An improved understanding of hydrologic responses to changing climatic conditions is needed to better inform water management practices. East Canyon Creek, a perennial, snowmelt-dominated stream in the Wasatch Mountains of northern Utah, is subjected to increasing development and demands on water in the Snyderville Basin and adjacent areas. In this study, streamflow and specific conductance measured at three U.S. Geological Survey streamgages on East Canyon Creek were used to estimate daily baseflow for water years 2011–22. Trends in these estimates and correlations with climate data from two Natural Resource Conservation Service snow telemetry (SNOTEL) stations within the Snyderville Basin above East Canyon Reservoir, were quantified and reported. Peak annual streamflow also was assessed for flood potential on the study reach of East Canyon Creek. The hydrograph separations showed consistent baseflow indices among all sites, with a larger baseflow component during the fall–spring period (September–April; baseflow indices approximately equal to [≈] 0.751–0.835) and smaller component during the summer period (May–August; baseflow indices ≈ 0.428–0.532). In-stream specific conductance during spring (February–April) was influenced by road salt application, limiting the utility of the hydrograph separation approach. Annual streamflow and climate data were evaluated for trends using the nonparametric Mann–Kendall test, with inconclusive results. Related tests for trends, the Seasonal and Regional Kendall tests, were used to evaluate data at monthly timesteps and indicated a decreasing trend in total streamflow and baseflow at all streamgages. The rank-based Kendall’s tau test for correlation was used to measure the ordinal association with climatic data at co-located SNOTEL stations. Total streamflow and baseflow were strongly correlated with precipitation and snow-water equivalent. By incorporating a predictive regression model, the nonparametric Theil–Sen line, these correlations could support the development of streamflow forecast models using climate data from SNOTEL stations. Such models would provide water managers with tools to help make proactive decisions, such as reservoir or water reclamation releases and curtailment of withdrawals, in response to regional drought or varying snowpack and spring runoff in a given year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255003","collaboration":"Prepared in cooperation with Snyderville Basin Water Reclamation District","usgsCitation":"Root, J.C., and Rumsey, C.A., 2025, Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah: U.S. Geological Survey Scientific Investigations Report 2025–5003, 29 p., https://doi.org/10.3133/sir20255003.","productDescription":"Report: viii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-162488","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":493759,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118539.htm","linkFileType":{"id":5,"text":"html"}},{"id":484540,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14SJDMX","text":"USGS data release","description":"Root, J.C., 2025, Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022: U.S. Geological Survey data release, https://doi.org/10.5066/P14SJDMX.","linkHelpText":"Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022"},{"id":484539,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5003/images"},{"id":484538,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.XML","description":"SIR 2025-5003 XML"},{"id":484537,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255003/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5003 HTML"},{"id":484536,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5003 PDF"},{"id":484535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5003/coverthb.jpg"}],"country":"United States","state":"Utah","county":"Morgan County, Summit County","otherGeospatial":"East Canyon Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.85739630382633,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 41.2514958778022\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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2329 West Orton Circle
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In 2023, an outbreak of highly pathogenic avian influenza occurred among critically endangered California condors (Gymnogyps californianus), and >21 died. We evaluated safety, immunogenicity, vaccination strategies, and correlates of antibody response of an influenza vaccine for poultry in black vultures (Coragyps atratus) and then California condors. We noted differences in antibody titers between vaccinated and unvaccinated birds (vultures p<0.004; condors p<0.02) but no adverse effects of vaccination. All vaccinated vultures and 80% of vaccinated condors showed maximum measured antibody response within the published range associated with survival of vaccinated and virally challenged chickens. We noted weak evidence of higher antibody responses for birds given two 0.5-mL vaccines versus those given one 1-mL vaccine but no correlation between antibody titers and sex for either species or between antibody titers and bone lead concentrations in vultures. Our results prompted initiation of a vaccination program for condors that could reduce spread of this disease among highly threatened species.
","language":"English","publisher":"U.S. Centers for Disease Control and Prevention","doi":"10.3201/eid3106.241558","usgsCitation":"Katzner, T., Blackford, A., Donahue, M., Gibbs, S.E., Lenoch, J.B., Martin, M.K., Rocke, T.E., Root, J.J., Styles, D., Cooper, S., Dean, K., Dvornicky-Raymond, Z., Keller, D., Sanchez, C., Dunlap, B., Grier, T., Jones, M., Nitzel, G., Patrick, E., Purcell, M., Specht, A., and Suarez, D.L., 2025, Safety and immunogenicity of poultry vaccine for protecting critically endangered avian species against highly pathogenic avian influenza virus, United States: Emerging Infectious Diseases, v. 31, no. 6, p. 1131-1139, https://doi.org/10.3201/eid3106.241558.","productDescription":"9 p.","startPage":"1131","endPage":"1139","ipdsId":"IP-171779","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":485999,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490125,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid3106.241558","text":"Publisher Index Page"}],"volume":"31","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":933551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackford, Ashleigh V.","contributorId":353436,"corporation":false,"usgs":false,"family":"Blackford","given":"Ashleigh V.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":933552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donahue, Mary","contributorId":353439,"corporation":false,"usgs":false,"family":"Donahue","given":"Mary","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":933553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Samantha E.J.","contributorId":225084,"corporation":false,"usgs":false,"family":"Gibbs","given":"Samantha","email":"","middleInitial":"E.J.","affiliations":[],"preferred":true,"id":933554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenoch, Julianna B.","contributorId":317921,"corporation":false,"usgs":false,"family":"Lenoch","given":"Julianna","email":"","middleInitial":"B.","affiliations":[{"id":69193,"text":"Wildlife Services National Wildlife Disease Program, Animal and Plant Health Inspections Service, USDA","active":true,"usgs":false}],"preferred":false,"id":933555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Michael K.","contributorId":214245,"corporation":false,"usgs":false,"family":"Martin","given":"Michael","email":"","middleInitial":"K.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":933556,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":933557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Root, J. 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2025 - Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2025-08-04T15:39:01.205508","indexId":"70266026","displayToPublicDate":"2025-04-15T10:32:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"title":"Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico","docAbstract":"Marine birds in the U.S. Gulf of Mexico have long been poorly studied. Given statutory obligations to protect migratory birds and endangered species, three broad-scale vessel and aerial programs initiated since 2010 have now surveyed the entire northern Gulf. Vessel coverage alone exceeds 700 d and 74,000 km of observer effort using 300-m strip transects. We supplemented these survey data with earlier, smaller-scale studies, eBird checklists, literature reviews, and other less accessible sources to create snapshot summaries of relative abundance, seasonal occurrence, and regional distribution for 117 taxa of marine and water birds reported from the northern Gulf (113 of which were substantiated with physical evidence). Using taxonomic and functional criteria, we identified 56 taxa characteristic of open shelf, slope, and pelagic waters (federal jurisdiction), 41 taxa with primarily coastal affinities (state and federal jurisdiction), and 20 taxa of sea and diving ducks. High species richness of marine birds in the northern Gulf is attributed to (1) a temperate-to-tropical gradient facilitating diverse marine environments year-round; (2) varied geographic origins of marine bird species using the Gulf; and (3) a mostly enclosed sea basin acting as a vagrant trap for wide-ranging species. Our taxonomic list and status updates seek to bridge information gaps for marine birds now subject to accelerated commercial uses of this region's continental shelf, including newly proposed offshore wind energy development. Other applications include guiding risk and vulnerability assessments of Gulf marine birds, providing core content for seabird observer training, and prioritizing environmental impact reviews and monitoring programs in offshore energy construction and operations plans.
","language":"English","publisher":"African Seabird Group/Pacific Seabird Group","doi":"10.5038/2074-1235.53.1.1634","usgsCitation":"Haney, J., Michael, P., Gleason, J.S., Wilson, R., Satgé, Y., Hixson, K.M., and Jodice, P.G., 2025, Relative abundance, seasonal occurrence, and distribution of marine birds in the northern Gulf of Mexico: Marine Ornithology: Journal of Seabird Research and Conservation, v. 53, p. 189-206, https://doi.org/10.5038/2074-1235.53.1.1634.","productDescription":"18 p.","startPage":"189","endPage":"206","ipdsId":"IP-164512","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":484987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493287,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5038/2074-1235.53.1.1634","text":"Publisher Index Page"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.06492683279039,\n 30.605180321059038\n ],\n [\n -99.06492683279039,\n 24.549635648982317\n ],\n [\n -81.11757130707277,\n 24.549635648982317\n ],\n [\n -81.11757130707277,\n 30.605180321059038\n ],\n [\n -99.06492683279039,\n 30.605180321059038\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Haney, J. 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In this study we explore the origin of the two modes of degassing revealed by time-series gas data at Turrialba volcano (Costa Rica) in the context of new melt inclusion (MI) data. To reconstruct the c[CO2] of undegassed magma, we developed a rapid-quench piston-cylinder assembly to rehomogenize the vapor bubble commonly contained in MIs. We focus on olivine-hosted MIs from a mafic scoria sample erupted from Turrialba in 1864–1866. The reconstructed CO2 contents in MIs decrease from ∼4000 to <1000 ppmw as S contents decrease from 3500 to <1000 ppmw. The highest reconstructed S and CO2 in the MIs resulted in an initial magmatic CO2/ ST ratio (molar) of 0.83. Informed by the MI data, we modeled the decompression degassing of Turrialba magma and vapor composition using the Sulfur_X and EVo models. Instead of being controlled by initial magmatic CO2/ST ratio as suggested by previous studies, we find that the quiescent gas emitted from Turrialba during 2014–2018 (CO2/ ST = 2.3 ± 0.8, molar) appears to reflectequilibrium with magmas stored at 4–8 km (Sulfur_X) or 2 km (EVo) depth, when H2O is degassing extensively from the magma. A magma storage region at 4–8 km is also supported by seismic tomography. The second gas mode is noted by spikes in CO2/ ST ∼ 7.9 ± 2 in the weeks prior to eruption. This gas reflects equilibrium with a magma at 12–18 km (Sulfur_X) or 4–8 km (EVo), where the ascending magma is saturated with a CO2-rich vapor. Thus, there are two important trans crustal depths beneath the volcano: one where the rate of H2O loss from the magma and thus magma viscosity increases, and one at greater depths where high CO2/ST vapor forms and may facilitate dike propagation. We interpret the shallower, H2O-loss region as the main site of magma stalling and storage, where quiescent gas is generated continuously. We interpret the greater depth (12–18 km) as the source of the precursory gas that precedes eruption, and where the mafic melt lastly equilibrated with a mush zone before ascending and triggering eruption weeks later. This hypothesis is ripe for testing at other volcanoes that exhibit two modes in gas geochemistry.
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Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X56Q8J","usgsCitation":"Jahn, K., and Walter, D.A., 2025, Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York: EarthArXiv, https://doi.org/10.31223/X56Q8J.","productDescription":"38 p.","ipdsId":"IP-170367","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jahn, Kalle 0000-0002-4976-0137","orcid":"https://orcid.org/0000-0002-4976-0137","contributorId":333053,"corporation":false,"usgs":true,"family":"Jahn","given":"Kalle","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951353,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263947,"text":"70263947 - 2025 - From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars","interactions":[],"lastModifiedDate":"2025-03-03T15:32:48.429612","indexId":"70263947","displayToPublicDate":"2025-04-15T08:25:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars","docAbstract":"On Earth, silica-rich phases from opal to quartz are important indicators and tracers of geological processes. Hydrated silica, such as opal, is a particularly good matrix for the preservation of molecular and macroscopic biosignatures. Cherts, a type of silica-dominated rocks, provide a unique archive of ancient terrestrial life while quartz is the emblematic mineral of the Earth's continental crust. On Mars, hydrated silica has been detected in several locations based on remote sensing and rover-based studies. In the present article we report on the detection of cobbles made of hydrated silica (opal or chalcedony), as well as well-crystallized quartz. These detections were made with the SuperCam instrument onboard Perseverance (Mars 2020 mission), using a combination of LIBS, infrared and Raman spectroscopy. Quartz-dominated stones are detected unambiguously for the first time on the Martian surface, and based on grain size and crystallinity are proposed to be of hydrothermal origin. Although these rocks were all found as float, we propose that these detections are part of a common hydrothermal system, and represent different depths / temperatures of precipitation. This attests that hydrothermal processes were active in and around Jezero crater, possibly triggered by the Jezero crater-forming impact. These silica-rich rocks, in particular opaline silica, are very promising targets for sampling and return to Earth given their high biosignature preservation potential.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2025.119256","usgsCitation":"Beck, P., Beyssac, O., Dehouck, E., Bernard, S., Pineau, M., Mandon, L., Royer, C., Clave, E., Schroder, S., Forni, O., Francis, R., Mangold, N., Bedford, C., Broz, A., Cloutis, E., Johnson, J., Poulet, F., Fouchet, T., Quantin-Nataf, C., Pilorget, C., Rapin, W., Meslin, P., Gabriel, T.S., Arana, G., Madariaga, J., Brown, A., Maurice, S., Clegg, S.M., Gasnault, O., Cousin, A., Wiens, R., and The SuperCam Team, 2025, From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars: Earth and Planetary Science Letters, v. 656, 119256, 12 p., https://doi.org/10.1016/j.epsl.2025.119256.","productDescription":"119256, 12 p.","ipdsId":"IP-175708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":487147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2025.119256","text":"Publisher Index Page"},{"id":482739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"656","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beck, P.S.A.","contributorId":223295,"corporation":false,"usgs":false,"family":"Beck","given":"P.S.A.","email":"","affiliations":[],"preferred":false,"id":929219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beyssac, O.","contributorId":290034,"corporation":false,"usgs":false,"family":"Beyssac","given":"O.","affiliations":[{"id":62313,"text":"Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, CNRS, Sorbonne Université","active":true,"usgs":false}],"preferred":false,"id":929220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dehouck, E.","contributorId":290073,"corporation":false,"usgs":false,"family":"Dehouck","given":"E.","affiliations":[{"id":62330,"text":"Univ. 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Aquatic insects provide critical nutritional subsidies linking aquatic and riparian food webs while simultaneously serving as a contaminant pathway for riparian insectivores in polluted ecosystems. Previous studies have characterized the transport and transfer of contaminants from aquatic to riparian ecosystems through insect metamorphosis, but both contaminant exposure and metamorphosis are energetically intensive processes that may cause host microbiomes to undergo radical transformation in structure and function, potentially affecting the host's physiology. We collected arthropods from three sites within Torch Lake, a historical copper mine in the Keweenaw Peninsula, Michigan, USA, and three sites within a nearby reference lake. Our objectives were to: 1) characterize the variation in microbiome communities and predicted metagenomic functions with legacy copper mining activity across space, among host types and family-level host taxonomy, 2) characterize how insect metamorphosis alters the microbiome community, including the degree of endosymbiotic infection, and predicted metagenomic function. We field-collected organisms, extracted their DNA, and sequenced the 16S region of the rRNA gene to characterize microbiome communities, then predicted metagenomic function. Site, lake, and host taxonomy affected the host microbiome community composition. Copper exposure increased the abundance of xenobiotic and lipid metabolism pathways in the Araneidae spider microbiome. Insect metamorphosis reduced the alpha diversity, altered the community composition, and predicted metagenomic function. We observed a bioconcentration of endosymbiotic bacteria in adult insects, especially holometabolous insects. Through metamorphosis, we observed a transition in function from xenobiotic degradation pathways to carbohydrate metabolism. Overall, contaminant exposure alters the microbiome composition in aquatic insects and riparian spiders and alters the function of the microbiome across the aquatic-riparian interface. Furthermore, metamorphosis is a critical element in shaping the aquatic insect microbiome across its life history.
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To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5–350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1–2.6, “Sustainability”; SSP 3–7.0, “Rocky Road”), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040–2050, followed by an equilibrium response and regained habitat by 2090–2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.
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While the relationship between seismic moment and moment magnitude (M or Mw) of log10(M0) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude ML and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and ML are coincident; for earthquakes smaller than ~3, ML ~ 1.0 log10 M0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that ML and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new ML-M0 to convert ML to M, refining the SCSN operational MLr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240162","usgsCitation":"Baltay Sundstrom, A.S., and Abercrombie, R., 2025, Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study: Bulletin of the Seismological Society of America, v. 115, no. 3, p. 1279-1293, https://doi.org/10.1785/0120240162.","productDescription":"15 p.","startPage":"1279","endPage":"1293","ipdsId":"IP-167974","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":485557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.78392771143658,\n 35.70994070706057\n ],\n [\n -117.78392771143658,\n 35.55296259649002\n ],\n [\n -117.5741750312894,\n 35.55296259649002\n ],\n [\n -117.5741750312894,\n 35.70994070706057\n ],\n [\n -117.78392771143658,\n 35.70994070706057\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":936193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abercrombie, Rachel E.","contributorId":293131,"corporation":false,"usgs":false,"family":"Abercrombie","given":"Rachel E.","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":936194,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70265520,"text":"ofr20241062 - 2025 - Characterizing Meteor Crater impact melts through geochemistry and textural analysis","interactions":[],"lastModifiedDate":"2025-08-07T20:55:19.201468","indexId":"ofr20241062","displayToPublicDate":"2025-04-14T15:15:42","publicationYear":"2025","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":"2024-1062","displayTitle":"Characterizing Meteor Crater Impact Melts Through Geochemistry and Textural Analysis","title":"Characterizing Meteor Crater impact melts through geochemistry and textural analysis","docAbstract":"The U.S. Geological Survey Astrogeology Science Center houses the Meteor Crater sample collection, an assemblage of over 2,500 meters of cuttings from 161 drill holes into Meteor Crater’s rim, flanks, and ejecta blanket. We have utilized this unique collection to study the composition and spatial distribution of impact-generated materials from within the ejecta blanket. Meteor Crater has historically been known to have generated only a relatively small amount of impact melt compared to other terrestrial craters of similar size. A detailed compositional and textural dataset of impact-derived melts from this impact can therefore be a useful asset in improving our understanding of crater formation, and in particular impact melt formation.
We have characterized 42 impact-melt particles from Meteor Crater using a scanning electron microscope and an electron microprobe for textural and compositional analysis. We analyzed samples from six drill holes in the ejecta blanket, situated to the northwest, southeast, south, and southwest of the crater (ejecta northeast of the crater is devoid of impact melts). Impact melts were collected from drill cuttings at various depths within the ejecta blanket, ranging from a few centimeters below the surface down to ~6.5 meters.
Backscattered electron (BSE) images were acquired for each analyzed impact-melt particle. To characterize the various textures and phases present in each impact melt, we also took many detailed BSE images. Our geochemical analyses include full spectral profiles using energy dispersive X-ray spectrometry and well-calibrated wavelength dispersive spectrometry for a number of phases, including minerals (olivine, pyroxene, and so on), pristine glass, and metallic inclusions. The full dataset is available in ScienceBase as a data release (Gullikson and others, 2024), accessible at https://doi.org/10.5066/P9OGAJ8P.
Our goal for this Open-File Report is to provide a summary of this immense dataset, details on data collection, descriptions of the different phases observed within impact-melt particles (both geochemically and texturally), and observable trends.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241062","usgsCitation":"Gullikson, A.L., Gaither, T.A., and Hagerty, J.J., 2024, Characterizing Meteor Crater impact melts through geochemistry and textural analysis: U.S. Geological Survey Open-File Report 2024–1062, 23 p., https://doi.org/10.3133/ofr20241062.","productDescription":"Report: vii, 23 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-162108","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":493758,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118538.htm","linkFileType":{"id":5,"text":"html"}},{"id":484534,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241062/full"},{"id":484524,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1062/images"},{"id":484387,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OGAJ8P","text":"USGS Data Release","description":"Gullikson, A.L., Gaither, T.A., and Hagerty, J.J., 2024, Geochemistry and high-resolution backscattered electron imaging of Meteor Crater impact melts: U.S. Geological Survey data release, https://doi.org/10.5066/P9OGAJ8P.","linkHelpText":"Geochemistry and high-resolution backscattered electron imaging of Meteor Crater impact melts"},{"id":484384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1062/covrthb.jpg"},{"id":484386,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1062/ofr20241062.XML","size":"200 KB","linkFileType":{"id":8,"text":"xml"}},{"id":484385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1062/ofr20241062.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Meteor Crater","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.03682408526112,\n 35.03726468620707\n ],\n [\n -111.03682408526112,\n 35.01842427092913\n ],\n [\n -111.01097319209285,\n 35.01842427092913\n ],\n [\n -111.01097319209285,\n 35.03726468620707\n ],\n [\n -111.03682408526112,\n 35.03726468620707\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The richness and abundance of freshwater mussels in the Big Darby Creek Basin has declined in recent decades, according to survey results published by the Ohio Biological Survey. In October 2016, a major mussel die-off of undetermined cause reportedly affected over 50 miles of Big Darby Creek; however, fishes and other wildlife were not noticeably impacted. Pollution, habitat destruction, climate change, and hydrologic modification have all been theorized as potential reasons for the widespread declines in freshwater mussel populations in North America. To better understand potential stressors to mussels and other aquatic organisms in the Big Darby Creek Basin, the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority, evaluated water quality and temporal changes in hydrology at selected locations. In addition, environmental deoxyribonucleic acid (eDNA) quantitative polymerase chain reaction (qPCR) assays were developed to detect the presence of selected mussels and macroinvertebrates using stream water.
Time-weighted average concentrations of pesticides, organic wastewater compounds (OWCs), and polycyclic aromatic hydrocarbons (PAHs) were determined for selected locations within the Big Darby Creek Basin. Passive samplers designed to mimic the respiratory exposure of aquatic organisms and the bioconcentration of organic contaminants into their fatty tissues were deployed three times annually at three sites within the Big Darby Creek Basin in 2020 and 2021. Analyses were done for 204 pesticide compounds, 38 OWCs, and 33 PAHs. Of the 204 pesticide compounds, 70 were detected in at least one sample; 30 were detected in all samples. Herbicides and herbicide degradates were the pesticides most frequently detected and also had some of the highest concentrations of the pesticides detected in this study. Three herbicides (atrazine, ametryn, and metribuzin) were detected in at least 88 percent of samples and two fungicides (azoxystrobin and propiconazole) were detected in all samples. Of the 38 OWCs, 24 were detected in at least one sample; however, only one (N,N-diethyltoluamide [DEET]) was detected in all samples. Of the 33 PAHs, 29 were detected in at least one sample; 12 were detected in all samples.
A continuous water-quality monitor was operated seasonally on Big Darby Creek above Georgesville, Ohio, from 2020 to 2022. Dissolved oxygen concentrations generally followed a daily cycle, peaking in early evening and troughing around sunrise. There were occasional 24-hour swings in dissolved oxygen concentration that had a range exceeding 10 milligrams per liter. However, dissolved oxygen concentrations never fell below Ohio’s aquatic life criteria for warmwater habitats (outside of mixing zones) of 4.0 milligrams per liter as an instantaneous minimum and 5.0 milligrams per liter as a minimum 24-hour average. The Ohio water-quality criteria for temperatures are 29.4 degrees Celsius as an instantaneous maximum and 27.8 degrees Celsius as a 24-hour average maximum. In 2020, there were 10 days when the maximum instantaneous value for temperature was exceeded and 3 consecutive days when the maximum 24-hour average temperature was exceeded.
Streamflow time-series data from three gaging stations within the Big Darby Creek Basin were evaluated for trends in annual flow statistics and daily nonexceedance probabilities over time. In general, the evaluation of streamflow conditions at the Big Darby Creek gage (with 97 years of record) indicated that streamflow changed between water years 1922 and 2021. During that time span, flows in general increased, the number of high-flow pulses became more frequent, and low-flow pulses and extreme low-flow periods became less frequent. The only strong indication of trends over time in annual flow statistics for the relatively short records for the other two gages (on Little Darby Creek, with 25 years of record, and Hellbranch Run, with 29 years of record) was that as time went on, reversals between rising and falling periods became more frequent.
The U.S. Geological Survey Ohio Water Microbiology Laboratory developed eDNA qPCR assays to detect Epioblasma rangiana (northern riffleshell mussels), Chimarra obscura (a species of caddisfly), Maccaffertium pulchellum (a species of mayfly), and optimized a preexisting eDNA qPCR assay to detect for Ptychobranchus fasciolaris (kidneyshell mussels). The assays were validated by using environmental sampling methods. Assay sensitivity was established by determining the limits of detection and quantification. Water samples were collected at 12 sites in the Big Darby Creek Basin between 2020 and 2022 and analyzed for eDNA with the qPCR assays developed for this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255005","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Huitger, C.A., Koltun, G.F., Stelzer, E.A., and Lynch, L.D., 2025, Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22: U.S. Geological Survey Scientific Investigations Report 2025–5005, 59 p., https://doi.org/10.3133/sir20255005.","productDescription":"Report: ix, 59 p.; 2 Appendices; 2 Data Releases","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-161896","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":484334,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GN45M","text":"USGS data release","linkHelpText":"Pesticide, organic wastewater compound (OWC) and polycyclic aromatic hydrocarbon (PAH) data determined from samples collected with instream passive samplers in the Big Darby Creek Basin, Ohio, 2020–21"},{"id":484333,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WELW7W","text":"USGS data release","linkHelpText":"Annual streamflow statistics for selected streamgages on Big and Little Darby Creeks and Hellbranch Run, Ohio (through water year 2021)"},{"id":484331,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005_app1_csv.zip","text":"Tables 1.1–1.17 (CSV)","size":"34.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"Appendix 1. Quality Control and Summary Information for Analyses of Pesticides, Organic Wastewater Compounds, and Polycyclic Aromatic Hydrocarbons"},{"id":484330,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005_app1_tables.xlsx","text":"Tables 1.1–1.17","size":"131 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Appendix 1. Quality Control and Summary Information for Analyses of Pesticides, Organic Wastewater Compounds, and Polycyclic Aromatic Hydrocarbons"},{"id":484329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5005/images/"},{"id":484328,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5005 XML"},{"id":493757,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118527.htm","linkFileType":{"id":5,"text":"html"}},{"id":484327,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255005/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5005 HTML"},{"id":484326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005.pdf","size":"4.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5005 PDF"},{"id":484324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5005/coverthb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Big Darby Creek basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.8333,\n 40.333\n ],\n [\n -83.8333,\n 39.5\n ],\n [\n -83,\n 39.5\n ],\n [\n -83,\n 40.333\n ],\n [\n -83.8333,\n 40.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Before implementing nontoxic shot requirements for hunting waterfowl and American coots Fulica americana in the United States in 1991, the U.S. Fish and Wildlife Service monitored lead poisoning in waterfowl on federal and state wildlife hunting areas during 1983-1986. Federal and state collaborators collected gizzards and livers from 9,029 hunter-killed waterfowl (10 species of dabbling ducks Anatinae, 9 diving ducks Aythyinae, 5 geese Anserinae, and tundra swans Cygnus columbianus) across the four flyways. At the U.S. Fish and Wildlife Service National Wildlife Health Center, Madison, Wisconsin, waterfowl gizzards were examined for ingested lead and nontoxic shot and livers were analyzed for lead concentrations. Diving ducks had the greatest frequency (8.7%) of one or more ingested lead shot, followed by dabbling ducks (5.5%) and geese (1.3%). No ingested shot were found in tundra swans. The frequency of elevated (≥ 2.0 mg/kg wet weight) liver lead concentrations was also greatest in diving ducks, followed by dabbling ducks and geese. Within each species group, the frequency of elevated liver lead concentrations was greater than ingested lead shot, an indication that lead shot ingestion alone underrepresents lead exposure. Thus, lead in the liver may remain elevated after the erosion and excretion of lead pellets from the gizzard. Our results provide historical baseline data and summarize a nationwide study of lead exposure, using both ingested lead shot and liver lead concentrations, in waterfowl in the United States before the implementation of nontoxic shot regulations in 1991. These data can be compared with previous studies of lead exposure in waterfowl, as well as current and future assessments to evaluate the success of nontoxic shot regulations nationwide and specifically within previously sampled waterfowl management areas.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/JFWM-24-041","usgsCitation":"Franson, J.C., and Bunck, C.M., 2025, Lead exposure in waterfowl before contoxic shot requirements: A nationwide study, 1983−1986: Journal of Fish and Wildlife Management, https://doi.org/10.3996/JFWM-24-041.","ipdsId":"IP-165936","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":488486,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-24-041","text":"Publisher Index Page"},{"id":484847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":934183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunck, Christine M. cbunck@usgs.gov","contributorId":731,"corporation":false,"usgs":true,"family":"Bunck","given":"Christine","email":"cbunck@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":934184,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70267451,"text":"70267451 - 2025 - Acute heat stress and the extirpation of a threatened coral species from a remote, subtropical reef system","interactions":[],"lastModifiedDate":"2025-05-23T15:04:53.305883","indexId":"70267451","displayToPublicDate":"2025-04-14T10:01:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Acute heat stress and the extirpation of a threatened coral species from a remote, subtropical reef system","docAbstract":"The ecological significance of the reef-building elkhorn coral, Acropora palmata, is threatened by heat-stress-induced mortality. The intensity and duration of the ocean heatwave affecting Dry Tortugas National Park in the summer of 2023 was historically unprecedented in its early timing and maximum temperatures reached and resulted in 100% A. palmata mortality. To understand the lethality of this event, we examined temperature data measured by in situ data loggers and estimated from satellites (National Oceanic and Atmospheric Administration’s Coral Reef Watch) to investigate the timing of peak ocean temperatures and coral mortality. The in situ dataset revealed warmer water temperatures during the heatwave than those reported from the satellites, and the difference between the datasets was significantly pronounced during the summer. Our results support that, at least for this subtropical population, A. palmata may have an upper-threshold temperature that caused lethality faster than expected from the gradual accumulation of heat stress.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00338-025-02653-6","usgsCitation":"Thompson, A., Stathakopoulos, A., Hollister, K., Lynch, A., Holder, J., and Kuffner, I.B., 2025, Acute heat stress and the extirpation of a threatened coral species from a remote, subtropical reef system: Coral Reefs, v. 44, p. 1023-1030, https://doi.org/10.1007/s00338-025-02653-6.","productDescription":"8 p.","startPage":"1023","endPage":"1030","ipdsId":"IP-170593","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":487956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-025-02653-6","text":"Publisher Index Page"},{"id":486508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.73251044641151,\n 24.731351709907827\n ],\n [\n -82.98561815624343,\n 24.731351709907827\n ],\n [\n -82.98561815624343,\n 24.542143688585085\n ],\n [\n -82.73251044641151,\n 24.542143688585085\n ],\n [\n -82.73251044641151,\n 24.731351709907827\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2025-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Ava Madeline 0009-0001-0095-9217","orcid":"https://orcid.org/0009-0001-0095-9217","contributorId":355840,"corporation":false,"usgs":true,"family":"Thompson","given":"Ava Madeline","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stathakopoulos, Anastasios 0000-0002-4404-035X astathakopoulos@usgs.gov","orcid":"https://orcid.org/0000-0002-4404-035X","contributorId":147744,"corporation":false,"usgs":true,"family":"Stathakopoulos","given":"Anastasios","email":"astathakopoulos@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollister, Karli J.","contributorId":355841,"corporation":false,"usgs":false,"family":"Hollister","given":"Karli J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Amelia M.","contributorId":355842,"corporation":false,"usgs":false,"family":"Lynch","given":"Amelia M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938245,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holder, Jordan C.","contributorId":355843,"corporation":false,"usgs":false,"family":"Holder","given":"Jordan C.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938246,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938247,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265777,"text":"70265777 - 2025 - Solution-collapse breccia pipe uranium deposits of the southern Colorado Plateau, northwestern Arizona, USA","interactions":[],"lastModifiedDate":"2025-04-15T15:02:28.048826","indexId":"70265777","displayToPublicDate":"2025-04-14T09:58:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Solution-collapse breccia pipe uranium deposits of the southern Colorado Plateau, northwestern Arizona, USA","docAbstract":"Non-native plants have the potential to harm ecosystems. Harm is classically related to their distribution and abundance, but this geographical information is often unknown. Here, we assess geographical commonness as a potential indicator of invasive status for non-native flora in the United States. Geographical commonness could inform invasion risk assessments across species and ecoregions.
Conterminous United States.
Through 2022.
Plants.
We compiled and standardised occurrence and abundance data from 14 spatial datasets and used this information to categorise non-native species as uncommon or common based on three dimensions of commonness: area of occupancy, habitat breadth and local abundance. To assess consistency in existing categorizations, we compared commonness to invasive status in the United States. We identified species with higher-than-expected abundance relative to their occupancy, habitat breadth or residence time. We calculated non-native plant richness within United States ecoregions and estimated unreported species based on rarefaction/extrapolation curves.
This comprehensive database identified 1874 non-native plant species recorded in 4,844,963 locations. Of these, 1221 species were locally abundant (> 10% cover) in 797,759 unique locations. One thousand one hundred one non-native species (59%) achieved at least one dimension of commonness, including 565 species that achieved all three. Species with longer residence times tended to meet more dimensions of commonness. We identified 132 species with higher-than-expected abundance. Ecoregions in the central United States have the largest estimated numbers of unreported, abundant non-native plants.
A high proportion of non-native species have become common in the United States. However, existing categorizations of invasive species are not always consistent with species' abundance and distribution, even after considering residence time. Considering geographical commonness and higher-than-expected abundance revealed in this new dataset could support more consistent and proactive identification of invasive plants and lead to more efficient management practices.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.70041","usgsCitation":"Bradley, B., Evans, A., Sofaer, H., Vilà, M., Barnett, D., Beaury, E.M., Blumenthal, D.M., Corbin, J., Dukes, J., Early, R., Ibanez, I., Pearse, I.S., Petri, L., and Sorte, C.J., 2025, A quantitative classification of the geography of non-native flora in the United States: Global Ecology and Biogeography, v. 34, e70041, 14 p., https://doi.org/10.1111/geb.70041.","productDescription":"e70041, 14 p.","ipdsId":"IP-157629","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":496397,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.70041","text":"Publisher Index Page"},{"id":485450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n \"type\": 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PFAS-impacted-groundwater community","docAbstract":"Tapwater (TW) safety and sustainability are priorities in the United States. Per/polyfluoroalkyl substance(s) (PFAS) contamination is a growing public-health concern due to prolific use, widespread TW exposures, and mounting human-health concerns. Historically-rural, actively-urbanizing communities that rely on surficial-aquifer private wells incur elevated risks of unrecognized TW exposures, including PFAS, due to limited private-well monitoring and contaminant-source proliferation in urbanizing landscapes. Here, a broad-analytical-scope TW-assessment was conducted in a hydrologically-vulnerable, Mississippi River alluvial-island community, where PFAS contamination of the shallow-alluvial drinking-water aquifer has been documented, but more comprehensive contaminant characterization to inform decision-making is currently lacking. In 2021, we analyzed 510 organics, 34 inorganics, and 3 microbial groups in 11 residential and community locations to assess (1) TW risks beyond recognized PFAS issues, (2) day-to-day and year-to-year risk variability, and (3) suitability of the underlying sandstone aquifer as an alternative source to mitigate TW-PFAS exposures. Seventy-six organics and 25 inorganics were detected. Potential human-health risks of detected TW exposures were explored based on cumulative benchmark-based toxicity quotients (∑TQ). Elevated risks (∑TQ ≥ 1) from organic and inorganic contaminants were observed in all alluvial-aquifer-sourced synoptic samples but not in sandstone-aquifer-sourced samples. Repeated sampling at 3 sites over 52–55 h indicated limited variability in risk over the short-term. Comparable PFAS-specific ∑TQ for spatial-synoptic, short-term (3 days) temporal, and long-term (3 years quarterly) temporal samples indicated that synoptic results provided useful insight into the risks of TW-PFAS exposures at French Island over the long-term. No PFAS detections in sandstone-aquifer-sourced samples over a 3 year period indicated no PFAS-associated risk and supported the sandstone aquifer as an alternative drinking-water source to mitigate community TW-PFAS exposures. This study illustrated the importance of expanded contaminant monitoring of private-well TW, beyond known concerns (in this case, PFAS), to reduce the risks of a range of unrecognized contaminant exposures.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D5EM00005J","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Donahue, L., Gaikowski, M., Hines, R.K., Breitmeyer, S.E., Gordon, S.E., Loftin, K.A., McCleskey, R., Meppelink, S.M., and Schreiner, M., 2025, Tapwater exposures, residential risk, and mitigation in a PFAS-impacted-groundwater community: Environmental Science: Processes and Impacts, 21 p., https://doi.org/10.1039/D5EM00005J.","productDescription":"21 p.","ipdsId":"IP-142462","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":488254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1039/d5em00005j","text":"Publisher Index Page"},{"id":484592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Campbell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.3046523459501,\n 43.87386653369529\n ],\n [\n -91.3046523459501,\n 43.86407274973604\n ],\n [\n -91.28224710242334,\n 43.86407274973604\n ],\n [\n -91.28224710242334,\n 43.87386653369529\n ],\n [\n -91.3046523459501,\n 43.87386653369529\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":205651,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donahue, Lee","contributorId":353363,"corporation":false,"usgs":false,"family":"Donahue","given":"Lee","affiliations":[{"id":84381,"text":"Town of Campbell, WI","active":true,"usgs":false}],"preferred":false,"id":933352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":933353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, Randy K. 0000-0002-5135-3135 rkhines@usgs.gov","orcid":"https://orcid.org/0000-0002-5135-3135","contributorId":3340,"corporation":false,"usgs":true,"family":"Hines","given":"Randy","email":"rkhines@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":933354,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":37464,"text":"WMA - 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Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. 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The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251008","collaboration":"Prepared in cooperation with the Wild Rice Watershed District","usgsCitation":"Groten, J.T., Levin, S.B., Storey, G.G., Coenen, E.N., Blount, J.D., Lund, J.W., and Brannon, D.J., 2025, Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023: U.S. Geological Survey Open-File Report 2025–1008, 38 p., https://doi.org/10.3133/ofr20251008.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154644","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":493754,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118525.htm","linkFileType":{"id":5,"text":"html"}},{"id":483763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1008/coverthb.jpg"},{"id":483764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1008"},{"id":483765,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.XML"},{"id":483766,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1008/images/"},{"id":483767,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483768,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251008/full"}],"country":"United States","state":"Minnesota","otherGeospatial":"Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97,\n 47.5833\n ],\n [\n -97,\n 47\n ],\n [\n -95.25,\n 47\n ],\n [\n -95.25,\n 47.5833\n ],\n [\n -97,\n 47.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70229","usgsCitation":"Osland, M., Bradford, J., Toth, L., Germino, M., Grace, J., Drexler, J.Z., Stagg, C.L., Grossman, E.E., Thorne, K., Romanach, S., Passeri, D., Noe, G.E., Lacy, J.R., Krauss, K., Kowalski, K., Guntenspergen, G.R., Ganju, N., Enwright, N., Carr, J., Byrd, K.B., and Buffington, K., 2025, Ecological thresholds and transformations due to climate change: The role of abiotic stress: Ecosphere, v. 16, no. 4, e70229, p., https://doi.org/10.1002/ecs2.70229.","productDescription":"e70229, p.","ipdsId":"IP-168454","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","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},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70229","text":"Publisher Index Page"},{"id":484845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":222814,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":934118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":934119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":219648,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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2025 - River floods under wetter antecedent conditions deliver coarser sediment to the coast","interactions":[],"lastModifiedDate":"2025-04-15T15:10:08.066152","indexId":"70265714","displayToPublicDate":"2025-04-13T10:05:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"River floods under wetter antecedent conditions deliver coarser sediment to the coast","docAbstract":"Increasing hydrologic volatility—more extreme rain, and larger variations between wet and dry years—has become apparent in some regions, but few data exist to determine how intensifying hydrologic extremes affect sedimentary systems. Using uniquely high-resolution records of fluvial suspended sediment and coastal morphology, we quantify sedimentary responses from a steep, 357-km2 watershed in California under extreme wet and dry hydrologic conditions. In years with multiple 2- to 10-year floods, fluvial sediment coarsened significantly as the wet season progressed, with late-season floods delivering dominantly sand-sized material to the coast. Greater and coarser sediment supply under wetter antecedent conditions affected nearshore geomorphic evolution for 4–5 years. The watershed and coastal changes we documented point to an increasing role of sediment-related hazards (flooding and hillslope erosion) and resources (nearshore accretion) as wet seasons intensify.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL115232","usgsCitation":"East, A.E., Snyder, A.G., Stevens, A.W., Warrick, J.A., Topping, D.J., Thomas, M.A., and Ritchie, A., 2025, River floods under wetter antecedent conditions deliver coarser sediment to the coast: Geophysical Research Letters, v. 52, no. 8, e2025GL115232, 10 p., https://doi.org/10.1029/2025GL115232.","productDescription":"e2025GL115232, 10 p.","ipdsId":"IP-175612","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl115232","text":"Publisher Index Page"},{"id":484583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Lorenzo River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.2795738662301,\n 37.28890656527331\n ],\n [\n -122.2795738662301,\n 36.95309077205526\n ],\n [\n -121.9584157989861,\n 36.95309077205526\n ],\n [\n -121.9584157989861,\n 37.28890656527331\n ],\n [\n -122.2795738662301,\n 37.28890656527331\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Alexander G. 0000-0001-6250-4827 agsnyder@usgs.gov","orcid":"https://orcid.org/0000-0001-6250-4827","contributorId":171654,"corporation":false,"usgs":true,"family":"Snyder","given":"Alexander","email":"agsnyder@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":933372,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":933373,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933374,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267347,"text":"70267347 - 2025 - Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","interactions":[],"lastModifiedDate":"2025-05-20T15:51:41.240547","indexId":"70267347","displayToPublicDate":"2025-04-11T10:50:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21640,"text":"Toxins","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","title":"Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","docAbstract":"As oceans warm, harmful algal blooms (HABs) are expected to increase, including blooms of Pseudo-nitzschia, a diatom that produces domoic acid (DA), which is a potent neurotoxin. Regulatory limits for human consumption (0.075–0.1 mg/kg/day; acute exposure) exist for the Pacific razor clam; however, fisheries currently do not have regulatory limits for chronic low-level exposure to DA even though razor clams can retain DA for over a year after an algal bloom. For bivalves, exposure to marine toxins may disrupt important cellular processes, leading to concerns about effects on their overall health and potential population- and ecosystem-level impacts. Transcriptomics was used to identify differentially expressed genes in razor clams (N = 30) from Long Beach, WA, collected prior to, during, and after a DA-producing bloom. Differentially expressed genes were identified that may indicate exposure of razor clams to DA, including clams with tissue DA concentrations that fall below regulatory limits for human consumption. Targeting these genes in real-time PCR assays may provide an early warning system for routine monitoring of DA in clams. Our results suggest DA exposure is associated with physiological responses ranging from decreased immune function to the potential disruption of cell communication, including retinoic acid catabolic processes, cell adhesion, collagen fibril organization, and immune effector processes. This work may also allow us to examine potential drivers of population-level change and whether chronic lower-level exposure to DA negatively impacts razor clam function, consequently affecting individual and population health.
","language":"English","publisher":"MDPI","doi":"10.3390/toxins17040194","usgsCitation":"Bowen, L., Waters-Dynes, S.C., Ballachey, B., Coletti, H., Forster, Z., Li, J., and Jenner, B., 2025, Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula): Toxins, v. 17, no. 4, 194, 21 p., https://doi.org/10.3390/toxins17040194.","productDescription":"194, 21 p.","ipdsId":"IP-175527","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490137,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/toxins17040194","text":"Publisher Index Page"},{"id":486224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballachey, Brenda 0000-0003-1855-9171","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":264735,"corporation":false,"usgs":false,"family":"Ballachey","given":"Brenda","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":937819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":937820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forster, Zachary","contributorId":355634,"corporation":false,"usgs":false,"family":"Forster","given":"Zachary","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":937821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Ji","contributorId":22916,"corporation":false,"usgs":true,"family":"Li","given":"Ji","email":"","affiliations":[],"preferred":false,"id":937822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jenner, Bradley","contributorId":355636,"corporation":false,"usgs":false,"family":"Jenner","given":"Bradley","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":937823,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273122,"text":"70273122 - 2025 - Multi-Scale Graph Learning for anti-sparse downscaling","interactions":[],"lastModifiedDate":"2025-12-16T16:51:11.338092","indexId":"70273122","displayToPublicDate":"2025-04-11T10:46:24","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Multi-Scale Graph Learning for anti-sparse downscaling","docAbstract":"Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e., fine scales, ≤ 1 km) enables precise interventions to maintain water quality and protect aquatic habitats. Although spatiotemporal models have made substantial progress in spatially coarse time series modeling, challenges persist in predicting at fine spatial scales due to the lack of data at that scale. To address the problem of insufficient fine-scale data, we propose a Multi-Scale Graph Learning (MSGL) method. This method employs a multi-task learning framework where coarse-scale graph learning, bolstered by larger datasets, simultaneously enhances fine-scale graph learning. Although existing multi-scale or multi-resolution methods integrate data from different spatial scales, they often overlook the spatial correspondences across graph structures at various scales. To address this, our MSGL introduces an additional learning task, cross-scale interpolation learning, which leverages the hydrological connectedness of stream locations across coarse- and fine-scale graphs to establish cross-scale connections, thereby enhancing overall model performance. Furthermore, we have broken free from the mindset that multi-scale learning is limited to synchronous training by proposing an Asynchronous Multi-Scale Graph Learning method (ASYNC-MSGL). Extensive experiments demonstrate the state-of-the-art performance of our method for anti-sparse downscaling of daily stream temperatures in the Delaware River Basin, USA, highlighting its potential utility for water resources monitoring and management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the AAAI conference on artificial intelligence","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Association for the Advancement of Artificial Intelligence","doi":"10.1609/aaai.v39i27.35014","usgsCitation":"Fan, Y., Yu, R., Barclay, J.R., Appling, A.P., Sun, Y., Xie, Y., and Jia, X., 2025, Multi-Scale Graph Learning for anti-sparse downscaling, in Proceedings of the AAAI conference on artificial intelligence, v. 39, no. 27, p. 27969-27977, https://doi.org/10.1609/aaai.v39i27.35014.","productDescription":"9 p.","startPage":"27969","endPage":"27977","ipdsId":"IP-167502","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":497731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1609/aaai.v39i27.35014","text":"Publisher Index Page"},{"id":497583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"27","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Yingda","contributorId":352470,"corporation":false,"usgs":false,"family":"Fan","given":"Yingda","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Runlong 0000-0003-4080-2377","orcid":"https://orcid.org/0000-0003-4080-2377","contributorId":352471,"corporation":false,"usgs":false,"family":"Yu","given":"Runlong","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":952394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Yiming","contributorId":352472,"corporation":false,"usgs":false,"family":"Sun","given":"Yiming","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":952396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":952397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266250,"text":"70266250 - 2025 - Detection of Giardia and Cryptosporidium in surface water of a subarctic city","interactions":[],"lastModifiedDate":"2025-05-02T14:34:36.525786","indexId":"70266250","displayToPublicDate":"2025-04-11T09:31:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16699,"text":"Food and Waterborne Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Detection of Giardia and Cryptosporidium in surface water of a subarctic city","title":"Detection of Giardia and Cryptosporidium in surface water of a subarctic city","docAbstract":"Giardia and Cryptosporidium spp. are globally distributed protozoan parasites that can cause gastrointestinal disease in humans and animals. These zoonotic parasites and their ecological relationships have been understudied in Alaska and elsewhere, despite being identified as priority zoonotic pathogens. We aimed to detect and characterize Giardia and Cryptosporidium spp. in waterbodies within Anchorage, Alaska, USA using two methods, including the Environmental Protection Agency (EPA) Method 1623 that relies on microscopy and a molecular detection approach. The molecular approach was ultimately unsuccessful and therefore only data obtained using Method 1623 are presented. Giardia or Cryptosporidium spp. was detected from nine of 15 urban streams and lakes sampled (60%), six of which were positive for both parasites (40%). Fewer than 10 cysts or oocysts were detected in 10 L of surface water. Further research to characterize Giardia and Cryptosporidium beyond the genus level would help elucidate the zoonotic potential and ecology of these parasites within the region and more broadly in Alaska.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fawpar.2025.e00262","usgsCitation":"Ahlstrom, C., Carey, M.P., Menning, D.M., O’Donnell, J.A., and Ramey, A.M., 2025, Detection of Giardia and Cryptosporidium in surface water of a subarctic city: Food and Waterborne Parasitology, v. 39, e00262, 6 p., https://doi.org/10.1016/j.fawpar.2025.e00262.","productDescription":"e00262, 6 p.","ipdsId":"IP-173920","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":487921,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fawpar.2025.e00262","text":"Publisher Index Page"},{"id":485323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.71809212582164,\n 61.26288495513296\n ],\n [\n -150.13097003492274,\n 61.26288495513296\n ],\n [\n -150.13097003492274,\n 61.05787266884491\n ],\n [\n -149.71809212582164,\n 61.05787266884491\n ],\n [\n -149.71809212582164,\n 61.26288495513296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":935084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":935085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":935086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":935087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":935088,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}