The U.S. Department of the Interior recently included uranium (U) on a list of mineral commodities that are considered critical to economic and national security. The uses of U for commercial and residential energy production, defense applications, medical device technologies, and energy generation for space vehicles and satellites are known, but the environmental impacts of uranium extraction are not always well quantified. We conducted a screening-level ecological risk analysis based on exposure to mining-related elements via diets and incidental soil ingestion for terrestrial biota to provide context to chemical characterization and exposures at breccia pipe U mines in northern Arizona. Relative risks, calculated as hazard quotients (HQs), were generally low for all biological receptor models. Our models screened for risk to omnivores and insectivores (HQs>1) but not herbivores and carnivores. Uranium was not the driver of ecological risk; arsenic, cadmium, copper, and zinc were of concern for biota consuming ground-dwelling invertebrates. Invertebrate species composition should be considered when applying these models to other mining locations or future sampling at the breccia pipe mine sites. Dietary concentration thresholds (DCTs) were also calculated to understand food concentrations that may lead to ecological risk. The DCTs indicated that critical concentrations were not approached in our model scenarios, as evident in the very low HQs for most models. The DCTs may be used by natural resource and land managers as well as mine operators to screen or monitor for potential risk to terrestrial receptors as mine sites are developed and remediated in the future.
1. The effects of changing climate and disturbance on mountain forest carbon stocks vary with tree species distributions and over elevational gradients. Warming can increase carbon uptake by stimulating productivity at high elevations but also enhance carbon release by increasing respiration and the frequency, intensity, and size of wildfires.
2. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species, and their combined effects on regional carbon stocks in forests of the Greater Yellowstone Ecosystem, USA with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario.
3. Total ecosystem carbon increased by 67% through 2100 in simulations with historical climate, and by 38 – 69% with GCM climate. Differences in carbon uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper treeline, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27 – 215% under GCM climate, with the largest increases after 2050. With warming >3 °C in mean annual temperature, the increased frequency of large fires reduced live carbon stocks by 4 – 36% relative to the control, historical climate scenario. However, relative losses in total carbon were delayed under GCMs with large increases in summer precipitation and buffered by carbon retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and carbon uptake.
4. Synthesis.Forests in the GYE can maintain a carbon sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live aboveground biomass, and ultimately, ecosystem carbon. Future changes in carbon stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13559","usgsCitation":"Henne, P., Hawbaker, T., Scheller, R.M., Zhao, F.S., He, H.S., Xu, W., and Zhu, Z., 2021, Increased burning in a warming climate reduces carbon uptake in the Greater Yellowstone Ecosystem despite productivity gains: Journal of Ecology, v. 109, no. 3801, p. 1148-1169, https://doi.org/10.1111/1365-2745.13559.","productDescription":"22 p.","startPage":"1148","endPage":"1169","ipdsId":"IP-110024","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":454241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13559","text":"Publisher Index Page"},{"id":436640,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94IA5B3","text":"USGS data release","linkHelpText":"Landscape inputs and simulation output for the LANDIS-II model in the Greater Yellowstone Ecosystem"},{"id":380677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 42.48019996901214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"3801","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":805423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheller, Robert M. 0000-0002-7507-4499","orcid":"https://orcid.org/0000-0002-7507-4499","contributorId":245139,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":805424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhao, Feng S 0000-0003-4534-933X","orcid":"https://orcid.org/0000-0003-4534-933X","contributorId":245140,"corporation":false,"usgs":false,"family":"Zhao","given":"Feng","email":"","middleInitial":"S","affiliations":[{"id":49091,"text":"Central China Normal University","active":true,"usgs":false}],"preferred":false,"id":805425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Hong S","contributorId":218764,"corporation":false,"usgs":false,"family":"He","given":"Hong","email":"","middleInitial":"S","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Wenru","contributorId":245141,"corporation":false,"usgs":false,"family":"Xu","given":"Wenru","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":805428,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216906,"text":"70216906 - 2021 - Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology","interactions":[],"lastModifiedDate":"2020-12-30T14:45:53.316375","indexId":"70216906","displayToPublicDate":"2020-11-20T07:04:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology","docAbstract":"Freshwater lenses underlying small ocean islands exhibit spatial variability and temporal fluctuations in volume, influencing ecologic management. For example, The Palmyra Atoll National Wildlife Refuge harbors one of the few surviving native stands of Pisonia grandis in the central Pacific Ocean, yet these trees face pressure from groundwater salinization, with little basic groundwater data to guide decision making. Adding to natural complexity, the geology of Palmyra was heavily altered by dredge and fill activities. Our study based at this atoll combines geophysical and hydrological field measurements from 2008 to 2019 with groundwater modeling to study the drivers of observed freshwater lens dynamics. Electromagnetic induction (EMI) field data were collected on the main atoll islands over repeat transects in 2008 following ‘strong’ La Niña conditions (wet) and in 2016 during ‘very strong’ El Niño conditions (dry). Shallow monitoring wells were installed adjacent to the geophysical transects in 2013 and screened within the fresh/saline groundwater transition zone. Temporal EMI and monitoring well data showed a strong contraction of the freshwater lens in response to El Niño conditions, and indicated a thicker lens toward the ocean side, an opposite spatial pattern to that observed for many other Pacific islands. On an outer islet where a stand of mature Pisonia trees exist, EMI surveys revealed only a thin (<3 m from land surface) layer of brackish groundwater during El Niño. Numerical groundwater simulations were performed for a range of permeability distributions and climate conditions at Palmyra. Results revealed that the observed atypical lens asymmetry is likely due to more efficient submarine groundwater discharge on the lagoon side as a result of lagoon dredging and filling with high-permeability material. Simulations also predict large decreases (40%) in freshwater lens volume during dry cycles and highlight threats to the Pisonia trees, yielding insight for atoll ecosystem management worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143838","usgsCitation":"Briggs, M.A., Cantelon, J., Kurylyk, B., Kulongoski, J.T., Mills, A., and Lane, J., 2021, Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology: Science of the Total Environment, v. 756, 143838, 14 p., https://doi.org/10.1016/j.scitotenv.2020.143838.","productDescription":"143838, 14 p.","ipdsId":"IP-124031","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.143838","text":"Publisher Index Page"},{"id":381317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.11434364318848,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.865525058703975\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"756","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":806900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cantelon, J","contributorId":245723,"corporation":false,"usgs":false,"family":"Cantelon","given":"J","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, B.","contributorId":222758,"corporation":false,"usgs":false,"family":"Kurylyk","given":"B.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Audrey","contributorId":245724,"corporation":false,"usgs":false,"family":"Mills","given":"Audrey","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":806904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806905,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217186,"text":"70217186 - 2021 - The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","interactions":[],"lastModifiedDate":"2021-01-11T16:11:26.62147","indexId":"70217186","displayToPublicDate":"2020-11-18T10:00:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","docAbstract":"Steamboat Geyser in Yellowstone National Park’s Norris Geyser Basin began a prolific sequence of eruptions in March 2018 after 34 y of sporadic activity. We analyze a wide range of datasets to explore triggering mechanisms for Steamboat’s reactivation and controls on eruption intervals and height. Prior to Steamboat’s renewed activity, Norris Geyser Basin experienced uplift, a slight increase in radiant temperature, and increased regional seismicity, which may indicate that magmatic processes promoted reactivation. However, because the geothermal reservoir temperature did not change, no other dormant geysers became active, and previous periods with greater seismic moment release did not reawaken Steamboat, the reason for reactivation remains ambiguous. Eruption intervals since 2018 (3.16 to 35.45 d) modulate seasonally, with shorter intervals in the summer. Abnormally long intervals coincide with weakening of a shallow seismic source in the geyser basin’s hydrothermal system. We find no relation between interval and erupted volume, implying unsteady heat and mass discharge. Finally, using data from geysers worldwide, we find a correlation between eruption height and inferred depth to the shallow reservoir supplying water to eruptions. Steamboat is taller because water is stored deeper there than at other geysers, and, hence, more energy is available to power the eruptions.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2020943118","usgsCitation":"Reed, M., Munoz-Saez, C., Hajimirza, S., Wu, S., Barth, A., Girona, T., Rasht-Behesht, M., Karplus, M., Hurwitz, S., and Manga, M., 2021, The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser: PNAS, v. 118, no. 2, e2020943118, 10 p., https://doi.org/10.1073/pnas.2020943118.","productDescription":"e2020943118, 10 p.","ipdsId":"IP-123913","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2020943118","text":"Publisher Index Page"},{"id":382060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Steamboat Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.71465730667114,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.71879196233473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Mara","contributorId":247557,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","affiliations":[],"preferred":false,"id":807890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munoz-Saez, Carolina","contributorId":131167,"corporation":false,"usgs":false,"family":"Munoz-Saez","given":"Carolina","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hajimirza, Sahand","contributorId":247558,"corporation":false,"usgs":false,"family":"Hajimirza","given":"Sahand","email":"","affiliations":[],"preferred":false,"id":807892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Sin-Mei","contributorId":175479,"corporation":false,"usgs":false,"family":"Wu","given":"Sin-Mei","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":807893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Anna","contributorId":247559,"corporation":false,"usgs":false,"family":"Barth","given":"Anna","email":"","affiliations":[],"preferred":false,"id":807894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":807895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rasht-Behesht, Majid","contributorId":247560,"corporation":false,"usgs":false,"family":"Rasht-Behesht","given":"Majid","email":"","affiliations":[],"preferred":false,"id":807896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karplus, M.S","contributorId":205767,"corporation":false,"usgs":false,"family":"Karplus","given":"M.S","email":"","affiliations":[{"id":37164,"text":"University of Texas, El Paso","active":true,"usgs":false}],"preferred":false,"id":807897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":807898,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manga, Michael","contributorId":131168,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807899,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70243772,"text":"70243772 - 2021 - Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","interactions":[],"lastModifiedDate":"2023-05-19T11:43:02.869837","indexId":"70243772","displayToPublicDate":"2020-11-18T06:33:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","title":"Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts","docAbstract":"An understanding of how undesirable and desirable fish species respond behaviorally to turbulent flow in fishways would guide development of selective fish passage techniques. We applied high-resolution computational fluid dynamics modeling and competing risks analysis towards the development of predictive selective passage models. Sea lamprey (Petromyzon marinus; an invasive fish in the Great Lakes Basin, North America) upstream passage probability declined from 0.73 to 0.03 as flow conditions became increasingly turbulent, while declines in white sucker (Catostomus commersonii, a native fish in the region) upstream passage probability were less substantial (0.53 to 0.44). Deploying a sea lamprey trap in the fishway did not effectively reduce sea lamprey upstream passage probability, though capture rate increased during trials with cooler water temperature and low total kinetic energy. Bifurcated fishways that maintain low turbulent flow in the entrapment route and high turbulent flow in the upstream passage route could increase the effectiveness of trapping sea lamprey in fishways as a means to advance selective passage goals.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0223","usgsCitation":"Lewandoski, S.A., Hrodey, P.J., Miehls, S.M., Piszczek, P., and Zielinski, D., 2021, Behavioral responses of sea lamprey (Petromyzon marinus) and white sucker (Catostomus commersonii) to turbulent flow during fishway passage attempts: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 409-421, https://doi.org/10.1139/cjfas-2020-0223.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-120067","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":417234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bois Brule River, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.61913799037413,\n 46.746319413615765\n ],\n [\n -91.61109265501442,\n 46.697600103611876\n ],\n [\n -91.60349428273015,\n 46.66908351070549\n ],\n [\n -91.610645691939,\n 46.6396312386392\n ],\n [\n -91.59455502121916,\n 46.61568945646317\n ],\n [\n -91.59008539046347,\n 46.5831713812953\n ],\n [\n -91.59768376274775,\n 46.54414318194961\n ],\n [\n -91.61735013807177,\n 46.5241572565657\n ],\n [\n -91.60751695040997,\n 46.48507053273994\n ],\n [\n -91.63612258724542,\n 46.45367061381313\n ],\n [\n -91.68126585787567,\n 46.44011995829479\n ],\n [\n -91.75201200283867,\n 46.40437245435308\n ],\n [\n -91.75201200283867,\n 46.39820791069087\n ],\n [\n -91.64652871700919,\n 46.43980506395201\n ],\n [\n -91.6128335861273,\n 46.45168996471648\n ],\n [\n -91.5878036538965,\n 46.483091025906276\n ],\n [\n -91.59853076771002,\n 46.527698611965775\n ],\n [\n -91.576629577008,\n 46.54522398535883\n ],\n [\n -91.57081905702584,\n 46.589166256606916\n ],\n [\n -91.57528868778131,\n 46.62048794471005\n ],\n [\n -91.59137935850114,\n 46.64381389971618\n ],\n [\n -91.58512187544464,\n 46.68098665401865\n ],\n [\n -91.59629595233312,\n 46.712255228466375\n ],\n [\n -91.5954020261823,\n 46.726657203488514\n ],\n [\n -91.60389432461741,\n 46.75361226678078\n ],\n [\n -91.61913799037413,\n 46.746319413615765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewandoski, Sean A.","contributorId":221007,"corporation":false,"usgs":false,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":873209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrodey, Peter J.","contributorId":205578,"corporation":false,"usgs":false,"family":"Hrodey","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":873210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":873211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piszczek, Paul","contributorId":305569,"corporation":false,"usgs":false,"family":"Piszczek","given":"Paul","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":873212,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zielinski, Daniel","contributorId":245798,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":873213,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215397,"text":"70215397 - 2021 - Sediment dynamics of a divergent bay–marsh complex","interactions":[],"lastModifiedDate":"2021-06-01T17:19:12.643911","indexId":"70215397","displayToPublicDate":"2020-11-17T12:55:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Sediment dynamics of a divergent bay–marsh complex","docAbstract":"Bay–marsh systems, composed of an embayment surrounded by fringing marsh incised by tidal channels, are widely distributed coastal environments. External sediment availability, marsh-edge erosion, and sea-level rise acting on such bay–marsh complexes may drive diverse sediment-flux regimes. These factors reinforce the ephemeral and dynamic nature of fringing marshes: material released by marsh-edge erosion becomes part of a bay–marsh exchange that fuels the geomorphic evolution of the coupled system. The dynamics of this sediment exchange determine the balance among seaward export, deposition on the embayment seabed, flux into tidal channels, and import to the marsh platform. In this work, we investigate the sediment dynamics of a transgressive bay–marsh complex and link them to larger-scale considerations of its geomorphic trajectory. Grand Bay, Alabama/Mississippi, is a shallow microtidal embayment surrounded by salt marshes with lateral erosion rates of up to 5 m year−1. We collected 6 months of oceanographic data at four moorings within Grand Bay and its tidal channels to assess hydrographic conditions and net sediment-flux patterns and augmented the observations with numerical modeling. The observations imply a divergent sedimentary system in which a majority of the suspended sediment is exported seaward, while a smaller fraction is imported landward via tidal channels, assisting in vertical marsh-plain accumulation, maintenance of channel and intertidal-flat morphologies, and landward transgression. These results describe a dynamic system that is responsive to episodic atmospheric forcing in the absence of a strong tidal signal and the presence of severe lateral marsh loss.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00855-5","usgsCitation":"Nowacki, D.J., and Ganju, N., 2021, Sediment dynamics of a divergent bay–marsh complex: Estuaries and Coasts, v. 44, p. 1216-1230, https://doi.org/10.1007/s12237-020-00855-5.","productDescription":"15 p.","startPage":"1216","endPage":"1230","ipdsId":"IP-120963","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-020-00855-5","text":"Publisher Index Page"},{"id":382512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Grand Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.43856811523438,\n 30.34562073484083\n ],\n [\n -88.35582733154297,\n 30.34562073484083\n ],\n [\n -88.35582733154297,\n 30.422032481449097\n ],\n [\n -88.43856811523438,\n 30.422032481449097\n ],\n [\n -88.43856811523438,\n 30.34562073484083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":802011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216779,"text":"70216779 - 2021 - Generalizing the inversion‐based PSHA source model for an interconnected fault system","interactions":[],"lastModifiedDate":"2023-03-27T16:59:07.467182","indexId":"70216779","displayToPublicDate":"2020-11-17T09:41:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Generalizing the inversion‐based PSHA source model for an interconnected fault system","docAbstract":"This article represents a step toward generalizing and simplifying the procedure for constructing an inversion‐based seismic hazard source model for an interconnected fault system, including the specification of adjustable segmentation constraints. A very simple example is used to maximize understandability and to counter the notion that an inversion approach is only applicable when an abundance of data is available. Also exemplified is how to construct a range of models to adequately represent epistemic uncertainties (which should be a high priority in any hazard assessment). Opportunity is also taken to address common concerns and misunderstandings associated with the third Uniform California Earthquake Rupture Forecast, including the seemingly disproportionate number of large‐magnitude events, and how well hazard is resolved given the overall problem is very underdetermined. However, the main aim of this article is to provide a general protocol for constructing such models.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200219","usgsCitation":"Field, E.H., Milner, K.R., and Page, M.T., 2021, Generalizing the inversion‐based PSHA source model for an interconnected fault system: Bulletin of the Seismological Society of America, v. 111, no. 1, p. 371-390, https://doi.org/10.1785/0120200219.","productDescription":"20 p.","startPage":"371","endPage":"390","ipdsId":"IP-122019","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":381034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":806224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":806225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":806226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249204,"text":"70249204 - 2021 - Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","interactions":[],"lastModifiedDate":"2023-10-02T11:46:50.38526","indexId":"70249204","displayToPublicDate":"2020-11-17T06:41:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","docAbstract":"We demonstrate successful crustal imaging via teleseismic P‐wave coda autocorrelation, using data recorded on a 261 station array of vertical‐component high‐frequency geophones in the area of the Bighorn Mountains, Wyoming, U.S.A. We autocorrelate the P‐wave coda of 30 teleseismic events and use phase‐weighted stacking to yield seismic profiles comparable to low‐passed versions of those produced via controlled‐source vertical seismic reflection. Our process recovers reflections from the bottoms of the Bighorn and Powder River basins that flank the Bighorn Mountains. We also identify a mid‐crustal reflector that aligns with a region of increased reflectivity, previously interpreted as a Precambrian province boundary. Our results demonstrate the utility of crustal imaging with teleseismic P‐wave coda energy using modern large‐array seismic data, and they corroborate previous interpretations of crustal structures in the study area.
Excavation of Ptolemaic Period (ca. 309–30 BC) strata within Theban Tombs 11, 12, -399-, and UE194A by the Spanish Mission to Dra Abu el-Naga (also known as the Djehuty Project), on the west bank of the Nile River opposite Luxor, Egypt, yielded remains of at least 175 individual small mammals that include four species of shrews (Eulipotypha: Soricidae) and two species of rodents (Rodentia: Muridae). Two of the shrews (Crocidura fulvastra and Crocidura pasha) no longer occur in Egypt, and one species (Crocidura olivieri) is known in the country only from a disjunct population inhabiting the Nile delta and the Fayum. Although deposited in the tombs by humans as part of religious ceremonies, these animals probably derived originally from local wild populations. The coexistence of this diverse array of shrew species as part of the mammal community near Luxor indicates greater availability of moist floodplain habitats than occur there at present. These were probably made possible by a greater flow of the Nile, as indicated by geomorphological and palynological evidence. The mammal fauna recovered by the Spanish Mission provides a unique snapshot of the native Ptolemaic community during this time period, and it permits us to gauge community turnover in the Nile valley of Upper Egypt during the last 2000 years. It also serves as a relevant example for understanding the extinction and extirpation of mammal species as effects of future environmental changes predicted by current climatic models.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2020.89","usgsCitation":"Woodman, N., and Ikram, S., 2021, Ancient Egyptian mummified shrews (Mammalia: Eulipotyphla: Soricidae) and mice (Rodentia: Muridae) from the Spanish Mission to Dra Abu el-Naga, and their implications for environmental change in the Nile valley during the past two millennia: Quaternary Research, v. 100, p. 21-31, https://doi.org/10.1017/qua.2020.89.","productDescription":"11 p.","startPage":"21","endPage":"31","ipdsId":"IP-122070","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":380835,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Egypt","otherGeospatial":"northern Egypt","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 24.873046874999996,\n 26.78484736105119\n ],\n [\n 33.2666015625,\n 26.78484736105119\n ],\n [\n 33.2666015625,\n 31.541089879585808\n ],\n [\n 24.873046874999996,\n 31.541089879585808\n ],\n [\n 24.873046874999996,\n 26.78484736105119\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationDate":"2020-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ikram, Salima","contributorId":245249,"corporation":false,"usgs":false,"family":"Ikram","given":"Salima","affiliations":[{"id":49125,"text":"American University in Cairo","active":true,"usgs":false}],"preferred":false,"id":805703,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216698,"text":"70216698 - 2021 - Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","interactions":[],"lastModifiedDate":"2020-12-01T13:34:28.581683","indexId":"70216698","displayToPublicDate":"2020-11-13T07:32:16","publicationYear":"2021","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":"Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","docAbstract":"The Mainstems data model implements the catchment and flowpath concepts from WaterML2 Part 3: Surface Hydrology Features (HY_Features) for persistent, cross-scale, identification of hydrologic features. The data model itself provides a focused and lightweight method to describe hydrologic networks with minimum but sufficient information. The design is intended to provide a model for data integration that can be used for network navigation and persistent hydrologic indexing (hydrographic addressing) functionality. Mainstems is designed to provide long-term stability with minimal maintenance requirements. The data model is not meant to advance hydrologic process representation or uniquely represent geomorphic characteristics. The principle assumption in Mainstems is that all drainage basins have one - and only one - headwater source area and a single mainstem that flows to a single outlet. Using these base feature types, (headwater, outlet, mainstem, and drainage basin) a nested set of drainage basins - and the associated dendritic network of mainstems - can be identified.
Maximum densities of juvenile river herring (Alewife Alosa pseudoharengus and Blueback Herring A. aestivalis) vary among freshwater lakes, likely due to densities of adult spawners. Differences in habitat availability and lake water quality may also contribute to variation in juvenile river herring productivity between populations, yet these relationships have not been tested across a large geographic scope. In this study we investigated relationships between juvenile river herring densities and (1) spawning adult river herring densities, (2) lake habitat availability, and (3) lake water quality in 29 freshwater lakes in the northeastern USA. Purse seines were used at night to sample juvenile river herring monthly in June–August 2014 and 2015, with concurrent collection of lake-specific physical (e.g., lake surface area, mean depth, depth to thermocline), chemical (e.g., nitrogen, phosphorus, dissolved organic carbon [DOC]), and biological (chlorophyll a, adult spawning density) data. Spawning adult density (number of adults per surface area of lake) explained 66.6% of the variation in juvenile densities using a generalized additive model. Juvenile densities increased with increasing adult density, peaking at roughly 1,000 adults/ha, and then declined at higher adult densities, suggesting a limit to carrying capacity in juvenile production. Linear mixed-effects models revealed that differences in water quality and habitat across lakes explained additional variation in juvenile densities. Specifically, DOC was negatively related to juvenile densities, suggesting that DOC limits the amount of suitable, well-oxygenated epilimnion habitat available to juvenile river herring in late summer. Our results can be used to help understand expected juvenile production based on adult density within a lake, to inform expectations about juvenile growth and survival, and to understand the mechanisms for how changes in habitat availability and water quality affect river herring populations.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10282","usgsCitation":"Devine, M.T., Rosset, J., Roy, A.H., Gahagan, B.I., Armstrong, M.P., Whiteley, A., and Jordaan, A., 2021, Feeling the squeeze: Adult run size and habitat availability limit juvenile river herring densities in lakes: Transactions of the American Fisheries Society, v. 150, no. 2, p. 207-221, https://doi.org/10.1002/tafs.10282.","productDescription":"16 p.","startPage":"207","endPage":"221","ipdsId":"IP-120456","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.66455078125,\n 44.6061127451739\n ],\n [\n -70.927734375,\n 44.62175409623324\n ],\n [\n -72.1142578125,\n 43.723474896114794\n ],\n [\n -73.4326171875,\n 41.31082388091818\n ],\n [\n -71.103515625,\n 41.1290213474951\n ],\n [\n -70.0048828125,\n 41.32732632036622\n ],\n [\n -69.54345703125,\n 41.88592102814744\n ],\n [\n -70.400390625,\n 42.827638636242284\n ],\n [\n -69.78515625,\n 43.48481212891603\n ],\n [\n -68.84033203125,\n 44.02442151965934\n ],\n [\n -68.66455078125,\n 44.6061127451739\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Devine, Matthew T.","contributorId":204986,"corporation":false,"usgs":false,"family":"Devine","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":836323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosset, Julianne","contributorId":197446,"corporation":false,"usgs":false,"family":"Rosset","given":"Julianne","email":"","affiliations":[],"preferred":false,"id":836324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gahagan, Benjamin I.","contributorId":200168,"corporation":false,"usgs":false,"family":"Gahagan","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":836325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Michael P.","contributorId":286850,"corporation":false,"usgs":false,"family":"Armstrong","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":40132,"text":"Massachusetts Division of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":836326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whiteley, Andrew R.","contributorId":286853,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew R.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":836327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":210892,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":836328,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216363,"text":"70216363 - 2021 - A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","interactions":[],"lastModifiedDate":"2021-06-01T17:01:46.95513","indexId":"70216363","displayToPublicDate":"2020-11-11T09:23:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","docAbstract":"Estuaries are among the world’s most productive ecosystems, but recent natural and anthropogenic changes have stressed these ecosystems. Tools to assess estuarine pelagic habitats are important to support and maintain healthy ecosystem function. In this work, we demonstrate that estuarine pelagic habitats can be identified by a simple ratio, termed the LE ratio, that takes into account the tidal excursion along a channel (a Lagrangian length scale) and the distance along that channel (an Eulerian length scale). To develop and assess this concept, numerical simulations of the 1D advection–dispersion equation of a conservative tracer and tidal excursion estimates based on data were used to formulize a conceptual model and to define exchange zones within a tidal channel. This conceptual model was then used to predict the extent of pelagic habitats in a terminal channel network in the Sacramento–San Joaquin Delta. Exchange zones mapped onto these channels were found to be in good agreement with independent estimates of residence time. Sensitivity analyses of the numerical model suggest that productive pelagic habitats can be expanded by a factor of 2 by either increasing dispersion or increasing spring–neap variability in mean tidal velocity. Such changes can also enhance flushing in upper channel reaches. These findings are relevant for tidal marsh restoration projects that aim to expand beneficial aquatic habitats by varying exchange or residence time over the spring–neap cycle, because this variability may interact synergistically with varying rates of phytoplankton growth due to spatiotemporal changes in environmental conditions.
In 2017 the rusty patched bumble bee (Bombus affinis) became the first bee listed under the Endangered Species Act in the continental United States due to population declines and an 87% reduction in the species’ distribution. Bombus affinis decline began in the 1990s, predating modern bee surveying initiatives, and obfuscating drivers of decline. While understood to be a highly generalist forager, little is known about the role that resource limitation or shifting floral community composition could have played in B. affinis decline. Determining which floral species support B. affinis could assist conservation efforts where B. affinis persists and identify floral species for restoration efforts. We constructed a historical foraging profile of B. affinis via DNA sequencing of pollen from museum specimens spanning seven states collected from 1913 to 2013. Molecular analysis revealed no temporal changes in the floral richness or composition of B. affinis pollen samples across our sampling period. Likewise, we found no temporal changes in the presence or proportion of native vs. introduced species in pollen samples, though we observed much greater use of introduced floral species than previously determined for B. affinis. Floral community composition was regionally dissimilar, inconsistent with patterns of B. affinis decline by state. Our results suggest B. affinis decline was unlikely to have been driven by spatial or temporal limitations of specific floral species. This work greatly expands the known forage of B. affinis and will provide managers with insight to aid the conservation of B. affinis.
Anglers face constraints that influence participation and dropout rates. Some recreational anglers may be able to negotiate constraints by altering the timing or frequency of participation, acquiring new skills, or modifying nonrecreational aspects such as family or work responsibilities. We consider data collected via a mail survey from Georgia-resident trout license holders to identify both perceived constraints and strategies used to negotiate them. To capture variation among anglers, survey responses were grouped by level of angler specialization using K-means cluster analysis, which resulted in a three-cluster solution of most, moderately, and least specialized anglers. Analyses of variance were used to detect potential differences among the three specialization clusters. Tests revealed that the least specialized anglers experienced constraints more intensely than the most or moderately specialized anglers. Likewise, least specialized anglers were less able to negotiate constraints when compared to the most or moderately specialized anglers. However, the least specialized anglers used negotiation strategies involving overcoming perceived lack of skill more intensely than their counterparts. The most intensely experienced constraints overall were lack of time due to work or family obligations and distance to Georgia’s trout waters from home. The most intensely used negotiation strategies overall were “learn to enjoy being outside and stress less about catching fish” and “encourage family or friends to go fishing with me.” This research benefits fishery managers by providing a method of identifying angling groups that perceive more constraints and are less likely to overcome these constraints through constraint negotiation strategies. With this information, managers may choose to tailor efforts towards reducing constraints for angling groups that have low participation and may drop out of the activity all together.
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J.","contributorId":276309,"corporation":false,"usgs":false,"family":"TenHarmsel","given":"H. J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boley, B. B.","contributorId":276310,"corporation":false,"usgs":false,"family":"Boley","given":"B. B.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennings, Cecil A. 0000-0002-6159-6026 jennings@usgs.gov","orcid":"https://orcid.org/0000-0002-6159-6026","contributorId":874,"corporation":false,"usgs":true,"family":"Jennings","given":"Cecil","email":"jennings@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834734,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217679,"text":"70217679 - 2021 - Spectral inversion for seismic site response in central Oklahoma: Low-frequency resonances from the Great Unconformity","interactions":[],"lastModifiedDate":"2021-02-04T14:23:24.955134","indexId":"70217679","displayToPublicDate":"2020-11-10T07:30:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7571,"text":"Bulletin of Seismological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Spectral inversion for seismic site response in central Oklahoma: Low-frequency resonances from the Great Unconformity","docAbstract":"We investigate seismic site response by inverting seismic ground‐motion spectra for site and source spectral properties, in a region of central Oklahoma, where previous ground‐motion studies have indicated discrepancies between observations and ground‐motion models (GMMs). The inversion is constrained by a source spectral model, which we computed from regional seismic records, using aftershocks as empirical Green’s functions to deconvolve site and path effects. Site spectra across the region exhibit multiple, strong, low‐frequency (f <2 Hz) resonances. Modeling of vertically propagating SH waves reproduces the mean amplitudes and frequencies of the site spectra and requires a deep (∼1–2 km) impedance contrast. Comparison of regional seismic velocity models and geologic profiles indicates that the seismic impedance contrast is, or is in proximity to, the Great Unconformity, which marks the interface between Precambrian basement rocks and overlying Paleozoic sedimentary rocks. Depth to Precambrian basement increases to the southwest across the study region (∼1500–4500 m), and the fundamental frequencies of the site spectra are anticorrelated with basement depth. The first higher‐mode resonance also exhibits dependence on basement depth; although modeling suggests that the second higher mode should depend on basement depth, site spectra do not support this. The low‐frequency resonances in central Oklahoma are not represented in the GMMs used in current seismic hazard analyses for tectonic earthquakes, though approaches to account for such features are under consideration in other regions of the central and eastern United States. Given the broad spatial extent of the Great Unconformity underlying eastern North America, it is likely that similar effects on seismic site response also occur in other areas. This study highlights the impact of regional geologic structure on earthquake ground motions and reiterates the need for modeling regional effects to improve ground‐motion predictions and seismic hazard assessments.
It is unknown how ungulate physiological responses to environmental perturbation influence overall population demographics. Moreover, neonatal physiological responses remain poorly studied despite the importance of neonatal survival to population growth. Glucocorticoid (GC) hormones potentially facilitate critical physiological and behavioral responses to environmental perturbations. However, elevated GC concentrations over time may compromise body condition and indirectly reduce survival. We evaluated baseline salivary cortisol (CORT; a primary GC in mammals) concentrations in 19 wild neonatal white-tailed deer (Odocoileus virginianus) in a northern (NS) and southern (SS) area in Pennsylvania. After ranking survival models consisting of variables hypothesized to influence neonate survival (i.e. weight, sex), the probability of neonate survival was best explained by CORT concentrations, where elevated CORT concentrations were associated with reduced survival probability to 12 weeks of age. Cortisol concentrations were greater in the SS where predation rates and predator densities were lower. As the first evaluation of baseline CORT concentrations in an ungulate neonate to our knowledge, this is also the first study to demonstrate CORT concentrations are negatively associated with ungulate survival at any life stage. Glucocorticoid hormones could provide a framework in which to better understand susceptibility to mortality in neonatal white-tailed deer.
","language":"English","publisher":"Wiley","doi":"10.1111/1749-4877.12499","usgsCitation":"Gingery, T.M., Diefenbach, D.R., Pritchard, C.E., Ensminger, D., Wallingford, B., and Rosenberry, C., 2021, Survival is negatively associated with glucocorticoids in a wild ungulate neonate: Integrative Zoology, v. 16, no. 2, p. 214-225, https://doi.org/10.1111/1749-4877.12499.","productDescription":"12 p.","startPage":"214","endPage":"225","ipdsId":"IP-118200","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gingery, Tess Michelle","contributorId":276204,"corporation":false,"usgs":false,"family":"Gingery","given":"Tess","email":"","middleInitial":"Michelle","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Catharine E.","contributorId":276205,"corporation":false,"usgs":false,"family":"Pritchard","given":"Catharine","email":"","middleInitial":"E.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ensminger, David C.","contributorId":276206,"corporation":false,"usgs":false,"family":"Ensminger","given":"David C.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":276207,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberry, Christopher S.","contributorId":276209,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834661,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228597,"text":"70228597 - 2021 - Clothianidin decomposition in Missouri wetland soils","interactions":[],"lastModifiedDate":"2022-02-14T17:58:00.120595","indexId":"70228597","displayToPublicDate":"2020-11-09T11:55:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Clothianidin decomposition in Missouri wetland soils","docAbstract":"Neonicotinoid pesticides can persist in soils for extended time periods; however, they also have a high potential to contaminate ground and surface waters. Studies have reported negative effects associated with neonicotinoids and nontarget taxa, including aquatic invertebrates, pollinating insect species, and insectivorous birds. This study evaluated factors associated with clothianidin (CTN) degradation and sorption in Missouri wetland soils to assess the potential for wetland soils to mitigate potential environmental risks associated with neonicotinoids. Solid-to-solution partition coefficients (Kd) for CTN sorption to eight wetland soils were determined via single-point sorption experiments, and sorption isotherm experiments were conducted using the two most contrasting soils. Clothianidin degradation was determined under oxic and anoxic conditions over 60 d. Degradation data were fit to zero- and first-order kinetic decay models to determine CTN half-life (t0.5). Sorption results indicated CTN sorption to wetland soil was relatively weak (average Kd, 3.58 L kg–1); thus, CTN has the potential to be mobile and bioavailable within wetland soils. However, incubation results showed anoxic conditions significantly increased CTN degradation rates in wetland soils (anoxic average t0.5, 27.2 d; oxic average t0.5, 149.1 d). A significant negative correlation was observed between anoxic half-life values and soil organic C content (r2 = .782; p = .046). Greater CTN degradation rates in wetland soils under anoxic conditions suggest that managing wetlands to facilitate anoxic conditions could mitigate CTN presence in the environment and reduce exposure to nontarget organisms.
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N.","contributorId":276298,"corporation":false,"usgs":false,"family":"Lerch","given":"R.","email":"","middleInitial":"N.","affiliations":[{"id":56949,"text":"USDA-Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":834721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mengel, D.","contributorId":244519,"corporation":false,"usgs":false,"family":"Mengel","given":"D.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216472,"text":"70216472 - 2021 - Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","interactions":[],"lastModifiedDate":"2021-10-04T16:46:47.880285","indexId":"70216472","displayToPublicDate":"2020-11-09T07:45:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","docAbstract":"Synthesis. Ultimately, we quantify the ball‐and‐cup conceptual model for a salt marsh ecosystem and its alternative state, mudflat. We find that increasing abiotic stress due to climate change diminishes ecosystem resilience, but the interaction with common episodic disturbances is necessary to reveal transitions to alternative states and quantify state change thresholds. Quantifying and mapping resilience and where alternative states may exist in this fashion improves ecologists’ ability to investigate the mechanisms of stress gradient control on emergent ecosystem properties, while providing spatially explicit resources for managing ecosystems according to their projected resilience.
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\"}}]}","volume":"109","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":222380,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yando, Erik S.","contributorId":127788,"corporation":false,"usgs":false,"family":"Yando","given":"Erik","email":"","middleInitial":"S.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":805231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, W. Ryan","contributorId":245037,"corporation":false,"usgs":false,"family":"James","given":"W.","email":"","middleInitial":"Ryan","affiliations":[{"id":13722,"text":"University of Louisiana-Lafayette","active":true,"usgs":false}],"preferred":false,"id":805232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hester, Mark W.","contributorId":195572,"corporation":false,"usgs":false,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":34316,"text":"University of Louisiana at Lafayette, Lafayette, LA, USA","active":true,"usgs":false}],"preferred":false,"id":805234,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216485,"text":"70216485 - 2021 - Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast","interactions":[],"lastModifiedDate":"2021-01-19T16:23:52.964451","indexId":"70216485","displayToPublicDate":"2020-11-07T08:25:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast","docAbstract":"Coastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely.
To examine the role of land cover diversity and composition in landscape response to SLR across the northeastern United States.
Using an existing probabilistic framework, we quantify the probability of inundation, a measure of vulnerability, under different SLR scenarios on the coastal landscape. Resistant areas—wherein a dynamic response is anticipated—are defined as unlikely (p < 0.33) to inundate. Results are assessed regionally for different land cover types and at 26 sites representing varying levels of land cover diversity.
Modeling results suggest that by the 2050s, 44% of low-lying, habitable land in the region is unlikely to inundate, further declining to 36% by the 2080s. In addition to a decrease in SLR resistance with time, these results show an increasing uncertainty that the coastal landscape will continue to evolve in response to SLR as it has in the past. We also find that resistance to SLR is correlated with land cover composition, wherein sites containing land cover types adaptable to SLR impacts show greater potential to undergo biogeomorphic state shifts rather than inundating with time.
Our findings support other studies that have highlighted the importance of ecological composition and diversity in stabilizing the physical landscape and suggest that flexible planning strategies, such as adaptive management, are particularly well suited for SLR preparation in diverse coastal settings.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-020-01136-z","usgsCitation":"Lentz, E.E., Zeigler, S.L., Thieler, E.R., and Plant, N.G., 2021, Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast: Landscape Ecology, v. 36, p. 223-241, https://doi.org/10.1007/s10980-020-01136-z.","productDescription":"9 p.","startPage":"223","endPage":"241","ipdsId":"IP-101344","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-020-01136-z","text":"Publisher Index Page"},{"id":380684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.169921875,\n 44.10336537791152\n ],\n [\n -70.751953125,\n 44.26093725039923\n ],\n [\n -73.05908203125,\n 42.261049162113856\n ],\n [\n -76.7724609375,\n 39.639537564366684\n ],\n [\n -78.37646484375,\n 37.666429212090605\n ],\n [\n -77.71728515624999,\n 36.58024660149866\n ],\n [\n -75.34423828125,\n 36.43896124085945\n ],\n [\n -75.73974609375,\n 37.3002752813443\n ],\n [\n -74.0478515625,\n 39.977120098439634\n ],\n [\n -71.9384765625,\n 40.81380923056958\n ],\n [\n -69.80712890625,\n 41.178653972331674\n ],\n [\n -69.89501953125,\n 42.049292638686836\n ],\n [\n -70.64208984375,\n 42.8115217450979\n ],\n [\n -69.169921875,\n 44.10336537791152\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationDate":"2020-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeigler, Sara L. 0000-0002-5472-769X szeigler@usgs.gov","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":169601,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","email":"szeigler@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805386,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218686,"text":"70218686 - 2021 - Uncertainty in critical source area predictions from watershed-scale hydrologic models","interactions":[],"lastModifiedDate":"2021-03-05T13:28:39.226167","indexId":"70218686","displayToPublicDate":"2020-11-07T07:25:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in critical source area predictions from watershed-scale hydrologic models","docAbstract":"Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or ‘targeted’ for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%–46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.
Time series of water‐year runoff for 2,109 hydrologic units (HUs) across the conterminous United States (CONUS) for the 1900 through 2014 period were used to identify drought and pluvial (i.e., wet) periods. Characteristics of the drought and pluvial events including frequency, duration, and severity were examined and compared. Additionally, a similar analysis was performed using gridded tree‐ring reconstructions of the Palmer Drought Severity Index (PDSI) for the period 1475 through 2005 to place the drought and pluvial characteristics determined using water‐year runoff for 1900 through 2014 in the context of multi‐century climate variability. The temporal and spatial variability of droughts and pluvials determined using runoff for the 1900 through 2014 period indicated that most drought events in the CONUS occurred before about 1970, whereas most pluvial periods occurred after about 1970. This change in the frequencies of drought and pluvial events around 1970 was largely related to an increase in fall (October through December) precipitation across much of the central United States. Also, the duration and severity of droughts and pluvials identified using runoff for the 1900 through 2014 period generally were not significantly different from the drought and pluvial characteristics identified using the PDSI for the 1475 through 2005 period.
Changing environments of temperature, precipitation and moisture availability can affect vegetation in ecosystems, by affecting regeneration from the seed bank. Our objective was to explore the responses of soil seed bank germination to climate-related environments along geographic gradients. We collected seed banks in baldcypress (Taxodium distichum) swamps along the Mississippi River and the Gulf of Mexico Coast in the United States, which have distinct temperature and/or precipitation gradients, and germinated them in a greenhouse. The frequency, richness and seed density of species germinated from the seed bank were compared between various geographic locations, experimental water regimes (saturated, flooded) and wetland types (tidal, non-tidal and inland swamps). We also analyzed the relationship of seed density to the environment by using a Non-metric Multi-dimensional Scaling (NMDS) model. Sixty-one species germinated from the seed bank, differing in pattern by geographic location, experimental water regime and wetland type. The foundation species (i.e., T. distichum and Cephalanthus occidentalis) germinated with a niche affinity for the northern part of the latitudinal gradient (Tennessee and Illinois) and these species may shift northward with climate change. Some species had higher seed density in the locations that were subject to more persistent drought conditions (e.g., Texas) including Cyperus rotundus and Gratiola virginiana, indicating that these species may be better adapted to sites with high temperature and low precipitation. In contrast, certain species including Saururus cernuus and Ludwigia palustris were present throughout the range of these gradients, and so may be more resilient to any future climate shifts. We found that the regeneration potential of baldcypress swamps might be altered by changes in local and climate environment because of nuances of responses of seed banks to climates along latitudinal and longitudinal gradients. Our study can help predict vegetation regeneration potential to climate change environments depending on the ability of these species to disperse and maintain seed banks.
Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2249","usgsCitation":"Sollmann, R., Eaton, M.J., Link, W., Mulundo, P., Ayebare, S., Prinsloo, S., Plumptre, A.J., and Johnson, D., 2021, A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity: Ecological Applications, v. 31, no. 2, e2249, https://doi.org/10.1002/eap.2249.","productDescription":"e2249","ipdsId":"IP-090810","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":454310,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2249","text":"External Repository"},{"id":380583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Sollmann, Rahel 0000-0002-1607-2039","orcid":"https://orcid.org/0000-0002-1607-2039","contributorId":244998,"corporation":false,"usgs":false,"family":"Sollmann","given":"Rahel","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":805121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":805123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulundo, Paul","contributorId":245000,"corporation":false,"usgs":false,"family":"Mulundo","given":"Paul","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayebare, Samuel","contributorId":245001,"corporation":false,"usgs":false,"family":"Ayebare","given":"Samuel","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prinsloo, Sarah","contributorId":245002,"corporation":false,"usgs":false,"family":"Prinsloo","given":"Sarah","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plumptre, Andrew J.","contributorId":213154,"corporation":false,"usgs":false,"family":"Plumptre","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, D.S.","contributorId":245003,"corporation":false,"usgs":false,"family":"Johnson","given":"D.S.","affiliations":[{"id":17856,"text":"National Marine Fisheries Service, NOAA","active":true,"usgs":false}],"preferred":false,"id":805128,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217747,"text":"70217747 - 2021 - Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","interactions":[],"lastModifiedDate":"2021-02-01T14:29:48.935866","indexId":"70217747","displayToPublicDate":"2020-11-02T06:35:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","docAbstract":"Growing worldwide concern over uranium contamination of groundwater resources has placed an emphasis on understanding uranium transport dynamics and potential toxicity in groundwater-surface water systems. In this study, we utilized novel in-situ sampling methods to establish the location and magnitude of contaminated groundwater entry into a receiving surface water environment, and to investigate the speciation and potential bioavailability of uranium in groundwater and surface water. Streambed temperature mapping successfully identified the location of groundwater entry to the Little Wind River, downgradient from the former Riverton uranium mill site, Wyoming, USA. Diffusive equilibrium in thin-film (DET) samplers further constrained the groundwater plume and established sediment pore water solute concentrations and patterns. In this system, evidence is presented for attenuation of uranium-rich groundwater in the shallow sediments where surface water and groundwater interaction occurs. Surface water grab and DET sampling successfully detected an increase in river uranium concentrations where the groundwater plume enters the Little Wind River; however, concentrations remained below environmental guideline levels. Uranium speciation was investigated using diffusive gradients in thin-film (DGT) samplers and geochemical speciation modelling. Together, these investigations indicate uranium may have limited bioavailability to organisms in the Little Wind River and, possibly, in other similar sites in the western U.S.A. This could be due to ion competition effects or the presence of non- or partially labile uranium complexes. Development of methods to establish the location of contaminated (uranium) groundwater entry to surface water environments, and the potential effects on ecosystems, is crucial to develop both site-specific and general conceptual models of uranium behavior and potential toxicity in affected ground and surface water environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143314","usgsCitation":"Byrne, P.A., Fuller, C.C., Naftz, D.L., Runkel, R.L., Lehto, N.J., and Dam, W., 2021, Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations: Science of the Total Environment, v. 761, 143314, 11 p., https://doi.org/10.1016/j.scitotenv.2020.143314.","productDescription":"143314, 11 p.","ipdsId":"IP-121496","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":454315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1776309","text":"Publisher Index Page"},{"id":382831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","city":"Riverton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39832305908203,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.00816202648563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"761","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Patrick A.","contributorId":247578,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":809453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lehto, Niklas J","contributorId":248588,"corporation":false,"usgs":false,"family":"Lehto","given":"Niklas","email":"","middleInitial":"J","affiliations":[{"id":49952,"text":"Lincoln University","active":true,"usgs":false}],"preferred":false,"id":809457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dam, William L","contributorId":248589,"corporation":false,"usgs":false,"family":"Dam","given":"William L","affiliations":[{"id":49955,"text":"Conserve-Prosper LLC","active":true,"usgs":false}],"preferred":false,"id":809458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}