In 2021, we initiated fieldwork to assess the relative importance of a staging area for Sterna hirundo (Common Tern) at a pier at the confluence of the Patuxent River and Chesapeake Bay, MD. During the post-breeding periods of 2021 through 2023, we resighted 378 banded Common Terns at this staging area, with individuals originating from 6 breeding colonies. Most banded individuals were from Poplar Island, a major nesting site 50 km north of the pier, with up to 37% of that island's annual hatch-year population observed at this staging area. Additionally, biologists have previously observed staging terns at this site, suggesting these observations do not reflect a change in the species' behavior within the region. Cumulatively, our data suggest that this habitat acts as an important staging area for the Chesapeake Bay's Common Tern population, particularly for those nesting on Poplar Island.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/045.031.0413","usgsCitation":"Springer, B., Sullivan, J.D., Prosser, D.J., Rambo, K., and Price, J., 2025, Common Terns (Sterna hirundo) use of a staging site in the Chesapeake Bay: Northeastern Naturalist, v. 31, no. 4, p. 555-564, https://doi.org/10.1656/045.031.0413.","productDescription":"10 p.","startPage":"555","endPage":"564","ipdsId":"IP-169973","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay, Patuxent River, Poplar Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.47539729451665,\n 38.83723086335985\n ],\n [\n -76.47539729451665,\n 38.64818684791629\n ],\n [\n -76.33733194779678,\n 38.64818684791629\n ],\n [\n -76.33733194779678,\n 38.83723086335985\n ],\n [\n -76.47539729451665,\n 38.83723086335985\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Springer, Benjamin","contributorId":347743,"corporation":false,"usgs":false,"family":"Springer","given":"Benjamin","affiliations":[{"id":52128,"text":"St. Mary’s College of Maryland","active":true,"usgs":false}],"preferred":false,"id":922361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":922362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rambo, Kyle","contributorId":347745,"corporation":false,"usgs":false,"family":"Rambo","given":"Kyle","affiliations":[{"id":83224,"text":"Naval Air Station","active":true,"usgs":false}],"preferred":false,"id":922364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Price, J. Jordan","contributorId":347746,"corporation":false,"usgs":false,"family":"Price","given":"J. Jordan","affiliations":[{"id":52128,"text":"St. Mary’s College of Maryland","active":true,"usgs":false}],"preferred":false,"id":922365,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261849,"text":"sim3529 - 2025 - Map of topographic lineaments interpreted as recent surface ruptures along the Bennett Valley and Southern Maacama Fault Zones, Sonoma County, California","interactions":[],"lastModifiedDate":"2025-07-10T15:31:33.467921","indexId":"sim3529","displayToPublicDate":"2025-01-07T13:37:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3529","displayTitle":"Map of Topographic Lineaments Interpreted As Recent Surface Ruptures Along the Bennett Valley and Southern Maacama Fault Zones, Sonoma County, California","title":"Map of topographic lineaments interpreted as recent surface ruptures along the Bennett Valley and Southern Maacama Fault Zones, Sonoma County, California","docAbstract":"This study documents lidar-illuminated topographic lineaments interpreted as evidence of recent surface fault ruptures and surface ruptures related to distributed deformation along the Bennett Valley Fault Zone and the southernmost Maacama Fault Zone in the northern San Francisco Bay area (fig. 1, on map sheet). Together, these fault zones form a structural connection across a right stepover between the main Maacama Fault Zone and the Rodgers Creek Fault, overlapping principal strands of the San Andreas plate boundary system north of San Francisco Bay (figs. 1, 2, on map sheet) that accommodate about a quarter of the ~40 millimeters per year of regional dextral tectonic slip (Parsons and others, 2013).
Although much of the Bennett Valley Fault Zone is seismically active (McLaughlin and others, 2012; Sowers and others, 2010), only the north end of the fault zone (the “Spring Valley strand,” indicated on southern map panel of map sheet and labeled “D” in figure 2, on map sheet) was previously known to have youthful geomorphic expression and to displace Holocene deposits (McLaughlin and others, 2008; Sowers and others, 2010; Sowers and others, 2016). Holocene activity along the length of the Bennett Valley Fault Zone and southernmost Maacama Fault Zone, with possible implications for rupture propagation, continuity, and slip transfer, had not been identified. However, fault splays that project eastward from the Rodgers Creek Fault have been mapped and hypothesized to accommodate slip transfer to the Bennett Valley Fault Zone (Hecker and Randolph Loar, 2018). The generally subtle and distributed nature of surface-rupture evidence along the Bennett Valley and southernmost Maacama Fault Zones, and extensive vegetation cover, had left recent faulting previously unmapped along most of the zone.
The map presented here represents a new compilation of inferred surface-rupture features detected using high-resolution topographic lidar data from an airborne lidar survey of Sonoma County, California (OpenTopography, 2014). These data, which enable subtle topographic features to be discerned, indicate that recent (likely Holocene) surface ruptures extend throughout the Bennett Valley and southernmost Maacama Fault Zones.
The rupture-lineament map was created using a GIS (geographic information system) framework and is included herein as an image map at a scale of 1:36,000 and as digital datasets (included as supplemental information to this report). The mapping is intended to lay the groundwork for future studies designed to better characterize how plate-boundary slip is accommodated on this important and complex system of faults.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3529","usgsCitation":"Hecker, S., 2024, Map of topographic lineaments interpreted as recent surface ruptures along the Bennett Valley and Southern Maacama Fault Zones, Sonoma County, California: U.S. Geological Survey Scientific Investigations Map 3529, scale 1:36,000, pamphlet 5 p., https://doi.org/10.3133/sim3529.","productDescription":"Pamphlet: iv, 5 p.; 1 Sheet: 50.91 x 40.68 inches; Supplemental Information","numberOfPages":"5","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-143849","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":465535,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3529/sim3529_sheet.pdf","text":"Sheet 1","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3529/sim3529_pamphlet.pdf","text":"Pamphlet","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465533,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3529/covrthb.jpg"},{"id":465536,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3529/sim3529_supInfo.zip","text":"Supplemental Information","size":"1 MB","linkFileType":{"id":6,"text":"zip"}},{"id":492016,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118275.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"Sonoma County","otherGeospatial":"Bennett Valley and Southern Maacama fault zones","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.125,\n 39\n ],\n [\n -123.125,\n 37.375\n ],\n [\n -121.5,\n 37.375\n ],\n [\n -121.5,\n 39\n ],\n [\n -123.125,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
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Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest R2 value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.
","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.20662","usgsCitation":"Krueger, K., Thompson, A., Li, Q., Radatz, A., Cooley, E., Stuntebeck, T.D., Winslow, C., Oldfield, E., and Ruark, M., 2025, Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models: Journal of Environmental Quality, v. 54, no. 2, p. 450-464, https://doi.org/10.1002/jeq2.20662.","productDescription":"15 p.","startPage":"450","endPage":"464","ipdsId":"IP-154553","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.20662","text":"Publisher Index Page"},{"id":466018,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.67253208931788,\n 46.453472239766626\n ],\n [\n -96.53357725011335,\n 43.52335979339341\n ],\n [\n -91.25197772229393,\n 43.462001703986346\n ],\n [\n -91.04740751323666,\n 42.83358085977116\n ],\n [\n -90.69567476916163,\n 42.6339355953327\n ],\n [\n -88.04201458813054,\n 42.48198884581308\n ],\n [\n -87.61145222121533,\n 43.8914402724194\n ],\n [\n -92.82542026317009,\n 45.7061001895253\n ],\n [\n -96.67253208931788,\n 46.453472239766626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Krueger, Kelsey 0000-0002-2412-0694","orcid":"https://orcid.org/0000-0002-2412-0694","contributorId":347852,"corporation":false,"usgs":false,"family":"Krueger","given":"Kelsey","affiliations":[{"id":83262,"text":"University of Wisconsin -Madison","active":true,"usgs":false}],"preferred":false,"id":922651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":922652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Qiang","contributorId":197310,"corporation":false,"usgs":false,"family":"Li","given":"Qiang","email":"","affiliations":[],"preferred":false,"id":922653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Radatz, Amber","contributorId":217384,"corporation":false,"usgs":false,"family":"Radatz","given":"Amber","email":"","affiliations":[{"id":39612,"text":"UW Madison-Extension, UW Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooley, Eric","contributorId":151059,"corporation":false,"usgs":false,"family":"Cooley","given":"Eric","email":"","affiliations":[{"id":18174,"text":"University of Wisconsin-Extension Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winslow, Christopher J.","contributorId":347853,"corporation":false,"usgs":false,"family":"Winslow","given":"Christopher J.","affiliations":[{"id":83263,"text":"Ohio Sea Grant College Program","active":true,"usgs":false}],"preferred":false,"id":922657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oldfield, Emily 0000-0002-6181-1267","orcid":"https://orcid.org/0000-0002-6181-1267","contributorId":347854,"corporation":false,"usgs":false,"family":"Oldfield","given":"Emily","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":922658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ruark, Matthew","contributorId":151056,"corporation":false,"usgs":false,"family":"Ruark","given":"Matthew","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":922659,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70264245,"text":"70264245 - 2025 - Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species","interactions":[],"lastModifiedDate":"2025-03-10T14:26:58.704938","indexId":"70264245","displayToPublicDate":"2025-01-07T09:22:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species","docAbstract":"The Great Lakes Restoration Initiative aims to protect and restore the nation’s largest freshwater resource, in part, by furthering our understanding of the effects of contaminants of emerging concern (CECs) and chemical mixtures on aquatic and terrestrial organisms. To address this goal, an interagency team conducted field studies at sites along the Maumee River in Ohio, USA, in 2016–2017, monitoring CEC levels along with diverse in vitro and in vivo biological effects in ecologically relevant species (fathead minnows, tree swallows, and golden clams). The objective of the present work was to prioritize the CECs in these studies for further monitoring and assessment by determining if there are patterns in chemical–bioeffect relations across data sets, species, and response types that indicate relatively high or low hazard to aquatic life from CEC exposure. Of the 748 monitored chemicals, 425 were detected and were analyzed for covariance with bioeffects. All 748 chemicals were placed into 10 bins based on their frequencies of monitoring, detection, and covariance with bioeffects across studies and species. We describe how chemicals can be prioritized across bins to aid monitoring and assessment efforts. Our approach using effects-based monitoring data is especially useful for prioritizing chemicals with little or no traditional toxicity testing data. Similar evidence-based prioritizations will allow agencies to more efficiently allocate limited resources to improve the ability to protect aquatic and terrestrial organisms from adverse impacts due to contaminant exposure.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae094","usgsCitation":"Vitense, K., Loken, L.C., Maloney, E., Blackwell, B., Collette, T.W., Corsi, S., Custer, C.M., Davenport, E., Kohno, S., and Hummel, S.E., 2025, Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species: Environmental Toxicology and Chemistry, v. 44, no. 3, p. 764-776, https://doi.org/10.1093/etojnl/vgae094.","productDescription":"13 p.","startPage":"764","endPage":"776","ipdsId":"IP-165045","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":487746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae094","text":"Publisher Index Page"},{"id":483135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.4,\n 41.75\n ],\n [\n -83.9,\n 41.75\n ],\n [\n -83.9,\n 41.35\n ],\n [\n -83.4,\n 41.35\n ],\n [\n -83.4,\n 41.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vitense, Kelsey","contributorId":195720,"corporation":false,"usgs":false,"family":"Vitense","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":930184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Erin C","contributorId":223418,"corporation":false,"usgs":false,"family":"Maloney","given":"Erin C","affiliations":[{"id":40713,"text":"USACE Chicago District","active":true,"usgs":false}],"preferred":false,"id":930186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":930187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collette, Timothy W.","contributorId":217482,"corporation":false,"usgs":false,"family":"Collette","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":930188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":930190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davenport, Erik","contributorId":245994,"corporation":false,"usgs":false,"family":"Davenport","given":"Erik","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":930191,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kohno, Satomi","contributorId":264174,"corporation":false,"usgs":false,"family":"Kohno","given":"Satomi","email":"","affiliations":[],"preferred":false,"id":930192,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hummel, Stephanie E.","contributorId":244149,"corporation":false,"usgs":false,"family":"Hummel","given":"Stephanie","email":"","middleInitial":"E.","affiliations":[{"id":25470,"text":"U.S. Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":930193,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70262108,"text":"70262108 - 2025 - Exposure, sensitivity, or adaptive capacity? Reviewing assessments that use only two of three elements of climate change vulnerability","interactions":[],"lastModifiedDate":"2025-01-14T15:24:57.27176","indexId":"70262108","displayToPublicDate":"2025-01-07T09:20:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Exposure, sensitivity, or adaptive capacity? Reviewing assessments that use only two of three elements of climate change vulnerability","docAbstract":"As climate change accelerates, understanding which species are most vulnerable and why they are vulnerable will be vital to inform conservation action. Climate change vulnerability assessments (CCVAs) are tools to assess species' responses to climate change, detect drivers of vulnerability, and inform conservation planning. CCVAs are commonly composed of three elements: exposure, sensitivity, and adaptive capacity. Incorporating all three elements can be challenging, and including only two of the three elements may be a more feasible approach in many systems. Although two-element CCVA approaches have become more common, their utility and procedures remain poorly documented. We conducted a literature review to explore the scope, methods, and rationale of CCVAs that use a two-element approach to assess vertebrate vulnerability. Despite the potential to expand CCVAs into understudied systems, two-element assessments had similar geographic and taxonomic biases as those previously detected in CCVAs in general. Methods varied, yet we found that variables used in two-element studies could be condensed into standardized categories to enhance comparability. Finally, limitations in data availability and computational resources were common rationales for using a two-element approach. By clarifying the purposes, opportunities, and limitations of two-element assessment, this review can aid in selecting appropriate methods for CCVAs.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.13293","usgsCitation":"Hyman, A., Crone, E., Benson, A., Dunham, J., Lynch, A., Thompson, L., and Mims, M.C., 2025, Exposure, sensitivity, or adaptive capacity? Reviewing assessments that use only two of three elements of climate change vulnerability: Conservation Science and Practice, v. 7, no. 1, e13293, 14 p., https://doi.org/10.1111/csp2.13293.","productDescription":"e13293, 14 p.","ipdsId":"IP-146253","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":466663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.13293","text":"Publisher Index Page"},{"id":466214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyman, Amanda A.","contributorId":348177,"corporation":false,"usgs":false,"family":"Hyman","given":"Amanda A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":923119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crone, Erin R.","contributorId":348203,"corporation":false,"usgs":false,"family":"Crone","given":"Erin R.","affiliations":[],"preferred":false,"id":923201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":202078,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":923120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":923121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":923122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":212190,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":923123,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":923124,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262111,"text":"70262111 - 2025 - Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems","interactions":[],"lastModifiedDate":"2025-01-14T15:19:09.571057","indexId":"70262111","displayToPublicDate":"2025-01-07T08:12:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17114,"text":"Natural Hazards and Earth Systems Sciences (NHESS)","active":true,"publicationSubtype":{"id":10}},"title":"Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems","docAbstract":"Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.","language":"English","publisher":"EGU-Copernicus Publications","doi":"10.5194/nhess-25-169-2025","usgsCitation":"Mirus, B., Bogaard, T., Greco, R., and Stähli, M., 2025, Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems: Natural Hazards and Earth Systems Sciences (NHESS), v. 25, no. 1, p. 169-182, https://doi.org/10.5194/nhess-25-169-2025.","productDescription":"14 p.","startPage":"169","endPage":"182","ipdsId":"IP-159239","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":466664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-169-2025","text":"Publisher Index Page"},{"id":466212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Sitka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.68999201861402,\n 58.275013995525285\n ],\n [\n -136.68999201861402,\n 56.12160659807034\n ],\n [\n -134.31603477353784,\n 56.12160659807034\n ],\n [\n -134.31603477353784,\n 58.275013995525285\n ],\n [\n -136.68999201861402,\n 58.275013995525285\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":923125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bogaard, Thom","contributorId":348180,"corporation":false,"usgs":false,"family":"Bogaard","given":"Thom","affiliations":[{"id":33885,"text":"Delft University of Technology, Netherlands","active":true,"usgs":false}],"preferred":false,"id":923126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greco, Roberto","contributorId":348181,"corporation":false,"usgs":false,"family":"Greco","given":"Roberto","affiliations":[{"id":83312,"text":"University of Campania, Italy","active":true,"usgs":false}],"preferred":false,"id":923127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stähli, Manfred","contributorId":348182,"corporation":false,"usgs":false,"family":"Stähli","given":"Manfred","affiliations":[{"id":83313,"text":"Swiss Federal Research Institute (WSL)","active":true,"usgs":false}],"preferred":false,"id":923128,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262760,"text":"70262760 - 2025 - Challenges and opportunities for data integration to improve estimation of migratory connectivity","interactions":[],"lastModifiedDate":"2025-02-11T15:46:13.615241","indexId":"70262760","displayToPublicDate":"2025-01-06T10:12:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Challenges and opportunities for data integration to improve estimation of migratory connectivity","docAbstract":"Protection of critically endangered species requires identification of factors limiting their survival and growth. Previous studies have demonstrated that unionid mussels are sensitive to some chemicals and the sensitivity was similar among different taxonomic families and tribes of mussels. However, common species of mussels were generally used in these previous studies; little is known about the sensitivity of endangered and threatened mussels relative to common species. The objective of this study was to evaluate the sensitivity of a critically endangered mussel (Tennessee bean, Venustaconcha trabalis) to seven chemicals with different modes of toxic action (ammonia, chloride, nitrite, potassium, cobalt, manganese, nickel) in acute 96-h exposures and to three chemicals (nitrite, cobalt, iron) in chronic 28-d exposures conducted following standard methods. A commonly tested mussel (fatmucket, Lampsilis siliquoidea) was also tested side-by-side with Tennessee bean in chronic exposures. Test chemicals were selected based on (1) chemicals of potential concern found in a review of existing data for the river where a population of Tennessee bean occurs or was historically present, (2) chemicals to which other mussels are sensitive, or (3) chemicals that had not been previously tested with mussels. Acute 50% effect concentrations (EC50s) for the seven chemicals from the Tennessee bean tests were within or close to the range of EC50s for other mussel species tested in previous studies, and chronic 20% effect concentrations for the three chemicals were similar between Tennessee bean and fatmucket, indicating the endangered species has sensitivity similar to other tested mussel species. Inclusion of the new mussel data in existing toxicity databases for freshwater organisms would rank one or more mussel species among the four most sensitive species to ammonia, chloride, potassium, and nickel in acute exposures and to nitrite, cobalt, and iron in chronic exposures.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae092","usgsCitation":"Wang, N., Ivey, C.D., Cleveland, D.M., Kunz, J.L., Schapansky, R., Lane, T.W., and Barnhart, M., 2025, Evaluation of the sensitivity of a federally endangered freshwater mussel (Venustaconcha trabalis) to selected chemicals: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgae092.","ipdsId":"IP-170240","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":487701,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae092","text":"Publisher Index Page"},{"id":482561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schapansky, Rebecca","contributorId":351559,"corporation":false,"usgs":false,"family":"Schapansky","given":"Rebecca","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":928914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, Timothy W.","contributorId":333081,"corporation":false,"usgs":false,"family":"Lane","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":79722,"text":"Virginia Department of Wildlife Resoures","active":true,"usgs":false}],"preferred":false,"id":928915,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnhart, M. 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Christopher","affiliations":[],"preferred":false,"id":928916,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263985,"text":"70263985 - 2025 - Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets","interactions":[],"lastModifiedDate":"2025-05-13T15:57:02.42202","indexId":"70263985","displayToPublicDate":"2025-01-06T09:16:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20195,"text":"Applied Computing and Geosciences.","active":true,"publicationSubtype":{"id":10}},"title":"Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets","docAbstract":"Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.acags.2024.100215","usgsCitation":"Smith, C., Bernier, J., Ellis, A.M., and Smith, K., 2025, Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets: Applied Computing and Geosciences., v. 25, 100215, 12 p., https://doi.org/10.1016/j.acags.2024.100215.","productDescription":"100215, 12 p.","ipdsId":"IP-168346","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":490116,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.acags.2024.100215","text":"Publisher Index Page"},{"id":482794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama. Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.28354140678013,\n 30.419771757548105\n ],\n [\n -88.46387852940934,\n 30.419771757548105\n ],\n [\n -88.46387852940934,\n 30.31160215154773\n ],\n [\n -88.28354140678013,\n 30.31160215154773\n ],\n [\n -88.28354140678013,\n 30.419771757548105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929422,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263830,"text":"70263830 - 2025 - Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries","interactions":[],"lastModifiedDate":"2025-02-25T15:13:12.08078","indexId":"70263830","displayToPublicDate":"2025-01-06T09:07:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries","docAbstract":"Ongoing anthropogenic activities and analytical advancements yield continuously expanding lists of environmental contaminants. This represents a challenge to environmental managers, who must prioritize chemicals for management actions (e.g., restriction, regulation, remediation) but are often hindered by resource limitations. To help facilitate prioritization efforts, this study presents several strategies for deriving environmental hazard concentrations using publicly accessible data and open-source computational tools. Using a Great Lakes tributaries aquatic monitoring dataset as a case study, environmental hazard concentrations were obtained or derived for 334 organic chemicals. These concentrations were based on (1) current water quality guidelines; (2) apical screening values; (3) apical and (4) nonapical effect concentrations from the ECOTOXicology Knowledgebase; (5) in vitro effect concentrations from the ToxCast database; (6) cytotoxic burst concentrations collated from the Comptox Dashboard; (7) “estimated screening values” derived from modeled or estimated data and available from various regulatory and nonregulatory agencies; (8) pharmaceutical potency estimates from the MaPPFAST database; and (9) quantitative structure-activity relationship (QSAR)–derived acute toxicity estimates. Environmental fate data included aquatic half-lives and bioconcentration factors collated from the Comptox Dashboard or estimated using QSARs. To identify patterns that could be used for characterization, availability of ecotoxicological concentrations and environmental fate data were evaluated. Furthermore, exceedances of hazard concentrations were evaluated and compared across diverse ecotoxicological data types. Altogether, by providing detailed methodology and practical examples generated with real monitoring data, this study demonstrated that these hazard concentration derivation strategies can be efficiently and effectively used with large, complex datasets and identified critical considerations for future prioritization efforts.
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Sites represented a range of urban to agricultural, forested, and wetland land uses and included a gradient of wastewater treatment effluent from zero to 44% of annual streamflow. Several sites also had airport influence. Twenty-one of 32 targeted PFAS compounds were detected in POCIS samplers, of which, 16 had available POCIS sampling rates, enabling time-weighted water concentration estimates and comparison with available effects data. Estimated water concentrations were compared with published water quality guidelines (available for nine PFAS), effect concentrations reported in primary literature within the ECOTOX Knowledgebase for apical endpoints (10 PFAS) and nonapical endpoints (10 PFAS), and in vitro high-throughput screening data from the U.S. Environmental Protection Agency Toxicity Forecaster (ToxCast; 14 PFAS). Based on a conservative evaluation approach that was also weighted for persistence and limitations in available toxicological information, five individual PFAS, including perfluorooctanesulfonic acid, perfluorohexanesulfonic acid, perfluorobutanesulfonic acid, perfluorooctanoic acid, and perfluorononanoic acid were identified as warranting additional investigation. Possible increased potency of PFAS mixtures over individual chemical effects, estimated by summation of exposure-activity ratios (EARs) for chemicals that influence common ToxCast assays and specified gene targets, indicated that EAR values increased up to 5.6-fold over individual chemicals, with up to 14 chemicals contributing to mixture effect predictions. Potential for biological effects from PFAS, as estimated by summed exposure-activity ratios, were correlated with urban land use and the proportion of streamflow contributed by wastewater effluent.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1093/etojnl/vgae053","usgsCitation":"Corsi, S., Loken, L.C., Ankley, G.T., Alvarez, D.A., and Villeneuve, D.L., 2025, Potential for biological effects of per- and polyfluoroalkyl substances in Great Lakes tributaries and associations with land cover and wastewater effluent: Environmental Toxicology and Chemistry, v. 44, no. 6, p. 1706-1722, https://doi.org/10.1093/etojnl/vgae053.","productDescription":"17 p.","startPage":"1706","endPage":"1722","ipdsId":"IP-159605","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":495738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae053","text":"Publisher Index Page"},{"id":495602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United Staes","otherGeospatial":"Great Lakes tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.57691865567881,\n 49.80505886092908\n ],\n [\n -92.57691865567881,\n 40.630914911656845\n ],\n [\n -75.84891837004692,\n 40.630914911656845\n ],\n [\n -75.84891837004692,\n 49.80505886092908\n ],\n [\n -92.57691865567881,\n 49.80505886092908\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ankley, Gerald T.","contributorId":361472,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald","middleInitial":"T.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":948871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":948872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Villeneuve, Daniel L.","contributorId":361475,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","middleInitial":"L.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":948873,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262012,"text":"70262012 - 2025 - Automating physics-based models to estimate thermoelectric-power water use","interactions":[],"lastModifiedDate":"2025-01-10T17:08:02.343623","indexId":"70262012","displayToPublicDate":"2025-01-05T11:02:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Automating physics-based models to estimate thermoelectric-power water use","docAbstract":"Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106265","usgsCitation":"Harris, M.A., Diehl, T.H., Gorman Sanisaca, L.E., Galanter, A.E., Lombard, M.A., Skinner, K.D., Chamberlin, C.A., McCarthy, B.A., Niswonger, R.G., Stewart, J.S., and Valseth, K., 2025, Automating physics-based models to estimate thermoelectric-power water use: Environmental Modelling and Software, v. 185, 106265, 16 p., https://doi.org/10.1016/j.envsoft.2024.106265.","productDescription":"106265, 16 p.","ipdsId":"IP-156740","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":466666,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106265","text":"Publisher Index Page"},{"id":466004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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Reduced taxonomic α-diversity is often reported under land use change, yet the impacts could be different at larger spatial scales (i.e., γ-diversity), either due to reduced β-diversity amplifying diversity loss or increased β-diversity dampening diversity loss. Additionally, studies often focus on taxonomic diversity, while other important biodiversity components, including phylogenetic diversity, can exhibit differential responses. Here, we evaluated how agricultural and urban land use alters the taxonomic and phylogenetic α-, β-, and γ-diversity of an important pollinator taxon—bees. Using a multicontinental dataset of 3117 bee assemblages from 157 studies, we found that taxonomic α-diversity was reduced by 16%–18% in both agricultural and urban habitats relative to natural habitats. Phylogenetic α-diversity was decreased by 11%–12% in agricultural and urban habitats. Compared with natural habitats, taxonomic and phylogenetic β-diversity increased by 11% and 6% in urban habitats, respectively, but exhibited no systematic change in agricultural habitats. We detected a 22% decline in taxonomic γ-diversity and a 17% decline in phylogenetic γ-diversity in agricultural habitats, but γ-diversity of urban habitats was not significantly different from natural habitats. These findings highlight the threat of agricultural expansions to large-scale bee diversity due to systematic γ-diversity decline. In addition, while both urbanization and agriculture lead to consistent declines in α-diversity, their impacts on β- or γ-diversity vary, highlighting the need to study the effects of land use change at multiple scales.
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Despite its ecological and economic importance, surprisingly little is known about red snapper biology and habitat use on the southeast United States Atlantic continental shelf (SEUS). We used data from a long-term baited trap and video survey (2011–2022), as well as from remotely operated vehicle (ROV) sampling (2021–2023), to quantify temporal changes in relative abundance, patterns of spatial distribution, and habitat use of red snapper in the SEUS. Using generalized additive models, we showed that red snapper increased in relative abundance from 2011 to 2022 by 960% in traps and 1,141% in video samples. Red snapper relative abundance was highest in mid-shelf waters off the east coast of Florida, Georgia, and, to a lesser extent, off the Outer Banks of North Carolina; red snapper were less common off southern North Carolina and South Carolina. Highest relative abundance of red snapper occurred in locations with a moderate amount of natural structured habitat and high seafloor complexity and were never observed at randomly selected ROV stations (n = 197) lacking structured habitat. These results increase our understanding of the spatial and temporal distribution of red snapper, improve our knowledge of red snapper habitat use, and can be used when scaling local density estimates to the entire SEUS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107200","usgsCitation":"Bacheler, N., Patterson III, W., Tarnecki, J., Shertzer, K., Buckel, J., Hostetter, N.J., Pacifici, K., Zulian, V., and Bubley, W., 2025, Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf: Fisheries Research, v. 281, 107200, 13 p., https://doi.org/10.1016/j.fishres.2024.107200.","productDescription":"107200, 13 p.","ipdsId":"IP-160875","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":486926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2024.107200","text":"Publisher Index Page"},{"id":482442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","otherGeospatial":"southeastern United States Atlantic continental shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.92593395494507,\n 33.15275092248328\n ],\n [\n -81.99045643689327,\n 31.10056957805797\n ],\n [\n -80.87712766876851,\n 28.48701241069105\n ],\n [\n -80.3042465673629,\n 31.325404220996276\n ],\n [\n -76.71024593975332,\n 34.122762076854926\n ],\n [\n -76.22924401859534,\n 35.13912357508609\n ],\n [\n -79.92593395494507,\n 33.15275092248328\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.13968222172028,\n 19.755747085043822\n ],\n [\n -155.13968222172028,\n 19.69242312727401\n ],\n [\n -155.07419576383438,\n 19.69242312727401\n ],\n [\n -155.07419576383438,\n 19.755747085043822\n ],\n [\n -155.13968222172028,\n 19.755747085043822\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"281","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bacheler, Nathan M.","contributorId":351435,"corporation":false,"usgs":false,"family":"Bacheler","given":"Nathan M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patterson III, William F.","contributorId":351436,"corporation":false,"usgs":false,"family":"Patterson III","given":"William F.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarnecki, Joseph H.","contributorId":351437,"corporation":false,"usgs":false,"family":"Tarnecki","given":"Joseph H.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shertzer, Kyle W.","contributorId":351439,"corporation":false,"usgs":false,"family":"Shertzer","given":"Kyle W.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckel, Jeffrey A.","contributorId":351441,"corporation":false,"usgs":false,"family":"Buckel","given":"Jeffrey A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":928519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pacifici, Krishna","contributorId":351444,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zulian, Viviane","contributorId":351446,"corporation":false,"usgs":false,"family":"Zulian","given":"Viviane","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928521,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bubley, Walter J.","contributorId":351447,"corporation":false,"usgs":false,"family":"Bubley","given":"Walter J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":928522,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261922,"text":"70261922 - 2025 - Evaluating a simulation-based wildfire burn probability map for the conterminous US","interactions":[],"lastModifiedDate":"2025-01-03T15:33:59.530102","indexId":"70261922","displayToPublicDate":"2025-01-02T09:26:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating a simulation-based wildfire burn probability map for the conterminous US","docAbstract":"Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography and ignition locations, and BP maps are key components of wildfire risk assessments.
Few studies have compared BP maps with real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous US based on the large fire simulation model FSim.
We compared BP with observed wildfires from 2016 to 2022 across 128 regions representing similar fire regimes (‘pyromes’). We evaluated the distribution of burned areas across BP values, and compared burned area distributions among fire size classes.
Across all pyromes, mean BP was moderately correlated with observed burned area. An average of 71% of burned area occurred in higher-BP classes, vs 79% expected. BP underpredicted burned area in the Mountain West, especially for extremely large fires.
The FSim BP map was useful for estimating subsequent wildfire hazard, but may have underestimated burned areas where input data did not reflect recent climate change, vegetation change or human ignition patterns.
Our evaluations indicate that caution is needed when relying on simulation-based BP maps to inform management decisions. Our results also highlight potential opportunities to improve model estimates.
The protection of headwater streams faces increasing challenges, exemplified by limited global recognition of headwater contributions to watershed resiliency and a recent US Supreme Court decision limiting federal safeguards. Despite accounting for ~77% of global river networks, the lack of adequate headwaters protections is caused, in part, by limited information on their extent and functions—in particular, their flow regimes, which form the foundation for decision-making regarding their protection. Yet, headwater streamflow is challenging to comprehensively measure and model; it is highly variable and sensitive to changes in land use, management and climate. Modelling headwater streamflow to quantify its cumulative contributions to downstream river networks requires an integrative understanding across local hillslope and channel (that is, watershed) processes. Here we begin to address this challenge by proposing a consistent definition for headwater systems and streams, evaluating how headwater streamflow is characterized and advocating for closing gaps in headwater streamflow data collection, modelling and synthesis.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00351-1","usgsCitation":"Golden, H.E., Christiensen, J., McMillan, H., Kelleher, C.A., Lane, C., Husic, A., Li, L., Ward, A., Hammond, J., Seybold, E.C., Jaeger, K.L., Zimmer, M.A., Sando, R., Jones, C., Segura, C., Mahoney, D.T., Price, A.N., and Chang, F., 2025, Advancing the science of headwater streamflow for global water protection: Nature Water, v. 3, p. 16-26, https://doi.org/10.1038/s44221-024-00351-1.","productDescription":"11 p.","startPage":"16","endPage":"26","ipdsId":"IP-161519","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":498448,"rank":2,"type":{"id":41,"text":"Open 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Hilary","contributorId":176321,"corporation":false,"usgs":false,"family":"McMillan","given":"Hilary","email":"","affiliations":[],"preferred":false,"id":922543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelleher, Christa A.","contributorId":46417,"corporation":false,"usgs":true,"family":"Kelleher","given":"Christa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":922544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":922524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Husic, Admin 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0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922515,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Seybold, Erin C. 0000-0002-0365-2333","orcid":"https://orcid.org/0000-0002-0365-2333","contributorId":340201,"corporation":false,"usgs":false,"family":"Seybold","given":"Erin","email":"","middleInitial":"C.","affiliations":[{"id":35641,"text":"Kansas Geological Survey","active":true,"usgs":false}],"preferred":false,"id":922528,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922516,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zimmer, Margaret Ann 0000-0001-8287-1923","orcid":"https://orcid.org/0000-0001-8287-1923","contributorId":337488,"corporation":false,"usgs":true,"family":"Zimmer","given":"Margaret","email":"","middleInitial":"Ann","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922518,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sando, Roy 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Nathan","contributorId":295982,"corporation":false,"usgs":false,"family":"Jones","given":"C. Nathan","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":922520,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Segura, Catalina","contributorId":192222,"corporation":false,"usgs":false,"family":"Segura","given":"Catalina","email":"","affiliations":[],"preferred":false,"id":922523,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mahoney, D. Tyler 0000-0003-0523-508X","orcid":"https://orcid.org/0000-0003-0523-508X","contributorId":304419,"corporation":false,"usgs":false,"family":"Mahoney","given":"D.","email":"","middleInitial":"Tyler","affiliations":[{"id":66062,"text":"University of Louisville","active":true,"usgs":false}],"preferred":false,"id":922525,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Price, Adam N. 0000-0002-7211-4758","orcid":"https://orcid.org/0000-0002-7211-4758","contributorId":295971,"corporation":false,"usgs":false,"family":"Price","given":"Adam","email":"","middleInitial":"N.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":922522,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Chang, Frederick","contributorId":347820,"corporation":false,"usgs":false,"family":"Chang","given":"Frederick","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":922526,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70267414,"text":"70267414 - 2025 - Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal","interactions":[],"lastModifiedDate":"2025-05-23T15:38:31.239395","indexId":"70267414","displayToPublicDate":"2025-01-01T10:31:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19856,"text":"Laurentian","active":true,"publicationSubtype":{"id":10}},"title":"Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal","docAbstract":"The Sandusky River, Ohio, USA, has experienced more than a century of alterations, including dam implementation and removal, causing a cascade of habitat changes. The physical changes in the river led to establishment of several invasive species. Ten hoop-net sampling sites, spaced about 500 m apart were established in the river to monitor fish assemblage and their habitat preferences. Four 10-d sampling events were completed from April through October 2021. Ordination analyses were used to assess fish-assemblage structure seasonably, species-habitat relationships, and life-history strategies of 31 species. Generalized linear mixed-effects models were used to assess temporal factors that may drive diversity and community assemblage. Models indicated increased species richness after removal of the dam. Presence and proportion of catch data were compared to Ohio Environmental Protection Agency 2009 pre-dam-removal data to further assess changes in fish assemblage. Several species, especially catostomids, have begun to use the habitat downstream of the former dam, altering fish assemblage throughout the river. We expect shifts in assemblage structure to persist, making continued monitoring essential for understanding how non-native and recreationally important species continue to respond to dam removal.
","language":"English","publisher":"Great Lakes Fishery Commission","doi":"10.70227/GDZU9409","usgsCitation":"Schulz, K., Acre, M.R., Mueller, A.T., Wamboldt, J.J., Broaddus, D., Hessler, T., Wilson, T., Mapes, R., Amberg, J., and Calfee, R.D., 2025, Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal: Laurentian, 2025-01, 26 p., https://doi.org/10.70227/GDZU9409.","productDescription":"2025-01, 26 p.","ipdsId":"IP-151712","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":498245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.70227/gdzu9409","text":"Publisher Index Page"},{"id":486517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Sandusky River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.00181931823779,\n 41.45338855338082\n ],\n [\n -83.09113294485806,\n 41.45338855338082\n ],\n [\n -83.09113294485806,\n 41.411024886695174\n ],\n [\n -83.00181931823779,\n 41.411024886695174\n ],\n [\n -83.00181931823779,\n 41.45338855338082\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulz, Kailee Amanda 0000-0002-0998-7951","orcid":"https://orcid.org/0000-0002-0998-7951","contributorId":339886,"corporation":false,"usgs":true,"family":"Schulz","given":"Kailee Amanda","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":938141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Andrew T. 0000-0001-8566-8023","orcid":"https://orcid.org/0000-0001-8566-8023","contributorId":238278,"corporation":false,"usgs":true,"family":"Mueller","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":192,"text":"Columbia Environmental Research 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0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":938149,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938150,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273770,"text":"70273770 - 2025 - Wind River subbasin restoration: Annual report of U.S. Geological Survey activities January 2023 through December 2023","interactions":[],"lastModifiedDate":"2026-01-28T15:33:34.368704","indexId":"70273770","displayToPublicDate":"2025-01-01T09:19:45","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":156,"text":"Annual Report","active":false,"publicationSubtype":{"id":3}},"title":"Wind River subbasin restoration: Annual report of U.S. Geological Survey activities January 2023 through December 2023","docAbstract":"We sampled juvenile wild Oncorhynchus mykiss (Steelhead Trout) in headwater streams of the Wind River, WA, to characterize population attributes and investigate life-history metrics, particularly migratory patterns, and early life-stage survival. We used passive integrated transponder (PIT) tagging and a series of instream PIT-tag interrogation systems (PTISs) to track juveniles and adults. The Wind River subbasin is considered a wild Steelhead refuge by Washington Department of Fish and Wildlife (WDFW). No hatchery Steelhead Trout have been released in the Wind River subbasin since 1997, and hatchery adults are estimated at less than one percent of spawners in most years. Over twenty years of Steelhead Trout status and trend monitoring and research in the subbasin is contributing to understanding of population response to numerous restoration actions in the subbasin, including removal of Hemlock Dam from Trout Creek in 2009, which had an inadequate adult ladder and contributed to increased water temperatures.
Data from our study, and companion work by Washington Department of Fish and Wildlife, are contributing to the Columbia Basin Fish and Wildlife Program (2008) Research, Monitoring, and Evaluation (RM&E) Strategy of Fish Population Status Monitoring. Specifically, this work addresses the sub-strategies of 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and Uncertainties Research regarding differing life histories of a wild Steelhead Trout population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives.
During summer and fall 2023, we PIT-tagged 1,294 Steelhead Trout parr (age-0 and age-1), in the Trout Creek and upper Wind River watersheds. Age-0 parr were at high abundance due to a strong spawning run in 2023 (estimate of 814 adults from September snorkel survey compared to 22-year median of 450; Charlie Cochran, WDFW Fish Biologist, personal commun., 2022), but age-1 parr abundance was low following poor spawner numbers in 2022 (estimate of 159 adults from September snorkel survey). An additional 189 age-2 or older parr were tagged to provide fish for estimating detection efficiencies at PTISs. Steelhead Trout parr were recaptured and detected through repeat headwater sampling, smolt trapping, instream PTISs and Columbia River PIT-tag detection. We maintained and upgraded six instream PTISs to detect PIT-tagged Steelhead Trout parr, smolts, and adults, providing data for population assessments, and life-cycle research.
Detection data from PIT-tagged adult Steelhead Trout at PTISs allow assessment of adult escapement to tributary watersheds within the Wind River subbasin. Adult Steelhead Trout detection efficiency estimates at our primary PTIS in Trout Creek have been greater than 99 percent during seven of the past nine years and have exceeded 97% at our primary PTIS in the Wind River during eight of the past nine years. Adult escapement estimates to tributary watersheds are helping evaluate the efficacy of the 2009 removal of Hemlock Dam from rkm 2.0 of Trout Creek, where it had potential negative effects on Steelhead Trout populations due to hydrologic impairment, increased temperatures, and adult passage issues because of an inadequate fish ladder.
Detections at the instream PTISs have shown trends of age-0 and age-1 Steelhead Trout parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. Our data suggest that often most fish from a cohort that migrate downstream will do so at age-1 for additional rearing downstream of their natal areas. It is unknown if this is ingrained behavior or a result of lack of habitat capacity. We have estimated that from 15 to 56% of parr tagged as age-0 fish in headwater areas make downstream migrations at age-1 for additional rearing. We have estimated that up to 27% of Steelhead Trout parr, tagged as age-1 fish, make downstream migrations during fall: this is especially pronounced in the upper Wind River portion of the watershed. These findings raise questions about preferred parr rearing habitat and whether migrations are density- or habitat-quality driven, and answers to such questions are part of the long-term goals of this study as active and passive habitat restoration actions occur.
Repeat sampling at sites in the subbasin within and between years has enabled assessment of juvenile Steelhead Trout growth patterns. Growth rates (relative change in weight) of age-0 PIT-tagged parr during summer have been similar across the subbasin, though slightly lower in the Trout Creek watershed. Summer growth rates have been lower for age-1 parr in the Trout Creek watershed than the upper Wind River watershed. Yearly relative growth was similar across the subbasin for both age-0 and age-1 tagged parr.
Non-native Salvelinus fontinalis (Brook Trout) are present in the subbasin, chiefly the Trout Creek watershed, and repeat sampling provides an index of their prevalence. Mean percent-of-catch that is Brook Trout, at four sample sites in Trout Creek, has declined from the period 1998 – 2003 to the period 2011 – 2024. Percent-of-catch and number of Brook Trout at the Trout Creek sites from 2011 through 2022, though variable, have generally declined.
Evaluation and planning of habitat restoration efforts are critical to ensure efficient use of money and resources. Assessing Steelhead Trout life history variation in the Wind River subbasin informs research and tracking of many populations and habitat restoration and water allocation planning. Movement of Steelhead Trout parr from natal areas to other rearing areas raises questions regarding juvenile abundance, origin, and habitat use within watersheds. Improved PTISs and focused PIT-tagging of age-0 and age-1 Steelhead Trout parr allow investigation of such questions. Detailed viable salmonid population and life-history data, such as that provided by PIT-tagging and instream PTIS networks inform fisheries policy and management and enable assessment of long-term effects of habitat restoration actions such as the removal of Hemlock Dam on Trout Creek and proposed major instream habitat restoration in the upper Wind River.
","language":"English","publisher":"Columbia Basin Fish & Wildlife Program","usgsCitation":"Jezorek, I., 2025, Wind River subbasin restoration: Annual report of U.S. Geological Survey activities January 2023 through December 2023: Annual Report, 58 p.","productDescription":"58 p.","ipdsId":"IP-170797","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.25,\n 46\n ],\n [\n -122.25,\n 45.75\n ],\n [\n -121.75,\n 45.75\n ],\n [\n -121.75,\n 46\n ],\n [\n -122.25,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian 0000-0002-3842-3485","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":217811,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954704,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70262126,"text":"70262126 - 2025 - Evaluating effects of tracking device attachment methods on Black Oystercatchers Haematopus bachmani","interactions":[],"lastModifiedDate":"2025-01-14T15:19:55.742575","indexId":"70262126","displayToPublicDate":"2025-01-01T09:13:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating effects of tracking device attachment methods on Black Oystercatchers Haematopus bachmani","title":"Evaluating effects of tracking device attachment methods on Black Oystercatchers Haematopus bachmani","docAbstract":"Advances in tracking technology are greatly improving our understanding of many aspects of avian ecology. However, the diversity of tracking devices and attachment methods necessitates better evaluation of how they affect particular taxa. We evaluated effects of tracking devices mounted on leg bands or attached using leg-loop harnesses on resighting rates of Black Oystercatchers Haematopus bachmani in Alaska and British Columbia. In Alaska, in 2019, geolocators were mounted on a leg band (n = 20) or encased in a nylon mount and attached using a leg-loop harness (n = 20), and GPS devices were attached using a leg-loop harness (n = 6). In British Columbia, Argos-PTT satellite transmitters were attached using a leg-loop harness (n = 26) in 2019 and 2020. Control birds were colour-banded (Alaska: n = 22; British Columbia: n = 27) but were not equipped with a tracking device. Surveys to resight birds with and without tracking devices were conducted in 2020 and 2021. Birds carrying geolocators, GPS devices, and Argos-PTT satellite transmitters attached using a leg-loop harness were as likely to be resighted (69% in Alaska and 62% in British Columbia) as control birds (59% in both areas). However, birds carrying geolocators mounted on leg bands were far less likely to be resighted (15%). We also used resighting data and a time-to-tag failure analysis to obtain a minimum annual survival estimate for the birds carrying an Argos-PTT satellite transmitter. The minimum annual survival estimate for these birds (0.81 ± 0.08 SE) did not differ from previously reported annual apparent survival estimates for Black Oystercatchers in British Columbia (0.91 ± 0.02 SE). These findings suggest that while Black Oystercatchers can successfully carry tracking devices weighing less than 3% of their body mass when attached using a leg-loop harness, they are negatively affected by small tracking devices mounted directly on leg bands.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00357","usgsCitation":"Rankin, C., Ware, L., Robinson, B.H., Esler, D., Coletti, H., Maftei, M., Hipfner, J.M., and Green, D., 2025, Evaluating effects of tracking device attachment methods on Black Oystercatchers Haematopus bachmani: Wader Study, v. 131, no. 3, p. 204-213, https://doi.org/10.18194/ws.00357.","productDescription":"10 p.","startPage":"204","endPage":"213","ipdsId":"IP-160860","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":466213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Rankin, Cole","contributorId":344232,"corporation":false,"usgs":false,"family":"Rankin","given":"Cole","email":"","affiliations":[],"preferred":false,"id":923173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ware, Lena","contributorId":344231,"corporation":false,"usgs":false,"family":"Ware","given":"Lena","email":"","affiliations":[{"id":82321,"text":"SFU","active":true,"usgs":false}],"preferred":false,"id":923174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Brian H.","contributorId":215576,"corporation":false,"usgs":false,"family":"Robinson","given":"Brian","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":923175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":923176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":923177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maftei, Mark","contributorId":127435,"corporation":false,"usgs":false,"family":"Maftei","given":"Mark","email":"","affiliations":[],"preferred":false,"id":923178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hipfner, J Mark","contributorId":243469,"corporation":false,"usgs":false,"family":"Hipfner","given":"J","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":923179,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Green, David","contributorId":167789,"corporation":false,"usgs":false,"family":"Green","given":"David","affiliations":[],"preferred":false,"id":923180,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70265458,"text":"70265458 - 2025 - Glass laser ablation-inductively coupled plasma-mass spectrometry analysis methods, precision, and accuracy data for tephra studies in Alaska","interactions":[],"lastModifiedDate":"2025-04-07T14:10:39.503614","indexId":"70265458","displayToPublicDate":"2025-01-01T09:08:17","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":20899,"text":"Alaska Division of Geological & Geophysical Surveys Techniques and Methods","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"1","title":"Glass laser ablation-inductively coupled plasma-mass spectrometry analysis methods, precision, and accuracy data for tephra studies in Alaska","docAbstract":"This publication reports the analytical conditions, standard reference material (SRM) results, and preferred post-processing methodologies for laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) measurements supporting tephra studies in Alaska between 2018 and 2024. We evaluate the long-term accuracy and precision of our methodologies by comparing our calculated SRM concentrations to the Geological and Environmental Reference Materials database (GeoReM) preferred concentration values for the following SRMs: BCR-2G, BHVO-2G, ATHO-G, NIST-612, GSD-1G, and GSE-1G. We show that our LA-ICP-MS methodologies produce accurate and consistent measurements across numerous analytical sessions, even when instrumentation changed. Overall, these results indicate that Alaska tephra matrix glass measurements, like SRM measurements, are accurate, precise, and comparable between analytical sessions. This work allows us to better correlate tephra units from Alaska volcanoes throughout the Alaska-Aleutian arc, ultimately enhancing our understanding of spatiotemporal patterns of volcanism in the region. This enhanced understanding will aid in refining volcanic hazard classification and response strategies. Future versions of this dataset will provide updates to SRM results or analytical routines for sessions that have transpired since the publishing of this version.
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Jordan Edward 0000-0002-3566-5091","orcid":"https://orcid.org/0000-0002-3566-5091","contributorId":330466,"corporation":false,"usgs":true,"family":"Lubbers","given":"Jordan","email":"","middleInitial":"Edward","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932764,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70261959,"text":"70261959 - 2025 - Public, bottled, and private drinking water: Shared contaminant-mixture exposures and effects challenge","interactions":[],"lastModifiedDate":"2025-01-07T15:28:51.665345","indexId":"70261959","displayToPublicDate":"2025-01-01T08:14:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Public, bottled, and private drinking water: Shared contaminant-mixture exposures and effects challenge","docAbstract":"BACKGROUND: Humans are primary drivers of environmental contaminant exposures worldwide, including in drinking-water (DW). In the United States (US), point-of-use DW (POU DW) is supplied via private tapwater (TW, predominantly private wells), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision making.
OBJECTIVES: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU DW contaminant mixture exposures and corresponding potential human health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical health benchmark weighted and bioactivity weighted effects predictions across previous studies by this research group.
DISCUSSION: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supply chains. Differences in contaminant or contaminant class exposures (e.g., trace metals, disinfection byproducts), with important implications for DW quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring.
CONCLUSION: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the full breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low level inorganic /organic contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased engagement in source-water protection and drinking-water treatment, including consumer point of use treatment, is necessary to reduce risks associated with long-term DW contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.
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University Mailman School of Public Health","active":true,"usgs":false}],"preferred":false,"id":922433,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nigra, Anne E.","contributorId":303387,"corporation":false,"usgs":false,"family":"Nigra","given":"Anne","email":"","middleInitial":"E.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":922434,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schreiner, Molly L. 0000-0001-9306-5564","orcid":"https://orcid.org/0000-0001-9306-5564","contributorId":296363,"corporation":false,"usgs":true,"family":"Schreiner","given":"Molly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922435,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70269033,"text":"70269033 - 2025 - Predictability and behavior of water transfers across basin boundaries","interactions":[],"lastModifiedDate":"2025-07-15T15:23:21.548418","indexId":"70269033","displayToPublicDate":"2024-12-31T10:12:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Predictability and behavior of water transfers across basin boundaries","docAbstract":"Inter-basin water transfers (IBTs) are important components of water balances of basins, and they can have substantial impact on regional water availability. Flow information is often not available at locations with known IBTs, which is a drawback in several published IBT databases. Few, if any, studies examine whether IBT flow behavior can be generalized, and if these behaviors can be predicted at undocumented locations or known IBT locations with no flow information. In this study, we employ a clustering method based on image matching to identify similar classes of flow behavior of IBTs. Machine learning models are used to assess how well IBT flow characteristics (e.g., average flow) associated with these behaviors can be predicted. These evaluations of IBTs are done for two regions in the United States. Three primary classes of IBTs (seasonal, nonseasonal/not mixed, and seasonal/mixed) are identified across the two regions analyzed. The IBT flow characteristics are accurately predicted in the northeast region. In the Colorado region, however, only the flow characteristics related to timing were accurately predicted. These results indicate that the proposed modeling framework can be used to identify generalizable IBT flow characteristics. This framework is shown to predict flow characteristics with a reasonable amount of accuracy to undocumented locations and improves previously published IBT databases by backfilling flow information to locations with a known IBT presence.
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Despite widespread recognition of the need for Indigenous knowledge and historical reference points as baseline data, archaeological data are rarely included in conservation biology research designs. Here we propose a novel multiproxy method to learn from former fisheries stewards by generating archaeological data on past salmonid population parameters. We used a newly developed, high throughput qPCR (HT-qPCR) chip, originally designed for environmental DNA (eDNA), for species identification of archaeological salmonid vertebrae. We combine this with the laser ablation split-stream (LASS) approach to identify ocean-migration versus freshwater residency. We test this multidisciplinary approach using both contemporary and archaeological salmonid samples and new radiocarbon dates from the Tronsdal Site on the Skagit River, Washington State, USA. This is a useful approach for extracting information about Salmonidae species and life history diversity from archaeological remains to reconstruct historic baselines for several population parameters in anadromous species with long periods of freshwater residency. The approach outlined in this paper may be particularly useful for research investigating past fisheries dynamics, offering hundreds to thousands of years of temporal depth for modern fisheries management, harvest policies, restoration ecology, and conservation biology.
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2025 - Biophysical simulation of wetland surface water flow to predict changing water availability in the Everglades","interactions":[],"lastModifiedDate":"2025-01-02T14:21:26.307264","indexId":"70261857","displayToPublicDate":"2024-12-25T09:40:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Biophysical simulation of wetland surface water flow to predict changing water availability in the Everglades","docAbstract":"A central challenge for water managers is to adaptively manage water availability to meet societal needs while simultaneously protecting ecosystems. Progress restoring the Everglades requires predictions of how overland flow of surface water can be increased to rehydrate and revive downstream areas without causing unintended harms. We developed a biophysical flow rate expression (BioFRE) that relates shallow overland flow to roughness dominated by spatially variable vegetation and microtopography. Hydraulic theory was combined with vegetation and topographic field data to quantify hydraulic roughness without calibrating the expression to fit hydrologic data. To assess changes in overland flow capacity, we benchmarked BioFRE against best available simulations of the historic Everglades and against present-day hydrologic data representing various levels of degradation. The simulations revealed that overland flow capacity of the Everglades in now half of what it was historically in the Everglades primarily because of the loss of deepwater sloughs. The relative sensitivity of simulated flows to the individual biophysical factors was quantified and related to habitat value and drought and flood resilience. Our approach can potentially be used in other flowing wetland and floodplain systems to understand and adaptively manage water and ecological resources.","language":"English","doi":"10.1016/j.ecoleng.2024.107491","usgsCitation":"Harvey, J., Choi, J., Wilcox, W., Brown, M., and Lal, W., 2025, Biophysical simulation of wetland surface water flow to predict changing water availability in the Everglades: Ecological Engineering, v. 212, 107491, 14 p., https://doi.org/10.1016/j.ecoleng.2024.107491.","productDescription":"107491, 14 p.","ipdsId":"IP-167812","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466672,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2024.107491","text":"Publisher Index Page"},{"id":465565,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.1076224101966,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 26.691819233104567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"212","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":922038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choi, Jay 0000-0003-1276-481X jchoi@usgs.gov","orcid":"https://orcid.org/0000-0003-1276-481X","contributorId":219096,"corporation":false,"usgs":true,"family":"Choi","given":"Jay","email":"jchoi@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":922039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilcox, Walter","contributorId":347595,"corporation":false,"usgs":false,"family":"Wilcox","given":"Walter","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":922042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Michael C.","contributorId":347681,"corporation":false,"usgs":false,"family":"Brown","given":"Michael C.","affiliations":[],"preferred":false,"id":922170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lal, Wasantha","contributorId":347594,"corporation":false,"usgs":false,"family":"Lal","given":"Wasantha","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":922041,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263061,"text":"70263061 - 2025 - Vertebrates in trade that pose high invasion risk to the United States","interactions":[],"lastModifiedDate":"2025-01-29T14:55:06.262244","indexId":"70263061","displayToPublicDate":"2024-12-24T08:40:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Vertebrates in trade that pose high invasion risk to the United States","docAbstract":"The United States imports thousands of live vertebrate species annually as part of legal trade. Escapes and releases from captivity are major pathways of invasion, however, the risk posed by the thousands of imported vertebrate species has not been systematically assessed. We conducted a horizon scan that used a data-driven climate match to filter a list of nearly 15,000 taxa drawn from across the globe of imported fish, amphibians, reptiles, birds, and mammals for rapid assessment by taxonomic experts. Experts evaluated 840 species and identified 32 (22 reptiles and 10 fishes) as having the highest risk for establishment, spread, and negative impacts. Of those high-risk species, the majority have the capacity to disrupt ecosystem processes via their role as top predators or the unique ecological niches that they occupy, while several of the snake species pose a threat to human health. High-risk species were often scored with high confidence while in contrast, low scores were attributed to a combination of ecological redundancy, low propagule pressure, or low climate match while low confidence arose from a lack of information in the literature (i.e., data deficiency). Our study therefore highlights legally imported species likely to cause the greatest harm with the recognition that many other species could also become invasive in the United States. The ranked list of vertebrate threats can be used to prioritize watchlists and inform the development of targeted regulations for importation can be applied to regions to provide a rapid, preliminary screening for large pools of potential invaders.
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