Recently reported detrital zircon (DZ) data help to associate the Paleogene strata of the Gulf of Mexico region to various provenance areas. By far, recent work has emphasised upper Paleocene-lower Eocene and upper Oligocene strata that were deposited during the two episodes of the highest sediment supply in the Paleogene. The data reveal a dynamic drainage history, including (1) initial routing of western Cordilleran drainages towards the Gulf of Mexico in the Paleocene, (2) an eastward shift of the western continental divide, from the Jura-Cretaceous cordilleran arc to the eastern edge of the Laramide province after the Paleocene and (3) a southward shift, along the eastern Laramide province, of the headwaters of river systems draining to the Mississippi and Houston embayments at some time between the early Eocene and Oligocene. However, DZ characterisation of most (~20 Myr) of the middle Eocene-lower Oligocene section remains limited. We present 60 DZ age spectra, most of which are from the middle or upper Eocene outcrop belts, with 50–200-km spacing. We define six to eight distinct groups of DZ age spectra for middle and upper Eocene strata. Data from this and other studies resolve at least six substantial temporal changes in age spectra at various positions along the continental margin. The evolving age spectra constrain the middle and upper Eocene drainage patterns of large parts of interior North America. The most well-resolved aspects of these drainage patterns include (1) persistent rivers that flowed from erosional landscapes across the Paleozoic Appalachian orogen either into the low-lying Mississippi embayment or directly into the eastern Gulf; (2) at least during marine regressions, a trunk channel that likely flowed southward along the axial part of Mississippi Embayment and integrated tributaries from the east and west; and (3) rivers that flowed to the Houston embayment in the middle Eocene that likely originated in the Laramide province in central Colorado and southern Wyoming, as Precambrian basement highs in those source areas were being unroofed.
The migration of larval fish from spawning to rearing habitat in rivers is not well understood. This paper describes a methodology to predict larval drift using a Lagrangian particle-tracking (LPT) model with passive and active behavioural components loosely coupled to a quasi-three-dimensional hydraulic model. In the absence of measured larval drift, a heuristic approach is presented for the larval drift of two species of interest, white sturgeon (Acipenser transmontanus) and burbot (Lota lota), in the Kootenai River, Idaho. Previous studies found that many fish species prefer certain vertical zones within the water column; sturgeon tend to be found near the bottom and burbot close to the water surface. Limiting the vertical movement of larvae is incorporated into the active component of the LPT model. The results illustrate a pattern of drift where secondary flow in meander bends and other zones of flow curvature redistributes particles toward the outside of the bend for surface drifters and toward the inside of the bend for bottom drifters. This pattern periodically reinforces the intersection of drifting larvae with channel margins in meander bends. In the absence of measured larval drift data, the model provides a tool for hypothesis testing and a guide to both field and laboratory experiments to further define the role of active behaviour in drifting larvae.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2019.1709102","usgsCitation":"McDonald, R.R., and Nelson, J.M., 2021, A Lagrangian particle-tracking approach to modelling larval drift in rivers: Journal of Ecohydraulics, v. 6, no. 1, p. 17-35, https://doi.org/10.1080/24705357.2019.1709102.","productDescription":"19 p.","startPage":"17","endPage":"35","ipdsId":"IP-102070","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":502662,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":436681,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K1U4O0","text":"USGS data release","linkHelpText":"fluvial-particle, U.S. Geological Survey software release"},{"id":415416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.1478357988205,\n 48.69782150172384\n ],\n [\n -116.12731836897655,\n 48.73211652626813\n ],\n [\n -116.32565352413204,\n 48.71948423713994\n ],\n [\n -116.34753878263186,\n 48.78261395455223\n ],\n [\n -116.35574575456924,\n 48.936497382156176\n ],\n [\n -116.41319455813164,\n 48.99935415693781\n ],\n [\n -116.58964445478699,\n 49.00025153683018\n ],\n [\n -116.55544873838093,\n 48.94907507626053\n ],\n [\n -116.45012593185005,\n 48.894249080754236\n ],\n [\n -116.43644764528761,\n 48.82135431506677\n ],\n [\n -116.4255050160379,\n 48.72038664873716\n ],\n [\n -116.33112483875708,\n 48.669826665231625\n ],\n [\n -116.1478357988205,\n 48.69782150172384\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868973,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223732,"text":"70223732 - 2021 - Factors influencing Cinnamon Teal nest attendance patterns","interactions":[],"lastModifiedDate":"2021-09-07T13:22:44.296825","indexId":"70223732","displayToPublicDate":"2020-04-18T07:38:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing Cinnamon Teal nest attendance patterns","docAbstract":"Patterns of nest attendance in birds result from complex behaviours and influence the success of reproductive events. Incubation behaviours vary based on individual body condition, energy requirements and environmental factors. We assessed nest attendance patterns in Cinnamon Teal Spatula cyanoptera breeding in the San Luis Valley of Colorado in 2016–2017 using trail and video cameras to observe behaviours throughout incubation. We evaluated the effect of temporal, life-history and environmental covariates on the frequency and duration of incubation recesses as well as the incubation constancy. There was considerable model uncertainty among the models used to evaluate recess frequency. Recess duration varied according to the interaction between nest age and a quadratic effect of time of day, with hens on older nests taking longer recesses in the afternoon and hens on nests earlier in incubation taking longer recesses in the morning and evening. Incubation constancy decreased with higher ambient temperatures in the study area. This study provides evidence that Cinnamon Teal modify their behaviour during incubation according to the age of the nest and the time of day. These results improve our knowledge of Cinnamon Teal breeding ecology and shed light on the behaviours that fast-lived species may use to cope with environmental factors during nesting.
Spatial information on the distribution of ecosystem patterns and processes can be a critical component of designing and implementing effective management programs in river‐floodplain ecosystems. For example, translating how flood pulses detected within a stream gauge record are spatially manifested across a river‐valley bottom can be used to evaluate whether the current distribution of physical conditions has the potential to support priority habitats or if intervention is needed to meet desired goals. The size and complexity of large river‐floodplain systems can make mapping inundation dynamics a challenging task. We used a geospatial model to simulate 40 years (1972–2011) of daily surface‐water inundation depths for 11,331 km2 of the Upper Mississippi River System floodplain. We identified discrete inundation events at each 4‐m × 4‐m pixel in the model as sequential days of submergence. We then quantified and mapped four aspects of inundation regime – event frequency, duration, magnitude, and timing – for each pixel. The spatial distribution of inundation regime attributes varied within and among multiple levels of river organization, including navigation pools and geomorphic reaches, but only event timing exhibited a strong down‐river trend. Non‐linear relations among inundation attributes and their geospatial distributions likely reflect complex interactions among topographic, hydrologic, and anthropogenic constraints on flooding dynamics. Together, our results reveal spatial gradients in inundation dynamics not captured by hydrologic data alone. Characterizing such diversity in inundation dynamics is important for testing hypotheses about ecological processes, developing models of ecosystem functions, and informing management actions.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3628","usgsCitation":"Van Appledorn, M., De Jager, N.R., and Rohweder, J.J., 2021, Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications: River Research and Applications, v. 37, no. 2, p. 241-255, https://doi.org/10.1002/rra.3628.","productDescription":"15 p.","startPage":"241","endPage":"255","ipdsId":"IP-113745","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":383139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.3955078125,\n 38.51378825951165\n ],\n [\n -88.154296875,\n 40.245991504199026\n ],\n [\n -86.572265625,\n 41.07935114946899\n ],\n [\n -86.7919921875,\n 41.50857729743935\n ],\n [\n -88.0224609375,\n 42.45588764197166\n ],\n [\n -89.3408203125,\n 44.213709909702054\n ],\n [\n -91.7578125,\n 45.85941212790755\n ],\n [\n -92.63671875,\n 46.195042108660154\n ],\n [\n -92.59277343749999,\n 47.724544549099676\n ],\n [\n -94.8779296875,\n 47.249406957888446\n ],\n [\n -95.9326171875,\n 47.30903424774781\n ],\n [\n -95.4052734375,\n 44.84029065139799\n ],\n [\n -93.6474609375,\n 42.13082130188811\n ],\n [\n -93.515625,\n 39.605688178320804\n ],\n [\n -90.3955078125,\n 38.51378825951165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218476,"text":"70218476 - 2021 - Using decision analysis to collaboratively respond to invasive species threats: A case study of Lake Erie grass carp (Ctenopharyngodon idella)","interactions":[],"lastModifiedDate":"2021-03-01T15:28:00.787039","indexId":"70218476","displayToPublicDate":"2020-04-15T09:20:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using decision analysis to collaboratively respond to invasive species threats: A case study of Lake Erie grass carp (Ctenopharyngodon idella)","title":"Using decision analysis to collaboratively respond to invasive species threats: A case study of Lake Erie grass carp (Ctenopharyngodon idella)","docAbstract":"Decisions about invasive species control and eradication can be difficult because of uncertainty in population demographics, movement ecology, and effectiveness of potential response actions. These decisions often include multiple stakeholders and management entities with potentially different objectives, management priorities, and jurisdictional authority. We provide a case study of using multi-party, collaborative decision analysis to aid decision makers in determining objectives and control actions for invasive grass carp (Ctenopharyngodon idella) in Lake Erie. Creating this process required binational (Canada-United States) and multi-state/provincial collaboration to craft a shared problem statement, establish objectives related to ecological, economic, and social concerns, determine potential response actions, and evaluate consequences and tradeoffs of these actions. We used participatory modeling and expert elicitation to evaluate the effectiveness of control scenarios that varied in action type (i.e., removal efforts and spawning barriers) and the temporal and spatial application of these actions. Using a matrix population model parameterized for western Lake Erie grass carp, we found that removal efforts concentrated in areas of high catchability, when paired with a spawning barrier on the Sandusky River, Ohio, USA, could effectively control grass carp in Lake Erie, if all assumptions are met. We determined a set of key uncertainties regarding gear catchability and current population size that have led to the transition to an adaptive management process. In addition, our work formed the basis for grass carp management plans for the states of Michigan and Ohio and has provided a means for collaboration among agencies for effective application of control efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.03.018","usgsCitation":"Robinson, K., DuFour, M.R., Jones, M., Herbst, S., Newcomb, T., Boase, J., Brenden, T.O., Chapman, D., Dettmers, J.M., Francis, J., Hartman, T., Kocovsky, P., Locke, B., Tyson, J., and Mayer, C., 2021, Using decision analysis to collaboratively respond to invasive species threats: A case study of Lake Erie grass carp (Ctenopharyngodon idella): Journal of Great Lakes Research, v. 47, no. 1, p. 108-119, https://doi.org/10.1016/j.jglr.2020.03.018.","productDescription":"12 p.","startPage":"108","endPage":"119","ipdsId":"IP-111132","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":383686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Ohio","otherGeospatial":"Lake Erie, Maumee River, River Raisin, Sandusky River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.73779296875,\n 41.290189955885644\n ],\n [\n -82.430419921875,\n 41.290189955885644\n ],\n [\n -82.430419921875,\n 42.07783959017503\n ],\n [\n -83.73779296875,\n 42.07783959017503\n ],\n [\n -83.73779296875,\n 41.290189955885644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kelly F.","contributorId":140157,"corporation":false,"usgs":false,"family":"Robinson","given":"Kelly F.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false},{"id":13267,"text":"Warnell School of Forestry and Natural Resources, University of Georgia","active":true,"usgs":false},{"id":473,"text":"New York Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":811138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuFour, Mark R.","contributorId":203270,"corporation":false,"usgs":false,"family":"DuFour","given":"Mark","email":"","middleInitial":"R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":811139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, M.W.","contributorId":239977,"corporation":false,"usgs":false,"family":"Jones","given":"M.W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":811140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herbst, Seth","contributorId":252926,"corporation":false,"usgs":false,"family":"Herbst","given":"Seth","affiliations":[{"id":50471,"text":"Michigan Department of Natural Resources, Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":811141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newcomb, Tammy","contributorId":252928,"corporation":false,"usgs":false,"family":"Newcomb","given":"Tammy","affiliations":[{"id":50471,"text":"Michigan Department of Natural Resources, Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":811142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boase, James C.","contributorId":38077,"corporation":false,"usgs":false,"family":"Boase","given":"James C.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":811143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brenden, Travis O.","contributorId":126759,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis","email":"","middleInitial":"O.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":811144,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":811145,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":811146,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Francis, James","contributorId":252929,"corporation":false,"usgs":false,"family":"Francis","given":"James","affiliations":[{"id":50473,"text":"Michigan Department of Natural Resources, Fisheries Division, Waterford Field Office, Waterford, MI","active":true,"usgs":false}],"preferred":false,"id":811147,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hartman, Travis","contributorId":66583,"corporation":false,"usgs":true,"family":"Hartman","given":"Travis","affiliations":[],"preferred":false,"id":811191,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":811148,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Locke, Brian","contributorId":252930,"corporation":false,"usgs":false,"family":"Locke","given":"Brian","affiliations":[{"id":50474,"text":"Ontario Ministry of Natural Resources and Forestry, Lake Erie Management Unit, Wheatley, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":811149,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tyson, Jeff","contributorId":147298,"corporation":false,"usgs":false,"family":"Tyson","given":"Jeff","affiliations":[],"preferred":false,"id":811151,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mayer, Christine","contributorId":237769,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","affiliations":[{"id":47604,"text":"University of Toledo, Lake Erie Center","active":true,"usgs":false}],"preferred":false,"id":811150,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70210111,"text":"70210111 - 2021 - Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","interactions":[],"lastModifiedDate":"2021-02-17T22:21:56.760044","indexId":"70210111","displayToPublicDate":"2020-04-06T11:01:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","docAbstract":"Studies integrating mangrove in-situ observations and remote sensing analysis for specific sites often lack precise estimates of carbon stocks over time frames that include disturbance events. This study quantifies change in mangrove area from 1985 to 2018 with Landsat time series analysis, estimates above and belowground stored carbon using field data, and evaluates aboveground carbon stock changes after the 2004 Category 4, Hurricane Charley, in J.N. “Ding” Darling National Wildlife Refuge. Two allometric equation methods yielding similar results were used to estimate aboveground carbon content in three mangrove species found in the refuge. Aboveground carbon contained 67 (SE = 2) MgC ha−1 with a total refuge estimate of 74,504 MgC in 2018. Sediment contained 259 (SE = 28) MgC ha−1 for a total of 288,008 MgC in the refuge. The initial reduction in mangrove area caused by Hurricane Charley was between 0.6% and 5.3%, equivalent to between 427 MgC and 3,599 MgC under three different scenarios of carbon loss. As a result of the hurricane, approximately 61 ha of mangroves were disturbed, of which 24 ha had recovered by 2018, with 37 ha (~3% of the pre-hurricane mangrove area) still not recovered 14 years after the event. The 37 ha of mangroves that have not recovered are located in a tidally restricted area of the refuge. A longer recovery time in this area will likely result in a greater loss of carbon storage than in the rest of the refuge.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2020.106750","usgsCitation":"Peneva-Reed, E.I., Krauss, K., Bullock, E.L., Zhu, Z., Woltz, V., Drexler, J.Z., Conrad, J.R., and Stehman, S.V., 2021, Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida: Estuarine, Coastal and Shelf Science, v. 248, 106750, 13 p., https://doi.org/10.1016/j.ecss.2020.106750.","productDescription":"106750, 13 p.","ipdsId":"IP-111057","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":374829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"J.N. “Ding” Darling National Wildlife Refuge, Sanibel Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.16949462890624,\n 26.434609799691536\n ],\n [\n -82.0513916015625,\n 26.434609799691536\n ],\n [\n -82.0513916015625,\n 26.49577131935652\n ],\n [\n -82.16949462890624,\n 26.49577131935652\n ],\n [\n -82.16949462890624,\n 26.434609799691536\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peneva-Reed, Elitsa I. 0000-0002-4570-4701","orcid":"https://orcid.org/0000-0002-4570-4701","contributorId":202809,"corporation":false,"usgs":true,"family":"Peneva-Reed","given":"Elitsa","email":"","middleInitial":"I.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":789169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bullock, Eric L. 0000-0003-3279-6771","orcid":"https://orcid.org/0000-0003-3279-6771","contributorId":224710,"corporation":false,"usgs":false,"family":"Bullock","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40922,"text":"Department of Earth & Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":789171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":789172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woltz, Victoria 0000-0001-7843-6486","orcid":"https://orcid.org/0000-0001-7843-6486","contributorId":223011,"corporation":false,"usgs":true,"family":"Woltz","given":"Victoria","email":"","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":789174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, Jeremy R.","contributorId":149347,"corporation":false,"usgs":false,"family":"Conrad","given":"Jeremy","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":789175,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":789176,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216167,"text":"70216167 - 2021 - Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques","interactions":[],"lastModifiedDate":"2021-11-01T14:41:49.052895","indexId":"70216167","displayToPublicDate":"2020-04-01T09:21:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2375,"text":"Journal of Maps","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques","docAbstract":"Increasing urbanization and suburban growth in cities globally has highlighted the importance of land planning using detailed geomorphologic maps that depict anthropogenic landform changes. Such mapping provides information crucial for land management, hazard identification, and the management of the challenges arising from urbanization. The development and use of quantitative and repeatable methods to map anthropogenic and natural processes are required to advance the science of urban geomorphological mapping. This study investigated the application of geospatial modeling, structure-from-motion (SfM) photogrammetric methods and DEM differencing as means of quantifying anthropogenic landform changes from archival aerial imagery. Anthropogenic landforms were incorporated into a detailed geomorphologic map in an urbanizing watershed located in the Washington, D.C. metropolitan suburb of Vienna, Virginia.
The Jinsha River, which comprises the upper reaches of the Yangtze River, has among the highest freshwater fish biodiversity and endemism in China, but these characteristics have rarely been quantitatively evaluated at the basin scale. We used fish presence–absence data collected from the entire Jinsha River basin (JRB) from 1964 to 2017 to determine patterns in fish biodiversity. In total, 229 freshwater fish species from 9 orders, 26 families, and 110 genera were recorded. Of these species, 161 were endemic to China, with 94 species being endemic to the Yangtze River basin, and 39 species were threatened. Fish species richness was higher in the downstream river reaches and was higher in the main stem than in the tributaries. Overfishing, water pollution, and dam construction have been threatening fish diversity in the JRB for several decades. Conservation strategies similar to those used in North America may be applicable to the JRB to help protect native fishes in this important river basin. Such strategies include (1) assessment of several tributaries as fish reserves; (2) regular adjustment of turbine operations during the fish spawning period; and (3) regulation of the many co-occurring human stressors in the JRB.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10441","usgsCitation":"Liu, H.W., Guo, C., Qu, X., Xiong, F., Paukert, C.P., Chen, Y., and Sullivan, W., 2021, Fish diversity, endemism, threats, and conservation in the Jinsha River basin (upper Yangtze River), China: North American Journal of Fisheries Management, v. 41, no. 4, p. 967-984, https://doi.org/10.1002/nafm.10441.","productDescription":"18 p.","startPage":"967","endPage":"984","ipdsId":"IP-113887","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Jinsha River Basin (Upper Yangtze River)","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 90.5,\n 24.6\n ],\n [\n 105.25,\n 24.6\n ],\n [\n 105.25,\n 35.7333\n ],\n [\n 90.5,\n 35.7333\n ],\n [\n 90.5,\n 24.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, H. W.","contributorId":152164,"corporation":false,"usgs":false,"family":"Liu","given":"H.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":835337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, C.","contributorId":272911,"corporation":false,"usgs":false,"family":"Guo","given":"C.","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qu, X.","contributorId":279670,"corporation":false,"usgs":false,"family":"Qu","given":"X.","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiong, F.","contributorId":279671,"corporation":false,"usgs":false,"family":"Xiong","given":"F.","affiliations":[{"id":57334,"text":"http://orcid.org/0000-0002-9369-8545","active":true,"usgs":false}],"preferred":false,"id":835340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Y.","contributorId":272912,"corporation":false,"usgs":false,"family":"Chen","given":"Y.","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sullivan, W.","contributorId":156266,"corporation":false,"usgs":false,"family":"Sullivan","given":"W.","affiliations":[],"preferred":false,"id":835343,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224613,"text":"70224613 - 2021 - Units recovery methods in compositional data analysis","interactions":[],"lastModifiedDate":"2021-09-30T11:55:22.832759","indexId":"70224613","displayToPublicDate":"2020-03-24T06:52:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Units recovery methods in compositional data analysis","docAbstract":"Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.
In an effort to determine contaminant presence, concentrations, and movement from a low‐level radioactive waste (LLRW) burial disposal site to ecosystems in the surrounding area, a study was developed to assess concentrations of per‐ and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), and tritium. To complete this assessment small mammals, vegetation, soil, and insect samples were collected from areas within and adjacent to the Beatty, Nevada, LLRW site and from a reference area located approximately 3 km south of the LLRW site. Samples underwent analysis via liquid chromatography tandem mass spectrometry, gas chromatography mass spectrometry, or scintillation spectroscopy depending on the analyte of interest. Small mammal tissues showed maximum concentrations of over 1700 ng/g for PFAS, 1600 ng/g for PCBs, and 10 000 Bq/kg for tritium. The primary contaminants found in soil samples were PCBs, with maximum concentrations exceeding 25 ng/g. Trace amounts of PFAS were also detected in soils and insects. Only qualitative data were obtained from vegetation samples because of the complex matrix of the dominant plant species (creosote bush; Larrea tridentata [Sessé & Moc. ex DC.] Coville). Overall, these data indicate the presence of various anthropogenic contaminants in the ecosystem surrounding the LLRW area, but additional analyses are necessary to confirm the sources and migration pathways of PFAS and PCBs in this hyperarid environment. Environ Toxicol Chem 2020;00:1–8. © 2020 SETAC
Ecologists have a limited understanding of the rangewide variation in movement behavior in freshwater fishes, but recent expansion of biotelemetry allows biologists to investigate how fish movement can help to predict behavioral shifts in response to changing environments. The Lake Sturgeon Acipenser fulvescens is a wide-ranging, migratory, coolwater species, making it a candidate species for studying patterns in movement ecology. We conducted a literature review and meta-analysis of seasonal movement data compiled from 38 Lake Sturgeon telemetry studies in North America to build an understanding of spatiotemporal variation in movement behavior. Lake Sturgeon movement studies were underrepresented for low-latitude populations in the Mississippi, Missouri, and Ohio/Tennessee River basins. Highest movement usually occurred during spring spawning migrations, whereas other populations exhibited their highest movement in the fall, potentially in order to overwinter near spawning grounds. Our meta-regression analysis indicated that latitude or summer maximum temperature best predicted standardized mean difference between spring and summer movement in Lake Sturgeon populations across the species’ range. Our results suggest that Lake Sturgeon populations at lower latitudes and those that experience warmer summer temperatures have lower summer movement relative to spring movement. Managers may use this information to prioritize actions promoting the conservation of seasonally important habitats for the continued recovery of migratory coolwater fish (e.g., Lake Sturgeon) that potentially experience stressful thermal conditions.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10416","usgsCitation":"Moore, M.J., Paukert, C.P., and Moore, T., 2021, Effects of latitude, season, and temperature on Lake Sturgeon movement: North American Journal of Fisheries Management, v. 41, no. 4, p. 916-928, https://doi.org/10.1002/nafm.10416.","productDescription":"13 p.","startPage":"916","endPage":"928","ipdsId":"IP-109393","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Michael J.","contributorId":274823,"corporation":false,"usgs":false,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, T.","contributorId":257287,"corporation":false,"usgs":false,"family":"Moore","given":"T.","affiliations":[],"preferred":false,"id":833349,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221844,"text":"70221844 - 2021 - Erosion and recovery: Sound-side inundation of Cape Lookout National Seashore during Hurricane Dorian","interactions":[],"lastModifiedDate":"2021-10-04T11:49:09.772716","indexId":"70221844","displayToPublicDate":"2020-02-01T10:13:48","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9367,"text":"North Carolina Sentinel Site Cooperative Newsletter","active":true,"publicationSubtype":{"id":30}},"title":"Erosion and recovery: Sound-side inundation of Cape Lookout National Seashore during Hurricane Dorian","docAbstract":"Hurricane Dorian tracked immediately offshore of Cape Lookout National Seashore (which includes the barrier islands of North and South Core Banks) and Ocracoke Island after devastating the Bahamas in early September, 2019. Dorian briefly made landfall at Cape Hatteras as a Category 1 hurricane on September 6 before moving northeast over the Atlantic Ocean. Winds on the Outer Banks, initially more than 40 m/s (about 90 mph) from the southeast, drove ocean waves and storm surge against the islands and pushed water across Pamlico Sound, resulting in elevated water levels in the sound’s northwestern rivers and creeks.","language":"English","collaboration":"none","usgsCitation":"Sherwood, C.R., 2021, Erosion and recovery: Sound-side inundation of Cape Lookout National Seashore during Hurricane Dorian: North Carolina Sentinel Site Cooperative Newsletter, v. 8, no. 1, p. 2-5.","productDescription":"4 p.","startPage":"2","endPage":"5","ipdsId":"IP-115890","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":390124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390123,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ncseagrant.ncsu.edu/program-areas/sustainable-communities/north-carolina-sentinel-site-cooperative-newsletters/"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Lookout National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.52046203613281,\n 34.58460567894334\n ],\n [\n -76.32476806640625,\n 34.83353199411513\n ],\n [\n -76.35635375976562,\n 34.837477162415986\n ],\n [\n -76.57264709472656,\n 34.62360274960748\n ],\n [\n -76.53556823730469,\n 34.57951775453086\n ],\n [\n -76.52046203613281,\n 34.58460567894334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818948,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70219477,"text":"70219477 - 2021 - Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats","interactions":[],"lastModifiedDate":"2021-04-12T12:01:31.478203","indexId":"70219477","displayToPublicDate":"2020-01-08T07:25:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats","docAbstract":"Increasing global energy demand is fostering the development of renewable energy as an alternative to fossil fuels. However, renewable energy facilities may adversely affect wildlife. Facility siting guidelines recommend or require project developers complete pre‐ and postconstruction wildlife surveys to predict risk and estimate effects of proposed projects. Despite this, there are no published studies that have quantified the types of surveys used or how survey types are standardized within and across facilities. We evaluated 628 peer‐reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the frequency of pre‐ and postconstruction surveys and whether that frequency changed over time; frequency of studies explicitly designed to allow before‐after or impact‐control analyses; and what types of survey data were collected during pre‐ and postconstruction periods and how those data types were standardized across periods and among facilities. Within our data set, postconstruction monitoring for wildlife fatalities and habitat use was a standard practice (n = 446 reports), but preconstruction estimation of baseline wildlife habitat use and mortality was less frequently reported (n = 84). Only 22% (n = 45) of the 203 facilities provided data from both pre‐ and postconstruction, and 29% (n = 59) had experimental study designs. Of 108 facilities at which habitat‐use surveys were conducted, only 3% estimated of detection probability. Thus, the available data generally preclude comparison of biological data across construction periods and among facilities. Use of experimental study designs and following similar field protocols would improve the knowledge of how renewable energy affects wildlife.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13457","usgsCitation":"Conkling, T., Loss, S.R., Diffendorfer, J., Duerr, A., and Katzner, T., 2021, Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats: Conservation Biology, v. 35, no. 1, p. 64-76, https://doi.org/10.1111/cobi.13457.","productDescription":"13 p.","startPage":"64","endPage":"76","ipdsId":"IP-099190","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":503858,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zotero.org/groups/5435545/items/DWMGIN3G","text":"External Repository"},{"id":384968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Conkling, Tara 0000-0003-1926-8106","orcid":"https://orcid.org/0000-0003-1926-8106","contributorId":217915,"corporation":false,"usgs":true,"family":"Conkling","given":"Tara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loss, S. R. 0000-0002-8753-2995","orcid":"https://orcid.org/0000-0002-8753-2995","contributorId":257044,"corporation":false,"usgs":false,"family":"Loss","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":51965,"text":"Department of Natural Resource Ecology & Management, Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":813723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":813724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duerr, A. 0000-0002-6145-8897","orcid":"https://orcid.org/0000-0002-6145-8897","contributorId":257045,"corporation":false,"usgs":false,"family":"Duerr","given":"A.","email":"","affiliations":[{"id":38830,"text":"Bloom Research Inc.","active":true,"usgs":false}],"preferred":false,"id":813725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813726,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220490,"text":"70220490 - 2021 - Two-event genesis of Butte lode veins: Geologic and geochronologic evidence from ore veins, dikes, and host plutons","interactions":[],"lastModifiedDate":"2021-06-02T12:12:51.770096","indexId":"70220490","displayToPublicDate":"2019-12-31T16:06:19","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Two-event genesis of Butte lode veins: Geologic and geochronologic evidence from ore veins, dikes, and host plutons","docAbstract":"The long-standing ore-genesis model for world-class deposits of the Butte mining district, Montana, is of deep pre-Main Stage porphyry Cu-Mo and overlying Main Stage Ag-Zn-Cu-zoned lode veinsformed from discrete hydrothermal systems related to rhyolite dikes. The lode-specific model describes metals zones that formed in the lode veins as hydrothermal processes diminished in intensity (changing temperature and chemical characteristics) outward from the district center. New geologic and multi-method geochronologic studies pro- vide new timing constraints on the lode veins and reevaluation of geologic relations (Lund and others, 2018), leading to a new model for formation of the lode veins and their relations to stockwork Cu-Mo deposits and igneous events.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Montana Mining and Mineral Symposium 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Montana Mining and Mineral Symposium 2019","conferenceDate":"October 9-11, 2019","language":"English","publisher":"Montana Bureau of Mines and Geology","usgsCitation":"Lund, K., McAleer, R.J., Aleinikoff, J.N., and Cosca, M., 2021, Two-event genesis of Butte lode veins: Geologic and geochronologic evidence from ore veins, dikes, and host plutons, in Proceedings of the Montana Mining and Mineral Symposium 2019, October 9-11, 2019, p. 71-73.","productDescription":"3 p.","startPage":"71","endPage":"73","ipdsId":"IP-112266","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":386095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385671,"type":{"id":15,"text":"Index Page"},"url":"https://www.mbmg.mtech.edu/mbmgcat/public/ListCitation.asp?pub_id=32264&"}],"country":"United States","state":"Montana","otherGeospatial":"Butte mining district","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.76916503906249,\n 45.882360730184025\n ],\n [\n -112.37640380859375,\n 45.882360730184025\n ],\n [\n -112.37640380859375,\n 46.086566879725034\n ],\n [\n -112.76916503906249,\n 46.086566879725034\n ],\n [\n -112.76916503906249,\n 45.882360730184025\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":815738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":815739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":815740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosca, Michael 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":33043,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":815741,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216098,"text":"70216098 - 2021 - Making Recursive Bayesian inference accessible","interactions":[],"lastModifiedDate":"2021-05-19T12:08:37.54648","indexId":"70216098","displayToPublicDate":"2019-11-04T13:50:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":747,"text":"American Statistician","active":true,"publicationSubtype":{"id":10}},"title":"Making Recursive Bayesian inference accessible","docAbstract":"Bayesian models provide recursive inference naturally because they can formally reconcile new data and existing scientific information. However, popular\nuse of Bayesian methods often avoids priors that are based on exact posterior distributions resulting from former studies. Two existing Recursive Bayesian methods\nare: Prior- and Proposal-Recursive Bayes. Prior-Recursive Bayes uses Bayesian\nupdating, fitting models to partitions of data sequentially, and provides a way\nto accommodate new data as they become available using the posterior from the\nprevious stage as the prior in the new stage based on the latest data. ProposalRecursive Bayes is intended for use with hierarchical Bayesian models and uses a\nset of transient priors in first stage independent analyses of the data partitions.\nThe second stage of Proposal-Recursive Bayes uses the posteriors from the first\nstage as proposals in an MCMC algorithm to fit the full model. We combine\nPrior- and Proposal-Recursive concepts to fit any Bayesian model, and often with\ncomputational improvements. We demonstrate our method with two case studies.\nOur approach has implications for big data, streaming data, and optimal adaptive\ndesign situations.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00031305.2019.1665584","usgsCitation":"Hooten, M., Johnson, D., and Brost, B., 2021, Making Recursive Bayesian inference accessible: American Statistician, v. 75, no. 2, p. 185-194, https://doi.org/10.1080/00031305.2019.1665584.","productDescription":"10 p.","startPage":"185","endPage":"194","ipdsId":"IP-101580","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454561,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1807.10981","text":"External Repository"},{"id":380171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":804074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":244505,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":804076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":244504,"corporation":false,"usgs":false,"family":"Brost","given":"Brian M.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":804075,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215993,"text":"70215993 - 2021 - Chemical controls for an integrated pest management program","interactions":[],"lastModifiedDate":"2021-04-22T18:37:34.89253","indexId":"70215993","displayToPublicDate":"2019-09-24T07:40:31","publicationYear":"2021","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":"Chemical controls for an integrated pest management program","docAbstract":"Chemical controls ranging from natural products to synthesized chemicals are widely used in aquatic pest management activities. Chemicals can be used to lure organisms to traps or can cause direct mortality by altering the physiological function of an organism. Much of what is known about controlling pests with chemicals is from research done on terrestrial pesticides. This paper focuses on how chemicals might be used as aquatic pesticides to control or eradicate aquatic invasive species. Current control tools are described, as are new technologies designed to selectively target the pest to reduce risks to nontarget organisms and the environment.
Aquatic invasive plants and animals are increasingly becoming a problem, causing severe economic and ecological damage to critical freshwater systems. The best strategy for controlling an invasive pest employs an integrated pest management (IPM) approach using a combination of biological, physical, chemical, and social/cultural control methods. Here, we examine the history and development of IPM and provide a discussion of the components of an IPM program involving development, evaluation, and management. Control approaches will be reviewed and the application of this technique to aquatic systems will be discussed. A discussion of the Great Lakes Fishery Commission's (GLFC) Integrated Management of Sea Lamprey Petromyzon marinus Control Program will be provided to illustrate the application of IPM to an aquatic system.
Mercury (Hg) bioaccumulates in aquatic ecosystems and may pose a risk to humans who consume fish. Selenium (Se) has the ability to reduce Hg toxicity, but the current guidance for human consumption of fish is based on Hg concentration alone. The purpose of the present study was to examine the relationship between Se and Hg in freshwater sportfish, for which there is a paucity of existing data. We collected three species of fish from different trophic positions from two drinking water reservoirs in central North Carolina, USA, to assess Hg and Se concentrations in relation to fish total length and to compare two measures of the protective ability of Se, the Se:Hg molar ratio and Se health benefit value (HBVSe), to current guidance for Hg. According to the Se:Hg molar ratio, all of the low trophic position fish sampled and the middle trophic position fish sampled from one of the reservoirs were safe for consumption. The same number of fish were considered safe using the HBVSe. More fish were deemed unsafe when using the Se:Hg molar ratio and HBVSe than were considered unsafe when using the U.S. Environmental Protection Agency (USEPA) Hg threshold. These findings suggest that the measures of Se protection may be unnecessarily conservative or that the USEPA Hg threshold may not be sufficiently protective of human health, especially the health of sensitive populations like pregnant or nursing mothers and young children. Future examination of the Se:Hg molar ratio and HBVSe from a variety of fish tissue samples would help refine the accuracy of these measures so that they may be appropriately utilized in ecological and human health risk assessment.
","language":"English","publisher":"MDPI","doi":"10.3390/ijerph15091864","usgsCitation":"Johnson, T.K., LePrevost, C.E., Kwak, T.J., and Cope, W.G., 2021, Selenium, mercury, and their molar ratios in sportfishes from drinking water reservoirs: International Journal of Environmental Research and Public Health, v. 15, no. 9, 1864, 17 p., https://doi.org/10.3390/ijerph15091864.","productDescription":"1864, 17 p.","ipdsId":"IP-100876","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijerph15091864","text":"Publisher Index Page"},{"id":388174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Tara K. B.","contributorId":264411,"corporation":false,"usgs":false,"family":"Johnson","given":"Tara","email":"","middleInitial":"K. B.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LePrevost, C. E.","contributorId":264412,"corporation":false,"usgs":false,"family":"LePrevost","given":"C.","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. G.","contributorId":264384,"corporation":false,"usgs":false,"family":"Cope","given":"W.","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821491,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204951,"text":"70204951 - 2021 - Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California","interactions":[{"subject":{"id":70204951,"text":"70204951 - 2021 - Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California","indexId":"70204951","publicationYear":"2021","noYear":false,"chapter":"8","title":"Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":1}],"isPartOf":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"lastModifiedDate":"2021-11-08T18:06:42.694758","indexId":"70204951","displayToPublicDate":"2019-08-27T09:14:28","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California","docAbstract":"We used geologic mapping, tephrochronology and 40Ar/39Ar dating to describe evidence of a ca. 3.5 Ma pluvial lake in Eureka Valley, eastern California, that we informally name herein Lake Andrei. We identified six different tuffs in the Eureka Valley drainage basin including two previously undescribed tuffs: the 3.509 ± 0.009 Ma tuff of Hanging Rock Canyon and the 3.506 ± 0.010 Ma tuff of Last Chance (informal names). We focused on four Pliocene stratigraphic sequences. Three sequences are composed of fluvial sandstone and conglomerate with basalt flows in two of these sequences. The fourth sequence, located about 1.5 km south of the Death Valley/Big Pine Road along the western piedmont of the Last Chance Range, included green, fine-grained, gypsiferous lacustrine deposits interbedded with the 3.506 Ma tuff of Last Chance that we interpret as evidence of a pluvial lake. Pluvial Lake Andrei is similar in age pluvial lakes in Searles Valley, Amargosa Valley, Fish Lake Valley and Death Valley of the western Great Basin. We interpret these simultaneous lakes in the region as indirect evidence of a significant glacial climate in western North America during Marine Isotope Stages MG5/M2 and a persistent Pacific jet stream south of 37°N.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From saline to freshwater: The diversity of western lakes in space and time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2536(08)","usgsCitation":"Knott, J.R., Wan, E., Deino, A.L., Casteel, M., Reheis, M.C., Phillips, F., Walkup, L., McCarty, K., Manoukian, D.N., and Nunez, E., 2021, Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California, chap. 8 of From saline to freshwater: The diversity of western lakes in space and time, p. 125-142, https://doi.org/10.1130/2018.2536(08).","productDescription":"18 p.","startPage":"125","endPage":"142","ipdsId":"IP-082661","costCenters":[{"id":312,"text":"Geology, 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basins","interactions":[],"lastModifiedDate":"2021-06-30T17:39:25.279033","indexId":"70206650","displayToPublicDate":"2019-07-31T14:53:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Influence of surrounding land-use on mussel growth and glycogen levels in the St. Croix and Minnesota River basins","docAbstract":"Freshwater mussels face threats from climate change and changing land use that are dramatically altering their habitat. The health of mussel populations and the state of current and past environmental conditions can be monitored by measuring mussel growth and glycogen levels. In this study we measured growth and glycogen levels in mussels from two small river basins impacted by different land uses. The Snake River in the St. Croix Basin had low levels of suspended sediments and was surrounded mostly by forest and some developed land. The Chippewa, Cottonwood, and Le Sueur rivers in the Minnesota River Basin had significantly higher annual suspended sediment loads and highly agricultural basins. Mussel growth was highest in the Le Sueur and Cottonwood rivers followed by the Chippewa and the Snake rivers. Mussels in the Minnesota Basin rivers all had higher foot glycogen concentrations than the Snake River. These patterns were similar for two mussel species, suggesting that environmental conditions are likely determining levels of growth. Although agriculture had a negative effect on mussel population abundance and diversity, it had a positive effect on growth and glycogen levels.","language":"English","publisher":"Springer","doi":"10.1007/s10750-019-04016-z","usgsCitation":"Hornbach, D.J., Stutzman, H., Hove, M.C., Kozarek, J., MacGregor, K., Newton, T., and Ries, P., 2021, Influence of surrounding land-use on mussel growth and glycogen levels in the St. Croix and Minnesota River basins: Hydrobiologia, v. 848, p. 3045-3063, https://doi.org/10.1007/s10750-019-04016-z.","productDescription":"19 p.","startPage":"3045","endPage":"3063","ipdsId":"IP-099796","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":454574,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10750-019-04016-z","text":"Publisher Index Page"},{"id":369253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Chippewa River, Cottonwood River, Le Sueur River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.74560546875,\n 43.492782808225\n ],\n [\n -92.52685546875,\n 43.492782808225\n ],\n [\n -92.52685546875,\n 46.927758623434435\n ],\n [\n -96.74560546875,\n 46.927758623434435\n ],\n [\n -96.74560546875,\n 43.492782808225\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"848","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Hornbach, Daniel J.","contributorId":220617,"corporation":false,"usgs":false,"family":"Hornbach","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":37385,"text":"Macalester College","active":true,"usgs":false}],"preferred":false,"id":775306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stutzman, Hayley","contributorId":220618,"corporation":false,"usgs":false,"family":"Stutzman","given":"Hayley","email":"","affiliations":[{"id":37385,"text":"Macalester College","active":true,"usgs":false}],"preferred":false,"id":775307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hove, Mark C.","contributorId":220619,"corporation":false,"usgs":false,"family":"Hove","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":775308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kozarek, Jessica","contributorId":220620,"corporation":false,"usgs":false,"family":"Kozarek","given":"Jessica","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":775309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"MacGregor, Kelly","contributorId":220621,"corporation":false,"usgs":false,"family":"MacGregor","given":"Kelly","email":"","affiliations":[{"id":37385,"text":"Macalester College","active":true,"usgs":false}],"preferred":false,"id":775310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newton, Teresa 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":150098,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":775305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ries, Patricia 0000-0001-5095-7896 pries@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-7896","contributorId":218175,"corporation":false,"usgs":true,"family":"Ries","given":"Patricia","email":"pries@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":775311,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70254933,"text":"70254933 - 2021 - Gray wolf (Canis lupus) predation patterns following recent recolonization in a multi-predator, multi-prey system","interactions":[],"lastModifiedDate":"2024-06-11T12:07:20.383228","indexId":"70254933","displayToPublicDate":"2019-07-19T07:04:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Gray wolf (Canis lupus) predation patterns following recent recolonization in a multi-predator, multi-prey system","docAbstract":"The late Eocene Florissant Formation in central Colorado is a rich and diverse continental Lagerstätte yielding well-preserved fossil assemblages from lacustrine and fluvial facies. This investigation focused on the lacustrine facies at Clare’s Quarry and used biotic and abiotic evidence to characterize aspects of the lake and processes that resulted in the accumulation and preservation of the host rock and its fossils. Autecology of modern analogs representing the fossil diatom taxa was used to augment sedimentary data in characterizing the lake, propose peripheral habitats within the catchment area, and suggest a terrestrial source for mudstone units.
The sedimentary and stratigraphic record at the study site reveals a lake with sufficient depth to allow bottom waters to remain isolated and anoxic for long periods. Sediments that accumulated in the lake produced distinct lacustrine lithofacies that are interpreted as representing at least three modes of origin: stable lake, pyroclastic, and mud turbidite sedimentation. Slow, suspension settling of fine clays and volcanic ash into a moderately deep, stable lake resulted in laminated shales. These laminated shales contain frustules of diatoms from planktic and benthic lake habitats; diatoms transported into the lake from streams and wetlands; fish, mollusks, ostracods, and insects; and plants from marginal and upslope environments. Intermittent volcanic eruptions produced air-fall ash and granular tuff that accumulated as interbeds within the lake shales. Periods of stable lake sedimentation were frequently interrupted by rapid influxes of suspended fine clays, perhaps as mud-dominated turbidites that prograded into the lake at intervals of high runoff triggered by climatic, volcanic, or tectonic events.
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Geophysically derived estimates of model structural uncertainty are then combined with hydrologic observations to assess the impact of model structural error on hydrologic calibration and prediction errors. Using a synthetic numerical model, we describe a sequential hydrogeophysical approach that: (1) uses Bayesian Markov chain Monte Carlo (McMC) methods to produce a robust estimate of uncertainty in electrical resistivity parameters, (2) combines geophysical parameter uncertainty estimates with borehole observations of lithology to produce probabilistic estimates of model structural uncertainty over the entire AEM survey area using geostatistical sequential indicator simulation algorithms, and (3) uses model structural estimates along with hydrologic observations to quantify both hydrologic parameter and prediction uncertainty using a second McMC sampling algorithm. Results of simulations will be presented that illustrate the complete workflow from geophysical parameter uncertainty analysis to the impact of model structural uncertainty on hydrologic parameter estimates.
","conferenceTitle":"7th International Workshop on Airborne Electromagnetics","conferenceDate":"June 17-20, 2018","conferenceLocation":"Kolding, Denmark","language":"English","publisher":"Aarhus University","usgsCitation":"Minsley, B.J., Christensen, N.K., Christensen, S., and Ley-Cooper, Y., 2021, Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data, 7th International Workshop on Airborne Electromagnetics, Kolding, Denmark, June 17-20, 2018, 4 p.","productDescription":"4 p.","ipdsId":"IP-095925","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":383107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383106,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.conferencemanager.dk/aem2018"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":809258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Nikolaj K","contributorId":199736,"corporation":false,"usgs":false,"family":"Christensen","given":"Nikolaj","email":"","middleInitial":"K","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":809259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Steen","contributorId":199737,"corporation":false,"usgs":false,"family":"Christensen","given":"Steen","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":809260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ley-Cooper, Yusen","contributorId":248494,"corporation":false,"usgs":false,"family":"Ley-Cooper","given":"Yusen","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":809261,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}