Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (>300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm−2 and mean Shannon-Wiener diversity per rock (H′[loge]) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.18290","usgsCitation":"Guraieb, M., Mendoza, G., Mizell, K., Rouse, G.W., McCarthy, R., Pereira, O.S., and Levin, L.A., 2024, Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland: PeerJ, v. 12, e18290, 33 p., https://doi.org/10.7717/peerj.18290.","productDescription":"e18290, 33 p.","ipdsId":"IP-166431","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466792,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.18290","text":"Publisher Index Page"},{"id":463531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern California Borderlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5,\n 34\n ],\n [\n -121.5,\n 31.5\n ],\n [\n -117,\n 31.5\n ],\n [\n -117,\n 34\n ],\n [\n -121.5,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Guraieb, Michelle","contributorId":345846,"corporation":false,"usgs":false,"family":"Guraieb","given":"Michelle","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Guillermo F","contributorId":156382,"corporation":false,"usgs":false,"family":"Mendoza","given":"Guillermo F","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":917696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouse, Gregory W.","contributorId":345848,"corporation":false,"usgs":false,"family":"Rouse","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarthy, R.A.","contributorId":345849,"corporation":false,"usgs":false,"family":"McCarthy","given":"R.A.","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pereira, Olivia S.","contributorId":340132,"corporation":false,"usgs":false,"family":"Pereira","given":"Olivia","email":"","middleInitial":"S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Levin, Lisa A.","contributorId":330607,"corporation":false,"usgs":false,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917701,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70260810,"text":"70260810 - 2024 - Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing","interactions":[],"lastModifiedDate":"2024-12-10T15:33:45.478559","indexId":"70260810","displayToPublicDate":"2024-10-31T06:56:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing","docAbstract":"Many freshwater forested wetlands along the southeastern United States coastline are rapidly transitioning from forest to marsh or open water, due to climate change-related disturbances. Recent studies have found early warning signals (EWS) of regime shifts in other ecosystems, but it is unclear if these can be detected for coastal wetlands. In this study, we examined the ability to detect EWS of regime shifts in coastal wetlands within the Albemarle Pamlico peninsula (APP), North Carolina, U.S.A. We used the Landsat record (1985–2021) to examine trends of normalized difference vegetation index (NDVI) time series for selected areas known to have undergone regime shifts. We found that while 77% of the APP was either stable or revegetating, 22% of the landscape underwent a decrease in NDVI that would indicate a transition from forest to marsh or open water. Of the areas that transitioned, about half (11%) experienced an abrupt decrease in NDVI and 10% experienced a gradual decline. Increasing standard deviation and skewness of time series could serve as EWS of abrupt transitions, but can also provide false negative and positives. Our results suggest that ecosystem transitions from a forest to a marsh or open water can occur both rapidly and slowly, and remote sensing of NDVI time series can help identify EWS for some areas, but not all. Our results allow for prioritization of conservation/restoration of coastlines which will become important in the face of climate change and sea level rise.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-024-00938-5","usgsCitation":"Martinez, M., Ardon, M.L., and Gray, J., 2024, Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing: Ecosystems, v. 27, p. 1060-1075, https://doi.org/10.1007/s10021-024-00938-5.","productDescription":"16 p.","startPage":"1060","endPage":"1075","ipdsId":"IP-133828","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":463847,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Albemarle Pamlico Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.63541246515713,\n 36.06271479689754\n ],\n [\n -77.19335586830498,\n 36.06271479689754\n ],\n [\n -77.19335586830498,\n 35.278844140439915\n ],\n [\n -75.63541246515713,\n 35.278844140439915\n ],\n [\n -75.63541246515713,\n 36.06271479689754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2024-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Melinda 0000-0001-6652-9220","orcid":"https://orcid.org/0000-0001-6652-9220","contributorId":290467,"corporation":false,"usgs":true,"family":"Martinez","given":"Melinda","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ardon, Marcelo L","contributorId":346120,"corporation":false,"usgs":false,"family":"Ardon","given":"Marcelo","email":"","middleInitial":"L","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":918160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Joshua","contributorId":346121,"corporation":false,"usgs":false,"family":"Gray","given":"Joshua","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":918161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260817,"text":"70260817 - 2024 - Early detection of wildlife disease pathogens using CRISPR-Cas system methods","interactions":[],"lastModifiedDate":"2024-12-26T16:53:43.313328","indexId":"70260817","displayToPublicDate":"2024-10-31T06:41:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19828,"text":"The CRISPR Journal","active":true,"publicationSubtype":{"id":10}},"title":"Early detection of wildlife disease pathogens using CRISPR-Cas system methods","docAbstract":"Wildlife diseases are a considerable threat to human health, conservation, and the economy. Surveillance is a critical component to mitigate the impact of animal diseases in these sectors. To monitor human diseases, CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated protein) biosensors have proven instrumental as diagnostic tools capable of detecting unique DNA and RNA sequences related to their associated pathogens. However, despite the significant advances in the general development of CRISPR-Cas biosensors, their use to support wildlife disease management is lagging. In some cases, wildlife diseases of concern could be rapidly surveyed using these tools with minimal technical, operational, or cost requirements to end users. This review explores the potential to further leverage this technology to advance wildlife disease monitoring and highlights how concerted standardization of protocols can help to ensure data reliability.","language":"English","publisher":"Mary Ann Liebert, Inc.","doi":"10.1089/crispr.2024.0030","usgsCitation":"Perez, A.A., Vazquez-Meves, G., and Hunter, M., 2024, Early detection of wildlife disease pathogens using CRISPR-Cas system methods: The CRISPR Journal, v. 7, no. 6, p. 327-342, https://doi.org/10.1089/crispr.2024.0030.","productDescription":"16 p.","startPage":"327","endPage":"342","ipdsId":"IP-162277","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":498262,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/crispr.2024.0030","text":"Publisher Index Page"},{"id":463845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perez, Adam Alberto 0000-0001-5057-1133","orcid":"https://orcid.org/0000-0001-5057-1133","contributorId":332516,"corporation":false,"usgs":true,"family":"Perez","given":"Adam","email":"","middleInitial":"Alberto","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez-Meves, Guelaguetza 0000-0001-8100-2945","orcid":"https://orcid.org/0000-0001-8100-2945","contributorId":346127,"corporation":false,"usgs":true,"family":"Vazquez-Meves","given":"Guelaguetza","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":918206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207584,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918207,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259877,"text":"ofr20241055 - 2024 - Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","interactions":[],"lastModifiedDate":"2025-12-22T20:25:53.918489","indexId":"ofr20241055","displayToPublicDate":"2024-10-30T13:10:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1055","displayTitle":"Sand Supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","title":"Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","docAbstract":"Sediment from the Central Valley via the Sacramento-San Joaquin Delta (Delta) and Suisun Bay is a primary source of sand to San Francisco Bay, California. Sand is mined from San Francisco Bay for commercial purposes, such as for use in concrete for construction. To better understand the supply of sand to Suisun Bay and San Francisco Bay, the U.S. Geological Survey (USGS), in cooperation with the San Francisco Bay Estuary Institute (SFEI) and the San Francisco Bay Conservation Development Commission (BCDC), initiated this study to compile and synthesize historical data and estimate the total sediment and sand portion of sediment exiting the Delta to Suisun Bay for a 20-year period between water years 2001 and 2020.
Sediment exiting the Delta is a combination of suspended sediment and bedload sediment. Seaward bedload transport was estimated using bedload transport equations and available hydraulic data at the two downstream-most streamgages in the Delta (where velocity is measured). Those two streamgages are about 25 kilometers upstream from the “exit” of the Delta at Mallard Island. The combined average annual net (seaward) bedload at these two streamgages was estimated to be 0.102 million cubic meters per year (Mm3/yr) for the study period. This volume of bedload is equivalent to 0.155 million metric tons per year (Mt/yr), assuming a bulk density of 1.517 metric tons per cubic meter (t/m3). The bedload composition was estimated to be 88 percent sand.
Between the two streamgages and Mallard Island, an annual average of 0.076 Mm3/yr of material was removed through mining during the study period, of which 97.5 percent was sand. In addition, 0.053 Mm3/yr was removed through dredging to support shipping and navigation, of which 76 percent was sand. The total volume of mined and dredged sediment material was approximately 0.128 Mm3/yr, equivalent to 0.194 Mt/yr, assuming a bulk density of 1.517 t/m3.
Assuming the estimated bedload reaching Mallard Island was reduced by mining and dredging, a mean bedload flux of −0.009 Mm3/yr was computed (using a bulk density of 1.517 t/m3), suggesting a deficit or landward transport of bedload. However, the total suspended-sediment and suspended-sand flux was in the seaward direction. The average total suspended flux of sediment to Suisun Bay through the cross section at the Mallard Island streamgage was estimated to be 0.482 million metric tons per year (Mt/yr; 0.015 Mt/yr sand) in the seaward direction. The results indicate a net flux out of the Delta of 0.469 Mt/yr of total sediment and 0.003 Mt/yr of sand.
The primary limitation of the study was the lack of physical bedload measurements to validate the bedload estimates. To better refine the estimates of bedload, physical measurements of bedload or repeat bathymetry would be necessary for a range of flow conditions. Such measurements could be used to calibrate transport equations and quantify the uncertainty in such estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241055","collaboration":"Prepared in cooperation with the San Francisco Estuary Institute Aquatic Science Center, the California State Coastal Conservancy, and the San Francisco Bay Conservation and Development Commission","programNote":"Water Availability and Use Science Program","usgsCitation":"Marineau, M.D., Hart, D., Ely, C.P., and McKee, L., 2024, Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California: U.S. Geological Survey Open-File Report 2024–1055, 18 p., https://doi.org/10.3133/ofr20241055.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-157560","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":463205,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1055/images"},{"id":463204,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.xml"},{"id":463203,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463201,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I18RGG","text":"USGS Data Release","description":"Ely, C.P., and Marineau, M.D., 2023, Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9I18RGG.","linkHelpText":"Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020"},{"id":497888,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117739.htm","linkFileType":{"id":5,"text":"html"}},{"id":463206,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20241055/full"},{"id":463202,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1055/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.29538442038356,\n 38.56577858557708\n ],\n [\n -122.29538442038356,\n 37.65383277017135\n ],\n [\n -121.19683028697757,\n 37.65383277017135\n ],\n [\n -121.19683028697757,\n 38.56577858557708\n ],\n [\n -122.29538442038356,\n 38.56577858557708\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Riparian ecosystems are some of the most valuable and vulnerable on the planet. Riparian tree mortality is increasing in the western United States, where altered streamflows are combining with warming climate. Between 2011 and 2013, one third of an extensive stand of Populus deltoides var. wislizeni (Rio Grande cottonwood) died along the middle Rio Grande on the Pueblo of Santa Ana in New Mexico. Mortality coincided with a severe drought that followed a decade of decreasing streamflow, but it was heterogeneous, with adjacent patches of dead and live trees. The goal of this research was to determine the drivers of mortality to provide insights into future risks of die-off and potential management interventions. We compared tree age, competition, tree-ring widths, sediment particle size and climate influences between live and dead forest patches in a nested plot design. Live and dead trees had similar age, stand density and particle sizes of shallow sediments. Tree-ring widths had the highest correlations with July–September streamflow (1932–2013). All trees had declining ring growth since 1992, coinciding with declining late summer streamflow. An accelerated decline in growth began in 2002, corresponding to recent warmer droughts. Trees that died had lower ring growth 3 years prior to death and in the mid-1900s. Dead trees also had coarser deep sediments 2.4–3.7 m below ground, suggesting that reduced water holding capacity was an important factor for mortality. Water management to increase streamflow during the late summer, especially during times of extended drought, could reduce mortality risk in the face of projected increasingly warm droughts.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.2692","usgsCitation":"Varani, H., Margolis, E.Q., Muldavin, E., and Pockman, W.T., 2024, Patterns and drivers of cottonwood mortality in the middle Rio Grande, New Mexico, USA: Ecohydrology, v. 17, no. 8, e2692, 13 p., https://doi.org/10.1002/eco.2692.","productDescription":"e2692, 13 p.","ipdsId":"IP-164113","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":466793,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eco.2692","text":"External Repository"},{"id":465568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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2007–22","interactions":[],"lastModifiedDate":"2025-12-22T20:23:35.597848","indexId":"sir20245097","displayToPublicDate":"2024-10-30T10:46:09","publicationYear":"2024","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":"2024-5097","displayTitle":"Use of Continuous Water-Quality Time-Series Data to Compute Total Phosphorus Concentrations and Loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","title":"Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","docAbstract":"In support of Missouri’s Nutrient Loss Reduction Strategy, which was created to reduce the nutrient contamination of Missouri’s waterways from point and nonpoint sources, total phosphorus concentrations and loads were computed for the Missouri River at St. Joseph, Missouri, streamgage (U.S. Geological Survey station 06818000) and the Missouri River at Hermann, Mo., streamgage (U.S. Geological Survey station 06934500) for October 2007 to September 2022 using surrogate models and continuous turbidity sensor data. To obtain a more complete total phosphorus record for the study period, LOAD ESTimator (LOADEST) regression models using flow were used when turbidity sensor data were unavailable to estimate daily total phosphorus loads. This report presents the methods and results for the computed total phosphorus concentrations, loads, and yields for the two study sites on the Missouri River. With continued data collection and ongoing model evaluation and maintenance, the surrogate models may be useful into the future for computing total phosphorus concentrations and loads.
Daily mean total phosphorus concentrations calculated using a surrogate model at the Missouri River at St. Joseph, Mo., streamgage during the 15-year study period (water years 2008 through 2022) ranged from 0.104 to 4.56 milligrams per liter (mg/L; median of 0.272 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 5.19 to 1,760 tons per day (tons/d; median of 36.5 tons/d). Annual loads ranged from 9,570 tons in water year 2022 to 50,500 tons in water year 2019. The total load for the study period was 437,000 tons.
For the Missouri River at Hermann, Mo., streamgage during the same 15-year study period, daily mean total phosphorus concentrations, calculated using surrogate models applied to low and high turbidity values, ranged from 0.183 to 1.97 mg/L (median of 0.319 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 12.7 to 1,970 tons/d (median of 76.8 tons/d). Annual loads ranged from 22,600 tons in water year 2022 to 101,000 tons in water year 2019. The total load for the study period was 833,000 tons, which is nearly twice that at the Missouri River at St. Joseph, Mo., streamgage.
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400 South Clinton Street, Suite 269
Iowa City, IA 52240
We implemented concepts of field geology at great ocean depths by constructing virtual outcrops from a string of overlapping video frames collected by remotely operated vehicles (ROVs). This lower-cost alternative to drilling boreholes allows stratigraphic extension into the offshore and regional interpretation of marine seismic profiles. The imagery was collected along a dive transect on the western wall of Mona Rift, a deep and narrow rift northwest of Puerto Rico, between water depths of 1560 m and 3927 m. The northern coast of Puerto Rico and its large offshore area are underlain by a mid-Eocene and younger forearc basin topped by a thick carbonate platform. There are no drill holes offshore, and tying seismic lines across the shoreline there is problematic. We describe our virtual outcrop and constrain its age and stratigraphy using seven rock samples collected by ROV and compare the outcrop's stratigraphy to deep boreholes and outcrops on land. Our formation descriptions and ages agree, for the most part, with those on land, but we identified a 100-m-thick section that is represented on land by an unconformity. Our stratigraphic interpretation indicates lateral variations in formation thicknesses and establishes a cross-section for additional sampling of the Eocene–Pliocene geology. It also suggests that Mona Rift has formed since the mid-Pliocene. The presence or absence of ferromanganese (Fe-Mn) crust on rocks along the transect may be correlated with the smoothness of the rock surface.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02762.1","usgsCitation":"ten Brink, U.S., Bialik, O.M., Chaytor, J., Flores, C., and Purkey Phillips, M., 2024, Field geology under the sea with a remotely operated vehicle: Mona Rift, Puerto Rico: Geosphere, v. 20, no. 6, p. 1575-1597, https://doi.org/10.1130/GES02762.1.","productDescription":"23 p.","startPage":"1575","endPage":"1597","ipdsId":"IP-163240","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466794,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02762.1","text":"Publisher Index Page"},{"id":465282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mona Rift, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.6333,\n 18.8333\n ],\n [\n -67.6333,\n 18.6833\n ],\n [\n -67.4583,\n 18.6833\n ],\n [\n -67.4583,\n 18.8333\n ],\n [\n -67.6333,\n 18.8333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bialik, Or M.","contributorId":347344,"corporation":false,"usgs":false,"family":"Bialik","given":"Or","email":"","middleInitial":"M.","affiliations":[{"id":25445,"text":"University of Münster","active":true,"usgs":false}],"preferred":false,"id":921436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":921437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flores, Claudia 0000-0003-0676-7061 cflores@usgs.gov","orcid":"https://orcid.org/0000-0003-0676-7061","contributorId":304396,"corporation":false,"usgs":true,"family":"Flores","given":"Claudia","email":"cflores@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purkey Phillips, Marcie","contributorId":346790,"corporation":false,"usgs":false,"family":"Purkey Phillips","given":"Marcie","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":921439,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262024,"text":"70262024 - 2024 - Penguin colony georegistration using camera pose estimation and phototourism","interactions":[],"lastModifiedDate":"2025-01-10T16:30:20.637582","indexId":"70262024","displayToPublicDate":"2024-10-30T10:26:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Penguin colony georegistration using camera pose estimation and phototourism","docAbstract":"Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location. Here we demonstrate the use of phototourism in an application involving Antarctic penguins, sentinel species whose dynamics are closely tracked as a measure of ecosystem functioning, and introduce a semi-automated pipeline for aligning and registering ground photographs using a digital elevation model (DEM) and satellite imagery. We employ the Segment Anything Model (SAM) for the interactive identification and segmentation of penguin colonies in these photographs. By creating a textured 3D mesh from the DEM and satellite imagery, we estimate camera poses to align ground photographs with the mesh and register the segmented penguin colony area to the mesh, achieving a detailed representation of the colony. Our approach has demonstrated promising performance, though challenges persist due to variations in image quality and the dynamic nature of natural landscapes. Nevertheless, our method offers a straightforward and effective tool for the georegistration of ad-hoc photographs in natural landscapes, with additional applications such as monitoring glacial retreat.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0311038","usgsCitation":"Wu, H., Flynn, C., Hall, C., Che-Castaldo, C., Samaras, D., Schwaller, M., and Lynch, H., 2024, Penguin colony georegistration using camera pose estimation and phototourism: PLoS ONE, v. 19, no. 10, e0311038, 18 p., https://doi.org/10.1371/journal.pone.0311038.","productDescription":"e0311038, 18 p.","ipdsId":"IP-160209","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0311038","text":"Publisher Index Page"},{"id":465996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Haoyu","contributorId":347903,"corporation":false,"usgs":false,"family":"Wu","given":"Haoyu","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Clare","contributorId":347904,"corporation":false,"usgs":false,"family":"Flynn","given":"Clare","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Carole","contributorId":347905,"corporation":false,"usgs":false,"family":"Hall","given":"Carole","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Samaras, Dimitris","contributorId":347907,"corporation":false,"usgs":false,"family":"Samaras","given":"Dimitris","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwaller, Mathew","contributorId":347909,"corporation":false,"usgs":false,"family":"Schwaller","given":"Mathew","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259868,"text":"fs20243034 - 2024 - Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023","interactions":[],"lastModifiedDate":"2025-12-22T20:21:53.699711","indexId":"fs20243034","displayToPublicDate":"2024-10-30T09:45:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3034","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in the Norphlet Formation, U.S. Gulf Coast Region, 2023","title":"Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey (USGS) estimated undiscovered, technically recoverable mean resources of 16 million barrels of oil and 348 billion cubic feet of gas in conventional reservoirs of the Norphlet Formation in the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243034","programNote":"National and Global Petroleum Assessment","usgsCitation":"Counts, J.W., Craddock, W.H., Gooley, J.T., Buursink, M., Mercier, T.J., Woodall, C.A., and Schenk, C.J., 2024, Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023: U.S. Geological Survey Fact Sheet 2024–3034, 4 p., https://doi.org/10.3133/fs20243034.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-157745","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":463490,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243034/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3034"},{"id":463435,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3034/fs20243034.xml"},{"id":463434,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3034/images"},{"id":463200,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3034/fs20243034.pdf","text":"Report","size":"1.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3034"},{"id":463207,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P132OJPA","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Norphlet Formation: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":463199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3034/coverthb.jpg"},{"id":497885,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117741.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Florida, Mississippi","otherGeospatial":"Norphlet Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.11177492185513,\n 34.53401166961133\n ],\n [\n -91.11177492185513,\n 29.73879554891593\n ],\n [\n -85.30780523167681,\n 29.73879554891593\n ],\n [\n -85.30780523167681,\n 34.53401166961133\n ],\n [\n -91.11177492185513,\n 34.53401166961133\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geology, Energy & Minerals Science Center
U.S. Geological Survey
956 National Center
Reston, VA 20192
Oxbow lakes are highly productive waterbodies that host multiple life stages of many freshwater aquatic species. These lakes also provide foraging and rearing habitat to the invasive silver carp (Hypophthalmichthys molitrix) enabling populations to grow in biomass and abundance that can add propagule pressure to connected waterways and oxbows within the Mississippi River Basin. Ecologically these fish are undesirable because they overlap in diet and may compete for resources with native fishes and negatively impact recreational fisheries. Our goal was to evaluate silver carp distribution patterns in a major Mississippi River oxbow lake to inform removal programs and precision harvesting. We implanted 35 adult silver carp with acoustic tags and released them into the lake. Periodic tracking over 365 d revealed that fish were predominantly found in lake areas with water depths ranging from 2.0 to 5.9 m during all seasons, despite the availability of shallower and deeper water. Silver carp tended to aggregate in the wintertime (December–February) relative to other seasons. This information about lake area uses and seasonal aggregations could inform removal efforts in invaded waterbodies by exploiting natural behavioral and temporal vulnerabilities of this highly invasive and difficult-to-capture fish.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2024.15.4.03","usgsCitation":"Besson, J., Miranda, L.E., Colvin, M.E., Dunn, C.G., and Riecke, D., 2024, Spatial distribution patterns of invasive silver carp can inform removal efforts in an oxbow lake of the Mississippi River: Management of Biological Invasions, v. 15, no. 4, p. 505-518, https://doi.org/10.3391/mbi.2024.15.4.03.","productDescription":"14 p.","startPage":"505","endPage":"518","ipdsId":"IP-161587","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2024.15.4.03","text":"Publisher Index Page"},{"id":480994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Moon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.56421475590851,\n 34.466966058199986\n ],\n [\n -90.56421475590851,\n 34.393119426569285\n ],\n [\n -90.49028391694011,\n 34.393119426569285\n ],\n [\n -90.49028391694011,\n 34.466966058199986\n ],\n [\n -90.56421475590851,\n 34.466966058199986\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Besson, Jordan C.","contributorId":349791,"corporation":false,"usgs":false,"family":"Besson","given":"Jordan C.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":924815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":924817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riecke, Dennis K.","contributorId":349837,"corporation":false,"usgs":false,"family":"Riecke","given":"Dennis K.","affiliations":[],"preferred":false,"id":924911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","interactions":[{"subject":{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261121","publicationYear":"2024","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"predicate":"SUPERSEDED_BY","object":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"id":1}],"supersededBy":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"lastModifiedDate":"2025-01-27T17:18:30.964189","indexId":"70261121","displayToPublicDate":"2024-10-30T08:30:41","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19836,"text":"Authorea","active":true,"publicationSubtype":{"id":32}},"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","docAbstract":"The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.","language":"English","publisher":"Authorea","doi":"10.22541/au.173030440.00154170/v1","usgsCitation":"Hardy, M., Williams, C.K., Ladman, B.S., Pitesky, M.E., Overton, C.T., Casazza, M.L., Matchett, E., Prosser, D.J., and Buler, J.J., 2024, Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways: Authorea, https://doi.org/10.22541/au.173030440.00154170/v1.","productDescription":"51 p.","ipdsId":"IP-172616","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466797,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":466796,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":464459,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hardy, Matthew J.","contributorId":343392,"corporation":false,"usgs":false,"family":"Hardy","given":"Matthew J.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":919360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Christopher K.","contributorId":202263,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":919361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":919362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":919363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919366,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":919367,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":919368,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260933,"text":"70260933 - 2024 - Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","interactions":[],"lastModifiedDate":"2024-11-15T14:33:52.68755","indexId":"70260933","displayToPublicDate":"2024-10-30T08:26:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","docAbstract":"One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.
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Indices of benthic macroinvertebrate integrity have declined in urban areas across the Chesapeake Bay watershed (CBW), and more information is needed about whether these declines may be due to elevated conductivity. A predictive SC model for the CBW was developed using monitoring data from the National Water Quality Portal. Predictor variables representing SC sources were compiled for nontidal reaches across the CBW. Random forests modeling was conducted to predict SC at four time periods (1999–2001, 2004–2006, 2009–2011, and 2014–2016), which were then compared to a national data set of background SC to quantify departures from background SC. Carbonate geology, impervious cover, forest cover, and snow depth were the most important variables for predicting SC. Observations and modeled results showed snow depth amplified the effect of impervious cover on SC. Elevated SC was predicted in two-thirds of reaches in the CBW, and these elevated conditions persisted over time in many areas. These results can be used in stressor identification assessments to prioritize future monitoring and to determine where management activities could be implemented to reduce salinization.
The lack of consolidated information regarding the response of wild bird species to infection with avian influenza virus (AIV) is a challenge to both conservation managers and researchers alike, with related sectors also impacted, such as public health and commercial poultry. Using two independent searches, we reviewed published literature for studies describing wild bird species experimentally infected with avian influenza to assess host species’ relative susceptibility to AIVs. Additionally, we summarize broad-scale parameters for elements such as shedding duration and minimum infectious dose that can be used in transmission modelling efforts. Our synthesis shows that waterfowl (i.e. Anatidae) compose the vast majority of published AIV pathobiology studies, whereas gulls and passerines are less represented in research despite evidence that they also are susceptible and contribute to highly pathogenic avian influenza disease dynamics. This study represents the first comprehensive effort to compile available literature regarding the pathobiology of AIVs in all wild birds in over a decade. This database can now serve as a tool to all researchers, providing generalized estimates of pathobiology parameters for a variety of wild avian families and an opportunity to critically examine and assess what is known and identify where further insight is needed.
Dryland restoration requires plant materials capable of performing well despite difficult growing conditions. Selecting plant materials with higher intraspecific trait variability (ITV) may support successful outcomes by enhancing the performance of those materials in restoration settings. However, maintaining ITV from wild populations is not well understood and requires further investigation if ITV is to be incorporated into native plant materials, which are often developed from wild-collected seed grown in agricultural settings. We used two perennial plant species to explore whether (1) ITV measured at field sites predicts ITV in a common garden, (2) rankings of ITV among populations remain stable over time, and (3) higher levels of ITV promote survival and reproductive effort in a common garden. We measured ITV in specific leaf area and height for Bouteloua curtipendula and Heterotheca villosa at field sites and over 2 years in a common garden, as well as survival and flower production in the common garden. We also calculated climate distance between field sites, where seeds were originally sourced, and the common garden to account for the impact of climatic differences on ITV. We found that (1) ITV measured at field sites did not predict ITV in the common garden, (2) rankings of ITV across populations were inconsistent, and (3) relationships between ITV and performance were rare and differed by species. Our findings indicate that the utility of ITV in wild populations as a predictive tool may be limited.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.14322","usgsCitation":"Samuel, E.M., Mitchell, R., Winkler, D.E., Davidson, Z.M., Lencioni, S.J., and Massatti, R., 2024, Intraspecific trait variability in wild populations predicts neither variability nor performance in a common garden: Restoration Ecology, e14322, 11 p., https://doi.org/10.1111/rec.14322.","productDescription":"e14322, 11 p.","ipdsId":"IP-164808","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":466801,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.14322","text":"Publisher Index Page"},{"id":463786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Samuel, Ella M.","contributorId":346114,"corporation":false,"usgs":false,"family":"Samuel","given":"Ella","email":"","middleInitial":"M.","affiliations":[{"id":82776,"text":"School of Earth and Sustainability, Northern Arizona University, 624 S. Knoles Dr, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":918135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Rachel M.","contributorId":300516,"corporation":false,"usgs":false,"family":"Mitchell","given":"Rachel M.","affiliations":[{"id":65185,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":918136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davidson, Zoe M.","contributorId":346115,"corporation":false,"usgs":false,"family":"Davidson","given":"Zoe","email":"","middleInitial":"M.","affiliations":[{"id":82777,"text":"Bureau of Land Management New Mexico State Office, 301 Dinosaur Trail, Santa Fe, NM 87508","active":true,"usgs":false}],"preferred":false,"id":918138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lencioni, Shannon Joy 0000-0002-7267-7585","orcid":"https://orcid.org/0000-0002-7267-7585","contributorId":346116,"corporation":false,"usgs":true,"family":"Lencioni","given":"Shannon","email":"","middleInitial":"Joy","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Massatti, Robert","contributorId":219513,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70268261,"text":"70268261 - 2024 - Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series","interactions":[],"lastModifiedDate":"2025-06-18T15:03:04.772207","indexId":"70268261","displayToPublicDate":"2024-10-30T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series","docAbstract":"Ponds are an important source of greenhouse gases (GHGs) to the atmosphere, yet evaluating their role in global biogeochemical cycling is currently hampered by limitations in quantifying their global distribution. Existing satellite-derived estimates of lake distributions have difficulty identifying small lakes (5–10 ha) and ponds (<5 ha) due to limitations in satellite resolution and challenges extracting individual small waterbodies from low-albedo surfaces, vegetated water, and lotic water systems including rivers and streams. In this study, we developed generalizable pond mapping strategies based on their spatial-temporal-spectral characteristics to fully exploit accessible medium-resolution optical and synthetic aperture radar (SAR) time series to identify ponds. Our novel approach entails: (1) making full use of ponds' characteristics from an object-based perspective; (2) extracting pond objects using seeds of prominent water pixels defined by the SAR VH signal; (3) constructing training samples of ponds with high representativeness; and (4) improving inter-class discrimination by combining features from optical and SAR data. We designed a novel Optical-SAR Pond Object Mapper (OptiSAR-POM) to achieve an improved estimate of pond size distribution by incorporating mapping strategies into the object-based image analysis framework. We generated landscape objects through an elaborate water-focused segmentation approach, which adaptively aligned the segmentation parameters with the size and distribution patterns of ponds to identify small waterbodies and increase inter-class variability. We further introduced an interactive learning process to construct random forests for object-based classification, which incorporated adaptive empirical thresholds to identify potential pond objects and select representative training samples of varying sizes. We tested the OptiSAR-POM framework using Sentinel-1/2 time series at three county-level study sites and three supplementary watershed-level study sites in the United States and China. Our approach yielded high overall accuracy (>95 %) for all sites and highlighted the ability of Sentinel-1/2 imagery to accurately detect small ponds (0.1–1 ha) across diverse landscapes. The average producer's accuracy for small ponds at county-level sites improved by ∼45 % compared to that of all other products with a 10-m or higher spatial resolution, addressing the absence of such information in existing regional and global datasets. The generated county-level pond maps revealed the numerical dominance of ponds in lentic waters, their substantial area contribution in human-impacted regions, and the relevance of studying biogeochemical processes in smaller waterbodies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2024.114484","usgsCitation":"Liu, D., Zhu, X., Holgerson, M., Bansal, S., and Xu, X., 2024, Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series: Remote Sensing of Environment, v. 315, 114484, 21 p., https://doi.org/10.1016/j.rse.2024.114484.","productDescription":"114484, 21 p.","ipdsId":"IP-167730","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":490911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Denghong","contributorId":357052,"corporation":false,"usgs":false,"family":"Liu","given":"Denghong","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Xioalin","contributorId":357055,"corporation":false,"usgs":false,"family":"Zhu","given":"Xioalin","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holgerson, Meredith","contributorId":218790,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":940633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Xiangtao","contributorId":348758,"corporation":false,"usgs":false,"family":"Xu","given":"Xiangtao","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259581,"text":"fs20243029 - 2024 - Developments in African industrial minerals for renewable energy","interactions":[],"lastModifiedDate":"2024-10-30T21:16:35.700196","indexId":"fs20243029","displayToPublicDate":"2024-10-29T13:20:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3029","displayTitle":"Developments in African Industrial Minerals for Renewable Energy","title":"Developments in African industrial minerals for renewable energy","docAbstract":"Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026.
Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243029","usgsCitation":"Yager, T., 2024, Developments in African industrial minerals for renewable energy: U.S. Geological Survey Fact Sheet 2024–3029, 6 p., https://doi.org/10.3133/fs20243029","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153789","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":463121,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243029/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3029 HTML"},{"id":463122,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.XML","description":"FS 2024-3029 XML"},{"id":463123,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3029/images"},{"id":462885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3029/coverthb2.jpg"},{"id":462886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3029 PDF"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -23.381408491331456,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n 38.850454189324125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"National Minerals Information Center
U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
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Email: nmicrecordsmgt@usgs.gov
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American raptors, songbirds, and other small avian species. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on avian species, and measures to reduce noise emissions. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. The effects of human-caused noise on songbirds are well researched, whereas, among raptors, only owl species have been well-studied in relation to noise. Several studies have established that noise can reduce owl hunting success because many owl species are heavily reliant on hearing prey when hunting. The effects of noise on songbirds depend on several factors. Typically, birds that rely on vocal communication for mating, predator detection, and spatial orientation, and that are less able to adjust the frequencies of their vocalizations, are more vulnerable to behavioral changes and decreased fitness in noisy areas. Techniques suggested in the literature for reducing noise emissions include artificial sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference to find literature or identify gaps in the literature about the effects of noise from oil and gas development on raptors and songbirds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245087","programNote":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Maxwell, L.M., Rutherford, T.K., Kleist, N.J., Teige, E.C., Lehrter, R.J., Gilbert, M.A., Wood, D.J.A., Johnston, A.N., Tull, J.C., Haby, T.S., and Carter, S.K., 2024, Effects of noise from oil and gas development on raptors and songbirds—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2024–5087, 66 p., https://doi.org/10.3133/sir20245087.","productDescription":"xi, 99 p.","onlineOnly":"Y","ipdsId":"IP-154746","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":463505,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5087"},{"id":463364,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.xml"},{"id":463363,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5087/images"},{"id":463212,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463211,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463210,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"},{"id":463209,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5087"},{"id":463208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5087/coverthb.jpg"},{"id":497884,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117742.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
We present 230Th-238U crystallization ages and trace element compositions for zircons spanning the late Pleistocene to Holocene rhyolite eruptive record at South Sister volcano in the central Oregon Cascade Range. Most zircon ages are between 100 and 20 ka, with very few in secular equilibrium (>350 ka). The weighted mean of zircon ages for the two oldest South Sister rhyolites, 31.5 ± 2.1 and 39.1 ± 2.4 ka, are significantly younger than the associated 40Ar/39Ar ages, 47.4 ± 9.7 and 51.4 ± 9.7 ka. We propose that these 40Ar/39Ar dates, performed on plagioclase separates, are compromised by a subtle amount of excess Ar and therefore the younger weighted mean zircon ages yield more reliable eruption ages. These results imply that the interval of rhyolite eruption at South Sister during the late Pleistocene was both shorter and more productive than previously thought and that eruption at South Sister initiated after Middle Sister. Compositionally, zircons from the Pleistocene rhyolites are broadly similar and show down-temperature zircon and plagioclase crystallization trends. However, we argue that destabilized amphibole and titanite in a common mush also exert leverage on the Pleistocene zircon trace element compositions. Divergence in the Eu/Eu* ratio between the Pleistocene and Holocene lavas implies chemically distinct magma reservoirs originating from the Pleistocene rhyolite eruptive sequence and the Holocene eruptive sequence. This work suggests a higher flux of rhyolite volcanism than previously thought and characterizes magmatic storage distinctions between the Pleistocene and Holocene rhyolites, aiding in the assessment of future eruptive hazards at South Sister volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GC011680","usgsCitation":"Dechert, A.E., Andersen, N.L., Dufek, J., and Jilly-Rehak, C.E., 2024, Zircon constraints on the eruptive sequence and magma evolution of rhyolites at South Sister volcano, Oregon: Geochemistry, Geophysics, Geosystems, v. 25, no. 8, e2024GC011680, 16 p., https://doi.org/10.1029/2024GC011680.","productDescription":"e2024GC011680, 16 p.","ipdsId":"IP-166341","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gc011680","text":"Publisher Index Page"},{"id":463333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"South Sister Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.4687761419247,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 44.8843098669841\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Dechert, Annika E.","contributorId":345692,"corporation":false,"usgs":false,"family":"Dechert","given":"Annika","email":"","middleInitial":"E.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":917269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Nathan Lee 0000-0002-4152-4914","orcid":"https://orcid.org/0000-0002-4152-4914","contributorId":345693,"corporation":false,"usgs":true,"family":"Andersen","given":"Nathan","email":"","middleInitial":"Lee","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dufek, Josef","contributorId":194001,"corporation":false,"usgs":false,"family":"Dufek","given":"Josef","email":"","affiliations":[],"preferred":false,"id":917271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jilly-Rehak, Christine E.","contributorId":344651,"corporation":false,"usgs":false,"family":"Jilly-Rehak","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":917272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260828,"text":"70260828 - 2024 - Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","interactions":[],"lastModifiedDate":"2024-11-12T15:09:09.782218","indexId":"70260828","displayToPublicDate":"2024-10-29T09:05:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","docAbstract":"In freshwater environments, low-micrometer microplastics (LMMPs) have captured significant attention due to their prevalence and toxicity. Yet, rapid detection of LMMPs (1–10 μm) at the single-particle level within complex freshwater matrices remains a hurdle. We developed an adaptable plasmonic membrane sensor for fast detection of individual LMMPs in eutrophic lake waters. The plasmonic membrane sensor functions both as a membrane filter and as a sensor for LMMP collection and analysis. Among the four types of membrane sensors, polycarbonate track-etch (PCTE) membrane sensors exhibit superior imaging quality for LMMPs due to their flat and homogeneous surfaces. Besides the significantly improved imaging contrast and reduced background interferences, the Raman intensity of LMMPs is enhanced by 48% ± 25% on PCTE membrane sensors compared to unmodified membranes. The increased Raman intensities of a chemical probe with an increasing gold layer thickness and a decreasing membrane pore size suggest a surface-enhanced Raman scattering effect from the membrane sensors. The membrane sensors achieve a detection limit of 1 μg/L and an ultrafast scanning time of 0.01 s for individual LMMPs across natural eutrophic lake water. The developed membrane sensors offer an adaptable tool for the swift and reliable detection of individual LMMPs in complex environmental matrices.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c06503","usgsCitation":"Wu, Z., Janssen, S., Tate, M., Wei, H., and Qin, M., 2024, Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water: Environmental Science and Technology, v. 58, no. 45, p. 20172-20180, https://doi.org/10.1021/acs.est.4c06503.","productDescription":"9 p.","startPage":"20172","endPage":"20180","ipdsId":"IP-171215","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c06503","text":"Publisher Index Page"},{"id":463868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"45","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Ziyan","contributorId":346132,"corporation":false,"usgs":false,"family":"Wu","given":"Ziyan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Hoaran","contributorId":346133,"corporation":false,"usgs":false,"family":"Wei","given":"Hoaran","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qin, Mohan","contributorId":346134,"corporation":false,"usgs":false,"family":"Qin","given":"Mohan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260429,"text":"70260429 - 2024 - Dynamics, monitoring and forecasting of tephra in the atmosphere","interactions":[],"lastModifiedDate":"2024-11-01T13:54:00.975813","indexId":"70260429","displayToPublicDate":"2024-10-29T08:52:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3283,"text":"Reviews of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics, monitoring and forecasting of tephra in the atmosphere","docAbstract":"Explosive volcanic eruptions inject hot mixtures of solid particles (tephra) and gasses into the atmosphere. Entraining ambient air, these mixtures can form plumes rising tens of kilometers until they spread laterally, forming umbrella clouds. While the largest clasts tend to settle in proximity to the volcano, the smallest fragments, commonly referred to as ash (≤2 mm in diameter), can be transported over long distances, forming volcanic clouds. Tephra plumes and clouds pose significant hazards to human society, affecting infrastructure, and human health through deposition on the ground or airborne suspension at low altitudes. Additionally, volcanic clouds are a threat to aviation, during both high-risk actions such as take-off and landing and at standard cruising altitudes. The ability to monitor and forecast tephra plumes and clouds is fundamental to mitigate the hazard associated with explosive eruptions. To that end, various monitoring techniques, ranging from ground-based instruments to sensors on-board satellites, and forecasting strategies, based on running numerical models to track the position of volcanic clouds, are efficiently employed. However, some limitations still exist, mainly due to the high unpredictability and variability of explosive eruptions, as well as the multiphase and complex nature of volcanic plumes. In the next decades, advances in monitoring and computational capabilities are expected to address these limitations and significantly improve the mitigation of the risk associated with tephra plumes and clouds.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023RG000808","usgsCitation":"Pardini, F., Barsotti, S., Bonadonna, C., de’ Michieli Vitturi, M., Folch, A., Mastin, L.G., Osores, S., and Prata, A.T., 2024, Dynamics, monitoring and forecasting of tephra in the atmosphere: Reviews of Geophysics, v. 62, e2023RG000808, 68 p., https://doi.org/10.1029/2023RG000808.","productDescription":"e2023RG000808, 68 p.","ipdsId":"IP-160162","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023rg000808","text":"Publisher Index Page"},{"id":463533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Pardini, Federica","contributorId":345831,"corporation":false,"usgs":false,"family":"Pardini","given":"Federica","email":"","affiliations":[{"id":82720,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Pisa, Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":917656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barsotti, Sara","contributorId":199711,"corporation":false,"usgs":false,"family":"Barsotti","given":"Sara","email":"","affiliations":[],"preferred":false,"id":917657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Contanza 0000-0002-2368-2193","orcid":"https://orcid.org/0000-0002-2368-2193","contributorId":339895,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Contanza","email":"","affiliations":[{"id":62805,"text":"Université de Genève","active":true,"usgs":false}],"preferred":false,"id":917658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de’ Michieli Vitturi, Mattia","contributorId":199708,"corporation":false,"usgs":false,"family":"de’ Michieli Vitturi","given":"Mattia","email":"","affiliations":[],"preferred":false,"id":917659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Folch, Arnau","contributorId":199712,"corporation":false,"usgs":false,"family":"Folch","given":"Arnau","email":"","affiliations":[],"preferred":false,"id":917660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":917661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osores, Soledad 0009-0002-3352-9245","orcid":"https://orcid.org/0009-0002-3352-9245","contributorId":345832,"corporation":false,"usgs":false,"family":"Osores","given":"Soledad","email":"","affiliations":[{"id":82723,"text":"Servicio Meteorológico Nacional, Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":917662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prata, Andrew T. 0000-0001-9115-1143","orcid":"https://orcid.org/0000-0001-9115-1143","contributorId":345833,"corporation":false,"usgs":false,"family":"Prata","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":917663,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264867,"text":"70264867 - 2024 - Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","interactions":[],"lastModifiedDate":"2025-03-26T15:38:39.371491","indexId":"70264867","displayToPublicDate":"2024-10-29T08:30:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7565,"text":"Earthquake Spectra Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","docAbstract":"The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/87552930241283201","usgsCitation":"Engler, D.T., Jaiswal, K.S., and Ganesh, M., 2024, Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications: Earthquake Spectra Journal, v. 41, no. 1, p. 524-546, https://doi.org/10.1177/87552930241283201.","productDescription":"23 p.","startPage":"524","endPage":"546","ipdsId":"IP-160589","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganesh, Mahadevan 0000-0002-7792-4119","orcid":"https://orcid.org/0000-0002-7792-4119","contributorId":352717,"corporation":false,"usgs":false,"family":"Ganesh","given":"Mahadevan","affiliations":[{"id":84292,"text":"Professor, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":932102,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260375,"text":"70260375 - 2024 - Population structure of Desmophyllum pertusum found along the United States eastern continental margin","interactions":[],"lastModifiedDate":"2024-11-01T14:13:20.307568","indexId":"70260375","displayToPublicDate":"2024-10-29T08:29:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":958,"text":"BMC Research Notes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","title":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","docAbstract":"The connectivity and genetic structuring of populations throughout a region influence a species’ resilience and probability of recovery from anthropogenic impacts. By gaining a comprehensive understanding of population connectivity, more effective management can be prioritized. To assess the connectivity and population genetic structure of a common cold-water coral species, Desmophyllum pertusum (Lophelia pertusa), we performed Restriction-site Associated DNA Sequencing (RADseq) on individuals from nine sites ranging from submarine canyons off New England to the southeastern coast of the United States (SEUS) and the Gulf of Mexico (GOM). Fifty-seven individuals and 3,180 single-nucleotide polymorphisms (SNPs) were used to assess genetic differentiation.
High connectivity exists among populations along the SEUS, yet these populations were differentiated from those to the north off New England and in Norfolk Canyon along the North Atlantic coast of the United States, as well as those in the GOM. Interestingly, Norfolk Canyon, located just north of North Carolina, and GOM populations exhibited low levels of genetic differentiation, corroborating previous microsatellite analyses and signifying gene flow between these populations. Increasing sample sizes from existing populations and including additional sampling sites over a larger geographic range would help define potential source populations and reveal fine-scale connectivity patterns among D. pertusum populations.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13104-024-06977-4","usgsCitation":"Weinnig, A.M., Aunins, A.W., Salamone, V.J., Quattrini, A., Nizinski, M.S., and Morrison, C., 2024, Population structure of Desmophyllum pertusum found along the United States eastern continental margin: BMC Research Notes, v. 17, no. 1, 326, 7 p., https://doi.org/10.1186/s13104-024-06977-4.","productDescription":"326, 7 p.","ipdsId":"IP-157145","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13104-024-06977-4","text":"Publisher Index Page"},{"id":463535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Unites States","otherGeospatial":"Atlantic coastal margin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.71142930127395,\n 28.923532210772052\n ],\n [\n -87.20770794927337,\n 29.778273658658676\n ],\n [\n -88.12002541768051,\n 29.69258193898787\n ],\n [\n -89.23879681191622,\n 28.44134714528691\n ],\n [\n -86.44254662826377,\n 27.912389547448754\n ],\n [\n -85.71142930127395,\n 28.923532210772052\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.9239384814065,\n 42.20254040148441\n ],\n [\n -67.63438293096546,\n 43.58902192305143\n ],\n [\n -69.21544486232233,\n 42.68212319523596\n ],\n [\n -69.57393034494278,\n 40.17025194363276\n ],\n [\n -73.58827669330255,\n 38.91808684375454\n ],\n [\n -74.60625646365936,\n 36.588016013722694\n ],\n [\n -75.5834673460983,\n 34.46068678372583\n ],\n [\n -79.47920624257769,\n 31.99090849493018\n ],\n [\n -80.4000384261637,\n 31.00478268172816\n ],\n [\n -79.478750607929,\n 26.481859079129094\n ],\n [\n -63.15489504288122,\n 42.1372460985159\n ],\n [\n -64.9239384814065,\n 42.20254040148441\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinnig, Alexis Marie 0000-0001-8858-4837","orcid":"https://orcid.org/0000-0001-8858-4837","contributorId":331476,"corporation":false,"usgs":true,"family":"Weinnig","given":"Alexis","email":"","middleInitial":"Marie","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salamone, Veronica J. 0000-0002-6274-6401","orcid":"https://orcid.org/0000-0002-6274-6401","contributorId":293174,"corporation":false,"usgs":true,"family":"Salamone","given":"Veronica","email":"","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":917479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nizinski, Martha S.","contributorId":174770,"corporation":false,"usgs":false,"family":"Nizinski","given":"Martha","email":"","middleInitial":"S.","affiliations":[{"id":27510,"text":"NMFS National Systematics Laboratory, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":917480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917481,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267297,"text":"70267297 - 2024 - The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","interactions":[],"lastModifiedDate":"2025-05-20T16:19:44.225742","indexId":"70267297","displayToPublicDate":"2024-10-29T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","docAbstract":"Perturbations in ecological processes can occur when wildlife alter their spatiotemporal activity patterns to avoid human activities that they perceive as a risk. Such perturbations can have cascading effects throughout wildlife communities. For greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse), nest predation plays an important role in population dynamics. Domestic cattle (Bos taurus) grazing has been hypothesized to increase nest predation by reducing grass height, and therefore reducing nest concealment, which may facilitate nest detection by predators. Grass height is lower on grazed pastures, but sage-grouse nest success appears similar on pastures grazed at varying intensities in several recent studies. Any reductions in nest concealment caused by grazing could potentially be offset by a localized response of one or more nest predators to the presence of cattle (i.e., the cattle avoidance hypothesis). A reduction in nest predator density or relative use within pastures could explain similar patterns of nest success on pastures grazed at varying intensities. Also, wildlife can potentially partition themselves temporally to avoid risks associated with human activities. For example, a shift in diel activity patterns by nest predators in response to cattle could result in predators being active during portions of the day when they are less efficient at locating sage-grouse nests. Thus, the effects of grazing could be offset by a temporal avoidance of cattle by predators. We deployed motion sensor cameras across six pastures to evaluate whether coyotes (Canis latrans; a primary sage-grouse nest predator) altered spatiotemporal activity patterns in response to cattle. We found that the probability of detecting coyotes had a positive relationship with cattle detections at camera sites (β = 0.22; 95% CI = 0.14,0.30). We also found that coyotes did not shift their diel activity patterns in response to cattle being in the pastures. Thus, in our system, similar sage-grouse nest success among pastures with different grazing intensities cannot be explained by the cattle avoidance hypothesis, at least for coyotes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.012","usgsCitation":"Helmstetter, N., Conway, C.J., Roberts, S., Makela, P., and Waits, L., 2024, The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator: Rangeland Ecology and Management, v. 98, p. 316-323, https://doi.org/10.1016/j.rama.2024.08.012.","productDescription":"8 p.","startPage":"316","endPage":"323","ipdsId":"IP-158843","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Butte, Pahsimeroi Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.07468470534926,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 44.658252472114754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":355566,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":355567,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":937661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Makela, Paul D.","contributorId":355569,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":84780,"text":"United States Department of Interior","active":true,"usgs":false}],"preferred":false,"id":937663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waits, Lisette P.","contributorId":355568,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937662,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}