Playa wetlands in the Great Plains, USA support a wide variety of plant species not found elsewhere in this agriculturally-dominated region due to the ephemeral presence of standing water and hydric soils within playas. If longer dry periods occur due to climate change or if changes in surrounding land use alter sediment accumulation rates and water storage capacity in playas, plant communities could experience decreased diversity, with lasting effects on ecosystem services provided by playas in the Great Plains and at a continental-level in North America. We quantified potential changes in playa wetland plant community composition associated with predicted changes in precipitation and land use in the Great Plains through the end of the 21st century. We conducted two six-month greenhouse experiments mimicking field conditions using intact mesocosms collected from playas in Nebraska and Texas. In the precipitation experiment, treatments derived from historical precipitation observations and three future moderate emissions (CMIP5 RCP4.5) downscaled climate projections were applied to mesocosms. For the land use experiment, treatments were simulated by nitrogen (N) applications to soil ranging from 0 to 100 mg-N L-1 with each precipitation event under historical rainfall patterns, representing increasing and decreasing area in agricultural use in playa watersheds. Plant communities tended to shift toward more native species under projected future climate conditions, but as N runoff increased, native species richness decreased. Agricultural land-use surrounding playas may have a greater effect on wetland plant communities than future alterations to hydrology based on climate change in the Great Plains; thus, efforts to reduce nutrient runoff into playas would likely mitigate loss in ecosystem function in the coming decades.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envexpbot.2020.104039","usgsCitation":"Owen, R.K., Webb, E.B., Haukos, D.A., and Goyne, K.W., 2020, Projected climate and land use changes drive plant community composition in agricultural wetlands: Environmental and Experimental Botany, v. 175, p. 1-12, https://doi.org/10.1016/j.envexpbot.2020.104039.","productDescription":"104039, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-111000","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":456171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envexpbot.2020.104039","text":"Publisher Index Page"},{"id":395691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska, Texas","otherGeospatial":"Rainwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.01953125,\n 40.01078714046552\n ],\n [\n -96.51489257812499,\n 40.01078714046552\n ],\n [\n -96.51489257812499,\n 41.77950486590359\n ],\n [\n -100.01953125,\n 41.77950486590359\n ],\n [\n -100.01953125,\n 40.01078714046552\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.07373046875,\n 32.02670629333614\n ],\n [\n -103.040771484375,\n 31.44741029142872\n ],\n [\n -98.668212890625,\n 31.475524020001806\n ],\n [\n -98.7451171875,\n 34.15272698011818\n ],\n [\n -98.85498046875,\n 34.19817309627726\n ],\n [\n -99.041748046875,\n 34.252676117101515\n ],\n [\n -99.151611328125,\n 34.20725938207231\n ],\n [\n -99.283447265625,\n 34.42503613021332\n ],\n [\n -99.42626953125,\n 34.46127728843705\n ],\n [\n -99.42626953125,\n 34.38877925439021\n ],\n [\n -99.60205078124999,\n 34.42503613021332\n ],\n [\n -99.66796875,\n 34.38877925439021\n ],\n [\n -99.986572265625,\n 34.58799745550482\n ],\n [\n -99.97558593749999,\n 36.518465989675875\n ],\n [\n -103.062744140625,\n 36.50963615733049\n ],\n [\n -103.07373046875,\n 32.02670629333614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"175","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Owen, Rachel K.","contributorId":273204,"corporation":false,"usgs":false,"family":"Owen","given":"Rachel","email":"","middleInitial":"K.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goyne, Keith W.","contributorId":204931,"corporation":false,"usgs":false,"family":"Goyne","given":"Keith","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228141,"text":"70228141 - 2020 - Defining the need for genetic stock assignment when describing stock demographics and dynamics: An example using Lake Whitefish in Lake Michigan","interactions":[],"lastModifiedDate":"2022-02-04T16:50:01.408572","indexId":"70228141","displayToPublicDate":"2020-07-01T10:39:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Defining the need for genetic stock assignment when describing stock demographics and dynamics: An example using Lake Whitefish in Lake Michigan","docAbstract":"Genetic stock assignment is not routinely used when describing the dynamics and demographics of individual stocks supporting mixed-stock fisheries, and capture location and timing are often used as alternative assignment methods. However, variation in stock demographics and dynamics may not be accounted for if stock assignments based on capture location or timing do not accurately reflect genetic assignments. We used Lake Whitefish Coregonus clupeaformis in Lake Michigan as a model fishery to determine whether stock mixing could undermine efforts to describe stock status when using October capture location as a proxy for genetic stock assignment. Accuracy of stock assignments based on October capture location ranged from 54% to 100% among management zones. Metrics describing length and age distributions, weight at length, fecundity, and growth varied among genetic stocks. Stock-specific metrics were typically similar between stock assignment methods (capture location versus genetics) because only one or two genetic stocks were collected in most locations and the majority of those fish were from spatially proximal stocks with similar metrics. However, more extensive mixing of Lake Whitefish stocks has been documented; thus, using capture location for stock assignment could result in incorrect conclusions regarding stock status and harvest management depending on stock composition. Ambiguity in genetic stock assignments was a problem in two management zones, where between 23% and 42% of Lake Whitefish did not assign to a specific stock with a probability of at least 0.70. In the future, using genomic techniques rather than microsatellites may provide different conclusions regarding genetic stock structure; these differences could affect the accuracy of using capture location for stock assignment. Use of capture location as a proxy for genetic stock assignment may not be warranted for all mixed-stock fisheries but may be appropriate when stock mixing is limited or is restricted to stocks with consistently similar characteristics.
","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10235","usgsCitation":"Isermann, D.A., Belnap, M.J., Turnquist, K.N., Sloss, B., VanDeHey, J.A., Hansen, S.P., and Caroffino, D.C., 2020, Defining the need for genetic stock assignment when describing stock demographics and dynamics: An example using Lake Whitefish in Lake Michigan: Transactions of the American Fisheries Society, v. 149, no. 4, p. 398-413, https://doi.org/10.1002/tafs.10235.","productDescription":"16 p.","startPage":"398","endPage":"413","ipdsId":"IP-105758","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": 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L.","affiliations":[],"preferred":false,"id":833204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"VanDeHey, Justin A.","contributorId":50800,"corporation":false,"usgs":true,"family":"VanDeHey","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":833205,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hansen, Scott P.","contributorId":79837,"corporation":false,"usgs":true,"family":"Hansen","given":"Scott","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":833206,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caroffino, David C.","contributorId":181527,"corporation":false,"usgs":false,"family":"Caroffino","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":833207,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70214490,"text":"70214490 - 2020 - A new data set of granitic rock strength values from Yosemite Valley, California: Applications to rock fall assessment","interactions":[],"lastModifiedDate":"2020-09-30T15:29:40.87055","indexId":"70214490","displayToPublicDate":"2020-07-01T10:26:05","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A new data set of granitic rock strength values from Yosemite Valley, California: Applications to rock fall assessment","docAbstract":"To explore connections between rock strength and rock falls, we undertook a comprehensive rock mechanics testing program for six granitic rock types in Yosemite Valley (California, USA) where rock falls are a common geomorphic and sometimes hazardous process. We collected samples from boulders located at the base of cliffs, with the inherent assumption that the intact boulders should provide reasonable estimates of full-strength values. Our testing program included unconfined compressive strength tests, triaxial compressive strength tests, Brazilian tensile strength tests, and Mode I fracture toughness strength testing using two different types of samples – chevron bend (CB) and cracked chevron notched Brazilian disk (CCNBD). Our results, consisting of 88 individual tests, provide the most detailed evaluation of rock strength in Yosemite Valley to date. These results provide the data needed to evaluate the various failure modes (e.g., shear failure of wedge instabilities, tensile failure of overhangs) that might be expected for rock falls from cliffs in Yosemite. We expect that these data will provide an important resource for the evaluation of rock falls and other geomorphological studies in Yosemite National Park.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"54th US Rock Mechanics/Geomechanics Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Rock Mechanics Association","collaboration":"National Park Service, University of Lausanne, École Polytechnique Fédérale de Lausanne – EPFL","usgsCitation":"Collins, B.D., Sandrone, F., Gastaldo, L., Stock, G.M., and Jaboyedoff, M., 2020, A new data set of granitic rock strength values from Yosemite Valley, California: Applications to rock fall assessment, in 54th US Rock Mechanics/Geomechanics Symposium, 7 p.","productDescription":"7 p.","ipdsId":"IP-116600","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":378919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378800,"type":{"id":15,"text":"Index Page"},"url":"https://www.onepetro.org/conference-paper/ARMA-2020-1412"}],"country":"United States","state":"California","otherGeospatial":"Yosemite Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.11627197265624,\n 37.60335225883687\n ],\n [\n -118.92974853515624,\n 37.60335225883687\n ],\n [\n -118.92974853515624,\n 38.151837403006766\n ],\n [\n -120.11627197265624,\n 38.151837403006766\n ],\n [\n -120.11627197265624,\n 37.60335225883687\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":799727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandrone, Federica","contributorId":225125,"corporation":false,"usgs":false,"family":"Sandrone","given":"Federica","email":"","affiliations":[{"id":27718,"text":"Ecole Polytechnique Federale de Lausanne","active":true,"usgs":false}],"preferred":true,"id":799728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gastaldo, Laurent","contributorId":225126,"corporation":false,"usgs":false,"family":"Gastaldo","given":"Laurent","email":"","affiliations":[{"id":27718,"text":"Ecole Polytechnique Federale de Lausanne","active":true,"usgs":false}],"preferred":true,"id":799729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stock, Greg M.","contributorId":202873,"corporation":false,"usgs":false,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":799730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaboyedoff, Michel","contributorId":205586,"corporation":false,"usgs":false,"family":"Jaboyedoff","given":"Michel","affiliations":[{"id":37117,"text":"University of Lausanne (Switzerland)","active":true,"usgs":false}],"preferred":false,"id":799731,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217905,"text":"70217905 - 2020 - The Cenozoic evolution of crustal shortening and left‐lateral shear in the central East Kunlun Shan: Implications for the uplift history of the Tibetan Plateau","interactions":[],"lastModifiedDate":"2021-02-10T14:05:13.86214","indexId":"70217905","displayToPublicDate":"2020-07-01T08:02:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"The Cenozoic evolution of crustal shortening and left‐lateral shear in the central East Kunlun Shan: Implications for the uplift history of the Tibetan Plateau","docAbstract":"The timing of crustal shortening and strike‐slip faulting along the East Kunlun Shan provides insight into the history of surface uplift and may constrain the time at which the Tibetan Plateau reached high elevations. We investigate a series of extensional basins and restraining bends along the Xidatan strand of the Kunlun strike‐slip fault, which provide an ideal setting to unravel the tectonic history of the northern plateau margin. We present new apatite (U‐Th)/He, apatite fission track, and zircon (U‐Th)/He ages and QTQt thermal modeling, 40Ar/39Ar fault gouge dating, and structural mapping from the central East Kunlun Shan. Our data suggest that the East Kunlun Shan experienced slow to negligible exhumation until late Cretaceous time, followed by an increase in rate by 65–50 Ma. Along with a ~47 Ma fault gouge age, we posit that the Paleocene–early Eocene was a time of crustal shortening along the northern plateau. Rapid exhumation along transpressional portions of the Xidatan fault initiated by 23–20 Ma, which we interpret as the local onset of strike‐slip faulting. An early Miocene transition from north‐south crustal shortening to left‐lateral shear along the East Kunlun Shan, the onset of normal and strike‐slip faulting in central and southern Tibet by 18 Ma, and lower crustal flow in eastern Tibet by 13 Ma suggest the establishment of orogen‐wide east‐west oriented extension and extrusion by the middle Miocene. The plateau‐wide shift in stress accommodation implies that high gravitational potential energy, and likely high elevation, was attained by the middle Miocene.
Careful design of a wildlife population monitoring strategy is necessary to obtain accurate and precise results whether the purpose of the survey is development of habitat suitability models, to estimate abundance, or assess site occupancy. Important characteristics to consider in survey design are sources of elevated variability, particularly within‐subject variability, which increases the amount of data needed to achieve statistical certainty either in terms of population trend analysis, hypothesis testing, or statistical power. However, alternative objectives, such as associating counts with habitat characteristics, may benefit from increased variation among counts when differences covary with habitat measures. This difference can result in competing needs when developing survey protocols. We investigated the relative precision of differing gamebird monitoring protocols to identify methods with the greatest statistical efficiency. We assessed call‐count transects using standard Breeding Bird Survey protocols (Passive call‐counts) and modified by including longer survey periods and call playback (Active call‐counts), autonomous recording units with supervised call detection (ARU‐recorded calls), camera traps, and roadside covey‐counts for Gambel's quail (Callipepla gambelii) in the Mojave Desert (CA, USA) during the spring of 2016. Active call‐counts had the lowest within‐site variation relative to estimated population index values, but Passive call‐count transects may be more efficient for some purposes because more survey stations can be completed within a single survey timeframe. The ARU‐recorded calls may provide a suitable alternative despite larger sample size needs, especially for occupancy surveys because multiple units can be deployed concurrently. The ultimate sample size required will depend on specific study objectives and scope of interest, but camera traps and breeding‐season covey counts are not likely to meet objectives in desert environments.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1105","usgsCitation":"Overton, C.T., Casazza, M.L., Connelley, D., and Gardner, S.C., 2020, Gambel’s quail survey variability and implications for survey design in the Mohave Desert: Wildlife Society Bulletin, v. 44, no. 3, p. 493-501, https://doi.org/10.1002/wsb.1105.","productDescription":"9 p.","startPage":"493","endPage":"501","ipdsId":"IP-104330","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436903,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SVPK0N","text":"USGS data release","linkHelpText":"Comparisons of Gambel's quail survey methods conducted in 2016 within the Mohave Desert of California with results and summaries"},{"id":380834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.597900390625,\n 33.8247936182649\n ],\n [\n -114.378662109375,\n 33.8247936182649\n ],\n [\n -114.378662109375,\n 35.576916524038616\n ],\n [\n -116.597900390625,\n 35.576916524038616\n ],\n [\n -116.597900390625,\n 33.8247936182649\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connelley, Daniel","contributorId":245293,"corporation":false,"usgs":false,"family":"Connelley","given":"Daniel","email":"","affiliations":[{"id":49140,"text":"Pheasants Forever, California","active":true,"usgs":false}],"preferred":false,"id":805781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":805782,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263639,"text":"70263639 - 2020 - California Historical Intensity Mapping Project (CHIMP): A consistently reinterpreted dataset of seismic intensities for the past 162 years and implications for seismic hazard maps","interactions":[],"lastModifiedDate":"2025-02-19T16:21:00.999385","indexId":"70263639","displayToPublicDate":"2020-07-01T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"California Historical Intensity Mapping Project (CHIMP): A consistently reinterpreted dataset of seismic intensities for the past 162 years and implications for seismic hazard maps","docAbstract":"Historical seismic intensity data are useful for myriad reasons, including assessment of the performance of Probabilistic Seismic Hazard Assessment (PSHA) models and corresponding hazard maps by comparing their predictions to a dataset of historically observed intensities in the region. To assess PSHA models for California, a long and consistently interpreted intensity record is necessary. For this purpose, the California Historical Intensity Mapping Project (CHIMP) has compiled a dataset that combines and reinterprets intensity information that has been stored in disparate and sometimes hard-to-access locations. The CHIMP dataset also includes new observations of intensity from archival research and oral history collection. Version 1 of the dataset includes 46,502 intensity observations for 62 earthquakes with estimated magnitudes ranging from 4.7 to 7.9. The 162 years of shaking data show observed shaking lower than expected from seismic hazard models. This discrepancy is reduced, but persists, if historical intensity data for the largest earthquakes are smoothed to reduce the effects of spatial under-sampling. Possible reasons for this discrepancy include other limitations of the CHIMP dataset, the hazard models, and the possibility that California seismicity throughout the historical period has been lower than the long-term average. Some of these issues may also explain similar discrepancies observed for Italy and Japan.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200065","usgsCitation":"Salditch, L., Gallahue, M.M., Lucas, M.C., Neely, J.S., Hough, S.E., and Stein, S., 2020, California Historical Intensity Mapping Project (CHIMP): A consistently reinterpreted dataset of seismic intensities for the past 162 years and implications for seismic hazard maps: Seismological Research Letters, v. 91, no. 5, p. 2631-2650, https://doi.org/10.1785/0220200065.","productDescription":"20 p.","startPage":"2631","endPage":"2650","ipdsId":"IP-119084","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"91","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Salditch, Leah","contributorId":263445,"corporation":false,"usgs":false,"family":"Salditch","given":"Leah","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927642,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927643,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212898,"text":"70212898 - 2020 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River Fall Chinook Salmon ESU: January 2019 - December 2019","interactions":[],"lastModifiedDate":"2020-09-01T23:43:54.567337","indexId":"70212898","displayToPublicDate":"2020-06-30T18:43:28","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River Fall Chinook Salmon ESU: January 2019 - December 2019","docAbstract":"The portion of the Snake River fall Chinook salmon Oncorhynchus tshawytscha evolutionary significant unit (ESU) that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 19922019 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, and (3) use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence have been relatively stable, but effects of density dependence are evident in juvenile life stages. Apparent abundance of juvenile fall Chinook salmon has increased and we noted the following responses: parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier; growth rate (g/d) and dispersal size of parr declined; and passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use this information in a comprehensive modeling effort to conduct action-effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management Research, Monitoring, and Evaluation (RM&E) progams.
In 2019, the U.S. Geological Survey (USGS) shifted survey efforts in the Snake River toward deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses because all unmanned aerial system (UAS) activities were suspended by the Department of the Interior two weeks into the spawning season. We counted 81 deepwater redds at 17 of the 29 sites surveyed. Redd depths averaged 3.6 m. We collected a total of 123 live fall Chinook salmon from 16 unique geographic locations that spanned 55 river kilometers. Forty-six fish were recovered at Eureka Bar (rkm 307.1) and Kirby Creek (rkm 352.0), which accounted for 37% of all collected fish in 2019. Most (73 fish) post-spawned salmon were collected from early to mid-November just after peak spawning. A summary of 2019 PBT results can be found in Appendix A.1.
In 2019, we PIT tagged subyearling fall Chinook salmon in both the Snake and Clearwater rivers. In the Snake River, we tagged 410 fish with 8-mm tags, 666 fish with 9-mm tags, and 1,082 fish 12-mm tags. During seining, our recapture rate of previously tagged fish was slightly higher in the lower reach at 11.4% than in the upper reach at 10.6%. In an effort to represent more of the population through tagging, we tagged fish as small as 45 mm with 8-mm tags at one site in the upper reach. This allowed us to increase the number of fish tagged in that reach by 17.7%. An additional 10.6% of collected fish could have been tagged in the lower reach had we used 8-mm tags in that reach. In the Clearwater River, we tagged 2,451 subyearlings and recaptured 260 (10.6%) fish in the river and 66 fish (48 tagged by USGS, 18 tagged by the Nez Perce Tribe) at Lower Granite Dam during October to provide information for growth estimation. Within riverine habitats, growth in both length and mass were higher for fish tagged with 8-mm tags than with 9- and 12-mm tags. Estimated growth in length and mass of subyearlings was higher in Lower Granite Reservoir than in riverine habitats.
We adapted existing statistical models used to estimate abundance of steelhead and spring/summer Chinook salmon for fall Chinook salmon passing Lower Granite Dam. Run reconstruction efforts to date at Lower Granite Dam for Snake River fall Chinook salmon have provided estimates of the number of returning adults but with no measure of uncertainty about the estimates. The objective of this study was to estimate the abundance, with uncertainty, of marked (coded-wire tagged CWT or adipose clipped) and unmarked fall Chinook salmon past Lower Granite Dam for return years 20032018. Estimating uncertainty is important for informing the state-space life cycle model (Chapter 5), which incorporates both observation and process uncertainty into parameter estimates. The coefficient of variation (CV) for log- abundance was 1.0% or less in all years, whereas the CV for abundance averaged 4.2% and ranged from 1.4% to 10.4% among years.
Over the past five years, we have been developing a two-stage state-space life-cycle model for naturally produced fall Chinook salmon in the Snake River basin. Initial efforts focused on generating juvenile and adult abundance estimates, with estimates of uncertainty, for informing the life-cycle model. In this report we 1) describe the statistical life-cycle model and improvements made since our last report to the Independent Scientific Advisory Board (ISAB), 2) estimate the effects of covariates on key demographic parameters, and 3) use the fitted life- cycle model to simulate population trajectories under hydrosystem actions proposed for the NOAA 2020 Biological Opinion (hereafter, the Proposed Action). Major recent advancements to the model include revised juvenile abundance estimates, the ability to estimate smolt-to-adult return rates (SAR) separately for subyearling and yearling juvenile fall Chinook salmon, and improvements in the observation model for estimating age, sex, and outmigration structure in adult returns. We examined the effect of numerous environmental, hydrosystem, and ocean covariates on key demographic parameters but only a few covariates were significant. For the adult-to-juvenile transition, we found the maximum weekly river flows during the winter egg- incubation period had a significant negative effect on the juvenile outmigrant abundance from that brood year. For subyearling outmigrants, percent spill during the summer had a significant positive effect on SAR and the mean winter PDO (Pacific Decadal Oscillation) had a significant negative effect on SAR. For yearling outmigrants, NPGO (North Pacific Gyre Oscillation) had a significant positive effect on SAR. We used the fitted model to simulate population trajectories under the Proposed Action, and the median 10-year geometric mean abundance was 8,222 female spawners (interquartile range: 2,592 26,714). Overall, the probability of quasi- extinction (probability of falling below 50 female spawners for 4 consecutive years) was low, with only 1.6% of all simulations having a quasi-extinction probability >0.95. Although quasi-extinction probability was low, we did not assess the additional effect of climate change, which would be expected to increase quasi-extinction probability.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"2020, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River Fall Chinook Salmon ESU: January 2019 - December 2019, v, 126 p.","productDescription":"v, 126 p.","ipdsId":"IP-119421","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":378076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378055,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P176701/84776-1.pdf"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.9375,\n 41.983994270935625\n ],\n [\n -113.31298828125,\n 41.983994270935625\n ],\n [\n -113.31298828125,\n 48.004625021133904\n ],\n [\n -120.9375,\n 48.004625021133904\n ],\n [\n -120.9375,\n 41.983994270935625\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":220176,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":797793,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":797794,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":70213311,"text":"70213311 - 2020 - A science business model for answering important questions","interactions":[],"lastModifiedDate":"2020-09-17T17:55:22.37147","indexId":"70213311","displayToPublicDate":"2020-06-30T12:48:18","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A science business model for answering important questions","docAbstract":"Perhaps the biggest question in science is how to do better science. Many ecologists, including this book’s editors and authors, have succeeded under the current science “business model” and, from our perspective, the status quo works well enough. But science business models are under increased scrutiny. For instance, since 2012, at least nine papers have critiqued government-sponsored biomedical research, with the most-suggested (self-serving) solution being to spend more government funds on science (Pickett et al. 2015). To get more funding, scientists might consider first improving their return on investment. To increase return on investment, ecologists (and scientists in general) could rethink training programs, reproducibility, funding distribution, synthesis, publication models, and evaluation metrics.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Unsolved Problems in Ecology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Princeton University Press","usgsCitation":"Lafferty, K.D., 2020, A science business model for answering important questions, chap. of Unsolved Problems in Ecology, p. 357-373.","productDescription":"17 p.","startPage":"357","endPage":"373","ipdsId":"IP-077013","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":378527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":799010,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70222472,"text":"70222472 - 2020 - 2023 Coastal master plan: Model improvement plan, ICM-wetlands, vegetation, and soil","interactions":[],"lastModifiedDate":"2021-09-08T15:43:58.264089","indexId":"70222472","displayToPublicDate":"2020-06-30T10:39:28","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":9334,"text":"Coastal Master Plan","active":true,"publicationSubtype":{"id":4}},"title":"2023 Coastal master plan: Model improvement plan, ICM-wetlands, vegetation, and soil","docAbstract":"As part of the model improvement effort for the 2023 Coastal Master Plan, the wetland processes captured by the morphology and vegetation models used during previous master plans were reevaluated to assess how Integrated Compartment Model (ICM) subroutines could be improved. This process considered technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plan cycles. The availability of new data and information that could be used to make model improvements was also considered. In many cases, the team considered and tested multiple options or approaches. As a result of this effort, recommended improvements are provided here.
The improvements recommended to be included in the 2023 Coastal Master Plan include: adjusting marsh collapse thresholds, refining organic matter accretion calculations, developing an unstructured grid for modeling vegetation, improving flotant marsh and forested wetlands algorithms, creating and applying an updated map of existing vegetation, adjusting model code, and updating the submerged aquatic vegetation (SAV) module.
This report describes the team’s work through a series of 7 distinct activities to identify and test options for model improvements to ensure the updated ICM used for the 2023 Coastal Master Plan appropriately captures ecological and morphological processes observed in Coastal Louisiana. As appropriate, relevant literature and data are discussed. Test runs to evaluate how changes influence model outputs are also documented. A final list of recommended updates, taking into account consideration of all options and results from test runs, is summarized at the end of the report. A later report will describe the final ICM-LAVegMod and ICM-Morph subroutines for the 2023 Coastal Master Plan, detailing the updates that have been incorporated.
","language":"English","publisher":"Coastal Protection and Restoration Authority","usgsCitation":"Baustian, M., Reed, D., Visser, J., Duke-Sylvester, S.M., Snedden, G., Wang, H., DeMarco, K., Foster-Martinez, M.R., Sharp, L.A., McGinnis, T., and Jarrell, E., 2020, 2023 Coastal master plan: Model improvement plan, ICM-wetlands, vegetation, and soil: Coastal Master Plan, 155 p.","productDescription":"155 p.","ipdsId":"IP-117713","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":388949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":388947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://coastal.la.gov/wp-content/uploads/2021/04/ICM-Wetlands-Veg-Soils-Model-Improvement-Report_June2020.pdf"},{"id":387563,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/technical-resources/"}],"country":"United 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M.","contributorId":175470,"corporation":false,"usgs":false,"family":"Duke-Sylvester","given":"Scott","email":"","middleInitial":"M.","affiliations":[{"id":12987,"text":"Department of Biology, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":820161,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":222172,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":820162,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":222383,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":820163,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":820164,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":820165,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sharp, Leigh Anne","contributorId":178418,"corporation":false,"usgs":false,"family":"Sharp","given":"Leigh","email":"","middleInitial":"Anne","affiliations":[],"preferred":false,"id":820166,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McGinnis, Tommy E.","contributorId":149677,"corporation":false,"usgs":false,"family":"McGinnis","given":"Tommy E.","affiliations":[{"id":17778,"text":"Coastal Protection and Restoration Authority of Louisiana","active":true,"usgs":false}],"preferred":false,"id":820167,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jarrell, Elizabeth","contributorId":261556,"corporation":false,"usgs":false,"family":"Jarrell","given":"Elizabeth","email":"","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":820168,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70236801,"text":"70236801 - 2020 - Automated extraction of areal extents for GNIS Summit features using the eminence core method","interactions":[],"lastModifiedDate":"2022-09-19T14:49:55.9415","indexId":"70236801","displayToPublicDate":"2020-06-30T09:47:34","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Automated extraction of areal extents for GNIS Summit features using the eminence core method","docAbstract":"An important objective of the U.S. Geological Survey (USGS) is to enhance the Geographic Names Information System (GNIS) by automatically associating boundaries with terrain features that are currently spatially represented as two-dimensional points. In this paper, the discussion focuses on experiments for mapping GNIS Summit features using the eminence core region-growing method, which maps the area between a peak and its key col (saddle). A secondary goal of this project is to improve the positional accuracy of GNIS Summit features, since those locations were derived long ago and need to be snapped to local morphometric peaks detected from analysis of the highest-resolution digital elevation models (DEMs). The eminence cores delineated for a subset of GNIS Summit features were compared visually against basemaps and manually digitized polygons created by USGS staff. The comparisons revealed substantial differences between the computationally derived eminence cores and the manually generated polygons. Results clearly suggest that the default core delineation method tested must be modified to “roll back” or truncate growth of unreasonably large cores to smaller extents that would match people’s intuitive expectations. However, these results are far more encouraging than any method tested previously, since this method guarantees a 1-1 correspondence between polygons and GNIS Summit features.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of geomorphometry 2020","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Geomorphetry 2020","conferenceDate":"June 22-26, 2020","conferenceLocation":"Perugia, Italy","language":"English","doi":"10.30437/GEOMORPHOMETRY2020_10","usgsCitation":"Sinha, G., and Arundel, S., 2020, Automated extraction of areal extents for GNIS Summit features using the eminence core method, in Proceedings of geomorphometry 2020, Perugia, Italy, June 22-26, 2020, p. 38-41, https://doi.org/10.30437/GEOMORPHOMETRY2020_10.","productDescription":"4 p.","startPage":"38","endPage":"41","ipdsId":"IP-116570","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":406960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sinha, Gaurav","contributorId":220051,"corporation":false,"usgs":false,"family":"Sinha","given":"Gaurav","email":"","affiliations":[{"id":12807,"text":"Ohio University","active":true,"usgs":false}],"preferred":false,"id":852202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":852203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210993,"text":"70210993 - 2020 - Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","interactions":[],"lastModifiedDate":"2020-08-04T14:24:42.736989","indexId":"70210993","displayToPublicDate":"2020-06-30T08:41:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","docAbstract":"In the arid landscape south of the Grand Canyon, natural springs and seeps are a critical resource for endemic species and Native American tribes. Groundwater is potentially threatened by expanding populations, visitations, and mineral extraction activities. Environmental tracers including noble gases, stable isotopes of hydrogen and oxygen in water, tritium, and carbon-14 were used to characterize recharge sources and flow paths in South Rim aquifers. Results confirm the regional Redwall-Muav Aquifer as the primary groundwater source to springs. However, a second local recharge source is required to explain the detection of tritium. Two probable sources are identified as: low-elevation infiltration of surface run-off with warm noble gas recharge temperatures, high excess air, and relatively low fractions of winter recharge, and high-elevation plateau recharge with cool recharge temperatures, low excess air, and fraction of winter recharge of ~ 1. Previous investigators have linked spring occurrence with regional faults and fractures. We show such features are also the likely control chemical mixing between the regional and local groundwater sources, the transport of deeply sourced and local recharge fluids, groundwater age, and thus the relative vulnerability of groundwater to depletion and contamination. The new conceptual model of groundwater sources and flow paths suggest many South Rim springs may respond on the order of 10s to 100s of years to groundwater depletion and contamination, even though the majority of groundwater flow is along longer flow paths with longer lag times. The magnitude of response to short term changes in the flow system remains unclear.","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02193-z","usgsCitation":"Solder, J.E., Beisner, K.R., Anderson, J.R., and Bills, D.J., 2020, Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers: Hydrogeology Journal, v. 28, p. 1593-1613, https://doi.org/10.1007/s10040-020-02193-z.","productDescription":"21 p.","startPage":"1593","endPage":"1613","ipdsId":"IP-110439","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":456198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-020-02193-z","text":"Publisher Index Page"},{"id":436904,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WX8N0L","text":"USGS data release","linkHelpText":"Noble gas isotopes and lumped parameter model results for environmental tracer based groundwater ages, South Rim Grand Canyon, Arizona, USA"},{"id":376255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"South Rim of the Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4835205078125,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 35.7019167328534\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":201953,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Jessica R. 0000-0002-3286-7552 jranderson@usgs.gov","orcid":"https://orcid.org/0000-0002-3286-7552","contributorId":193158,"corporation":false,"usgs":true,"family":"Anderson","given":"Jessica","email":"jranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bills, Donald J. 0000-0001-8955-3370 djbills@usgs.gov","orcid":"https://orcid.org/0000-0001-8955-3370","contributorId":177439,"corporation":false,"usgs":true,"family":"Bills","given":"Donald","email":"djbills@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216279,"text":"70216279 - 2020 - Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico","interactions":[],"lastModifiedDate":"2020-11-11T13:41:55.681915","indexId":"70216279","displayToPublicDate":"2020-06-30T07:37:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico","docAbstract":"Mobility is an important element of landslide hazard and risk assessments yet has been seldom studied for shallow landslides and debris flows in tropical environments. In September 2017, Hurricane Maria triggered > 70,000 landslides across Puerto Rico. Using aerial imagery and a lidar digital elevation model (DEM), we mapped and characterized the mobility of debris slides and flows in four different geologic materials: (1) mudstone, siltstone, and sandstone; (2) submarine basalt and chert; (3) marine volcaniclastics; and (4) granodiorite. We used the ratio of landslide-fall height (H) to travel length (L), H/L, to assess the mobility of landslides in each material. Additionally, we differentiated between landslides with single and multiple source areas and landslides that either did or did not enter drainages. Overall, extreme rainfall contributed to the mobility of landslides during Hurricane Maria, and our results showed that the mobility of debris slides and flows in Puerto Rico increased linearly as a function of the number of source areas that coalesced. Additionally, landslides that entered drainages were more mobile than those that did not. We found that landslides in soils developed on marine volcaniclastics were the most mobile and landslides in soils on submarine basalt and chert were the least mobile. While landslides were generally small (< 100 m2) and displayed a wide range of H/L values (0.1–2), coalescence increased the mobility of landslides that transitioned to debris flows. The high but variable mobility of landslides that occurred during Hurricane Maria and the associated hazards highlight the importance of characterizing and understanding the factors influencing landslide mobility in Puerto Rico and other tropical environments.
The study was conducted in the Northern Atlantic Coastal Plain aquifer system, in the eastern USA.
Groundwater pH and redox conditions are fundamental chemical characteristics controlling the distribution of many contaminants of concern for drinking water or the ecological health of receiving waters. In this study, pH and redox conditions were modeled and mapped in a complex, layered aquifer system. Machine-learning methods (boosted regression trees) were applied to data from 3000 to 5000 wells. Predicted pH and the probability of anoxic conditions, defined by three thresholds of dissolved oxygen (0.5, 1, and 2 mg/L), were mapped at the 1-km2 scale for each of 10 regional aquifer layers.
Maps depict the extent of acidic groundwater and oxic conditions in the shallow, unconfined surficial aquifer and in unconfined, recharge-proximal areas of underlying aquifers, in contrast to alkaline and anoxic groundwater elsewhere. Geographic patterns and influential predictors–including elevation, overlying confining-units thickness, and simulated groundwater age and flux–are consistent with prior understanding of the processes controlling pH and redox in the aquifer system. The model-based maps support robust estimates of aquifer proportions, either areal or volumetric, likely to contain groundwater of a specified quality or be vulnerable to specific pH- or redox-sensitive contaminants. The machine-learning methods were an effective tool to map groundwater quality at the regional scale.
Mars has several different types of slope feature that resemble aqueous flows. However, the current cold, dry conditions are inimical to liquid water, resulting in uncertainty about its role in modern surface processes. Dark slope streaks were among the first distinctive young slope features to be identified on Mars and the first with activity seen in orbital images. They form markings on steep slopes that can persist for decades, and the role of water in their formation remains a matter of debate. Here I analyse the geomorphic features of new slope streaks using high-resolution orbital images. Comparison of images before and after streak formation reveal how this process affects the surface and provides information about the cause. These observations demonstrate that slope streaks erode and deposit material in some instances. They also reveal that streaks can jump slopes and may be erosive very near their termini. These observations support a formation model where dark slope streaks form as ground-hugging, low-density avalanches of dry surface dust. Such streaks need not be treated as Special Regions for planetary protection.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41561-020-0598-x","usgsCitation":"Dundas, C.M., 2020, Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars: Nature Geoscience, v. 13, p. 473-476, https://doi.org/10.1038/s41561-020-0598-x.","productDescription":"4 p.","startPage":"473","endPage":"476","ipdsId":"IP-110925","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":456222,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8243413","text":"External Repository"},{"id":385891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":816346,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70210866,"text":"70210866 - 2020 - Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA","interactions":[],"lastModifiedDate":"2020-06-30T12:38:45.776529","indexId":"70210866","displayToPublicDate":"2020-06-28T07:32:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA","docAbstract":"Tools to evaluate reservoir thermal energy storage (RTES; heat storage in slow-moving or stagnant geochemically evolved permeable zones in strata that underlie well-connected regional aquifers) are developed and applied to the Columbia River Basalt Group (CRBG) beneath the Portland Basin, Oregon, USA. The performance of RTES for heat storage and recovery in the Portland Basin is strongly dependent on the operational schedule of heat injection and extraction. We examined the effects of the operational schedule, based on an annual solar hot water supply pattern and a building heating demand model, using heat and fluid flow simulations with SUTRA. We show RTES to be feasible for supply of heating energy for a large combined research/teaching building on the Oregon Health and Science University South Waterfront expansion, an area of planned future development. Initially, heat is consumed to increase the reservoir temperature, and conductive heat loss is high due to high temperature gradients between the reservoir and surrounding rock. Conductive heat loss continues into the future, but the rate of heat loss decreases, and heat recovery efficiency of the RTES system increases over time. Simulations demonstrate the effects of varying heat-delivery rate and temperature on the heat production history of the reservoir. If 100% of building heating needs are to be supplied by combined solar/RTES, then the solar system must be sized to meet building needs plus long-term thermal losses (i.e., conductive losses once the system is heated to pseudo-steady state) from the RTES system. If the solar heating system barely meets these criteria, then during early years, less than 100% of the building demand will be supplied until the reservoir is fully-heated. The duration of supplying less than 100% of building demand can be greatly shortened by pre-heating the reservoir before building heating operations or by adding extra heat from external sources during early years. Analytic solutions are developed to evaluate efficacy and to help design RTES systems (e.g., well-spacing, thermal source sizing, etc.). A map of thermal energy storage capacity is produced for the CRBG beneath the Portland Basin. The simulated building has an annual heat load of ∼1.9 GWh, and the total annual storage capacity of the Portland Basin is estimated to be 43,400 GWh assuming seasonal storage of heat yields water from which 10 °C can be extracted via heat exchange, indicating a tremendous heating capacity of the CRBG.
In recent decades, many bumble bee species have declined due to changes in habitat, climate, and pressures from pathogens, pesticides, and introduced species. The western bumble bee (Bombus occidentalis ), once common throughout western North America, is a species of concern and will be considered for listing by the U.S. Fish and Wildlife Service (USFWS) under the Endangered Species Act (ESA). We attempt to improve alignment of data collection and research with USFWS needs to consider redundancy, resiliency, and representation in the upcoming species status assessment. We reviewed existing data and literature on B. occidentalis , highlighting information gaps and priority topics for research. Priorities include increased knowledge of trends, basic information on several life‐history stages, and improved understanding of the relative and interacting effects of stressors on population trends, especially the effects of pathogens, pesticides, climate change, and habitat loss. An understanding of how and where geographic range extent has changed for the two subspecies of B. occidentalis is also needed. We outline data that could be easily collected in other research projects that would increase their utility for understanding range‐wide trends of bumble bees. We modeled the overall trend in occupancy from 1998 to 2018 of Bombus occidentalis within the continental United States using existing data. The probability of local occupancy declined by 93% over 21 yr from 0.81 (95% CRI = 0.43, 0.98) in 1998 to 0.06 (95% CRI = 0.02, 0.16) in 2018. The decline in occupancy varied spatially by landcover and other environmental factors. Detection rates vary in both space and time, but peak detection across the continental United States occurs in mid‐July. We found considerable spatial gaps in recent sampling, with limited sampling in many regions, including most of Alaska, northwestern Canada, and the southwestern United States. We therefore propose a sampling design to address these gaps to best inform the ESA species status assessment through improved assessment of how the spatial distribution of stressors influences occupancy changes. Finally, we request involvement via data sharing, participation in occupancy sampling with repeated visits to distributed survey sites, and complementary research to address priorities outlined in this paper.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3141","usgsCitation":"Graves, T., Janousek, W.M., Gaulke, S., Nicholas, A., Keinath, D., Bell, C.M., Cannings, S., Hatfield, R.G., Heron, J.M., Koch, J.B., Loffland, H.L., Richardson, L., Rohde, A., Rykken, J., Strange, J.P., Tronstead, L., and Sheffield, C., 2020, Western bumble bee: Declines in United States and range-wide information gaps: Ecosphere, v. 11, no. 6, e03141, 13 p., https://doi.org/10.1002/ecs2.3141.","productDescription":"e03141, 13 p.","ipdsId":"IP-113225","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":456241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3141","text":"Publisher Index Page"},{"id":436910,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QY8ZA0","text":"USGS data release","linkHelpText":"Western bumble bee 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0000-0003-4939-3047","orcid":"https://orcid.org/0000-0003-4939-3047","contributorId":204143,"corporation":false,"usgs":false,"family":"Rohde","given":"Ashley T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":795750,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Rykken, Jessica","contributorId":150931,"corporation":false,"usgs":false,"family":"Rykken","given":"Jessica","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":795751,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Strange, James P.","contributorId":224183,"corporation":false,"usgs":false,"family":"Strange","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":795752,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tronstead, Lusha","contributorId":237991,"corporation":false,"usgs":false,"family":"Tronstead","given":"Lusha","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":795753,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sheffield, Cory","contributorId":237992,"corporation":false,"usgs":false,"family":"Sheffield","given":"Cory","email":"","affiliations":[{"id":47672,"text":"Royal Saskatchewan Museum","active":true,"usgs":false}],"preferred":false,"id":795754,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70210574,"text":"ofr20201044 - 2020 - Supporting natural resource-management decisions — The role of economics at the U.S. Department of the Interior (DOI) — 2018 DOI Economics Training Workshop","interactions":[],"lastModifiedDate":"2022-01-19T14:34:44.24721","indexId":"ofr20201044","displayToPublicDate":"2020-06-26T10:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1044","displayTitle":"Supporting Natural Resource-Management Decisions—The Role of Economics at the U.S. Department of the Interior (DOI)—2018 DOI Economics Training Workshop","title":"Supporting natural resource-management decisions — The role of economics at the U.S. Department of the Interior (DOI) — 2018 DOI Economics Training Workshop","docAbstract":"The second U.S. Department of the Interior (DOI) Economics Training Workshop (hereafter “Workshop”) was held during September 25–27, 2018, in Washington, D.C., to identify, highlight, and better understand needs and opportunities for economic analysis to support DOI’s mission. Building on the first workshop in 2017, the second Workshop, jointly convened by the DOI Office of Policy Analysis and the U.S. Geological Survey (USGS) Science and Decisions Center, provided an opportunity for DOI economists to share expertise and experiences and to build collaboration and communication channels across DOI. In addition, the second Workshop provided training sessions on a variety of relevant economic and modeling topics. More than 40 DOI economists gathered at the Workshop to share their work, discuss shared challenges, and identify approaches to advance the use and contribution of economics at the DOI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201044","collaboration":"Prepared in cooperation with the U.S. Department of the Interior Office of Policy Analysis","usgsCitation":"Alhassan, M., Pindilli, E.J., Crowley, C.S.L., Shapiro, C.D., and Simon, B.M., 2020, Supporting natural resource-management decisions—The role of economics at the U.S. Department of the Interior (DOI)—2018 DOI Economics Training Workshop: U.S. Geological Survey Open-File Report 2020–1044, 26 p., https://doi.org/10.3133/ofr20201044.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112653","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":375485,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181054","text":"Open-File Report 2018-1054","linkHelpText":"- Supporting natural resource management—The role of economics at the Department of the Interior—A workshop report"},{"id":375947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1044/ofr20201044.pdf","text":"Report","size":"6.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":375483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1044/coverthb.jpg"}],"contact":"Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Fisheries managers have a growing interest in the use of carbon dioxide (CO2) as a tool for controlling invasive fishes. However, limited published data exist on susceptibility of many commonly encountered species to elevated CO2 concentrations. Our objective was to estimate the 24-h 50% lethal concentration (LC50) and 95% lethal concentration (LC95) of CO2 for four fishes (Rainbow Trout Oncorhynchus mykiss, Common Carp Cyprinus carpio, Channel Catfish Ictalurus punctatus, and Westslope Cutthroat Trout Oncorhynchus clarkii lewisi). In the laboratory, we exposed juvenile fish to a range of CO2 concentrations for 24 h in unpressurized, flow-through tanks. We developed a Bayesian hierarchical model to estimate the dose-response relationship for each fish species with associated uncertainty, and estimated 24-h LC50 and LC95 values based on laboratory trials for each species. The minimum concentration inducing mortality differed among cold water–adapted species and warm water–adapted species groups: 150 mg CO2/L for Westslope Cutthroat Trout and Rainbow Trout and 225 mg CO2/L for Common Carp and Channel Catfish. We observed complete mortality at 275 mg CO2/L (38,672 microatmospheres [μatm]), 225 mg CO2/L (30,711 μatm), and 495 mg CO2/L (65,708 μatm [Common Carp]; 77,213 μatm [Channel Catfish]) for Westslope Cutthroat Trout, Rainbow Trout, and both Common Carp and Channel Catfish, respectively. There was evidence of a statistical difference between the 24-h LC95 values of Westslope Cutthroat Trout and Rainbow Trout (245.0 [222.2–272.2] and 190.6 [177.2–207.8] mg CO2/L, respectively). Additionally, these values were almost half the estimated 24-h LC95 values for Common Carp and Channel Catfish (422.5 [374.7–474.5] and 434.2 [377.2–492.2] mg CO2/L, respectively). Although the experimental findings show strong relationships between increased CO2 concentration and higher mortality, additional work is required to assess the efficacy and feasibility of a CO2 application in a field setting.
Polycyclic aromatic hydrocarbons (PAHs) are among the most widespread and potentially toxic contaminants in Great Lakes (USA/Canada) tributaries. The sources of PAHs are numerous and diverse, and identifying the primary source(s) can be difficult. The present study used multiple lines of evidence to determine the likely sources of PAHs to surficial streambed sediments at 71 locations across 26 Great Lakes Basin watersheds. Profile correlations, principal component analysis, positive matrix factorization source‐receptor modeling, and mass fractions analysis were used to identify potential PAH sources, and land‐use analysis was used to relate streambed sediment PAH concentrations to different land uses. Based on the common conclusion of these analyses, coal‐tar–sealed pavement was the most likely source of PAHs to the majority of the locations sampled. The potential PAH‐related toxicity of streambed sediments to aquatic organisms was assessed by comparison of concentrations with sediment quality guidelines. The sum concentration of 16 US Environmental Protection Agency priority pollutant PAHs was 7.4–196 000 µg/kg, and the median was 2600 µg/kg. The threshold effect concentration was exceeded at 62% of sampling locations, and the probable effect concentration or the equilibrium partitioning sediment benchmark was exceeded at 41% of sampling locations. These results have important implications for watershed managers tasked with protecting and remediating aquatic habitats in the Great Lakes Basin.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4727","usgsCitation":"Baldwin, A.K., Corsi, S., Oliver, S.K., Lenaker, P.L., Nott, M.A., Mills, M.A., Norris, G.A., and Paatero, P., 2020, Primary sources of polycyclic aromatic hydrocarbons to streambed sediment in Great Lakes tributaries using multiple lines of evidence: Environmental Toxicology and Chemistry, v. 39, no. 7, p. 1392-1408, https://doi.org/10.1002/etc.4727.","productDescription":"17 p.","startPage":"1392","endPage":"1408","numberOfPages":"17","ipdsId":"IP-106377","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456268,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4727","text":"Publisher Index Page"},{"id":376159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana, Michigan, Minnesota, New York, Ohio, Wisconsin","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.74658203125,\n 40.48038142908172\n ],\n [\n -75.1025390625,\n 40.48038142908172\n ],\n [\n -75.1025390625,\n 47.989921667414194\n ],\n [\n -92.74658203125,\n 47.989921667414194\n ],\n [\n -92.74658203125,\n 40.48038142908172\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792257,"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":792258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":792261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Norris, Gary A.","contributorId":228850,"corporation":false,"usgs":false,"family":"Norris","given":"Gary","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":792262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paatero, Pentti","contributorId":228851,"corporation":false,"usgs":false,"family":"Paatero","given":"Pentti","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":792263,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211892,"text":"70211892 - 2020 - A mixed length scale model for migrating fluvial bedforms","interactions":[],"lastModifiedDate":"2020-08-11T13:59:35.822256","indexId":"70211892","displayToPublicDate":"2020-06-24T08:54:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"A mixed length scale model for migrating fluvial bedforms","docAbstract":"With the expansion of hydropower, in‐stream converters, flood‐protection infrastructures, and growing concerns on deltas fragile ecosystems, there is a pressing need to evaluate and monitor bedform sediment mass flux. It is critical to estimate real‐time bedform size and migration velocity and provide a theoretical framework to convert easily accessible time histories of bed elevations into spatially evolving patterns. We collected spatiotemporally resolved bathymetries from laboratory flumes and the Colorado River in statistically steady, homogeneous, subcritical flow conditions. Wave number and frequency spectra of bed elevations show compelling evidence of scale‐dependent velocity for the hierarchy of migrating bedforms observed in the laboratory and field. New scaling laws were applied to describe the full range of migration velocities as function of two dimensionless groups based on the bed shear velocity, sediment diameter, and water depth. Further simplification resulted in a mixed length scale model estimating scale‐dependent migration velocities, without requiring bedform classification or identification.
On 14–15 April 2015, an intense intermountain cyclone in the western USA caused high winds and a dust storm that degraded air quality in the eastern Great Basin, and deposited dust-on-snow (DOS) in the Wasatch Range near Salt Lake City, Utah. We analyzed the storm and documented its “source-to-sink” development to relate the frontal passage with dust mobilization, air quality changes, and dust deposition on montane snowpack near Alta, Utah. This case study is first to track a dust storm and measure the elemental composition and radiative properties of the resulting DOS as a single specific event layer in Wasatch montane snowpack; prior studies have assessed seasonally aggregated DOS deposits. Dust plumes on MODIS imagery indicate mobilization from known regional “hotspots” for aeolian activity, including clay- and silt-rich alluvium, modern playas, and disturbed areas within the Pleistocene Paleolake Bonneville Basin. This 2015 single event dust layer was 1–3 cm thick with a median dust size of 10.81–12.55 µm; its measured radiative properties are similar to aggregated dusts previously assessed in Wasatch snowpack. Dust from the 2015 DOS event is enriched in the elements As, Cd, Cu, and Mo by a 10× factor relative to average elemental concentrations in the upper continental crust; its heavy metals (Cu, Pb, As, Cd, Mo, Zn) are probably derived from regional mine operations. Tracking elemental fluxes from source-to-sink is important for resolving environmental impacts, and informing future analysis of single storm dust loading, ecosystem impacts, and quantity and quality of meltwater-fed drinking water.