Aeolian processes are important drivers of ecosystem dynamics in drylands, and important feedbacks exist among aeolian—hydrological processes and vegetation. The trapping of wind‐borne sediments by vegetation canopies may result in changes in soil properties beneath the vegetation, which, in turn, can alter hydrological and biogeochemical processes. Despite the relevance of aeolian transport to ecosystem dynamics, the interactions between aeolian transport and vegetation in shaping dryland landscapes where sediment distribution is altered by relatively rapid changes in vegetation composition such as shrub encroachment, are not well understood. Here, we used a computational fluid dynamics modelling framework to investigate the sediment trapping efficiencies of vegetation canopies commonly found in a shrub‐grass ecotone in the Chihuahuan Desert (New Mexico, USA) and related the results to spatial heterogeneity in soil texture and infiltration measured in the field. The vegetation structures were created using a computer‐aided design software, with inherent canopy porosities, which were derived using Light Detection and Ranging (LiDAR) measurements of plant canopies. Results show that considerable heterogeneity in infiltration and soil grain size distribution exist between the microsites, with higher infiltration and coarser soil texture under shrubs. Numerical simulations further indicate that the differential trapping of canopies might contribute to the observed heterogeneity in soil texture. In the early stages of encroachment, the shrub canopies, by trapping coarser particles more efficiently, might maintain higher infiltration rates leading to faster development of the microsites with enhanced ecological productivity, which might provide positive feedbacks to shrub encroachment.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1986","usgsCitation":"Gonzales, H.B., Ravi, S., Li, J., and Sankey, J.B., 2018, Ecohydrological implications of aeolian sediment trapping by sparse vegetation in drylands: Ecohydrology, v. 11, no. 7, p. 1-11, https://doi.org/10.1002/eco.1986.","productDescription":"e1986; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-093901","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":354650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-30","publicationStatus":"PW","scienceBaseUri":"5b155d73e4b092d9651e1afc","contributors":{"authors":[{"text":"Gonzales, Howell B.","contributorId":202737,"corporation":false,"usgs":false,"family":"Gonzales","given":"Howell","email":"","middleInitial":"B.","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":736877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ravi, Sujith","contributorId":202738,"corporation":false,"usgs":false,"family":"Ravi","given":"Sujith","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":736878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Junran","contributorId":202740,"corporation":false,"usgs":false,"family":"Li","given":"Junran","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":736879,"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":736876,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197378,"text":"70197378 - 2018 - Exposure-related effects of Zequanox on juvenile lake sturgeon (Acipenser fulvescens) and lake trout (Salvelinus namaycush)","interactions":[],"lastModifiedDate":"2018-05-31T14:55:13","indexId":"70197378","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exposure-related effects of Zequanox on juvenile lake sturgeon (Acipenser fulvescens) and lake trout (Salvelinus namaycush)","title":"Exposure-related effects of Zequanox on juvenile lake sturgeon (Acipenser fulvescens) and lake trout (Salvelinus namaycush)","docAbstract":"The environmental fate, persistence, and non-target animal impacts of traditional molluscicides for zebra, Dreissena polymorpha, and quagga, D. bugensis, mussel control led to the development of the biomolluscicide Zequanox. Although previous research has demonstrated the specificity of Zequanox, one study indicated sensitivity of salmonids and lake sturgeon, Acipenser fulvescens, following non-label compliant exposures to Zequanox. This study was conducted to evaluate sublethal and lethal impacts of Zequanox exposure on juvenile lake sturgeon and lake trout, Salvelinus namaycush, following applications that were conducted in a manner consistent with the Zequanox product label. Fish were exposed to 50 or 100 mg/L of Zequanox as active ingredient for 8 h and then held for 33 d to evaluate latent impacts. No acute mortality was observed in either species; however, significant latent mortality (P < 0.01, df = 9; 46.2%) was observed in lake trout that were exposed to the highest dose of Zequanox. Statistically significant (P < 0.03, df = 9), but biologically minimal differences were observed in the weight (range 20.17 to 21.49 g) of surviving lake sturgeon at the termination of the 33 d post-exposure observation period. Statistically significant (P < 0.05, df = 9) and biologically considerable differences were observed in the weight (range 6.19 to 9.55 g) of surviving lake trout at the termination of the 33 d post-exposure observation period. Histologic evaluation of lake trout gastrointestinal tracts suggests that the mode of action in lake trout is different from the mode of action that induces zebra and quagga mussel mortality. Further research could determine the sensitivity of other salmonid species to Zequanox and determine if native fish will avoid Zequanox treated water.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2018.9.2.09","collaboration":".","usgsCitation":"Luoma, J.A., Severson, T.J., Wise, J.K., and Barbour, M., 2018, Exposure-related effects of Zequanox on juvenile lake sturgeon (Acipenser fulvescens) and lake trout (Salvelinus namaycush): Management of Biological Invasions, v. 9, no. 2, p. 163-175, https://doi.org/10.3391/mbi.2018.9.2.09.","productDescription":"13 p.","startPage":"163","endPage":"175","ipdsId":"IP-090152","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468716,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2018.9.2.09","text":"Publisher Index Page"},{"id":437888,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23ZGT","text":"USGS data release","linkHelpText":"Exposure-related effects of Zequanox on juvenile lake sturgeon (Acipenser fulvescens) and lake trout (Salvelinus namaycush) Data"},{"id":354644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d71e4b092d9651e1af2","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Jeremy K. 0000-0003-0184-6959 jwise@usgs.gov","orcid":"https://orcid.org/0000-0003-0184-6959","contributorId":5009,"corporation":false,"usgs":true,"family":"Wise","given":"Jeremy","email":"jwise@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbour, Matthew T. 0000-0002-0095-9188 mbarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-0095-9188","contributorId":195580,"corporation":false,"usgs":true,"family":"Barbour","given":"Matthew","email":"mbarbour@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197385,"text":"70197385 - 2018 - Habitat selection, movement patterns, and hazards encountered by northern leopard frogs (Lithobates pipiens) in an agricultural landscape","interactions":[],"lastModifiedDate":"2018-05-31T14:57:37","indexId":"70197385","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat selection, movement patterns, and hazards encountered by northern leopard frogs (Lithobates pipiens) in an agricultural landscape","title":"Habitat selection, movement patterns, and hazards encountered by northern leopard frogs (Lithobates pipiens) in an agricultural landscape","docAbstract":"Telemetry data for 59 Northern Leopard Frogs (Lithobates pipiens) breeding in ponds in Houston and Winona Counties, MN; 2001-2002. Agricultural intensification is causing declines in many wildlife species, including Northern Leopard Frogs (Lithobates pipiens). Specific information about frog movements, habitat selection, and sources of mortality can be used to inform conservation-focused land management and acquisition. We studied Northern Leopard Frogs in southeastern Minnesota, part of the Driftless Area ecoregion, characterized by hills and valleys and a mix of agriculture, forests, small towns and farmsteads. In this area, small farm ponds, originally built to control soil erosion are used by the species for breeding and wintering in addition to riparian wetlands. But, this agricultural landscape may be hazardous for frogs moving between breeding, feeding, and wintering habitats. We surgically implanted transmitters into the peritoneal cavity of 59 Northern Leopard Frogs and tracked them from May to October 2001-2002. The total distance traveled by radio-tagged frogs ranged from 12 to 3316 m, the 95% home range averaged 5.3 ± 1.2 (SE) ha, and the 50% core area averaged 1.05 ± 0.3 (SE) ha. As expected, Northern Leopard Frogs selected wetlands over all other land cover classes and row crops were generally avoided at all levels of selection. Only a few tracked frogs were successful at dispersing (n = 6). Most frogs attempting to disperse (n =31) ended up missing (n = 14), died due to mowing (n = 8), or were recorded as transmitter failure (n = 2) or unknown mortalities (n = 1). For the conservation of Northern Leopard Frogs in this agricultural setting, we must consider both the aquatic and the terrestrial needs of this species. Conservation agencies that restore, manage, and acquire wetlands should consider the hazards posed by land uses adjacent to frog breeding and wintering sites and plan for movement corridors between these locations. For example, grasslands that are mowed or hayed between April and October in the north central U.S. and are adjacent to wetlands, pose a direct threat to frogs because these cultivated grasslands are primary locations for summer occupancy. When conservation land managers are selecting sites for acquisition or restoration they should avoid investments that will situate the wetland adjacent to heavily travelled roads and agricultural lands likely to be mowed or hayed. Increasing habitat amount and quality at amphibian breeding, feeding and wintering sites should reduce the energy required and hazards associated with moving long distances. Large, diverse wetlands probably provide all of the requirements needed by Northern Leopard Frogs for survival including food, shelter, breeding and overwintering areas.","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Knutson, M.G., Herner-Thogmartin, J., Thogmartin, W.E., Kapfer, J.M., and Nelson, J.C., 2018, Habitat selection, movement patterns, and hazards encountered by northern leopard frogs (Lithobates pipiens) in an agricultural landscape: Herpetological Conservation and Biology, v. 13, no. 1, p. 113-130.","productDescription":"18 p.","startPage":"113","endPage":"130","ipdsId":"IP-085717","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":354645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354643,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org10.5066/F7930S4R"},{"id":354629,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol13_issue1.html"}],"country":"United States","state":"Minnesota","county":"Houston County, Winona County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.0379638671875,\n 43.375108633273086\n ],\n [\n -91.08489990234375,\n 43.375108633273086\n ],\n [\n -91.08489990234375,\n 44.319918120477425\n ],\n [\n -92.0379638671875,\n 44.319918120477425\n ],\n [\n -92.0379638671875,\n 43.375108633273086\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d71e4b092d9651e1af0","contributors":{"authors":[{"text":"Knutson, Melinda G.","contributorId":205325,"corporation":false,"usgs":false,"family":"Knutson","given":"Melinda","email":"","middleInitial":"G.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":736941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herner-Thogmartin, Jennifer H.","contributorId":205326,"corporation":false,"usgs":false,"family":"Herner-Thogmartin","given":"Jennifer H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":736942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kapfer, Joshua M.","contributorId":176248,"corporation":false,"usgs":false,"family":"Kapfer","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":736943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, John C. 0000-0002-7105-0107 jcnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-7105-0107","contributorId":149361,"corporation":false,"usgs":true,"family":"Nelson","given":"John","email":"jcnelson@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197395,"text":"70197395 - 2018 - Effects of air temperature and discharge on Upper Mississippi River summer water temperatures","interactions":[],"lastModifiedDate":"2018-07-13T14:06:07","indexId":"70197395","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of air temperature and discharge on Upper Mississippi River summer water temperatures","docAbstract":"Recent interest in the potential effects of climate change has prompted studies of air temperature and precipitation associations with water temperatures in rivers and streams. We examined associations between summer surface water temperatures and both air temperature and discharge for 5 reaches of the Upper Mississippi River during 1994–2011. Water–air temperature associations at a given reach approximated 1:1 when estimated under an assumption of reach independence but declined to approximately 1:2 when water temperatures were permitted to covary among reaches and were also adjusted for upstream air temperatures. Estimated water temperature–discharge associations were weak. An apparently novel feature of this study is that of addressing changes in associations between water and air temperatures when both are correlated among reaches.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3278","usgsCitation":"Gray, B.R., Robertson, D.M., and Rogala, J.T., 2018, Effects of air temperature and discharge on Upper Mississippi River summer water temperatures: River Research and Applications, v. 34, no. 6, p. 506-515, https://doi.org/10.1002/rra.3278.","productDescription":"10 p.","startPage":"506","endPage":"515","ipdsId":"IP-074111","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437887,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76972TT","text":"USGS data release","linkHelpText":"SAS code for analyzing water temperature data"},{"id":354642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.6806640625,\n 36.94989178681327\n ],\n [\n -89.033203125,\n 36.94989178681327\n ],\n [\n -89.033203125,\n 44.715513732021336\n ],\n [\n -92.6806640625,\n 44.715513732021336\n ],\n [\n -92.6806640625,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-19","publicationStatus":"PW","scienceBaseUri":"5b155d70e4b092d9651e1aec","contributors":{"authors":[{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":204668,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736986,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736987,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197376,"text":"70197376 - 2018 - Managing salinity in Upper Colorado River Basin streams: Selecting catchments for sediment control efforts using watershed characteristics and random forests models","interactions":[],"lastModifiedDate":"2018-05-31T10:52:21","indexId":"70197376","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Managing salinity in Upper Colorado River Basin streams: Selecting catchments for sediment control efforts using watershed characteristics and random forests models","docAbstract":"Elevated concentrations of dissolved-solids (salinity) including calcium, sodium, sulfate, and chloride, among others, in the Colorado River cause substantial problems for its water users. Previous efforts to reduce dissolved solids in upper Colorado River basin (UCRB) streams often focused on reducing suspended-sediment transport to streams, but few studies have investigated the relationship between suspended sediment and salinity, or evaluated which watershed characteristics might be associated with this relationship. Are there catchment properties that may help in identifying areas where control of suspended sediment will also reduce salinity transport to streams? A random forests classification analysis was performed on topographic, climate, land cover, geology, rock chemistry, soil, and hydrologic information in 163 UCRB catchments. Two random forests models were developed in this study: one for exploring stream and catchment characteristics associated with stream sites where dissolved solids increase with increasing suspended-sediment concentration, and the other for predicting where these sites are located in unmonitored reaches. Results of variable importance from the exploratory random forests models indicate that no simple source, geochemical process, or transport mechanism can easily explain the relationship between dissolved solids and suspended sediment concentrations at UCRB monitoring sites. Among the most important watershed characteristics in both models were measures of soil hydraulic conductivity, soil erodibility, minimum catchment elevation, catchment area, and the silt component of soil in the catchment. Predictions at key locations in the basin were combined with observations from selected monitoring sites, and presented in map-form to give a complete understanding of where catchment sediment control practices would also benefit control of dissolved solids in streams.
","language":"English","publisher":"MDPI","doi":"10.3390/w10060676","usgsCitation":"Tillman, F.D., Anning, D., Heilman, J.A., Buto, S.G., and Miller, M.P., 2018, Managing salinity in Upper Colorado River Basin streams: Selecting catchments for sediment control efforts using watershed characteristics and random forests models: Water, v. 10, no. 6, Article 676; , https://doi.org/10.3390/w10060676.","productDescription":"Article 676; ","ipdsId":"IP-082147","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":460911,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10060676","text":"Publisher Index Page"},{"id":354625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112,\n 36.5\n ],\n [\n -106,\n 36.5\n ],\n [\n -106,\n 44\n ],\n [\n -112,\n 44\n ],\n [\n -112,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-24","publicationStatus":"PW","scienceBaseUri":"5b155d71e4b092d9651e1af4","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. 0000-0002-4470-3387","orcid":"https://orcid.org/0000-0002-4470-3387","contributorId":202783,"corporation":false,"usgs":true,"family":"Anning","given":"David W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heilman, Julian A. 0000-0002-2987-4057 jahr@usgs.gov","orcid":"https://orcid.org/0000-0002-2987-4057","contributorId":202192,"corporation":false,"usgs":true,"family":"Heilman","given":"Julian","email":"jahr@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736918,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197394,"text":"70197394 - 2018 - Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal","interactions":[],"lastModifiedDate":"2018-05-31T14:50:00","indexId":"70197394","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal","docAbstract":"The American pika is a thermally sensitive, alpine lagomorph species. Recent climate-associated population extirpations and genetic signatures of reduced population sizes range-wide indicate the viability of this species is sensitive to climate change. To test for potential adaptive responses to climate stress, we sampled pikas along two elevational gradients (each ~470 to 1640 m) and employed three outlier detection methods, BAYESCAN, LFMM, and BAYPASS, to scan for genotype-environment associations in samples genotyped at 30,763 SNP loci. We resolved 173 loci with robust evidence of natural selection detected by either two independent analyses or replicated in both transects. A BLASTN search of these outlier loci revealed several genes associated with metabolic function and oxygen transport, indicating natural selection from thermal stress and hypoxia. We also found evidence of directional gene flow primarily downslope from large high-elevation populations and reduced gene flow at outlier loci, a pattern suggesting potential impediments to the upward elevational movement of adaptive alleles in response to contemporary climate change. Finally, we documented evidence of reduced genetic diversity associated the south-facing transect and an increase in corticosterone stress levels associated with inbreeding. This study suggests the American pika is already undergoing climate-associated natural selection at multiple genomic regions. Further analysis is needed to determine if the rate of climate adaptation in the American pika and other thermally sensitive species will be able to keep pace with rapidly changing climate conditions.","language":"English","publisher":"Wiley","doi":"10.1111/mec.14701","usgsCitation":"Waterhouse, M.D., Erb, L.P., Beever, E., and Russello, M.A., 2018, Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal: Molecular Ecology, v. 27, no. 11, p. 2512-2528, https://doi.org/10.1111/mec.14701.","productDescription":"17 p.","startPage":"2512","endPage":"2528","ipdsId":"IP-090154","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":354641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.77197265625,\n 47.010225655683485\n ],\n [\n -119.44335937499999,\n 47.010225655683485\n ],\n [\n -119.44335937499999,\n 49.15296965617042\n ],\n [\n -123.77197265625,\n 49.15296965617042\n ],\n [\n -123.77197265625,\n 47.010225655683485\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-15","publicationStatus":"PW","scienceBaseUri":"5b155d71e4b092d9651e1aee","contributors":{"authors":[{"text":"Waterhouse, Matthew D.","contributorId":191666,"corporation":false,"usgs":false,"family":"Waterhouse","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":736982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erb, Liesl P.","contributorId":205335,"corporation":false,"usgs":false,"family":"Erb","given":"Liesl","email":"","middleInitial":"P.","affiliations":[{"id":37083,"text":"Departments of Biology and Environmental Studies, Warren Wilson College","active":true,"usgs":false}],"preferred":false,"id":736983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":147685,"corporation":false,"usgs":true,"family":"Beever","given":"Erik A.","email":"ebeever@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":736981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russello, Michael A.","contributorId":205336,"corporation":false,"usgs":false,"family":"Russello","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":37084,"text":"Department of Biology, University of British Columbia, Okanagan Campus","active":true,"usgs":false}],"preferred":false,"id":736984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197370,"text":"70197370 - 2018 - Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept","interactions":[],"lastModifiedDate":"2022-10-31T16:09:43.898412","indexId":"70197370","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept","docAbstract":"Under-ice discharge is estimated using open-water reference hydrographs; however, the ratings for ice-affected sites are generally qualified as poor. The U.S. Geological Survey (USGS), in collaboration with the Colorado Water Conservation Board, conducted a proof-of-concept to develop an alternative method for computing under-ice discharge using hydroacoustics and the Probability Concept.
The study site was located south of Minturn, Colorado (CO), USA, and was selected because of (1) its proximity to the existing USGS streamgage 09064600 Eagle River near Minturn, CO, and (2) its ease-of-access to verify discharge using a variety of conventional methods. From late September 2014 to early March 2015, hydraulic conditions varied from open water to under ice. These temporal changes led to variations in water depth and velocity. Hydroacoustics (tethered and uplooking acoustic Doppler current profilers and acoustic Doppler velocimeters) were deployed to measure the vertical-velocity profile at a singularly important vertical of the channel-cross section. Because the velocity profile was non-standard and cannot be characterized using a Power Law or Log Law, velocity data were analyzed using the Probability Concept, which is a probabilistic formulation of the velocity distribution. The Probability Concept-derived discharge was compared to conventional methods including stage-discharge and index-velocity ratings and concurrent field measurements; each is complicated by the dynamics of ice formation, pressure influences on stage measurements, and variations in cross-sectional area due to ice formation.
No particular discharge method was assigned as truth. Rather one statistical metric (Kolmogorov-Smirnov; KS), agreement plots, and concurrent measurements provided a measure of comparability between various methods. Regardless of the method employed, comparisons between each method revealed encouraging results depending on the flow conditions and the absence or presence of ice cover.
For example, during lower discharges dominated by under-ice and transition (intermittent open-water and under-ice) conditions, the KS metric suggests there is not sufficient information to reject the null hypothesis and implies that the Probability Concept and index-velocity rating represent similar distributions. During high-flow, open-water conditions, the comparisons are less definitive; therefore, it is important that the appropriate analytical method and instrumentation be selected. Six conventional discharge measurements were collected concurrently with Probability Concept-derived discharges with percent differences (%) of −9.0%, −21%, −8.6%, 17.8%, 3.6%, and −2.3%.
This proof-of-concept demonstrates that riverine discharges can be computed using the Probability Concept for a range of hydraulic extremes (variations in discharge, open-water and under-ice conditions) immediately after the siting phase is complete, which typically requires one day. Computing real-time discharges is particularly important at sites, where (1) new streamgages are planned, (2) river hydraulics are complex, and (3) shifts in the stage-discharge rating are needed to correct the streamflow record. Use of the Probability Concept does not preclude the need to maintain a stage-area relation. Both the Probability Concept and index-velocity rating offer water-resource managers and decision makers alternatives for computing real-time discharge for open-water and under-ice conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.04.073","usgsCitation":"Fulton, J.W., Henneberg, M.F., Mills, T.J., Kohn, M.S., Epstein, B., Hittle, E.A., Damschen, W., Laveau, C., Lambrecht, J.M., and Farmer, W.H., 2018, Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept: Journal of Hydrology, v. 562, p. 733-748, https://doi.org/10.1016/j.jhydrol.2018.04.073.","productDescription":"16 p.","startPage":"733","endPage":"748","ipdsId":"IP-072689","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":468717,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2018.04.073","text":"Publisher Index Page"},{"id":354617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Eagle River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.40344033567112,\n 39.55549288908489\n ],\n [\n -106.40344033567112,\n 39.552795008656176\n ],\n [\n -106.40000726492562,\n 39.552795008656176\n ],\n [\n -106.40000726492562,\n 39.55549288908489\n ],\n [\n -106.40344033567112,\n 39.55549288908489\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"562","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d72e4b092d9651e1af8","contributors":{"authors":[{"text":"Fulton, John W. 0000-0002-5335-0720 jwfulton@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":2298,"corporation":false,"usgs":true,"family":"Fulton","given":"John","email":"jwfulton@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henneberg, Mark F. 0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":173569,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":false,"id":736893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mills, Taylor J. 0000-0001-7252-0521 tmills@usgs.gov","orcid":"https://orcid.org/0000-0001-7252-0521","contributorId":4658,"corporation":false,"usgs":true,"family":"Mills","given":"Taylor","email":"tmills@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Epstein, Brian","contributorId":205319,"corporation":false,"usgs":false,"family":"Epstein","given":"Brian","email":"","affiliations":[],"preferred":false,"id":736896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hittle, Elizabeth A. 0000-0002-1771-7724 ehittle@usgs.gov","orcid":"https://orcid.org/0000-0002-1771-7724","contributorId":2038,"corporation":false,"usgs":true,"family":"Hittle","given":"Elizabeth","email":"ehittle@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Damschen, William C. wcdamsch@usgs.gov","contributorId":1610,"corporation":false,"usgs":true,"family":"Damschen","given":"William C.","email":"wcdamsch@usgs.gov","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Laveau, Christopher D. 0000-0002-4009-1889","orcid":"https://orcid.org/0000-0002-4009-1889","contributorId":205320,"corporation":false,"usgs":true,"family":"Laveau","given":"Christopher D.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":736899,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lambrecht, Jason M. jmlambre@usgs.gov","contributorId":4019,"corporation":false,"usgs":true,"family":"Lambrecht","given":"Jason","email":"jmlambre@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":736900,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736901,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198335,"text":"70198335 - 2018 - Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data","interactions":[],"lastModifiedDate":"2018-07-30T16:11:03","indexId":"70198335","displayToPublicDate":"2018-05-30T15:39:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data","docAbstract":"This study uses an airborne Light Detection and Ranging (LiDAR) survey, historical aerial photography and historical climate data to describe the character and dynamics of the Nogahabara Sand Dunes, a sub-Arctic dune field in interior Alaska’s discontinuous permafrost zone. The Nogahabara Sand Dunes consist of a 43-km2 area of active transverse and barchanoid dunes within a 3200-km2 area of vegetated dune and sand sheet deposits. The average dune height in the active portion of the dune field is 5.8 m, with a maximum dune height of 28 m. Dune spacing is variable with average crest-to-crest distances for select transects ranging from 66–132 m. Between 1952 and 2015, dunes migrated at an average rate of 0.52 m a−1. Dune movement was greatest between 1952 and 1978 (0.68 m a−1) and least between 1978 and 2015 (0.43 m a−1). Dunes migrated predominantly to the southeast; however, along the dune field margin, net migration was towards the edge of the dune field regardless of heading. Better constraining the processes controlling dune field dynamics at the Nogahabara dunes would provide information that can be used to model possible reactivation of more northerly dune fields and sand sheets in response to climate change, shifting fire regimes and permafrost thaw.
","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/rs10050792","usgsCitation":"Baughman, C., Jones, B.M., Bodony, K.L., Mann, D.H., Larsen, C.F., Himmelstoss, E., and Smith, J., 2018, Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data: Remote Sensing, v. 10, no. 5, p. 1-19, https://doi.org/10.3390/rs10050792.","productDescription":"Article 792; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-082492","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468719,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10050792","text":"Publisher Index Page"},{"id":356010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-05-19","publicationStatus":"PW","scienceBaseUri":"5b6fc444e4b0f5d57878ea3b","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":741101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodony, Karin L.","contributorId":206563,"corporation":false,"usgs":false,"family":"Bodony","given":"Karin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":741125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mann, Daniel H.","contributorId":67010,"corporation":false,"usgs":true,"family":"Mann","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":741126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larsen, Christopher F.","contributorId":147408,"corporation":false,"usgs":false,"family":"Larsen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":741127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Himmelstoss, Emily A. ehimmelstoss@usgs.gov","contributorId":2508,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily A.","email":"ehimmelstoss@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":741128,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Jeremy","contributorId":62919,"corporation":false,"usgs":true,"family":"Smith","given":"Jeremy","affiliations":[],"preferred":false,"id":741129,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200590,"text":"70200590 - 2018 - The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska","interactions":[],"lastModifiedDate":"2018-10-25T11:50:24","indexId":"70200590","displayToPublicDate":"2018-05-30T11:50:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska","docAbstract":"The youngest part of the Farewell terrane in interior Alaska (USA) is the enigmatic Devonian–Cretaceous Mystic subterrane. New U-Pb detrital zircon, fossil, geochemical, neodymium isotopic, and petrographic data illuminate the origin of the rocks of this subterrane. The Devonian–Permian Sheep Creek Formation yielded youngest detrital zircons of Devonian age, major detrital zircon age probability peaks between ca. 460 and 405 Ma, and overall age spectra like those from the underlying Dillinger subterrane. Samples are sandstones rich in sedimentary lithic clasts, and differ from approximately coeval strata to the east that have abundant volcanic lithic clasts and late Paleozoic detrital zircons. The Permian Mount Dall conglomerate has mainly carbonate and chert clasts and yielded youngest detrital zircons of latest Pennsylvanian age. Permian quartz-carbonate sandstone in the northern Farewell terrane yielded abundant middle to late Permian detrital zircons.
Late Triassic–Early Jurassic mafic igneous rocks occur in the central and eastern Mystic subterrane. New whole-rock geochemical and isotopic data indicate that magmas were rift related and derived from subcontinental mantle. Triassic and Jurassic strata have detrital zircon age spectra much like those of the Sheep Creek Formation, with major age populations between ca. 430 and 410 Ma. These rocks include conglomerate with clasts of carbonate ± chert and youngest detrital zircons of Late Triassic age and quartz-carbonate sandstone with youngest detrital zircons of Early Jurassic age. Lithofacies indicating highly productive oceanographic conditions (upwelling?) bracket the main part of the Mystic succession: Upper Devonian bedded barite and phosphatic Upper Devonian and Lower Jurassic rocks.
The youngest part of the Mystic subterrane consists of Lower Cretaceous (Valanginian–Aptian) limestone, calcareous sandstone, and related strata. These rocks are partly coeval with the oldest parts of the Kahiltna assemblage, an overlap succession exposed along the southern margin of the Farewell terrane.
Our findings support previous models suggesting that the Farewell terrane was proximal to the Alexander-Wrangellia-Peninsular composite terrane during the late Paleozoic, and further suggest that such proximity continued into (or recurred during) the Late Triassic–Early Jurassic. But middle to late Permian detrital zircons in northern Farewell require another source; the Yukon-Tanana terrane is one possibility.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01588.1","usgsCitation":"Dumoulin, J.A., Jones, J.V., Box, S.E., Bradley, D., Ayuso, R.A., and O’Sullivan, P.B., 2018, The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska: Geosphere, v. 14, no. 4, p. 1501-1543, https://doi.org/10.1130/GES01588.1.","productDescription":"43 p.","startPage":"1501","endPage":"1543","ipdsId":"IP-095640","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":468720,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01588.1","text":"Publisher Index Page"},{"id":437889,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7765DN7","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Detrital Zircon Grains, Whole Rock Major and Trace-element Geochemistry, and Whole Rock Isotopic Data from Selected Rocks from the Western Alaska Range, Medfra area, and Livengood area, Alaska"},{"id":358807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"14","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-30","publicationStatus":"PW","scienceBaseUri":"5c10a9abe4b034bf6a7e53b3","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":749662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Dwight 0000-0001-9116-5289 bradleyorchard2@gmail.com","orcid":"https://orcid.org/0000-0001-9116-5289","contributorId":2358,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","email":"bradleyorchard2@gmail.com","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":749664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Sullivan, Paul B.","contributorId":193544,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":749665,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237793,"text":"70237793 - 2018 - Tundra be dammed: Beaver colonization of the Arctic","interactions":[],"lastModifiedDate":"2022-10-24T15:32:03.784703","indexId":"70237793","displayToPublicDate":"2018-05-30T10:29:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Tundra be dammed: Beaver colonization of the Arctic","docAbstract":"Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293 km2) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14332","usgsCitation":"Tape, K.D., Jones, B.M., Arp, C.D., Nitze, I., and Grosse, G., 2018, Tundra be dammed: Beaver colonization of the Arctic: Global Change Biology, v. 24, no. 10, p. 4478-4488, https://doi.org/10.1111/gcb.14332.","productDescription":"11 p.","startPage":"4478","endPage":"4488","ipdsId":"IP-090358","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":468721,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://epic.awi.de/id/eprint/47723/1/Tape_etal_2018.pdf","text":"External Repository"},{"id":408648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lower Noatak River, Wulik, and Kivalina River watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.63101775418127,\n 68.8694953372669\n ],\n [\n -166.63101775418127,\n 66.85108524558379\n ],\n [\n -160.3609756043501,\n 66.85108524558379\n ],\n [\n -160.3609756043501,\n 68.8694953372669\n ],\n [\n -166.63101775418127,\n 68.8694953372669\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Tape, Ken D.","contributorId":297109,"corporation":false,"usgs":false,"family":"Tape","given":"Ken","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":855656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nitze, Ingemar","contributorId":298467,"corporation":false,"usgs":false,"family":"Nitze","given":"Ingemar","email":"","affiliations":[{"id":62783,"text":"Alfred Wegener Institute","active":true,"usgs":false}],"preferred":false,"id":855658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":855659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215708,"text":"70215708 - 2018 - Characterizing local and range wide variation in demography and adaptive capacity of a forest indicator species","interactions":[],"lastModifiedDate":"2021-01-28T16:12:48.29301","indexId":"70215708","displayToPublicDate":"2018-05-30T10:09:08","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"Characterizing local and range wide variation in demography and adaptive capacity of a forest indicator species","docAbstract":"The red-backed salamander (Plethodon cinereus) is considered an indicator of forest health. The range of the species covers much of the eastern and central US, and is often locally abundant where it occurs, primarily in deciduous forest. While there are expectations that changes in climate will result in changes in forest ecosystems, the ability of a forest indicator such as the red-backed salamanderto adapt to those changes, has not been assessed. We found that the red-backed salamander may have little adaptive capacity, but that changes in climate conditions may be buffered by salamander behavior, including its typical response to retreat underground during times of high temperature or during short-term drought. Effective conservation measures will likely need to increase the range of within-population climate tolerance in order for populations to persist locally.
","language":"English","publisher":"Northeast Climate Adaptation Science Center","usgsCitation":"Campbell Grant, E.H., 2018, Characterizing local and range wide variation in demography and adaptive capacity of a forest indicator species: Final Report, 15 p.","productDescription":"15 p.","ipdsId":"IP-098881","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":382762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382761,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://necsc.umass.edu/biblio/final-report-characterizing-local-and-range-wide-variation-demography-and-adaptive-capacity"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803175,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203040,"text":"70203040 - 2018 - Gas hydrate quantification using full-waveform inversion of sparse ocean-bottom seismic data: A case study from Green Canyon Block 955, Gulf of Mexico","interactions":[],"lastModifiedDate":"2019-04-15T10:46:45","indexId":"70203040","displayToPublicDate":"2018-05-30T09:29:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Gas hydrate quantification using full-waveform inversion of sparse ocean-bottom seismic data: A case study from Green Canyon Block 955, Gulf of Mexico","docAbstract":"We present a case study of gas hydrate quantification using dense short-offset multichannel seismic (MCS) and sparse long-offset ocean-bottom-seismometer (OBS) data in lease block Green Canyon 955 (GC955), Gulf of Mexico (GOM), where the presence of gas hydrate was interpreted using logging while drilling (LWD) data acquired by the GOM Gas Hydrate Joint Industry Project Leg II expedition. We use frequency-domain full-waveform inversion (FWI) of seven OBS gathers to invert for a P-wave velocity model of an approximately 7 km long MCS profile connecting two LWD sites, GC955-H and GC955-Q. We build the starting model for FWI using traveltime inversion (TI) of the MCS and OBS data. In addition, we use the TI model for depth migrating the MCS stack. At the LWD sites, we constrain the hydrate saturation (Sgh) using sonic and resistivity logs. Unfortunately, as is typical of seismic quantification problems, the FWI model resolution is not sufficient to extrapolate the LWD-based Sgh. Therefore, we apply Backus averaging to the sonic log, at 60 m wavelength, bringing it within approximately 8% of the FWI model and make the assumption that averaging the sonic log is same as redistributing the gas hydrate within the Backus wavelength. In this manner, instead of Sgh, the FWI model is able to estimate the total gas hydrate volume. In the end, we use the FWI model and the migrated stack to constrain the locations and bulk volumes of free gas and gas hydrate. Our results demonstrate that with careful processing, reasonable estimates on locations and bulk volumes of submarine gas hydrate accumulations can be achieved even with sparse seismic data that are not adequate for amplitude-based assessments.","language":"English","publisher":"SEG","doi":"10.1190/geo2017-0414.1","usgsCitation":"Wang, J., Jaiswal, P., Haines, S.S., Hart, P.E., and Wu, S., 2018, Gas hydrate quantification using full-waveform inversion of sparse ocean-bottom seismic data: A case study from Green Canyon Block 955, Gulf of Mexico: Geophysics, v. 83, no. 4, p. B167-B181, https://doi.org/10.1190/geo2017-0414.1.","productDescription":"15 p.","startPage":"B167","endPage":"B181","ipdsId":"IP-065223","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":362942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","volume":"83","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Jiliang","contributorId":214827,"corporation":false,"usgs":false,"family":"Wang","given":"Jiliang","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":760908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Priyank","contributorId":214828,"corporation":false,"usgs":false,"family":"Jaiswal","given":"Priyank","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":760909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":760910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Shiguo","contributorId":214829,"corporation":false,"usgs":false,"family":"Wu","given":"Shiguo","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":760911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196632,"text":"fs20183026 - 2018 - Groundwater quality in the shallow aquifers of the Monterey Bay, Salinas Valley, and adjacent highland areas, California","interactions":[],"lastModifiedDate":"2026-01-22T16:55:26.454677","indexId":"fs20183026","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3026","title":"Groundwater quality in the shallow aquifers of the Monterey Bay, Salinas Valley, and adjacent highland areas, California","docAbstract":"Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State’s groundwater quality and increases public access to groundwater-quality information. The shallow aquifers of the groundwater basins around Monterey Bay, the Salinas Valley, and the highlands adjacent to the Salinas Valley constitute one of the study units.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183026","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Burton, C.A., 2018, Groundwater quality in the shallow aquifers of the Monterey Bay, Salinas Valley, and adjacent highland areas, California (ver. 1.1, June 2018): U.S. Geological Survey Fact Sheet 2018–3026, 4 p., https://doi.org/10.3133/fs20183026.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-092656","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":354603,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3026/coverthb.jpg"},{"id":354604,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3026/fs20183026_v1.1.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3026 Version 1.1"},{"id":354756,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2018/3026/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Fact Sheet 2018-3026 Version History"}],"country":"United States","state":"California","otherGeospatial":"Monterey-Salinas Shallow Aquifer Study Unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.904296875,\n 36.53170884914869\n ],\n [\n -121.761474609375,\n 36.527294814546245\n ],\n [\n -121.58569335937501,\n 36.49638952000399\n ],\n [\n -121.5142822265625,\n 36.40359962073253\n ],\n [\n -121.4813232421875,\n 36.363798554158635\n ],\n [\n -121.33300781249999,\n 36.33282808737917\n ],\n [\n -121.234130859375,\n 36.27085020723902\n ],\n [\n -121.17370605468749,\n 36.19995805932895\n ],\n [\n -121.08581542968751,\n 36.10237644873644\n ],\n [\n -121.01989746093749,\n 36.02688935430189\n ],\n [\n -120.94299316406249,\n 35.96911507577482\n ],\n [\n -120.88256835937499,\n 35.89795019335754\n ],\n [\n -120.80566406250001,\n 35.79999392988527\n ],\n [\n -120.89080810546875,\n 35.66622234103479\n ],\n [\n -120.8551025390625,\n 35.61488368245436\n ],\n [\n -120.6683349609375,\n 35.46961797120201\n ],\n [\n -120.56945800781249,\n 35.37113502280101\n ],\n [\n -120.465087890625,\n 35.37113502280101\n ],\n [\n -120.2838134765625,\n 35.37113502280101\n ],\n [\n -120.12451171875,\n 35.37561413174875\n ],\n [\n -120.0146484375,\n 35.44277092585766\n ],\n [\n -119.94323730468749,\n 35.46514408578589\n ],\n [\n -119.99267578124999,\n 35.53222622770337\n ],\n [\n -120.10253906249999,\n 35.59925232772949\n ],\n [\n -120.2838134765625,\n 35.755428369259626\n ],\n [\n -120.421142578125,\n 35.88905007936091\n ],\n [\n -120.50903320312501,\n 35.97356075349624\n ],\n [\n -120.673828125,\n 36.09349937380574\n ],\n [\n -120.80566406250001,\n 36.22211876039103\n ],\n [\n -120.94299316406249,\n 36.359374956015856\n ],\n [\n -121.06933593749999,\n 36.46988944681576\n ],\n [\n -121.55273437499999,\n 36.83127162140714\n ],\n [\n -121.61315917968749,\n 36.88840804313823\n ],\n [\n -121.72302246093749,\n 36.9806150652861\n ],\n [\n -121.84936523437499,\n 37.020098201368114\n ],\n [\n -121.9976806640625,\n 37.03325468997236\n ],\n [\n -122.06909179687501,\n 37.01132594307015\n ],\n [\n -122.1075439453125,\n 36.96306042436515\n ],\n [\n -122.0855712890625,\n 36.92793899776678\n ],\n [\n -121.9976806640625,\n 36.94989178681327\n ],\n [\n -121.92626953124999,\n 36.96306042436515\n ],\n [\n -121.86584472656251,\n 36.94989178681327\n ],\n [\n -121.8438720703125,\n 36.88401445049676\n ],\n [\n -121.8109130859375,\n 36.80928470205937\n ],\n [\n -121.8109130859375,\n 36.760891249565624\n ],\n [\n -121.83288574218749,\n 36.69044623523481\n ],\n [\n -121.8438720703125,\n 36.641977814705946\n ],\n [\n -121.8878173828125,\n 36.602299135790446\n ],\n [\n -121.9317626953125,\n 36.602299135790446\n ],\n [\n -121.915283203125,\n 36.56260003738545\n ],\n [\n -121.904296875,\n 36.53170884914869\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: June 2018; Version. 1.0: May 2018","publicComments":"Groundwater Ambient Monitoring and Assessment (GAMA) Program","contact":"Bats in the eastern U.S. are facing numerous threats and many species are in decline. Although several species of bats commonly roost in cliffs, little is known about use of cliffs for foraging and roosting. Because rock climbing is a rapidly growing sport and may cause disturbance to bats, our objectives were to examine use of cliff habitats by bats and to assess the effects of climbing on their activity. We used radio-telemetry to track small-footed bats (Myotis leibii) to day roosts, and Anabat SD2 detectors to compare bat activity between climbed and unclimbed areas of regularly climbed cliff faces, and between climbed and unclimbed cliffs. Four adult male small-footed bats were tracked to nine day roosts, all of which were in various types of crevices including five cliff face roosts (three on climbed and two on unclimbed faces). Bat activity was high along climbed cliffs and did not differ between climbed and unclimbed areas of climbed cliffs. In contrast, overall bat activity was significantly higher along climbed cliffs than unclimbed cliffs; species richness did not differ between climbed and unclimbed cliffs or areas. Lower activity along unclimbed cliffs may have been related to lower cliff heights and more clutter along these cliff faces. Due to limited access to unclimbed cliffs of comparable size to climbed cliffs, we could not thoroughly test the effects of climbing on bat foraging and roosting activity. However, the high overall use of climbed and unclimbed cliff faces for foraging and commuting that we observed suggests that cliffs may be important habitat for a number of bat species. Additional research on bats' use of cliff faces will improve our understanding of the factors that affect their use of this habitat including the impacts of climbing.
","language":"English","publisher":"American Geophysical Union","doi":"10.3996/032017-JFWM-020","usgsCitation":"Loeb, S.C., and Jodice, P.G., 2018, Activity of southeastern bats along sandstone cliffs used for rock climbing: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 255-265, https://doi.org/10.3996/032017-JFWM-020.","productDescription":"11 p.","startPage":"255","endPage":"265","ipdsId":"IP-084559","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/032017-jfwm-020","text":"Publisher Index Page"},{"id":354563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","county":"Morgan County","otherGeospatial":"Obed Wild and Scenic River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-84.7011,36.3709],[-84.7,36.3695],[-84.6893,36.3581],[-84.6462,36.309],[-84.6406,36.3026],[-84.6277,36.2884],[-84.6249,36.2852],[-84.6154,36.2747],[-84.6132,36.2724],[-84.6012,36.2754],[-84.5937,36.2771],[-84.5876,36.2666],[-84.5733,36.2669],[-84.5708,36.2501],[-84.5703,36.2483],[-84.5687,36.2419],[-84.5688,36.2369],[-84.5717,36.2333],[-84.574,36.2302],[-84.5678,36.2274],[-84.5633,36.2269],[-84.5552,36.2299],[-84.5523,36.2335],[-84.5132,36.219],[-84.5008,36.2143],[-84.4849,36.2087],[-84.4713,36.204],[-84.4698,36.1971],[-84.4687,36.193],[-84.4591,36.1893],[-84.4586,36.1843],[-84.4592,36.1816],[-84.4463,36.1728],[-84.4441,36.1696],[-84.4414,36.1636],[-84.4426,36.1578],[-84.445,36.1519],[-84.4485,36.1465],[-84.4498,36.1411],[-84.447,36.1383],[-84.4408,36.1364],[-84.43,36.1317],[-84.4267,36.1272],[-84.4251,36.1226],[-84.4203,36.1085],[-84.4141,36.1057],[-84.4067,36.1038],[-84.4016,36.1041],[-84.3959,36.1041],[-84.3931,36.1022],[-84.3931,36.1004],[-84.3858,36.0985],[-84.379,36.0952],[-84.3608,36.0696],[-84.3435,36.0507],[-84.3418,36.0493],[-84.347,36.048],[-84.3573,36.0441],[-84.3868,36.0214],[-84.3983,36.0156],[-84.4065,36.008],[-84.4185,36.0027],[-84.4461,35.9863],[-84.4564,35.9842],[-84.4672,35.9839],[-84.4774,35.9849],[-84.4888,35.9851],[-84.4939,35.9847],[-84.5169,35.9759],[-84.5288,35.9738],[-84.5374,35.9707],[-84.554,35.9645],[-84.5547,35.96],[-84.5543,35.9505],[-84.5765,35.9503],[-84.5844,35.9495],[-84.5907,35.9486],[-84.5969,35.9501],[-84.602,35.9524],[-84.6049,35.9515],[-84.6067,35.9456],[-84.609,35.9411],[-84.6159,35.9385],[-84.6194,35.934],[-84.6256,35.9336],[-84.6319,35.9305],[-84.6393,35.931],[-84.6433,35.9288],[-84.6462,35.9275],[-84.6502,35.928],[-84.653,35.9262],[-84.6566,35.9199],[-84.6611,35.9181],[-84.6703,35.9155],[-84.6749,35.9115],[-84.6795,35.9075],[-84.7201,35.9946],[-84.7268,36.0001],[-84.7896,36.057],[-84.7901,36.0583],[-84.7918,36.0602],[-84.7951,36.0666],[-84.8006,36.0784],[-84.8045,36.088],[-84.8055,36.0907],[-84.8113,36.0872],[-84.8147,36.0899],[-84.8152,36.0949],[-84.8197,36.0954],[-84.8214,36.0941],[-84.8231,36.0945],[-84.8249,36.0941],[-84.8278,36.0891],[-84.8324,36.0842],[-84.8597,36.1216],[-84.8625,36.1253],[-84.872,36.1381],[-84.8794,36.1409],[-84.8856,36.1455],[-84.8964,36.1474],[-84.9037,36.1511],[-84.9059,36.157],[-84.9018,36.1656],[-84.9005,36.1765],[-84.9078,36.1851],[-84.91,36.1897],[-84.9082,36.196],[-84.9126,36.2083],[-84.9114,36.2124],[-84.9033,36.22],[-84.8987,36.2227],[-84.8936,36.224],[-84.8918,36.2276],[-84.8905,36.2385],[-84.8876,36.2403],[-84.8842,36.2416],[-84.8829,36.248],[-84.8816,36.2593],[-84.8792,36.2679],[-84.8773,36.2819],[-84.872,36.2896],[-84.8646,36.2936],[-84.8543,36.2917],[-84.8413,36.287],[-84.8332,36.292],[-84.8234,36.2987],[-84.8171,36.2977],[-84.8138,36.294],[-84.808,36.2958],[-84.8023,36.2975],[-84.7943,36.2988],[-84.7919,36.3024],[-84.7918,36.3124],[-84.7854,36.3191],[-84.7864,36.3246],[-84.7858,36.326],[-84.7778,36.3268],[-84.7749,36.3299],[-84.7743,36.3344],[-84.7731,36.3349],[-84.7686,36.3339],[-84.7623,36.3307],[-84.7595,36.3311],[-84.756,36.3343],[-84.7537,36.3342],[-84.7497,36.3333],[-84.7474,36.3346],[-84.7394,36.3368],[-84.7405,36.3409],[-84.7443,36.35],[-84.7425,36.3541],[-84.7408,36.3541],[-84.734,36.3504],[-84.7317,36.3508],[-84.7283,36.3512],[-84.7265,36.3539],[-84.7322,36.3567],[-84.7327,36.3635],[-84.7303,36.3689],[-84.7228,36.3702],[-84.725,36.3752],[-84.7244,36.3766],[-84.7216,36.3761],[-84.7131,36.3706],[-84.7097,36.3683],[-84.7051,36.3682],[-84.7034,36.3695],[-84.7011,36.3709]]]},\"properties\":{\"name\":\"Morgan\",\"state\":\"TN\"}}]}","volume":"9","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-07","publicationStatus":"PW","scienceBaseUri":"5b155d74e4b092d9651e1b0e","contributors":{"authors":[{"text":"Loeb, Susan C.","contributorId":138944,"corporation":false,"usgs":false,"family":"Loeb","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":6762,"text":"U.S. Forest Service, La Grande, Oregon","active":true,"usgs":false}],"preferred":false,"id":736750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197346,"text":"70197346 - 2018 - Influence of climate on alpine stream chemistry and water sources","interactions":[],"lastModifiedDate":"2018-07-03T11:14:16","indexId":"70197346","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","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":"Influence of climate on alpine stream chemistry and water sources","docAbstract":"The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 1994 to 2015, to explore how the partitioning of water sources and associated hydrologic resilience change in response to climate. Our results indicate that four water sources are significant contributors to Andrews Creek, including snow, rain, soil water, and talus groundwater. Seasonal patterns in source‐water contributions reflected the seasonal hydrologic cycle, which is driven by the accumulation and melting of seasonal snowpack. Flushing of soil water had a large effect on stream chemistry during spring snowmelt, despite making only a small contribution to streamflow volume. Snow had a large influence on stream chemistry as well, contributing large amounts of water with low concentrations of weathering products. Interannual patterns in end‐member contributions reflected responses to drought and wet periods. Moderate and significant correlations exist between annual end‐member contributions and regional‐scale climate indices (the Palmer Drought Severity Index, the Palmer Hydrologic Drought Index, and the Modified Palmer Drought Severity Index). From water year 1994 to 2015, the percent contribution from the talus‐groundwater end member to Andrews Creek increased an average of 0.5% per year (p < 0.0001), whereas the percent contributions from snow plus rain decreased by a similar amount (p = 0.001). Our results show how water and solute sources in alpine environments shift in response to climate variability and highlight the role of talus groundwater and soil water in providing hydrologic resilience to the system.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13124","usgsCitation":"Foks, S., Stets, E.G., Singha, K., and Clow, D.W., 2018, Influence of climate on alpine stream chemistry and water sources: Hydrological Processes, v. 32, no. 13, p. 1993-2008, https://doi.org/10.1002/hyp.13124.","productDescription":"16 p.","startPage":"1993","endPage":"2008","ipdsId":"IP-090691","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":468725,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13124","text":"Publisher Index Page"},{"id":354581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","volume":"32","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-29","publicationStatus":"PW","scienceBaseUri":"5b155d74e4b092d9651e1b0c","contributors":{"authors":[{"text":"Foks, Sydney 0000-0002-7668-9735","orcid":"https://orcid.org/0000-0002-7668-9735","contributorId":205290,"corporation":false,"usgs":true,"family":"Foks","given":"Sydney","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736784,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197338,"text":"70197338 - 2018 - Diel habitat selection of largemouth bass following woody structure installation in Table Rock Lake, Missouri","interactions":[],"lastModifiedDate":"2018-05-30T11:44:47","indexId":"70197338","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Diel habitat selection of largemouth bass following woody structure installation in Table Rock Lake, Missouri","docAbstract":"Largemouth bass Micropterus salmoides (Lacepède) use of installed habitat structure was evaluated in a large Midwestern USA reservoir to determine whether or not these structures were used in similar proportion to natural habitats. Seventy largemouth bass (>380 mm total length) were surgically implanted with radio transmitters and a subset was relocated monthly during day and night for one year. The top habitat selection models (based on Akaike's information criterion) suggest largemouth bass select 2–4 m depths during night and 4–7 m during day, whereas littoral structure selection was similar across diel periods. Largemouth bass selected boat docks at twice the rate of other structures. Installed woody structure was selected at similar rates to naturally occurring complex woody structure, whereas both were selected at a higher rate than simple woody structure. The results suggest the addition of woody structure may concentrate largemouth bass and mitigate the loss of woody habitat in a large reservoir.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12266","usgsCitation":"Harris, J., Paukert, C.P., Bush, S., Allen, M., and Siepker, M., 2018, Diel habitat selection of largemouth bass following woody structure installation in Table Rock Lake, Missouri: Fisheries Management and Ecology, v. 25, no. 2, p. 107-115, https://doi.org/10.1111/fme.12266.","productDescription":"9 p.","startPage":"107","endPage":"115","ipdsId":"IP-083719","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Table Rock Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.2352294921875,\n 36.0624217151089\n ],\n [\n -92.3895263671875,\n 36.0624217151089\n ],\n [\n -92.3895263671875,\n 36.83566824724438\n ],\n [\n -94.2352294921875,\n 36.83566824724438\n ],\n [\n -94.2352294921875,\n 36.0624217151089\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-25","publicationStatus":"PW","scienceBaseUri":"5b155d75e4b092d9651e1b14","contributors":{"authors":[{"text":"Harris, J.M.","contributorId":42751,"corporation":false,"usgs":true,"family":"Harris","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":736806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":147821,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bush, S.C.","contributorId":205298,"corporation":false,"usgs":false,"family":"Bush","given":"S.C.","email":"","affiliations":[],"preferred":false,"id":736807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, M.J.","contributorId":205302,"corporation":false,"usgs":false,"family":"Allen","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":736808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siepker, Michael","contributorId":145583,"corporation":false,"usgs":false,"family":"Siepker","given":"Michael","email":"","affiliations":[],"preferred":false,"id":736809,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196064,"text":"pp1837A - 2018 - Geochemistry of groundwater in the eastern Snake River Plain aquifer, Idaho National Laboratory and vicinity, eastern Idaho","interactions":[],"lastModifiedDate":"2023-04-14T16:55:56.536311","indexId":"pp1837A","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"A","title":"Geochemistry of groundwater in the eastern Snake River Plain aquifer, Idaho National Laboratory and vicinity, eastern Idaho","docAbstract":"Nuclear research activities at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) in eastern Idaho produced radiochemical and chemical wastes that were discharged to the subsurface, resulting in detectable concentrations of some waste constituents in the eastern Snake River Plain (ESRP) aquifer. These waste constituents may pose risks to the water quality of the aquifer. In order to understand these risks to water quality the U.S. Geological Survey, in cooperation with the DOE, conducted a study of groundwater geochemistry to improve the understanding of hydrologic and chemical processes in the ESRP aquifer at and near the INL and to understand how these processes affect waste constituents in the aquifer.
Geochemistry data were used to identify sources of recharge, mixing of water, and directions of groundwater flow in the ESRP aquifer at the INL. The geochemistry data were analyzed from 167 sample sites at and near the INL. The sites included 150 groundwater, 13 surface-water, and 4 geothermal-water sites. The data were collected between 1952 and 2012, although most data collected at the INL were collected from 1989 to 1996. Water samples were analyzed for all or most of the following: field parameters, dissolved gases, major ions, dissolved metals, isotope ratios, and environmental tracers.
Sources of recharge identified at the INL were regional groundwater, groundwater from the Little Lost River (LLR) and Birch Creek (BC) valleys, groundwater from the Lost River Range, geothermal water, and surface water from the Big Lost River (BLR), LLR, and BC. Recharge from the BLR that may have occurred during the last glacial epoch, or paleorecharge, may be present at several wells in the southwestern part of the INL. Mixing of water at the INL primarily included mixing of surface water with groundwater from the tributary valleys and mixing of geothermal water with regional groundwater. Additionally, a zone of mixing between tributary valley water and regional groundwater, trending southwesterly, extended from near the northeastern boundary of the INL to the southern boundary of the INL. Groundwater flow directions for regional groundwater were southwesterly, and flow directions for tributary groundwater were southeasterly upon entering the ESRP, but eventually began to flow southwesterly in a direction parallel with regional groundwater.
Several discrepancies were identified from comparison of sources of recharge determined from geochemistry data and backward particle tracking with a groundwater-flow model. Some discrepancies observed in the particle tracking results included representation of recharge from BC near the north INL boundary, groundwater from the BC valley not extending far enough south, regional groundwater that extends too far west in the southern part of the INL, and no representation of recharge from geothermal water in model layer 1 or recharge from the BLR in the southwestern part of the INL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837A","collaboration":"DOE/ID-22246Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
We compare the thermophysical properties and particle sizes derived from the Mars Science Laboratory rover's Ground Temperature Sensor of the Bagnold dunes, specifically Namib dune, to those derived orbitally from Thermal Emission Imaging System, ultimately linking these measurements to ground truth particle sizes determined from Mars Hand Lens Imager images. In general, we find that all three datasets report consistent particle sizes for the Bagnold dunes (~110–350 μm and are within measurement and model uncertainties), indicating that particle sizes of homogeneous materials inferred from temperature measurements and thermophysical models are reliable. Furthermore, we examine the effects of two physical characteristics that could influence the modeled thermal inertia and particle sizes, including (1) fine‐scale (centimeter to meter scale) ripples and (2) thin layering of indurated/armored materials. To first order, we find that small‐scale ripples and thin (approximately centimeter scale) layers do not significantly affect the determination of bulk thermal inertia from orbital thermal data using a single nighttime temperature. Modeling of a layer of coarse or indurated material reveals that a thin layer (< ~5 mm; similar to what was observed by the Curiosity rover) would not significantly change the observed thermal properties of the surface and would be dominated by the properties of the underlying material. Thermal inertia and particle sizes of relatively homogeneous materials derived from nighttime orbital data should be considered as reliable, as long as there are no significant subpixel anisothermality effects (e.g., lateral mixing of multiple thermophysically distinct materials).
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JE005501","usgsCitation":"Edwards, C., Piqueux, S., Hamilton, V.E., Fergason, R.L., Herkenhoff, K., Vasavada, A.R., Bennett, K.A., Sacks, L., Lewis, K., and Smith, M.D., 2018, The thermophysical properties of the Bagnold Dunes, Mars: Ground truthing orbital data: Journal of Geophysical Research: Planets, v. 123, no. 5, p. 1307-1326, https://doi.org/10.1029/2017JE005501.","productDescription":"15 p.","startPage":"1307","endPage":"1326","ipdsId":"IP-085162","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017je005501","text":"Publisher Index Page"},{"id":355551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bagnold Dunes, Mars","volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e584e4b060350a15d1c0","contributors":{"authors":[{"text":"Edwards, Christopher S.","contributorId":206168,"corporation":false,"usgs":false,"family":"Edwards","given":"Christopher S.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":739692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":739693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Victoria E.","contributorId":206169,"corporation":false,"usgs":false,"family":"Hamilton","given":"Victoria","email":"","middleInitial":"E.","affiliations":[{"id":37270,"text":"Southwest Research Institute, Boulder, Colo.","active":true,"usgs":false}],"preferred":false,"id":739694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fergason, Robin L. 0000-0002-2044-1714","orcid":"https://orcid.org/0000-0002-2044-1714","contributorId":206167,"corporation":false,"usgs":true,"family":"Fergason","given":"Robin","email":"","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":739695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vasavada, Ashwin R.","contributorId":200409,"corporation":false,"usgs":false,"family":"Vasavada","given":"Ashwin","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":739696,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bennett, Kristen A.","contributorId":206171,"corporation":false,"usgs":false,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":739697,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sacks, Leah","contributorId":206172,"corporation":false,"usgs":false,"family":"Sacks","given":"Leah","email":"","affiliations":[{"id":37271,"text":"Carelton College, Northfield, Minn.","active":true,"usgs":false}],"preferred":false,"id":739698,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lewis, Kevin","contributorId":195296,"corporation":false,"usgs":false,"family":"Lewis","given":"Kevin","affiliations":[],"preferred":false,"id":739699,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Michael D.","contributorId":206173,"corporation":false,"usgs":false,"family":"Smith","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":739700,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197339,"text":"70197339 - 2018 - Combining genetic, isotopic, and field data to better describe the influence of dams and diversions on Burbot Movement in the Wind River Drainage, Wyoming","interactions":[],"lastModifiedDate":"2018-05-30T11:14:07","indexId":"70197339","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","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":"Combining genetic, isotopic, and field data to better describe the influence of dams and diversions on Burbot Movement in the Wind River Drainage, Wyoming","docAbstract":"Dams and water diversions fragment habitat, entrain fish, and alter fish movement. Many Burbot Lota lota populations are declining, with dams and water diversions thought to be a major threat. We used multiple methods to identify Burbot movement patterns and assess entrainment into an irrigation system in the Wind River, Wyoming. We assessed seasonal movement of Burbot with a mark–recapture (PIT tagging) study, natal origins of entrained fish with otolith microchemistry, and historic movement with genotyping by sequencing. We found limited evidence of entrainment in irrigation waters across all approaches. The mark–recapture study indicated that out‐migration from potential source populations could be influenced by flow regime but was generally low. Otolith and genomic results suggested the presence of a self‐sustaining population within the irrigation network. We conclude that emigration from natural tributary populations is not the current source of the majority of Burbot found in irrigation waters. Instead, reservoir and irrigation canal construction has created novel habitat in which Burbot have established a population. Using a multi‐scale approach increased our inferential abilities and mechanistic understanding of movement patterns between natural and managed systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10062","usgsCitation":"Hooley-Underwood, Z., Mandeville, E.G., Gerrity, P.C., Deromedi, J.W., Johnson, K., and Walters, A.W., 2018, Combining genetic, isotopic, and field data to better describe the influence of dams and diversions on Burbot Movement in the Wind River Drainage, Wyoming: Transactions of the American Fisheries Society, v. 147, no. 3, p. 606-620, https://doi.org/10.1002/tafs.10062.","productDescription":"15 p.","startPage":"606","endPage":"620","ipdsId":"IP-084464","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Wind River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.632568359375,\n 42.19596877629178\n ],\n [\n -108.21533203125,\n 42.19596877629178\n ],\n [\n -108.21533203125,\n 43.89789239125797\n ],\n [\n -109.632568359375,\n 43.89789239125797\n ],\n [\n -109.632568359375,\n 42.19596877629178\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5b155d75e4b092d9651e1b12","contributors":{"authors":[{"text":"Hooley-Underwood, Zachary","contributorId":205292,"corporation":false,"usgs":false,"family":"Hooley-Underwood","given":"Zachary","affiliations":[],"preferred":false,"id":736787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mandeville, Elizabeth G.","contributorId":166947,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":736788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerrity, Paul C.","contributorId":104198,"corporation":false,"usgs":true,"family":"Gerrity","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":736789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deromedi, J. W.","contributorId":200247,"corporation":false,"usgs":false,"family":"Deromedi","given":"J.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":736790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Kevin","contributorId":181825,"corporation":false,"usgs":false,"family":"Johnson","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":736791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":736744,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197340,"text":"70197340 - 2018 - Green‐wave surfing increases fat gain in a migratory ungulate","interactions":[],"lastModifiedDate":"2018-07-03T11:15:21","indexId":"70197340","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Green‐wave surfing increases fat gain in a migratory ungulate","docAbstract":"Each spring, migratory herbivores around the world track or ‘surf’ green waves of newly emergent vegetation to distant summer or wet‐season ranges. This foraging tactic may help explain the great abundance of migratory herbivores on many seasonal landscapes. However, the underlying fitness benefits of this life‐history strategy remain poorly understood. A fundamental prediction of the green‐wave hypothesis is that migratory herbivores obtain fitness benefits from surfing waves of newly emergent vegetation more closely than their resident counterparts. Here we evaluate whether this behavior increases body‐fat levels – a critically important correlate of reproduction and survival for most ungulates – in elk Cervus elaphus of the Greater Yellowstone Ecosystem. Using satellite imagery and GPS tracking data, we found evidence that migrants (n = 23) indeed surfed the green wave, occupying sites 12.7 days closer to peak green‐up than residents (n = 16). Importantly, individual variation in surfing may help account for up to 6 kg of variation in autumn body‐fat levels. Our findings point to a pathway for anthropogenic changes to the green wave (e.g. climate change) or migrants’ ability to surf it (e.g. development) to impact migratory populations. To explore this possibility, we evaluated potential population‐level consequences of constrained surfing with a heuristic model. If green‐wave surfing deteriorates by 5–15 days from observed, our model predicts up to a 20% decrease in pregnancy rates, a 2.5% decrease in population growth, and a 30% decrease in abundance over 50 years. By linking green‐wave surfing to fitness and illustrating potential effects on population growth, our study provides new insights into the evolution of migratory behavior and the prospects for the persistence of migratory ungulate populations in a changing world.
","language":"English","publisher":"Wiley","doi":"10.1111/oik.05227","usgsCitation":"Middleton, A., Merkle, J., McWhirter, D.E., Cook, J.G., Cook, R.C., White, P., and Kauffman, M., 2018, Green‐wave surfing increases fat gain in a migratory ungulate: Oikos, v. 127, no. 7, p. 1060-1068, https://doi.org/10.1111/oik.05227.","productDescription":"9 p.","startPage":"1060","endPage":"1068","ipdsId":"IP-084519","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":460913,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/oik.05227","text":"Publisher Index Page"},{"id":354565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.09374999999999,\n 42.50450285299051\n ],\n [\n -107.6220703125,\n 42.50450285299051\n ],\n [\n -107.6220703125,\n 44.99588261816546\n ],\n [\n -111.09374999999999,\n 44.99588261816546\n ],\n [\n -111.09374999999999,\n 42.50450285299051\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-22","publicationStatus":"PW","scienceBaseUri":"5b155d75e4b092d9651e1b10","contributors":{"authors":[{"text":"Middleton, Arthur D.","contributorId":99440,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur D.","affiliations":[],"preferred":false,"id":736764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, Jerod","contributorId":172972,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","affiliations":[{"id":35288,"text":"Wyoming Cooperative Fish and Wildlife Research Unit, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":736765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWhirter, Douglas E.","contributorId":90623,"corporation":false,"usgs":true,"family":"McWhirter","given":"Douglas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":736766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, John G.","contributorId":12903,"corporation":false,"usgs":true,"family":"Cook","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":736767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Rachel C.","contributorId":19064,"corporation":false,"usgs":true,"family":"Cook","given":"Rachel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":736768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, P.J.","contributorId":194049,"corporation":false,"usgs":false,"family":"White","given":"P.J.","email":"","affiliations":[],"preferred":false,"id":736769,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":736745,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196624,"text":"sir20185057 - 2018 - Status and understanding of groundwater quality in the Monterey-Salinas Shallow Aquifer Study Unit, 2012–13: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2018-09-21T15:03:20","indexId":"sir20185057","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5057","title":"Status and understanding of groundwater quality in the Monterey-Salinas Shallow Aquifer Study Unit, 2012–13: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 7,820-square-kilometer (km2) Monterey-Salinas Shallow Aquifer (MS-SA) study unit was investigated from October 2012 to May 2013 as part of the second phase of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is in the central coast region of California in the counties of Santa Cruz, Monterey, and San Luis Obispo. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in cooperation with the U.S. Geological Survey and the Lawrence Livermore National Laboratory.
The MS-SA study was designed to provide a statistically robust assessment of untreated-groundwater quality in the shallow aquifer systems. The assessment was based on water-quality samples collected by the U.S. Geological Survey from 100 groundwater sites and 70 household tap sites, along with ancillary data such as land use and well-construction information. The shallow aquifer systems were defined by the depth interval of wells associated with domestic supply. The MS-SA study unit consisted of four study areas—Santa Cruz (210 km2), Pajaro Valley (360 km2), Salinas Valley (2,000 km2), and Highlands (5,250 km2).
This study had two primary components: the status assessment and the understanding assessment. The first primary component of this study—the status assessment—assessed the quality of the groundwater resource indicated by data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally present inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources in the shallow aquifer system of the MS-SA study unit, not the treated drinking water delivered to consumers by water purveyors. As opposed to the public wells, however, water from private wells, which often tap the shallow aquifer, is usually consumed without any treatment. The second component of this study—the understanding assessment—identified the natural and human factors that potentially affect groundwater quality by evaluating land-use characteristics, measures of location, geologic factors, groundwater age, and geochemical conditions of the shallow aquifer. An additional component of this study was a comparison of MS-SA water-quality results to those of the GAMA Monterey Bay and Salinas Valley Groundwater Basins study unit. This study unit covered much of the same areal extent as the MS-SA, but assessed the deeper, public drinking-water aquifer system.
Relative concentrations (sample concentration divided by the benchmark concentration) were used to evaluate concentrations of constituents in groundwater samples relative to water-quality benchmarks for those constituents that have Federal or California benchmarks, such as maximum contaminant levels. For organic and special-interest constituents, relative concentrations were classified as high, greater than 1.0; moderate, greater than 0.1 and less than or equal to 1.0; or low, less than or equal to 0.1. For inorganic constituents, relative concentrations were classified as high, greater than 1.0; moderate, greater than 0.5 and less than or equal to 1.0; or low, less than or equal to 0.5. A relative concentration greater than 1.0 indicates that the concentration was greater than a benchmark. Aquifer-scale proportions were used to quantify regional-scale groundwater quality. The aquifer-scale proportions are the areal percentages of the shallow aquifer system where relative concentrations for a given constituent or class of constituents were high, moderate, or low.
Inorganic constituents were measured at high and moderate relative concentrations more frequently than organic constituents. In the MS-SA study unit, inorganic constituents with benchmarks were detected at high relative concentrations in 51 percent of the study unit. The greatest proportions of high relative concentrations of trace elements and radioactive constituents were in the Highlands and Santa Cruz study areas, whereas high relative concentrations of nutrients were most often detected in the Salinas Valley and Pajaro Valley study areas and salinity indicators were most often detected in the Highlands and Salinas Valley study areas. The trace elements detected at high relative concentrations were arsenic, boron, iron, manganese, molybdenum, selenium, and strontium. The radioactive constituents detected at high relative concentrations were adjusted gross alpha radioactivity and uranium. The nutrient detected at high relative concentrations was nitrate plus nitrite. The salinity indicators detected at high relative concentrations were chloride, sulfate, and total dissolved solids.
Organic constituents (VOCs and pesticides) were not detected at high relative concentrations in any of the study areas. The fumigant 1,2-dichloropropane was detected at moderate relative concentrations. The VOC chloroform and the pesticide simazine were the only organic constituents detected in more than 10 percent of samples. The constituents of special interest NDMA (N-nitrosodimethylamine) and perchlorate were detected at high relative concentrations in the MS-SA study unit.
Selected constituents were evaluated with explanatory factors to identify potential sources or processes that could explain their presence and distribution. Trace elements and radioactive constituents came from natural sources and were not elevated by anthropogenic sources or processes, except for selenium and the radioactive constituent uranium. Arsenic, manganese, iron, selenium, and uranium concentrations were all influenced by oxidation-reduction conditions.
Unlike other trace elements and radioactive constituents, uranium and selenium can be affected by agricultural practices. Uranium and selenium can be released from aquifer sediments as a result of irrigation recharge water interacting with bicarbonate systems.
Nitrate can be strongly affected by anthropogenic sources. Nitrate concentrations were significantly higher in modern groundwater, indicating recent inputs of nitrate to the shallow aquifer system. Nitrate was positively correlated with agricultural land use, indicating that irrigation-return water could be leaching nitrogen fertilizer and naturally present nitrate to elevate nitrate concentrations in shallow groundwater.
The salinity indicators total dissolved solids, chloride, and sulfate all had natural sources in the MS-SA study unit, primarily marine sediments. Concentrations of the constituents were elevated as a result of evaporative concentration of irrigation water or precipitation. Sulfate concentrations were significantly correlated to agricultural land use, indicating that agricultural land-use practices are a contributing source of sulfate to groundwater.
The samples with most of the detections of VOCs were from sites in the Pajaro Valley and northern part of the Salinas Valley. Most of the samples with pesticide detections were from sites in the Salinas Valley study area. The herbicide simazine was positively correlated to the percentage of agricultural land use, and its concentrations were higher in modern groundwater than in pre-modern groundwater.
Perchlorate, similar to nitrate, has natural and anthropogenic sources. Correlations of perchlorate to dissolved oxygen, nitrate, and percentage of agricultural land use indicated that the irrigation-return water could be leaching naturally present perchlorate, as well as perchlorate from historical applications of Chilean nitrate fertilizer, to increase perchlorate concentrations in groundwater.
The quality of the water in the shallow aquifer system from this study was compared with the quality of water in the public drinking-water aquifer in a previous GAMA (MS-PA) study in the same area. The shallow system was more oxic and had more sites with modern groundwater than the public drinking-water aquifer, which was more anoxic and had sites with more pre-modern groundwater. Arsenic and selenium were found at high relative concentrations in a greater proportion of the shallow system. Manganese and iron were found at high relative concentrations in a greater proportion of the public drinking-water aquifer. Uranium was found at higher relative concentrations in a greater proportion of the shallow system. Concentrations of arsenic, iron, manganese, and molybdenum are not likely to change much as groundwater percolates from the shallow system to the public drinking-water aquifer because there are no anthropogenic sources affecting these constituents. Uranium and selenium concentrations in the public drinking-water aquifer could be affected by the higher concentrations in the shallow system because of irrigation-return water, however.
Nitrate and salinity indicators had concentrations that were much higher in the shallow system than the deeper public drinking-water aquifer. High concentrations of these constituents in the shallow system could lead to increased concentrations in the public drinking-water aquifer in parts of the study units because of land-use practices, such as irrigated agriculture.
Organic constituents were detected more frequently in the public drinking-water aquifer than in the shallow system, possibly because more of the sites sampled in the public drinking-water aquifer were in urban areas compared to the sites sampled for the shallow system or because sources of contamination have decreased as a result of changes in use at the land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185057","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Burton, C.A., and Wright, M.T., 2018, Status and understanding of groundwater quality in the Monterey-Salinas Shallow Aquifer study unit, 2012–13: California GAMA Priority Basin Project (ver. 1.1, September 2018): U.S. Geological Survey Scientific Investigations Report 2018–5057, 116 p., https://doi.org/10.3133/sir20185057.","productDescription":"Report: x, 116 p.","numberOfPages":"132","onlineOnly":"Y","ipdsId":"IP-056428","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":357554,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5057/sir20185057_versionhist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018-5057"},{"id":354600,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5057/coverthb.jpg"},{"id":354601,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5057/sir20185057_v1.1.pdf","text":"Report","size":"38.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5057"}],"country":"United States","state":"California","otherGeospatial":"Monterey-Salinas Shallow Aquifer study unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.904296875,\n 36.53170884914869\n ],\n [\n -121.761474609375,\n 36.527294814546245\n ],\n [\n -121.58569335937501,\n 36.49638952000399\n ],\n [\n -121.5142822265625,\n 36.40359962073253\n ],\n [\n -121.4813232421875,\n 36.363798554158635\n ],\n [\n -121.33300781249999,\n 36.33282808737917\n ],\n [\n -121.234130859375,\n 36.27085020723902\n ],\n [\n -121.17370605468749,\n 36.19995805932895\n ],\n [\n -121.08581542968751,\n 36.10237644873644\n ],\n [\n -121.01989746093749,\n 36.02688935430189\n ],\n [\n -120.94299316406249,\n 35.96911507577482\n ],\n [\n -120.88256835937499,\n 35.89795019335754\n ],\n [\n -120.80566406250001,\n 35.79999392988527\n ],\n [\n -120.89080810546875,\n 35.66622234103479\n ],\n [\n -120.8551025390625,\n 35.61488368245436\n ],\n [\n -120.6683349609375,\n 35.46961797120201\n ],\n [\n -120.56945800781249,\n 35.37113502280101\n ],\n [\n -120.465087890625,\n 35.37113502280101\n ],\n [\n -120.2838134765625,\n 35.37113502280101\n ],\n [\n -120.12451171875,\n 35.37561413174875\n ],\n [\n -120.0146484375,\n 35.44277092585766\n ],\n [\n -119.94323730468749,\n 35.46514408578589\n ],\n [\n -119.99267578124999,\n 35.53222622770337\n ],\n [\n -120.10253906249999,\n 35.59925232772949\n ],\n [\n -120.2838134765625,\n 35.755428369259626\n ],\n [\n -120.421142578125,\n 35.88905007936091\n ],\n [\n -120.50903320312501,\n 35.97356075349624\n ],\n [\n -120.673828125,\n 36.09349937380574\n ],\n [\n -120.80566406250001,\n 36.22211876039103\n ],\n [\n -120.94299316406249,\n 36.359374956015856\n ],\n [\n -121.06933593749999,\n 36.46988944681576\n ],\n [\n -121.55273437499999,\n 36.83127162140714\n ],\n [\n -121.61315917968749,\n 36.88840804313823\n ],\n [\n -121.72302246093749,\n 36.9806150652861\n ],\n [\n -121.84936523437499,\n 37.020098201368114\n ],\n [\n -121.9976806640625,\n 37.03325468997236\n ],\n [\n -122.06909179687501,\n 37.01132594307015\n ],\n [\n -122.1075439453125,\n 36.96306042436515\n ],\n [\n -122.0855712890625,\n 36.92793899776678\n ],\n [\n -121.9976806640625,\n 36.94989178681327\n ],\n [\n -121.92626953124999,\n 36.96306042436515\n ],\n [\n -121.86584472656251,\n 36.94989178681327\n ],\n [\n -121.8438720703125,\n 36.88401445049676\n ],\n [\n -121.8109130859375,\n 36.80928470205937\n ],\n [\n -121.8109130859375,\n 36.760891249565624\n ],\n [\n -121.83288574218749,\n 36.69044623523481\n ],\n [\n -121.8438720703125,\n 36.641977814705946\n ],\n [\n -121.8878173828125,\n 36.602299135790446\n ],\n [\n -121.9317626953125,\n 36.602299135790446\n ],\n [\n -121.915283203125,\n 36.56260003738545\n ],\n [\n -121.904296875,\n 36.53170884914869\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: September 2018; Version 1.0: May 2018","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio‐economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models, 43 were commonly applied due to their versatility, accessibility, user‐friendliness, and excellent user‐support. Forty‐one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user‐support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user‐friendly forms, increasing user‐support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Nonetheless, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1966","usgsCitation":"Brewer, S.K., Worthington, T., Mollenhauer, R., Stewart, D., McManamay, R., Guertault, L., and Moore, D., 2018, Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions: Ecohydrology, v. 11, no. 7, p. 1-26, https://doi.org/10.1002/eco.1966.","productDescription":"e1966; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-083229","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468724,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1435332","text":"External Repository"},{"id":354585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5b155d75e4b092d9651e1b16","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worthington, Thomas","contributorId":205274,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":736737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mollenhauer, Robert","contributorId":205275,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":736738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, David","contributorId":205276,"corporation":false,"usgs":false,"family":"Stewart","given":"David","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":736739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McManamay, Ryan","contributorId":205277,"corporation":false,"usgs":false,"family":"McManamay","given":"Ryan","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":736740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guertault, Lucie","contributorId":205278,"corporation":false,"usgs":false,"family":"Guertault","given":"Lucie","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":736741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Desiree","contributorId":205279,"corporation":false,"usgs":false,"family":"Moore","given":"Desiree","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":736742,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}