The glacial aquifer system, which is a collection of aquifers within Quaternary sediments in the glaciated conterminous United States, is a principal aquifer that supplies groundwater that serves about 42 million people and accounts for about 5 percent of the Nation’s drinking water. This aquifer system (the area of maximum glacial advance) underlies parts of 25 States and covers 1.87×106 square kilometers. A hydrogeologic framework is presented that divides the glaciated United States into 17 distinct hydrogeologic terranes using a geologic approach based on previous mapping. Each hydrogeologic terrane contains Quaternary sediment that is derived from a common depositional history and can be characterized by similar texture and thickness. Characteristics of Quaternary sediments are described using attributes computed from a lithologic database of well logs compiled from 24 States (excluding Kentucky). The hydrogeologic framework presents a nationwide picture of the glacial aquifer system and provides generalizations concerning the nature of aquifers within it (for example, whether the aquifers are shallow or deep, and unconfined or confined). In this way insights can be gained from understanding the similarities and differences in distinct parts of the glacial aquifer system and how they relate to water use and quality and to aquifer vulnerability.
Delineation of hydrogeologic terranes was based on an interpretation of existing geologic mapping of Quaternary sediments and the thickness of unconsolidated material. Overall thickness of Quaternary sediment was used to qualitatively rank the generalized complexity of the hydrogeologic framework in each terrane: “lower” complexity (assigned a terrane code 1), “moderate” complexity (terrane code 2), and “higher” complexity (terrane code 3). Letter designations appended to the terrane codes (for example, 1A, 1B, or 1C) differentiate terranes of similar complexity. Two unique areas, where thick, stratified, coarse-grained sediment dominates, were assigned terrane code 4.
Elements of this hydrogeologic framework include a glacial environments and surficial sediments geodatabase, which includes lithologic, geomorphic, and stratigraphic characterization of Quaternary sediments based on previous mapping; a gridded database of sediment and aquifer characteristics computed from lithologic logs obtained from water-well driller records; a water-use database with information on public-water supply systems and sources of groundwater; and estimated recharge computed from a geologically based soil-water balance model. A generalized map of the bedrock geology based on previous State-level mapping is included as well.
Quaternary sediment in the glaciated United States includes glacial, postglacial (Holocene) and nonglacial sediments. At land surface, 60 percent of the glacial sediment is till. Large areas of outwash and ice contact sediments are extensive throughout the Midwest but generally are confined to valleys in the Northeast and the Northwest. Lacustrine sediments were deposited in proglacial lakes adjacent to the present Great Lakes and in glacial Lake Agassiz in the eastern Dakotas and northwestern Minnesota. The median thickness of Quaternary sediment ranges from 6 to 45 meters across the 17 hydrogeologic terranes, but the maximum thickness is more than 500 meters in some areas. Quaternary sediments generally contain less than 10 percent coarse material; the median range is near zero percent under till to about 50 percent under ice contact and outwash sediments. About 80 percent of the coarse material lies within 25 to 40 meters of land surface.
In most of the glaciated United States, there is a small likelihood of penetrating an aquifer-material interval containing coarse material at least 3 meters thick. A single aquifer-material interval was recorded in about 44 percent of lithologic logs, whereas about 11 percent of the logs penetrated multiple intervals. About 44 percent of water wells in the lithologic database are completed in Quaternary sediment, and many of these Quaternary water wells (42 percent) are confined by at least 7.5 meters of fine materials. About 33 percent of these Quaternary water wells are unconfined—the remainder are where only thin layers (less than 3 meters) of coarse material are present. The median depths of Quaternary water wells range from 13 to 40 meters among the 17 hydrogeologic terranes.
Recharge ranges from more than 400 millimeters per year in the Northeast to 11 millimeters or less per year in the Dakotas and Montana (median value of 136 millimeters per year). Annual groundwater withdrawals compiled by county range on an areal basis from less than 1 to 370 millimeters per year, and the mean is 7.4 millimeters per year. About 36 percent of the withdrawals are for public-water supply, of which 70 percent are derived from Quaternary sediments. Groundwater withdrawals are less than 10 percent of recharge throughout most of the glaciated conterminous United States but are a larger proportion of recharge near urban areas in the Northeast and the Midwest, and in counties throughout drier parts of the Midwest.
The salient characteristics of the 17 hydrogeologic terranes are presented through maps and a set of descriptive plots to facilitate visual comparisons between selected sediment and aquifer characteristics. The thickness of Quaternary sediment generally increases from the lower complexity terranes through the higher complexity terranes, consistent with their delineation. Median proportions of coarse material in Quaternary sediment and depths to aquifer-material intervals are highly variable (less than 10 to 50 percent, and 0 to 30 meters, respectively). Median thicknesses of aquifer-material intervals generally fall within a narrow range (10 to 20 meters), except in two terranes that contain thick coarse-grained sediment (30 to 35 meters). The source of water in wells varies from mostly bedrock wells in the lower complexity terranes to mostly Quaternary wells in the higher complexity terranes where the sediment is thickest. A tree diagram compiled from a hierarchical cluster analysis of a matrix composed of metrics based on sediment and aquifer characteristics, and the distribution of water wells in each terrane, indicates some groups of terranes that can be treated as comparable when analyzing groundwater flow and quality.
Aquifer-material intervals indicated on maps prepared from the lithologic logs, including unconfined and confined conditions, correlate well with aquifer systems delineated on state maps for Illinois, Indiana, and North Dakota. The large scale of the study limits the resolution at which the maps can be interpreted, however, and alluvial units are not mapped correctly for some valleys in the Northeast and the Northwest. Lithologic logs used in the study are biased toward shallow depths because not all logs penetrate the entire thickness of Quaternary sediment, but this bias should not limit the utility of the sediment and aquifer descriptions because shallow depths are commonly exploited for water supply. The hydrogeologic framework will support ongoing studies of groundwater flow and quality in the U.S. Geological Survey National Water Quality Assessment program for the glaciated United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185091","usgsCitation":"Yager, R.M., Kauffman, L.J., Soller, D.R., Haj, A.E., Heisig, P.M., Buchwald, C.A., Westenbroek, S.M., and Reddy, J.E., 2019, Characterization and occurrence of confined and unconfined aquifers in Quaternary sediments in the glaciated conterminous United States (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Report 2018–5091, 90 p., https://doi.org/10.3133/sir20185091.","productDescription":"Report: ix, 90 p.; Interactive Leaflet maps; Data releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081249","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":359750,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6PQG","text":"USGS data release","description":"USGS data release","linkHelpText":"Databases used to develop a hydrogeologic framework for Quaternary sediments in the glaciated conterminous United States"},{"id":359748,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/ds1090","text":"Data Series 1090","linkHelpText":"- Hydrogeologic Framework for Characterization and Occurrence of Confined and Unconfined Aquifers in Quaternary Sediments in the Glaciated Conterminous United States—A Digital Map Compilation and Database"},{"id":359747,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J8X","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital products from a hydrogeologic framework for Quaternary sediments within the glaciated conterminous United States"},{"id":359745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5091/coverthb2.jpg"},{"id":359749,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2018/5091/sir20185091_index.html","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Index page for oversized, interactive Leaflet maps"},{"id":359746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5091/sir20185091.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5091"},{"id":361089,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5091/versionHist.txt","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.969069883,\n 35.090811167\n ],\n [\n -65.343237884,\n 35.090811167\n ],\n [\n -65.343237884,\n 50.932504994\n ],\n [\n -124.969069883,\n 50.932504994\n ],\n [\n -124.969069883,\n 35.090811167\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2019; Version 1.0: December 2018","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
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Iowa City, IA 52240
The U.S. Geological Survey, in cooperation with the City of Cedar Rapids, began a study in 2013 to better understand the effects of drought stress on the Cedar River alluvial aquifer. After an evaluation of the existing groundwater-flow models for the alluvial aquifer, a plan was begun to construct an updated groundwater-flow model capable of evaluating the effect of prolonged drought and increased demand. As part of the effort to update the existing groundwater-flow model, data were collected during an airborne electromagnetic (AEM) survey in May 2017. The study area for the AEM survey encompasses about 53 square kilometers of the Cedar River Basin, west of Cedar Rapids, Iowa, and includes a 19-kilometer reach of the Cedar River. The AEM survey of the Cedar River alluvial aquifer and adjacent areas was completed to characterize the subsurface geology of the area to refine a lithologic framework. The collected AEM data were postprocessed by numerical inversion using the program EM1DFM to produce subsurface apparent resistivity cross sections. Changes observed in resistivity profile values with depth were used to infer lithologic changes and delineate three of the four lithologic units designated in the lithologic framework for this area: alluvial deposits, glacial till, and bedrock; hereafter referred to as the “lithologic framework.” The fourth unit, composed of surficial eolian sediments, was not delineated in these profiles because these units are thin and discontinuous and are not reliably distinguishable from flood plain alluvial deposits. For the purposes of delineating lithologic units using the AEM data, bedrock was assumed to be the lowest unit in a profile, glacial till was deposited on a bedrock surface, and alluvium was deposited on erosional till or bedrock surfaces.
A three-dimensional fence diagram was created as part of the lithologic framework to further define the extent and thickness of the lithologic units near the Cedar River alluvial aquifer. The fence diagram shows a three-dimensional perspective of unit thickness, extent, and orientation of the delineated lithologic framework. A lithologic framework, by design, is intended to represent a simplification of a more complex natural system through data interpolation between known points, which usually are lithologic logs. The resistivity profiles produced from the AEM survey allow for continuous mapping and accurate interpolation of lithology between lithologic logs; however, the apparent resistivity value may reflect several characteristics of subsurface materials including variations in lithology, porosity, water quality, grain sorting, and degree of saturation. In this study, the only variables considered were those related to changes in the subsurface material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3423","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Valder, J.F., Haj, A.E., Bristow, E.L., and Valseth, K.J., 2019, Delineation of selected lithologic units using airborne electromagnetic data near Cedar Rapids, Iowa (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Map 3423, 2 sheets, 9-p. pamphlet, https://doi.org/10.3133/sim3423.","productDescription":"Pamphlet: vi, 9 p.; 2 Sheets: 42.0 x 24.0 inches and 44.0 x 28.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101741","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":361084,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3423/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3423 Version History"},{"id":360194,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_sheet2.pdf","text":"Sheet 2","size":"2.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Sheet 2"},{"id":360192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_pamphlet.pdf","text":"Pamphlet","size":"2.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Pamphlet"},{"id":360191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3423/coverthb2.jpg"},{"id":360193,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_sheet1.pdf","text":"Sheet 1","size":"7.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Sheet 1"},{"id":360208,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BS882S","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Airborne electromagnetic and magnetic survey data and inverted resistivity models, Cedar Rapids, Iowa, May 2017"}],"country":"United States","state":"Iowa","city":"Cedar Rapids","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8,\n 42\n ],\n [\n -91.7,\n 42\n ],\n [\n -91.7,\n 42.0667\n ],\n [\n -91.8,\n 42.0667\n ],\n [\n -91.8,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2019; Version 1.0: December 2018","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Located on the northern edge of the West Pacific Warm Pool and having a developed economy and modern infrastructure, Guam is well positioned and equipped for obtaining natural records of the west Pacific maritime paleoclimate. This study was a proof of concept to explore whether useful climate proxy records might be obtained from coral at readily accessible, even if geochemically nonoptimal, coastal sites. A 50-year Sr/Ca record (1960–2010) was thus obtained from a shallow-water, near-shore Porites luteacolony at a recreational facility inside Guam's Apra Harbor and compared with local and regional meteorological records, including the El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) indices. The accessibility of the site enabled documentation of relevant environmental variables for 16 months (September 2009–December 2010): seawater δ18O, pH, seawater cations, and nitrate. Time series of seawater δ18O, pH, and cations show evidence of freshwater input from direct rainfall and stream discharge into the harbor. An anomalously higher mean and variable concentrations of Ba suggest the presence of river-borne, fine-grained terrigenous sediment. Nevertheless, the Sr/Ca time series reproduces a long-term warming trend seen in historical records of local air temperature and regional sea-surface temperature (SST) and closely tracks the ENSO and PDO indices over the entire 50-year record. The consistency of the results with Guam's historical instrumental records, previous coral δ18O results from Guam obtained by others, and previous Sr/Ca proxy results for SST in similar environments elsewhere demonstrate that accessible near-shore sites—where environmental conditions can be monitored—can produce useful Sr/Ca records of local and regional climate phenomena.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-16-00099.1","usgsCitation":"Bell, T., Lander, M., Jenson, J., Randall, R., Partin, J.W., and Prouty, N.G., 2019, A 50-year Sr/Ca time series from an enclosed, shallow-water Guam coral: In situ monitoring and extraction of a temperature trend, annual cycle, and ENSO and PDO signals: Journal of Coastal Research, v. 35, no. 2, p. 269-286, https://doi.org/10.2112/JCOASTRES-D-16-00099.1.","productDescription":"18 p.","startPage":"269","endPage":"286","ipdsId":"IP-075254","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8e2e4b034bf6a7e4dbb","contributors":{"authors":[{"text":"Bell, Tomoko","contributorId":211310,"corporation":false,"usgs":false,"family":"Bell","given":"Tomoko","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":753624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lander, Mark","contributorId":211311,"corporation":false,"usgs":false,"family":"Lander","given":"Mark","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenson, John","contributorId":211312,"corporation":false,"usgs":false,"family":"Jenson","given":"John","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randall, Richard","contributorId":211313,"corporation":false,"usgs":false,"family":"Randall","given":"Richard","email":"","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Partin, Judson W.","contributorId":203459,"corporation":false,"usgs":false,"family":"Partin","given":"Judson","email":"","middleInitial":"W.","affiliations":[{"id":36624,"text":"Institute for Geophysics, Jackson School of Geosciences, University of Texas at Austin, J. J. Pickle Research Campus, Building 196, 10100 Burnet Road (R2200), Austin, Texas 78758, USA","active":true,"usgs":false}],"preferred":false,"id":753628,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753623,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201350,"text":"70201350 - 2019 - Food‐web structure and ecosystem function in the Laurentian Great Lakes—Toward a conceptual model","interactions":[],"lastModifiedDate":"2019-01-28T08:36:06","indexId":"70201350","displayToPublicDate":"2018-12-11T11:00:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Food‐web structure and ecosystem function in the Laurentian Great Lakes—Toward a conceptual model","docAbstract":"Severity and heterogeneity of stress are major constraints of beta diversity, but their relative influence is poorly understood. Here, we addressed this question by examining the patterns of beta diversity in stress‐sensitive versus stress‐tolerant stream diatoms and their response to local versus regional factors along gradients of stress severity and heterogeneity.
The Adirondack region of New York.
Beta diversity was measured as multivariate dispersion of communities across high stress, low stress, and high + low stress (heterogeneous) environments, encompassing 200 stream samples. Null models were implemented to assess community similarity relative to randomly assembled communities and the importance of local assembly processes versus the regional species pool.
The overall beta diversity was influenced by a combination of severity and heterogeneity of stress, while beta diversity of sensitive species increased with heterogeneity. Beta diversity of tolerant species did not vary with either severity or heterogeneity of stress. Heterogeneity decreased community similarity relative to the null expectation in all groups of species. Stress reduced the importance of local assembly mechanisms for the overall beta diversity and sensitive species beta diversity. In contrast, the importance of local assembly mechanisms increased with stress regarding beta diversity of tolerant species.
Beta diversity responded to both severity and heterogeneity of stress, but turnover along these gradients was mostly driven by sensitive species. The overall beta diversity and beta diversity of sensitive species became more constrained by the depauperate regional species pool, as opposed to local assembly mechanisms. While heterogeneous stress contributed to beta diversity, severe stress suppressed beta diversity through elimination of sensitive species. Therefore, an increase in beta diversity in an environmentally‐stressed region may serve as a forewarning for future loss of sensitive species, should the stress continue to intensify.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12865","usgsCitation":"Pound, K., Lawrence, G.B., and Passy, S., 2019, Beta diversity response to stress severity and heterogeneity in sensitive versus tolerant stream diatoms: Diversity and Distributions, v. 25, no. 3, p. 374-384, https://doi.org/10.1111/ddi.12865.","productDescription":"11 p.","startPage":"374","endPage":"384","ipdsId":"IP-073100","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12865","text":"Publisher Index Page"},{"id":383086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Park, Black River basin, Oswegatchie River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.3936767578125,\n 43.201171681272456\n ],\n [\n -74.33349609375,\n 43.201171681272456\n ],\n [\n -74.33349609375,\n 44.453388800301774\n ],\n [\n -75.3936767578125,\n 44.453388800301774\n ],\n [\n -75.3936767578125,\n 43.201171681272456\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Pound, Katrina L","contributorId":139826,"corporation":false,"usgs":false,"family":"Pound","given":"Katrina L","affiliations":[{"id":13288,"text":"Graduate student, Dept of Biology, Univ of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":809943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passy, Sophia","contributorId":248812,"corporation":false,"usgs":false,"family":"Passy","given":"Sophia","affiliations":[{"id":50025,"text":"Associate Professor, University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":809945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201280,"text":"70201280 - 2019 - Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models","interactions":[],"lastModifiedDate":"2018-12-10T12:41:37","indexId":"70201280","displayToPublicDate":"2018-12-10T12:41:32","publicationYear":"2019","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":"Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models","docAbstract":"Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.11.235","usgsCitation":"Azareh, A., Rahmati, O., Rafiei-Sardooi, E., Sankey, J.B., Lee, S., Shahabi, H., and Bin Ahmad, B., 2019, Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models: Science of the Total Environment, v. 655, p. 684-696, https://doi.org/10.1016/j.scitotenv.2018.11.235.","productDescription":"13 p.","startPage":"684","endPage":"696","ipdsId":"IP-091094","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.11.235","text":"Publisher Index Page"},{"id":360103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 46.1667,\n 33.3333\n ],\n [\n 47,\n 33.3333\n ],\n [\n 47,\n 33.8333\n ],\n [\n 46.1667,\n 33.8333\n ],\n [\n 46.1667,\n 33.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"655","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0f8977e4b0c53ecb2c71de","contributors":{"authors":[{"text":"Azareh, Ali","contributorId":211256,"corporation":false,"usgs":false,"family":"Azareh","given":"Ali","email":"","affiliations":[{"id":38202,"text":"Department of Geography, University of Jiroft, Kerman, Iran","active":true,"usgs":false}],"preferred":false,"id":753469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rahmati, Omid","contributorId":211254,"corporation":false,"usgs":false,"family":"Rahmati","given":"Omid","email":"","affiliations":[{"id":38200,"text":"Department of Watershed Management, Faculty of Agriculture and Natural Resources Management, Lorestan University, Iran","active":true,"usgs":false}],"preferred":false,"id":753467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rafiei-Sardooi, Elham","contributorId":211257,"corporation":false,"usgs":false,"family":"Rafiei-Sardooi","given":"Elham","email":"","affiliations":[{"id":38203,"text":"Faculty of Natural Resources, University of Jiroft, Kerman, Iran","active":true,"usgs":false}],"preferred":false,"id":753470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":753466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Saro","contributorId":211255,"corporation":false,"usgs":false,"family":"Lee","given":"Saro","email":"","affiliations":[{"id":38201,"text":"Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon 305350, Korea","active":true,"usgs":false}],"preferred":false,"id":753468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shahabi, Himan","contributorId":211258,"corporation":false,"usgs":false,"family":"Shahabi","given":"Himan","email":"","affiliations":[{"id":38204,"text":"Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran","active":true,"usgs":false}],"preferred":false,"id":753471,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bin Ahmad, Baharin","contributorId":211259,"corporation":false,"usgs":false,"family":"Bin Ahmad","given":"Baharin","email":"","affiliations":[{"id":38205,"text":"Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia (UTM), Malaysia","active":true,"usgs":false}],"preferred":false,"id":753472,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201281,"text":"70201281 - 2019 - Energetic constraints and the paradox of a diffusing population in a heterogeneous environment","interactions":[],"lastModifiedDate":"2019-01-28T08:37:33","indexId":"70201281","displayToPublicDate":"2018-12-10T12:36:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3593,"text":"Theoretical Population Biology","active":true,"publicationSubtype":{"id":10}},"title":"Energetic constraints and the paradox of a diffusing population in a heterogeneous environment","docAbstract":"Previous mathematical analyses have shown that, for certain parameter ranges, a population, described by logistic equations on a set of connected patches, and diffusing among them, can reach a higher equilibrium total population when the local carrying capacities are heterogeneously distributed across patches, than when carrying capacities having the same total sum are homogeneously distributed across the patches. It is shown here that this apparently paradoxical result is explained when the resultant differences in energy inputs to the whole multi-patch system are taken into account. We examine both Pearl–Verhulst and Original Verhulst logistic models and show that, when total input of energy or limiting resource, is constrained to be the same in the homogeneous and heterogeneous cases, the total population in the heterogeneous patches can never reach an asymptotic equilibrium that is greater than the sum of the carrying capacities over the homogeneous patches. We further show that, when the dynamics of the limiting resources are explicitly modeled, as in a chemostat model, the paradoxical result of the logistic models does not occur. These results have implications concerning the use of some ubiquitous equations of population ecology in modeling populations in space.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tpb.2018.11.003","usgsCitation":"Wang, Y., and DeAngelis, D.L., 2019, Energetic constraints and the paradox of a diffusing population in a heterogeneous environment: Theoretical Population Biology, v. 125, p. 30-37, https://doi.org/10.1016/j.tpb.2018.11.003.","productDescription":"8 p.","startPage":"30","endPage":"37","ipdsId":"IP-092638","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tpb.2018.11.003","text":"Publisher Index Page"},{"id":360102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0f8979e4b0c53ecb2c71e5","contributors":{"authors":[{"text":"Wang, Yuanshi","contributorId":207814,"corporation":false,"usgs":false,"family":"Wang","given":"Yuanshi","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":753474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":753473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223253,"text":"70223253 - 2019 - Running on empty: Recharge dynamics from animal movement data","interactions":[],"lastModifiedDate":"2021-08-19T16:21:18.119233","indexId":"70223253","displayToPublicDate":"2018-12-09T11:19:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Running on empty: Recharge dynamics from animal movement data","docAbstract":"Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion (Puma concolor; in Colorado, USA) and African buffalo (Syncerus caffer; in Kruger National Park, South Africa) recharge dynamics.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.13198","usgsCitation":"Hooten, M., Scharf, H.R., and Morales, J.M., 2019, Running on empty: Recharge dynamics from animal movement data: Ecology Letters, v. 22, no. 2, p. 377-389, https://doi.org/10.1111/ele.13198.","productDescription":"13 p.","startPage":"377","endPage":"389","ipdsId":"IP-101207","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.gla.ac.uk/277798/","text":"External Repository"},{"id":388161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":821532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharf, Henry R.","contributorId":206652,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":37371,"text":"Colorado State University, Department of Statistics","active":true,"usgs":false}],"preferred":false,"id":821533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":821534,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204350,"text":"70204350 - 2019 - River reach restored by dam removal offers suitable spawning habitat for endangered Shortnose Sturgeon","interactions":[],"lastModifiedDate":"2019-07-18T14:39:38","indexId":"70204350","displayToPublicDate":"2018-12-07T14:38:10","publicationYear":"2019","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":"River reach restored by dam removal offers suitable spawning habitat for endangered Shortnose Sturgeon","docAbstract":"The lowermost dam on the Penobscot River, Maine, was removed in 2013, making new habitat available for migratory fish. There is no evidence that endangered Shortnose Sturgeon Acipenser brevirostrum have spawned in the Penobscot River in recent years, but dam removal has facilitated access to potential freshwater habitat essential for spawning. Spawning success also depends on the quality of the available habitat. We sought to describe the distribution and amount of suitable spawning habitat in the first 5-km reach upstream of the removed dam. Previously collected river elevation and bottom substrate data were used to create two-dimensional hydrodynamic simulations of the reach for spring discharges ranging from 310 to 1480 m3 s-1 using the program River2D. Simulations were validated and adjusted using field-collected data. Suitable spawning habitat was predicted based on literature-informed suitability curves of depth, velocity, and bottom substrate. Between 41% and 63% of the study area offered usable spawning habitat, depending on river discharge. Velocity was the most limiting characteristic to overall suitability at all modeled discharges. Embeddedness was minimal at suitable sites. Based on the habitat characteristics considered, the newly accessible reach of the Penobscot River could support Shortnose Sturgeon spawning, offering critical habitat for this endangered species.","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10126","usgsCitation":"Zydlewski, J.D., Johnston, C., Gayle Barbin Zydlewski, Sean Smith, and Kinnison, M.T., 2019, River reach restored by dam removal offers suitable spawning habitat for endangered Shortnose Sturgeon: Transactions of the American Fisheries Society, v. 148, no. 1, p. 163-175, https://doi.org/10.1002/tafs.10126.","productDescription":"13 p.","startPage":"163","endPage":"175","ipdsId":"IP-079297","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468034,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/tafs.10126","text":"External Repository"},{"id":365727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":766468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnston, Catherine","contributorId":217260,"corporation":false,"usgs":false,"family":"Johnston","given":"Catherine","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":766469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gayle Barbin Zydlewski","contributorId":217261,"corporation":false,"usgs":false,"family":"Gayle Barbin Zydlewski","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":766470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sean Smith","contributorId":217262,"corporation":false,"usgs":false,"family":"Sean Smith","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":766471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kinnison, Michael T.","contributorId":169682,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":766472,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201539,"text":"70201539 - 2019 - Pulsed salmonfly emergence and its potential contribution to terrestrial detrital pools","interactions":[],"lastModifiedDate":"2019-01-28T08:29:07","indexId":"70201539","displayToPublicDate":"2018-12-06T13:08:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5453,"text":"Food Webs","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed salmonfly emergence and its potential contribution to terrestrial detrital pools","docAbstract":"Adult aquatic insects are a globally important subsidy in terrestrial food webs. However, our understanding of their importance is largely limited to studies that measure predation of live insects by terrestrial predators. Yet the flux of adult aquatic insects to terrestrial detrital pools may also be an important subsidy pathway, particularly in cases where insect production exceeds the consumption capacity of predators. We used empirical measures of giant salmonfly (Pteronarcys californica) emergence from 37 sites to model potential detrital deposition in nearshore riparian soil food webs. Typically, giant salmonflies emerge en masse for one week each year, and can be locally superabundant. Median detrital deposition by salmonflies ranged between 0.4 and 0.7 gC, 0.04 to 0.09 gN, and 0.002 to 0.005 gP/m2/yr, depending on whether 25% or 100% of available salmonflies entered detrital pools. For a small number of sites with large salmonfly populations, deposition equaled or exceeded annual secondary production of terrestrial insects, annual atmospheric N deposition, and annual atmospheric P deposition. The fact that these values rival yearly nutrient budgets is particularly striking because giant salmonfly deposition represents a subsidy from a single species emerging over a single week. The consequences of this deposition in terrestrial food webs are largely unknown, but it is likely that salmonflies can have important effects on nearshore soil nutrient budgets similar in magnitude to those of other important ecosystem processes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fooweb.2018.e00105","usgsCitation":"Wesner, J., Walters, D., and Zuellig, R.E., 2019, Pulsed salmonfly emergence and its potential contribution to terrestrial detrital pools: Food Webs, v. 18, p. 1-7, https://doi.org/10.1016/j.fooweb.2018.e00105.","productDescription":"e00105; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-099294","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468036,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fooweb.2018.e00105","text":"Publisher Index Page"},{"id":360371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c425e4b006c4f856acda","contributors":{"authors":[{"text":"Wesner, Jeff","contributorId":211583,"corporation":false,"usgs":false,"family":"Wesner","given":"Jeff","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":754419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":754418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754420,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203671,"text":"70203671 - 2019 - Probability of streamflow permanence model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest","interactions":[],"lastModifiedDate":"2023-03-27T22:23:55.781374","indexId":"70203671","displayToPublicDate":"2018-12-05T16:31:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Probability of streamflow permanence model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest","docAbstract":"The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (probabilistic predictions) of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions correspond to any pixel on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Total annual precipitation and percent forest cover were consistently the most important predictor variables among global and most subregional models, which had error rates between 17 and 22%. Probabilities were converted to wet and dry streamflow permanence classes with an associated confidence. Wet and dry classifications were used to derive descriptors that characterize the statistical and spatial distribution of streamflow permanence in three focal basins. Predicted dry channel segments account for 52 to 92% of the stream network across the three focal basins; streamflow permanence decreased during climatically drier years. Predictions are publicly available through the USGS StreamStats platform. Results demonstrate the utility of the PROSPER model as a tool for identifying areas that may be resilient or sensitive to drought conditions, allowing for management efforts that target protecting critical reaches. Importantly, PROSPER’s successful predictive performance can be improved with new datasets of streamflow permanence underscoring the importance of field observations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2018.100005","usgsCitation":"Jaeger, K., Sando, R., McShane, R.R., Dunham, J.B., Hockman-Wert, D., Kaiser, K.E., Hafen, K., Risley, J., and Blasch, K.W., 2019, Probability of streamflow permanence model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest: Journal of Hydrology X, v. 2, 100005, 19 p., https://doi.org/10.1016/j.hydroa.2018.100005.","productDescription":"100005, 19 p.","onlineOnly":"N","ipdsId":"IP-093406","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water 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jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8647-7031","contributorId":215958,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763535,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blasch, Kyle W. 0000-0002-0590-0724","orcid":"https://orcid.org/0000-0002-0590-0724","contributorId":203415,"corporation":false,"usgs":true,"family":"Blasch","given":"Kyle","email":"","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763536,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201190,"text":"70201190 - 2019 - Water-quality trends in US rivers: Exploring effects from streamflow trends and changes in watershed management","interactions":[],"lastModifiedDate":"2018-12-05T10:49:25","indexId":"70201190","displayToPublicDate":"2018-12-05T10:49:21","publicationYear":"2019","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":"Water-quality trends in US rivers: Exploring effects from streamflow trends and changes in watershed management","docAbstract":"We present a conceptual model that explores the relationship of streamflow trends to 15 water-quality parameters at 370 sites across the contiguous United States (US). Our analytical framework uses discrete water-quality data, daily streamflow records, and a statistical model to estimate water-quality trends between 1982 and 2012 and parse these trends into the amount of change attributed to trends in streamflow versus changes in watershed management, such as changes in point or non-point sources related to pollution control efforts. We conceptualize a water-quality trend as an additive function of these two trend components. We found that for most of these records the water-quality trends were more strongly affected by changes in watershed management as opposed to trends in streamflow. However, the importance of these trend components on water quality varied by estimate type (i.e. concentration versus load trends), parameter, and site. Trends in load were more influenced by changes in the streamflow regime than trends in concentration. Trends in major ions, salinity, and sediment were more sensitive to changes in streamflow than nutrients. When results were aggregated by site, 25% of the sites had at least 1 parameter where streamflow trends attributed >7.5% to the water-quality trend for concentrations. For loads, this was the case for 66% of the sites. The findings of this work have important implications for the analysis of water-quality trends. Understanding the relative role of streamflow and management changes can help to isolate the effects of pollution control efforts on water quality and provide clearer understanding of progress, or lack thereof, towards water-quality goals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.11.255","usgsCitation":"Murphy, J.C., and Sprague, L.A., 2019, Water-quality trends in US rivers: Exploring effects from streamflow trends and changes in watershed management: Science of the Total Environment, v. 656, p. 645-658, https://doi.org/10.1016/j.scitotenv.2018.11.255.","productDescription":"14 p.","startPage":"645","endPage":"658","ipdsId":"IP-101146","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":468039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.11.255","text":"Publisher Index Page"},{"id":359958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"656","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c08f1c4e4b0815414d0bbf9","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":753131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sprague, Lori A. 0000-0003-2832-6662 lsprague@usgs.gov","orcid":"https://orcid.org/0000-0003-2832-6662","contributorId":726,"corporation":false,"usgs":true,"family":"Sprague","given":"Lori","email":"lsprague@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":753132,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226716,"text":"70226716 - 2019 - Geographic attribution of soils using probabilistic modeling of GIS data for forensic search efforts","interactions":[],"lastModifiedDate":"2021-12-07T13:10:00.198493","indexId":"70226716","displayToPublicDate":"2018-12-05T07:07:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Geographic attribution of soils using probabilistic modeling of GIS data for forensic search efforts","docAbstract":"Examinations of soil traces associated with forensic evidence can be used to narrow potential source area(s) by characterizing features of the trace soil assemblage, some of which are limited to specific regions. Soil characteristics may be used to infer the likelihoods of the soil trace being derived from distinct areas within digital maps, including both maps of discrete classes such as formations on geologic maps and land cover, and continuous geospatial data, such as distance from a point source. Seldom do digital maps precisely represent the observable characteristics in a soil trace. Nevertheless, logical assigned likelihoods based on the correspondence between the mapped characteristics and the observed soil particulate assemblage permit creation of a model of the more probable sources of the soil trace. This approach is applied to a 2003 case in which forensic soil samples derived from digging tools were characterized for investigative leads and to narrow the search area of a clandestine grave. This grave site was located in 2005. The suspect traveled approximately 5,000 km before arrest, so narrowing the prioritized search area for law enforcement would be beneficial. Soil examination and case circumstances were used to assign relative likelihoods within digital maps (GIS or Geographic Information Systems data) of geology, soil mineralogy, plant distributions, power plant locations, and proximity to the known travel path. The product of these individual probability maps generates joint probability models to narrow the recommended search area. The digital model output can be easily overlaid on infrastructure maps to aid law enforcement searches.
Using empirical location data from individuals to model habitat quality and species distributions is valuable towards understanding habitat use of wildlife, especially for conservation and management planning. Incorporating measures of reproductive success or survival into these models helps address the role of vital rates (a surrogate of fitness) in affecting a species’ distribution. We used 24-year datasets of Arctic peregrine falcon (Falco peregrinus tundrius) nest-site locations and productivity from the Colville River Special Area, Alaska, USA to model suitability of breeding habitat and the relative quality of used and potential nest sites. We used zero-inflated negative binomial regression models and covariates describing nest-site productivity, area of surrounding prey habitat, geology, topography, and land-cover type to model and predict intensity of Arctic peregrine falcon nest-site use along the Colville River, and developed a predictive map of intensity of nest-site use. Regions of higher predicted intensity of use were characterized by steeper slopes, greater area of prey habitat, and higher average productivity, which are likely attributed to minimizing predation risk, gaining advantages for hunting, having sufficient prey resources, site quality, and overall fitness. Including productivity in intensity of nest-site use models improved the models, supporting our supposition that adding a fitness parameter enhanced the predictive capability of the species distribution model. Areas predicted to have higher intensity of use by our model can be used to focus efforts of continued protection of areas with frequently occupied and productive nest sites, and conversely, identify areas where protection of nest sites is likely to have few conservation benefits.
","language":"English","publisher":"BioOne","doi":"10.2981/wlb.00475","usgsCitation":"Andersen, D.E., Bruggeman, J.E., Swem, T., Kennedy, P.L., and Debora Nigro, 2019, Incorporating productivity as a measure of fitness into models of breeding area quality of Arctic peregrine falcons: Wildlife Biology, 00475, 12 p., https://doi.org/10.2981/wlb.00475.","productDescription":"00475, 12 p.","ipdsId":"IP-084116","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00475","text":"Publisher Index Page"},{"id":365941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Colville River Special Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -158.0,67.0 ], [ -158.0,71.5 ], [ -141.57,71.5 ], [ -141.57,67.0 ], [ -158.0,67.0 ] ] ] } } ] }","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":767010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bruggeman, Jason E.","contributorId":217529,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":767011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swem, Ted","contributorId":217530,"corporation":false,"usgs":false,"family":"Swem","given":"Ted","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":767012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Patricia L.","contributorId":217531,"corporation":false,"usgs":false,"family":"Kennedy","given":"Patricia","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":767013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Debora Nigro","contributorId":217532,"corporation":false,"usgs":false,"family":"Debora Nigro","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":767014,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203173,"text":"70203173 - 2019 - Long-term streamflow trends in Hawai‘i and implications for native stream fauna","interactions":[],"lastModifiedDate":"2019-12-04T15:35:53","indexId":"70203173","displayToPublicDate":"2018-12-02T16:32:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Long-term streamflow trends in Hawai‘i and implications for native stream fauna","docAbstract":"Climate change has fundamentally altered the water cycle in tropical islands, which is a critical driver of freshwater ecosystems. To examine how changes in streamflow regime have impacted habitat quality for native migratory aquatic species, we present a 50‐year (1967–2016) analysis of hydrologic records in 23 unregulated streams across the five largest Hawaiian Islands. For each stream, flow was separated into direct run‐off and baseflow and high‐ and low‐flow statistics (i.e., Q10 and Q90) with ecologically important hydrologic indices (e.g., frequency of flooding and low flow duration) derived. Using Mann–Kendall tests with a running trend analysis, we determined the persistence of streamflow trends through time. We analysed native stream fauna from ~400 sites, sampled from 1992 to 2007, to assess species richness among islands and streams. Declines in streamflow metrics indicated a general drying across the islands. In particular, significant declines in low flow conditions (baseflows), were experienced in 57% of streams, compared with a significant decline in storm flow conditions for 22% of streams. The running trend analysis indicated that many of the significant downward trends were not persistent through time but were only significant if recent decades (1987–2016) were included, with an average decline in baseflow and run‐off of 10.90% and 8.28% per decade, respectively. Streams that supported higher native species diversity were associated with moderate discharge and baseflow index, short duration of low flows, and negligible downward trends in flow. A significant decline in dry season flows (May–October) has led to an increase in the number of no‐flow days in drier areas, indicating that more streams may become intermittent, which has important implications for mauka to makai (mountain to ocean) hydrological connectivity and management of Hawai'i's native migratory freshwater fauna.
Identifying floodplains with high rates of denitrification will help prioritize restoration projects for the removal of nitrogen. Currently, relationships of denitrification with hydrogeomorphic, physiographic, and climate (i.e., largescale) characteristics of floodplains are relatively unknown, even though these characteristics have datasets (e.g., geographic mapping tools) that are publicly available (or soon-to-become) that could be used to understand denitrification variability. Thus, we investigated control of denitrification by these largescale characteristics in eighteen nontidal floodplains of the Chesapeake Bay watershed (i.e., at regional scale, >100 km, scale), using measurements or compiled data at the scales of the stream reach and respective catchment; floodplain soil and herbaceous vegetation (i.e., local) characteristics were additionally investigated. Soil denitrification potentials were measured in May, July, and August using complementary acetylene-based techniques under an anoxic environment. Linear largescale predictors of denitrification potential measurements included stream nitrogen and phosphorus concentrations (+), channel width-to-depth ratio (+), floodplain sedimentation (+), forested (−) and urban (+) catchment land cover, and seasonal air temperature (−). Three predictors, catchment forested land cover (strongly related to agricultural land cover), catchment urban land cover, and floodplain sedimentation were related to the most number of denitrification potential measurements. Soil structure, soil nutrient concentrations, and herbaceous vegetation characteristics that were seasonally measured (with a few exceptions) were linear predictors of denitrification potentials in May and August, with nitrogen and carbon characteristics the most consistent (positive) predictors across measurements. Nutrient amendment assays further supported the importance of nitrogen and carbon controls. Using the local characteristics as statistical mediators in path analysis, greater non-forested catchment land cover indirectly increased denitrification through greater floodplain soil nitrate, total phosphorus, and herbaceous aboveground biomass. Additionally, greater floodplain sedimentation indirectly increased denitrification through greater soil pH, total phosphorus, and potential carbon mineralization. Due to the consistency of relationships across denitrification potential measurements along with path modeling results, hotspots of floodplain denitrification should be found in urban and agricultural catchments where river-floodplain hydrologic connectivity promotes sedimentation. Largescale predictors explained 43–57% of the variation in denitrification potentials and should be useful for prediction in floodplains. Siting restoration projects in watersheds for maximum nitrate removal using publicly available largescale datasets is both feasible and effective.
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gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":752885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahn, Changwoo","contributorId":191303,"corporation":false,"usgs":false,"family":"Ahn","given":"Changwoo","email":"","affiliations":[],"preferred":false,"id":752887,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204011,"text":"70204011 - 2019 - Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management","interactions":[],"lastModifiedDate":"2019-06-27T08:40:40","indexId":"70204011","displayToPublicDate":"2018-11-30T08:39:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5830,"text":"Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management","docAbstract":"In the western U.S., produced water from oil and gas wells discharged to surface water augments downstream supplies used for irrigation and livestock watering. Here we investigate six permitted discharges on three neighboring tributary systems in Wyoming. During 2013-16, we evaluated radium activities of the permitted discharges and the potential for radium accumulation in associated stream sediments. Radium activities of the sediments at the points of discharge ranged from approximately 200-3600 Bq/kg with elevated activities above the background of 74 Bq/kg over 30 km downstream of one permitted discharge. Sediment as deep as 30 cm near the point of discharge had radium activities elevated above background. X-ray diffraction and targeted sequential extraction of radium in sediments indicate that radium is likely coprecipitated with carbonate, and to a lesser extent sulfate minerals. PHREEQC modeling predicts radium coprecipitation with aragonite and barite, but over-estimates the latter compared to observations of downstream sediment, where carbonate predominates. Mass-balance calculations indicate over 3 billion Bq of radium activity (226Ra+228Ra) is discharged each year from five of the discharges, combined, with only 5 percent of the annual load retained in stream sediments within 100m of the effluent discharges; the remaining 95 percent of the radium is transported farther downstream as sediment-associated and aqueous species","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/C8EM00336J","usgsCitation":"McDevitt, B., McLaughlin, M., Cravotta, C.A., Ajemigbitse, M.A., Van Sice, K.J., Blotevogel, J., Borch, T., and Warner, N.R., 2019, Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management: Environmental Science, v. 21, no. 2, p. 324-338, https://doi.org/10.1039/C8EM00336J.","productDescription":"15 p.","startPage":"324","endPage":"338","ipdsId":"IP-102035","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":365100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365097,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.rsc.org/en/content/articlehtml/2019/em/c8em00336j"}],"volume":"21","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDevitt, Bonnie","contributorId":211455,"corporation":false,"usgs":false,"family":"McDevitt","given":"Bonnie","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Molly","contributorId":216622,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Molly","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. 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Impact effects in the “brim” (annular trough) surrounding and adjacent to the transient crater, between the transient crater rim and the outer margin, primarily were limited to the target-sediment layer. Analysis of published and new lithostratigraphic, biostratigraphic, sedimentologic, petrologic, and mineralogic studies of three core holes, and published studies of a fourth core hole, provided information for the interpretation of the impact processes, their interactions and relative timing, their resulting products, and sedimentation in the brim. Most studies of marine impact-crater materials have focused on those found in the central crater. There are relatively few large, complex marine craters, of which most display a wide brim around the central crater. However, most have been studied using minimal data sets. The large number of core holes and seismic profiles available for study of the Chesapeake Bay impact structure presents a special opportunity for research. The physical and chronologic records supplied by study of the sediment and rock cores of the Chesapeake Bay impact indicate that the effects of the initial, short-lived contact and compression and excavation stages of the impact event primarily were limited to the transient crater. Only secondary effects of these processes are evident in the brim. The preserved record of the brim was created primarily in the subsequent modification stage. In the brim, the records of early impact processes (e.g., outgoing tsunamis, overturned flap collapse) were modified or removed by later processes. Transported and rotated, large and small clasts of target sediments, and intervals of fluidized sands indicate that seismic shaking fractured and partially fluidized the Cretaceous and Paleogene target sediments, which led to their inward transport by collapse and lateral spreading toward the transient crater. The succeeding inward seawater-resurge flow quickly overtook and interacted with the lateral spreading, further facilitating sediment transport across the brim and into the transient crater. Variations in the cohesion and relative depth of the target sediments controlled their degree of disaggregation and redistribution during these events. Melt clasts and shocked and unshocked rock clasts in the resurge sediments indicate fallout from the ejecta curtain and plume. Basal parautochthonous remnant sections of target Cretaceous sediments in the brim thin toward the collapsed transient crater. Overlying seawater-resurge deposits consist primarily of diamictons that vary laterally in thickness, and vertically and laterally in maximum grain size. After cessation of resurge flow and re-establishment of pre-impact sea level, sandy sediment gravity flows moved from the margin to the center of the partially filled impact structure (shelf basin). The uppermost unit consists of stratified sediments deposited from suspension. Postimpact clayey silts cap the crater fill and record the return to shelf sedimentation at atypically large paleodepths within the shelf basin. An unresolved question involves a section of gravel and sand that overlies Neoproterozoic granite in the inner part of the brim in one core hole. This section may represent previously unrecognized, now parautochthonous Cretaceous sediments lying nonconformably above basement granite, or it may represent target sediments that were moved significant distances by lateral spreading above basement rocks or above a granite megaclast from the overturned flap. The Chesapeake Bay impact structure is perhaps the best documented example of the small group of multilayer, marine-target impacts formed in continental shelves or beneath epeiric seas.
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Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca (Melaleuca quinquenervia) and Old World climbing fern (Lygodium microphyllum), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).
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Pseudomorphic replacement of primary burbankite by an assemblage of ancylite, strontianite, and barite is the result of interaction with late-stage hydrothermal fluids that added Sr, Ba, S, F, and REE, analogous to the replacement processes described for some carbonatite complexes of Russia's Kola Peninsula. Carbon and oxygen stable isotope ratios indicate that the primary carbonatite mineralogy experienced degassing/pneumatolysis and alteration by fluids of variable temperature, CO2/H2O ratios, and/or meteoric water content. Isotopic differences of matrix calcite between Group 1 carbonatites (avg. δ13C = −7.3‰; δ18O = 9.1‰) and Group 2 carbonatites (avg. δ13C = −9.9‰; δ18O = 10.2‰) are consistent with loss of CO2 during degassing. The open-system alteration of burbankite caused a pronounced positive δ18O-shift in bulk ancylite pseudomorphs (δ18O: 14.3–25.7‰) relative to matrix calcite (δ18O: 8.7–11.2‰). Oxygen isotope compositions of biotite (δ18O: 4.5–5.9‰) and K-feldspar (δ18O: 7.3–7.9‰) in unoxidized carbonatite are typical of primary magmatic silicates and suggest that fluids responsible for the burbankite-to-ancylite conversion remained predominantly magmatic (carbohydrothermal). Concomitant increases toward the surface in 13C and 18O, oxidation, matrix carbonate dissolution, and the replacement of REE carbonates (ancylite, carbocernaite, and burbankite) by Ca-REE fluorocarbonates (bastnäsite, parisite, synchysite) suggest interaction with late-stage, low temperature (<250 °C) fluids characterized by lower CO2/H2O ratios, and an increasing meteoric water component. The first 40Ar/39Ar ages from carbonatite-hosted biotite and K-feldspar at the BLAC are between 51.45 ± 0.08 and 51.89 ± 0.14 Ma. Although carbonatite is commonly observed as the final intrusive phase in alkaline igneous complexes, relative-age relationships and previously published geochronology for Bear Lodge rocks indicate that alkaline silicate magmatism both preceded and followed carbonatite emplacement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2018.11.030","usgsCitation":"Andersen, A.K., Larson, P.B., and Cosca, M.A., 2019, C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA: LITHOS, v. 324-324, p. 640-660, https://doi.org/10.1016/j.lithos.2018.11.030.","productDescription":"21 p.","startPage":"640","endPage":"660","ipdsId":"IP-097912 ","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":370516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bear Lodge alkaline complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.79721069335938,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.40827836571936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"324-324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":778124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Peter B.","contributorId":22645,"corporation":false,"usgs":true,"family":"Larson","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":778125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":778126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204970,"text":"70204970 - 2019 - Overview of spirit microscopic imager results","interactions":[],"lastModifiedDate":"2019-08-28T10:57:49","indexId":"70204970","displayToPublicDate":"2018-11-28T14:22:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Overview of spirit microscopic imager results","docAbstract":"This paper provides an overview of Mars Exploration Rover Spirit Microscopic Imager (MI) operations and the calibration, processing, and analysis of MI data. The focus of this overview is on the last five Earth years (2005–2010) of Spirit's mission in Gusev crater, supplementing the previous overview of the first 450 sols of the Spirit MI investigation. Updates to radiometric calibration using in‐flight data and improvements in high‐level processing are summarized. Released data products are described, and a table of MI observations, including target/feature names and associated data sets, is appended. The MI observed natural and disturbed exposures of rocks and soils as well as magnets and other rover hardware. These hand‐lens‐scale observations have provided key constraints on interpretations of the formation and geologic history of features, rocks, and soils examined by Spirit. MI images complement observations by other Spirit instruments, and together show that impact and volcanic processes have dominated the origin and evolution of the rocks in Gusev crater, with aqueous activity indicated by the presence of silica‐rich rocks and sulfate‐rich soils. The textures of some of the silica‐rich rocks are similar to terrestrial hot spring deposits, and observations of subsurface cemented layers indicate recent aqueous mobilization of sulfates in places. Wind action has recently modified soils and abraded many of the rocks imaged by the MI, as observed at other Mars landing sites.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JE005774","usgsCitation":"Herkenhoff, K., Squyres, S., Arvidson, R.E., Cole, S.B., Sullivan, R., Yingst, A., Cabrol, N., Lee, E., Richie, J., Sucharski, R.M., Calef, F.J., Bell, J., Chapman, M., Geissler, P., Edgar, L.A., Franklin, B., Hurowitz, J.A., Jensen, E., Johnson, J.R., Kirk, R.L., Lanagan, P., Mullins, K., Leff, C., Maki, J., Redding, B.L., Rice, M., Sims, M.H., Spanovich, N., Soderblom, L.A., Sunda, A., Springer, R., and Vaughan, A., 2019, Overview of spirit microscopic imager results: Journal of Geophysical Research E: Planets, v. 124, no. 2, p. 528-584, https://doi.org/10.1029/2018JE005774.","productDescription":"57 p.","startPage":"528","endPage":"584","ipdsId":"IP-087430","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468048,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/633773","text":"External Repository"},{"id":367004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gusev Crater, Mars","volume":"124","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Squyres, Steve W","contributorId":218471,"corporation":false,"usgs":false,"family":"Squyres","given":"Steve W","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arvidson, Raymond E.","contributorId":106626,"corporation":false,"usgs":false,"family":"Arvidson","given":"Raymond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":769334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Shoshanna B","contributorId":218473,"corporation":false,"usgs":false,"family":"Cole","given":"Shoshanna","email":"","middleInitial":"B","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Rob","contributorId":218474,"corporation":false,"usgs":false,"family":"Sullivan","given":"Rob","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yingst, Aileen","contributorId":172313,"corporation":false,"usgs":false,"family":"Yingst","given":"Aileen","email":"","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":769337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cabrol, Nathalie","contributorId":218475,"corporation":false,"usgs":false,"family":"Cabrol","given":"Nathalie","affiliations":[{"id":39853,"text":"NASA Ames Research Center/SETI Institute","active":true,"usgs":false}],"preferred":false,"id":769338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lee, Ella 0000-0001-6144-7197 elee@usgs.gov","orcid":"https://orcid.org/0000-0001-6144-7197","contributorId":218476,"corporation":false,"usgs":true,"family":"Lee","given":"Ella","email":"elee@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richie, Janet 0000-0003-4151-1010","orcid":"https://orcid.org/0000-0003-4151-1010","contributorId":206347,"corporation":false,"usgs":true,"family":"Richie","given":"Janet","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769329,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sucharski, Robert M. bsucharski@usgs.gov","contributorId":5051,"corporation":false,"usgs":true,"family":"Sucharski","given":"Robert","email":"bsucharski@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":769601,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calef, Fred J.","contributorId":146331,"corporation":false,"usgs":false,"family":"Calef","given":"Fred","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":769341,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bell, James F. 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