Linear dune gullies on poleward-facing Martian slopes are enigmatic. Formation by CO2-ice block or snow cornice falls has been proposed based on optical imagery of bright, high-albedo features inside gully channels. Because these features often resemble patchy frost residue rather than three-dimensional blocks, more evidence is needed to support the ice-block formation mechanism. Satellite imagery captured two simultaneous airborne plumes with in-channel sources at the Russell crater megadune, thrust up, and dispersed outward along the path of linear dune gullies. We use spectral data analyses, climatic analyses of bolometric temperatures, and thermal modeling to further develop the mechanistic framework for linear dune gully development. Basal sublimation and CO2 gas venting likely cause CO2-ice-block detachment and falls from gully alcoves in southern early spring, accompanied by ice-block off-gassing and saltation of sands and coarse silts that are redeposited around gully channels, and lofting of sublimation lag (coarse dust/silt) into airborne plumes.
","language":"English","publisher":"Wiley","doi":"10.1029/2020GL091920","usgsCitation":"Dinwiddie, C., and Titus, T.N., 2021, Airborne dust plumes lofted by dislodged ice blocks at Russell Crater, Mars: Geophysical Research Letters, v. 48, no. 6, e2020GL091920, 9 p., https://doi.org/10.1029/2020GL091920.","productDescription":"e2020GL091920, 9 p.","ipdsId":"IP-149099","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":453321,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl091920","text":"Publisher Index Page"},{"id":419474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars, Russell Crater","volume":"48","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dinwiddie, Cynthia L.","contributorId":38880,"corporation":false,"usgs":true,"family":"Dinwiddie","given":"Cynthia L.","affiliations":[],"preferred":false,"id":879399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":879400,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218775,"text":"70218775 - 2021 - Broadening the ecology of fear: Non-lethal effects arise from diverse responses to predation and parasitism","interactions":[],"lastModifiedDate":"2021-03-11T13:36:57.765821","indexId":"70218775","displayToPublicDate":"2021-02-24T07:32:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Broadening the ecology of fear: Non-lethal effects arise from diverse responses to predation and parasitism","docAbstract":"Research on the ‘ecology of fear’ posits that defensive prey responses to avoid predation can cause non-lethal effects across ecological scales. Parasites also elicit defensive responses in hosts with associated non-lethal effects, which raises the longstanding, yet unresolved question of how non-lethal effects of parasites compare with those of predators. We developed a framework for systematically answering this question for all types of predator–prey and host–parasite systems. Our framework reveals likely differences in non-lethal effects not only between predators and parasites, but also between different types of predators and parasites. Trait responses should be strongest towards predators, parasitoids and parasitic castrators, but more numerous and perhaps more frequent for parasites than for predators. In a case study of larval amphibians, whose trait responses to both predators and parasites have been relatively well studied, existing data indicate that individuals generally respond more strongly and proactively to short-term predation risks than to parasitism. Apart from studies using amphibians, there have been few direct comparisons of responses to predation and parasitism, and none have incorporated responses to micropredators, parasitoids or parasitic castrators, or examined their long-term consequences. Addressing these and other data gaps highlighted by our framework can advance the field towards understanding how non-lethal effects impact prey/host population dynamics and shape food webs that contain multiple predator and parasite species.
In response to the dramatic increase in earthquake rates in the central United States, the U.S Geological Survey began releasing 1 yr earthquake hazard models for induced earthquakes in 2016. Although these models have been shown to accurately forecast earthquake hazard, they rely purely on earthquake statistics because there was no precedent for forecasting induced earthquakes based upon wastewater injection data. Since the publication of these hazard models, multiple physics‐based methods have been proposed to forecast earthquake rates using injection data. Here, we use one of these methods to generate earthquake hazard forecasts. Our earthquake hazard forecasts are more accurate than statistics‐based hazard forecasts. These results imply that fluid injection data, where and when available, and the physical implications of fluid injection should be included in future induced earthquake hazard forecasts.
Linear dune gullies on poleward‐facing Martian slopes are enigmatic. Formation by CO2‐ice block or snow cornice falls has been proposed based on optical imagery of bright, high‐albedo features inside gully channels. Because these features often resemble patchy frost residue rather than three‐dimensional blocks, more evidence is needed to support the ice‐block formation mechanism. Satellite imagery captured two simultaneous airborne plumes with in‐channel sources at the Russell crater megadune, thrust up and dispersed outward along the path of linear dune gullies. We use spectral data analyses, climatic analyses of bolometric temperatures and thermal modeling to further develop the mechanistic framework for linear dune gully development. Basal sublimation and CO2 gas venting likely cause CO2‐ice‐block detachment and falls from gully alcoves in southern early spring, accompanied by ice‐block offgassing and saltation of sands and coarse silts that are redeposited around gully channels, and lofting of sublimation lag (coarse dust/silt) into airborne plumes.
Ensemble-tree machine learning (ML) regression models can be prone to systematic bias: small values are overestimated and large values are underestimated. Additional bias can be introduced if the dependent variable is a transform of the original data. Six methods were evaluated for their ability to correct systematic and introduced bias. Method performance was evaluated using four case studies of groundwater quality: the units of the dependent variable were pH in two and log-concentration in the others. When performance metrics (bias and RMSE for both points and the CDF) were computed using the same units as those in the ML model, empirical distribution matching (EDM) provided the best results. When the metrics were computed using retransformed concentration, EDM and a method incorporating Duan's smearing estimate were both effective. A method based on the Z-score transform approximates EDM if the correlation coefficient between rank-ordered ML estimates and rank-ordered observations approaches one.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105006","usgsCitation":"Belitz, K., and Stackelberg, P.E., 2021, Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression model: Environmental Modeling and Software, v. 139, 105006, 12 p., https://doi.org/10.1016/j.envsoft.2021.105006.","productDescription":"105006, 12 p.","ipdsId":"IP-122742","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":453331,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105006","text":"Publisher Index Page"},{"id":436490,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LCTYI2","text":"USGS data release","linkHelpText":"Data Release for Evaluation of Six Methods for Correcting Bias in Estimates from Ensemble Tree Machine Learning Regression Models"},{"id":384773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":813265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":813266,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218199,"text":"ofr20201149 - 2021 - Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing","interactions":[],"lastModifiedDate":"2021-02-24T12:54:58.879829","indexId":"ofr20201149","displayToPublicDate":"2021-02-23T14:19:37","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1149","displayTitle":"Hydrographic and Benthic Mapping—St. Croix National Scenic Riverway—Osceola Landing","title":"Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing","docAbstract":"High-resolution topographic and bathymetric mapping can assist in the analysis of river habitat. The National Park Service has been planning to relocate a boat ramp along the St. Croix River in Minnesota, across the river from the town of Osceola, Wisconsin, to improve visitor safety, improve operations for commercial use, enhance the overall visitor experience, and eliminate deferred maintenance at the landing. This landing grants access to the St. Croix River, which is a part of the National Park Service St. Croix National Scenic Riverway. Hydrographic and topographic surveys were needed to determine where the new location should be. The objective for these surveys was to provide baseline information in order to assess the direct effects of the landing relocation on physical habitat in areas adjacent to Osceola, Wisconsin. The study area for these surveys was about 18.5 hectares and located directly off the existing landing. Although the existing boat launch is referred to as the Osceola landing, it is located on the Minnesota side of the river and is the busiest National Park Service landing on the St. Croix River (National Park Service St. Croix National Scenic Riverway, 2020). This report documents methods and results of aquatic benthic mapping in a small area of the St. Croix River.
The hydroacoustic and topographic surveys were collected from October 16–17, 2019. The hydrographic surveys consisted of multibeam and sidescan sound navigation and ranging (sonars). The topographic shoreline survey consisted of light detection and ranging (lidar) captured by boat adjacent to riverbanks. Additionally, an acoustic Doppler current profiler was used to measure flow velocities. The water level was higher than normal, and therefore had faster flow during the hydroacoustic surveys. Multibeam, lidar, and sidescan surveys occurred the first day, and the velocity mapping and ground truthing was conducted the second day. Multibeam and lidar provided derivative datasets that included bathymetry and a topobathy with a spatial resolution of 1 foot. From these data, additional data could be measured including slope and terrain ruggedness. Sidescan (acoustic reflectance measures) provided imagery that was used to help with interpretation of the river bottom.
Outcomes from these combined datasets were substrate and bedform maps. Much of the area was covered in sand ripples or small dunes. A small area running adjacent to the deeper valley or cut down the river consisted of harder substrates, such as cobble and gravel. Large woody debris piles were found throughout the study area. Multiple stationary moving-bed tests were completed, and no corrections were recommended for the conditions occurring during survey. Mussel presence was noted in some of the underwater videos. The physical parameters of depth, flow, bedforms, and substrate derived from the datasets provided baseline measures for a benthic habitat map. Further analysis of benthic habitat might be possible with additional biological and chemical data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201149","collaboration":"Prepared in cooperation with the National Park Service, the St. Croix National Scenic Riverway, and the Denver Service Center","usgsCitation":"Hanson, J.L., and Strange, J.M., 2021, Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing: U.S. Geological Survey Open-File Report 2020–1149, 26 p., https://doi.org/10.3133/ofr20201149.","productDescription":"Report: vi, 26 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118301","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":383330,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1149/coverthb3.jpg"},{"id":383331,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1149/ofr20201149.pdf","text":"Report","size":"37.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1149"},{"id":383332,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O0QH8B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Saint Croix National Scenic Riverway (SACN)—Osceola boat landing 2019 benthic and bathymetry data"}],"country":"United States","state":"Wisconsin","county":"Osceola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.72460937499999,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.3111146177239\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
Monitoring temporal dynamics of rangelands to detect and understand change in vegetation cover and composition provides a wealth of information to improve management and sustainability. Remote sensing allows the evaluation of both abrupt and gradual rangeland change at unprecedented spatial and temporal extents. Here, we describe the production of the National Land Cover Database (NLCD) Back in Time (BIT) dataset which quantified the percent cover of rangeland components (bare ground, herbaceous, annual herbaceous, litter, shrub, and sagebrush (Artemisia spp. Nutt.) across the western United States using Landsat imagery from 1985 to 2018. We evaluate the relationships of component trends with climate drivers at an ecoregion scale, describe the nature of landscape change, and demonstrate several case studies related to changes in grazing management, prescribed burns, and vegetation treatments. Our results showed the net cover of shrub, sagebrush, and litter significantly (p < 0.01) decreased, bare ground and herbaceous cover had no significant change, and annual herbaceous cover significantly (p < 0.05) increased. Change was ubiquitous, with a mean of 92% of pixels with some change and 38% of pixels with significant change (p < 0.10). However, most change was gradual, well over half of pixels have a range of less than 10%, and most change occurred outside of known disturbances. The BIT data facilitate a comprehensive assessment of rangeland condition, evaluation of past management actions, understanding of system variability, and opportunities for future planning.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13040813","usgsCitation":"Rigge, M.B., Homer, C., Shi, H., Meyer, D., Bunde, B., Granneman, B.J., Postma, K., Danielson, P., Case, A., and Xian, G.Z., 2021, Rangeland fractional components across the western United States from 1985 to 2018: Remote Sensing, v. 13, no. 4, 813, 24 p., https://doi.org/10.3390/rs13040813.","productDescription":"813, 24 p.","ipdsId":"IP-119778","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":453335,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13040813","text":"Publisher Index Page"},{"id":436491,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ODAZHC","text":"USGS data release","linkHelpText":"Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2021"},{"id":384677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395378,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IQ4BT","text":"USGS data release","description":"USGS data release","linkHelpText":"Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oklahoma, Oregon, South Dakota, Texas, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.4697265625,\n 29.53522956294847\n ],\n [\n -102.6123046875,\n 32.58384932565662\n ],\n [\n -104.1064453125,\n 34.488447837809304\n ],\n [\n -100.0634765625,\n 37.020098201368114\n ],\n [\n -103.095703125,\n 39.50404070558415\n ],\n [\n -104.23828125,\n 40.38002840251183\n ],\n [\n -104.2822265625,\n 41.672911819602085\n ],\n [\n -101.162109375,\n 43.58039085560784\n ],\n [\n -102.3486328125,\n 48.60385760823255\n ],\n [\n -104.0185546875,\n 48.951366470947725\n ],\n [\n -121.025390625,\n 48.980216985374994\n ],\n [\n -122.25585937500001,\n 43.58039085560784\n ],\n [\n -123.04687499999999,\n 39.232253141714885\n ],\n [\n -121.81640624999999,\n 36.27970720524017\n ],\n [\n -120.58593749999999,\n 34.27083595165\n ],\n [\n -116.98242187499999,\n 32.54681317351514\n ],\n [\n -114.697265625,\n 32.69486597787505\n ],\n [\n -114.78515624999999,\n 32.39851580247402\n ],\n [\n -111.97265625,\n 31.690781806136822\n ],\n [\n -111.1376953125,\n 31.316101383495624\n ],\n [\n -108.19335937499999,\n 31.39115752282472\n ],\n [\n -108.19335937499999,\n 31.728167146023935\n ],\n [\n -106.2158203125,\n 31.765537409484374\n ],\n [\n -104.67773437499999,\n 30.29701788337205\n ],\n [\n -104.58984375,\n 29.649868677972304\n ],\n [\n -103.22753906249999,\n 28.9600886880068\n ],\n [\n -102.39257812499999,\n 29.916852233070173\n ],\n [\n -101.4697265625,\n 29.53522956294847\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin 0000-0003-4755-8135","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":252931,"corporation":false,"usgs":false,"family":"Homer","given":"Collin","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":811153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer, Debbie 0000-0002-8841-697X debbie.meyer.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":192361,"corporation":false,"usgs":true,"family":"Meyer","given":"Debbie","email":"debbie.meyer.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":811155,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bunde, Brett 0000-0003-0228-779X brett.bunde.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":198821,"corporation":false,"usgs":true,"family":"Bunde","given":"Brett","email":"brett.bunde.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811156,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Granneman, Brian J. 0000-0002-1910-0955 grann@usgs.gov","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":4209,"corporation":false,"usgs":true,"family":"Granneman","given":"Brian","email":"grann@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":811157,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":252852,"corporation":false,"usgs":true,"family":"Postma","given":"Kory","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811158,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":811159,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Case, Adam 0000-0002-6342-5853","orcid":"https://orcid.org/0000-0002-6342-5853","contributorId":252932,"corporation":false,"usgs":true,"family":"Case","given":"Adam","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811160,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xian, George Z. 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":238919,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811161,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70218700,"text":"70218700 - 2021 - Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA","interactions":[],"lastModifiedDate":"2023-11-03T21:40:15.552191","indexId":"70218700","displayToPublicDate":"2021-02-22T07:02:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA","docAbstract":"The Fairweather fault (southeastern Alaska, USA) is Earth’s fastest-slipping intracontinental strike-slip fault, but its long-term role in localizing Yakutat–(Pacific–)North America plate motion is poorly constrained. This plate boundary fault transitions northward from pure strike slip to transpression where it comes onshore and undergoes a <25°, 30-km-long restraining double bend. To the east, apatite (U-Th)/He (AHe) ages indicate that North America exhumation rates increase stepwise from ~0.7 to 1.7 km/m.y. across the bend. In contrast, to the west, AHe age-depth data indicate that extremely rapid 5–10 km/m.y. Yakutat exhumation rates are localized within the bend. Further northwest, Yakutat AHe and zircon (U-Th)/He (ZHe) ages gradually increase from 0.3 to 2.6 Ma over 150 km and depict an interval of extremely rapid >6–8 km/m.y. exhumation rates that increases in age away from the bend. We interpret this migration of rapid, transient exhumation to reflect prolonged advection of the Cenozoic–Cretaceous sedimentary cover of the eastern Yakutat microplate through a stationary restraining bend along the edge of the North America plate. Yakutat cooling ages imply a long-term strike-slip rate (54 ± 6 km/m.y.) that mimics the millennial (53 ± 5 m/k.y.) and decadal (46 mm/yr) rates. Fairweather fault slip can account for all Pacific–North America relative plate motion throughout Quaternary time and indicates stability of highly localized plate boundary strike slip on a single fault where extreme rock uplift rates are persistently localized within a restraining bend.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G48464.1","usgsCitation":"Lease, R.O., Haeussler, P., Witter, R., Stockli, D.F., Bender, A., Kelsey, H., and O’Sullivan, P., 2021, Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA: Geology, v. 49, no. 5, p. 602-606, https://doi.org/10.1130/G48464.1.","productDescription":"5 p.","startPage":"602","endPage":"606","ipdsId":"IP-124679","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":453351,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g48464.1","text":"Publisher Index Page"},{"id":436496,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FUIJG8","text":"USGS data release","linkHelpText":"Low-Temperature Thermochronometric Data along the Fairweather Fault, Southeast Alaska, 2015-2020"},{"id":384056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"southern Fairweather fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.64734789789867,\n 60.62832977945311\n ],\n [\n -142.84447658755874,\n 56.344276134374155\n ],\n [\n -130.03801608165645,\n 54.104139652147495\n ],\n [\n -130.03801608165645,\n 60.62832977945311\n ],\n [\n -146.64734789789867,\n 60.62832977945311\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":811420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","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":811421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":811422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockli, Daniel F. 0000-0001-7652-2129","orcid":"https://orcid.org/0000-0001-7652-2129","contributorId":254375,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":811423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelsey, Harvey","contributorId":254376,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":811425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":811426,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218456,"text":"70218456 - 2021 - Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation","interactions":[],"lastModifiedDate":"2021-02-26T13:42:46.530587","indexId":"70218456","displayToPublicDate":"2021-02-21T07:32:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation","docAbstract":"Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (<15 km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ∼20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.
Mangrove forests are likely vulnerable to accelerating sea-level rise; however, we lack the tools necessary to understand their future resilience. On the Pacific island of Pohnpei, Federated States of Micronesia, mangroves are habitat to endangered species and provide critical ecosystem services that support local communities. We developed a generalizable modeling framework for mangroves that accounts for species interactions and the belowground processes that dictate soil elevation. The modeling framework was calibrated with extensive field datasets, including accretion rates derived from thirty 1-meter-deep soil cores dated with lead-210, more than 300 forest inventory plots, water-level monitoring, and differential leveling elevation surveys. We applied the model using a community of five mangrove species and across seven regions around Pohnpei to identify which regions are most vulnerable to sea-level rise. The responses of mean elevation and the mangrove community composition were analyzed under four global sea-level rise scenarios: an increase of 37, 52, 67, or 117 centimeters by 2100. The model was validated against a 20-year surface elevation table record (1999–2019) and showed good agreement when driven by observed water levels.
The model projected that mangroves around Pohnpei can build their elevations relative to moderate rates of sea-level rise to prevent submergence, with limited changes in mangrove community composition through 2060. By 2100, however, the model projected a decreasing abundance of high-elevation mangrove species and an increasing abundance of lower elevation species adapted to more persistent flooding. Under higher sea-level rise scenarios, forest elevation decreased substantially relative to mean sea level and there were more drastic changes in the tree community composition and loss of suitable mangrove habitat by 2100. Variation in accretion rates, water levels, and initial forest elevation led to differential vulnerability around the island, such that mangroves on the leeward side of the island generally were the most at-risk to higher rates of sea-level rise. Our findings indicate that the relatively undisturbed state of the mangrove forests and the surrounding landscape is an important factor in their ability to keep pace with sea-level rise.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211002","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Buffington, K.J., MacKenzie, R.A., Carr, J.A., Apwong, M., Krauss, K.W., and Thorne, K.M., 2021, Mangrove species’ response to sea-level rise across Pohnpei, Federated States of Micronesia: U.S. Geological Survey Open-File Report 2021–1002, 44 p., https://doi.org/10.3133/ofr20211002.","productDescription":"Report: vii, 44 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-121673","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436498,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96R8MZQ","text":"USGS data release","linkHelpText":"Mangrove Elevation and Species' Responses to Sea-level Rise Across Pohnpei, Federated States of Micronesia (ver. 1.1, December 2021)"},{"id":383370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1002/covrthb.jpg"},{"id":383371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1002/ofr20211002.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":383372,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1002/ofr20211002.xml"},{"id":383373,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1002/images"},{"id":383374,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DDZX32","linkHelpText":"Pohnpei, Federated States of Micronesia Mangrove Elevation Survey Data"}],"country":"Federated States of Micronesia","state":"Pohnpei","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 158.06442260742188,\n 6.7723525317661215\n ],\n [\n 158.3740997314453,\n 6.7723525317661215\n ],\n [\n 158.3740997314453,\n 7.013667927566642\n ],\n [\n 158.06442260742188,\n 7.013667927566642\n ],\n [\n 158.06442260742188,\n 6.7723525317661215\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Human enterprise has led to large‐scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage‐grouse (Centrocercus urophasianus; hereafter sage‐grouse) are a widespread sagebrush (Artemisia spp.) obligate species that has experienced population declines since the mid‐1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage‐grouse’ distribution, where a remnant population remains despite recent development of energy‐related infrastructure. Resource managers in this region have determined a need to augment sage‐grouse populations using translocation techniques that can be important management tools for countering species decline from range contraction. Although translocations are a common tool for wildlife management, very little research has evaluated habitat following translocation, to track individual behaviors such as habitat selection and fidelity to the release site, which can help inform habitat requirements to guide selection of future release sites. We provide an example where locations from previously released radio‐marked sage‐grouse are used in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluated possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential for long‐term recovery.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7228","usgsCitation":"Lazenby, K.D., Coates, P.S., O’Neil, S.T., Kohl, M.T., and Dahlgren, D.K., 2021, Nesting, brood rearing, and summer habitat selection by translocated greater sage‐grouse in North Dakota, USA: Ecology and Evolution, v. 11, no. 6, p. 2741-2760, https://doi.org/10.1002/ece3.7228.","productDescription":"20 p.","startPage":"2741","endPage":"2760","ipdsId":"IP-119290","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453379,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7228","text":"External Repository"},{"id":436499,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91GQXVE","text":"USGS data release","linkHelpText":"Geospatial Information and Predictive Maps of Greater Sage-grouse Habitat Selection in Southwestern North Dakota, USA"},{"id":385280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.7216796875,\n 45.48324350868221\n ],\n [\n -103.3154296875,\n 45.48324350868221\n ],\n [\n -103.3154296875,\n 46.70973594407157\n ],\n [\n -104.7216796875,\n 46.70973594407157\n ],\n [\n -104.7216796875,\n 45.48324350868221\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.2208251953125,\n 42.05337156043361\n ],\n [\n -106.8585205078125,\n 42.05337156043361\n ],\n [\n -106.8585205078125,\n 42.549033612225145\n ],\n [\n -108.2208251953125,\n 42.549033612225145\n ],\n [\n -108.2208251953125,\n 42.05337156043361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Lazenby, Kade D.","contributorId":257564,"corporation":false,"usgs":false,"family":"Lazenby","given":"Kade","email":"","middleInitial":"D.","affiliations":[{"id":52056,"text":"Department of Wildland Resources, Jack H. Berryman Institute, S. J. Quinney College of Natural Resources, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":814629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":814630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":814631,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohl, Michel T.","contributorId":204214,"corporation":false,"usgs":false,"family":"Kohl","given":"Michel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":814632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahlgren, David K.","contributorId":257565,"corporation":false,"usgs":false,"family":"Dahlgren","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":52056,"text":"Department of Wildland Resources, Jack H. Berryman Institute, S. J. Quinney College of Natural Resources, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":814633,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236823,"text":"70236823 - 2021 - Response study of a 51-story-tall Los Angeles, California building inferred from motions of the Mw7.1 July 5, 2019 Ridgecrest, California earthquake","interactions":[],"lastModifiedDate":"2024-09-24T18:42:02.563556","indexId":"70236823","displayToPublicDate":"2021-02-19T08:55:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1101,"text":"Bulletin of Earthquake Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Response study of a 51-story-tall Los Angeles, California building inferred from motions of the Mw7.1 July 5, 2019 Ridgecrest, California earthquake","docAbstract":"A 51-story building in downtown Los Angeles that is equipped with a seismic monitoring accelerometric array recorded the Mw7.1 Ridgecrest, California earthquake of July 5, 2019. The building is a dual-core reinforced-concrete shear-wall and perimeter-column structure with ~ 80% of floors constructed as post-tensioned flat slabs, which makes it a trending design. Using system identification methods, spectral analyses, and coherence-phase angle computations, the recorded response data allowed the identification of dynamic response characteristics (fundamental frequencies of [NS] 0.21 Hz, [EW] 0.28 Hz, and [Torsional] 0.45 Hz, critical damping percentages < 2.5%, and associated mode shapes), as well as computation of drift ratios with maximum peaks of 0.145% for both NS and EW directions. The critical damping percentages are consistent with those recommended by LATBSDC (2017). There is no indication from the records that post-tensioned slab design played any role in altering the dynamic characteristics.
","language":"English","publisher":"Springer","doi":"10.1007/s10518-021-01053-9","usgsCitation":"Celebi, M., Swensen, D., and Haddadi, H., 2021, Response study of a 51-story-tall Los Angeles, California building inferred from motions of the Mw7.1 July 5, 2019 Ridgecrest, California earthquake: Bulletin of Earthquake Engineering, v. 19, p. 1797-1814, https://doi.org/10.1007/s10518-021-01053-9.","productDescription":"18 p.","startPage":"1797","endPage":"1814","ipdsId":"IP-119102","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":406956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.28189849853514,\n 34.022786817002\n ],\n [\n -118.21495056152342,\n 34.022786817002\n ],\n [\n -118.21495056152342,\n 34.07768740409027\n ],\n [\n -118.28189849853514,\n 34.07768740409027\n ],\n [\n -118.28189849853514,\n 34.022786817002\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2021-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swensen, Dan","contributorId":296724,"corporation":false,"usgs":false,"family":"Swensen","given":"Dan","email":"","affiliations":[{"id":35312,"text":"CGS-CSMIP","active":true,"usgs":false}],"preferred":false,"id":852279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haddadi, Hamid","contributorId":296690,"corporation":false,"usgs":false,"family":"Haddadi","given":"Hamid","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":852280,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218255,"text":"70218255 - 2021 - Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning","interactions":[],"lastModifiedDate":"2021-02-22T14:29:43.76892","indexId":"70218255","displayToPublicDate":"2021-02-19T08:20:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning","docAbstract":"In this study, we explored the use of statistical machine learning and long-term groundwater nitrate monitoring data to estimate vadose zone and saturated zone lag times in an irrigated alluvial agricultural setting. Unlike most previous statistical machine learning studies that sought to predict groundwater nitrate concentrations within aquifers, the focus of this study was to leverage available groundwater nitrate concentrations and other environmental variables to determine mean regional vertical velocities (transport rates) of water and solutes in the vadose zone and saturated zone (3.50 and 3.75 m yr−1, respectively). The statistical machine learning results are consistent with two primary recharge processes in this western Nebraska aquifer, namely (1) diffuse recharge from irrigation and precipitation across the landscape and (2) focused recharge from leaking irrigation conveyance canals. The vadose zone mean velocity yielded a mean recharge rate (0.46 m yr−1) consistent with previous estimates from groundwater age dating in shallow wells (0.38 m yr−1). The saturated zone mean velocity yielded a recharge rate (1.31 m yr−1) that was more consistent with focused recharge from leaky irrigation canals, as indicated by previous results of groundwater age dating in intermediate-depth wells (1.22 m yr−1). Collectively, the statistical machine learning model results are consistent with previous observations of relatively high water fluxes and short transit times for water and nitrate in the primarily oxic aquifer. Partial dependence plots from the model indicate a sharp threshold in which high groundwater nitrate concentrations are mostly associated with total travel times of 7 years or less, possibly reflecting some combination of recent management practices and a tendency for nitrate concentrations to be higher in diffuse infiltration recharge than in canal leakage water. Limitations to the machine learning approach include the non-uniqueness of different transport rate combinations when comparing model performance and highlight the need to corroborate statistical model results with a robust conceptual model and complementary information such as groundwater age.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-25-811-2021","usgsCitation":"Wells, M.J., Gilmore, T., Nelson, N., Mittelstet, A., and Bohlke, J., 2021, Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning: Hydrology and Earth System Sciences, v. 25, p. 811-829, https://doi.org/10.5194/hess-25-811-2021.","productDescription":"19 p.","startPage":"811","endPage":"829","ipdsId":"IP-118404","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":453386,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-25-811-2021","text":"Publisher Index Page"},{"id":383417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","county":"Scotts Bluff County, Sioux County","otherGeospatial":"Dutch Flats","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.03228759765625,\n 41.27367811566259\n ],\n [\n -102.39257812499999,\n 41.27367811566259\n ],\n [\n -102.39257812499999,\n 42.407234661551875\n ],\n [\n -104.03228759765625,\n 42.407234661551875\n ],\n [\n -104.03228759765625,\n 41.27367811566259\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2021-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Martin J.","contributorId":251868,"corporation":false,"usgs":false,"family":"Wells","given":"Martin","email":"","middleInitial":"J.","affiliations":[{"id":50406,"text":"U Nebraska","active":true,"usgs":false}],"preferred":false,"id":810735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilmore, Troy E.","contributorId":251869,"corporation":false,"usgs":false,"family":"Gilmore","given":"Troy E.","affiliations":[{"id":50406,"text":"U Nebraska","active":true,"usgs":false}],"preferred":false,"id":810736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Natalie","contributorId":251870,"corporation":false,"usgs":false,"family":"Nelson","given":"Natalie","affiliations":[{"id":50407,"text":"North Carolina State U","active":true,"usgs":false}],"preferred":false,"id":810737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mittelstet, Aaron","contributorId":251871,"corporation":false,"usgs":false,"family":"Mittelstet","given":"Aaron","affiliations":[{"id":50406,"text":"U Nebraska","active":true,"usgs":false}],"preferred":false,"id":810738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":810739,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70224974,"text":"70224974 - 2021 - An attention U-Net model for detection of fine-scale hydrologic streamlines","interactions":[],"lastModifiedDate":"2021-10-11T12:42:39.84326","indexId":"70224974","displayToPublicDate":"2021-02-19T07:38:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"An attention U-Net model for detection of fine-scale hydrologic streamlines","docAbstract":"Surface water is an irreplaceable resource for human survival and environmental sustainability. Accurate, finely detailed cartographic representations of hydrologic streamlines are critically important in various scientific domains, such as assessing the quantity and quality of present and future water resources, modeling climate changes, evaluating agricultural suitability, mapping flood inundation, and monitoring environmental changes. Conventional approaches to detecting such streamlines cannot adequately incorporate information from the complex three-dimensional (3D) environment of streams and land surface features. Such information is vital to accurately delineate streamlines. In recent years, high accuracy lidar data has become increasingly available for deriving both 3D information and terrestrial surface reflectance. This study develops an attention U-net model to take advantage of high-accuracy lidar data for finely detailed streamline detection and evaluates model results against a baseline of multiple traditional machine learning methods. The evaluation shows that the attention U-net model outperforms the best baseline machine learning method by an average F1 score of 11.25% and achieves significantly better smoothness and connectivity between classified streamline channels. These findings suggest that our deep learning approach can harness high-accuracy lidar data for fine-scale hydrologic streamline detection, and in turn produce desirable benefits for many scientific domains.
The need for basic information on spatial distribution and abundance of plant species for research and management in semiarid ecosystems is frequently unmet. This need is particularly acute in the large areas impacted by megafires in sagebrush steppe ecosystems, which require frequently updated information about increases in exotic annual invaders or recovery of desirable perennials. Remote sensing provides one avenue for obtaining this information. We considered how a vegetation model based on Landsat satellite imagery (30 m pixel resolution; annual images from 1985 to 2018) known as the National Land Cover Database (NLCD) “Back-in-Time” fractional component time-series, compared with field-based vegetation measurements. The comparisons focused on detection thresholds of post-fire emergence of fire-intolerant Artemisia L. species, primarily A. tridentata Nutt. (big sagebrush). Sagebrushes are scarce after fire and their paucity over vast burn areas creates challenges for detection by remote sensing. Measurements were made extensively across the Great Basin, USA, on eight burn scars encompassing ~500 000 ha with 80 plots sampled, and intensively on a single 113 000 ha burned area where we sampled 1454 plots.
Estimates of sagebrush cover from the NLCD were, as a mean, 6.5% greater than field-based estimates, and variance around this mean was high. The contrast between sagebrush cover measurements in field data and NLCD data in burned landscapes was considerable given that maximum cover values of sagebrush were ~35% in the field. It took approximately four to six years after the fire for NLCD to detect consistent, reliable signs of sagebrush recovery, and sagebrush cover estimated by NLCD ranged from 3 to 13% (equating to 0 to 7% in field estimates) at these times. The stabilization of cover and presence four to six years after fire contrasted with previous field-based studies that observed fluctuations over longer time periods.
While results of this study indicated that further improvement of remote sensing applications would be necessary to assess initial sagebrush recovery patterns, they also showed that Landsat satellite imagery detects the influence of burns and that the NLCD data tend to show faster rates of recovery relative to field observations.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-021-00091-7","usgsCitation":"Applestein, C., and Germino, M., 2021, Detecting shrub recovery in sagebrush steppe: Comparing Landsat-derived maps with field data on historical wildfires: Fire Ecology, v. 17, no. 5, 11 p., https://doi.org/10.1186/s42408-021-00091-7.","productDescription":"11 p.","ipdsId":"IP-121781","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":453394,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-021-00091-7","text":"Publisher Index Page"},{"id":383586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Idaho, Nevada, Utah","otherGeospatial":"Sagebrush steppe of the Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.35546875000001,\n 40.84706035607122\n ],\n [\n -111.357421875,\n 40.84706035607122\n ],\n [\n -111.357421875,\n 44.15068115978094\n ],\n [\n -119.35546875000001,\n 44.15068115978094\n ],\n [\n -119.35546875000001,\n 40.84706035607122\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218003,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":810810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":810811,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219567,"text":"70219567 - 2021 - Ungaged inflow and loss patterns in urban and agricultural sub‐reaches of the Logan River Observatory","interactions":[],"lastModifiedDate":"2021-04-14T12:03:32.609531","indexId":"70219567","displayToPublicDate":"2021-02-18T06:55:15","publicationYear":"2021","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":"Ungaged inflow and loss patterns in urban and agricultural sub‐reaches of the Logan River Observatory","docAbstract":"Streams in semi‐arid urban and agricultural environments are often heavily diverted for anthropogenic purposes. However, they simultaneously receive substantial inflows from a variety of ungaged sources including stormwater returns, tile drainage, and irrigation runoff that help sustain flow during dry periods. Due to the inability to identify sources or directly gage many of these inflows, there is a clear need for methods to understand source origination while quantifying potential gains and losses over highly impacted reaches. In the context of the Logan River Observatory, historical gage data illustrate the importance of ungaged and unidentified inflows on maintaining or enhancing flows in both urban and agricultural reaches containing large diversions. To understand the inflows in this portion of the Logan River, we first analysed water samples for ions collected from a subset of representative inflow sources and applied clustering analyses to establish inflow source classifications and associated ion concentration ranges. These representative concentration ranges, combined with mainstem flow and river ion samples taken at sub‐reach scales, allow for the application of flow and mass balances to quantify inflow rates from different sources as well as any losses. These calculations demonstrate significant gains and losses occurring in many sub‐reaches during three sampling events. The dominant land use (urban or agriculture) and flow regime at the time of sampling were the primary drivers of gains and losses. These exchanges were found to be most important below large diversions during low flow conditions. This highlights the need to classify inflow sources (urban or agriculture, surface or groundwater) and estimate their contributions to anticipate instream consequences of land use and water management decisions. As irrigation and water conveyance practices become more efficient, a portion of these ungaged inflows could be diminished or eliminated, thus further depleting streamflow during dry periods.
The U.S. Geological Survey (USGS) National Water-Use Science Project strives to report water-use estimates using the best available information for the period of the estimates. The information available on water used for irrigation activities varies from State to State and in some areas from county to county within a State, which results in many information sources and methods being used to estimate water withdrawals and consumption for the Nation. The variety of estimation methods makes it difficult to compare information across States and makes it difficult to understand how different methods or data sources bias irrigation water-use estimates and trends over time. The sources of information and methods used by USGS Water Science Centers to estimate irrigation water use (the number of irrigated acres by irrigation system type, withdrawal values by water source type, and consumed-water values) for 2015 are compiled and described herein to assist with interpreting the water-use estimates. State-level summaries of information sources and methods are compiled in appendix 1, and a dataset of calendar-year, county-level estimates of actual evapotranspiration for the conterminous United States and Hawaii is provided in an associated USGS data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205139","usgsCitation":"Painter, J.A., Brandt, J.T., Caldwell, R.R., Haynes, J.V., and Read, A.L., 2021, Documentation of methods and inventory of irrigation information collected for the 2015 U.S. Geological Survey estimated use of water in the United States: U.S. Geological Survey Scientific Investigations Report 2020–5139, 39 p., https://doi.org/10.3133/sir20205139.","productDescription":"Report: vi, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117889","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":399408,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205139/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2020-5139"},{"id":383301,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5139/sir20205139.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5139"},{"id":399394,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5139/images/"},{"id":383257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5139/coverthb.jpg"},{"id":383259,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O1TMR6","text":"USGS data release","linkHelpText":"2015 calendar-year county-level estimates of actual evapotranspiration for the conterminous United States and Hawaii"},{"id":399393,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5139/sir20205139.XML"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n -135.3076171875,\n 59.833775202184206\n ],\n [\n -136.38427734375,\n 59.65664225341022\n ],\n [\n -136.6259765625,\n 59.23217626921806\n ],\n [\n -137.52685546875,\n 58.938673187948304\n ],\n [\n -137.65869140625,\n 59.33318942659219\n ],\n [\n -138.8232421875,\n 60.009970961180386\n ],\n [\n -139.21874999999997,\n 60.108670463036\n ],\n [\n -139.04296875,\n 60.403001945865476\n ],\n [\n -139.85595703125,\n 60.337823495982015\n ],\n [\n -140.99853515625,\n 60.337823495982015\n ],\n [\n -141.15234374999997,\n 69.71810669906763\n ],\n [\n -143.4375,\n 70.17020068549206\n ],\n [\n -145.1953125,\n 70.08056215839737\n ],\n [\n -149.765625,\n 70.58341752317065\n ],\n [\n -152.40234375,\n 70.61261423801925\n ],\n [\n -152.314453125,\n 70.95969716686398\n ],\n [\n -157.1484375,\n 71.35706654962706\n ],\n [\n -159.9609375,\n 70.8734913192635\n ],\n [\n -162.0703125,\n 70.31873847853124\n ],\n [\n -163.916015625,\n 69.06856318696033\n ],\n [\n -166.376953125,\n 68.942606818121\n ],\n [\n -166.376953125,\n 68.26938680456564\n ],\n [\n -163.30078125,\n 66.86108230224609\n ],\n [\n -161.982421875,\n 66.47820814385636\n ],\n [\n -163.564453125,\n 66.08936427047088\n ],\n [\n -163.564453125,\n 66.6181218846659\n ],\n [\n -165.76171875,\n 66.40795547978848\n ],\n [\n -168.0908203125,\n 65.69447579373418\n ],\n [\n -166.55273437499997,\n 65.14611484756372\n ],\n [\n -166.904296875,\n 65.05360170595502\n ],\n [\n -166.3330078125,\n 64.41592147626879\n ],\n [\n -162.861328125,\n 64.39693778132846\n ],\n [\n -160.927734375,\n 64.90491004905083\n ],\n [\n -161.0595703125,\n 64.47279382008166\n ],\n [\n -161.4990234375,\n 64.49172504435471\n ],\n [\n -160.8837890625,\n 63.87939001720202\n ],\n [\n -161.1474609375,\n 63.470144746565424\n ],\n [\n -162.6416015625,\n 63.64625919492172\n ],\n [\n -163.212890625,\n 63.05495931065107\n ],\n [\n -164.2236328125,\n 63.37183226679281\n ],\n [\n -166.1572265625,\n 61.75233128411639\n ],\n [\n -165.3662109375,\n 60.54377524118842\n ],\n [\n -167.431640625,\n 60.326947742998414\n ],\n [\n -167.255859375,\n 59.866883195210214\n ],\n [\n -165.8935546875,\n 59.7563950493563\n ],\n [\n -162.68554687499997,\n 59.734253447591364\n ],\n [\n -162.3779296875,\n 60.174306261926034\n ],\n [\n -161.806640625,\n 59.46740794183739\n ],\n [\n -162.0263671875,\n 59.108308258604964\n ],\n [\n -161.806640625,\n 58.768200159239576\n ],\n [\n -162.20214843749997,\n 58.65408464530598\n ],\n [\n -160.83984375,\n 58.44773280389084\n ],\n [\n -159.9609375,\n 58.6769376725869\n ],\n [\n -159.08203125,\n 58.309488840677645\n ],\n [\n -156.88476562499997,\n 58.92733441827545\n ],\n [\n -157.5,\n 58.516651799363785\n ],\n [\n -157.8076171875,\n 57.61010702068388\n ],\n [\n -161.54296875,\n 56.022948079627454\n ],\n [\n -168.6181640625,\n 53.4357192066942\n ],\n [\n -174.9462890625,\n 52.26815737376817\n ],\n [\n -178.2421875,\n 51.83577752045248\n ],\n [\n -173.1884765625,\n 51.590722643120145\n ],\n [\n -162.5537109375,\n 54.23955053156177\n ],\n [\n -155.302734375,\n 55.52863052257191\n ],\n [\n -151.4794921875,\n 57.51582286553883\n ],\n [\n -146.9970703125,\n 60.08676274626006\n ],\n [\n -145.546875,\n 60.21799073323445\n ],\n [\n -144.228515625,\n 59.689926220143356\n ],\n [\n -142.3828125,\n 59.93300042374631\n ],\n [\n -138.3837890625,\n 58.83649009392136\n ],\n [\n -135.6591796875,\n 56.31653672211301\n ],\n [\n -133.2421875,\n 54.521081495443596\n ],\n [\n -130.67138671875,\n 54.686534234529695\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.796875,\n 44.902577996288876\n ],\n [\n -67.67578124999999,\n 45.583289756006316\n ],\n [\n -67.939453125,\n 47.57652571374621\n ],\n [\n -69.2578125,\n 47.338822694822\n ],\n [\n -71.19140625,\n 45.27488643704891\n ],\n [\n -75.146484375,\n 44.96479793033101\n ],\n [\n -78.046875,\n 43.644025847699496\n ],\n [\n -79.1015625,\n 43.51668853502906\n ],\n [\n -79.1015625,\n 42.87596410238256\n ],\n [\n -82.68310546875,\n 41.65649719441145\n ],\n [\n -83.14453125,\n 42.049292638686836\n ],\n [\n -83.07861328125,\n 42.374778361114195\n ],\n [\n -82.529296875,\n 42.601619944327965\n ],\n [\n -82.24365234375,\n 43.6599240747891\n ],\n [\n -82.41943359375,\n 45.058001435398275\n ],\n [\n -83.60595703125,\n 45.85941212790755\n ],\n [\n -83.49609375,\n 46.027481852486645\n ],\n [\n -83.7158203125,\n 46.164614496897094\n ],\n [\n -83.95751953125,\n 46.07323062540835\n ],\n [\n -84.24316406249999,\n 46.558860303117164\n ],\n [\n -84.72656249999999,\n 46.558860303117164\n ],\n [\n -84.90234375,\n 46.92025531537451\n ],\n [\n -88.41796875,\n 48.3416461723746\n ],\n [\n -89.3408203125,\n 47.96050238891509\n ],\n [\n -90.76904296874999,\n 48.122101028190805\n ],\n [\n -90.87890625,\n 48.22467264956519\n ],\n [\n -91.51611328125,\n 48.10743118848039\n ],\n [\n -92.2412109375,\n 48.37084770238366\n ],\n [\n -92.39501953125,\n 48.23930899024907\n ],\n [\n -92.94433593749999,\n 48.61838518688487\n ],\n [\n -93.44970703125,\n 48.63290858589535\n ],\n [\n -94.7021484375,\n 48.748945343432936\n ],\n [\n -94.833984375,\n 49.23912083246698\n ],\n [\n -95.1416015625,\n 49.396675075193976\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -123.22265625000001,\n 48.99463598353405\n ],\n [\n -123.0908203125,\n 48.80686346108517\n ],\n [\n -123.24462890625,\n 48.66194284607006\n ],\n [\n -123.1787109375,\n 48.32703913063476\n ],\n [\n -124.78271484375,\n 48.472921272487824\n ],\n [\n -124.93652343749999,\n 48.16608541901253\n ],\n [\n -124.365234375,\n 46.58906908309182\n ],\n [\n -124.541015625,\n 44.15068115978094\n ],\n [\n -124.93652343749999,\n 42.69858589169842\n ],\n [\n -124.541015625,\n 41.22824901518529\n ],\n [\n -124.73876953125,\n 40.43022363450862\n ],\n [\n -124.03564453125,\n 39.35129035526705\n ],\n [\n -124.01367187499999,\n 38.8225909761771\n ],\n [\n -122.05810546875,\n 36.12012758978146\n ],\n [\n -120.95947265624999,\n 34.88593094075317\n ],\n [\n -120.80566406250001,\n 34.08906131584994\n ],\n [\n -118.21289062499999,\n 32.2313896627376\n ],\n [\n -117.22412109375,\n 32.54681317351514\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -114.78515624999999,\n 32.491230287947594\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.297327991404266\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.435546875,\n 31.765537409484374\n ],\n [\n -104.9853515625,\n 30.600093873550072\n ],\n [\n -104.47998046875,\n 29.592565403314087\n ],\n [\n -103.20556640625,\n 28.94086176940557\n ],\n [\n -102.65625,\n 29.76437737516313\n ],\n [\n -102.3486328125,\n 29.84064389983441\n ],\n [\n -101.49169921875,\n 29.7453016622136\n ],\n [\n -100.83251953125,\n 29.267232865200878\n ],\n [\n -100.30517578125,\n 28.246327971048842\n ],\n [\n -99.60205078124999,\n 27.586197857692664\n ],\n [\n -99.47021484375,\n 27.31321389856826\n ],\n [\n -99.228515625,\n 26.52956523826758\n ],\n [\n -98.2177734375,\n 26.05678288577881\n ],\n [\n -97.75634765625,\n 26.03704188651584\n ],\n [\n -97.44873046875,\n 25.839449402063185\n ],\n [\n -97.20703125,\n 25.93828707492375\n ],\n [\n -96.8994140625,\n 26.194876675795218\n ],\n [\n -96.78955078125,\n 27.858503954841247\n ],\n [\n -93.75732421875,\n 29.420460341013133\n ],\n [\n -90.2197265625,\n 28.998531814051795\n ],\n [\n -88.22021484375,\n 29.05616970274342\n ],\n [\n -87.91259765625,\n 30.14512718337613\n ],\n [\n -86.5283203125,\n 30.183121842195515\n ],\n [\n -85.2978515625,\n 29.49698759653577\n ],\n [\n -84.13330078125,\n 29.80251790576445\n ],\n [\n -82.81494140625,\n 28.555576049185973\n ],\n [\n -83.21044921875,\n 27.800209937418252\n ],\n [\n -82.77099609375,\n 26.941659545381516\n ],\n [\n -82.08984375,\n 25.878994400196202\n ],\n [\n -81.5625,\n 25.264568475331583\n ],\n [\n -82.28759765625,\n 24.467150664739002\n ],\n [\n -82.0458984375,\n 24.046463999666567\n ],\n [\n -80.6396484375,\n 24.56710835257599\n ],\n [\n -79.78271484375,\n 25.34402602913433\n ],\n [\n -79.60693359375,\n 27.27416111737468\n ],\n [\n -80.68359375,\n 30.713503990354965\n ],\n [\n -80.66162109375,\n 31.50362930577303\n ],\n [\n -76.81640625,\n 34.07086232376631\n ],\n [\n -75.16845703124999,\n 35.263561862152095\n ],\n [\n -75.498046875,\n 37.055177106660814\n ],\n [\n -73.58642578125,\n 39.90973623453719\n ],\n [\n -71.3671875,\n 40.84706035607122\n ],\n [\n -69.63134765625,\n 40.9964840143779\n ],\n [\n -70.0048828125,\n 42.342305278572816\n ],\n [\n -70.3564453125,\n 42.89206418807337\n ],\n [\n -67.2802734375,\n 44.37098696297173\n ],\n [\n -67.0166015625,\n 44.69989765840318\n ],\n [\n -66.796875,\n 44.902577996288876\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2308349609375,\n 17.96305758238804\n ],\n [\n -67.2198486328125,\n 17.910795834978483\n ],\n [\n -66.5716552734375,\n 17.866361230891894\n ],\n [\n -66.16790771484375,\n 17.90556881196468\n ],\n [\n -65.85205078125,\n 17.973508079068797\n ],\n [\n -65.7861328125,\n 18.04142122189195\n ],\n [\n -65.50323486328125,\n 18.06231230454674\n ],\n [\n -65.2587890625,\n 18.114529138838503\n ],\n [\n -65.269775390625,\n 18.15629140283545\n ],\n [\n -65.4400634765625,\n 18.18238775108558\n ],\n [\n -65.51422119140625,\n 18.14324176648384\n ],\n [\n -65.5609130859375,\n 18.40665471391907\n ],\n [\n -65.64880371093749,\n 18.404048629104647\n ],\n [\n -65.77789306640625,\n 18.417078658661257\n ],\n [\n -65.9124755859375,\n 18.46918890441719\n ],\n [\n -66.24755859375,\n 18.510865709091377\n ],\n [\n -66.4837646484375,\n 18.503052080569763\n ],\n [\n -66.98638916015625,\n 18.51347017266187\n ],\n [\n -67.115478515625,\n 18.534304453676864\n ],\n [\n -67.181396484375,\n 18.48742375381096\n ],\n [\n -67.16217041015625,\n 18.432713391700858\n ],\n [\n -67.2637939453125,\n 18.375379094031825\n ],\n [\n -67.19238281249999,\n 18.2397859708389\n ],\n [\n -67.2308349609375,\n 17.96305758238804\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
Managing wildlife in landscapes under private ownership requires partnership between landowners, resource users, and governing agencies. Agencies often call on landowners to voluntarily change their practices to achieve collective goals. Landowner support for management action is partially a function of normative beliefs about managing wildlife. Understanding factors that support development of normative beliefs is important for program design, with implications beyond deer. Drawing on norm activation theory, identity theory, and community attachment, we hypothesized that landowners’ ascription of responsibility to manage deer were a function of their identity as a wildlife steward and attachment to their community. We tested our hypotheses using structural equation modeling with data from a survey of southeast Minnesota landowners. Results revealed ascribed responsibility to be a function of identity. In turn, identity was predicted by affect toward the community. Findings suggest community-based approaches to wildlife management could improve goal achievement.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08941920.2020.1852636","usgsCitation":"Landon, A.C., Fulton, D.C., Pradhananga, A., Cornicelli, L., and Davenport, M., 2021, Community attachment and stewardship identity influence responsibility to manage wildlife: Society & Natural Resources: An International Journal, v. 34, no. 5, p. 571-584, https://doi.org/10.1080/08941920.2020.1852636.","productDescription":"14 p.","startPage":"571","endPage":"584","ipdsId":"IP-113324","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.204691,46.704041],[-92.205192,46.698341],[-92.183091,46.695241],[-92.176091,46.686341],[-92.204092,46.666941],[-92.201592,46.656641],[-92.207092,46.651941],[-92.242493,46.649241],[-92.256592,46.658741],[-92.270592,46.650741],[-92.274392,46.657441],[-92.286192,46.660342],[-92.287392,46.667342],[-92.291292,46.668142],[-92.292192,46.663308],[-92.294033,46.074377],[-92.332912,46.062697],[-92.35176,46.015685],[-92.372717,46.014198],[-92.410649,46.027259],[-92.428555,46.024241],[-92.442259,46.016177],[-92.453373,45.992913],[-92.464512,45.985038],[-92.461138,45.980216],[-92.469354,45.973811],[-92.527052,45.983245],[-92.548459,45.969056],[-92.551186,45.95224],[-92.60246,45.940815],[-92.614314,45.934529],[-92.638824,45.934166],[-92.638474,45.925971],[-92.659549,45.922937],[-92.676167,45.912072],[-92.675737,45.907478],[-92.707702,45.894901],[-92.734039,45.868108],[-92.739278,45.84758],[-92.765146,45.830183],[-92.757815,45.806574],[-92.776496,45.790014],[-92.784621,45.764196],[-92.809837,45.744172],[-92.869193,45.717568],[-92.870025,45.697272],[-92.875488,45.689014],[-92.887929,45.639006],[-92.882529,45.610216],[-92.886442,45.598679],[-92.883749,45.575483],[-92.871082,45.567581],[-92.823309,45.560934],[-92.770223,45.566939],[-92.726082,45.541112],[-92.726677,45.514462],[-92.702224,45.493046],[-92.680234,45.464344],[-92.653549,45.455346],[-92.646602,45.441635],[-92.650422,45.398507],[-92.664102,45.393309],[-92.676961,45.380137],[-92.678223,45.373604],[-92.70272,45.358472],[-92.698967,45.336374],[-92.709968,45.321302],[-92.737122,45.300459],[-92.761013,45.289028],[-92.760615,45.278827],[-92.751659,45.26591],[-92.760249,45.2496],[-92.751708,45.218666],[-92.763908,45.204866],[-92.767408,45.190166],[-92.764872,45.182812],[-92.752404,45.173916],[-92.757707,45.155466],[-92.739584,45.115598],[-92.744938,45.108309],[-92.791528,45.079647],[-92.803079,45.060978],[-92.793282,45.047178],[-92.770362,45.033803],[-92.76206,45.02432],[-92.771231,45.001378],[-92.769445,44.97215],[-92.754603,44.955767],[-92.750645,44.937299],[-92.758701,44.908979],[-92.774571,44.898084],[-92.773946,44.889997],[-92.764133,44.875905],[-92.769102,44.862167],[-92.765278,44.837186],[-92.78043,44.812589],[-92.785206,44.792303],[-92.805287,44.768361],[-92.807988,44.75147],[-92.787906,44.737432],[-92.737259,44.717155],[-92.700948,44.693751],[-92.660988,44.660884],[-92.632105,44.649027],[-92.619779,44.634195],[-92.621456,44.615017],[-92.601516,44.612052],[-92.586216,44.600088],[-92.569434,44.603539],[-92.549777,44.58113],[-92.549957,44.568988],[-92.540551,44.567258],[-92.518358,44.575183],[-92.493808,44.566063],[-92.481001,44.568276],[-92.455105,44.561886],[-92.433256,44.5655],[-92.399281,44.558292],[-92.361518,44.558935],[-92.336114,44.554004],[-92.314071,44.538014],[-92.302466,44.516487],[-92.302215,44.500298],[-92.291005,44.485464],[-92.232472,44.445434],[-92.195378,44.433792],[-92.124513,44.422115],[-92.111085,44.413948],[-92.078605,44.404869],[-92.056486,44.402729],[-92.038147,44.388731],[-91.970266,44.365842],[-91.941311,44.340978],[-91.92559,44.333548],[-91.918625,44.322671],[-91.913534,44.311392],[-91.924613,44.291815],[-91.896388,44.27469],[-91.896008,44.262871],[-91.88704,44.251772],[-91.892698,44.231105],[-91.877429,44.212921],[-91.872369,44.199167],[-91.829167,44.17835],[-91.808064,44.159262],[-91.751747,44.134786],[-91.721552,44.130342],[-91.710597,44.12048],[-91.708207,44.105186],[-91.69531,44.09857],[-91.68153,44.0974],[-91.667006,44.086964],[-91.647873,44.064109],[-91.638115,44.063285],[-91.610487,44.04931],[-91.59207,44.031372],[-91.507121,44.01898],[-91.48087,44.008145],[-91.463515,44.009041],[-91.432522,43.996827],[-91.407395,43.965148],[-91.385785,43.954239],[-91.366642,43.937463],[-91.357426,43.917231],[-91.347741,43.911964],[-91.338141,43.897664],[-91.320605,43.888491],[-91.310991,43.867381],[-91.284138,43.847065],[-91.262436,43.792166],[-91.244135,43.774667],[-91.255431,43.744876],[-91.255932,43.729849],[-91.268455,43.709824],[-91.273252,43.666623],[-91.271749,43.654929],[-91.262397,43.64176],[-91.268748,43.615348],[-91.232707,43.583533],[-91.232812,43.564842],[-91.243214,43.550722],[-91.243183,43.540309],[-91.232941,43.523967],[-91.218292,43.514434],[-91.217706,43.50055],[-96.453049,43.500415],[-96.453067,45.298115],[-96.489065,45.357071],[-96.521787,45.375645],[-96.562142,45.38609],[-96.617726,45.408092],[-96.680454,45.410499],[-96.692541,45.417338],[-96.731396,45.45702],[-96.76528,45.521414],[-96.857751,45.605962],[-96.844211,45.639583],[-96.835769,45.649648],[-96.760866,45.687518],[-96.745086,45.701576],[-96.662595,45.738682],[-96.641941,45.759871],[-96.627778,45.786239],[-96.583085,45.820024],[-96.574517,45.843098],[-96.561334,45.945655],[-96.57035,45.963595],[-96.57794,46.026874],[-96.559271,46.058272],[-96.554507,46.083978],[-96.557952,46.102442],[-96.56692,46.11475],[-96.563043,46.119512],[-96.571439,46.12572],[-96.56926,46.133686],[-96.579453,46.147601],[-96.577952,46.165843],[-96.587408,46.178164],[-96.584372,46.204155],[-96.59755,46.227733],[-96.598645,46.241626],[-96.590942,46.250183],[-96.59887,46.26069],[-96.595014,46.275135],[-96.60136,46.30413],[-96.599761,46.330386],[-96.619991,46.340135],[-96.618147,46.344295],[-96.629211,46.352654],[-96.644335,46.351908],[-96.646341,46.360982],[-96.655206,46.365964],[-96.658436,46.373391],[-96.666028,46.374566],[-96.669132,46.390037],[-96.680687,46.407383],[-96.688082,46.40788],[-96.701358,46.420584],[-96.703078,46.429467],[-96.718074,46.438255],[-96.715557,46.463232],[-96.73627,46.48138],[-96.737798,46.489785],[-96.733612,46.497224],[-96.737702,46.50077],[-96.738475,46.525793],[-96.744341,46.533006],[-96.743003,46.54294],[-96.74883,46.558127],[-96.744436,46.56596],[-96.746442,46.574078],[-96.772446,46.600129],[-96.774094,46.613288],[-96.78995,46.631531],[-96.790663,46.649112],[-96.798823,46.658071],[-96.792958,46.677427],[-96.784339,46.685054],[-96.790906,46.70297],[-96.779252,46.727429],[-96.784279,46.732993],[-96.781216,46.740944],[-96.787466,46.756753],[-96.784314,46.766973],[-96.796195,46.789881],[-96.795756,46.807795],[-96.801446,46.810401],[-96.80016,46.819664],[-96.787657,46.827817],[-96.789663,46.832306],[-96.779347,46.843672],[-96.781358,46.879363],[-96.768458,46.879563],[-96.767358,46.883663],[-96.773558,46.884763],[-96.776558,46.895663],[-96.759241,46.918223],[-96.761757,46.934663],[-96.78312,46.925482],[-96.79038,46.929398],[-96.791558,46.944464],[-96.797734,46.9464],[-96.798737,46.962399],[-96.821852,46.969372],[-96.82318,46.999965],[-96.834221,47.006671],[-96.829499,47.021537],[-96.818557,47.02778],[-96.821422,47.032842],[-96.819321,47.0529],[-96.824479,47.059682],[-96.818175,47.104193],[-96.827344,47.120144],[-96.824807,47.124968],[-96.831547,47.142017],[-96.822377,47.162744],[-96.829637,47.17497],[-96.826962,47.182802],[-96.838806,47.197894],[-96.832789,47.203911],[-96.838806,47.22502],[-96.832946,47.237588],[-96.83766,47.240876],[-96.835368,47.250428],[-96.841672,47.258164],[-96.838997,47.267716],[-96.842531,47.269531],[-96.844088,47.289981],[-96.832884,47.30449],[-96.841958,47.316907],[-96.835845,47.321014],[-96.835845,47.335914],[-96.852417,47.366241],[-96.848907,47.370565],[-96.852676,47.374973],[-96.846925,47.376891],[-96.840621,47.389881],[-96.845492,47.394179],[-96.844919,47.399815],[-96.863593,47.418775],[-96.85748,47.440457],[-96.859868,47.470926],[-96.85471,47.478281],[-96.85853,47.489934],[-96.851653,47.497098],[-96.851367,47.509037],[-96.866363,47.524893],[-96.85471,47.535973],[-96.859153,47.566355],[-96.853689,47.570381],[-96.856373,47.575749],[-96.851293,47.589264],[-96.856903,47.602329],[-96.855421,47.60875],[-96.873671,47.613654],[-96.871005,47.616832],[-96.879496,47.620576],[-96.882393,47.633489],[-96.888573,47.63845],[-96.882376,47.649025],[-96.88697,47.653049],[-96.887126,47.666369],[-96.895271,47.67357],[-96.899352,47.689473],[-96.908928,47.688722],[-96.907266,47.693976],[-96.920119,47.710383],[-96.923544,47.718201],[-96.919471,47.722515],[-96.932809,47.737139],[-96.928505,47.748037],[-96.934173,47.752412],[-96.939179,47.768397],[-96.9644,47.782995],[-96.957283,47.790147],[-96.966068,47.797297],[-96.975131,47.798326],[-96.980579,47.805614],[-96.979327,47.824533],[-96.986685,47.837639],[-96.998295,47.841724],[-96.998144,47.858882],[-97.005557,47.863977],[-97.002456,47.868677],[-97.023156,47.874978],[-97.019355,47.880278],[-97.024955,47.886878],[-97.019155,47.889778],[-97.024955,47.894978],[-97.020155,47.900478],[-97.024955,47.908178],[-97.017254,47.905678],[-97.015354,47.910278],[-97.023754,47.915878],[-97.018054,47.918078],[-97.035754,47.930179],[-97.036054,47.939379],[-97.054554,47.946279],[-97.052454,47.957179],[-97.061454,47.96358],[-97.053553,47.991612],[-97.064289,47.998508],[-97.066762,48.009558],[-97.063012,48.013179],[-97.072239,48.019107],[-97.068987,48.026267],[-97.072257,48.048068],[-97.097772,48.07108],[-97.103052,48.071669],[-97.099431,48.082106],[-97.105226,48.09044],[-97.104872,48.097851],[-97.109535,48.104723],[-97.123205,48.106648],[-97.120702,48.114987],[-97.131956,48.139563],[-97.141401,48.14359],[-97.138911,48.157793],[-97.146745,48.168556],[-97.141474,48.179099],[-97.146233,48.186054],[-97.134372,48.210434],[-97.136304,48.228984],[-97.141254,48.234668],[-97.135763,48.237596],[-97.138765,48.244991],[-97.127276,48.253323],[-97.131846,48.267589],[-97.11657,48.279661],[-97.12216,48.290056],[-97.128862,48.292882],[-97.122072,48.300865],[-97.132443,48.315489],[-97.127601,48.323319],[-97.134854,48.331314],[-97.131145,48.339722],[-97.147748,48.359905],[-97.140106,48.380479],[-97.145592,48.394195],[-97.135012,48.406735],[-97.142849,48.419471],[-97.1356,48.424369],[-97.139173,48.430528],[-97.134229,48.439797],[-97.137689,48.447583],[-97.132746,48.459942],[-97.144116,48.469212],[-97.141397,48.476256],[-97.144981,48.481571],[-97.140291,48.484722],[-97.138864,48.494362],[-97.148133,48.503384],[-97.153076,48.524148],[-97.150481,48.536877],[-97.163105,48.543855],[-97.160863,48.549236],[-97.152459,48.552326],[-97.158638,48.564067],[-97.149616,48.569876],[-97.14974,48.579516],[-97.142915,48.583733],[-97.143684,48.597066],[-97.137504,48.612268],[-97.132931,48.61338],[-97.130089,48.621166],[-97.125639,48.620919],[-97.125269,48.629694],[-97.108466,48.632658],[-97.111921,48.642918],[-97.100551,48.658614],[-97.102652,48.664793],[-97.097708,48.68395],[-97.118286,48.700573],[-97.116185,48.709348],[-97.136083,48.727763],[-97.139488,48.746611],[-97.151289,48.757428],[-97.147478,48.763698],[-97.154854,48.774515],[-97.157093,48.790024],[-97.163535,48.79507],[-97.165624,48.809627],[-97.180028,48.81845],[-97.177747,48.824815],[-97.181116,48.832741],[-97.173811,48.838309],[-97.175618,48.853105],[-97.187362,48.867598],[-97.185738,48.87222],[-97.197982,48.880341],[-97.197982,48.898332],[-97.210541,48.90439],[-97.211161,48.916649],[-97.217992,48.919735],[-97.218666,48.931781],[-97.224505,48.9341],[-97.232147,48.948955],[-97.230859,48.960891],[-97.239209,48.968684],[-97.237297,48.985696],[-97.230833,48.991303],[-97.229039,49.000687],[-95.153711,48.998903],[-95.15335,49.383079],[-95.126467,49.369439],[-95.058404,49.35317],[-95.014415,49.356405],[-94.988908,49.368897],[-94.957465,49.370186],[-94.854245,49.324154],[-94.816222,49.320987],[-94.824291,49.308834],[-94.82516,49.294283],[-94.797244,49.214284],[-94.797527,49.197791],[-94.773223,49.120733],[-94.750221,49.099763],[-94.750218,48.999992],[-94.718932,48.999991],[-94.683069,48.883929],[-94.684217,48.872399],[-94.692527,48.86895],[-94.693044,48.853392],[-94.685681,48.840119],[-94.701968,48.831778],[-94.704284,48.824284],[-94.694974,48.809206],[-94.694312,48.789352],[-94.690889,48.778066],[-94.651765,48.755913],[-94.645164,48.749975],[-94.645083,48.744143],[-94.61901,48.737374],[-94.58715,48.717599],[-94.549069,48.714653],[-94.533057,48.701262],[-94.452332,48.692444],[-94.438701,48.694889],[-94.416191,48.710948],[-94.384221,48.711806],[-94.342758,48.703382],[-94.308446,48.710239],[-94.290737,48.707747],[-94.260541,48.696381],[-94.251169,48.683514],[-94.254643,48.663888],[-94.250497,48.656654],[-94.224276,48.649527],[-94.091244,48.643669],[-94.065775,48.646104],[-94.035616,48.641018],[-94.006933,48.643193],[-93.944221,48.632294],[-93.91153,48.634673],[-93.840754,48.628548],[-93.824144,48.610724],[-93.806763,48.577616],[-93.811201,48.542385],[-93.818253,48.530046],[-93.794454,48.516021],[-93.656652,48.515731],[-93.643091,48.518294],[-93.628865,48.53121],[-93.612844,48.521876],[-93.60587,48.522472],[-93.594379,48.528793],[-93.547191,48.528684],[-93.467504,48.545664],[-93.460798,48.550552],[-93.456675,48.561834],[-93.465199,48.590659],[-93.438494,48.59338],[-93.405269,48.609344],[-93.395022,48.603303],[-93.371156,48.605085],[-93.362132,48.613832],[-93.35324,48.613378],[-93.349095,48.624935],[-93.254854,48.642784],[-93.207398,48.642474],[-93.178095,48.623339],[-93.088438,48.627597],[-92.984963,48.623731],[-92.954876,48.631493],[-92.95012,48.630419],[-92.949839,48.608269],[-92.929614,48.606874],[-92.909947,48.596313],[-92.894687,48.594915],[-92.728046,48.53929],[-92.657881,48.546263],[-92.634931,48.542873],[-92.625739,48.518189],[-92.631117,48.508252],[-92.627237,48.503383],[-92.636696,48.499428],[-92.654039,48.501635],[-92.661418,48.496557],[-92.698824,48.494892],[-92.712562,48.463013],[-92.687998,48.443889],[-92.656027,48.436709],[-92.507285,48.447875],[-92.475585,48.418793],[-92.456325,48.414204],[-92.456389,48.401134],[-92.47675,48.37176],[-92.469948,48.351836],[-92.437825,48.309839],[-92.416285,48.295463],[-92.369174,48.220268],[-92.336831,48.235383],[-92.269742,48.248241],[-92.273706,48.256747],[-92.294541,48.27156],[-92.292999,48.276404],[-92.301451,48.288608],[-92.294527,48.306454],[-92.306309,48.316442],[-92.304561,48.322977],[-92.295412,48.323957],[-92.288994,48.342991],[-92.26228,48.354933],[-92.222813,48.349203],[-92.216983,48.345114],[-92.206803,48.345596],[-92.203684,48.352063],[-92.178418,48.351881],[-92.177354,48.357228],[-92.145049,48.365651],[-92.143583,48.356121],[-92.083513,48.353865],[-92.077961,48.358253],[-92.055228,48.359213],[-92.045734,48.347901],[-92.046562,48.33474],[-92.037721,48.333183],[-92.030872,48.325824],[-92.000133,48.321355],[-92.01298,48.297391],[-92.006577,48.265421],[-91.989545,48.260214],[-91.976903,48.244626],[-91.971056,48.247667],[-91.971779,48.252977],[-91.954432,48.251678],[-91.952209,48.244394],[-91.957683,48.242683],[-91.957798,48.232989],[-91.941838,48.230602],[-91.915772,48.238871],[-91.89347,48.237699],[-91.884691,48.227321],[-91.867882,48.219095],[-91.864382,48.207031],[-91.815772,48.211748],[-91.809038,48.206013],[-91.79181,48.202492],[-91.789011,48.196549],[-91.756637,48.205022],[-91.749075,48.198844],[-91.741932,48.199122],[-91.742313,48.204491],[-91.714931,48.19913],[-91.711611,48.1891],[-91.721413,48.180255],[-91.724584,48.170657],[-91.705318,48.170775],[-91.70726,48.153661],[-91.698174,48.141643],[-91.699981,48.13184],[-91.712226,48.116883],[-91.703524,48.113548],[-91.682845,48.122118],[-91.687623,48.111698],[-91.676876,48.107264],[-91.665208,48.107011],[-91.653261,48.114137],[-91.653571,48.109567],[-91.640175,48.096926],[-91.559272,48.108268],[-91.552962,48.103012],[-91.569746,48.093348],[-91.575471,48.066294],[-91.575672,48.048791],[-91.567254,48.043719],[-91.488646,48.068065],[-91.45033,48.068806],[-91.437582,48.049248],[-91.429642,48.048608],[-91.391128,48.057075],[-91.370872,48.06941],[-91.365143,48.066968],[-91.340159,48.073236],[-91.332589,48.069331],[-91.26638,48.078713],[-91.214428,48.10294],[-91.190461,48.124891],[-91.183207,48.122235],[-91.176181,48.125811],[-91.137733,48.14915],[-91.139402,48.154738],[-91.092258,48.173101],[-91.082731,48.180756],[-91.024208,48.190072],[-90.976955,48.219452],[-90.914971,48.230603],[-90.88548,48.245784],[-90.875107,48.237784],[-90.847352,48.244443],[-90.839176,48.239511],[-90.836313,48.176963],[-90.832589,48.173765],[-90.821115,48.184709],[-90.817698,48.179569],[-90.804207,48.177833],[-90.796596,48.159373],[-90.777917,48.163801],[-90.778031,48.148723],[-90.79797,48.136894],[-90.787305,48.134196],[-90.789919,48.129902],[-90.76911,48.116585],[-90.761555,48.100133],[-90.751608,48.090968],[-90.641596,48.103515],[-90.626886,48.111846],[-90.59146,48.117546],[-90.582217,48.123784],[-90.55929,48.121683],[-90.555845,48.117069],[-90.569763,48.106951],[-90.567482,48.101178],[-90.556838,48.096008],[-90.487077,48.099082],[-90.467712,48.108818],[-90.438449,48.098747],[-90.403219,48.105114],[-90.374542,48.090942],[-90.367658,48.094577],[-90.344234,48.094447],[-90.330052,48.102399],[-90.312386,48.1053],[-90.289337,48.098993],[-90.224692,48.108148],[-90.188679,48.107947],[-90.176605,48.112445],[-90.136191,48.112136],[-90.116259,48.104303],[-90.073873,48.101138],[-90.023595,48.084708],[-90.015057,48.067188],[-90.008446,48.068396],[-89.997852,48.057567],[-89.99305,48.028404],[-89.97718,48.023501],[-89.968255,48.014482],[-89.954605,48.011516],[-89.95059,48.015901],[-89.934489,48.015628],[-89.915341,47.994866],[-89.897414,47.987599],[-89.873286,47.985419],[-89.868153,47.989898],[-89.847571,47.992442],[-89.842568,48.001368],[-89.830385,48.000284],[-89.820483,48.014665],[-89.797744,48.014505],[-89.763967,48.022969],[-89.724048,48.018996],[-89.721038,48.017965],[-89.724044,48.013675],[-89.716114,48.016441],[-89.716417,48.010251],[-89.702528,48.006325],[-89.673798,48.01151],[-89.667128,48.007421],[-89.657051,48.009954],[-89.649057,48.003853],[-89.617867,48.010947],[-89.611678,48.017529],[-89.607821,48.006566],[-89.594749,48.004332],[-89.582117,47.996314],[-89.564288,48.00293],[-89.489226,48.014528],[-89.495344,48.002356],[-89.541521,47.992841],[-89.551555,47.987305],[-89.555015,47.974849],[-89.572315,47.967238],[-89.58823,47.9662],[-89.611412,47.980731],[-89.624559,47.983153],[-89.631825,47.980039],[-89.640129,47.96793],[-89.638285,47.954275],[-89.697619,47.941288],[-89.793539,47.891358],[-89.85396,47.873997],[-89.87158,47.874194],[-89.923649,47.862062],[-89.930844,47.857723],[-89.92752,47.850825],[-89.933899,47.84676],[-89.974296,47.830514],[-90.072025,47.811105],[-90.075559,47.803303],[-90.1168,47.79538],[-90.16079,47.792807],[-90.178755,47.786414],[-90.187636,47.77813],[-90.248794,47.772763],[-90.323446,47.753771],[-90.332686,47.746387],[-90.437712,47.731612],[-90.441912,47.726404],[-90.458365,47.7214],[-90.537105,47.703055],[-90.551291,47.690266],[-90.735927,47.624343],[-90.86827,47.5569],[-90.907494,47.532873],[-90.914247,47.522639],[-90.939072,47.514532],[-91.032945,47.458236],[-91.045646,47.456525],[-91.097569,47.413888],[-91.128131,47.399619],[-91.146958,47.381464],[-91.156513,47.378816],[-91.188772,47.340082],[-91.238658,47.304976],[-91.262512,47.27929],[-91.288478,47.26596],[-91.326019,47.238993],[-91.357803,47.206743],[-91.418805,47.172152],[-91.477351,47.125667],[-91.497902,47.122579],[-91.518793,47.108121],[-91.573817,47.089917],[-91.591508,47.068684],[-91.626824,47.049953],[-91.644564,47.026491],[-91.666477,47.014297],[-91.704649,47.005246],[-91.780675,46.945881],[-91.806851,46.933727],[-91.841349,46.925215],[-91.883238,46.905728],[-91.914984,46.883836],[-91.952985,46.867037],[-92.094089,46.787839],[-92.088289,46.773639],[-92.06449,46.745439],[-92.025789,46.710839],[-92.01529,46.706469],[-92.020289,46.704039],[-92.03399,46.708939],[-92.08949,46.74924],[-92.10819,46.74914],[-92.13789,46.73954],[-92.14329,46.73464],[-92.141291,46.72524],[-92.146291,46.71594],[-92.167291,46.719941],[-92.189091,46.717541],[-92.204691,46.704041]]]},\"properties\":{\"name\":\"Minnesota\",\"nation\":\"USA \"}}]}","volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Landon, Adam C.","contributorId":279373,"corporation":false,"usgs":false,"family":"Landon","given":"Adam","email":"","middleInitial":"C.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":834907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pradhananga, Amit","contributorId":279374,"corporation":false,"usgs":false,"family":"Pradhananga","given":"Amit","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":834908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornicelli, Lou","contributorId":279375,"corporation":false,"usgs":false,"family":"Cornicelli","given":"Lou","email":"","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":834909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davenport, Mae A.","contributorId":279376,"corporation":false,"usgs":false,"family":"Davenport","given":"Mae A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":834910,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218177,"text":"sir20215002 - 2021 - Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","interactions":[],"lastModifiedDate":"2021-02-17T12:58:55.815161","indexId":"sir20215002","displayToPublicDate":"2021-02-16T13:00:15","publicationYear":"2021","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":"2021-5002","displayTitle":"Multilevel Groundwater Monitoring of Hydraulic Head, Water Temperature, and Chemical Constituents in the Eastern Snake River Plain Aquifer, Idaho National Laboratory, Idaho, 2014–18","title":"Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","docAbstract":"Radiochemical and chemical wastewater discharged to infiltration ponds and disposal wells since the early 1950s at the Idaho National Laboratory (INL), southeastern Idaho, has affected the water quality of the eastern Snake River Plain (ESRP) aquifer. In 2006, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, added a multilevel well-monitoring network to their ongoing monitoring program to begin describing the vertical movement and distribution of the chemical constituents in the ESRP aquifer.
The multilevel monitoring system (MLMS) at the INL has been ongoing since 2006, and this report summarizes data collected during 2014–18 from 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected, including 177 measurements from hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within well USGS 134 was not monitored owing to a valve failure.
Note: This is a partial abstract.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215002","collaboration":"DOE/ID-22254Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Milford Lake has been listed as impaired and designated hypereutrophic because of excessive nutrient loading, specifically biologically available orthophosphate. It is the largest lake by surface area in Kansas and is a reservoir built for purposes including water supply and recreation. In 2015, the Kansas Department of Health and Environment (KDHE) divided the lake into three zones (Zones A, B, and C) for recreational monitoring of harmful algal blooms (HABs). Upstream Zone C has historically been more affected by HABs than Zones B and A, and Zone C has historically had the highest phosphorus concentrations.
The U.S. Geological Survey, in cooperation with the KDHE, completed a study in 2017–18 to assess the spatial and temporal variability of nutrients and algae in the Republican River (the primary inflow to Milford Lake) and Milford Lake using spatially and temporally dense data. During the study period, discrete water-quality samples were collected at 36 lake sites, 21 river sites, and 1 pond. All samples were analyzed for nutrients; some samples were also analyzed for chlorophyll, phycocyanin, microcystin, and (or) phytoplankton community composition and abundance. Results from this study provide perspective for understanding the potential role nutrient and algal conditions have in facilitating the formation of HABs and may inform future actions to prevent and mitigate HABs and their potential effects on human and environmental health.
In 2017, one low-flow floating synoptic on the Republican River into Zone C of Milford Lake and one 24-hour synoptic in Zone C of Milford Lake were completed. Results from the low-flow floating synoptic on July 17, 2017, at 21 river sites, 8 lake sites, and 1 pond site indicated that the Republican River was not contributing dissolved orthophosphate or total phosphorus concentrations higher than those in the main body of Milford Lake.
No patterns in nutrient or total microcystin concentrations were evident from the 24-hour synoptic at two sites on August 24–25, 2017. Total nitrogen was dominated by total Kjeldahl nitrogen (TKN) at both sites. Different oscillation activity in algal biomass and chlorophyll at the two sites demonstrated the variable nature of algal accumulations and their effects on nutrient and dissolved oxygen concentrations. Different patterns in chlorophyll and microcystin concentrations indicate that the relation between algal biomass and cyanotoxin concentrations were different at the two sites, possibly because of differences among algal communities present at each site.
Three whole-lake synoptics through Zones A, B, and C in Milford Lake were completed on July 10, August 9, and October 16–17, 2018, at 30 lake sites. Orthophosphate was consistently at least 77 percent of total phosphorus at all sites except the two most uplake sites. At the two most uplake sites, orthophosphate was between 52 and 72 percent of the total phosphorus present at the site.
Concentrations of TKN were not consistently increasing or decreasing during 2018. Total nitrogen was dominated by TKN in July and August. Very low concentrations of dissolved nitrate plus nitrite indicate that the nutrient was likely tied up in algal biomass. By October, total nitrogen was approximately one-half TKN and one-half dissolved nitrate plus nitrite. Higher concentrations of dissolved orthophosphate and dissolved nitrate plus nitrite in October than in July and August were likely caused by reduced biological activity (less uptake of nutrients) and lower air and water temperatures. Multiple inflow events (streamflow greater than median daily value) between August and October also may have moved nutrients through the lake.
Chlorophyll, phycocyanin, microcystin, and phytoplankton samples were collected at eight sites in 2018. Most sites had their highest chlorophyll concentrations in August. The three most uplake sites had their highest phycocyanin concentrations in July, whereas the other five sites had their highest phycocyanin concentrations in August. Two of 23 samples had detections of total microcystin (0.11 and 0.12 microgram per liter). Phytoplankton community composition mainly consisted of Bacillariophyta, Chlorophyta, Cryptophyta, and Cyanobacteria. Phytoplankton community composition and abundance data described broad seasonal patterns and did not capture the full range of possible conditions at each site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205135","collaboration":"Prepared in cooperation with the Kansas Department of Health and Environment","usgsCitation":"Leiker, B.M., Abel, J.R., Graham, J.L., Foster, G.M., King, L.R., Stiles, T.C., and Buley, R.P., 2021, Spatial and temporal variability of nutrients and algae in the Republican River and Milford Lake, Kansas, June through November 2017 and May through November 2018: U.S. Geological Survey Scientific Investigations Report 2020–5135, 53 p., https://doi.org/10.3133/sir20205135.","productDescription":"Report: viii, 53 p.; 3 Data Releases; Dataset","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-116622","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":383231,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":383228,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XO24L3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phytoplankton data for Milford Lake, Kansas, June through October 2018"},{"id":383226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5135/coverthb.jpg"},{"id":383227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5135/sir20205135.pdf","text":"Report","size":"6.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5135"},{"id":383230,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZA2HE7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Vertical profiles of water-quality data from two sites in Milford Lake, Kansas, August 24–25, 2017"},{"id":383229,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CX2GFI","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Time-lapse photography of Milford Lake, Kansas, June through November 2017 and June through November 2018"}],"country":"United States","state":"Kansas","otherGeospatial":"Republican River, Milford Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.12875366210938,\n 39.03838632847035\n ],\n [\n -96.82937622070312,\n 39.03838632847035\n ],\n [\n -96.82937622070312,\n 39.32367475355144\n ],\n [\n -97.12875366210938,\n 39.32367475355144\n ],\n [\n -97.12875366210938,\n 39.03838632847035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Science impacts our daily lives and guides national and international policies (1). Thus, results of scientific studies are of paramount importance; yet, there are concerns that many studies are not reproducible or replicable (2). To address these concerns, the National Research Council conducted a Consensus Study [NASEM 2019 (3)] that provides definitions of key concepts, discussions of problems, and recommendations for dealing with these problems. These recommendations are useful and well considered, but they do not go far enough in our opinion. The NASEM recommendations treat reproducibility and replicability as single-study issues, despite clear acknowledgement of the limitations of isolated studies and the need for research synthesis (3). We advocate a strategic approach to research, focusing on the accumulation of evidence via designed sequences of studies, as a means of dealing more effectively with reproducibility, replicability, and related problems. These sequences are designed to provide iterative tests based on comparison of data from empirical studies with predictions from competing hypotheses. Evidence is then formally accumulated based on the relative predictive abilities of the different hypotheses as the sequential studies proceed.
Resource managers in the Pacific Northwest (USA) actively thin second-growth forests to accelerate the development of late-successional conditions and seek to expand these restoration thinning treatments into riparian zones. Riparian forest thinning, however, may impact stream temperatures–a key water quality parameter often regulated to protect stream habitat and aquatic organisms. To better understand the effects of riparian thinning on shade, light, and stream temperature, we employed a manipulative field experiment following a replicated Before-After-Control-Impact (BACI) design in three watersheds in the redwood forests of northern California, USA. Thinning treatments were intended to reduce canopy closure or basal area within the riparian zone by up to 50% on both sides of the stream channel along a 100–200 m stream reach. We found that responses to thinning ranged widely depending on the intensity of thinning treatments. In the watersheds with more intensive treatments, thinning reduced shade, increased light, and altered stream thermal regimes in thinned and downstream reaches. Thinning shifted thermal regimes by increasing maximum temperatures, thermal variability, and the frequency and duration of elevated temperatures. These thermal responses occurred primarily during summer but also extended into spring and fall. Longitudinal profiles indicated that increases in temperature associated with thinning frequently persisted downstream, but downstream effects depended on the magnitude of upstream temperature increases. Model selection analyses indicated that local changes in shade as well as upstream thermal conditions and proximity to upstream treatments explained variation in stream temperature responses to thinning. In contrast, in the study watershed with less intensive thinning, smaller changes in shade and light resulted in minimal stream temperature responses. Collectively, our data shed new light on the stream thermal responses to riparian thinning. These results provide relevant information for managers considering thinning as a viable restoration strategy for second-growth riparian forests.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0246822","usgsCitation":"Roon, D., Dunham, J.B., and Groom, J.D., 2021, Shade, light, and stream temperature responses to riparian thinning in second-growth redwood forests of northern California: PLoS ONE, v. 16, no. 2, e0246822, 25 p., https://doi.org/10.1371/journal.pone.0246822.","productDescription":"e0246822, 25 p.","ipdsId":"IP-124305","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":453427,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0246822","text":"Publisher Index Page"},{"id":384959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Redwood National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.21142578125,\n 41.50034959128928\n ],\n [\n -123.651123046875,\n 41.50034959128928\n ],\n [\n -123.651123046875,\n 42.00032514831621\n ],\n [\n -124.21142578125,\n 42.00032514831621\n ],\n [\n -124.21142578125,\n 41.50034959128928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Roon, David","contributorId":257063,"corporation":false,"usgs":false,"family":"Roon","given":"David","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":813772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Groom, Jeremiah D","contributorId":257065,"corporation":false,"usgs":false,"family":"Groom","given":"Jeremiah","email":"","middleInitial":"D","affiliations":[{"id":51978,"text":"Groom Analytics, LLC","active":true,"usgs":false}],"preferred":false,"id":813774,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218464,"text":"70218464 - 2021 - The Mars 2020 Perseverance rover mast camera zoom (Mastcam-Z) multispectral, stereoscopic imaging investigation","interactions":[],"lastModifiedDate":"2021-03-01T17:29:10.522513","indexId":"70218464","displayToPublicDate":"2021-02-15T11:15:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3454,"text":"Space Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The Mars 2020 Perseverance rover mast camera zoom (Mastcam-Z) multispectral, stereoscopic imaging investigation","docAbstract":"Mastcam-Z is a multispectral, stereoscopic imaging investigation on the Mars 2020 mission’s Perseverance rover. Mastcam-Z consists of a pair of focusable, 4:1 zoomable cameras that provide broadband red/green/blue and narrowband 400-1000 nm color imaging with fields of view from 25.6° × 19.2° (26 mm focal length at 283 μrad/pixel) to 6.2° × 4.6° (110 mm focal length at 67.4 μrad/pixel). The cameras can resolve (≥ 5 pixels) ∼0.7 mm features at 2 m and ∼3.3 cm features at 100 m distance. Mastcam-Z shares significant heritage with the Mastcam instruments on the Mars Science Laboratory Curiosity rover. Each Mastcam-Z camera consists of zoom, focus, and filter wheel mechanisms and a 1648 × 1214 pixel charge-coupled device detector and electronics. The two Mastcam-Z cameras are mounted with a 24.4 cm stereo baseline and 2.3° total toe-in on a camera plate ∼2 m above the surface on the rover’s Remote Sensing Mast, which provides azimuth and elevation actuation. A separate digital electronics assembly inside the rover provides power, data processing and storage, and the interface to the rover computer. Primary and secondary Mastcam-Z calibration targets mounted on the rover top deck enable tactical reflectance calibration. Mastcam-Z multispectral, stereo, and panoramic images will be used to provide detailed morphology, topography, and geologic context along the rover’s traverse; constrain mineralogic, photometric, and physical properties of surface materials; monitor and characterize atmospheric and astronomical phenomena; and document the rover’s sample extraction and caching locations. Mastcam-Z images will also provide key engineering information to support sample selection and other rover driving and tool/instrument operations decisions.
","language":"English","publisher":"Springer","doi":"10.1007/s11214-020-00755-x","usgsCitation":"Bell, J., Maki, J.N., Mehall, G.L., Ravine, M.A., Caplinger, M.A., Bailey, Z.J., Brylow, S., Schaffner, J.A., Kinch, K.M., Madsen, M.B., Winhold, A., Hayes, A.G., Corlies, P., Tate, C., Barrington, M., Cisneros, E., Jensen, E., Parise, K.L., Crawford, K., Rojas, C., Mehall, L., Joseph, J., Proton, J.B., Cluff, N., Deen, R.G., Betts, B., Cloutis, E., Coates, A.J., Colaprete, A., Edgett, K.S., Ehlmann, B.L., Fagents, S.A., Grotzinger, J., Hardgrove, C., Herkenhoff, K., Horgan, B.H., Jaumann, R., Johnson, J., Lemmon, M.T., Paar, G., Caballo-Perucha, M., Gupta, S., Traxler, C., Preusker, F., Rice, M.S., Robinson, M., Schmitz, N., Sullivan, R., and Wolff, M.J., 2021, The Mars 2020 Perseverance rover mast camera zoom (Mastcam-Z) multispectral, stereoscopic imaging investigation: Space Science Reviews, v. 217, 24, 40 p., https://doi.org/10.1007/s11214-020-00755-x.","productDescription":"24, 40 p.","ipdsId":"IP-119257","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":453429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11214-020-00755-x","text":"Publisher Index Page"},{"id":383699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"217","noUsgsAuthors":false,"publicationDate":"2021-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Bell, J. F. III","contributorId":252853,"corporation":false,"usgs":false,"family":"Bell","given":"J. F.","suffix":"III","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, J. N.","contributorId":252854,"corporation":false,"usgs":false,"family":"Maki","given":"J.","email":"","middleInitial":"N.","affiliations":[{"id":50450,"text":"JPL/Caltech, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":811019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mehall, G. L.","contributorId":252855,"corporation":false,"usgs":false,"family":"Mehall","given":"G.","email":"","middleInitial":"L.","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravine, M. A.","contributorId":252856,"corporation":false,"usgs":false,"family":"Ravine","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":50451,"text":"Malin Space Science Systems, Inc; San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":811021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caplinger, M. A.","contributorId":252857,"corporation":false,"usgs":false,"family":"Caplinger","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":50451,"text":"Malin Space Science Systems, Inc; San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":811022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bailey, Z. J.","contributorId":252858,"corporation":false,"usgs":false,"family":"Bailey","given":"Z.","email":"","middleInitial":"J.","affiliations":[{"id":50450,"text":"JPL/Caltech, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":811023,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brylow, S.","contributorId":252859,"corporation":false,"usgs":false,"family":"Brylow","given":"S.","affiliations":[{"id":50451,"text":"Malin Space Science Systems, Inc; San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":811024,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schaffner, J. A.","contributorId":252860,"corporation":false,"usgs":false,"family":"Schaffner","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":50451,"text":"Malin Space Science Systems, Inc; San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":811025,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kinch, K. M.","contributorId":252861,"corporation":false,"usgs":false,"family":"Kinch","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":40283,"text":"University of Copenhagen, Denmark","active":true,"usgs":false}],"preferred":false,"id":811026,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Madsen, M. B.","contributorId":252862,"corporation":false,"usgs":false,"family":"Madsen","given":"M.","email":"","middleInitial":"B.","affiliations":[{"id":40283,"text":"University of Copenhagen, Denmark","active":true,"usgs":false}],"preferred":false,"id":811027,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Winhold, A.","contributorId":252863,"corporation":false,"usgs":false,"family":"Winhold","given":"A.","email":"","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811028,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hayes, A. G.","contributorId":252864,"corporation":false,"usgs":false,"family":"Hayes","given":"A.","email":"","middleInitial":"G.","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":811029,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Corlies, P.","contributorId":252865,"corporation":false,"usgs":false,"family":"Corlies","given":"P.","email":"","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":811030,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Tate, C.","contributorId":252866,"corporation":false,"usgs":false,"family":"Tate","given":"C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":811031,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Barrington, M.","contributorId":252867,"corporation":false,"usgs":false,"family":"Barrington","given":"M.","email":"","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":811032,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cisneros, E.","contributorId":196213,"corporation":false,"usgs":false,"family":"Cisneros","given":"E.","email":"","affiliations":[{"id":34032,"text":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287","active":true,"usgs":false}],"preferred":false,"id":811033,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Jensen, E.","contributorId":196211,"corporation":false,"usgs":false,"family":"Jensen","given":"E.","affiliations":[{"id":24734,"text":"Malin Space Science Systems, San Diego","active":true,"usgs":false}],"preferred":false,"id":811034,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Parise, Katy L.","contributorId":201310,"corporation":false,"usgs":false,"family":"Parise","given":"Katy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":811035,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Crawford, Kelon","contributorId":248362,"corporation":false,"usgs":false,"family":"Crawford","given":"Kelon","email":"","affiliations":[],"preferred":false,"id":811036,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rojas, C.","contributorId":252868,"corporation":false,"usgs":false,"family":"Rojas","given":"C.","email":"","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811037,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Mehall, L.","contributorId":252869,"corporation":false,"usgs":false,"family":"Mehall","given":"L.","email":"","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811038,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Joseph, J.","contributorId":252870,"corporation":false,"usgs":false,"family":"Joseph","given":"J.","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":811039,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Proton, J. B.","contributorId":252871,"corporation":false,"usgs":false,"family":"Proton","given":"J.","email":"","middleInitial":"B.","affiliations":[{"id":50452,"text":"Opscode LLC, Healdsburg, CA","active":true,"usgs":false}],"preferred":false,"id":811040,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Cluff, N.","contributorId":252872,"corporation":false,"usgs":false,"family":"Cluff","given":"N.","email":"","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811041,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Deen, R. G.","contributorId":196214,"corporation":false,"usgs":false,"family":"Deen","given":"R.","email":"","middleInitial":"G.","affiliations":[{"id":27151,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":811042,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Betts, B.","contributorId":252873,"corporation":false,"usgs":false,"family":"Betts","given":"B.","email":"","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":811043,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Cloutis, Edward A.","contributorId":147771,"corporation":false,"usgs":false,"family":"Cloutis","given":"Edward A.","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":811044,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Coates, A. J.","contributorId":252874,"corporation":false,"usgs":false,"family":"Coates","given":"A.","email":"","middleInitial":"J.","affiliations":[{"id":50453,"text":"Mullard Space Science Laboratory, (MSSL) University College, London, England","active":true,"usgs":false}],"preferred":false,"id":811045,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Colaprete, Anthony","contributorId":197548,"corporation":false,"usgs":false,"family":"Colaprete","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":811046,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Edgett, K. S.","contributorId":252875,"corporation":false,"usgs":false,"family":"Edgett","given":"K.","email":"","middleInitial":"S.","affiliations":[{"id":50451,"text":"Malin Space Science Systems, Inc; San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":811047,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Ehlmann, B. L.","contributorId":252876,"corporation":false,"usgs":false,"family":"Ehlmann","given":"B.","email":"","middleInitial":"L.","affiliations":[{"id":50450,"text":"JPL/Caltech, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":811048,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Fagents, Sarah A.","contributorId":243389,"corporation":false,"usgs":false,"family":"Fagents","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":48709,"text":"University of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":811049,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Grotzinger, J. P.","contributorId":252877,"corporation":false,"usgs":false,"family":"Grotzinger","given":"J. P.","affiliations":[{"id":50454,"text":"Caltech, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":811050,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Hardgrove, C.","contributorId":196209,"corporation":false,"usgs":false,"family":"Hardgrove","given":"C.","affiliations":[{"id":34032,"text":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287","active":true,"usgs":false}],"preferred":false,"id":811051,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"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":811052,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Horgan, Briony H. N.","contributorId":174123,"corporation":false,"usgs":false,"family":"Horgan","given":"Briony","email":"","middleInitial":"H. N.","affiliations":[{"id":27363,"text":"Purdue University, Dept. Earth, Atmospheric, and Planetary Sciences","active":true,"usgs":false}],"preferred":false,"id":811053,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Jaumann, R.","contributorId":238487,"corporation":false,"usgs":false,"family":"Jaumann","given":"R.","affiliations":[],"preferred":false,"id":811054,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Johnson, J. R.","contributorId":252878,"corporation":false,"usgs":false,"family":"Johnson","given":"J. R.","affiliations":[{"id":50455,"text":"APL/Johns Hopkins University, Laurel, MD","active":true,"usgs":false}],"preferred":false,"id":811055,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Lemmon, M. T.","contributorId":196203,"corporation":false,"usgs":false,"family":"Lemmon","given":"M.","email":"","middleInitial":"T.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":811056,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Paar, G.","contributorId":252879,"corporation":false,"usgs":false,"family":"Paar","given":"G.","email":"","affiliations":[{"id":50456,"text":"Joanneum Research, Graz, Austria","active":true,"usgs":false}],"preferred":false,"id":811057,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Caballo-Perucha, M","contributorId":252880,"corporation":false,"usgs":false,"family":"Caballo-Perucha","given":"M","email":"","affiliations":[{"id":50456,"text":"Joanneum Research, Graz, Austria","active":true,"usgs":false}],"preferred":false,"id":811058,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Gupta, S.","contributorId":177658,"corporation":false,"usgs":false,"family":"Gupta","given":"S.","email":"","affiliations":[],"preferred":false,"id":811059,"contributorType":{"id":1,"text":"Authors"},"rank":42},{"text":"Traxler, C","contributorId":252881,"corporation":false,"usgs":false,"family":"Traxler","given":"C","email":"","affiliations":[{"id":50456,"text":"Joanneum Research, Graz, Austria","active":true,"usgs":false}],"preferred":false,"id":811060,"contributorType":{"id":1,"text":"Authors"},"rank":43},{"text":"Preusker, F.","contributorId":238492,"corporation":false,"usgs":false,"family":"Preusker","given":"F.","affiliations":[],"preferred":false,"id":811061,"contributorType":{"id":1,"text":"Authors"},"rank":44},{"text":"Rice, M. S.","contributorId":252882,"corporation":false,"usgs":false,"family":"Rice","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":50457,"text":"Western Washington University, Bellingham, WA","active":true,"usgs":false}],"preferred":false,"id":811062,"contributorType":{"id":1,"text":"Authors"},"rank":45},{"text":"Robinson, M. S.","contributorId":252883,"corporation":false,"usgs":false,"family":"Robinson","given":"M. S.","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":811063,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Schmitz, N.","contributorId":252884,"corporation":false,"usgs":false,"family":"Schmitz","given":"N.","affiliations":[{"id":50458,"text":"DLR/German Aerospace Center, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":811064,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Sullivan, R.","contributorId":167408,"corporation":false,"usgs":false,"family":"Sullivan","given":"R.","email":"","affiliations":[],"preferred":false,"id":811065,"contributorType":{"id":1,"text":"Authors"},"rank":48},{"text":"Wolff, M. J.","contributorId":252885,"corporation":false,"usgs":false,"family":"Wolff","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":50459,"text":"Space Science Institute, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":811066,"contributorType":{"id":1,"text":"Authors"},"rank":49}]}} ]}