{"pageNumber":"377","pageRowStart":"9400","pageSize":"25","recordCount":184660,"records":[{"id":70231845,"text":"ofr20221013 - 2022 - Water-budget accounting for tropical regions model (WATRMod) documentation","interactions":[],"lastModifiedDate":"2026-03-27T19:49:35.907978","indexId":"ofr20221013","displayToPublicDate":"2022-06-01T11:17:20","publicationYear":"2022","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":"2022-1013","displayTitle":"Water-Budget Accounting for Tropical Regions Model (WATRMod) Documentation","title":"Water-budget accounting for tropical regions model (WATRMod) documentation","docAbstract":"

Regional groundwater recharge commonly is estimated using a threshold-type water-budget approach in which groundwater recharge is assumed to occur when water in the plant-root zone exceeds the soil’s moisture storage capacity. A water budget of the plant-soil system accounts for water inputs (rainfall, fog interception, irrigation, septic-system leachate, and other inputs), water outputs (runoff, evaporation, transpiration, and recharge), and changes in stored water during a specified time interval. Water budgets can be computed on any desired interval, including annual, monthly, daily, and subdaily intervals. In general, uncertainty in recharge estimates is expected to be lower using daily or subdaily intervals relative to monthly and annual intervals. Average recharge rates computed over a period of a year or multiple years are commonly determined from water budgets computed using a daily computation interval capable of capturing rainfall and land-cover changes during the period.

This report documents the Water-budget Accounting for Tropical Regions Model, or WATRMod, code that can be used to estimate spatially variable, daily water-budget components in tropical-island and other appropriate settings. The purpose of this report is to provide descriptions of WATRMod’s (1) approach to computing a daily water budget, (2) represented processes, (3) limitations, and (4) execution procedure, input requirements, output files, and example files. The model computes a daily water budget for each hydrologically independent subarea within the overall study area. A subarea is defined by its climatic, soil, land-cover, and human-related (for example, adding irrigation or other water) characteristics. The water-budget model can represent processes including rainfall, fog interception, irrigation, septic-system leachate, direct recharge that bypasses the plant-soil system, runoff, canopy evaporation in forested areas, evapotranspiration, and groundwater recharge. The water-budget model can represent either one of the following different accounting orders: (1) accounting for loss of water by evapotranspiration before accounting for recharge, and (2) accounting for recharge before accounting for evapotranspiration. WATRMod’s limitations include: (1) uncharacterized, subdaily transient changes in water inputs and outputs from the plant-soil system, (2) unrepresented precipitation in the form of snow and sublimation, and (3) routing runoff from one subarea to an adjacent subarea that is not directly represented.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221013","usgsCitation":"Oki, D.S., 2022, Water-budget accounting for tropical regions model (WATRMod) documentation: U.S. Geological Survey Open-File Report 2022-1013, 77 p., https://doi.org/10.3133/ofr20221013.","productDescription":"Report: viii, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"Y","ipdsId":"IP-126805","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":501758,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113077.htm","linkFileType":{"id":5,"text":"html"}},{"id":401381,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPAY41","text":"WATRMod, a Water-budget accounting for tropical regions model—source code, executable file, and example files","description":"Oki, D.S., 2022, WATRMod, a Water-budget accounting for tropical regions model—source code, executable file, and example files: U.S. Geological Survey data release, https://doi.org/10.5066/P9VPAY41."},{"id":401379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1013/covrthb.jpg"},{"id":401380,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1013/ofr20221013.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022-1013"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.3848876953125,\n 20.555652403773365\n ],\n [\n -156.0003662109375,\n 20.6379249854131\n ],\n [\n -155.9454345703125,\n 20.776659051878816\n ],\n [\n -156.26678466796875,\n 20.964004409178308\n ],\n [\n -156.47003173828125,\n 20.925527866647226\n ],\n [\n -156.610107421875,\n 21.056307701901847\n ],\n [\n -156.72271728515625,\n 20.94604992010052\n ],\n [\n -156.67327880859375,\n 20.822875478868443\n ],\n [\n -156.55792236328122,\n 20.761250430919652\n ],\n [\n -156.48651123046875,\n 20.771523019513364\n ],\n [\n -156.4617919921875,\n 20.622502259344817\n ],\n [\n -156.3848876953125,\n 20.555652403773365\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-06-01","noUsgsAuthors":false,"publicationDate":"2022-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843964,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70236749,"text":"70236749 - 2022 - Lake Ontario April prey fish survey results and Alewife assessment, 2022","interactions":[],"lastModifiedDate":"2022-09-19T16:05:20.398376","indexId":"70236749","displayToPublicDate":"2022-06-01T11:00:23","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Lake Ontario April prey fish survey results and Alewife assessment, 2022","docAbstract":"

The annual Lake Ontario April bottom trawl survey and Alewife, Alosa pseudoharengus, population assessment provide science to inform management decisions related to predator-prey balance and fish community dynamics. The 2022 survey was conducted from March 31 to April 26, included 235 trawls in the main lake and embayments, and sampled depths from 5 to 219 m (16 – 723 ft). The survey captured 311,770 fish from 30 species with a total weight of 7,740 kg (17,028 lbs.). Alewife were 85% of the catch by number while Rainbow Smelt, Osmerus mordax, Round Goby, Neogobius melanostomus, and Deepwater Sculpin, Myoxocephalus thompsonii, comprised 6%, 4%, and 4% of the catch, respectively. The 2022 biomass index for Rainbow Smelt decreased 80% relative to the high values observed in 2021 as did the value for Cisco, Coregonus artedi, (46% decline). Emerald Shiner, Notropis atherinoides, biomass index increased in 2021 and Threespine Stickleback, Gasterosteus aculeatus, biomass remained low. No Bloater, Coregonus hoyi, were captured during the 2022 survey.

In 2022, Alewife biomass in U.S. waters (58.1 kilograms per hectare, kg·ha-1) was substantially higher than Canadian waters (26.3 kg·ha-1). The 2022 Alewife biomass index (41.6 kg·ha-1) decreased 10% from 2021 while the 2022 density index decreased 62% from 2021. Prediction modeling indicated the growth of the abundant 2020 Alewife year class, sampled as age-1 fish in 2021, would cause the adult Alewife biomass to increase in 2022. Although the adult Alewife biomass did increase relative to 2021 (61%), the increase was lower than predicted. The difference between the predictions and observations was because survival of age-1 fish from 2021 to 2022 was lower than had previously been observed. In the three previous years of observations the proportion of age-1 Alewife surviving to age 2 ranged from 0.33 to 0.53; however, that proportion was only 0.21 from 2021 to 2022. Survival estimates of Alewife age-5 through age-8 were higher than previously observed, possibly because salmonid predation focused on the abundant younger Alewife. The catch of age-1 Alewife in 2022, which is a measure of reproductive success in 2021, was below average and similar to the abundances of the 2018 and 2019 year classes. Simulation modeling results indicated the adult Alewife biomass is likely to increase slightly in 2023, whereas predictions for 2024 are less certain.

Hydroacoustic sampling was used to estimate prey fish densities in open-water, pelagic habitats not sampled by the bottom trawl. Bottom trawl-based densities from the lake bottom were at least 25 times greater than densities of prey fish in the water column above the trawl. These results support the idea that, in April, when the warmest, most dense water is on the lake bottom, Alewife and most other pelagic prey fish primarily inhabit deep, near bottom habitats and can be effectively sampled with bottom trawling.

","language":"English","publisher":"Great Lakes Fishery Commission","collaboration":"NYSDEC, OMNRF","usgsCitation":"Weidel, B., Gutowsky, L.F., Goretzke, J., Holden, J., and Minihkeim, S.P., 2022, Lake Ontario April prey fish survey results and Alewife assessment, 2022, 11 p.","productDescription":"11 p.","ipdsId":"IP-144324","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":406900,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-ontario-committee.php"},{"id":406974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.925537109375,\n 43.265206318396025\n ],\n [\n -79.8101806640625,\n 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Jessica","contributorId":268339,"corporation":false,"usgs":false,"family":"Goretzke","given":"Jessica","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":852089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holden, Jeremy","contributorId":139654,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":12864,"text":"OMNRF","active":true,"usgs":false}],"preferred":false,"id":852090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minihkeim, Scott P. 0000-0003-4958-2462","orcid":"https://orcid.org/0000-0003-4958-2462","contributorId":265808,"corporation":false,"usgs":true,"family":"Minihkeim","given":"Scott","email":"","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":852091,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248097,"text":"70248097 - 2022 - 2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation","interactions":[],"lastModifiedDate":"2023-09-05T15:55:29.98934","indexId":"70248097","displayToPublicDate":"2022-06-01T10:53:59","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/EQD/NRR-2022/2395","title":"2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation","docAbstract":"The National Park Service (NPS) manages the Nation’s most iconic destinations that attract millions of visitors from across the Nation and around the world. Trip-related spending by NPS visitors generates and supports economic activity within park gateway communities. This report summarizes the annual economic contribution analysis that measures how NPS visitor spending cycles through local economies, generating business sales and supporting jobs and income.\nIn 2021, the National Park System received over 297 million recreation visits (up 25% from 2020). Visitors to national parks spent an estimated $20.5 billion in local gateway regions (up 41% from 2020). The estimated contribution of this spending to the national economy was 322,600 jobs, $14.6 billion in labor income, $24.3 billion in value added, and $42.5 billion in economic output. The lodging sector saw the highest direct effects, with $7 billion in economic output directly contributed to this sector nationally. The restaurants sector saw the next greatest effects, with $4.2 billion in economic output directly contributed to this sector nationally.\nResults from the Visitor Spending Effects report series are available online via an interactive tool. Users can view year-by-year trend data and explore current year visitor spending, jobs, labor income, value added, and economic output effects by sector for national, state, and local economies. The interactive tool is available at https://www.nps.gov/subjects/socialscience/vse.htm.","language":"English","publisher":"National Park Service","usgsCitation":"Cullinane Thomas, C., Flyr, M., and Koontz, L., 2022, 2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation: Natural Resource Report NPS/NRSS/EQD/NRR-2022/2395, v, 63 p.","productDescription":"v, 63 p.","ipdsId":"IP-139225","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420493,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nps.gov/nature/customcf/NPS_Data_Visualization/docs/NPS_2021_Visitor_Spending_Effects.pdf"},{"id":420494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine M. 0000-0001-8168-1271","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":328910,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flyr, Matthew 0000-0002-4723-3763","orcid":"https://orcid.org/0000-0002-4723-3763","contributorId":291828,"corporation":false,"usgs":false,"family":"Flyr","given":"Matthew","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":881840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":881841,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237855,"text":"70237855 - 2022 - The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","interactions":[],"lastModifiedDate":"2022-10-27T15:51:09.02612","indexId":"70237855","displayToPublicDate":"2022-06-01T10:44:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","docAbstract":"

Snake fungal disease (SFD; ophidiomycosis), caused by the pathogen Ophidiomyces ophiodiicola (Oo), has been documented in wild snakes in North America and Eurasia, and is considered an emerging disease in the eastern United States of America. However, a lack of historical disease data has made it challenging to determine whether Oo is a recent arrival to the USA or whether SFD emergence is due to other factors. Here, we examined the genomes of 82 Oo strains to determine the pathogen’s history in the eastern USA. Oo strains from the USA formed a clade (Clade II) distinct from European strains (Clade I), and molecular dating indicated that these clades diverged too recently (approximately 2,000 years ago) for transcontinental dispersal of Oo to have occurred via natural snake movements across Beringia. A lack of nonrecombinant intermediates between clonal lineages in Clade II indicates that Oo has actually been introduced multiple times to North America from an unsampled source population, and molecular dating indicates that several of these introductions occurred within the last few hundred years. Molecular dating also indicated that the most common Clade II clonal lineages have expanded recently in the USA, with time of most recent common ancestor mean estimates ranging from 1985 to 2007 CE. The presence of Clade II in captive snakes worldwide demonstrates a potential mechanism of introduction and highlights that additional incursions are likely unless action is taken to reduce the risk of pathogen translocation and spillover into wild snake populations.

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North Carolina’s rich history and importance in the colonial days played a critical role in the Nation’s economic development. It was also the setting for events like the Wright Brothers’ famous first flight of a powered aircraft, called “Wright Flyer,” which took place in Kitty Hawk in 1903. Today, North Carolina license plates proudly proclaim the State as “First in Flight.”

The aerospace and defense sectors remain large players in the State’s economy to this day. Boeing, Lockheed Martin, General Electric Aviation, and others maintain a presence in the Tar Heel State, and military installations dot the landscape.

It is fitting, then, that North Carolinians rely upon a satellite system to monitor and study the health of their State’s vast and varied terrain: its coastal plain, the sweeping valleys and peaks of the Blue Ridge Mountains, and the fertile rolling plateau of the Piedmont ecoregion that separates the two. The U.S. Geological Survey Landsat satellite program’s unparalleled 50-year record of Earth surface change offers scientists, watershed and land managers, urban planners, and others insight into landscape change, both drastic and mild. Landsat observations document everything from posthurricane floods that push inland to subtle shifts in forest composition and coastal encroachment on urban and military infrastructure.

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Carolina\",\"nation\":\"USA \"}}]}","contact":"

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U.S. Geological Survey
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-01","noUsgsAuthors":false,"publicationDate":"2022-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":202815,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":844053,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70232214,"text":"70232214 - 2022 - Late Paleozoic flexural extension and overprinting shortening in the southern Ozark dome, Arkansas, USA: Evolving fault kinematics in the foreland of the Ouachita orogen","interactions":[],"lastModifiedDate":"2022-06-14T13:55:55.492663","indexId":"70232214","displayToPublicDate":"2022-06-01T08:52:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Late Paleozoic flexural extension and overprinting shortening in the southern Ozark dome, Arkansas, USA: Evolving fault kinematics in the foreland of the Ouachita orogen","docAbstract":"

Faults and folds on the southern flank of the Ozark dome in northern Arkansas, USA, record flexural extension in a foreland area followed by shortening in response to the late Paleozoic Ouachita orogeny. Map-scale structures and an analysis of fault-slip data collected systematically during geologic mapping demonstrate that most deformation in the area accommodated north-south extension as the southern margin of Laurentia was flexed beneath the thrust load of the Ouachita belt, probably during Middle Pennsylvanian. Extension was concentrated in northeast- and west-northwest-trending structural zones having sets of discontinuous, often en echelon normal and strike-slip faults and associated monoclinal folds. Reactivation of basement weaknesses that underlie these zones is indicated by their close match to oblique-rift models in which both the proportions of normal and strike-slip faulting and the internal extension directions vary with orientation of the zones. Subsequent propagation of north-south Ouachita shortening into the foreland formed small-offset strike-slip and sparse reverse faults that overprinted older extensional structures. Strike-slip faults were concentrated in reactivated northeast-trending structural zones. In two areas, reverse faults and local anticlines were developed in the footwalls of older normal faults, both near intersections of northeast- and west-northwest-trending structural zones. These are interpreted as areas of incipient inversion due to compressional stress concentrations at fault-block corners. Spatial overlap of areas of north-south shortening and fluid flux marked by silicification or lead-zinc mineralization indicates that regional fluid flow of brines was coeval with and may have enhanced inversion during Late Pennsylvanian to early Permian.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021TC006706","usgsCitation":"Hudson, M., and Turner, K.J., 2022, Late Paleozoic flexural extension and overprinting shortening in the southern Ozark dome, Arkansas, USA: Evolving fault kinematics in the foreland of the Ouachita orogen: Tectonics, v. 41, e2021TC006706, 27 p., https://doi.org/10.1029/2021TC006706.","productDescription":"e2021TC006706, 27 p.","ipdsId":"IP-125523","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447580,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021tc006706","text":"Publisher Index Page"},{"id":435830,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92TLPU2","text":"USGS data release","linkHelpText":"Fault data collected between 1996 and 2019 from the Buffalo River watershed area, northern Arkansas"},{"id":402148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.63623046875,\n 35.51434313431818\n ],\n [\n -92.83447265624999,\n 35.60371874069731\n ],\n [\n -92.30712890625,\n 35.71083783530009\n ],\n [\n -88.22021484375,\n 36.24427318493909\n ],\n [\n -88.3740234375,\n 37.055177106660814\n ],\n [\n -89.14306640625,\n 37.125286284966805\n ],\n [\n -89.5166015625,\n 37.71859032558816\n ],\n [\n -90.28564453124999,\n 38.09998264736481\n ],\n [\n -91.34033203125,\n 38.238180119798635\n ],\n [\n -92.0654296875,\n 38.34165619279595\n ],\n [\n -93.4716796875,\n 38.22091976683121\n ],\n [\n -94.52636718749999,\n 37.47485808497102\n ],\n [\n -94.9658203125,\n 37.23032838760387\n ],\n [\n -95.1416015625,\n 36.58024660149866\n ],\n [\n -95.361328125,\n 35.90684930677121\n ],\n [\n -94.89990234375,\n 35.496456056584165\n ],\n [\n -94.63623046875,\n 35.51434313431818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2022-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":844677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":844678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255746,"text":"70255746 - 2022 - Distribution of niclosamide following granular Bayluscide applications in lotic systems","interactions":[],"lastModifiedDate":"2024-07-03T14:03:07.647204","indexId":"70255746","displayToPublicDate":"2022-06-01T08:47:05","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":7568,"text":"Project Completion Report","active":true,"publicationSubtype":{"id":3}},"title":"Distribution of niclosamide following granular Bayluscide applications in lotic systems","docAbstract":"

The granular formulation of Bayluscide [Bayluscide 3.2% Granular Sea Lamprey Larvicide, granular Bayluscide (gB)] is applied in lentic and lotic systems to survey (assessment) and kill (treatment) larval sea lampreys (Petromyzon marinus; Linnaeus, 1758) in the Great Lakes basin. Granules are spread on the water surface, settle to the sediment surface, and dissolve. The potential risk of niclosamide exposure (2′,5-dichloro-4′-nitrosalicylanilide), the active ingredient of gB, to non-target organisms located downstream of survey plots, is a concern of partner agencies (state-level natural resource departments, U.S. Fish and Wildlife Service Ecological Services, and Fisheries and Oceans Canada Species at Risk Branch). Spatiotemporal distribution of niclosamide in the water column and sediment was evaluated in and downstream of five larval survey plots in two rivers following the application of gB. Water samples were collected at 0.25, 2, 4, 6, 8, and 24 h from three depths in the water column (10 cm above the sediment, ½ the water column depth, and the water surface) at three locations inside each survey plot, and 1 meter upstream from three sediment sample grids positioned 10, 30, and 100 m downstream. Sediment samples were collected from inside the grids at 0.25, 2, 4, 6, 8, and 24 h, and from inside the survey plots, 8 and 24 h after gB application. Niclosamide was detected in the sediment and water at all sample locations. From 2 to 24 h after application, average water concentrations 1) varied between study sites, 2) decreased from the survey plots to 100 m downstream, 3) varied by depth in the water column, and 4) decreased over time. Average sediment concentrations varied by distance downstream and time post-application, but not by study site or river. Data suggest there would be negligible exposure to non-target organisms downstream of a gB survey plot based on low niclosamide concentrations measured in the water and sediment. The depletion rate of niclosamide was also evaluated in St. Clair River sediment dosed at the field application rate. Niclosamide concentration decreased at a rate of 2.28% per hour over the 24 hours measured, equating to a half-life of 1.27 days. This indicates the length of time an organism in the sediment in a survey plot might be exposed. Underwater cameras were placed along the edge of two St. Clair River survey plots to document gB distribution on the sediment and any potential target and non-target effects. Video was inconclusive in tracking gB through the water column. Larval sea lamprey and non-target mortality were not observed. Additional video footage of one St. Clair River survey plot showed large areas of river bottom without gB.

","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Kaye, C., Bernardy, J.A., Schueller, J., Schloesser, N., Henson, M., Andresen, C.K., and Kirkeeng, C., 2022, Distribution of niclosamide following granular Bayluscide applications in lotic systems: Project Completion Report, 51 p.","productDescription":"51 p.","ipdsId":"IP-124289","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":430758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430738,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Michigan","county":"Alger County, St. Clair County","otherGeospatial":"Au Train River, St. Clair River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.57645899273449,\n 42.61812499759989\n ],\n [\n -82.64420763126448,\n 42.60751672353578\n ],\n [\n -82.69105509407704,\n 42.5650651070078\n ],\n [\n -82.58510775509997,\n 42.58947764353198\n ],\n [\n -82.57645899273449,\n 42.61812499759989\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.85011260876064,\n 46.41879658960383\n ],\n [\n -86.81383102571745,\n 46.41879658960383\n ],\n [\n -86.81383102571745,\n 46.43674452905637\n ],\n [\n -86.85011260876064,\n 46.43674452905637\n ],\n [\n -86.85011260876064,\n 46.41879658960383\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaye, Cheryl","contributorId":167292,"corporation":false,"usgs":false,"family":"Kaye","given":"Cheryl","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":905523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernardy, Jeffry A 0000-0001-7443-1995","orcid":"https://orcid.org/0000-0001-7443-1995","contributorId":296763,"corporation":false,"usgs":false,"family":"Bernardy","given":"Jeffry","email":"","middleInitial":"A","affiliations":[{"id":64165,"text":"former USGS, UMESC employee (retired)","active":true,"usgs":false}],"preferred":false,"id":905524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henson, Mary P.","contributorId":339882,"corporation":false,"usgs":false,"family":"Henson","given":"Mary P.","affiliations":[{"id":81410,"text":"USFWS, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":905527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andresen, Chad K.","contributorId":335684,"corporation":false,"usgs":false,"family":"Andresen","given":"Chad","email":"","middleInitial":"K.","affiliations":[{"id":80467,"text":"Marquette Biological Station, US Fish and Wildlife Service, Marquette, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":905528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirkeeng, Courtney A. 0000-0002-7141-1216","orcid":"https://orcid.org/0000-0002-7141-1216","contributorId":237026,"corporation":false,"usgs":true,"family":"Kirkeeng","given":"Courtney","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905529,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237644,"text":"70237644 - 2022 - Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","interactions":[],"lastModifiedDate":"2022-10-18T13:57:05.161824","indexId":"70237644","displayToPublicDate":"2022-06-01T08:44:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","title":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","docAbstract":"

Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel (Dreissena spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.

","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.06","usgsCitation":"Sepulveda, A., Smith, D.R., O'Donnell, K., Owens, N., White, B., Richter, C.A., Merkes, C.M., Wolf, S., Rau, M., Neilson, M., Daniel, W., Dumoulin, C.E., and Hunter, M., 2022, Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA: Management of Biological Invasions, v. 13, no. 2, p. 344-368, https://doi.org/10.3391/mbi.2022.13.2.06.","productDescription":"25 p.","startPage":"344","endPage":"368","ipdsId":"IP-133646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447583,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.2.06","text":"Publisher Index Page"},{"id":435831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2IQTS","text":"USGS data release","linkHelpText":"Predicted consequences of detecting dreissenid mussel eDNA in Jordanelle Reservoir Utah, 2021"},{"id":408476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":854796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Donnell, Katherine M. 0000-0001-9023-174X","orcid":"https://orcid.org/0000-0001-9023-174X","contributorId":289575,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Katherine M.","affiliations":[{"id":62192,"text":"Compass Resource Management","active":true,"usgs":false}],"preferred":false,"id":854798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, Nathan","contributorId":297990,"corporation":false,"usgs":false,"family":"Owens","given":"Nathan","email":"","affiliations":[],"preferred":false,"id":854799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Brittany","contributorId":297992,"corporation":false,"usgs":false,"family":"White","given":"Brittany","email":"","affiliations":[],"preferred":false,"id":854803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richter, Cathy A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":1878,"corporation":false,"usgs":true,"family":"Richter","given":"Cathy","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":854801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854944,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolf, Skylar","contributorId":279472,"corporation":false,"usgs":false,"family":"Wolf","given":"Skylar","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":854802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rau, 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0000-0001-7587-9417","orcid":"https://orcid.org/0000-0001-7587-9417","contributorId":298038,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":854943,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":854800,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70237405,"text":"70237405 - 2022 - Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries","interactions":[],"lastModifiedDate":"2022-10-12T13:52:58.684473","indexId":"70237405","displayToPublicDate":"2022-06-01T08:41:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries","docAbstract":"Inland recreational fisheries provide numerous socio- economic benefits to fishers, families and communities. Recreationally harvested fish are also frequently consumed and may provide affordable and sustainable but undervalued contributions to human nutrition. Quantifying the degree to which recreationally harvested fish contribute to food security and subsistence is impeded by lack of data on harvest and consumption and by the difficulty in differentiating among recreational and subsistence fisheries. Recreational harvest records tend to be limited to wealthy, food- secure countries and well- monitored fisheries with clear regulations or permitting systems. These records often neglect components of recreational harvest among food- insecure fishers who are potentially more likely to have consumption as a motivation. Here, we highlight the ‘fuzzy boundary’ that can exist between inland recreational and subsistence fisheries and argue that unreported consumption is likely to be a hidden contributor to food security in some populations. We draw on local case studies from around the world to highlight specific instances where recreationally harvested fish species contribute food and subsistence benefits to participating communities. We use these examples to highlight the diversity of ways that inland recreational fisheries contribute to human nutrition, knowledge gaps in understanding recreational fishing for food, and consequences of not accounting for them as food fisheries in policy and management. The aim of this paper is to draw the attention of resource managers and policy makers, create greater social awareness of the importance of recreational fisheries and bring to light this hidden contribution of inland fisheries to nutrition and subsistence.","language":"English","publisher":"Wiley","doi":"10.1111/faf.12688","usgsCitation":"Nyboer, E.A., Embke, H.S., Robertson, A., Arlinghaus, R., Bower, S., Baigun, C., Beard, T., Cooke, S.J., Cowx, I.G., Koehn, J.D., Lyach, R., Milardi, M., Potts, W.M., and Lynch, A., 2022, Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries: Fish and Fisheries, v. 23, no. 6, p. 1282-1298, https://doi.org/10.1111/faf.12688.","productDescription":"17 p.","startPage":"1282","endPage":"1298","ipdsId":"IP-135314","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500571,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Wildfire affects many types of communities and is a particular concern for communities in the wildland urban interface (WUI), such as those of Teton County, Wyoming. The core intent of this project was to provide evidence to support the Teton Area Wildfire Protection Coalition (TAWPC) and affiliated organizations in their wildfire mitigation and education programming. This report analyzes existing wildfire risk data collected in fall 2020 and pairs it with social data collected in the winter and spring of 2021, in order to better understand residents’ knowledge, experiences, and perceptions about wildfire risk. This greater understanding will help TAWPC focus its programs and outreach and ultimately promote increased mitigation and reduced wildfire risk in Teton County. The results of the wildfire risk assessment, covering 725 private residential properties in the study area, suggest that 89% face high, very high, or extreme risk of wildfire. In comparison, only 41% of residents estimated their risk of wildfire to be high, very high, or extreme. This suggests a “gap” between rapid assessment and survey estimates.

","language":"English","publisher":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","doi":"10.2737/RMRS-RN-93","collaboration":"USDA Forest Service; Jackson Hole Fire/EMSE; Teton Conservation District; Bureau of Land Management; Wildfire Research Center","usgsCitation":"Goolsby, J.B., Champ, P.A., Brenkert-Smith, H., Clauson, B.J., Sgroi, R.M., Williams, L., Barth, C.M., Meldrum, J., Donovan, C., and Wagner, C., 2022, Living with wildfire in Teton County, Wyoming: 2021 data report: Research Note RMRS-RN-93, 92 p., https://doi.org/10.2737/RMRS-RN-93.","productDescription":"92 p.","ipdsId":"IP-136533","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":447586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/rmrs-rn-93","text":"Publisher Index 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J","contributorId":292608,"corporation":false,"usgs":false,"family":"Clauson","given":"Bobbi","email":"","middleInitial":"J","affiliations":[{"id":62943,"text":"Jackson Hole Fire/EMS, Teton Area Wildfire Protection Coalition","active":true,"usgs":false}],"preferred":false,"id":845270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sgroi, Robert M","contributorId":292609,"corporation":false,"usgs":false,"family":"Sgroi","given":"Robert","email":"","middleInitial":"M","affiliations":[{"id":27732,"text":"Teton Conservation District","active":true,"usgs":false}],"preferred":false,"id":845271,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Lesley","contributorId":292610,"corporation":false,"usgs":false,"family":"Williams","given":"Lesley","email":"","affiliations":[{"id":62945,"text":"U.S. Department of Agriculture, Forest Service, Bridger-Teton National 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over the 2008–2018 summit eruption of Kīlauea Volcano","docAbstract":"
Magma rheology and volatile contents exert primary and highly nonlinear controls on volcanic activity. Subtle changes in these magma properties can modulate eruption style and hazards, making in situ inference of their temporal evolution vital for volcano monitoring. Here, we study thousands of impulsive magma oscillations within the shallow conduit and lava lake of Kīlauea Volcano, Hawai‘i, USA, over the 2008–2018 summit eruptive sequence, encoded by “very-long-period” seismic events and ground deformation. Inversion of these data with a petrologically informed model of magma dynamics reveals significant variation in temperature and highly disequilibrium volatile contents over days to years, within a transport network that evolved over the eruption. Our results suggest a framework for inferring subsurface magma dynamics associated with prolonged eruptions in near real time that synthesizes petrologic and geophysical volcano monitoring approaches.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.abm4310","usgsCitation":"Crozier, J.A., and Karlstrom, L., 2022, Evolving magma temperature and volatile contents over the 2008–2018 summit eruption of Kīlauea Volcano: Science Advances, v. 8, no. 22, eabm4310, 9 p., https://doi.org/10.1126/sciadv.abm4310.","productDescription":"eabm4310, 9 p.","ipdsId":"IP-134239","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":447589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.abm4310","text":"Publisher Index Page"},{"id":423013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.4622437871858,\n 19.5593064442494\n ],\n [\n -155.4622437871858,\n 19.256216654399836\n ],\n [\n -155.02279066218574,\n 19.256216654399836\n ],\n [\n -155.02279066218574,\n 19.5593064442494\n ],\n [\n -155.4622437871858,\n 19.5593064442494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crozier, Joshua Allen 0000-0001-8996-3441","orcid":"https://orcid.org/0000-0001-8996-3441","contributorId":331790,"corporation":false,"usgs":true,"family":"Crozier","given":"Joshua","email":"","middleInitial":"Allen","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":888784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlstrom, Leif 0000-0002-2197-2349","orcid":"https://orcid.org/0000-0002-2197-2349","contributorId":261729,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Leif","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":888785,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70243331,"text":"70243331 - 2022 - Luminescence sediment tracing reveals the complex dynamics of colluvial wedge formation","interactions":[],"lastModifiedDate":"2023-05-09T11:59:46.047485","indexId":"70243331","displayToPublicDate":"2022-06-01T06:51:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Luminescence sediment tracing reveals the complex dynamics of colluvial wedge formation","docAbstract":"
Paleoearthquake studies that inform seismic hazard rely on assumptions of sediment transport that remain largely untested. Here, we test a widespread conceptual model and a new numerical model on the formation of colluvial wedges, a key deposit used to constrain the timing of paleoearthquakes. We perform this test by applying luminescence, a sunlight-sensitive sediment tracer, at a field site displaying classic colluvial wedge morphostratigraphy. The model and data comparison reveals complex sediment transport processes beyond the predictions of either conceptual or numerical models, including periods of simultaneous debris and wash facies forming processes, erosion, and reworking. These processes could lead to preservation bias, such as incomplete or overinterpretable paleoearthquake records, given the right environmental conditions. Attention to the site-specific mechanics of fault zone depositional systems, such as via sediment tracing, may buffer against the possible effects of preservation bias on paleoseismic study.
","language":"English","publisher":"Science","doi":"10.1126/sciadv.abo0747","usgsCitation":"Gray, H., DuRoss, C., Nicovich, S., and Gold, R.D., 2022, Luminescence sediment tracing reveals the complex dynamics of colluvial wedge formation: Science, v. 8, no. 22, eabo0747, 11 p., https://doi.org/10.1126/sciadv.abo0747.","productDescription":"eabo0747, 11 p.","ipdsId":"IP-132616","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447592,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abo0747","text":"External Repository"},{"id":416851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, Harrison J. 0000-0002-4555-7473","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":207019,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":872065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicovich, Sylvia","contributorId":210054,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":872067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872068,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249758,"text":"70249758 - 2022 - Newly documented behavior of free-ranging Arctic wolf pups","interactions":[],"lastModifiedDate":"2023-10-26T11:50:33.442431","indexId":"70249758","displayToPublicDate":"2022-06-01T06:40:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"title":"Newly documented behavior of free-ranging Arctic wolf pups","docAbstract":"

Whereas much is known about the behavior and development of captive young wolf (Canis lupus) pups, less detail has been published about some aspects of free-ranging wolf pup behavior. This article synthesizes 42 observations of free-ranging Arctic wolf pups from ages 13 through 52 days made during 10 summers from 1987 through 2006 on Ellesmere Island, Nunavut, Canada. Besides listing key behaviors such as howling and caching, I record unique observations of ages of pup urination without adult stimulation (22, 33, 42, 52 days), knowledge of which is important to studies of wolf domestication, and of a 48-day-old pup that traveled 39 km during a 12 h and 19 min round trip between the den and a prey carcass, including a 26.5 km trek in 5 h. These observations should lead to a deeper and more complete understanding of this critical period of pup growth and development.

","language":"English","publisher":"Arctic Institute of North America","doi":"10.14430/arctic75056","usgsCitation":"Mech, L.D., 2022, Newly documented behavior of free-ranging Arctic wolf pups: Arctic, v. 75, no. 2, p. 272-276, https://doi.org/10.14430/arctic75056.","productDescription":"5 p.","startPage":"272","endPage":"276","ipdsId":"IP-130372","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447594,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14430/arctic75056","text":"Publisher Index Page"},{"id":435832,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EJCD4K","text":"USGS data release","linkHelpText":"Number of adult wolves and pups each year studied near Eureka, Ellesmere Island, Nunavut, Canada, 1987-2006"},{"id":422125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Nunavut","otherGeospatial":"Ellesmere","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.88387582346442,\n 80.33816075766248\n ],\n [\n -67.69223489149664,\n 80.74337450793786\n ],\n [\n -63.938079528913974,\n 81.44942829571119\n ],\n [\n -64.1715116908075,\n 81.64616495959865\n ],\n [\n -61.83335643099281,\n 81.99562892407235\n ],\n [\n -60.54514701980895,\n 82.25799911656247\n ],\n [\n -61.287077929813194,\n 82.58435309048807\n ],\n [\n -62.78245500282728,\n 82.66419057131895\n ],\n [\n -63.22114404802285,\n 82.89109241712504\n ],\n [\n -66.53679971545958,\n 83.03757574761522\n ],\n [\n -68.76320918300232,\n 83.10240338856744\n ],\n [\n -69.93057621300261,\n 83.17705266552835\n ],\n [\n -72.95059327110386,\n 83.15659230675533\n ],\n [\n -74.96085697096262,\n 83.18576340185913\n ],\n [\n -77.95955023951343,\n 83.11793648909529\n ],\n [\n -80.93180021324898,\n 82.96375046397776\n ],\n [\n -82.14261196457582,\n 82.76674982525694\n ],\n [\n -82.92674711136465,\n 82.46231613428324\n ],\n [\n -85.53068662209213,\n 82.58914675893578\n ],\n [\n -86.42540367112377,\n 82.36508800295414\n ],\n [\n -88.89454329198469,\n 82.14664509679355\n ],\n [\n -89.81302168509785,\n 82.00095563339218\n ],\n [\n -91.65631644558027,\n 81.8400397010048\n ],\n [\n -92.43418396457702,\n 81.62098823257122\n ],\n [\n -90.6916556110018,\n 81.28790294998134\n ],\n [\n -90.90940848914443,\n 81.09648488314039\n ],\n [\n -88.75758561141419,\n 80.66109671967558\n ],\n [\n -87.04927134718821,\n 80.50270409088293\n ],\n [\n -86.92177530416336,\n 80.3500245649584\n ],\n [\n -86.77234217171491,\n 80.01009312797558\n ],\n [\n -86.74299477239734,\n 79.7887943214931\n ],\n [\n -85.5877193957188,\n 79.63821783814922\n ],\n [\n -85.02928355860075,\n 79.36539416151408\n ],\n [\n -84.67269614439482,\n 79.17716486038717\n ],\n [\n -85.75849606587093,\n 79.09250342916752\n ],\n [\n -86.64154631941005,\n 78.93649539310613\n ],\n [\n -87.62639666688324,\n 78.5201740852132\n ],\n [\n -87.86949302147252,\n 78.03779496705795\n ],\n [\n -88.6082792710926,\n 77.70292361178596\n ],\n [\n -88.09149952761157,\n 77.5362408740148\n ],\n [\n -88.056596579599,\n 77.36387961025929\n ],\n [\n -87.57102078073198,\n 77.26474061508972\n ],\n [\n -88.63509802565198,\n 77.16676725941494\n ],\n [\n -89.5106705211971,\n 76.99766318045431\n ],\n [\n -90.80825633293244,\n 76.79826009052474\n ],\n [\n -90.23421294885912,\n 76.44350759438194\n ],\n [\n -88.75180892641345,\n 76.38193037865264\n ],\n [\n -87.7102058348687,\n 76.25467712334833\n ],\n [\n -87.14078687702545,\n 76.32960442618182\n ],\n [\n -86.33899990767884,\n 76.28180114043965\n ],\n [\n -84.24486671834995,\n 76.22837532291558\n ],\n [\n -83.63088939087142,\n 76.303328473159\n ],\n [\n -81.66682000365212,\n 76.37625890592167\n ],\n [\n -81.67492099243864,\n 76.01220866642039\n ],\n [\n -79.16378631801689,\n 76.162969919478\n ],\n [\n -77.14454023213592,\n 76.64391297858982\n ],\n [\n -77.60630652111992,\n 77.11896940229857\n ],\n [\n -78.65574649423108,\n 77.10125412081042\n ],\n [\n -77.10695875969516,\n 77.55350276995543\n ],\n [\n -77.62519223796996,\n 77.82434372642628\n ],\n [\n -75.7966361104242,\n 77.8025244627687\n ],\n [\n -73.58736344454267,\n 78.68587525427046\n ],\n [\n -74.2071031613077,\n 78.92332303684364\n ],\n [\n -74.189651370556,\n 79.29626187736939\n ],\n [\n -72.19459843728198,\n 79.52379261066676\n ],\n [\n -70.67502496448732,\n 79.75832709103807\n ],\n [\n -68.88387582346442,\n 80.33816075766248\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"75","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":886938,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249673,"text":"70249673 - 2022 - Inversion of induced polarization-affected towed-transient electromagnetic data in a lateritic regolith geology: A case study from western Tanzania","interactions":[],"lastModifiedDate":"2023-10-24T11:47:23.229236","indexId":"70249673","displayToPublicDate":"2022-06-01T06:37:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Inversion of induced polarization-affected towed-transient electromagnetic data in a lateritic regolith geology: A case study from western Tanzania","docAbstract":"

For several decades, induced polarization (IP) effects on transient electromagnetic (TEM) responses have been observed. These effects can manifest as late-time negative transients or as rapidly decaying curves and are usually associated with highly polarizable bodies. If neglected, IP effects can lead to erroneous resistivity models. Recent work allows IP effects to be incorporated into the inversion of TEM data on a more routine basis. In a recent field survey in western Tanzania, strongly IP-affected TEM signals are observed using a towed-transient electromagnetic (tTEM) system. The survey have been carried out to locate drinking water resources in a weathered regolith setting. In these settings, an inversion of tTEM data using a resistivity-only forward model (i.e., IP neglected) cannot fit the data and severely limits the value of the TEM data for hydrogeologic interpretation. To account for IP effects, we have applied a modified version of the Cole-Cole model called the maximum phase angle (MPA) model to invert IP-affected tTEM data. The MPA model incorporates four inversion model parameters: resistivity (⁠ρ\">ρ), MPA (⁠ϕmax\">ϕmax⁠), relaxation time (⁠τ\">τ), and frequency exponent (⁠c\">c). The MPA model fits the data well and improves the reliability of the resistivity model. In much of the surveyed region, the inverted models using MPA display a three-layer system consisting of an upper resistive laterite layer of varying thickness and an intermediate polarizable conductive unit overlying more resistive weathered basement rocks. The conductive polarizable layer is interpreted as a chemically weathered saprolite separating the surficial and deeper aquifers. Overall, tTEM inversion results provide a local understanding of groundwater systems, especially in such regions with very limited subsurface knowledge.

","language":"English","publisher":"Society of Exploration Geophysics","doi":"10.1190/geo2021-0396.1","usgsCitation":"Maurya, P.K., Grombacher, D., Lind, J., Lane, J.W., and Auken, E., 2022, Inversion of induced polarization-affected towed-transient electromagnetic data in a lateritic regolith geology: A case study from western Tanzania: Geophysics, v. 87, no. 4, p. B247-B254, https://doi.org/10.1190/geo2021-0396.1.","productDescription":"8 p.","startPage":"B247","endPage":"B254","ipdsId":"IP-129592","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":422061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tanzania","city":"Kaguruka, Kitagata","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 30.26631758554646,\n -4.307213040551957\n ],\n [\n 30.26631758554646,\n -4.45300782969197\n ],\n [\n 30.49585195666816,\n -4.45300782969197\n ],\n [\n 30.49585195666816,\n -4.307213040551957\n ],\n [\n 30.26631758554646,\n -4.307213040551957\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 30.2257012708871,\n -4.777233849561554\n ],\n [\n 30.2257012708871,\n -4.817521702247873\n ],\n [\n 30.294869797065786,\n -4.817521702247873\n ],\n [\n 30.294869797065786,\n -4.777233849561554\n ],\n [\n 30.2257012708871,\n -4.777233849561554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Maurya, Pradip Kumar","contributorId":214855,"corporation":false,"usgs":false,"family":"Maurya","given":"Pradip","email":"","middleInitial":"Kumar","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":886697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grombacher, Denys","contributorId":331071,"corporation":false,"usgs":false,"family":"Grombacher","given":"Denys","email":"","affiliations":[],"preferred":false,"id":886698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":886675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lind, Johan","contributorId":331072,"corporation":false,"usgs":false,"family":"Lind","given":"Johan","email":"","affiliations":[],"preferred":false,"id":886699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Auken, Esben","contributorId":193991,"corporation":false,"usgs":false,"family":"Auken","given":"Esben","email":"","affiliations":[],"preferred":false,"id":886700,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262275,"text":"70262275 - 2022 - Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York","interactions":[],"lastModifiedDate":"2025-01-22T20:31:54.917634","indexId":"70262275","displayToPublicDate":"2022-06-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York","docAbstract":"

Round Goby Neogobius melanostomus, a nonnative fish species to North America, has been rapidly expanding through the connected waterways of the Laurentian Great Lakes. Herein, we document the eastward and southern expansion of Round Goby into the Hudson River, New York, an iconic coastal estuary that drains to Long Island Sound and the Atlantic seaboard. In summer and early fall 2021, routine fish monitoring conducted by the New York State Department of Environmental Conservation documented a population of Round Goby in the tidal portion of the Hudson River. Over the course of monitoring in 2021, personnel collected 112 Round Goby between Albany, New York, and Poughkeepsie, New York, with the southernmost collection occurring approximately 140 km downstream of invasion front as reported in 2020 within the New York State Canal System. Although Round Goby previously colonized large rivers and streams in the Great Lakes watershed, there is little information about the invasion success and ecological impacts of Round Goby in estuarine environments in North America. We discuss the distribution and biological characteristics of the Hudson River Round Goby population as well as the potential ecological implications and areas of future research and monitoring for this range expansion.

","language":"English","publisher":"Allen Press","doi":"10.3996/jfwm-22-012","usgsCitation":"Pendleton, R., Berdan, R., George, S.D., Kenney, G., and Sethi, S., 2022, Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 524-533, https://doi.org/10.3996/jfwm-22-012.","productDescription":"10 p.","startPage":"524","endPage":"533","ipdsId":"IP-138487","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-22-012","text":"Publisher Index Page"},{"id":480950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson 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York\",\"nation\":\"USA \"}}]}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Pendleton, Richard","contributorId":348720,"corporation":false,"usgs":false,"family":"Pendleton","given":"Richard","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":923718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berdan, Russell","contributorId":348721,"corporation":false,"usgs":false,"family":"Berdan","given":"Russell","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":923719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenney, Gregg","contributorId":348722,"corporation":false,"usgs":false,"family":"Kenney","given":"Gregg","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":923721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923722,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262182,"text":"70262182 - 2022 - Review of field methods for monitoring Asian bears","interactions":[],"lastModifiedDate":"2025-01-15T15:48:50.052344","indexId":"70262182","displayToPublicDate":"2022-06-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Review of field methods for monitoring Asian bears","docAbstract":"

Efficient and effective monitoring methods are required to assess population status and gauge efficacy of conservation actions for threatened species. Here we review the spectrum of field methods useful for monitoring distribution, occupancy, abundance, and population trend for the five species of Asian terrestrial bears. Methods reviewed include expert opinion, local knowledge, bear sign, visual observations, camera traps, DNA-based methods (hair and scat derived), and radio telemetry. We examine the application of each method in terms of realizing specific monitoring objectives, their assumptions, challenges, and advantages. Our goal is to assist researchers in matching appropriate field methods with sought-after project objectives and to highlight shortfalls and trade-offs. Methods vary greatly in terms of cost, logistics, required number and expertise of staff, and the reliability of the data they provide. Many Asian bear population assessments have relied on expert opinion, local interviews, and sign surveys to provide estimates of distribution, abundance, and trend, in part because these are inexpensive and relatively easy to employ. However, increasing use of camera traps and DNA-based methods now allow for better monitoring via occupancy or rigorous capture–recapture population estimation, with the caveat that these methods may be restricted by inadequate budgets or logistical constraints. For distribution monitoring, camera traps and DNA yield the most definitive records of presence, but in low density bear populations, sign and local knowledge may be more effective. For occupancy, camera traps and DNA are advantageous in providing definitive detections in known time periods. For abundance/density or population trend monitoring in relatively small areas (<10,000 km2), bears must be individually identified and used in a mark-recapture design. This requires DNA from collections of hair or scat, or a camera-based survey in which natural chest marks are clearly visible and individually distinguishable. DNA-methods or camera traps within individual identification is best for population trend when sufficient funding is available. Alternatively, careful use of local knowledge or expert opinion may be viable options, but come with greater uncertainty. For the foreseeable future, we believe that expert opinion will likely continue to play a large part in monitoring Asian bears, but these opinions should be informed by more rigorous data from the other methods we discuss.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02080","usgsCitation":"Proctor, M., Garshelis, D., Thatte, P., Steinmetz, R., Crudge, B., McLellan, B., McShea, W., Ngoprasert, D., Nawaz, M., Wong, S.T., Sharma, S., Fuller, A.K., Dharaiya, N., Pigeon, K., Fredriksson, G., Wang, D., Li, S., and Hwang, M., 2022, Review of field methods for monitoring Asian bears: Global Ecology and Conservation, v. 35, e02080, 25 p., https://doi.org/10.1016/j.gecco.2022.e02080.","productDescription":"e02080, 25 p.","ipdsId":"IP-135698","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02080","text":"Publisher Index Page"},{"id":466419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Proctor, Michael F.","contributorId":348345,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael F.","affiliations":[{"id":83340,"text":"IUCN SSC Bear Specialist Group","active":true,"usgs":false}],"preferred":false,"id":923379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garshelis, David L.","contributorId":348346,"corporation":false,"usgs":false,"family":"Garshelis","given":"David L.","affiliations":[{"id":83340,"text":"IUCN SSC Bear Specialist Group","active":true,"usgs":false}],"preferred":false,"id":923380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thatte, Prachi","contributorId":348347,"corporation":false,"usgs":false,"family":"Thatte","given":"Prachi","affiliations":[{"id":83342,"text":"Tata Institute of Fundamental Research","active":true,"usgs":false}],"preferred":false,"id":923381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steinmetz, Robert","contributorId":348348,"corporation":false,"usgs":false,"family":"Steinmetz","given":"Robert","affiliations":[{"id":83340,"text":"IUCN SSC Bear Specialist Group","active":true,"usgs":false}],"preferred":false,"id":923382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crudge, Brian","contributorId":348349,"corporation":false,"usgs":false,"family":"Crudge","given":"Brian","affiliations":[{"id":83344,"text":"University of South-Eastern Norway","active":true,"usgs":false}],"preferred":false,"id":923383,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McLellan, Bruce N.","contributorId":348350,"corporation":false,"usgs":false,"family":"McLellan","given":"Bruce N.","affiliations":[{"id":83345,"text":"Lands and Natural Resource Operations and Rural Development","active":true,"usgs":false}],"preferred":false,"id":923384,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McShea, William J.","contributorId":348351,"corporation":false,"usgs":false,"family":"McShea","given":"William J.","affiliations":[{"id":37784,"text":"Smithsonian Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":923385,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ngoprasert, Dusit","contributorId":348352,"corporation":false,"usgs":false,"family":"Ngoprasert","given":"Dusit","affiliations":[{"id":83346,"text":"King Mongkut’s University of Technology Thonburi","active":true,"usgs":false}],"preferred":false,"id":923386,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nawaz, M. Ali","contributorId":348353,"corporation":false,"usgs":false,"family":"Nawaz","given":"M. Ali","affiliations":[{"id":54794,"text":"Qatar University","active":true,"usgs":false}],"preferred":false,"id":923387,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wong, Siew Te","contributorId":245378,"corporation":false,"usgs":false,"family":"Wong","given":"Siew","email":"","middleInitial":"Te","affiliations":[{"id":49173,"text":"Bornean Sun Bear Conservation Centre","active":true,"usgs":false}],"preferred":false,"id":923585,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sharma, Sandeep","contributorId":348362,"corporation":false,"usgs":false,"family":"Sharma","given":"Sandeep","affiliations":[{"id":62105,"text":"University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":923586,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923378,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dharaiya, Nishith","contributorId":348566,"corporation":false,"usgs":false,"family":"Dharaiya","given":"Nishith","affiliations":[],"preferred":false,"id":923587,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pigeon, Karine","contributorId":247532,"corporation":false,"usgs":false,"family":"Pigeon","given":"Karine","email":"","affiliations":[{"id":49573,"text":"fRi Research, Alberta","active":true,"usgs":false}],"preferred":false,"id":923588,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fredriksson, Gabriella","contributorId":348567,"corporation":false,"usgs":false,"family":"Fredriksson","given":"Gabriella","affiliations":[],"preferred":false,"id":923589,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wang, Dajun","contributorId":348568,"corporation":false,"usgs":false,"family":"Wang","given":"Dajun","affiliations":[],"preferred":false,"id":923590,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Li, Sheng","contributorId":334448,"corporation":false,"usgs":false,"family":"Li","given":"Sheng","affiliations":[],"preferred":false,"id":923591,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Hwang, Mei-hsiu","contributorId":348569,"corporation":false,"usgs":false,"family":"Hwang","given":"Mei-hsiu","affiliations":[],"preferred":false,"id":923592,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70231844,"text":"fs20223036 - 2022 - Rangeland Condition Monitoring Assessment and Projection (RCMAP)","interactions":[],"lastModifiedDate":"2023-01-26T13:30:44.024178","indexId":"fs20223036","displayToPublicDate":"2022-05-31T13:41:39","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3036","displayTitle":"Rangeland Condition Monitoring Assessment and Projection (RCMAP)","title":"Rangeland Condition Monitoring Assessment and Projection (RCMAP)","docAbstract":"

The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project has partnered with the Bureau of Land Management to provide annual maps of rangeland vegetation condition across the Western United States from 1985 to present. Annual mapping can assist land managers and scientists with monitoring changes to vegetation composition, evaluating past management practices, targeting future improvements, determining locations of critical wildlife habitat, and assessing landscape health and fragmentation. Impacts of climate variability and long-term change are often gradual and frequently do not present as a land cover change (for example, shrubland to grassland); however, RCMAP fractional vegetation cover data capture these gradual changes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223036","usgsCitation":"Rigge, M.B., 2022, Rangeland Condition Monitoring Assessment and Projection (RCMAP): U.S. Geological Survey Fact Sheet 2022–3036, 2 p., https://doi.org/10.3133/fs20223036.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-139947","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":401389,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223036/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":401374,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3036/coverthb.jpg"},{"id":401375,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3036/fs20223036.pdf","text":"Report","size":"8.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3036"},{"id":401377,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3036/images"},{"id":401376,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3036/fs20223036.XML"}],"contact":"

Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-31","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":843952,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256660,"text":"70256660 - 2022 - Modeling and estimating co-occurrence between the invasive Shiny Cowbird and its Puerto Rican hosts","interactions":[],"lastModifiedDate":"2024-08-29T15:47:20.559343","indexId":"70256660","displayToPublicDate":"2022-05-31T10:33:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and estimating co-occurrence between the invasive Shiny Cowbird and its Puerto Rican hosts","docAbstract":"

Invasive species threaten island biodiversity globally. For example, the Shiny Cowbird (Molothrus bonariensis) parasitizes many of Puerto Rico’s endemic species, particularly in the open forests in the island’s southwest. Less is known, however, about cowbird parasitism in the agro-ecological highlands, which contain a patchwork of forests, shaded-coffee plantations, and coffee farms without shade. In this paper, we estimated co-occurrence rates, a potential indicator of parasitism rates, between the cowbird and four host species across these three land uses, hypothesizing that cowbirds would most likely co-occur with their hosts in shaded-coffee farms. We also hypothesized that the presence of host species would increase the probability of cowbird occurrence. To investigate these hypotheses, we developed three Bayesian hierarchical occupancy models: one where the hosts and parasite occurred independently, one that used the latent host species richness as a predictor of cowbird occurrence, and one that used each latent host occurrence state as predictors. These methods addressed observation errors and appropriately propagated error to our predictions of co-occurrence rates. We selected the best performing model using WAIC, then used it to predict co-occurrence rates. While there was some evidence that host species richness increased the probability of cowbirds, the parsimonious model assumed no interaction. With this model, we found that cowbirds were more likely to overlap with certain hosts in shaded-coffee plantations. This may suggest increased parasitism at these plantations, potentially presenting challenges for managers who advocate for shade restoration to gain ecological services such as biodiversity conservation.

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0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908540,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231843,"text":"70231843 - 2022 - 2021 Tinian Island forest bird abundance estimates","interactions":[],"lastModifiedDate":"2022-05-31T13:46:34.099268","indexId":"70231843","displayToPublicDate":"2022-05-31T08:25:54","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":257,"text":"Hawai‘i Cooperative Studies Unit Technical Report","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"105","title":"2021 Tinian Island forest bird abundance estimates","docAbstract":"

The U.S. Navy, through Micronesian Environmental Services, surveyed landbirds in the Military Lease Area on Tinian Island in May and June 2021 using point-transect distance sampling methods. There were 2,074 individuals of 14 species detected during 123 point counts. Six species were detected during >50% of the counts and were observed at relatively high abundances, while eight species occurred at <50% of the counts and were uncommon to rare. Densities of native landbirds in the Military Lease Area ranged from the uncommon Mariana kingfisher (Todiramphus albicilla) at 0.46 birds/ha (95% confidence interval [CI] = 0.33–0.63) to the very abundant bridled white-eye (Zosterops conspicillatus) at 102.63 birds/ha (95%CI = 86.70–122.91). Most distances recorded during the 2021 Military Lease Area survey were rounded to distance intervals of 0 and 5. Measuring exact distances of detected animals is preferable to collecting distances grouped into bins or rounding. Direct comparison with previously published estimates was not possible because of changes in the sampling frame; however, densities of six species were greater, two were smaller, and one was similar to the 2008 survey estimates for the Hagoi, Diablo, and Masalog regions. Our findings indicate that the landbird community in the Military Lease Area appears to be dynamic and resilient.

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LANDFIRE is a Federal program that provides a suite of spatial datasets indicating areas of disturbance, vegetation and fuels distributions and structure, and historical conditions. The level of detail presented in LANDFIRE’s classifications of disturbance, vegetation, and fuels is unparalleled and can be used in a variety of applications, including (1) modeling wildfire risk and fire behavior, (2) modeling habitat and species ranges, (3) understanding how disturbances affect the landscape, and (4) researching departure from precolonial conditions. Additionally, the all-lands paradigm of LANDFIRE mapping creates spatial data that do not stop at jurisdictional boundaries. The primary research and management applications of LANDFIRE data are detailed in this fact sheet, providing users with a well-rounded understanding of the potential of LANDFIRE’s spatial data layers.

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LANDFIRE help desk
Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-31","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"La Puma, Inga P. 0000-0002-6865-820X","orcid":"https://orcid.org/0000-0002-6865-820X","contributorId":206011,"corporation":false,"usgs":false,"family":"La Puma","given":"Inga","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":843525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatten, Timothy D. 0000-0003-3413-4325","orcid":"https://orcid.org/0000-0003-3413-4325","contributorId":291959,"corporation":false,"usgs":false,"family":"Hatten","given":"Timothy D.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":843526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256099,"text":"70256099 - 2022 - Lake Barkley BioAcoustic fish fence effectiveness study project status update","interactions":[],"lastModifiedDate":"2024-07-22T11:55:34.569373","indexId":"70256099","displayToPublicDate":"2022-05-31T06:51:22","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Lake Barkley BioAcoustic fish fence effectiveness study project status update","docAbstract":"

No abstract available. 

","language":"English","publisher":"U.S. Fish and Wildlife Service","collaboration":"Great Lakes Fishery Commission (GLFC); Great Lakes Restoration Initiative (GLRI); Invasive Carp Regional Coordinating Committee (ICRCC); U.S. Army Corps of Engineers (USACE); U.S. Fish and Wildlife Service (USFWS); Kentucky Department of Fish and Wildlife Resources; University of MN; and Fish Guidance Systems","usgsCitation":"Simmonds, R., Knights, B.C., Fritts, A.K., Stanton, J.C., Brey, M.K., and Vallazza, J.M., 2022, Lake Barkley BioAcoustic fish fence effectiveness study project status update, 1 p.","productDescription":"1 p.","ipdsId":"IP-136972","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":431300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":431290,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://controlinvasivecarpmn.com/wp-content/uploads/2022/02/lake-barkley-bio-acoustic-fish-fence-Jan-2022-pahmplet-1-1.pdf"}],"country":"United States","state":"Kentucky","otherGeospatial":"Lake Barkley, Barkley Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.3011119114417,\n 37.03353323113609\n ],\n [\n -88.3011119114417,\n 36.99818111699841\n ],\n [\n -88.24551735688884,\n 36.99818111699841\n ],\n [\n -88.24551735688884,\n 37.03353323113609\n ],\n [\n -88.3011119114417,\n 37.03353323113609\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Simmonds, Rob","contributorId":317890,"corporation":false,"usgs":false,"family":"Simmonds","given":"Rob","email":"","affiliations":[{"id":68344,"text":"U.S. Fish and Wildlife Service (USFWS)","active":true,"usgs":false}],"preferred":false,"id":906685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906689,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906690,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237968,"text":"70237968 - 2022 - River Metabolism Estimation Tools (RiverMET) with demo in the Illinois River Basin","interactions":[],"lastModifiedDate":"2022-11-02T11:49:35.521099","indexId":"70237968","displayToPublicDate":"2022-05-31T06:47:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12802,"text":"ESSOAr","active":true,"publicationSubtype":{"id":10}},"title":"River Metabolism Estimation Tools (RiverMET) with demo in the Illinois River Basin","docAbstract":"

Ecosystem metabolism quantifies the rate of production, maintenance, and decay of organic matter in terrestrial and aquatic systems. It is a fundamental measure of energy flow associated with biomass production by photosynthesizing organisms and biomass oxidation by respiring plants, animals, algae, and bacteria (Bernhardt et al., 2022) . Ecosystem metabolism also provides an understanding of energy flow to higher trophic levels that supports secondary and tertiary productivity, as well as helping to explain when aquatic ecosystems undergo out-of-balance behaviors such as harmful algal blooms and hypoxia. Recent advances in sensor technology and modeling capabilities have enabled estimation of aquatic system metabolism and gas exchange over long time periods in rivers, streams, ponds, and wetlands where oxygen sensors have been deployed. Here we present RiverMET, a framework for estimation of river metabolism, with workflows to streamline data preparation, run a stream metabolism model, assess the model performance, and flag and censor final output data. The workflows are specifically tailored to use streamMetabolizer, a model for one-station calculations of stream metabolism that calculates gross primary productivity (GPP), ecosystem respiration (ER) and the air-water gas exchange rate constant (K600). We advise potential users of RiverMET to review core publications for the streamMetabolizer model (Appling et al., 2018 a, b, c) to ensure best practices that produce the most useful results. We encourage feedback about our workflows, although issues regarding the streamMetabolizer model itself should be referred to the model authors. We tested RiverMET by calculating GPP, ER, and K600 across 17 river sites in the Illinois River basin (ILRB). Each river had between one and nine years of sensor data appropriate for modeling metabolism. In total, metabolism was modeled on 15,176 days between 2005 and 2020. Overall confidence in the results was rated as high at nine river sites, medium at six river sites, and poor at two river sites. Twenty-nine percent of the total modeled days had performance metrics that triggered flags. Metrics used for daily flagging are provided with the final output, with an option to only retain the censored daily outputs with high confidence (representing 72 %, i.e., 10,938 days, of the total days modeled). This work was completed as part of the U.S. Geological Survey Proxies Project, an effort supported by the Water Mission Area (WMA) Water Quality Processes program to develop estimation methods for harmful algal blooms (HABs), per- and polyfluoroalkyl substances (PFAS), and metals, at multiple spatial and temporal scales.

","language":"English","publisher":"Earth and Space Science Open Archive","doi":"10.1002/essoar.10511255.1","usgsCitation":"Choi, J., Quion, K.M., Reed, A., and Harvey, J., 2022, River Metabolism Estimation Tools (RiverMET) with demo in the Illinois River Basin: ESSOAr, 22 p., https://doi.org/10.1002/essoar.10511255.1.","productDescription":"22 p.","ipdsId":"IP-139945","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":435833,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TEBOUR","text":"USGS data release","linkHelpText":"RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020"},{"id":409056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Illinois River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.901423683579,\n 42.70071815175049\n ],\n [\n -91.86724399607925,\n 42.70071815175049\n ],\n [\n -91.86724399607925,\n 39.14935275277796\n ],\n [\n -86.901423683579,\n 39.14935275277796\n ],\n [\n -86.901423683579,\n 42.70071815175049\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choi, Jay 0000-0003-1276-481X jchoi@usgs.gov","orcid":"https://orcid.org/0000-0003-1276-481X","contributorId":219096,"corporation":false,"usgs":true,"family":"Choi","given":"Jay","email":"jchoi@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":856403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quion, Katherine Michelle Bernabe 0000-0003-2388-7508","orcid":"https://orcid.org/0000-0003-2388-7508","contributorId":298787,"corporation":false,"usgs":true,"family":"Quion","given":"Katherine","email":"","middleInitial":"Michelle Bernabe","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":856404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Ariel 0000-0002-0792-5204","orcid":"https://orcid.org/0000-0002-0792-5204","contributorId":298788,"corporation":false,"usgs":false,"family":"Reed","given":"Ariel","affiliations":[],"preferred":false,"id":856405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":856406,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239791,"text":"70239791 - 2022 - Hydrologic controls on peat permafrost and carbon processes: New insights from past and future modeling","interactions":[],"lastModifiedDate":"2023-01-20T12:46:34.734013","indexId":"70239791","displayToPublicDate":"2022-05-31T06:44:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic controls on peat permafrost and carbon processes: New insights from past and future modeling","docAbstract":"

Soil carbon (C) in permafrost peatlands is vulnerable to decomposition with thaw under a warming climate. The amount and form of C loss likely depends on the site hydrology following permafrost thaw, but antecedent conditions during peat accumulation are also likely important. We test the role of differing hydrologic conditions on rates of peat accumulation, permafrost formation, and response to warming at an Arctic tundra fen using a process-based model of peatland dynamics in wet and dry landscape settings that persist from peat initiation in the mid-Holocene through future simulations to 2100 CE and 2300 CE. Climate conditions for both the wet and dry landscape settings are driven by the same downscaled TraCE-21ka transient paleoclimate simulations and CCSM4 RCP8.5 climate drivers. The landscape setting controlled the rates of peat accumulation, permafrost formation and the response to climatic warming and permafrost thaw. The dry landscape scenario had high rates of initial peat accumulation (11.7 ± 3.4 mm decade−1) and rapid permafrost aggradation but similar total C stocks as the wet landscape scenario. The wet landscape scenario was more resilient to 21st century warming temperatures than the dry landscape scenario and showed 60% smaller C losses and 70% more new net peat C additions by 2100 CE. Differences in the modeled responses indicate the largest effect is related to the landscape setting and basin hydrology due to permafrost controls on decomposition, suggesting an important sensitivity to changing runoff patterns. These subtle hydrological effects will be difficult to capture at circumpolar scales but are important for the carbon balance of permafrost peatlands under future climate warming.

","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2022.892925","usgsCitation":"Treat, C.C., Jones, M.C., Alder, J.R., and Frolking, S., 2022, Hydrologic controls on peat permafrost and carbon processes: New insights from past and future modeling: Frontiers in Environmental Science, v. 10, 892925, 14 p., https://doi.org/10.3389/fenvs.2022.892925.","productDescription":"892925, 14 p.","ipdsId":"IP-136803","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":447603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.892925","text":"Publisher Index Page"},{"id":412111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Treat, Claire C.","contributorId":150798,"corporation":false,"usgs":false,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":861966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":861967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":861968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frolking, Steve","contributorId":301087,"corporation":false,"usgs":false,"family":"Frolking","given":"Steve","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":861969,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231871,"text":"70231871 - 2022 - Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region","interactions":[],"lastModifiedDate":"2022-08-02T14:22:39.473636","indexId":"70231871","displayToPublicDate":"2022-05-31T06:32:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region","docAbstract":"

Sea level rise (SLR) and saltwater intrusion are driving inland shifts in coastal ecosystems. Here, we make high-resolution (1 m) predictions of land conversion under future SLR scenarios in 81 watersheds surrounding Chesapeake Bay, United States, a hotspot for accelerated SLR and saltwater intrusion. We find that 1050–3748 km2 of marsh could be created by 2100, largely at the expense of forested wetlands. Predicted marsh migration exceeds total current tidal marsh area and is ~ 4× greater than historical observations. Anthropogenic land use in marsh migration areas is concentrated within a few watersheds and minimally impacts calculated metrics of marsh resilience. Despite regional marsh area maintenance, local ecosystem service replacement within vulnerable watersheds remains uncertain. However, our work suggests that topography rather than land use drives spatial variability in wetland vulnerability regionally, and that rural land conversion is needed to compensate for extensive areal losses on heavily developed coasts globally.

","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10262","usgsCitation":"Molino, G., Carr, J., Ganju, N., and Kirwan, M.L., 2022, Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region: Limnology and Oceanography Letters, v. 7, no. 4, p. 321-331, https://doi.org/10.1002/lol2.10262.","productDescription":"11 p.","startPage":"321","endPage":"331","ipdsId":"IP-133300","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447606,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/lol2.10262","text":"External Repository"},{"id":401520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.849609375,\n 39.52099229357195\n ],\n [\n -76.201171875,\n 39.774769485295465\n ],\n [\n -76.79443359375,\n 39.740986355883564\n ],\n [\n -77.23388671874999,\n 39.36827914916014\n ],\n [\n -77.40966796875,\n 38.496593518947584\n ],\n [\n -77.27783203125,\n 37.24782120155428\n ],\n [\n -76.81640625,\n 36.66841891894786\n ],\n [\n -76.1572265625,\n 36.50963615733049\n ],\n [\n -75.89355468749999,\n 36.56260003738545\n ],\n [\n -76.00341796875,\n 36.94989178681327\n ],\n [\n -74.970703125,\n 38.37611542403604\n ],\n [\n -75.25634765625,\n 38.41055825094609\n ],\n [\n -75.498046875,\n 38.25543637637947\n ],\n [\n -75.7177734375,\n 38.30718056188316\n ],\n [\n -75.849609375,\n 39.027718840211605\n ],\n [\n -75.849609375,\n 39.52099229357195\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Molino, Grace 0000-0001-7345-8619","orcid":"https://orcid.org/0000-0001-7345-8619","contributorId":292186,"corporation":false,"usgs":false,"family":"Molino","given":"Grace","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":844013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Matt L.","contributorId":189205,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matt","middleInitial":"L.","affiliations":[],"preferred":false,"id":844016,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232391,"text":"70232391 - 2022 - Geochemical characterization of natural gases in the pre-salt section of the Santos Basin (Brazil) focused on hydrocarbons and volatile organic sulfur compounds","interactions":[],"lastModifiedDate":"2022-08-02T15:05:01.533248","indexId":"70232391","displayToPublicDate":"2022-05-30T17:40:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical characterization of natural gases in the pre-salt section of the Santos Basin (Brazil) focused on hydrocarbons and volatile organic sulfur compounds","docAbstract":"

The objective of this work is to characterize the geochemistry of a suite of natural gas samples from five fields in order to improve the understanding of the lacustrine petroleum system of the pre-salt section from the Santos Basin (Brazil). Additionally, the distribution of volatile organic sulfur compounds (VOSC) in petroleum reservoirs was examined to investigate possible applications to petroleum systems assessments. The hydrocarbon gases were generated by thermogenic processes associated with the oil window. The 13C-enriched values for C1 (>−40‰) were interpreted as an organic source signature rather than an indication of thermal maturity, except for the oil occurrence (Field B), where a different fluid charge mainly composed of methane and CO2 from a minor external kitchen area in the Santos Basin was identified. The molecular composition and the carbon and hydrogen isotopic data of the hydrocarbon gases, when combined with the VOSC molecular compositional data, allow the identification of four gas families associated with different kitchens and/or migrations pathways. The total VOSC concentrations range from 0.7 to 23.9 ppm by volume (ppmV). The organic sulfides are mainly composed of carbonyl sulfide (COS) and diethyl sulfide. The main thiol compound is ethanethiol. The cyclic VOSC are primarily composed of thiophene, with a negligible amount of branched thiophenes (<0.1 ppmV). H2S showed a strong positive Pearson's correlation with COS and methanethiol (MeSH) concentrations (r = 0.943 and 0.807, respectively). This suggests that COS and MeSH formation was linked to H2S generation and/or post-catagenetic interactions between hydrocarbons and H2S, mainly related to thermochemical sulfate reduction (TSR). In contrast, the distribution of higher molecular weight VOSC seems to be controlled by source rock facies, rather than H2S concentration. Principal component analysis of the VOSC compositional data identified some subgroups within the gas families mainly associated with TSR. The results presented in this work reveal that VOSC can be an important auxiliary tool in petroleum system studies.

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