Collection of juvenile salmonids at Round Butte Dam is a critical part of the effort to enhance populations of anadromous fish species in the upper Deschutes River because fish that are not collected at the dam may either incur increased mortality during dam passage or remain landlocked and lost to the anadromous fish population. Adaptive resolution imaging sonar systems were used to assess the behavior, abundance, and timing of fish at the entrance to the Selective Water Withdrawal (SWW) intake and fish collection structure located in the forebay of Round Butte Dam during the spring of 2020. The purpose of the SWW is to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. The objective of this study was to assess the abundance and behaviors of smolt-size fish (95–300 millimeters) observed near the SWW and to determine if the presence of bull trout (Salvelinus confluentus; >350 millimeters), the predominant predator of juvenile salmonids, influenced the behavior of downriver migrants.
Two imaging sonar units were deployed during the spring of 2020 smolt out-migration period. One unit monitored fish movements near the entrances and one unit monitored in one of the collection flumes of the SWW. The imaging sonar technology was informative for assessing abundance and spatial and temporal behaviors of smolt and bull trout-size fish. Smolt and bull trout-size fish were regularly observed near the entrance to and in the collection flume. Increased abundances were observed during the night, with corresponding increased discharge through the SWW, compared to during the day when discharge was reduced. Behavioral differences also were observed at different discharge rates, with smolt-size fish exhibiting more directed movement toward the collector during periods of increased discharge. Additionally, the presence of bull trout-size fish may have affected the behavior of smolt-size fish because a greater percentage of smolt-size fish were observed traveling away from the SWW when bull trout-size fish were present than when bull trout-size fish were absent. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that smolt-size fish are more abundant near the entrance and in the flume of the SWW during periods of increased discharge, and bull trout-size fish were present at the SWW and may have affected smolt collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221038","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., Hatton, T.W., and Adams, N.S., 2022, Monitoring fish abundance and behavior, using multi-beam acoustic imaging sonar, at a Selective Water Withdrawal structure in Lake Billy Chinook, Deschutes River, Oregon, 2020: U.S. Geological Survey Open-File Report 2022–1038, 31 p., https://doi.org/10.3133/ofr20221038.","productDescription":"viii, 31 p.","onlineOnly":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":400087,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1038/coverthb.jpg"},{"id":400088,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1038/ofr20221038.pdf","text":"Report","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1038"},{"id":400089,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1038/images"},{"id":400090,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1038/ofr20221038.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook, Round Butte Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.56990051269533,\n 44.43623132529392\n ],\n [\n -121.07414245605469,\n 44.43623132529392\n ],\n [\n -121.07414245605469,\n 44.73454012555642\n ],\n [\n -121.56990051269533,\n 44.73454012555642\n ],\n [\n -121.56990051269533,\n 44.43623132529392\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends of bat populations.
• We analyzed data from a total of 12 bat species (Table 1), 11 of which have tested positive for Pseudogymnoascus destructans (Pd), a fungal pathogen that causes white-nose syndrome (WNS)—a disease that has led to significant rates of mortality for subterranean hibernating bat species in North America. A twelfth species was also selected because of high rates of mortality at wind energy facilities. Additional species were considered but not selected due to data limitations.
• We estimated occupancy probabilities for 2010 through 2019 for three species (Myotis lucifugus, MYLU; Myotis septentrionalis, MYSE; and Perimyotis subflavus, PESU). For an additional nine species, we estimated occupancy probabilities for 2016 through 2019 (Myotis evotis, MYEV; Myotis grisescens, MYGR; Myotis leibii, MYLE; Myotis thysanodes, MYTH; Myotis volans, MYVO; Myotis yumanensis, MYYU; Eptesicus fuscus, EPFU; Lasionycteris noctivagans, LANO; and Lasiurus cinereus, LACI). • For each species, we provide range-wide occupancy probability predictions (e.g., predicted summer occupancy distribution maps) each year at a spatial resolution of 100 km2 and provide regional estimates of mean occupancy probability aggregated at larger spatial scales (state/province/territory, range-wide).
• For each species, we also provide trends over time (average annual change rate and total change rate) in mean occupancy probabilities at multiple spatial scales (state/province/territory, range-wide) and when possible, over multiple timescales (short, medium, long).
• Results suggest that over the short-term (2016-2019), two (Myotis lucifugus and Perimyotis subflavus) of 12 species have experienced declines in range-wide average occupancy probability with at least 95% certainty. Seven species showed either minor increases or decreases in range-wide average occupancy probability but with less than 95% certainty in both trend indicators. Results over the longer term (eight years and 10 years of sampling) suggest that three hibernating species known to be highly affected by white-nose syndrome (Myotis lucifugus, Myotis septentrionalis, and Perimyotis subflavus) have experienced marked declines in range-wide average occupancy probabilities, with severity varying by species and region. Finally, the results for three species (Eptesicus fuscus, Lasiurus cinereus, Lasionycteris noctivagans) were inconclusive due to 1) borderline convergence issues in the model fitting procedure which suggests potentially unreliable estimates, 2) failure to reliably distinguish between false positives and true positive detections for ambiguous detections, and 3) largely uninformative covariates for occupancy and detection.
• For Myotis lucifugus, Myotis septentrionalis, and Perimyotis subflavus we found meaningful associations in space and time between declining winter populations (likely a result of WNS) and summer occupancy distributions.
• The representativeness of sampling data for each species’ status and trend estimates (e.g., state/province/territory) were also evaluated based on the percent of grid cells sampled each year with a goal of understanding the reliability of regional estimates and improving future monitoring efforts.
• This work represents the most comprehensive effort to date to model North American bat distributions across their continental ranges. Despite current limitations highlighted in the discussion, the analytical methods and resulting status and trends estimates provide the best available science on summer bat populations across North America and will continue to improve over time as monitoring data sets and analytical methods improve.
• Moving forward, our occupancy analyses will continue to improve with submission of more 1) data from currently underrepresented areas (i.e., improved geographic representation), 2) manually-vetted acoustic recordings, 3) capture records, and 4) roost location and count data (summer and winter).
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.7944/P927I36K","usgsCitation":"Udell, B.J., Straw, B., Cheng, T.L., Enns, K., Frick, W., Gotthold, B., Irvine, K., Lausen, C., Loeb, S., Reichard, J., Rodhouse, T., Smith, D., Stratton, C., Thogmartin, W.E., and Reichert, B., 2022, Status and trends of North American bats: Summer occupancy analysis 2010-2019, xvi, 231 p., https://doi.org/10.7944/P927I36K.","productDescription":"xvi, 231 p.","ipdsId":"IP-136669","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":435864,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92JGACB","text":"USGS data release","linkHelpText":"Status and Trends of North American Bats Summer Occupancy Analysis 2010-2019 Data 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Center","active":true,"usgs":true}],"preferred":true,"id":860277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frick, Winifred F.","contributorId":139722,"corporation":false,"usgs":false,"family":"Frick","given":"Winifred F.","affiliations":[{"id":12892,"text":"Dept of Ecology & Evolutionary Biology, Univ of California","active":true,"usgs":false}],"preferred":false,"id":860278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gotthold, Benjamin 0000-0003-4234-5042","orcid":"https://orcid.org/0000-0003-4234-5042","contributorId":248484,"corporation":false,"usgs":true,"family":"Gotthold","given":"Benjamin","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":860280,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lausen, Cori","contributorId":204261,"corporation":false,"usgs":false,"family":"Lausen","given":"Cori","affiliations":[{"id":36893,"text":"Wildlife Conservation Society Canada","active":true,"usgs":false}],"preferred":false,"id":860281,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loeb, Susan","contributorId":204263,"corporation":false,"usgs":false,"family":"Loeb","given":"Susan","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":860282,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reichard, Jonathan D.","contributorId":138946,"corporation":false,"usgs":false,"family":"Reichard","given":"Jonathan D.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":860283,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rodhouse, Thomas","contributorId":244880,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":860284,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Dane 0000-0002-8010-0313","orcid":"https://orcid.org/0000-0002-8010-0313","contributorId":299580,"corporation":false,"usgs":true,"family":"Smith","given":"Dane","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860285,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":860286,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":860287,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860288,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70234131,"text":"70234131 - 2022 - Hematology and biochemistry reference intervals for American alligator (Alligator mississippiensis) in South Florida, USA","interactions":[],"lastModifiedDate":"2025-05-13T18:38:06.361394","indexId":"70234131","displayToPublicDate":"2022-04-21T06:49:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Hematology and biochemistry reference intervals for American alligator (Alligator mississippiensis) in South Florida, USA","docAbstract":"We calculated reference intervals for 48 blood parameters from 120 wild American alligators (Alligator mississippiensis) in South Florida, US. Although previously reported by others, this study includes additional parameters not yet reported in wild populations. Most previously reported blood parameter values were similar to ours and fell within our reference intervals.
Natural resource agencies need effective strategies to control the spread of aquatic invasive species (AIS) such as invasive fish, which can expand their range using rivers as hydrological pathways to access new areas. Lock and dam structures within major rivers are prospective locations to deploy techniques, such as carbon dioxide (CO2) infusion into lock water, that could impede upstream AIS migration without disrupting vessel passage and lock operation. The current pesticide label for CO2 in the United States allows injections of 100–150 mg/LCO2 as a behavioral deterrent treatment for invasive carps. This research describes the first operationalizing and testing of a CO2 injection and manifold distribution system at a 1,548,000-L navigation lock chamber on the Fox River near Kaukauna, Wisconsin, USA. Two chemical distribution manifolds located on the floor and wall of the chamber were independently tested to quantify mixing time, mixing homogeneity, injection efficiency, and operational power requirements under a range of operating parameters. Both manifold configurations were able to meet most performance benchmarks established during previous fish behavior studies. Certain limitations were exhibited and quantified for both manifold configurations in terms of mixing homogeneity and operational power. This research details the design and performance of CO2-to-water infusion systems that could be used to deter the spread of AIS at navigation pinch-points. These results may inform future CO2 system designs and operating conditions to support natural resource management plans to limit the spread of AIS.
Historically, the Monongahela, Tygart, and Cheat River watersheds in West Virginia were impaired by acidification from acid mine drainage and Walleye Sander vitreus were extirpated from these watersheds by the 1940s. Walleye were reestablished after water quality improvements following passage of environmental legislation and subsequent reintroduction efforts. We compared population characteristics, with emphasis on growth, of Walleye and used modeling to predict the potential effects of harvest regulations in the Monongahela River and two main-stem reservoirs in the Cheat River and Tygart River watersheds. Statistical comparisons of von Bertalanffy growth curves and relative growth indices indicated that Walleye growth significantly differed across all water bodies. Relative growth index results suggested that Walleye growth was above average in Cheat Lake, average in the Monongahela River, and below average in Tygart Lake relative to other North American populations. Growth was negatively correlated with Walleye relative abundance and positively correlated with estimates of productivity (total phosphorus, chlorophyll a). Walleye diets significantly differed across all water bodies, with diets dominated by Yellow Perch Perca flavescens and Gizzard Shad Dorosoma cepedianum in Cheat Lake, where growth was fastest. Population modeling suggested that effects of exploitation on yield, spawning potential, and size structure were similar under regulations of no length limit and a minimum length limit (381 mm). Models suggested that removing length limits in Tygart Lake could increase angler harvest opportunities and pose minimal threat to the fishery. Models suggested that a protected slot limit could provide increased protection to the spawning potential of Cheat Lake and the Monongahela River populations. Additionally, models predicted that a protected slot limit could increase the number of large (>630-mm) Walleye in these waters. Our findings demonstrate the different characteristics that Walleye populations can develop after reestablishment based on abiotic and biotic conditions and the need for watershed-specific management.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10723","usgsCitation":"Smith, D., Hilling, C., Welsh, S.A., and Wellman Jr., D., 2022, Differences in population characteristics and modeled response to harvest regulations in reestablished Appalachian Walleye populations: North American Journal of Fisheries Management, v. 42, no. 3, p. 612-629, https://doi.org/10.1002/nafm.10723.","productDescription":"18 p.","startPage":"612","endPage":"629","ipdsId":"IP-127935","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake, Monongahela River, Tygart Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.43609032800657,\n 39.70971363776053\n ],\n [\n -80.43609032800657,\n 39.288105835150134\n ],\n [\n -79.48527811621443,\n 39.288105835150134\n ],\n [\n -79.48527811621443,\n 39.70971363776053\n ],\n [\n -80.43609032800657,\n 39.70971363776053\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Dustin M.","contributorId":349597,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin M.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":924503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilling, Corbin D.","contributorId":349598,"corporation":false,"usgs":false,"family":"Hilling","given":"Corbin D.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":924504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wellman Jr., David I.","contributorId":349599,"corporation":false,"usgs":false,"family":"Wellman Jr.","given":"David I.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":924505,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228524,"text":"70228524 - 2022 - Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2022-07-07T16:38:12.50761","indexId":"70228524","displayToPublicDate":"2022-01-07T06:37:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","docAbstract":"Aquifer storage and recovery (ASR) expands the portfolio of public water supply and improves resiliency to drought and future water demand. This study investigated the feasibility of ASR in the Bedell Flat Hydrographic Area using land-based methods including in-channel managed aquifer recharge (MAR) and rapid infiltration basins (RIB). Bedell Flat, one of two flow-through groundwater basins near Reno, Nevada, was a likely candidate for ASR because of its deep basin fill, proximity to supplemental water sources and infrastructure, and lack of development. In-channel MAR feasibility was determined from seepage losses along the Bird Springs ephemeral channel measured using Parshall flumes and heat-as-a-tracer inverse modeling. The feasibility of RIB was evaluated by characterizing vadose zone boreholes installed with roto-sonic drilling to water table. Field characterization of sediment and lithologic descriptions was accomplished at 1-foot (ft) increments. Bulk sediment samples were collected every 5 ft and cores from a split spoon were sampled at 10, 20, 30, 40, 60 and 100 ft below land surface (bls). Collected samples were analyzed for texture, moisture content, and geochemistry.
Infiltration rates in Bird Springs channel increased downgradient with the hydraulic conductivity of the upper reaches ranging from 0.002 to 0.14 meter per hour (m/h) and the lower reaches from 0.5 to 1.5 m/h. Differences in discharge measurements indicate that seepage losses also increase down channel. When normalized to 1 ft of channel stage, modeled seepage loss rates ranged from 0.02 to 5.34 cubic feet per second (ft3/s) per mile (mi). Perched zones of soil moisture residing on top of dry fine-textured, clay-rich layers were prevalent in the Bird Springs drainage, indicating complicated flow paths for any supplement recharge water. Characterization of boreholes in Bird Springs drainage indicates low permeability clay layers 1–10 ft thick interbedded within extensive, grussy sands of high permeability. The presence of low permeability clay layers (1–10 ft thick) prompted a shift in analysis to the adjacent Sand Hills drainage where four additional boreholes indicated fewer perched water zones and at greater depths. Nitrates in the sediment pore-water (a condition that would discourage ASR) were integrated with depth to the aquifer 180 ft bls. Wells BF-MW-04 (Bird Springs) and BF-MW-07 (Sand Hills) contained 4,270 and 2,436 kilograms per hectare of nitrogen, respectively, which could potentially load excessive nitrogen to a receiving aquifer.
An economically viable ASR project requires a minimum input of 2 million gallons per day (approximately 3 ft3/s), which either channel appears to have the sufficient capacity to infiltrate such a volume before reaching the valley bottom of Bedell Flat. However, the trajectory of the infiltrated water is complicated by the lithology and lateral transmissivity of the underlying sediments. There is also concern that this volume of infiltrated water may cause undesirable groundwater levels at the outflow in less than 5 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215137","collaboration":"Prepared in cooperation with the Truckee Meadows Water Authority","programNote":"Water Availability and Use Science Program","usgsCitation":"Caldwell, T., Naranjo, R., Smith, D., and Kropf, C., 2021, Surface infiltration and unsaturated zone characterization in support of managed aquifer recharge in Bedell Flat, Washoe County, Nevada: U.S. Geological Survey Scientific Investigations Report 2021–5137, 52 p., https://doi.org/10.3133/sir20215137.","productDescription":"Report: ix, 52 p.; 2 Data Releases","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-108566","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":502283,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112066.htm","linkFileType":{"id":5,"text":"html"}},{"id":393672,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OAF8L8","linkHelpText":"Supplemental data—Surface infiltration and unsaturated zone characterization in support of managed aquifer recharge, Bedell Flat, Washoe County, Nevada"},{"id":393670,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5137/sir20215137.xml"},{"id":393667,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5137/covrthb.png"},{"id":393671,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U9Q5PC","linkHelpText":"Documentation of VS2DH seepage models—Surface infiltration and unsaturated zone characterization in support of managed aquifer recharge, Washoe County, Nevada"},{"id":393669,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5137/images"},{"id":393668,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5137/sir20215137.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Nevada","county":"Washoe County","otherGeospatial":"Bedell Flat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.96383666992189,\n 39.79798577319723\n ],\n [\n -119.65621948242188,\n 39.79798577319723\n ],\n [\n -119.65621948242188,\n 39.95185892663005\n ],\n [\n -119.96383666992189,\n 39.95185892663005\n ],\n [\n -119.96383666992189,\n 39.79798577319723\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
Leavenworth Creek, a tributary of South Clear Creek and Clear Creek near Georgetown, Colorado, contains copper, lead, and zinc at concentrations close to or in excess of aquatic-life standards. In the summer of 2012, the U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety, conducted monitoring to (1) quantify the effects of diel cycling and perform synoptic sampling in a way to minimize those effects, (2) separate “point” or distinct single tributaries or sources of load from diffuse load sources along the study reach to aid remediation planning, and (3) quantify metal loading from transmountain diversion of water from Peru Creek through the Vidler Tunnel into Leavenworth Creek. The study included monitoring for diel cycles in June 2012 and diel and synoptic sampling in August 2012 along an approximately 2-kilometer stream reach. Synoptic samples were collected at 26 stream and 35 inflow, tributary, mine waste seep, and mine tunnel sites from August 28 to 30, 2012.
In June 2012, temperature, dissolved oxygen, and pH showed strong diel signals at two sites in Leavenworth Creek, with temperature and pH having minimum values near dawn and maximum values during the afternoon and dissolved oxygen having maximum values in the early morning and minimum values in late afternoon. Concentrations of zinc, cadmium, cobalt, manganese, and yttrium showed strong diel fluctuations at both sites with minimum concentrations during daytime and maximum concentrations during nighttime. Because of these diel cycles, all stream sites were sampled during synoptic sampling at 1200 hours on August 30, 2012. During synoptic sampling from August 28 to 30, 2012, zinc showed maximum concentrations at nighttime and minimum concentrations at midday and diel variation ranged from 26 to 33 percent.
Inflows from the Wilcox Tunnel and Waldorf seep area were the greatest source of zinc load to the stream (about 45 percent), and a left-bank inflow in the dispersed tailings area was the greatest source of lead (about 45 percent) and manganese (about 25 percent) loads to the stream, and a secondary source for zinc (about 40 percent). Copper load was almost equally divided (about 35 percent) between these two sources. Diffuse loading, likely from left-bank sources, was evident for copper, lead, manganese, and zinc in the stream reach from approximately 800 to 1,200 meters, and for copper, lead, and, to a lesser extent, manganese in the reach containing left-bank dispersed tailings (from approximately 1,300 to 1,800 meters). The load values reported herein are minimum estimates because the stream synoptic samples were collected at 1200 hours when positively charged elements, including copper, lead, manganese, and zinc, have minimum concentrations. Diel patterns measured for zinc during the synoptic sampling indicate maximum daily zinc loads were as much as 33 percent greater than those measured at 1200 hours on August 30, 2012.
Transmountain diversion of water through Vidler Tunnel negatively affects water quality in Leavenworth Creek as indicated by much greater metal loads and concentrations and a visually evident mixing zone where Vidler Tunnel water joins Leavenworth Creek when diversion is active compared to when it is not.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211078","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Forest Service and the Colorado Division of Reclamation, Mining and Safety","usgsCitation":"Walton-Day, K., Runkel, R.L., Smith, C.D., and Kimball, B.A., 2021, Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012: U.S. Geological Survey Open-File Report 2021–1078, 37 p., https://doi.org/10.3133/ofr20211078.","productDescription":"Report: viii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-102543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":392247,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGC2V4","text":"USGS data release","linkHelpText":"Stream discharge, sodium, bromide, and specific conductance data for stream and hyporheic zone samples affected by injection of sodium bromide tracer, Leavenworth Creek, Clear Creek County, Colorado, August 2012"},{"id":392246,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1078/ofr20211078.pdf","text":"Report","size":"5.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1078"},{"id":392245,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1078/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Clear Creek County","otherGeospatial":"Leavenworth Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86219787597655,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.595371402863655\n ],\n [\n -105.69602966308594,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.71405356154611\n ],\n [\n -105.86219787597655,\n 39.595371402863655\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Identifying mechanisms that underpin animal migration patterns and examining variability in space use within populations is crucial for understanding population dynamics and management implications. In this study, we quantified the migration rates, seasonal changes in migratory connectivity, and residency across population demographics (age and sex) to understand the proximate cues of migration timing in American horseshoe crabs (Limulus polyphemus). Juvenile (n = 25) and adult (n = 70) horseshoe crabs were tracked with acoustic telemetry techniques for a 3-yr period in Moriches Bay, NY. Connectivity metrics and residency probability were quantified through spatial network analysis and empirically derived Markov Chain models (EDMC), respectively. The migratory probability of adult horseshoe crabs between Moriches Bay and the Atlantic Ocean was estimated to be 41.0% (95% CI: 34.0–59.8); in contrast, only 8% (95% CI: 1.2–31.6) of juveniles migrated into the ocean. Migration timing was influenced by the interaction of photoperiod and temperature, revealing seasonal differences in migration timing and a 50% narrower range of photoperiod and temperature over which fall migrations occurred compared to spring. Sex-specific differences in space use and connectivity within each season were largely absent; however, centralized habitats were important for maintaining connectivity across all seasons. EDMC results revealed that when standardized to the number of horseshoe crab detections on each receiver, the centrally located habitats in Moriches Bay and Inlet accounted for >50% of the total relative residency probability within most seasons, indicating these areas may be preferred by adult horseshoe crabs. Ontogenetic differences in maximum spatial extent, space use, and connectivity were observed in the bay, as juveniles exhibited lower linkages between locations (n = 4) relative to adults (n = 13) during the same temporal period. Our work highlights the application of novel quantitative approaches for addressing the movement dynamics of horseshoe crabs that can be readily applied to other taxa in the context of wildlife conservation.
Maintaining healthy, productive ecosystems in the face of pervasive and accelerating human impacts including climate change requires globally coordinated and sustained observations of marine biodiversity. Global coordination is predicated on an understanding of the scope and capacity of existing monitoring programs, and the extent to which they use standardized, interoperable practices for data management. Global coordination also requires identification of gaps in spatial and ecosystem coverage, and how these gaps correspond to management priorities and information needs. We undertook such an assessment by conducting an audit and gap analysis from global databases and structured surveys of experts. Of 371 survey respondents, 203 active, long-term (>5 years) observing programs systematically sampled marine life. These programs spanned about 7% of the ocean surface area, mostly concentrated in coastal regions of the United States, Canada, Europe, and Australia. Seagrasses, mangroves, hard corals, and macroalgae were sampled in 6% of the entire global coastal zone. Two-thirds of all observing programs offered accessible data, but methods and conditions for access were highly variable. Our assessment indicates that the global observing system is largely uncoordinated which results in a failure to deliver critical information required for informed decision-making such as, status and trends, for the conservation and sustainability of marine ecosystems and provision of ecosystem services. Based on our study, we suggest four key steps that can increase the sustainability, connectivity and spatial coverage of biological Essential Ocean Variables in the global ocean: (1) sustaining existing observing programs and encouraging coordination among these; (2) continuing to strive for data strategies that follow FAIR principles (findable, accessible, interoperable, and reusable); (3) utilizing existing ocean observing platforms and enhancing support to expand observing along coasts of developing countries, in deep ocean basins, and near the poles; and (4) targeting capacity building efforts. Following these suggestions could help create a coordinated marine biodiversity observing system enabling ecological forecasting and better planning for a sustainable use of ocean resources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2021.737416","usgsCitation":"Satterthwaite, E.V., Bax, N.J., Miloslavich, P., Ratnarajah, L., Canonico, G., Dunn, D., Simmons, S.E., Carini, R., Evans, K., Allain, V., Appeltans, W., Batten, S., Benedetti-Cecchi, L., Bernard, A.T., Bristol, R., Benson, A., Buttigieg, P.L., Gerhardinger, L.C., Chiba, S., Davies, T.E., Duffy, J., Giron-Nava, A., Hsu, A.J., Kraberg, A.C., Kudela, R.M., Lear, D., Montes, E., Muller-Karger, F., O’Brien, T.D., Obura, D., Provoost, P., Pruckner, S., Rebelo, L., Selig, E.R., Kjesbu, O.S., Starger, C., Stuart-Smith, R.D., Vierros, M., Waller, J.S., Weatherdon, L.V., Wellman, T., and Zivian, A., 2021, Establishing the foundation for the global observing system for marine life: Frontiers in Marine Science, v. 8, 737416, 19 p., https://doi.org/10.3389/fmars.2021.737416.","productDescription":"737416, 19 p.","ipdsId":"IP-127529","costCenters":[{"id":191,"text":"Colorado Water Science 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J.","contributorId":270547,"corporation":false,"usgs":false,"family":"Bax","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":829550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miloslavich, Patricia","contributorId":206627,"corporation":false,"usgs":false,"family":"Miloslavich","given":"Patricia","email":"","affiliations":[{"id":37357,"text":"University of Tasmania, Hobart, Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":829551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratnarajah, Lavenia","contributorId":270548,"corporation":false,"usgs":false,"family":"Ratnarajah","given":"Lavenia","email":"","affiliations":[],"preferred":false,"id":829552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Canonico, Gabrielle","contributorId":217563,"corporation":false,"usgs":false,"family":"Canonico","given":"Gabrielle","email":"","affiliations":[{"id":39659,"text":"National Oceanographic and Atmospheric Administration, US Integrated Ocean Observing System, Silver Spring, MD, USA","active":true,"usgs":false}],"preferred":false,"id":829553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunn, Daniel","contributorId":206672,"corporation":false,"usgs":false,"family":"Dunn","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":829554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simmons, Samantha E.","contributorId":156320,"corporation":false,"usgs":false,"family":"Simmons","given":"Samantha","email":"","middleInitial":"E.","affiliations":[{"id":20313,"text":"Marine Mammal Commission","active":true,"usgs":false}],"preferred":false,"id":829555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carini, Roxanne J.","contributorId":270549,"corporation":false,"usgs":false,"family":"Carini","given":"Roxanne J.","affiliations":[],"preferred":false,"id":829556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Evans, Karen","contributorId":270550,"corporation":false,"usgs":false,"family":"Evans","given":"Karen","email":"","affiliations":[],"preferred":false,"id":829557,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Allain, Valerie","contributorId":206680,"corporation":false,"usgs":false,"family":"Allain","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":829558,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Appeltans, Ward","contributorId":206673,"corporation":false,"usgs":false,"family":"Appeltans","given":"Ward","email":"","affiliations":[],"preferred":false,"id":829559,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Batten, Sonia","contributorId":258846,"corporation":false,"usgs":false,"family":"Batten","given":"Sonia","affiliations":[{"id":52316,"text":"Marine Biological 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F.","contributorId":270552,"corporation":false,"usgs":false,"family":"Bernard","given":"Anthony","email":"","middleInitial":"T. F.","affiliations":[],"preferred":false,"id":829562,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":173672,"corporation":false,"usgs":true,"family":"Bristol","given":"R. 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Emmett","contributorId":270555,"corporation":false,"usgs":false,"family":"Duffy","given":"J. Emmett","affiliations":[],"preferred":false,"id":829569,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Giron-Nava, Alfredo","contributorId":270557,"corporation":false,"usgs":false,"family":"Giron-Nava","given":"Alfredo","email":"","affiliations":[],"preferred":false,"id":829570,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Hsu, Astrid J.","contributorId":270559,"corporation":false,"usgs":false,"family":"Hsu","given":"Astrid","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":829571,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Kraberg, Alexandra C.","contributorId":270560,"corporation":false,"usgs":false,"family":"Kraberg","given":"Alexandra","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":829572,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Kudela, Raphael M.","contributorId":205181,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":829573,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Lear, Dan","contributorId":270562,"corporation":false,"usgs":false,"family":"Lear","given":"Dan","email":"","affiliations":[],"preferred":false,"id":829574,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Montes, Enrique","contributorId":217565,"corporation":false,"usgs":false,"family":"Montes","given":"Enrique","email":"","affiliations":[{"id":39661,"text":"University of South Florida, St Petersburg, FL USA","active":true,"usgs":false}],"preferred":false,"id":829575,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Muller-Karger, Frank","contributorId":267728,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":829576,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"O’Brien, Todd D.","contributorId":270564,"corporation":false,"usgs":false,"family":"O’Brien","given":"Todd","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":829577,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Obura, David","contributorId":270566,"corporation":false,"usgs":false,"family":"Obura","given":"David","affiliations":[],"preferred":false,"id":829578,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Provoost, Pieter","contributorId":206674,"corporation":false,"usgs":false,"family":"Provoost","given":"Pieter","email":"","affiliations":[],"preferred":false,"id":829579,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Pruckner, Sara","contributorId":270567,"corporation":false,"usgs":false,"family":"Pruckner","given":"Sara","email":"","affiliations":[],"preferred":false,"id":829580,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Rebelo, Lisa-Maria","contributorId":192423,"corporation":false,"usgs":false,"family":"Rebelo","given":"Lisa-Maria","email":"","affiliations":[],"preferred":false,"id":829581,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Selig, Elizabeth R.","contributorId":270569,"corporation":false,"usgs":false,"family":"Selig","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":829582,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Kjesbu, Olav Sigurd","contributorId":270571,"corporation":false,"usgs":false,"family":"Kjesbu","given":"Olav","email":"","middleInitial":"Sigurd","affiliations":[],"preferred":false,"id":829583,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Starger, Craig","contributorId":270572,"corporation":false,"usgs":false,"family":"Starger","given":"Craig","email":"","affiliations":[],"preferred":false,"id":829584,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Stuart-Smith, Rick D.","contributorId":270573,"corporation":false,"usgs":false,"family":"Stuart-Smith","given":"Rick","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":829585,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Vierros, Marjo","contributorId":270575,"corporation":false,"usgs":false,"family":"Vierros","given":"Marjo","email":"","affiliations":[],"preferred":false,"id":829586,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Waller, John S.","contributorId":167055,"corporation":false,"usgs":false,"family":"Waller","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":16272,"text":"National Park Service, Glacier National Park, West Glacier, MT","active":true,"usgs":false}],"preferred":false,"id":829587,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Weatherdon, Lauren V.","contributorId":270577,"corporation":false,"usgs":false,"family":"Weatherdon","given":"Lauren","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":829588,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829589,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Zivian, Anna","contributorId":270580,"corporation":false,"usgs":false,"family":"Zivian","given":"Anna","email":"","affiliations":[],"preferred":false,"id":829590,"contributorType":{"id":1,"text":"Authors"},"rank":42}]}} ,{"id":70223672,"text":"70223672 - 2021 - Monitoring native, resident nonsalmonids for the incidence of gas bubble trauma downstream of Snake and Columbia River Dams, 2021","interactions":[],"lastModifiedDate":"2021-09-01T13:49:48.74866","indexId":"70223672","displayToPublicDate":"2021-08-31T08:44:49","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Monitoring native, resident nonsalmonids for the incidence of gas bubble trauma downstream of Snake and Columbia River Dams, 2021","docAbstract":"In 2020, a new spill program was implemented to aid the downstream passage of juvenile \nsalmonids at mainstem dams on the Snake and Columbia rivers. Under this program, the total \ndissolved gas (TDG) cap was increased to 125% and monitoring of native, resident nonsalmonid \n(NRN) fishes for gas bubble trauma (GBT) became a requirement. The primary objective of this \nwork was to measure the incidence and severity of GBT in NRN fishes resulting from increased \njuvenile fish passage spill and associated levels of TDG during the spring spill period. A \nsecondary objective was to measure the incidence of GBT in incidentally collected juvenile \nsalmonids when NRN sample size targets were met. NRN fishes were collected downstream \nfrom Bonneville, McNary, and Ice Harbor dams and examined for the incidence and severity of \nGBT in 2021. Fish were collected at each location weekly (6 April to 17 June) during the spring \nspill period by backpack electrofishing and beach seining. Washington and Oregon state water \nquality agencies established minimum and target sample sizes for monitoring, and in all weeks \nthe minimum sample size of 50 fish was met and in most weeks the target sample size of 100 \nfish was met. Collected fish were examined for GBT according to the criteria and protocol \nestablished for the regional smolt monitoring program (SMP). Overall, GBT incidence and \nseverity rankings were low and did not exceed the thresholds that would have triggered changes \nto the spill program. Using SMP criteria, weekly GBT incidences ranged from 0 to 1.0% \ndownstream from Bonneville Dam, 0 to 6.2% downstream from McNary Dam, and 0 to 1.9% \ndownstream from Ice Harbor Dam. Except for one three-spined stickleback (Gasterosteus \naculeatus) collected downstream of Bonneville Dam, the only NRN species that showed signs of \nGBT was sculpin spp. GBT was observed in sculpin in body locations other than the unpaired \nfins and eyes (i.e., SMP criteria). If GBT incidence in all areas on the fish (i.e., paired fins, \nunpaired fins, eyes, body) are combined, then weekly GBT incidence rates increase and range \nfrom 0 to 4.3% downstream from Bonneville Dam, 0 to 15.4% downstream from McNary Dam, \nand 0 to 4.7% downstream from Ice Harbor Dam. This illustrates the effect of using different \ncriteria to determine the incidence of GBT in NRN fishes. It also shows how the proportion of a \nspecies in a sample that is more prone to show GBT can influence GBT incidence rate. On a \nnumber of occasions, incidental catch of subyearling fall Chinook salmon were examined for \nGBT downstream of Bonneville Dam but none showed any signs. The DG was generally below \n120% and never reached the 125% gas cap during the spring spill season, which may be why \nGBT incidence rates were so low as past research has shown that GBT signs in NRN fishes are \nrelatively low below this TDG level.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K.F., Smith, C.D., Eller, N.J., and Warren, J.J., 2021, Monitoring native, resident nonsalmonids for the incidence of gas bubble trauma downstream of Snake and Columbia River Dams, 2021, vii, 37 p.","productDescription":"vii, 37 p.","ipdsId":"IP-132589","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":388727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":388710,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/Viewer/P186658"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.28906250000001,\n 45.43700828867391\n ],\n [\n -118.16894531249999,\n 45.43700828867391\n ],\n [\n -118.16894531249999,\n 46.76996843356982\n ],\n [\n -121.28906250000001,\n 46.76996843356982\n ],\n [\n -121.28906250000001,\n 45.43700828867391\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":220176,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eller, Nicole Joy 0000-0001-8760-8884","orcid":"https://orcid.org/0000-0001-8760-8884","contributorId":265130,"corporation":false,"usgs":true,"family":"Eller","given":"Nicole","email":"","middleInitial":"Joy","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warren, Joe J. 0000-0001-5632-730X jwarren@usgs.gov","orcid":"https://orcid.org/0000-0001-5632-730X","contributorId":265131,"corporation":false,"usgs":true,"family":"Warren","given":"Joe","email":"jwarren@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822282,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224253,"text":"70224253 - 2021 - Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations","interactions":[],"lastModifiedDate":"2021-09-16T12:32:41.667684","indexId":"70224253","displayToPublicDate":"2021-08-18T07:31:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations","docAbstract":"Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent. We take advantage of the characteristics of inverse sampling to adaptively inform practitioners when it is efficient to move on to sample new areas. We introduce Adaptive Two-stage Inverse Sampling (ATIS), which is designed to leave a selected area after observation of an a priori number of only non-rare units and to continue sampling in the area when rare units are observed. ATIS is efficient in many cases and yields more rare units than conventional sampling for a rare and clustered population. We derive unbiased estimators of population total and variance. We also introduce an easy-to-compute estimator, which is nearly as efficient as the unbiased estimator. A simulation study on a rare plant population of buttercups (Ranunculus) shows that ATIS even with the easy-to-compute estimator is more efficient than its conventional sampling counterparts and is more efficient than Two-stage Adaptive Cluster Sampling (TACS) for small and moderate final sample sizes. Additional simulations reveal that ATIS is efficient for binary data (e.g., presence or absence) whereas TACS is inefficient for binary data. The overall results indicate that ATIS is consistently efficient compared to conventional sampling and to adaptive cluster sampling in some important cases.
The study of ancient DNA is revolutionizing our understanding of paleo-ecology and the evolutionary history of species. Insects are essential components in many ecosystems and constitute the most diverse group of animals. Yet they are largely neglected in ancient DNA studies. We report the results of the first targeted investigation of insect ancient DNA to positively identify subfossil insects to species, which includes the recovery of endogenous content from samples as old as ~ 34,355 ybp. Potential inhibitors currently limiting widespread research on insect ancient DNA are discussed, including the lack of closely related genomic reference sequences (decreased mapping efficiency) and the need for more extensive collaborations with insect taxonomists. The advantages of insect-based studies are also highlighted, especially in the context of understanding past climate change. In this regard, insect remains from ancient packrat middens are a rich and largely uninvestigated resource for exploring paleo-ecology and species dynamics over time.
Controlling range expansion of invasive carp (specifically Hypophthalmichthys spp.) on the Tennessee River is important to conserve the ecological and economic benefits provided by the river. We collaborated with State and Federal agencies (the stakeholder group) to develop a decision framework and decision support model to evaluate strategies to control carp expansion in the Tennessee River. Using this decision framework, we assessed the efficacy of various barrier strategies (technologies and locations) on reducing bigheaded carp (Hypophthalmichthys nobilis [bighead carp] and Hypophthalmichthys molitrix [silver carp]) relative abundance under different patterns and magnitudes of population growth and movement. We also assessed whether or not these strategies induced tradeoffs between reducing bigheaded carp relative abundance and other considerations for public satisfaction, effects on lock operation, and native species. For the purpose of comparing options to control carp in a quantitative framework, we codeveloped a carp population dynamics model with the stakeholder group. We then used the model to compare invasive carp management options within the Tennessee River system. The actions we considered included barrier placement at lock and dam systems and targeted removal through harvest, which were believed to impede upstream carp spread and establishment. To account for the uncertainty in carp population growth and movement rates, the group developed four population models that varied in the underlying population dynamics and population growth rates. The models affected population growth through either the stock-recruitment relation or intrinsic density-dependent growth rate. We then tasked the stakeholder group to test various strategies using the model. We then developed a more formal optimization framework and solved for strategies that performed well under scenarios of barrier effectiveness, movement rate, recruitment frequency, fishing mortality, and variation in population growth rate. The results of our qualitative and quantitative analyses indicated that strategies designed to first protect reservoirs just above the leading edge of carp invasion by installing barriers and removing fish below that point would perform best; however, this depended on barrier effectiveness. When barrier effectiveness was high, simply cutting off the presumed source of carp and blocking the leading the edge was enough to stop carp invasion; however, lower effectiveness meant that more barriers would be needed to slow, but not completely stop, carp invasion. We discuss what these findings mean in terms of future monitoring and management efforts to reduce the potential for expanding carp invasion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211068","programNote":"Biological Threats Research Program","usgsCitation":"Post van der Burg, M., Smith, D.R., Cupp, A.R., Rogers, M.W., and Chapman, D.C., 2021, Decision analysis of barrier placement and targeted removal to control invasive carp in the Tennessee River Basin: U.S. Geological Survey Open-File Report 2021–1068, 18 p., https://doi.org/10.3133/ofr20211068.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-129842","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386492,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1068/coverthb2.jpg"},{"id":386493,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1068/ofr20211068.pdf","text":"Report","size":"979 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1068"}],"country":"United States","state":"Kentucky","otherGeospatial":"Tennessee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.516845703125,\n 37.01132594307015\n ],\n [\n -87.12158203125,\n 37.42252593456307\n ],\n [\n -85.111083984375,\n 38.212288054388175\n ],\n [\n -84.13330078125,\n 38.74551518488265\n ],\n [\n -84.48486328124999,\n 39.036252959636606\n ],\n [\n -85.078125,\n 39.13006024213511\n ],\n [\n -85.97900390625,\n 38.98503278695909\n ],\n [\n -87.022705078125,\n 38.54816542304656\n ],\n [\n -87.945556640625,\n 38.24680876017446\n ],\n [\n -88.72558593749999,\n 37.70120736474139\n ],\n [\n -88.78051757812499,\n 37.32648861334206\n ],\n [\n -88.472900390625,\n 36.99377838872517\n ],\n [\n -88.516845703125,\n 37.01132594307015\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
On June 24, 2019, Congressman Raul Grijalva of Arizona, Chair of the House Committee on Natural Resources, sent a letter to the directors of the U.S. Fish and Wildlife Service and the U.S. Geological Survey to request their assistance in answering questions regarding coastal sediment resource management within the Coastal Barrier Resources System as defined by the Coastal Barrier Resources Act (Public Law 97–348; 96 Stat. 1653; 16 U.S.C. 3501 et seq.). For the purposes of this response, coastal sediment resource management refers to the removal of sediment from one part of a barrier island system for placement in another part of the coastal system, for either hazard mitigation (for example, erosion or flood control) or coastal restoration (for example, expansion or restoration of beach, dune, and [or] marsh habitats). The specific topics of concern are as follows (paraphrased from Congressman Grijalva’s letter):
1. Disruption of coastal sediment supply resulting from sediment removal and placement, including the replenishment rate of removed sediments and impacts to other components of the barrier island system (discussed in sec. 3).
2. Physical and biological impacts of sediment removal and placement on benthic habitats (discussed in sec. 4).
3. Impacts of sediment removal and placement on fish and other marine species (discussed in sec. 5).
4. Changes in migratory bird nesting and foraging habitats resulting from sediment removal and placement (discussed in sec. 6).
5. Long-term impacts of sediment removal and placement on physical coastal resiliency (discussed in sec. 7).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211062","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Coastal and Marine Hazards and Resources Program and Ecosystems Mission Area","usgsCitation":"Miselis, J.L., Flocks, J.G., Zeigler, S., Passeri, D., Smith, D.R., Bourque, J., Sherwood, C.R., Smith, C.G., Ciarletta, D.J., Smith, K., Hart, K., Kazyak, D., Berlin, A., Prohaska, B., Calleson, T., and Yanchis, K., 2021, Impacts of sediment removal from and placement in coastal barrier island systems: U.S. Geological Survey Open-File Report 2021–1062, 94 p., https://doi.org/10.3133/ofr20211062.","productDescription":"viii, 94 p.","numberOfPages":"106","onlineOnly":"Y","ipdsId":"IP-125418","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":485919,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_111412.htm","linkFileType":{"id":5,"text":"html"}},{"id":386003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1062/coverthb.jpg"},{"id":386004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1062/ofr20211062.pdf","text":"Report","size":"9.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1062"},{"id":386005,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1062/images"}],"contact":"Program Coordinator, Coastal and Marine Hazards and Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Decreased availability of forage, as well as increased pesticide exposure, are important factors in the decline of honey bee health. Here, we isolate land cover transitions and their effect on honey production at 160 commercial apiaries in the Northern Great Plains. We found that land cover changes from 2008 to 2012 caused an annual decline in honey yields of 0.9% in the study area. Transitions from grassland to soybean (but not corn) were particularly detrimental to honey yields, potentially due to bee contact with pesticides within and around agricultural fields. When our results are applied to known apiary locations across all of North Dakota (U.S.A.), we estimate a 2.5% (1.6 million USD) decline in 2012 honey yields due to land cover changes occurring between 2008 and 2012. Even when controlling for changes in land cover, we found that on average colonies in the study area experienced a 14% annual decline in honey yields. We discuss possible explanations for these non-land-cover-related honey yield declines, including changing economic conditions (e.g. pollination services), changes in land management (e.g. pesticides), and increases in pests or diseases.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/abfde8","usgsCitation":"Smith, D., Davis, A.Y., Hitaj, C., Hellerstein, D., Preslicka, A., Kirkpatrick, E., Mushet, D., and Lonsdorf, E., 2021, The contribution of land cover change to the decline of honey yields in the Northern Great Plains: Environmental Research Letters, v. 16, 064050, 12 p., https://doi.org/10.1088/1748-9326/abfde8.","productDescription":"064050, 12 p.","ipdsId":"IP-105742","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abfde8","text":"Publisher Index Page"},{"id":387285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.755859375,\n 43.004647127794435\n ],\n [\n -96.50390625,\n 43.004647127794435\n ],\n [\n -96.50390625,\n 44.465151013519616\n ],\n [\n -99.755859375,\n 44.465151013519616\n ],\n [\n -99.755859375,\n 43.004647127794435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David","contributorId":261251,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Amelie Y. 0000-0001-7373-7618","orcid":"https://orcid.org/0000-0001-7373-7618","contributorId":261252,"corporation":false,"usgs":false,"family":"Davis","given":"Amelie","email":"","middleInitial":"Y.","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitaj, Claudia 0000-0002-6408-9265","orcid":"https://orcid.org/0000-0002-6408-9265","contributorId":261253,"corporation":false,"usgs":false,"family":"Hitaj","given":"Claudia","email":"","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hellerstein, Dan","contributorId":261254,"corporation":false,"usgs":false,"family":"Hellerstein","given":"Dan","affiliations":[{"id":52784,"text":"U.S. Department of Agriculture, Economic Research Service","active":true,"usgs":false}],"preferred":false,"id":819597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preslicka, Amanda","contributorId":261255,"corporation":false,"usgs":false,"family":"Preslicka","given":"Amanda","email":"","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirkpatrick, Emma","contributorId":261256,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"Emma","email":"","affiliations":[{"id":17754,"text":"Miami University, Department of Geography & Institute for the Environment and Sustainability","active":true,"usgs":false}],"preferred":false,"id":819599,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819600,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lonsdorf, Eric","contributorId":261257,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","affiliations":[{"id":52785,"text":"University of Minnesota, Institute on the Environment","active":true,"usgs":false}],"preferred":false,"id":819601,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220322,"text":"sir20215021 - 2021 - Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","interactions":[],"lastModifiedDate":"2025-05-14T18:34:47.405035","indexId":"sir20215021","displayToPublicDate":"2021-05-07T07:51:36","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5021","displayTitle":"Hydraulic Characterization of Carbonate-Rock and Basin-Fill Aquifers near Long Canyon, Goshute Valley, Northeastern Nevada","title":"Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","docAbstract":"Understanding groundwater flow and pumping effects near pending mining operations requires accurate subsurface hydraulic characterization. To improve conceptual models of groundwater flow and development in the complex hydrogeologic system near Long Canyon Mine, in northwestern Goshute Valley, northeastern Nevada, the U.S. Geological Survey characterized the hydraulic properties of carbonate rocks and basin-fill aquifers using an integrated analysis of steady-state and stressed aquifer conditions informed by water chemistry and aquifer-test data. Hydraulic gradients and groundwater-age data in northern Goshute Valley indicate carbonate rocks in the Pequop Mountains just west and south of the Long Canyon Mine project area constitute a more permeable and active flow system than saturated rocks in the northern Pequop Mountains, western Toano Range, and basin fill. Permeable carbonate rocks in the northern Pequop Mountains, in part, discharge to the Johnson Springs wetland complex (JSWC), where mean groundwater ages range from 500 to 2,400 years and samples all contain a small fraction of modern waters, relative to mean ages of 8,600 to more than 22,000 years for most groundwater sampled to the north and east. Recharge to the JSWC occurs from a roughly 27-square-mile area in the upgradient Pequop Mountains to the west, composed mostly of permeable carbonate rock and fractured quartzite, and bounded by low-permeability shales and marbleized and siliclastic rocks.
Single-well aquifer-test analyses provided transmissivity estimates at pumped wells. Transmissivity estimates ranged from 7,000 to 400,000 feet squared per day (ft2/d) in carbonate rocks and from 2,000 to 80,000 ft2/d in basin fill near the Long Canyon Mine. Water-level drawdown from multiple-well aquifer testing and rise from unintentional leakage into the overlying basin-fill aquifer were estimated and distinguished from natural fluctuations in 93 pumping and monitoring sites using analytical water-level models. Leakage of disposed aquifer-test pumpage occurred south of the aquifer test area through an unlined irrigation ditch. Drawdown was detected at distances of as much as 3 miles (mi) from pumping wells at all but one carbonate-rock site, at basin-fill sites on the alluvial fan immediately downgradient from pumping wells, and in Big Spring and spring NS-05. Similar drawdowns in carbonate rocks within the drawdown detection area suggest all wells penetrate a highly transmissive zone (HTZ) that is bounded by low-permeability rocks. Drawdown was not detected in carbonate rocks to the west of Canyon fault, in any basin-fill sites on the valley floor east of the Hardy fault, or at volcanic sites to the north, indicating that these major fault structures and (or) permeability contrasts between hydrogeologic units impeded groundwater flow or obscured pumping signals. Alternatively, unintentional leakage might have obscured drawdown at basin-fill sites on the valley floor, where water-level rise was detected at nine sites over 3 mi.
Consistent hydraulic properties were estimated by simultaneously interpreting steady-state flow during predevelopment conditions and changes in groundwater levels and springflows from the 2016 carbonate-rock aquifer test with an integrated groundwater-flow model. Hydraulic properties were distributed across carbonate rocks, basin fill, volcanic rocks, and siliciclastic rocks with a hydrogeologic framework developed from geologic mapping and hydraulic testing. Estimated transmissivity distributions spanned at least three orders of magnitude in each rock unit. In the HTZ, simulated transmissivities ranged from 10,000 to 23,000,000 ft2/d, with the most transmissive areas occurring around Big Spring. Comparatively low carbonate-rock transmissivities of less than 10,000 ft2/d were estimated in the northern Pequop Mountains and poorly defined values of less than 1,000 ft2/d were estimated in the western Toano Range. Transmissivities in basin fill ranged from less than 10 to 80,000 ft2/d and were minimally constrained by the 2016 carbonate-rock aquifer test because poorly quantified leakage affected water levels more so than pumping. The most transmissive areas were informed by single-well aquifer tests along the eastern edge of the Pequop Mountains near Long Canyon Mine and could be indicative of a hydraulic connection between basin fill and more transmissive underlying carbonate rocks. Simulated transmissivities of volcanic and low-permeability rocks mostly are less than 1,000 ft2/d. The estimated hydraulic-property distributions and informed interpretation of hydraulic connections among hydrogeologic units improved the characterization and representation of groundwater flow near the Long Canyon Mine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215021","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Garcia, C.A., Halford, K.J., Gardner, P.M., and Smith, D.W., 2021, Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada: U.S. Geological Survey Scientific Investigations Report 2021–5021, 99 p., https://doi.org/10.3133/sir20215021.","productDescription":"Report: xii, 99 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-094004","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":397361,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.XML"},{"id":397360,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5021/images"},{"id":385454,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P1P7QV","text":"USGS data release","description":"USGS data release","linkHelpText":"Appendixes and supplemental data—Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada, 2011–16."},{"id":385453,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JI8NQF","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 and PEST models used to simulate the 2016 carbonate-rock aquifer test and characterize hydraulic properties of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada."},{"id":385451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5021/coverthb.jpg"},{"id":385452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5021"}],"country":"United States","state":"Nevada","otherGeospatial":"Goshute Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.98840332031249,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Flathead Catfish Pylodictis olivaris have been either intentionally or accidentally introduced into Atlantic Slope drainages extending from Florida to Pennsylvania and have quickly become established. In Pennsylvania, Flathead Catfish were first detected in the Schuylkill River at the Fairmont Dam in 1999 and in the Susquehanna River at Safe Harbor Dam in 2002. The species has since moved throughout the respective basins, with subsequent detections during 244 riverine surveys in these drainages. Fishway and electrofishing surveys in the tidal Schuylkill River, a Delaware River tributary, have documented an increase in abundances since 2004, when the surveys were first implemented. Hoop-net surveys in nontidal large-river reaches found mean (±SD) catch rates varying from 0.00 to 4.51 ± 4.38 fish/series. A Bayesian hierarchical Poisson regression model indicated that Flathead Catfish abundance decreased as the distance from the initial point of detection increased, demonstrating a general pattern of fish expansion upstream from the point of detection. The distance downstream of the nearest dam, although not significant, had a relatively high posterior probability of being negatively correlated with Flathead Catfish abundance. Ongoing and future targeted surveys should help to better understand changes in the distribution and abundance of Flathead Catfish in these systems.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10628","usgsCitation":"Smith, G.D., Massie, D.L., Perillo, J., Wagner, T., and Pierce, D., 2021, Range expansion and factors affecting abundance of invasive Flathead Catfish in the Delaware and Susquehanna Rivers, Pennsylvania, USA: North American Journal of Fisheries Management, v. 41, no. S1, p. S205-S220, https://doi.org/10.1002/nafm.10628.","productDescription":"16 p.","startPage":"S205","endPage":"S220","ipdsId":"IP-116902","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Delaware River, Juniata River, Lehigh River, Schuylkill River, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.7774658203125,\n 39.7240885773337\n ],\n [\n -75.73974609375,\n 39.7240885773337\n ],\n [\n -75.16845703124999,\n 39.80853604144591\n ],\n [\n -74.619140625,\n 40.111688665595956\n ],\n [\n -75.16845703124999,\n 40.713955826286046\n ],\n [\n -74.94873046875,\n 40.863679665481676\n ],\n [\n -75.08056640625,\n 40.9964840143779\n ],\n [\n -74.739990234375,\n 41.45919537950706\n ],\n [\n -74.81689453125,\n 41.463311976686235\n ],\n [\n -74.9542236328125,\n 41.50446357504803\n ],\n [\n -75.0311279296875,\n 41.611335399441735\n ],\n [\n -75.0311279296875,\n 41.775408403663285\n ],\n [\n -75.1025390625,\n 41.87774145109676\n ],\n [\n -75.223388671875,\n 41.89001042401827\n ],\n [\n -75.322265625,\n 42.00848901572399\n ],\n [\n -78.7335205078125,\n 42.00032514831621\n ],\n [\n -78.7774658203125,\n 39.7240885773337\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"S1","noUsgsAuthors":false,"publicationDate":"2021-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Geoffrey D.","contributorId":274361,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":834438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massie, Danielle L.","contributorId":196717,"corporation":false,"usgs":false,"family":"Massie","given":"Danielle","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":834439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perillo, Joseph","contributorId":275966,"corporation":false,"usgs":false,"family":"Perillo","given":"Joseph","email":"","affiliations":[{"id":56915,"text":"Philadelphia Water Department","active":true,"usgs":false}],"preferred":false,"id":834440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pierce, Daryl","contributorId":276044,"corporation":false,"usgs":false,"family":"Pierce","given":"Daryl","email":"","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":834514,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248847,"text":"70248847 - 2021 - Leveraging risk communication science across US federal agencies","interactions":[],"lastModifiedDate":"2023-09-22T13:44:15.71951","indexId":"70248847","displayToPublicDate":"2021-03-18T08:36:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16869,"text":"Nature Human Behavior","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging risk communication science across US federal agencies","docAbstract":"Many US federal agencies apply principles from risk communication science across a wide variety of hazards. In so doing, they identify key research and practice gaps that, if addressed, could help better serve the nation’s communities and greatly enhance practice, research, and policy development.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41562-021-01081-0","usgsCitation":"Klein, W.M., Boutte, A., Brake, H., Beal, M., Lyon-Daniel, K., Eisenhauer, E., Grasso, M., Hubbell, B., Jenni, K., Lauer, C., Lupia, A., Prue, C., Rausch, P., Shapiro, C.D., Smith, M.D., and Riley, W., 2021, Leveraging risk communication science across US federal agencies: Nature Human Behavior, v. 5, p. 411-413, https://doi.org/10.1038/s41562-021-01081-0.","productDescription":"3 p.","startPage":"411","endPage":"413","ipdsId":"IP-122303","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":453026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41562-021-01081-0","text":"Publisher Index Page"},{"id":421069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Klein, William M. P.","contributorId":330034,"corporation":false,"usgs":false,"family":"Klein","given":"William","email":"","middleInitial":"M. P.","affiliations":[],"preferred":false,"id":883898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boutte, Alycia","contributorId":330014,"corporation":false,"usgs":false,"family":"Boutte","given":"Alycia","email":"","affiliations":[{"id":29855,"text":"National Cancer Institute","active":true,"usgs":false}],"preferred":false,"id":883860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brake, Heather","contributorId":330035,"corporation":false,"usgs":false,"family":"Brake","given":"Heather","email":"","affiliations":[],"preferred":false,"id":883861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beal, Madeline","contributorId":330017,"corporation":false,"usgs":false,"family":"Beal","given":"Madeline","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyon-Daniel, Katherine","contributorId":330019,"corporation":false,"usgs":false,"family":"Lyon-Daniel","given":"Katherine","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":883863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eisenhauer, Emily","contributorId":330021,"corporation":false,"usgs":false,"family":"Eisenhauer","given":"Emily","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grasso, Monica","contributorId":211877,"corporation":false,"usgs":false,"family":"Grasso","given":"Monica","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":883865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubbell, Bryan","contributorId":330023,"corporation":false,"usgs":false,"family":"Hubbell","given":"Bryan","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883866,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jenni, Karen 0000-0001-9927-7509","orcid":"https://orcid.org/0000-0001-9927-7509","contributorId":219401,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883867,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lauer, Christopher","contributorId":330025,"corporation":false,"usgs":false,"family":"Lauer","given":"Christopher","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":883868,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lupia, Arthur","contributorId":330027,"corporation":false,"usgs":false,"family":"Lupia","given":"Arthur","email":"","affiliations":[{"id":65942,"text":"NSF","active":true,"usgs":false}],"preferred":false,"id":883869,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Prue, Christine","contributorId":330029,"corporation":false,"usgs":false,"family":"Prue","given":"Christine","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":883870,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rausch, Paula","contributorId":330031,"corporation":false,"usgs":false,"family":"Rausch","given":"Paula","email":"","affiliations":[{"id":78768,"text":"FDA","active":true,"usgs":false}],"preferred":false,"id":883871,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883874,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Smith, Michael D.","contributorId":206173,"corporation":false,"usgs":false,"family":"Smith","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":883872,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Riley, William","contributorId":222533,"corporation":false,"usgs":false,"family":"Riley","given":"William","affiliations":[],"preferred":false,"id":883873,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70218752,"text":"ofr20211026 - 2021 - Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","interactions":[],"lastModifiedDate":"2021-04-07T01:36:23.477755","indexId":"ofr20211026","displayToPublicDate":"2021-03-10T15:49:09","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1026","displayTitle":"Expected Warning Times from the ShakeAlert® Earthquake Early Warning System for Earthquakes in the Pacific Northwest","title":"Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","docAbstract":"The ShakeAlert® earthquake early warning system has been live since October 2019 for the testing of public alerting to mobile devices in California and will soon begin testing this modality in Oregon and Washington. The Pacific Northwest presents new challenges and opportunities for ShakeAlert owing to the different types of earthquakes that occur in the Cascadia subduction zone. Many locations in the Pacific Northwest are expected to experience shaking from shallow crustal earthquakes (similar to those in California), earthquakes that occur deep within the subducted slab, and large megathrust earthquakes that occur primarily offshore. The different geometries and maximum magnitudes associated with these types of earthquakes lead to a range of warning times that are possible between when the initial ShakeAlert Message is issued and when a user experiences strong shaking. After an earthquake begins, the strategy of the ShakeAlert system for public alerting is to warn people who are located close enough to the fault that the system estimates they will experience at least weak to moderate shaking. By alerting the public at these low levels of expected shaking, it is possible to provide sufficient warning times for some users to take protective actions before strong shaking begins. In this study, we present an analysis of past ShakeAlert Messages as well as simulations of historical earthquakes and potential future Cascadia earthquakes to quantify the range of warning times that users who experience strong or worse shaking are likely to receive. Additional applications for ShakeAlert involve initiation of automatic protective actions prior to the onset of shaking, such as slowing trains, shutting water supplies, and opening firehouse doors, which are beyond the scope of this paper. Users in the Pacific Northwest should expect that the majority of alerts they receive will be from shallow crustal and intraslab earthquakes. In these cases, users will only have a few seconds of warning before strong shaking begins. This remains true even during infrequent, offshore great (magnitude ≥8) megathrust earthquakes, where warning times will generally range from seconds to tens of seconds, depending on the user’s location and the intensity of predicted shaking that a user chooses to be alerted for, with the longest warning times of 50–80 seconds possible only for users located at considerable distance from the epicenter. ShakeAlert thus requires short, readily understood alerts stating that earthquake shaking is imminent and suggesting protective actions users should take. Extensive education and outreach efforts that emphasize the need to take actions quickly will be required for ShakeAlert to successfully reduce injuries and losses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211026","usgsCitation":"McGuire, J.J., Smith, D.E., Frankel, A.D., Wirth, E.A., McBride, S.K., and de Groot, R.M., 2021, Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest (ver. 1.1, March 24, 2021): U.S. Geological Survey Open-File Report 2021–1026, 37 p., https://doi.org/10.3133/ofr20211026.","productDescription":"v, 37 p.","onlineOnly":"Y","ipdsId":"IP-125131","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384638,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1026/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":384281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1026/ofr20211026_v1.1.pdf","text":"Report","size":"12 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\"}}]}","edition":"Version 1.0: Marhc 10, 2021; Version 1.1: March 24, 2021","contact":"Earthquake Science Center—Menlo Park, Calif. Office
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Water radiolysis continuously produces H2 and oxidized chemicals in wet sediment and rock. Radiolytic H2 has been identified as the primary electron donor (food) for microorganisms in continental aquifers kilometers below Earth’s surface. Radiolytic products may also be significant for sustaining life in subseafloor sediment and subsurface environments of other planets. However, the extent to which most subsurface ecosystems rely on radiolytic products has been poorly constrained, due to incomplete understanding of radiolytic chemical yields in natural environments. Here we show that all common marine sediment types catalyse radiolytic H2 production, amplifying yields by up to 27X relative to pure water. In electron equivalents, the global rate of radiolytic H2 production in marine sediment appears to be 1-2% of the global organic flux to the seafloor. However, most organic matter is consumed at or near the seafloor, whereas radiolytic H2 is produced at all sediment depths. Comparison of radiolytic H2 consumption rates to organic oxidation rates suggests that water radiolysis is the principal source of biologically accessible energy for microbial communities in marine sediment older than a few million years. Where water permeates similarly catalytic material on other worlds, life may also be sustained by water radiolysis.
The presence of many pathogens varies in a predictable manner with latitude, with infections decreasing from the equator towards the poles. We investigated the geographic trends of pathogens infecting a widely distributed carnivore: the gray wolf (Canis lupus). Specifically, we investigated which variables best explain and predict geographic trends in seroprevalence across North American wolf populations and the implications of the underlying mechanisms. We compiled a large serological dataset of nearly 2000 wolves from 17 study areas, spanning 80° longitude and 50° latitude. Generalized linear mixed models were constructed to predict the probability of seropositivity of four important pathogens: canine adenovirus, herpesvirus, parvovirus, and distemper virus—and two parasites: Neospora caninum and Toxoplasma gondii. Canine adenovirus and herpesvirus were the most widely distributed pathogens, whereas N. caninum was relatively uncommon. Canine parvovirus and distemper had high annual variation, with western populations experiencing more frequent outbreaks than eastern populations. Seroprevalence of all infections increased as wolves aged, and denser wolf populations had a greater risk of exposure. Probability of exposure was positively correlated with human density, suggesting that dogs and synanthropic animals may be important pathogen reservoirs. Pathogen exposure did not appear to follow a latitudinal gradient, with the exception of N. caninum. Instead, clustered study areas were more similar: wolves from the Great Lakes region had lower odds of exposure to the viruses, but higher odds of exposure to N. caninum and T. gondii; the opposite was true for wolves from the central Rocky Mountains. Overall, mechanistic predictors were more informative of seroprevalence trends than latitude and longitude. Individual host characteristics as well as inherent features of ecosystems determined pathogen exposure risk on a large scale. This work emphasizes the importance of biogeographic wildlife surveillance, and we expound upon avenues of future research of cross-species transmission, spillover, and spatial variation in pathogen infection.
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We develop a metapopulation model that tracks two key components of a species’ social system: average group size and number of groups within a population. While the model is general, we parameterize it to mimic the dynamics of the Yellowstone wolf population and two associated pathogens: sarcoptic mange and canine distemper. In the initial absence of disease, we show that group size is mainly determined by the birth and death rates and the rates at which groups fission to form new groups. The total number of groups is determined by rates of fission and fusion, as well as environmental resources and rates of intergroup aggression. Incorporating pathogens into the models reduces the size of the host population, predominantly by reducing the number of social groups. Average group size responds in more subtle ways: infected groups decrease in size, but uninfected groups may increase when disease reduces the number of groups and thereby reduces intraspecific aggression. Our modeling approach allows for easy calculation of prevalence at multiple scales (within group, across groups, and population level), illustrating that aggregate population-level prevalence can be misleading for group-living species. The model structure is general, can be applied to other social species, and allows for a dynamic assessment of how pathogens can affect social structure and vice versa.
Many questions relevant to conservation decision making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecological processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecological applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield Elicitation Framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. This study demonstrates the remote use of the SHELF protocol for an extinction risk assessment of three subterranean aquatic species petitioned for listing under the US Endangered Species Act. Experts were provided an empirical threat assessment for each known locality using video conferencing and asked for judgments on the probability of population persistence over four generations using online submission forms and R‐shiny apps available through the SHELF package. Despite large uncertainty for all populations, results reveal key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and microhabitat use. The resulting probability distributions provide decision makers with a full picture of uncertainty that is consistent with the probabilistic nature of risk assessments, and discussions during the behavioral aggregation stage clearly document dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat preferences. Our virtual implementation of the SHELF protocol demonstrates the flexibility of this approach for conservation applications operating on budgets and timelines that can limit in‐person meetings of geographically dispersed experts.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13694","usgsCitation":"Fitzgerald, D.B., Smith, D.R., Culver, D.C., Feller, D., Fong, D.W., Hajenga, J., Niemiller, M.L., Nolfi, D.C., Orndorff, W.D., Douglas, B., Maloney, K.O., and Young, J.A., 2021, Using expert knowledge to support Endangered Species Act decision‐making for data‐deficient species: Conservation Biology, v. 35, no. 5, p. 1627-1638, https://doi.org/10.1111/cobi.13694.","productDescription":"12 p.","startPage":"1627","endPage":"1638","ipdsId":"IP-124137","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":453793,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Using_expert_knowledge_to_support_Endangered_Species_Act_decision-making_for_data-deficient_species/23894598","text":"External 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