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At least 109 records · Page 6Linked to original sources
USGS2015

Wyoming Basin Rapid Ecoregional Assessment

The Wyoming Basin Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM). The overall goals of the BLM Rapid Ecoregional Assessments (REAs) are to identify important ecosystems and wildlife habitats at broad spatial scales; identify where these resources are at risk from Change Agents, including development, wildfire, invasive species, disease and climate change; quantify cumulative effects of anthropogenic stressors; and assess current levels of risk to ecological resources across a range of spatial scales and jurisdictional boundaries by assessing all lands within an ecoregion. There are several components of the REAs. Management Questions, developed by the BLM and stakeholders for the ecoregion, identify the regionally significant information needed for addressing land-management responsibilities. Conservation Elements represent regionally significant species and ecological communities that are of management concern. Change Agents that currently affect or are likely to affect the condition of species and communities in the future are identified and assessed. REAs also identify areas that have high conservation potential that are referred to as “large intact areas.” At the ecoregion level, the ecological value of large intact areas is based on the assumption that because these areas have not been greatly altered by human activities (such as development), they are more likely to contain a variety of plant and animal communities and to be resilient and resistant to changes resulting from natural disturbances such as fire, insect outbreaks, and disease. The Wyoming Basin Ecoregion encompasses approximately 133,656 square kilometers (51,604.87 square miles), including portions of Wyoming, Colorado, Utah, Idaho, and Montana. The Wyoming Basin has some of the highest quality wildlife habitats remaining in the Intermountain West. The wide variety of habitats includes intermountain basins dominated by sagebrush shrublands interspersed with deciduous and conifer woodlands and montane or subalpine forests at higher elevations. The Wyoming Basin also supports ranching and agricultural operations that are important to the region’s economy and vital to conserving habitats for wildlife. The region also contains abundant energy resources, including large natural gas reserves and areas of high wind-energy potential. Combined with increased residential and industrial development, fast-paced energy development is resulting in notable land-use changes, including habitat loss and fragmentation. In the Wyoming Basin REA, we evaluated the following seven communities as Conservation Elements: streams and rivers, wetlands, riparian forests and shrublands, sagebrush steppe, desert shrublands, foothill shrublands and woodlands, and mountain forests and alpine zones. We evaluated a total of 14 species and species assemblages as Conservation Elements: aspen forests and woodlands, five-needle pine forests and woodlands, juniper woodlands, cutthroat trout, three-species fish assemblage, northern leatherside chub, sauger, spadefoot assemblage, greater sage-grouse, golden eagle, ferruginous hawk, sagebrush-obligate birds, pygmy rabbit, and mule deer. We evaluated Management Questions (Core and Integrated) for each species and community for the Wyoming Basin REA. Core Management Questions address primary management issues, including (1) where is the Conservation Element, and what are its key ecological attributes (characteristics of species and communities that may affect their long-term persistence or viability); (2) what and where are the Change Agents; and (3) how do the Change Agents affect the key ecological attributes? Integrated Management Questions synthesize the Core Management Questions as follows: (1) where are the areas with high landscape-level ecological values; (2) where are the areas with high landscape-level risks; and (3) where are the potential areas for conservation, restoration, and development? The associated maps and key findings for each Management Question are summarized for each Conservation Element in individual chapters. Additional chapters on landscape intactness and an REA synthesis are included.

Colorado, Idaho, Montana, Utah, Wyoming↗
USGS2020

Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model

The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al . in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al . in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al . compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al . performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al . performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al . outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al . reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al . for yearly average wind profiles.

Quarterly Journal of the Royal Meteorological Soci↗
USGS2017

Determining fine-scale use and movement patterns of diving bird species in federal waters of the Mid-Atlantic United States using satellite telemetry

Offshore wind energy development in the United States is projected to expand in the upcoming decades to meet growing energy demands and reduce fossil fuel emissions. There is particular interest in commercial offshore wind development within Federal waters (i.e., > 3 nautical miles from shore) of the mid-Atlantic. In order to understand the potential for adverse effects on marine birds in this area, information on distribution and behavior (e.g., flight pathways, timing, etc.) is required for a broad suite of species. In areas where offshore wind development is likely to occur, such information can be used to identify high use areas during critical life stages, which can inform the siting of offshore facilities. It can also be used to provide baseline data for understanding broad changes in distributions that occur after offshore wind developments are constructed in a specific area.

Report↗
USGS2014

Spatio-temporal analysis of gyres in oriented lakes on the Arctic Coastal Plain of northern Alaska based on remotely sensed images

The formation of oriented thermokarst lakes on the Arctic Coastal Plain of northern Alaska has been the subject of debate for more than half a century. The striking elongation of the lakes perpendicular to the prevailing wind direction has led to the development of a preferred wind-generated gyre hypothesis, while other hypotheses include a combination of sun angle, topographic aspect, and/or antecedent conditions. A spatio-temporal analysis of oriented thermokarst lake gyres with recent (Landsat 8) and historical (Landsat 4, 5, 7 and ASTER) satellite imagery of the Arctic Coastal Plain of northern Alaska indicates that wind-generated gyres are both frequent and regionally extensive. Gyres are most common in lakes located near the Arctic coast after several days of sustained winds from a single direction, typically the northeast, and decrease in number landward with decreasing wind energy. This analysis indicates that the conditions necessary for the Carson and Hussey (1962) wind-generated gyre for oriented thermokarst lake formation are common temporally and regionally and correspond spatially with the geographic distribution of oriented lakes on the Arctic Coastal Plain. Given an increase in the ice-free season for lakes as well as strengthening of the wind regime, the frequency and distribution of lake gyres may increase. This increase has implications for changes in northern high latitude aquatic ecosystems, particularly if wind-generated gyres promote permafrost degradation and thermokarst lake expansion.

Alaska↗
USGS2023

California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California

Coastal and Marine Ecological Classification Standard geoform, substrate, and biotic component geographic information system products were developed for the California State waters of south-central California in the region offshore of Morro Bay. The study was motivated by interest in development of offshore wind-energy capacity and infrastructure in Federal waters offshore. The Bureau of Ocean Energy Management, in coordination with the State of California and many other members of the California Intergovernmental Renewable Energy Task Force, issued calls for information in 2018 for the study area offshore of Morro Bay, California. The study area is adjacent to a nuclear power plant (currently scheduled for decommissioning) with a developed electric grid connection, and in an area of high wind resource potential. The Bureau of Ocean Energy Management is the lead agency responsible for planning and leasing in the U.S. Exclusive Economic Zone and funded this project to assess baseline conditions of, and the potential effects on, the seafloor environment. This project, carried out by the U.S. Geological Survey, resulted in three data releases for individual map blocks that are part of the California State Waters Map Series: (1) Offshore of Point Estero, (2) Offshore of Morro Bay, and (3) Offshore of Point Buchon. The study area consists of 341 square kilometers (km 2 ) of multibeam echo sounder (MBES) data acquired by Fugro, Inc., in 2010. Towed camera-sled video was acquired in 2012 to supervise the classification of the MBES data into habitats. There were 935 annotations of organisms and habitat made from 22 video transects. Using video observations of habitat as ground truth, derivatives of the MBES data were classified into 3 seafloor character types (hard-rugged, hard-flat, and soft-flat), 25 modifier groups, and 9 geoforms. The study area substrate is predominantly soft-flat sediment (mud and fine sand) covering 191.3 km 2 (56.1 percent) of the area. Hard-flat substrate areas, predominantly coarse sediment in scour depressions, cover 52.2 km 2 (15.3 percent) of the study area. The hard-rugged substrate areas are primarily outcrops of layered sedimentary bedrock and constitute 97.5 km 2 of the study area (28.6 percent). After classification of bathymetry and backscatter raster images according to substrate, false-positive hard areas produced by noise artifacts were removed by manual editing. Nine geoforms were then identified in the analysis. The predominant geoforms mirror the seafloor character results, shelf geoforms (flat areas covered in soft sediment), rock outcrop geoforms (hard, rugged areas), and scour depression geoforms (flat areas covered in coarse sediment formed by bottom currents).

California↗
USGS2020

Hawaiian hoary bat (Lasiurus cinereus semotus) behavior at wind turbines on Maui

This study examined the activity of the endemic Hawaiian hoary bat (Lasiurus cinereus semotus) at wind turbines operated by Auwahi Wind Energy, LLC, on southern Maui Island, from August to November 2018. The research was conducted to assess the potential effect of wind speed and turbine operation on bat presence and behavior and compared information obtained from both acoustic monitoring and thermal videography. During the four months of nightly surveillance at four wind turbines, we observed 384 visual (videographic) and 244 acoustic detection events involving bats. Bats were infrequently detected, averaging 0.08 events per hour for both visual and acoustic samples. Detections occurred throughout the monitoring period, but bat presence was only evident for a fraction (acoustic: 30%; visual: 44%) of the turbine-nights sampled. Bats were present throughout the night, but detections exhibited a unimodal peak centered on the first third of the night, with events largely absent in the latter half of the night and no apparent seasonal trend towards earlier or later occurrence within nights. However, a decline in the visual detection rate was noted over the four-month period (a similar assessment was not available from acoustic samples due to missing data for much of the later months). Visual bat detections were not significantly correlated over nights (i.e., temporally), but were positively associated among turbines (i.e., spatially). Visual detections were generally brief (median = 9.0 sec), infrequent (median time between events = 49.0 min), and involved single passes (57%) largely comprised of a single bat (94%). The amount of time during which bats were visually observed amounted to only 0.05% of total videographic monitoring (2.5 hours of 5,066 total hours). Although not directly comparable to the video results because of differences in the volume of airspace sampled and nature of observation, acoustic detection events were similarly brief (median = 6.0 sec), infrequent (median time between passes = 38.8 min), and also composed only 0.05% of the total period of acoustic monitoring (1.6 hours of 3,036 total hours). Most visual observations (61%) were of individuals flying at some point during the event to within about 15 m of the turbine nacelle (machinery housing atop the monopole). Erratic flight paths were the most prevalent flight type with bats often repeatedly approaching and circling the nacelle. Terminal-phase (“feeding buzz”) calls were only noted in 3% of all acoustic events. Bats were most frequently detected visually at relatively low wind speeds (median = 3.4 m/sec); however, 10% of events occurred at wind speeds over 8.5 m/sec. Nightly bat detection rates for the four-month period of monitoring were negatively correlated with total daily precipitation. Generalized linear mixed model analysis confirmed that detection rates were negatively associated with wind speed and precipitation and indicated a positive relation with intermittent wind speed and its consequent effect on turbine blade rotation (i.e., frequent intervals of starting and stopping). The co-occurrence of bat detection obtained from videographic and acoustic monitoring methods was generally low, and in instances when individuals were visually observed, bats were detected acoustically during only 12% (within a 10-minute window), 22% (within a 2-hour window), and 56% (at some point during the entire night) of such events. Most visual detections (65% within a 2-hour window) lacking an acoustic detection involved bats observed flying within about 15 m of the turbine nacelle on which acoustic detector microphones were situated.

Hawaii↗
USGS2020

Assessing the exposure of three diving bird species to offshore wind areas on the U.S. Atlantic Outer Continental Shelf using satellite telemetry

Aim The United States Atlantic Outer Continental Shelf (OCS) has considerable offshore wind energy potential. Capturing that resource is part of a broader effort to reduce CO 2 emissions. While few turbines have been constructed in U.S. waters, over a dozen currently planned offshore wind projects have the potential to displace marine birds, potentially leading to effective habitat loss. We focused on three diving birds identified in Europe to be vulnerable to displacement. Our research aimed to determine their potential exposure to areas designated or proposed for offshore wind development along the Atlantic OCS. Methods Satellite tracking technology was used to determine the spatial and temporal use and movement patterns of Surf Scoters ( Melanitta perspicillata ), Red‐throated Loons ( Gavia stellata ) and Northern Gannets ( Morus bassanus ), and calculate their exposure to each offshore wind area. We tagged 236 adults in 2012–2015 on the Atlantic OCS from New Jersey to North Carolina; an additional 147 birds tagged in previous tracking studies were integrated into our analyses. Tracking data were analysed in two‐week intervals using dynamic Brownian bridge movement models to develop composite spatial utilization distributions. For each species, these distributions were then used to calculate the spatio‐temporal exposure to each offshore wind area. Results Surf Scoters and Red‐throated Loons were exposed to offshore wind areas almost exclusively during migration because these species were distributed among coastal and inshore waters during winter months. In contrast, Northern Gannets ranged over a much larger area, reaching farther offshore and south in winter, thus exhibited the greatest exposure to extant offshore wind areas. Conclusions Results of this study provide better understanding of how diving birds use current and potential future offshore wind areas on the Atlantic OCS, and can inform permitting, risk assessment and pre‐ and post‐construction impact assessments of offshore energy infrastructure.

Atlantic Outer Continental Shelf↗
USGS2016

U.S. Geological Survey—Energy and Wildlife Research Annual Report for 2016

Recent growth and development of renewable energy and unconventional oil and gas extraction are rapidly diversifying the energy supply of the United States. Yet, as our Nation works to advance energy security and conserve wildlife, some conflicts have surfaced. To address these challenges, the U.S. Geological Survey (USGS) is conducting innovative research and developing workable solutions to reduce the impacts of energy production on wildlife. USGS scientists collaborate on many studies with scientists from other Federal, State, and local government agencies; Tribal nations; academic research institutions; and nongovernmental and private organizations. The mix of fuels used for electricity generation is evolving. Solar, natural gas, and wind energy made up most electricity generation additions in 2015 and 2016. The United States now leads the world in natural gas production, with new record highs for each year from 2011 through 2015. More than 48,000 wind turbines now contribute to power grids in most States, providing about 5 percent of U.S. end-use electricity demand in an average year. The number of utility-scale solar-energy projects is growing rapidly with solar energy projected to contribute to the largest electricity generation addition in 2016. A substantial number of large energy projects have been constructed on undeveloped public lands, and more are anticipated at an increasing rate, creating new stress to wildlife. Direct impacts include collisions with wind turbines and structures at solar facilities and loss of habitat which may negatively affect sensitive species. Recent estimates suggest 250,000 to 500,000 birds die each year at wind turbine facilities. Bat fatality rates at wind turbine facilities are less certain, but may average several hundred thousand per year throughout North America. Because new projects may be located in or near sensitive wildlife habitats, ecological science plays a key role in helping to guide project siting and operational decisions.

Open-File Report↗
USGS2018

Landscape-scale wildlife species richness metrics to inform wind and solar energy facility siting: An Arizona case study

The juxtaposition of wildlife and wind or solar energy facility infrastructure can present problems for developers, planners, policy makers, and management agencies. Guidance on siting of these renewable energy facilities may help identify potential wildlife-facility conflicts with species of regulatory or economic concern. However, existing spatial guidance usually does not consider all wildlife that might use a potential facility location or corridors for its servicing infrastructure. We illustrate an approach toward assessing potential wildlife-facility conflicts using readily available vertebrate habitat models. The U.S. Geological Survey's Gap Analysis Program (GAP) has developed spatial models of potential habitat for vertebrate species across the entire nation. To illustrate their applicability, we used GAP models to estimate richness of all native, terrestrial vertebrates within Arizona and for those vertebrates grouped by class or by sensitivity to the type of facility infrastructure. We examined the spatial overlap of high species richness of each group with agency-developed guidance used to inform facility-siting decisions and found that GAP-based richness mappings augmented existing guidance. As the GAP vertebrate habitat models are publicly available for the entire USA, use of these data can provide a coarse view of potential wildlife-facility conflicts and inform facility planning early in the process.

Arizona↗
USGS2013

Abundance and density of lesser prairie-chickens and leks in Texas

Lesser prairie-chickens (LEPCs; Tympanuchus pallidicinctus) have experienced population declines due to both direct and indirect habitat loss, including conversion of native rangeland to cropland and disturbance from energy development. Our objectives were to 1) determine the current density of LEPC leks and LEPCs within the Texas (USA) occupied range, including areas with high potential for wind-energy development; and 2) find new leks. To estimate lek and LEPC density, we employed a line-transect-based aerial survey method using a Robinson 22 helicopter to count leks. We surveyed 26,810.9 km of transect in the spring of 2010 and 2011 and we detected 96 leks. We estimated a density of 2.0 leks/100 km(2) (90% CI = 1.4-2.7 leks/100 km(2)) and 12.3 LEPCs/100 km(2) (90% CI = 8.5-17.9 LEPCs/100 km(2)) and an abundance of 293.6 leks (90% CI = 213.9-403.0 leks) and 1,822.4 LEPCs (90% CI = 1,253.7-2,649.1 LEPCs) for our sampling frame. Our best model indicated that lek size and lek type (AIC(c) wt = 0.235) influenced lek detectability. Lek detectability was greater for larger leks and natural leks versus man-made leks. Our statewide survey efforts provide wildlife managers and biologists with population estimates, new lek locations, and areas to target for monitoring and conservation.

Wildlife Society Bulletin↗
USGS2011

Locations and attributes of wind turbines in New Mexico, 2009

The New Mexico wind-turbine data series provides geospatial data for all wind turbines established within the State as of August 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, and county. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, year the facility went online, and development status of wind facility. Turbine locations were derived from 1-meter August 2009 true-color aerial photographs produced by the National Agriculture Imagery Program; the photographs have a positional accuracy of about + or - 5 meters. The location of turbines under construction during August 2009 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas currently (2011) in development by the U.S. Geological Survey. The Energy Atlas will synthesize data on existing and potential energy development in Colorado and New Mexico and will include additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools will be included in the Energy Atlas. The format of the Energy Atlas will facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

Data Series↗
USGS2011

Locations and attributes of wind turbines in Colorado, 2009

The Colorado wind-turbine data series provides geospatial data for all wind turbines established within the State as of August 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, and county. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, year the facility went online, and development status of wind facility. Turbine locations were derived from August 2009 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program; the photographs have a positional accuracy of about + or - 5 meters. The location of turbines under construction during August 2009 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas currently (2011) in development by the U.S. Geological Survey. The Energy Atlas will synthesize data on existing and potential energy development in Colorado and New Mexico and will include additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools will be included in the Energy Atlas. The format of the Energy Atlas will facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

Data Series↗
USGS2021

Behavioral patterns of bats at a wind turbine confirm seasonality of fatality risk

Bat fatalities at wind energy facilities in North America are predominantly comprised of migratory, tree-dependent species, but it is unclear why these bats are at higher risk. Factors influencing bat susceptibility to wind turbines might be revealed by temporal patterns in their behaviors around these dynamic landscape structures. In northern temperate zones, fatalities occur mostly from July through October, but whether this reflects seasonally variable behaviors, passage of migrants, or some combination of factors remains unknown. In this study, we examined video imagery spanning one year in the state of Colorado in the United States, to characterize patterns of seasonal and nightly variability in bat behavior at a wind turbine. We detected bats on 177 of 306 nights representing approximately 3,800 hr of video and > 2,000 discrete bat events. We observed bats approaching the turbine throughout the night across all months during which bats were observed. Two distinct seasonal peaks of bat activity occurred in July and September, representing 30% and 42% increases in discrete bat events from the preceding months June and August, respectively. Bats exhibited behaviors around the turbine that increased in both diversity and duration in July and September. The peaks in bat events were reflected in chasing and turbine approach behaviors. Many of the bat events involved multiple approaches to the turbine, including when bats were displaced through the air by moving blades. The seasonal and nightly patterns we observed were consistent with the possibility that wind turbines invoke investigative behaviors in bats in late summer and autumn coincident with migration and that bats may return and fly close to wind turbines even after experiencing potentially disruptive stimuli like moving blades. Our results point to the need for a deeper understanding of the seasonality, drivers, and characteristics of bat movement across spatial scales.

Ecology and Evolution↗
USGS2012

Model of whooping crane energetics as foundation for development of a method to assess potential take during migration

A whooping crane energetic model was developed as a component of a larger effort to ascertain potential take, as defined by the Endangered Species Act, of whooping cranes from proposed development of wind-energy infrastructure in the Great Plains of North America. The primary objectives of this energetic model were to (1) predict extra flight energy that whooping cranes may require to find suitable migration stopover sites if they are unable to use a primary site; and (2) express energy expended as additional time required to replenish lipid reserves used to fuel flight. The energetic model is based on three elements related to energy: expenditure of energy, intake of energy, and constraints to energy intake. The energetic model estimates each element and recognizes interactions among them. This framework will be most useful when integrated into a migration model that predicts incidence of avoidance of wind towers by whooping cranes and distances they might fly to find alternative stopover habitat. This report details work conducted in accordance with the U.S. Geological Survey and U.S. Fish and Wildlife Service Quick Response Program funded in fiscal year 2011 and will serve as a final report.

Open-File Report↗
USGS2017

Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy

In 2014 the U.S. Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) entered into Intra-agency agreement M13PG00037 to map an area of the Oregon Outer Continental Shelf (OCS) off of Coos Bay, Oregon, under consideration for development of a floating wind energy farm. The BOEM requires seafloor mapping and site characterization studies in order to evaluate the impact of seafloor and sub-seafloor conditions on the installation, operation, and structural integrity of proposed renewable energy projects, as well as to assess the potential effects of construction and operations on archaeological resources. The mission of the USGS is to provide geologic, topographic, and hydrologic information that contributes to the wise management of the Nation's natural resources and that promotes the health, safety, and well being of the people. This information consists of maps, databases, and descriptions and analyses of the water, energy, and mineral resources, land surface, underlying geologic structure, and dynamic processes of the earth. For the Oregon OCS study, the USGS acquired multibeam echo sounder and seafloor video data surrounding the proposed development site, which is 95 km2 in area and 15 miles offshore from Coos Bay. The development site had been surveyed by Solmar Hydro Inc. in 2013 under a contract with WindFloat Pacific. The USGS subsequently produced a bathymetry digital elevation model and a backscatter intensity grid that were merged with existing data collected by the contractor. The merged grids were published along with visual observations of benthic geo-habitat from the video data in an associated USGS data release (Cochrane and others, 2015). This report includes the results of analysis of the video data conducted by Oregon State University and the geo-habitat interpretation of the multibeam echo sounder (MBES) data conducted by the USGS. MBES data was published in Cochrane and others (2015). Interpretive data associated with this publication is published in Cochrane (2017). All the data is provided as geographic information system (GIS) files that contain both Esri ArcGIS geotiffs or shapefiles. For those who do not own the full suite of Esri GIS and mapping software, the data can be read using Esri ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed August 29, 2016). Web services, which consist of standard implementations of ArcGIS representational state transfer (REST) Service and Open Geospatial Consortium (OGC) GIS web map service (WMS), also are available for all published GIS data. Web services were created using an ArcGIS service definition file, resulting in data layers that are symbolized as shown on the associated report figures. Both the ArcGIS REST Service and OGC WMS Service include all the individual GIS layers. Data layers are bundled together in a map-area web service; however, each layer can be symbolized and accessed individually after the web service is ingested into a desktop application or web map. Web services enable users to download and view data, as well as to easily add data to their own workflows, using any browser-enabled, standalone or mobile device. Though the surficial substrate is dominated by combinations of mud and sand substrate, a diverse assortment of geomorphologic features are related to geologic processes—one anticlinal ridge where bedrock is exposed, a slump and associated scarps, and pockmarks. Pockmarks are seen in the form of fields of small pockmarks, a lineation of large pockmarks with methanogenic carbonates, and areas of large pockmarks that have merged into larger variously shaped depressions. The slump appears to have originated at the pockmark lineation. Video-supervised numerical analysis of the MBES backscatter intensity data and vector ruggedness derived from the MBES bathymetry data was used to produce a substrate model called a seafloor character raster for the study area. The seafloor character raster consists of three substrate classes: soft-flat areas, hard-flat areas, and hard-rugged areas. A Coastal and Marine Ecological Classification Standard (CMECS) geoform and substrate map was also produced using depth, slope, and benthic position index classes to delineate geoform boundaries. Seven geoforms were identified in this process, including ridges, slump scars, slump deposits, basins, and pockmarks. Statistical analysis of the video data for correlations between substrate, depth, and invertebrate assemblages resulted in the identification of seven biomes: three hard-bottom biomes and four softbottom biomes. A similar analysis of vertebrate observations produces a similar set of biomes. The biome between-group dissimilarity was very high or high. Invertebrates alone represent most of the structure of the whole benthic community into different assemblages. A biotope map was generated using the seafloor character raster and the substrate and depth values of the biomes. Hard substrate biotopes were small in size and were located primarily on the ridge and in pockmarks along the pockmark lineation. The soft-bottom bitopes consisted of large contiguous areas delimited by isobaths.

Open-File Report↗
USGS2018

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2016 annual report

This is the ninth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In fiscal year (FY) 2016, there were 26 active USGS WLCI science-based projects. Of these 26 projects, one project was new for FY2016, and three were completed by the end of the fiscal year (though final products were still in preparation or review). USGS WLCI projects were grouped under five categories: (1) Baseline Synthesis, (2) Long-Term Monitoring, (3) Effectiveness Monitoring, (4) Mechanistic Studies of Wildlife, and (5) Data and Information Management. Each of these topic areas is designed to address WLCI management needs: identifying key drivers of change, identifying the condition and distribution of key wildlife species and habitats and of species’ habitat requirements, development of an integrated inventory and monitoring strategy, use of emerging technologies and development and testing of innovative methods for maximizing the efficiency and efficacy of monitoring efforts, evaluating the effectiveness of habitat treatment projects, evaluating the responses of wildlife to development, and developing a data clearinghouse and information management framework to support and provide access to results of most USGS WLCI projects. In FY2016, we assisted with updating the WLCI Conservation Action Plan and associated databases as part of the Comprehensive Assessment, and we also assisted with the Bureau of Land Management 2015 WLCI annual report. By the end of FY2016, we completed or had nearly completed assessments of WLCI energy and mineral resources and had submitted a manuscript on modeled effects of oil and gas development on wildlife to a peer-reviewed journal. We also initiated a study on the effects of wind energy on wildlife in the WLCI region. A USGS circular on WLCI long-term monitoring was in review at the end of the fiscal year, and seven projects monitoring water and vegetation (including changes in sagebrush cover and patterns of sagebrush mortality) continued through the year. USGS scientists continued many projects in FY2016 that evaluate the effectiveness of habitat conservation actions (including sagebrush, cheatgrass, and aspen habitat treatments) and provide tools in support of mechanistic studies of wildlife. In FY2016, USGS scientists, along with university and State partners, continued work on five focal wildlife species/communities (pygmy rabbits [ Brachylagus idahoensis ], greater sage grouse , mule deer, sagebrush songbirds, and native fish). In FY2016, the USGS Information Management Team presented information to WLCI scientists on how USGS tools and resources can be used to fulfill the requirements of new USGS policies regarding data release, data management, and data visualization.

Wyoming↗
USGS2024

Realizing the potential of eDNA biodiversity monitoring tools in the marine environment with application to offshore renewable energy

The U.S. Geological Survey (USGS) researches the biological diversity and distribution of species to support management, conservation, and resource use decisions. USGS scientists advance detection and monitoring technologies to assess changes in fish and wildlife populations, biodiversity, and the health of ecosystems. The United States is planning to install 30 gigawatts of offshore marine and wind energy by 2030. However, the effects on fish and wildlife and their habitats are not well understood. The USGS is a leader in the field of eDNA technologies and has helped advance robotic eDNA samplers, has extensive experience working in the offshore environment, and has developed novel and actionable statistical methods and standards for eDNA monitoring applications. This fact sheet presents key eDNA research and development advances needed for realizing the potential of eDNA biodiversity monitoring tools in the marine environment and applying eDNA monitoring to offshore renewable energy development. New and cost-effective tools for measuring changes in biodiversity in response to offshore renewable energy development can help to inform natural resource management and project planning and permitting decisions.

Fact Sheet↗
USGS2019

Reducing greenhouse gas emissions of Amazon hydropower with strategic dam planning

Hundreds of dams have been proposed throughout the Amazon basin, one of the world’s largest untapped hydropower frontiers. While hydropower is a potentially clean source of renewable energy, some projects produce high greenhouse gas (GHG) emissions per unit electricity generated (carbon intensity). Here we show how carbon intensities of proposed Amazon upland dams (median = 39 kg CO 2 eq MWh −1 , 100-year horizon) are often comparable with solar and wind energy, whereas some lowland dams (median = 133 kg CO 2 eq MWh −1 ) may exceed carbon intensities of fossil-fuel power plants. Based on 158 existing and 351 proposed dams, we present a multi-objective optimization framework showing that low-carbon expansion of Amazon hydropower relies on strategic planning, which is generally linked to placing dams in higher elevations and smaller streams. Ultimately, basin-scale dam planning that considers GHG emissions along with social and ecological externalities will be decisive for sustainable energy development where new hydropower is contemplated.

Nature Communications↗