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At least 127 records · Page 7Linked to original sources
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↗
USGS2011

Turtles and culverts, and alternative energy development: an unreported but potentially significant mortality threat to the desert tortoise ( Gopherus agassizii )

Culverts are often used to increase the permeability of roaded landscapes for wildlife, including turtles. Although the benefits of culverts as safe passages for turtles are well documented, under some conditions culverts can entrap them and cause mortality. Here we report a culvert-related mortality in the federally threatened desert tortoise ( Gopherus agassizii ) at a wind energy facility in California and offer simple recommendations to mitigate the negative effects of culverts for wildlife in general.

Chelonian Conservation and Biology↗
USGS2000

Hurricanes, coral reefs and rainforests: resistance, ruin and recovery in the Caribbean

The coexistence of hurricanes, coral reefs, and rainforests in the Caribbean demonstrates that highly structured ecosystems with great diversity can flourish in spite of recurring exposure to intense destructive energy. Coral reefs develop in response to wave energy and resist hurricanes largely by virtue of their structural strength. Limited fetch also protects some reefs from fully developed hurricane waves. While storms may produce dramatic local reef damage, they appear to have little impact on the ability of coral reefs to provide food or habitat for fish and other animals. Rainforests experience an enormous increase in wind energy during hurricanes with dramatic structural changes in the vegetation. The resulting changes in forest microclimate are larger than those on reefs and the loss of fruit, leaves, cover, and microclimate has a great impact on animal populations. Recovery of many aspects of rainforest structure and function is rapid, though there may be long-term changes in species composition. While resistance and repair have maintained reefs and rainforests in the past, human impacts may threaten their ability to survive.

Ambio↗
USGS2015

Onshore industrial wind turbine locations for the United States up to March 2014

Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.

Scientific Data↗
USGS2022

California Deepwater Investigations and Groundtruthing (Cal DIG) I, volume 3 — Benthic habitat characterization offshore Morro Bay, California

Coastal and Marine Ecological Classification Standard (CMECS) geoform, substrate, and biotic component geographic information system (GIS) products were developed for the U.S. Exclusive Economic Zone (U.S. EEZ) of south-central California in the region of Santa Lucia Bank motivated by interest in development of offshore wind-energy capacity and infrastructure. The Bureau of Ocean Energy Management (BOEM), in coordination with the State of California and many other members of the California Task Force, issued calls for information in 2018 for the study area offshore of Morro Bay, California. The study area is in depths of 500 to 1,200 meters (m) and adjacent to a decommissioned nuclear power plant with a developed electric grid connection, and in an area of high wind resource. BOEM is the lead agency responsible for planning and leasing in the U.S. EEZ 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 (USGS), resulted in three reports: one on biological analysis of seafloor video data, one on analysis of the geologic framework and hazards, and this report on seafloor habitat. The study area consists of 8,424 square kilometers (km 2 ) of multibeam echo sounder (MBES) data acquired during five surveys from 2016 to 2019. Remotely operated vehicle (ROV) video was acquired in 2019 to supervise the classification of the MBES data into habitats. Derivatives of the MBES data were classified into 16 unique biotopes, 6 substrate types, 28 modifier groups, and 22 geoforms. The study area substrate is predominantly soft sediment (mud and fine sand) covering 7,804 km 2 (92.7 percent) of the area. Mixed substrate areas on rocky banks, channel scarps, and the shelf break comprise 404 km 2 (4.8 percent) of the study area. Hard substrate areas are found predominantly on the tops and flanks of banks and on bank ridges that separate canyons incising the banks. Hard substrates comprise 211 km 2 of the study area (2.5 percent). After the bathymetry and backscatter raster images (rasters) were classified, manual editing was also done to remove noise artifacts. This effort was not completely successful and there are numerous erroneous small areas in the rasters that have been passed on to the CMECS polygon product. Nearly 120,000 annotations of organisms and their habitat were made from 25 video transects selected from 185 hours of ROV video. In total, 2,714 km 2 of seafloor were successfully assigned to biotopes. Some biotopes were assigned to separate areas spatially distant from the transects that define the biotope. Expected relations between physical habitat and biota such as the number of species and the substrate induration and rugosity were verified. Slope is typically a predictive variable and was used in the classification of habitat, but the ground truth used for biotic component analysis included very little steeply sloping area. Ground-truth ROV operations were reduced by the sea state; additional ground truth could improve the biotic results and increase confidence in the spatial distribution of classifications reported here.

California↗
USGS2026

Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines

Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.

Ecological Informatics↗
USGS2024

Efficacy of non-lead ammunition distribution programs to offset fatalities of golden eagles in southeast Wyoming

Golden eagles ( Aquila chrysaetos ) face many anthropogenic risks including illegal shooting, electrocution, collision with wind turbines and vehicles, and lead poisoning. Minimizing or offsetting eagle deaths resulting from human-caused sources is often viewed as an important management objective. Despite understanding the leading anthropogenic sources of eagle fatalities, existing scientific research supports few practical solutions to mitigate these causes of death. We implemented a non-lead ammunition distribution program in southeast Wyoming, USA, and evaluated its effectiveness as a compensatory mitigation action to offset incidental take (i.e., fatalities) of golden eagles at wind energy facilities. In 2020 and 2022, we distributed non-lead ammunition to 699 hunters with big-game tags specific to our >400,000-ha study area. These hunters harvested 296 pronghorn ( Antilocapra americana ), 14 deer ( Odocoileus spp.), and 33 elk ( Cervus canadensis ) in the study area, which accounted for 6.9% and 6.5% of the harvest in these hunt units in 2020 and 2022, respectively. We used road surveys in 2020 to estimate a density of 0.036 (95% CI = 0.018–0.058) golden eagles/km 2 during the big game hunting season in our study area. Model output suggests that our non-lead ammunition distribution program offset the fatality of 3.84 (95% CI = 1.06–23.72) eagles over the course of these 2 hunting seasons. Our work illustrates the potential usefulness of non-lead ammunition distribution programs as an action to mitigate eagle fatalities caused by wind facilities or other anthropogenic causes of death.

Wyoming↗
USGS2012

Evidence of late-summer mating readiness and early sexual maturation in migratory tree-roosting bats found dead at wind turbines

Understanding animal mating systems is an important component of their conservation, yet the precise mating times for many species of bats are unknown. The aim of this study was to better understand the details and timing of reproductive events in species of bats that die most frequently at wind turbines in North America, because such information can help inform conservation strategies. We examined the reproductive anatomy of hoary bats (Lasiurus cinereus), eastern red bats (L. borealis), and silver-haired bats (Lasionycteris noctivagans) found dead beneath industrial-scale wind turbines to learn more about when they mate. We evaluated 103 L. cinereus, 18 L. borealis, and 47 Ln. noctivagans from wind energy facilities in the United States and Canada. Histological analysis revealed that most male L. cinereus and L. borealis, as well as over half the Ln. noctivagans examined had sperm in the caudae epididymides by late August, indicating readiness to mate. Testes regression in male hoary bats coincided with enlargement of seminal vesicles and apparent growth of keratinized spines on the glans penis. Seasonality of these processes also suggests that mating could occur during August in L. cinereus. Spermatozoa were found in the uterus of an adult female hoary bat collected in September, but not in any other females. Ovaries of all females sampled had growing secondary or tertiary follicles, indicating sexual maturity even in first-year females. Lasiurus cinereus, L. borealis, and Ln. noctivagans are the only North American temperate bats in which most first-year young of both sexes are known to sexually mature in their first autumn. Our findings provide the first detailed information published on the seasonal timing of mating readiness in these species most affected by wind turbines.

PLoS ONE↗
USGS2014

Accounting for unsearched areas in estimating wind turbine-caused fatality

With wind energy production expanding rapidly, concerns about turbine-induced bird and bat fatality have grown and the demand for accurate estimation of fatality is increasing. Estimation typically involves counting carcasses observed below turbines and adjusting counts by estimated detection probabilities. Three primary sources of imperfect detection are 1) carcasses fall into unsearched areas, 2) carcasses are removed or destroyed before sampling, and 3) carcasses present in the searched area are missed by observers. Search plots large enough to comprise 100% of turbine-induced fatality are expensive to search and may nonetheless contain areas unsearchable because of dangerous terrain or impenetrable brush. We evaluated models relating carcass density to distance from the turbine to estimate the proportion of carcasses expected to fall in searched areas and evaluated the statistical cost of restricting searches to areas near turbines where carcass density is highest and search conditions optimal. We compared 5 estimators differing in assumptions about the relationship of carcass density to distance from the turbine. We tested them on 6 different carcass dispersion scenarios at each of 3 sites under 2 different search regimes. We found that even simple distance-based carcass-density models were more effective at reducing bias than was a 5-fold expansion of the search area. Estimators incorporating fitted rather than assumed models were least biased, even under restricted searches. Accurate estimates of fatality at wind-power facilities will allow critical comparisons of rates among turbines, sites, and regions and contribute to our understanding of the potential environmental impact of this technology.

Journal of Wildlife Management↗
USGS2022

Aerial counts for surface-nesting seabirds at Lehua Island and Moku Manu Islet and Ulupaʻu Crater, Oʻahu, in 2019

Among important seabird breeding sites in the main Hawaiian Islands, Lehua Island offshore Niʻihau and Moku Manu Islets offshore Oʻahu support diverse and abundant seabird breeding populations. Both offshore islands provide excellent nesting habitat for surface-nesting boobies ( Sula spp .) and terns but, of the two, only Moku Manu supports relatively large breeding populations of Sooty Tern ( Onychoprion fuscatus ) and Brown Noddy ( Anous stolidus ). Additionally, Ulupaʻu Crater, near Moku Manu on Oʻahu, is one of only a few sites within the eight main Hawaiian islands and the only site on the main island of Oʻahu that supports a nesting population of Red-footed Boobies ( Sula sula ). Despite their importance for informing renewable offshore energy planning off Hawaiʻi, robust and accurate seabird population survey data exist and are available for some locations (Lehua; Raine and others, 2021), but at Moku Manu and Ulupa‘u Crater, recent information are not yet available (E. VanderWerf, written commun. 2021). In this study, we completed comprehensive aerial photographic counts at these three sites for six surface-nesting seabird species present during the 2019 breeding season: Brown Booby ( Sula leucogaster ), Red-footed Booby, Masked Booby ( S. dactylatra ), Great Frigatebird ( Fregata minor ), Sooty Tern, and Brown Noddy. We estimated 5,782, 102, and 1,446 nesting pairs of Red-footed Boobies at Lehua, Ulupaʻu Crater, and Moku Manu, respectively. At Lehua and Moku Manu, we estimated 692 and 65 nesting pairs of Brown Boobies, respectively. At Moku Manu, we estimated 95 nesting pairs of Masked Boobies, one of only three nesting locales for this species in the main Hawaiian Islands. Based on digital photograph counts of sampled areas and area-based extrapolation, we estimated 17,938 terns (mostly Sooty Tern with fewer Brown Noddy) on Moku Manu. We observed Great Frigatebirds roosting at the two island sites, but we did not detect any sign of nesting for this species. We found that inter-observer counts for behavioral classifications (nesting, roosting, unknown) ranged in precision (D=0.13–0.31), but generally, counts among photographs accounting for all seabird targets (D=0.10–0.22) and for boobies classified as nesting (D=0.13–0.18) were more precise than for roosting and unknown categories (D=0.13–0.31), indicating that at least some of the variation in count precision relates to differences in how independent counters identified behavioral classifications. The nesting population sizes (and number of terns present on Moku Manu) present during aerial counts likely are minimum estimates because individuals among these species can exhibit asynchronous nesting phenologies, and not all members of the nesting populations would be expected to be attending the sites when we surveyed. The results of these counts provide current and accurate abundance estimates for these species that can serve as benchmarks for future management and monitoring and as important components of population-level assessments aimed at quantifying seabird vulnerability to potential offshore wind energy development in the main Hawaiian Islands.

Hawaii↗
USGS2019

Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors

Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat ( Myotis lucifugus ) and the hoary bat ( Lasiurus cinereus ). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat ( = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ( = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.

Oregon, Washington↗
USGS2022

Structural and functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion

The lesser prairie-chicken ( Tympanuchus pallidicinctus ) is a species of conservation concern on the Southern High Plains of Texas and New Mexico, USA. Because fragmentation and isolation have increased since pre-settlement, dispersal through this heterogeneous landscape may be constrained, with serious implications for conservation and management of this species. Our objectives were to quantify landscape connectivity for lesser prairie-chickens within a patch network of potentially isolated leks (breeding display grounds), and examine effects of land use change on modeled lesser prairie-chicken movements through the landscape. We used graph theory to quantify structural landscape connectivity and circuit theory to quantify functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion of the Southern High Plains. There was a high degree of clustering among leks ( n = 1,023 leks), with a 41.9-km coalescence distance of the network. We identified 3 leks as cutpoints within the network, meaning if the habitat patches containing these leks were fragmented, the remaining leks would become isolated from each other. We also identified several leks that were important for maintaining overall population connectivity for lesser prairie-chickens on the Southern High Plains. Conservation Reserve Program land was important for maintaining connectivity among leks to the north and west of the main lek core area located in New Mexico, but wind energy development constrained pathways to the north and south of this main lek core area. Our results suggest that landscape connectivity was reduced by row-crop agriculture and energy production and facilitated by the Conservation Reserve Program within the Sand Shinnery Oak Prairie Ecoregion.

New Mexico, Texas↗