Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs (Ascaphus truei), coastal giant salamanders (Dicamptodon tenebrosus), and Columbia torrent salamanders (Rhyacotriton kezeri) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri. Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.
Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn (Antilocapra americana), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer (Odocoileus hemionus), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.
Compressional-wave seismic velocity (velocity) and bulk density (density) data were compiled from published sources for rock suites and earth materials that are significant for geophysical modeling of the Mesoproterozoic Midcontinent Rift System in the Lake Superior region. The data include laboratory measurements of outcrop and drill core samples, seismic refraction studies, and a sonic log from a 1.5-kilometer-deep exploration well. Rock suites of the Midcontinent Rift System include basalts of the Mesoproterozoic Keweenawan Supergroup, Oronto Group sedimentary rocks (divided into arenaceous versus argillaceous units), and several sedimentary formations overlying the Oronto Group that have been correlated across the area. Intrusive units include diabase, gabbro, and felsic igneous rocks. Other geologic units important for geophysical modeling in the Lake Superior region include Archean crystalline crust, Paleoproterozoic metasedimentary and crystalline rocks, lower Mesoproterozoic sedimentary rocks, and Holocene to Pleistocene surficial deposits.
Empirical velocity-density relations for each rock suite were determined by comparing the compiled data to published relations, such as the Nafe-Drake curve, Gardner’s relation, and best-fit equations developed for different rock types from laboratory studies. Graphical representations of these velocity-density relations provide a way to easily understand how velocity and density differ between tectonic settings and by rock type. Overlaps in velocity and density ranges for different geologic units are significant and have especially important implications for geologic interpretation of seismic data. Important examples include similar velocities but differing densities for argillaceous Oronto Group versus units overlying the Oronto Group and arenaceous Oronto Group versus basalt of the Keweenawan Supergroup. Similar densities but differing velocities were found for diabase versus gabbro. In addition, expected velocity ranges by rock type show that high-velocity intervals (6.9–7.1 kilometers per second) interpreted as basalt in previous seismic-reflection studies more likely indicate diabase or gabbro, suggesting that these interpretations may warrant additional consideration.
Center Director, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 1 (January–March) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 safehold anomaly. On January 26, 2023, the Global Positioning System (GPS) onboard Landsat 8 became invalid because the GPS fault tripped. Later that same day, the GPS was reinitialized, but a Field of View 1 fault trip occurred early the next morning, causing the observatory to go into Earth Point Safe mode, which put the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) into safehold. Once it was safe to reactivate the sensors, the OLI was transitioned to operational status late on January 27 and TIRS was reactivated early on January 28. Additional information about the Landsat 8 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-8-recovers-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231050","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023: U.S. Geological Survey Open-File Report 2023–1050, 39 p., https://doi.org/10.3133/ofr20231050.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-152817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419162,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":419161,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1050/images/"},{"id":419158,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1050/coverthb.jpg"},{"id":419181,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231050/full"},{"id":419160,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.XML"},{"id":419159,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1050"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
New geophysical profiles across the central Dead Sea Transform (DST) near the Sea of Galilee, Israel, and surrounding highlands, augmented by static stress modeling, allow us to study continental transform plate deformation. The DST separates a ∼10 km thick sedimentary column above a thinned (16–23 km) crust to the west from a ∼7 km column above a ∼30-km thick crust to the east. Crustal thinning starts under the DST, as observed also farther south, indicating that the DST is indeed located along the boundary between the Arabian plate and its continental margin. Moho step here is gradual. The DST's eastern shoulder dips westward toward the DST unlike the upward flexed shoulder observed farther south, perhaps delineating the northern limit of a thinner and hotter lithosphere. The shape of the Sea of Galilee is modeled as an asymmetric pull-apart basin formed by a left-lateral stepover of 2.6 km between slightly divergent and underlapping strike-slip fault strands dipping 70° to the west. Reflection data indicate that these strands are not connected. Several fault traces within the Sea of Galilee have previously been suggested to carry part of the relative plate motion. However, given slip along the main DST faults, Coulomb stress will increase only on fault portions in the northern part of the lake, in accord with the geographical distribution of seismicity, suggesting that these faults are likely secondary. Mismatch between the DST strand locations in the geophysical profiles and the subsidence model, may reflect temporal changes in fault geometry.
To determine the most relevant climatic and economic factors driving water demand for Providence, Rhode Island, and to further the understanding of human interactions with water availability, linear regression models were developed to estimate single-family and multifamily residential, commercial, and industrial water demand for the service area of Providence Water for 2014–21. Monthly water use delivery data were provided by Providence Water. An array of climatic and economic data, the drought index, and binary variables to represent seasonal water use and the onset of the coronavirus (COVID–19) were investigated as possible explanatory variables for the water demand models. The water demand model with the best fit with the least amount of error was the single-family residential water demand followed in descending order of accuracy by the commercial, multifamily residential, and industrial water demand. Seasonal variables were significant in all models, and the COVID–19 binary variable was significant in the commercial and industrial models. One or two economic variables were significant in all models and one climatic variable was significant in all models except the commercial model.
Overall residential, commercial, and industrial water demand in the Providence, Rhode Island, service area has decreased during the study period most likely because of widescale drought conditions and policies designed to improve water efficiencies. The linear regression models developed for single-family and multifamily residential, commercial, and industrial water use explained 94, 85, 91, and 77 percent, respectively, of the variability in monthly water use. Multifamily residential water demand displayed a less distinct seasonal trend than that observed for single-family residential customers, likely because multifamily homes tend to use less water outdoors. The commercial water-demand model included no climatic variables, one economic variable, the COVID–19 pandemic variable, and the high and low water use seasonal variables—the latter two variables indicating the importance of seasonal fluctuations in water use. The COVID–19 pandemic and a concomitant State executive order had the immediate effect of severely reducing commercial water use. The industrial water-demand model did not perform as well as the other models because industrial water delivery data display a greater range of values, both seasonally and for the overall study period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235057","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Stagnitta, T.J., and Medalie, L., 2023, Assessment of factors that influence human water demand for Providence, Rhode Island: U.S. Geological Survey Scientific Investigations Report 2023–5057, 18 p., https://doi.org/10.3133/sir20235057.","productDescription":"Report: vi, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-142026","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":419046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5057/coverthb.jpg"},{"id":500938,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114971.htm","linkFileType":{"id":5,"text":"html"}},{"id":419051,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91H5QOY","text":"USGS data release","linkHelpText":"Data for regression models to estimate water use in Providence, Rhode Island, 2014–2021"},{"id":419050,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5057/images/"},{"id":419049,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5057/sir20235057.XML"},{"id":419048,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235057/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 20023-5057"},{"id":419047,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5057/sir20235057.pdf","text":"Report","size":"1.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 20023-5057"}],"country":"United States","state":"Rhode Island","city":"Providence","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.496115199193,\n 41.87371310909353\n ],\n [\n -71.496115199193,\n 41.785379633702576\n ],\n [\n -71.37573267926174,\n 41.785379633702576\n ],\n [\n -71.37573267926174,\n 41.87371310909353\n ],\n [\n -71.496115199193,\n 41.87371310909353\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Beginning in September 2010, the U.S. Geological Survey installed continuous water-quality monitors at several streamgages across Indiana as part of a network of supergages to meet cooperator information needs. Two types (or models) of water-quality monitors deployed at each site measured and recorded water temperature, dissolved oxygen, specific conductance, pH, and turbidity every 15 minutes during the study period. Associated discrete water samples were collected at regular intervals and analyzed for concentrations of suspended sediment and total phosphorus. Surrogate regression models were developed between the continuously measured turbidity values and turbidity values in the associated samples to compute continuous concentrations and loads of suspended sediment and total phosphorus. Starting in November 2018, the original extended deployment system monitors were replaced with the newest model of multiparameter water-quality monitors and were equipped with turbidity smart sensors because the older monitors were phased out of production. The updated monitor and smart sensor yield different but relatable turbidity values.
Turbidity data collected concurrently by the two sensors from November 2018 to December 2021 were compared and analyzed to quantify the relation between them at six supergage sites in northwestern Indiana and one site in the town of Zionsville in central Indiana. Ordinary least squares regression was used to calculate site-specific conversion factors so that turbidity data from the newer monitors can be used in published surrogate models based on the older monitor data. Regression analyses explained approximately 98 percent of the variation in turbidity readings between the two sensors. From these analyses, conversion factors were developed that may be applied to older turbidity readings to calculate near real-time concentrations of phosphorus and suspended sediment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235077","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management, Iroquois River Conservancy District, Kankakee River Basin and Yellow River Basin Development Commission, and the Town of Zionsville","usgsCitation":"Messner, M.L., Perkins, M.K., and Bunch, A.R., 2023, Comparison of turbidity sensors at U.S. Geological Survey supergages in Indiana from November 2018 to December 2021: U.S. Geological Survey Scientific Investigations Report 2023–5077, 13 p., https://doi.org/10.3133/sir20235077.","productDescription":"Report: iv, 13 p.; Dataset","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129902","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":501040,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114970.htm","linkFileType":{"id":5,"text":"html"}},{"id":419012,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System","linkHelpText":"- U.S. Geological Survey water data for the nation"},{"id":419011,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5077/images/"},{"id":419010,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5077/sir20235077.XML"},{"id":419009,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235077/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5077"},{"id":419008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5077/sir20235077.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5077"},{"id":419007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5077/coverthb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Kankakee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.47825888394271,\n 41.7055943665263\n ],\n [\n -87.47825888394271,\n 40.75718260396678\n ],\n [\n -86.31031406433961,\n 40.75718260396678\n ],\n [\n -86.31031406433961,\n 41.7055943665263\n ],\n [\n -87.47825888394271,\n 41.7055943665263\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd.
Indianapolis, IN 46278
Rapid and simple estimation of the mass eruption rate (MER) from column height is essential for real-time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER-height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER-height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics-based models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL102633","usgsCitation":"Aubry, T.J., Engwell, S., Bonadonna, C., Mastin, L.G., Carazzo, G., Van Eaton, A.R., Jessop, D.E., Grainger, R.G., Scollo, S., Taylor, I.A., Jellinek, A.M., Schmidt, A., Biass, S., and Gouhier, M., 2023, New insights into the relationship between mass eruption rate and volcanic column height based on the IVESPA dataset: Geophysical Research Letters, v. 50, no. 14, e2022GL102633, 12 p., https://doi.org/10.1029/2022GL102633.","productDescription":"e2022GL102633, 12 p.","ipdsId":"IP-152764","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442739,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl102633","text":"Publisher Index Page"},{"id":422333,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"14","noUsgsAuthors":false,"publicationDate":"2023-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Aubry, Thomas J.","contributorId":331321,"corporation":false,"usgs":false,"family":"Aubry","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":887344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engwell, Samantha 0000-0001-7719-6257","orcid":"https://orcid.org/0000-0001-7719-6257","contributorId":251719,"corporation":false,"usgs":false,"family":"Engwell","given":"Samantha","email":"","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":887345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Costanza","contributorId":199721,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Costanza","email":"","affiliations":[],"preferred":false,"id":887346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carazzo, Guillaume","contributorId":260384,"corporation":false,"usgs":false,"family":"Carazzo","given":"Guillaume","email":"","affiliations":[{"id":52575,"text":"CNRS, Paris, France","active":true,"usgs":false}],"preferred":false,"id":887348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":887349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jessop, David E.","contributorId":331322,"corporation":false,"usgs":false,"family":"Jessop","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":79186,"text":"Universite Clermont-Avergne","active":true,"usgs":false}],"preferred":false,"id":887350,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grainger, Roy G.","contributorId":331323,"corporation":false,"usgs":false,"family":"Grainger","given":"Roy","email":"","middleInitial":"G.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":887351,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scollo, Simona","contributorId":260385,"corporation":false,"usgs":false,"family":"Scollo","given":"Simona","email":"","affiliations":[{"id":27605,"text":"INGV, Catania, Italy","active":true,"usgs":false}],"preferred":false,"id":887352,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Taylor, Isabelle A","contributorId":260386,"corporation":false,"usgs":false,"family":"Taylor","given":"Isabelle","email":"","middleInitial":"A","affiliations":[{"id":30742,"text":"University of Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":887353,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jellinek, A. Mark","contributorId":54364,"corporation":false,"usgs":true,"family":"Jellinek","given":"A.","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":887354,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schmidt, Anja","contributorId":260391,"corporation":false,"usgs":false,"family":"Schmidt","given":"Anja","email":"","affiliations":[{"id":52574,"text":"University of Cambridge, UK","active":true,"usgs":false}],"preferred":false,"id":887355,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Biass, Sebastien","contributorId":331324,"corporation":false,"usgs":false,"family":"Biass","given":"Sebastien","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":887356,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gouhier, Mathieu","contributorId":260388,"corporation":false,"usgs":false,"family":"Gouhier","given":"Mathieu","email":"","affiliations":[{"id":29878,"text":"Université Clermont Auvergne, Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":887357,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70247692,"text":"70247692 - 2023 - Water quality impacts of climate change, land use, and population growth in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2023-12-20T17:47:57.414032","indexId":"70247692","displayToPublicDate":"2023-07-18T08:53:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Water quality impacts of climate change, land use, and population growth in the Chesapeake Bay watershed","docAbstract":"The 2010 Chesapeake Bay Total Maximum Daily Load was established for the water quality and ecological restoration of the Chesapeake Bay. In 2017, the latest science, data, and modeling tools were used to develop revised Watershed Implementation Plans (WIPs). In this article, we examine the vulnerability of the Chesapeake Bay watershed to the combined pressures of climate change and growth in population, agricultural intensity, and economic activity for the 60-year period 1995–2055. The results will be used to revise WIPs, as needed, to account for expected increases in loads. Assessing changes relative to 1995 for the years 2025, 2035, 2045, and 2055, mean annual precipitation increases of 3.11%, 4.21%, 5.34%, and 6.91%, respectively, air temperature increases of 1.12, 1.45, 1.84, and 2.12°C, respectively, and potential evapotranspiration increases of 3.36%, 4.43%, 5.54%, and 6.35%, respectively, are projected. Population in the watershed is expected to grow by 3.5 million between 2025 and 2055. Watershed model results show incremental increases in streamflow (2.3%–6.2%), nitrogen (2.6%–10.8%), phosphorus (4.5%–26.7%), and sediment (3.8%–18.8%) loads to the tidal Bay due to climate change. Growth in population, agricultural intensity, development, and economic activity resulted in relatively smaller increases in loads compared to climate change.
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0000-0002-2737-2379","orcid":"https://orcid.org/0000-0002-2737-2379","contributorId":306024,"corporation":false,"usgs":false,"family":"Hinson","given":"Kyle","email":"","middleInitial":"E.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":880058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Claggett, Peter 0000-0002-5335-2857","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":238920,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":880059,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248826,"text":"70248826 - 2023 - Current and future sinkhole susceptibility in karst and pseudokarst areas of the conterminous United States","interactions":[],"lastModifiedDate":"2023-09-22T13:52:11.321375","indexId":"70248826","displayToPublicDate":"2023-07-18T08:49:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Current and future sinkhole susceptibility in karst and pseudokarst areas of the conterminous United States","docAbstract":"Sinkholes in karst and pseudokarst regions threaten infrastructure, property, and lives. We mapped closed depressions in karst and pseudokarst regions of the conterminous United States (U.S.) from 10-m-resolution elevation data using high-performance computing, and then created a heuristic additive model of sinkhole susceptibility that also included nationally consistent data for factors related to geology, soils, precipitation extremes, and development. Maps identify potential sinkhole hotspots based on current conditions and projections for 50 years into the future (the years 2070–2079) based on climate change and urban development scenarios. Areas characterized as having either high or very high sinkhole susceptibility contain 94%–99% of known or probable sinkhole locations from three U.S. state databases. States and counties with the highest amounts and percentages of land in zones of highest sinkhole susceptibility are identified. Projected changes in extreme precipitation and development did not substantially change current hotspots of highest sinkhole susceptibility. Results provide a uniform index of sinkhole potential that can support national planning, instead of existing assessments produced through various methods within individual states or smaller areas.
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nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":883803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":883804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":883805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":883806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248825,"text":"70248825 - 2023 - Modeling non-structural strategies to reduce pedestrian evacuation times for mitigating local tsunami threats in Guam","interactions":[],"lastModifiedDate":"2023-09-22T11:57:25.815889","indexId":"70248825","displayToPublicDate":"2023-07-16T06:51:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Modeling non-structural strategies to reduce pedestrian evacuation times for mitigating local tsunami threats in Guam","docAbstract":"Reducing the potential for loss of life from local tsunamis is challenging for emergency managers given the need for self-protective behavior of at-risk individuals within brief windows of time to evacuate. There has been considerable attention paid to discussing the use of tsunami vertical-evacuation structures for areas where there may be insufficient time to evacuate. This strategy may not be feasible or needed for at-risk populations in island communities for multiple reasons. We examine the influence of three non-structural interventions (reducing departure delays, increasing travel speeds, and managing vegetation to create new paths) that may improve the evacuation potential for at-risk individuals in island communities and use the United States territory of Guam as our case study. We model pedestrian travel times out of a modeled inundation zone for a local tsunami generated by a Mw 8.3 earthquake within the Mariana subduction zone. Evacuation-modeling results indicate that reducing departure delays has a larger impact than increasing travel speeds or creating evacuation corridors through heavy brush on reducing the number of at-risk individuals with insufficient time to evacuate. Travel times to safety are less than wave-arrival times for almost all at-risk individuals in the tsunami-hazard zone if one assumes all three interventions are implemented.
Increasingly frequent megafires are dramatically altering landscapes and critical habitats around the world. Across the western United States, megafires have become an almost annual occurrence, but the implication of these fires for the conservation of native wildlife remains relatively unknown. Woodland savannas are among the world's most biodiverse ecosystems and provide important food and structural resources to a variety of wildlife, but they are threatened by megafires. Despite this, the great majority of fire impact studies have only been conducted in coniferous forests. Understanding the resistance and resilience of wildlife assemblages following these extreme perturbations can help inform future management interventions that limit biodiversity loss due to megafire. We assessed the resistance of a woodland savanna mammal community to the short-term impacts of megafire using camera trap data collected before, during, and after the fire. Specifically, we utilized a 5-year camera trap data set (2016–2020) from the Hopland Research and Extension Center to examine the impacts of the 2018 Mendocino Complex Fire, California's largest recorded wildfire at the time, on the distributions of eight observed mammal species. We used a multispecies occupancy model to quantify the effects of megafire on species' space use, to assess the impact on species size and diet groups, and to create robust estimates of fire's impacts on species diversity across space and time. Megafire had a negative effect on the detection of certain mammal species, but overall, most species showed high resistance to the disturbance and returned to detection and site use levels comparable to unburned sites by the end of the study period. Following megafire, species richness was higher in burned areas that retained higher canopy cover relative to unburned and burned sites with low canopy cover. Fire management that prevents large-scale canopy loss is critical to providing refugia for vulnerable species immediately following fire in oak woodlands, and likely other mixed-forest landscapes.
This report provides analysis to extend the 2040 forecasts of polar bear (Ursus maritimus) land use for the southern Beaufort and Chukchi Sea populations presented in a recent publication (Rode and others, 2022) through the year 2065. To inform long-term polar bear management considerations, we provide point-estimate forecasts and 95-percent prediction intervals of the proportion of polar bear populations summering onshore for 21 days or more (≥) and their duration onshore every 5 years from 2040 to 2065. Because sea-ice projections based on earth system models show greater divergence with emission scenarios after 2040, we have provided forecasts for three greenhouse gas emission scenarios, SSP1-2.6, SSP2-4.5 and SSP5-8.5, compared to the two emission scenarios used in Rode and others (2022). Our forecasting methods estimated that 61–97 percent of polar bears in the southern Beaufort Sea and 80–100 percent of polar bears in the Chukchi Sea populations may summer onshore for ≥21 days by 2065. Forecasts of mean duration onshore were 105–158 days for polar bears in the southern Beaufort Sea and 111–178 days in the Chukchi Sea populations by 2065. Sea ice conditions projected to occur by 2065 could alter the current patterns of bear behavior from what has been observed over the past 30 years. As a result, these extended projections are associated with a higher degree of uncertainty than estimates through 2040, especially under the SSP5-8.5 scenario.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231048","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Rode, K.D., Douglas, D.C., Atwood, T.C., and Wilson, R.R., Forecasts of polar bear (Ursus maritimus) land use in the southern Beaufort and Chukchi Seas, 2040–65: U.S. Geological Survey Open-File Report 2023–1048, 7 p., https://doi.org/10.3133/ofr20231048.","productDescription":"Report: vi, 7 p.; Data Release","numberOfPages":"7","onlineOnly":"Y","ipdsId":"IP-148069","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":418953,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211048/full"},{"id":418955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1048/images"},{"id":418954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1048/ofr20231048.xml"},{"id":418956,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XEOBWV","text":"Polar bear Continuous Time-Correlated Random Walk (CTCRW) location data derived from satellite location data, Chukchi and Beaufort Seas, July-November 1985-2017","description":"Rode, K. D., Douglas, D. C., Atwood, T. C., Durner, G. M., Wilson, R. R., Bromaghin, J. F., Pagano, A. M. and Simac, K. S., 2022, Polar bear Continuous Time-Correlated Random Walk (CTCRW) location data derived from satellite location data, Chukchi and Beaufort Seas, July-November 1985-2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9XEOBWV."},{"id":418951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1048/covrthb.jpg"},{"id":418952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1048/ofr20231048.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris-flow incision rate formulations that produce morphology consistent with natural landscapes. In many landscapes, including the San Gabriel Mountains (SGM), California, steady-state fluvial channel longitudinal profiles are concave-up and exhibit a power-law relationship between channel slope and drainage area. At low drainage areas, however, valley slopes become nearly constant. These topographic forms result in a characteristically curved slope-area signature in log-log space. Here, we use a one-dimensional landform evolution model that incorporates debris-flow erosion to reproduce the relationship between this curved slope-area signature and erosion rate in the SGM. Topographic analysis indicates that the drainage area at which steepland valleys transition to fluvial channels correlates with measured erosion rates in the SGM, and our model results reproduce these relationships. Further, the model only produces realistic valley profiles when parameters that dictate the relationship between debris-flow erosion, valley-bottom slope, and debris-flow depth are within a narrow range. This result helps place constraints on the mathematical form of a debris-flow incision law. Finally, modeled fluvial incision outpaces debris-flow erosion at drainage areas less than those at which valleys morphologically transition from near-invariant slopes to concave profiles. This result emphasizes the critical role of debris-flow incision for setting steepland form, even as fluvial incision becomes the dominant incisional process.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF007017","usgsCitation":"Struble, W., McGuire, L.A., McCoy, S., Barnhart, K.R., and Marc, O., 2023, Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California: JGR Earth Surface, v. 128, no. 7, e2022JF007017, 29 p., https://doi.org/10.1029/2022JF007017.","productDescription":"e2022JF007017, 29 p.","ipdsId":"IP-147440","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":442759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf007017","text":"Publisher Index Page"},{"id":419301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gabriel Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.01260424279738,\n 34.14566760098988\n ],\n [\n -117.67000792883225,\n 34.147752407886856\n ],\n [\n -117.3853506973756,\n 34.19777233450243\n ],\n [\n -117.11076982809459,\n 34.09144456704166\n ],\n [\n -116.9344334900242,\n 33.94110717551865\n ],\n [\n -116.67244800052214,\n 33.974538472354965\n ],\n [\n -116.69511981541675,\n 34.30812790101858\n ],\n [\n -117.29718245539995,\n 34.32893347252433\n ],\n [\n -117.75313784383901,\n 34.445349311566275\n ],\n [\n -118.02268053203237,\n 34.51387565376443\n ],\n [\n -118.46855955829582,\n 34.40586922676006\n ],\n [\n -118.51390318808532,\n 34.34141433967626\n ],\n [\n -118.01260424279738,\n 34.14566760098988\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Struble, William 0000-0002-8163-5088","orcid":"https://orcid.org/0000-0002-8163-5088","contributorId":241913,"corporation":false,"usgs":false,"family":"Struble","given":"William","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":878951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":878952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":878953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":878954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marc, Odin","contributorId":198732,"corporation":false,"usgs":false,"family":"Marc","given":"Odin","email":"","affiliations":[],"preferred":false,"id":878955,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246768,"text":"70246768 - 2023 - Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity","interactions":[],"lastModifiedDate":"2023-07-19T13:54:11.562487","indexId":"70246768","displayToPublicDate":"2023-07-14T08:52:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1092,"text":"Bulletin, Southern California Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity","docAbstract":"Risk analysis protocols for prioritizing the management of non-native species are numerous, yet few incorporate risk and management in the same analysis or accommodate a broad diversity of taxa outside of a specific geographic area. We adapted a protocol that accounts for these factors to address non-native animal species in the Southern California/Northern Baja California Coast Ecoregion near the international border in San Diego County, an area with high indigenous biodiversity and high numbers of species of conservation concern. This stepwise, semi-quantitative protocol is applicable to any animal group in any predefined geographic area, relies on consensus-building among taxonomic experts, and has been vetted through previous use and in peer-reviewed literature. Our results show that the final prioritization was driven mainly by management feasibility, with top-ranked species having multitrophic effects that favor other non-native invaders over native residents. Conditions within the assessment area required some modification to the protocol as it was originally designed, namely a shift in emphasis from eradication to control, given that eradication is implausible for most non-native species in the assessment area. We call attention to taxon-specific issues that surfaced during the analysis, identify areas for improvement in this first-ever risk assessment for invasive animal species in the Natural Communities Conservation Plan/Habitat Conservation Plan (NCCP/HCP) reserve system of San Diego County, and provide suggestions for further refinement of the protocol. This study builds on the effort to standardize risk analysis for invasive species globally, given that many of the same invaders present threats to indigenous biodiversity worldwide.
","language":"English","publisher":"Southern California Academy of Sciences","doi":"10.3160/0038-3872-122.2.101","usgsCitation":"Richmond, J.Q., Kingston, J., Ewing, B., Bear, W.M., Hathaway, S.A., Lee, C., Swift, C.C., Preston, K.L., Schultz, A.J., Kus, B., Russell, K., Unitt, P., Hollingsworth, B.D., Espinoza, R.E., Wall, M., Tremor, S., Palenscar, K., and Fisher, R., 2023, Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity: Bulletin, Southern California Academy of Sciences, v. 122, no. 2, p. 101-121, https://doi.org/10.3160/0038-3872-122.2.101.","productDescription":"21 p.","startPage":"101","endPage":"121","ipdsId":"IP-152994","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":419150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"San Diego 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0000-0002-4167-8059","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":206793,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Cedric","contributorId":316748,"corporation":false,"usgs":false,"family":"Lee","given":"Cedric","email":"","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schultz, Allison J.","contributorId":316750,"corporation":false,"usgs":false,"family":"Schultz","given":"Allison","email":"","middleInitial":"J.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":878242,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878243,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Russell, Kerwin","contributorId":297133,"corporation":false,"usgs":false,"family":"Russell","given":"Kerwin","email":"","affiliations":[{"id":64299,"text":"Riverside-Corona Resource Conservation District","active":true,"usgs":false}],"preferred":false,"id":878244,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Unitt, Philip","contributorId":316753,"corporation":false,"usgs":false,"family":"Unitt","given":"Philip","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878245,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hollingsworth, Bradford D.","contributorId":316755,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"Bradford","email":"","middleInitial":"D.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878246,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Espinoza, Robert E.","contributorId":316757,"corporation":false,"usgs":false,"family":"Espinoza","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":39477,"text":"California State University Northridge","active":true,"usgs":false}],"preferred":false,"id":878247,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wall, Michael","contributorId":316760,"corporation":false,"usgs":false,"family":"Wall","given":"Michael","email":"","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":878248,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tremor, Scott","contributorId":207768,"corporation":false,"usgs":false,"family":"Tremor","given":"Scott","email":"","affiliations":[{"id":37631,"text":"San Diego Natural History Museum, San Diego, California","active":true,"usgs":false}],"preferred":false,"id":878249,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Palenscar, Kai","contributorId":297131,"corporation":false,"usgs":false,"family":"Palenscar","given":"Kai","email":"","affiliations":[{"id":64298,"text":"San Bernardino Valley Municipal Water District","active":true,"usgs":false}],"preferred":false,"id":878250,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":878251,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70268264,"text":"70268264 - 2023 - Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam","interactions":[],"lastModifiedDate":"2025-06-18T14:21:46.788451","indexId":"70268264","displayToPublicDate":"2023-07-13T09:14:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39The extrusion tectonic model for the southeastern margin of the Himalayan orogeny links the crustal shear activity along the Red River Shear Zone (RRSZ) to the opening of the South China Sea (SCS). The Day Nui Con Voi (DNCV) metamorphic massif in northern Vietnam strikes NW-SE, is bounded by the RRSZ to the south and continues along the strike where it meets the SCS. The DNCV is thus a critical area to document thermotectonic history in order to advance our understanding of the tectonic evolution of Indochina extrusion and its relationship to the opening of the SCS. Our new 40Ar/39Ar data combined with microstructural and petrological analyses constrained the timing of the left-lateral shearing of the RRSZ and revealed the thermal evolution of the DNCV metamorphic massif. Three ductile deformation events were observed. D1 formed NNW-SSE striking upright folds under granulite to upper amphibolite facies conditions. D2 was a horizontal to sub-horizontal folding event that occurred at amphibolite facies conditions. D3 was a doming event that formed NW-SE striking up-right folds bounded by left-lateral shearing mylonite belts along the two limbs. The S/C fabrics were defined by muscovite fish, quartz + albite + K-feldspar aggregates, and muscovite folia. The D3 doming event exhumed the DNCV metamorphic massif from amphibolite facies conditions to the lower greenschist facies conditions. The 40Ar/39Ar ages obtained from amphibole (∼26 Ma), phlogopite (∼25 Ma), muscovites (∼24-23 Ma), biotite (∼25-23 Ma), and K-feldspars (∼25-22 Ma) from different structural domains of the DNCV metamorphic massif indicated a rapid exhumation ∼26–22 Ma. We interpreted this as the time period for the D3 event, with the onset of left-lateral shearing occurring around 24 Ma based on ages obtained from syn-kinematic muscovites. This age was much younger than the initiation of sea-floor spreading of the SCS (since 32 Ma) but coincided with the age for the ridge jump event in the SCS. Based on these new data, we proposed that extrusion tectonism cannot be the cause for the initial opening of the SCS. Rather, the extrusion of the Indochina block was temporally correlative with the southward ridge jump event of the already opened SCS.","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2023.1125279","usgsCitation":"Dinh, T., Yeh, M., Lee, T., Kunk, M., Wintsch, R., and McAleer, R.J., 2023, Extrusion tectonism of Indochina reassessed: constraints from 40Ar/39Ar geochronology from the Day Nui Con Voi metamorphic massif, Vietnam: Frontiers in Earth Science, v. 11, 1125279, 33 p., https://doi.org/10.3389/feart.2023.1125279.","productDescription":"1125279, 33 p.","ipdsId":"IP-149630","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":490983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1125279","text":"Publisher Index Page"},{"id":490907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Vietnam","otherGeospatial":"Day Nui Con Voi massif","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 104,\n 22.5\n ],\n [\n 104,\n 21\n ],\n [\n 106,\n 21\n ],\n [\n 106,\n 22.5\n ],\n [\n 104,\n 22.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Dinh, Thi-Hue","contributorId":306116,"corporation":false,"usgs":false,"family":"Dinh","given":"Thi-Hue","affiliations":[{"id":66371,"text":"Department of Earth Sciences, National Central University, Taoyuan City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeh, Meng-Wan","contributorId":306117,"corporation":false,"usgs":false,"family":"Yeh","given":"Meng-Wan","affiliations":[{"id":66372,"text":"Department of Earth Sciences, National Taiwan Normal University, Taipei City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Tung-Yi","contributorId":306118,"corporation":false,"usgs":false,"family":"Lee","given":"Tung-Yi","affiliations":[{"id":66372,"text":"Department of Earth Sciences, National Taiwan Normal University, Taipei City, Taiwan","active":true,"usgs":false}],"preferred":false,"id":940638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunk, Michael J. 0000-0003-4424-7825","orcid":"https://orcid.org/0000-0003-4424-7825","contributorId":291942,"corporation":false,"usgs":false,"family":"Kunk","given":"Michael J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":940639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wintsch, Robert P.","contributorId":148989,"corporation":false,"usgs":false,"family":"Wintsch","given":"Robert P.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":940640,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":940641,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248941,"text":"70248941 - 2023 - Impacts of a Cascadia subduction zone earthquake on water levels and wetlands of the lower Columbia River and Estuary","interactions":[],"lastModifiedDate":"2023-09-27T12:07:10.761375","indexId":"70248941","displayToPublicDate":"2023-07-13T07:05:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of a Cascadia subduction zone earthquake on water levels and wetlands of the lower Columbia River and Estuary","docAbstract":"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.
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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Wildlife Diseases","indexId":"tm15","publicationYear":"2015","noYear":false,"title":"Field Manual of Wildlife Diseases"},"lastModifiedDate":"2023-07-11T16:22:57.262049","indexId":"tm15E1","displayToPublicDate":"2023-07-11T11:09:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"15-E1","displayTitle":"White-Nose Syndrome Diagnostic Laboratory Network Handbook","title":"White-Nose Syndrome Diagnostic Laboratory Network handbook","docAbstract":"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
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