{"pageNumber":"328","pageRowStart":"8175","pageSize":"25","recordCount":165270,"records":[{"id":70237558,"text":"70237558 - 2022 - Multispecies approaches to status assessments in support of endangered species classifications","interactions":[],"lastModifiedDate":"2022-11-16T17:13:33.687452","indexId":"70237558","displayToPublicDate":"2022-10-05T11:53:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Multispecies approaches to status assessments in support of endangered species classifications","docAbstract":"

Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12825","usgsCitation":"Fitzgerald, D.B., Freeman, M., Maloney, K.O., Young, J.A., Rosenberger, A.E., Kazyak, D., and Smith, D.R., 2022, Multispecies approaches to status assessments in support of endangered species classifications: Conservation Science and Practice, v. 4, no. 11, e12825, 11 p., https://doi.org/10.1111/csp2.12825.","productDescription":"e12825, 11 p.","ipdsId":"IP-127956","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12825","text":"Publisher Index Page"},{"id":408261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Daniel Bruce 0000-0002-3254-7428","orcid":"https://orcid.org/0000-0002-3254-7428","contributorId":245718,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Daniel","email":"","middleInitial":"Bruce","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263564,"text":"70263564 - 2022 - Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults","interactions":[],"lastModifiedDate":"2025-02-13T17:17:51.912547","indexId":"70263564","displayToPublicDate":"2022-10-05T11:16:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults","docAbstract":"

Widespread surface creep is observed across a number of active faults included in the United States (US) National Seismic Hazard Model (NSHM). In northern California, creep occurs on the central section of the San Andreas fault, along the Hayward and Calaveras faults through the San Francisco Bay Area, and to the north coast region along the Maacama and Bartlett Springs faults. In southern California, creep is observed across the Coachella segment of the San Andreas fault, through the Brawley Seismic Zone, and along the Imperial and Superstition Hills faults. Seismic hazard assessments for California have accounted for creep using various data and methods, including the most recent Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) in 2013. The purpose of this study is to expand and update the UCERF3 creep rate data set for the 2023 release of the US NSHM and to invert geodetic data and the surface creep rate data for the spatial distribution of interseismic fault creep on California faults using an elastic model with physical creep constraints. The updated surface creep rate compilation consists of a variety of data types including alignment arrays, offset cultural markers, creepmeters, Interferometric Synthetic Aperture Radar, and Global Positioning System data. We compile a total of 497 surface creep rate measurements, 400 of which are new and 97 of which appear in the UCERF3 compilation. We compute creep rate distributions for each of the five 2023 NSHM geodetic‐based and geologic‐based deformation models. Computed creep rates are used to reduce the total fault moment rate available for earthquake sequences in the NSHM model. We find that, despite relatively large variability in model long‐term slip rates across all five deformation models, the variability in depth‐averaged creep rate across all models is relatively small, typically 5–10 mm/yr along the creeping San Andreas fault section and only 2–4 mm/yr along the Maacama and Rodgers Creek‐Hayward faults.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/ 0220220186","usgsCitation":"Johnson, K., Murray, J.R., and Wespestad, C., 2022, Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults: Seismological Research Letters, v. 93, no. 6, p. 3151-3169, https://doi.org/10.1785/ 0220220186.","productDescription":"19 p.","startPage":"3151","endPage":"3169","ipdsId":"IP-142160","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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M.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":927345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wespestad, Crystal","contributorId":296055,"corporation":false,"usgs":false,"family":"Wespestad","given":"Crystal","email":"","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":927347,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256624,"text":"70256624 - 2022 - Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex","interactions":[],"lastModifiedDate":"2024-08-27T15:29:22.998417","indexId":"70256624","displayToPublicDate":"2022-10-05T10:24:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex","docAbstract":"

The Neosho Bass (Micropterus velox), a former subspecies of the keystone top-predator and globally popular Smallmouth Bass (M. dolomieu), is endemic and narrowly restricted to small, clear streams of the Arkansas River Basin in the Central Interior Highlands (CIH) ecoregion, USA. Previous studies have detected some morphological, genetic, and genomic differentiation between the Neosho and Smallmouth Basses; however, the extent of neutral and adaptive divergence and patterns of intraspecific diversity are poorly understood. Furthermore, lineage diversification has likely been impacted by gene flow in some Neosho populations, which may be due to a combination of natural biogeographic processes and anthropogenic introductions. We assessed: (1) lineage divergence, (2) local directional selection (adaptive divergence), and (3) demographic history among Smallmouth Bass populations in the CIH using population genomic analyses of 50,828 single-nucleotide polymorphisms (SNPs) obtained through ddRAD-seq. Neosho and Smallmouth Bass formed monophyletic clades with 100% bootstrap support. We identified two major lineages within each species. We discovered six Neosho Bass populations (two nonadmixed and four admixed) and three nonadmixed Smallmouth Bass populations. We detected 29 SNPs putatively under directional selection in the Neosho range, suggesting populations may be locally adapted. Two populations were admixed via recent asymmetric secondary contact, perhaps after anthropogenic introduction. Two other populations were likely admixed via combinations of ancient and recent processes. These species comprise independently evolving lineages, some having experienced historical and natural admixture. These results may be critical for management of Neosho Bass as a distinct species and may aid in the conservation of other species with complex biogeographic histories.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9370","usgsCitation":"Gunn, J., Berkman, L., Kopplelman, J., Taylor, A., Brewer, S.K., Long, J.M., and Eggert, L., 2022, Genomic divergence, local adaptation, and complex demographic history may inform management of a popular sportfish species complex: Ecology and Evolution, v. 12, no. 10, e9370, 19 p., https://doi.org/10.1002/ece3.9370.","productDescription":"e9370, 19 p.","ipdsId":"IP-131849","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446220,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9370","text":"Publisher Index Page"},{"id":433201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Gunn, J.C.","contributorId":341410,"corporation":false,"usgs":false,"family":"Gunn","given":"J.C.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkman, L.K.","contributorId":341411,"corporation":false,"usgs":false,"family":"Berkman","given":"L.K.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kopplelman, J.","contributorId":341412,"corporation":false,"usgs":false,"family":"Kopplelman","given":"J.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, A.T.","contributorId":286995,"corporation":false,"usgs":false,"family":"Taylor","given":"A.T.","email":"","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":908369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eggert, L.S.","contributorId":341413,"corporation":false,"usgs":false,"family":"Eggert","given":"L.S.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908372,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256651,"text":"70256651 - 2022 - Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes","interactions":[],"lastModifiedDate":"2024-08-29T14:42:33.295584","indexId":"70256651","displayToPublicDate":"2022-10-05T09:34:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes","docAbstract":"

Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing. In Oregon's sagebrush steppe, for example, juniper tree removal resulted in a 21% increase in one pasture's productivity and an 18% decline in another. In Nebraska's Loess Canyons, perennial grass productivity initially declined 80% at sites invaded by trees that were prescriptively burned, but then fully recovered post-fire, representing a 492% increase from nadir. In Kansas' Shortgrass Prairie, plant biomass increased 4-fold (966,809 kg/ha) in pastures that were prescriptively grazed, with gains highly dependent upon precipitation as evidenced by sensitivity of remotely sensed estimates (SD ± 951,308 kg/ha). Our results emphasize that next-generation remote sensing datasets empower land managers to move beyond simplistic control versus treatment study designs to explore nuances in plant biomass in unprecedented ways. The products of new remote sensing technologies also accelerate adaptive management and help communicate wildlife and livestock forage benefits from management to diverse stakeholders.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.116359","usgsCitation":"Roberts, C.P., Naugle, D., Allred, B.W., Donovan, V.M., Fogarty, D.T., Jones, M., Maestas, J., Olsen, A.C., and Twidwell, D., 2022, Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes: Journal of Environmental Management, v. 324, 116359, 8 p., https://doi.org/10.1016/j.jenvman.2022.116359.","productDescription":"116359, 8 p.","ipdsId":"IP-137365","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.116359","text":"Publisher Index Page"},{"id":433304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Nebraska, Oregon","geographicExtents":"{\n \"type\": 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Montana","active":true,"usgs":false}],"preferred":false,"id":908492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allred, Brady W.","contributorId":341485,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":908493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Victoria M.","contributorId":341486,"corporation":false,"usgs":false,"family":"Donovan","given":"Victoria","email":"","middleInitial":"M.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":908494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fogarty, Dillon T.","contributorId":341487,"corporation":false,"usgs":false,"family":"Fogarty","given":"Dillon","email":"","middleInitial":"T.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":908495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Matthew O.","contributorId":341488,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew O.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":908496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maestas, Jeremy D.","contributorId":341489,"corporation":false,"usgs":false,"family":"Maestas","given":"Jeremy D.","affiliations":[{"id":65354,"text":"USDA Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":908497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Olsen, Andrew C.","contributorId":341490,"corporation":false,"usgs":false,"family":"Olsen","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":7041,"text":"The Nature 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Technology","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to 17α-ethinylestradiol results in differential susceptibility of largemouth bass (Micropterus salmoides) to bacterial infection","docAbstract":"

Disease outbreaks, skin lesions, mortality events, and reproductive abnormalities have been observed in wild populations of centrarchids. The presence of estrogenic endocrine disrupting compounds (EEDCs) has been implicated as a potential causal factor for these effects. The effects of prior EEDC exposure on immune response were examined in juvenile largemouth bass (Micropterus salmoides) exposed to a potent synthetic estrogen (17α-ethinylestradiol, EE2) at a low (EE2Low, 0.87 ng/L) or high (EE2High, 9.08 ng/L) dose for 4 weeks, followed by transfer to clean water and injection with an LD40 dose of the Gram-negative bacteria Edwardsiella piscicida. Unexpectedly, this prior exposure to EE2High significantly increased survivorship at 10 d post-infection compared to solvent control or EE2Low-exposed, infected fish. Both prior exposure and infection with E. piscicida led to significantly reduced hepatic glycogen levels, indicating a stress response resulting in depletion of energy stores. Additionally, pathway analysis for liver and spleen indicated differentially expressed genes associated with immunometabolic processes in the mock-injected EE2High treatment that could underlie the observed protective effect and metabolic shift in EE2High-infected fish. Our results demonstrate that exposure to a model EEDC alters metabolism and immune function in a fish species that is ecologically and economically important in North America.

","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.2c02250","usgsCitation":"Leet, J.K., Greer, J., Richter, C.A., Iwanowicz, L., Spinard, E., McDonald, J., Conway, C.M., Gale, R.W., Tillitt, D.E., and Hansen, J.D., 2022, Exposure to 17α-ethinylestradiol results in differential susceptibility of largemouth bass (Micropterus salmoides) to bacterial infection: Environmental Science and Technology, v. 56, no. 20, p. 14375-14386, https://doi.org/10.1021/acs.est.2c02250.","productDescription":"12 p.","startPage":"14375","endPage":"14386","ipdsId":"IP-139357","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":446225,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.2c02250","text":"Publisher Index Page"},{"id":435665,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93OHUUS","text":"USGS data release","linkHelpText":"Physiological and molecular endpoints observed in juvenile largemouth bass in response to an estrogen (17α-ethinylestradiol) and subsequently a bacterial challenge (Edwardsiella piscicida) exposure under laboratory conditions."},{"id":408607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"20","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Leet, Jessica Kristin 0000-0001-8142-6043","orcid":"https://orcid.org/0000-0001-8142-6043","contributorId":225505,"corporation":false,"usgs":true,"family":"Leet","given":"Jessica","email":"","middleInitial":"Kristin","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greer, Justin","contributorId":298316,"corporation":false,"usgs":false,"family":"Greer","given":"Justin","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richter, Cathy A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":1878,"corporation":false,"usgs":true,"family":"Richter","given":"Cathy","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":855381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spinard, Edward","contributorId":298319,"corporation":false,"usgs":false,"family":"Spinard","given":"Edward","email":"","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Jacquelyn","contributorId":298321,"corporation":false,"usgs":false,"family":"McDonald","given":"Jacquelyn","email":"","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":855383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":855384,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gale, Robert W. 0000-0002-8533-141X rgale@usgs.gov","orcid":"https://orcid.org/0000-0002-8533-141X","contributorId":2808,"corporation":false,"usgs":true,"family":"Gale","given":"Robert","email":"rgale@usgs.gov","middleInitial":"W.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855385,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855386,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hansen, John D. 0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":855387,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237281,"text":"70237281 - 2022 - Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","interactions":[],"lastModifiedDate":"2022-10-06T14:37:55.932771","indexId":"70237281","displayToPublicDate":"2022-10-05T09:31:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","title":"Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola","docAbstract":"

Uncovering the historical and contemporary processes shaping rare species with complex distributions is of growing importance due to threats such as habitat destruction and climate change. Species restricted to specialized, patchy habitat may persist by virtue of life history characteristics facilitating ongoing gene flow and dispersal, but they could also reflect the remnants of formerly widespread, suitable habitat that existed during past climate regimes. If formerly widespread species did not rely upon traits facilitating high dispersibility to persist, contemporary populations could be at high risk of extirpation or extinction. Fortunately, genomic investigations provide an opportunity to illuminate such alternative scenarios while simultaneously offering guidance for future management interventions. Herein, we test the role of these mechanisms in shaping patterns of genomic diversity and differentiation across a highly restricted and rare ecosystem: desert hanging gardens. We focus on Carex specuicola (Cyperaceae), a hanging garden obligate narrowly distributed in the Four Corners region of the southwestern United States that is listed as Threatened under the United States Endangered Species Act. Population structure and diversity analyses reveal that hanging garden populations are shaped by strong genetic drift, but that individuals in gardens are occasionally more closely related to individuals at other gardens than to individuals within the same garden. Similarly, gardens separated by long geographic distances may contain individuals that are more closely related compared to individuals in gardens separated by short geographic distances. Demographic modeling supports historical gene flow between some contemporary garden pairs, which is corroborated by low estimates of inbreeding coefficients and recent divergence times. As such, multiple lines of evidence support dispersal and gene flow across C. specuicola populations at both small and large spatial scales, indicating that even if C. specuicola was formerly more widespread, it may be well suited to persist in hanging gardens so long as suitable habitat remains available. Analyses like those demonstrated herein may be broadly applicable for understanding the short- and long-term evolutionary processes influencing rare species, and especially those having complex distributions across heterogeneous landscapes.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2022.941002","usgsCitation":"Chapin, K.J., Jones, M.R., Winkler, D.E., Rink, G., and Massatti, R., 2022, Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola: Frontiers in Conservation Science, v. 3, 941002, 15 p., https://doi.org/10.3389/fcosc.2022.941002.","productDescription":"941002, 15 p.","ipdsId":"IP-141134","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":446227,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.941002","text":"Publisher Index Page"},{"id":435666,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LLZ1XD","text":"USGS data release","linkHelpText":"Carex specuicola genomic data for the southern Colorado Plateau Desert"},{"id":408036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"southern Colorado Plateau Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.478515625,\n 35.88905007936091\n ],\n [\n -109.072265625,\n 35.88905007936091\n ],\n [\n -109.072265625,\n 37.75334401310656\n ],\n [\n -110.478515625,\n 37.75334401310656\n ],\n [\n -110.478515625,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapin, Kenneth James 0000-0002-8382-4050","orcid":"https://orcid.org/0000-0002-8382-4050","contributorId":297377,"corporation":false,"usgs":true,"family":"Chapin","given":"Kenneth","email":"","middleInitial":"James","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Matthew R","contributorId":297378,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":64389,"text":"formerly: USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rink, Glenn","contributorId":297379,"corporation":false,"usgs":false,"family":"Rink","given":"Glenn","affiliations":[{"id":64390,"text":"Deaver Herbarium, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853973,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237282,"text":"70237282 - 2022 - A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2022-10-31T14:50:23.413345","indexId":"70237282","displayToPublicDate":"2022-10-05T09:12:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model","docAbstract":"

A fault‐based crustal deformation model with deep driven dislocation sources is applied to estimate long‐term on‐fault slip rates and off‐fault moment rate distribution in the western United States (WUS) for the 2023 update to the National Seismic Hazard Model (NSHM). This model uses the method of Zeng and Shen (2017) to invert for slip rate and strain‐rate parameters based on inputs from Global Positioning System (GPS) velocities and geologic slip‐rate constraints. The model connects adjacent major fault segments in California and the Cascadia subduction zone to form blocks that extend to the boundaries of the study area. Faults within the blocks are obtained from the NSHM geologic fault section database. The model slip rates are determined using a least‐squares inversion with a normalized chi‐square of 6.6. I also apply a time‐dependent correction called “ghost transient” effect to account for the viscoelastic responses from large historic earthquakes along the San Andreas fault and Cascadia subduction zone. Major discrepancies between model slip rates and geologic slip rates along the San Andreas fault, for example, from the Cholame to the Mojave and San Bernardino segments of the San Andreas, are well reduced after the ghost transient correction is applied to GPS velocities. The off‐fault moment rate distribution is consistent with regional tectonics and seismicity patterns with a total rate of 1.6×1019  N·m/yr\">1.6×1019  N⋅m/yr for the WUS.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220209","usgsCitation":"Zeng, Y., 2022, A fault‐based crustal deformation model with deep driven dislocation sources for the 2023 update to the U.S. National Seismic Hazard Model: Seismological Research Letters, v. 93, no. 6, p. 3170-3185, https://doi.org/10.1785/0220220209.","productDescription":"16 p.","startPage":"3170","endPage":"3185","ipdsId":"IP-142327","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":408032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.7822265625,\n 31.80289258670676\n ],\n [\n -105,\n 31.80289258670676\n ],\n [\n -105,\n 48.922499263758255\n ],\n [\n -126.7822265625,\n 48.922499263758255\n ],\n [\n -126.7822265625,\n 31.80289258670676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":853974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237593,"text":"70237593 - 2022 - Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns","interactions":[],"lastModifiedDate":"2022-10-31T14:53:37.328533","indexId":"70237593","displayToPublicDate":"2022-10-04T14:10:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns","docAbstract":"Ocean acidification (OA) has resulted in global-scale changes in ocean chemistry, which can disturb marine organisms and ecosystems. Despite its extensively populated coastline, many marine-dependent communities, and valuable economies, the Gulf of Mexico (GOM) remains a relatively understudied region with respect to acidification. In general, the warm waters of the GOM are better buffered from acidification compared to higher latitude seas, yet long-term acidification has been documented in several GOM regions. OA within the GOM is recognized as spatially variable, particularly within the coastal zone where numerous physical and biogeochemical processes contribute to carbonate chemistry dynamics. The historical progression of OA within the entire GOM is difficult to assess because only a few dedicated long-term monitoring sites have recently been established, and full-water column observations are limited. However, environmental drivers on smaller scales that affect GOM acidification were found to include freshwater, nutrient, and carbonate discharge from large rivers; ocean warming, circulation and residence times; and episodic extreme weather events. GOM marine ecosystems provide essential services, including coastline protection and carbon dioxide removal, and habitats for many marine species that are economically and ecologically important. However, organismal and ecosystem responses to OA are not well constrained for the GOM due to a lack of studies examining the specific effects of OA on regionally relevant species under contemporary and projected conditions. Tackling the vast number of remaining scientific unknowns in this region can be best coordinated through regional capacity networks, such as the Gulf of Mexico Coastal Acidification Network (GCAN), working to achieve a system-wide understanding of Gulf OA and its impacts. Here we synthesize the current peer-reviewed literature on GOM acidification across the ocean-estuarine continuum and identify critical knowledge, research, and monitoring gaps that require future attention.","language":"English","publisher":"Elsevier","doi":"10.1016/j.pocean.2022.102882","usgsCitation":"Osborne, E., Hu, X., Hall, E.R., Yates, K.K., Vreeland-Dawson, J., Shamberger, K., Barbero, L., Hernandez-Ayon, J., Gomez, F., Hicks, T., Xu, Y., McCutcheon, M.R., Acquafredda, M., Chapa-Balcorta, C., Norzagaray, O., Pierrot, D., Munoz-Caravaca, A., Dobson, K.L., Williams, N., Rabalais, N.N., and Dash, P., 2022, Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns: Progress in Oceanography, v. 209, 102882, 23 p., https://doi.org/10.1016/j.pocean.2022.102882.","productDescription":"102882, 23 p.","ipdsId":"IP-135936","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.pocean.2022.102882","text":"Publisher Index Page"},{"id":408276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.82421875,\n 21.207458730482642\n ],\n [\n -87.099609375,\n 21.779905342529645\n ],\n [\n -83.935546875,\n 22.59372606392931\n ],\n [\n -80.947265625,\n 24.926294766395593\n ],\n [\n -82.265625,\n 27.137368359795584\n ],\n [\n -82.705078125,\n 28.38173504322308\n ],\n [\n -83.75976562499999,\n 30.06909396443887\n ],\n [\n -84.990234375,\n 29.53522956294847\n ],\n [\n -86.484375,\n 30.372875188118016\n ],\n [\n -87.978515625,\n 30.372875188118016\n ],\n [\n -90.087890625,\n 30.14512718337613\n ],\n [\n -89.384765625,\n 29.6880527498568\n ],\n [\n -90.263671875,\n 28.998531814051795\n ],\n [\n -91.23046875,\n 29.22889003019423\n ],\n [\n -92.021484375,\n 29.76437737516313\n ],\n [\n -93.8671875,\n 29.53522956294847\n ],\n [\n -95.537109375,\n 28.844673680771795\n ],\n [\n -96.85546875,\n 27.994401411046148\n ],\n [\n -97.646484375,\n 26.980828590472107\n ],\n [\n -97.3828125,\n 25.24469595130604\n ],\n [\n -97.55859375,\n 22.836945920943855\n ],\n [\n -97.3828125,\n 20.96143961409684\n ],\n [\n -96.328125,\n 19.476950206488414\n ],\n [\n -94.21875,\n 18.396230138028827\n ],\n [\n -92.28515625,\n 18.396230138028827\n ],\n [\n -91.0546875,\n 18.979025953255267\n ],\n [\n -90.3515625,\n 21.207458730482642\n ],\n [\n -89.82421875,\n 21.207458730482642\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Osborne, Emily","contributorId":279621,"corporation":false,"usgs":false,"family":"Osborne","given":"Emily","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":854555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Xinping 0000-0002-0613-6545","orcid":"https://orcid.org/0000-0002-0613-6545","contributorId":297889,"corporation":false,"usgs":false,"family":"Hu","given":"Xinping","email":"","affiliations":[{"id":64434,"text":"Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, US","active":true,"usgs":false}],"preferred":false,"id":854556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, E. 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Martin 0000-0001-6869-6225","orcid":"https://orcid.org/0000-0001-6869-6225","contributorId":297892,"corporation":false,"usgs":false,"family":"Hernandez-Ayon","given":"J. Martin","affiliations":[{"id":64439,"text":"Autonomous University of Baja California, Mexico","active":true,"usgs":false}],"preferred":false,"id":854562,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gomez, Fabian 0000-0002-2335-478X","orcid":"https://orcid.org/0000-0002-2335-478X","contributorId":297893,"corporation":false,"usgs":false,"family":"Gomez","given":"Fabian","email":"","affiliations":[{"id":64440,"text":"Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":854563,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hicks, Tacey 0000-0002-4064-7496","orcid":"https://orcid.org/0000-0002-4064-7496","contributorId":297894,"corporation":false,"usgs":false,"family":"Hicks","given":"Tacey","email":"","affiliations":[{"id":34980,"text":"Department of Oceanography, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":854564,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xu, Yuan-Yuan 0000-0001-5103-468X","orcid":"https://orcid.org/0000-0001-5103-468X","contributorId":297895,"corporation":false,"usgs":false,"family":"Xu","given":"Yuan-Yuan","email":"","affiliations":[{"id":64440,"text":"Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":854565,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McCutcheon, Melissa R. 0000-0003-1289-9191","orcid":"https://orcid.org/0000-0003-1289-9191","contributorId":297896,"corporation":false,"usgs":false,"family":"McCutcheon","given":"Melissa","email":"","middleInitial":"R.","affiliations":[{"id":64434,"text":"Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, US","active":true,"usgs":false}],"preferred":false,"id":854566,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Acquafredda, Michael 0000-0003-2006-6026","orcid":"https://orcid.org/0000-0003-2006-6026","contributorId":297897,"corporation":false,"usgs":false,"family":"Acquafredda","given":"Michael","email":"","affiliations":[{"id":64441,"text":"Ocean Acidification Program, National Oceanographic and Atmospheric Administration, Silver Spring, MD, US","active":true,"usgs":false}],"preferred":false,"id":854567,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chapa-Balcorta, Cecilia 0000-0001-8305-0844","orcid":"https://orcid.org/0000-0001-8305-0844","contributorId":297898,"corporation":false,"usgs":false,"family":"Chapa-Balcorta","given":"Cecilia","email":"","affiliations":[{"id":64442,"text":"Instituto de Recursos, Universidad del Mar. Puerto Angel, Oaxaca, Mexico","active":true,"usgs":false}],"preferred":false,"id":854568,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Norzagaray, Orion 0000-0002-9769-0030","orcid":"https://orcid.org/0000-0002-9769-0030","contributorId":297899,"corporation":false,"usgs":false,"family":"Norzagaray","given":"Orion","email":"","affiliations":[{"id":64439,"text":"Autonomous University of Baja California, Mexico","active":true,"usgs":false}],"preferred":false,"id":854569,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pierrot, Denis","contributorId":176446,"corporation":false,"usgs":false,"family":"Pierrot","given":"Denis","email":"","affiliations":[],"preferred":false,"id":854570,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Munoz-Caravaca, Alain 0000-0003-1261-0159","orcid":"https://orcid.org/0000-0003-1261-0159","contributorId":297900,"corporation":false,"usgs":false,"family":"Munoz-Caravaca","given":"Alain","email":"","affiliations":[{"id":64443,"text":"Center for Environmental Studies in Cienfuegos, Cuba","active":true,"usgs":false}],"preferred":false,"id":854571,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Dobson, Kerri L. 0000-0003-1363-4195","orcid":"https://orcid.org/0000-0003-1363-4195","contributorId":297901,"corporation":false,"usgs":false,"family":"Dobson","given":"Kerri","email":"","middleInitial":"L.","affiliations":[{"id":64441,"text":"Ocean Acidification Program, National Oceanographic and Atmospheric Administration, Silver Spring, MD, US","active":true,"usgs":false}],"preferred":false,"id":854572,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, N. 0000-0002-6541-9385","orcid":"https://orcid.org/0000-0002-6541-9385","contributorId":297902,"corporation":false,"usgs":false,"family":"Williams","given":"N.","email":"","affiliations":[{"id":64444,"text":"College of Marine Science, University of South Florida, Saint Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":854573,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rabalais, N. N.","contributorId":198497,"corporation":false,"usgs":false,"family":"Rabalais","given":"N.","email":"","middleInitial":"N.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":854574,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Dash, Padmanava 0000-0003-3851-6830","orcid":"https://orcid.org/0000-0003-3851-6830","contributorId":297903,"corporation":false,"usgs":false,"family":"Dash","given":"Padmanava","email":"","affiliations":[{"id":64445,"text":"Department of Geosciences, Mississippi State University, Mississippi State, MS, US","active":true,"usgs":false}],"preferred":false,"id":854575,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70237137,"text":"fs20223069 - 2022 - Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019","interactions":[],"lastModifiedDate":"2022-10-05T10:54:58.073609","indexId":"fs20223069","displayToPublicDate":"2022-10-04T11:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3069","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in Mesozoic Total Petroleum Systems of the Central European Basin System, 2019","title":"Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019","docAbstract":"

Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable continuous resources of 5.8 billion barrels of oil and 22.4 trillion cubic feet of gas in the Mesozoic Total Petroleum Systems of the Central European Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223069","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Leathers-Miller, H.M., Le, P.A., Drake, R.M., II, Kinney, S.A., and Brownfield, M.E., 2022, Assessment of undiscovered conventional oil and gas resources in Mesozoic total petroleum systems of the Central European Basin system, 2019: U.S. Geological Survey Fact Sheet 2022–3069, 4 p., https://doi.org/10.3133/fs20223069.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115545","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":407698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N5F8XY","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Mesozoic Petroleum Systems of Central European Basin System: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":407696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3069/coverthb.jpg"},{"id":407697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3069/fs20223069.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3069"}],"otherGeospatial":"Central European Basin system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -9.667968749999975,\n 50.2893392532918\n ],\n [\n 9.93164062500003,\n 50.2893392532918\n ],\n [\n 9.93164062500003,\n 63.11463763252086\n ],\n [\n -9.667968749999975,\n 63.11463763252086\n ],\n [\n -9.667968749999975,\n 50.2893392532918\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

","tableOfContents":"","publishedDate":"2022-10-04","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":255366,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodall, Cheryl A. 0000-0002-4844-5768 cwoodall@usgs.gov","orcid":"https://orcid.org/0000-0002-4844-5768","contributorId":194924,"corporation":false,"usgs":true,"family":"Woodall","given":"Cheryl","email":"cwoodall@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathers-Miller, Heidi M. 0000-0001-5208-9906","orcid":"https://orcid.org/0000-0001-5208-9906","contributorId":210000,"corporation":false,"usgs":true,"family":"Leathers-Miller","given":"Heidi M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":853467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Le, Phuong A. 0000-0003-2477-509X","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":255367,"corporation":false,"usgs":true,"family":"Le","given":"Phuong A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853466,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drake, Ronald M. II 0000-0002-1770-4667","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":206291,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald M.","suffix":"II","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":853470,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238634,"text":"70238634 - 2022 - Regional models do not outperform continental models for invasive species","interactions":[],"lastModifiedDate":"2022-12-02T13:01:29.078063","indexId":"70238634","displayToPublicDate":"2022-10-04T07:00:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Regional models do not outperform continental models for invasive species","docAbstract":"

Aim: Species distribution models can guide invasive species prevention and management by characterizing invasion risk across space. However, extrapolation and transferability issues pose challenges for developing useful models for invasive species. Previous work has emphasized the importance of including all available occurrences in model estimation, but managers attuned to local processes may be skeptical of models based on a broad spatial extent if they suspect the captured responses reflect those of other regions where data are more numerous. We asked whether species distribution models for invasive plants performed better when developed at national versus regional extents.

Location: Continental United States.

Methods: We developed ensembles of species distribution models trained nationally, on sagebrush habitat, or on sagebrush habitat within three ecoregions (Great Basin, eastern sagebrush, and Great Plains) for nine invasive plants of interest for early detection and rapid response at local or regional scales. We compared the performance of national versus regional models using spatially independent withheld test data from each of the three ecoregions.

Results: We found that models trained using a national spatial extent tended to perform better than regionally trained models. Regional models did not outperform national ones even when considerable occurrence data were available for model estimation within the focal region. Information was often unavailable to fit informative regional models precisely in those areas of greatest interest for early detection and rapid response.

Main conclusions: Habitat suitability models for invasive plant species trained at a continental extent can reduce extrapolation while maximizing information on species’ responses to environmental variation. Standard modeling methods can capture spatially varying limiting factors, while regional or hierarchical models may only be advantageous when populations differ in their responses to environmental conditions, a condition expected to be relatively rare at the expanding boundaries of invasive species’ distributions.

","language":"English","publisher":"NeoBiota","doi":"10.3897/neobiota.77.86364","usgsCitation":"Jarnevich, C.S., Sofaer, H., Engelstad, P., and Belamaric, P., 2022, Regional models do not outperform continental models for invasive species: NeoBiota, v. 77, https://doi.org/10.3897/neobiota.77.86364.","productDescription":"22 p.","startPage":"1-22","ipdsId":"IP-137001","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446233,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.77.86364","text":"Publisher Index Page"},{"id":435667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90AL0PN","text":"USGS data release","linkHelpText":"Data to create and evaluate distribution models for invasive species for different geographic extents"},{"id":409981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belamaric, Pairsa 0000-0001-7529-0370","orcid":"https://orcid.org/0000-0001-7529-0370","contributorId":299593,"corporation":false,"usgs":false,"family":"Belamaric","given":"Pairsa","affiliations":[{"id":64897,"text":"Student Contractor to the USGS Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":858159,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237881,"text":"70237881 - 2022 - Hurdles to developing quantitative decision support for Endangered Species Act resource allocation","interactions":[],"lastModifiedDate":"2022-10-31T12:01:40.279728","indexId":"70237881","displayToPublicDate":"2022-10-04T06:58:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Hurdles to developing quantitative decision support for Endangered Species Act resource allocation","docAbstract":"

The U.S. Fish and Wildlife Service oversees the recovery of many species protected by the U.S. Endangered Species Act (ESA). Recent research suggests that a structured approach to allocating conservation resources could increase recovery outcomes for ESA listed species. Quantitative approaches to decision support can efficiently allocate limited financial resources and maximize desired outcomes. Yet, developing quantitative decision support under real-world constraints is challenging. Approaches that pair research teams and end-users are generally the most effective. However, co-development requires overcoming “hurdles” that can arise because of differences in the mental models of the co-development team. These include perceptions that: (1) scarce funds should be spent on action, not decision support; (2) quantitative approaches are only useful for simple decisions; (3) quantitative tools are inflexible and prescriptive black boxes; (4) available data are not good enough to support decisions; and (5) prioritization means admitting defeat. Here, we describe how we addressed these misperceptions during the development of a prototype resource allocation decision support tool for understanding trade-offs in U.S. endangered species recovery. We describe how acknowledging these hurdles and identifying solutions enabled us to progress with development. We believe that our experience can assist other applications of developing quantitative decision support for resource allocation.

","language":"English","publisher":"Frontiers","doi":"10.3389/fcosc.2022.1002804","usgsCitation":"Iacona, G.D., Avery-Gomm, S., Maloney, R.F., Brazill-Boast, J., Crouse, D.T., Drew, C., Epanchin-Niell, R.S., Hall, S.B., Maguire, L.A., Male, T., Newman, J., Possingham, H.P., Rumpff, L., Runge, M.C., Weiss, K.C., Wilson, R.S., Zablan, M.A., and Gerber, L.R., 2022, Hurdles to developing quantitative decision support for Endangered Species Act resource allocation: Frontiers in Conservation Science, v. 3, 1002804, 9 p., https://doi.org/10.3389/fcosc.2022.1002804.","productDescription":"1002804, 9 p.","ipdsId":"IP-114585","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.1002804","text":"Publisher Index Page"},{"id":408877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Iacona, Gwenllian D.","contributorId":213094,"corporation":false,"usgs":false,"family":"Iacona","given":"Gwenllian","email":"","middleInitial":"D.","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avery-Gomm, Stephanie","contributorId":213093,"corporation":false,"usgs":false,"family":"Avery-Gomm","given":"Stephanie","email":"","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Richard F.","contributorId":213091,"corporation":false,"usgs":false,"family":"Maloney","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":38703,"text":"New Zealand Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":856071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brazill-Boast, James","contributorId":213095,"corporation":false,"usgs":false,"family":"Brazill-Boast","given":"James","email":"","affiliations":[{"id":38705,"text":"New South Wales Office of Environment and Heritage","active":true,"usgs":false}],"preferred":false,"id":856072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crouse, Deborah T.","contributorId":173709,"corporation":false,"usgs":false,"family":"Crouse","given":"Deborah","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":856073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drew, C Ashton","contributorId":298628,"corporation":false,"usgs":false,"family":"Drew","given":"C Ashton","affiliations":[{"id":64631,"text":"KDV Decision Analysis LLC","active":true,"usgs":false}],"preferred":false,"id":856074,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Epanchin-Niell, Rebecca S.","contributorId":175364,"corporation":false,"usgs":false,"family":"Epanchin-Niell","given":"Rebecca","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":856075,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Sarah B.","contributorId":213157,"corporation":false,"usgs":false,"family":"Hall","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":856076,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Maguire, Lynn A.","contributorId":213097,"corporation":false,"usgs":false,"family":"Maguire","given":"Lynn","email":"","middleInitial":"A.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":856077,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Male, Tim","contributorId":213158,"corporation":false,"usgs":false,"family":"Male","given":"Tim","email":"","affiliations":[],"preferred":false,"id":856078,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Newman, Jeff","contributorId":213099,"corporation":false,"usgs":false,"family":"Newman","given":"Jeff","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":856079,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Possingham, Hugh P.","contributorId":20882,"corporation":false,"usgs":false,"family":"Possingham","given":"Hugh","email":"","middleInitial":"P.","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":856080,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rumpff, Libby","contributorId":197117,"corporation":false,"usgs":false,"family":"Rumpff","given":"Libby","email":"","affiliations":[],"preferred":false,"id":856081,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"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":856082,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Weiss, Katherine C B","contributorId":298629,"corporation":false,"usgs":false,"family":"Weiss","given":"Katherine","email":"","middleInitial":"C B","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":856083,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wilson, Robyn S.","contributorId":175362,"corporation":false,"usgs":false,"family":"Wilson","given":"Robyn","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":856084,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zablan, Marilet A.","contributorId":175046,"corporation":false,"usgs":false,"family":"Zablan","given":"Marilet","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":856085,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Gerber, Leah R.","contributorId":147236,"corporation":false,"usgs":false,"family":"Gerber","given":"Leah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":856086,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70246290,"text":"70246290 - 2022 - Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","interactions":[],"lastModifiedDate":"2023-06-30T11:51:09.714357","indexId":"70246290","displayToPublicDate":"2022-10-04T06:49:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve","docAbstract":"

We used data collected during surveys of seven North American Breeding Bird Survey routes in eastern Texas to estimate avian populations within Big Thicket National Preserve. On only 61 of the 350 count locations located along these routes did observers monitor birds within the boundaries of this preserve. On selected routes, we recorded initial bird detections during the 3-min bird count within 1-min time intervals and within two distance classes (≤50 or >50 m). We used these data, combined with data collected using standard Breeding Bird Survey protocols during 2009–2016, to estimate detection probabilities and effective detection radii for commonly detected species. For species often detected in flocks, we estimated these parameters for group detections. From these parameters, we estimated regional densities for 60 species. Because habitat within Big Thicket National Preserve differed from habitat along surveyed routes, for each species we adjusted the projected population estimate to account for the relationship between density of detected birds and habitat descriptors from the National Land Cover database. On the basis of our estimates of regional density of each species, and accounting for differences in habitat availability, we estimated that commonly detected avian species comprises a population of 192,201 breeding birds (95% confidence interval = 144,269–340,790) within Big Thicket National Preserve.

","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-66.3.240","usgsCitation":"Twedt, D.J., and Shackelford, C.E., 2022, Use of regional breeding bird surveys to estimate bird populations in Big Thicket National Preserve: The Southwestern Naturalist, v. 66, no. 3, p. 240-249, https://doi.org/10.1894/0038-4909-66.3.240.","productDescription":"10 p.","startPage":"240","endPage":"249","ipdsId":"IP-065568","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":418650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Big Thicket National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.4910453710765,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.35392517388506\n ],\n [\n -94.20415064179676,\n 30.60117874378041\n ],\n [\n -94.4910453710765,\n 30.60117874378041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":876669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shackelford, Clifford E.","contributorId":315488,"corporation":false,"usgs":false,"family":"Shackelford","given":"Clifford","email":"","middleInitial":"E.","affiliations":[{"id":68340,"text":"Texas Parks and Wildlife Department, 506 Hayter St., Nacogdoches, Texas 75965","active":true,"usgs":false}],"preferred":false,"id":876670,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237237,"text":"70237237 - 2022 - Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases","interactions":[],"lastModifiedDate":"2022-10-05T11:43:40.442998","indexId":"70237237","displayToPublicDate":"2022-10-04T06:40:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases","docAbstract":"

Negative imagery of destruction may induce or inhibit action to reduce risks from climate-exacerbated hazards, such as wildfires. This has generated conflicting assumptions among experts who communicate with homeowners: half of surveyed wildfire practitioners perceive a lack of expert agreement about the effect of negative imagery (a burning house) on homeowner behavior, yet most believe negative imagery is more engaging. We tested whether this expectation matched homeowner response in the United States. In an online experiment, homeowners who viewed negative imagery reported more negative emotions but the same behavioral intentions compared to those who viewed status-quo landscape photos. In a pre-registered field experiment, homeowners who received a postcard showing negative imagery were equally likely, overall, to visit a wildfire risk webpage as those whose postcard showed a status quo photo. However, the negative imagery decreased webpage visits as homeowners’ wildfire risk increased. These results illustrate the importance of testing assumptions to encourage behavioral adaptation to climate change.

","language":"English","publisher":"Nature","doi":"10.1038/s43247-022-00505-7","usgsCitation":"Byerly Flint, H., Champ, P.A., Meldrum, J., and Brenkert-Smith, H., 2022, Wildfire imagery reduces risk information-seeking among homeowners as property wildfire risk increases: Communications Earth & Environment, v. 3, 229, 8 p., https://doi.org/10.1038/s43247-022-00505-7.","productDescription":"229, 8 p.","ipdsId":"IP-129193","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446238,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-022-00505-7","text":"Publisher Index Page"},{"id":407950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Byerly Flint, Hilary 0000-0002-7445-2099","orcid":"https://orcid.org/0000-0002-7445-2099","contributorId":297251,"corporation":false,"usgs":false,"family":"Byerly Flint","given":"Hilary","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":853706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":853707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":853708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":853709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237176,"text":"cir1500 - 2022 - 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","interactions":[{"subject":{"id":70212975,"text":"cir1468 - 2020 - 2020 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","indexId":"cir1468","publicationYear":"2020","noYear":false,"displayTitle":"2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium","title":"2020 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium"},"predicate":"SUPERSEDED_BY","object":{"id":70237176,"text":"cir1500 - 2022 - 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","indexId":"cir1500","publicationYear":"2022","noYear":false,"title":"2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium"},"id":1}],"lastModifiedDate":"2022-10-04T19:55:21.162292","indexId":"cir1500","displayToPublicDate":"2022-10-03T17:23:03","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1500","displayTitle":"2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium","title":"2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium","docAbstract":"

The Joint Agency Commercial Imagery Evaluation (JACIE) is a collaboration between six Federal agencies that are major users and producers of satellite land remote sensing data. In recent years, the JACIE group has observed ever-increasing numbers of remote sensing satellites being launched. This rapidly growing wave of new systems creates a need for a single reference for land remote sensing satellites that provides basic system specifications and linkage to any JACIE assessment that may have been completed on existing systems. This volume has been assembled by the Requirements, Capabilities, and Analysis for Earth Observation Project under the U.S. Geological Survey National Land Imaging Program as a contribution to the JACIE community. This is the third edition of the JACIE compendium, which is planned to be updated and released annually.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1500","usgsCitation":"Ramaseri Chandra, S.N., Christopherson, J.B., Casey, K.A., Lawson, J., and Sampath, A., 2022, 2022 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium: U.S. Geological Survey Circular 1500, 279 p., https://doi.org/10.3133/cir1500. [Supersedes USGS Circular 1468.]","productDescription":"xiii, 279 p.","numberOfPages":"298","onlineOnly":"N","ipdsId":"IP-139076","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":407832,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1500/circ1500.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1500"},{"id":407831,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1500/coverthb.jpg"}],"contact":"

Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-10-03","noUsgsAuthors":false,"publicationDate":"2022-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramaseri Chandra, Shankar N. 0000-0002-4434-4468","orcid":"https://orcid.org/0000-0002-4434-4468","contributorId":216043,"corporation":false,"usgs":true,"family":"Ramaseri Chandra","given":"Shankar","email":"","middleInitial":"N.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":853556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopherson, Jon B. 0000-0002-2472-0059","orcid":"https://orcid.org/0000-0002-2472-0059","contributorId":297156,"corporation":false,"usgs":false,"family":"Christopherson","given":"Jon","email":"","middleInitial":"B.","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":853557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casey, Kimberly A. 0000-0002-6115-7525","orcid":"https://orcid.org/0000-0002-6115-7525","contributorId":239829,"corporation":false,"usgs":false,"family":"Casey","given":"Kimberly A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":853558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawson, Jane 0000-0002-4812-7487","orcid":"https://orcid.org/0000-0002-4812-7487","contributorId":297157,"corporation":false,"usgs":false,"family":"Lawson","given":"Jane","email":"","affiliations":[],"preferred":false,"id":853559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sampath, Aparajithan 0000-0002-6922-4913 asampath@usgs.gov","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":3622,"corporation":false,"usgs":true,"family":"Sampath","given":"Aparajithan","email":"asampath@usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":853560,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70255125,"text":"70255125 - 2022 - Wildlife migrations highlight importance of both private lands and protected areas in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-06-12T16:47:45.780934","indexId":"70255125","displayToPublicDate":"2022-10-03T11:33:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife migrations highlight importance of both private lands and protected areas in the Greater Yellowstone Ecosystem","docAbstract":"

Formally protected areas are an important component of wildlife conservation, but face limitations in their effectiveness for migratory species. Improved stewardship of working lands around protected areas is one solution for conservation planning, but private working lands are vulnerable to development. In the Greater Yellowstone Ecosystem (GYE), ungulates such as elk (Cervus canadensis) use both protected areas and private lands throughout their annual migrations. We studied patterns of landownership, protection, and conservation challenges within the ranges of migratory elk in the GYE. We used GPS data from 1088 elk in 26 herds to define herd-level seasonal ranges, and extracted covariates related to landownership and protection, land use, and human infrastructure and development. All elk herds used land encompassing >1 ownership type. Most elk herds (92.3 % of herds, n = 24) used the highest proportion of private land in the winter (mean = 36.2 % private land). Most elk herds' winter ranges contained the highest building densities (mean = 1.24 buildings/km2), fence densities (mean = 1.02 km fence/km2), and cattle grazing (mean = 1.9 cows/km2), compared to migratory and summer ranges. Out of all ranges, 36.5 % of ranges did not have any zoning regulations, indicating the potential for future development. Our results show that elk in the GYE rely on habitat outside of protected areas, and face landscape-scale conservation challenges such as habitat fragmentation from human development, particularly in winter ranges. Future conservation strategies for wildlife in this system need to encompass coordination across both public and private land to ensure migratory connectivity.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109752","usgsCitation":"Gigliottia, L.C., Wenjing Xu, Zuckerman, G., Atwood, M.P., Eric K. Cole, Alyson Courtemanch, Dewey, S., Gude, J.A., Hnilicka, P., Kauffman, M., Kroetz, K., Lawson, A., Leonard, B., MacNulty, D., Maichak, E., McWhirter, D., Mong, T.W., Proffitt, K., Scurlock, B., Stahler, D., and Middleton, A.D., 2022, Wildlife migrations highlight importance of both private lands and protected areas in the Greater Yellowstone Ecosystem: Biological Conservation, v. 275, 109752, 9 p., https://doi.org/10.1016/j.biocon.2022.109752.","productDescription":"109752, 9 p.","ipdsId":"IP-141698","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":446239,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109752","text":"Publisher Index Page"},{"id":430023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.79292022701935,\n 45.50034062999211\n ],\n [\n -111.79292022701935,\n 43.92815809407176\n ],\n [\n -109.67116747387536,\n 43.92815809407176\n ],\n [\n -109.67116747387536,\n 45.50034062999211\n ],\n [\n -111.79292022701935,\n 45.50034062999211\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"275","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gigliottia, Laura C.","contributorId":338702,"corporation":false,"usgs":false,"family":"Gigliottia","given":"Laura","email":"","middleInitial":"C.","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":903466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenjing Xu","contributorId":338703,"corporation":false,"usgs":false,"family":"Wenjing Xu","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":903467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zuckerman, Gabriel","contributorId":338704,"corporation":false,"usgs":false,"family":"Zuckerman","given":"Gabriel","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":903468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, M. 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2022 - Corrigendum: Associations between cyanobacteria and indices of secondary production in the western basin of Lake Erie","interactions":[],"lastModifiedDate":"2024-09-26T13:40:43.394886","indexId":"70258749","displayToPublicDate":"2022-10-03T08:32:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Corrigendum: Associations between cyanobacteria and indices of secondary production in the western basin of Lake Erie","docAbstract":"

In the last year, we became aware that data used in our above-referenced manuscript from 2018 published in Limnology and Oceanography contained significant errors. In the 2018 manuscript, we found that indices of secondary production were negatively correlated to indices of cyanobacterial abundance and toxicity. Unfortunately, one of our indices of cyanobacterial abundance (biovolume) and our measurement of toxicity (microcystin concentration) were inaccurate in the data we used in the 2018 manuscript. Upon discovering these errors, we immediately began correcting the repositories where these data were available. Having corrected those data repositories, we are now reporting on the re-analysis of the data using the methods previously described in the 2018 manuscript. Although the relationships are slightly different, our interpretation is that the conclusions of the 2018 manuscript are still valid using the corrected data. The data errors we experienced were traced to a spreadsheet that was used to share data among the research team, which had errors caused by mistakes in copy-pasting formulas instead of data and ‘inadvertent’ edits that were saved by the spreadsheet's auto-save function. We apologize to the scientific community for these errors.

","language":"English","publisher":"ASLO","doi":"10.1002/lno.12216","usgsCitation":"Larson, J.H., Evans, M.A., Kennedy, R., Bailey, S., Loftin, K.A., Laughrey, Z.R., Femmer, R.A., Schaeffer, J., Richardson, W., Wynne, T., Nelson, J.C., and Duris, J.W., 2022, Corrigendum: Associations between cyanobacteria and indices of secondary production in the western basin of Lake Erie: Limnology and Oceanography, v. 67, no. 11, p. 2617-2620, https://doi.org/10.1002/lno.12216.","productDescription":"4 p.","startPage":"2617","endPage":"2620","ipdsId":"IP-138062","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":462275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.51669311523438,\n 41.51063406062076\n ],\n [\n -82.77923583984375,\n 41.51063406062076\n ],\n [\n -82.77923583984375,\n 42.04011410708205\n ],\n [\n -83.51669311523438,\n 42.04011410708205\n ],\n [\n -83.51669311523438,\n 41.51063406062076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":913946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":913947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Robert J 0000-0003-2135-5022","orcid":"https://orcid.org/0000-0003-2135-5022","contributorId":215686,"corporation":false,"usgs":false,"family":"Kennedy","given":"Robert J","affiliations":[{"id":39305,"text":"Former UMESC employee - 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2022 - Last Glacial Maximum and early deglaciation in the Stura Valley, southwestern European Alps","interactions":[],"lastModifiedDate":"2022-10-04T11:59:18.208422","indexId":"70237184","displayToPublicDate":"2022-10-03T06:55:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Last Glacial Maximum and early deglaciation in the Stura Valley, southwestern European Alps","docAbstract":"

We combined data from geomorphologic surveys, glacial modelling, and 10Be exposure ages of boulders on moraines, to investigate the Last Glacial Maximum (LGM) and the early retreat glacial phases in the Stura Valley of the Maritime Alps. We used the exposure ages to reconstruct the timing of standstills or readvances which interrupted the post-LGM withdrawal, initiated ∼24 ka. We mapped and dated the frontal moraines of a first glacial standstill/readvance at a short distance (∼7 km) from the maximum external limit of the LGM, which occurred at ∼22 ka, and a second one at ∼19 ka (Bühl stadial). This morpho-chronologic succession is congruent with that obtained in the adjacent Gesso Valley and, combined with the similarity of Equilibrium Line Altitude values, demonstrates a consistent glacial response in the Maritime Alps to climatic forcing.

Our data are chronologically consistent with those of the southern flank of the European Alps, stressing not only a general synchroneity of the LGM across the various sectors, but also that of a LGM recessional standstill or readvance at ∼22 ka. The short distance between the LGM moraines and the recessionary phase moraines, and minimal difference in ELA indicate a modest variation in the mass balance of the Maritime Alps glaciers during this time interval. A similar modest variation between LGM and the first recessional phase glacier mass balance is also found throughout the western sector of the Southern Alps but is considerably more pronounced for the glaciers of the central-eastern sectors. This behaviour can be explained by the interplay between the moisture supplied by southern currents sourced in the Western Mediterranean and that advected by the westerlies sourced in the North Atlantic, which affected the various sectors of the Southern Alps differently.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2022.107770","usgsCitation":"Ribolini, A., Spagnolo, M., Cyr, A.J., and Federici, P.R., 2022, Last Glacial Maximum and early deglaciation in the Stura Valley, southwestern European Alps: Quaternary Science Reviews, v. 295, 107770, 17 p., https://doi.org/10.1016/j.quascirev.2022.107770.","productDescription":"107770, 17 p.","ipdsId":"IP-140334","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2022.107770","text":"Publisher Index Page"},{"id":435668,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HCE4EC","text":"USGS data release","linkHelpText":"Data release for cosmogenic beryllium-10 exposure ages of moraine boulders in the Stura Valley, Maritime Alps, northwestern Italy"},{"id":407853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy, France","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 7.305908203125,\n 43.97700467496408\n ],\n [\n 7.80029296875,\n 43.97700467496408\n ],\n [\n 7.80029296875,\n 44.32384807250689\n ],\n [\n 7.305908203125,\n 44.32384807250689\n ],\n [\n 7.305908203125,\n 43.97700467496408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"295","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ribolini, Adriano 0000-0001-5851-8775","orcid":"https://orcid.org/0000-0001-5851-8775","contributorId":291770,"corporation":false,"usgs":false,"family":"Ribolini","given":"Adriano","email":"","affiliations":[{"id":62747,"text":"Department of Earth Sciences, University of Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":853586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spagnolo, Matteo 0000-0002-2753-338X","orcid":"https://orcid.org/0000-0002-2753-338X","contributorId":291771,"corporation":false,"usgs":false,"family":"Spagnolo","given":"Matteo","email":"","affiliations":[{"id":62748,"text":"Department of Geography & Environment, University of Aberdeen, UK","active":true,"usgs":false}],"preferred":false,"id":853587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cyr, Andrew J. 0000-0003-2293-5395 acyr@usgs.gov","orcid":"https://orcid.org/0000-0003-2293-5395","contributorId":3539,"corporation":false,"usgs":true,"family":"Cyr","given":"Andrew","email":"acyr@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":853588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Federici, Paolo Roberto","contributorId":297167,"corporation":false,"usgs":false,"family":"Federici","given":"Paolo","email":"","middleInitial":"Roberto","affiliations":[{"id":64311,"text":"retired, Department of Earth Sciences, University of Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":853589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237716,"text":"70237716 - 2022 - Urbanization of grasslands in the Denver area affects streamflow responses to rainfall events","interactions":[],"lastModifiedDate":"2022-10-20T11:54:45.648562","indexId":"70237716","displayToPublicDate":"2022-10-03T06:52:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization of grasslands in the Denver area affects streamflow responses to rainfall events","docAbstract":"

A thorough understanding of how urbanization affects stream hydrology is crucial for effective and sustainable water management, particularly in rapidly urbanizing regions. This study presents a comprehensive analysis of changes in streamflow response to rainfall events across a rural to urban gradient in the semi-arid area of Denver, Colorado. We used 8 years of April to October instantaneous streamflow data in 21 watersheds ranging in size from 0.8 to 90 km2 and with impervious areas ranging from 1% to 47%. With these data, we applied a semi-automated method to identify a total of 2877 streamflow responses, which were analysed for event-based metrics of peak flow, runoff depth, runoff to rainfall ratio, time to peak, duration and number of streamflow responses to rainfall events. We also determined whether streamflow responses could be predicted by a precipitation threshold. Watersheds with >10% impervious cover had a precipitation threshold of 1–2 mm/hr needed to produce a streamflow response, compared to thresholds of 4–36 mm/hr for watersheds with less than 10% impervious surface cover. This lower precipitation threshold in more impervious watersheds led to more frequent streamflow responses. On average, streamflow responses had shorter duration and higher peak flows in watersheds with more impervious surface cover. In contrast to other regions, runoff depth, runoff to rainfall ratio and time to peak either gave mixed results or did not vary significantly with imperviousness. These alterations in streamflow response to rainfall events indicate the specific ways that urban development changes how streams respond to rain events in a semi-arid setting. This work points to the need for local adaptation of stormwater management to mitigate the effects of streamflow changes with urbanization.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14720","usgsCitation":"Wilson, S., Bhaskar, A.S., Choat, B., Kampf, S.K., Green, T., and Hopkins, K.G., 2022, Urbanization of grasslands in the Denver area affects streamflow responses to rainfall events: Hydrological Processes, v. 36, no. 10, e14720, 16 p., https://doi.org/10.1002/hyp.14720.","productDescription":"e14720, 16 p.","ipdsId":"IP-137466","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":446243,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14720","text":"Publisher Index Page"},{"id":408568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.44465584565634,\n 40.0300464557578\n ],\n [\n -105.44465584565634,\n 39.475337664909006\n ],\n [\n -104.54814508035963,\n 39.475337664909006\n ],\n [\n -104.54814508035963,\n 40.0300464557578\n ],\n [\n -105.44465584565634,\n 40.0300464557578\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"36","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Stacy","contributorId":298303,"corporation":false,"usgs":false,"family":"Wilson","given":"Stacy","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":855344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhaskar, Aditi S.","contributorId":199824,"corporation":false,"usgs":false,"family":"Bhaskar","given":"Aditi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":855345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choat, Benjamin","contributorId":270774,"corporation":false,"usgs":false,"family":"Choat","given":"Benjamin","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":855346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kampf, Stephanie K. 0000-0001-8991-2679","orcid":"https://orcid.org/0000-0001-8991-2679","contributorId":225146,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","email":"","middleInitial":"K.","affiliations":[{"id":41048,"text":"Associate Professor, Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":855347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, Timothy","contributorId":298305,"corporation":false,"usgs":false,"family":"Green","given":"Timothy","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":855348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855349,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238435,"text":"70238435 - 2022 - One hundred years of cobalt production in the Democratic Republic of the Congo","interactions":[],"lastModifiedDate":"2022-11-23T12:42:47.997751","indexId":"70238435","displayToPublicDate":"2022-10-03T06:40:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3266,"text":"Resources Policy","active":true,"publicationSubtype":{"id":10}},"title":"One hundred years of cobalt production in the Democratic Republic of the Congo","docAbstract":"

Cobalt is an indispensable element for the manufacture of strategic technologies including advanced batteries, jet engines, rare-earth permanent magnets, petroleum catalysts, and tool parts that enable construction, manufacturing, and mining. Cobalt routinely scores high in mineral supply risk assessments due to the concentration of cobalt mine production in the Democratic Republic of the Congo (DRC). This stands in contrast to the fact that DRC cobalt mine production had a 20% compound annual growth rate from 1995 through 2020—in large part due to investments by Chinese firms beginning in the mid-2000s. Given this continuous growth, one may ask why this supply is perceived to be so risky. This analysis illuminates the causes of historic disruptions to DRC cobalt mine and refinery production by analyzing country-level production, historical reports, and cobalt prices back to 1924. The results indicate that the main causes of supply disruptions were damage to transportation routes, underinvestment in maintaining nationalized mining assets, and the disintegration of the DRC economy during the early 1990s. On the other hand, cobalt mine production increased 50% from 1977 to 1979 despite two secessionist conflicts in DRC's cobalt producing region and increased seven-fold from 1996 to 2003 despite two African wars over the DRC and its resources. These results indicate that—barring another economic disintegration or mining industry nationalization—DRC mine production will likely continue to be the dominant supplier of the world's growing demand for cobalt in lithium-ion batteries. These results also indicate that sustained development of transportation (and other) infrastructure in Africa, as well as support for good governance in the DRC may prove key to the continued stability of DRC cobalt mine supplies.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.resourpol.2022.103007","usgsCitation":"Gulley, A.L., 2022, One hundred years of cobalt production in the Democratic Republic of the Congo: Resources Policy, v. 79, 103007, 10 p., https://doi.org/10.1016/j.resourpol.2022.103007.","productDescription":"103007, 10 p.","ipdsId":"IP-140472","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":467159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.resourpol.2022.103007","text":"Publisher Index Page"},{"id":409584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Democratic Republic of the Congo","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[30.83386,3.50917],[30.77335,2.33988],[31.17415,2.20447],[30.85267,1.8494],[30.46851,1.58381],[30.08615,1.06231],[29.87578,0.59738],[29.8195,-0.20531],[29.58784,-0.58741],[29.57947,-1.34131],[29.29189,-1.62006],[29.25483,-2.21511],[29.11748,-2.29221],[29.02493,-2.83926],[29.27638,-3.29391],[29.34,-4.49998],[29.51999,-5.41998],[29.41999,-5.94],[29.62003,-6.52002],[30.2,-7.07998],[30.74002,-8.34001],[30.34609,-8.23826],[29.00291,-8.40703],[28.73487,-8.52656],[28.44987,-9.16492],[28.67368,-9.60592],[28.49607,-10.78988],[28.37225,-11.79365],[28.64242,-11.97157],[29.34155,-12.36074],[29.616,-12.17889],[29.69961,-13.25723],[28.93429,-13.24896],[28.52356,-12.6986],[28.15511,-12.27248],[27.3888,-12.13275],[27.16442,-11.60875],[26.55309,-11.92444],[25.75231,-11.78497],[25.41812,-11.33094],[24.78317,-11.23869],[24.31452,-11.26283],[24.25716,-10.95199],[23.91222,-10.92683],[23.45679,-10.86786],[22.83735,-11.01762],[22.4028,-10.99308],[22.15527,-11.0848],[22.20875,-9.8948],[21.87518,-9.52371],[21.8018,-8.90871],[21.94913,-8.3059],[21.74646,-7.92008],[21.72811,-7.29087],[20.51475,-7.29961],[20.60182,-6.93932],[20.09162,-6.94309],[20.03772,-7.11636],[19.4175,-7.15543],[19.16661,-7.73818],[19.01675,-7.98825],[18.46418,-7.84701],[18.13422,-7.98768],[17.47297,-8.06855],[17.09,-7.54569],[16.86019,-7.2223],[16.57318,-6.62264],[16.32653,-5.87747],[13.3756,-5.86424],[13.02487,-5.98439],[12.73517,-5.96568],[12.32243,-6.10009],[12.18234,-5.78993],[12.43669,-5.6843],[12.468,-5.24836],[12.63161,-4.99127],[12.99552,-4.7811],[13.25824,-4.88296],[13.60023,-4.50014],[14.14496,-4.51001],[14.20903,-4.79309],[14.5826,-4.97024],[15.17099,-4.34351],[15.75354,-3.85516],[16.00629,-3.53513],[15.9728,-2.71239],[16.40709,-1.74093],[16.86531,-1.22582],[17.52372,-0.74383],[17.63864,-0.42483],[17.66355,-0.05808],[17.82654,0.28892],[17.77419,0.85566],[17.89884,1.74183],[18.09428,2.36572],[18.39379,2.90044],[18.45307,3.50439],[18.54298,4.20179],[18.93231,4.70951],[19.46778,5.03153],[20.29068,4.69168],[20.92759,4.32279],[21.65912,4.22434],[22.40512,4.02916],[22.70412,4.63305],[22.84148,4.71013],[23.29721,4.60969],[24.41053,5.10878],[24.80503,4.89725],[25.12883,4.92724],[25.2788,5.17041],[25.65046,5.25609],[26.40276,5.15087],[27.04407,5.12785],[27.37423,5.23394],[27.97998,4.40841],[28.42899,4.28715],[28.69668,4.45508],[29.15908,4.38927],[29.716,4.6008],[29.9535,4.1737],[30.83386,3.50917]]]},\"properties\":{\"name\":\"Democratic Republic of the Congo\"}}]}","volume":"79","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gulley, Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":857494,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237116,"text":"ofr20221079 - 2022 - Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15","interactions":[],"lastModifiedDate":"2026-03-30T20:33:32.538431","indexId":"ofr20221079","displayToPublicDate":"2022-10-03T06:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1079","displayTitle":"Evaluation of the Bushy Park Reservoir Three-Dimensional Hydrodynamic and Water-Quality Model, South Carolina, 2012–15","title":"Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15","docAbstract":"

The Bushy Park Reservoir is a relatively shallow impoundment in southeastern South Carolina. The reservoir, located under a semi-tropical climate, is the principal water supply for the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there was an adequate supply of freshwater in the reservoir in 2022, water-quality concerns are present over taste-and-odor and saltwater-intrusion issues. From 2013 to 2015, the U.S. Geological Survey (USGS), in cooperation with the Charleston Water System, engaged in a multi-year study of the hydrology and hydrodynamics of Bushy Park Reservoir to better understand factors affecting water-quality conditions in the reservoir. As part of this study, Charleston Water System worked with Tetra Tech, Inc., a consulting and engineering firm, to develop a Bushy Park Reservoir hydrodynamic and water-quality modeling framework, built upon earlier efforts by both Tetra Tech and the U.S. Army Corps of Engineers. At the completion of the new modeling framework, the USGS was requested to evaluate the calibrated hydrodynamic and water-quality model.

The Bushy Park Reservoir Environmental Fluid Dynamics Code (EFDC) model was calibrated for the time period from January 1, 2012, to December 31, 2015. The general modeling approach for the newly revised modeling framework, as briefly detailed in this report, was developed with EFDC. The EFDC is a grid-based modeling package that can simulate three-dimensional flow, transport, and water quality in surface-water systems. This report evaluated the capacity of Tetra Tech’s Bushy Park EFDC model to simulate water discharge, water circulation, surface elevations, temperature, salinity, and other water-quality parameters.

The USGS model review focused specifically on the following criteria: (1) determine if the model, with additional effort, could be developed into an adequate planning tool for Bushy Park Reservoir; (2) assess the capacity of the model to specifically address water-quality issues in the reservoir related to taste-and-odor and saltwater intrusions; and, (3) evaluate three preliminary water-management scenarios related to reduced water withdrawals in the reservoir and the effect on saltwater intrusion.

Overall, the model was able to simulate discharge, flow velocity, and water-surface elevations with generally good agreement between the simulated and measured values. Specifically, the model was able to demonstrate good agreement for discharge at two USGS continuous discharge locations (USGS station 02172002; USGS station 02172040), with Wilmott index of agreements of 0.86 and 0.75, respectively. A total of seven USGS streamgages, located on the West Branch of the Cooper River, Durham Canal, and the Cooper River, were available for water-surface elevations, with index of agreements ranging from 0.74 to 0.99. However, model-simulated water-surface elevation ranges were appreciably high (compared to measured ranges) for two locations near Pinopolis Dam, farthest upstream on the West Branch of the Cooper River. This result may indicate that too much simulated tidal energy propagated through the model domain.

For water temperature, 16 calibration stations were available for at least part of the 4-year simulation. The index of agreement range for temperature comparisons was from 0.95 to 1.00, indicating excellent agreement between the measured and simulated results. One of the primary future applications for the Bushy Park Reservoir EFDC model is to determine the extent of saltwater intrusions. A wide range in the salinity prediction quality was simulated with the model. The prediction quality ranged from an index of agreement of 0.15 at Cooper River approximately 2.75 miles southeast of the Tee, South Carolina, to 0.92 at West Branch Cooper River near Moncks Corner, South Carolina. Although the model did not accurately simulate some of the larger salinity deviations resulting during individual hydrologic events, the seasonal salinity trends were adequately simulated with the model during the study period (2012–15). Therefore, it may be difficult to simulate extreme hydrologic events, such as during large storms, where high salinity water is exchanged with Bushy Park Reservoir. There was agreement in model simulation with the measured data either on the quantitative index of agreement values or qualitative agreement in the seasonal salinity data trends.

For water quality, the index of agreement values were generally low for total nitrogen, ammonia, nitrate, total Kjeldahl nitrogen, total phosphorus, and orthophosphate. Although general trends were adequately simulated at specific stations, particularly for Bushy Park Reservoir, the model-simulated fit was low across all the constituents described above with index of agreements usually below 0.50. A limitation for simulating nutrient concentrations across the model domain was the lack of characterization for the constituents directly entering Bushy Park Reservoir, or the lack of data directly attributed to the boundary condition (for example, the Cooper River). The other two calibrated water-quality constituents (besides the nutrients mentioned above) were dissolved oxygen and chlorophyll a. Dissolved oxygen varied from index of agreement values from 0.58 to 0.94 for 11 stations, generally indicating agreement with the available measured data. Chlorophyll a, calibrated for seven stations, had a wider range from 0.11 to 0.74 for the index of agreement.

With the current modeling framework, taste-and-odor events, related to cyanobacterial blooms, cannot be directly simulated. However, indirect estimates of cyanobacteria concentrations may be obtained by using the chlorophyll a model outputs, which represent total phytoplankton biomass, and the phytoplankton biovolume data by group (diatoms, green algae, cyanobacteria and others) collected from 2012 to 2015. For the Bushy Park Reservoir modeling framework to be used directly for taste-and-odor issues, cyanobacteria must be simulated and calibrated based on observations of cyanobacteria biomass concentrations. In addition to the cyanobacteria sampling conducted within the reservoir between 2012 and 2015, the new model calibration would also require new algae biomass data-collection efforts to characterize the external sources of cyanobacteria entering the Bushy Park Reservoir from tributaries, as well as the internal cycling, production, and decay of cyanobacteria in the hydrologic system.

Further improvements to the EFDC model would include expanding the collection of boundary condition datasets, such as water-quality monitoring to determine improved nutrient loads into the model domain. Along with improved water-quality monitoring for the major boundary conditions, continuous discharge, for both Foster Creek and the Back River, would further constrain the flow balance and the loads into Bushy Park Reservoir. In addition to better boundary-condition characterization, it is important to better characterize possible shortcomings specifically to the model domain, such as the grid resolution, bathymetry, and numerical hydrodynamic errors. Further consideration of the model may involve a sensitivity analysis to determine if errors in the simulation outputs, such as discharge, water-surface elevations, and salinity, were more likely caused by poor boundary condition characterization or, specifically, the model setup.

Three model scenarios were run with the revised Bushy Park Reservoir model: (1) reduced withdrawals from one of the large intake-discharge locations for Bushy Park Reservoir, the Williams Station; (2) elevated (above background levels) ocean water level causing saltwater intrusion from the ocean through Durham Canal into Bushy Park Reservoir; and (3) overtopping of the Back River Dam at the southernmost end of Bushy Park Reservoir. For the reduced withdrawals scenarios, the largest shift in flow resulted near the Williams Station intake, with the next largest flow change at the southern end of Bushy Park Reservoir, and a net increase in flow out of the Bushy Park Reservoir to the Cooper River by way of the Durham Canal. The effect resulting from scenario 3 on water quality and salinity was small, with larger increases for dissolved oxygen than other constituents at several monitoring stations. For the two scenarios related to saltwater intrusion (including dam overtopping), the changes in salinity generally were found to dissipate in the following 2 weeks and generally back to baseline salinity conditions within 3 months. This result did vary depending on the severity of the storm or length of the dam overtopping event.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221079","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Smith, E.A., Akasapu-Smith, M., Petkewich, M.D., and Conrads, P.A., 2022, Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15: U.S. Geological Survey Open-File Report 2022–1079, 35 p., https://doi.org/10.3133/ofr20221079.","productDescription":"Report: ix, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087955","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501828,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113612.htm","linkFileType":{"id":5,"text":"html"}},{"id":407629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1079/coverthb.jpg"},{"id":407630,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1079/ofr20221079.pdf","text":"Report","size":"5.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1079"},{"id":407632,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1079/ofr20221079.XML"},{"id":407633,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1079/images/"},{"id":407634,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NG4NVX","text":"USGS data release","linkHelpText":"Water quality data for Bushy Park Reservoir, South Carolina 2013–2015"},{"id":407631,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1079"}],"country":"United States","state":"South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.39794921875,\n 32.676372772089806\n ],\n [\n -79.661865234375,\n 32.676372772089806\n ],\n [\n -79.661865234375,\n 33.458942753687616\n ],\n [\n -80.39794921875,\n 33.458942753687616\n ],\n [\n -80.39794921875,\n 32.676372772089806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road, Suite 129
Columbia, SC 29210

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-10-03","noUsgsAuthors":false,"publicationDate":"2022-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Erik A. 0000-0001-8434-0798 easmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":1405,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","email":"easmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akasapu-Smith, Madhu","contributorId":297121,"corporation":false,"usgs":false,"family":"Akasapu-Smith","given":"Madhu","email":"","affiliations":[{"id":16286,"text":"Tetra Tech","active":true,"usgs":false}],"preferred":false,"id":853379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul A. 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":198982,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853381,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237254,"text":"70237254 - 2022 - Barrier islands influence the assimilation of terrestrial energy in nearshore fishes","interactions":[],"lastModifiedDate":"2023-03-24T16:26:50.745968","indexId":"70237254","displayToPublicDate":"2022-10-03T06:35:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12614,"text":"Estuarine, Costal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Barrier islands influence the assimilation of terrestrial energy in nearshore fishes","docAbstract":"

We examined the relative importance of landscape features on estuarine fish trophic structure and dependence on terrestrial organic matter (OMterr) in four barrier island lagoon systems along the Alaskan Beaufort Sea coast. Our study compared two relatively large lagoon systems characterized by high river discharge and relatively free ocean water exchanges (central region near Prudhoe Bay, Alaska) with two highly protected lagoons characterized by low river discharge and limited exchange with ocean waters (eastern region near Kaktovik, Alaska). We hypothesized that freshwater discharge would be a strong determinant of food web structure for both resident marine and diadromous fishes if more discharge increases availability of OMterr relative to lagoons with limited or no river inputs. To consider differences in trophic characteristics in fishes between study regions, we estimated community-wide measures of trophic structure (hereafter, community metrics) and the relative use of OMterr from mixing models using stable isotope composition (δ13C and δ15N; muscle tissue) among 12 species and identified the influences of region and body size. Fish captured in lagoons well protected by barrier islands had more distinct and diverse isotopic niches relative to those in more exposed lagoons based on community metrics. The use of OMterr by nearshore fishes in both regions was substantial and was >50% for diadromous species. Between regions, OMterr use differed in 6 of the 8 species considered but was not consistently higher in one region. The relative importance of OMterr varied with fish size in 7 of 10 species considered, with more OMterr used by smaller individuals. This work highlights the importance of OMterr to Arctic fishes and fisheries, some of which are of subsistence importance, even when feeding grounds are primarily marine. We propose that landscape features, particularly barrier islands, play an important role in structuring nearshore food webs. Barrier islands may provide a previously undocumented ecosystem service of increasing food web complexity, which may promote system resilience.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2022.108094","usgsCitation":"Stanek, A.E., von Biela, V.R., Laske, S.M., Taylor, R.L., and Dunton, K., 2022, Barrier islands influence the assimilation of terrestrial energy in nearshore fishes: Estuarine, Costal and Shelf Science, v. 278, 108094, 12 p., https://doi.org/10.1016/j.ecss.2022.108094.","productDescription":"108094, 12 p.","ipdsId":"IP-137604","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":446244,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2022.108094","text":"Publisher Index Page"},{"id":435669,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DAFMJD","text":"USGS data release","linkHelpText":"Nearshore Fish Isotope Values, Beaufort Sea, Alaska, 2017-2019"},{"id":407949,"rank":1,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.21484375,\n 68.75231494434473\n ],\n [\n -141.1083984375,\n 68.75231494434473\n ],\n [\n -141.1083984375,\n 71.91088787611527\n ],\n [\n -155.21484375,\n 71.91088787611527\n ],\n [\n -155.21484375,\n 68.75231494434473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"278","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanek, Ashley E. 0000-0001-5184-2126","orcid":"https://orcid.org/0000-0001-5184-2126","contributorId":290682,"corporation":false,"usgs":true,"family":"Stanek","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":853856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":853857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","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":853858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":853859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunton, Kenneth H.","contributorId":171775,"corporation":false,"usgs":false,"family":"Dunton","given":"Kenneth H.","affiliations":[],"preferred":false,"id":853860,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262263,"text":"70262263 - 2022 - Small anthropogenic landforms from past charcoal production control moisture dynamics and chemistry in northcentral Appalachian soils","interactions":[],"lastModifiedDate":"2025-01-17T16:53:38.4344","indexId":"70262263","displayToPublicDate":"2022-10-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Small anthropogenic landforms from past charcoal production control moisture dynamics and chemistry in northcentral Appalachian soils","docAbstract":"Throughout the northeastern United States (U.S.) and Europe, relict charcoal hearths (RCHs) are regularly being discovered in proximity to furnaces once used for the extraction of metal from ore or quick-lime production; charcoal produced in hearths was used as a furnace fuel. Given previous research has shown that topographic and subsurface disturbance can be great when a hearth is constructed, we hypothesize that hearth construction alters surface hydrology and soil chemistry in environments in and near hearths. We used a landscape classification process to identify 6,758 hearths near furnaces at Greenwood and Pine Grove Furnace State Park, central and southcentral Pennsylvania, U.S. Two types of digital elevation model wetness indexes were used to quantify surface hydrology effects in and around hearths. Modeled wetness conditions were compared to field soil volumetric water content in RCHs near Greenwood Furnace State Park. Modeled wetness indexes indicate that RCH interiors are significantly wetter than RCH rim areas; RCHs are acting as a landscape moisture sink. Results also indicate that RCHs on slopes result in downslope drier conditions below RCHs. Field measured volumetric water content indicates that as distance from the center of the hearth increases, soil moisture significantly decreases. Geomorphic position was found to not be related to RCH wetness. Soil from RCHs, compared to nearby native soils, has significantly higher total C, a lower Mehlich 3 extractable acidity, higher Ca and P. No trend was evident with RCH soil chemistry and geomorphic position. The high frequency of RCH occurrence, in proximity to the furnace’s RCHs supported, suggests that RCHs today could locally be an important niche for understory flora and fauna. Further research could explore how RCHs might be affecting surrounding plant populations and how within RCH patterns, especially on hillslopes, might represent a distinctly different scale of physical and chemical variability.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2022.108379","usgsCitation":"Bayuzick, S., Guarin, D., Bonhage, A., Hirsch, F., Diefenbach, D.R., McDill, M., Raab, T., and Drohan, P., 2022, Small anthropogenic landforms from past charcoal production control moisture dynamics and chemistry in northcentral Appalachian soils: Geomorphology, v. 415, 108379, 11 p., https://doi.org/10.1016/j.geomorph.2022.108379.","productDescription":"108379, 11 p.","ipdsId":"IP-143732","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2022.108379","text":"Publisher Index Page"},{"id":480751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Greenwood Furnace State Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.96106385041638,\n 40.65430370223336\n ],\n [\n -77.96106385041638,\n 40.5738214187607\n ],\n [\n -77.78470131822338,\n 40.5738214187607\n ],\n [\n -77.78470131822338,\n 40.65430370223336\n ],\n [\n -77.96106385041638,\n 40.65430370223336\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"415","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bayuzick, S.","contributorId":348658,"corporation":false,"usgs":false,"family":"Bayuzick","given":"S.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guarin, D.","contributorId":348662,"corporation":false,"usgs":false,"family":"Guarin","given":"D.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonhage, A.","contributorId":348664,"corporation":false,"usgs":false,"family":"Bonhage","given":"A.","affiliations":[{"id":83395,"text":"Brandenburg University of Technology","active":true,"usgs":false}],"preferred":false,"id":923686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, F.","contributorId":348665,"corporation":false,"usgs":false,"family":"Hirsch","given":"F.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDill, M.","contributorId":348666,"corporation":false,"usgs":false,"family":"McDill","given":"M.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Raab, T.","contributorId":348667,"corporation":false,"usgs":false,"family":"Raab","given":"T.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923690,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drohan, P.J.","contributorId":348668,"corporation":false,"usgs":false,"family":"Drohan","given":"P.J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923691,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70247393,"text":"70247393 - 2022 - Waveform signatures of earthquakes located close to the subducted Gorda Plate interface","interactions":[],"lastModifiedDate":"2024-09-16T10:52:41.577713","indexId":"70247393","displayToPublicDate":"2022-10-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Waveform signatures of earthquakes located close to the subducted Gorda Plate interface","docAbstract":"

Complex seismic velocity structure near the earthquake source can affect rupture dynamics and strongly modify the seismic waveforms recorded near the fault. Fault‐zone waves are commonly observed in continental crustal settings but are less clear in subduction zones due to the spatial separation between seismic stations and the plate boundary fault. We observed anomalously long duration S waves from earthquake clusters located near the interface of the subducted Gorda plate north of the Mendocino triple junction. In contrast, earthquakes located just a few kilometers below each cluster show impulsive S waves. A nodal array experiment was conducted around the Northern California Seismic Network station KCT for two months to investigate the origin of the complex S waves. Beamforming analysis shows that the S waves contain three arrivals that have different horizontal slownesses, which we term S1, S2, and S coda. Similar analysis on P waves also show two arrivals with different horizontal slownesses, which we term P1 and P2. P1 and S1 have larger horizontal slowness than P2 and S2, respectively, indicating that the phase pairs are body waves with different ray paths. Building upon a seismic refraction profile, we construct 1D velocity models and test different thicknesses and VP/VS ratios for the subducted oceanic crust. The arrival times and relative slownesses of P1/P2 and S1/S2 phases indicate that they are the direct and the Moho reflected phases, respectively. Their properties are consistent with a crustal thickness of ∼6 km and a moderate VP/VS ratio (∼1.8). The S coda is more difficult to characterize but has a clear dominant frequency that likely reflects the near‐source velocity and attenuation structure. Our study indicates that waveforms from earthquakes near the interface of the subducted slab can be used to infer detailed structural information about the plate‐boundary zone at seismogenic depths.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210261","usgsCitation":"Gong, J., and McGuire, J.J., 2022, Waveform signatures of earthquakes located close to the subducted Gorda Plate interface: Bulletin of the Seismological Society of America, v. 112, no. 5, p. 2440-2453, https://doi.org/10.1785/0120210261.","productDescription":"14 p.","startPage":"2440","endPage":"2453","ipdsId":"IP-133636","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Gorda Plate interface","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124,\n 41\n ],\n [\n -125.5,\n 41\n ],\n [\n -125.5,\n 40\n ],\n [\n -124,\n 40\n ],\n [\n -124,\n 41\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"112","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gong, Jianhua","contributorId":317847,"corporation":false,"usgs":false,"family":"Gong","given":"Jianhua","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":879443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":220939,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879444,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70247723,"text":"70247723 - 2022 - Limits to coseismic landslides triggered by Cascadia Subduction Zone earthquakes","interactions":[],"lastModifiedDate":"2023-08-15T14:51:21.183298","indexId":"70247723","displayToPublicDate":"2022-10-02T09:47:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Limits to coseismic landslides triggered by Cascadia Subduction Zone earthquakes","docAbstract":"

Landslides are a significant hazard and dominant feature throughout the landscape of the Pacific Northwest. However, the hazard and risk posed by coseismic landslides triggered by great Cascadia Subduction Zone (CSZ) earthquakes is highly uncertain due to a lack of local and global data. Despite a wealth of other geologic evidence for past earthquakes on the Cascadia Subduction Zone, no landslides have been definitively linked to such earthquakes, even in areas otherwise highly susceptible to failure. While shallow landslides may not leave a lasting topographical signature in the landscape, there are thousands of deep-seated landslides in Cascadia, and these deposits often persist for hundreds of years and multiple earthquake cycles. Synthesizing newly developed inventories of dated large deep-seated landslides in the Oregon Coast Range, we use statistical methods to estimate the proportion of these types of landslides that could have been triggered during past great Cascadia Subduction Zone earthquakes. Statistical analysis of high-precision dendrochronology ages of landslide-dammed lakes and surface roughness-dated bedrock landslides reveal Cascadia Subduction Zone earthquakes may have triggered 0–15 % of large deep-seated landslides in the Oregon Coast Range over multiple earthquake cycles. Our results refine estimates from previous studies and further suggest that coseismic triggering accounts for a small fraction of the total deep-seated bedrock landslides mapped in coastal Cascadia. However, if the real rate of coseismic landslide triggering during CSZ earthquakes is near our estimated upper bound for the 1700 CSZ earthquake, we estimate up to 2400 coseismic large deep-seated landslides could occur in the Oregon Coast Range in a single earthquake. These findings suggest Cascadia is consistent with global observations from other subduction zones and that coseismic landslides may still represent a serious geohazard in the region.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2022.108477","usgsCitation":"Grant, A.R., Struble, W., and LaHusen, S.R., 2022, Limits to coseismic landslides triggered by Cascadia Subduction Zone earthquakes: Geomorphology, v. 418, 108477, 9 p., https://doi.org/10.1016/j.geomorph.2022.108477.","productDescription":"108477, 9 p.","ipdsId":"IP-135543","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":419819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.28385322714739,\n 46.162939083720374\n ],\n [\n -124.07715534899053,\n 46.16100010342029\n ],\n [\n -124.77236586647153,\n 42.306995247191736\n ],\n [\n -122.40618418763233,\n 42.306995247191736\n ],\n [\n -122.28385322714739,\n 46.162939083720374\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"418","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struble, William 0000-0002-8163-5088","orcid":"https://orcid.org/0000-0002-8163-5088","contributorId":241913,"corporation":false,"usgs":false,"family":"Struble","given":"William","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":880167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaHusen, Sean Richard 0000-0003-4246-4439","orcid":"https://orcid.org/0000-0003-4246-4439","contributorId":294677,"corporation":false,"usgs":true,"family":"LaHusen","given":"Sean","email":"","middleInitial":"Richard","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":880168,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237667,"text":"70237667 - 2022 - Climate and land use driven ecosystem homogenization in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2022-10-18T14:46:34.062232","indexId":"70237667","displayToPublicDate":"2022-10-02T09:39:53","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":"Climate and land use driven ecosystem homogenization in the Prairie Pothole Region","docAbstract":"

The homogenization of freshwater ecosystems and their biological communities has emerged as a prevalent and concerning phenomenon because of the loss of ecosystem multifunctionality. The millions of prairie-pothole wetlands scattered across the Prairie Pothole Region (hereafter PPR) provide critical ecosystem functions at local, regional, and continental scales. However, an estimated loss of 50% of historical wetlands and the widespread conversion of grasslands to cropland make the PPR a heavily modified landscape. Therefore, it is essential to understand the current and potential future stressors affecting prairie-pothole wetland ecosystems in order to conserve and restore their functions. Here, we describe a conceptual model that illustrates how (a) historical wetland losses, (b) anthropogenic landscape modifications, and (c) climate change interact and have altered the variability among remaining depressional wetland ecosystems (i.e., ecosystem homogenization) in the PPR. We reviewed the existing literature to provide examples of wetland ecosystem homogenization, provide implications for wetland management, and identify informational gaps that require further study. We found evidence for spatial, hydrological, chemical, and biological homogenization of prairie-pothole wetlands. Our findings indicate that the maintenance of wetland ecosystem multifunctionality is dependent on the preservation and restoration of heterogenous wetland complexes, especially the restoration of small wetland basins.

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