The U.S. Geological Survey (USGS) National Cooperative Geologic Mapping Program (NCGMP) has published a strategic plan entitled “Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge”. This plan provides the following vision, mission, and goals for the program for the years 2020–30:
To achieve the goal outlined in the strategic plan, the NCGMP has developed an Implementation Plan. This Implementation Plan will guide annual reviews of the FEDMAP component (that is, the component of the USGS NCGMP that funds geologic mapping by USGS geologists) of the NCGMP projects described in the plan and the development of the annual FEDMAP prospectus, which will ensure the application of the NCGMP strategy.
This publication is part of the Implementation Plan of the NCGMP strategy and addresses the following three major topics:
The regions used in this chapter correspond with physiographic divisions of the United States as defined by Fenneman. Physiographic divisions are delineated on the basis of topography, and to a lesser extent, the geologic structure and history. The physiographic divisions are subdivided into physiographic provinces, and the physiographic provinces are subdivided into physiographic sections. Fenneman’s physiographic divisions of the United States provide a robust and useful spatial organization for delineating large geographic regions of the United States for various scientific and industrial applications.
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U.S. Geological Survey
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The U.S. Geological Survey (USGS) 21st-century science strategy 2020–30 promotes a bureau-wide strategy to develop and deliver an integrated, predictive science capability that works at the scales and timelines needed to inform societally relevant resource management and protection and public safety and environmental health decisions (U.S. Geological Survey, 2021). This is the overarching goal of the USGS Earth Monitoring, Analysis, and Prediction (EarthMAP) vision, which consists of three components: (1) integrated data and information, (2) integrated predictive science, and (3) actionable information—all designed and delivered to respond to user needs. To launch this vision and help shape the design and implementation of integrated predictive science, the USGS Regional Offices each developed a set of use cases (hereafter Use Cases)—short descriptions of potential science applications that could clearly address high priority decision-making needs of our stakeholders and that align with an integrated science focus. Use Cases are not actionable science planning documents, nor stand-alone scholarly works, but should be considered as innovative, next-generation science ideas that can be considered as potential components of science plans still under development. The goal of Use Case development was to (1) identify and characterize existing USGS scientific capacities and expertise that can support science goals and products, (2) identify opportunities to leverage current capacities for next-generation science, and (3) foster engagement across the entire Bureau to further refine the USGS strategy for EarthMAP and integrated predictive science.
The Use Case development effort documented in this report was coordinated by the Use Case Development Team (UCDT), consisting of representatives from each region. The UCDT undertook five tasks: (1) develop a unified approach to engage bureau scientists consistently across all regions in aspirational thinking about what can be accomplished; (2) work with the regions and their Science Centers to generate an initial set of Use Cases, authored directly by scientists; (3) characterize, summarize, and document the initial set of Use Case submissions from authors to illuminate bureau-level demand for integrated science; (4) compare existing and needed capacities from the Use Case descriptions with preliminary results of the EarthMAP Capacity Assessment (Keisman and others, 2021); and (5) describe lessons learned from the Use Case development process and provide recommendations to inform future efforts to generate integrated science activities. This report outlines the approach the UCDT developed to solicit Use Cases from the regions and summarizes the high-level qualitative findings from this first-round effort.
The UCDT received 36 Use Cases from the regions and identified potential points of convergence and commonalities considered useful in making connections among the participating scientists. The Southwest (SW) Region and the Rocky Mountain (RM) Region asked scientists to give special consideration to Use Cases with applicability to the Colorado River Basin, and seven of the Use Cases specifically named that geographic area as a focus. Coastal hazards and coastal resilience were identified in Use Cases from the Alaska (AK), Northeast (NE), and Southeast (SE) Regions. Aspects of wildfire and post-wildfire response were part of Uses Cases from AK, RM, and SW Regions. The greatest convergence of Use Case themes was related to conservation of public lands and waters, which is a powerful linkage lending strength to future collaborative efforts.
The most common type of stakeholder decisions that would be informed by the Use Case science applications were related to adaptation, mitigation, and response (for example, how to increase the resilience of coastal communities to climate-related stressors and how to prevent or respond to harmful algal blooms). Other common types of decisions included water and land management decisions (including operational water management decisions such as reservoir operations and land use planning in the sagebrush biome), decisions about how to manage and conserve habitats and species, and risk management decisions (such as managing the post-wildfire flood risks). These decision types are not exclusive because many Use Cases cross categories.
Use Case authors identified existing and needed science and technology capabilities required for Use Case implementation, which were then aligned to capabilities assessed in the EarthMAP Capacity Assessment (Keisman and others, 2021). Strong alignment was found for data and information integration approaches, modeling and prediction approaches, and capabilities related to delivery of actionable information. A majority of Use Cases indicated insufficient current capacity for needed data collection methods, data integration, and modeling and prediction approaches, whereas only 25 percent indicated insufficient capacity for actionable information delivery. Overall, many Use Case capacity demand gaps could potentially be met by existing bureau-wide capacity. In addition, nearly half of the Use Cases could potentially be implemented within 3 years if funding, capabilities, and personnel impediments were removed and science priorities were realigned.
Several challenges emerged during the Use Case development process. The first challenge was developing an approach that was flexible enough to accommodate regional differences in planning and implementation, while also ensuring enough guidance to promote meaningful summary analyses. The UCDT encountered a strong demand for continuous communication and education to improve overall understanding of the integrated predictive science strategy. Another challenge was managing expectations about EarthMAP activities as a design effort that was not aligned to an immediate funding opportunity. Connecting the Use Cases to stakeholder needs without the opportunity for direct stakeholder engagement was also challenging. The last notable challenge was in obtaining consistent interpretation and characterization of the qualitative data housed in the narrative descriptions of Use Cases, written in different styles.
Overall, the 36 Use Cases can serve as components of a road map for advancing integrated monitoring and predictive science throughout the USGS by revealing opportunities to (1) encourage cross-region initiatives that address shared interests in common themes by integrating similar Use Cases and through direct involvement of stakeholders in identifying needs and designing effective responses, (2) leverage the Use Cases to target investments that are aligned with the Bureau and Department of the Interior (DOI) priorities, (3) connect Use Cases and the results of the companion EarthMAP Capacity Assessment (Keisman and others, 2021) to identify potential priorities for capacity building investments, and (4) raise awareness of common integrated and interdisciplinary science interests within and across the regions through Use Case and Capacity Assessment summary outreach activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211108","programNote":"Science Synthesis, Analysis and Research Program","usgsCitation":"Wilson, T.S., Wiltermuth, M.T., Jenni, K.E., Horton, R.J., Hunt, R.J., Williams, D.M., Nolan, V.P., Aumen, N.G., Brown, D.S., Blasch, K.W., and Murdoch, P.S., 2022, Use case development for earth monitoring, analysis, and prediction (EarthMAP)—A road map for future integrated predictive science at the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2021–1108, 137 p., https://doi.org/10.3133/ofr20211108.","productDescription":"vii, 132 p.","numberOfPages":"132","onlineOnly":"Y","ipdsId":"IP-129972","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":394402,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1108/covrthb.jpg"},{"id":394403,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1108/ofr20211108.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":394404,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1108/ofr20211108.xml"},{"id":394405,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1108/images"}],"contact":"Director,
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12201 Sunrise Valley Drive
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No abstract available.
","language":"English","publisher":"The Capital Area Ground Water Conservation Commission","usgsCitation":"Di Leonardo, D., Dausman, A., Clark, R., Runge, M.C., Dalyander, S., Hemmerling, S., Grismore, A., Afinowicz, J., Taucer, P., Skipwith, J., and Tsai, F.T., 2022, Long-term strategic plan for the Capital Area Ground Water Conservation Commission: Phase 2A final report, 441 p.","productDescription":"441 p.","ipdsId":"IP-146051","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":419402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419375,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://thewaterinstitute.org/reports/long-term-strategic-plan-for-the-capital-area-ground-water-conservation-commission-phase2a-final-report"}],"country":"United States","state":"Louisiana","otherGeospatial":"Southern Hills aquifer syttem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.8,\n 31.1\n ],\n [\n -91.8,\n 30.4\n ],\n [\n -90.5,\n 30.4\n ],\n [\n -90.5,\n 31.1\n ],\n [\n -91.8,\n 31.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Di Leonardo, Diana","contributorId":317725,"corporation":false,"usgs":false,"family":"Di Leonardo","given":"Diana","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":879172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dausman, Alyssa","contributorId":223766,"corporation":false,"usgs":false,"family":"Dausman","given":"Alyssa","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":879173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Ryan","contributorId":193538,"corporation":false,"usgs":false,"family":"Clark","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":879174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":879175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dalyander, Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":221905,"corporation":false,"usgs":false,"family":"Dalyander","given":"Soupy","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":879176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hemmerling, Scott","contributorId":221274,"corporation":false,"usgs":false,"family":"Hemmerling","given":"Scott","affiliations":[],"preferred":false,"id":879177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grismore, Audrey","contributorId":317726,"corporation":false,"usgs":false,"family":"Grismore","given":"Audrey","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":879178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Afinowicz, Jason","contributorId":317729,"corporation":false,"usgs":false,"family":"Afinowicz","given":"Jason","email":"","affiliations":[{"id":69136,"text":"Freese and Nichols, Inc.","active":true,"usgs":false}],"preferred":false,"id":879180,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taucer, Philip","contributorId":317730,"corporation":false,"usgs":false,"family":"Taucer","given":"Philip","email":"","affiliations":[{"id":69136,"text":"Freese and Nichols, Inc.","active":true,"usgs":false}],"preferred":false,"id":879181,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Skipwith, Jordan","contributorId":317731,"corporation":false,"usgs":false,"family":"Skipwith","given":"Jordan","email":"","affiliations":[{"id":69136,"text":"Freese and Nichols, Inc.","active":true,"usgs":false}],"preferred":false,"id":879182,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tsai, Frank T.-C.","contributorId":305938,"corporation":false,"usgs":false,"family":"Tsai","given":"Frank","email":"","middleInitial":"T.-C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":879183,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70227427,"text":"70227427 - 2022 - U.S. Atlantic margin gas hydrates","interactions":[],"lastModifiedDate":"2022-01-14T16:44:10.454953","indexId":"70227427","displayToPublicDate":"2022-01-14T10:18:10","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"U.S. Atlantic margin gas hydrates","docAbstract":"The minimum distribution of gas hydrates on the U.S. Atlantic margin is from offshore South Carolina northward to the longitude of Shallop Canyon on the southern New England margin. Few wells have logged or sampled the gas hydrate zone on this margin, meaning that the presence of gas hydrates is inferred primarily based on seismic data that reveal bottom simulating reflections, mostly at water depths greater than 2000 m. The highest hydrate saturations most likely exist in sandy sediments of the Whale Prospect offshore New Jersey, New York, and the western part of Cape Cod, an area characterized by strong bottom simulating reflections. Such reflections are also imaged on the well-studied Blake Ridge, where fine-grained sediments host lower hydrate saturations that have been constrained by drilling. Within the section of the margin stretching from south of Cape Hatteras to nearly Hudson Canyon, the diagnostic seismic reflections are hard to discern, making inferences about gas hydrate distributions more uncertain. The recognition of as-yet unmapped bottom simulating reflections or top of gas features seaward of the 2000 m bathymetric contour (e.g., Cape Fear Slide, Currituck slide, beneath deepwater gas seeps) within the Mid-Atlantic Bight expands the area of probable gas hydrates on this margin.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_24","usgsCitation":"Ruppel, C.D., Shedd, W., Miller, N.C., Kluesner, J.W., Frye, M., and Hutchinson, D., 2022, U.S. Atlantic margin gas hydrates, chap. of World atlas of submarine gas hydrates in continental margins, p. 287-302, https://doi.org/10.1007/978-3-030-81186-0_24.","productDescription":"16 p.","startPage":"287","endPage":"302","ipdsId":"IP-122469","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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Increasing transdisciplinary and interdisciplinary collaboration efforts will build the foundation for identifying sustainable solutions and adaptation strategies to reduce future risks for those living on, working at and visiting the rapidly changing Arctic coast.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s43017-021-00232-1","usgsCitation":"Irrgang, A.M., Bendixen, M., Farquharson, L.M., Baranskaya, A.V., Erikson, L.H., Gibbs, A.E., Ogorodov, S.A., Overduin, P.P., Lantuit, H., Grigoriev, M.N., and Jones, B., 2022, Drivers, dynamics and impacts of changing Arctic coasts: Nature Reviews Earth & Environment, v. 3, p. 39-54, https://doi.org/10.1038/s43017-021-00232-1.","productDescription":"16 p.","startPage":"39","endPage":"54","ipdsId":"IP-129580","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488911,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Irrgang, Anna M.","contributorId":248316,"corporation":false,"usgs":false,"family":"Irrgang","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":830821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bendixen, Mette","contributorId":248329,"corporation":false,"usgs":false,"family":"Bendixen","given":"Mette","email":"","affiliations":[{"id":49858,"text":"Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, USA","active":true,"usgs":false}],"preferred":false,"id":830822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farquharson, Louise M. 0000-0001-8884-511X","orcid":"https://orcid.org/0000-0001-8884-511X","contributorId":208626,"corporation":false,"usgs":false,"family":"Farquharson","given":"Louise","email":"","middleInitial":"M.","affiliations":[{"id":37849,"text":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":830823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baranskaya, Alisa V.","contributorId":271099,"corporation":false,"usgs":false,"family":"Baranskaya","given":"Alisa","email":"","middleInitial":"V.","affiliations":[{"id":56279,"text":"Lomonosov State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":830824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830825,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830826,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ogorodov, Stanislav A.","contributorId":271100,"corporation":false,"usgs":false,"family":"Ogorodov","given":"Stanislav","email":"","middleInitial":"A.","affiliations":[{"id":56279,"text":"Lomonosov State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":830827,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Overduin, Pier Paul","contributorId":271101,"corporation":false,"usgs":false,"family":"Overduin","given":"Pier","email":"","middleInitial":"Paul","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":830828,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lantuit, Hugues","contributorId":248317,"corporation":false,"usgs":false,"family":"Lantuit","given":"Hugues","email":"","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":830829,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grigoriev, Mikhail N.","contributorId":271102,"corporation":false,"usgs":false,"family":"Grigoriev","given":"Mikhail","email":"","middleInitial":"N.","affiliations":[{"id":56280,"text":"Melnikov Permafrost Institute, Yakutsk, Russia","active":true,"usgs":false}],"preferred":false,"id":830830,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, Benjamin M. 0000-0002-1517-4711","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":208625,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin M.","affiliations":[{"id":37848,"text":"Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":true,"id":830831,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70227428,"text":"70227428 - 2022 - Nutrient identity modifies the destabilising effects of eutrophication in grasslands","interactions":[],"lastModifiedDate":"2022-04-11T16:52:33.801569","indexId":"70227428","displayToPublicDate":"2022-01-14T09:37:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient identity modifies the destabilising effects of eutrophication in grasslands","docAbstract":"Nutrient enrichment can simultaneously increase and destabilise plant biomass production, with co-limitation by multiple nutrients potentially intensifying these effects. Here, we test how factorial additions of nitrogen (N), phosphorus (P) and potassium with essential nutrients (K+) affect the stability (mean/standard deviation) of aboveground biomass in 34 grasslands over 7 years. Destabilisation with fertilisation was prevalent but was driven by single nutrients, not synergistic nutrient interactions. On average, N-based treatments increased mean biomass production by 21–51% but increased its standard deviation by 40–68% and so consistently reduced stability. Adding P increased interannual variability and reduced stability without altering mean biomass, while K+ had no general effects. Declines in stability were largest in the most nutrient-limited grasslands, or where nutrients reduced species richness or intensified species synchrony. We show that nutrients can differentially impact the stability of biomass production, with N and P in particular disproportionately increasing its interannual variability.
Repeated sampling of spatially distributed river chemistry can be used to assess the location, scale, and persistence of carbon and nutrient contributions to watershed exports. Here, we provide a comprehensive set of water chemistry measurements and ecohydrological metrics describing the biogeochemical conditions of permafrost-affected Arctic watersheds. These data were collected in watershed-wide synoptic campaigns in six stream networks across northern Alaska. Three watersheds are associated with the Arctic Long-Term Ecological Research site at Toolik Field Station (TFS), which were sampled seasonally each June and August from 2016 to 2018. Three watersheds were associated with the National Park Service (NPS) of Alaska and the U.S. Geological Survey (USGS) and were sampled annually from 2015 to 2019. Extensive water chemistry characterization included carbon species, dissolved nutrients, and major ions. The objective of the sampling designs and data acquisition was to characterize terrestrial–aquatic linkages and processing of material in stream networks. The data allow estimation of novel ecohydrological metrics that describe the dominant location, scale, and overall persistence of ecosystem processes in continuous permafrost. These metrics are (1) subcatchment leverage, (2) variance collapse, and (3) spatial persistence. Raw data are available at the National Park Service Integrated Resource Management Applications portal (O'Donnell et al., 2021, https://doi.org/10.5066/P9SBK2DZ) and within the Environmental Data Initiative (Abbott, 2021, https://doi.org/10.6073/pasta/258a44fb9055163dd4dd4371b9dce945).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-14-95-2022","usgsCitation":"Shogren, A., Zarnetske, J.P., Abbott, B., Bratsman, S.P., Brown, B.C., Carey, M.P., Fulweiber, R., Greaves, H., Haines, E., Iannucci, F., Koch, J.C., Medvedeff, A., O’Donnell, J.A., Patch, L., Poulin, B., Williamson, T.J., and Bowden, W.B., 2022, Multi-year, spatially extensive, watershed-scale synoptic stream chemistry and water quality conditions for six permafrost-underlain Arctic watersheds: Earth System Science Data, v. 14, p. 95-116, https://doi.org/10.5194/essd-14-95-2022.","productDescription":"22 p.","startPage":"95","endPage":"116","ipdsId":"IP-127222","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":491327,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SBK2DZ","text":"USGS data release","linkHelpText":"Stream and River Chemistry in Watersheds of Northwestern Alaska, 2015-2019"},{"id":449165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-14-95-2022","text":"Publisher Index Page"},{"id":408641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150,\n 69\n ],\n [\n -150,\n 68\n ],\n [\n -148.75,\n 68\n ],\n [\n -148.75,\n 69\n ],\n [\n -150,\n 69\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163,\n 66.75\n ],\n [\n -157,\n 66.75\n ],\n [\n -157,\n 68\n ],\n [\n -163,\n 68\n ],\n [\n -163,\n 66.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2022-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Shogren, Arial","contributorId":298443,"corporation":false,"usgs":false,"family":"Shogren","given":"Arial","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":855623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarnetske, Jay P.","contributorId":210073,"corporation":false,"usgs":false,"family":"Zarnetske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":855624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abbott, Benjamin 0000-0001-5861-3481","orcid":"https://orcid.org/0000-0001-5861-3481","contributorId":215170,"corporation":false,"usgs":false,"family":"Abbott","given":"Benjamin","email":"","affiliations":[{"id":39191,"text":"Bringham Young Unviersity","active":true,"usgs":false}],"preferred":false,"id":855625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bratsman, Samuel P.","contributorId":247668,"corporation":false,"usgs":false,"family":"Bratsman","given":"Samuel","email":"","middleInitial":"P.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":855626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Brian C.","contributorId":257319,"corporation":false,"usgs":false,"family":"Brown","given":"Brian","email":"","middleInitial":"C.","affiliations":[{"id":48387,"text":"BYU","active":true,"usgs":false}],"preferred":false,"id":855627,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":855628,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fulweiber, Randy","contributorId":298445,"corporation":false,"usgs":false,"family":"Fulweiber","given":"Randy","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855629,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Greaves, Heather","contributorId":298447,"corporation":false,"usgs":false,"family":"Greaves","given":"Heather","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855630,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Haines, Emma","contributorId":298448,"corporation":false,"usgs":false,"family":"Haines","given":"Emma","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":855631,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Iannucci, Frances","contributorId":298450,"corporation":false,"usgs":false,"family":"Iannucci","given":"Frances","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":855632,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":855633,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Medvedeff, Alex","contributorId":298453,"corporation":false,"usgs":false,"family":"Medvedeff","given":"Alex","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":855634,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":855635,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Patch, Leika","contributorId":298455,"corporation":false,"usgs":false,"family":"Patch","given":"Leika","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":855636,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Poulin, Brett 0000-0002-5555-7733","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":260893,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett","affiliations":[{"id":52706,"text":"Department of Environmental Toxicology, University of California Davis, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":855637,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Williamson, Tanner J.","contributorId":223165,"corporation":false,"usgs":false,"family":"Williamson","given":"Tanner","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":855638,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Bowden, William B.","contributorId":169388,"corporation":false,"usgs":false,"family":"Bowden","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":855639,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70227459,"text":"70227459 - 2022 - Response to comment on “Evidence of humans in North America during the Last Glacial Maximum”","interactions":[],"lastModifiedDate":"2022-01-18T13:25:51.653562","indexId":"70227459","displayToPublicDate":"2022-01-14T07:24:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Response to comment on “Evidence of humans in North America during the Last Glacial Maximum”","docAbstract":"Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle (Glyptemys insculpta) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λmean = 0.952, 95% CI: 0.87–1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.
Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.
Dry conditions during 2020 and 2021 affected the water supply within the Souris River Basin and highlighted the need for better understanding of the streamflow dynamics for managing the resource during low-flow conditions. In June 2021, a loss of streamflow was observed on the Souris River between U.S. Geological Survey streamgages on the Souris River near Foxholm, North Dakota (site 1), and near Verendrye, N. Dak. (site 22). The largest loss was upstream from the Souris River above Minot, N. Dak. (site 7). On June 6, 2021, the daily mean streamflow decreased from 33.8 cubic feet per second at site 1 to 16.3 cubic feet per second at site 7, a loss of 17.5 cubic feet per second. To better understand where streamflow losses occurred in the reach from site 1 to site 22, multiple sites were selected for streamflow measurements between the three streamgages (sites 1, 7, and 22). Streamflow measurements made at 22 selected sites on the Souris River on August 31 and September 1, 2021, did not indicate the loss in streamflow that was observed at the three streamgages (sites 1, 7, and 22) in June 2021. Measurements made at the three streamgages (sites 1, 7, and 22) on August 31 had streamflows of 44.2, 45.9, and 46.8 cubic feet per second, respectively. Streamflow measured at all 22 sites on August 31 and September 1 on the Souris River ranged from 38.4 (site 9) to 49.8 cubic feet per second (site 12). In general, the largest change in streamflow was measured among sites on the Souris River in or near the city of Minot, N. Dak.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221005","collaboration":"Prepared in cooperation with the North Dakota Department of Water Resources, the U.S. Fish and Wildlife Service, and the U.S. Army Corps of Engineers, St. Paul District","usgsCitation":"Galloway, J.M., and Hanson, B.R., 2022, Measurements of streamflow gain and loss on the Souris River between Lake Darling and Verendrye, North Dakota, August 31 and September 1, 2021: U.S. Geological Survey Open-File Report 2022–1005, 10 p., https://doi.org/10.3133/ofr20221005.","productDescription":"Report: vi, 10 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-135605","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":394315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1005/coverthb.jpg"},{"id":394317,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":394316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1005/ofr20221005.pdf","text":"Report","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1005"},{"id":501538,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112123.htm","linkFileType":{"id":5,"text":"html"}},{"id":394329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1005/images","description":"OFR 2022–1005 images"},{"id":394328,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1005/ofr20221005.XML","description":"OFR 2022–1005 XML"}],"country":"United States","state":"North Dakota","otherGeospatial":"Souris River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.6667,\n 48\n ],\n [\n -100.5,\n 48\n ],\n [\n -100.5,\n 48.50\n ],\n [\n -101.6667,\n 48.50\n ],\n [\n -101.6667,\n 48\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
We present a new field measurement and numerical interpretation method (combined termed ‘test’) to parameterize the diffusion of trichloroethene (TCE) and its biodegradation products (DPs) from the matrix of sedimentary rock. The method uses a dual-packer system to interrogate a low-permeability section of the rock matrix adjacent to a previously contaminated borehole and uses the borehole monitoring history to establish the pre-test condition. TCE and its DPs are removed from the groundwater between the packers at the onset of the testing. The parameters estimated by fitting a radial diffusion model to the concentration history and borehole concentration data, also termed back-diffusion, are the tortuosity factor and sorption coefficients of TCE and DPs in the rock matrix and the TCE and DP biodegradation rate coefficients in the borehole. We demonstrate the equipment design and the interpretive method using a borehole accessing the grey mudstone at a TCE contaminated site in the Newark Basin. In this test, both nonreactive (bromide) and reactive (trichlorofluoroethene) tracers are used to constrain the estimated parameters; however, the bromide tracer was not needed to estimate the parameters in this test. The parameters estimated from the field test are consistent with values measured independently in laboratory experiments using field samples of similar lithology. From the interpretation, we compute the TCE and DP concentration distributions in the rock matrix prior to the test to illustrate how the results can be used to enhance understanding of contaminant distribution in the rock matrix.
","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwmr.12495","usgsCitation":"Allen-King, R.M., Kiekhaefer, R.L., Goode, D.J., Hsieh, P.A., Lorah, M.M., and Imbrigiotta, T.E., 2022, A borehole test for chlorinated solvent diffusion and degradation rates in sedimentary rock: Groundwater Monitoring and Remediation, v. 42, no. 2, p. 23-34, https://doi.org/10.1111/gwmr.12495.","productDescription":"12 p.","startPage":"23","endPage":"34","ipdsId":"IP-122580","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":394652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394804,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99I50JE","text":"USGS data release","linkHelpText":"A finite-difference algorithm used to simulate radial diffusion, adsorption, and reactions of chlorinated ethenes in porous media"}],"volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen-King, Richelle M. 0000-0001-5559-1213","orcid":"https://orcid.org/0000-0001-5559-1213","contributorId":272047,"corporation":false,"usgs":false,"family":"Allen-King","given":"Richelle","email":"","middleInitial":"M.","affiliations":[{"id":56340,"text":"University at Buffalo, SUNY","active":true,"usgs":false}],"preferred":false,"id":831399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiekhaefer, Rebecca L.","contributorId":272048,"corporation":false,"usgs":false,"family":"Kiekhaefer","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":56340,"text":"University at Buffalo, SUNY","active":true,"usgs":false}],"preferred":false,"id":831400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goode, Daniel J. 0000-0002-8527-2456","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":216750,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":831402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831404,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227657,"text":"70227657 - 2022 - Paleoclimatology and paleoceanography perspectives on integrated, coordinated, open, networked (ICON) science","interactions":[],"lastModifiedDate":"2022-01-25T13:20:16.177398","indexId":"70227657","displayToPublicDate":"2022-01-13T07:14:14","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":"Paleoclimatology and paleoceanography perspectives on integrated, coordinated, open, networked (ICON) science","docAbstract":"This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman et al., 2021, https://doi.org/10.1002/essoar.10508554.1) in the AGU section paleoclimatology and paleoceanography (P&P), and a discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, technology transfer and application, reproducibility, and data sharing and infrastructure; (Section 3) Local knowledge, global gain: improving interactions within the scientific community and with locals, indigenous communities, stakeholders, and the public; (Section 4) Field, experimental, remote sensing, and real-time data research and application. P&P projects can better include ICON principles by directly incorporating them into research proposals. A promising way to overcome the challenges of interdisciplinarity and integration is to foster networking, which will advance our research discipline through the application of ICON.
Faults on microcontinents record the dynamic evolution of plate boundaries. However, most microcontinents are submarine and difficult to study. Here, we show that the southern part of the Isla Ángel de la Guarda (IAG) microcontinent, in the northern Gulf of California rift, is densely faulted by a late Quaternary-active normal fault zone. To characterize the onshore kinematics of this Almeja fault zone, we integrated remote fault mapping using high-resolution satellite- and drone-based topography with neotectonic field-mapping. We produced 13 luminescence ages from sediment deposits offset or impounded by faults to constrain the timing of fault offsets. We found that north-striking normal faults in the Almeja fault zone continue offshore to the south and likely into the nascent North Salsipuedes basin southwest of IAG. Late Pleistocene and Holocene luminescence ages indicate that the most recent onshore fault activity occurred in the last ∼50 kyr. These observations suggest that the North Salsipuedes basin is kinematically linked with and continues onshore as the active Almeja fault zone. We suggest that fragmentation of the evolving IAG microcontinent may not yet be complete and that the Pacific-North America plate boundary is either not fully localized onto the Ballenas transform fault and Lower Delfin pull-apart basin or is in the initial stage of a plate boundary reorganization.
Individual variation in behavior, particularly consistent among-individual differences (i.e., personality), has important ecological and evolutionary implications for population and community dynamics, trait divergence, and patterns of speciation. Nevertheless, individual variation in spatial behaviors, such as home range behavior, movement characteristics, or habitat use has yet to be incorporated into the concepts or methodologies of ecology and evolutionary biology. To evaluate evidence for the existence of consistent among-individual differences in spatial behavior – which we refer to as “spatial personality” – we performed a meta-analysis of 200 repeatability estimates of home range size, movement metrics, and habitat use. We found that the existence of spatial personality is a general phenomenon, with consistently high repeatability (r) across classes of spatial behavior (r = 0.67–0.82), taxa (r = 0.31–0.79), and time between repeated measurements (r = 0.54–0.74). These results suggest: 1) repeatable spatial behavior may either be a cause or consequence of the environment experienced and lead to spatial personalities that may limit the ability of individuals to behaviorally adapt to changing landscapes; 2) interactions between spatial phenotypes and environmental conditions could result in differential reproduction, survival, and dispersal, suggesting that among-individual variation may facilitate population-level adaptation; 3) spatial patterns of species' distributions and spatial population dynamics may be better understood by shifting from a mean field analytical approach towards methods that account for spatial personalities and their associated fitness and ecological dynamics.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/beheco/arab147","usgsCitation":"Stuber, E.F., Carlson, B., and Jesmer, B., 2022, Spatial personalities: A meta-analysis of consistent individual differences in spatial behavior: Behavioral Ecology, v. 33, no. 3, p. 477-486, https://doi.org/10.1093/beheco/arab147.","productDescription":"10 p.","startPage":"477","endPage":"486","ipdsId":"IP-130986","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arab147","text":"Publisher Index Page"},{"id":429855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":902619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Ben","contributorId":337694,"corporation":false,"usgs":false,"family":"Carlson","given":"Ben","affiliations":[{"id":61502,"text":"yu","active":true,"usgs":false}],"preferred":false,"id":902620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett","contributorId":337695,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","affiliations":[{"id":61502,"text":"yu","active":true,"usgs":false}],"preferred":false,"id":902621,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266212,"text":"70266212 - 2022 - Non-target effects of herbicides on the Zerene silverspot butterfly, a surrogate subspecies for the threatened Oregon silverspot butterfly","interactions":[],"lastModifiedDate":"2025-05-01T13:25:50.118613","indexId":"70266212","displayToPublicDate":"2022-01-13T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2356,"text":"Journal of Insect Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Non-target effects of herbicides on the Zerene silverspot butterfly, a surrogate subspecies for the threatened Oregon silverspot butterfly","docAbstract":"Herbicides are used as management tools to improve habitat for native plants and animals, but their application may also have harmful effects on the native community. The federally threatened Oregon silverspot butterfly (Speyeria = Argynnis zerene hippolyta) resides in remnant native grasslands along the Pacific Northwest coast. However, like many grasslands, many of these areas have high incidences of invasive plants, such as false dandelion (Hypochaeris radicata) and velvet grass (Holcus lanatus). These and other invasive plants severely limit the abundance of the Oregon silverspot’s larval host plant, the early blue violet (Viola adunca). Selective herbicides, such as clopyralid and fluazifop-P-butyl, can reduce invasive plant abundance. However, non-target effects of these herbicides, and of adjuvants applied with these herbicides, on Oregon silverspots are unknown. In our study, we applied herbicides and adjuvants to host plants and Zerene silverspot (S. z. zerene) larvae, a subspecies closely related to Oregon silverspots. Responses in silverspot larvae measured in two experiments included survival, sex ratio, development time, mass, morphology, fecundity, and behavior. Our results suggest that negative effects of herbicides, clopyralid and fluazifop-P-butyl, and adjuvants, Agri-Dex® and Nu-Film®-IR, are limited. However, we detected weak effects from clopyralid and fluazifop-P-butyl with and without Agri-Dex® on larval and pupal development time and pupal mass.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10841-021-00355-2","usgsCitation":"Doll, C., Converse, S.J., and Schultz, C., 2022, Non-target effects of herbicides on the Zerene silverspot butterfly, a surrogate subspecies for the threatened Oregon silverspot butterfly: Journal of Insect Conservation, v. 26, p. 1-15, https://doi.org/10.1007/s10841-021-00355-2.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-129351","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Doll, Cassandra F.","contributorId":354012,"corporation":false,"usgs":false,"family":"Doll","given":"Cassandra F.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":934950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":934949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Cheryl B.","contributorId":354013,"corporation":false,"usgs":false,"family":"Schultz","given":"Cheryl B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":934951,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227867,"text":"70227867 - 2022 - Quantifying regional effects of best management practices on nutrient losses from agricultural lands","interactions":[],"lastModifiedDate":"2022-02-01T18:12:27.328917","indexId":"70227867","displayToPublicDate":"2022-01-12T13:12:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying regional effects of best management practices on nutrient losses from agricultural lands","docAbstract":"Nitrogen (N) and phosphorus (P) losses from agricultural areas have degraded the water quality of downstream rivers, lakes, and oceans. As a result, investment in the adoption of agricultural best management practices (BMPs) has grown, but assessments of their effectiveness at large spatial scales have lagged. This study applies regional Spatially Referenced Regression On Watershed-attributes (SPARROW) models developed for the Midwest, Northeast, and Southeast United States to quantify potential regional effects of BMPs on nutrient losses from agricultural lands. These models were used because they account for specific BMPs in the prediction of instream nutrient loads. The BMPs included in the models were cover crops, no-till, and conservation tillage. Sensitivity testing for the BMPs on agricultural nutrient loads was done using simulations that varied the intensity of BMPs specified in each region. When the BMP intensity was increased 50% relative to the 2012 intensity, the predicted agricultural load of total P decreased across all regions (4% to 14%). The predicted reduction in average P yields in the Midwest, Northeast, and Southeast was 706, 544, and 26 kg km–2, respectively. Increasing BMPs by 50% decreased predicted agricultural total N loads by 3.5% in the Southeast but increased predicted N loads in the Midwest and Northeast by 4.7% and 1.8%, respectively. Model-predicted average N yields increased by 402 kg km–2 and 302 kg km–2 in the Midwest and Northeast, respectively, and decreased in the Southeast by 329 kg km–2. In model simulations, cover crops were more effective at reducing N and P loads than the tillage BMPs despite lower intensity of implementation in 2012. However, at the regional scale of this investigation, implementation of BMPs result in only moderate predicted effects on agricultural nutrient loads
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.2022.00162","usgsCitation":"Roland, V.L., Garcia, A.M., Saad, D.A., Ator, S., Robertson, D., and Schwarz, G.E., 2022, Quantifying regional effects of best management practices on nutrient losses from agricultural lands: Journal of Soil and Water Conservation, v. 77, no. 1, p. 15-29, https://doi.org/10.2489/jswc.2022.00162.","productDescription":"15 p.","startPage":"15","endPage":"29","ipdsId":"IP-119875","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":449184,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2489/jswc.2022.00162","text":"Publisher Index Page"},{"id":435998,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H2NDWU","text":"USGS data release","linkHelpText":"Nutrient Load Data used to Quantify Regional Effects of Agricultural Best Management Practices: An application of the 2012 SPARROW models for the Midwest, Northeast, and Southeast United States"},{"id":395226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Victor L. II 0000-0002-6260-9351 vroland@usgs.gov","orcid":"https://orcid.org/0000-0002-6260-9351","contributorId":212248,"corporation":false,"usgs":true,"family":"Roland","given":"Victor","suffix":"II","email":"vroland@usgs.gov","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saad, David A. 0000-0001-6559-6181 dasaad@usgs.gov","orcid":"https://orcid.org/0000-0001-6559-6181","contributorId":204667,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ator, Scott W. 0000-0002-9186-4837","orcid":"https://orcid.org/0000-0002-9186-4837","contributorId":220504,"corporation":false,"usgs":true,"family":"Ator","given":"Scott W.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832445,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229185,"text":"70229185 - 2022 - The impact of future climate on wetland habitat in a critical migratory waterfowl corridor of the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2022-03-03T15:34:56.28404","indexId":"70229185","displayToPublicDate":"2022-01-12T09:27:17","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"The impact of future climate on wetland habitat in a critical migratory waterfowl corridor of the Prairie Pothole Region","docAbstract":"Depressional wetlands are extremely sensitive to changes in temperature and precipitation, so understanding how wetland inundation dynamics respond to changes in climate is essential for describing potential effects on wildlife breeding habitat. Millions of depressional basins make up the largest wetland complex in North America known as the Prairie Pothole Region (PPR). The wetland ecosystems that have formed in these basins provide important migratory-bird breeding habitat. The southeast portion of the U.S. PPR in Minnesota and Iowa has faced some of the greatest challenges in wetland conservation. Many existing prairie-pothole wetlands are small (<1 ha) and shallow (<2 m) and are typically not inundated with surface water year-round. Our goal with this project is to increase the efficacy of mapping tools used by management agencies to predict future changes in water levels in the PPR. We accomplish this goal by improving the link between existing data (about wetland water characteristics) and existing tools (mapping products). Our results successfully validated (2009-2021) the current mapping tool (a wetland hydrology model) used by the U.S. Fish and Wildlife Service (USFWS) to manage 22 wetlands in Minnesota. We were able to hindcast wetland water levels to 1984 and assess the accuracy of a satellite-derived surface water product and forecast water levels through 2099 using a suite of modeled climate data. This newly refined link between monitoring data and remote sensing tools will increase understanding and prediction for other wetlands beyond our study sites and through the Minnesota and Iowa portions of the PPR. Through conference presentations, publications, and development of an interactive climate change dashboard we are now working with managers to determine how we can help incorporate these predicted changes to waterfowl breeding habitat into their future management, acquisition, and restoration strategy.
Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using grey wolves (Canis lupus). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs and trade-offs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk and seasonality. It accomplished this using simple behavioural rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behaviour.
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\"}}]}","volume":"289","issue":"1966","noUsgsAuthors":false,"publicationDate":"2022-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sells, Sarah N.","contributorId":171706,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":902988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S.","contributorId":338172,"corporation":false,"usgs":false,"family":"Mitchell","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luis, Angela D.","contributorId":33199,"corporation":false,"usgs":true,"family":"Luis","given":"Angela","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":902989,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Emlen, Douglas J.","contributorId":338162,"corporation":false,"usgs":false,"family":"Emlen","given":"Douglas","email":"","middleInitial":"J.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":902990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Podruzny, Kevin M.","contributorId":85865,"corporation":false,"usgs":true,"family":"Podruzny","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":902992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230367,"text":"70230367 - 2022 - Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy","interactions":[],"lastModifiedDate":"2022-04-11T14:00:54.827276","indexId":"70230367","displayToPublicDate":"2022-01-12T08:52:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy","docAbstract":"This work investigates bituminite (amorphous sedimentary organic matter) in Upper Jurassic Kimmeridge Clay source rock via confocal laser scanning microscopy (CLSM) and atomic force microscopy (AFM). These petrographic tools were used to provide better understanding of the nature of bituminite, which has been historically difficult to identify and differentiate from similar organic matter types in source rocks. As part of an International Committee for Coal and Organic Petrology (ICCP) working group, an immature (0.42% vitrinite reflectance), organic-rich (44.1 wt% total organic carbon content) sample of Kimmeridge Clay was distributed to multiple laboratories for CLSM characterization. The primary observations from CLSM imaging and spectroscopy include: 1) the interpreted presence of Botryococcus algae as a contributor to bituminite precursors; 2) color red-shift of sulfide reflectance and bituminite auto-fluorescence from below the sample surface; 3) positive alteration of bituminite from laser-induced photo-oxidation of the sample surface, including fluorescence blue-shift; 4) fluorescence blue-shift associated to higher fluorescence intensity regions in bituminite indicative of compositional (fluorophore) differences; 5) the need for fluorescence spectroscopy standardization as applied via CLSM; and 6) the suitability of CLSM fluorescence spectroscopy to predict solid bitumen reflectance from bituminite spectral emission via calibration to an extant dataset. Secondary CLSM observations include detection of reflected laser light from highly reflective inclusions in bituminite, including sulfides and fusinite, and radiolytic alteration of bituminite caused by substitution of U for Fe in sulfides. Findings from AFM include the observation that surface roughening or surface flattening of bituminite are induced by differential broad ion beam (BIB) milling and are dependent on the location and scale of AFM topology measurement. This result highlights our still limited understanding of the effects of BIB milling on sedimentary organic matter and indicates the need for further research before this technique can be advanced as a standard practice in petrographic sample preparation. Collectively, the results of this study illustrate the general applicability and versatility of AFM and CLSM as tools for organic petrology research, specifically for better understanding of the nature and properties of the bituminite maceral.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.103927","usgsCitation":"Hackley, P.C., Kus, J., Mendonca Filho, J.G., Czaja, A.D., Borrego, A., Životić, D., Valentine, B.J., and Hatcherian, J.J., 2022, Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy: International Journal of Coal Geology, v. 251, 103927, 17 p., https://doi.org/10.1016/j.coal.2022.103927.","productDescription":"103927, 17 p.","ipdsId":"IP-133126","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":449187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2022.103927","text":"Publisher Index Page"},{"id":398465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"England","city":"Kimmeridge","otherGeospatial":"Upper Jurassic Kimmeridge Clay Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -2.1928024291992188,\n 50.58607046502884\n ],\n [\n -2.0602798461914062,\n 50.58607046502884\n ],\n [\n -2.0602798461914062,\n 50.629428887865565\n ],\n [\n -2.1928024291992188,\n 50.629428887865565\n ],\n [\n -2.1928024291992188,\n 50.58607046502884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"251","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":840090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Jolanta","contributorId":289942,"corporation":false,"usgs":false,"family":"Kus","given":"Jolanta","affiliations":[{"id":62291,"text":"BGR.de","active":true,"usgs":false}],"preferred":false,"id":840091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mendonca Filho, Joao Graciano","contributorId":289943,"corporation":false,"usgs":false,"family":"Mendonca Filho","given":"Joao","email":"","middleInitial":"Graciano","affiliations":[{"id":62294,"text":"UFRJ","active":true,"usgs":false}],"preferred":false,"id":840092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Czaja, Andrew D.","contributorId":289944,"corporation":false,"usgs":false,"family":"Czaja","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":62295,"text":"Univ. Cincinnati,","active":true,"usgs":false}],"preferred":false,"id":840093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borrego, Angeles G.","contributorId":289945,"corporation":false,"usgs":false,"family":"Borrego","given":"Angeles G.","affiliations":[{"id":27409,"text":"Incar","active":true,"usgs":false}],"preferred":false,"id":840094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Životić, Dragana","contributorId":289946,"corporation":false,"usgs":false,"family":"Životić","given":"Dragana","affiliations":[{"id":62296,"text":"Univ. Belgrade","active":true,"usgs":false}],"preferred":false,"id":840095,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":840096,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":840097,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252840,"text":"70252840 - 2022 - Assessment of native fish passage through Brandon Road Lock and Dam, Des Plaines River, Illinois, using fin ray microchemistry","interactions":[],"lastModifiedDate":"2024-04-09T12:25:01.204236","indexId":"70252840","displayToPublicDate":"2022-01-12T07:22:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of native fish passage through Brandon Road Lock and Dam, Des Plaines River, Illinois, using fin ray microchemistry","docAbstract":"This study examined evidence of native fish passage through Brandon Road Lock and Dam (BRLD) on the Des Plaines River, Illinois, in light of proposed modifications to prevent the upstream passage of invasive carps. Direct evidence of upstream passage by native fishes at BRLD is lacking and could help to inform assessment of the impacts of barrier technology installation. Fin ray microchemistry was used to assess upstream BRLD passage in the native taxa Centrarchidae, Catostomidae, Ictaluridae, and Lepisosteidae. The fin ray edge strontium : calcium ratio (Sr:Ca) of fish sampled from the Des Plaines River upstream of BRLD and in rivers downstream of BRLD was used to characterize ranges of river-specific fin ray Sr:Ca for each taxon. These were applied to Sr:Ca data along a transect from fin ray core to edge to infer the environmental history of individual fish that were captured upstream from BRLD and to estimate the proportion of fish that had passed upstream through BRLD. Depending on the taxon, 6–37% of individuals sampled upstream from BRLD exhibited fin ray Sr:Ca indicating prior residency in rivers downstream of BRLD and therefore upstream passage through BRLD. Upstream passage was indeterminate for 19–91% of individuals in each taxon due to uncertainty in environmental history inferred from fin ray Sr:Ca. These results provide the first definitive evidence of upstream native fish passage at BRLD and suggest that the installation of barrier technology could have an impact on native fish.
Tidal marsh survival in the face of sea level rise (SLR) and declining sediment supply often depends on the ability of marshes to build soil vertically. However, numerical models typically predict survival under rates of SLR that far exceed field-based measurements of vertical accretion. Here, we combine novel measurements from seven U.S. Atlantic Coast marshes and data from 70 additional marshes from around the world to illustrate that—over continental scales—70% of variability in marsh accretion rates can be explained by suspended sediment concentratin (SSC) and spring tidal range (TR). Apparent discrepancies between models and measurements can be explained by differing responses in high marshes and low marshes, the latter of which accretes faster for a given SSC and TR. Together these results help bridge the gap between models and measurements, and reinforce the paradigm that sediment supply is the key determinant of wetland vulnerability at continental scales.
No abstract available.
","language":"English","publisher":"The Groundwater Project","usgsCitation":"Nordstrom, D.K., and Smedley, P.L., 2022, Fluoride in groundwater, 130 p.","productDescription":"130 p.","ipdsId":"IP-131380","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":398392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392719,"type":{"id":15,"text":"Index Page"},"url":"https://gw-project.org/books/fluoride-in-groundwater/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":828182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smedley, Pauline L 0000-0001-6327-308X","orcid":"https://orcid.org/0000-0001-6327-308X","contributorId":269961,"corporation":false,"usgs":false,"family":"Smedley","given":"Pauline","email":"","middleInitial":"L","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":828183,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255092,"text":"70255092 - 2022 - Genetic diversity and mate selection in a reintroduced population of gray wolves","interactions":[],"lastModifiedDate":"2024-06-12T15:50:25.589669","indexId":"70255092","displayToPublicDate":"2022-01-11T10:48:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity and mate selection in a reintroduced population of gray wolves","docAbstract":"The genetic composition of an individual can markedly affect its survival, reproduction, and ultimately fitness. As some wildlife populations become smaller, conserving genetic diversity will be a conservation challenge. Many imperiled species are already supported through population augmentation efforts and we often do not know if or how genetic diversity is maintained in translocated species. As a case study for understanding the maintenance of genetic diversity in augmented populations, I wanted to know if genetic diversity (i.e., observed heterozygosity) remained high in a population of gray wolves in the Rocky Mountains of the U.S. > 20 years after reintroduction. Additionally, I wanted to know if a potential mechanism for such diversity was individuals with below average genetic diversity choosing mates with above average diversity. I also asked whether there was a preference for mating with unrelated individuals. Finally, I hypothesized that mated pairs with above average heterozygosity would have increased survival of young. Ultimately, I found that females with below average heterozygosity did not choose mates with above average heterozygosity and wolves chose mates randomly with respect to genetic relatedness. Pup survival was not higher for mated pairs with above average heterozygosity in my models. The dominant variables predicting pup survival were harvest rate during their first year of life and years pairs were mated. Ultimately, genetic diversity was relatively unchanged > 20 years after reintroduction. The mechanism for maintaining such diversity does not appear related to individuals preferentially choosing more genetically diverse mates. Inbreeding avoidance, however, appears to be at least one mechanism maintaining genetic diversity in this population.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-04449-4","usgsCitation":"Ausband, D.E., 2022, Genetic diversity and mate selection in a reintroduced population of gray wolves: Scientific Reports, v. 12, 535, 7 p., https://doi.org/10.1038/s41598-021-04449-4.","productDescription":"535, 7 p.","ipdsId":"IP-130898","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449194,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-04449-4","text":"Publisher Index Page"},{"id":430019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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