Stream fish distributions are hypothesized to be strongly associated with landscape characteristics at multiple scales. Variation in flow regimes and intensity of landscape disturbance are associated with stream fish distributions; however, relationships are poorly understood in many high-diversity regions. Our objective was to identify occurrence relationships between fish distributions and streamflow and landscape characteristics in the south-central United States.
Our study area was the central Red River catchment in Oklahoma, Texas and Arkansas, USA.
We used existing fish surveys to model the occurrence of a diverse, warmwater assemblage among hydraulic response units (HRUs). We used multispecies occupancy modelling to identify variation in occurrence probability among 111 stream fishes in relation to landscape disturbance and flow regime characteristics.
We found occurrence relationships with landscape disturbance and 11 metrics comprising all flow-regime components. The relationships varied within both major species groups and some genera. Frequency and duration were the most common metrics underlying flow regime relationships. More common stream fishes tended to be positively associated with higher levels of landscape disturbance and flow regime metrics representing variability; conversely, narrow-ranged fishes tended to be negatively associated. Occurrence relationships with flow metrics representing high-flow events were predominately negative. As expected, many species were strongly associated with ecoregion with landscape disturbance and flow relationships held constant.
Our study informs land use and water management decisions and stream fish conservation at multiple spatial scales. Collectively, the findings suggest potential homogenization of the Red River fish assemblage with increased landscape disturbance and streamflow variability. A reduction in landscape disturbance and maintenance of natural flow patterns at coarser scales may benefit endemic and narrow-ranged fishes. Our findings also help guide finer-scale land use and water management decisions by identifying stream network areas with a high occurrence probability of less tolerant fishes.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13595","usgsCitation":"Mollenhauer, R., Mouser, J., Roland, V., and Brewer, S.K., 2022, Increased landscape disturbance and streamflow variability threaten fish biodiversity in the Red River catchment, USA: Diversity and Distributions, v. 28, no. 9, p. 1934-1950, https://doi.org/10.1111/ddi.13595.","productDescription":"17 p.","startPage":"1934","endPage":"1950","ipdsId":"IP-122736","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13595","text":"Publisher Index Page"},{"id":433318,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Oklahoma, Texas","otherGeospatial":"Red River catchment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.5,\n 35.5\n ],\n [\n -98.5,\n 33\n ],\n [\n -92.5,\n 33\n ],\n [\n -92.5,\n 35.5\n ],\n [\n -98.5,\n 35.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, R.","contributorId":276144,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"R.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roland, Victor L. vroland@usgs.gov","contributorId":5879,"corporation":false,"usgs":true,"family":"Roland","given":"Victor L.","email":"vroland@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":908551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908552,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232473,"text":"70232473 - 2022 - A model of the spatiotemporal dynamics of soil carbon following coastal wetland loss applied to a Louisiana salt marsh in the Mississippi River Deltaic Plain","interactions":[],"lastModifiedDate":"2023-06-09T13:37:02.064318","indexId":"70232473","displayToPublicDate":"2022-07-04T10:04:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"A model of the spatiotemporal dynamics of soil carbon following coastal wetland loss applied to a Louisiana salt marsh in the Mississippi River Deltaic Plain","docAbstract":"The potential for carbon sequestration in coastal wetlands is high due to protection of carbon (C) in flooded soils. However, excessive flooding can result in the conversion of the vegetated wetland to open water. This transition results in the loss of wetland habitat in addition to the potential loss of soil carbon. Thus, in areas experiencing rapid wetland submergence, such as the Mississippi River Delta, coastal wetlands could become a significant source of carbon emissions if land loss is not mitigated. To accurately assess the capacity of wetlands to store (or emit) carbon in dynamic environments, it is critical to understand the fate of soil carbon following the transition from vegetated wetland to open water. We developed a simple soil carbon model representing soil depths to 1 m using the data collected from a Louisiana coastal salt marsh in the Mississippi River Deltaic Plain to predict soil carbon density and stock following the transition from a vegetated salt marsh to an open water pond. While immediate effects of ponding on the distribution of carbon within the 1-m soil profile were apparent, there were no effects of ponding on the overall, integrated, carbon stocks 14 years, following wetland submergence. Rather, the model predicts that soil carbon losses in the first meter will be realized over long periods of time (∼200 years) due to changes in the source of carbon (biomass vs. mineral sediment) with minimal losses through mineralization.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JG006807","usgsCitation":"Schoolmaster, D.R., Stagg, C., Creamer, C., Laurenzano, C., Ward, E., Waldrop, M., Baustian, M., Aw, T., Merino, S., Villani, R.K., and Scott, L., 2022, A model of the spatiotemporal dynamics of soil carbon following coastal wetland loss applied to a Louisiana salt marsh in the Mississippi River Deltaic Plain: Journal of Geophysical Research: Biogeosciences, v. 127, no. 6, e2022JG006807, 15 p.; Data Release, https://doi.org/10.1029/2022JG006807.","productDescription":"e2022JG006807, 15 p.; Data Release","ipdsId":"IP-133880","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":402921,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417836,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P916JH3L"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.0050048828125,\n 29.807284450222504\n ],\n [\n -91.263427734375,\n 29.176145182559758\n ],\n [\n -90.274658203125,\n 29.036960648558267\n ],\n [\n -89.17053222656249,\n 28.91682310329166\n ],\n [\n -89.000244140625,\n 29.10897615145302\n ],\n [\n -89.3023681640625,\n 29.869228848968312\n ],\n [\n -90.439453125,\n 30.130875412002318\n ],\n [\n -90.889892578125,\n 30.424992973925598\n ],\n [\n -91.351318359375,\n 31.01057105944174\n ],\n [\n -91.9171142578125,\n 30.99173704508671\n ],\n [\n -92.0050048828125,\n 29.807284450222504\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":845615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":220330,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":218316,"corporation":false,"usgs":false,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845618,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":217389,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":845620,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baustian, Melissa M.","contributorId":189569,"corporation":false,"usgs":false,"family":"Baustian","given":"Melissa M.","affiliations":[],"preferred":false,"id":845621,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Aw, Tiong","contributorId":292731,"corporation":false,"usgs":false,"family":"Aw","given":"Tiong","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":845622,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Merino, Sergio 0000-0002-2834-2243 merinos@usgs.gov","orcid":"https://orcid.org/0000-0002-2834-2243","contributorId":3653,"corporation":false,"usgs":true,"family":"Merino","given":"Sergio","email":"merinos@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845623,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Villani, Rachel Katherine 0000-0002-8494-8178","orcid":"https://orcid.org/0000-0002-8494-8178","contributorId":290308,"corporation":false,"usgs":true,"family":"Villani","given":"Rachel","email":"","middleInitial":"Katherine","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845624,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Scott, Laura 0000-0003-0303-5340","orcid":"https://orcid.org/0000-0003-0303-5340","contributorId":292733,"corporation":false,"usgs":false,"family":"Scott","given":"Laura","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":845625,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70232470,"text":"70232470 - 2022 - Mentoring is more than a mentor","interactions":[],"lastModifiedDate":"2022-07-04T15:03:50.571981","indexId":"70232470","displayToPublicDate":"2022-07-04T09:59:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Mentoring is more than a mentor","docAbstract":"Recent work has highlighted the substantial positive impact of multi-dimensional mentoring, particularly a mentoring network, in one’s professional development and overall well-being (SAGE Open 2017; doi.org/10.1177/2158244017710288) (Nat Comm 2022; doi.org/10.1038/s41467-022-28667-0). The Women in Soil Ecology (WiSE) network (https://womeninsoilecology.github.io) was born out of a desire to develop mentoring relationships between women from different institutions and career stages – to fill the gaps in traditional faculty–graduate student advising relationships. These gaps included the need for advice and role models in dealing with issues such as harassment and safety in the field and at conferences, work–life balance, navigating family and childcare responsibilities, equal pay and representation, and being a woman in the male-dominated field of soil science (Soil Sci Soc Am J 2019; doi.org/10.2136/sssaj2019.03.0085). Four years and an ongoing pandemic later, our network has grown into much more than we initially envisioned and now connects women with a passion for soil ecology from across the globe.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2518","usgsCitation":"Collins, C.G., Phillips, M.L., Beals, K., Baliey, L., O’Brien, J., Dhungana, I., and Jech, S., 2022, Mentoring is more than a mentor: Frontiers in Ecology and the Environment, v. 20, no. 5, p. 271-271, https://doi.org/10.1002/fee.2518.","productDescription":"1 p.","startPage":"271","endPage":"271","ipdsId":"IP-141108","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":447228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2518","text":"Publisher Index Page"},{"id":402920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Courtney G. 0000-0001-5455-172X","orcid":"https://orcid.org/0000-0001-5455-172X","contributorId":260909,"corporation":false,"usgs":false,"family":"Collins","given":"Courtney","email":"","middleInitial":"G.","affiliations":[{"id":52708,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO USA","active":true,"usgs":false}],"preferred":false,"id":845608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beals, Kendall","contributorId":292722,"corporation":false,"usgs":false,"family":"Beals","given":"Kendall","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":845610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baliey, Lydia","contributorId":292723,"corporation":false,"usgs":false,"family":"Baliey","given":"Lydia","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":845611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Brien, Joy","contributorId":292724,"corporation":false,"usgs":false,"family":"O’Brien","given":"Joy","email":"","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":845612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dhungana, Ishwora","contributorId":292725,"corporation":false,"usgs":false,"family":"Dhungana","given":"Ishwora","email":"","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":845613,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jech, Sierra","contributorId":292726,"corporation":false,"usgs":false,"family":"Jech","given":"Sierra","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":845614,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232468,"text":"70232468 - 2022 - Genome-wide genetic diversity may help identify fine-scale genetic structure among lake whitefish spawning groups in Lake Erie","interactions":[],"lastModifiedDate":"2022-09-27T16:52:01.341745","indexId":"70232468","displayToPublicDate":"2022-07-04T09:43:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Genome-wide genetic diversity may help identify fine-scale genetic structure among lake whitefish spawning groups in Lake Erie","docAbstract":"In Lake Erie, lake whitefish Coregonus clupeaformis supported lucrative fisheries before populations were decimated by overfishing and water quality degradation. In recent years, there has been a renewed interest in lake whitefish and management of the fishery they support. Lake whitefish spawn on several reefs throughout Lake Erie, but the relative recruitment dynamics and contributions of spawning groups to the fishery are not well understood. Modern high-throughput sequencing approaches offer new opportunities to census population diversity and to identify subtle differences among closely related populations. We used high-throughput sequencing data to evaluate the genetic structure and diversity of lake whitefish collected opportunistically across broad spatial scales in Lake Erie. Using RAD-capture (Rapture), we sequenced and genotyped individuals (N = 88) from the west, central, and east basin of Lake Erie at 120,268 single nucleotide polymorphisms (SNPs). Lake whitefish from Niagara and Crib Reefs (west basin) diverged from the three collections. Interestingly, these were the only lake whitefish collected during the act of spawning (late November), and all other fish were collected pre-spawn (August-early November). These results suggest that some lake whitefish spawning reefs may be reproductively isolated, though definition of these groups into stocks will require more intentional sampling during the act of spawning.
A new 3-D resistivity model, estimated from inversion of magnetotelluric data, images crustal and upper-mantle structure of the Wyoming Province and adjacent areas. The Archean province is imaged as a coherent resistive domain, in sharp contrast to active tectonic domains of the western U.S. Prominent high-conductivity belts define the northern, eastern, and southern margins of the Wyoming Province and are interpreted as sutures marking the remnants of Paleoproterozoic orogens. The model results suggest the northern boundary of the Wyoming Province is located 150 km south of its traditional placement and adjacent to a composite orogen separating the Wyoming Province and Medicine Hat block. The eastern province boundary is clearly imaged along the Black Hills, whereas the western margin is obscured by Cenozoic extension and magmatism. An internal boundary within the Wyoming Province is interpreted to represent a Neoarchean suture; in stark contrast to Proterozoic sutures, though, it is not marked by a high-conductivity belt. This difference in conductivity is speculated to reflect changes in the subduction process through time. The absence of high-conductivity along Archean sutures appears to be global in nature and related to reduced continental freeboard in the Archean which limited continental weathering and the delivery of carbon-rich sediments to the seafloor. Although the entire Wyoming Province has been proposed to have undergone lithospheric modification that lessened its stability, the resistivity model suggests a thick lithospheric root remains in place except along its western margin. These results suggest that Archean cratons may be more resistant to lithospheric modification by influx of heat and fluids associated with extension and plumes than previously thought, and that metasomatism does not necessarily weaken the lithosphere and set a craton on the path to destruction.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36417.1","usgsCitation":"Bedrosian, P.A., and Frost, C.D., 2022, Geophysical extent of the Wyoming Province, western USA: Insights into ancient subduction and craton stability: Geological Society of America Bulletin, v. 135, no. 3-4, p. 725-742, https://doi.org/10.1130/B36417.1.","productDescription":"18 p.","startPage":"725","endPage":"742","ipdsId":"IP-136962","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":501613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36417.1","text":"Publisher Index Page"},{"id":501589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Montana, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.26750794943243,\n 48.72244507268985\n ],\n [\n -113.26750794943243,\n 39.45653001110685\n ],\n [\n -102.04436648017622,\n 39.45653001110685\n ],\n [\n -102.04436648017622,\n 48.72244507268985\n ],\n [\n -113.26750794943243,\n 48.72244507268985\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"135","issue":"3-4","noUsgsAuthors":false,"publicationDate":"2022-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":957812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frost, Carol D. 0000-0002-1674-2725","orcid":"https://orcid.org/0000-0002-1674-2725","contributorId":367851,"corporation":false,"usgs":false,"family":"Frost","given":"Carol","middleInitial":"D.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":957813,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248764,"text":"70248764 - 2022 - Sediment thickness and ground motion site amplification along the United States Atlantic and Gulf Coastal Plains","interactions":[],"lastModifiedDate":"2023-09-20T15:57:28.944415","indexId":"70248764","displayToPublicDate":"2022-07-01T10:46:31","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sediment thickness and ground motion site amplification along the United States Atlantic and Gulf Coastal Plains","docAbstract":"Past and present research on earthquake ground motions along the Atlantic and Gulf Coastal Plains and Mississippi Embayment show significant period-dependent site response that is not presently accounted for in ground motion models. These deviations are strongly correlated with the thickness of Mesozoic and younger syn- and post-rift sediments. With the recent incorporation of deep basin depth measurements in the U.S. Geological Survey National Seismic Hazard Model for select regions in the western United States, we move toward a similar analysis in the greater Coastal Plains region by constructing a sediment thickness model and considering three new site response models conditioned on sediment thickness. As of the preparation of this conference paper, we have performed a preliminary evaluation of the Chapman and Guo model and find that the predicted ratio between pseudo-spectral accelerations for the Coastal Plains relative to the continental interior are broadly consistent with our independent dataset.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th National Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Salt Lake City, UT","conferenceLocation":"June 27–30, 2022","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Boyd, O.S., Churchwell, D.H., Moschetti, M.P., Thompson, E.M., Pratt, T.L., Chapman, M.C., and Rezaeian, S., 2022, Sediment thickness and ground motion site amplification along the United States Atlantic and Gulf Coastal Plains, in Proceedings of the 12th National Conference on Earthquake Engineering, June 27–30, 2022, Salt Lake City, UT, 6 p.","productDescription":"6 p.","ipdsId":"IP-136161","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - 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2022 - Standard operating protocol for mark and recapture monitoring of Brook Floater in streams","interactions":[],"lastModifiedDate":"2025-08-25T15:33:06.25202","indexId":"70270792","displayToPublicDate":"2022-07-01T10:32:28","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-142-2022","title":"Standard operating protocol for mark and recapture monitoring of Brook Floater in streams","docAbstract":"The Brook Floater (Alasmidonta varicosa) is a small (<100 mm) freshwater mussel (Family: Unionidae) found in streams of the eastern United States (U.S.) (Nedeau 2008). While there has been limited effort to document the status of Brook Floater across its range, there is evidence of Brook Floater range contraction and declining local abundances over recent decades (Wicklow et al. 2017, NatureServe 2021). Brook Floater is a Species of Greatest Conservation Need (SGCN) in 15 states (94% of range); listed as endangered, threatened, or special concern in nearly every state and province where it still occurs; and has been extirpated from two states (Rhode Island and Delaware). Brook Floater was petitioned for Federal listing under the U.S. Endangered Species Act; however, the listing was determined not to be warranted (U.S. FWS 2019), although it remains a Regional SGCN of very high concern in U.S. Fish & Wildlife Service (U.S. FWS) Regions 5 (Terwilliger 2015) and 4 (SEAFWA-WDC 2019) and is an At-Risk Species in U.S. FWS Region 5.
A critical component of understanding population declines is site-specific information about population density and demographics (e.g., growth, age structure) to assess population viability. This information had previously only been collected for a few populations of Brook Floater (e.g., Massachusetts Division of Fisheries & Wildlife, North Carolina Wildlife Resources Commission) and methods to collect these data varied from state to state, thus limiting comparisons across the range. In 2016, a competitive State Wildlife Grant (SWG) was awarded to develop a standardized monitoring technique that will aid in understanding differences in population viability across its range and assess changes in populations through time. The protocol described in this report was subsequently developed and tested by Massachusetts and Maine (2 sites in each state) and revised based on field experiences. Data collected using this protocol will allow for state managers to make informed decisions about management actions for Brook Floater.
Monitoring approaches are ideally designed to meet management objectives. Management objectives are specific, quantifiable outcomes that reflect the values of the decision makers and relate directly to the management decisions (Conroy and Peterson 2013). Lack of well-defined objectives hinders success of conservation and management actions because there are undefined metrics to determine when the objectives have been met (Yoccoz et al. 2001, Nichols and Thompson 2006). While monitoring to understand a system (i.e., status and trends; Reynolds et al. 2016) provides baseline information for developing management recommendations in the future, Nichols and Thompson (2006) criticize status and trends monitoring because of time lags associated with conservation and the costs and resource availability needed for surveillance, among other reasons. State partners in the Brook Floater SWG have a variety of different monitoring objectives (e.g., abundance/density, survival, recruitment) that depend on the population sizes and demographics.
There are many approaches for estimating population parameters such as density, age structure, recruitment, and growth rates. For example, presence/absence (i.e., multistate models), counts (i.e., multi-state models or Dail-Madsen model; Dail and Madsen 2011), and capture mark-recapture (CMR; e.g. Cormack-Jolly-Seber models; Lindberg and Rexstad 2002) are all approaches for assessing population status and viability.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css67282137","usgsCitation":"Sterrett, S., Roy, A.H., Hazelton, P., Swartz, B., Nedeau, E., Carmignani, J., and Skorupa, A., 2022, Standard operating protocol for mark and recapture monitoring of Brook Floater in streams: Cooperator Science Series CSS-142-2022, https://doi.org/10.3996/css67282137.","ipdsId":"IP-132939","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Sterrett, Sean","contributorId":360459,"corporation":false,"usgs":false,"family":"Sterrett","given":"Sean","affiliations":[{"id":69149,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":947082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":947081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazelton, Peter","contributorId":360462,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":947083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swartz, Beth","contributorId":360463,"corporation":false,"usgs":false,"family":"Swartz","given":"Beth","affiliations":[{"id":86011,"text":"Maine Department of Inland Fisheries & Wildlife","active":true,"usgs":false}],"preferred":false,"id":947084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nedeau, Ethan","contributorId":360464,"corporation":false,"usgs":false,"family":"Nedeau","given":"Ethan","affiliations":[{"id":86012,"text":"Biodrawversity","active":true,"usgs":false}],"preferred":false,"id":947085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carmignani, Jason","contributorId":360465,"corporation":false,"usgs":false,"family":"Carmignani","given":"Jason","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":947086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skorupa, Ayla","contributorId":360466,"corporation":false,"usgs":false,"family":"Skorupa","given":"Ayla","affiliations":[{"id":69149,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":947087,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237200,"text":"70237200 - 2022 - Modelagem de qualidade da agua: Aplicação do SPARROW","interactions":[],"lastModifiedDate":"2022-10-05T15:34:58.137568","indexId":"70237200","displayToPublicDate":"2022-07-01T10:18:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Modelagem de qualidade da agua: Aplicação do SPARROW","docAbstract":"No abstract available.
","language":"Portuguese","publisher":"Agência Nacional de Águas e Saneamento Básico","usgsCitation":"Hadler Troger, F., Ayrimoraes Soares, S.R., Leite Cavalcanti, D., de Souza, M.L., Restivo, D., and Miller, O.L., 2022, Modelagem de qualidade da agua: Aplicação do SPARROW, 44 p.","productDescription":"44 p.","ipdsId":"IP-134335","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":407964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407963,"rank":1,"type":{"id":15,"text":"Index 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sensor measurements","interactions":[],"lastModifiedDate":"2022-10-03T14:39:39.236191","indexId":"70231411","displayToPublicDate":"2022-07-01T09:37:59","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Medium-fidelity CFD modeling of multicopter wakes for airborne sensor measurements","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 78th annual vertical flight society forum and technology display","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"78th Annual Vertical Flight Society Forum and Technology Display","conferenceDate":"May 10-12, 2022","conferenceLocation":"Fort Worth, TX","language":"English","usgsCitation":"Chiew, J., Aftosmis, M., and Manies, K.L., 2022, Medium-fidelity CFD modeling of multicopter wakes for airborne sensor measurements, in Proceedings of the 78th annual vertical flight society forum and technology display, Fort Worth, TX, May 10-12, 2022, Paper 50.","productDescription":"Paper 50","ipdsId":"IP-140470","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":407788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400373,"type":{"id":15,"text":"Index Page"},"url":"https://vtol.org/annual-forum/forum-78-proceedings","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chiew, Jonathan","contributorId":291573,"corporation":false,"usgs":false,"family":"Chiew","given":"Jonathan","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":842529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aftosmis, Michael","contributorId":291575,"corporation":false,"usgs":false,"family":"Aftosmis","given":"Michael","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":842530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":842531,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232420,"text":"70232420 - 2022 - Continental shelves as detrital mixers: U-Pb and Lu-Hf detrital zircon provenance of the Pleistocene–Holocene Bering Sea and its margins","interactions":[],"lastModifiedDate":"2022-09-27T16:51:10.428879","indexId":"70232420","displayToPublicDate":"2022-07-01T08:20:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5781,"text":"The Depositional Record","active":true,"publicationSubtype":{"id":10}},"title":"Continental shelves as detrital mixers: U-Pb and Lu-Hf detrital zircon provenance of the Pleistocene–Holocene Bering Sea and its margins","docAbstract":"Continental shelves serve as critical transfer zones in sediment-routing systems, linking the terrestrial erosional and deep-water depositional domains. The degree to which clastic sediment is mixed and homogenized during transfer across broad shelves has important implications for understanding deep-sea detrital records. Wide continental shelves are thought to act as capacitors characterized by transient sediment storage during sea level rise and sediment remobilization during sea level fall. This study attempts to test the hypothesis that sea level lowstand yields more efficient and direct sediment transfer from fluvial sources to deep-sea sinks compared to highstand when sediment is sequestered and mixed on the shelf. We test this by evaluating U-Pb and Lu-Hf detrital zircon provenance trends along the vast Bering Sea shelf and deep-marine Beringian continental margin. We present 5884 U-Pb ages and 402 Lu-Hf analyses from 30 samples to characterize the provenance of modern to Pleistocene sediment across the Bering Sea region. We used both forward and inverse numerical mixture modeling to estimate the abundance of distinct fluvial sources in shelfal and deep-water deposits. These results demonstrate that sediment in the Bering Sea is derived from a mixture of regional fluvial sources, but that the Yukon River is the primary detrital source for sediment throughout the region. Although Yukon River signatures are abundant in all basin samples, the relative proportions of Yukon vs other sources vary spatially across the shelf. A comparison of Holocene and surficial sediment with Pleistocene deposits shows that sediment across the shelf and in the deep-sea remains well-mixed between climate states. Thus, detrital provenance signatures in deep-marine deposits outward of broad transfer zones are likely to represent mixtures of fluvial sources regardless of sea level.","language":"English","publisher":"Wiley","doi":"10.1002/dep2.203","usgsCitation":"Malkowski, M., Johnstone, S., Sharman, G.R., White, C.J., Scheirer, D.S., and Barth, G., 2022, Continental shelves as detrital mixers: U-Pb and Lu-Hf detrital zircon provenance of the Pleistocene–Holocene Bering Sea and its margins: The Depositional Record, v. 8, no. 3, p. 1008-1030, https://doi.org/10.1002/dep2.203.","productDescription":"23 p.","startPage":"1008","endPage":"1030","ipdsId":"IP-130161","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447258,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/dep2.203","text":"Publisher Index Page"},{"id":435789,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FUXON3","text":"USGS data release","linkHelpText":"Detrital zircon geochronology and geochemistry data from the seafloor of the Bering Sea and adjacent river systems"},{"id":402821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -179.9,\n 50\n ],\n [\n -150,\n 50\n ],\n [\n -150,\n 68\n ],\n [\n -179.9,\n 68\n ],\n [\n -179.9,\n 50\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 160,\n 50\n ],\n [\n 179.9,\n 50\n ],\n [\n 179.9,\n 66\n ],\n [\n 160,\n 66\n ],\n [\n 160,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Malkowski, Matthew A.","contributorId":221753,"corporation":false,"usgs":false,"family":"Malkowski","given":"Matthew A.","affiliations":[{"id":40415,"text":". Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":845488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":845489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":845490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Colin J.","contributorId":292687,"corporation":false,"usgs":false,"family":"White","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":845491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scheirer, Daniel S. 0000-0001-8015-7072 dscheirer@usgs.gov","orcid":"https://orcid.org/0000-0001-8015-7072","contributorId":214825,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel","email":"dscheirer@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barth, Ginger 0000-0003-0867-7799 gbarth@usgs.gov","orcid":"https://orcid.org/0000-0003-0867-7799","contributorId":264955,"corporation":false,"usgs":true,"family":"Barth","given":"Ginger","email":"gbarth@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":845493,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234209,"text":"70234209 - 2022 - Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination","interactions":[],"lastModifiedDate":"2022-08-03T11:53:39.776188","indexId":"70234209","displayToPublicDate":"2022-07-01T06:49:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11444,"text":"Nature Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination","docAbstract":"The distribution of groundwater age is useful for evaluating the susceptibility and sustainability of groundwater resources. Here, we compute the aquifer-scale cumulative distribution function to characterize the age distribution for 21 Principal Aquifers that account for ~80% of public-supply pumping in the United States. The aquifer-scale cumulative distribution function for each Principal Aquifer was derived from an ensemble of modeled age distributions (~60 samples per aquifer) based on multiple tracers: tritium, tritiogenic helium-3, sulfur hexafluoride, chlorofluorocarbons, carbon-14, and radiogenic helium-4. Nationally, the groundwater is 38% Anthropocene (since 1953), 34% Holocene (75 – 11,800 years ago), and 28% Pleistocene (>11,800 years ago). The Anthropocene fraction ranges from <5 to 100%, indicating a wide range in susceptibility to land-surface contamination. The Pleistocene fraction of groundwater exceeds 50% in 7 eastern aquifers that are predominately confined. The Holocene fraction of groundwater exceeds 50% in 5 western aquifers that are predominately unconfined. The sustainability of pumping from these Principal Aquifers depends on rates of recharge and release of groundwater stored in fine-grained layers.
Cyanobacterial blooms are an issue drawing increasing concern in freshwater lakes and reservoirs in the United States due to the real and sometimes perceived harms they can cause through cyanotoxin production or other effects. These types of blooms are often referred to as cyanobacterial harmful algal blooms (cyanoHABs). Cyanotoxin exposure can potentially lead to human health effects through recreation and consumption of drinking water and may impact fisheries, wildlife, domestic pets, and livestock. Characterizing the societal impacts of cyanotoxin production, exposure, and effects and estimating the potential value of information of an early warning system can inform and support freshwater lake and reservoir management decisions and future research directions. A Bayesian decision tree analysis was utilized to identify uses, users, and benefits of the information provided by this research. Specifically, the potential value related to a cyanoHAB early warning system, based on potential toxicity, was analyzed that would provide information two additional days earlier relative to cyanoHAB toxicity. The evaluation considers the application of this information for freshwater lake management - whether or not to post an advisory or warning to avoid recreational water contact. The model was parameterized with data from the state of Kansas and the value of avoided foregone recreation and avoided health effects was derived. The estimated annual value of information ranges between \\$565 thousand to \\$2.3 million (2018 United States Dollars (USD)) for the state of Kansas alone based on provided assumptions. The results demonstrate a lower bound of the value of a cyanoHAB early warning system and suggest additional research to understand how the use and value of this information could support research prioritization and further illustrate the return on research investment. This analysis does not incorporate the full suite of potential societal costs that may be associated with a cyanoHAB event such as drinking water treatment, impacts to irrigation, or power generation.
As humans increasingly dominate the nitrogen cycle, deposition of reactive nitrogen (Nr) will continue to have adverse consequences for ecosystems. In the Rocky Mountains, Nr deposition remains elevated and has become increasingly dominated by ammonium, despite efforts to reduce emissions. Currently, spatial models of Nr deposition do not fully account for urban and agricultural emissions, sources that contribute to the observed high rates of ammonium deposition in adjacent ecosystems. To address this gap in the Colorado Front Range, we measured Nr deposition along a transect from urban and agricultural plains to subalpine forests. We found elevated values of wet Nr deposition at the urban and foothill sites (4.7 and 4.4 kg N ha−1 yr−1, respectively), and lower values at the montane and subalpine sites (2.5–2.8 kg N ha−1 yr−1). Ammonium dominated wet and bulk Nr deposition, accounting for approximately 69% of bulk Nr deposition. Seasonally, bulk Nr deposition was highest in the spring months, when air masses from the plains are transported west into the mountains. Previous work has demonstrated that high elevations of the Colorado Front Range are especially sensitive to Nr deposition due to thin soil and minimal vegetation. Our results indicate that despite lower precipitation, the fire-prone forested foothills receive even greater Nr deposition than higher elevations, due to proximity to urban and agricultural Nr sources. The interaction between elevated Nr deposition and wildfire in this region may pose a risk to water supplies and ecosystems, and is an important topic for future research.
The Lucerne Valley is in the southwestern part of the Mojave Desert and is about 75 miles northeast of Los Angeles, California. The Lucerne Valley groundwater basin encompasses about 230 square miles and is separated from the Upper Mojave Valley groundwater basin by splays of the Helendale Fault. Since its settlement, groundwater has been the primary source of water for agricultural, industrial, municipal, and domestic uses. Groundwater withdrawal from pumping has exceeded the amount of water recharged to the basin, causing groundwater declines of more than 100 feet between 1917 and 2016 in the center of the basin. The continued withdrawal has resulted in an increase in pumping costs, reduced well efficiency, and land subsidence near Lucerne Lake. Although the volume of pumping has declined in recent years, there is concern that new agricultural growth and limits on imported water will continue to strain the sustainability of the groundwater system.
To address these concerns, the U.S. Geological Survey entered into a cooperative agreement with the Mojave Water Agency to develop a better understanding of the Lucerne Valley hydrogeologic system and provide tools to help evaluate and manage the effects of future development in the Lucerne Valley. The objectives of this study were to (1) improve the understanding of the aquifer system, (2) improve the understanding of subsidence in the basin, and (3) incorporate the understanding into a groundwater-flow model that can be used to help manage the groundwater resources in the Lucerne Valley. The model developed for this study covers the period of 1942–2016 and can help evaluate various proposed water-management scenarios during different climatic and hydrologic conditions.
The aquifer system consists of a shallow aquifer, a confining unit, and middle and lower aquifers. These layered water-bearing units were identified based on geologic units of the mostly unconsolidated sediments and hydrologic properties. These alluvial deposits consist of clay, silt, sand, and gravel; some places also contain clay and silty clay lacustrine deposits. Several faults act, at least in part, as barriers to groundwater flow on the eastern, southern, and western edges of the basin. Present-day natural recharge is primarily from the infiltration of runoff from the San Bernardino Mountains to the south; however, stable and radioactive isotopes show that groundwater from the middle of the Lucerne Valley was older than about 10,000 years and probably was recharged as infiltration from streams draining the mountains in the Mojave Desert to the north, which probably does not occur under present-day climatic conditions. The annual average natural recharge for 1942–2016, estimated by a Basin Characterization Model, was about 635 acre-feet per year; the average amount of treated wastewater effluent transferred to the Lucerne Valley for artificial recharge annually ranged from about 1,500 to 4,000 acre-feet per year during 1980–2016. Pumpage estimates for 1942–2016 ranged from about 3,000 acre-feet in 1942 to about 18,300 acre-feet in 1984. The total cumulative amount of groundwater removed from the basin by pumping between 1942 and 2016 was estimated to be about 700,000 acre-feet, which was about 10 times greater than the cumulative amount of recharge to the entire Lucerne Valley groundwater basin. Before groundwater development, the direction of groundwater flow was from the southern part of the basin northward to discharge areas near Lucerne Lake, where it discharged through springs along the Helendale Fault and by evapotranspiration. Since the early 1900s, groundwater-level declines have mostly eliminated the areas where natural discharge occurred and exceeded 100 feet in the middle of the basin between the early 1950s and mid-1990s, and as much as 25 feet near the margins from about the mid-1950s to 2000s. A decrease in the rate of pumping after the mid-1990s lessened the hydraulic stress on the middle and lower aquifers and enabled hydraulic heads in the middle of the basin to recover slightly as groundwater near the margins of the basin moved toward the pumping depression. Although trends in groundwater levels in the center of the basin have reversed since the mid-1990s, levels at the basin margins continue to decline as the movement of groundwater from the margins fills the pumping depression and gradually flattens the groundwater table throughout the basin.
The long-term extraction of groundwater and associated dewatering of the fine-grained sediments present within the aquifer system has resulted in aquifer compaction and consequently land subsidence, primarily near Lucerne Lake. Analysis of interferometric synthetic aperture radar data shows that almost 11 inches of land subsidence has occurred south of Lucerne Lake between April 1992 and November 2009; less subsidence occurred elsewhere in the basin during this period. This differential land subsidence has caused fissures and cracks in the ground surface, which have buckled the pavement and undercut roads in several locations.
The Lucerne Valley Hydrologic Model was developed using the finite-difference groundwater modeling software One Water Hydrologic Model to represent the hydrologic conditions and stresses during 1942–2016. The model has a uniform grid of approximately 92 acres per cell (2,000 feet by 2,000 feet) and has four layers representing the water-bearing units. The results from the calibrated model simulations indicated that groundwater pumpage exceeded recharge, resulting in an estimated net cumulative depletion of groundwater storage (discharge minus recharge) of about 465,000 acre-feet from 1942 to 2016. The model simulated as much as 7.5 feet (90 inches; 2,286 millimeters) of aquifer compaction, which indicates the extensive fine-grained deposits and measured subsidence near Lucerne Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225048","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Stamos, C.L., Larsen, J.D., Powell, R.E., Matti, J.C., and Martin, P., 2022, Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2022-5048, 120 p., https://doi.org/10.3133/sir20225048.","productDescription":"Report: xi, 120 p.; Appendix; Data Release","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095487","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":403187,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221063","text":"Open-File Report 2022-1063","description":"Fackrell, J.K., 2022, Groundwater quality of the Lucerne Valley groundwater basin, California: U.S. Geological Survey Open-File Report 2022-1063, 19 p., https://doi.org/10.3133/ofr20221063.","linkHelpText":"- Groundwater Quality of the Lucerne Valley Groundwater Basin, California"},{"id":402644,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94W41EL","text":"MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California","description":"Larsen, J.D., 2022, MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California: U.S. Geological Survey data release, https://doi.org/10.5066/P94W41EL."},{"id":402643,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048_appendix1.txt","text":"Appendix 1","size":"27 KB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Sites with groundwater-level data available on the U. S. Geological Survey National Water Inventory System Web service (NWISWeb) from 1911-2016 within the Lucerne Valley, California"},{"id":402641,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.xml"},{"id":402640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5048"},{"id":402639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5048/covrthb.jpg"},{"id":402695,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225048/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5048"},{"id":402642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5048/images"}],"country":"United States","state":"California","otherGeospatial":"Lucerne Valley Groundwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.666667,\n 34.266667\n ],\n [\n -117.083333,\n 34.266667\n ],\n [\n -117.083333,\n 34.666667\n ],\n [\n -116.666667,\n 34.666667\n ],\n [\n -116.666667,\n 34.266667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass (Zostera marina L.) and surf smelt (Hypomesus pretiosus) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221054","usgsCitation":"Smith, C.D., and Liedtke, T.L., 2022, Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington: U.S. Geological Survey Open-File Report 2022–1054, 17 p., https://doi.org/10.3133/ofr20221054.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-117971","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":402574,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGJ3ZH","text":"USGS data release","description":"USGS Data Release.","linkHelpText":"Data collected in 2010 to evaluate habitat availability for surf smelt and eelgrass in response to sea level rise on Bainbridge Island, Puget Sound, Washington State, USA"},{"id":402572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1054/coverthb.jpg"},{"id":402573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1054"},{"id":402619,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221054/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1054"},{"id":402575,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1054/images"},{"id":402576,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.XML"},{"id":501780,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113219.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6678466796875,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.487513008956554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2022.894571","usgsCitation":"Friedl, M.A., Woodcock, C.E., Olofsson, P., Zhu, Z., Loveland, T., Stanimirova, R., Arevalo, P., Bullock, E.L., Hu, K., Zhang, Y., Turlej, K., Tarrio, K., Kristina, M., Gorelick, N., Wang, J.A., Barber, C., and Souza Jr., C., 2022, Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat: Frontiers in Remote Sensing, v. 3, 894571, 15 p., https://doi.org/10.3389/frsen.2022.894571.","productDescription":"894571, 15 p.","ipdsId":"IP-142442","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":447282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2022.894571","text":"Publisher Index 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Pontus","contributorId":131007,"corporation":false,"usgs":false,"family":"Olofsson","given":"Pontus","email":"","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":901839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0003-4716-2309","orcid":"https://orcid.org/0000-0003-4716-2309","contributorId":272038,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":901840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":337044,"corporation":false,"usgs":false,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":7248,"text":"emeritus USGS","active":true,"usgs":false}],"preferred":false,"id":901841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanimirova, Radost","contributorId":337045,"corporation":false,"usgs":false,"family":"Stanimirova","given":"Radost","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901842,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arevalo, Paulo","contributorId":337046,"corporation":false,"usgs":false,"family":"Arevalo","given":"Paulo","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901843,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bullock, Eric L. 0000-0003-3279-6771","orcid":"https://orcid.org/0000-0003-3279-6771","contributorId":224710,"corporation":false,"usgs":false,"family":"Bullock","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40922,"text":"Department of Earth & Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":901844,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hu, Kai-Ting","contributorId":337047,"corporation":false,"usgs":false,"family":"Hu","given":"Kai-Ting","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901845,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhang, Yingtong","contributorId":337048,"corporation":false,"usgs":false,"family":"Zhang","given":"Yingtong","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901846,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Turlej, Konrad","contributorId":337049,"corporation":false,"usgs":false,"family":"Turlej","given":"Konrad","email":"","affiliations":[{"id":78943,"text":"Jagiellonian 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Noel","contributorId":294417,"corporation":false,"usgs":false,"family":"Gorelick","given":"Noel","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":901850,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Jonathan A.","contributorId":337052,"corporation":false,"usgs":false,"family":"Wang","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":901851,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Barber, Christopher P. 0000-0003-0570-1140","orcid":"https://orcid.org/0000-0003-0570-1140","contributorId":223102,"corporation":false,"usgs":true,"family":"Barber","given":"Christopher","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901852,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Souza Jr., Carlos","contributorId":337053,"corporation":false,"usgs":false,"family":"Souza Jr.","given":"Carlos","affiliations":[{"id":80958,"text":"IMAZON","active":true,"usgs":false}],"preferred":false,"id":901853,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70231886,"text":"70231886 - 2022 - The role of organic matter diversity on the Re-Os systematics of organic-rich sedimentary units: Insights into the controls of isochron age determinations from the lacustrine Green River Formation","interactions":[],"lastModifiedDate":"2022-06-01T12:22:53.418642","indexId":"70231886","displayToPublicDate":"2022-06-28T07:20:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The role of organic matter diversity on the Re-Os systematics of organic-rich sedimentary units: Insights into the controls of isochron age determinations from the lacustrine Green River Formation","docAbstract":"The range of 187Re/188Os values measured from samples of five organic-rich lacustrine mudstones units in the Eocene Green River Formation in the easternmost Uinta Basin covaries with organic matter diversity driven by changing water column conditions. A set of samples from the Douglas Creek Member has the highest pristane/phytane ratio and lowest β-carotane/n-C30 ratio compared to overlying units, indicating deposition in an oxic-anoxic environment with low salinity that would have allowed for the accumulation of a diverse assemblage of aquatic organisms. These samples define the broadest 187Re/188Os range of 1504. In contrast, samples from the R6 and Mahogany zones possess lower pristane/phytane ratios and higher β-carotane/n-C30 ratios indicating deposition in a more restricted lacustrine environment with elevated salinities and alkalinities that would have limited aquatic organic matter diversity. The R6 and Mahogany zones have the narrowest range of 187Re/188Os values measured in this study of 254.9 and 154.6, respectively. As noted by previous workers, these results suggest that organic matter diversity plays a primary role in determining the range of 187Re/188Os ratios in a sample set, and in turn the uncertainty of Re-Os age determinations from organic-rich sedimentary rocks.
The Re-Os data from the R3 zone and R6 zone yield ages of 49.7 ± 3.4 Ma and 42.0 ± 18 Ma, respectively, which are statistically indistinguishable based on 2σ uncertainty from three previously reported Re-Os age determinations and those provided by 40Ar/39Ar geochronology of interbedded volcanic ash beds. Although the age uncertainty is high, these findings further highlight the importance of Re-Os geochronology in lacustrine basins, particularly those with thick mudstone successions that lack volcanic ash layers, reliable biostratigraphy, or magnetostratigraphic control. In these cases, even ages with large uncertainties can be useful to constrain burial history and thermal history models.
Together, the initial 187Os/188Os ratios of five sets of samples analyzed from the Uinta Basin define the largest Os isotope stratigraphic record from any lacustrine basin compiled to date and record a shift from a value of 1.40 to 1.48 between the R3 and R4 zones in the lower part of the Parachute Creek Member. This small shift may signify a change in the chemical weathering products that entered the lake preserved 20 to 50 m above the contact between the Douglas Creek and the lower Parachute Creek members during a period when the basin transitioned from a shallow lake with mostly open hydrology to an alkaline lake with more frequent basin restrictions.
The need to balance economic development with impacts to Arctic wildlife has been a prominent subject since petroleum exploration began on the North Slope of Alaska, USA, in the late 1950s. The North Slope region includes polar bears (Ursus maritimus) of the southern Beaufort Sea subpopulation, which has experienced a long-term decline in abundance. Pregnant polar bears dig dens in snow drifts during winter and are vulnerable to disturbance, as den abandonment and mortality of neonates may result. Maternal denning coincides with the peak season of petroleum exploration and construction, raising concerns that human activities may disrupt denning. To minimize disturbance of denning polar bears, aerial infrared (AIR) surveys are routinely used to search for dens within planned industry activity areas and that information is used to implement mitigation. Aerial infrared surveys target the heat signature emanating from dens. Despite use by industry for >15 years, the efficacy of AIR and the factors that impact its ability to detect dens remains uncertain. Here, we evaluate AIR using artificial dens and observers naïve to locations to estimate detection probability and its relationship with covariates including weather variables, den characteristics, infrared sensor and altitude, and survey order to identify potential evidence of in-flight observer learning occurring between surveys. In December 2019 we constructed 14 dens (each with an artificial heat source), and 11 control sites (disturbed sites without dens). Between December 2019 and January 2020, 3 survey crews flew 6 independent AIR surveys within the vicinity of dens and control sites and video-recorded AIR imagery. Observers identified putative dens either in flight or during post-flight review of recordings. We assessed detection probability with a simple Bayesian model using 3 subsets of data: 1) all detection/non-detection data; 2) detection/non-detection data restricted to instances where sample sites were confirmed to have been properly scanned by AIR during post-study verification (i.e., when den locations were known); and 3) all dens visible on the recorded imagery during post-study verification, even if they were not seen during the survey or during post-flight review. Subsets 1 and 2 most closely resembled den surveys flown for oil and gas industry and had detection probabilities of 0.15 (95% CI = 0.08–0.23) and 0.24 (95% CI = 0.13–0.37), respectively. Detection probability was 0.41 (95% CI = 0.25–0.58) for subset 3. Higher wind speeds and larger den volume negatively influenced detection probability. Our low detection rate compared to previous studies could partially be the result of differences in study design, such as survey flight patterns. Our results suggest that AIR, as it is currently used, is unlikely to detect most polar bear dens in surveyed areas. Resource managers who use AIR should consider a suite of additional methods (e.g., habitat mapping, probabilistic den distribution, AIR methodology improvements) for minimizing impacts of industry on denning polar bears.
An analysis of the potential for deposits of critical minerals and elements in Maine presented here includes data and discussions for antimony, beryllium, cesium, chromium, cobalt, graphite, lithium, manganese, niobium, platinum group elements, rhenium, rare earth elements, tin, tantalum, tellurium, titanium, uranium, vanadium, tungsten, and zirconium. Deposits are divided into two groups based on geological settings and common ore-deposit terminology. One group consists of known deposits (sediment-hosted manganese, volcanogenic massive sulphide, porphyry copper-molybdenum, mafic- and ultramafic-hosted nickel-copper [-cobalt-platinum group elements], pegmatitic lithium-cesium-tantalum) that are in most cases relatively large, well-documented, and have been explored extensively in the past. The second, and much larger group of different minerals and elements, comprises small deposits, prospects, and occurrences that are minimally explored or unexplored. The qualitative assessment used in this study relies on three key criteria: (1) the presence of known deposits, prospects, or mineral occurrences; (2) favourable geologic settings for having certain deposit types based on current ore deposit models; and (3) geochemical anomalies in rocks or stream sediments, including panned concentrates. Among 20 different deposit types considered herein, a high resource potential is assigned only to three: (1) sediment-hosted manganese, (2) mafic- and ultramafic-hosted nickel-copper(-cobalt-platinum group elements), and (3) pegmatitic lithium-cesium-tantalum. Moderate potential is assigned to 11 other deposit types, including: (1) porphyry copper-molybdenum (-rhenium, selenium, tellurium, bismuth, platinum group elements); (2) chromium in ophiolites; (3) platinum group elements in ophiolitic ultramafic rocks; (4) granite-hosted uranium-thorium; (5) tin in granitic plutons and veins; (6) niobium, tantalum, and rare earth elements in alkaline intrusions; (7) tungsten and bismuth in polymetallic veins; (8) vanadium in black shales; (9) antimony in orogenic veins and replacements; (10) tellurium in epithermal deposits; and (11) uranium in peat.
","language":"English","publisher":"Atlantic Geology","doi":"10.4138/atlgeo.2022.007","usgsCitation":"Slack, J.F., Beck, F., Bradley, D., Felch, M.M., Marvinney, R.G., and Whittaker, A., 2022, Potential for critical mineral deposits in Maine, USA: Atlantic Geoscience, v. 58, p. 155-191, https://doi.org/10.4138/atlgeo.2022.007.","productDescription":"37 p.","startPage":"155","endPage":"191","ipdsId":"IP-138621","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":447292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.4138/atlgeo.2022.007","text":"External Repository"},{"id":418503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"58","noUsgsAuthors":false,"publicationDate":"2022-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, F.M.","contributorId":313567,"corporation":false,"usgs":false,"family":"Beck","given":"F.M.","email":"","affiliations":[],"preferred":false,"id":876279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, D.C.","contributorId":313568,"corporation":false,"usgs":false,"family":"Bradley","given":"D.C.","email":"","affiliations":[],"preferred":false,"id":876280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Felch, M. M.","contributorId":313569,"corporation":false,"usgs":false,"family":"Felch","given":"M.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":876281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marvinney, Robert G.","contributorId":131130,"corporation":false,"usgs":false,"family":"Marvinney","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":7257,"text":"Maine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":876282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whittaker, A.T.H.","contributorId":313570,"corporation":false,"usgs":false,"family":"Whittaker","given":"A.T.H.","email":"","affiliations":[],"preferred":false,"id":876283,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232282,"text":"70232282 - 2022 - A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels","interactions":[],"lastModifiedDate":"2022-06-27T15:24:43.923098","indexId":"70232282","displayToPublicDate":"2022-06-27T10:16:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels","docAbstract":"Many populated, tropical coastlines fronted by fringing coral reefs are exposed to wave-driven marine flooding that is exacerbated by sea-level rise. Most fringing coral reef are not alongshore uniform, but bisected by shore-normal channels; however, little is known about the influence of such channels on alongshore variations on runup and flooding of the adjacent coastline. We con-ducted a parametric study using the numeric model XBeach that demonstrates that a shore-normal channel results in substantial alongshore variations in waves, wave-driven water levels, and the resulting runup. Depending on the geometry and forcing, runup is greater either on the coastline adjacent to the channel terminus or at locations near the alongshore extent of the channel. The impact of channels on runup increases for higher incident waves, lower incident wave steepness, wider channels, a narrower reef, and shorter channel spacing. Alongshore varia-tion of infragravity waves is predominantly responsible for large-scale variations in runup out-side the channel, whereas setup, sea-swell waves, and very-low frequency waves mainly increase runup inside the channel. These results provide insight into which coastal locations adjacent to shore-normal channels are most vulnerable to high runup events, using only widely available data such as reef geometry and offshore wave conditions.","language":"English","publisher":"MDPI","doi":"10.3390/jmse10060828","usgsCitation":"Storlazzi, C.D., Rey, A., and van Dongeren, A., 2022, A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels: Journal of Marine Science and Engineering, v. 10, no. 6, 828, 13 p., https://doi.org/10.3390/jmse10060828.","productDescription":"828, 13 p.","ipdsId":"IP-140197","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447301,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse10060828","text":"Publisher Index Page"},{"id":435793,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A0HFKV","text":"USGS data release","linkHelpText":"Model parameter input files to compare the influence of channels in fringing coral reefs on alongshore variations in wave-driven runup along the shoreline"},{"id":402509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8075-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8075-4490","contributorId":292540,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":845005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rey, Annouk","contributorId":292541,"corporation":false,"usgs":false,"family":"Rey","given":"Annouk","email":"","affiliations":[{"id":27619,"text":"TU Delft","active":true,"usgs":false}],"preferred":false,"id":845006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":845007,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232393,"text":"70232393 - 2022 - 21st-century stagnation in unvegetated sand-sea activity","interactions":[],"lastModifiedDate":"2022-07-01T12:05:08.833034","indexId":"70232393","displayToPublicDate":"2022-06-27T07:02:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"21st-century stagnation in unvegetated sand-sea activity","docAbstract":"Sand seas are vast expanses of Earth’s surface containing large areas of aeolian dunes—topographic patterns manifest from above-threshold winds and a supply of loose sand. Predictions of the role of future climate change for sand-sea activity are sparse and contradictory. Here we examine the impact of climate on all of Earth’s presently-unvegetated sand seas, using ensemble runs of an Earth System Model for historical and future Shared Socioeconomic Pathway (SSP) scenarios. We find that almost all of the sand seas decrease in activity relative to present-day and industrial-onset for all future SSP scenarios, largely due to more intermittent sand-transport events. An increase in event wait-times and decrease in sand transport is conducive to vegetation growth. We expect dune-forming winds will become more unimodal, and produce larger incipient wavelengths, due to weaker and more seasonal winds. Our results indicate that these qualitative changes in Earth’s deserts cannot be mitigated.
In low-permeability systems, groundwater may be accompanied by separate-phase fluids, and measured pore water pressures may deviate from those expected in steady-state, single-phase systems. These same systems may be of interest for storage of nuclear waste in Deep Geologic Repositories. Therefore, it is important to understand the relationship between the presence of a separate phase and anomalous pressure development. At the Bruce site in Southern Ontario, a significant underpressure was observed, and there is evidence for the presence of gas-phase methane in situ. This study used a one-dimensional (vertical) numerical model of the subsurface down to a depth of 844 m beneath the Bruce site to evaluate possible effects of hydromechanical coupling with multiphase flow on pressure evolution during glacial loading and unloading. The simulated pressure conditions were affected strongly by the amount of methane initially present in the system, and the maximum simulated underpressure varied nonmonotonically with increasing initial methane content. When the initial methane content was below the solubility limit, exsolution led to underpressures that briefly exceeded those that formed in the single-phase case. At intermediate initial methane contents (sufficient to produce an immobile gas phase), the gas phase dampened the hydromechanical effects of the glacial cycle. At large initial methane contents (when a mobile gas phase was present), gas migration caused a large decrease in relative liquid permeability, which further contributed to underpressure development in the pore water. Multiple scenarios that spanned a range of initial methane contents yielded underpressures like those observed at the Bruce site.
One of the risks faced by habitat restoration practitioners is whether habitats included in restoration planning will be used by the target species or, conversely, whether habitats excluded from restoration planning would have benefited the target species. With the goal of providing a quantitative decision-making approach that represented varying levels of risk tolerance, we used multiple probability decision thresholds (PDT) to predict the range of occurrence for three anadromous fishes (Oncorhynchus spp.) in a watershed in southwestern Washington, USA. For each species, we compared the predicted range of occurrence to the distribution used for restoration planning and quantified the amount of habitat blocked by anthropogenic barriers. Coho salmon (O. kisutch) had the broadest predicted range of occurrence (3061.6–6357.9 km; 0.75–0.25 PDT), followed by steelhead trout (O. mykiss; 1828.8–2836.8 km) and chum salmon (O. keta; 1373.9–1629.1 km). For each species, the predicted range of occurrence was similar or greater than the distribution used for restoration planning, suggesting that the current plan may exclude habitats that would benefit each species. Coho salmon had the greatest percentage of habitat blocked by anthropogenic barriers, followed by steelhead trout and chum salmon, respectively. Modeling species distributions at multiple risk-tolerance scenarios acknowledges uncertainty in restoration planning and allows practitioners to weigh the ecological benefits and budgetary constraints when considering locations for restoration. To effectively communicate restoration science to support practitioners in decision-making, we developed an R Shiny application online user interface available at: https://shiny.wdfw-fish.us/ChehalisRiverBasinSalmonidRangeOfOccurence/.
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