameter values can easily be set to evaluate different conditions or to examine the sensitivity of output to various assumptions. Sets of parameter values were developed to represent four general cases or scenarios: (1) a shallow (5 m), cold environment with ice cover during a substantial fraction of the year, such as might be encountered in the Beaufort Sea, Alaska; (2) a shallow (20 m), temperate environment, such as might be encountered in the Gulf of Mexico; (3) a deeper (80 m), temperate environment, such as might be encountered in the Gulf of Mexico; and (4) a very deep (1,000 m) environment, such as might be encountered on the Atlantic slope. The focus of the modeling effort was on the connection of a reasonable representation of physical fate to the biological responses of populations, rather than on highly detailed representations of individual processes. For example, the calculations of physical fate are not as detailed as those in the recently published model of Brandsma et al. (1983). The value of the model described herein is in the broad scope of processes that are explicitly represented and linked together. The model cannot be considered to produce reliable predictions of the quantitative impacts of discharged drilling fluids and cuttings on biological populations at a particular site. Limitations of the model in predicting integrated fate and effects can be traced to three general areas: level of refinement of the algorithms used in the model; lack of understanding of the processes determining fate and effects; and parameter and data values. Despite the limitations, several qualitative conclusions concerning both potential impacts and the importance of various remaining data gaps can be drawn from the modeling effort. These include: (1) Simple, unequivocal conclusions about fate and effects across geographical regions and drilling operations are difficult, if not misleading, due to the large amount of variability in characteristics of discharged materials (e.g., oil content and toxicity), discharge conditions (e.g., duration of drilling operations), physical environments (e.g., water depth, current direction, and sediment disturbance regimes), and biological communities (e.g., intrinsic growth rates). Different combinations of these characteristics can result in substantial differences in simulated environmental fate and biological effects. For examples, simulated recovery in some high-energy environments occurs within months after the cessation of discharge operations, even at heavily impacted sites, whereas simulated recover in some low-energy environments takes years at heavily impacted sites. <2) Considerable difficulties remain in the reliable extrapolation of results from laboratory toxicity experiments to predictions of population effects in the field. (3) The volume of material discharged and duration of operations in the production drilling operations simulated by the model are sufficient to produce substantial simulated biological impacts at some plots, both in terms of differences from a control plot during the period of discharge operations, and in terms of the recovery period following the perturbations. Evaluation of the significance of potential effects involves the following factors: • Definition of a specific spatial and temporal reference frame (e.g., What is the natural variation? Is 1 year to be considered a "long" or "short" time? Is 50 m to be considered a "large" or "trivial" distance? • Consideration of rare or unique resources and particularly sensitive biotic assemblages. • Consideration of the potential for long term, cumulative effects. Some of these aspects are clearly beyond the scope of this modeling efforts (e.g., the model does not simulate the long term fate of resuspended material). The model does, however, contain an internal "reference frame" by comparison to simulated behavior at a control plot. The model, in general, simulates substantial "natural" variation at the reference or control plots, both over time, due to sediment disturbance events in medium to high energy environments, and over space, due to geographically varying conditions, such as water depth and current regime.

Report↗
USGS2018

Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana, vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

Louisiana↗
USGS2017

Life history and status of Shortnose Sturgeon (Acipenser brevirostrum LeSueur, 1818)

Shortnose Sturgeon = SNS (Acipenser brevirostrum) is a small diadromous species with most populations living in large Atlantic coast rivers and estuaries of North America from New Brunswick, Canada, to GA, USA. There are no naturally landlocked populations, so all populations require access to fresh water and salt water to complete a natural life cycle. The species is amphidromous with use of fresh water and salt water (the estuary) varied across the species range, a pattern that may reflect whether freshwater or saltwater habitats provide optimal foraging and growth conditions. Migration is a dominant behavior during life history, beginning when fish are hatchling free embryos (southern SNS) or larvae (northeastern and far northern SNS). Migration continues by juveniles and nonspawning adult life stages on an individual time schedule with fish moving between natal river and estuary to forage or seek refuge, and by spawning adults migrating to and from riverine spawning grounds. Coastal movements by adults throughout the range (but particularly in the Gulf of Maine = GOM and among southern rivers) suggest widespread foraging, refuge use, and widespread colonization of new rivers. Colonization may also be occurring in the Potomac River, MD–VA–DC (midAtlantic region). Genetic studies (mtDNA and nDNA) identified distinct individual river populations of SNS, and recent rangewide nDNA studies identified five distinct evolutionary lineages of SNS in the USA: a northern metapopulation in GOM rivers; the Connecticut River; the Hudson River; a Delaware River–Chesapeake Bay metapopulation; and a large southern metapopulation (SC rivers to Altamaha River, GA). The Saint John River, NB, Canada, in the Bay of Fundy (north of the GOM), is the sixth distinct genetic lineage within SNS. Life history information from telemetry tracking supports the genetic information documenting extensive movement of adults among rivers within the three metapopulations. However, individual river populations with spawning adults are still the best basal unit for management and recovery planning. The focus on individual river populations should be complemented with attention to migratory processes and corridors that foster metapopulation level risks and benefits. The species may be extirpated at the center of the range, i.e., the midAtlantic region (Chesapeake Bay, MD–VA, and probably, NC), but large rivers in VA, including the James and Potomac rivers, need study. The largest SNS populations in GOM and northeastern rivers, like the Kennebec, Hudson, and Delaware rivers, typically have tens of thousands of adults. This contrasts with southern rivers, where rivers typically have much fewer (<2500) adults, except for the Altamaha River (>6000 adults). River damming in the 19th and 20th Centuries extirpated some populations, and also, created two dysfunctional segmented populations: the Connecticut River SNS in CT–MA and the SanteeCooper rivers–Lake Marion SNS in SC. The major anthropogenic impact on SNS in marine waters is fisheries bycatch. The major impacts that determine annual recruitment success occur in freshwater firstly, where adult spawning migrations and spawning are blocked or spawning success is affected by river regulation and secondly, where poor survival of early life stages is caused by river dredging, pollution, and unregulated impingement/entrainment in water withdrawal facilities. Climate warming has the potential to reduce abundance or eliminate SNS in many rivers, particularly in the South. In 1998, the National Marine Fisheries Service (NMFS) recommended management of 19 rivers as distinct population segments (DPSs) based on strong fidelity to natal rivers. A Biological Assessment completed in 2010 reaffirmed this approach. NMFS has not formally listed DPSs under the ESA and the species remains listed as endangered rangewide in the USA.

Journal of Applied Ichthyology↗
USGS2011

Networks - The assessment of marine reserve networks: Guidelines for ecological evaluation

As marine ecosystems are plagued by an ever-increasing suite of threats including climate change, pollution, habitat degradation, and fisheries impacts (Roessig et al ., 2004; Lotze et al ., 2006; Jackson, 2008), there are now no ocean areas that are exempt from anthropogenic impacts (Halpern et al ., 2008). In order to preserve marine biodiversity, ecosystem function, and the goods and services provided by resistant and/or resilient systems, marine reserves have been increasingly recommended as part of an ecosystem-based approach to management (Browman and Stergiou, 2004; Levin et al ., 2009). Marine reserves are defined as “areas of the ocean completely protected from all extractive and destructive activities” (Lubchenco et al ., 2003) and can be experimental controls for evaluating the impact of these activities on marine ecosystems. Growing scientific information has shown consistent increases in species density, biomass, size, and diversity in response to full protection inside reserves of varying sizes and ages located in diverse regions (Claudet et al ., 2008; Lester et al ., 2009; Molloy et al ., 2009). However, most of these data are from individual marine reserves and therefore have inherently limited transferability to networks of marine reserves, which when properly designed can outperform single marine reserves for a variety of ecological, economic, and social management goals (Roberts et al ., 2003; Almany et al ., 2009; Gaines et al ., 2010). The concept of marine reserve networks grew out of a desire to achieve both conservation and fishery management goals by minimizing the potential negative economic, social, and cultural impacts of a single large reserve while still producing similar or even greater ecological and economic returns (Murray et al ., 1999; Gaines et al ., 2010). In addition, reserves networks can provide insurance by protecting areas across a region and spreading the risk that these sites may be impacted by localized catastrophes such as hurricanes or oil spills (Allison et al ., 2003). The World Conservation Union's Marine Programme defines a network as “a collection of individual marine protected areas (MPAs) or reserves operating co-operatively and synergistically, at various spatial scales and with a range of protection levels that are designed to meet objectives that a single reserve cannot achieve” (IUCN–WCPA, 2008). However, general terms such as “co-operatively” and “synergistically” can have myriad meanings. Without a clear definition of a network, it becomes difficult to identify attainable management goals and design a process for evaluating whether the network achieves those goals. Besides, different management goals may in turn result in the need for different types of networks. The use of MPAs with varying protection levels together with no-take zones in multiple-zoning schemes adds another layer of complexity to network design and evaluation; however, partially protected areas are generally used to manage coastal uses and avoid conflicts (rather than for strict ecological purposes) and are therefore a function of the local social, economic, and cultural context. As we are here interested in the ecological effects of networks, for the purposes of this chapter, we focus on marine reserves because these areas are no-take and therefore offer greater ecological benefits than other types of MPAs that allow some forms of extraction (Lester and Halpern, 2008).

Book chapter↗
USGS2010

EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 2009: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived 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 National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 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 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 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↗
USGS2016

Report A: Fish and habitat assessment in Rock Creek, Klickitat County, Washington, June 2013-December 2015

The U.S. Geological Survey (USGS) and the Yakama Nation have collaborated in the Rock Creek subbasin, southeastern, Washington since 2009 to assess steelhead (Oncorynchus mykiss) populations and habitat conditions. Rock Creek, flows south to the Columbia River at river kilometer (rkm) 368. During 2015, a habitat survey was conducted, and monitoring of Passive Integrated Transponder (PIT)-tagged salmonids in the Rock Creek subbasin continued. Two multiplexing PIT-tag interrogation systems (PTISs) were installed in Rock Creek in the fall of 2009 to evaluate timing and degree of salmonid movement, smolting success, stray rates, and other life history attributes. These have been monitored every year since, during the spring, fall, and winter months. Returning adult steelhead detection histories are summarized from past Rock Creek PIT-tagging efforts. Detection histories and detection efficiencies were used to estimate a smolt-to-adult return rate (SAR) for Rock Creek PIT-tagged steelhead (tagged from 2009 to 2012) that ranged from 2.2% to 5.5%. Additionally, a SAR was also estimated for Rock Creek PIT-tagged steelhead returning to Bonneville Dam, Columbia River (rkm 235). The SAR rate to Bonneville Dam was always higher (2.4% to 10.4%), indicating straying of adults to other sites for spawning potentially further upstream or in other tributaries, or pre-spawn mortality. Twenty-two Rock Creek PIT-tagged steelhead were detected returning to Rock Creek and 35 were detected at Bonneville Dam from past tagging efforts (2009 – 2012). Monitoring of the Rock Creek PTISs [Rock Creek Lower (RCL) and Rock Creek Squaw (RCS)] provide evidence for PIT-tagged salmonid use from fish tagged outside of Rock Creek subbasin (out-of-basin) origins. A total of 82 out-of-basin PIT-tagged fish have been detected at the Rock Creek PTISs since installation. The habitat survey was conducted in Rock Creek from September 16 to October 7, 2015. The survey started at rkm 2 and continued upstream to rkm 29.3, and included portions of the major tributaries, ranging from 1 to 9 rkm survey length upstream from their confluence. During the survey, we measured the lengths of all dry and non-pool wet sections, and for pools: the length, wetted width, average residual depth, maximum residual depth, and temperature. During the 2015 survey of Rock Creek, 38% of the river between rkm 2 and 29 was classified as dry, with a higher relative proportion (57%) of dry being in the lower river section (rkm 2-13) than the upper river section (33%, rkm 14-22). This was higher than during survey years 2010 to 2012, which ranged from 29% to 43% in the lower river. As a result of the increase in dry area the percent of non-pool wet habitat was less (22%) than previous years (range 34% to 43%), as well as the percent of pools (21%). However, more river kilometers were surveyed in the lower river section (rkm 2-13) than previous years. For the 2015 survey length (rkm 2 to 29), 19% was classified as pools and 43% was non-pool wet. This work informs potential restoration actions by identifying the persistent pools across years and in years of low water flow (i.e., 2015). This work also provides a baseline to evaluate effectiveness of future restoration actions. Potential restoration actions could include headwater and upland restoration to improve base flows and pool habitat enhancement, through increased structure and vegetation plantings for increased cover. The Rock Creek steelhead population remains to be an important cultural resource for the Rock Creek Band of the Yakama Nation Tribe. The Rock Creek steelhead population is part of the Cascades Eastern Slope major population group (MPG), one of four MPGs contributing to the Middle Columbia steelhead distinct population segment (DPS). The National Marine Fisheries Service recovery plan for Rock Creek (NMFS 2009a) identifies an overall biological recovery goal for Rock Creek steelhead to contribute to recovery of the Mid-Columbia D

Washington↗
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↗
USGS2010

EAARL Coastal Topography-Fire Island National Seashore, New York, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced 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 post-Nor'Ida (November 2009 nor'easter) on December 4, 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 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 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↗
USGS2010

EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 2007. 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 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 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↗
USGS2010

EAARL Coastal Topography-Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced 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 Sandy Hook Unit of Gateway National Recreation Area in New Jersey, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 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 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 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↗
USGS2010

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 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 Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 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 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 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↗
USGS2001

Cruise Report; RV Moana Wave cruise M1-01-GM; the bathymetry and acoustic backscatter of the mid shelf to upper slope off Panama City, Florida, northeastern Gulf of Mexico; September 3, through October 12, 2001, Panama City, FL to Panama City, FL

A zone of deep-water reefs is thought to extend from the mid and outer shelf south of Mississippi and Alabama to at least the northwestern Florida shelf off Panama City, Florida (Figure 1, 67kb). The reefs off Mississippi and Alabama are found in water depths of 60 to 120 m (Ludwick and Walton, 1957; Gardner et al., in press) and were the focus of a multibeam echosounder (MBES) mapping survey by the U.S. Geological Survey (USGS) in 2000 (Gardner et al., 2000; in press). If this deep-water-reef trend does exist along the northwestern Florida shelf, then it is critical to determine the accurate geomorphology and type of the reefs that occur because of their importance as benthic habitats for fisheries. Precisely georeferenced high-resolution mapping of bathymetry is a fundamental first step in the study of areas suspected to be critical habitats. Morphology is thought to be critical to defining the distribution of dominant demersal plankton/planktivores communities. Fish faunas of shallow hermatypic reefs have been well studied, but those of deep ahermatypic reefs have been relatively ignored. The ecology of deep-water ahermatypic reefs is fundamentally different from hermatypic reefs because autochthonous intracellular symbiotic zooxanthellae (the carbon source for hermatypic corals) do not form the base of the trophic web in ahermatypic reefs. Instead, exogenous plankton, transported to the reef by currents, serves as the primary carbon source. Thus, one of the principle uses of the morphology data will be to identify whether any reefs found are hermatypic or ahermatypic in origin. Community structure and trophodynamics of demersal fishes of the outer continental of the northeastern Gulf of Mexico presently are the focus of a major USGS reseach project. A goal of the project is to answer questions concerning the relative roles played by morphology and surficial geology in controling biological differentiation. Deep-water reefs are important because they are fish havens, key spawning sites, and are critical early larval and juvenile habitats for economically important sport/food fishes. It is known that deep-water reefs function as a key source for re-population (via seasonal and ontogenetic migration) of heavily impacted inshore reefs. The deep-water reefs south of Mississippi and Alabama support a lush fauna of ahermatypic hard corals, soft corals, black corals, sessile crinoids and sponges, that together form a living habitat for a well-developed fish fauna. The fish fauna comprises typical Caribbean reef fishes and Carolinian shelf fishes, plus epipelagic fishes, and a few deep-sea fishes. The base of the megafaunal invertebrate food web is plankton, borne by essentially continuous semi-laminar currents generated by eddies, spawned off the Loop Current, that periodically travel across the shelf edge. A few, sidescan-sonar surveys have been made of areas locally identified as Destin Pinnacles, Steamboat Lumps Marine Reserve (Koenig et al., 2000; Scanlon, et al., 2000; 2001), Twin Ridges (Briere, et al., 2000; Scanlon, et al., 2000), and Madison-Swanson Marine Reserve (Koenig et al., 2000; Scanlon, et al., 2000; 2001). However, no quantitative and little qualitative information about the geomorphology and surficial geology can be gained from these data. Existing bathymetry along the northwestern Florida shelf suggests the existence of areas of possible isolated deep-water reefs. NOAA bathymetric maps NOS NH16-9 and NG16-12 show geomorphic expressions that hint of the presence of reefs in isolated areas rather than in a continuous zone. There has been no systematic, high-resolution bathymetry collected in this area, prior to this cruise. After the successful mapping of the deep-water reefs on the Mississippi and Alabama shelf (Gardner et al., 2000; in press), a partnership composed of the USGS, Minerals Management Service, and NOAA was formed to continue the deep-reef mapping to the northwest Florida mid shelf and upper slope. This cruise is the first fruit of that partnership.

Florida↗
USGS2010

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

These remotely sensed, geographically referenced 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; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 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 multispectral 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 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↗
USGS2011

Range-wide assessment of livestock grazing across the sagebrush biome

Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and synthesize recommendations from federal and university rangeland science experts about how BLM might prioritize collection of different types of livestock grazing-related natural resource data. 4. Investigate whether range-wide datasets (Objective 1) could be used in conjunction with remotely sensed imagery to identify across broad scales (a) allotments potentially not meeting BLM Land Health Standards (LHS) and (b) allotments in which unmet standards might be attributable to livestock grazing. Objective 1: We identified four datasets that potentially could be used for analyses of livestock grazing effects on sagebrush ecosystems. First, we obtained the most current spatial data (typically up to 2007, 2008, or 2009) for all BLM allotments and compiled data into a coarse, topologically enforced dataset that delineated grazing allotment boundaries. Second, we obtained LHS evaluation data (as of 2007) for all allotments across all districts and regions; these data included date of most recent evaluation, BLM determinations of whether region-specific standards were met, and whether BLM deemed livestock to have contributed to any unmet standards. Third, we examined grazing records of three types: Actual Use (permittee-reported), Billed Use (BLM-reported), and Permitted Use (legally authorized). Finally, we explored the possibility of using existing Natural Resources Conservation Service (NRCS) Ecological Site Description (ESD) data to make up-to-date estimates of production and forage availability on BLM allotments. Objective 2: We investigated the availability of BLM livestock grazing-related monitoring data and the status of LHS across 310 randomly selected allotments in 13 BLM field offices. We found that, relative to other data types, the most commonly available monitoring data were Actual Use numbers (permittee-reported livestock numbers and season-of-use), followed by Photo Point, forage Utilization, and finally, Vegetation Trend measurement data. Data availability and frequency of data collection varied across allotments and field offices. Analysis of the BLM's LHS data indicated 67 percent of allotments analyzed were meeting standards. For those not meeting standards, livestock were considered the causal factor in 45 percent of cases (about 15 percent of all allotments). Objective 3: We sought input from 42 university and federal rangeland science experts about how best to prioritize rangeland monitoring activities associated with ascertaining livestock impacts on vegetation resources. When we presented a hypothetical scenario to these scientists and asked them to prioritize monitoring activities, the most common response was to measure ground and vegetation cover, a variable that in many cases (10 of 13 field offices sampled) BLM had already identified as a monitoring priority. Experts identified several other traditional (for example, photo points) and emerging approaches (for example, high-resolution aerial photography) to monitoring. Objective 4: We used spatial allotment data (described in Objective 1) and remotely sensed vegetation data (sagebrush cover, herbaceous vegetation cover, litter and bare soil) to assess differences in allotment LHS status ("Not met" vs. "Met"; if "Not met" - livestock-caused vs. not). We then developed logistic regression models, using vegetation variables to predict LHS status of BLM allotments in sagebrush steppe habitats in Wyoming and portions of Montana and Colorado. In general, we found that more consistent data collection at the local level might improve suitability of data for broad-scale analyses of livestock impacts. As is, data collection methodologies varied across field offices and States, and we did not find any local-level monitoring data (Actual Use, Utilization, Vegetation Trend) that had been collected consistently enough over time or space for range-wide analyses. Moreover, continued and improved emphasis on monitoring also may aid local management decisions, particularly with respect to effects of livestock grazing. Rangeland science experts identified ground cover as a high monitoring priority for assessing range condition and emphasized the importance of tracking livestock numbers and grazing dates. Ultimately, the most effective monitoring program may entail both increased data collection effort and the integration of alternative monitoring approaches (for example, remote sensing or monitoring teams). In the course of our study, we identified three additional datasets that could potentially be used for range-wide analyses: spatial allotment boundary data for all BLM allotments range-wide, LHS evaluations of BLM allotments, and livestock use data (livestock numbers and grazing dates). It may be possible to use these spatial datasets to help prioritize monitoring activities over the extensive land areas managed by BLM. We present an example of how we used spatial allotment boundary data and LHS data to test whether remotely sensed vegetation characteristics could be used to predict which allotments met or did not meet LHS. This approach may be further improved by the results of current efforts by BLM to test whether more intensive (higher resolution) LHS assessments more accurately describe land health status. Standardized data collection in more ecologically meaningful land units may improve our ability to use local-level data for broad-scale analyses.

Open-File Report↗