{"pageNumber":"376","pageRowStart":"9375","pageSize":"25","recordCount":184776,"records":[{"id":70232246,"text":"70232246 - 2022 - Resisting-accepting-directing: Ecosystem management guided by an ecological resilience assessment","interactions":[],"lastModifiedDate":"2022-09-01T14:39:17.941033","indexId":"70232246","displayToPublicDate":"2022-06-17T08:52:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Resisting-accepting-directing: Ecosystem management guided by an ecological resilience assessment","docAbstract":"As anthropogenic influences push ecosystems past tipping points and into new regimes, complex management decisions are complicated by rapid ecosystem changes that may be difficult to reverse. For managers who grapple with how to manage ecosystems under novel conditions and heightened uncertainty, advancing our understanding of regime shifts is paramount. As part of an ecological resilience assessment, researchers and managers have collaborated to identify alternate regimes and build an understanding of the thresholds and factors that govern regime shifts in the Upper Mississippi River System. To describe the management implications of our assessment, we integrate our findings with a recently developed framework that explicitly acknowledges ecosystem regime change and outlines management approaches of resisting change, accepting change, or directing change. More specifically, we developed guidance for using knowledge of desirability of current conditions, distance to thresholds, and general resilience (that is, an ecosystem’s capacity to cope with uncertain disturbances) to navigate the resist-accept-direct (RAD) framework. We applied this guidance to outline strategies that resist, accept, or direct change in the context of management of aquatic vegetation, floodplain vegetation, and fish communities across nearly 2000 river kilometers. We provide a case study for how knowledge of ecological dynamics can aid in assessing which management approach(es) are likely to be most ecologically feasible in a changing world. Continued learning from management decisions will be critical to advance our understanding of how ecosystems respond and inform the management of ecosystems for desirable and resilient outcomes.","language":"English","publisher":"Springer","doi":"10.1007/s00267-022-01667-y","usgsCitation":"Bouska, K.L., De Jager, N.R., and Houser, J.N., 2022, Resisting-accepting-directing: Ecosystem management guided by an ecological resilience assessment: Environmental Management, v. 70, p. 381-400, https://doi.org/10.1007/s00267-022-01667-y.","productDescription":"20 p.","startPage":"381","endPage":"400","ipdsId":"IP-136096","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":402324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Kentucky, Minnesota, Missouri, Wisconsin","otherGeospatial":"Mississippi River","geographicExtents":"{\n 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kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":844789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":844790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":844791,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232245,"text":"70232245 - 2022 - Data-driven modeling of wind waves in upper Delaware Bay with living shorelines","interactions":[],"lastModifiedDate":"2023-06-09T13:38:42.887571","indexId":"70232245","displayToPublicDate":"2022-06-17T08:36:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2924,"text":"Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Data-driven modeling of wind waves in upper Delaware Bay with living shorelines","docAbstract":"Living shoreline projects have been built to preserve coastal ecosystems under future climate change and sea level rise. To quantify the wave power variation across living shorelines, the wave characteristics around the constructed oyster reefs (CORs) in upper Delaware Bay were investigated in this study. Wave parameters seaward and shoreward of CORs were recorded by wave gauges in early 2018. Four winter storms happened in this period and induced strong winds and coastal flooding at the study site. To estimate the wind wave characteristics across the CORs on a yearly basis, soft computing-based models combining fully connected neural networks and long short-term memory were developed to extend the two-month energetic wave measurements. The results show that when CORs were emergent or slightly submerged, the averaged wave height attenuation was about 39.8% from the offshore gauge to the nearshore gauge (behind CORs) during 2018–2020, owing to the combined effect of nearshore bathymetric changes and CORs. Furthermore, it was found that the annually averaged wave power reduction from offshore to nearshore at the study site was about 30.0% in 2018, 2019, and 2020. This study provides a novel framework to predict long-term wave characteristics based on short-term wave measurements using soft computing-based models.","language":"English","publisher":"Elsevier","doi":"10.1016/j.oceaneng.2022.111669","usgsCitation":"Wang, N., Chen, Q., Zhu, L., and Wang, H., 2022, Data-driven modeling of wind waves in upper Delaware Bay with living shorelines: Ocean Engineering, v. 257, 111669, 17 p.; Data Release, https://doi.org/10.1016/j.oceaneng.2022.111669.","productDescription":"111669, 17 p.; Data Release","ipdsId":"IP-134698","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447399,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oceaneng.2022.111669","text":"Publisher Index Page"},{"id":402319,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417837,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YEUNTM"}],"country":"United States","state":"New Jersey","otherGeospatial":"Delaware Bay, Gandys Beach, Money Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.26407241821289,\n 39.26601861676037\n ],\n [\n -75.20862579345703,\n 39.26601861676037\n ],\n [\n -75.20862579345703,\n 39.29179704377487\n ],\n [\n -75.26407241821289,\n 39.29179704377487\n ],\n [\n -75.26407241821289,\n 39.26601861676037\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"257","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Nan 0000-0001-7569-9598","orcid":"https://orcid.org/0000-0001-7569-9598","contributorId":291600,"corporation":false,"usgs":false,"family":"Wang","given":"Nan","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":844785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":844786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":844787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844788,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232341,"text":"70232341 - 2022 - Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","interactions":[],"lastModifiedDate":"2022-06-28T12:44:32.089718","indexId":"70232341","displayToPublicDate":"2022-06-17T07:39:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10939,"text":"Frontiers in Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","docAbstract":"

In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fbuil.2022.884849","usgsCitation":"Salatin, R., Wang, H., Chen, Q., and Zhu, L., 2022, Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines: Frontiers in Built Environment, v. 8, 884849, 16 p., https://doi.org/10.3389/fbuil.2022.884849.","productDescription":"884849, 16 p.","ipdsId":"IP-138476","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fbuil.2022.884849","text":"Publisher Index Page"},{"id":402591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.849609375,\n 38.496593518947584\n ],\n [\n -74.5751953125,\n 38.496593518947584\n ],\n [\n -74.5751953125,\n 40.019201307686785\n ],\n [\n -75.849609375,\n 40.019201307686785\n ],\n [\n -75.849609375,\n 38.496593518947584\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Salatin, Reza 0000-0001-5372-3948","orcid":"https://orcid.org/0000-0001-5372-3948","contributorId":292618,"corporation":false,"usgs":false,"family":"Salatin","given":"Reza","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":845287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845288,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232243,"text":"sir20225055 - 2022 - Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","interactions":[],"lastModifiedDate":"2026-04-23T16:36:07.756303","indexId":"sir20225055","displayToPublicDate":"2022-06-17T07:23:22","publicationYear":"2022","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":"2022-5055","displayTitle":"Assessment of Streamflow Trends in the Eastern Dakotas, Water Years 1960–2019","title":"Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","docAbstract":"

Hydrologic extremes, whether periods of drought or flooding, are occurring more frequently with greater severity and can have substantial economic impacts. Along with flooding, the timing and volume of streamflow also is changing across the United States. The focus of this report is to characterize a unique trend in mean annual streamflow occurring in eastern North and South Dakota, hereafter referred to as the eastern Dakotas, that is not being observed anywhere else in the conterminous United States.

Streamflow records for 1,853 U.S. Geological Survey streamgages obtained from the U.S. Geological Survey National Water Information System database with a continuous record of mean annual streamflow during water years 1960–2019 were included in this study. Using a Kendall tau statistical test (p-value less than or equal to 0.10), 573 streamgages had a statistically significant upward trend in mean annual streamflow and are primarily located in the Midwest and northeastern United States. Of the streamgages, 182 had a statistically significant downward trend and are located primarily in the western and southeastern States. Several sites had increases in streamflow between 100 and 500 percent. Most of the streamgages with the highest increases in mean annual streamflow are along the same rivers in the eastern Dakotas, regardless of basin size.

A comparison of mean annual streamflow of the last decade (2010–19) to the first decade (1960–69) of the study period shows that the largest increases in annual streamflow volumes in the United States also are in the eastern Dakotas. Among all 1,853 streamgages in the United States, the Sheyenne River near Warwick, North Dakota (U.S. Geological Survey station 05056000), has the greatest percent change, with an increase of 486 percent. Several factors may be contributing to increasing trends in streamflow in the eastern Dakotas and may include, in part, precipitation changes owing to climatic variation within the region, geologic makeup of the subsurface, and land-use changes. A better understanding of these research areas will help producers, resource managers, and infrastructure engineers to make more informed environmental and economic decisions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225055","usgsCitation":"Norton, P.A., Delzer, G.C., Valder, J.F., Tatge, W.S., and Ryberg, K.R., 2022, Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019: U.S. Geological Survey Scientific Investigations Report 2022–5055, 11 p., https://doi.org/10.3133/sir20225055.","productDescription":"Report: iv, 11 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-134818","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":402287,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":402283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5055/coverthb.jpg"},{"id":402285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.XML"},{"id":402284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5055"},{"id":402286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5055/images"},{"id":402316,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225055/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":503369,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113196.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.7666015625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 42.90816007196054\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-17","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Delzer, Gregory C. 0000-0002-7077-4963 gcdelzer@usgs.gov","orcid":"https://orcid.org/0000-0002-7077-4963","contributorId":986,"corporation":false,"usgs":true,"family":"Delzer","given":"Gregory","email":"gcdelzer@usgs.gov","middleInitial":"C.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":220912,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844777,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236046,"text":"70236046 - 2022 - Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA","interactions":[],"lastModifiedDate":"2022-08-26T12:16:47.972733","indexId":"70236046","displayToPublicDate":"2022-06-17T07:10:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA","docAbstract":"

The Salton Trough (southeastern California, USA) is the northernmost transtensional stepover of the Gulf of California oblique-divergent plate boundary and is also where the southern terminus of the San Andreas fault occurs. Until recently, the distribution of active faults in and around the Salton Sea and their displacement histories were largely unknown. Subbottom CHIRP (compressed high-intensity radar pulse) surveys in the Salton Sea are used to develop a seismic facies model for ancient Lake Cahuilla deposits, a detailed map of submerged active faults, and reconstructed fault displacement histories during the late Holocene. We observe as many as fourteen Lake Cahuilla sequences in the Salton Sea (last ~3 k.y.) and develop a chronostratigraphic framework for the last six sequences (last ~1200 yr) by integrating CHIRP data and cone penetrometer logs with radiocarbon-dated stratigraphy at an onshore paleoseismic site. The Salton Sea contains northern and southern subbasins that appear to be separated by a tectonic hinge zone, and a subsidence signal across hinge-zone faults of 6–9 mm/yr (since ca. A.D. 940) increases toward the south to >15 mm/yr. The faults mapped to the south of the hinge zone appear to accommodate transtension within the San Andreas–Imperial fault stepover. We identify 8–15 distinct growth events across hinge-zone faults, meaning growth occurred at least once every 100 yr since Lake Cahuilla sedimentation began. Several faults offset the top of the most recent Lake Cahuilla highstand deposits, and at least two faults have offset the Salton Sea flood deposits. Active faults and folds were also mapped to a limited extent within the northern subbasin and display growth, but their kinematics and rupture histories require further study. The broad distribution of active faulting suggests that strain between the San Andreas, San Jacinto, and Imperial faults is highly distributed, thus discrepancies between geologic and geodetic slip-rate estimates from these major fault systems are to be expected.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02468.1","usgsCitation":"Brothers, D., Driscoll, N.W., Kent, G., Baskin, R.L., Harding, A.J., and Kell, A., 2022, Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA: Geosphere, v. 18, no. 4, p. 1354-1376, https://doi.org/10.1130/GES02468.1.","productDescription":"23 p.","startPage":"1354","endPage":"1376","ipdsId":"IP-138899","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":447403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02468.1","text":"Publisher Index Page"},{"id":405678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salton Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.5,\n 32.5\n ],\n [\n -115,\n 32.5\n ],\n [\n -115,\n 34\n ],\n [\n -116.5,\n 34\n ],\n [\n -116.5,\n 32.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Brothers, Daniel","contributorId":295722,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":849801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Neal W.","contributorId":63266,"corporation":false,"usgs":true,"family":"Driscoll","given":"Neal","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":849802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kent, Graham","contributorId":7608,"corporation":false,"usgs":true,"family":"Kent","given":"Graham","affiliations":[],"preferred":false,"id":849803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baskin, Robert L. 0000-0002-2175-8502 rbaskin@usgs.gov","orcid":"https://orcid.org/0000-0002-2175-8502","contributorId":360,"corporation":false,"usgs":true,"family":"Baskin","given":"Robert","email":"rbaskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":849804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harding, Alistair J.","contributorId":53270,"corporation":false,"usgs":true,"family":"Harding","given":"Alistair","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":849805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kell, Annie","contributorId":68176,"corporation":false,"usgs":true,"family":"Kell","given":"Annie","affiliations":[],"preferred":false,"id":849806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232392,"text":"70232392 - 2022 - Hidden in plain sight: Migration routes of the elusive Anadyr bar-tailed godwit revealed by satellite tracking","interactions":[],"lastModifiedDate":"2022-09-01T14:43:07.854381","indexId":"70232392","displayToPublicDate":"2022-06-16T11:53:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Hidden in plain sight: Migration routes of the elusive Anadyr bar-tailed godwit revealed by satellite tracking","docAbstract":"

Satellite and GPS tracking technology continues to reveal new migration patterns of birds which enables comparative studies of migration strategies and distributional information useful in conservation. Bar-tailed godwits in the East Asian–Australasian Flyway Limosa lapponica baueri and L. l. menzbieri are known for their long non-stop flights, however these populations are in steep decline. A third subspecies in this flyway, L. l. anadyrensis, breeds in the Anadyr River basin, Chukotka, Russia, and is morphologically distinct from menzbieri and baueri based on comparison of museum specimens collected from breeding areas. However, the non-breeding distribution, migration route and population size of anadyrensis are entirely unknown. Among 24 female bar-tailed godwits tracked in 2015–2018 from northwest Australia, the main non-breeding area for menzbieri, two birds migrated further east than the rest to breed in the Anadyr River basin, i.e. they belonged to the anadyrensis subspecies. During pre-breeding migration, all birds staged in the Yellow Sea and then flew to the breeding grounds in the eastern Russian Arctic. After breeding, these two birds migrated southwestward to stage in Russia on the Kamchatka Peninsula and on Sakhalin Island en route to the Yellow Sea. This contrasts with the other 22 tracked godwits that followed the previously described route of menzbieri, i.e. they all migrated northwards to stage in the New Siberian Islands before turning south towards the Yellow Sea, and onwards to northwest Australia. Since the Kamchatka Peninsula was not used by any of the tracked menzbieri birds, the 4500 godwits counted in the Khairusova–Belogolovaya estuary in western Kamchatka may well be anadyrensis. Comparing migration patterns across the three bar-tailed godwits subspecies, the migration strategy of anadyrensis lies between that of menzbieri and baueri. Future investigations combining migration tracks with genomic data could reveal how differences in migration routines are evolved and maintained.

","language":"English","publisher":"Wiley","doi":"10.1111/jav.02988","usgsCitation":"Chan, Y., Tibbitts, T.L., Dorofeev, D., Hassell, C.J., and Piersma, T., 2022, Hidden in plain sight: Migration routes of the elusive Anadyr bar-tailed godwit revealed by satellite tracking: Journal of Avian Biology, v. 2022, no. 8, e02988, 11 p., https://doi.org/10.1111/jav.02988.","productDescription":"e02988, 11 p.","ipdsId":"IP-134993","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":447405,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jav.02988","text":"External Repository"},{"id":402766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, China, Russia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 179.6484375,\n 64.32087157990324\n ],\n [\n 177.18749999999997,\n 68.9110048456202\n ],\n [\n 152.9296875,\n 71.52490903732816\n ],\n [\n 103.0078125,\n 5.965753671065536\n ],\n [\n 109.6875,\n -22.593726063929296\n ],\n [\n 117.7734375,\n -21.943045533438166\n ],\n [\n 130.4296875,\n -12.897489183755892\n ],\n [\n 139.5703125,\n 37.16031654673677\n ],\n [\n 179.6484375,\n 64.32087157990324\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2022","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Chan, Ying-Chi","contributorId":167762,"corporation":false,"usgs":false,"family":"Chan","given":"Ying-Chi","email":"","affiliations":[{"id":24822,"text":"Department of Marine Ecology, NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":845416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":845417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorofeev, Dmitry","contributorId":292661,"corporation":false,"usgs":false,"family":"Dorofeev","given":"Dmitry","email":"","affiliations":[{"id":62965,"text":"All Russian Research Institute for Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":845418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hassell, Chris J.","contributorId":127818,"corporation":false,"usgs":false,"family":"Hassell","given":"Chris","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":845419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piersma, Theunis 0000-0001-9668-466X","orcid":"https://orcid.org/0000-0001-9668-466X","contributorId":203123,"corporation":false,"usgs":false,"family":"Piersma","given":"Theunis","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":845420,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232229,"text":"70232229 - 2022 - Highly pathogenic avian influenza (HPAI): An emerging disease threat in North America","interactions":[],"lastModifiedDate":"2022-06-16T14:58:31.90211","indexId":"70232229","displayToPublicDate":"2022-06-16T09:32:02","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Highly pathogenic avian influenza (HPAI): An emerging disease threat in North America","docAbstract":"Highly pathogenic avian influenza (HPAI) is an ecologically and economically significant avian disease that is quickly spreading among wild and domestic birds throughout North America. 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chemistry and plasma protein values between gold standard analyzers and four point-of-care devices in free-ranging canvasbacks (Aythya valisineria)","docAbstract":"

Accurate, timely, and cost-effective blood chemistry analysis is an essential tool for directing emergency treatment, monitoring the health status of captive and free-ranging individuals and flocks, and improving the efficacy of conservation actions. Blood samples were obtained from 52 canvasbacks (Aythya valisineria) that were captured on San Francisco Bay, California, during December 2017 as part of a long-term study. Reference values and clinical agreement were determined for blood chemistry and plasma protein parameters among four commonly used point-of-care devices (VetScan® VS2, i-STAT®, AlphaTRAK®2 glucometer, refractometer) and two gold standard laboratory analyzers (Roche cobas® c501, Helena SPIFE 3000 system). Canvasback reference values were generally within expected ranges for Anatidae species with the exception of higher upper limits for sodium and chloride. Creatine kinase and aspartate transaminase values exceeded a published threshold for diagnosis of capture myopathy even though study birds were captured using low-stress techniques and successfully released. With the exception of higher alkaline phosphatase in hatch-year canvasbacks, no age or sex differences were observed for any analyte in this population that was captured during a nonbreeding period. Analysis of analyzer agreement found raw VetScan aspartate transaminase, calcium, glucose, and uric acid values; corrected VetScan albumin, potassium, sodium, and total protein values; raw i-STAT glucose and potassium values; and corrected i-STAT sodium and chloride values were clinically interchangeable with Roche cobas values. Raw VetScan and i-STAT glucose values were also interchangeable. However, none of the Roche or point-of-care analyzer plasma protein values were in clinical agreement with gold standard electrophoresis values. The findings of this study highlight the need for analyzer- or technique-specific reference values and provide biologists and veterinarians quantitative reference values using currently available analyzers to better assess and respond to the health of individuals and populations.

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Drayer Wildlife Health Center, School of Veterinary Medicine, 1 Shields Avenue, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":863483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziccardi, Michael H.","contributorId":74617,"corporation":false,"usgs":false,"family":"Ziccardi","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":863484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martinez-Lopez, Beatriz","contributorId":241986,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Beatriz","email":"","affiliations":[{"id":48468,"text":"University of California Agricultural Issues Center, Davis, Shields Ave, Davis, California 95616, USA","active":true,"usgs":false}],"preferred":false,"id":863485,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232232,"text":"70232232 - 2022 - A refined assessment of the paleoceanographic and tectonic influences on the deposition of the Monterey Formation in California","interactions":[],"lastModifiedDate":"2022-06-16T14:30:09.884587","indexId":"70232232","displayToPublicDate":"2022-06-16T09:14:07","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5614,"text":"Special Papers of the Geological Society of America","printIssn":"0072-1077","active":true,"publicationSubtype":{"id":24}},"title":"A refined assessment of the paleoceanographic and tectonic influences on the deposition of the Monterey Formation in California","docAbstract":"Application of updated diatom biochronology to the Monterey Formation and related biosiliceous rocks reveals the imprint of both global paleoclimatic/\npaleoceanographic and regional tectonic events. A rise in global sea level combined with regional tectonic deepening associated with the development of the transform California margin resulted in the abrupt onset of deposition of fine-grained Monterey sediments between 18 and 16 Ma. The base of the Monterey does not mark a silica shift in diatom deposition from the North Atlantic to the North Pacific. Rather, a North Atlantic decline of diatoms after ~13 Ma and increasing divergence in nutrient levels between the North Atlantic and North Pacific between ~13 and 11 Ma, coincided with a major enhancement of diatom deposition in the Monterey Formation. A stratigraphically condensed interval of phosphate-rich sediments between 13 and 10 Ma in coastal southern California appears to have resulted from sediment starvation on offshore banks during a period of higher sea level, as inland sections commonly contain thick sequences of diatomaceous sediment. Increasing latitudinal thermal gradients in the latest Miocene, which triggered a biogenic bloom in the equatorial Pacific at 8 Ma, also lead to enhanced diatom deposition in the uppermost Monterey and overlying biosiliceous rocks. Uplift of the California coastal ranges after ~5.2 Ma resulted in an increasing detrital contribution that obscured the presence of diatoms in onshore sediments. Major reduction in coastal upwelling in the early Pliocene at ~4.6 Ma caused a drastic reduction of diatoms in sediments of offshore southern California.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Understanding the Monterey Formation and similar biosiliceous units across space and time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.2556(06)","usgsCitation":"Barron, J.A., 2022, A refined assessment of the paleoceanographic and tectonic influences on the deposition of the Monterey Formation in California, chap. of Understanding the Monterey Formation and similar biosiliceous units across space and time: Special Papers of the Geological Society of America, v. 556, 16 p., https://doi.org/10.1130/2022.2556(06).","productDescription":"16 p.","ipdsId":"IP-115927","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.01367187499999,\n 39.436192999314095\n ],\n [\n -123.837890625,\n 38.89103282648846\n ],\n [\n -122.73925781250001,\n 37.77071473849609\n ],\n [\n -122.45361328124999,\n 36.98500309285596\n ],\n [\n -122.08007812499999,\n 36.84446074079564\n ],\n [\n -122.03613281249999,\n 36.61552763134925\n ],\n [\n -121.9482421875,\n 36.24427318493909\n ],\n [\n -121.37695312499999,\n 35.55010533588552\n ],\n [\n -120.80566406250001,\n 35.02999636902566\n ],\n [\n -120.78369140624999,\n 34.43409789359469\n ],\n [\n -119.46533203125,\n 34.27083595165\n ],\n [\n -119.15771484375,\n 33.99802726234877\n ],\n [\n -118.63037109375,\n 33.90689555128866\n ],\n [\n -118.5205078125,\n 33.7243396617476\n ],\n [\n -118.125,\n 33.61461929233378\n ],\n [\n -117.66357421875,\n 33.30298618122413\n ],\n [\n -117.39990234375,\n 33.02708758002874\n ],\n [\n -117.31201171875001,\n 32.509761735919426\n ],\n [\n -115.77392578125,\n 32.62087018318113\n ],\n [\n -115.51025390625,\n 34.17999758688084\n ],\n [\n -115.82885742187499,\n 34.52466147177172\n ],\n [\n -118.487548828125,\n 35.79108281624994\n ],\n [\n -118.94897460937499,\n 36.66841891894786\n ],\n [\n -119.937744140625,\n 37.579412513438385\n ],\n [\n -120.81665039062499,\n 38.46219172306828\n ],\n [\n -121.904296875,\n 38.272688535980976\n ],\n [\n -122.26684570312499,\n 38.976492485539396\n ],\n [\n -122.40966796874999,\n 39.37677199661635\n ],\n [\n -122.54150390625,\n 39.59722324495565\n ],\n [\n -124.01367187499999,\n 39.436192999314095\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"556","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Aiello, Ivano","contributorId":292488,"corporation":false,"usgs":false,"family":"Aiello","given":"Ivano","email":"","affiliations":[],"preferred":false,"id":844762,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844763,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Ravelo, Christina","contributorId":23057,"corporation":false,"usgs":true,"family":"Ravelo","given":"Christina","email":"","affiliations":[],"preferred":false,"id":844764,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844739,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70232236,"text":"70232236 - 2022 - Enumerating plausible multifault ruptures in complex fault systems with physical constraints","interactions":[],"lastModifiedDate":"2022-08-02T14:30:33.803665","indexId":"70232236","displayToPublicDate":"2022-06-16T09:04:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Enumerating plausible multifault ruptures in complex fault systems with physical constraints","docAbstract":"We propose a new model for determining the set of plausible multifault ruptures in an interconnected fault system. We improve upon the rules used in the Third Uniform California Earthquake Rupture Forecast (UCERF3) to increase connectivity and the physical consistency of ruptures. We replace UCERF3’s simple azimuth change rules with new Coulomb favorability metrics and increase the maximum jump distance to 15 km. Although the UCERF3 rules were appropriate for faults with similar rakes, the Coulomb calculations used here inherently encode preferred orientations between faults with different rakes. Our new rules are designed to be insensitive to discretization details and are generally more permissive than their UCERF3 counterparts; they allow more than twice the connectivity compared to UCERF3, yet heavily penalize long ruptures that take multiple improbable jumps. The set of all possible multifault ruptures in the California fault system is near-infinite, but our model produces a tractable set of 326,707 ruptures (a modest 29% increase over UCERF3, despite the greatly increased connectivity). Inclusion in the rupture set does not dictate that a rupture receives a significant rate in the final model; rupture rates are subsequently determined by data constraints used in an inversion.\n\nWe describe the rupture building algorithm and its components in detail and provide comparisons with ruptures generated by a physics-based multicycle earthquake simulator. We find that greater than twice as many ruptures generated by the simulator violate the UCERF3 rules than violate our proposed model.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210322","usgsCitation":"Milner, K.R., Shaw, B.E., and Field, E.H., 2022, Enumerating plausible multifault ruptures in complex fault systems with physical constraints: Bulletin of the Seismological Society of America, v. 112, no. 4, p. 1806-1824, https://doi.org/10.1785/0120210322.","productDescription":"19 p.","startPage":"1806","endPage":"1824","ipdsId":"IP-139511","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":402266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"112","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":844759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaw, Bruce E.","contributorId":194146,"corporation":false,"usgs":false,"family":"Shaw","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":844761,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232235,"text":"70232235 - 2022 - Mapping a magnetic superstorm: March 1989 geoelectric hazards and impacts on United States power systems","interactions":[],"lastModifiedDate":"2022-06-16T14:00:42.556778","indexId":"70232235","displayToPublicDate":"2022-06-16T08:55:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Mapping a magnetic superstorm: March 1989 geoelectric hazards and impacts on United States power systems","docAbstract":"A study is made of the relationships between geomagnetic and geoelectric field variation, Earth-surface impedance, and operational interference (anomalies) experienced on electric-power systems across the contiguous United States during the March 13-14, 1989 magnetic storm. For this, a 1-minute-resolution sequence of geomagnetic field maps is constructed from magnetometer time series acquired at ground-based observatories. Induced geoelectric field maps are calculated by convolving the geomagnetic maps with magnetotelluric impedance tensors. During the storm, anomalies were concentrated where the lithosphere is electrically resistive, and when and where geoelectric field amplitudes were high. This was particularly true in the Mid-Atlantic, Northeast, and the upper Midwest. Few anomalies were experienced in other parts of the Midwest and across\nmuch of the West, where the lithosphere is more conductive, and when and where geoelectric field amplitudes were low. Peak 1-minute-resolution geoelectric field amplitude ranged from 21.66 V/km in Maine and 19.02 V/km in Virginia to < 0.02 V/km in Idaho. Latitude-dependent organization of geoelectric hazards by auroral-zone electrojet currents is detectable, but it is much weaker than geographic organization due to surface impedance. Hazardous geoelectric fields were induced during different storm phases, at different local times, and, by inference, by a variety of ionospheric currents. Compared to geoelectric field amplitudes realized across the United States during March 1989, hazard maps used by utility companies to estimate systems exposure have much less geographic detail and a much smaller maximum-to-minimum range in geoelectric field amplitude. Future research will benet from denser geomagnetic monitoring, additional magnetotelluric surveying, and access to power-system impact data.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021SW003030","usgsCitation":"Love, J.J., Lucas, G., Rigler, E.J., Murphy, B.S., Kelbert, A., and Bedrosian, P.A., 2022, Mapping a magnetic superstorm: March 1989 geoelectric hazards and impacts on United States power systems: Space Weather, v. 20, no. 5, e2021SW003030, 27 p., https://doi.org/10.1029/2021SW003030.","productDescription":"e2021SW003030, 27 p.","ipdsId":"IP-140408","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":447410,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021sw003030","text":"Publisher Index 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]\n}","volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":844753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":844754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigler, E. 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In recent decades, lakes have experienced unprecedented ice loss with widespread ramifications for winter ecological processes. The rapid loss of ice, resurgence of winter biology, and proliferation of remote sensing technologies, presents a unique opportunity to integrate disciplines to further understand the broad spatial and temporal patterns in ice loss and its consequences. Here, we summarize ice phenology records for 78 lakes in 12 countries across North America, Europe, and Asia to permit the inclusion and harmonization of in situ ice phenology observations in future interdisciplinary studies. These ice records represent some of the longest climate observations directly collected by people. We highlight the importance of applying the same definition of ice-on and ice-off within a lake across the time-series, regardless of how the ice is observed, to broaden our understanding of ice loss across vast spatial and temporal scales.

","language":"English","publisher":"Scientific Data","doi":"10.1038/s41597-022-01391-6","usgsCitation":"Sharma, S., Filazzola, A., Nguyen, T., Imrit, M., Blagrave, K., Bouffard, D., Daly, J., Feldman, H., Feldsine, N., Hendricks-Franssen, H., Granin, N., Hecock, R., L'Abee-Lund, J., Hopkins, E., Howk, N., Iacono, M., Knoll, L.B., Korhonen, J., Malmquist, H., Marszelewski, W., Matsuzaki, S.S., Miyabara, Y., Miyasaka, K., Mills, A., Olson, L., Peters, T., Richardson, D., Robertson, D., Rudstam, L., Wain, D., Waterfield, H., Weyhenmeyer, G.A., Wiltse, B., Yao, H., Zhdanov, A., and Magnuson, J.J., 2022, Long-term ice phenology records spanning up to 578 years for 78 lakes around the Northern Hemisphere: Scientific Data, v. 9, 318, 15 p., https://doi.org/10.1038/s41597-022-01391-6.","productDescription":"318, 15 p.","ipdsId":"IP-133292","costCenters":[{"id":37947,"text":"Upper Midwest Water Science 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Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

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Noninvasive methods for measuring fat reserves in both captive and free-ranging animals are important for monitoring individual and population health, but chelonian anatomy and physiology present challenges to accurate measurements. Standard field-based methods for assessing body condition in Mojave desert tortoises (Gopherus agassizii) involve the qualitative body condition score, which relies on the apparent height of the temporalis muscle relative to the sagittal crest (in addition to other characteristics) and quantitative body condition indices that measure relative mass at size. However, it is unclear how these metrics relate to body fat reserves in this species. The aims of this study were to (1) describe the use of noninvasive computed tomography in measuring body fat volume of Mojave desert tortoises, (2) describe the location of fat reserves, (3) investigate relationships between fat reserves and body condition score and body condition index, and (4) explore whether relative temporalis muscle depth, measured via computed tomography, correlates with body condition score. Body condition scores were assessed for eight captive Mojave desert tortoises prior to euthanasia, and computed tomography was performed postmortem to quantify fat volume and measure temporalis muscle depth. At necropsy, the distribution of fat was documented. Fat volume calculated by computed tomography ranged from 2.83 to 145.38 cm3 (0.07–2.5% body volume). Neither qualitative body condition score nor quantitative body condition index was correlated with fat volume. Bladder content did not compromise body condition index. Body condition score was not correlated with relative temporalis muscle depth. Computed tomography is a noninvasive method for successfully identifying fat reserves and estimating total fat volume in Mojave desert tortoises. The lack of a relationship between computed tomography-determined metrics and commonly used body condition metrics indicates that computed tomography fills a critical gap in the health assessment tool kit for captive and free-ranging Mojave desert tortoises.

","language":"English","publisher":"BioOne","doi":"10.1638/2020-0168","usgsCitation":"Walden, M., Jania, R., Kinney, M.E., Devan-Song, A., Drake, K.K., Esque, T., and Shoemaker, K., 2022, Computed tomography for measuring body fat reserves in threatened Mohave desert tortoise (Gopherus agassizii): Journal of Zoo and Wildlife Medicine, v. 53, no. 2, p. 412-423, https://doi.org/10.1638/2020-0168.","productDescription":"12 p.","startPage":"412","endPage":"423","ipdsId":"IP-122392","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":414540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walden, M A","contributorId":303287,"corporation":false,"usgs":false,"family":"Walden","given":"M A","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":867036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jania, Rachel","contributorId":303289,"corporation":false,"usgs":false,"family":"Jania","given":"Rachel","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":867037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Matthew E","contributorId":303291,"corporation":false,"usgs":false,"family":"Kinney","given":"Matthew","email":"","middleInitial":"E","affiliations":[{"id":65749,"text":"San Diego Zoo Safari Park","active":true,"usgs":false}],"preferred":false,"id":867038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Devan-Song, Anne","contributorId":303293,"corporation":false,"usgs":false,"family":"Devan-Song","given":"Anne","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":867039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shoemaker, Kevin T.","contributorId":288541,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin T.","affiliations":[{"id":61793,"text":"University of Nevada – Reno","active":true,"usgs":false}],"preferred":false,"id":867042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232905,"text":"70232905 - 2022 - Statistical assessment on determining local presence of rare bat species","interactions":[],"lastModifiedDate":"2022-07-13T11:50:01.124415","indexId":"70232905","displayToPublicDate":"2022-06-16T06:47:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Statistical assessment on determining local presence of rare bat species","docAbstract":"

Surveying cryptic, sparsely distributed taxa using autonomous recording units, although cost-effective, provides imperfect knowledge about species presence. Summertime bat acoustic surveys in North America exemplify the challenges with characterizing sources of uncertainty: observation error, inability to census populations, and natural stochastic variation. Statistical uncertainty, if not considered thoroughly, hampers determining rare species presence accurately and/or estimating rangewide status and trends with suitable precision. Bat acoustic data are processed using an automated workflow in which proprietary or open-source algorithms assign a species label to each recorded high-frequency echolocation sequence. A false-negative occurs, if a species is actually present but not recorded and/or all recordings from the species are of such poor quality that a correct species identity cannot be assigned to any observation. False positives for a focal species are a direct result of the presence and incorrect identification of a recording from another species. We compare four analytical approaches in terms of parameter estimation and their resulting (in)correct decisions regarding species presence or absence using realistic data-generating scenarios for bat acoustic data within a simulation study. The current standard for deciding species presence or absence uses a multinomial likelihood-ratio test p value (maximum likelihood estimate [MLE]-metric) that accounts for known species misidentifications, but not imperfect detection and only returns a binary outcome (evidence of presence or not). We found that the MLE-metric had estimated median correct decisions less than 60% for presence and greater than 85% for absence. Alternatively, a multispecies count detection model was equivalent to or better than the MLE-metric for correct claims of rare species presence or absence using the posterior probability a species was present at a site and, importantly, provided unbiased estimates of relative activity and probability of occurrence, creating opportunities for reducing posterior uncertainty through the inclusion of meaningful covariates. Single-species occupancy models with and without false-positive detections removed were insufficient for determining local presence because of substantially biased occurrence and detection probabilities. We propose solutions to potential barriers for integrating local, short-term and rangewide, long-term acoustic surveys within a cohesive statistical framework that facilitates determining local species presence with uncertainty concurrent with estimating species–environment relationships.

","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4142","usgsCitation":"Irvine, K.M., Banner, K., Stratton, C., Ford, W., and Reichert, B., 2022, Statistical assessment on determining local presence of rare bat species: Ecosphere, v. 13, no. 6, e4142, 15 p., https://doi.org/10.1002/ecs2.4142.","productDescription":"e4142, 15 p.","ipdsId":"IP-133431","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":447424,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.4142","text":"External Repository"},{"id":403588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":846458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Katharine M.","contributorId":244876,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":846459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":846460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. 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Throughout their careers, environmental professionals often collect data on many individual projects that address similar sets of natural resource conservation problems. Consequently, the institutions, agencies, and organizations that employ these environmental professionals accumulate a large reservoir of project-specific information. However, bigger-picture opportunities to advance broader natural resource conservation goals are lost if individual projects and datasets are not integrated. Here we illustrate how our adaptive problem mapping (APM) process provides a framing and internal structure that charts relationships among pertinent information types, germane data sets, applicable concepts, and relevant decisions. In the APM process, appropriately defined problem statements and coordinated bridging questions connect data and concepts to build a network of increasingly informed and defensible decisions. Although our APM process can be applied to many environmental problems, here we focus on examples from aquatic systems in which fish are conservation priorities. Prioritizing an initial evaluation and regular modification of the relationships among datasets and decisions using the APM process helps manager-research-administrator teams envision, track, and update what is known, unknown, learned, and needed. The resulting broader point of view advances strategic planning, evaluations of progress, assessments of opportunity costs, identification of options, and justifications of decision-related actions. \n ","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.114826","usgsCitation":"Mather, M.E., and Dettmers, J., 2022, Adaptive problem maps (APM): Connecting data dots to build increasingly informed and defensible environmental conservation decisions: Journal of Environmental Management, v. 312, 114826, 10 p., https://doi.org/10.1016/j.jenvman.2022.114826.","productDescription":"114826, 10 p.","ipdsId":"IP-138779","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"312","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettmers, John M.","contributorId":341569,"corporation":false,"usgs":false,"family":"Dettmers","given":"John M.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":908630,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256682,"text":"70256682 - 2022 - Durability and longevity of Tympanuchus pallidicinctus (Lesser Prairie-Chicken) fence tags in Kansas and Colorado","interactions":[],"lastModifiedDate":"2024-08-30T15:33:17.338998","indexId":"70256682","displayToPublicDate":"2022-06-15T10:27:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Durability and longevity of Tympanuchus pallidicinctus (Lesser Prairie-Chicken) fence tags in Kansas and Colorado","title":"Durability and longevity of Tympanuchus pallidicinctus (Lesser Prairie-Chicken) fence tags in Kansas and Colorado","docAbstract":"

No abstract available.

","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.40.2.83","usgsCitation":"Teige, E., Parker, N.J., Vhay, M.P., and Haukos, D.A., 2022, Durability and longevity of Tympanuchus pallidicinctus (Lesser Prairie-Chicken) fence tags in Kansas and Colorado: Ecological Restoration, v. 40, no. 2, p. 83-87, https://doi.org/10.3368/er.40.2.83.","productDescription":"5 p.","startPage":"83","endPage":"87","ipdsId":"IP-135749","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, 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\"}}]}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Teige, Elisabeth C.","contributorId":341573,"corporation":false,"usgs":false,"family":"Teige","given":"Elisabeth C.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Nicholas J.","contributorId":341574,"corporation":false,"usgs":false,"family":"Parker","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vhay, Megan P.","contributorId":341575,"corporation":false,"usgs":false,"family":"Vhay","given":"Megan","email":"","middleInitial":"P.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908635,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254299,"text":"70254299 - 2022 - Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region","interactions":[],"lastModifiedDate":"2024-05-17T13:58:51.399871","indexId":"70254299","displayToPublicDate":"2022-06-15T08:54:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region","docAbstract":"

For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 2015–2018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 2000–2016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R2 =0.81; Kansas R2 =0.51) and temporal cross-validation (Colorado R2 =0.82; Kansas R2 =0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2022.107764","usgsCitation":"Filippelli, S.S., Sloggy, M.R., Vogeler, J.C., Manning, D.T., Goemans, C., and Senay, G.B., 2022, Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region: Agricultural Water Management, v. 271, 107764, 15 p., https://doi.org/10.1016/j.agwat.2022.107764.","productDescription":"107764, 15 p.","ipdsId":"IP-137832","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2022.107764","text":"Publisher Index Page"},{"id":428798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado Kansas","otherGeospatial":"Ogallala aquifer, Republican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.00825131829713,\n 36.98969791337646\n ],\n [\n -97.51352205922755,\n 36.9837502608661\n ],\n [\n -97.3406085961385,\n 38.44391430535899\n ],\n [\n -98.0932074623356,\n 38.87773029390084\n ],\n [\n -99.65122819650178,\n 39.098871590431884\n ],\n [\n -99.26469253047271,\n 40.0142028593921\n ],\n [\n -102.06717715371995,\n 40.032435593038315\n ],\n [\n -102.11261804171953,\n 40.992555768008174\n ],\n [\n -104.06597899342937,\n 40.93187765306061\n ],\n [\n -104.48051561524214,\n 39.43819239944247\n ],\n [\n -103.69918549158801,\n 38.5715258326463\n ],\n [\n -102.64452864991789,\n 38.27521479596666\n ],\n [\n -102.4653590264147,\n 36.967066532161525\n ],\n [\n -102.00825131829713,\n 36.98969791337646\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"271","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Filippelli, Steven S 0000-0001-7291-0888","orcid":"https://orcid.org/0000-0001-7291-0888","contributorId":336733,"corporation":false,"usgs":false,"family":"Filippelli","given":"Steven","email":"","middleInitial":"S","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sloggy, Matthew R 0000-0001-5129-0755","orcid":"https://orcid.org/0000-0001-5129-0755","contributorId":336734,"corporation":false,"usgs":false,"family":"Sloggy","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":900930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogeler, Jody C.","contributorId":264796,"corporation":false,"usgs":false,"family":"Vogeler","given":"Jody","email":"","middleInitial":"C.","affiliations":[{"id":54555,"text":"umn","active":true,"usgs":false}],"preferred":false,"id":900931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Dale T 0000-0001-6465-5530","orcid":"https://orcid.org/0000-0001-6465-5530","contributorId":336735,"corporation":false,"usgs":false,"family":"Manning","given":"Dale","email":"","middleInitial":"T","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goemans, Christopher 0000-0003-4930-4278","orcid":"https://orcid.org/0000-0003-4930-4278","contributorId":336736,"corporation":false,"usgs":false,"family":"Goemans","given":"Christopher","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":900934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232417,"text":"70232417 - 2022 - The consequences of climate change for dryland biogeochemistry","interactions":[],"lastModifiedDate":"2022-09-15T14:13:41.119439","indexId":"70232417","displayToPublicDate":"2022-06-15T07:20:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10948,"text":"New Phytologist Foundation","active":true,"publicationSubtype":{"id":10}},"title":"The consequences of climate change for dryland biogeochemistry","docAbstract":"

Drylands, which cover more than 40% of Earth’s terrestrial surface, are dominant drivers of global biogeochemical cycling and home to more than one third of the human population. Climate projections predict warming, drought frequency and severity, and evaporative demand will increase in drylands at faster rates than global means. Due to extreme temperatures and high biological dependency on limited water availability, drylands are predicted to be exceptionally sensitive to climate change and, indeed, significant climate impacts are already being observed. Yet our understanding and ability to forecast climate change effects on dryland biogeochemistry and ecosystem functions lag behind many mesic systems. To improve our capacity to forecast ecosystem change, we propose focusing on the controls and consequences of two key characteristics affecting dryland biogeochemistry: i) high spatial and temporal heterogeneity in environmental conditions and ii) generalized resource scarcity. In addition to climate change, drylands are experiencing accelerating land use change. Building our understanding of dryland biogeochemistry in both intact and disturbed systems will better equip us to address the interacting effects of climate change and landscape degradation. Responding to these challenges will require a diverse, globally distributed, and interdisciplinary community of dryland experts united towards better understanding these vast and important ecosystems.

","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.18312","usgsCitation":"Osborne, B.B., Bestelmeyer, B.T., Currier, C.M., Homyak, P.M., Throop, H.L., Young, K., and Reed, S., 2022, The consequences of climate change for dryland biogeochemistry: New Phytologist Foundation, v. 236, no. 1, p. 15-20, https://doi.org/10.1111/nph.18312.","productDescription":"6 p.","startPage":"15","endPage":"20","ipdsId":"IP-136307","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.18312","text":"Publisher Index Page"},{"id":402816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"236","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Osborne, Brooke Bossert 0000-0003-4771-7677","orcid":"https://orcid.org/0000-0003-4771-7677","contributorId":247600,"corporation":false,"usgs":true,"family":"Osborne","given":"Brooke","email":"","middleInitial":"Bossert","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":845479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Currier, Courtney M.","contributorId":214702,"corporation":false,"usgs":false,"family":"Currier","given":"Courtney","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":845480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homyak, Peter M 0000-0003-0671-8358","orcid":"https://orcid.org/0000-0003-0671-8358","contributorId":292686,"corporation":false,"usgs":false,"family":"Homyak","given":"Peter","email":"","middleInitial":"M","affiliations":[{"id":62973,"text":"Department of Environmental Sciences, University of California, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":845481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":845482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":845483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845484,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262405,"text":"70262405 - 2022 - On the multiple identities of stakeholders in wolf management in Minnesota, United States","interactions":[],"lastModifiedDate":"2025-01-17T17:31:28.733664","indexId":"70262405","displayToPublicDate":"2022-06-15T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"On the multiple identities of stakeholders in wolf management in Minnesota, United States","docAbstract":"

Social identity theory offers a means to understand attitudes about wolves, with consequences for management support. Using data from a mail survey about wolves, we explored relationships among seven identities (i.e., wolf advocate, hunter, environmentalist, nature enthusiast, farmer, trapper, conservationist) using multidimensional scaling (MDS) and principal components analysis (PCA). We examined how identities correlated with political ideology, trust in a wildlife management agency, wildlife value orientations (WVOs) and attitudes about wolves, and we evaluated whether WVOs mediated the relationship between identities and attitudes. PCA suggested two factors in identifying relationships among stakeholders, while MDS and correlations found diversity among stakeholders beyond these factors. Hunter identity was most strongly associated with a domination WVO and conservative political ideology. Farmer identity was most strongly associated with agency distrust and negative wolf attitudes. Wolf advocate was most strongly associated with a mutualism WVO (i.e., beliefs that humans are meant to coexist in harmonious relationships with wildlife), agency trust, and positive wolf attitudes. Conservationist identity was positively correlated with all other identities. WVOs partially mediated the relationship between identities and attitudes.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.798795","usgsCitation":"Schroeder, S., Landon, A., Fulton, D.C., and McInenly, L., 2022, On the multiple identities of stakeholders in wolf management in Minnesota, United States: Frontiers in Ecology and Evolution, v. 10, 798795, 14 p., https://doi.org/10.3389/fevo.2022.798795.","productDescription":"798795, 14 p.","ipdsId":"IP-134202","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.798795","text":"Publisher Index Page"},{"id":480756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Cooperative Unit","active":true,"usgs":false}],"preferred":true,"id":924130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McInenly, Leslie","contributorId":349185,"corporation":false,"usgs":false,"family":"McInenly","given":"Leslie","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":924131,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232182,"text":"ofr20221050 - 2022 - Implementation plan of the National Cooperative Geologic Mapping Program strategy — Appalachian Piedmont and Blue Ridge Provinces","interactions":[],"lastModifiedDate":"2022-09-27T13:49:52.6265","indexId":"ofr20221050","displayToPublicDate":"2022-06-14T17:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File 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The National Cooperative Geologic Mapping Program is publishing a strategic plan titled “Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge.” The plan provides a vision, mission, and goals for the program for the years 2020–30:

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221050","usgsCitation":"Merschat, A.J., Carter, M.W., and Piedmont and Blue Ridge Working Group, 2022, Implementation plan of the National Cooperative Geologic Mapping Program strategy — Appalachian Piedmont and Blue Ridge Provinces: U.S. Geological Survey Open-File Report 2022–1050, 24 p., https://doi.org/10.3133/ofr20221050.","productDescription":"v, 24 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-129273","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":402186,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221050/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1050"},{"id":402041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1050/coverthb.jpg"},{"id":402042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1050/ofr20221050.pdf","text":"Report","size":"3.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1050"},{"id":402043,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1050/ofr20221050.XML"},{"id":402044,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1050/images"}],"country":"United States","state":"Alabama, Georgia, Illinois, Indiana, Kentucky, Maryland, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Vermont, Virginia, West Virginia","otherGeospatial":"Appalachian Piedmont and Blue Ridge Provinces","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.4287109375,\n 37.61423141542417\n ],\n [\n -88.505859375,\n 36.98500309285596\n ],\n [\n -87.3193359375,\n 35.782170703266075\n ],\n [\n -87.451171875,\n 34.27083595165\n ],\n [\n -86.220703125,\n 33.02708758002874\n ],\n [\n -83.75976562499999,\n 33.063924198120645\n ],\n [\n -82.001953125,\n 33.211116472416855\n ],\n [\n -80.6396484375,\n 34.27083595165\n ],\n [\n -79.1455078125,\n 35.209721645221386\n ],\n [\n -78.2666015625,\n 36.527294814546245\n ],\n [\n -77.6953125,\n 38.34165619279595\n ],\n [\n -76.7724609375,\n 39.33429742980725\n ],\n [\n -75.5419921875,\n 40.38002840251183\n ],\n [\n -74.44335937499999,\n 40.613952441166596\n ],\n [\n -74.00390625,\n 41.04621681452063\n ],\n [\n -75.4541015625,\n 40.81380923056958\n ],\n [\n -74.091796875,\n 41.57436130598913\n ],\n [\n -73.1689453125,\n 42.87596410238256\n ],\n [\n -73.125,\n 44.05601169578525\n ],\n [\n -73.7841796875,\n 43.96119063892024\n ],\n [\n -74.794921875,\n 43.51668853502906\n ],\n [\n -75.41015624999999,\n 44.213709909702054\n ],\n [\n -75.7177734375,\n 44.11914151643737\n ],\n [\n -75.41015624999999,\n 43.51668853502906\n ],\n [\n -76.9921875,\n 42.8115217450979\n ],\n [\n -78.92578124999999,\n 42.58544425738491\n ],\n [\n -81.73828125,\n 41.47566020027821\n ],\n [\n -82.5732421875,\n 40.78054143186033\n ],\n [\n -82.30957031249999,\n 40.245991504199026\n ],\n [\n -82.8369140625,\n 39.470125122358176\n ],\n [\n -83.84765625,\n 38.89103282648846\n ],\n [\n -84.375,\n 39.36827914916014\n ],\n [\n -85.078125,\n 39.26628442213066\n ],\n [\n -85.5615234375,\n 38.685509760012\n ],\n [\n -86.1328125,\n 39.198205348894795\n ],\n [\n -86.748046875,\n 39.095962936305476\n ],\n [\n -87.62695312499999,\n 38.47939467327645\n ],\n [\n -88.5498046875,\n 38.03078569382294\n ],\n [\n -89.4287109375,\n 37.61423141542417\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":844483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":844484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"2018 Piedmont and Blue Ridge Working Group","contributorId":292465,"corporation":true,"usgs":false,"organization":"2018 Piedmont and Blue Ridge Working Group","id":844648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232208,"text":"ofr20221043 - 2022 - Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data","interactions":[],"lastModifiedDate":"2022-06-15T14:11:27.09211","indexId":"ofr20221043","displayToPublicDate":"2022-06-14T14:20:00","publicationYear":"2022","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":"2022-1043","displayTitle":"Opportunities To Improve Alignment With the FAIR Principles for U.S. Geological Survey Data","title":"Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data","docAbstract":"

In 2016, an interdisciplinary, international group of 53 scientists introduced a framework named “the FAIR Principles” for addressing 21st century scientific data challenges. The FAIR Principles are increasingly used as a guide for producing digital scientific products that are findable, accessible, interoperable, and reusable (FAIR), especially to enable use of such products in automated systems. Data aligned with the FAIR Principles can increase the efficiency of science integration capabilities such as those envisioned for the U.S. Geological Survey (USGS) Earth Monitoring, Analyses, and Projections (EarthMAP) initiative.

The FAIR Principles clearly define the characteristics of reusable scientific products, but it is less clear how to facilitate consistency in achieving these characteristics across the Bureau. USGS data are produced by local research projects distributed over more than 100 centers in 7 regions. After data are approved for release, they could be managed in numerous repositories and online data systems. The diversity of USGS data is illustrated by the topical range of the USGS mission areas: Core Science Systems, Ecosystems, Energy and Minerals, Natural Hazards, and Water Resources. In the USGS context, realizing the EarthMAP vision for automated, predictive, integrated science that provides timely and actionable results involves providing knowledge and support services and developing the skills, infrastructure, and culture to enable Bureau-wide implementation of the FAIR Principles.

In 2019, the USGS Community for Data Integration funded a project to convene a broadly representative workshop and produce recommendations to enable consistency with the FAIR Principles across the USGS. The workshop, held in Fort Collins, Colorado, in September 2019, brought together 28 participants for 3 days to engage with the FAIR Principles, analyze USGS use cases, and discuss the roles of data producers and managers, data storage and catalogs, value-added services, and policy makers in implementing the FAIR Principles. Workshop participants agreed that scientific reproducibility requires the extension of the FAIR Principles beyond measured data to include physical samples, research methods, software, and tools at the USGS. Workshop discussions focused on how the USGS can implement the FAIR Principles by supporting research teams in creating data, metadata, and other scientific products and also by supporting enterprise systems that maintain and leverage the products’ consistency with the FAIR Principles.

The resulting FAIR roadmap of recommendations describes nine proposed interdependent strategies that could be achieved by coordinated actions taken by different parts of the USGS. A proposed early action would be the creation of a coordinating council that includes representatives from the groups engaged in activities consistent with better alignment with the FAIR Principles. The nine proposed strategies, which are presented in more detail in this roadmap report, focus on enabling improvements to individual data products, providing infrastructure, and structuring administrative activities to support an organizational culture that values the FAIR Principles.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221043","usgsCitation":"Lightsom, F.L., Hutchison, V.B., Bishop, B., Debrewer, L.M., Govoni, D.L., Latysh, N., and Stall, S., 2022, Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data: U.S. Geological Survey Open-File Report 2022–1043, 23 p., https://doi.org/10.3133/ofr20221043.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125836","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":402133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1043/coverthb.jpg"},{"id":402134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1043"},{"id":402135,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1043/images/"},{"id":402136,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.XML"}],"contact":"

Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Lightsom, Frances L. 0000-0003-4043-3639 flightsom@usgs.gov","orcid":"https://orcid.org/0000-0003-4043-3639","contributorId":1535,"corporation":false,"usgs":true,"family":"Lightsom","given":"Frances","email":"flightsom@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":173674,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian","email":"vhutchison@usgs.gov","middleInitial":"B.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":844642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Bradley","contributorId":292462,"corporation":false,"usgs":false,"family":"Bishop","given":"Bradley","email":"","affiliations":[{"id":62912,"text":"University of Tennessee School of Information Sciences","active":true,"usgs":false}],"preferred":false,"id":844643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Debrewer, Linda M. 0000-0002-0511-4010 lmdebrew@usgs.gov","orcid":"https://orcid.org/0000-0002-0511-4010","contributorId":5713,"corporation":false,"usgs":true,"family":"Debrewer","given":"Linda","email":"lmdebrew@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":844644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Govoni, David L. 0000-0002-2707-0098 dgovoni@usgs.gov","orcid":"https://orcid.org/0000-0002-2707-0098","contributorId":292463,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":844645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Latysh, Natalie 0000-0003-0149-3962","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":215667,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","affiliations":[{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true}],"preferred":true,"id":844646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stall, Shelley","contributorId":292464,"corporation":false,"usgs":false,"family":"Stall","given":"Shelley","email":"","affiliations":[{"id":35616,"text":"American Geophysical Union","active":true,"usgs":false}],"preferred":false,"id":844647,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232209,"text":"fs20223042 - 2022 - Arkansas and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:06:03.914652","indexId":"fs20223042","displayToPublicDate":"2022-06-14T09:25:10","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3042","displayTitle":"Arkansas and Landsat","title":"Arkansas and Landsat","docAbstract":"

Scenic Arkansas certainly lives up to its nickname, “The Natural State.” The Ozark Plateau and Ouachita Mountains boast stunning views, vast resources, and recreation. Hardwood and pine forests cover one-half of the State. The major rivers—Arkansas, Ouachita, Red, and White—offer recreation and navigation as they drain toward the Mississippi River, which forms the State’s eastern border. Smaller streams and rivers, reservoirs, and rice fields serve as homes for wildlife as well, including birds migrating along the Mississippi Flyway.

Agriculture has always been a key industry in Arkansas, which is the top rice producer in the United States. Poultry, soybeans, cotton, cattle, and timber are among other agricultural products that contribute to the State’s economy. The aquaculture industry has diversified from just goldfish to more than 20 species of fish and crustaceans.

Geological features include waterfalls, limestone caves, and the country’s only active diamond mine, Crater of Diamonds State Park, where visitors can keep any rock or mineral they find in the volcanic crater. Hot Springs National Park—within the city of Hot Springs—features thermal springs of water heated deep belowground that follow a fault line of the Ouachita Mountains up to the surface.

Here are a few ways Landsat has benefited Arkansas.

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U.S. Geological Survey
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":844649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70255287,"text":"70255287 - 2022 - Bayesian inverse reinforcement learning for collective animal movement","interactions":[],"lastModifiedDate":"2024-06-14T12:14:05.470606","indexId":"70255287","displayToPublicDate":"2022-06-14T07:12:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian inverse reinforcement learning for collective animal movement","docAbstract":"

Agent-based methods allow for defining simple rules that generate complex group behaviors. The governing rules of such models are typically set a priori, and parameters are tuned from observed behavior trajectories. Instead of making simplifying assumptions across all anticipated scenarios, inverse reinforcement learning provides inference on the short-term (local) rules governing long-term behavior policies by using properties of a Markov decision process. We use the computationally efficient linearly-solvable Markov decision process to learn the local rules governing collective movement for a simulation of the selfpropelled-particle (SPP) model and a data application for a captive guppy population. The estimation of the behavioral decision costs is done in a Bayesian framework with basis function smoothing. We recover the true costs in the SPP simulation and find the guppies value collective movement more than targeted movement toward shelter.

","language":"English","publisher":"Project Euclid","doi":"10.1214/21-AOAS1529","usgsCitation":"Schafer, T.L., Wikle, C., and Hooten, M., 2022, Bayesian inverse reinforcement learning for collective animal movement: Annals of Applied Statistics, v. 16, no. 2, p. 999-1013, https://doi.org/10.1214/21-AOAS1529.","productDescription":"15 p.","startPage":"999","endPage":"1013","ipdsId":"IP-122147","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447431,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/2009.04003","text":"External Repository"},{"id":430198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schafer, Toryn L. J.","contributorId":339344,"corporation":false,"usgs":false,"family":"Schafer","given":"Toryn","email":"","middleInitial":"L. J.","affiliations":[{"id":81080,"text":"umo","active":true,"usgs":false}],"preferred":false,"id":904102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wikle, Christopher K.","contributorId":339345,"corporation":false,"usgs":false,"family":"Wikle","given":"Christopher K.","affiliations":[{"id":81080,"text":"umo","active":true,"usgs":false}],"preferred":false,"id":904103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":904101,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232608,"text":"70232608 - 2022 - Resist, accept, and direct responses to biological invasions: A social–ecological perspective","interactions":[],"lastModifiedDate":"2022-08-02T15:08:13.718872","indexId":"70232608","displayToPublicDate":"2022-06-14T06:38:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Resist, accept, and direct responses to biological invasions: A social–ecological perspective","docAbstract":"

Biological invasions represent an important and unique case of ecological transformation that can strongly influence species and entire ecosystems. Challenges in managing invasions arise on multiple fronts, ranging from diverse and often divergent values associated with native and introduced species, logistical constraints, and transformation via other change agents (e.g., climate and land-use change). We address biological invasions considering the Resist-Accept-Direct (RAD) framework for addressing ecological transformation. Because RAD is focused on decisions, we address both social and ecological factors that influence preferences for decision alternatives. We address social factors first as these can constrain the range of alternatives considered in an ecological context. Next, we address ecological dynamics by modeling trajectories from RAD alternatives in a two-species scenario involving impacts of introduced brook trout (Salvelinus fontinalis) on native bull trout (S. confluentus). Results reveal that decision alternatives aligned with each of the major components of RAD can produce positive outcomes. In a management context, these findings highlight the value of investing in early engagement to fully identify decision alternatives, formalizing models of system dynamics to understand ecological trajectories, and applying this knowledge to set the stage for longer term efforts to address biological invasions.

","language":"English","publisher":"Wiley","doi":"10.1111/fme.12574","usgsCitation":"Dunham, J.B., Benjamin, J.R., Lawrence, D.J., and Clifford, K., 2022, Resist, accept, and direct responses to biological invasions: A social–ecological perspective: Fisheries Management and Ecology, v. 29, no. 4, p. 475-485, https://doi.org/10.1111/fme.12574.","productDescription":"11 p.","startPage":"475","endPage":"485","ipdsId":"IP-140669","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447432,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/51896","text":"External Repository"},{"id":403257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"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":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":846052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":846053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, David J. 0000-0002-1457-9944","orcid":"https://orcid.org/0000-0002-1457-9944","contributorId":225585,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":41167,"text":"U.S. Park Service","active":true,"usgs":false}],"preferred":false,"id":846054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clifford, Katherine","contributorId":260139,"corporation":false,"usgs":false,"family":"Clifford","given":"Katherine","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":846055,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}