The U.S. Army Corps of Engineers American River Watershed Common Features project (ACRF) seeks to reduce flood risk for the City of Sacramento, California, and surrounding areas. The project includes levee-remediation measures to address seepage, stability, erosion, and height concerns as well as the widening of the Sacramento Weir and Bypass. The project reach is in the lower extent of the Sacramento River migration corridor for the federally threatened southern Distinct Population Segment of North American green sturgeon (Acipenser medirostris). To establish baseline migratory behavior, we examined adult green sturgeon transit through the project area prior to construction. Biologists from the U.S. Army Corps of Engineers collected and tagged 55 adult green sturgeon with acoustic and passive integrated transponders, near Hamilton City, California, at river kilometer 332 of the Sacramento River each fall from 2020 to 2022. To evaluate fish movements, we deployed five acoustic detection sites at river kilometers 101, 90, 76, and 21 on the Sacramento River and in Tule Canal near the Sacramento Bypass at river kilometer 101 of the Sacramento River. The acoustic receivers detected nearly all tagged fish moving downstream through the ARCF study area during the same water year (October 1–September 30) in which they were tagged. Three fish released in October of 2020 arrived at the ARCF study area more than 362 days later in October 2021. The timing of tagged fish movements was associated with increases in river flow and not hour of day. Adult green sturgeon moved downstream from January to August when streamflows exceeded 15,000 cubic feet per second. During water year 2023 and the critically dry water year 2022, fish moved with the first peaks in flow occurring from mid-October to early January. Fish tagged in the critically dry water year 2021 entered the ARCF study area over an extended period from January to October, when flows remained around 10,000 cubic feet per second all year. Fish moved quickly between sites within the ARCF study area and generally spent less than 1 hour at each detection site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241025","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansen, A.C., Burdick, S.M., Johnson, R.P., Chase, R.D., and Thomas, M.J., 2024, Adult green sturgeon (Acipenser medirostris) movements in the Sacramento–San Joaquin River Delta, California, December 2020–January 2023: U.S. Geological Survey Open-File Report 2024–1025, 17 p., https://doi.org/10.3133/ofr20241025.","productDescription":"vii, 17 p.","onlineOnly":"Y","ipdsId":"IP-160183","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":428182,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1025/ofr20241025.pdf","text":"Report","size":"6.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1025 PDF"},{"id":428183,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1025 HTML"},{"id":428185,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1025/ofr20241025.XML"},{"id":428181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1025/ofr20241025.jpg"},{"id":428184,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1025/images"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.72096146410857,\n 38.13471307768137\n ],\n [\n -121.39983277185577,\n 38.13471307768137\n ],\n [\n -121.39983277185577,\n 38.595842840770814\n ],\n [\n -121.72096146410857,\n 38.595842840770814\n ],\n [\n -121.72096146410857,\n 38.13471307768137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Lotic fish species distributions are frequently predicted using remotely sensed habitat variables that characterize the adjacent landscape and serve as proxies for instream habitat. Recent advancements in statistical methodology, however, allow for leveraging fish assemblage data when predicting distributions. This is important because assemblage composition likely provides better information about instream habitat compared to landscape-derived metrics and therefore may improve predictions. To better understand the value of using multi-species fish data in species distribution modeling, we fit two conditional random fields (CRF) models to quantify the relative importance of fish assemblage co-occurrence, landscape-derived habitat variables, and interactions between these two predictor groups (i.e., effects of co-occurrence could be context-dependent) at over 1200 stream catchments in Pennsylvania, USA. We first compared predictive performance of CRF models against traditionally used single-species logistic regressions (generalized linear models; GLMs) and found that inclusion of fish assemblage data often improved predictive performance. The multi-species CRF models performed significantly better at predicting occurrence for 63% of species with an average percent increase in AUC of 25% compared to GLMs. Furthermore, the CRF identified species co-occurrences as more informative, and thus relatively more important, at predicting occurrence than the other effect types. The CRF also suggested that allowing these biotic effects to be context-dependent was important for predicting occurrence of many species. These findings illustrate the value of fish assemblage data for landscape-scale species distribution modeling and leveraging this information can improve predictions and inferences to help inform the management and conservation of freshwater fishes.
","language":"English","publisher":"Springer","doi":"10.1007/s42974-024-00183-9","usgsCitation":"Custer, C., Fischer, D., Smith, G., Henning, A., Kepler Schall, M., Shank, M.K., Wertz, T.A., and Isermann, D.A., 2024, Quantifying the relative importance of biotic and abiotic factors in landscape-based models of stream fish distributions: Community Ecology, v. 25, p. 145-196, https://doi.org/10.1007/s42974-024-00183-9.","productDescription":"52 p.","startPage":"145","endPage":"196","ipdsId":"IP-147148","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s42974-024-00183-9","text":"Publisher Index Page"},{"id":433512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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rupture","interactions":[],"lastModifiedDate":"2024-05-17T14:11:32.22052","indexId":"70254306","displayToPublicDate":"2024-04-30T09:11:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17454,"text":"Seismica","active":true,"publicationSubtype":{"id":10}},"title":"Late-Quaternary surface displacements on accretionary wedge splay faults in the Cascadia Subduction Zone: Implications for megathrust rupture","docAbstract":"Because splay faults branch at a steep dip angle from the plate-boundary décollement in an accretionary wedge, their coseismic displacement can potentially result in larger tsunamis with distinct characteristics compared to megathrust-only fault ruptures, posing an enhanced hazard to coastal communities. Elsewhere, there is evidence of coseismic slip on splay faults during many of the largest subduction zone earthquakes, but our understanding of potentially active splay faults and their hazards at the Cascadia subduction zone remains limited. To identify the most recently active splay faults at Cascadia, we conduct stratigraphic and structural interpretations of near-surface deformation in the outer accretionary wedge for the ~400 km along-strike length of the landward vergence zone. We analyze recently acquired high-frequency sparker seismic data and crustal-scale multi-channel seismic data to examine the record of deformation in shallow slope basins and the upper ~1 km of the surrounding accreted sediments and to investigate linkages to deeper décollement structure. We present a new fault map for widest, most completely locked portion of Cascadia from 45 to 48°N latitude, which documents the distribution of faults that show clear evidence of recent late Quaternary activity. We find widespread evidence for active splay faulting up to 30 km landward of the deformation front, in what we define as the active domain, and diminished fault activity landward outside of this zone. The abundance of surface-deforming splay faults in the active outer wedge domain suggests Cascadia megathrust events may commonly host distributed shallow rupture on multiple splay faults located within 30 km of the deformation front.
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Therefore, the study of ancient permafrost (existing since the Pleistocene or earlier) and past permafrost (Late Pleistocene or older permafrost that no longer exists) and their dynamics may inform about climate and environmental changes in the past. In this chapter, we provide a brief overview of characteristics, detection and dating methods of ancient and past permafrost, before presenting a spatial and temporal history of permafrost in the middle and high northern latitudes. While the first permafrost may have formed about 3 million years ago, the late Pliocene and Early Pleistocene were characterized by frequent thawing and new formation of permafrost. It was not until the Middle and Late Pleistocene that permafrost became more persistent and widespread due to prolonged cooling. The most ancient dated permafrost formed between 800 and 600 ka in Yukon/Canada and East Siberia. Interglacial warming after the last ice age has led to massive thawing of permafrost and large areas in Europe, Asia and America are now characterized by traces of past permafrost.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in Earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-99931-1.00258-0","usgsCitation":"Opel, T., Bertran, P., Grosse, G., Jones, M.C., Luetscher, M., Schirrmeister, L., Stadelmeier, K., and Veremeeva, A., 2024, Ancient permafrost and past permafrost in the Northern Hemisphere, chap. of Reference module in Earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-323-99931-1.00258-0.","productDescription":"HTML Document","ipdsId":"IP-164376","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":439707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-04581090","text":"External Repository"},{"id":433194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Hemisphere","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 89\n ],\n [\n -179.9,\n 1\n ],\n [\n 179.9,\n 1\n ],\n [\n 179.9,\n 89\n ],\n [\n -179.9,\n 89\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Opel, Thomas","contributorId":195054,"corporation":false,"usgs":false,"family":"Opel","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":911664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bertran, Pascal","contributorId":343679,"corporation":false,"usgs":false,"family":"Bertran","given":"Pascal","email":"","affiliations":[{"id":82154,"text":"Institut National de Recherches Archéologiques Préventives","active":true,"usgs":false}],"preferred":false,"id":911665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":911666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":911667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luetscher, Marc","contributorId":343680,"corporation":false,"usgs":false,"family":"Luetscher","given":"Marc","email":"","affiliations":[{"id":82157,"text":"Swiss Institute for Speleology and Karst Studies","active":true,"usgs":false}],"preferred":false,"id":911668,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schirrmeister, Lutz","contributorId":200976,"corporation":false,"usgs":false,"family":"Schirrmeister","given":"Lutz","email":"","affiliations":[],"preferred":false,"id":911669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stadelmeier, Kim","contributorId":343681,"corporation":false,"usgs":false,"family":"Stadelmeier","given":"Kim","email":"","affiliations":[{"id":82158,"text":"Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research Troposphere Research (IMKTRO","active":true,"usgs":false}],"preferred":false,"id":911670,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veremeeva, Alexandra","contributorId":194028,"corporation":false,"usgs":false,"family":"Veremeeva","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":911671,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70253582,"text":"70253582 - 2024 - NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","interactions":[],"lastModifiedDate":"2024-05-02T13:42:54.186655","indexId":"70253582","displayToPublicDate":"2024-04-30T08:41:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","docAbstract":"Models of rocky-coast erosion help us understand the physical phenomena that control coastal morphology and evolution, infer the processes shaping coasts in remote environments, and evaluate risk from natural hazards and future climate change. Existing models, however, are highly complex, are computationally expensive, and depend on many input parameters; this limits our ability to explore planform erosion of rocky coasts over long timescales (thousands to millions of years) and over a range of conditions. In this paper, we present a simplified cellular model of coastline evolution in closed basins through uniform erosion and wave-driven erosion. Uniform erosion is modeled as a constant rate of retreat. Wave erosion is modeled as a function of fetch, the distance over which the wind blows to generate waves, and the angle between the incident wave and the shoreline. This reduced-complexity model can be used to evaluate how a detachment-limited coastal landscape reflects climate, sea-level history, material properties, and the relative influence of different erosional processes.
","language":"English","publisher":"Copernicus","doi":"10.5194/gmd-17-3433-2024","usgsCitation":"Palermo, R.E., Perron, J.T., Soderblom, J.M., Birch, S.P., Hayes, A.G., and Ashton, A.D., 2024, NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps: Geoscientific Model Development, v. 17, no. 8, p. 3433-3445, https://doi.org/10.5194/gmd-17-3433-2024.","productDescription":"13 p.","startPage":"3433","endPage":"3445","ipdsId":"IP-157241","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-17-3433-2024","text":"Publisher Index Page"},{"id":428321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Palermo, Rose Elizabeth 0000-0002-7438-361X","orcid":"https://orcid.org/0000-0002-7438-361X","contributorId":300046,"corporation":false,"usgs":true,"family":"Palermo","given":"Rose","email":"","middleInitial":"Elizabeth","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":899974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":899975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soderblom, Jason M.","contributorId":193866,"corporation":false,"usgs":false,"family":"Soderblom","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":899976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birch, Samuel P. D.","contributorId":202322,"corporation":false,"usgs":false,"family":"Birch","given":"Samuel","email":"","middleInitial":"P. D.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":899977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Alexander G.","contributorId":211180,"corporation":false,"usgs":false,"family":"Hayes","given":"Alexander","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":899978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ashton, Andrew D.","contributorId":300047,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":899979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70270998,"text":"70270998 - 2024 - Thick- and thin-skinned contractional styles and the tectonic evolution of the northern Sangre de Cristo Mountains, Colorado, USA","interactions":[],"lastModifiedDate":"2025-08-27T13:49:11.414989","indexId":"70270998","displayToPublicDate":"2024-04-30T08:39:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Thick- and thin-skinned contractional styles and the tectonic evolution of the northern Sangre de Cristo Mountains, Colorado, USA","docAbstract":"The Sangre de Cristo Mountains of southern Colorado and northern New Mexico, USA, contain an unusual combination of thick- and thin-skinned contractional structures involving both basement and cover rocks in the Laramide Rocky Mountain foreland. These structures are truncated by down-faulted extensional basins to the east and west. Together with synorogenic sediments, these structures preserve a record of the rise of the Ancestral Rocky Mountains, the Laramide orogeny, and Rio Grande rifting. Laramide structures within the mountains provide clues to processes that link the three events and to necessary conditions for thin-skinned and thick-skinned contractional structures to form together in continental interiors.
To examine the full variety of structural styles, a portion of the northern Sangre de Cristo fold- and-thrust belt in Colorado was described and interpreted using geologic maps and structural cross-sections. Stratigraphic relations of the Ancestral Rocky Mountain highlands and basin fill were reconstructed from existing maps. These relations allow identification of faults inherited from the Ancestral Rocky Mountains, differentiation of thrust sheets, and in some cases, estimation of the magnitude of displacement. To examine relations between Laramide thrusts and Rio Grande rifting, kinematic data were collected from a thrust fault adjacent to rift faults.
Three thrust fault styles were recognized: thin-skinned basement, thin-skinned cover rocks, and thick-skinned basement. Thin-skinned thrusts arising from a hinterland beneath the present San Luis Valley carried sheets of Proterozoic basement rocks northeast over a Laramide foreland. These basement thrusts are interpreted to be faults of the Ancestral Rocky Mountains that reactivated during the Laramide orogeny. The Laramide foreland consists of thin-skinned thrusts and folds in sedimentary cover rocks as young as 49 Ma. Both thin-skinned thrusts in basement and cover rocks are bounded by thick-skinned basement thrusts that moved intermittently throughout the Laramide orogeny.
We infer that thin-skinned thrusts form in continental interiors where deformation is focused in weak strata of thick basin fill and in fluid-reaction weakened preexisting faults in basement rocks. Both conditions are met in the Sangre de Cristo Mountains. Basement thrusts adjacent to the San Luis Valley contain evidence of plastic contractional microstructures overprinted by extensional microstructures that may record the transition from Laramide contraction to Rio Grande extension of the crust.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.1130/GES02635.1","usgsCitation":"Lindsey, D.A., and Caine, J., 2024, Thick- and thin-skinned contractional styles and the tectonic evolution of the northern Sangre de Cristo Mountains, Colorado, USA: Geosphere, v. 20, no. 3, p. 678-710, https://doi.org/10.1130/GES02635.1.","productDescription":"33 p.","startPage":"678","endPage":"710","ipdsId":"IP-147576","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02635.1","text":"Publisher Index Page"},{"id":494940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"northern Sangre de Cristo Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 38\n ],\n [\n -105.75,\n 37.5\n ],\n [\n -105.25,\n 37.5\n ],\n [\n -105.25,\n 38\n ],\n [\n -105.75,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lindsey, David A. 0000-0002-9466-0899 dlindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-9466-0899","contributorId":773,"corporation":false,"usgs":true,"family":"Lindsey","given":"David","email":"dlindsey@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":947462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":947463,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70253904,"text":"70253904 - 2024 - Double take: Ingestion of two rats by a juvenile Burmese Python (Python bivittatus) in Big Cypress National Preserve, FL, USA","interactions":[],"lastModifiedDate":"2024-05-03T13:47:04.292684","indexId":"70253904","displayToPublicDate":"2024-04-30T08:39:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16296,"text":"Reptiles and Amphibians","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Double take: Ingestion of two rats by a juvenile Burmese Python (Python bivittatus) in Big Cypress National Preserve, FL, USA","title":"Double take: Ingestion of two rats by a juvenile Burmese Python (Python bivittatus) in Big Cypress National Preserve, FL, USA","docAbstract":"No abstract available.
","language":"English","publisher":"International Reptile Conservation Foundation","doi":"10.17161/randa.v31i1.21283","usgsCitation":"Evers, T.M., Currylow, A.F., Sandfoss, M.R., McBride, L.M., Romagosa, C.M., Boone, W.W., Guzy, J.C., Anderson, G.E., Hart, K., McCollister, M., and Yackel Adams, A.A., 2024, Double take: Ingestion of two rats by a juvenile Burmese Python (Python bivittatus) in Big Cypress National Preserve, FL, USA: Reptiles and Amphibians, v. 31, no. 1, e21283, 4 p., https://doi.org/10.17161/randa.v31i1.21283.","productDescription":"e21283, 4 p.","ipdsId":"IP-157030","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":439710,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17161/randa.v31i1.21283","text":"Publisher Index Page"},{"id":428349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.3341666035976,\n 26.245742642743366\n ],\n [\n -81.3341666035976,\n 25.602570520385427\n ],\n [\n -80.85144777670084,\n 25.602570520385427\n ],\n [\n -80.85144777670084,\n 26.245742642743366\n ],\n [\n -81.3341666035976,\n 26.245742642743366\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Evers, Teah M.","contributorId":336149,"corporation":false,"usgs":false,"family":"Evers","given":"Teah","email":"","middleInitial":"M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":900046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Currylow, Andrea F.","contributorId":336151,"corporation":false,"usgs":false,"family":"Currylow","given":"Andrea","email":"","middleInitial":"F.","affiliations":[{"id":27471,"text":"US Army Corp of Engineers","active":true,"usgs":false}],"preferred":false,"id":900047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sandfoss, Mark Robert 0000-0002-0162-7265","orcid":"https://orcid.org/0000-0002-0162-7265","contributorId":328884,"corporation":false,"usgs":true,"family":"Sandfoss","given":"Mark","email":"","middleInitial":"Robert","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McBride, Lisa Marie 0000-0003-4558-5391","orcid":"https://orcid.org/0000-0003-4558-5391","contributorId":303824,"corporation":false,"usgs":true,"family":"McBride","given":"Lisa","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":900050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, Wesley W.","contributorId":316654,"corporation":false,"usgs":false,"family":"Boone","given":"Wesley","email":"","middleInitial":"W.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":900051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":900052,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900053,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":900054,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCollister, Matthew","contributorId":302902,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":900055,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900056,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70253227,"text":"sir20245025 - 2024 - Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","interactions":[],"lastModifiedDate":"2026-02-03T18:10:33.629761","indexId":"sir20245025","displayToPublicDate":"2024-04-30T07:15:01","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5025","displayTitle":"Simulation of Hydrodynamics and Water Temperature in a 21-Mile Reach of the Upper Illinois River, Illinois, 2020–22","title":"Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","docAbstract":"This report describes the development of a CE-QUAL-W2 river hydrodynamics and temperature model of a 21-mile reach of the Illinois River including a 3-mile reach of a major tributary, the Fox River. Model outputs consist of streamflow, water velocity, water-surface elevation, and water-temperature time series that can be used to simulate summer conditions in years with and without extensive development of harmful algal blooms (HABs). These analyses may provide a better understanding of some complex factors contributing to HAB development along the Illinois River. Such an understanding may provide more accurate HAB timing and location predictions and may help determine potential mitigating activities to prevent or limit the size and duration of HABs.
Using the observed and simulated hydrodynamic conditions in the Illinois River study reach, it was possible to compare and contrast streamflow, velocity, and temperature conditions in years with varying HAB distributions. Occurrences of extensive HABs were documented in the study reach in June 2020 and June 2021, but only a small HAB restricted to the Marseilles Lock and Dam pool occurred in the summer of 2022. The objective then was to find similarities in site conditions between 2020 and 2021 that may contrast with the conditions in 2022. Among the 3 years included in the study, the variability in simulated water temperature exceeded variability in observed streamflow and simulated velocities. The longest period of water temperatures greater than 27 degrees Celsius (°C) in the selected locations in June of the three analysis years was in the second half of June 2022, yet no study-area wide HAB was documented in 2022. Simulations indicated that after warm water temperatures were established in the reach in June 2022, a cooling period broke up the warming period. This period of cooling was greater in magnitude and duration downstream from the location of a localized HAB perhaps limiting the spread of the bloom.
Residence times differed substantially in segments representing different channel features; values ranged from 0.28 to 17.3 (days per 500 meters of channel) between the main stem and backwater areas, respectively. Variation in average June residence times was also greater among different channel features than among different years in the study period. The HABs in 2020 and 2021 at Starved Rock Dam were documented when water temperatures were about 26 °C. River backwater areas at some locations did attain these temperatures 2 to 3 days before the conditions in the main stem. Residence times in the backwater areas, however, generally exceeded 9 days, thus limiting the exchange of water carrying algal biomass into the main channel.
Hydrodynamic model calibration involved adjusting model parameters until observed and simulated daily water-surface elevations, daily streamflows, discrete velocities, and channel areas were similar. Temperature calibration was done with near-surface continuous time-series data and discrete vertical profile temperatures. Observed and simulated water temperatures generally were within 1 °C at all monitoring locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245025","usgsCitation":"Ament, M.R., and Heimann, D.C., 2024, Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22 (ver. 1.1, October 2024): U.S. Geological Survey Scientific Investigations Report 2024–5025, 35 p., https://doi.org/10.3133/sir20245025.","productDescription":"Report: viii, 35 p.; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-147887","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497947,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116400.htm","linkFileType":{"id":5,"text":"html"}},{"id":462442,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5025/versionHist.txt","size":"2.7 KB","linkFileType":{"id":2,"text":"txt"}},{"id":428192,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245025/full"},{"id":428191,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":428190,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BV9EG2","text":"USGS data release","linkHelpText":"Hydrodynamic and water-temperature model of a 21-mile reach of the upper Illinois River, Illinois (ver. 1.1, October 2024)"},{"id":428189,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5025/images/"},{"id":428186,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5025/coverthb2.jpg"},{"id":428187,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5025/sir20245025.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5025"},{"id":428188,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5025/sir20245025.XML"}],"country":"United States","state":"Illinois","otherGeospatial":"Upper Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.09651850759147,\n 41.39468681338917\n ],\n [\n -89.09651850759147,\n 41.27302034876615\n ],\n [\n -88.30008450383568,\n 41.27302034876615\n ],\n [\n -88.30008450383568,\n 41.39468681338917\n ],\n [\n -89.09651850759147,\n 41.39468681338917\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: April 30, 2024; Version 1.1: October 1, 2024","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Data citation promotes accessibility and discoverability of data through measures carried out by researchers, publishers, repositories, and the scientific community. This paper examines how a data citation workflow has been implemented by the U.S. Geological Survey (USGS) by evaluating publication and data linkages. Two different methods were used to identify data citations: examining publication structural metadata and examining the full text of the publication. A growing number of USGS researchers are complying with publisher data sharing policies aimed to capture data citation information in a standardized way within associated publications. However, inconsistencies in how data citation information is documented in publications has limited the accessibility and discoverability of the data. This paper demonstrates how organizational evaluations of publication and data linkages can be used to identify obstacles in advancing data citation efforts and improve data citation workflows.
","language":"English","publisher":"The Committee on Data of the International Science Council (CODATA)","doi":"10.5334/dsj-2024-024","usgsCitation":"Donovan, G.C., and Langseth, M., 2024, Are researchers citing their data? A case study from the U.S. Geological Survey: Data Science Journal, v. 23, 24 p., https://doi.org/10.5334/dsj-2024-024.","productDescription":"24 p.","ipdsId":"IP-156543","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":439712,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5334/dsj-2024-024","text":"Publisher Index Page"},{"id":434969,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPC9M2","text":"USGS data release","linkHelpText":"U.S. Geological Survey Data Citation Analysis, 2016-2022"},{"id":428265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, Grace C. 0000-0002-6632-4564","orcid":"https://orcid.org/0000-0002-6632-4564","contributorId":219931,"corporation":false,"usgs":true,"family":"Donovan","given":"Grace","email":"","middleInitial":"C.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":899849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langseth, Madison 0000-0002-4472-9106 mlangseth@usgs.gov","orcid":"https://orcid.org/0000-0002-4472-9106","contributorId":191744,"corporation":false,"usgs":true,"family":"Langseth","given":"Madison","email":"mlangseth@usgs.gov","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":899850,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70254552,"text":"70254552 - 2024 - Role of edaphic, hydrologic, and land cover variables in determining dissolved organic carbon in Missouri (USA) reservoirs and streams","interactions":[],"lastModifiedDate":"2024-06-03T11:35:41.932352","indexId":"70254552","displayToPublicDate":"2024-04-30T06:28:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Role of edaphic, hydrologic, and land cover variables in determining dissolved organic carbon in Missouri (USA) reservoirs and streams","docAbstract":"In Missouri, distinct geophysical gradients influence statewide patterns in water quality. Here, we quantify the spatiotemporal variability of dissolved organic carbon (DOC) in reservoirs and streams and the edaphic, hydrologic, and land cover variables that account for cross-system variation. Datasets included statewide inventories collected over decades and studies with greater temporal resolution (n = >6350 DOC measurements). Among reservoirs, the smallest DOC concentration was measured in a spring-fed system within a forested watershed, and the largest was where agricultural biosolids were applied to the land (range 1.0–15.9 mg/L, overall mean 5.8 mg/L). Reservoir values increased from the southern forested Highlands (mean 4.7 mg/L) to the northern agricultural Plains (mean 7.0 mg/L). Stream DOC was similar to reservoir values (overall mean in streams 6.3 mg/L; Highlands mean 4.0 mg/L; Plains mean 6.6 mg/L), despite differences in study design and collection period. Reservoir DOC increased in spring, indicative of allochthonous loading, with small autochthonous additions during a broad summer peak. Temporal variability in DOC was low relative to macronutrients and chlorophyll in both reservoirs and streams, indicating DOC may be a sensitive and readily detected indicator of temporal change in these systems. In regression analyses, watershed features accounted for more than 60% of overall cross-system variability in DOC in both reservoirs and streams. Driver-response relations, however, differed between regions. This analysis extends our understanding of environmental influences on surface water chemistry in Missouri and indicates DOC is nearly as predictable as macronutrients using landscape-level features.
Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.
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Laura","contributorId":336723,"corporation":false,"usgs":false,"family":"Lukens","given":"Laura","affiliations":[{"id":80852,"text":"Monarch Joint Venture","active":true,"usgs":false}],"preferred":false,"id":900890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":900891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Christian","contributorId":336724,"corporation":false,"usgs":false,"family":"Newman","given":"Christian","email":"","affiliations":[{"id":80850,"text":"Electric Power Research Institute","active":true,"usgs":false}],"preferred":false,"id":900892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253576,"text":"70253576 - 2024 - Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","interactions":[],"lastModifiedDate":"2024-07-01T14:41:54.77567","indexId":"70253576","displayToPublicDate":"2024-04-29T08:28:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","docAbstract":"An important provision of the Minamata Convention on Mercury is to monitor and evaluate the effectiveness of the adopted measures and its implementation. Here, we describe for the first time currently available biotic mercury (Hg) data on a global scale to improve the understanding of global efforts to reduce the impact of Hg pollution on people and the environment. Data from the peer-reviewed literature were compiled in the Global Biotic Mercury Synthesis (GBMS) database (>550,000 data points). These data provide a foundation for establishing a biomonitoring framework needed to track Hg concentrations in biota globally. We describe Hg exposure in the taxa identified by the Minamata Convention: fish, sea turtles, birds, and marine mammals. Based on the GBMS database, Hg concentrations are presented at relevant geographic scales for continents and oceanic basins. We identify some effective regional templates for monitoring methylmercury (MeHg) availability in the environment, but overall illustrate that there is a general lack of regional biomonitoring initiatives around the world, especially in Africa, Australia, Indo-Pacific, Middle East, and South Atlantic and Pacific Oceans. Temporal trend data for Hg in biota are generally limited. Ecologically sensitive sites (where biota have above average MeHg tissue concentrations) have been identified throughout the world. Efforts to model and quantify ecosystem sensitivity locally, regionally, and globally could help establish effective and efficient biomonitoring programs. We present a framework for a global Hg biomonitoring network that includes a three-step continental and oceanic approach to integrate existing biomonitoring efforts and prioritize filling regional data gaps linked with key Hg sources. We describe a standardized approach that builds on an evidence-based evaluation to assess the Minamata Convention’s progress to reduce the impact of global Hg pollution on people and the environment.
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To date, the progress toward the wetlands outcome (creation/ restoration of 85,000 acres and enhancement of 150,000 acres) has been very slow and the outcome is projected to be off course for 2025. Two specific confounding issues arise in efforts to achieve the Bay wetlands goal: 1) the idea that restoration is driven, and incentivized and accounted for, in order to meet the TMDL’s water quality (WQ) benefits, leaving habitat benefits undervalued; and 2) there is often tension between competing restoration priorities and financial resources among different Best Management Practice (BMP) types that include wetlands, such as wetland restoration/creation/rehabilitation, stream restoration, and the creation or restoration of forest buffers.
The collaborative workshop “Evaluating an Improved Systems Approach to Wetland Crediting: Consideration of Wetland Ecosystem Services” was held March 22-23, 2022 to explore the wetland accounting system and provide insight on improved approaches to promote wetland projects toward the wetlands outcome. Four sessions were organized around topics of 1) Accounting, 2) Landscape Systems Approach, 3) Wetlands Projects and Co-Benefits, and 4) Management Implications and Recommendation Development with 21 presentations, Q and A and facilitated discussions.
Acknowledgement of the limitations of the current management framework to achieve significant gains in wetland area supports the conclusion that absent significant adaptive management of wetlands efforts, any outcome for net wetlands gains beyond 2025 will be similarly confounded. Workshop findings included suggestions for how to approach restoration projects at a systems level (e.g., creek, shoreline reach, watershed) in order to maximize synergies for multiple ecological outcomes and ecosystem services. Recommendations for improvement on existing efforts, as well as new processes, tools and partnerships are suggested from the workshop’s analysis of the state of the science as considerations to increase implementation of wetlands projects.
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Environment","active":true,"usgs":false}],"preferred":false,"id":899779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Claggett, Sally","contributorId":335927,"corporation":false,"usgs":false,"family":"Claggett","given":"Sally","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":899780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goerman, Dave","contributorId":335928,"corporation":false,"usgs":false,"family":"Goerman","given":"Dave","email":"","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":899781,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Landry, Brooke J.","contributorId":295485,"corporation":false,"usgs":false,"family":"Landry","given":"Brooke","email":"","middleInitial":"J.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":899782,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Santoro, Alison","contributorId":335929,"corporation":false,"usgs":false,"family":"Santoro","given":"Alison","email":"","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":899783,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70254152,"text":"70254152 - 2024 - Snow avalanches are a primary climate-linked driver of mountain ungulate populations","interactions":[],"lastModifiedDate":"2024-05-10T12:04:31.268887","indexId":"70254152","displayToPublicDate":"2024-04-29T07:01:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17775,"text":"Nature Communications Biology","active":true,"publicationSubtype":{"id":10}},"title":"Snow avalanches are a primary climate-linked driver of mountain ungulate populations","docAbstract":"Snow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in rapidly changing mountain ecosystems is particularly critical. Whereas effects of snow on food availability, energy expenditure, and predation are well documented, we report how avalanches exert major impacts on an ecologically significant mountain ungulate - the coastal Alaskan mountain goat (Oreamnos americanus). Using long-term GPS data and field observations across four populations (421 individuals over 17 years), we show that avalanches caused 23−65% of all mortality, depending on area. Deaths varied seasonally and were directly linked to spatial movement patterns and avalanche terrain use. Population-level avalanche mortality, 61% of which comprised reproductively important prime-aged individuals, averaged 8% annually and exceeded 22% when avalanche conditions were severe. Our findings reveal a widespread but previously undescribed pathway by which snow can elicit major population-level impacts and shape demographic characteristics of slow-growing populations of mountain-adapted animals.
Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples (n = 98) were collected biweekly, and sewage influent samples (n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides, human Lachnospiraceae) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.
Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.
Birds are used as bioindicators of environmental mercury (Hg) contamination, and toxicity reference values are needed for injury assessments. We conducted a comprehensive review, summarized data from 168 studies, performed a series of Bayesian hierarchical meta-analyses, and developed new toxicity reference values for the effects of methylmercury (MeHg) on birds using a benchmark dose analysis framework. Lethal and sublethal effects of MeHg on birds were categorized into nine biologically relevant endpoint categories and three age classes. Effective Hg concentrations where there was a 10% reduction (EC10) in the production of juvenile offspring (0.55 µg/g wet wt adult blood-equivalent Hg concentrations, 80% credible interval: [0.33, 0.85]), histology endpoints (0.49 [0.15, 0.96] and 0.61 [0.09, 2.48]), and biochemical markers (0.77 [<0.25, 2.12] and 0.57 [0.35, 0.92]) were substantially lower than those for survival (2.97 [2.10, 4.73] and 5.24 [3.30, 9.55]) and behavior (6.23 [1.84, >13.42] and 3.11 [2.10, 4.64]) of juveniles and adults, respectively. Within the egg age class, survival was the most sensitive endpoint (EC10 = 2.02 µg/g wet wt adult blood-equivalent Hg concentrations [1.39, 2.94] or 1.17 µg/g fresh wet wt egg-equivalent Hg concentrations [0.80, 1.70]). Body morphology was not particularly sensitive to Hg. We developed toxicity reference values using a combined survival and reproduction endpoints category for juveniles, because juveniles were more sensitive to Hg toxicity than eggs or adults. Adult blood-equivalent Hg concentrations (µg/g wet wt) and egg-equivalent Hg concentrations (µg/g fresh wet wt) caused low injury to birds (EC1) at 0.09 [0.04, 0.17] and 0.04 [0.01, 0.08], moderate injury (EC5) at 0.6 [0.37, 0.84] and 0.3 [0.17, 0.44], high injury (EC10) at 1.3 [0.94, 1.89] and 0.7 [0.49, 1.02], and severe injury (EC20) at 3.2 [2.24, 4.78] and 1.8 [1.28, 2.79], respectively. Maternal dietary Hg (µg/g dry wt) caused low injury to juveniles at 0.16 [0.05, 0.38], moderate injury at 0.6 [0.29, 1.03], high injury at 1.1 [0.63, 1.87], and severe injury at 2.4 [1.42, 4.13]. We found few substantial differences in Hg toxicity among avian taxonomic orders, including for controlled laboratory studies that injected Hg into eggs. Our results can be used to quantify injury to birds caused by Hg pollution.
This study focuses on understanding the association of rare earth elements (REE; lanthanides + yttrium + scandium) with organic matter from the Middle Devonian black shales of the Appalachian Basin. Developing a better understanding of the role of organic matter (OM) and thermal maturity in REE partitioning may help improve current geochemical models of REE enrichment in a wide range of black shales. We studied relationships between whole rock REE content and total organic carbon (TOC) and compared the correlations with a suite of global oil shales that contain TOC as high as 60 wt.%. The sequential leaching of the Appalachian shale samples was conducted to evaluate the REE content associated with carbonates, Fe–Mn oxyhydroxides, sulfides, and organics. Finally, the residue from the leaching experiment was analyzed to assess the mineralogical changes and REE extraction efficiency. Our results show that heavier REE (HREE) have a positive correlation with TOC in our Appalachian core samples. However, data from the global oil shales display an opposite trend. We propose that although TOC controls REE enrichment, thermal maturation likely plays a critical role in HREE partitioning into refractory organic phases, such as pyrobitumen. The REE inventory from a core in the Appalachian Basin shows that (1) the total REE ranges between 180 and 270 ppm and the OM-rich samples tend to contain more REE than the calcareous shales; (2) there is a relatively higher abundance of middle REE (MREE) to HREE than lighter REE (LREE); (3) there is a disproportionate increase in Y and Tb with TOC likely due to the rocks being over-mature; and (4) the REE extraction demonstrates that although the OM has higher HREE concentration, the organic leachates contain more LREE, suggesting it is more challenging to extract HREE from OM than using traditional leaching techniques.
","language":"English","publisher":"MDPI","doi":"10.3390/en17092107","usgsCitation":"Bhattacharya, S., Sharma, S., Agrawal, V., Dix, M.C., Zanoni, G., Birdwell, J.E., Wylie, A.S., and Wagner, T., 2024, Influence of organic matter thermal maturity on rare earth element distribution: A study of Middle Devonian black shales from the Appalachian Basin, USA: Energies, v. 17, no. 9, 2107, 23 p., https://doi.org/10.3390/en17092107.","productDescription":"2107, 23 p.","ipdsId":"IP-160281","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":439736,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en17092107","text":"Publisher Index Page"},{"id":428357,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Middle Devonian Appalachian Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.019722212101,\n 35.09354117626262\n ],\n [\n -80.0893868493873,\n 35.83616426236574\n ],\n [\n -75.48876301910367,\n 41.23650512855389\n ],\n [\n -74.6944038739024,\n 43.48785346597265\n ],\n [\n -79.3043542917768,\n 42.997887934674736\n ],\n [\n -83.72355980871455,\n 37.83971543304291\n ],\n [\n -85.019722212101,\n 35.09354117626262\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhattacharya, Shailee","contributorId":336153,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Shailee","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharma, Shikha","contributorId":336154,"corporation":false,"usgs":false,"family":"Sharma","given":"Shikha","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agrawal, Vikas","contributorId":336156,"corporation":false,"usgs":false,"family":"Agrawal","given":"Vikas","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dix, Michael C.","contributorId":336159,"corporation":false,"usgs":false,"family":"Dix","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":80761,"text":"Consultant (formerly with PremierCorex)","active":true,"usgs":false}],"preferred":false,"id":900060,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zanoni, Giovanni","contributorId":336160,"corporation":false,"usgs":false,"family":"Zanoni","given":"Giovanni","email":"","affiliations":[{"id":80763,"text":"RohmTek, Houston, TX","active":true,"usgs":false}],"preferred":false,"id":900061,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":900062,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wylie, Albert S. 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Chronic wasting disease (CWD) has been detected in cervids inhabiting North America, the Nordic countries, and South Korea. CWD-prion spread is partially attributed to carcass transport and disposal. We employed a forensic approach to investigate an illegal carcass dump site connected with a CWD-positive herd. We integrated anatomic, genetic, and prion amplification methods to discover CWD-positive remains from six white-tailed deer (Odocoileus virginianus) and, using microsatellite markers, confirmed a portion originated from the CWD-infected herd. This approach provides a foundation for future studies of carcass prion transmission risk.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/19336896.2024.2343298","usgsCitation":"Schwabenlander, M.D., Bartz, J.C., Carstensen, M., Fameli, A., Glaser, L., Larsen, R.J., Li, M., Shoemaker, R.L., Rowden, G., Stone, S., Walter, W., Wolf, T.M., and Larsen, P.A., 2024, Prion forensics: A multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site: Prion, v. 18, no. 1, p. 72-86, https://doi.org/10.1080/19336896.2024.2343298.","productDescription":"15 p.","startPage":"72","endPage":"86","ipdsId":"IP-148949","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19336896.2024.2343298","text":"Publisher Index Page"},{"id":433385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Beltrami 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U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.
Many forests globally are experiencing increases in large, high-severity wildfires, often with increasingly inadequate post-fire tree regeneration. To identify areas that might need post-fire planting, forest managers have a growing need for seedling reference densities – the natural seedling densities expected to be adequate to regenerate a forest – to compare with observed post-fire seedling densities. The most useful reference densities will meet five criteria: they will (1) be specific to natural post-fire reproduction rather than planted seedlings (because planted seedlings can have substantially greater survival than natural seedlings, thus underestimating adequate natural reproduction), (2) apply to the first few years following fire (when management decisions and actions are most likely), (3) be specific to each of those post-fire years (because post-fire seedling densities can change rapidly with time since fire), (4) be associated with estimates of uncertainty, and (5) include consideration of novel environmental conditions during management applications (because most reference densities will be based on data collected under more environmentally benign conditions). The world’s most massive tree species, the giant sequoia (Sequoiadendron giganteum) of California’s Sierra Nevada, recently experienced historically unprecedented wildfires that killed an estimated 13–19% of mature sequoias across their native range. Seedlings germinating after these fires then experienced exceptional summer heat and the two most severe summer droughts of the 121-year historical record. To help inform management responses to these events, we used seedling censuses from past fires (mostly prescribed fires) to calculate sequoia seedling reference densities meeting the five criteria. The reference densities had three striking features, which are partly attributable to giant sequoia’s status as a pioneer species. First, despite being inherently conservative, the reference densities were quite high. For example, mean first-year reference density was 172,599 seedlings ha−1. Second, reference densities declined precipitously with time since fire: the mean fifth-year reference density was only 5% of the mean first-year density. Third, the reference densities were associated with relatively substantial uncertainty, a consequence of density variations among seedling plots; for example, the 95% credible interval for first-year reference density was 64,377 to 313,438 seedlings ha−1. Despite this uncertainty, a case-study sequoia grove that recently burned in a high-severity wildfire had second-year post-fire seedling densities that were significantly (and dramatically) lower than the corresponding second-year reference density, suggesting inadequate post-fire reproduction. Our results highlight the value of the five criteria for reference densities – criteria that, in current practice, are rarely all met.