Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no-flow fraction, date of first no flow, and duration of the dry-down period, with further divergence between natural and human-altered watersheds. Aridity was a primary driver of no-flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry-down duration showed stronger associations with nonclimate drivers compared to no-flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL090794","usgsCitation":"Hammond, J., Zimmer, M., Shanafield, M., Kaiser, K.E., Godsey, S., Mims, M.C., Zipper, S., Burrow, R., Kampf, S.K., Dodds, W., Jones, C., Krabbenhoft, C., Boersma, K., Datry, T., Olden, J., Allen, G., Price, A.N., Costigan, K., Hale, R., Ward, A.S., and Allen, D., 2021, Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States: Geophysical Research Letters, v. 48, no. 2, e2020GL090794, 11 p., https://doi.org/10.1029/2020GL090794.","productDescription":"e2020GL090794, 11 p.","ipdsId":"IP-119781","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":454097,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020gl090794","text":"External Repository"},{"id":436624,"rank":0,"type":{"id":30,"text":"Data 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The method is sufficiently sensitive and selective to ensure accurate and precise quantitation of As(III), As(V), DMA, and MMA in surface water and groundwater samples with As species concentrations from tens of nanograms per liter to 50 µg/L without dilution of the sample. Mean recoveries of the four species spiked into reagent water, surface water and groundwater and measured periodically over three months ranged from 87.2 % to 108.7 % and relative standard deviation of replicates of all analytes ranged from 1.1 % to 9.0 %.
The depth of active groundwater circulation is a fundamental control on stream flows and chemistry in mountain watersheds, yet it remains challenging to characterize and is rarely well constrained. We collected hydraulic conductivity, hydraulic head, temperature, chemical, noble gas, and 3H/3He groundwater age data from discrete levels in two boreholes 46 and 81 m deep in an alpine watershed, in combination with chemical and age data from shallow groundwater discharge, to discern groundwater flow rates at different depths and directly observe active and inactive groundwater. Vertical head gradients are steep (average of 0.4) and thermal profiles are consistent with typical linear conductive continental geotherms. Groundwater deeper than ∼20 m is distinct from shallow groundwater and creek water in its chemistry, noble gas signature, and age (dominantly >65 years compared to <9 years). Together these results suggest low vertical groundwater flow velocities and a relatively shallow active circulation depth of ∼20 m. This hypothesis is tested with a simple 2‐D numerical fluid flow and heat transport model representing a hillslope transect through the two boreholes. The modeling indicates that the subhorizontally bedded sedimentary rocks underlying the basin are highly anisotropic with low vertical hydraulic conductivity, and at most ∼10% of bedrock recharge (equivalent to <2% of stream baseflow) flows below a depth of 20 m. The study demonstrates the considerable value of discrete‐depth hydrogeologic, chemical, and age data for determining active circulation depth, and illustrates an approach for maximizing the utility of individual boreholes drilled for mountain bedrock aquifer characterization.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028548","usgsCitation":"Manning, A.H., Ball, L.B., Wanty, R., and Williams, K.H., 2021, Direct observation of the depth of active groundwater circulation in an alpine watershed: Water Resources Research, v. 57, no. 2, e2020WR028548, 21 p., https://doi.org/10.1029/2020WR028548.","productDescription":"e2020WR028548, 21 p.","ipdsId":"IP-121573","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028548","text":"Publisher Index Page"},{"id":384621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Redwell Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.13043212890625,\n 38.792626957868904\n ],\n [\n -106.80084228515625,\n 38.792626957868904\n ],\n [\n -106.80084228515625,\n 38.99997583555929\n ],\n [\n -107.13043212890625,\n 38.99997583555929\n ],\n [\n -107.13043212890625,\n 38.792626957868904\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":812858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wanty, Richard B. 0000-0002-2063-6423","orcid":"https://orcid.org/0000-0002-2063-6423","contributorId":209899,"corporation":false,"usgs":true,"family":"Wanty","given":"Richard","middleInitial":"B.","affiliations":[],"preferred":true,"id":812859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Kenneth H. 0000-0002-3568-1155","orcid":"https://orcid.org/0000-0002-3568-1155","contributorId":176791,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":812860,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263957,"text":"70263957 - 2021 - Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics","interactions":[],"lastModifiedDate":"2025-03-03T15:36:19.470968","indexId":"70263957","displayToPublicDate":"2020-12-11T09:30:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics","docAbstract":"Regional triplication waveforms of five intermediate-depth events are modeled to simultaneously obtain the compressional (P) and shear (SH) wave velocity structure beneath northwestern Pacific subduction zone. Both the P- and SH-wave velocity models for three different sub-regions show a low-velocity layer (LVL) with a thickness of ∼55-80 km lying above the 410-km discontinuity with a ∼900 km lateral extent from the Japan Sea to the northeastern Asian continental margin. With the dihedral angle approaching to zero around 400 km, a minute amount of melt atop the 410-km discontinuity caused by the hydrous slab might completely wet olivine grain boundaries and result in a low seismic velocity layer in this specific subduction zone. This mechanism suggests that the 410-LVL is a low viscosity zone that would partially decouple the upper mantle from the transition zone. We infer that the widespread 410-LVL provides evidence for a water-bearing mantle transition zone beneath the western Pacific subduction zone.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2020.116642","usgsCitation":"Han, G., Li, J., Guo, G., Mooney, W.D., Karato, S., and Yuen, D., 2021, Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics: Earth and Planetary Science Letters, v. 554, 116642, 13 p., https://doi.org/10.1016/j.epsl.2020.116642.","productDescription":"116642, 13 p.","ipdsId":"IP-122067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2020.116642","text":"Publisher Index Page"},{"id":482740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"554","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Han, Guangjie","contributorId":351730,"corporation":false,"usgs":false,"family":"Han","given":"Guangjie","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Juan","contributorId":351731,"corporation":false,"usgs":false,"family":"Li","given":"Juan","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guo, Guangrui","contributorId":351732,"corporation":false,"usgs":false,"family":"Guo","given":"Guangrui","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mooney, Walter D. 0000-0002-5310-3631 mooney@usgs.gov","orcid":"https://orcid.org/0000-0002-5310-3631","contributorId":3194,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","email":"mooney@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karato, Shun-Ichiro","contributorId":351733,"corporation":false,"usgs":false,"family":"Karato","given":"Shun-Ichiro","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":929346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuen, David A.","contributorId":351734,"corporation":false,"usgs":false,"family":"Yuen","given":"David A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":929347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217056,"text":"70217056 - 2021 - Permafrost promotes shallow groundwater flow and warmer headwater streams","interactions":[],"lastModifiedDate":"2021-03-05T21:14:01.609787","indexId":"70217056","displayToPublicDate":"2020-12-11T07:09:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost promotes shallow groundwater flow and warmer headwater streams","docAbstract":"The presence of permafrost influences the flow paths of water through Arctic landscapes and thereby has the potential to impact stream discharge and thermal regimes. Observations from eleven headwater streams in Alaska showed that July water temperatures were higher in catchments with more near‐surface permafrost. We apply a fully coupled cryohydrology model to investigate if the impact of permafrost on flow path depth could cause the same pattern in temperatures of groundwater discharging from hillslopes to streams. The model simulates surface energy and water balances, snow, and subsurface water and energy balances for two‐dimensional hillslope model cases with varying permafrost extent. We find that hillslopes with continuous permafrost have more shallow flow paths and twice as high rates of evapotranspiration, compared to hillslopes with no permafrost. For our simulated cases, 6.7 % of the horizontal water flux moves through the top organic soil layers when there is continuous permafrost, while only 0.5 % moves through organic layers without permafrost. The deeper flow paths in permafrost‐free simulations buffer seasonal temperature extremes, so that summer groundwater discharge temperatures are highest with continuous permafrost. Our results suggest that permafrost thawing alters groundwater flow paths and can lead to decreases in summer stream temperatures and reductions in evapotranspiration in headwater catchments. These changes are of potential importance for stream biotic components of ecosystems, however, the full impact remains unknown.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027463","usgsCitation":"Sjoberg, Y., Janke, A.K., Painter, S., Coonradt, E., Carey, M.P., O’Donnell, J.A., and Koch, J.C., 2021, Permafrost promotes shallow groundwater flow and warmer headwater streams: Water Resources Research, v. 57, no. 2, e2020WR027463, 20 p., https://doi.org/10.1029/2020WR027463.","productDescription":"e2020WR027463, 20 p.","ipdsId":"IP-117601","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":491329,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91HI62H","text":"USGS data release","linkHelpText":"Stream Temperature, Dissolved Oxygen, Conductivity, and Photosynthetically Active Radiation (PAR) in River Basins of Northwest Alaska, 2017-2024"},{"id":454110,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr027463","text":"Publisher Index Page"},{"id":436625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C3JYUH","text":"USGS data release","linkHelpText":"Physical, Hydraulic, and Thermal Properties of Soils in the Noatak River Basin, Alaska, 2016"},{"id":381798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"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 -163.685302734375,\n 66.93866882358137\n ],\n [\n -154.8193359375,\n 66.93866882358137\n ],\n [\n -154.8193359375,\n 68.62854757995426\n ],\n [\n -163.685302734375,\n 68.62854757995426\n ],\n [\n -163.685302734375,\n 66.93866882358137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"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":807421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":807422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, S 0000-0002-0901-6987","orcid":"https://orcid.org/0000-0002-0901-6987","contributorId":245978,"corporation":false,"usgs":false,"family":"Painter","given":"S","email":"","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":807423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coonradt, E. 0000-0001-8124-9622","orcid":"https://orcid.org/0000-0001-8124-9622","contributorId":140134,"corporation":false,"usgs":false,"family":"Coonradt","given":"E.","affiliations":[{"id":13388,"text":"ADF&G - Commercial Fisheries, 304 Lake Street, Sitka, Alaska 99835","active":true,"usgs":false}],"preferred":false,"id":807424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":807425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":807426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":807427,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218730,"text":"70218730 - 2021 - Seasonal periphyton response to low-level nutrient exposure in a least disturbed mountain stream, the Buffalo River, Arkansas","interactions":[],"lastModifiedDate":"2021-03-10T13:14:06.685619","indexId":"70218730","displayToPublicDate":"2020-12-11T07:06:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal periphyton response to low-level nutrient exposure in a least disturbed mountain stream, the Buffalo River, Arkansas","docAbstract":"Like most streams located in the Ozark Plateaus, the Buffalo River in Arkansas generally has excellent water quality. Water-quality conditions in Big Creek, however, a major tributary of the middle Buffalo River, have been less favorable than that of other Buffalo River tributaries. Concerns regarding the influence of water quality in Big Creek on the Buffalo River magnified in 2013 when a large confined animal feeding operation (CAFO) began operating in the watershed. In response to these concerns, the U.S. Geological Survey compared monthly nutrient concentrations and seasonal periphyton assemblage metrics of a site on Big Creek downstream of the CAFO, two Buffalo River control sites upstream of the confluence with Big Creek, and three Buffalo River test sites downstream of the confluence with Big Creek. In addition to identifying potential nutrient patterns and periphyton responses along a low-level nutrient exposure gradient, the study determined how nutrient contributions from Big Creek (and the CAFO) are affecting ecological conditions and consequent ecosystem services in the Buffalo River. Nutrient and periphyton data exhibited more temporal than spatial variability. Nutrient concentrations were generally highest of all sites at the Big Creek site. Concentrations at the five sites on the Buffalo River were typically low (near laboratory reporting limits), and concentrations at the three test sites rarely exceeded those of the two control sites. An index developed with three ecologically relevant periphyton metrics (oligotrophic taxa and Homoeothrix percent relative abundance and mesotrophic diatoms percent taxa richness) suggested that nutrient uptake at sites downstream of the Big Creek-Buffalo River confluence resulted in subtle shifts in downstream periphyton assemblages. The periphyton index of biological integrity at control sites was slightly and generally more favorable compared to test sites. Even so, when periphyton data were considered in conjunction with both hydrology and water-quality data, the negative consequences of antecedent high flows and associated scouring exceeded the potential positive effects that low-level nutrients had on algal productivity. These findings emphasize the importance of comparing biological and chemical data across extended temporal scales, particularly when working with low-level nutrient gradients.
A boosted regression tree model was developed to predict pH conditions in three dimensions throughout the glacial aquifer system of the contiguous United States using pH measurements in samples from 18,386 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and, when coupled with long flowpaths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate‐poor, pH conditions remain acidic. At depths typical of drinking‐water supplies, predicted pH >7.5—which is associated with arsenic mobilization—occurs more frequently than predicted pH <6—which is associated with water corrosivity and the mobilization of other trace elements. A novel aspect of this model was the inclusion of numerically based estimates of groundwater flow characteristics (age and flowpath length) as predictor variables. The sensitivity of pH predictions to these variables was consistent with hydrologic understanding of groundwater flow systems and the geochemical evolution of groundwater quality. The model was not developed to provide precise estimates of pH at any given location. Rather, it can be used to more generally identify areas where contaminants may be mobilized into groundwater and where corrosivity issues may be of concern to prioritize areas for future groundwater monitoring.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13063","usgsCitation":"Stackelberg, P.E., Belitz, K., Brown, C., Erickson, M., Elliott, S.M., Kauffman, L.J., Ransom, K.M., and Reddy, J., 2021, Machine learning predictions of pH in the Glacial Aquifer System, Northern USA: Groundwater, v. 37, no. 4, p. 531-543, https://doi.org/10.1111/gwat.13063.","productDescription":"13 p.","startPage":"531","endPage":"543","ipdsId":"IP-122702","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454116,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gwat.13063","text":"External Repository"},{"id":436626,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RF0R6E","text":"USGS data release","linkHelpText":"Data for machine learning predictions of pH in the glacial aquifer system, northern USA"},{"id":382483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":808740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kauffman, Leon J. 0000-0003-4564-0362","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":206428,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ransom, Katherine Marie 0000-0001-6195-7699","orcid":"https://orcid.org/0000-0001-6195-7699","contributorId":239552,"corporation":false,"usgs":true,"family":"Ransom","given":"Katherine","email":"","middleInitial":"Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808746,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reddy, James E. 0000-0002-6998-7267","orcid":"https://orcid.org/0000-0002-6998-7267","contributorId":206426,"corporation":false,"usgs":true,"family":"Reddy","given":"James E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808747,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216892,"text":"70216892 - 2021 - The impact of ventilation patterns on calcite dissolution rates within karst conduits","interactions":[],"lastModifiedDate":"2020-12-30T14:53:23.957547","indexId":"70216892","displayToPublicDate":"2020-12-10T08:47:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The impact of ventilation patterns on calcite dissolution rates within karst conduits","docAbstract":"Erosion rates in streams vary dramatically over time, as differences in streamflow and sediment load enhance or inhibit erosion processes. Within cave streams, and other bedrock channels incising soluble rocks, changes in water chemistry are an important factor in determining how erosion rates will vary in both time and space. Prior studies in surface streams, springs, and caves suggest that variation in dissolved CO2 is the strongest control on variation in calcite dissolution rates. However, the controls on CO2 variation remain poorly quantified. Limited data suggest that ventilation of karst systems can substantially influence dissolved CO2 within karst conduits. However, the interactions among cave ventilation, air-water CO2 exchange, and dissolution dynamics have not been studied in detail. In this study, three years of time series measurements of dissolved and gaseous CO2, cave airflow velocity, and specific conductance from Blowing Springs Cave, Arkansas, were analyzed and used to estimate continuous calcite dissolution rates and quantify the correlations between those rates and potential physical and chemical drivers. We find that chimney effect airflow creates temperature-driven switches in airflow direction, and that the resulting seasonal changes in airflow regulate both gaseous and dissolved CO2 within the cave. As in previous studies, partial pressure of CO2 (pCO2) is the strongest chemical control of dissolution rate variability. However, we also show that cave airflow direction, rather than streamflow, is the strongest physical driver of changes in dissolution rate, contrary to the typical situation in surface channel erosion where floods largely determine the timing and extent of geomorphic work. At the study site, chemical erosion is typically active in the summer, during periods of cave downdraft (airflow from upper to lower entrances), and inactive in the winter, during updraft (airflow from lower to upper entrances). Storms provide only minor perturbations to this overall pattern. We also find that airflow direction modulates dissolution rate variation during storms, with higher storm variability during updraft than during downdraft. Finally, we compare our results with the limited set of other studies that have examined dissolution rate variation within cave streams and draw an initial hypothesis that evolution of cave ventilation patterns strongly impacts how dissolution rate dynamics evolve over the lifetime of karst conduits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125824","usgsCitation":"Covington, M.D., Knierim, K.J., Young, H.H., Rodriguez, J., and Gnoza, H., 2021, The impact of ventilation patterns on calcite dissolution rates within karst conduits: Journal of Hydrology, v. 593, 125824, 17 p., https://doi.org/10.1016/j.jhydrol.2020.125824.","productDescription":"125824, 17 p.","ipdsId":"IP-118284","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":381252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","city":"Bella Vista","otherGeospatial":"Blowing Springs Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.47624206542969,\n 36.380937621825886\n ],\n [\n -94.13360595703125,\n 36.380937621825886\n ],\n [\n -94.13360595703125,\n 36.61111838494165\n ],\n [\n -94.47624206542969,\n 36.61111838494165\n ],\n [\n -94.47624206542969,\n 36.380937621825886\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"593","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Covington, Matthew D.","contributorId":192015,"corporation":false,"usgs":false,"family":"Covington","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":806758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Holly H","contributorId":222433,"corporation":false,"usgs":false,"family":"Young","given":"Holly","email":"","middleInitial":"H","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez, Josue","contributorId":245654,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Josue","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":806761,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gnoza, Hannah","contributorId":245655,"corporation":false,"usgs":false,"family":"Gnoza","given":"Hannah","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":806762,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216939,"text":"70216939 - 2021 - Effect of temperature, nitrate concentration, pH and bicarbonate addition on biomass and lipid accumulation in the sporulating green alga PW95","interactions":[],"lastModifiedDate":"2020-12-17T14:16:12.365392","indexId":"70216939","displayToPublicDate":"2020-12-10T08:13:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5275,"text":"Algal Research","active":true,"publicationSubtype":{"id":10}},"title":"Effect of temperature, nitrate concentration, pH and bicarbonate addition on biomass and lipid accumulation in the sporulating green alga PW95","docAbstract":"The mixed effects of temperature (20 °C, 25 °C and 30 °C), nitrate concentration (0.5 mM and 2.0 mM), pH buffer, and bicarbonate addition (trigger) on biomass growth and lipid accumulation were investigated in the environmental alga PW95 during batch experiments in standardized growth medium. PW95 was isolated from coal-bed methane production water and classified as a Chlamydomonas-like species by morphological characterization and phylogenetic analysis (18S, ITS, rbcL). A factorial experimental design tested the mixed effects on PW95 before and after nitrate depletion to determine a low cost, high efficiency combination of treatments for biomass growth and lipid accumulation. Results showed buffer addition affected growth for most of the treatments and bicarbonate trigger had no statistically significant effect on growth and lipid accumulation. PW95 displayed the highest growth rate and chlorophyll content at 30 °C and 2.0 mM nitrate and there was an inverse relation between biomass accumulation and lipid accumulation at the extremes of nitrate concentration and temperature. The combination of higher temperature (30 °C) and lower nitrate level (0.5 mM) without the use of a buffer or bicarbonate addition resulted in maximal daily biomass accumulation (5.30 × 106 cells/mL), high biofuel potential before and after nitrate depletion (27% and 20%), higher biofuel productivity (16 and 15 mg/L/d, respectively), and desirable fatty acid profiles (saturated and unsaturated C16 and C18 chains). Our results indicate an important interaction between low nitrate levels, temperature, and elevated pH for trade-offs between biomass and lipid production in PW95. This work serves as a model to approach and advance the study of physiological responses of novel microalgae to diverse culture conditions that mimic environmental changes for outdoor biofuel production. The most promising conditions for growth and biofuel production were identified for PW95 and this approach can be implemented for other microalgal production systems.
The introduction of exotic species has the potential to cause resource competition with native species and may lead to competitive exclusion when resources are limiting. On the other hand, information is lacking to predict under what alternate trophic conditions coexistence may occur. Comparing diets of native yellow perch Perca flavescens and nonindigenous white perch Morone americana, we examined variation in resource partitioning and body condition across a prominent longitudinal nutrient gradient in Lake Erie (north‐eastern United States, Canada). As measured with Analysis of Similarity and Schoener's index, diet similarity declined monotonically from west to east tracking declines in nutrients, productivity and relative abundance of both species. Additionally, diet similarity increased from spring through fall, following seasonal development of stratification and hypolimnetic hypoxia—phenomena which tend to increase spatial overlap between these species. Finally, relative weights of both species peaked in the Central Basin (relative weights > 0.85), which, on average, had intermediate values of prey diversity, ecosystem trophic status and water clarity. Our results highlight that native yellow perch coexist with invasive white perch under a wide range of trophic conditions. Of importance to fishery managers, mesotrophy in the Central Basin correlated with the highest body conditions and intermediate prey resource partitioning, although the effect size was small and variable. While competitive exclusion appears unlikely, the goal of reducing nutrient inputs in Lake Erie could affect not only the distributions of both species but also stakeholder decisions about where to fish.
","language":"English","doi":"10.1111/eff.12586","usgsCitation":"Kraus, R., Schmitt, J., and Keretz, K.R., 2021, Resource partitioning across a trophic gradient between a freshwater fish and an intraguild exotic: Ecology of Freshwater Fish, v. 30, no. 3, p. 320-333, https://doi.org/10.1111/eff.12586.","productDescription":"14 p.","startPage":"320","endPage":"333","ipdsId":"IP-112101","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.2548828125,\n 42.65012181368022\n ],\n [\n -83.07861328125,\n 42.16340342422401\n ],\n [\n -83.5400390625,\n 41.64007838467894\n ],\n [\n -81.71630859375,\n 41.36031866306708\n ],\n [\n -79.98046875,\n 42.08191667830631\n ],\n [\n -78.7060546875,\n 42.8115217450979\n ],\n [\n -79.47509765625,\n 42.89206418807337\n ],\n [\n -81.2548828125,\n 42.65012181368022\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keretz, Kevin R. 0000-0002-4808-8350 kkeretz@usgs.gov","orcid":"https://orcid.org/0000-0002-4808-8350","contributorId":5859,"corporation":false,"usgs":true,"family":"Keretz","given":"Kevin","email":"kkeretz@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":806929,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219516,"text":"70219516 - 2021 - From forests to fish: Mercury in mountain lake food webs influenced by factors at multiple scales","interactions":[],"lastModifiedDate":"2021-04-22T17:46:08.628605","indexId":"70219516","displayToPublicDate":"2020-12-09T09:15:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"From forests to fish: Mercury in mountain lake food webs influenced by factors at multiple scales","docAbstract":"Mountain lakes, while seemingly pristine, have been subjected to historical fish stocking practices and exposure to atmospherically deposited contaminants like mercury. Mercury bioaccumulation in these ecosystems varies widely due to strong environmental gradients, and there are complex, hierarchical factors that affect mercury transport and loading, methylmercury production, and food web biomagnification. We sought to assess how representative variables associated with watershed, lake, and food web‐scale processes—specifically, catchment tree cover, lake benthic primary production, and fish diet, respectively—are associated with mercury concentrations in mountain lake fish. Mean fish mercury concentrations varied threefold between lakes, with nearshore tree cover and fish diet accounting for the most variance in fish mercury. Tree cover was likely positively correlated to fish Hg due to its contributions to local deposition and its effect on lake biogeochemistry. Fish with benthic diets tended to have higher mercury concentrations, illustrating that food web processes are an important consideration when investigating drivers of contaminant bioaccumulation. Our results suggest that both landscape and ecological factors are determinants of fish mercury bioaccumulation, and thus variables at multiple scales should be considered when managing mountain lake food webs for mercury exposure risk.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11659","usgsCitation":"Chiapella, A.M., Eagles-Smith, C., and Strecker, A.L., 2021, From forests to fish: Mercury in mountain lake food webs influenced by factors at multiple scales: Limnology and Oceanography, v. 66, no. 4, p. 1021-1035, https://doi.org/10.1002/lno.11659.","productDescription":"15 p.","startPage":"1021","endPage":"1035","ipdsId":"IP-113076","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://cedar.wwu.edu/esci_facpubs/62","text":"Publisher Index Page"},{"id":385014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. Baker‐Snoqualmie National Forest, Mount Rainier National Park, North Cascades National Park, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.18969726562499,\n 47.37603463349758\n ],\n [\n -122.80517578125,\n 47.754097979680026\n ],\n [\n -122.98095703125,\n 48.019324184801185\n ],\n [\n -124.23339843749999,\n 48.21003212234042\n ],\n [\n -124.49707031249999,\n 48.070738264258296\n ],\n [\n -124.365234375,\n 47.82053186746053\n ],\n [\n -124.15649414062499,\n 47.502358951968574\n ],\n [\n -123.585205078125,\n 47.24194882163242\n ],\n [\n -123.18969726562499,\n 47.37603463349758\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.77246093750001,\n 47.44294999517949\n ],\n [\n -120.5255126953125,\n 47.44294999517949\n ],\n [\n -120.5255126953125,\n 48.99103162515999\n ],\n [\n -121.77246093750001,\n 48.99103162515999\n ],\n [\n -121.77246093750001,\n 47.44294999517949\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.288818359375,\n 46.14939437647686\n ],\n [\n -120.67932128906249,\n 46.14939437647686\n ],\n [\n -120.67932128906249,\n 47.14116119721898\n ],\n [\n -122.288818359375,\n 47.14116119721898\n ],\n [\n -122.288818359375,\n 46.14939437647686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Chiapella, Ariana M.","contributorId":257254,"corporation":false,"usgs":false,"family":"Chiapella","given":"Ariana","email":"","middleInitial":"M.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":813899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strecker, Angela L","contributorId":257255,"corporation":false,"usgs":false,"family":"Strecker","given":"Angela","email":"","middleInitial":"L","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":813901,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217147,"text":"70217147 - 2021 - Effective hydrological events in an evolving mid‐latitude mountain river system following cataclysmic disturbance—A saga of multiple influences","interactions":[],"lastModifiedDate":"2021-02-18T12:41:01.836757","indexId":"70217147","displayToPublicDate":"2020-12-09T07:25:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Effective hydrological events in an evolving mid‐latitude mountain river system following cataclysmic disturbance—A saga of multiple influences","docAbstract":"Cataclysmic eruption of Mount St. Helens (USA) in 1980 reset 30 km of upper North Fork Toutle River (NFTR) valley to a zero‐state fluvial condition. Consequently, a new channel system evolved. Initially, a range of streamflows eroded channels (tens of meters incision, hundreds of meters widening) and transported immense sediment loads. Now, single, large‐magnitude or multiple moderate‐magnitude events are needed to accomplish substantial channel modification. Three large floods (two ≥100‐year events; one ∼10–25‐year event along lower Toutle River) from 1996 to 2015 indicate flood effectiveness in this environment is affected by both geomorphic and environmental factors. The largest and smallest of these floods (February 1996, November 2006) transported the most sediment by single floods since 1982; erosion and sediment transport by an ∼100‐year flood in December 2015 was not exceptional. Strong coupling between NFTR and its tall corridor banks, local geologic and hydraulic conditions promoting threshold erosion, event sequencing, and possibly a longitudinal gradient in stream power are important factors affecting event effectiveness on channel modification. In addition, environmental factors have also been influential, as variations in snowpack, storm trajectories and rainfall distributions, and episodic mobilization of debris flows have also influenced geomorphic response. Other factors such as vegetation anchoring, strong channel–hillside coupling, disparities between flood frequencies and perturbation relaxation times, and large variations in flood duration do not appear to be critical influences. Climate forecasts for warmer temperatures and a shift from snowfall to rainfall at high elevations may promote further acute geomorphic responses.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR026851","usgsCitation":"Major, J.J., Spicer, K.R., and Mosbrucker, A.R., 2021, Effective hydrological events in an evolving mid‐latitude mountain river system following cataclysmic disturbance—A saga of multiple influences: Water Resources Research, v. 57, no. 2, e2019WR026851, https://doi.org/10.1029/2019WR026851.","productDescription":"e2019WR026851","ipdsId":"IP-123125","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":807738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":807740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":807739,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218694,"text":"70218694 - 2021 - Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models","interactions":[],"lastModifiedDate":"2021-03-05T13:14:47.975659","indexId":"70218694","displayToPublicDate":"2020-12-09T07:10:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models","docAbstract":"Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.
Specific conductivity (SC) is commonly used to estimate the proportion of baseflow (i.e., waters from within catchments such as groundwater, interflow, or bank return flows) contributing to rivers. Reach-scale SC comparisons are also useful for identifying where multiple water stores contribute to baseflow. Daily SC values of adjacent gauges in Australian (the Barwon, Glenelg, and Campaspe Rivers) and North American (the Upper Colorado River) catchments are commonly not well correlated (R2 = 0.32 to 0.82). Smoothed inter-gauge SC values averaged over 7 to 45 days are better correlated and define a series of hysteresis loops. The variable SC patterns between adjacent gauges probably reflect varying proportions of groundwater, bank return waters, interflow, and soil water contributing to baseflow. In some rivers using SC values to compare baseflow along river reaches on sub-annual timescales may be not be feasible.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125895","usgsCitation":"Cartwright, I., and Miller, M., 2021, Temporal and spatial variations in river specific conductivity: Implications for understanding sources of river water and hydrograph separations: Journal of Hydrology, v. 593, 125895, 8 p., https://doi.org/10.1016/j.jhydrol.2020.125895.","productDescription":"125895, 8 p.","ipdsId":"IP-120526","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":381795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"593","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cartwright, Ian 0000-0001-5300-4716","orcid":"https://orcid.org/0000-0001-5300-4716","contributorId":245985,"corporation":false,"usgs":false,"family":"Cartwright","given":"Ian","email":"","affiliations":[{"id":27278,"text":"Monash University","active":true,"usgs":false}],"preferred":false,"id":807452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228565,"text":"70228565 - 2021 - Temporal invariance of social-ecological catchments","interactions":[],"lastModifiedDate":"2022-02-14T19:55:29.246571","indexId":"70228565","displayToPublicDate":"2020-12-08T14:55:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Temporal invariance of social-ecological catchments","docAbstract":"Natural resources such as waterbodies, public parks, and wildlife refuges attract people from varying distances on the landscape, creating \"social-ecological catchments.\" Catchments have provided great utility for understanding physical and social relationships within specific disciplines. Yet, catchments are rarely used across disciplines, such as its application to understand complex spatiotemporal dynamics between mobile human users and patchily distributed natural resources. We collected residence ZIP codes from 19,983 angler parties during 2014–2017 to construct seven angler–waterbody catchments in Nebraska, USA. We predicted that sizes of dense (10% utilization distribution) and dispersed (95% utilization distribution) angler–waterbody catchments would change across seasons and years as a function of diverse resource selection among mobile anglers. Contrary to expectations, we revealed that catchment size was invariant. We discuss how social (conservation actions) and ecological (low water quality, reduction in species diversity) conditions are expected to impact landscape patterns in resource use. We highlight how this simple concept and user-friendly technique can inform timely landscape-level conservation decisions within coupled social-ecological systems that are currently difficult to study and understand.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2272","usgsCitation":"Kaemingk, M., Bender, C.N., Chizinski, C., Bunch, A., and Pope, K.L., 2021, Temporal invariance of social-ecological catchments: Ecological Applications, v. 31, no. 2, e02272, 7 p., https://doi.org/10.1002/eap.2272.","productDescription":"e02272, 7 p.","ipdsId":"IP-118117","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kaemingk, Mark A.","contributorId":276159,"corporation":false,"usgs":false,"family":"Kaemingk","given":"Mark A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bender, Christine N.","contributorId":276158,"corporation":false,"usgs":false,"family":"Bender","given":"Christine","email":"","middleInitial":"N.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":834614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chizinski, Christopher J.","contributorId":274559,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunch, Aaron J.","contributorId":276161,"corporation":false,"usgs":false,"family":"Bunch","given":"Aaron J.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":834618,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217113,"text":"70217113 - 2021 - Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie","interactions":[],"lastModifiedDate":"2021-01-07T12:36:19.107351","indexId":"70217113","displayToPublicDate":"2020-12-07T07:00:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie","docAbstract":"The spatial distribution, concentration, particle size, and polymer compositions of microplastics in Lake Michigan and Lake Erie sediment were investigated. Fibers/lines were the most abundant of the five particle types characterized. Microplastic particles were observed in all samples with mean concentrations for particles greater than 0.355 mm of 65.2 p kg–1 in Lake Michigan samples (n = 20) and 431 p kg–1 in Lake Erie samples (n = 12). Additional analysis of particles with size 0.1250–0.3549 mm in Lake Erie resulted in a mean concentration of 631 p kg–1. The majority of polymers in Lake Michigan samples were poly(ethylene terephthalate) (PET), high-density polyethylene (HDPE), and semisynthetic cellulose (S.S. Cellulose), and in Lake Erie samples were S.S. Cellulose, polypropylene (PP), and poly(vinyl chloride) (PVC). Polymer density estimates indicated that 85 and 74% of observed microplastic particles have a density greater than 1.1 g cm–3 for Lake Michigan and Lake Erie, respectively. The current study provided a multidimensional dataset on the spatial distribution of microplastics in benthic sediment from Lake Michigan and Lake Erie and valuable information for assessment of the fate of microplastics in the Great Lakes.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06087","usgsCitation":"Lenaker, P.L., Corsi, S., and Mason, S.A., 2021, Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie: Environmental Science & Technology, v. 55, no. 1, p. 373-384, https://doi.org/10.1021/acs.est.0c06087.","productDescription":"12 p.","startPage":"373","endPage":"384","ipdsId":"IP-119261","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":454148,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.0c06087","text":"Publisher Index Page"},{"id":436628,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WJUODZ","text":"USGS data release","linkHelpText":"Microplastics in the surficial benthic sediment from Lake Michigan and Lake Erie, 2013 and 2014"},{"id":381937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Ontario, Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.71484375,\n 41.50857729743935\n ],\n [\n -86.1328125,\n 41.50857729743935\n ],\n [\n -86.1328125,\n 46.255846818480315\n ],\n [\n -87.71484375,\n 46.255846818480315\n ],\n [\n -87.71484375,\n 41.50857729743935\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.3203125,\n 41.244772343082076\n ],\n [\n -79.013671875,\n 41.244772343082076\n ],\n [\n -79.013671875,\n 42.48830197960227\n ],\n [\n -83.3203125,\n 42.48830197960227\n ],\n [\n -83.3203125,\n 41.244772343082076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Sherri A.","contributorId":176172,"corporation":false,"usgs":false,"family":"Mason","given":"Sherri","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":807636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217085,"text":"70217085 - 2021 - Factors affecting nitrate concentrations in stream base flow","interactions":[],"lastModifiedDate":"2021-07-02T13:38:46.739023","indexId":"70217085","displayToPublicDate":"2020-12-04T07:16:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting nitrate concentrations in stream base flow","docAbstract":"Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow (n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c02495","usgsCitation":"Wherry, S., Tesoriero, A.J., and Terziotti, S., 2021, Factors affecting nitrate concentrations in stream base flow: Environmental Science and Technology, v. 55, no. 2, p. 902-911, https://doi.org/10.1021/acs.est.0c02495.","productDescription":"10 p.","startPage":"902","endPage":"911","ipdsId":"IP-109230","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":436629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RXR45G","text":"USGS data release","linkHelpText":"Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)"},{"id":381871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, 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Center","active":true,"usgs":true}],"preferred":true,"id":807557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217898,"text":"70217898 - 2021 - Evidence that watershed nutrient management practices effectively reduce estrogens in environmental waters","interactions":[],"lastModifiedDate":"2021-02-10T13:41:33.260981","indexId":"70217898","displayToPublicDate":"2020-12-03T07:37:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evidence that watershed nutrient management practices effectively reduce estrogens in environmental waters","docAbstract":"We evaluate the impacts of different nutrient management strategies on the potential for co-managing estrogens and nutrients in environmental waters of the Potomac watershed of the Chesapeake Bay. These potential co-management approaches represent agricultural and urban runoff, wastewater treatment plant effluent, and combined sewer overflow replacements. Twelve estrogenic compounds and their metabolites were analysed by gas chromatography–mass spectrometry. Estrogenic activity (E2Eq) was measured by in vitro bioassay. We detected estrone E1 (0.05–6.97 ng L−1) and estriol E3 (below detection-8.13 ng L−1) and one conjugated estrogen (estrone-3-sulfate E1-3S; below detection-8.13 ng L−1). E1 was widely distributed and positively correlated with E2Eq, water temperature, and dissolved organic carbon (DOC). Among nonpoint sources, E2Eq, and concentrations of E1, soluble reactive phosphorus (SRP) and total dissolved nitrogen (TDN) decreased by 51–61%, 77–82%, 62–64%, 4–16% in restored urban and agricultural streams with best management practices (BMPs) relative to unrestored streams without BMPs. In a wastewater treatment plant (Blue Plains WWTP), >94% of E1, E1-3S, E3, E2Eq and TDN were removed while SRP increased by 305% during nitrification/denitrification as a part of advanced wastewater treatment. Consequently, E1 and TDN concentrations in WWTP effluents were comparable or even lower than those observed in the receiving stream or river waters, and the effects of wastewater discharges on downstream E1 and TDN concentrations were minor. Highest E2Eq value and concentrations of E1, E3, and TDN were detected in combined sewer overflow (CSO). This study suggests that WWTP upgrades with biological nutrient removal, CSO management, and certain agricultural and urban BMPs for nutrient controls have the potential to remove estrogens from point and nonpoint sources along with other contaminants in streams and rivers.
Long known as the island chain farthest from any continental landmass, the Hawaiian Islands are the subaerial expression of volcanism above the relatively fixed Hawaiian hot spot as the Pacific plate drifts northwest above it. Each island is built by one or several overlapping shield volcanoes, some of the most voluminous on Earth. Plate translation creates the well-known age-progressive sequence of shield volcanoes from northwest to southeast. Total volume of magma produced along the Hawaiian chain has been irregular but generally increasing for the past 50 million years, a trend that has peaked in the last 3 million years.
Hawaiian volcanoes grow through stages that have geologic expression and geochemical differences that reflect position relative to the underlying hot spot. Of these stages, the shield stage is the most productive when an estimated 80–95% of a volcano's ultimate volume is emplaced. The shield stage endures for about 1 million years.
The burden of shield volcanoes depresses the ocean crust near the hot spot, creating the Hawaiian Moat. Greatest rate of subsidence today occurs at the Island of Hawai‘i, 2–3 mm per year along its coast. Flexural rebound occurs as volcanoes move away from the hot spot; the Island of O‘ahu shows the greatest uplift. Slow subsidence resumes downstream from the flexure, leading ultimately to submergence of each island in the chain.
Large landslides, albeit infrequent, can occur at any stage of island evolution. Ground water is the principal source of potable and agricultural water on all islands; its distribution both reflects and influences island geology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12513-8","usgsCitation":"Sinton, J., and Sherrod, D.R., 2021, Geology of the Hawaiian Islands, chap. of Encyclopedia of geology, p. 742-757, https://doi.org/10.1016/B978-0-12-409548-9.12513-8.","productDescription":"16 p.","startPage":"742","endPage":"757","ipdsId":"IP-114676","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":387632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sinton, John M","contributorId":261682,"corporation":false,"usgs":false,"family":"Sinton","given":"John M","affiliations":[{"id":52956,"text":"University of Hawai‘i at Mānoa, Honolulu, Hawai‘i,","active":true,"usgs":false}],"preferred":false,"id":820408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820409,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251779,"text":"70251779 - 2021 - Porphyry and epithermal mineral deposits","interactions":[],"lastModifiedDate":"2024-02-28T15:46:44.606969","indexId":"70251779","displayToPublicDate":"2020-12-02T09:45:21","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Porphyry and epithermal mineral deposits","docAbstract":"Porphyry and epithermal mineral deposits form large economic ore bodies that provide the global economy with copper, molybdenum, gold, silver and other byproducts (Re, Te, Se). They form in the upper crust and are related to sulfur- and water-rich intermediate to silicic magmatic sources of hydrothermal fluids that move upward and produce extensive hydrolytic and alkali wall-rock alteration, quartz veins, and sulfides. Porphyry-type deposits are formed above magma chambers where fluids hydrofracture rock at 700–350 °C and at pressures ranging from supra-lithostatic to supra-hydrostatic. The depth of formation ranges from 2 to 10 km and influences orebody geometries and the types and mineralogy of veins, sulfides and wall-rock alteration. The temporal evolution of hydrothermal events is documented by cross-cutting veins and is commonly characterized by a decline in fluid temperature and concordant evolution from potassic alteration to sericitic alteration, with attendant increase in sulfidation state of copper-iron sulfides.
In some localities porphyry copper deposits transition upwards to lower temperature base metal lodes (350–200 °C) and eventually the formation of near surface (<1.5 km depth) intermediate- and high-sulfidation epithermal deposits (~300–120 °C). Extensional environments are often characterized by porphyry molybdenum and low-sulfidation epithermal deposits. In the base metal lode and epithermal environments, mixtures of magmatic and meteoric fluids produce ore fluids at hydrostatic pressures that advect freely both vertically and laterally along permeability provided by faults, joints, and porous lithologies. Wall-rock alteration ranges from hydrolytic to alkali-carbonate, and from high- to low-sulfidation state sulfide assemblages, respectively.
In porphyry, base metal lode, and epithermal environments, geology and the zonation of wall-rock alteration, veins, sulfide assemblages, and metals are useful for exploration.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology (secind editon)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-102908-4.00005-9","usgsCitation":"Dilles, J.H., and John, D.A., 2021, Porphyry and epithermal mineral deposits, chap. of Encyclopedia of geology (secind editon), p. 847-866, https://doi.org/10.1016/B978-0-08-102908-4.00005-9.","productDescription":"20 p.","startPage":"847","endPage":"866","ipdsId":"IP-116791","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":426066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dilles, John H","contributorId":214317,"corporation":false,"usgs":false,"family":"Dilles","given":"John","email":"","middleInitial":"H","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216879,"text":"70216879 - 2021 - Ocean floor manganese deposits","interactions":[],"lastModifiedDate":"2020-12-11T14:49:39.09465","indexId":"70216879","displayToPublicDate":"2020-12-02T08:46:13","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Ocean floor manganese deposits","docAbstract":"Much of the dissolved Mn delivered to the oceans is slowly oxidized and precipitated alongside varying amounts of Fe into Mn and ferromanganese (FeMn) mineral deposits that occur extensively in the deep ocean wherever sediment accumulation is low and substrate is available. FeMn crusts grow as pavements on rock outcrops throughout the global ocean whereas nodules form as individual FeMn-encrusted particles on the sediment-covered abyssal plains. Both crusts and nodules are composed predominantly of Fe and Mn oxide minerals that precipitate from seawater and for some nodules also from porewaters of deep-sea sediment. In contrast, hydrothermal oxide deposits consist predominantly of Mn or Fe oxide. FeMn crusts and nodules exhibit very high specific surface areas that allow them to scavenge abundant metals and other elements, recording the history of the source waters. Crusts especially serve as an important record of paleoceanographic conditions over the past 70 + million years. Critical metals essential to many computer, military, and green technologies are enriched in crust and nodule deposits to concentrations high enough to compare with, or exceed, typical terrestrial deposits, and they can be considered as potential resources for mining in the near future. Twenty-three contracts pertaining to exploration for nodules and crusts have been signed with the International Seabed Authority, and resource/reserve, baseline, and environmental impact assessments are underway. Many challenges remain to be addressed before full-scale mining of marine FeMn deposits will occur. However, their unique genesis and the growing worldwide need for rare and critical metals keep these deep-ocean deposits relevant to industry, scientists, and governments.
The PHREEQ-N-AMDTreat aqueous geochemical modeling tools described herein simulate changes in pH and solute concentrations resulting from passive and active treatment of acidic or alkaline mine drainage (AMD). The “user-friendly” interactive tools, which are publicly available software, utilize PHREEQC equilibrium aqueous and surface speciation models and kinetics models for O2 ingassing and CO2 outgassing, iron and manganese oxidation and precipitation, limestone dissolution, and organic carbon oxidation combined with reduction of nitrate, sulfate, and ferric iron. Reactions with synthetic caustic chemicals (CaO, Ca(OH)2, NaOH, Na2CO3) or oxidizing agents (H2O2) also may be simulated separately or combined with sequential kinetic steps. A user interface facilitates input of water chemistry data for one or two (mixed) influent AMD solutions and adjustment of kinetic variables. Graphical and tabular output indicates the changes in pH, metals and other solute concentrations, total dissolved solids, and specific conductance of treated effluent plus the cumulative quantity of precipitated solids as a function of retention time or the amount of caustic agent added. By adjusting kinetic variables or chemical dosing, the effects of independent or sequential treatment steps that have different retention time (volume/flow rate), aeration rate, quantities of reactive solids, and temperature can be simulated for the specified influent quality. The size (land area) of a treatment system can then be estimated using reaction time estimates (volume for a corresponding treatment step is the product of reaction time and flow rate; area is volume divided by depth). Given the estimated system size, the AMDTreat cost-analysis model may be used to compute approximate costs for installation (capital) and annual operations and maintenance. Thus, various passive and/or active treatment strategies can be identified that could potentially achieve the desired effluent quality, but require different land area, equipment, and costs for construction and operation.
Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12465","usgsCitation":"Smith, C.D., Plumb, J., Adams, N.S., and Wyatt, G.J., 2021, Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon: Fisheries Management and Ecology, v. 28, no. 2, p. 172-182, https://doi.org/10.1111/fme.12465.","productDescription":"11 p.","startPage":"172","endPage":"182","ipdsId":"IP-097283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":384347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Estacada","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38632202148438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.273920035433605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":811725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218662,"text":"70218662 - 2021 - Assessment of two techniques for remediation of lacustrine rocky reef spawning habitat","interactions":[],"lastModifiedDate":"2021-04-22T18:16:06.965503","indexId":"70218662","displayToPublicDate":"2020-11-30T07:46:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of two techniques for remediation of lacustrine rocky reef spawning habitat","docAbstract":"Rocky reef habitats in lacustrine systems constitute important areas for lithophilic‐spawning fishes. Interstitial spaces created by the structure of rocky reefs form microenvironments where incubating embryos and juvenile fish are potentially protected from predators and physical displacement. However, if interstitial spaces are filled or blocked by sediment or biofouling, the reef structure may lose these benefits. Common practices to restore reef habitat include augmentation of existing reef structures or construction of new reefs, though these practices can be costly. We explored an alternative approach for reef remediation. In 2018, we developed two benthic sled cleaning devices that used either propulsion or pressurized water jets and were towed behind a small vessel to clean reefs. We used the devices to clean two impaired natural rocky reefs in Saginaw Bay, Lake Huron. We indexed effectiveness of cleaning by measured changes in substrate relative hardness before and after cleaning. A biological response to reef cleaning was also measured by egg deposition of fall (Lake Whitefish Coregonus clupeaformis) and spring (Walleye Sander vitreus) lithophilic spawners. We found that our propulsion cleaning device was more effective in increasing substrate relative hardness than was the water jet device, although this was not consistent among all study locations. We also found that egg deposition on study plots was variable, but in general, egg deposition was highest on study plots that had the greatest increases in relative hardness post‐cleaning. The practicality of cleaning devices is likely related to the magnitude of site‐specific degradation. Our results indicate that the use of these or similar devices can potentially increase the quality of spawning habitat by displacing sediments that have deposited on reef structures.
Documenting responses of biotic assemblages to coal-mining impacts is crucial to informing regulatory and reclamation actions. However, attributing biotic patterns to specific stressors is difficult given the dearth of preimpact studies and prevalence of confounding factors. Analysing species distributions and abundances, especially stratified by species traits, provides insights into how assemblage composition shifts occur. We evaluated stream habitats and fish assemblages along a mining intensity gradient in 83 headwater (2nd- and 3rd-order) streams of the upper Clinch and Powell river basins in Virginia. Our multivariate gradient (MINE.PC1) was based on percentages of watershed area covered by surface mine, underground mine and valley fill to represent spatial variance in mining intensity. MINE.PC1 was positively correlated with conductivity and percentage of substrate as cobble. Forty fish-assemblage metrics were analysed via boosted regression trees to assess assemblage responses to mining intensity, while accounting for environmental variation and spatial structure among sites. Conductivity and MINE.PC1 were strongly negatively related to occurrences of Fantail Darter (Etheostoma flabellare) and sculpin (Cottus) spp. Several taxonomic, trophic and reproductive metrics of assemblage composition responded strongly to mining intensity or its instream correlates. For example, coal mining favoured omnivore-herbivores, but inhibited invertivores, simple lithophils and nonsimple nonlithophils. We revealed distinct negative and positive responses to mining-related stressors, which suggest changes to macroinvertebrate prey availability and/or contaminant loads contribute to fish extirpations in coalfield streams. Future assessments of mining impacts on fish assemblages could be more instructive by including characterisations of physicochemical stressors and regionally calibrated biotic metrics with demonstrated sensitivity to mining.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12588","usgsCitation":"Martin, Z.P., Angermeier, P.L., Ciparis, S., and Orth, D., 2021, Coal-mining intensity influences species and trait distributions of stream fishes in two Central Appalachian watersheds: Ecology of Freshwater Fish, v. 30, no. 3, p. 347-365, https://doi.org/10.1111/eff.12588.","productDescription":"19 p.","startPage":"347","endPage":"365","ipdsId":"IP-113479","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454189,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eff.12588","text":"External Repository"},{"id":396022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Powell River, upper Clinch River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.71630859375,\n 37.153749608429415\n ],\n [\n -82.03765869140625,\n 37.470498470798724\n ],\n [\n -82.89459228515624,\n 36.96306042436515\n ],\n [\n -83.6444091796875,\n 36.61773216000592\n ],\n [\n -82.694091796875,\n 36.602299135790446\n ],\n [\n -81.71630859375,\n 37.153749608429415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Zachary P. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":279461,"corporation":false,"usgs":false,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"P.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciparis, Serena","contributorId":279464,"corporation":false,"usgs":false,"family":"Ciparis","given":"Serena","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orth, Donald J.","contributorId":279468,"corporation":false,"usgs":false,"family":"Orth","given":"Donald J.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834960,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}