The Williston Basin, which includes parts of Montana, North Dakota, and South Dakota in the United States and parts of Manitoba and Saskatchewan in Canada, has been explored as a potential source of energy resources since the early 20th century; however, commercially viable petroleum drilling and recovery began in earnest in the 1950s. When oil prices rose in the mid-1980s, the number of wells also increased and then subsequently declined. Interest in the Williston Basin increased again in the mid-2000s with the application of new drilling technology. Since then, development has increased rather quickly. Most of this new development has been facilitated by advances in horizontal drilling and hydraulic fracturing technologies. The North Dakota Department of Mineral Resources reported an increase of more than 10,000 producing wells between 2000 and the spring of 2016. In total, 84 percent of those 10,000 wells target the Bakken Formation, which is now home to one of the Nation’s largest energy booms. Current estimates suggest that exploration and drilling activities are expected to continue for the next 20 to 50 years; however, future activity will likely ebb and flow in response to energy prices.
Although most energy has been developed on non-Federal property, more than 2,000 wells were started on federally managed lands in the three States that contain the Williston Basin between 2004 and 2015, though these numbers do not reflect whether or not these wells targeted the Bakken Formation. Executive Order no. 13604 (March 22, 2012) directs Federal agencies to improve the timeliness of the permitting process for extracting publically owned minerals, while minimizing negative environmental effects. This means that Federal agencies need information about how energy development may affect other resources they are tasked with managing. One example of where information about potential effects of development may be useful is the Bureau of Land Management’s permitting process. Permits may include stipulations or special conditions that limit unforeseen negative consequences or ameliorate potential conflicts of future development. Federal agencies also need to coordinate permitting actions to ensure that development complies with existing regulations (for example, the Endangered Species Act [16 U.S.C. § 1531 et seq.] or the National Environmental Protection Act [42 U.S.C. § 4321 et seq.]) without unnecessarily restricting or delaying development. Part of this coordination entails agreeing on the information that will be used to assess the potential effects of energy development, which should also improve efficiency of the permitting process. Within the Williston Basin, a group of Federal agencies called the Bakken Federal Executive Group is developing coordination strategies for numerous energy-related issues on Federal lands. This report was developed in cooperation with the Bureau of Land Management to provide them with the best available scientific information to support documentation of potential effects on resources that Federal agencies manage. This report summarizes information about the effects of energy development on air, water, and biological resources within the U.S. part of the Williston Basin.
The topics discussed in the report were based on a prioritized list of information needs elicited from the Bakken Federal Executive Group. The list was developed using a process known as structured decision making or decision analysis. This process began with an initial scoping workshop to determine the range of decisions made by those involved directly in managing energy development and resources on public land. U.S. Geological Survey staff then developed a simple quantitative ranking tool to assess which information needs were of greatest importance to those decisions.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20175070A","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Post van der Burg, M., Vining, K.C., and Frankforter, J.D., 2022, Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Executive summary: U.S. Geological Survey Scientific Investigations Report 2017–5070–A, 7 p., https://doi.org/10.3133/sir20175070A.","productDescription":"Report: v, 7 p.; Appendix","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088211","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501943,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113504.htm","linkFileType":{"id":5,"text":"html"}},{"id":405441,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5070/a/sir20175070a_appendixa1.pdf","text":"Appendix A1","size":"625 kB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"—Summary of Scoping Process for Bakken Environmental Status and Trends (BEST) Report"},{"id":405439,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5070/a/coverthb2.jpg"},{"id":405440,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5070/a/sir20175070a.pdf","text":"Report","size":"0.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5070–A"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 49.009050809382046\n ],\n [\n -108.5,\n 49.009050809382046\n ],\n [\n -108.5,\n 45.120052841530544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The ecosystems of the Williston Basin provide direct and indirect benefits to society. These benefits include carbon sequestration, flood control, nutrient rich soils for agricultural productivity, and habitat for wildlife. This chapter’s main focus is on the effects of energy development on species that occupy the ecosystems in the Williston Basin. We compiled a list of documented species of conservation concern that are of most interest to Federal regulators and resource managers. Species of concern were either listed as endangered or threatened under the Endangered Species Act or listed by States as species of concern in Natural Heritage Program checklists or State Wildlife Action Plans. All told, we determined that 357 species of concern likely occupy the Williston Basin. These species represented seven different taxonomic groups: plants (native and nonnative), terrestrial invertebrates, birds, mammals, reptiles and amphibians, and fish and mussels.
We reviewed the existing scientific information pertaining to potential effects of energy development on these taxonomic groups. Currently, little is known about the abundance and distribution of many of these species. But some information exists that may be useful in predicting the potential effects of energy development on certain taxonomic groups. Most of this information has been developed through scientific research focused on effects to mammal and bird populations. Effects to other taxonomic groups seems to be understudied. In general, it seems that disturbances and modifications associated with development have the potential to negatively affect a wide range of species; however, many studies produce uncertain results because they are not designed to compare populations before and after energy development takes place. Most of these studies also do not monitor resources over multiple years and thus cannot detect population trends. Likewise, there are few examples of landscape-scale assessments of the cumulative effects of energy development that could be used for species or habitat management purposes. We suggest that more research needs to be completed to measure potential effects to a broad range of species in multiple taxonomic groups. This may require also developing some understanding about the basic ecology of many of the species covered in this report. In concert with this more basic research, we also suggest that more comprehensive assessments of potential negative cumulative effects across the Williston Basin should be developed in an effort to guide more strategic management of biological resources.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota (Scientific Investigations Report 2017–5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175070D","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Post van der Burg, M., Symstad, A.J., Igl, L.D., Mushet, D.M., Larson, D.L., Sargeant, G.A., Harper, D.D., Farag, A.M., Tangen, B.A., and Anteau, M.J., 2022, Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Species of conservation concern: U.S. Geological Survey Scientific Investigations Report 2017–5070–D, 41 p., https://doi.org/10.3133/sir20175070D.","productDescription":"Report: vii, 41 p.; 5 Tables","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077345","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501946,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_106212.htm","linkFileType":{"id":5,"text":"html"}},{"id":346079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/coverthb2.jpg"},{"id":346080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d.pdf","text":"Report","size":"5.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5070–D"},{"id":346081,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d_tableD1-1.csv","text":"Table D1–1","size":"41.4 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2017–5070–D Table D1–1"},{"id":346082,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d_tableD1-2.csv","text":"Table D1–2","size":"9.41 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2017–5070–D Table D1–2"},{"id":346083,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d_tableD1-3.csv","text":"Table D1–3","size":"11.1 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2017–5070–D Table D1–3"},{"id":346084,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d_tableD1-4.csv","text":"Table D1–4","size":"7.77 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2017–5070–D Table D1–4"},{"id":346085,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5070/d/sir20175070d_tableD1-5.csv","text":"Table D1–5","size":"5.79 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2017–5070–D Table D1–5"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Bakken Formation, Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 45.120052841530544\n ],\n [\n -96.94335937499999,\n 49.009050809382046\n ],\n [\n -108.5,\n 49.009050809382046\n ],\n [\n -108.5,\n 45.120052841530544\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.850830078125,\n 47.24194882163242\n ],\n [\n -108.544921875,\n 47.24194882163242\n ],\n [\n -108.544921875,\n 48.98742700601184\n ],\n [\n -115.850830078125,\n 48.98742700601184\n ],\n [\n -115.850830078125,\n 47.24194882163242\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The Williston Basin, which includes parts of Montana, North Dakota, and South Dakota in the United States, has been a leading domestic oil and gas producing area. To better understand the potential effects of energy development on environmental resources in the Williston Basin, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, and in support of the needs identified by the Bakken Federal Executive Group (consisting of representatives from 13 Federal agencies and Tribal groups), began work to synthesize existing information on science topics to support management decisions related to energy development. This report is divided into four chapters (A–D). Chapter A provides an executive summary of the report and principal findings from chapters B–D. Chapter B provides a brief compilation of information regarding the history of energy development, physiography, climate, land use, demographics, and related studies in the Williston Basin. Chapter C synthesizes current information about water resources, identifies potential effects from energy development, and summarizes water resources research and information needs in the Williston Basin. Chapter D summarizes information about ecosystems, species of conservation concern, and potential effects to those species from energy development in the Williston Basin.
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U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 278 million barrels of oil and 25.7 trillion cubic feet of gas in Paleozoic total petroleum systems of the Central European Basin System.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20223066","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Leathers-Miller, H.M., Le, P.A., Drake, R.M., II, and Brownfield, M.E., 2022, Assessment of undiscovered conventional oil and gas resources in Paleozoic total petroleum systems of the Central European Basin system, 2019: U.S. Geological Survey Fact Sheet 2022–3066, 4 p., https://doi.org/10.3133/fs20223066.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115741","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":406405,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R9DNDO","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Paleozoic Petroleum Systems of Central European Basin System: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":406404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3066/fs20223066.pdf","text":"Report","size":"7.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS2022-3066"},{"id":406403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3066/coverthb.jpg"}],"country":"Belgium, Denmark, Germany, Netherlands, Norway, Poland, Sweden, United Kingdom","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -1.58203125,\n 51.25\n ],\n [\n 20.0390625,\n 51.25\n ],\n [\n 20.0390625,\n 58.26328705248601\n ],\n [\n -1.58203125,\n 58.26328705248601\n ],\n [\n -1.58203125,\n 51.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The 1989, Mw = 6.9 Loma Prieta earthquake resulted in tens of lives lost and cost California almost 3% of its gross domestic product. Despite widespread damage, the earthquake did not clearly rupture the surface, challenging the identification and characterization of these hidden hazards. Here, we show that they can be illuminated by inverting fluvial topography for slip-and moment accrual-rates—fundamental components in earthquake hazard assessments—along relief-generating geologic faults. We applied this technique to thrust faults bounding the mountains along the western side of Silicon Valley in the San Francisco Bay Area, and discovered that these structures may be capable of generating a Mw = 6.9 earthquake every 250–300 years based on moment accrual rates. This method may be deployed broadly to evaluate seismic hazard in developing regions with limited geological and geophysical information.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL099220","usgsCitation":"Aron, F., Johnstone, S., Mavrommatis, A., Sare, R.M., Maerten, F., Loveless, J., Baden, C., and Hilley, G.E., 2022, Mountain rivers reveal the earthquake hazard of geologic faults in Silicon Valley: Geophysical Research Letters, v. 49, no. 19, e2022GL099220, 12 p., https://doi.org/10.1029/2022GL099220.","productDescription":"e2022GL099220, 12 p.","ipdsId":"IP-116855","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":446446,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl099220","text":"Publisher Index Page"},{"id":408321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Silicon Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.55,\n 36.75\n ],\n [\n -121.5,\n 36.75\n ],\n [\n -121.5,\n 37.5\n ],\n [\n -122.5,\n 37.5\n ],\n [\n -122.5,\n 36.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"19","noUsgsAuthors":false,"publicationDate":"2022-10-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Aron, Felipe","contributorId":222423,"corporation":false,"usgs":false,"family":"Aron","given":"Felipe","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":854619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":854620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mavrommatis, Andreas","contributorId":297911,"corporation":false,"usgs":false,"family":"Mavrommatis","given":"Andreas","email":"","affiliations":[{"id":64450,"text":"Department of Geophysics, Stanford University, Stanford, CA 94305","active":true,"usgs":false}],"preferred":false,"id":854621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sare, Robert M.","contributorId":210055,"corporation":false,"usgs":false,"family":"Sare","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":38061,"text":"Department of Geological Sciences, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":854622,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maerten, Frantz","contributorId":297912,"corporation":false,"usgs":false,"family":"Maerten","given":"Frantz","email":"","affiliations":[{"id":64451,"text":"YouWol, 455, Avenue Alfred Sauvy, Le Lancaster, 34470 Perols, France","active":true,"usgs":false}],"preferred":false,"id":854623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loveless, Jack","contributorId":297913,"corporation":false,"usgs":false,"family":"Loveless","given":"Jack","email":"","affiliations":[{"id":64453,"text":"Department of Geoscience, Smith College, Northampton, MA 01063","active":true,"usgs":false}],"preferred":false,"id":854624,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baden, Curtis W","contributorId":222424,"corporation":false,"usgs":false,"family":"Baden","given":"Curtis W","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":854625,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hilley, George E.","contributorId":197258,"corporation":false,"usgs":false,"family":"Hilley","given":"George","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":854626,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236576,"text":"70236576 - 2022 - Integrated modeling of dynamic marsh feedbacks and evolution under sea-level rise in a mesotidal estuary (Plum Island, MA, USA)","interactions":[],"lastModifiedDate":"2022-09-12T13:40:47.337166","indexId":"70236576","displayToPublicDate":"2022-09-12T08:30:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Integrated modeling of dynamic marsh feedbacks and evolution under sea-level rise in a mesotidal estuary (Plum Island, MA, USA)","docAbstract":"Around the world, wetland vulnerability to sea-level rise (SLR) depends on different factors including tidal regimes, topography, creeks and estuary geometry, sediment availability, vegetation type, etc. The Plum Island estuary (PIE) is a mesotidal wetland system on the east coast of the United States. This research applied a newly updated Hydro-MEM (integrated hydrodynamic-marsh) model to assess the impacts of intermediate-low (50 cm), intermediate (1 m), and intermediate-high (1.5 m) SLR on marsh evolution by the year 2100. Model advancements include capturing vegetation change, inorganic and below and aboveground organic matter portion of marsh platform accretion, and mudflat creation. Although the results indicate a low vulnerability marsh at the PIE, the vegetation changes from high to low marsh under all SLR scenarios (2%–22%), with the higher bounds belonging to higher rise scenarios. Lower SLR produces more productive marsh (13% gain in high productivity regions), whereas the highest SLR scenario causes increased tidal inundation, which leads to loss in productivity (12% change from high to low productivity regions), generation of mudflats (17% of the domain land), and marsh migration to higher lands. Sensitive nonlinear tidal flow changes, which may be increased or decreased with SLR as a result of mudflat creation, marsh migration, and bottom friction change, emphasize the importance of integrated modeling approaches that include dynamic marsh feedbacks in hydrodynamic modeling and varying hydrodynamic effects on the marsh system.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032225","usgsCitation":"Alizad, K., Morris, J.T., Bilskie, M.V., Passeri, D., and Hagen, S.C., 2022, Integrated modeling of dynamic marsh feedbacks and evolution under sea-level rise in a mesotidal estuary (Plum Island, MA, USA): Water Resources Research, v. 58, no. 8, e2022WR032225, 18 p., https://doi.org/10.1029/2022WR032225.","productDescription":"e2022WR032225, 18 p.","ipdsId":"IP-141664","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr032225","text":"Publisher Index Page"},{"id":406523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Plum Island, Plum Island Estuary","geographicExtents":"{\n 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T.","contributorId":288074,"corporation":false,"usgs":false,"family":"Morris","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":61699,"text":"Belle W. Baruch Institute for Marine and Coastal Sciences, University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":851430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bilskie, Matthew V.","contributorId":166891,"corporation":false,"usgs":false,"family":"Bilskie","given":"Matthew","email":"","middleInitial":"V.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":851431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":851432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, Scott C.","contributorId":166890,"corporation":false,"usgs":false,"family":"Hagen","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":851433,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236590,"text":"70236590 - 2022 - Climate change weakens the impact of disturbance interval on the growth rate of natural populations of Venus flytrap","interactions":[],"lastModifiedDate":"2022-11-16T17:05:26.495283","indexId":"70236590","displayToPublicDate":"2022-09-12T08:18:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Climate change weakens the impact of disturbance interval on the growth rate of natural populations of Venus flytrap","docAbstract":"Disturbances elicit both positive and negative effects on organisms; these effects vary in their strength and their timing. Effects of disturbance interval (i.e., the length of time between disturbances) on population growth will depend on both the timing and strength of positive and negative effects of disturbances. Climate change can modify the relative strengths of these positive and negative effects, leading to altered optimal disturbance intervals (the disturbance interval at which population growth rate is highest) and changes in the sensitivity of population growth rate to disturbance interval. While we know that climate may alter impacts of disturbance in some systems, we have a poor understanding of which effects of disturbance and which vital rates might drive an altered response to disturbance interval in a changing climate. We use demographic monitoring of natural populations of Dionaea muscipula, the Venus flytrap, that have experienced natural and managed fires, combined with realistic past and future climate projections, to construct climate- and fire-driven integral projection models (IPMs). We use these IPMs to compare the effect of fire return interval (FRI) on population growth rate in past and future climates. To dissect the mechanisms driving FRI response, we then construct IPMs with demographic data from an experimental manipulation of fire effects (ash addition, neighbor removal) and an accidental fire. Our results show that an FRI of 10 years is optimal for D. muscipula in past climate conditions, but a longer FRI (12 years) is optimal in future climate conditions. Further, deviations from optimal FRI reduce population growth rate dramatically in the past climate, but this reduction is muted in a future climate (future minus past sensitivity = 0.006, 95% CI [0.002, 0.011]). Finally, our experimental work suggests that fire effects are driven in part by positive, additive effects of competitor removal and ash addition immediately following a fire; for one population, both these treatments significantly increased population growth rate. Our work suggests that climate change can alter the response of populations to disturbance, highlighting the need to consider the interacting effects of multiple abiotic drivers when projecting future population growth and geographical distributions.
","language":"English","publisher":"Wiley","doi":"10.1002/ecm.1528","usgsCitation":"Louthan, A.M., Keighron, M., Kiekebusch, E., Cayton, H., Terando, A., and Morris, W., 2022, Climate change weakens the impact of disturbance interval on the growth rate of natural populations of Venus flytrap: Ecological Monographs, v. 92, e1528, 18 p., https://doi.org/10.1002/ecm.1528.","productDescription":"e1528, 18 p.","ipdsId":"IP-114086","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":446451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1528","text":"Publisher Index Page"},{"id":406517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.310791015625,\n 34.59478059328729\n ],\n [\n -76.7230224609375,\n 34.59478059328729\n ],\n [\n -76.7230224609375,\n 35.018750379438295\n ],\n [\n -77.310791015625,\n 35.018750379438295\n ],\n [\n -77.310791015625,\n 34.59478059328729\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.28970336914062,\n 35.04011643687423\n ],\n [\n -78.8818359375,\n 35.04011643687423\n ],\n [\n -78.8818359375,\n 35.3308118573182\n ],\n [\n -79.28970336914062,\n 35.3308118573182\n ],\n [\n -79.28970336914062,\n 35.04011643687423\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","noUsgsAuthors":false,"publicationDate":"2022-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Louthan, Allison M","contributorId":266009,"corporation":false,"usgs":false,"family":"Louthan","given":"Allison","email":"","middleInitial":"M","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keighron, Melina","contributorId":296421,"corporation":false,"usgs":false,"family":"Keighron","given":"Melina","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiekebusch, Elsita","contributorId":257676,"corporation":false,"usgs":false,"family":"Kiekebusch","given":"Elsita","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":851463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayton, Heather","contributorId":229344,"corporation":false,"usgs":false,"family":"Cayton","given":"Heather","email":"","affiliations":[{"id":41625,"text":"Kellogg Biological Station and Department of Integrative Biology, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":851464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Terando, Adam J. 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":216875,"corporation":false,"usgs":true,"family":"Terando","given":"Adam J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":851465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, William F.","contributorId":266011,"corporation":false,"usgs":false,"family":"Morris","given":"William F.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851466,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236586,"text":"70236586 - 2022 - A machine learning approach to predicting equilibrium ripple wavelength","interactions":[],"lastModifiedDate":"2022-09-28T16:48:59.256996","indexId":"70236586","displayToPublicDate":"2022-09-12T08:11:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A machine learning approach to predicting equilibrium ripple wavelength","docAbstract":"Sand ripples are geomorphic features on the seafloor that affect bottom boundary layer dynamics including wave attenuation and sediment transport. We present a new equilibrium ripple predictor using a machine learning approach that outputs a probability distribution of wave-generated equilibrium wavelengths and statistics including an estimate of ripple height, the most probable ripple wavelength, and sediment and flow parameterizations. The Bayesian Optimal Model System (BOMS) is an ensemble machine learning system that combines two machine learning algorithms and two deterministic empirical ripple predictors with a Bayesian meta-learner to produce probabilistic wave-generated equilibrium ripple wavelength estimates in sandy locations. A ten-fold cross validation of BOMS resulted in an adjusted R-squared value of 0.93 and an average root mean square error (RMSE) of 8.0 cm. During both cross validation and testing on three unique field datasets, BOMS provided more accurate wavelength predictions than each individual base model and other common ripple predictors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2022.105509","usgsCitation":"Phillip, R.E., Penko, A.M., Palmsten, M.L., and DuVal, C.B., 2022, A machine learning approach to predicting equilibrium ripple wavelength: Environmental Modeling and Software, v. 157, 105509, 13 p., https://doi.org/10.1016/j.envsoft.2022.105509.","productDescription":"105509, 13 p.","ipdsId":"IP-133890","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2022.105509","text":"Publisher Index Page"},{"id":406515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phillip, Ryan E.","contributorId":296413,"corporation":false,"usgs":false,"family":"Phillip","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penko, Allison M.","contributorId":296414,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","email":"","middleInitial":"M.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":851447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuVal, Carter B.","contributorId":296415,"corporation":false,"usgs":false,"family":"DuVal","given":"Carter","email":"","middleInitial":"B.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851448,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249322,"text":"70249322 - 2022 - Sedimentary organics in Glen Torridon, Gale Crater, Mars: Results from the SAM instrument suite and supporting laboratory analyses","interactions":[],"lastModifiedDate":"2023-10-04T12:21:37.460362","indexId":"70249322","displayToPublicDate":"2022-09-12T07:17:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9967,"text":"JGR Planets","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary organics in Glen Torridon, Gale Crater, Mars: Results from the SAM instrument suite and supporting laboratory analyses","docAbstract":"The Sample Analysis at Mars (SAM) suite instrument on board NASA's Curiosity rover has characterized the inorganic and organic chemical composition of seven samples from the Glen Torridon (GT) clay-bearing unit. A variety of organic molecules were detected with SAM using pyrolysis (up to ∼850°C) and wet chemistry experiments coupled with evolved gas analysis (EGA) and gas chromatography-mass spectrometry. SAM EGA and GCMS analyses revealed a greater diversity and abundance of sulfur-bearing aliphatic and aromatic organic compounds in the sediments of this Gale crater unit than earlier in the mission. We also report the detection of nitrogen-containing, oxygen-containing, and chlorine-containing molecules, as well as polycyclic aromatic hydrocarbons found in GT, although the sources of some of these organics may be related to the presence of chemical reagents in the SAM instrument background. However, sulfur-bearing organics released at high temperature (≥600°C) are likely derived from Martian sources (e.g., igneous, hydrothermal, atmospheric, or biological) or exogenous sources and consistent with the presence of recalcitrant organic materials in the sample. The SAM measurements of the GT clay-bearing unit expand the inventory of organic matter present in Gale crater and is also consistent with the hypothesis that clay minerals played an important role in the preservation of ancient refractory organic matter on Mars. These findings deepen our understanding of the past habitability and biological potential of Gale crater.
Dome-building volcanic eruptions are often associated with frequent Vulcanian explosions, which constitute a substantial threat to proximal communities. One proposed mechanism driving such explosions is the sealing of the shallow volcanic system followed by pressurization due to gas accumulation beneath the seal. We investigate this hypothesis at Sinabung Volcano (Sumatra, Indonesia), which has been in a state of eruption since August 2010. In 2013, the volcano began erupting a lava dome and lava flow, and frequent explosions produced eruptive columns that rose many kilometers into the atmosphere and at times sent pyroclastic density currents down the southeast flanks. A network of scanning Differential Optical Absorption Spectrometers (DOAS) was installed on the volcano’s eastern flank in 2016 to continuously monitor SO2 emission rates during daytime hours. Analysis of the DOAS data from October 2016 to September 2017 revealed that passive SO2 emissions were generally lower in the 5 days leading up to explosive events (∼100 t/d) than was common in 5-day periods leading up to days on which no explosions occurred (∼200 t/d). The variability of passive SO2 emissions, expressed as the standard deviation, also took on a slightly wider range of values before days with explosions (0–103 t/d at 1-sigma) than before days without explosions (43–117 t/d). These observations are consistent with the aforementioned seal-failure model, where the sealing of the volcanic conduit blocks gas emissions and leads to pressurization and potential Vulcanian explosions. We develop a forecasting methodology that allows calculation of a relative daily explosion probability based solely on measurements of the SO2 emission rate in the preceding days. We then calculate forecast explosion probabilities for the remaining SO2 emissions dataset (October 2017—September 2021). While the absolute accuracy of forecast explosion probabilities is variable, the method can inform the probability of an explosion occurring relative to that on other days in each test period. This information can be used operationally by volcano observatories to assess relative risk. The SO2 emissions-based forecasting method is likely applicable to other open vent volcanoes experiencing dome-forming eruptions.
The Glen Torridon (GT) region within Gale crater, Mars, occurs in contact with the southern side of Vera Rubin ridge (VRR), a well-defined geomorphic feature that is comparatively resistant to erosion. Prior to detailed ground-based investigation of GT, its geologic relationship with VRR was unknown. Distinct lithologic subunits within the Jura member (Murray formation), which forms the upper part of VRR, made it possible to be also identified within GT. This indicates that the strata pass across the geomorphic divide between regions. Furthermore, the cross-bedded lower part of the overlying Knockfarril Hill member (Carolyn Shoemaker formation) also occurs within both VRR and GT. Correlation of both units demonstrates that the strata form a continuous stratigraphic succession regardless of large-scale geomorphic expression. The lithologic change from mudstone (Jura member) to cross-bedded sandstone (Knockfarril Hill member) heralds a significant shift in paleoenvironment from lacustrine to fluvial. The upper part of the Knockfarril Hill member consists of interbedded mudstone and sandstone that transitions to the overlying finely laminated mudstone of the Glasgow member, and a return to lacustrine deposition. In GT, the Stimson formation unconformably overlies the Glasgow member, where it demarks the southern boundary of GT. Contacts for each stratigraphic unit were defined and transferred to a high-resolution image base to make a geologic map and cross sections perpendicular to the NE strike. Stratal dips cannot exceed 2° NW to retain the positions of stratigraphic units in the locations they are exposed throughout GT.
Within nearshore waters off Bimini, The Bahamas, Atlantic spotted (Stenella frontalis) and common bottlenose (Tursiops truncatus) dolphins are sympatric but separated spatially in different geographic areas and water depth ranges. Afternoon surveys during summer months across a 16-year period showed S. frontalis used the northern part of the nearshore area more, while T. truncatus used the southern area more. Generally, examination of geographic zones and water depth distributions of both species before and after construction of a pier in the study area suggested these dolphins were not impacted, long-term, by this anthropogenic activity. Still some differences in use of the nearshore area were identified. For water depth, S. frontalis varied use between 5–<12 m and 12–<20 m, depending on location along the coast. In contrast, T. truncatus consistently used the 5–<12 m depths. This difference may be related to how each species used the nearshore area, with T. truncatus feeding more and S. frontalis travelling and doing other activities. A small change in the distribution of S. frontalis by water depth off the northern coast of Bimini was found, specifically an increased use of deeper (12–20 m) water post 2014, which is unlikely an effect of pier construction as S. frontalis continued to use the 5–12 m depths as they had before pier construction. How this change might be related to an unprecedented 2013 S. frontalis immigration event, which might have disrupted the social structure, habitat/resource use, and distribution of both species, is discussed.
","language":"English","publisher":"BioOne","doi":"10.18475/cjos.v52i2.a3","usgsCitation":"Levengood, A., Melillo-Sweeting, K., Ribic, C., Beck, A., and Dudzinski, K., 2022, Atlantic spotted and bottlenose dolphin sympatric distribution in nearshore waters off Bimini, The Bahamas, 2003–2018: Caribbean Journal of Science, v. 52, no. 2, p. 162-176, https://doi.org/10.18475/cjos.v52i2.a3.","productDescription":"15 p.","startPage":"162","endPage":"176","ipdsId":"IP-136851","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"The Bahamas","otherGeospatial":"Bimini","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.37704714400411,\n 25.826924686024014\n ],\n [\n -79.37704714400411,\n 25.649096003650968\n ],\n [\n -79.1858998236686,\n 25.649096003650968\n ],\n [\n -79.1858998236686,\n 25.826924686024014\n ],\n [\n -79.37704714400411,\n 25.826924686024014\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levengood, Alexis L.","contributorId":349054,"corporation":false,"usgs":false,"family":"Levengood","given":"Alexis L.","affiliations":[{"id":82938,"text":"University of the Sunshine Coast","active":true,"usgs":false}],"preferred":false,"id":923960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melillo-Sweeting, Kelly","contributorId":349055,"corporation":false,"usgs":false,"family":"Melillo-Sweeting","given":"Kelly","affiliations":[{"id":56353,"text":"Dolphin Communication Project","active":true,"usgs":false}],"preferred":false,"id":923961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":923962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Albert J.","contributorId":349056,"corporation":false,"usgs":false,"family":"Beck","given":"Albert J.","affiliations":[{"id":83418,"text":"Wisconsin Cooperative Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":923963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudzinski, Kathleen M.","contributorId":349057,"corporation":false,"usgs":false,"family":"Dudzinski","given":"Kathleen M.","affiliations":[{"id":56353,"text":"Dolphin Communication Project","active":true,"usgs":false}],"preferred":false,"id":923964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243031,"text":"70243031 - 2022 - Climate matching with the climatchR R package","interactions":[],"lastModifiedDate":"2023-04-27T12:13:41.49622","indexId":"70243031","displayToPublicDate":"2022-09-11T07:11:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14260,"text":"Environmental Software & Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Climate matching with the climatchR R package","docAbstract":"Climate matching allows comparisons of climatic conditions between different locations to understand location and species range climatic suitability. The approach may be used as part of horizon scanning exercises such as those conducted for invasive species. We implemented the CLIMATCH algorithm into an R package, climatchR. The package allows automated and scripted climate matching exercises across all steps from downloading data to summarizing species climate matches. We also show how climatchR may be used with high-throughput computing to process many species. For example, we were able to calculate climate scores for over 8,000 species in less than 3 days using this package. This automation allows high-throughput processing of species data, a new development for improving the efficiency and speed of climate matching and horizon scanning.
The Smoky Madtom Noturus baileyi is a federally endangered species, whose native distribution includes lower Abrams Creek in Great Smoky Mountains National Park (GRSM) and Citico Creek in nearby Cherokee National Forest. Due to challenges for bio-monitoring posed by its nocturnality and cryptic life history, an environmental DNA (eDNA)-based approach for detection would be useful to complement existing electrofishing and seining efforts to better understand the distribution of this species. We developed a probe-based droplet digital PCR (ddPCR) assay to detect Smoky Madtoms from non-invasively collected water samples. The assay was specific to N. baileyi and did not amplify concentrated genomic DNA of 16 co-occurring or regional fish species, including the yellowfin madtom N. flavipinnis and stonecat N. flavus. The assay limit of detection (LOD) was determined to be 4.18 copies (95% CI: 3.95, 4.41). Several 2 L water samples collected from throughout various streams in GRSM in 2016 and 2017 were tested for the presence of N. baileyi using the ddPCR assay. N. baileyi was detected at two different sites in 2016 and 2017 within Abrams Creek previously known to contain N. baileyi, but no novel detections in other sampled streams were observed. This assay should prove useful for continued surveys of N. baileyi in GRSM.
Biodiversity conservation efforts have been criticized for generating inequitable socio-economic outcomes. These equity challenges are largely analyzed as place-based problems affecting local communities directly impacted by conservation programs. The conservation of migratory species extends this problem geographically since people in one place may benefit while those in another bear the costs of conservation. The spatial subsidies approach offers an effective tool for analyzing such relationships between places connected by migratory species. Designed to quantify ecosystem services provided and received in specific locations across a migratory species’ range—and the disparities between them—the spatial subsidies approach highlights three axes of inequity: between indigenous and settler colonial societies, between urban and rural populations, and between the Global North and Global South. Recognizing these relationships is critical to achieving two mutually reinforcing policy goals: avoiding inequitable conservation outcomes in efforts to conserve migratory species, and ensuring effective long-term conservation of migratory species. In demonstrating how the spatial subsidies approach enables the identification and quantification of inequities involving three migratory species (northern pintail ducks, monarch butterflies, and Mexican free-tailed bats), we argue that a spatial subsidies approach could apply to migratory species conservation efforts worldwide under the context of “payments for ecosystem services.”
The U.S. Geological Survey (USGS) operates an extensive nationwide network of stream, rain, and groundwater gages. These instruments are used to monitor how much water there is across the Nation at any given moment. Stream data are collected at streamgages every 15 minutes, transmitted to USGS servers, and updated online in real time. To improve awareness of current water conditions and possible flooding, stream data are combined with rain data collected at nearby USGS rain gages. The National Weather Service uses the USGS stream and rain data to forecast when flooding might occur and issue flood warnings.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223076","collaboration":"Prepared in cooperation with National Weather Service","usgsCitation":"Sobieszczyk, S., 2022, How USGS gages are used in flood forecasting: U.S. Geological Survey Fact Sheet 2022–3076, 2 p., https://doi.org/10.3133/fs20223076. [In English and Spanish.]","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-143721","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":406458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3076/fs20223076.pdf","size":"422 kB","linkFileType":{"id":1,"text":"pdf"},"description":"fs 2022-3076"},{"id":406457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3076/coverthb.jpg"}],"contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 12.9 billion barrels of oil and 684.3 trillion cubic feet of gas in the West Siberian Basin Province of Russia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20223047","usgsCitation":"Schenk, C.J., Mercier, T.J., Ellis, G.S., Woodall, C.A., Le, P.A., Leathers-Miller, H.M., and Drake, R.M., II, 2022, Assessment of undiscovered conventional oil and gas resources of the West Siberian Basin Province, Russia, 2020: U.S. Geological Survey Fact Sheet 2022−3047, 2 p., https://doi.org/10.3133/fs20223047.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-129429","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":406337,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3047/fs20223047.pdf","text":"Report","size":"8.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3047"},{"id":406336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3047/coverthb.jpg"},{"id":406338,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGOVUB","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-West Siberian Basin Province of Russia: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"}],"country":"Russia","state":"Siberia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 48,\n 54\n ],\n [\n 102,\n 54\n ],\n [\n 102,\n 74\n ],\n [\n 48,\n 74\n ],\n [\n 48,\n 54\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Little is known about water movement, volume, or residence time (RT), and how those characteristics affect sediment trapping efficiency (TE) and dissolved oxygen concentrations (DO) in the United States' largest remaining bottomland hardwood swamp, the Atchafalaya River Basin. To better understand these dynamics, this study used bathymetry, lidar, and stage records to determine volumes in the Basin's hydrologically distinct water management units (WMUs). Discharge measurements determined flow distribution and RT. Residence time was compared with DO to identify conditions that coincided with DO increases or decreases. Suspended sediment concentrations (SSC) were used to determine TE relative to calculated and measured discharge and RT. Discharge through units (85–2,200 m3/s) and RT (0.37–231 d) depended on connectivity and river stage. At high stages, with water temperatures >20°C, DO in the largest WMU declined by −0.21 mg/l/day. DO trends indicated less well-connected areas of the WMU contributed hypoxic waters as the flood wave lengthened and stages fell. In the two WMUs examined for TE, TE (−266% to 99% and up to 38 Gg/day) correlated with hydrologic connectivity, SSC, RT, water volume, and, in one WMU, discharge losses. Long RT and high TE indicated a high potential to process nutrients. These relationships varied among WMUs. Large volumes of sediment-laden water moving over the floodplain combined with long RT, high TE, and hypoxia indicate that this ecosystem has continental-scale importance in reducing nutrient loads to the northern Gulf of Mexico. Reports from other systems suggest similar processes may be operating on other large river floodplains globally.
","language":"English","publisher":"Wiley","doi":"10.1029/2021WR030731","usgsCitation":"Kroes, D., Day, R., Kaller, M.D., Demas, C.R., Kelso, W.E., Pasco, T., Harlan, R., and Roberts, S., 2022, Hydrologic connectivity and residence time affect the sediment trapping efficiency and dissolved oxygen concentrations of the Atchafalaya River Basin: Water Resources Research, v. 58, no. 11, e2021WR030731, 25 p., https://doi.org/10.1029/2021WR030731.","productDescription":"e2021WR030731, 25 p.","ipdsId":"IP-122676","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":446481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030731","text":"Publisher Index Page"},{"id":411722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.19842494954662,\n 29.43299698721681\n ],\n [\n -91.0065616177603,\n 29.745824547354005\n ],\n [\n -91.69407188999388,\n 30.994196767826082\n ],\n [\n -91.98986119316385,\n 30.994196767826082\n ],\n [\n -91.91791244374411,\n 30.39269246892897\n ],\n [\n -91.62212314057413,\n 29.849884487088616\n ],\n [\n -91.4622370307522,\n 29.540858164204536\n ],\n [\n -91.19842494954662,\n 29.43299698721681\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Richard 0000-0002-5959-7054","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":221895,"corporation":false,"usgs":true,"family":"Day","given":"Richard","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":861387,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaller, Michael D. 0000-0002-1239-7725","orcid":"https://orcid.org/0000-0002-1239-7725","contributorId":300764,"corporation":false,"usgs":false,"family":"Kaller","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861388,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demas, Charles R.","contributorId":300765,"corporation":false,"usgs":false,"family":"Demas","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":861389,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelso, William E.","contributorId":300766,"corporation":false,"usgs":false,"family":"Kelso","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861390,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pasco, Tiffany","contributorId":300767,"corporation":false,"usgs":false,"family":"Pasco","given":"Tiffany","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":861391,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harlan, Raynie","contributorId":300768,"corporation":false,"usgs":false,"family":"Harlan","given":"Raynie","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":861392,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roberts, Steven","contributorId":300769,"corporation":false,"usgs":false,"family":"Roberts","given":"Steven","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":861393,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70237821,"text":"70237821 - 2022 - A reproducible and reusable pipeline for segmentation of geoscientific imagery","interactions":[],"lastModifiedDate":"2022-10-25T14:30:48.574122","indexId":"70237821","displayToPublicDate":"2022-09-09T09:27:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"A reproducible and reusable pipeline for segmentation of geoscientific imagery","docAbstract":"Segmentation of Earth science imagery is an increasingly common task. Among modern techniques that use Deep Learning, the UNet architecture has been shown to be a reliable for segmenting a range of imagery. We developed software–Segmentation Gym–to implement a data-model pipeline for segmentation of scientific imagery using a family of UNet models. With an existing set of imagery and labels, the software uses a single configuration file that handles data set creation, as well as model setup and model training. Key benefits of this software are (a) the focus on reproducible data set creation and modeling, and (b) the ability for quick model experimentation through changes to a configuration file. Quick experimentation permits researchers to prototype different model architectures, sizes, and adjust common hyperparameters to find a suitable model. We demonstrate the use of the software using a data set of 419 labeled Landsat-8 scenes of coastal environments and compare results across two model architectures, five model sizes, and three loss functions. This demonstration highlights that our software enables rapid, reproducible experimentation to determine optimal hyperparameters for specific data sets and research questions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EA002332","usgsCitation":"Buscombe, D.D., and Goldstein, E.B., 2022, A reproducible and reusable pipeline for segmentation of geoscientific imagery: Earth and Space Science, v. 9, e2022EA002332, 11 p., https://doi.org/10.1029/2022EA002332.","productDescription":"e2022EA002332, 11 p.","ipdsId":"IP-136939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446483,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ea002332","text":"Publisher Index Page"},{"id":408698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":855767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Evan B. 0000-0001-9358-1016","orcid":"https://orcid.org/0000-0001-9358-1016","contributorId":184210,"corporation":false,"usgs":false,"family":"Goldstein","given":"Evan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":855768,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241528,"text":"70241528 - 2022 - Rapid SNP genotyping, sex identification, and hybrid-detection in threatened bull trout","interactions":[],"lastModifiedDate":"2023-03-22T13:27:31.459044","indexId":"70241528","displayToPublicDate":"2022-09-09T08:21:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Rapid SNP genotyping, sex identification, and hybrid-detection in threatened bull trout","docAbstract":"We developed new bull trout genetic markers using Restriction-site Associated DNA sequencing (RAD-seq) to improve our ability to address questions important for their conservation and management. Samples from across the species range were sequenced and 5020 high quality single nucleotide polymorphism (SNP) loci were discovered, including hundreds with high heterozygosity (H > 0.30). We developed 63 high-heterozygosity bull trout polymorphic SNPs and one sex-identification SNP and tested them on range-wide samples. In addition, we tested previously published SNP assays including 11 species-diagnostic SNPs differentiating bull trout from brook trout and 3 brook trout variable SNPs on a broad set of range-wide samples. Genotypes from the sex-identification SNP showed 95% agreement with the field sex identification across 113 samples. The eleven species-diagnostic loci reliably discriminated between known brook trout, bull trout, and F1 hybrid control samples. These SNP assays will facilitate genotyping of partially degraded museum fin clips, and tissues with low DNA content such as scales and otoliths. Finally, these loci will allow rapid genotyping for improved resolution of bull trout population structure, sex ratios, movement patterns, and introgressive hybridization with non-native brook trout for a wide range of management questions.
","language":"English","publisher":"Springer","doi":"10.1007/s12686-022-01289-w","usgsCitation":"Amish, S.J., Bernall, S., DeHaan, P.W., Miller, M.A., O'Rourke, S., Boyer, M., Muhlfeld, C.C., Lodmell, A., Leary, R., and Luikart, G., 2022, Rapid SNP genotyping, sex identification, and hybrid-detection in threatened bull trout: Conservation Genetics Resources, v. 14, p. 421-427, https://doi.org/10.1007/s12686-022-01289-w.","productDescription":"7 p.","startPage":"421","endPage":"427","ipdsId":"IP-144024","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":414544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Idaho, Montana, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n 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Resources","active":true,"usgs":false}],"preferred":false,"id":867123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O'Rourke, Sean M.","contributorId":224282,"corporation":false,"usgs":false,"family":"O'Rourke","given":"Sean M.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":867124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyer, Matthew","contributorId":124595,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":867125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":867126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lodmell, Angela","contributorId":303305,"corporation":false,"usgs":false,"family":"Lodmell","given":"Angela","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":867127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Leary, Robb F.","contributorId":126726,"corporation":false,"usgs":false,"family":"Leary","given":"Robb F.","affiliations":[{"id":6582,"text":"Montana Fish, Wildlife and Parks, Missoula, Montana 59801, USA","active":true,"usgs":false}],"preferred":false,"id":867128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":867129,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237158,"text":"70237158 - 2022 - Simulation of heat flow in a synthetic watershed: Lags and dampening across multiple pathways under a climate-forcing scenario","interactions":[],"lastModifiedDate":"2022-10-03T11:38:05.919553","indexId":"70237158","displayToPublicDate":"2022-09-09T06:36:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of heat flow in a synthetic watershed: Lags and dampening across multiple pathways under a climate-forcing scenario","docAbstract":"1. The relationships between macrophytes and the physical and biological characteristics of the environments that aquatic organisms inhabit are complex. Previous studies have shown that the macrophytes, Ranunculus (subgenus Batrachium), which are dominant in lowland chalk streams and widespread across Europe, can enhance juvenile Atlantic salmon abundance and growth to a greater degree than other physical and biological habitat characteristics. However, mechanistic understanding of how this effect might arise requires consideration of the direct and indirect relationships among habitat characteristics that are likely to be influenced by the presence of macrophyte cover.
2. We applied structural equation modelling to data collected during a 2-year in-river manipulative experiment in the River Frome (southern England, U.K.) designed to quantify the magnitude and the relative importance of direct and indirect influences of Ranunculus cover and other physical and biological variables, including water velocity, water depth, prey biomass and body size, and abundance of con- and hetero-specifics, on abundance and somatic growth of 0+ salmon.
3. Results indicated a strongly positive direct influence of Ranunculus cover on salmon abundance, as well as positive influences of Ranunculus on velocity heterogeneity and water depth that are indirectly related to decreased salmon abundance. Interestingly, there was no indication of a direct influence of Ranunculus cover on salmon growth, although Ranunculus was indirectly related to increased salmon growth through its positive influence on prey biomass, an effect mediated by velocity heterogeneity and proportion of fast velocities.
4. These findings provide novel mechanistic insights into the key role of Ranunculus in their native lowland rivers to enhance abundance and improve conditions for multiple food web components. Strategies to maintain or enhance naturally occurring Ranunculus in these rivers are therefore likely to return wide ranging ecosystem benefits, including for species of high conservation value, such as salmon. These mechanistic impacts on habitat heterogeneity and ecosystem productivity could generalise to native macrophytes in other river systems, particularly where habitat is dominated by vegetation in the absence of large substrates.