The Big River is a tributary to the Meramec River in south-central Missouri. It drains an area that has been historically one of the largest lead producers in the world, and associated mine wastes have contaminated sediments in much of the river corridor. This study investigated hydraulic conditions in four study reaches to evaluate the potential contribution of physical habitat dynamics to mechanical and physiological stress on native mussel populations. We quantified hydraulic conditions and relative bed stability in previously identified and delineated mussel habitats (MHs) and in the surrounding reaches to refine understanding of the reach-scale (about 1 kilometer) hydraulic characteristics that affect the distribution of mussel aggregations in the river. Two-dimensional hydrodynamic models were compiled for discharge scenarios from base flow (90-percent flow exceedance) to the approximate bankfull discharge (2-year mean return interval peak flow) for the reaches. Discharge, velocity, and water-surface elevation data were collected at all four study reaches at various discharges to calibrate the models across a range of discharges. Shields values to predict incipient motion of the substrate were computed for the MHs and surrounding reaches using bed-surface sediment data collected during this study and previous studies.
The distributions of hydraulic values at the range of simulated discharge scenarios were significantly different among the MHs. Depth values in the MHs ranged from 0.03 to 5.7 meters, with parts remaining dry at some lower flow scenarios (for example, 90- and 50-percent flow exceedance). MH velocities and bed shear stresses (shear stresses) reached 3.1 meters per second and 31 newtons per square meter, respectively. Through the range of simulated discharges, velocity and shear stress within the MHs were limited by reach-scale hydraulic behavior.
Our calculations predicted sand mobility within at least 50 percent of the wetted area of all four MHs for discharges from the 50-percent exceedance flow to the approximate bankfull discharge, whereas 50th-percentile (median) particle size fraction mobility was only predicted within a small area of one of the MHs at the 2-year peak discharge. These results indicate that finer size fractions are mobile within the four MHs, but the larger framework grains of the substrate are predominantly stable at the most frequent discharges.
Our results indicate that suitable mussel habitat on the Big River cannot be identified within a narrow range of velocities, depths, and shear stresses. However, the consistent patterns of sediment mobility and the slow increase of hydraulic forces with increasing discharge within all the MHs indicate that flushing flows at low discharges and coarse sediment stability at higher discharges are important for habitat suitability in the Big River. These patterns of sediment mobility are comparable among the robust and depauperate MHs, indicating that the depauperate beds are likely not impaired by bed instability or siltation. Coarse sediment stability up to bankfull discharges further indicates that bed instability is not widespread in these modeled reaches and is likely not related to the spatial distribution of mussels in these locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225002","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Roberts, M.O., Jacobson, R.B., and Erwin, S.O., 2022, Hydraulics of freshwater mussel habitat in select reaches of the Big River, Missouri: U.S. Geological Survey Scientific Investigations Report 2022–5002, 49 p., https://doi.org/10.3133/sir20225002.","productDescription":"Report: viii, 49 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-122009","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":399191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5002/coverthb.jpg"},{"id":399688,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5002"},{"id":399192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5002/sir20225002.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5002"},{"id":399193,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5002/sir20225002.XML"},{"id":399194,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5002/images"},{"id":399195,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K3ENAX","text":"USGS data release","linkHelpText":"Hydraulic measurements from select reaches of the Big River, Missouri"},{"id":399196,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":502289,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112957.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25244140624999,\n 37.63163475580645\n ],\n [\n -90.32958984375,\n 37.63163475580645\n ],\n [\n -90.32958984375,\n 38.53097889440026\n ],\n [\n -91.25244140624999,\n 38.53097889440026\n ],\n [\n -91.25244140624999,\n 37.63163475580645\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
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Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management. Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.
The Okaloosa darter (Etheostoma okaloosae) is a diminutive, perch-like, benthic fish that inhabits only six small, clear, and shallow creek systems that flow almost entirely within Eglin Air Force Base in the panhandle of northwest Florida. Listed as Endangered by the U.S. Fish and Wildlife Service (USFWS) in 1973, improvements in erosion control and habitat restoration led to the Okaloosa darter being downlisted from Endangered to Threatened in 2011. However, the long-term management of the species is hampered by the lack of knowledge of the spatial extent of the recharge areas that ultimately support creek flow through groundwater discharge. To address this lack of data, we collected groundwater samples from the sand and gravel aquifer beneath 11 headwater and 11 downgradient sites across six creek basins during February and December 2020. The groundwater samples were collected from 1 to 1.2 m beneath the creek bottom. Concentrations of sulfur hexafluoride (SF6) were analyzed and used to calculate groundwater age (residence time), and indicated that at the 11 headwater sites, recharge occurred between 11 and 28 years ago. Groundwater ages in downgradient parts of the same creeks indicated that recharge occurred between 5 and 25 years ago. When combined with representative values of hydraulic conductivity for the sand and gravel aquifer, the ages reveal that the extent of the maximum recharge distance from the sampling sites ranged from about 222 to 2011 m from the creeks. This new information can be used by natural resource managers as additional evidence to support the USFWS Recovery Plan and proposed delisting of the Okaloosa darter from the Endangered Species List. Moreover, these results may also be useful to fisheries biologists to incorporate groundwater inputs to facilitate fisheries management.
","language":"English","publisher":"MDPI","doi":"10.3390/hydrology9050069","usgsCitation":"Landmeyer, J.E., McBride, W.S., and Tate, W., 2022, Determination of recharge areas that supply decades old groundwater to creeks inhabited by the threatened Okaloosa darter: Hydrology, v. 9, no. 5, 69, 24 p., https://doi.org/10.3390/hydrology9050069.","productDescription":"69, 24 p.","ipdsId":"IP-137426","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":448016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology9050069","text":"Publisher Index Page"},{"id":401642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Elgin Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.59561157226562,\n 30.484183951487754\n ],\n [\n -86.23443603515625,\n 30.484183951487754\n ],\n [\n -86.23443603515625,\n 30.681620845933267\n ],\n [\n -86.59561157226562,\n 30.681620845933267\n ],\n [\n -86.59561157226562,\n 30.484183951487754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Landmeyer, James E. 0000-0002-5640-3816","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":216137,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBride, W. Scott 0000-0003-1828-2838","orcid":"https://orcid.org/0000-0003-1828-2838","contributorId":201573,"corporation":false,"usgs":true,"family":"McBride","given":"W.","email":"","middleInitial":"Scott","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":844083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, William B.","contributorId":55538,"corporation":false,"usgs":true,"family":"Tate","given":"William B.","affiliations":[],"preferred":false,"id":844084,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230832,"text":"70230832 - 2022 - Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology","interactions":[],"lastModifiedDate":"2022-04-26T14:13:49.664763","indexId":"70230832","displayToPublicDate":"2022-04-25T09:08:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology","docAbstract":"National and global greenhouse gas (GHG) budgets are continually being refined as data become available. Primary sources of the potent GHG nitrous oxide (N2O) include agricultural soil management and burning of fossil fuels, but comprehensive N2O budgets also incorporate less prominent factors such as wetlands. Freshwater wetland GHG flux estimates, however, have high uncertainty, and wetlands have been identified as both sources and sinks. Here, we analyzed a regional database of >26,000 N2O chamber flux measurements sampled across >150 wetlands from the Prairie Pothole Region (PPR) in the Great Plains of North America. Our goal was to identify important land use and hydrologic drivers of N2O flux to help reduce uncertainty in N2O models, and to incorporate these drivers into an upscaled estimate of wetland N2O emissions from the U.S. portion of the PPR. Within individual wetlands, exposed soils with no standing water, such as along wetland edges, were hotspots that accounted for greater than 90% of wetland N2O emissions. In contrast wet (i.e., ponded) areas had minimal or negative N2O flux. N2O flux from wetlands nested within croplands (16.3–17.3 μg N2O m−2 hr−1) was, in some instances, nearly double that from wetlands within grasslands (9.2–14.4 μg N2O m−2 h−1). We estimated that seasonal N2O flux from PPR wetlands equated to roughly 0.2% (1.04 Tg CO2 equivalents) of the U.S. N2O budget (c. 2019). Overall, even though PPR wetlands are a small net source of N2O to the atmosphere, their emissions are negligible relative to agricultural soil management. Policy and management to restore wetland hydrology and surrounding uplands from cropland to grasslands can reduce landscape N2O fluxes. Future activities focused on wetland N2O flux would benefit from inclusion of adjacent land use and hydrologic factors, as well as from incorporation of temporally dynamic ponded wetland areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2022.108968","usgsCitation":"Tangen, B., and Bansal, S., 2022, Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology: Agricultural and Forest Meteorology, v. 320, 108968, 10 p., https://doi.org/10.1016/j.agrformet.2022.108968.","productDescription":"108968, 10 p.","ipdsId":"IP-134939","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":399665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, Montana, North Dakota, South Dakota","otherGeospatial":"Prairie Potholes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.9296875,\n 48.86471476180277\n ],\n [\n -101.162109375,\n 47.57652571374621\n ],\n [\n -100.283203125,\n 45.706179285330855\n ],\n [\n -100.72265625,\n 44.653024159812\n ],\n [\n -99.755859375,\n 43.83452678223682\n ],\n [\n -97.119140625,\n 43.068887774169625\n ],\n [\n -96.767578125,\n 43.96119063892024\n ],\n [\n -95.625,\n 43.32517767999296\n ],\n [\n -94.306640625,\n 41.77131167976407\n ],\n [\n -92.724609375,\n 42.293564192170095\n ],\n [\n -93.07617187499999,\n 44.213709909702054\n ],\n [\n -97.20703125,\n 48.22467264956519\n ],\n [\n -98.7890625,\n 48.980216985374994\n ],\n [\n -107.9296875,\n 48.86471476180277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"320","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":841430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":841431,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236256,"text":"70236256 - 2022 - Assessing placement bias of the global river gauge network","interactions":[],"lastModifiedDate":"2022-08-31T13:33:17.808542","indexId":"70236256","displayToPublicDate":"2022-04-25T08:20:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5791,"text":"Nature Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Assessing placement bias of the global river gauge network","docAbstract":"Knowing where and when rivers flow is paramount to managing freshwater ecosystems. Yet stream gauging stations are distributed sparsely across rivers globally and may not capture the diversity of fluvial network properties and anthropogenic influences. Here we evaluate the placement bias of a global stream gauge dataset on its representation of socioecological, hydrologic, climatic and physiographic diversity of rivers. We find that gauges are located disproportionally in large, perennial rivers draining more human-occupied watersheds. Gauges are sparsely distributed in protected areas and rivers characterized by non-perennial flow regimes, both of which are critical to freshwater conservation and water security concerns. Disparities between the geography of the global gauging network and the broad diversity of streams and rivers weakens our ability to understand critical hydrologic processes and make informed water-management and policy decisions. Our findings underscore the need to address current gauge placement biases by investing in and prioritizing the installation of new gauging stations, embracing alternative water-monitoring strategies, advancing innovation in hydrologic modelling, and increasing accessibility of local and regional gauging data to support human responses to water challenges, both today and in the future.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41893-022-00873-0","usgsCitation":"Krabbenhoft, C., Allen, G.H., Lin, P., Godsey, S., Allen, D., Burrows, R., DelVecchia, A., Fritz, K.M., Shanafield, M., Burgin, A.J., Zimmer, M., Datry, T., Dodds, W., Jones, C., Mimms, M., Franklin, C., Hammond, J., Zipper, S., Ward, A.S., Costigan, K., Beck, H., and Olden, J., 2022, Assessing placement bias of the global river gauge network: Nature Sustainability, v. 5, p. 586-592, https://doi.org/10.1038/s41893-022-00873-0.","productDescription":"7 p.","startPage":"586","endPage":"592","ipdsId":"IP-130183","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":448023,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/s41893-022-00873-0","text":"External 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Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":850340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lin, Peirong","contributorId":295975,"corporation":false,"usgs":false,"family":"Lin","given":"Peirong","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":850342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godsey, Sarah E","contributorId":223120,"corporation":false,"usgs":false,"family":"Godsey","given":"Sarah E","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":850343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Daniel C. 0000-0002-0451-0564","orcid":"https://orcid.org/0000-0002-0451-0564","contributorId":225169,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","middleInitial":"C.","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":850351,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burrows, Ryan","contributorId":295995,"corporation":false,"usgs":false,"family":"Burrows","given":"Ryan","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":850357,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DelVecchia, Amanda 0000-0003-4252-5991","orcid":"https://orcid.org/0000-0003-4252-5991","contributorId":225165,"corporation":false,"usgs":false,"family":"DelVecchia","given":"Amanda","email":"","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":850361,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":850345,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shanafield, Margaret","contributorId":106772,"corporation":false,"usgs":true,"family":"Shanafield","given":"Margaret","affiliations":[],"preferred":false,"id":850344,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burgin, Amy J. 0000-0001-8489-4002","orcid":"https://orcid.org/0000-0001-8489-4002","contributorId":296009,"corporation":false,"usgs":false,"family":"Burgin","given":"Amy","email":"","middleInitial":"J.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":850356,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zimmer, 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Nathan","contributorId":295982,"corporation":false,"usgs":false,"family":"Jones","given":"C. Nathan","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":850346,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mimms, Meryl","contributorId":295998,"corporation":false,"usgs":false,"family":"Mimms","given":"Meryl","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":850360,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Franklin, Catherin","contributorId":295985,"corporation":false,"usgs":false,"family":"Franklin","given":"Catherin","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":850348,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":850353,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":850350,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ward, Adam S","contributorId":191363,"corporation":false,"usgs":false,"family":"Ward","given":"Adam","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":850352,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Costigan, Katie H.","contributorId":166700,"corporation":false,"usgs":false,"family":"Costigan","given":"Katie H.","affiliations":[],"preferred":false,"id":850359,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Beck, Hylke","contributorId":295993,"corporation":false,"usgs":false,"family":"Beck","given":"Hylke","affiliations":[{"id":37958,"text":"University of Amsterdam","active":true,"usgs":false}],"preferred":false,"id":850355,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":850341,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70254825,"text":"70254825 - 2022 - A suction pump sampler for invertebrate drift detects exceptionally high concentrations of small invertebrates that drift nets miss","interactions":[],"lastModifiedDate":"2024-06-11T20:41:35.813266","indexId":"70254825","displayToPublicDate":"2022-04-22T15:34:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"A suction pump sampler for invertebrate drift detects exceptionally high concentrations of small invertebrates that drift nets miss","docAbstract":"Invertebrate drift is a key process in riverine ecosystems controlling aquatic invertebrate movement, distribution, and availability to fish as prey. However, accurately sampling drift across a wide range of invertebrate sizes is difficult because small invertebrates slip through coarse-mesh drift nets, and fine mesh clogs more easily, which reduces filtration efficiency and measurement accuracy. To avoid this limiting tradeoff, we developed a gas-powered drift pump which pours 20 m3/hour of river water through nested 80- and 750-m nets suspended in the air, and we tested it against a conventional 250-m drift net during low and high flows in a clearwater Alaskan river. The drift pump detected a geometric mean drift concentration of 467 invertebrates m-3 and maximum of 5637 m-3, eleven times the mean concentration of 42 m-3 from the drift net. Invertebrates 3 mm length, primarily chironomids, comprised the entire difference. Studies in which the drift of 0.5 – 3 mm invertebrates might be relevant, such as foraging models investigating the growth of juvenile drift-feeding fishes, should consider using similar methods to quantify small invertebrate drift, lest they underestimate it by an order of magnitude.","language":"English","publisher":"Springer","doi":"10.1007/s10750-022-04849-1","usgsCitation":"Neuswanger, J., Schoen, E.R., Wipfli, M.S., Volk, C.J., and Savereide, J.W., 2022, A suction pump sampler for invertebrate drift detects exceptionally high concentrations of small invertebrates that drift nets miss: Hydrobiologia, v. 849, p. 2077-2089, https://doi.org/10.1007/s10750-022-04849-1.","productDescription":"13 p.","startPage":"2077","endPage":"2089","ipdsId":"IP-132981","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Neuswanger, Jason R.","contributorId":337745,"corporation":false,"usgs":false,"family":"Neuswanger","given":"Jason R.","affiliations":[{"id":81040,"text":"South Fork Research, Inc","active":true,"usgs":false}],"preferred":false,"id":902649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoen, Erik R.","contributorId":184107,"corporation":false,"usgs":false,"family":"Schoen","given":"Erik","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":902650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Volk, Carol J.","contributorId":337746,"corporation":false,"usgs":false,"family":"Volk","given":"Carol","email":"","middleInitial":"J.","affiliations":[{"id":81040,"text":"South Fork Research, Inc","active":true,"usgs":false}],"preferred":false,"id":902651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":902652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256688,"text":"70256688 - 2022 - Defining oyster resource zones across coastal Louisiana for restoration and aquaculture","interactions":[],"lastModifiedDate":"2024-08-30T16:16:03.768478","indexId":"70256688","displayToPublicDate":"2022-04-22T11:06:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"Defining oyster resource zones across coastal Louisiana for restoration and aquaculture","docAbstract":"Eastern oysters (Crassostrea virginica) are a critical ecological and commercial resource in the northern Gulf of Mexico facing changing environmental conditions from river management and climate change. In Louisiana, USA, development of restored reefs, and off-bottom aquaculture would benefit from the identification of locations supportive of sustainable oyster populations (i.e., metapopulations) and high consistent production. This study defines four oyster resource zones across coastal Louisiana based on environmental conditions known to affect oyster survival, growth, and reproduction. Daily data from 2015 to 2019 were interpolated to generate salinity and temperature profiles across Louisiana's estuaries, which were then used to classify zones based on monthly and annual salinity mean and variance. Zones were classified as supportive of (1) broodstock sanctuary reefs (i.e., support reproductive populations), (2) productive reefs during dry (salty) years, (3) productive reefs during wet (fresh) years, and (4) off-bottom aquaculture development. Of the 38,000 km2 investigated, over 11,000 km2 of potential oyster zone area was identified across the Louisiana coast. The Broodstock Sanctuary Zone was the smallest (∼540 km2), as salinity variance limited this zone in many areas, as it is driven largely by riverine inputs across many estuaries. Located up-estuary (Dry Restoration Zone) and down-estuary (Wet Restoration Zone) of the Broodstock Sanctuary Zone, Dry and Wet Restoration Zone areas covered ∼2400 km2 and ∼3900 km2, respectively. Mapped reefs in Louisiana currently exist largely within the Dry Restoration zones, suggesting a potential strategy to focus reef development in Wet Restoration zones to ensure reef network sustainability through years with high precipitation and river inflow. The off-bottom Aquaculture Zone was the largest (∼6400 km2) zone identified, with much of this area located more down-estuary and off-shore. Accounting for variable water quality conditions enables the development of a network of reefs resilient to environmental variability, and more stable areas for consistent off-bottom aquaculture production. Spatial planning and identification of oyster resource zones reduces focus on individual reef success and supports management of oyster metapopulation outcomes, while identifying zones supportive of off-bottom aquaculture.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2022.106178","usgsCitation":"Swam, L.M., Couvillion, B., Callam, B., La Peyre, J., and La Peyre, M., 2022, Defining oyster resource zones across coastal Louisiana for restoration and aquaculture: Ocean and Coastal Management, v. 225, 106178, 11 p., https://doi.org/10.1016/j.ocecoaman.2022.106178.","productDescription":"106178, 11 p.","ipdsId":"IP-134836","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499824,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/animalsciences_pubs/2261","text":"External Repository"},{"id":433380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.28531382800476,\n 30.084673161811594\n ],\n [\n -89.8627113518053,\n 30.384080583724042\n ],\n [\n -90.30515265860349,\n 30.512183704575193\n ],\n [\n -90.81872980801528,\n 30.23163703531037\n ],\n [\n -91.21166619938886,\n 30.068757329434987\n ],\n [\n -93.742248457641,\n 30.376322644227812\n ],\n [\n -93.94164092204788,\n 29.613593061579024\n ],\n [\n -92.27979250199853,\n 29.44209715796825\n ],\n [\n -91.10243386209395,\n 29.085644613779976\n ],\n [\n -89.98832868271369,\n 28.980943971169282\n ],\n [\n -88.89450433276538,\n 28.983731357632564\n ],\n [\n -89.28531382800476,\n 30.084673161811594\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren M.","contributorId":341585,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":908656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callam, Brian","contributorId":341586,"corporation":false,"usgs":false,"family":"Callam","given":"Brian","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":341587,"corporation":false,"usgs":false,"family":"La Peyre","given":"Jerome F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908655,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231662,"text":"70231662 - 2022 - Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals","interactions":[],"lastModifiedDate":"2022-08-15T13:53:03.596218","indexId":"70231662","displayToPublicDate":"2022-04-21T08:24:44","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals","docAbstract":"The transition from a global hydrocarbon economy to a green energy economy and the rapidly growing middle class in developing countries are driving the need for considerable new sources of critical materials. Deep-ocean minerals, namely cobalt-rich ferromanganese crusts and polymetallic nodules, are two such new resources generating interest.
Polymetallic nodules are essentially two-dimensional mineral deposits sitting on abyssal plain sediments at about 3,500–6,000 m water depths. Metals of economic interest enriched in nodules include nickel, copper, manganese, cobalt and molybdenum. Cobalt-rich ferromanganese crusts are also two-dimensional deposits forming pavements on rock outcrops on seamounts and ridges at water depths of 400–7,000 m. Metals of economic interest for crusts include cobalt, manganese, nickel, molybdenum, tellurium, platinum, vanadium and rare earth elements.
A conservative estimate is that 21.1 billion dry tons of polymetallic nodules exist in the Clarion-Clipperton Zone (CCZ) manganese nodule field, the largest in area and tonnage of the known global nodule fields. Based on that estimate, tonnages of many critical metals in the CCZ nodules are greater than those found in global terrestrial reserves. About 7.5 billion dry tons of cobalt-rich ferromanganese crusts are estimated to occur in the Pacific Ocean Prime Crust Zone, the area with the highest tonnage of critical-metal-rich crust deposits, with many elements contained therein estimated to be greater than those found in global terrestrial reserves.
Deep-ocean mining has not yet been carried out in the Exclusive Economic Zone of any nation, nor in the Areas beyond national jurisdiction, although extensive mineral exploration and environmental studies are being conducted and exploitation regulations codified, indicating that mining activities will likely begin in the near future. If deep-ocean mining follows the evolution of offshore production of petroleum, we can expect that about 35–45 per cent of the demand for critical metals will come from deep-ocean mines by 2065.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The United Nations convention on the law of the sea, part XI regime and the international seabed authority: A twenty-five year journey","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Brill","doi":"10.1163/9789004507388_013","usgsCitation":"Hein, J.R., and Mizell, K., 2022, Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals, chap. 8 of The United Nations convention on the law of the sea, part XI regime and the international seabed authority: A twenty-five year journey, p. 177-197, https://doi.org/10.1163/9789004507388_013.","productDescription":"21 p.","startPage":"177","endPage":"197","ipdsId":"IP-120065","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400795,"type":{"id":15,"text":"Index Page"},"url":"https://brill.com/view/book/edcoll/9789004507388/BP000021.xml"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843290,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230675,"text":"70230675 - 2022 - The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river","interactions":[],"lastModifiedDate":"2022-04-21T14:11:22.868251","indexId":"70230675","displayToPublicDate":"2022-04-20T09:05:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river","docAbstract":"In near-field remote sensing, noncontact methods (radars) that measure stage and surface water velocity have the potential to supplement traditional bridge scour monitoring tools because they are safer to access and are less likely to be damaged compared with in-stream sensors. The objective of this study was to evaluate the use of radars for monitoring the hydraulic conditions that contribute to bridge–pier scour in gravel-bed channels. Measurements collected with a radar were also leveraged along with minimal field measurements to evaluate whether time-integrated stream power per unit area (Ω) was correlated with observed scour depth at a scour-critical bridge in Colorado. The results of this study showed that (1) there was close agreement between radar-based and U.S. Geological Survey streamgage-based measurements of stage and discharge, indicating that radars may be viable tools for monitoring flow conditions that lead to bridge pier scour; (2) Ω and pier scour depth were correlated, indicating that radar-derived Ω measurements may be used to estimate scour depth in real time and predict scour depth based on the measured trajectory of Ω. The approach presented in this study is intended to supplement, rather than replace, existing high-fidelity scour monitoring techniques and provide data quickly in information-poor areas.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14091978","usgsCitation":"Hempel, L.A., Malenda, H.F., Fulton, J.W., Henneberg, M.F., Cederberg, J., and Moramarco, T., 2022, The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river: Remote Sensing, v. 14, no. 9, 1978, 31 p., https://doi.org/10.3390/rs14091978.","productDescription":"1978, 31 p.","ipdsId":"IP-123910","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":448069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14091978","text":"Publisher Index Page"},{"id":399397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.52638244628906,\n 38.966082600437986\n ],\n [\n -108.4134292602539,\n 38.966082600437986\n ],\n [\n -108.4134292602539,\n 39.055984163572404\n ],\n [\n -108.52638244628906,\n 39.055984163572404\n ],\n [\n -108.52638244628906,\n 38.966082600437986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malenda, Helen F. 0000-0003-4143-6460","orcid":"https://orcid.org/0000-0003-4143-6460","contributorId":211885,"corporation":false,"usgs":false,"family":"Malenda","given":"Helen","email":"","middleInitial":"F.","affiliations":[{"id":38341,"text":"Colorodo School of Mines","active":true,"usgs":false}],"preferred":true,"id":841125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulton, John W, 0000-0002-5335-0720","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":213630,"corporation":false,"usgs":true,"family":"Fulton","given":"John","middleInitial":"W,","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henneberg, Mark F. 0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":187481,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841127,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cederberg, Jay 0000-0001-6649-7353","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":219724,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moramarco, Tommaso 0000-0002-9870-1694","orcid":"https://orcid.org/0000-0002-9870-1694","contributorId":225686,"corporation":false,"usgs":false,"family":"Moramarco","given":"Tommaso","email":"","affiliations":[{"id":41180,"text":"IRPI-Consiglio Nazionale delle Ricerche","active":true,"usgs":false}],"preferred":false,"id":841129,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70235714,"text":"70235714 - 2022 - Central Andean (28–34°S) flood record 0–25 ka from Salinas del Bebedero, Argentina","interactions":[],"lastModifiedDate":"2022-09-27T16:56:37.687376","indexId":"70235714","displayToPublicDate":"2022-04-20T06:54:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Central Andean (28–34°S) flood record 0–25 ka from Salinas del Bebedero, Argentina","docAbstract":"The Salinas del Bebedero occupies an isolated basin in the foreland of central Argentina at 33°S and was flooded repeatedly over past 25 ka. Isotopic evidence demonstrates that this flooding was due to overflow of the nearby Río Desaguadero with waters derived from the distant (≥300 km) central Andes between 28–34°S. Stratigraphic and shoreline evidence shows that floods occurred most frequently between 14.4 and 15.7 ka, followed by lesser events between 14.3 to 11.4 ka, and during the late Holocene from 2.6 to ca. 0.2 ka. Hydraulic modeling (2D HEC-RAS) shows that these floods could have originated from repeated subglacial drainage or sudden outbursts with a volume of >100 × 106 m3 and a peak discharge of >1,000 m3 s-1 each. The absence of flood deposits from 11 to 3 ka points to exceptionally dry and virtually ice-free conditions in the Andes between 28–34°S. The floods were probably caused by major rainfall or dammed-lake outbursts clustered largely during wet pluvial periods in the otherwise moisture-limited central Andes and Atacama Desert, such as when the Intertropical Convergence Zone was shifted southward. These include Central Andean pluvial events (CAPE) I (17–14.5 ka) and II (12.5–9 ka), and the Neoglacial/Formative archeological period 2500 ka to near-present.
pyGSFLOW is a python package designed to create new GSFLOW integrated hydrologic models, read existing models, edit model input data, run GSFLOW models, process output, and visualize model data.
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","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8796","usgsCitation":"Hitchcock, C.J., Gallegos, E., Backlin, A.R., Barabe, R., Bloom, P., Boss, K., Brehme, C.S., Brown, C., Clark, D., Clark, E.R., Cooper, K., Donnell, J., Ervin, E., Famolaro, P., Guilliam, K.M., Hancock, J., Hess, N., Howard, S., Hubbartt, V., Lieske, P., Lovich, R.E., Matsuda, T., Meyer-Wilkins, K., Muri, K., Nerhus, B., Nordland, J.A., Ortega, B., Packard, R., Ramirez, R., Stewart, S.C., Sweet, S., Warburton, M.L., Wells, J., Winkleman, R., Winter, K., Zitt, B., and Fisher, R., 2022, Range-wide persistence of the endangered arroyo toad (Anaxyrus californicus) for 20+ years following a prolonged drought: Ecology and Evolution, v. 12, no. 4, e8796, 21 p., https://doi.org/10.1002/ece3.8796.","productDescription":"e8796, 21 p.","ipdsId":"IP-137785","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448085,"rank":0,"type":{"id":41,"text":"Open 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Permafrost thaw and increased subsurface flow have been inferred from the chemistry of large rivers, but there is limited empirical evidence of the impacts to headwater streams. Here we demonstrate how changing vegetation cover and soil thaw may alter headwater catchment hydrology using water budgets, stream discharge trends, and chemistry across a gradient of ground temperature in northwestern Alaska. Colder, tundra-dominated catchments shed precipitation through stream discharge, whereas in warmer catchments with greater forest extent, evapotranspiration and infiltration are substantial fluxes. Forest soils thaw earlier, remain thawed longer, and display seasonal water content declines, consistent with greater evapotranspiration and infiltration. Streambed infiltration and water chemistry indicate that even minor warming can lead to increased infiltration and subsurface flow. Additional warming, permafrost loss, and vegetation shifts in the Arctic will deliver water back to the atmosphere and to subsurface aquifers in many regions, with the potential to substantially reduce discharge in headwater streams, if not compensated by increasing precipitation. Decreasing discharge in headwater streamflow will have important implications for aquatic and riparian ecosystems.","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ac5f2d","usgsCitation":"Koch, J.C., Sjoberg, Y., O’Donnell, J.A., Carey, M.P., Sullivan, P., and Terskaia, A., 2022, Sensitivity of headwater streamflow to thawing permafrost and vegetation change in a warming Arctic: Environmental Research Letters, v. 17, no. 4, 044074, 14 p., https://doi.org/10.1088/1748-9326/ac5f2d.","productDescription":"044074, 14 p.","ipdsId":"IP-128694","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":448088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac5f2d","text":"Publisher Index Page"},{"id":491321,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EIX8ET","text":"USGS data release","linkHelpText":"Water Level, Temperature, and Discharge of Headwater Streams in the Noatak and Kobuk River Basins, Northwest Alaska, 2015-2017"},{"id":399083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Agashashok River, Akillik River, Brooks Range, Cutler River, Kobuk Valley National Park, Noatak National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -163.23486328125,\n 66.60067571342496\n ],\n [\n -158.302001953125,\n 66.60067571342496\n ],\n [\n -158.302001953125,\n 68.06509825098962\n ],\n [\n -163.23486328125,\n 68.06509825098962\n ],\n [\n -163.23486328125,\n 66.60067571342496\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":840925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sjoberg, Ylva 0000-0002-4292-5808","orcid":"https://orcid.org/0000-0002-4292-5808","contributorId":194635,"corporation":false,"usgs":false,"family":"Sjoberg","given":"Ylva","email":"","affiliations":[],"preferred":false,"id":840926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":840927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":840928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Pamela","contributorId":190446,"corporation":false,"usgs":false,"family":"Sullivan","given":"Pamela","affiliations":[],"preferred":false,"id":840929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terskaia, A.","contributorId":290400,"corporation":false,"usgs":false,"family":"Terskaia","given":"A.","email":"","affiliations":[{"id":62417,"text":"Lomonosov Moscow State University","active":true,"usgs":false}],"preferred":false,"id":840930,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230723,"text":"70230723 - 2022 - Methanogenic archaea in subsurface coal seams are biogeographically distinct: An analysis of metagenomically-derived mcrA sequences","interactions":[],"lastModifiedDate":"2022-09-27T16:44:03.117871","indexId":"70230723","displayToPublicDate":"2022-04-19T06:37:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1548,"text":"Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Methanogenic archaea in subsurface coal seams are biogeographically distinct: An analysis of metagenomically-derived mcrA sequences","docAbstract":"The production of methane as an end-product of organic matter degradation in the absence of other terminal electron acceptors is common, and has often been studied in environments such as animal guts, soils, and wetlands due to its potency as a greenhouse gas. To date however, the study of the biogeographic distribution of methanogens across coal seam environments has been minimal. Here, we show that coal seams are host to a diverse range of methanogens, which are distinctive to each geological basin. Based on comparisons to close relatives from other methanogenic environments, the dominant methanogenic pathway in these basins is hydrogenotrophic, with acetoclastic being a second major pathway in the Surat Basin. Finally, mcrA and 16S rRNA gene primer biases were predominantly seen to affect the detection of Methanocellales, Methanomicrobiales and Methanosarcinales taxa in this study. Subsurface coal methanogenic community distributions and pathways presented here provide insights into important metabolites and bacterial partners for in situ coal biodegradation.
","language":"English","publisher":"Society for Applied Microbiology","doi":"10.1111/1462-2920.16014","usgsCitation":"Campbell, B., Greenfield, P., , G., Barnhart, E.P., Midgley, D.J., Paulsen, I.T., and George, S.C., 2022, Methanogenic archaea in subsurface coal seams are biogeographically distinct: An analysis of metagenomically-derived mcrA sequences: Environmental Microbiology, v. 24, no. 9, p. 4065-4078, https://doi.org/10.1111/1462-2920.16014.","productDescription":"14 p.","startPage":"4065","endPage":"4078","ipdsId":"IP-139639","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":448092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1462-2920.16014","text":"Publisher Index Page"},{"id":399486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Bronwyn C","contributorId":290556,"corporation":false,"usgs":false,"family":"Campbell","given":"Bronwyn C","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":841239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greenfield, Paul","contributorId":290557,"corporation":false,"usgs":false,"family":"Greenfield","given":"Paul","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":841240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":" Gong","contributorId":290560,"corporation":false,"usgs":false,"given":"Gong","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":841241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Midgley, David J.","contributorId":290564,"corporation":false,"usgs":false,"family":"Midgley","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":841243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paulsen, Ian T.","contributorId":290566,"corporation":false,"usgs":false,"family":"Paulsen","given":"Ian","email":"","middleInitial":"T.","affiliations":[{"id":16788,"text":"Macquarie University","active":true,"usgs":false}],"preferred":false,"id":841244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"George, Simon C.","contributorId":290569,"corporation":false,"usgs":false,"family":"George","given":"Simon","email":"","middleInitial":"C.","affiliations":[{"id":16788,"text":"Macquarie University","active":true,"usgs":false}],"preferred":false,"id":841245,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230520,"text":"sir20225025 - 2022 - Development of continuous bathymetry and two-dimensional hydraulic models for the Willamette River, Oregon","interactions":[],"lastModifiedDate":"2022-04-19T11:02:31.280556","indexId":"sir20225025","displayToPublicDate":"2022-04-18T11:26:01","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5025","displayTitle":"Development of Continuous Bathymetry and Two-Dimensional Hydraulic Models for the Willamette River, Oregon","title":"Development of continuous bathymetry and two-dimensional hydraulic models for the Willamette River, Oregon","docAbstract":"The Willamette River is home to at least 69 species of fish, 33 of which are native, including Chinook salmon (Oncorhynchus tshawytscha) and steelhead (Oncorhynchus mykiss). These fish need suitable hydraulic conditions, such as water depth and velocity, to fulfill various stages of their life. Hydraulic conditions are driven by interactions between channel morphology and streamflow, which throughout the Willamette River are strongly influenced by the operation of flood-control dams in upstream tributaries. To assess how streamflow management at these dams affects downstream fish habitat, the U.S. Geological Survey has developed high-resolution bathymetric datasets to support the development of two-dimensional hydraulic models. The datasets were created by combining data collected by airborne topo-bathymetric Light Detection and Ranging with boat-based sonar to create a seamless modeling surface over which a computational mesh with a resolution of roughly 5 by 5 meters was overlaid using the U.S. Army Corps of Engineers Hydraulic Engineering Center’s River Analysis System 5.0.7 hydraulic modeling software. Models were developed for about 200 river kilometers, separated into five modeling reaches, and hydraulic conditions were simulated at flows ranging from extremely low values to annual peak flows. Results of the simulations highlight distinct patterns of inundation extents, water depths, and velocities that vary longitudinally along the Willamette River. In the two farthest upstream model reaches, from Eugene to Corvallis, the river is slower, shallower, and inundates more area at similar seasonal flows than in reaches downstream from Corvallis, where the river generally is deeper and faster. These findings align with previous geomorphic analysis of the Willamette River showing the upper reaches of the river to be geomorphically more dynamic compared to the largely single-thread channel farther downstream. Results of simulations made with these hydraulic models can be used to drive fish-habitat models to further inform flow-management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225025","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"White, J.S., and Wallick, J.R., 2022, Development of continuous bathymetry and two-dimensional hydraulic models for the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5025, 67 p., https://doi.org/10.3133/sir20225025.","productDescription":"viii, 67 p.","onlineOnly":"Y","ipdsId":"IP-112990","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":435874,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NB0KUT","text":"USGS data release","linkHelpText":"Two-dimensional HEC-RAS models and topo-bathymetric datasets for the Willamette River, Oregon"},{"id":435873,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92TTY4R","text":"USGS data release","linkHelpText":"Single-beam Echosounder Bathymetry of the Willamette River, Oregon 2015-2018"},{"id":398795,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5025/images"},{"id":398794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5025/sir20225025.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5025"},{"id":398793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5025/coverthb.jpg"},{"id":398796,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5025/sir20225025.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.59619140625001,\n 43.94537239244209\n ],\n [\n -121.904296875,\n 43.94537239244209\n ],\n [\n -121.904296875,\n 45.521743896993634\n ],\n [\n -123.59619140625001,\n 45.521743896993634\n ],\n [\n -123.59619140625001,\n 43.94537239244209\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
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The management of the quantity and timing of freshwater flow into and through the San Francisco Estuary (SFE) is a perennial source of controversy in California. It is well known that freshwater outflow is a major environmental driver in estuarine ecosystems, including the SFE. However, the estuary is also the hub of California’s water distribution system, which supplies water to over 25 million Californians and a multibillion-dollar agricultural industry. This tension between water supply and maintaining flows to maintain environmental quality is at the core of the controversy.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"IEP technical report #98: White papers providing a synthesis of knowledge relating to Delta Smelt biology in the San Francisco Estuary, emphasizing effects of flow","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"California Department of Water Resources","usgsCitation":"Brown, L.R., 2022, Introduction to the Delta Smelt flow alteration white papers, chap. of IEP technical report #98: White papers providing a synthesis of knowledge relating to Delta Smelt biology in the San Francisco Estuary, emphasizing effects of flow, p. 5-9.","productDescription":"5 p.","startPage":"5","endPage":"9","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":416626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416625,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=200748","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.98094279060476,\n 38.310018990096125\n ],\n [\n -122.98094279060476,\n 37.38439884189815\n ],\n [\n -121.79974134416376,\n 37.38439884189815\n ],\n [\n -121.79974134416376,\n 38.310018990096125\n ],\n [\n -122.98094279060476,\n 38.310018990096125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70230753,"text":"70230753 - 2022 - Dynamic abiotic habitat","interactions":[],"lastModifiedDate":"2023-05-02T16:11:26.398534","indexId":"70230753","displayToPublicDate":"2022-04-18T10:45:47","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Dynamic abiotic habitat","docAbstract":"The factors affecting an organism can be divided into two general classes, abiotic and biotic. Abiotic factors include features of the physical and chemical environment, such as climate, water movement, and many aspects of water quality. Biotic factors refer to those involving living organisms and their interactions, such as the organisms and processes in a food web. We also distinguish between dynamic and stationary abiotic factors. Stationary abiotic factors are fixed in the environment and include things like landscape features (e.g., bays, channels, and surface elevations) that change relatively slowly over time. Dynamic abiotic factors vary over time and space at various scales ranging from sub-daily (e.g., tidal direction and velocity) to annually (e.g., total water inflow and outflow).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"IEP technical report #98: White papers providing a synthesis of knowledge relating to Delta Smelt biology in the San Francisco Estuary, emphasizing effects of flow","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"California Department of Water Resources","usgsCitation":"Brown, L.R., Slater, S.B., and MacWilliams, M.L., 2022, Dynamic abiotic habitat, chap. of IEP technical report #98: White papers providing a synthesis of knowledge relating to Delta Smelt biology in the San Francisco Estuary, emphasizing effects of flow, p. 10-54.","productDescription":"45 p.","startPage":"10","endPage":"54","ipdsId":"IP-135366","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":416624,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416623,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=200748","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.98094279060476,\n 38.310018990096125\n ],\n [\n -122.98094279060476,\n 37.38439884189815\n ],\n [\n -121.79974134416376,\n 37.38439884189815\n ],\n [\n -121.79974134416376,\n 38.310018990096125\n ],\n [\n -122.98094279060476,\n 38.310018990096125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Larry R. 0000-0001-6702-4531","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":269405,"corporation":false,"usgs":false,"family":"Brown","given":"Larry","email":"","middleInitial":"R.","affiliations":[{"id":55970,"text":"USGS CAWSC (not in system - posthumous)","active":true,"usgs":false}],"preferred":false,"id":841285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Steven B.","contributorId":178380,"corporation":false,"usgs":false,"family":"Slater","given":"Steven","email":"","middleInitial":"B.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":841286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacWilliams, Michael L.","contributorId":173010,"corporation":false,"usgs":false,"family":"MacWilliams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":841287,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230515,"text":"sir20225037 - 2022 - Conceptual models of groundwater flow in the Grand Canyon region, Arizona","interactions":[],"lastModifiedDate":"2022-04-19T10:51:47.459506","indexId":"sir20225037","displayToPublicDate":"2022-04-18T10:34:30","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5037","displayTitle":"Conceptual models of groundwater flow in the Grand Canyon region, Arizona","title":"Conceptual models of groundwater flow in the Grand Canyon region, Arizona","docAbstract":"The conceptual models of groundwater flow outlined herein synthesize what is known and hypothesized about the groundwater-flow systems that discharge to the Grand Canyon of Arizona. These models interpret the hydrogeologic characteristics and hydrologic dynamics of the physical systems into a framework for understanding key aspects of the physical systems as they relate to groundwater flow and contaminant transport. This report describes five individual groundwater-flow systems draining to the Grand Canyon: Kaibab, Uinkaret-Kanab, Marble-Shinumo, Cataract, and Blue Spring. These systems are present in the saturated parts of the lower Paleozoic carbonate section exposed on the walls of the Grand Canyon; specifically, the Mississippian Redwall Limestone down through the Cambrian Muav Limestone of Tonto Group. Together, the systems described in this report compose the regional groundwater-flow system. Local to subregional flow systems in the sedimentary units of the overlying Permian section could provide transport pathways from the land surface to the regional flow system. Despite the potential importance of the local systems, the focus of this report is on the systems present in the lower Paleozoic section because all major springs in the Grand Canyon discharge from those units.
The most important hydrogeologic characteristics include system boundaries imposed by major tectonic structures, and the degree to which karstification influences the magnitude and direction of flow in each system. Important hydrologic dynamics include locations and rates of potential groundwater recharge, vertical pathways to the regional aquifer, and the locations, magnitude, geochemical signature, and hydrostratigraphic setting of groundwater discharge from springs. Unknown properties or conditions that represent the greatest uncertainties in our current understanding of the regional groundwater-flow system are identified for additional consideration.
Groundwater data are sparse owing to geographic remoteness and extreme depth to water throughout much of the study area. This paucity of information was diminished with the development of a structural contour map of the top and bottom surfaces of the regional aquifer, and a Soil-Water-Balance model that produces spatial distributions of rates of potential recharge. Investigation of the five groundwater-flow systems reveals important, though mostly qualitative, characteristics controlling the rates and directions of groundwater flow. Karstification has produced dissolution-enhanced conduit flow pathways to various degrees in each of the systems. Parts of each system exhibit relative structural uplift or downdropping of the hydrostratigraphic units of the regional aquifer, with some uplifted sections dipping inward toward the Grand Canyon and others dipping outward. The Kaibab groundwater system is archetypical of an uplifted, inward-dipping karst system, whereas the Blue Spring groundwater system and most of the Cataract groundwater system are representative instances of a downdropped or basin karst system. The Uinkaret-Kanab groundwater-flow system is structurally similar to the basin karst systems but karstification has not progressed to nearly the same degree. The Marble-Shinumo groundwater system does not fall cleanly into either category and its boundaries are the most uncertain of all the groundwater systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225037","usgsCitation":"Knight, J.E., and Huntoon, P.W., 2022, Conceptual models of groundwater flow in the Grand Canyon region, Arizona: U.S. Geological Survey Scientific Investigation Report 2022–5037, 51 p., https://doi.org/10.3133/sir20225037.","productDescription":"Report: vi, 51 p.; Data Release","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-097904","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":398738,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5037/covrthb.jpg"},{"id":398739,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5037/sir20225037.pdf","text":"Report","size":"24 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":398737,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FQ7BSY","text":"Soil-Water-Balance (SWB) model archive used to simulate potential mean annual recharge in the Grand Canyon region, Arizona","description":"Knight, J.E., and Jones, C.J., 2022, Soil-Water-Balance (SWB) model archive used to simulate potential mean annual recharge in the Grand Canyon region, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9FQ7BSY."}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.64257812499999,\n 34.79576153473033\n ],\n [\n -110.58837890625,\n 34.79576153473033\n ],\n [\n -110.58837890625,\n 36.96744946416934\n ],\n [\n -113.64257812499999,\n 36.96744946416934\n ],\n [\n -113.64257812499999,\n 34.79576153473033\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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520 N. Park Avenue
Tucson, AZ 85719
Harmful algal blooms (HABs) present an emerging threat to human and ecosystem health in the Alaskan Arctic. Two HAB toxins are of concern in the region: saxitoxins (STXs), a family of compounds produced by the dinoflagellate Alexandrium catenella, and domoic acid (DA), produced by multiple species in the diatom genus Pseudo-nitzschia. These potent neurotoxins cause paralytic and amnesic shellfish poisoning, respectively, in humans, and can accumulate in marine organisms through food web transfer, causing illness and mortality among a suite of wildlife species. With pronounced warming in the Arctic, along with enhanced transport of cells from southern waters, there is significant potential for more frequent and larger HABs of both types. STXs and DA have been detected in the tissues of a range of marine organisms in the region, many of which are important food resources for local residents. The unique nature of the Alaskan Arctic, including difficult logistical access, lack of response infrastructure, and reliance of coastal populations on the noncommercial acquisition of marine resources for nutritional, cultural, and economic well-being, poses urgent and significant challenges as this region warms and the potential for impacts from HABs expands.
","language":"English","publisher":"Oceanography Society","doi":"10.5670/oceanog.2022.121","usgsCitation":"Anderson, D., Fachon, E., Hubbard, K., Lefebvre, K., Lin, P., Pickart, R., Richlen, M., Sheffield, G., and Van Hemert, C.R., 2022, Harmful algal blooms in the Alaskan Arctic: An emerging threat as oceans warm: Oceanography, v. 35, no. 2, 27 p., https://doi.org/10.5670/oceanog.2022.121.","productDescription":"27 p.","ipdsId":"IP-136279","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":448098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2022.121","text":"Publisher Index Page"},{"id":402672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Donald","contributorId":189872,"corporation":false,"usgs":false,"family":"Anderson","given":"Donald","affiliations":[],"preferred":false,"id":845353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fachon, Evangeline","contributorId":292636,"corporation":false,"usgs":false,"family":"Fachon","given":"Evangeline","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":845354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, Katherine","contributorId":292637,"corporation":false,"usgs":false,"family":"Hubbard","given":"Katherine","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":845355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lefebvre, Kathi","contributorId":257892,"corporation":false,"usgs":false,"family":"Lefebvre","given":"Kathi","affiliations":[{"id":52164,"text":"Environmental and Fisheries Science Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":845356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Peigen","contributorId":292640,"corporation":false,"usgs":false,"family":"Lin","given":"Peigen","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":845357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pickart, Robert","contributorId":292641,"corporation":false,"usgs":false,"family":"Pickart","given":"Robert","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":845358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richlen, Mindy","contributorId":292643,"corporation":false,"usgs":false,"family":"Richlen","given":"Mindy","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":845359,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sheffield, Gay","contributorId":257533,"corporation":false,"usgs":false,"family":"Sheffield","given":"Gay","email":"","affiliations":[{"id":52049,"text":"Alaska Sea Grant","active":true,"usgs":false}],"preferred":false,"id":845360,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":845361,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70230544,"text":"sir20225038 - 2022 - Using microbial source tracking to identify fecal contamination sources in Lake Montauk on Long Island, New York","interactions":[],"lastModifiedDate":"2022-09-27T13:54:56.679894","indexId":"sir20225038","displayToPublicDate":"2022-04-15T14:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5038","displayTitle":"Using Microbial Source Tracking To Identify Fecal Contamination Sources in Lake Montauk on Long Island, New York","title":"Using microbial source tracking to identify fecal contamination sources in Lake Montauk on Long Island, New York","docAbstract":"The U.S. Geological Survey worked in cooperation with the Concerned Citizens of Montauk and the New York State Department of Environmental Conservation to assess the potential sources of fecal contamination entering Lake Montauk, an artificial embayment on the tip of the southern fork of Suffolk County, Long Island, New York. Water samples are routinely collected by the New York State Department of Environmental Conservation in the harbor and analyzed for fecal coliform bacteria, an indicator of fecal contamination, to determine the need for closure of shellfish beds for harvest and consumption. Fecal coliform and other bacteria are an indicator of the potential presence of pathogenic (disease-causing) bacteria. However, indicator bacteria alone cannot determine the biological or geographical sources of contamination; therefore, microbial source tracking was implemented to determine various biological sources of contamination. In addition, information such as the location, weather and season, and surrounding land use where a sample was collected help determine the geographical source and conveyance of land-based water to the embayment.
Overall, human and waterfowl markers were infrequently and sporadically present in source and receptor samples at low concentrations. By evaluating the microbial source tracking markers alongside fecal coliform data and land-use information, geographical sources of fecal contamination discharging from various source sites, such as culverts and ponds, were better differentiated. Analysis revealed that stormwater runoff and pond drainage were the most likely transport mechanisms for fecal contamination to Lake Montauk. When considering Lake Montauk as a whole, the highest frequency of fecal coliform detections in source site samples was found to be under wet summer conditions, as evidenced by the high fecal coliform concentrations at the South Beach, Stepping Stones Pond, and Stepping Stones Pond Culvert sites (300, 220, and more than 16,000 most probable number per 100 milliliters, respectively). No point sources of fecal coliform contamination to Lake Montauk were identified; however, receptor site samples adjacent to marinas (Lake Montauk Inlet and Star Island North sites) had a high frequency of human marker detections but were associated with fecal coliform concentrations at or below the reporting limit. The absence of fecal coliform and human microbial source tracking markers in groundwater samples indicated that water from septic systems did not influence the lake during this study. Further, the sandy sediment sample collected at the South Beach site was negative for all microbial source tracking markers and is unlikely to contribute fecal coliform from the tested host organisms when resuspended in the water column through tidal shifts or boat activity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225038","collaboration":"Prepared in cooperation with Concerned Citizens of Montauk and New York State Department of Environmental Conservation","usgsCitation":"Tagliaferri, T.N., Fisher, S.C., Kephart, C.M., Cheung, N., Reed, A.P., and Welk, R.J., 2022, Using microbial source tracking to identify fecal contamination sources in Lake Montauk on Long Island, New York: U.S. Geological Survey Scientific Investigations Report 2022–5038, 16 p., https://doi.org/10.3133/sir20225038.","productDescription":"Report: vi, 16 p.; Database","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129971","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":398849,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225038/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5038"},{"id":398819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5038/sir20225038.pdf","text":"Report","size":"1.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5038"},{"id":398818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5038/coverthb.jpg"},{"id":398822,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the nation"},{"id":398821,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5038/images/"},{"id":398820,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5038/sir20225038.XML"},{"id":398823,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20215033","text":"Scientific Investigations Report 2021–5033","linkHelpText":"- Overview and Methodology for a Study To Identify Fecal Contamination Sources Using Microbial Source Tracking in Seven Embayments on Long Island, New York"}],"country":"United States","state":"New York","otherGeospatial":"Lake Montauk","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.95701599121094,\n 41.03715373847282\n ],\n [\n -71.87461853027344,\n 41.03715373847282\n ],\n [\n -71.87461853027344,\n 41.084009326420926\n ],\n [\n -71.95701599121094,\n 41.084009326420926\n ],\n [\n -71.95701599121094,\n 41.03715373847282\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
The U.S. Geological Survey constructed the potentiometric surface of the Upland terrace and upper Ponchatoula aquifers and the “400-foot” sand using the altitude of water levels from 121 wells measured January 2014 to March 2015. Differences in water levels in the Upland terrace and upper Ponchatoula aquifers and “400-foot” sand were measured at 55 wells in 2009 and again at the same wells in 2014–15. Long-term hydrographs for most wells screened in the Upland terrace aquifer and “400-foot” sand show seasonal fluctuations with little net change in water levels.
The potentiometric surface of the “600-foot” sand was constructed by using the altitude of water levels from 14 wells measured from January 2014 to March 2015. Differences in water levels between 2009 and 2014–15 were determined in the “600-foot” sand by using measurements collected at seven wells. These differences do not necessarily indicate a trend but show water levels declined by more than 5 feet from 2009 to 2015. Long-term hydrographs for two wells screened in the “600-foot” sand show declines in water levels but vary in their drawdown and recovery based on location relative to areas of substantial groundwater withdrawal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3488","collaboration":"Prepared in cooperation with the Louisiana Department of Natural Resources","usgsCitation":"Frederick, C.P., 2022, Potentiometric surface, 2014–15, and water-level differences, 2009 to 2014–15, in the Chicot equivalent aquifer system in southeastern Louisiana: U.S. Geological Survey Scientific Investigations Map 3488, 2 sheets, https://doi.org/10.3133/sim3488.","productDescription":"2 Sheets: 38.00 × 36.00 inches; Data Release; Dataset","ipdsId":"IP-060348","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":501932,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112936.htm","linkFileType":{"id":5,"text":"html"}},{"id":398562,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":398549,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3488/sim3488.pdf","text":"Sheets 1 and 2","size":"1.41 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":398561,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","linkHelpText":"Water withdrawals by source and category in Louisiana parishes, 2014–2015"},{"id":398548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3488/coverthb2.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chicot Equivalent Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.58203125,\n 30.088107753367257\n ],\n [\n -89.681396484375,\n 30.088107753367257\n ],\n [\n -89.681396484375,\n 31.071755902820133\n ],\n [\n -91.58203125,\n 31.071755902820133\n ],\n [\n -91.58203125,\n 30.088107753367257\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
The primary focus of this study was to document cadmium, copper, lead, and zinc concentrations in selected streams near the U.S. Army Joint Readiness Training Center (JRTC) and Fort Polk Military Reservation and to compare those values to Federal and State aquatic-life criteria guidelines. The acute aquatic-life criteria used for this study are as follows: the U.S. Environmental Protection Agency (EPA) aquatic-life criterion maximum concentration (CMC) based on hardness, the EPA CMC for copper based on the biotic ligand model (BLM), and the Louisiana Department of Environmental Quality (LDEQ) acute aquatic-life criteria based on hardness. The chronic aquatic-life criteria used for this study are as follows: the EPA aquatic-life criterion continuous concentration (CCC) based on hardness, the EPA CCC for copper based on the BLM, and the LDEQ chronic aquatic-life criteria based on hardness.
Cadmium was detected in one stream-water sample collected near the Peason Ridge training area, hereinafter referred to as Peason Ridge, and one stream-water sample collected near North and South Fort Polk, hereinafter referred to as the Main Post. A cadmium concentration of an estimated (E) 0.48 microgram per liter (μg/L) in a stream-water sample collected during high stage near Peason Ridge exceeded the EPA CMC of 0.10 μg/L. A second cadmium concentration of E0.33 μg/L in a stream-water sample collected during low stage exceeded the EPA CMC of 0.22 μg/L, and a 4-day average cadmium concentration of E0.16 μg/L exceeded the EPA CCC of 0.14 μg/L.
Copper was detected in 34 stream-water samples collected near Peason Ridge and 22 stream-water samples collected near the Main Post. The EPA acute criteria for copper were exceeded 17 times in stream-water samples collected near Peason Ridge and 19 times in stream-water samples collected near the Main Post. The EPA chronic criteria for copper were exceeded five times in stream-water samples collected near Peason Ridge and seven times in stream-water samples collected near the Main Post.
Lead was detected in 31 stream-water samples collected near Peason Ridge and 16 stream-water samples collected near the Main Post. A concentration of 6.0 μg/L in a stream-water sample collected during high stage at site 2 near Peason Ridge exceeded the EPA CMC of 5.5 μg/L, and a concentration of 4.1 μg/L in a stream-water sample collected during high stage at site 4 near the Main Post exceeded the EPA CMC of 2.9 μg/L. The EPA chronic criteria for lead were exceeded nine times in stream-water samples collected near Peason Ridge and three times in stream-water samples collected near the Main Post. The LDEQ chronic criteria were exceeded two times in stream-water samples near Peason Ridge and none near the Main Post.
Zinc was detected in 35 stream-water samples collected near Peason Ridge and 17 stream-water samples collected near the Main Post. A concentration of 100 μg/L in a stream-water sample collected at site 3 near Peason Ridge exceeded the EPA CMC of 8.9 μg/L and the LDEQ acute aquatic-life criteria of 36 μg/L. One 4-day average zinc concentration, E28 μg/L for stream-water samples collected from site 3 near Peason Ridge, exceeded the EPA CCC of 8.2 μg/L; however, no concentrations of zinc exceeded the LDEQ chronic aquatic-life criteria near Peason Ridge or the Main Post.
The presence of copper, lead, and zinc at concentrations above the calculated acute or chronic aquatic-life criteria for some stream-water samples collected in relatively pristine streams near Peason Ridge and the Main Post indicates that these waters are susceptible to elevated trace element concentrations likely because of low ionic strength and hardness.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215101","collaboration":"Prepared in cooperation with the U.S. Army Joint Readiness Training Center and the Fort Polk Military Reservation","usgsCitation":"Tollett, R.W., 2022, Aquatic-life criteria compared to concentrations of cadmium, copper, lead, and zinc in streams near Fort Polk Military Reservation, Louisiana, December 2015–August 2016: U.S. Geological Survey Scientific Investigations Report 2021–5101, 40 p., https://doi.org/10.3133/sir20215101.","productDescription":"Report: viii, 40 p.; Data Release; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-106720","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":397567,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5101/sir20215101.XML"},{"id":397566,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5101/sir20215101.pdf","text":"Report","size":"4.37 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":502115,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112935.htm","linkFileType":{"id":5,"text":"html"}},{"id":397571,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397570,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74M93FJ","text":"USGS data release","linkHelpText":"Water-quality and grain-size data collected at three sites near the Peason Ridge training area and two sites near the Main Post at the Joint Readiness Training Center and Fort Polk, 2015–2016"},{"id":397568,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5101/images"},{"id":397565,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5101/coverthb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Fort Polk Military Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.39340209960938,\n 30.9187201197222\n ],\n [\n -92.58865356445312,\n 30.9187201197222\n ],\n [\n -92.58865356445312,\n 31.431006719178512\n ],\n [\n -93.39340209960938,\n 31.431006719178512\n ],\n [\n -93.39340209960938,\n 30.9187201197222\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
The importance of terrestrial coastal ecosystems for maintaining healthy coral reef ecosystems remains understudied. Sea kraits are amphibious snakes that require healthy coral reefs for foraging, but little is known about their requirements of terrestrial habitats, where they slough their skin, digest prey, and breed. Using concurrent microclimate measurements and behavior surveys, we show that a small, topographically flat atoll in Fiji with coastal forest provides many microhabitats that relate to the behaviors of Yellow Lipped Sea Kraits, Laticauda colubrina. Microclimates were significantly related to canopy cover, leaf litter depth, and distance from the high-water mark (HWM). Sea kraits were almost exclusively observed in coastal forest within 30 m of the HWM. Sloughing of skins only occurred within crevices of mature or dying trees. Resting L. colubrina were significantly more likely to occur at locations with higher mean diurnal temperatures, lower leaf litter depths, and shorter distances from the HWM. On Leleuvia, behavior of L. colubrina therefore relates to environmental heterogeneity created by old-growth coastal forests, particularly canopy cover and crevices in mature and dead tree trunks. The importance of healthy coastal habitats, both terrestrial and marine, for L. colubrina suggests it could be a good flagship species for advocating integrated land-sea management. Furthermore, our study highlights the importance of coastal forests and topographically flat atolls for biodiversity conservation. Effective conservation management of amphibious species that utilize land- and seascapes is therefore likely to require a holistic approach that incorporates connectivity among ecosystems and environmental heterogeneity at all relevant scales.
Ceratonova shasta is a myxozoan parasite endemic to the Pacific Northwest of North America that is linked to low survival rates of juvenile salmonids in some watersheds such as the Klamath River basin. The density of C. shasta actinospores in the water column is typically highest in the spring (March–June), and directly influences infection rates for outmigrating juvenile salmonids. Current management approaches require quantities of C. shasta density to assess disease risk and estimate survival of juvenile salmonids. Therefore, we developed a model to simulate the density of waterborne C. shasta actinospores using a mechanistic framework based on abiotic drivers and informed by empirical data. The model quantified factors that describe the key features of parasite abundance during the period of juvenile salmon outmigration, including the week of initial detection (onset), seasonal pattern of spore density, and peak density of C. shasta. Spore onset was simulated by a bio-physical degree-day model using the timing of adult salmon spawning and accumulation of thermal units for parasite development. Normalized spore density was simulated by a quadratic regression model based on a parabolic thermal response with river water temperature. Peak spore density was simulated based on retained explanatory variables in a generalized linear model that included the prevalence of infection in hatchery-origin Chinook juveniles the previous year and the occurrence of flushing flows (≥171 m3/s). The final model performed well, closely matched the initial detections (onset) of spores, and explained inter-annual variations for most water years. Our C. shasta model has direct applications as a management tool to assess the impact of proposed flow regimes on the parasite, and it can be used for projecting the effects of alternative water management scenarios on disease-induced mortality of juvenile salmonids such as with an altered water temperature regime or with dam removal.