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At least 811 records · Page 45Linked to original sources

USGS2023

Challenges and solutions for automated avian recognition in aerial imagery

Remote aerial sensing provides a non-invasive, large geographical-scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mitigate this manual image processing requirement. The implementation of AI methods, however, has several challenges: (1) imbalanced (i.e., long-tailed) data distribution, (2) annotation uncertainty in categorization, and (3) dataset discrepancies across different study sites. Here we use aerial imagery data of waterbirds around Cape Cod and Lake Michigan in the United States to examine how these challenges limit avian recognition performance. We review existing solutions and demonstrate as use cases how methods like Label Distribution Aware Marginal Loss with Deferred Re-Weighting, hierarchical classification, and FixMatch address the three challenges. We also present a new approach to tackle the annotation uncertainty challenge using a Soft-fine Pseudo-Label methodology. Finally, we aim with this paper to increase awareness in the ecological remote sensing community of these challenges and bridge the gap between ecological applications and state-of-the-art computer science, thereby opening new doors to future research.

Remote Sensing in Ecology and Conservation↗

USGS2024

Ion exchange processes for CO2 mineralization using industrial waste streams: Pilot plant demonstration and life cycle assessment

An attractive technique for removing CO 2 from the environment is sequestration within stable carbonate solids (e. g., calcite). However, continuous addition of alkalinity is required to achieve favorable conditions for carbonate precipitation (pH>8) from aqueous streams containing dissolved CO 2 (pH<4.5) and Ca 2+ ions. In this study, a pH-swing process using ion exchange was demonstrated to process 300 L of produced water brine per day for CO 2 mineralization. Proton titration capacities were quantified for aqueous streams in equilibrium with gas streams at various concentrations of CO 2 (pCO 2 =0.03–0.20 atm) and at various flow rates (0.5–2.0 L min −1 ). Energy intensities for the process were determined to be between 30 and 65 kWh per tonne of CO 2 sequestered depending on the composition of the brine stream. A life cycle assessment was performed to analyze the net carbon emissions of the technology which indicated a net CO 2 reduction for pCO 2 ≥0.12 atm (−0.06–−0.39 kg CO 2 e per kg precipitated CaCO 3 ) utilizing calcium-rich brines. The results from this study indicate the ion exchange process can be used as a scalable method to provide alkalinity necessary for the capture and storage of CO 2 in Ca-rich waste streams.

Chemistry Select↗

USGS2015

Blind identification of the Millikan Library from earthquake data considering soil–structure interaction

The Robert A. Millikan Library is a reinforced concrete building with a basement level and nine stories above the ground. Located on the campus of California Institute of Technology (Caltech) in Pasadena California, it is among the most densely instrumented buildings in the U.S. From the early dates of its construction, it has been the subject of many investigations, especially regarding soil–structure interaction effects. It is well accepted that the structure is significantly interacting with the surrounding soil, which implies that the true foundation input motions cannot be directly recorded during earthquakes because of inertial effects. Based on this limitation, input–output modal identification methods are not applicable to this soil–structure system. On the other hand, conventional output-only methods are typically based on the unknown input signals to be stationary whitenoise, which is not the case for earthquake excitations. Through the use of recently developed blind identification (i.e. output-only) methods, it has become possible to extract such information from only the response signals because of earthquake excitations. In the present study, we employ such a blind identification method to extract the modal properties of the Millikan Library. We present some modes that have not been identified from force vibration tests in several studies to date. Then, to quantify the contribution of soil–structure interaction effects, we first create a detailed Finite Element (FE) model using available information about the superstructure; and subsequently update the soil–foundation system's dynamic stiffnesses at each mode such that the modal properties of the entire soil–structure system agree well with those obtained via output-only modal identification.

California↗

USGS2013

The Anemomilos prediction methodology for Dst

This paper describes new capabilities for operational geomagnetic D isturbance s torm t ime (Dst) index forecasts. We present a data‐driven, deterministic algorithm called Anemomilos for forecasting Dst out to a maximum of 6 days for large, medium, and small storms, depending upon transit time to the Earth. This capability is used for operational satellite management and debris avoidance in Low Earth Orbit (LEO). Anemomilos has a 15 min cadence, 1 h time granularity, 144 h prediction window (+6 days), and up to 1 h latency. A new finding is that nearly all flare events above a certain irradiance threshold, occurring within a defined solar longitude/latitude region and having sufficient estimated liftoff velocity of ejected material, will produce a geoeffective Dst perturbation. Three solar observables are used for operational Dst forecasting: flare magnitude, integrated flare irradiance through time, and event location. Magnitude is a proxy for ejecta quantity or mass and, combined with speed derived from the integrated flare irradiance, represents the kinetic energy. Speed is estimated as the line‐of‐sight velocity for events within 45° radial of solar disk center. Storms resulting from high‐speed streams emanating from coronal holes are not modeled or predicted. A new result is that solar disk, not limb, observable features are used for predictive techniques. Comparisons between Anemomilos predicted and measured Dst for every hour over 25 months in three continuous time frames between 2001 (high solar activity), 2005 (low solar activity), and 2012 (rising solar activity) are shown. The Anemomilos operational algorithm was developed for a specific customer use related to thermospheric mass density forecasting. It is an operational space weather technology breakthrough using solar disk observables to predict geomagnetically effective Dst up to several days at 1 h time granularity. Real‐time forecasts are presented at http://sol.spacenvironment.net/~sam_ops/index.html?

Space Weather↗

USGS2020

Comparison of underwater video with electrofishing and dive‐counts for stream fish abundance estimation

Advances in video technology enable new strategies for stream fish research. We compared juvenile (age‐0) and adult (age 1+) Brook Trout Salvelinus fontinalis abundance estimates from underwater video with backpack electrofishing and dive‐count methods across a series of stream pools in Shenandoah National Park, Virginia ( n = 41). Video methods estimated greater mean abundance of adult trout than 1‐pass electrofishing but were not different than 3‐pass electrofishing or dive‐count methods in this regard. In contrast, videos underestimated abundance of juvenile trout, and we suggest this is because predator avoidance‐behaviors by juvenile trout limit their use of microhabitat locations visible to cameras. Integrated abundance estimates from 2 cameras increased correspondence to comparison methods relative to single cameras, demonstrating the importance of an expanded field of view for video sampling in streams. Geomorphic features helped explain method‐wise differences: more adult trout were estimated with video than 3‐pass electrofishing as riffle crest depth and boulder composition increased, indicating habitat associations with trout escapement from electrofishing. Our results demonstrated that video techniques can provide a robust alternative or supplement to traditional methods for estimating adult trout abundance in stream pools.

Virgiinia↗

USGS2026

Network-wide assessment of soil water content calibration and sensitivity to biomass proxies using cosmic-ray neutron sensing in the Roaring Fork Basin, Colorado

Soil water content (SWC) is a key state variable of the climate system but is often uncertain in water balance monitoring, especially in alpine environments. SWC measurements can be challenging in alpine environments due to the topography and rocky soils. In 2022, the US Geological Survey's Next Generation Water Observing System Program began research to evaluate water balance monitoring technologies, including cosmic-ray neutron sensors (CRNS). This work evaluated the uncertainty resulting from network-wide calibration of CRNS for SWC monitoring in an alpine watershed and investigated the stability of the calibration parameters across space and time, focusing on potential influence of biomass dynamics. Fifteen stations with moderated and unmoderated (bare) CRNS were deployed and made operational within the Roaring Fork Basin in west-central Colorado. The root mean squared error of the network-wide calibration using the moderated CRNS was 0.042 or 0.047 cm 3 cm −3 , depending on the calibration equation used. Relative SWC dynamics from CRNS were correlated with the in situ probes with a correlation coefficient of 0.91 or 0.87 (depending on calibration equation). We did not find significant relationships between the calibration parameters and stationary site-specific variables. However, the calibration parameters derived from in situ probe SWC dynamics varied over time and were correlated with biomass proxies of cumulative growing degree-day, cumulative growing season index, and bare neutron counts. Future use of the CRNS network can leverage the reliable relative SWC data from network-wide calibration for watershed modeling and continue to research sensitivity of bare neutron measurements to biomass dynamics.

Colorado↗

USGS2026

Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering

A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.

Wind Energy↗

USGS2013

Hysteresis in suspended sediment to turbidity relations due to changing particle size distributions

Turbidity (T) is the most ubiquitous of surrogate technologies used to estimate suspended-sediment concentration (SSC). The effects of sediment size on turbidity are well documented; however, effects from changes in particle size distributions (PSD) are rarely evaluated. Hysteresis in relations of SSC-to-turbidity (SSC~T) for single stormflow events was observed and quantified for a data set of 195 concurrent measurements of SSC, turbidity, discharge, velocity, and volumetric PSD collected during five stormflows in 2009–2010 on Yellow River at Gees Mill Road in metropolitan Atlanta, Georgia. Regressions of SSC-normalized turbidity (T/SSC) on concurrently measured PSD percentiles show an inverse, exponential influence of particle size on turbidity that is not constant across the size range of the PSD. The majority of the influence of PSD on T/SSC is from particles of fine-silt and smaller sizes (finer than 16 microns). This study shows that small changes in the often assumed stability of the PSD are significant to SSC~T relations. Changes of only 5 microns in the fine silt and smaller size fractions of suspended sediment PSD can produce hysteresis in the SSC~T rating that can increase error and produce bias. Observed SSC~T hysteresis may be an indicator of changes in sediment properties during stormflows and of potential changes in sediment sources. Trends in the PSD time series indicate that sediment transport is capacity-limited for sand-sized sediment in the channel and supply-limited for fine silt and smaller sediment from the hillslope.

Georgia↗

USGS2020

Using ultrasonic acoustics to detect cryptic flying squirrels: Effects of season and habitat suitability

New technologies allow for more efficient and effective monitoring of rare or elusive species. However, standardizing protocol to ensure high detection rates is important prior to widespread use of a new technique. The use of ultrasonic acoustic detectors to survey for flying squirrels ( Glaucomys spp.) is a novel method that is more efficient than traditional methods. However, certain methodologies for this technique still need to be refined. During 2015, we conducted a seasonal and habitat quality study on the endangered Carolina northern flying squirrel ( G. sabrinus coloratus ) in western North Carolina, USA. Our seasonal study examined differences in probability of detection (POD) and latency to detection (LTD) at 30 high-quality sites across 10 survey nights in spring, summer, and autumn. The habitat quality study focused on POD and LTD among 15 sites with varying habitat quality (5 High, 5 Medium, 5 Low) across 20 survey nights. We found POD similar between seasons, with POD 15–20% greater during spring. The LTD was comparable among seasons. We found that POD and LTD varied at sites with different habitat quality. The POD was similar between High and Medium sites (0.26 ± 0.04 SE and 0.29 ± 0.05, respectively), but greater than Low sites (0.02 ± 0.02). The LTD was not different among sites with differing habitat quality, although LTD at High sites was 2.7 and 4.5 times lower than Medium and Low sites, respectively. Trill calls, the most distinctive species-specific call type produced by species of flying squirrels, was recorded at greater rates in spring versus other times of the year. Our results indicate flying squirrels can be surveyed during any season, although habitat quality needs to be considered when determining survey length. For Carolina northern flying squirrel, the optimal time to perform acoustic surveys is during the spring season for 6–10 survey nights at sites with high or medium habitat quality.

North Carolina↗

USGS2021

Enumerating white-tailed deer using unmanned aerial vehicles

The white‐tailed deer ( Odocoileus virginianus ) is an ecologically important species in forests of North America. Effective management of forests requires accurate, precise estimates of deer population abundance to plan and justify management actions. Spotlight surveys in combination with distance sampling are a common method of estimating deer population abundance; however, spotlight surveys are known to have serious drawbacks such as high costs and sampling biases. Therefore, we tested the effectiveness of enumerating deer from unmanned aerial vehicle (UAV) flights, conducted 1 and 6 March 2018, to develop population and density estimates in 2 United States National Parks: Harpers Ferry National Historic Park (HAFE) and Monocacy National Battlefield (MONO). Concurrent spotlight surveys at MONO enabled us to compare estimates obtained by the 2 methods. Deer density estimates by 4 observers of UAV‐obtained thermal imagery from HAFE were 94.5 ± 3.9 deer/km 2 . Concurrent UAV and spotlight surveys at MONO found 19.7 ± 0.5 deer/km 2 and 6.4 ± 4.9 deer/km 2 , respectively; suggesting that spotlight surveys may significantly underestimate deer densities. Despite the logistical challenges to UAV operation, our findings demonstrate that UAVs will become an invaluable tool for wildlife management as technology improves. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Maryland, West Virginia↗

USGS2022

Optimizing surveys of fall-staging geese using aerial imagery and automated counting

Ocular aerial surveys allow efficient coverage of large areas and can be used to monitor abundance and distribution of wild populations. However, uncertainty around resulting population estimates can be large due to difficulty in visually identifying and counting animals from aircraft, as well as logistical challenges in estimating detection probabilities. Photographic aerial surveys can mitigate these challenges and can allow flight at higher altitudes to minimize disturbance of birds and improve safety for surveyors. We evaluated a photographic aerial survey that incorporated a systematic sampling design with automated photo capture and processing for fall-staging geese at Izembek Lagoon, Alaska, in 2017–2019. Ocular aerial surveys have been completed at Izembek Lagoon for >40 years. For the new photo survey, we used a commercial system to automatically trigger cameras at preset points. We then applied a machine-learning algorithm trained to automatically identify and count geese in our photos, manually corrected those counts, and quantified the algorithm's accuracy. We translated corrected counts into density and extrapolated mean density across the entire lagoon to estimate total population size for Pacific brant ( Branta bernicla ) and cackling geese ( B. hutchinsii ). The automated algorithm undercounted geese, but successfully identified the small subset of photos containing geese. Manual correction was therefore needed only for photos automatically identified as containing geese, allowing substantial reduction of workload. Manually-corrected, photo-based estimates of Pacific brant and cackling goose population sizes were larger and more precise than ocular estimates in all 3 years. To reduce costs with little penalty for variance around population estimates, the photographic survey design could be optimized by reducing the number of transects to ~67% of the current number while still manually correcting all photos in which the automated algorithm detected geese. Further years of both ocular and photo surveys would be needed to calibrate the photo estimates against the >40-year timeseries of the ocular survey, after which the photo series could successfully guide management of Pacific brant. As technologies continue to advance, we expect photographic surveys with automated counting to be easily implemented and advantageous to many monitoring programs.

Alaska↗

USGS2025

Development and evaluation of the remote passive integrated transponder tag reader for customizable monitoring of wildlife

Increasing the quantity and quality of mark-reencounter data can be important when individual identification data are needed to address research or management questions. Physical recapture methods tend to be labor-intensive and therefore expensive, while remote detection methods are not easily applied to all taxa or are proprietary and thus difficult to customize. However, partnerships between wildlife scientists and engineers have the potential to provide innovative solutions that improve data collection while reducing costs. We describe a collaborative effort to improve the collection of mark-reencounter data on an invasive reptile, the brown treesnake ( Boiga irregularis ). In laboratory trials conducted on Guåhan (CHamoru; Guam in English) in 2021, we assessed the feasibility of detecting snakes fitted with passive integrated transponder (PIT) tags using customized remote PIT-tag readers (RePTaR) paired with baited snake traps. We evaluated differences in scanning success as a function of snake traits, location of PIT tags within snakes, and the distance of the PIT tag from the reader. We successfully scanned all individuals, on average 529 times but ranging from 3 to 6,436 times, during 12-hour trials using a designed customizable RePTaR unit. Snake characteristics and marking location explained little of the variability in scanning success, with distance from the reader as the best-supported covariate. By building cross-disciplinary partnerships, we can develop customizable technological solutions and provide additional tools with which to address challenges in wildlife research and management.

Guam↗

USGS2026

Regional conservation planning tool: A spreadsheet model to support spatial prioritization and resource allocation decisions

Prioritization is a central component of natural resource management because conservation needs routinely exceed available resources. Waterfowl and wetland conservation programs in North America are at the forefront of landscape-scale prioritization and transboundary management decisions due to the migratory nature of ducks, geese, and swans. The growing availability of geographic information systems (GIS) and geospatial technologies has accelerated the development of multi-objective landscape prioritization models, including applications of structured decision making and multi-criteria decision analysis to spatial planning for waterfowl and wetlands at the continental scale. However, regional managers and conservationists could benefit from flexibility in downscaling continental tools, selecting objectives, and assigning weights for rapid production of spatial prioritization models at smaller spatial scales without extensive computer coding or GIS analysis. We developed a spatial value model that prioritizes landscapes at sub-continental scales (e.g., states and provinces, bird conservation regions, etc.) and provides flexibility for users to select waterfowl conservation objectives of interest and weights. Our model can be used for direct downscaling of an existing continental geospatial model or further customized with region-specific geospatial data. We illustrate how regional prioritization can vary with the spatial scale selected by the user. The spatial value modeling framework and the downscaling tool presented here could increase the use of multi-criteria decision analysis and linear value modeling in spatial landscape prioritization, while also providing flexibility for selecting scales, objectives, and weights. Our spreadsheet tool was developed specifically for use by regional biologists, conservationists, and managers and does not require knowledge of GIS software (although results can be exported from the spreadsheet for spatial analysis using GIS). Together, the model outputs and the accompanying spreadsheet tool provide a bridge between continental waterfowl conservation and regional implementation, enabling rapid, stakeholder-driven, value-explicit prioritization.

Wildlife Society Bulletin↗

USGS2017

Variable terrestrial GPS telemetry detection rates: Addressing the probability of successful acquisitions

Studies using global positioning system (GPS) telemetry rarely result in 100% fix success rates (FSR), which may bias datasets because data loss is systematic rather than a random process. Previous spatially explicit models developed to correct for sampling bias have been limited to small study areas, a small range of data loss, or were study-area specific. We modeled environmental effects on FSR from desert to alpine biomes, investigated the full range of potential data loss (0–100% FSR), and evaluated whether animal body position can contribute to lower FSR because of changes in antenna orientation based on GPS detection rates for 4 focal species: cougars ( Puma concolor ), desert bighorn sheep ( Ovis canadensis nelsoni ), Rocky Mountain elk ( Cervus elaphus nelsoni ), and mule deer ( Odocoileus hemionus ). Terrain exposure and height of over story vegetation were the most influential factors affecting FSR. Model evaluation showed a strong correlation (0.88) between observed and predicted FSR and no significant differences between predicted and observed FSRs using 2 independent validation datasets. We found that cougars and canyon-dwelling bighorn sheep may select for environmental features that influence their detectability by GPS technology, mule deer may select against these features, and elk appear to be nonselective. We observed temporal patterns in missed fixes only for cougars. We provide a model for cougars, predicting fix success by time of day that is likely due to circadian changes in collar orientation and selection of daybed sites. We also provide a model predicting the probability of GPS fix acquisitions given environmental conditions, which had a strong relationship ( r 2 = 0.82) with deployed collar FSRs across species.

Wildlife Society Bulletin↗

USGS1998

Mass collecting and the diet breadth model: A Great Basin example

The energetic return rates of many small animal and plant resources are often density dependent. When these resources are collected in mass, change in abundance can dramatically affect diet rank, and challenges the assumption that return rates are generally correlated with body size. When mass collecting is employed, as a result of either natural events (e.g. windrows) or technological developments (e.g. nets), population density may largely determine the overall return rate for a resource. Since a single food or resource type can be many prey types, an increase in the abundance of a food resource can change its diet rank. We examined this relationship at Lakeside Cave in northwestern Utah, and discovered that when the abundance of grasshoppers is high, and mass collecting is productive, the hunting of bighorn sheep and other large animal resources may have been abandoned, contradicting commonly held assumptions about prey size. In archaeological situations it may be necessary to determine what foraging technique was used before assuming that the presence of small animals and fish in the diet is a result of reduced foraging efficiency.

Journal of Archaeological Science↗

USGS1993

Harvesting and replenishment policies for renewable natural resources

The current paper links the optimal intertemporal use of renewable natural resources to the harvesting activities of various economic agents. Previous contributions cite market forces as a causative factor inducing the extirpation of renewable natural resources. The analysis given here discusses investment in the stock of renewable resources and cites important examples of this activity. By introducing joint harvesting and replenishment strategies into a model of renewable resource use, the analysis adds descriptive reality and relevance to positive and normative discussions of renewable natural resource use. A high price for the yield or a high discount rate tend to diminish the size of the optimum stationary stock of the resource with a non-replenishment harvesting strategy. Optimal non-replenishment harvesting strategies for renewable natural resources will exhaustion or extirpation of the resource if the price of the yield or the discount rate are sufficiently large. However, the availability of a replenishment technology and the use of replenishment activities tends to buffer the resource against exhaustion or extirpation.

Journal of Environmental Management↗

USGS2020

The transformative impact of genomics on sage-grouse conservation and management

For over two decades, genetic studies have been used to assist in the conservation and management of both Greater Sage-grouse ( Centrocercus urophasianus ) and Gunnison Sage-grouse ( C. minimus ), addressing a wide variety of topics including taxonomy, parentage, population connectivity, and demography. The field of conservation genetics has been transformed by dramatic improvements in sequencing technology, facilitating genomic studies in many wildlife species. The quality and amount of data generated by genomic methods vastly exceed that of traditional genetic studies, allowing for increased precision in estimating genetic parameters of interest. Perhaps more importantly, genomic methods can provide insight into non-neutral evolution such as adaptive divergence. Here we recount the shift from genetic to genomic methods using two wildlife species of substantial conservation interest, focusing on the improved capabilities and advantages of genomic methods. For instance, reassessment of divergence in sage-grouse using genomic methods confirmed strong differentiation between the two species and revealed that a small population in the state of Washington was more genetically distinct than previously recognized. Further, new genomic resources and approaches have been used to identify a family of genes linked to local dietary adaptation suggesting that sage-grouse may possess digestive and metabolic adaptations that mitigate the effects of consuming plant secondary metabolites like those found in sagebrush. Genetic variation among populations in these gene regions is thought to be involved with local dietary adaptations, and therefore maintaining the tie between sage-grouse and the chemistry of local sagebrush may be an important management consideration. We posit that the integration of newly developed genomic resources combined with the vast wealth of ecological and behavioral data for sage-grouse has the potential to shed light on mechanistic relationships that ultimately are vital to the conservation and management of these species.

Book chapter↗

USGS2012

Volcanoes: observations and impact

Volcanoes are critical geologic hazards that challenge our ability to make long-term forecasts of their eruptive behaviors. They also have direct and indirect impacts on human lives and society. As is the case with many geologic phenomena, the time scales over which volcanoes evolve greatly exceed that of a human lifetime. On the other hand, the time scale over which a volcano can move from inactivity to eruption can be rather short: months, weeks, days, and even hours. Thus, scientific study and monitoring of volcanoes is essential to mitigate risk. There are thousands of volcanoes on Earth, and it is impractical to study and implement ground-based monitoring at them all. Fortunately, there are other effective means for volcano monitoring , including increasing capabilities for satellite-based technologies.

Book chapter↗