Subsidence after a subduction zone earthquake can cause major changes in estuarine bathymetry. Here, we quantify the impacts of earthquake-induced subsidence on hydrodynamics and habitat distributions in a major system, the lower Columbia River Estuary, using a hydrodynamic and habitat model. Model results indicate that coseismic subsidence increases tidal range, with the smallest changes at the coast and a maximum increase of ∼10% in a region of topographic convergence. All modeled scenarios reduce intertidal habitat by 24%–25% and shifts ∼93% of estuarine wetlands to lower-elevation habitat bands. Incorporating dynamic effects of tidal change from subsidence yields higher estimates of remaining habitat by multiples of 0–3.7, dependent on the habitat type. The persistent tidal change and chronic habitat disturbance after an earthquake poses strong challenges for estuarine management and wetland restoration planning, particularly when coupled with future sea-level rise effects.
Shifts in the frequency and intensity of high discharge events due to climate change may have important consequences for the hydrology and biogeochemistry of rivers. However, our understanding of event-scale biogeochemical dynamics in large rivers lags that of small streams. To fill this gap, we used high-frequency sensor data collected during four consecutive summers from a main channel and backwater site of the Upper Mississippi River. We identified high discharge events and calculated event concentration-discharge responses for both physical-chemical (nitrate, turbidity, and fluorescent dissolved organic matter) and biological (chlorophyll-a and cyanobacteria) constituents using metrics of hysteresis and slope. We found a range of responses across events, particularly for nitrate. Although fluorescent dissolved organic matter (FDOM) and turbidity exhibited more consistent responses across events, contrasting hysteresis metrics indicated that FDOM was flushed to the river from more distant sources than turbidity. Biological responses (chlorophyll a and cyanobacteria) differed more between sites than physical and chemical constituents. Lastly, we found that the event characteristics best explaining concentration responses differed between sites, with event magnitude more frequently related to responses in the main channel, and antecedent wetness conditions associated with response variation in the backwater. Our results indicate that event responses in large rivers are distinct across the diverse habitats and biogeochemical components of a large floodplain river, which has implications for local and downstream ecosystems as the climate shifts.
As larger tracts of land experience degradation, seed-based restoration (SBR) will be a primary tool to reestablish vegetation and ecosystem function. SBR has advanced in terms of technical and technological approaches, yet plant recruitment remains a major barrier in some systems, notably drylands. There is an unmet opportunity to test science-based approaches to seed mix design and application, based not only on diversity or local provenance, but on the unique recruitment strategies of species. We lay out a framework that uses a quantitative representation of species' recruitment niches to match them to targeted goals (e.g. drought or invasion resistance) and methods (e.g. precision tools and technologies) in SBR. We first describe how to quantify the recruitment niche with seed and seedling traits tied to observed recruitment responses to environmental factors. We then show how a quantified recruitment niche framework can serve as the foundation to address three major restoration challenges: (1) designing forward-looking seed mixes that increase resilience to future climate and disturbance, (2) accounting for natural recovery in SBR planning, and (3) applying precision seeding practices to maximize restoration success. Finally, we demonstrate these ideas with existing data and discuss key challenges to adoption in SBR practice. While the ideas in this framework are based in ecological theory, they will require substantial testing and refinement by scientists engaged in SBR efforts. If this framework is integrated into research agendas, we believe it has the potential to unify and advance diverse elements of seed-based restoration ecology and improve restoration outcomes.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13959","usgsCitation":"Larson, J.E., Agneray, A.C., Boyd, C.S., Bradford, J., Kildisheva, O.A., Suding, K.N., and Copeland, S., 2023, A recruitment niche framework for improving seed-based restoration: Restoration Ecology, v. 31, no. 7, e13959, 15 p., https://doi.org/10.1111/rec.13959.","productDescription":"e13959, 15 p.","ipdsId":"IP-150987","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442774,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13959","text":"Publisher Index Page"},{"id":419229,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Julie E.","contributorId":261604,"corporation":false,"usgs":false,"family":"Larson","given":"Julie","email":"","middleInitial":"E.","affiliations":[{"id":52914,"text":"Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA","active":true,"usgs":false}],"preferred":false,"id":878516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agneray, A. C.","contributorId":316842,"corporation":false,"usgs":false,"family":"Agneray","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":68710,"text":"Bureau of Land Management, Nevada State Office, 1340 Financial Blvd, Reno, NV, US 89502","active":true,"usgs":false}],"preferred":false,"id":878517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Chad S.","contributorId":255106,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","email":"","middleInitial":"S.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":878518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":878519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kildisheva, O. A.","contributorId":316844,"corporation":false,"usgs":false,"family":"Kildisheva","given":"O.","email":"","middleInitial":"A.","affiliations":[{"id":68711,"text":"The Nature Conservancy, 999 Disk Drive, Suite 104, Bend, OR, US 97702","active":true,"usgs":false}],"preferred":false,"id":878520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suding, Katharine N. 0000-0002-5357-0176","orcid":"https://orcid.org/0000-0002-5357-0176","contributorId":168385,"corporation":false,"usgs":false,"family":"Suding","given":"Katharine","email":"","middleInitial":"N.","affiliations":[{"id":6709,"text":"University of Colorado, Denver","active":true,"usgs":false}],"preferred":false,"id":878521,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":878522,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246656,"text":"sir20235070 - 2023 - Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016","interactions":[],"lastModifiedDate":"2026-03-09T17:10:18.876972","indexId":"sir20235070","displayToPublicDate":"2023-07-12T15:04:42","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5070","displayTitle":"Spatiotemporal Variations in Copper, Arsenic, Cadmium, and Zinc Concentrations in Surface Water, Fine-Grained Bed Sediment, and Aquatic Macroinvertebrates in the Upper Clark Fork Basin, Western Montana—A 20-Year Synthesis, 1996–2016","title":"Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016","docAbstract":"The legacy of mining-related contamination in the upper Clark Fork Basin created an extensive longitudinal gradient in metal concentrations, extending from Silver Bow Creek to Lake Pend Oreille, Idaho. Downstream metal concentrations continue to decline, but, despite such improvements, the ecological health of much of the river remains uncertain. Understanding the long-term consequences of the Clark Fork River mining legacy may be supported by environmental monitoring techniques that include a holistic assessment of biological health or response to define organism exposure to complex contaminant mixtures and the consequences of such exposures. This report presents the spatiotemporal patterns of mining-related contaminants, copper, arsenic, cadmium, and zinc, in surface water, fine-grained bed sediment, and macroinvertebrate (aquatic insect) tissue in the upper Clark Fork from near Butte to Missoula, Montana. Overall, the patterns in water column sample concentrations observed in this study were consistent with previously observed trends, but bed sediment concentrations and concentrations of copper and arsenic varied more in tissue samples among sites. Trace element concentrations, especially copper, often exceeded the chronic aquatic life criteria and consistently exceeded the sediment probable effects level PEL for copper, particularly in the upper and middle river segments. The 20 years considered here were the wettest period since remediation started, and this increase in precipitation may have affected patterns in contaminant concentrations.
Results of this study demonstrated the utility of a continued, comprehensive biomonitoring program to help guide and evaluate future environmental cleanup activities in the Clark Fork. Despite variation in defining complete restoration in these watersheds, using multiple lines of evidence in this study provided quantifiable measures of the timing and completeness of recovery relative to reference conditions. Successful recovery in the Clark Fork may benefit from an adaptive management strategy to continue collecting a comprehensive, multivariate dataset to evaluate whether established goals are being met and for subsequent adjustments and management, as needed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235070","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Caldwell Eldridge, S.L., and Hornberger, M.I., 2023, Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016: U.S. Geological Survey Scientific Investigations Report 2023–5070, 55 p., https://doi.org/10.3133/sir20235070.","productDescription":"Report: viii, 55 p.; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-124462","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":500950,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114966.htm","linkFileType":{"id":5,"text":"html"}},{"id":418908,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235070/full"},{"id":418905,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":418904,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5070/images/"},{"id":418903,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5070/sir20235070.XML"},{"id":418902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5070/sir20235070.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5070"},{"id":418901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5070/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.19960466889883,\n 47.19600162794333\n ],\n [\n -114.19960466889883,\n 45.651910037647326\n ],\n [\n -110.76235872576048,\n 45.651910037647326\n ],\n [\n -110.76235872576048,\n 47.19600162794333\n ],\n [\n -114.19960466889883,\n 47.19600162794333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Differential Optical Absorption Spectroscopy (DOAS) is commonly used to measure gas emissions from volcanoes. DOAS instruments measure the absorption of solar ultraviolet (UV) radiation scattered in the atmosphere by sulfur dioxide (SO2) and other trace gases contained in volcanic plumes. The standard spectral retrieval methods assume that all measured light comes from behind the plume and has passed through the plume along a straight line. However, a fraction of the light that reaches the instrument may have been scattered beneath the plume and thus has passed around it. Since this component does not contain the absorption signatures of gases in the plume, it effectively “dilutes” the measurements and causes underestimation of the gas abundance in the plume. This dilution effect is small for clean-air conditions and short distances between instrument and plume. However, plume measurements made at long distance and/or in conditions with significant atmospheric aerosol, haze, or clouds may be severely affected. Thus, light dilution is regarded as a major error source in DOAS measurements of volcanic degassing. Several attempts have been made to model the phenomena and the physical mechanisms are today relatively well understood. However, these models require knowledge of the local atmospheric aerosol composition and distribution, parameters that are almost always unknown. Thus, a practical algorithm to quantitatively correct for the dilution effect is still lacking. Here, we propose such an algorithm focused specifically on SO2 measurements. The method relies on the fact that light absorption becomes non-linear for high SO2 loads, and that strong and weak SO2 absorption bands are unequally affected by the diluting signal. These differences can be used to identify when dilution is occurring. Moreover, if we assume that the spectral radiance of the diluting light is identical to the spectrum of light measured away from the plume, a measured clean air spectrum can be used to represent the dilution component. A correction can then be implemented by iteratively subtracting fractions of this clean air spectrum from the measured spectrum until the respective absorption signals on strong and weak SO2 absorption bands are consistent with a single overhead SO2 abundance. In this manner, we can quantify the magnitude of light dilution in each individual measurement spectrum as well as obtaining a dilution-corrected value for the SO2 column density along the line of sight of the instrument. This paper first presents the theory behind the method, then discusses validation experiments using a radiative transfer model, as well as applications to field data obtained under different measurement conditions at three different locations; Fagradalsfjall located on the Reykjanaes peninsula in south Island, Manam located off the northeast coast of mainland Papua New Guinea and Holuhraun located in the inland of north east Island.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2023.1088768","usgsCitation":"Galle, B., Arellano, S., Johansson, M., Kern, C., and Pfeffer, M., 2023, An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy: Frontiers in Earth Science, v. 11, 1088768, 14 p., https://doi.org/10.3389/feart.2023.1088768.","productDescription":"1088768, 14 p.","ipdsId":"IP-151840","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1088768","text":"Publisher Index Page"},{"id":419499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Galle, Bo","contributorId":255645,"corporation":false,"usgs":false,"family":"Galle","given":"Bo","email":"","affiliations":[{"id":51629,"text":"Chalmers University, Sweden","active":true,"usgs":false}],"preferred":false,"id":879452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":879453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johansson, Mattias","contributorId":255657,"corporation":false,"usgs":false,"family":"Johansson","given":"Mattias","email":"","affiliations":[{"id":51629,"text":"Chalmers University, Sweden","active":true,"usgs":false}],"preferred":false,"id":879454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":879455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pfeffer, Melissa","contributorId":199349,"corporation":false,"usgs":false,"family":"Pfeffer","given":"Melissa","affiliations":[],"preferred":false,"id":879456,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247285,"text":"70247285 - 2023 - Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation","interactions":[],"lastModifiedDate":"2023-12-04T17:00:29.407097","indexId":"70247285","displayToPublicDate":"2023-07-12T08:49:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation","docAbstract":"The fore‐arc of the southern Cascadia subduction zone (CSZ), north of the Mendocino triple junction (MTJ), is home to a network of Quaternary‐active crustal faults that accumulate strain due to the interaction of the North American, Juan de Fuca (Gorda), and Pacific plates. These faults, including the Little Salmon and Mad River fault (LSF and MRF) zones, are located near the most populated parts of California’s north coast and show paleoseismic evidence for three slip events of several‐meter scale in the past 1700 yr. However, the geodetic slip rates of these faults are poorly constrained. In this work, we analyze a new compilation of interseismic geodetic velocities from Global Navigation Satellite Systems, leveling, and tide gauge data near the MTJ to constrain present‐day slip deficit rates on upper‐plate faults and coupling on the megathrust. We construct Green’s functions for interseismic slip deficit for discrete faults embedded in an elastic plate overlying a viscoelastic mantle. We then use a constrained least‐squares inversion to determine best‐fitting slip rates on the major faults and investigate slip rate trade‐offs between faults. Results indicate that the LSF and MRF systems together accumulate 4–5 mm/yr of reverse‐slip deficit, although their separate slip rates cannot be determined independently. Modeling of the horizontal and vertical velocities suggests that the southernmost CSZ is coupled interseismically to deeper than 25 km depth. We also find that 6–17 mm/yr of right‐lateral slip deficit extends north of the MTJ and into the southern Cascadia fore‐arc. These results reinforce the notion that both the southernmost Cascadia megathrust and the smaller fore‐arc faults above it contribute to regional seismic hazard.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230007","usgsCitation":"Materna, K.Z., Murray, J.R., Pollitz, F., and Patton, J.R., 2023, Slip deficit rates on southern Cascadia faults resolved with viscoelastic earthquake cycle modeling of geodetic deformation: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2505-2518, https://doi.org/10.1785/0120230007.","productDescription":"14 p.","startPage":"2505","endPage":"2518","ipdsId":"IP-145972","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia fault zone, Mendocino triple junction","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.02213582197189,\n 46.78612877852626\n ],\n [\n -126.15645523900434,\n 46.78612877852626\n ],\n [\n -126.15645523900434,\n 36.43464818238357\n ],\n [\n -120.02213582197189,\n 36.43464818238357\n ],\n [\n -120.02213582197189,\n 46.78612877852626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Materna, Kathryn Zerbe 0000-0002-6687-980X","orcid":"https://orcid.org/0000-0002-6687-980X","contributorId":261337,"corporation":false,"usgs":true,"family":"Materna","given":"Kathryn","email":"","middleInitial":"Zerbe","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patton, Jason R.","contributorId":317714,"corporation":false,"usgs":false,"family":"Patton","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":879119,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255972,"text":"70255972 - 2023 - Widespread regeneration failure in ponderosa pine forests of the southwestern United States","interactions":[],"lastModifiedDate":"2024-07-11T13:35:51.985737","indexId":"70255972","displayToPublicDate":"2023-07-12T08:28:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Widespread regeneration failure in ponderosa pine forests of the southwestern United States","docAbstract":"As climate changes in coming decades, ponderosa pine forest persistence may be increasingly dictated by their regeneration. Sustained regeneration failure has been predicted for forests of the southwestern US (SWUS) even in absence of stand-replacing wildfire, but regeneration in undisturbed and lightly disturbed forests has been studied infrequently and at a limited number of locations. We characterized 77 ponderosa pine sites in 7 SWUS locations, documented regeneration occurring over the past
Climate change may induce mismatches between wildlife reproductive phenology and temporal occurrence of resources necessary for reproductive success. Verifying and elucidating the causal mechanisms behind potential mismatches requires large-scale, longer-duration data. We used eastern wild turkey (Meleagris gallopavo silvestris) nesting data collected across the southeastern U.S. over eight years to investigate potential climatic drivers of variation in nest initiation dates. We investigated climactic relationships with two datasets, one inclusive of successful and unsuccessful nests (full dataset) and another of just successful nests (successfully hatched dataset), to determine whether successfully hatched nests responded differently to weather changes than all nests did. In the full dataset, each 10 cm increase in January precipitation was associated with nesting occurring 0.46-0.66 days earlier, and each 10 cm increase in precipitation during the 30 days preceding nesting was associated with nesting occurring 0.17-0.21 days later. In the successfully hatched dataset, a 10 cm increase in March precipitation was associated with nesting occurring 0.67-0.74 days earlier, and an increase of one unit of variation in February maximum temperature was associated with nesting occurring 0.02 days later. We combined the results of these modeled relationships with multiple climate scenarios to understand potential implications of future climate change on wild turkey nesting phenology; results indicated that mean nest initiation date is projected to change by <0.1 day by 2040-2060. Wild turkey nesting phenology did not track changes in spring green-up timing, which could result in phenological mismatch between the timing of nesting and the availability of resources critical for successful reproduction.
To evaluate the vulnerability of Bull Trout Salvelinus confluentus to potential climate changes across its range in Oregon, we compiled disparate expert knowledge of the distribution of spawning and rearing and combined these probabilistic statements as data along with documented records of breeding and rearing in a joint occupancy model.
The joint expert knowledge–occupancy model, which was based on discrete patches of cold water (≤13°C) suitable for spawning and rearing, permitted the association of true occupancy with climate and other explanatory variables while accounting for variation in detection probability. We then applied estimated relationships of patch occupancy with explanatory variables to projected coldwater patch configurations in the years 2040 and 2080.
Projections of the kilometers of occupied coldwater patch in future decades suggest precipitous declines if current relationships of occupancy with environmental variables are maintained. Impacts of climate changes in future decades manifest directly through the outright loss of coldwater patches and increases in winter high flows but also indirectly by increased isolation.
Combining probabilistic statements of species distributions from knowledgeable experts with sparse occupancy data may be a robust and timely alternative when large numbers of repeated occupancy surveys are infeasible.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10905","usgsCitation":"Chelgren, N., Dunham, J., Gunckel, S.L., Hockman-Wert, D.P., and Allen, C.S., 2023, Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection: North American Journal of Fisheries Management, v. 43, no. 3, p. 839-858, https://doi.org/10.1002/nafm.10905.","productDescription":"20 p.","startPage":"839","endPage":"858","ipdsId":"IP-139349","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":498031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10905","text":"Publisher Index Page"},{"id":418940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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resources for Native Hawaiians. Currently, Hawaiian coastal wetlands are degraded by development, sedimentation, and invasive species and, thus, require restoration. Little is known about their original structure and function due to the large-scale alteration of the lowland landscape since European contact. Here, we used 1) rapid field assessments of hydrology, vegetation, soils, and birds, 2) a comprehensive analysis of endangered bird habitat value, 3) site spatial characteristics, 4) sea-level rise projections for 2050 and 2100 and wetland migration potential, and 5) preferences of the Native Hawaiian community in a GIS site suitability analysis to prioritize restoration of coastal wetlands on the island of Molokaʻi. The site suitability analysis is the first, to our knowledge, to incorporate community preferences, habitat criteria for endangered waterbirds, and sea-level rise into prioritizing wetland sites for restoration. The rapid assessments showed that groundwater is a ubiquitous water source for coastal wetlands. A groundwater-fed, freshwater herbaceous peatland or “coastal fen” not previously described in Hawaiʻi was found adjacent to the coastline at a site being used to grow taro, a staple crop for Native Hawaiians. In traditional ecological knowledge, such a groundwater-fed, agro-ecological system is referred to as a loʻipūnāwai (spring pond). Overall, 39 plant species were found at the 12 sites; 26 of these were wetland species and 11 were native. Soil texture in the wetlands ranged from loamy sands to silt and silty clays and the mean % organic carbon content was 10.93% ± 12.24 (sd). In total, 79 federally endangered waterbirds, 13 Hawaiian coots (‘alae keʻokeʻo; Fulica alai) and 66 Hawaiian stilts (aeʻo; Himantopus mexicanus knudseni), were counted during the rapid field assessments. The site suitability analysis consistently ranked three sites the highest, Kaupapaloʻi o Kaʻamola, Kakahaiʻa National Wildlife Refuge, and ʻŌhiʻapilo Pond, under three different weighting approaches. Site prioritization represents both an actionable plan for coastal wetland restoration and an alternative protocol for restoration decision-making in places such as Hawaiʻi where no pristine “reference” sites exist for comparison.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1212206","usgsCitation":"Drexler, J.Z., Raine, H., Jacobi, J.D., House, S., Lima, P., Haase, W., Dibben-Young, A., and Wolfe, B.T., 2023, A prioritization protocol for coastal wetland restoration on Molokaʻi, Hawaiʻi: Frontiers in Environmental Science, v. 11, 1212206, 19 p., https://doi.org/10.3389/fenvs.2023.1212206.","productDescription":"1212206, 19 p.","ipdsId":"IP-151868","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":442791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1212206","text":"Publisher Index Page"},{"id":419231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Sates","state":"Hawaii","otherGeospatial":"Molokai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.32066368665434,\n 21.259659773693144\n ],\n [\n -157.31792520913558,\n 21.020418290169815\n ],\n [\n -156.7035934191068,\n 21.020418290169815\n ],\n [\n -156.7035934191068,\n 21.2622119405154\n ],\n [\n -157.32066368665434,\n 21.259659773693144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":878553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raine, Helen","contributorId":240849,"corporation":false,"usgs":false,"family":"Raine","given":"Helen","email":"","affiliations":[],"preferred":false,"id":878554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":878555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"House, Sally 0000-0002-3398-4742 shouse@usgs.gov","orcid":"https://orcid.org/0000-0002-3398-4742","contributorId":151032,"corporation":false,"usgs":true,"family":"House","given":"Sally","email":"shouse@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lima, Pulama","contributorId":316859,"corporation":false,"usgs":false,"family":"Lima","given":"Pulama","email":"","affiliations":[{"id":68716,"text":"Ka Ipu Makani, Kaunakakai, HI, USA","active":true,"usgs":false}],"preferred":false,"id":878557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haase, William","contributorId":316860,"corporation":false,"usgs":false,"family":"Haase","given":"William","email":"","affiliations":[{"id":68718,"text":"Moloka‘i Land Trust, PO Box 1884, Kaunakakai, HI, USA","active":true,"usgs":false}],"preferred":false,"id":878558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dibben-Young, Arleone","contributorId":316861,"corporation":false,"usgs":false,"family":"Dibben-Young","given":"Arleone","email":"","affiliations":[{"id":68719,"text":"Hawaiian Islands Conservation Collective, P.O. Box 1327, Kaunakakai, HI, USA","active":true,"usgs":false}],"preferred":false,"id":878559,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolfe, Brett T.","contributorId":266136,"corporation":false,"usgs":false,"family":"Wolfe","given":"Brett","email":"","middleInitial":"T.","affiliations":[{"id":54926,"text":"School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA","active":true,"usgs":false}],"preferred":false,"id":878561,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246579,"text":"sir20235081 - 2023 - User engagement to improve coastal data access and delivery","interactions":[],"lastModifiedDate":"2023-07-13T23:07:15.396628","indexId":"sir20235081","displayToPublicDate":"2023-07-11T12:25:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5081","displayTitle":"User Engagement to Improve Coastal Data Access and Delivery","title":"User engagement to improve coastal data access and delivery","docAbstract":"A priority of the U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program focus on coastal change hazards is to provide accessible and actionable science that meets user needs. To understand these needs, 10 virtual Coastal Data Delivery Listening Sessions were completed with 5 coastal data user types that coastal change hazards data are intended to serve: resource managers, consultants, local planners, State planners, and non-USGS researchers.
During these listening sessions, participants revealed challenges to coastal data use including being overwhelmed by too many webtools, having a lack of capacity to search for and understand new information, facing difficulties finding data, and not understanding how to apply data.
The specific coastal data and information needs described by participants are also detailed in the report and describe data gaps, a need for simpler tools, data needs that differ across spatial and temporal scales, and more outreach on coastal topics and climate change. Participants also suggested leveraging data across study sites and regions to help improve capacity issues and called for more communication and collaboration among and within Federal agencies.
The synthesized information from the Coastal Data Delivery Listening Sessions provided in this report can help the USGS and those working on coastal challenges better understand barriers to coastal information use and the exact data requirements of different coastal data users.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20235081","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"Stoltz, A.D., Cravens, A.E., Lentz, E., and Himmelstoss, E., 2023, User engagement to improve coastal data access and\ndelivery: U.S. Geological Survey Scientific Investigations Report 2023–5081, 29 p., https://doi.org/10.3133/sir20235081.","productDescription":"iv, 29 p.","onlineOnly":"Y","ipdsId":"IP-146290","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":418931,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235081/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5081"},{"id":418834,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5081/sir20235081.pdf","text":"Report","size":"1.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5081"},{"id":418833,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5081/coverthb.jpg"},{"id":418929,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5081/sir20235081.xml"},{"id":418928,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5081/images"}],"contact":"
Center Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Rd.
Woods Hole, MA 02543
When responding to a wildlife disease outbreak, managers depend on consistent and clear data to make decisions. However, diagnostic methods for detecting pathogens of wildlife often lack the level of procedural and interpretational standardization that occurs in the investigation of human and domestic animal diseases. This lack of standardization can hamper diagnostic reliability in two ways. First is the inappropriate application of tests to new species or in situations that are outside of the original (in other words, validated) purpose. Second is the use of laboratory-specific modifications or analytical parameters without thorough investigation of how those changes affect result comparisons across institutions or the ability to make broader conclusions about pathogen or disease.
White-nose syndrome (WNS) is a disease caused by the fungal pathogen Pseudogymnoascus destructans (Pd), which has spread rapidly and is causing population-level declines in some species of North American bats. During the last decade, quantitative polymerase chain reaction (qPCR) has become the most common method of testing for Pd because of qPCR’s speed, accuracy, and simplicity across a wide range of invasive and noninvasive sample types. Its widespread use by many State, Federal, Provincial, and academic institutions has inevitably led to variations in methodology and interpretation among laboratories. The progressive geographic spread of fungus and disease has also led to sampling contexts and strategies that differ from those for which the qPCR assay was originally developed and validated. These factors have resulted in inconsistencies among results tested in different laboratories and, subsequently, confusion for managers and decision makers.
To address these challenges, the WNS National Response Team Diagnostic Working Group launched a project congruent with increased calls for the harmonization of wildlife disease diagnostic results, and reporting standards across disparate methodologies and laboratories. Beginning in 2019, interlaboratory testing was done to better understand how variations to Pd qPCR methodology affect diagnostic consistency and to reassess the assay’s fit for purpose in new testing contexts. This information led to expanded conversations within the Diagnostic Working Group related to best practices in Pd qPCR diagnostic testing, the development of common interpretation language for classifying test results, and the incorporation of that language into an updated WNS case definition. This handbook is the resulting product and is intended to help further harmonize Pd qPCR diagnostic testing by establishing recommendations related to voluntary participation in a WNS Diagnostic Laboratory Network, documenting the currently (2022) practiced Pd qPCR methodologies, discussing general best practices for molecular diagnostics and laboratory networks, and elaborating on the epidemiologic and diagnostic basis of the agreed-upon classification language for Pd qPCR results. Through this voluntary, consensus-based approach to diagnostic harmonization, this work aims to improve the confidence of management agencies in reported Pd qPCR results and can serve as an example of national diagnostic coordination for other unregulated wildlife diseases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm15E1","usgsCitation":"Alger, K., and White Nose Syndrome National Response Team Diagnostic Working Group, 2023, White-Nose Syndrome Diagnostic Laboratory Network handbook: U.S. Geological Survey Techniques and Methods, book 15, chap. E1, 50 p., https://doi.org/10.3133/tm15E1.","productDescription":"Report: x, 50 p.; Data Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-137564","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":418802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/15/e01/coverthb.jpg"},{"id":418803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/15/e01/tm15e1.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 15–E1"},{"id":418805,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/15/e01/tm15e1.XML"},{"id":418806,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/15/e01/images/"},{"id":418808,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SXYL0","text":"USGS Data Release","linkHelpText":"Pd qPCR interlaboratory testing results"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) into the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. However, progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present a comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane Database (GriMeDB; https://doi.org/10.6073/pasta/f48cdb77282598052349e969920356ef, Stanley et al., 2023) includes 24 024 records of CH4 concentration and 8205 flux measurements from 5029 unique sites derived from publications, reports, data repositories, unpublished data sets, and other outlets that became available between 1973 and 2021. Flux observations are reported as diffusive, ebullitive, and total CH4 fluxes, and GriMeDB also includes 17 655 and 8409 concurrent measurements of concentrations and 4444 and 1521 fluxes for carbon dioxide (CO2) and nitrous oxide (N2O), respectively. Most observations are date-specific (i.e., not site averages), and many are supported by data for 1 or more of 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or the presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass the broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (arid regions, tropical regions, high-latitude and high-altitude systems). The global median CH4 concentration (0.20 µmol L−1) and diffusive flux (0.44 mmol m-2 d-1) in GRiMeDB are lower than estimates from prior site-averaged compilations, although ranges (0 to 456 µmol L−1 and −136 to 4057 mmol m-2 d-1) and standard deviations (10.69 and 86.4) are greater for this larger and more temporally resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Nonetheless, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and contextualizing site-based investigations.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-15-2879-2023","usgsCitation":"Stanley, E.H., Loken, L.C., Casson, N.J., Oliver, S.K., Sponseller, R.A., Wallin, M.B., Zhang, L., and Rocher-Ros, G., 2023, GRiMeDB: The Global River Database Methane Database of concentrations and fluxes: Earth System Science Data, v. 15, no. 7, p. 2879-2926, https://doi.org/10.5194/essd-15-2879-2023.","productDescription":"48 p.","startPage":"2879","endPage":"2926","ipdsId":"IP-146293","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-15-2879-2023","text":"Publisher Index Page"},{"id":420723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":882857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":882859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sponseller, Ryan A.","contributorId":329667,"corporation":false,"usgs":false,"family":"Sponseller","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":24847,"text":"Umea University","active":true,"usgs":false}],"preferred":false,"id":882861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallin, Marcus B.","contributorId":329668,"corporation":false,"usgs":false,"family":"Wallin","given":"Marcus","email":"","middleInitial":"B.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":882862,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhang, Liwei","contributorId":329669,"corporation":false,"usgs":false,"family":"Zhang","given":"Liwei","email":"","affiliations":[{"id":57409,"text":"Peking University","active":true,"usgs":false}],"preferred":false,"id":882863,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rocher-Ros, Gerard","contributorId":329670,"corporation":false,"usgs":false,"family":"Rocher-Ros","given":"Gerard","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":882864,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70247429,"text":"70247429 - 2023 - Cross-continental evaluation of landscape-scale drivers and their impacts to fluvial fishes: Understanding frequency and severity to improve fish conservation in Europe and the United States","interactions":[],"lastModifiedDate":"2023-08-07T15:02:48.175538","indexId":"70247429","displayToPublicDate":"2023-07-11T09:22:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Cross-continental evaluation of landscape-scale drivers and their impacts to fluvial fishes: Understanding frequency and severity to improve fish conservation in Europe and the United States","docAbstract":"Fluvial fishes are threatened globally from intensive human landscape stressors degrading aquatic ecosystems. However, impacts vary regionally, as stressors and natural environmental factors differ between ecoregions and continents. To date, a comparison of fish responses to landscape stressors over continents is lacking, limiting understanding of consistency of impacts and hampering efficiencies in conserving fishes over large regions. This study addresses these shortcomings through a novel, integrative assessment of fluvial fishes throughout Europe and the conterminous United States. Using large-scale datasets, including information on fish assemblages from more than 30,000 locations on both continents, we identified threshold responses of fishes summarized by functional traits to landscape stressors including agriculture, pasture, urban area, road crossings, and human population density. After summarizing stressors by catchment unit (local and network) and constraining analyses by stream size (creeks vs. rivers), we analyzed stressor frequency (number of significant thresholds) and stressor severity (value of identified thresholds) within ecoregions across Europe and the United States. We document hundreds of responses of fish metrics to multi-scale stressors in ecoregions across two continents, providing rich findings to aid in understanding and comparing threats to fishes across the study regions. Collectively, we found that lithophilic species and, as expected, intolerant species are most sensitive to stressors in both continents, while migratory and rheophilic species are similarly strongly affected in the United States. Also, urban land use and human population density were most frequently associated with declines in fish assemblages, underscoring the pervasiveness of these stressors in both continents. This study offers an unprecedented comparison of landscape stressor effects on fluvial fishes in a consistent and comparable manner, supporting conservation of freshwater habitats in both continents and worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.165101","usgsCitation":"Ublacker, M.M., Infante, D.M., Cooper, A.R., Daniel, W., Schmutz, S., and Schinegger, R., 2023, Cross-continental evaluation of landscape-scale drivers and their impacts to fluvial fishes: Understanding frequency and severity to improve fish conservation in Europe and the United States: Science of the Total Environment, v. 897, 165101, 14 p., https://doi.org/10.1016/j.scitotenv.2023.165101.","productDescription":"165101, 14 p.","ipdsId":"IP-154519","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.165101","text":"Publisher Index Page"},{"id":419565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. In this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.
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University","active":true,"usgs":false}],"preferred":false,"id":878875,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":" Roy 0000-0002-6279-8447","orcid":"https://orcid.org/0000-0002-6279-8447","contributorId":317086,"corporation":false,"usgs":false,"given":"Roy","email":"","affiliations":[{"id":68938,"text":"Civil and Environmental Engineering, University of Nebraska-Lincoln, NE, USA","active":true,"usgs":false}],"preferred":false,"id":878593,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Xu, Chonggang","contributorId":207944,"corporation":false,"usgs":false,"family":"Xu","given":"Chonggang","email":"","affiliations":[],"preferred":false,"id":878594,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Lawson, Kathryn","contributorId":265776,"corporation":false,"usgs":false,"family":"Lawson","given":"Kathryn","affiliations":[{"id":54792,"text":"Civil and Environmental Engineering, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":878595,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}} ,{"id":70253132,"text":"70253132 - 2023 - Thermography captures the differential sensitivity of dryland functional types to changes in rainfall event timing and magnitude","interactions":[],"lastModifiedDate":"2024-04-19T12:08:14.090033","indexId":"70253132","displayToPublicDate":"2023-07-11T07:05:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Thermography captures the differential sensitivity of dryland functional types to changes in rainfall event timing and magnitude","docAbstract":"Basaltic caldera collapses are episodic, producing very-long-period (VLP) earthquakes up to Mw 5.4, with prolific inter-collapse (between collapses) volcano-tectonic (VT) seismicity. During the 2018 caldera collapse of Kīlauea Volcano, VT seismicity ceased following each collapse, and then accelerated to a quasi-steady rate prior to the next collapse, marking a temporal pattern distinct from typical foreshock/aftershock sequences. There is currently no consensus on the mechanism(s) that generates the VT seismicity. Here we demonstrate that inter-collapse ring fault creep, induced by chamber depressurization, was the main driver of VT seismicity at Kīlauea in 2018. This is evidenced by: 1) the correlation between cumulative number of VT events and GNSS-derived ring fault creep; 2) agreement between repeating earthquake and GNSS derived creep rates; and 3) consistency between the time dependence of mechanically modeled, creep-driven seismicity and observations. We further show that, ring fault creep can be explained by velocity strengthening friction alone or in conjunction with viscous shear zone rheology. The simultaneous occurrence of creep and seismicity highlights the spatially heterogeneous velocity weakening/strengthening friction on the ring fault. If the VT seismicity-creep correlation can be replicated at other basaltic volcanoes, it would demonstrate that VT seismicity can be used as a proxy for ring fault creep in the absence of GNSS measurements on subsiding caldera block(s).
Coal is increasingly evaluated as a source of rare earth elements (REEs) in the United States to address the overreliance on imported REEs. The objective of this study was to assess the distribution of REEs in lignites from selected mining areas in the Texas Gulf Coastal Plain region. Thirty-one archived lignite and rock samples previously collected by the U.S. Geological Survey were analyzed for their rare earth element and critical mineral content. These include samples from one core (5400 and 5500 lignite horizons) and two opencast lignite mines (Gibbons Creek 3500 and 4500 horizons, and San Miguel horizons A to D) in the Eocene Jackson Group of the Texas Gulf of Mexico Coastal Plain. Some lithologies in the Gibbons Creek 3500 and 4500 lignite-bearing sections have high total rare earth, yttrium (Y), and scandium (Sc) (REYSc) values, up to 7800 ppm (ash basis) REYSc. The lignite lithologies show an enrichment in rare earths, [samarium (Sm) through gadolinium (Gd)]. The basal Gibbons Creek 3500 lignite bench shows a heavy rare earth element enrichment pattern resembling that often seen in peats through high volatile A bituminous coals. The 5500 lignite sequence, overlying the latter lignite sections, shows a light rare earth enrichment. The San Miguel lignite benches have heavy rare earth enrichments with a negative europium (Eu) anomaly.
Salinity control efforts in the Colorado River Basin have focused on mobilization of salts from irrigated land, but nonirrigated rangelands are also a source of salinity. In particular, lands where soils have formed from the Late Cretaceous Mancos Shale under arid and semiarid climates contain considerable quantities of salt, mainly in the subsurface. Hundreds of thousands of contour furrows and check dams (gully plugs) were constructed by the Bureau of Land Management (BLM) and Bureau of Reclamation in the late 1950s and 1960s to reduce runoff, sedimentation, and salt mobilization from ephemeral stream channels on rangelands. Sediment-retention ponds associated with check dams are dry most of the year, except immediately following substantial rain events. Generally, no maintenance has been performed on these structures, some have degraded over time, and their current and past influence on salinity is poorly understood. To assess the influence of check dams and their associated ponds on salt retention and mobilization, the U.S. Geological Survey, in cooperation with the BLM, conducted a study of such ponds within the Gunnison Gorge National Conservation Area (GGNCA) near Delta, Colorado.
This report includes conceptual models of how sediment-retention ponds function relative to salinity, and a collection of environmental data to evaluate the conceptual models. An inventory of 69 ponds indicated that 38 percent no longer had water holding capacity, and another 20 percent could hold 1 foot or less of water. Check-dam degradation was the main cause, but sediment infill of ponds contributed as well. Water content of soil profiles collected beneath ponds and immediately downstream from check dams indicated little penetration of water below 60 centimeters for most ponds and little evidence for lateral movement of water beneath check dams. Patterns of salt content in the soil profiles indicated no accumulation of salts at the pond surface from evaporating waters and little evidence for salt redistribution in the form of salt bulges or salt depletion curves at intermediate depths. Based on the conceptual models presented and interpretations of data collected by this study, it appears that the sediment-retention ponds in the GGNCA have neither mobilized nor retained substantial quantities of salt during their lifetimes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235071","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Availability and Use Science Program","usgsCitation":"Richards, R.J., Bern, C.R., and Moreno, V., 2023, Assessment of salinity retention or mobilization by sediment-retention ponds near Delta, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2023–5071, 21 p., https://doi.org/10.3133/sir20235071.","productDescription":"Report: v, 21 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-134766","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":418430,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WZNJL6","text":"USGS data release","linkHelpText":"Data from the assessment of sediment-retention ponds near Delta, Colorado, 2019"},{"id":418428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5071/coverthb.jpg"},{"id":418429,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.pdf","text":"Report","size":"4.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5071"},{"id":500951,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114965.htm","linkFileType":{"id":5,"text":"html"}},{"id":418866,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5071"},{"id":418837,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.xml"},{"id":418836,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5071/images"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.55,\n 38.4\n ],\n [\n -107.55,\n 38.36\n ],\n [\n -107.53,\n 38.36\n ],\n [\n -107.53,\n 38.4\n ],\n [\n -107.55,\n 38.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25048, Mail Stop 415
Denver, Colorado 80225
Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black-tailed jackrabbits (Lepus californicus), kit foxes (Vulpes macrotis), and pronghorns (Antilocapra americana) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated-manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine-learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species-specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species-level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi-automated workflow that produced reliable estimates and inferences. Thus, camera-based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification.
","language":"English","publisher":"Wiley","doi":"10.1002/rse2.356","usgsCitation":"Lonsinger, R.C., Dart, M.M., Larsen, R., and Knight, R.N., 2023, Efficacy of machine learning image classification for automated occupancy-based monitoring: Remote Sensing in Ecology and Conservation, v. 10, no. 1, p. 56-71, https://doi.org/10.1002/rse2.356.","productDescription":"16 p.","startPage":"56","endPage":"71","ipdsId":"IP-150309","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442810,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.356","text":"Publisher Index Page"},{"id":432056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Dugway Proving Ground, Lund, Mojave Desert, Beaver Dam Wash, Colorado Plateau Great Basin 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\"}}]}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dart, Marlin M.","contributorId":340675,"corporation":false,"usgs":false,"family":"Dart","given":"Marlin","email":"","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":907445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larsen, Randy T.","contributorId":340676,"corporation":false,"usgs":false,"family":"Larsen","given":"Randy T.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":907446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Robert N.","contributorId":340677,"corporation":false,"usgs":false,"family":"Knight","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":81648,"text":"US Army Dugway Proving Ground","active":true,"usgs":false}],"preferred":false,"id":907447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246549,"text":"sir20235075 - 2023 - Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2026-03-12T20:44:43.104195","indexId":"sir20235075","displayToPublicDate":"2023-07-10T12:38:28","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5075","displayTitle":"Potential Effects of Projected Pumping Scenarios on Future Water-Table Elevations Near Kirtland Air Force Base in Albuquerque, New Mexico","title":"Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","docAbstract":"The U.S. Geological Survey, in cooperation with the Air Force Civil Engineer Center, simulated different groundwater pumping scenarios from 2016 to 2050 to determine the potential future changes in groundwater levels in areas around the Kirtland Air Force Base Bulk Fuels Facility and an ethylene dibromide (EDB) plume. Projections of water supply and demand created by the Albuquerque Bernalillo County Water Utility Authority were used to develop the future groundwater pumping scenarios used as inputs for a refined local-scale model within the updated Middle Rio Grande Basin regional model.
The simulated water-table elevations in model cells that contain the EDB plume in the medium demand and medium supply scenario rose 29 feet (ft) until 2035, then remained within 10 ft of that elevation through 2050, whereas the water-table elevations in the high demand and low supply scenario rose about 26 ft until 2035 and then decreased by more than 10 ft. Simulated water-table elevations in the low demand and high supply scenario continued to rise throughout most of the future simulation period and peaked at about 44 ft over the 2016 water-table elevation. All of the scenarios ended the future simulation period with higher simulated water-table elevations than at the beginning of the future simulation period. Simulations that represented the potentially highest and lowest volume of groundwater pumping near the EDB plume by adjusting the spatial distribution of pumping had similar simulated water-table elevations as the nonadjusted scenarios, with maximum water-table elevation changes that only differed by about 2 ft from the nonadjusted scenarios. Consideration should be taken when using these model results to inform decisions because the model results are subject to uncertainty from many different sources, including uncertainty in the future pumping scenarios as well as the model itself because of the simplification of the hydrogeologic system.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.0, provides guidance and protocols for the measurement of field parameters on site, which include the selection of sites and methods for measurement in groundwater and surface water and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.0, version 2.0, by Franceska D. Wilde. Field parameters are routinely measured when water samples are collected, are often measured continually at USGS streamgages, and are regularly measured during laboratory and field experiments. The field methods for measuring field parameters described in this chapter are applicable to most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.er.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
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","tableOfContents":"Coordinated wildlife disease surveillance (WDS) can help professionals across disciplines effectively safeguard human, animal, and environmental health. The aims of this study were to understand how WDS in Thailand is utilized, valued, and can be improved within a One Health framework. An online questionnaire was distributed to 183 professionals (55.7% response rate) across Thailand working in wildlife, marine animal, livestock, domestic animal, zoo animal, environmental, and public health sectors. Twelve semi-structured interviews with key professionals were then performed. Three-quarters of survey respondents reported using WDS data and information. Sectors agreed upon ranking disease control (76.5% of respondents) as the most beneficial outcome of WDS, while fostering new ideas through collaboration was valued by few participants (2.0%). Accessing data collected by ones own sector was identified as the most challenging (50%) yet least difficult to improve (88.3%). Having legal authority to conduct WDS was the second most frequently identified challenge. Interviewees explained that legal documentation required for crossinstitutional collaborations posed a barrier to efficient communication and use of human resources. Survey respondents identified allocation of human resources (75.5%), adequate budget (71.6%), and having a clear communication system between sectors (71.6%) as highest priority areas for improvement to WDS in Thailand. Authorization from administrative officials and support from local community members were identified as challenges during in-person interviews. Future outreach should be directed towards these groups. As 42.9% of marine health professionals had difficulty knowing whom to contact in other sectors and 28.4% of survey respondents indicated that communication with marine health professionals was not applicable to their work, connecting the marine sector with other sectors may be prioritized. This study identifies priorities for addressing current challenges in the establishment of a general WDS system and information management system in Thailand while presenting a model for such evaluation in other regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2023.100600","usgsCitation":"George, S.E., Smink, M., Sangkachai, N., Wiratsudakul, A., Sakcamduang, W., Suwanpakdee, S., and Sleeman, J.M., 2023, Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand: One Health Newsletter, v. 17, 100600, 10 p., https://doi.org/10.1016/j.onehlt.2023.100600.","productDescription":"100600, 10 p.","ipdsId":"IP-154964","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":442811,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2023.100600","text":"Publisher Index 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