Recovery of salmon populations in the upper Cowlitz River Basin depends on trap-and-haul efforts owing to impassable dams. Therefore, successful recovery depends on the collection of out-migrating juvenile salmon at Cowlitz Falls Dam (CFD) for transport below downstream dams, as well as the collection of adults for transport upstream from the dams. Tacoma Power began downstream fish collection efforts at CFD in the mid-1990s and has been working consistently since then to improve collection efficiency to support self-sustaining salmon and steelhead (Onchorhynchus spp.) populations in the upper Cowlitz River Basin. Although much work has focused on estimating fish collection efficiency (FCE), there has been relatively little focus on modeling population dynamics to understand how fish collection efficiency and other factors drive production of both juvenile and adult salmon over their life cycle. As a first step towards understanding the factors affecting population dynamics of Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, we developed a statistical life cycle model using adult escapement and age structure data, juvenile collection data, and juvenile fish collection efficiency estimates. The goal of the statistical life cycle model is to estimate annual production and survival during two critical life-stage transitions: the freshwater production from escapement of adults upstream from CFD to collection of juveniles at CFD, and the juvenile-to-adult survival from the time of collection at the dam to the return of adults. To structure the life cycle model, we used the Ricker stock-recruitment model to estimate juvenile production from the number of parent spawners. This approach allowed us to account for density dependence at high spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. We then expressed productivity as a function two key variables affecting the number of juveniles collected and transported at CFD: (1) annual FCE, and (2) the annual number of days that spill occurred at CFD from September 1 to April 30.
Our key findings were as follows:
Additionally, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE=1, was 108.4 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river compared to the ocean environment and fish life stages, the model estimates should help inform fishery managers about the overall role that fish collection at CFD may have on the recovery and sustainability of coho salmon populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201068","collaboration":"Prepared in cooperation with Tacoma Power","usgsCitation":"Plumb, J.M., and Perry, R.W., 2020, Development of a two-stage life cycle model for Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, Washington: U.S. Geological Survey Open-File Report 2020–1068, 25 p., https://doi.org/10.3133/ofr20201068.","productDescription":"iv, 25 p.","onlineOnly":"Y","ipdsId":"IP-117483","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":376162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1068/coverthb.jpg"},{"id":376163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1068/ofr20201068.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1068"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.97821044921875,\n 46.09228143052647\n ],\n [\n -121.8548583984375,\n 46.09228143052647\n ],\n [\n -121.8548583984375,\n 46.70596917928676\n ],\n [\n -122.97821044921875,\n 46.70596917928676\n ],\n [\n -122.97821044921875,\n 46.09228143052647\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
While the physical processes governing groundwater flow are well understood, and the computational resources now exist for solving the governing equations in three dimensions over continental-scale domains, there remains substantial uncertainty about the subsurface distribution of the properties that control groundwater flow and transport for much of the contiguous United States (CONUS). The transmissivity of the shallow subsurface is a key parameter for the simulation of water table position, shallow groundwater flow, and base-flow discharge, but is not well-characterized at large regional to continental scales. We used a process-based inversion of CONUS-extent groundwater information to generate national data sets of (a) the transmissivity of the shallow groundwater system, (b) the depth to the water table, (c) groundwater discharge as base-flow, and (d) long-term average water content in the unsaturated zone. CONUS-extent coverage was developed in the form of 75 subdomain models, with the spatial distribution of long-term average transmissivity for each subdomain model calibrated against water-levels derived from U.S. Geological Survey (USGS) observation wells, NHDPlusV2 first-order perennial streams, and National Wetlands Inventory (NWI) freshwater wetlands. Estimated transmissivities were lower in the western CONUS than the eastern CONUS, and across the CONUS both transmissivity and depth to water correlate with recharge, elevation, and topographic slope. These generated data sets provide spatially distributed, long-term average estimates of subsurface properties and hydrological states that we anticipate will complement other environmental modeling efforts as explanatory variables, boundary conditions, or transport pathways.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR026724","usgsCitation":"Zell, W.O., and Sanford, W.E., 2020, Calibrated simulation of the long-term average surficial groundwater system and derived spatial distributions of its characteristics for the contiguous United States: Water Resources Research, v. 56, no. 8, e2019WR026724, 16 p.; Data Release, https://doi.org/10.1029/2019WR026724.","productDescription":"e2019WR026724, 16 p.; Data Release","ipdsId":"IP-117925","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436888,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91LFFN1","text":"USGS data release","linkHelpText":"MODFLOW 6 models used to simulate the long-term average surficial groundwater system for the contiguous United 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0000-0002-8782-6627","orcid":"https://orcid.org/0000-0002-8782-6627","contributorId":339721,"corporation":false,"usgs":true,"family":"Zell","given":"Wesley","email":"","middleInitial":"O.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212531,"text":"70212531 - 2020 - Deep Learning as a tool to forecast hydrologic response for landslide-prone hillslopes","interactions":[],"lastModifiedDate":"2020-08-19T13:25:09.670826","indexId":"70212531","displayToPublicDate":"2020-07-08T08:19:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Deep Learning as a tool to forecast hydrologic response for landslide-prone hillslopes","docAbstract":"Empirical thresholds for landslide warning systems have benefitted from the incorporation of soil‐hydrologic monitoring data, but the mechanistic basis for their predictive capabilities is limited. Although physically based hydrologic models can accurately simulate changes in soil moisture and pore pressure that promote landslides, their utility is restricted by high computational costs and nonunique parameterization issues. We construct a deep learning model using soil moisture, pore pressure, and rainfall monitoring data acquired from landslide‐prone hillslopes in Oregon, USA, to predict the timing and magnitude of hydrologic response at multiple soil depths for 36‐hr intervals. We find that observation records as short as 6 months are sufficient for accurate predictions, and our model captures hydrologic response for high‐intensity rainfall events even when those storm types are excluded from model training. We conclude that machine learning can provide an accurate and computationally efficient alternative to empirical methods or physical modeling for landslide hazard warning.
Assessments of groundwater and surface water budgets at a large scale, such as the contiguous United States, often separately analyze the complex dynamics linking the surface and subsurface categories of water resources. These dynamics include recharge and groundwater contributions to streamflow. The time-varying simulation of these complex hydrologic dynamics, across large spatial and temporal scales, remains a scientific challenge due to the complexity of the processes and data availability. In this study, groundwater fluxes and surface hydrologic processes are simulated across the contiguous US for 1950-2010. The simulation estimates the monthly water budget components, such as groundwater recharge, surface runoff, and evapotranspiration; streamflow in major rivers is routed while accounting for groundwater exchange. Human impacts are included through groundwater pumping, and climate variability is included, including variability in precipitation, temperature and potential evapotranspiration. The simulated groundwater level and river discharge have strong correlation with USGS observation wells and streamflow gages, with R2 values of 0.992 and 0.946, respectively. The simulated evapotranspiration is compared with three other published estimation methods, showing that it is able to capture the magnitude and seasonality of evapotranspiration over the Mississippi River basin. As such, the model is able to reasonably simulate the surface and groundwater budgets over the US, allowing for questions of the relative importance of climate and human impacts to be explored in the future.
As the Arctic warms and wildfire occurrence increases, talik formation in permafrost regions is projected to expand and affect the cycling of water and carbon. Yet, few unified field and modeling studies have examined this process in detail, particularly in areas of continuous permafrost. We address this gap by presenting multimethod, multiseasonal geophysical measurements of permafrost and liquid‐water content that reveal substantial talik development in response to recent wildfire in continuous permafrost of boreal Alaska. Results from observation‐based cryohydrogeologic model simulations suggest that predisturbance subsurface conditions are key factors influencing thaw response to fire disturbance and air temperature warming. Our high‐resolution integrated study illustrates enhanced vulnerability of boreal continuous permafrost, with observed talik formation that exceeds coarse‐scale model projections by ~100 years even under the most extreme future emissions scenario. Results raise important scaling questions for representing extreme permafrost thaw phenomena of growing widespread importance in large‐scale predictive models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL087565","usgsCitation":"Rey, D., Walvoord, M.A., Minsley, B.J., Ebel, B., Voss, C., and Singha, K., 2020, Wildfire-initiated talik development exceeds current thaw projections: Observations and models from Alaska's continuous permafrost zone: Geophysical Research Letters, v. 47, no. 15, e2020GL087565, 11 p., https://doi.org/10.1029/2020GL087565.","productDescription":"e2020GL087565, 11 p.","ipdsId":"IP-116894","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl087565","text":"Publisher Index Page"},{"id":381213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Northeast Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.82031249999997,\n 64.77412531292873\n ],\n [\n -140.9765625,\n 64.77412531292873\n ],\n [\n -140.9765625,\n 70.37785394109224\n ],\n [\n -150.82031249999997,\n 70.37785394109224\n ],\n [\n -150.82031249999997,\n 64.77412531292873\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"15","noUsgsAuthors":false,"publicationDate":"2020-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":806698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806700,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":806701,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211281,"text":"70211281 - 2020 - A national-scale assessment of mercury bioaccumulation in United States National Parks using dragonfly larvae as biosentinels through a citizen-science framework","interactions":[],"lastModifiedDate":"2020-07-22T15:35:59.640558","indexId":"70211281","displayToPublicDate":"2020-07-07T10:31:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"A national-scale assessment of mercury bioaccumulation in United States National Parks using dragonfly larvae as biosentinels through a citizen-science framework","docAbstract":"We conducted a national-scale assessment of mercury (Hg) bioaccumulation in aquatic ecosystems using dragonfly larvae as biosentinels, by developing a citizen science network to facilitate biological sampling. Implementing a carefully designed sampling methodology for citizen scientists, we developed an effective framework for landscape-level inquiry that might otherwise be resource limited. We assessed variation in dragonfly Hg concentrations across >450 sites spanning 100 US National Park Service units, and examined intrinsic and extrinsic factors associated with variation in Hg concentrations. Mercury concentrations ranged between 10.4-1,411 ng/g dry weight across sites and varied among habitat types. Dragonfly total Hg (THg) concentrations were up to 1.8-fold higher in lotic habitats than in lentic habitats, and 37% higher in waterbodies with abundant wetlands along their margins than those without wetlands. Mercury concentrations in dragonflies differed among families, but were correlated (R2>0.80) with each other, enabling adjustment to a consistent family to facilitate spatial comparisons among sampling units. Dragonfly THg concentrations were positively correlated with THg in both fish and amphibians from the same locations, indicating that dragonfly larvae are effective indicators of Hg bioavailability in aquatic food webs. Collectively, this continental-scale study demonstrates the utility of dragonfly larvae for estimating potential mercury risk to fish and wildlife in aquatic ecosystems and provides a framework for engaging citizen science as a component of landscape Hg monitoring programs.","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.0c01255","usgsCitation":"Eagles-Smith, C., Willacker, J., Nelson, S.J., Flanagan Pritz, C.M., Krabbenhoft, D.P., Chen, C.Y., Ackerman, J., Campbell Grant, E.H., and Pilliod, D.S., 2020, A national-scale assessment of mercury bioaccumulation in United States National Parks using dragonfly larvae as biosentinels through a citizen-science framework: Environmental Science and Technology, v. 54, no. 14, p. 8779-8790, https://doi.org/10.1021/acs.est.0c01255.","productDescription":"12 p.","startPage":"8779","endPage":"8790","ipdsId":"IP-117106","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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Maine","active":true,"usgs":false}],"preferred":false,"id":793492,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flanagan Pritz, Collen M","contributorId":229537,"corporation":false,"usgs":false,"family":"Flanagan Pritz","given":"Collen","email":"","middleInitial":"M","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793493,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793494,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Celia Y.","contributorId":145630,"corporation":false,"usgs":false,"family":"Chen","given":"Celia","email":"","middleInitial":"Y.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":793495,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":793496,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":793497,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":210334,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":793498,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211080,"text":"70211080 - 2020 - Height-related changes in forest composition, not tree vulnerability, explain increasing mortality with height during an extreme drought","interactions":[],"lastModifiedDate":"2020-07-14T15:31:00.828545","indexId":"70211080","displayToPublicDate":"2020-07-07T10:30:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Height-related changes in forest composition, not tree vulnerability, explain increasing mortality with height during an extreme drought","docAbstract":"Recently, Stovall et al.1 (hereafter SSY) showed that during an extreme drought, remotely sensed mortality of tall trees was more than double that of short trees. They interpreted this to be a consequence of inherently greater hydraulic vulnerability of tall trees, and suggested that tall-tree vulnerability should thus generalize more broadly. Here we reassess their conclusions using contemporaneous, ground-based data from near their study sites. We found that 90% of trees belonged to taxonomic groups showing declining, not increasing, mortality with height, and that the overall increase in mortality with height was instead a consequence of height-related changes in forest composition, not intrinsically greater vulnerability of tall trees. Similar mechanisms likely explain mortality patterns at SSY’s sites, and, regardless, we show that SSY’s conclusions should not be accepted in the absence of robust tests of alternative mechanisms.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-020-17213-5","usgsCitation":"Stephenson, N.L., and Das, A., 2020, Height-related changes in forest composition, not tree vulnerability, explain increasing mortality with height during an extreme drought: Nature Communications, v. 11, 3402, 4 p., https://doi.org/10.1038/s41467-020-17213-5.","productDescription":"3402, 4 p.","ipdsId":"IP-117776","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":456109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-17213-5","text":"Publisher Index Page"},{"id":376363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2020-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":792713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":792714,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211310,"text":"70211310 - 2020 - Beloniformes: Belonidae (Needlefishes) and Hemiramphidae (Halfbeaks)","interactions":[],"lastModifiedDate":"2020-07-23T15:16:27.184145","indexId":"70211310","displayToPublicDate":"2020-07-07T10:13:36","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Beloniformes: Belonidae (Needlefishes) and Hemiramphidae (Halfbeaks)","docAbstract":"The order Beloniformes (or Synentognathi) contains two suborders, six families, 37 genera, and about 235 species of atherinomorph fishes (Rosen & Parenti 1981; Collette et al. 1984; Collette 2004). Features common to these fishes include dorsal and anal fins on the rear half of the body, abdominal pelvic fins with six soft rays, no fin spines, lateral line running along the ventral edge of the body, an open nasal pit, and lower pharyngeal bones fused into a triangular plate (leading to the name Synentognathi). Two families, the Flying fishes (Exocoetidae) and the Sauries (Scomberesocidae) are restricted to marine waters but several genera of Needlefishes (Belonidae) and Halfbeaks (Hemiramphidae and Zenarchopteridae) are restricted to fresh waters and other genera contain estuarine, freshwater, and marine species. The family name Belonidae, based on the type genus Belone, means needle in reference to the unusually long and slender jaws of most Needlefishes. Similarly, the family name Hemiramphidae means half-beak, alluding to the conspicuous presence of a long slender lower jar and a short upper jaw in most species. Two species of Needlefishes (Belonidae, Strongylura) and two species of Halfbeaks (Hemiramphidae, Hyporhamphus) occur in North American fresh waters.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Freshwater fishes of North America, volume 2: Characidae to poeciliidae","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Bruce B. Collette, and Walsh, S., 2020, Beloniformes: Belonidae (Needlefishes) and Hemiramphidae (Halfbeaks), chap. of Freshwater fishes of North America, volume 2: Characidae to poeciliidae, v. 2, p. 449-462.","productDescription":"14 p.","startPage":"449","endPage":"462","ipdsId":"IP-077208","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":376667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376654,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/freshwater-fishes-north-america/table-of-contents"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bruce B. Collette","contributorId":229620,"corporation":false,"usgs":false,"family":"Bruce B. Collette","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":793694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Stephen 0000-0002-1009-8537","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":214723,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":793695,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210855,"text":"ofr20201061 - 2020 - Continuous stream discharge, salinity, and associated data collected in the Lower St. Johns River and its tributaries, Florida, 2018","interactions":[],"lastModifiedDate":"2020-07-07T15:39:00.489347","indexId":"ofr20201061","displayToPublicDate":"2020-07-07T09:20:44","publicationYear":"2020","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":"2020-1061","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2018","title":"Continuous stream discharge, salinity, and associated data collected in the Lower St. Johns River and its tributaries, Florida, 2018","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, plans to deepen the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel, beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the third annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project and contains information pertinent to the data collection during the 2018 water year, from October 2017 to September 2018. Changes to the network on the main stem of the St. Johns River include the addition of (1) three new stations to monitor water temperature and salinity at Racy Point, Shands Bridge, and above Buckman Bridge; (2) stage data collection at both Buckman Bridge and Dames Point Bridge; and (3) three additional parameters, namely stage, velocity, and streamflow direction, to the St. Johns River at Jacksonville and Dames Point Bridge.
Discharge and salinity varied widely during the data collection period, which included residual effects from Hurricane Irma in September 2017 and above-average rainfall for all counties in the project area over the 4-month period from April to July. The annual mean discharge at Durbin Creek was greatest among the tributaries, followed by annual mean discharges at Ortega River, Trout River, Cedar River, Julington Creek, Clapboard Creek, Broward River, Pottsburg Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was higher in the 2018 water year than that of the previous 2 years of this study. Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and lowest at Durbin Creek and Ortega River, the sites farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which is expected. Relative to annual mean salinity calculated since the 2016 water year, annual mean salinity at all monitoring locations was lower for the 2018 water year, except for Durbin Creek, which was the same.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201061","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the Lower St. Johns River and its tributaries, Florida, 2018: U.S. Geological Survey Open-File Report 2020–1061, 34 p., https://doi.org/10.3133/ofr20201061.","productDescription":"viii, 34 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-107711","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":375991,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1061/coverthb.jpg"},{"id":375992,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1061/ofr20201061.pdf","text":"Report","size":"25.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1061"}],"country":"United States","state":"Florida","otherGeospatial":"Lower St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.947021484375,\n 29.504159065872624\n ],\n [\n -81.00769042968749,\n 29.504159065872624\n ],\n [\n -81.00769042968749,\n 30.488917676126846\n ],\n [\n -81.947021484375,\n 30.488917676126846\n ],\n [\n -81.947021484375,\n 29.504159065872624\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Mercury (Hg) is a pervasive environmental pollutant and contaminant of concern for both people and wildlife that has been a focus of environmental remediation efforts for decades. A growing body of literature has motivated calls for revising Hg consumption advisories to co-consider selenium (Se) levels in seafood and implies that remediating aquatic ecosystems with ecosystem-scale Se additions could be a robust solution to Hg contamination. Provided that elevated Se concentrations are also known toxicological threats to aquatic animals, we performed a literature search to evaluate the strength of evidence supporting three assertions underpinning the ameliorating benefits of Se: (1) dietary Se reduces MeHg toxicity in consumers; (2) environmental Se reduces Hg bioaccumulation and biomagnification in aquatic food webs; and (3) Se inhibits Hg bioavailability to, and/or methylmercury production by, microbial communities. Limited or ambiguous support for each criterion indicates that many scientific uncertainties and gaps remain regarding Se mediation of Hg behavior and toxicity in abiotic and biotic compartments. Significantly more information is needed to provide a strong scientific basis for modifying current fish consumption advisories on the basis of Se:Hg ratios or for applying Se amendments to remediate Hg-contaminated ecosystems.
Coastal wetlands are among the most productive habitats on Earth and sequester globally significant amounts of atmospheric carbon (C). Extreme rates of soil C accumulation are widely assumed to reflect efficient C storage. Yet the fraction of wetland C lost via hydrologic export has not been directly quantified, since comprehensive budgets including direct estimates of lateral C loss are lacking. We present a complete net ecosystem C budget (NECB), demonstrating that lateral losses of C are a major component of the NECB for the largest stable brackish tidal marsh on the U.S. Pacific coast. Mean annual net ecosystem exchange of CO2 with the atmosphere (NEE = −185 g C m2 year−1, negative NEE denoting ecosystem uptake) was compared to long-term soil C burial (87–110 g C m2 year−1), suggesting only 47–59% of fixed atmospheric C accumulates in soils. Consistently, direct monitoring in 2017–2018 showed NEE of −255 g C m−2 year−1, and hydrologic export of 105 g C m−2 year−1 (59% of NEE remaining on site). Despite their high C sequestration capacity, lateral losses from coastal wetlands are typically a larger fraction of the NECB when compared to other terrestrial ecosystems. Loss of inorganic C (the least measured NECB term) was 91% of hydrologic export and may be the most important term limiting C sequestration. The high productivity of coastal wetlands thus serves a dual function of C burial and estuarine export, and the multiple fates of fixed C must be considered when evaluating wetland capacity for C sequestration.
Mercury contamination in river systems due to historic and current Hg releases is a persistent concern for both wildlife and human health. In larger rivers, like the Ohio River, USA, it is difficult to directly link Hg discharges to bioaccumulation due to the existence of multiple industrial Hg sources as well as the varied dietary and migratory habits of biota. To better understand how industrial effluent influences the cycling and bioaccumulation of Hg within the Ohio River, Hg stable isotope analysis was applied to various nonbiological and biological media. High Hg concentrations in suspended particulate matter suggest this vector was the largest contributor of Hg to the water column, and distinct Hg source signatures were observed in effluent particulates from different industrial processes, such as chlor‐alkali activity (δ202Hg = −0.52‰) and coal power plant discharge (δ202Hg = −1.39‰). Despite this distinction, average sediments (δ202Hg = −1.00 ± 0.23‰) showed intermediate isotopic signatures that suggest the accumulation of a mixed Hg source driven by multiple industrial discharges. Biota in the system were shown to have a conserved range of δ202Hg and estimation approaches related these signatures back to particulate matter within Hannibal Pool. Mussels were found to conserve Hg isotopes signatures independently of food web drivers and served as ideal water column indicators of bioaccumulated Hg sources. This study highlights the complexity of Hg cycling within an industrialized river and shows that an isotope tracer approach can provide insight to water column sources of Hg. Integr Environ Assess Manag 2021;17:233−242. Published 2020. This article is a US Government work and is in the public domain in the USA.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.4308","usgsCitation":"Janssen, S., Patnode, K.A., Pluta, B.R., and Krabbenhoft, D.P., 2020, Insights into mercury source identification and bioaccumulation using stable isotope approaches in the Hannibal Pool of the Ohio River: Integrated Environmental Assessment and Management, v. 17, no. 1, p. 233-242, https://doi.org/10.1002/ieam.4308.","productDescription":"10 p.","startPage":"233","endPage":"242","ipdsId":"IP-119884","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456115,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8043245","text":"External Repository"},{"id":436892,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95QMNJ4","text":"USGS data release","linkHelpText":"Mercury concentrations and isotopic compositions in biota and sediments from the Hannibal Pool of the Ohio River"},{"id":381755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Hannibal Pool, Ohio River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.134033203125,\n 39.47860556892209\n ],\n [\n -80.61767578124999,\n 39.47860556892209\n ],\n [\n -80.61767578124999,\n 40.36328834091583\n ],\n [\n -81.134033203125,\n 40.36328834091583\n ],\n [\n -81.134033203125,\n 39.47860556892209\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patnode, Kathleen A.","contributorId":127355,"corporation":false,"usgs":false,"family":"Patnode","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":807371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pluta, Bruce R","contributorId":245948,"corporation":false,"usgs":false,"family":"Pluta","given":"Bruce","email":"","middleInitial":"R","affiliations":[{"id":49378,"text":"US EPA Hazardous Clean-up Division","active":true,"usgs":false}],"preferred":false,"id":807372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217768,"text":"70217768 - 2020 - Dietary versus nondietary fatty acid profiles of lake trout ecotypes from Lake Superior and Great Bear Lake: Are fish really what they eat?","interactions":[],"lastModifiedDate":"2021-02-03T21:19:33.260532","indexId":"70217768","displayToPublicDate":"2020-07-07T07:08:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Dietary versus nondietary fatty acid profiles of lake trout ecotypes from Lake Superior and Great Bear Lake: Are fish really what they eat?","docAbstract":"Fatty acids are well-established biomarkers used to characterize trophic ecology, food-web linkages, and the ecological niche of many different taxa. Most often, fatty acids that are examined include only those previously identified as “dietary” or “extended dietary” biomarkers. Fatty acids considered as nondietary biomarkers, however, represent numerous fatty acids that can be extracted. Some studies may include nondietary fatty acids (i.e., combined with dietary fatty acids), but do not specifically assess them, whereas in other studies, these data are discarded. In this study, we explored whether nondietary biomarker fatty acids can provide worthwhile information by assessing their ability to discriminate intraspecific diversity within and between lakes. Nondietary fatty acids used as biomarkers delineated variation among regions, among locations within a lake, and among ecotypes within a species. Physiological differences that arise from differences in energy processing can be adaptive and linked to habitat use by a species’ ecotype and likely explains why nondietary fatty acid biomarkers can be a relevant tool to delineate intraspecific diversity. Little is known about the nondietary-mediated differences in fatty acid composition, but our results showed that nondietary fatty acid biomarkers can be useful tool in identifying variation.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0343","usgsCitation":"Chavarie, L., Hoffmann, J., Muir, A.M., Krueger, C.C., Bronte, C., Howland, K., Gallagher, S., Sitar, S.P., Hansen, M., Vinson, M., Baker, L., Loseto, L., Tonn, W.M., and Swanson, H., 2020, Dietary versus nondietary fatty acid profiles of lake trout ecotypes from Lake Superior and Great Bear Lake: Are fish really what they eat?: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 7, p. 1209-1220, https://doi.org/10.1139/cjfas-2019-0343.","productDescription":"12 p.","startPage":"1209","endPage":"1220","ipdsId":"IP-117041","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":456118,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2019-0343","text":"Publisher Index Page"},{"id":382870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.22021484375,\n 48.99463598353405\n ],\n [\n -88.516845703125,\n 48.857487002645485\n ],\n [\n -88.626708984375,\n 48.516604348867475\n ],\n [\n -88.857421875,\n 48.334343174592014\n ],\n [\n -88.79150390625,\n 48.574789910928864\n ],\n [\n -89.23095703125,\n 48.42920055556841\n ],\n [\n -89.241943359375,\n 48.3416461723746\n ],\n [\n -89.58251953125,\n 48.026672195436014\n ],\n [\n -90.95581054687499,\n 47.57652571374621\n ],\n [\n -92.076416015625,\n 46.76244305208004\n ],\n [\n -91.82373046875,\n 46.649436163350245\n ],\n [\n -90.823974609375,\n 46.9502622421856\n ],\n [\n -90.867919921875,\n 46.717268685073954\n ],\n [\n -90.977783203125,\n 46.63435070293566\n ],\n [\n -90.68115234375,\n 46.649436163350245\n ],\n [\n -90.37353515625,\n 46.59661864884465\n ],\n [\n -89.791259765625,\n 46.81509864599243\n ],\n [\n -88.9453125,\n 47.03269459852135\n ],\n [\n -88.143310546875,\n 47.487513008956554\n ],\n [\n -87.73681640625,\n 47.45037978769006\n ],\n [\n -88.077392578125,\n 47.32393057095941\n ],\n [\n -88.5498046875,\n 46.882723010671945\n ],\n [\n -88.472900390625,\n 46.76996843356982\n ],\n [\n -88.1982421875,\n 46.92025531537451\n ],\n [\n -87.615966796875,\n 46.78501604269254\n ],\n [\n -87.29736328125,\n 46.5286346952717\n ],\n [\n -87.000732421875,\n 46.50595444552049\n ],\n [\n -86.66015624999999,\n 46.53619267489863\n ],\n [\n -86.7919921875,\n 46.45299704748289\n ],\n [\n -86.0009765625,\n 46.68713141244413\n ],\n [\n -84.979248046875,\n 46.76996843356982\n ],\n [\n -85.078125,\n 46.46813299215554\n ],\n [\n -84.57275390625,\n 46.475699386607516\n ],\n [\n -84.48486328124999,\n 46.717268685073954\n ],\n [\n -84.825439453125,\n 46.98025235521883\n ],\n [\n -84.605712890625,\n 47.27922900257082\n ],\n [\n -85.01220703125,\n 47.628380027447136\n ],\n [\n -84.869384765625,\n 47.98256841921405\n ],\n [\n -85.67138671875,\n 47.931066347509784\n ],\n [\n -86.11083984375,\n 48.151428143221224\n ],\n [\n -86.37451171875,\n 48.748945343432936\n ],\n [\n -88.22021484375,\n 48.99463598353405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chavarie, Louise","contributorId":156227,"corporation":false,"usgs":false,"family":"Chavarie","given":"Louise","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":809605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoffmann, John P.","contributorId":207031,"corporation":false,"usgs":false,"family":"Hoffmann","given":"John P.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":809606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muir, A. 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P.","contributorId":248505,"corporation":false,"usgs":false,"family":"Sitar","given":"S.","email":"","middleInitial":"P.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":809612,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hansen, M.J.","contributorId":248626,"corporation":false,"usgs":false,"family":"Hansen","given":"M.J.","affiliations":[],"preferred":false,"id":809613,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809614,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Baker, L.F.","contributorId":248633,"corporation":false,"usgs":false,"family":"Baker","given":"L.F.","email":"","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":809615,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Loseto, L.L.","contributorId":248683,"corporation":false,"usgs":false,"family":"Loseto","given":"L.L.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":809616,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tonn, William M.","contributorId":204532,"corporation":false,"usgs":false,"family":"Tonn","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":809617,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Swanson, H.","contributorId":152186,"corporation":false,"usgs":false,"family":"Swanson","given":"H.","email":"","affiliations":[],"preferred":false,"id":809618,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70217801,"text":"70217801 - 2020 - Improved fish counting method accurately quantifies high‐density fish movement in dual‐frequency identification sonar data files from a coastal wetland environment","interactions":[],"lastModifiedDate":"2021-02-03T21:20:22.369695","indexId":"70217801","displayToPublicDate":"2020-07-07T06:46:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Improved fish counting method accurately quantifies high‐density fish movement in dual‐frequency identification sonar data files from a coastal wetland environment","docAbstract":"There are many ways to quantify fish movement through shallow‐water habitats, but most noninvasive methods (e.g., visual counts) are not effective in turbid coastal wetland waters of the Great Lakes. Dual‐frequency identification sonar (DIDSON) technology (Sound Metrics) offers a noninvasive, hydroacoustic‐based approach to characterize fish movement in wetlands and other habitats by collecting highly detailed fish movement data regardless of light and water quality conditions. High‐resolution data can be analyzed to estimate fish movement in areas where visual observations are difficult. However, enumerating a complex mix of fish sizes by manually counting fish visible in echogram files requires training and is very time consuming. Therefore, four counting techniques were tested to estimate fish abundance from DIDSON echograms that were collected at a hydrologically reconnected coastal wetland in the Great Lakes. Briefly, the four counting methods were (1) manually viewing the entire length of the echogram (full‐hour manual count), (2) manually viewing subsections of the echogram before generating fish estimates by per‐minute average (subsample manual count), (3) using Echoview automated software to generate automated estimates, and (4) using DIDSON viewer software to generate automated estimates. Over 800 echogram‐hours were recorded over a 9‐month period at an open‐flow water control structure connecting a coastal wetland to a tributary to Lake Erie. Commercial fish tracking software (Echoview) and custom software scripts from Milne Technologies were used to semi‐automate fish count estimates for a small subset of data. Semi‐automated software counts were compared to manual counts of identical data files to assess differences in accuracy, cost, processing time, and counter effort. Semi‐automated fish count estimates using Echoview and custom pre‐ and postprocessing software scripts did not differ from baseline manual counts, suggesting that the semi‐automated count process could be a reliable tool to increase efficiency when processing large DIDSON data sets.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10451","usgsCitation":"Eggleston, M., Milne, S.W., Ramsay, M., and Kowalski, K., 2020, Improved fish counting method accurately quantifies high‐density fish movement in dual‐frequency identification sonar data files from a coastal wetland environment: North American Journal of Fisheries Management, v. 40, no. 4, p. 883-892, https://doi.org/10.1002/nafm.10451.","productDescription":"10 p.","startPage":"883","endPage":"892","ipdsId":"IP-108651","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436893,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CMU62C","text":"USGS data release","linkHelpText":"DIDSON video collection of Coastal Lake Erie Wetland, Lucas Co, Ohio in 2011"},{"id":382918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.59277343749999,\n 40.78054143186033\n ],\n [\n -75.6298828125,\n 40.78054143186033\n ],\n [\n -75.6298828125,\n 49.55372551347579\n ],\n [\n -92.59277343749999,\n 49.55372551347579\n ],\n [\n -92.59277343749999,\n 40.78054143186033\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Eggleston, Michael R. 0000-0003-1068-3290","orcid":"https://orcid.org/0000-0003-1068-3290","contributorId":248759,"corporation":false,"usgs":true,"family":"Eggleston","given":"Michael R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milne, Scott W.","contributorId":248760,"corporation":false,"usgs":false,"family":"Milne","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":40886,"text":"Milne Technologies","active":true,"usgs":false}],"preferred":false,"id":809798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsay, Maxwell","contributorId":248761,"corporation":false,"usgs":false,"family":"Ramsay","given":"Maxwell","email":"","affiliations":[],"preferred":false,"id":809799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208210,"text":"pp1842FF - 2020 - The effects of management practices on grassland birds—Savannah Sparrow (Passerculus sandwichensis)","interactions":[{"subject":{"id":70208210,"text":"pp1842FF - 2020 - The effects of management practices on grassland birds—Savannah Sparrow (Passerculus sandwichensis)","indexId":"pp1842FF","publicationYear":"2020","noYear":false,"chapter":"FF","displayTitle":"The Effects of Management Practices on Grassland Birds—Savannah Sparrow (Passerculus sandwichensis)","title":"The effects of management practices on grassland birds—Savannah Sparrow (Passerculus sandwichensis)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T21:00:19.255841","indexId":"pp1842FF","displayToPublicDate":"2020-07-06T14:59:50","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"FF","displayTitle":"The Effects of Management Practices on Grassland Birds—Savannah Sparrow (Passerculus sandwichensis)","title":"The effects of management practices on grassland birds—Savannah Sparrow (Passerculus sandwichensis)","docAbstract":"Keys to Savannah Sparrow (Passerculus sandwichensis) management are providing extensive grasslands of intermediate height and density with a well-developed litter layer, controlling succession, and protecting nesting habitat from disturbance during the breeding season. Savannah Sparrows have been reported to use habitats with 11–190 centimeters (cm) average vegetation height, 4–50 cm visual obstruction reading (VOR), 15–66 percent grass cover, 4–45 percent forb cover, less than (<) 29 percent shrub cover, <38 percent bare ground, 10–63 percent litter cover, and less than or equal to (≤) 21 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842FF","usgsCitation":"Swanson, D.A., Shaffer, J.A., and Igl, L.D., 2020, The effects of management practices on grassland birds—Savannah Sparrow (Passerculus sandwichensis) (ver. 1.1, May 2023), chap. FF of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 35 p., https://doi.org/10.3133/pp1842FF.","productDescription":"v, 35 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-093915","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":417300,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1842/ff/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":376127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/ff/coverthb2.jpg"},{"id":376128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/ff/pp1842ff.pdf","text":"Report","size":"2.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–FF"}],"edition":"Version 1.0: July 6, 2020; Version 1.1: May 23, 2023","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The Bighorn Basin is a large intermontane sedimentary and structural basin that formed during the Laramide orogeny. The first commercial hydrocarbon production in the Bighorn Basin was established in 1906 from Cretaceous reservoirs at Garland field followed by the discovery of Greybull field in 1907. Since then, many important conventional oil and gas resources have been discovered from reservoirs ranging in age from Cambrian to Tertiary. In addition, a potential continuous (unconventional) basin-centered gas accumulation may be present in Cretaceous reservoirs in the deeper parts of the basin. The maps presented in this report were constructed as part of a project carried out by the U.S. Geological Survey to better characterize the geologic framework of potential undiscovered continuous (unconventional) oil and gas resources of the Niobrara interval of the Upper Cretaceous Cody Shale in the Bighorn Basin in north-central Wyoming and south-central Montana.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3457","usgsCitation":"Finn, T.M., 2020, Structure contour and overburden maps of the Niobrara interval of the Upper Cretaceous Cody Shale in the Bighorn Basin, Wyoming and Montana: U.S. Geological Survey Scientific Investigations Map 3457, scale 1:500,000, 2 sheets, 9 p. pamphlet, https://doi.org/10.3133/sim3457.","productDescription":"Report: iii, 9 p.; 2 Sheets: 30.00 x 26.99 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-111081","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375955,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YEQO6X","text":"USGS data release","linkHelpText":"Tops file for the Niobrara interval of the Upper Cretaceous Cody Shale and associated strata in the Bighorn Basin, Wyoming and Montana"},{"id":375952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3457/sim3457_pamphlet.pdf","text":"Report","size":"2.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3457 Pamphlet"},{"id":375954,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3457/sim3457_sheet2.pdf","text":"Sheet 2—Depth to the Base of the Niobrara Interval of the Upper Cretaceous Cody Shale in the Bighorn Basin, Wyoming and Montana","size":"868 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3457 Sheet 2"},{"id":375953,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3457/sim3457_sheet1.pdf","text":"Sheet 1—Structure Contour Map of the Base of the Niobrara Interval of the Upper Cretaceous Cody Shale in the Bighorn Basin, Wyoming and Montana","size":"928 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3457 Sheet 1"},{"id":375951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3457/coverthb_sheet1.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Big Horn Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.4627685546875,\n 43.40504748787035\n ],\n [\n -107.02880859375,\n 43.75125720420175\n ],\n [\n -107.02331542968749,\n 44.044167353572185\n ],\n [\n -107.5506591796875,\n 44.574817404670306\n ],\n [\n -108.7481689453125,\n 45.213003555993964\n ],\n [\n -109.3743896484375,\n 45.65244828675087\n ],\n [\n -109.632568359375,\n 45.65628792636447\n ],\n [\n -109.7589111328125,\n 45.66012730272194\n ],\n [\n -109.4512939453125,\n 45.31739181570158\n ],\n [\n -109.2041015625,\n 45.24008561090264\n ],\n [\n -109.25354003906249,\n 44.68427737181225\n ],\n [\n -109.18212890625,\n 44.36313311380771\n ],\n [\n -109.248046875,\n 44.10336537791152\n ],\n [\n -108.995361328125,\n 43.84245116699039\n ],\n [\n -108.7646484375,\n 43.61619382369185\n ],\n [\n -107.67150878906249,\n 43.34116005412307\n ],\n [\n -107.4627685546875,\n 43.40504748787035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Contemporary conditions in Lake Michigan where cisco (Coregonus artedi) populations are expanding are vastly different from those encountered by the historic fish community. Invasive species introductions have substantially altered the Lake Michigan ecosystem in the last half century. Successful management efforts for cisco in Lake Michigan hinge on our ability to understand their contemporary ecology, especially diet. We collected 725 cisco stomachs opportunistically from commercial fisheries (2%) and in agency surveys (98%) over six years (2014–2019). The majority (70%) of stomachs were from East Grand Traverse Bay and 96% of these were collected at Elk Rapids. Additional samples were collected from Charlevoix (8%), Little Traverse Bay (11%), other sites in northern Lake Michigan (4%), Central Lake Michigan (6%), and Green Bay (1%). Our results indicated a high degree of piscivory, in contrast to historical and contemporary accounts of planktivory for cisco in the other Laurentian Great Lakes. The top three prey items by mass were not native to the Great Lakes and these accounted for 87% of all observed prey mass consumed: round goby (Neogobius melanostomus) (58%), Bythotrephes longimanus (15%), and alewife (Alosa pseudoharengus) (14%). Round goby dominated the prey in the spring and summer, while B. longimanus and alewife occurred more in summer and fall diets. The contemporary population of cisco in Lake Michigan has been able to uniquely capitalize on abundant invasive prey resources, which may be less limiting and more energy-rich than a more typical planktivorous cisco diet.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.06.013","usgsCitation":"Breaker, B.S., Pangle, K.L., Donner, K., Smith, J., Turschak, B.A., Claramunt, R.M., Bunnell, D.B., and Jonas, J.L., 2020, Piscivory in recovering Lake Michigan Cisco (Coregonus artedi): The role of invasive species: Journal of Great Lakes Research, v. 46, no. 5, p. 1402-1411, https://doi.org/10.1016/j.jglr.2020.06.013.","productDescription":"10 p.","startPage":"1402","endPage":"1411","ipdsId":"IP-113329","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":376905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.41796875,\n 42.13082130188809\n ],\n [\n -84.68261718749999,\n 42.13082130188809\n ],\n [\n -84.68261718749999,\n 46.195042108660154\n ],\n [\n -88.41796875,\n 46.195042108660154\n ],\n [\n -88.41796875,\n 42.13082130188809\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Breaker, Ben S","contributorId":236853,"corporation":false,"usgs":false,"family":"Breaker","given":"Ben","email":"","middleInitial":"S","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":794481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pangle, Kevin L.","contributorId":205579,"corporation":false,"usgs":false,"family":"Pangle","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":37116,"text":"Department of Biology, Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":794482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donner, Kevin","contributorId":190499,"corporation":false,"usgs":false,"family":"Donner","given":"Kevin","affiliations":[{"id":33110,"text":"Little Traverse Bay Bands of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":794483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Jason","contributorId":215444,"corporation":false,"usgs":false,"family":"Smith","given":"Jason","affiliations":[{"id":39249,"text":"Little Traverse Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":794484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turschak, Benjamin A.","contributorId":150497,"corporation":false,"usgs":false,"family":"Turschak","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":true,"id":794485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Claramunt, Randall M.","contributorId":190497,"corporation":false,"usgs":false,"family":"Claramunt","given":"Randall","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":794486,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bunnell, David B. 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216540,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794487,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jonas, Jory L.","contributorId":215449,"corporation":false,"usgs":false,"family":"Jonas","given":"Jory","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":794488,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210956,"text":"70210956 - 2020 - Accidental chlorophacinone exposure of lactating ewes: Clinical follow-up and human health dietary implications","interactions":[],"lastModifiedDate":"2020-08-04T14:22:37.376039","indexId":"70210956","displayToPublicDate":"2020-07-06T10:25:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1685,"text":"Food and Chemical Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Accidental chlorophacinone exposure of lactating ewes: Clinical follow-up and human health dietary implications","docAbstract":"Anticoagulant rodenticides are widely used for rodent control in agricultural and urban settings. Their intense use can sometimes result in accidental exposure and even poisoning of livestock. Can milk, eggs or meat derived from such accidentally exposed animals be consumed by humans? Data on the pharmacokinetics of chlorophacinone in milk of accidentally exposed ewes were used to estimate the risk associated with its consumption. Three days after accidental ingestion, chlorophacinone was detected in plasma of 18 ewes, with concentrations exceeding 100 ng/mL in 11 animals. Chlorophacinone was detected in milk on day 2 post-exposure and remained quantifiable for at least 7 days in milk of these 11 ewes. Concentrations in milk were much lower than in plasma and decreased quickly (mean half-life of 2 days). This study demonstrated dose-dependent mammary transfer of ingested chlorophacinone. Variation in prothrombin time (PT) on Day 3 suggested that some of the ewes that ingested chlorophacinone may have been adversely affected, but PT did not facilitate estimation of the quantity of chlorophacinone consumed. Using safety factors described in the literature, consumption of dairy products derived from these ewes after a one-week withdrawal period would pose low risk to consumers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fct.2020.111518","usgsCitation":"Moriceau, M., Lefebvre, S., Fourel, I., Benoit, E., Rattner, B.A., and Lattard, V., 2020, Accidental chlorophacinone exposure of lactating ewes: Clinical follow-up and human health dietary implications: Food and Chemical Toxicology, v. 143, 111518, 8 p., https://doi.org/10.1016/j.fct.2020.111518.","productDescription":"111518, 8 p.","ipdsId":"IP-117861","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":456122,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-02896032","text":"External Repository"},{"id":376204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France","otherGeospatial":"Creuse","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":792343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fourel, Isabelle","contributorId":228856,"corporation":false,"usgs":false,"family":"Fourel","given":"Isabelle","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":792344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benoit, Etienne","contributorId":228857,"corporation":false,"usgs":false,"family":"Benoit","given":"Etienne","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":792345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":792346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lattard, Virginie","contributorId":228858,"corporation":false,"usgs":false,"family":"Lattard","given":"Virginie","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":792347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211284,"text":"70211284 - 2020 - The role of warm, dry summers and variation in snowpack on phytoplankton dynamics in high-elevation lakes","interactions":[],"lastModifiedDate":"2020-10-12T17:06:21.880134","indexId":"70211284","displayToPublicDate":"2020-07-06T10:20:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The role of warm, dry summers and variation in snowpack on phytoplankton dynamics in high-elevation lakes","docAbstract":"Abstract\nClimate change is altering biogeochemical, metabolic, and ecological functions in lakes across the globe. Historically, mountain lakes in temperate regions have been unproductive due to brief ice-free seasons, a snowmelt-driven hydrograph, cold temperatures, and steep topography with low vegetation and soil cover. We tested the relative importance of winter and summer weather, watershed characteristics, and water chemistry as drivers of phytoplankton dynamics. Using boosted regression tree models for 28 mountain lakes in Colorado we examined regional, intra-seasonal, and inter-annual drivers of variability in chlorophyll a as a proxy for lake phytoplankton. Phytoplankton biomass was inversely related to the maximum snow water equivalent (SWE) of the previous winter, as others have found. However, even in years with average SWE, summer precipitation extremes and warming enhanced phytoplankton biomass. Peak seasonal phytoplankton biomass coincided with the warmest water temperatures and lowest nitrogen-to-phosphorus ratios. While links between snowpack, lake temperature, nutrients, and organic matter dynamics are increasingly recognized as critical drivers of change in high elevation lakes, our results highlight the additional influence of summer conditions on lake productivity in response to ongoing changes in climate. Continued changes in the timing, type, and magnitude of precipitation in combination with other global change drivers (e.g., nutrient deposition) will affect production in mountain lakes, potentially shifting these historically oligotrophic lakes toward new ecosystem states. Ultimately, a deeper understanding of these drivers and pattern at multiple scales will allow us to better anticipate ecological consequences of global change.","language":"English","publisher":"Wiley","doi":"10.1002/ecy.3132","usgsCitation":"Oleksy, I., Beck, W., Lammers, R., Steger, C., Wilson, C., Christensen, K., Vincent, K., Johnson, P., and Baron, J., 2020, The role of warm, dry summers and variation in snowpack on phytoplankton dynamics in high-elevation lakes: Ecology, v. 101, no. 10, e03132, 12 p., https://doi.org/10.1002/ecy.3132.","productDescription":"e03132, 12 p.","ipdsId":"IP-114262","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456124,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3132","text":"Publisher Index Page"},{"id":376637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Front Range of the Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.84228515625,\n 39.98132938627215\n ],\n [\n -105.01281738281249,\n 39.98132938627215\n ],\n [\n -105.01281738281249,\n 40.65563874006118\n ],\n [\n -105.84228515625,\n 40.65563874006118\n ],\n [\n -105.84228515625,\n 39.98132938627215\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Oleksy, Isabella A.","contributorId":229538,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella A.","affiliations":[{"id":33412,"text":"Cary Institute for Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":793504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Whitney","contributorId":229539,"corporation":false,"usgs":false,"family":"Beck","given":"Whitney","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":793505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lammers, R.","contributorId":229540,"corporation":false,"usgs":false,"family":"Lammers","given":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steger, Cara","contributorId":229541,"corporation":false,"usgs":false,"family":"Steger","given":"Cara","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Cody","contributorId":229542,"corporation":false,"usgs":false,"family":"Wilson","given":"Cody","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793508,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Christensen, Kyle","contributorId":229543,"corporation":false,"usgs":false,"family":"Christensen","given":"Kyle","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793509,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vincent, Kim","contributorId":229544,"corporation":false,"usgs":false,"family":"Vincent","given":"Kim","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":793510,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Pieter","contributorId":229545,"corporation":false,"usgs":false,"family":"Johnson","given":"Pieter","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":793511,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baron, Jill 0000-0002-5902-6241 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6241","contributorId":222907,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":793512,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211293,"text":"70211293 - 2020 - Dating silica sinter (geyserite): A cautionary tale","interactions":[],"lastModifiedDate":"2020-07-22T14:40:18.175529","indexId":"70211293","displayToPublicDate":"2020-07-06T09:37:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Dating silica sinter (geyserite): A cautionary tale","docAbstract":"We describe a new effort to date hydrothermal silica sinter deposits (geyserite) from the Upper Geyser Basin of Yellowstone National Park using 14C of co-deposited organic matter, U-series and cosmogenic 10Be methods. A majority of the samples were collected from stratigraphic sections, mainly at Riverside, Giant, and Castle Geysers. Ages obtained from 41 14C analyses range from modern to 12.1 cal ka BP. Nearly all the 14C ages show inconsistencies with their stratigraphic positions, and several replicate 14C analyses from the same sample result in significantly different ages. The δ13C values of the organic material in the sinter range from -26.6‰ to -12.7‰. The more enriched values are attributed to microbial fixation of dissolved inorganic carbon (DIC), which has heavier δ13C values and is 14C-depleted relative to atmospheric CO2, leading to apparent older ages. U-series analyses on 4 samples yielded ages between 2.2 and 7.4 ka. Large 230Th/U age uncertainties in the sinter, due to low uranium concentrations along with elevated 232Th and associated initial 230Th, make these ages imprecise for use on Holocene deposits. A single cosmogenic 10Be exposure age of 596±18 ka is considerably older than the age of underlying rhyolite and is thus unreliable. This apparent old age results from contamination by meteoric 10Be trapped in the opal that overprints the very small amount of cosmogenic 10Be. By presenting the problems we encountered and discussing their probable cause, this paper highlights the difficulty in obtaining reliable, high-precision geochronological data necessary to use sinter deposits as paleoenvironmental and paleo-hydrothermal archives.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2020.106991","usgsCitation":"Churchill, D.M., Manga, M., Hurwitz, S., Peek, S., Licciardi, J., and Paces, J.B., 2020, Dating silica sinter (geyserite): A cautionary tale: Journal of Volcanology and Geothermal Research, v. 402, 106991, 12 p., https://doi.org/10.1016/j.jvolgeores.2020.106991.","productDescription":"106991, 12 p.","ipdsId":"IP-119376","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":376631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.060791015625,\n 43.88205730390537\n ],\n [\n -109.3304443359375,\n 43.88205730390537\n ],\n [\n -109.3304443359375,\n 44.999767019181284\n ],\n [\n -111.060791015625,\n 44.999767019181284\n ],\n [\n -111.060791015625,\n 43.88205730390537\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"402","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Churchill, Dakota M.","contributorId":229593,"corporation":false,"usgs":false,"family":"Churchill","given":"Dakota","email":"","middleInitial":"M.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":793593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael","contributorId":229594,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":793594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":793595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":793596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Licciardi, Joseph","contributorId":229595,"corporation":false,"usgs":false,"family":"Licciardi","given":"Joseph","affiliations":[{"id":41689,"text":"U. New Hampshire","active":true,"usgs":false}],"preferred":false,"id":793597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":215864,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":793598,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211541,"text":"70211541 - 2020 - Hydrologic modeling to examine the influence of the forestry reclamation approach and climate change on mineland hydrology","interactions":[],"lastModifiedDate":"2020-07-30T15:25:29.367702","indexId":"70211541","displayToPublicDate":"2020-07-05T10:18:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic modeling to examine the influence of the forestry reclamation approach and climate change on mineland hydrology","docAbstract":"Forests in the Appalachian region of the U.S. are threatened by a variety of short- and long-term pressures, including climate change, invasive species, and resource extraction. Surface mining for coal is one of the most important drivers of land-use change in the region, reducing native forest cover, causing forest fragmentation, eliminating intact soil, and affecting water resources. The Forestry Reclamation Approach (FRA) has been demonstrated as a successful best practice for restoring forests on mine-impacted landscapes, but little information exists on how the practice will affect hydrologic processes. A study was initiated to examine soil-water movement, as in-situ saturated hydraulic conductivity (Ksat), combined with soil porosity to quantify the potential influence on streamflow of reclaimed mines relative to an unmined, forested control site in eastern Kentucky. We compared different reclamation techniques and time since reclamation to determine the extent to which hydrologic function can be restored. We also simulated evapotranspiration at the watershed scale as a function of reclamation technique for both historical and projected (2050) climate. Results indicate that conventional grassland reclamation critically changes how soil water transitions to streamflow, primarily due to Ksat variability that exceeds that measured for intact and FRA soils. Sites reclaimed using FRA exhibited a soil-water environment that was more similar to the unmined control. However, all reclaimed mine soils were thinner, retained and stored less soil water, and thus could provide less plant-available water during the growing season. The plant-available water stored in reclaimed landscapes may not be sufficient to support forest health and this is exacerbated by projected climate conditions. However, soil development under a combination of FRA techniques has the potential to mitigate this limitation.
Aerial application of management tools can provide a cost‐effective means to conserve or control wildlife populations at the landscape scale. Large spatial scales, however, present difficulties when assessing in situ reliability and integrity of the devices themselves. We demonstrate application of a distance‐sampling density estimation approach to assess the performance of a newly developed toxicant bait system for the control of invasive brown treesnakes (Boiga irregularis). Bait cartridges were designed to open in flight to expose the toxicant‐laced bait and tangle in the forest canopy via a plastic ribbon component. Following application of 12,686 bait cartridges from an automated aerial delivery system over a 55‐ha site on Guam, USA, we employed distance sampling techniques to evaluate cartridge performance. We performed 22 line‐transect surveys for a total distance of 10.3 km, during which we recorded all observations of unopened bait cartridges, instances in which the ribbon did not remain attached to the cartridge capsule (i.e., ribbon failure), and carcasses of brown treesnakes and nontarget species. Too few undeployed bait cartridges (n = 6), brown treesnake carcasses (n = 1), or nontarget carcasses (n = 0) were observed during surveys to support additional analysis. We detected 299 instances of ribbon failure. Using standard distance‐sampling analyses, we estimate that ribbon failure occurred in 3,376 ± 351 (estimate ± SE; 95% CL = 2,746–4,150) cartridges or 21.6–32.7% of the total applied. Our results demonstrate the utility of distance‐sampling density estimation techniques to validate performance and reliability of aerially applied management tools.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.1106","usgsCitation":"Goetz, S.M., Yackel Adams, A.A., and Siers, S.S., 2020, Validating deployment of aerially delivered toxic bait cartridges for control of invasive brown treesnakes: Wildlife Society Bulletin, v. 44, no. 3, p. 617-622, https://doi.org/10.1002/wsb.1106.","productDescription":"6 p.","startPage":"617","endPage":"622","ipdsId":"IP-111498","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456130,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1106","text":"Publisher Index Page"},{"id":436896,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JWLL91","text":"USGS data release","linkHelpText":"Failed Brown Treesnake bait cartridges from an aerially application in Guam, 2018"},{"id":376256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.57733154296875,\n 13.199838554004245\n ],\n [\n 144.98931884765625,\n 13.199838554004245\n ],\n [\n 144.98931884765625,\n 13.675344552820276\n ],\n [\n 144.57733154296875,\n 13.675344552820276\n ],\n [\n 144.57733154296875,\n 13.199838554004245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Goetz, Scott Michael 0000-0002-8705-5316","orcid":"https://orcid.org/0000-0002-8705-5316","contributorId":228868,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":792360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":792361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Siers, Shane S","contributorId":228869,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"S","affiliations":[{"id":41523,"text":"USDA NWRC","active":true,"usgs":false}],"preferred":false,"id":792362,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}