{"pageNumber":"280","pageRowStart":"6975","pageSize":"25","recordCount":165309,"records":[{"id":70241818,"text":"70241818 - 2023 - Salvage using electrofishing methods caused minimal mortality of burrowed and emerged larval lampreys in dewatered habitats","interactions":[],"lastModifiedDate":"2024-01-24T17:12:18.488436","indexId":"70241818","displayToPublicDate":"2023-03-18T06:36:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Salvage using electrofishing methods caused minimal mortality of burrowed and emerged larval lampreys in dewatered habitats","docAbstract":"

Objective

Human-induced dewatering of freshwater habitats causes mortality of larval lampreys (family Petromyzontidae). Salvage by electrofishing at dewatering events is assumed to reduce this mortality, but to our knowledge this assumption remains unassessed.

Methods

We estimated mortality of salvaged larval lampreys (Lampetra spp. and Pacific Lamprey Entosphenus tridentatus) within 24 h following collection at field dewatering events in July and October. To assess when salvage may reduce mortality, we compared mortality of salvaged individuals from field dewatering events to mortality of burrowed and emerged individuals in dewatered habitats in the laboratory. Salvage protocols included electrofishing and foot pressure from walking in test enclosures before and after dewatering. Electrofishing after dewatering (“dry shocking”) involves positioning probes on moist sediment to entice burrowed larval lampreys to emerge.

Result

During the July salvage, air temperature averaged 36°C, bottom water temperature averaged 20°C, and many emerged larval lampreys were dead on the sediment surface. During two October events, air temperatures averaged 18 and 11°C, bottom water temperatures averaged 12 and 7°C, and only one dead emerged larval lamprey was observed. Estimated mortality of salvaged larval lampreys was 0.20 (90% credible interval = 0.09–0.37) in July and 0.00 (90% credible interval = 0.00–0.06) and 0.06 (90% credible interval = 0.01–0.18) in October. All larval lampreys that remained burrowed and were excavated from enclosures after salvage were dead in July but alive in October. Logistic regression suggested that mortality declined with increasing larval length. Mortality of salvaged 80-mm larval lampreys in October was lower than that of 80-mm individuals emerged for 1 h or burrowed for 8 h at similar water temperatures (8–10°C) in the laboratory.

Conclusion

In this study, electrofishing for salvage caused minimal mortality of burrowed and emerged larval lampreys in dewatered habitats. Thus, salvage using electrofishing methods could aid conservation of native lampreys by reducing mortality associated with human-induced dewatering events, especially when temperatures are elevated.

","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10894","usgsCitation":"Harris, J.E., Liedtke, T.L., Skalicky, J.J., and Weiland, L.K., 2023, Salvage using electrofishing methods caused minimal mortality of burrowed and emerged larval lampreys in dewatered habitats: North American Journal of Fisheries Management, v. 43, no. 6, p. 1553-1566, https://doi.org/10.1002/nafm.10894.","productDescription":"14 p.","startPage":"1553","endPage":"1566","ipdsId":"IP-142268","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":498005,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10894","text":"Publisher Index Page"},{"id":414806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.80504720443415,\n 45.59714982675632\n ],\n [\n -119.80504720443415,\n 47.017425415416\n ],\n [\n -122.92684344647026,\n 47.017425415416\n ],\n [\n -122.92684344647026,\n 45.59714982675632\n ],\n [\n -119.80504720443415,\n 45.59714982675632\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Julianne E. 0000-0003-1343-5911","orcid":"https://orcid.org/0000-0003-1343-5911","contributorId":247527,"corporation":false,"usgs":false,"family":"Harris","given":"Julianne","email":"","middleInitial":"E.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":867819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":867820,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joseph J. 0000-0002-6467-5037","orcid":"https://orcid.org/0000-0002-6467-5037","contributorId":247528,"corporation":false,"usgs":false,"family":"Skalicky","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":867821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiland, Lisa K. 0000-0002-9729-4062 lweiland@usgs.gov","orcid":"https://orcid.org/0000-0002-9729-4062","contributorId":3565,"corporation":false,"usgs":true,"family":"Weiland","given":"Lisa","email":"lweiland@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":867822,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243534,"text":"70243534 - 2023 - Uses of epistemic uncertainties in the USGS National Seismic Hazard Models","interactions":[],"lastModifiedDate":"2023-05-16T18:21:23.693721","indexId":"70243534","displayToPublicDate":"2023-03-18T06:34:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Uses of epistemic uncertainties in the USGS National Seismic Hazard Models","docAbstract":"
The need for US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) to report estimates of epistemic uncertainties in the hazard (e.g. fractile hazard curves) in all forthcoming releases is increasing. With fractile hazard curves as potential new outputs from the USGS 2023 NSHM, a simultaneous need is to help end-users better understand these epistemic uncertainties and clarify their potential uses. In this article, we address the latter need by (1) characterizing epistemic uncertainties in two updates of the USGS NSHM (2014 for California and 2021 for Hawaii), (2) illustrating a variety of downstream applications of fractile hazard curves in both hazard and risk contexts, and (3) discussing implications from the various types of uncertainties. We found that the epistemic uncertainty in hazard is generally larger for Hawaii than for California, the epistemic uncertainty in hazard can be reasonably approximated with a lognormal distribution for most of the cases considered, and the correlation between epistemic uncertainty in hazard at two different intensity measure levels generally varies with both location and type of intensity measure. Furthermore, we developed models for readily generating approximate fractile hazard curves in California and Hawaii. Finally, given the complexities involved in the hazard modeling process, we developed an open-source interactive tool to enable a broad range of users to independently examine and potentially start using such epistemic uncertainties for their respective applications.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930231157424","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2023, Uses of epistemic uncertainties in the USGS National Seismic Hazard Models: Earthquake Spectra, v. 39, no. 2, p. 1058-1087, https://doi.org/10.1177/87552930231157424.","productDescription":"30 p.","startPage":"1058","endPage":"1087","ipdsId":"IP-146101","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":490039,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930231157424","text":"Publisher Index Page"},{"id":416950,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417104,"rank":2,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9N5QTIN","linkFileType":{"id":5,"text":"html"}}],"volume":"39","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872251,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241101,"text":"sir20235017 - 2023 - Per- and polyfluoroalkyl substances in groundwater from the Great Miami buried-valley aquifer, southwestern Ohio, 2019–20","interactions":[],"lastModifiedDate":"2026-03-02T22:05:38.701036","indexId":"sir20235017","displayToPublicDate":"2023-03-17T12:59:48","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5017","displayTitle":"Per- and Polyfluoroalkyl Substances in Groundwater from the Great Miami Buried-Valley Aquifer, Southwestern Ohio, 2019–20","title":"Per- and polyfluoroalkyl substances in groundwater from the Great Miami buried-valley aquifer, southwestern Ohio, 2019–20","docAbstract":"

Groundwater samples were collected during 2019 and 2020 from 23 wells in the Great Miami buried-valley aquifer (GM-BVA) in southwestern Ohio by the U.S. Geological Survey, in cooperation with the Miami Conservancy District, Dayton, Ohio, to determine concentrations of selected per- and polyfluoroalkyl substances (PFAS). The GM-BVA is a glacial outwash and alluvial fill aquifer that is the sole source of water supply for much of the region. Wells had total depths that ranged from 21 to 101 feet below land surface, and groundwater levels that ranged from 1.39 to 52.15 feet below land surface before sampling in 2019.

Groundwater and related quality-control samples were sequentially collected from 22 of the 23 wells and analyzed for 24 different PFAS by 2 methods that used proprietary isotope-dilution based adaptations of U.S. Environmental Protection Agency (EPA) method 537.1, termed methods 1 and 2. Method 2 had smaller reporting limits (RL) for 22 of 24 PFAS analyzed and smaller detection limits (DLs) for all 24 PFAS analyzed compared with method 1, which made method 2 more sensitive to detect PFAS.

Concentrations of perfluorooctanesulfonate (PFOS) in a groundwater (GW)-method 2 sample from well CL–275 of 1.9 nanograms per liter (ng/L) and perfluorooctanoate (PFOA) in a GW-method 2 sample from well BU–1106 of 2.1 ng/L were greater than their EPA interim health advisory guidances for drinking water (as of June 2022) by about 9,500 and 52,500 percent, respectively. The EPA interim health advisory guidances for PFOS (0.02 ng/L) and PFOA (0.004 ng/L) were also 65 and 215 times less, respectively, than the smallest method 2 DLs for PFOS (1.3 ng/L) and PFOA (0.86 ng/L).

Other PFAS were either not detected in GM-BVA groundwater samples or were detected in concentrations less than Ohio action levels or Federal health-risk-based guidance. The most detected PFAS in groundwater was perfluorobutanesulfonate (PFBS), which had concentrations in samples from eight wells that ranged from 1.0 to 8.0 ng/L or from 0.05 to 0.4 percent of its EPA health advisory of 2,000 ng/L for drinking water.

The similarity of PFBS (7.8 ng/L), perfluoropentanesulfonate (PFPeS; 8.1 ng/L), and perfluorohexanesulfonate (PFHxS; 14 ng/L) concentrations yielded from the GW-method 1 sample from well CL–275 on July 9, 2019, to those of PFBS (8.0 ng/L), PFPeS (7.8 ng/L), and PFHxS (16 ng/L) from the paired GW-method 2 sample demonstrated the capability of both methods to reproduce PFAS concentrations that were greater than their respective DLs. Non-detection of these PFAS in follow-up GW-method 1 and sequential replicate (Rep–GW-method 1) samples from CL–275 on April 21, 2020, indicated that the 2019 results represented a transient detection in groundwater.

Eleven of twenty-three wells sampled in 2019 had from 1 to 4 PFAS detected in one or more groundwater samples or in a paired replicate sample: PFBS in 8 wells and 9 samples; PFHxS in 4 wells and 5 samples; and PFPeS, PFOS, perfluorobutanoate, perfluoropentanoate, PFOA, and perfluorooctanesulfonamide in 1 well and 1 sample each. More PFAS were detected in GW-method 2 samples than GW-method 1 samples because method 2 had smaller RLs and DLs. Results indicate benefits from the analysis of paired samples, sequential replicate samples, and other quality-control samples using analytical methods with sensitive RLs and DLs to verify PFAS concentrations in groundwater.

Groundwater-age estimates indicate that water produced from all sampled wells had infiltrated to the water table within the 1947–present (2022) period of PFAS use or environmental presence. Eight wells with detectable PFBS in groundwater from 2019 samples also had groundwater-recharge dates that ranged from 1991 to 2016. Those ages coincided with the possible environmental presence of PFBS as a PFAS byproduct or use as an alternative to PFOS after about 2002. Two wells that had detections of PFHxS in 2019 groundwater samples also had post-2000 groundwater-recharge dates that coincided with the period of use of PFHxS as an alternative to PFOS. Six of nine wells with more than 66-percent of urban land use that was within 0.3 miles of each well, as of 2012, also had 1 to 4 PFAS detected in one of their groundwater samples. Seven of nine wells that produced groundwater in 2019 with an oxic redox category also had one or more PFAS detected in a sample.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235017","collaboration":"Prepared in cooperation with Miami Conservancy District","usgsCitation":"Buszka, P.M., Mailot, B.E., and Mathes, N.A., 2023, Per- and polyfluoroalkyl substances in groundwater from the Great Miami buried-valley aquifer, southwestern Ohio, 2019–20: U.S. Geological Survey Scientific Investigations Report 2023–5017, 71 p., https://doi.org/10.3133/sir20235017.","productDescription":"Report: x, 71 p.; Data Release","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119136","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":413923,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J7H3LB","text":"USGS data release","linkHelpText":"Per- and polyfluoroalkyl substance concentrations, age estimates, redox categories, and related data for groundwater from the Great Miami buried-valley aquifer, southwestern Ohio, 2019–20"},{"id":413918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5017/coverthb.jpg"},{"id":413920,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235017/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5017"},{"id":413921,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5017/sir20235017.XML"},{"id":413922,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5017/images/"},{"id":413919,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5017/sir20235017.pdf","text":"Report","size":"36.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5017"},{"id":500711,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114611.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.8370243365812,\n 39.08165626710482\n ],\n [\n -83.34351797428778,\n 39.08165626710482\n ],\n [\n -83.34351797428778,\n 40.49918868264902\n ],\n [\n -84.8370243365812,\n 40.49918868264902\n ],\n [\n -84.8370243365812,\n 39.08165626710482\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278-1996

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-03-17","noUsgsAuthors":false,"publicationDate":"2023-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Buszka, Paul M. 0000-0001-8218-826X pmbuszka@usgs.gov","orcid":"https://orcid.org/0000-0001-8218-826X","contributorId":1786,"corporation":false,"usgs":true,"family":"Buszka","given":"Paul","email":"pmbuszka@usgs.gov","middleInitial":"M.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mailot, Brian E. 0000-0003-1602-7999 bemailot@usgs.gov","orcid":"https://orcid.org/0000-0003-1602-7999","contributorId":302979,"corporation":false,"usgs":true,"family":"Mailot","given":"Brian","email":"bemailot@usgs.gov","middleInitial":"E.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mathes, Neal A. 0000-0002-0642-0407","orcid":"https://orcid.org/0000-0002-0642-0407","contributorId":302980,"corporation":false,"usgs":true,"family":"Mathes","given":"Neal","email":"","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866085,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252795,"text":"70252795 - 2023 - An assessment of the relation between metal contaminated sediment and freshwater mussel populations in the Big River, Missouri","interactions":[],"lastModifiedDate":"2024-04-05T15:34:21.606254","indexId":"70252795","displayToPublicDate":"2023-03-17T10:32:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of the relation between metal contaminated sediment and freshwater mussel populations in the Big River, Missouri","docAbstract":"

The Big River in southeast Missouri drains the largest historical lead mining area in the United States. Ongoing releases of metal contaminated sediments into this river are well documented and are suspected of suppressing freshwater mussel populations. We characterized the spatial extent of metal contaminated sediments and evaluated its relationship with mussel populations in the Big River. Mussels and sediments were collected at 34 sites with potential metal effects and 3 reference sites. Analysis of sediment samples showed that lead (Pb) and zinc (Zn) concentrations were 1.5 to 65 times greater than background concentrations in the reach extending 168 km downstream from Pb mining releases. Mussel abundance decreased acutely downstream from these releases where sediment Pb concentrations were highest and increased gradually as Pb sediment concentrations attenuated downstream. We compared current species richness with historical survey data from three reference rivers with similar physical habitat characteristics and human effects, but without Pb-contaminated sediment. Big River species richness was on average about one-half that expected based on reference stream populations and was 70–75 % lower in reaches with high median Pb concentrations. Sediment Zn and cadmium, and particularly Pb, had significant negative correlations with species richness and abundance. The association of sediment Pb concentrations with mussel community metrics in otherwise high-quality habitat indicates that Pb toxicity is likely responsible for depressed mussel populations observed within the Big River. We used concentration-response regressions of mussel density verses sediment Pb to determine that the Big River mussel community is adversely affected when sediment Pb concentrations are above 166 ppm, the concentration associated with 50 % decreases in mussel density. Based on this assessment of metals concentrations sediment and mussel fauna, our findings indicate that sediment in approximately 140 km of the Big River with suitable habitat has a toxic effect to mussels.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.162743","usgsCitation":"Roberts, A.D., Besser, J.M., Hundley, J., Mosby, D., Rosenberger, A.E., Bouska, K.L., Simmons, B., McMurray, S.E., Faiman, S., and Lueckenhoff, L., 2023, An assessment of the relation between metal contaminated sediment and freshwater mussel populations in the Big River, Missouri: Science of the Total Environment, v. 876, 162743, 15 p., https://doi.org/10.1016/j.scitotenv.2023.162743.","productDescription":"162743, 15 p.","ipdsId":"IP-138980","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":427520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Big River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.22364511337068,\n 38.57772207145226\n ],\n [\n -91.4690104795392,\n 38.57772207145226\n ],\n [\n -91.4690104795392,\n 37.97217349400049\n ],\n [\n -90.22364511337068,\n 37.97217349400049\n ],\n [\n -90.22364511337068,\n 38.57772207145226\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"876","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Andrew D","contributorId":335385,"corporation":false,"usgs":false,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D","affiliations":[{"id":68344,"text":"U.S. Fish and Wildlife Service (USFWS)","active":true,"usgs":false}],"preferred":false,"id":898244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Besser, John M. 0000-0002-9464-2244 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Simultaneous short-pulse injections of two tracers (sodium bromide [Br–] and fluorescein dye) were made in a losing reach of Snake Creek in Great Basin National Park, Nevada, USA, to evaluate the quantity of stream loss through permeable carbonates that resurfaces at a spring approximately 10 km down drainage. A revised hydrogeologic cross section for a possible flow path of the infiltrated Snake Creek water is presented, and the results may inform water management in the region. First arrival and peak concentration of the two tracers occurred at 9.5 and 12.7 days after injection, respectively. Fracture transport simulations indicate that Br– preferentially diffuses into immobile regions of the aquifer, and this diffusive flux is likely responsible for the major differences in the breakthrough curves. When considering the diffusive tracer flux, total apparent Br– and fluorescein dye recoveries were 16.9–22.1% and 21.7–24.3%, respectively. These findings imply that consideration of diffusive flux and long-term monitoring in fracture-dominated flow may support accurate quantification of tracer recovery. In addition, the apparent power law slopes of the breakthrough tails for both tracers were steeper at early times than have been attributed to heterogeneous advection or channeling in meter-scale tests, but the late-time Br– power law slope becomes less steep than has been attributed to diffusive exchange. These deviations may reflect fracture transport patterns that occur at larger scales.

","language":"English","publisher":"Springer","doi":"10.1007/s10040-023-02619-4","usgsCitation":"Humphrey, C., Gardner, P.M., Spangler, L.E., Nelson, N.C., Toran, L., and Solomon, D.K., 2023, Quantifying stream-loss recovery in a spring using dual-tracer injections in the Snake Creek drainage, Great Basin National Park, Nevada, USA: Hydrogeology Journal, v. 31, p. 1051-1066, https://doi.org/10.1007/s10040-023-02619-4.","productDescription":"16 p.","startPage":"1051","endPage":"1066","ipdsId":"IP-130571","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":444184,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s10040-023-02619-4","text":"Publisher Index Page"},{"id":435409,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GAZX5","text":"USGS data release","linkHelpText":"Data from two tracer investigations in the Snake Creek drainage, Great Basin National Park, White Pine County, Nevada"},{"id":414433,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin National Park, Snake Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.3,\n 38.9583\n ],\n [\n -114.3,\n 38.9\n ],\n [\n -114.033,\n 38.9\n ],\n [\n -114.033,\n 38.9583\n ],\n [\n -114.3,\n 38.9583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2023-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Humphrey, C. Eric 0000-0002-1174-8458","orcid":"https://orcid.org/0000-0002-1174-8458","contributorId":303277,"corporation":false,"usgs":false,"family":"Humphrey","given":"C. Eric","affiliations":[{"id":65744,"text":"University of Utah, Dept. of Geology & Geophysics","active":true,"usgs":false}],"preferred":false,"id":866978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Philip M. 0000-0003-3005-3587 pgardner@usgs.gov","orcid":"https://orcid.org/0000-0003-3005-3587","contributorId":962,"corporation":false,"usgs":true,"family":"Gardner","given":"Philip","email":"pgardner@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spangler, Lawrence E. 0000-0003-3928-8809 spangler@usgs.gov","orcid":"https://orcid.org/0000-0003-3928-8809","contributorId":973,"corporation":false,"usgs":true,"family":"Spangler","given":"Lawrence","email":"spangler@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Nora C. 0000-0001-8248-2004","orcid":"https://orcid.org/0000-0001-8248-2004","contributorId":207229,"corporation":false,"usgs":true,"family":"Nelson","given":"Nora","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toran, Laura","contributorId":81622,"corporation":false,"usgs":false,"family":"Toran","given":"Laura","email":"","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":866982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Solomon, D. Kip","contributorId":201955,"corporation":false,"usgs":false,"family":"Solomon","given":"D.","email":"","middleInitial":"Kip","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":866983,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241820,"text":"70241820 - 2023 - Living with wildfire in Park County, Colorado 2021 data report","interactions":[],"lastModifiedDate":"2023-03-28T12:05:16.612644","indexId":"70241820","displayToPublicDate":"2023-03-17T07:03:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Living with wildfire in Park County, Colorado 2021 data report","docAbstract":"

Wildfire affects many types of communities and is a particular concern for communities in the wildland urban interface (WUI), such as those of Park County, Colorado. The core intent of this project was to provide evidence to support the Platte Canyon Fire Protection District (PCFPD) and Fire Adapted Bailey in their wildfire mitigation and education programming. This report describes wildfire risk data collected in fall 2020 and pairs it with social data collected in the fall and winter of 2020-2021, in order to better understand residents’ knowledge, experiences, and perceptions about wildfire risk in the communities of the Burland Ranchettes Homeowners Association (HOA) area and surrounding neighborhoods. This greater understanding will help PCFPD focus its programs and outreach and ultimately promote increased mitigation and reduced wildfire risk in Park County.

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2023 - Fault roughness at seismogenic depths and links to earthquake behavior","interactions":[],"lastModifiedDate":"2023-03-24T12:01:22.059966","indexId":"70241609","displayToPublicDate":"2023-03-17T06:59:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Fault roughness at seismogenic depths and links to earthquake behavior","docAbstract":"

Fault geometry affects the initiation, propagation, and cessation of earthquake rupture, as well as, potentially, the statistical behavior of earthquake sequences. We analyze 18,250 (−0.27 < M < 4.4) earthquakes of the 2016–2019 Cahuilla, California, swarm and, for the first time, use these high‐resolution earthquake locations to map, in detail, the roughness across an active fault surface at depth. We find that the strike‐slip fault is 50% rougher in the slip‐perpendicular direction than parallel to slip. 3D mapping of fault roughness at seismogenic depths suggests that roughness varies by a factor of 8 for length scales of 1 km. We observe that the largest earthquake (M 4.4) occurred where there is significant fault complexity and the highest measured roughness. We also find that b‐values are weakly positively correlated with fault roughness. Following the largest earthquake, we observe a distinct population of earthquakes with comparatively low b‐values occurring in an area of high roughness within the rupture area of the M 4.4 earthquake. Finally, we measure roughness at multiple scales and find that the fault is self‐affine with a Hurst exponent of 0.52, consistent with a Brownian surface.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320220043","usgsCitation":"Cochran, E.S., Page, M.T., van der Elst, N., Ross, Z.E., and Trugman, D.T., 2023, Fault roughness at seismogenic depths and links to earthquake behavior: The Seismic Record, v. 3, no. 1, p. 37-47, https://doi.org/10.1785/0320220043.","productDescription":"10 p.","startPage":"37","endPage":"47","ipdsId":"IP-147560","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":444188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320220043","text":"Publisher Index Page"},{"id":414691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.17641781318886,\n 34.53155441621385\n ],\n [\n -118.17641781318886,\n 33.29215093390583\n ],\n [\n -115.91420733196797,\n 33.29215093390583\n ],\n [\n -115.91420733196797,\n 34.53155441621385\n ],\n [\n -118.17641781318886,\n 34.53155441621385\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":867481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":867482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":867483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Zachary E.","contributorId":196001,"corporation":false,"usgs":false,"family":"Ross","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":867484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trugman, Daniel T.","contributorId":197011,"corporation":false,"usgs":false,"family":"Trugman","given":"Daniel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":867485,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256528,"text":"70256528 - 2023 - Effects of environment and metacommunity delineation on multiple dimensions of stream fish beta diversity","interactions":[],"lastModifiedDate":"2024-08-21T16:46:56.236543","indexId":"70256528","displayToPublicDate":"2023-03-16T11:43:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Effects of environment and metacommunity delineation on multiple dimensions of stream fish beta diversity","docAbstract":"

Introduction: Beta diversity represents changes in community composition among locations across a landscape. While the effects of human activities on beta diversity are becoming clearer, few studies have considered human effects on the three dimensions of beta diversity: taxonomic, functional, and phylogenetic. Including anthropogenic factors and multiple dimensions of biodiversity may explain additional variation in stream fish beta diversity, providing new insight into how metacommunities are structured within different spatial delineations.

Methods: In this study, we used a 350 site stream fish abundance dataset from South Carolina, United States to quantify beta diversity explainable by spatial, natural environmental, and anthropogenic variables. We investigated three spatial delineations: (1) a single whole-state metacommunity delineated by political boundaries, (2) two metacommunities delineated by a natural geomorphic break separating uplands from lowlands, and (3) four metacommunities delineated by natural watershed boundaries. Within each metacommunity we calculated taxonomic, functional, and phylogenetic beta diversity and used variation partitioning to quantify spatial, natural environmental, and anthropogenic contributions to variations in beta diversity.

Results: We explained 25–81% of the variation in stream fish beta diversity. The importance of these three factors in structuring metacommunities differed among the diversity dimensions, providing complementary perspectives on the processes shaping beta diversity in fish communities. The effect of spatial, natural environmental, and anthropogenic factors varied among the spatial delineations, which indicate conclusions drawn from variation partitioning may depend on the spatial delineation chosen by researchers.

Discussion: Our study highlights the importance of considering human effects on metacommunity structure, quantifying multiple dimensions of beta diversity, and careful consideration of user-defined metacommunity boundaries in beta diversity analyses.

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Carolina\",\"nation\":\"USA \"}}]}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Stocsynski, Lauren","contributorId":341032,"corporation":false,"usgs":false,"family":"Stocsynski","given":"Lauren","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Mark C.","contributorId":341033,"corporation":false,"usgs":false,"family":"Scott","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bower, Luke Max 0000-0002-0739-858X","orcid":"https://orcid.org/0000-0002-0739-858X","contributorId":341034,"corporation":false,"usgs":true,"family":"Bower","given":"Luke","email":"","middleInitial":"Max","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peoples, Brandon K.","contributorId":177551,"corporation":false,"usgs":false,"family":"Peoples","given":"Brandon","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":907833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273471,"text":"70273471 - 2023 - Microscale spatial variations in coseismic temperature rise on hematite fault mirrors in the Wasatch fault damage zone","interactions":[],"lastModifiedDate":"2026-01-15T15:20:05.080663","indexId":"70273471","displayToPublicDate":"2023-03-16T09:11:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Microscale spatial variations in coseismic temperature rise on hematite fault mirrors in the Wasatch fault damage zone","docAbstract":"

Coseismic temperature rise activates fault dynamic weakening that promotes earthquake rupture propagation. The spatial scales over which peak temperatures vary on slip surfaces are challenging to identify in the rock record. We present microstructural observations and electron backscatter diffraction data from three small-displacement hematite-coated fault mirrors (FMs) in the Wasatch fault damage zone, Utah, to evaluate relations between fault properties, strain localization, temperature rise, and weakening mechanisms during FM development. Millimeter- to cm-thick, matrix-supported, hematite-cemented breccia is cut by ∼25–200 μm-thick, texturally heterogeneous veins that form the hematite FM volume (FMV). Grain morphologies and textures vary with FMV thickness over μm to mm lengthscales. Cataclasite grades to ultracataclasite where FMV thickness is greatest. Thinner FMVs and geometric asperities are characterized by particles with subgrains, serrated grain boundaries, and(or) low-strain polygonal grains that increase in size with proximity to the FM surface. Comparison to prior hematite deformation experiments suggests FM temperatures broadly range from ≥400°C to ≥800–1100°C, compatible with observed coeval brittle and plastic deformation mechanisms, over sub-mm scales on individual slip surfaces during seismic slip. We present a model of FM development by episodic hematite precipitation, fault reactivation, and strain localization, where the thickness of hematite veins controls the width of the deforming zones during subsequent fault slip, facilitating temperature rise and thermally activated weakening. Our data document intrasample coseismic temperatures, resultant deformation and dynamic weakening mechanisms, and the length scales over which these vary on slip surfaces.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB025069","usgsCitation":"McDermott, R.G., Ault, A.K., Wetzel, K.F., Evans, J.P., and Shen, F., 2023, Microscale spatial variations in coseismic temperature rise on hematite fault mirrors in the Wasatch fault damage zone: JGR Solid Earth, v. 128, no. 3, e2022JB025069, 20 p., https://doi.org/10.1029/2022JB025069.","productDescription":"e2022JB025069, 20 p.","ipdsId":"IP-142375","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Wasatch fault damage zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.0333,\n 41.425\n ],\n [\n -112.0333,\n 41.366667\n ],\n [\n -111.966667,\n 41.366667\n ],\n [\n -111.966667,\n 41.425\n ],\n [\n -112.0333,\n 41.425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McDermott, Robert Gregory 0000-0002-2550-0322","orcid":"https://orcid.org/0000-0002-2550-0322","contributorId":360810,"corporation":false,"usgs":true,"family":"McDermott","given":"Robert","middleInitial":"Gregory","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ault, Alexis K.","contributorId":365163,"corporation":false,"usgs":false,"family":"Ault","given":"Alexis","middleInitial":"K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":953857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wetzel, Kelsey F.","contributorId":365164,"corporation":false,"usgs":false,"family":"Wetzel","given":"Kelsey","middleInitial":"F.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":953858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, James P.","contributorId":365165,"corporation":false,"usgs":false,"family":"Evans","given":"James","middleInitial":"P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":953859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shen, Fen-Ann","contributorId":365166,"corporation":false,"usgs":false,"family":"Shen","given":"Fen-Ann","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":953860,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248415,"text":"70248415 - 2023 - Increasing hypoxia on global coral reefs under ocean warming","interactions":[],"lastModifiedDate":"2023-09-12T14:09:20.916709","indexId":"70248415","displayToPublicDate":"2023-03-16T09:02:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Increasing hypoxia on global coral reefs under ocean warming","docAbstract":"

Ocean deoxygenation is predicted to threaten marine ecosystems globally. However, current and future oxygen concentrations and the occurrence of hypoxic events on coral reefs remain underexplored. Here, using autonomous sensor data to explore oxygen variability and hypoxia exposure at 32 representative reef sites, we reveal that hypoxia is already pervasive on many reefs. Eighty-four percent of reefs experienced weak to moderate (≤153 µmol O2 kg−1 to ≤92 µmol O2 kg−1) hypoxia and 13% experienced severe (≤61 µmol O2 kg−1) hypoxia. Under different climate change scenarios based on four Shared Socioeconomic Pathways (SSPs), we show that projected ocean warming and deoxygenation will increase the duration, intensity and severity of hypoxia, with more than 94% and 31% of reefs experiencing weak to moderate and severe hypoxia, respectively, by 2100 under SSP5-8.5. This projected oxygen loss could have negative consequences for coral reef taxa due to the key role of oxygen in organism functioning and fitness.

","language":"English","publisher":"Nature","doi":"10.1038/s41558-023-01619-2","usgsCitation":"Pezner, A.K., Courtney, T.A., Barkley, H., Chou, W., Chu, H., Clements, S.M., Cyronak, T., DeGrandpre, M.D., Kekuewa, S.A., Kline, D.I., Liang, Y., Martz, T.R., Mitarai, S., Page, H.N., Rintoul, M.S., Smith, J.E., Soong, K., Takeshita, Y., Tresguerres, M., Wei, Y., Yates, K.K., and Andersson, A.J., 2023, Increasing hypoxia on global coral reefs under ocean warming: Nature Climate Change, v. 13, p. 403-409, https://doi.org/10.1038/s41558-023-01619-2.","productDescription":"7 p.","startPage":"403","endPage":"409","ipdsId":"IP-138099","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467117,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://oist.repo.nii.ac.jp/record/2000571/files/Pezner_MS_edits_clean_coauthors.pdf","text":"External Repository"},{"id":420717,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2023-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pezner, Ariel K. 0000-0002-6076-7049","orcid":"https://orcid.org/0000-0002-6076-7049","contributorId":329646,"corporation":false,"usgs":false,"family":"Pezner","given":"Ariel","email":"","middleInitial":"K.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Courtney, Travis A.","contributorId":218225,"corporation":false,"usgs":false,"family":"Courtney","given":"Travis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":882825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barkley, Hannah","contributorId":329648,"corporation":false,"usgs":false,"family":"Barkley","given":"Hannah","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":882826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chou, Wen-Chen 0000-0002-5107-7978","orcid":"https://orcid.org/0000-0002-5107-7978","contributorId":329650,"corporation":false,"usgs":false,"family":"Chou","given":"Wen-Chen","email":"","affiliations":[{"id":78679,"text":"National Taiwan Ocean University","active":true,"usgs":false}],"preferred":false,"id":882827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chu, Hui-Chuan","contributorId":329651,"corporation":false,"usgs":false,"family":"Chu","given":"Hui-Chuan","email":"","affiliations":[{"id":78679,"text":"National Taiwan Ocean University","active":true,"usgs":false}],"preferred":false,"id":882828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clements, Samanth M. 0000-0003-3094-2173","orcid":"https://orcid.org/0000-0003-3094-2173","contributorId":329652,"corporation":false,"usgs":false,"family":"Clements","given":"Samanth","email":"","middleInitial":"M.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882829,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cyronak, Tyler 0000-0003-3556-7616","orcid":"https://orcid.org/0000-0003-3556-7616","contributorId":329653,"corporation":false,"usgs":false,"family":"Cyronak","given":"Tyler","email":"","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":882830,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DeGrandpre, Michael D.","contributorId":187412,"corporation":false,"usgs":false,"family":"DeGrandpre","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":882831,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kekuewa, Samuel A.H. 0000-0003-0395-2261","orcid":"https://orcid.org/0000-0003-0395-2261","contributorId":329654,"corporation":false,"usgs":false,"family":"Kekuewa","given":"Samuel","email":"","middleInitial":"A.H.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882832,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kline, David I","contributorId":141143,"corporation":false,"usgs":false,"family":"Kline","given":"David","email":"","middleInitial":"I","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":882833,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Liang, Yi-Bei 0000-0002-8622-8596","orcid":"https://orcid.org/0000-0002-8622-8596","contributorId":329656,"corporation":false,"usgs":false,"family":"Liang","given":"Yi-Bei","email":"","affiliations":[{"id":78681,"text":"National Sun Yat-sen University Taiwan","active":true,"usgs":false}],"preferred":false,"id":882834,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Martz, Todd R.","contributorId":199920,"corporation":false,"usgs":false,"family":"Martz","given":"Todd","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":882835,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mitarai, Satoshi","contributorId":218228,"corporation":false,"usgs":false,"family":"Mitarai","given":"Satoshi","email":"","affiliations":[],"preferred":false,"id":882836,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Page, Heather N. 0000-0001-9997-0004","orcid":"https://orcid.org/0000-0001-9997-0004","contributorId":329657,"corporation":false,"usgs":false,"family":"Page","given":"Heather","email":"","middleInitial":"N.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882837,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rintoul, Max S. 0000-0001-9141-9779","orcid":"https://orcid.org/0000-0001-9141-9779","contributorId":329658,"corporation":false,"usgs":false,"family":"Rintoul","given":"Max","email":"","middleInitial":"S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882838,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, Jennifer E. 0000-0002-4516-6931","orcid":"https://orcid.org/0000-0002-4516-6931","contributorId":329659,"corporation":false,"usgs":false,"family":"Smith","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882839,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Soong, Keryea 0000-0002-4371-7103","orcid":"https://orcid.org/0000-0002-4371-7103","contributorId":329660,"corporation":false,"usgs":false,"family":"Soong","given":"Keryea","email":"","affiliations":[{"id":78681,"text":"National Sun Yat-sen University Taiwan","active":true,"usgs":false}],"preferred":false,"id":882840,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Takeshita, Yuichiro","contributorId":329673,"corporation":false,"usgs":false,"family":"Takeshita","given":"Yuichiro","email":"","affiliations":[],"preferred":false,"id":882841,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tresguerres, Martin 0000-0002-7090-9266","orcid":"https://orcid.org/0000-0002-7090-9266","contributorId":329662,"corporation":false,"usgs":false,"family":"Tresguerres","given":"Martin","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":882842,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wei, Yi","contributorId":329663,"corporation":false,"usgs":false,"family":"Wei","given":"Yi","email":"","affiliations":[{"id":30216,"text":"National Taiwan University","active":true,"usgs":false}],"preferred":false,"id":882843,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Yates, Kimberly K. 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":214349,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":882844,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Andersson, Andreas J","contributorId":141142,"corporation":false,"usgs":false,"family":"Andersson","given":"Andreas","email":"","middleInitial":"J","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":882845,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70251433,"text":"70251433 - 2023 - A 600-kyr reconstruction of deep Arctic seawater δ18O from benthic foraminiferal oxygen isotopes and ostracode Mg/Ca paleothermometry","interactions":[],"lastModifiedDate":"2024-02-10T13:50:03.510105","indexId":"70251433","displayToPublicDate":"2023-03-16T07:43:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"A 600-kyr reconstruction of deep Arctic seawater δ18O from benthic foraminiferal oxygen isotopes and ostracode Mg/Ca paleothermometry","docAbstract":"

The oxygen isotopic composition of benthic foraminiferal tests (δ18Ob) is one of the pre-eminent tools for correlating marine sediments and interpreting past terrestrial ice volume and deep-ocean temperatures. Despite the prevalence of δ18Ob applications to marine sediment cores over the Quaternary, its use is limited in the Arctic Ocean because of low benthic foraminiferal abundances, challenges with constructing independent sediment core age models, and an apparent muted amplitude of Arctic δ18Ob variability compared to open-ocean records. Here we evaluate the controls on Arctic δ18Ob by using ostracode Mg/Ca\"> paleothermometry to generate a composite record of the δ18O of seawater (δ18Osw) from 12 sediment cores in the intermediate to deep Arctic Ocean (700–2700 m) that covers the last 600 kyr based on biostratigraphy and orbitally tuned age models. Results show that Arctic δ18Ob was generally higher than open-ocean δ18Ob during interglacials but was generally equivalent to global reference records during glacial periods. The reduced glacial–interglacial Arctic δ18Ob range resulted in part from the opposing effect of temperature, with intermediate to deep Arctic warming during glacials counteracting the whole-ocean δ18Osw increase from expanded terrestrial ice sheets. After removing the temperature effect from δ18Ob, we find that the intermediate to deep Arctic experienced large (≥1 ‰) variations in local δ18Osw, with generally higher local δ18Osw during interglacials and lower δ18Osw during glacials. Both the magnitude and timing of low local δ18Osw intervals are inconsistent with the recent proposal of freshwater intervals in the Arctic Ocean during past glaciations. Instead, we suggest that lower local δ18Osw in the intermediate to deep Arctic Ocean during glaciations reflected weaker upper-ocean stratification and more efficient transport of low-δ18Osw Arctic surface waters to depth by mixing and/or brine rejection.

","language":"English","publisher":"European Geophysical Union","doi":"10.5194/cp-19-555-2023","usgsCitation":"Farmer, J., Keller, K., Poirier, R., Dwyer, G.S., Schaller, M., Coxall, H.K., O’Regan, M., and Cronin, T.M., 2023, A 600-kyr reconstruction of deep Arctic seawater δ18O from benthic foraminiferal oxygen isotopes and ostracode Mg/Ca paleothermometry: Climate of the Past, v. 19, no. 3, p. 555-578, https://doi.org/10.5194/cp-19-555-2023.","productDescription":"24 p.","startPage":"555","endPage":"578","ipdsId":"IP-146090","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":444195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-19-555-2023","text":"Publisher Index Page"},{"id":425565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Farmer, Jesse","contributorId":279623,"corporation":false,"usgs":false,"family":"Farmer","given":"Jesse","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":894561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keller, Katherine 0000-0001-6915-5455","orcid":"https://orcid.org/0000-0001-6915-5455","contributorId":218048,"corporation":false,"usgs":false,"family":"Keller","given":"Katherine","email":"","affiliations":[{"id":39732,"text":"Natural Systems Analysts, Harvard University","active":true,"usgs":false}],"preferred":false,"id":894562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poirier, Robert 0000-0001-5380-4545","orcid":"https://orcid.org/0000-0001-5380-4545","contributorId":261201,"corporation":false,"usgs":true,"family":"Poirier","given":"Robert","email":"","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":894563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dwyer, Gary S.","contributorId":197070,"corporation":false,"usgs":false,"family":"Dwyer","given":"Gary","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":894564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaller, Morgan","contributorId":260723,"corporation":false,"usgs":false,"family":"Schaller","given":"Morgan","email":"","affiliations":[],"preferred":false,"id":894565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coxall, Helen K","contributorId":290629,"corporation":false,"usgs":false,"family":"Coxall","given":"Helen","email":"","middleInitial":"K","affiliations":[{"id":62460,"text":"Stockholm University, Stockholm Sweden","active":true,"usgs":false}],"preferred":false,"id":894566,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":894567,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":894568,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252900,"text":"70252900 - 2023 - Editorial: Volcanic forecasting, crisis management, and risk communication","interactions":[],"lastModifiedDate":"2024-04-10T11:54:05.552398","indexId":"70252900","displayToPublicDate":"2023-03-16T06:52:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Volcanic forecasting, crisis management, and risk communication","docAbstract":"Volcanic eruptions intermittently punctuate periods of repose at volcanic centers and fields. Forecasting the timing, style, distribution, and magnitude of these eruptions is difficult, because eruptive activity varies over time, commonly in an irregular way. Furthermore, the impacts of eruptions can include loss of lives, property damage, and social and economic disturbance, where every eruption produces different impacts. Mitigation of volcanic risk is therefore complex, requiring community action that is aided by preparedness actions of emergency managers, stakeholders, community leaders, and individuals, and by timely delivery and reception of hazard information during a crisis.\n\nThis Research Topic addresses efforts to understand complexities in these relations dealing with volcanic unrest, eruptions, and eruption impacts. Research Topic range from eruption forecasting (Wild et al.; Christophersen et al.; Bernard et al.) and volcanic hazard assessment (Mead et al.) to risk communication and action (Martinez-Villegas et al.; Todesco et al.; Graham et al.; Bernard et al.) prior to and during volcanic crises. The studies use various methodologies and approaches, touching on various parts of the integrated, multi-partner systems that exist to improve risk mitigation.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2023.1182252","usgsCitation":"Andreastuti, S., Wright, H.M., Fontijn, K., and Miller, V., 2023, Editorial: Volcanic forecasting, crisis management, and risk communication: Frontiers in Earth Science, v. 11, 1182252, 2 p., https://doi.org/10.3389/feart.2023.1182252.","productDescription":"1182252, 2 p.","ipdsId":"IP-151731","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1182252","text":"Publisher Index Page"},{"id":427638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Andreastuti, Supriyati","contributorId":243218,"corporation":false,"usgs":false,"family":"Andreastuti","given":"Supriyati","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":898613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":898614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fontijn, Karen","contributorId":184084,"corporation":false,"usgs":false,"family":"Fontijn","given":"Karen","email":"","affiliations":[],"preferred":false,"id":898615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Victoria","contributorId":335533,"corporation":false,"usgs":false,"family":"Miller","given":"Victoria","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":898616,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241223,"text":"ofr20231007 - 2023 - Geospatial standard operating procedures of the Chesapeake Bay Program","interactions":[],"lastModifiedDate":"2023-03-16T10:48:56.467409","indexId":"ofr20231007","displayToPublicDate":"2023-03-16T05:45:00","publicationYear":"2023","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":"2023-1007","displayTitle":"Geospatial Standard Operating Procedures of the Chesapeake Bay Program","title":"Geospatial standard operating procedures of the Chesapeake Bay Program","docAbstract":"

Introduction 

The Chesapeake Bay Program (CBP) has operated a geographic information system (GIS) program since the early 1990s to address the established and growing need for and use of geospatial data, maps, and analysis within the CBP Partnership. This report is intended to detail the standard operating procedures of the CBP GIS program and address the quality assurance, quality control, and other technical activities that CBP will implement to ensure the commitment of the CBP GIS Team to performance standards (U.S. Environmental Protection Agency, 2003). The report is intended as an update to the 2011 Quality Assurance Project Plan (QAPP). For specialized tasks or analytical projects beyond the scope of this QAPP, a separate specialized QAPP with details on quality control, assurance procedures, and the geospatial methods associated with all aspects of the project may be required.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231007","collaboration":"Prepared in cooperation with the University of Maryland Center for Environmental Science","usgsCitation":"Wolf, J., Ahmed, L., Claggett, P., Fitch, A., Irani, F., McDonald, S., Strong, D., Thompson, R., and Wei, Z., 2023, Geospatial standard operating procedures of the Chesapeake Bay Program: U.S. Geological Survey Open-File Report 2023–1007, 22 p., https://doi.org/10.3133/ofr20231007.","productDescription":"vi; 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-116901","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":414217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1007/coverthb.jpg"},{"id":414218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1007/ofr20231007.pdf","text":"Report","size":"1.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1007"},{"id":414219,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1007"},{"id":414220,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1007/ofr20231007.XML"},{"id":414221,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1007/images/"}],"contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-03-16","noUsgsAuthors":false,"publicationDate":"2023-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolf, John C. 0000-0002-9970-2250","orcid":"https://orcid.org/0000-0002-9970-2250","contributorId":303114,"corporation":false,"usgs":true,"family":"Wolf","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahmed, Labeeb 0000-0003-4524-9611","orcid":"https://orcid.org/0000-0003-4524-9611","contributorId":303117,"corporation":false,"usgs":true,"family":"Ahmed","given":"Labeeb","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claggett, Peter 0000-0002-5335-2857","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":238920,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":866583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitch, Andrew 0000-0002-5213-9501","orcid":"https://orcid.org/0000-0002-5213-9501","contributorId":303120,"corporation":false,"usgs":true,"family":"Fitch","given":"Andrew","email":"","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866586,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irani, Frederick 0000-0002-2424-0135 firani@usgs.gov","orcid":"https://orcid.org/0000-0002-2424-0135","contributorId":303119,"corporation":false,"usgs":true,"family":"Irani","given":"Frederick","email":"firani@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Sarah 0000-0003-3534-325X","orcid":"https://orcid.org/0000-0003-3534-325X","contributorId":303116,"corporation":false,"usgs":true,"family":"McDonald","given":"Sarah","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866581,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strong, David 0000-0002-4687-8076 dstrong@usgs.gov","orcid":"https://orcid.org/0000-0002-4687-8076","contributorId":303118,"corporation":false,"usgs":true,"family":"Strong","given":"David","email":"dstrong@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Renee 0000-0003-1463-5173 rthompson1@usgs.gov","orcid":"https://orcid.org/0000-0003-1463-5173","contributorId":303115,"corporation":false,"usgs":true,"family":"Thompson","given":"Renee","email":"rthompson1@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866579,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wei, Zhaoying","contributorId":245828,"corporation":false,"usgs":false,"family":"Wei","given":"Zhaoying","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":866580,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262886,"text":"70262886 - 2023 - Dynamics of the December 2020 ash-poor plume formed by lava-water interaction at the summit of Kilauea Volcano, Hawaii","interactions":[],"lastModifiedDate":"2025-01-27T17:34:03.218669","indexId":"70262886","displayToPublicDate":"2023-03-16T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of the December 2020 ash-poor plume formed by lava-water interaction at the summit of Kilauea Volcano, Hawaii","docAbstract":"

On 20 December 2020, after more than 2 years of quiescence at Kīlauea Volcano, Hawaiʻi, renewed volcanic activity in the summit crater caused boiling of the water lake over a period of ∼90 min. The resulting water-rich, electrified plume rose to 11–13 km above sea level, which is among the highest plumes on record for Kīlauea. Although conventional models would infer a high mass flux from explosive magma-water interaction, the plume was not associated with an infrasound signal indicative of “explosive” activity, nor did it produce a measurable ash-fall deposit. We use multisensor data to characterize lava-water interaction and plume generation during this opening phase of the 2020–21 eruption. Satellite, weather radar, and eyewitness observations revealed that the plume was rich in water vapor and hydrometeors but transported less ash than expected from its maximum height. Volcanic lightning flashes detected by ground-based cameras were confined to freezing altitudes of the upper cloud, suggesting that the ice formation drove the electrification of this plume. The low acoustic energy from lava-water interaction points to a weakly explosive style of hydrovolcanism. Heat transfer calculations show that the lava to water heat flux was sufficient to boil the lake within 90 min. Limited mixing of lava and water inhibited major steam explosions and fine fragmentation. Results from one-dimensional plume modeling suggest that the models may underpredict plume height due to overestimation of crosswind air-entrainment. Our findings shed light on an unusual style of volcanism in which weakly explosive lava-water interaction generated an outsized plume.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GC010718","usgsCitation":"Cahalan, R.C., Mastin, L.G., Van Eaton, A.R., Hurwitz, S., Smith, A., Dufek, J., Solovitz, S.A., Patrick, M.R., Schmith, J., Parcheta, C., Thelen, W., and Downs, D.T., 2023, Dynamics of the December 2020 ash-poor plume formed by lava-water interaction at the summit of Kilauea Volcano, Hawaii: Geochemistry, Geophysics, Geosystems, v. 24, no. 3, e2022GC010718, 23 p., https://doi.org/10.1029/2022GC010718.","productDescription":"e2022GC010718, 23 p.","ipdsId":"IP-145500","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":489752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gc010718","text":"Publisher Index Page"},{"id":481272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2803669612127,\n 19.458319847666203\n ],\n [\n -155.2803669612127,\n 19.37101672587596\n ],\n [\n -155.17107998542878,\n 19.37101672587596\n ],\n [\n -155.17107998542878,\n 19.458319847666203\n ],\n [\n -155.2803669612127,\n 19.458319847666203\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Cahalan, Ryan Cain 0000-0002-3322-0654","orcid":"https://orcid.org/0000-0002-3322-0654","contributorId":302355,"corporation":false,"usgs":true,"family":"Cahalan","given":"Ryan","email":"","middleInitial":"Cain","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":925179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":925180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":925181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - 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2023 - Diurnal time–activity budget and habitat use of Whooping Cranes (Grus americana) in the reintroduced Louisiana nonmigratory population","interactions":[],"lastModifiedDate":"2024-08-26T22:40:40.917527","indexId":"70256615","displayToPublicDate":"2023-03-15T17:34:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7509,"text":"The Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Diurnal time–activity budget and habitat use of Whooping Cranes (Grus americana) in the reintroduced Louisiana nonmigratory population","docAbstract":"

Time–activity budget studies provide valuable insights for better understanding animal behavior relative to spatial and temporal habitat use. We examined a reintroduced, nonmigratory Whooping Crane (Grus americana) population to determine how time–activity budgets change relative to crane age, sex, habitat type, and season. Our study area encompassed natural marshes and working wetlands primarily in southwestern Louisiana. From June 2012 to January 2016, we conducted continuous focal sampling on individuals (n = 27) from the first 4 captive-reared cohorts released in the state. We classified age groups as juveniles, subadults, and adults, and identified 5 main habitat types utilized by cranes in Louisiana: crawfish ponds, rice fields, agricultural levees/farm roads, fallow fields, and natural wetlands. On average, cranes spent approximately 53% of their diurnal time–activity budget foraging. Maintenance/rest (28%), vigilance (12%), locomotion (6%), and other/unknown (2%) behaviors accounted for the remainder of the time observed. Foraging most frequently occurred in fallow fields and crawfish ponds where cranes likely encountered greater invertebrate biomass and density. Cranes tended to spend less time foraging and more time on maintenance as they aged, which could indicate age-dependent differences based on experience on the landscape. Vigilance levels were not significantly affected by age, but males tended to be more vigilant than females. As this young population continues to mature, additional study of breeding pairs and family groups may elucidate other behavioral differences in response to the dynamic habitat conditions in the region.

","language":"English","publisher":"BioOne","doi":"10.1676/22-00039","usgsCitation":"Vasseur, P., King, S.L., and Kaller, M., 2023, Diurnal time–activity budget and habitat use of Whooping Cranes (Grus americana) in the reintroduced Louisiana nonmigratory population: The Wilson Journal of Ornithology, v. 135, no. 1, p. 31-45, https://doi.org/10.1676/22-00039.","productDescription":"15 p.","startPage":"31","endPage":"45","ipdsId":"IP-139263","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":444201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1676/22-00039","text":"Publisher Index Page"},{"id":433172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vasseur, Phillip L.","contributorId":341374,"corporation":false,"usgs":false,"family":"Vasseur","given":"Phillip L.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":908319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaller, Michael D.","contributorId":341375,"corporation":false,"usgs":false,"family":"Kaller","given":"Michael D.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908321,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250816,"text":"70250816 - 2023 - Crossing the threshold: Invasive grasses inhibit forest restoration on Hawaiian islands","interactions":[],"lastModifiedDate":"2024-01-08T17:12:25.046632","indexId":"70250816","displayToPublicDate":"2023-03-15T11:07:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Crossing the threshold: Invasive grasses inhibit forest restoration on Hawaiian islands","docAbstract":"

Forest removal for livestock grazing is a striking example of human-caused state change leading to a stable, undesirable invasive grass system that is resistant to restoration efforts. Understanding which factors lead to resilience to the alternative grass state can greatly benefit managers when planning forest restoration. We address how thresholds of grass cover and seed rain might influence forest recovery in a restoration project on Hawaiʻi Island, USA. Since the 1980s, over 400,000 Acacia koa (koa) trees have been planted across degraded pasture, and invasive grasses still dominate the understory with no native woody-plant recruitment. Between this koa/grass matrix are remnant native Metrosideros polymorpha (ʻōhiʻa) trees beneath which native woody plants naturally recruit. We tested whether there were threshold levels of native woody understory that accelerate recruitment under both tree species by monitoring seed rain at 40 trees (20 koa and ʻōhiʻa) with a range of native woody understory basal area (BA). We found a positive relationship between total seed rain (but not bird-dispersed seed rain) and native woody BA and a negative relationship between native woody BA and grass cover, with no indication of threshold dynamics. We also experimentally combined grass removal levels with seed rain density (six levels) of two common understory species in plots under koa (n = 9) and remnant ʻōhiʻa (n = 9). Few seedlings emerged when no grass was removed despite adding seeds at densities two to 75 times higher than naturally occurring. However, seedling recruitment increased two to three times once at least 50% of grass was removed. Existing survey data of naturally occurring seedlings also supported a threshold of grass cover below which seedlings were able to establish. Thus, removal of all grasses is not necessary to achieve system responses: Even moderate reductions (~50%) can increase rates of native woody recruitment. The nonlinear thresholds found here highlight how incremental changes to an inhibitory factor lead to limited restoration success until a threshold is crossed. The resources needed to fully eradicate an invasive species may be unwarranted for state change, making understanding where thresholds lie of the utmost importance to prioritize resources.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2841","usgsCitation":"Rehm, E.M., D'Antonio, C., and Yelenik, S.G., 2023, Crossing the threshold: Invasive grasses inhibit forest restoration on Hawaiian islands: Ecological Applications, v. 33, no. 4, e2841, 16 p., https://doi.org/10.1002/eap.2841.","productDescription":"e2841, 16 p.","ipdsId":"IP-146381","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":444204,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2841","text":"Publisher Index Page"},{"id":435410,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98OUTPW","text":"USGS data release","linkHelpText":"Hakalau Forest NWR seedling and substrate data, 2015"},{"id":424193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.33984563763397,\n 19.888564964992852\n ],\n [\n -155.33984563763397,\n 19.7594436528868\n ],\n [\n -155.2208910771554,\n 19.7594436528868\n ],\n [\n -155.20855397426797,\n 19.931097090422853\n ],\n [\n -155.33984563763397,\n 19.888564964992852\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rehm, Evan M","contributorId":216487,"corporation":false,"usgs":false,"family":"Rehm","given":"Evan","email":"","middleInitial":"M","affiliations":[{"id":39457,"text":"University of California at Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":891660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Antonio, Carla M.","contributorId":27992,"corporation":false,"usgs":false,"family":"D'Antonio","given":"Carla M.","affiliations":[],"preferred":false,"id":891661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":891662,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252452,"text":"70252452 - 2023 - Ecological harm and economic damages of chemical contamination to linked aquatic-terrestrial food webs: A study-design tool for practitioners","interactions":[],"lastModifiedDate":"2024-09-18T16:03:02.473007","indexId":"70252452","displayToPublicDate":"2023-03-15T09:51:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Ecological harm and economic damages of chemical contamination to linked aquatic-terrestrial food webs: A study-design tool for practitioners","docAbstract":"

Contamination of aquatic ecosystems can have cascading effects on terrestrial consumers by altering the availability and quality of aquatic insect prey. Comprehensive assessment of these indirect food-web effects of contaminants on natural resources and their associated services necessitates using both ecological and economic tools. In the present study we present an aquatic-terrestrial assessment tool (AT2), including ecological and economic decision trees, to aid practitioners and researchers in designing contaminant effect studies for linked aquatic-terrestrial insect-based food webs. The tool is tailored to address the development of legal claims by the US Department of the Interior's Natural Resource Damage Assessment and Restoration Program, which aims to restore natural resources injured by oil spills and hazardous substance releases into the environment. Such cases require establishing, through scientific inquiry, the existence of natural resource injury as well as the determination of the monetary or in-kind project-based damages required to restore this injury. However, this tool is also useful to researchers interested in questions involving the effects of contaminants on linked aquatic-terrestrial food webs. Stylized cases exemplify how application of AT2 can help practitioners and researchers design studies when the contaminants present at a site are likely to lead to injury of terrestrial aerial insectivores through loss of aquatic insect prey and/or dietary contaminant exposure. Designing such studies with ecological endpoints and economic modeling inputs in mind will increase the relevance and cost-effectiveness of studies, which can in turn improve the outcomes of cases and studies involving the ecological effects of contaminants on food webs. 

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Serena","contributorId":279464,"corporation":false,"usgs":false,"family":"Ciparis","given":"Serena","affiliations":[{"id":12428,"text":"U. S. 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A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

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A total of 60 people participated. Our workshop attendees included scientists from 28 institutions and 11 countries (United States of America, Australia, Brazil, Czech Republic, China, France, Germany, Japan, New Zealand, Saudi Arabia, and Switzerland). Twenty-eight of our workshop participants were students or postdocs. The workshop agenda and participant list are on the last page of this report, and the workshop agenda and presentation videos and slides of most of the talks can be found on our SCEC workshop website: https://www.scec.org/workshops/2023/dynrup.","language":"English","publisher":"Southern California Earthquake Center","usgsCitation":"Harris, R.A., and Barall, M., 2023, January 12, 2023 SCEC workshop, Dynamic Rupture TAG – Investigating new ideas in earthquake source mechanics(SCEC Project 22157), 10 p.","productDescription":"10 p.","ipdsId":"IP-151300","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":417206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417195,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.scec.org/proposal/report/22157"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563 mbarall@usgs.gov","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":271197,"corporation":false,"usgs":true,"family":"Barall","given":"Michael","email":"mbarall@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873148,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242077,"text":"70242077 - 2023 - Droughting a megadrought: Ecological consequences of a decade of experimental drought atop aridification on the Colorado Plateau","interactions":[],"lastModifiedDate":"2023-05-25T15:57:00.53524","indexId":"70242077","displayToPublicDate":"2023-03-15T07:13:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Droughting a megadrought: Ecological consequences of a decade of experimental drought atop aridification on the Colorado Plateau","docAbstract":"

Global dryland vegetation communities will likely change as ongoing drought conditions shift regional climates towards a more arid future. Additional aridification of drylands can impact plant and ground cover, biogeochemical cycles, and plant-soil feedbacks, yet how and when these crucial ecosystem components will respond to drought intensification requires further investigation. Using a long-term precipitation reduction experiment (35% reduction) conducted across the Colorado Plateau and spanning ten years into a 20+ year regional megadrought, we explored how vegetation cover, soil conditions, and growing season nitrogen (N) availability are impacted by drying climate conditions. We observed large declines for all dominant plant functional types (C3 and C4 grasses and C3 and C4 shrubs) across measurement period, both in the drought treatment and control plots, likely due to ongoing regional megadrought conditions. In experimental drought plots, we observed less plant cover, less biological soil crust cover, warmer and drier soil conditions, and more soil resin-extractable N compared to the control plots. Observed increases in soil N availability were best explained by a negative correlation with plant cover regardless of treatment, suggesting that declines in vegetation N uptake may be driving increases in available soil N. However, in ecosystems experiencing long-term aridification, increased N availability may ultimately result in N losses if soil moisture is consistently too dry to support plant and microbial N immobilization and ecosystem recovery. These results show dramatic, worrisome declines in plant cover with long-term drought. Additionally, this study highlights that more plant cover losses are possible with further drought intensification, and underscore that, in addition to large drought effects on aboveground communities, drying trends drive significant changes to critical soil resources such as N availability, all of which could have long-term ecosystem impacts for drylands.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16681","usgsCitation":"Finger-Higgens, R.A., Bishop, T.B., Belnap, J., Geiger, E.L., Grote, E.E., Hoover, D., Reed, S., and Duniway, M.C., 2023, Droughting a megadrought: Ecological consequences of a decade of experimental drought atop aridification on the Colorado Plateau: Global Change Biology, v. 29, no. 12, p. 3364-3377, https://doi.org/10.1111/gcb.16681.","productDescription":"14 p.","startPage":"3364","endPage":"3377","ipdsId":"IP-146361","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444211,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16681","text":"Publisher Index Page"},{"id":435411,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BKCYSX","text":"USGS data release","linkHelpText":"Vegetation cover, ground cover, plant mortality, and species abundance across an experimental drought treatment on the Colorado Plateau from 2010-2022"},{"id":415332,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Finger-Higgens, Rebecca A 0000-0002-7645-504X","orcid":"https://orcid.org/0000-0002-7645-504X","contributorId":290211,"corporation":false,"usgs":true,"family":"Finger-Higgens","given":"Rebecca","email":"","middleInitial":"A","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Tara Boyce Belnap 0000-0001-7828-1541","orcid":"https://orcid.org/0000-0001-7828-1541","contributorId":302273,"corporation":false,"usgs":true,"family":"Bishop","given":"Tara","email":"","middleInitial":"Boyce Belnap","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geiger, Erika L. 0000-0003-4546-3503","orcid":"https://orcid.org/0000-0003-4546-3503","contributorId":207502,"corporation":false,"usgs":true,"family":"Geiger","given":"Erika","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grote, Edmund E. 0000-0002-9103-9482 ed_grote@usgs.gov","orcid":"https://orcid.org/0000-0002-9103-9482","contributorId":4271,"corporation":false,"usgs":true,"family":"Grote","given":"Edmund","email":"ed_grote@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoover, David","contributorId":239685,"corporation":false,"usgs":false,"family":"Hoover","given":"David","affiliations":[{"id":47973,"text":"Rangeland Resources & Systems Research Unit, U.S. Department of Agriculture, Agricultural Research Service, Fort Collins 80526","active":true,"usgs":false}],"preferred":false,"id":868772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":868774,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241200,"text":"fs20233006 - 2023 - Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022","interactions":[],"lastModifiedDate":"2026-02-04T20:37:47.514644","indexId":"fs20233006","displayToPublicDate":"2023-03-14T16:03:33","publicationYear":"2023","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":"2023-3006","displayTitle":"Application of Geophysical Methods to Enhance Aquifer Characterization and Groundwater-Flow Model Development, Des Moines River Alluvial Aquifer, Des Moines, Iowa, 2022","title":"Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022","docAbstract":"

Des Moines Water Works (DMWW) is one of the largest water providers in Iowa and as population growth continues, demand for drinking water is increasing. DMWW uses groundwater and surface water as raw water sources to supply the City of Des Moines and surrounding communities. In response to current and future demands, DMWW is in need of a thorough understanding of local groundwater resources, specifically the Des Moines River alluvial aquifer. The Des Moines River alluvial aquifer is hydraulically connected to the Des Moines River and consists of alluvial deposits and glacial outwash sands and gravels. To ensure a sustainable groundwater supply, additional information to better understand and manage groundwater availability within the Des Moines River alluvial aquifer would be beneficial. Beginning in 2018, DMWW partnered with the U.S. Geological Survey to construct a groundwater-flow model to increase understanding of the hydrologic system in the Des Moines area. The model hydrogeologic framework will be enhanced by using multiple geophysical methods of data collection in the Des Moines River, Beaver Creek, and the Des Moines River alluvial aquifer that could provide a better understanding of the geology in the model area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233006","usgsCitation":"Thomas, J.C., Spring, M.A., Gruhn, L.R., and Bristow, E.L., 2023, Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022: U.S. Geological Survey Fact Sheet 2023–3006, 4 p., https://doi.org/10.3133/fs20233006.","productDescription":"Report: 4 p.; 2 Data Releases; Dataset","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-136349","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414104,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3006"},{"id":414105,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.XML","description":"FS 2023–3006"},{"id":414103,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3006/coverthb2.jpg"},{"id":414112,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/national-hydrography/access-national-hydrography-products","text":"USGS dataset","linkHelpText":"—National Hydrography Dataset— USGS National Hydrography Dataset Best Resolution for Hydrologic Unit 4 – 2001"},{"id":414109,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B9AVKJ","text":"USGS data release","linkHelpText":"Geophysical data collected in the Des Moines River, Beaver Creek, and the Des Moines River floodplain, Des Moines, Iowa, 2018"},{"id":414110,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":499566,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114475.htm","linkFileType":{"id":5,"text":"html"}},{"id":414138,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":414113,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3006/images"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Des Moines River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.69895287733283,\n 41.66093681949087\n ],\n [\n -93.69895287733283,\n 41.52388190639587\n ],\n [\n -93.51363729010005,\n 41.52388190639587\n ],\n [\n -93.51363729010005,\n 41.66093681949087\n ],\n [\n -93.69895287733283,\n 41.66093681949087\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-03-14","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spring, Morgan A. 0000-0002-8781-604X mspring@usgs.gov","orcid":"https://orcid.org/0000-0002-8781-604X","contributorId":303050,"corporation":false,"usgs":true,"family":"Spring","given":"Morgan","email":"mspring@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bristow, Emilia L. 0000-0002-7939-166X ebristow@usgs.gov","orcid":"https://orcid.org/0000-0002-7939-166X","contributorId":214538,"corporation":false,"usgs":true,"family":"Bristow","given":"Emilia L.","email":"ebristow@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241433,"text":"70241433 - 2023 - Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","interactions":[],"lastModifiedDate":"2023-03-17T12:05:34.434371","indexId":"70241433","displayToPublicDate":"2023-03-14T07:01:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","docAbstract":"

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. Finally, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102693","usgsCitation":"Smith, C.M., Faulds, J., Brown, S.C., Coolbaugh, M., DeAngelo, J., Glen, J.M., Burns, E.R., Siler, D.L., Treitel, S., Mlawsky, E., Fehler, M., Gu, C., and Ayling, B.F., 2023, Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis: Geothermics, v. 111, 102693, 21 p., https://doi.org/10.1016/j.geothermics.2023.102693.","productDescription":"102693, 21 p.","ipdsId":"IP-145803","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1999607","text":"Publisher Index Page"},{"id":414334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.08429216037908,\n 42.0233321964142\n ],\n [\n -120.08429216037908,\n 38.470780571367555\n ],\n [\n -114.02241339577863,\n 38.470780571367555\n ],\n [\n -114.02241339577863,\n 42.0233321964142\n ],\n [\n -120.08429216037908,\n 42.0233321964142\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Connor M.","contributorId":237894,"corporation":false,"usgs":false,"family":"Smith","given":"Connor","email":"","middleInitial":"M.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E.","contributorId":252834,"corporation":false,"usgs":false,"family":"Faulds","given":"James 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jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siler, Drew Lorenz 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":303226,"corporation":false,"usgs":false,"family":"Siler","given":"Drew","email":"","middleInitial":"Lorenz","affiliations":[{"id":65720,"text":"Geologica Geothermal Group, LLC.","active":true,"usgs":false}],"preferred":false,"id":866835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Treitel, Sven","contributorId":237884,"corporation":false,"usgs":false,"family":"Treitel","given":"Sven","email":"","affiliations":[{"id":47634,"text":"Hi-Q Geophysical, Inc.","active":true,"usgs":false}],"preferred":false,"id":866836,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mlawsky, Eli","contributorId":237889,"corporation":false,"usgs":false,"family":"Mlawsky","given":"Eli","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866837,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fehler, Michael","contributorId":237888,"corporation":false,"usgs":false,"family":"Fehler","given":"Michael","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":866838,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gu, Chen","contributorId":237896,"corporation":false,"usgs":false,"family":"Gu","given":"Chen","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":866839,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ayling, Bridget F.","contributorId":237899,"corporation":false,"usgs":false,"family":"Ayling","given":"Bridget","email":"","middleInitial":"F.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866840,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70250381,"text":"70250381 - 2023 - Stream temperature prediction in a shifting environment: The influence of deep learning architecture","interactions":[],"lastModifiedDate":"2023-12-06T12:43:59.163691","indexId":"70250381","displayToPublicDate":"2023-03-14T06:40:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Stream temperature prediction in a shifting environment: The influence of deep learning architecture","docAbstract":"

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process-guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR033880","usgsCitation":"Topp, S.N., Barclay, J.R., Diaz, J.A., Sun, A.Y., Jia, X., Lubin, D., Sadler, J., and Appling, A.P., 2023, Stream temperature prediction in a shifting environment: The influence of deep learning architecture: Water Resources Research, v. 59, no. 4, e2022WR033880, 19 p., https://doi.org/10.1029/2022WR033880.","productDescription":"e2022WR033880, 19 p.","ipdsId":"IP-146111","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":444217,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr033880","text":"Publisher Index Page"},{"id":435412,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HU7BLR","text":"USGS data release","linkHelpText":"Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin"},{"id":423260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.07997541667648,\n 38.70906787639316\n ],\n [\n -74.80531721355018,\n 39.00778043156808\n ],\n [\n -74.33839826823872,\n 40.4450386444411\n ],\n [\n -73.72865705730113,\n 40.994591290300974\n ],\n [\n -73.7835886979261,\n 42.478350475454334\n ],\n [\n -75.40956526042564,\n 42.295772510663625\n ],\n [\n -75.42055158855078,\n 41.8349594674406\n ],\n [\n -76.34340315105082,\n 40.43667721449637\n ],\n [\n -75.78859358073888,\n 39.713504216020766\n ],\n [\n -75.76662092448927,\n 39.578152174338356\n ],\n [\n -75.66225080730156,\n 39.41283383409595\n ],\n [\n -75.50294904948888,\n 39.22584914314203\n ],\n [\n -75.47548322917642,\n 39.042631522344635\n ],\n [\n -75.33266096355176,\n 38.846103881559685\n ],\n [\n -75.07997541667648,\n 38.70906787639316\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Topp, Simon Nemer 0000-0001-7741-5982","orcid":"https://orcid.org/0000-0001-7741-5982","contributorId":268229,"corporation":false,"usgs":true,"family":"Topp","given":"Simon","email":"","middleInitial":"Nemer","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":889640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diaz, Jeremy Alejandro 0000-0001-7087-7949","orcid":"https://orcid.org/0000-0001-7087-7949","contributorId":302986,"corporation":false,"usgs":true,"family":"Diaz","given":"Jeremy","email":"","middleInitial":"Alejandro","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":889642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sun, Alexander Y. 0000-0002-6365-8526","orcid":"https://orcid.org/0000-0002-6365-8526","contributorId":302987,"corporation":false,"usgs":false,"family":"Sun","given":"Alexander","email":"","middleInitial":"Y.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":889643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":889644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lubin, Daniel","contributorId":174974,"corporation":false,"usgs":false,"family":"Lubin","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":889645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadler, Jeffrey M 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":302989,"corporation":false,"usgs":false,"family":"Sadler","given":"Jeffrey M","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":889646,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":889647,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241861,"text":"70241861 - 2023 - Variable effects of long-term livestock grazing across the western United States suggest diverse approaches are needed to meet global change challenges","interactions":[],"lastModifiedDate":"2023-03-29T11:37:46.725493","indexId":"70241861","displayToPublicDate":"2023-03-14T06:33:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Variable effects of long-term livestock grazing across the western United States suggest diverse approaches are needed to meet global change challenges","docAbstract":"

Aims

Livestock production is the most widespread land use globally and occurs across a diverse set of ecosystems. Variability in long-term livestock grazing impacts across ecosystems is poorly characterized, particularly at larger spatial scales, despite strong relationships with various ecosystem services related to soil fertility and stabilization and vegetation productivity. Here we examine the effects of grazing on vegetation and the implications for resistance and resilience to global change.

Methods

We use six long-term research stations in the western United States, spanning two ecoregions, multiple ecosystems, and 311 total site-years of research. Across these sites we evaluate convergence and divergence of vegetation response to grazing vs grazing removal, focusing on interactions with drivers of global change.

Results

We found that at long time scales (multiple decades), grazing has numerous convergent and divergent effects across ecoregions and ecosystems. Similarity among precipitation patterns and plant traits linked to grazing and production timing were key elements explaining convergence or divergence in long-term patterns of livestock grazing response. Ecosystem differences across western US rangelands are also associated with variable effects of grazing on resistance and resilience to invasive species and climate change.

Conclusions

These results suggest that unique ecosystem or ecoregion responses to future global change may result from complex interactions between grazing and environmental factors, such as precipitation timing and plant traits. Adapting livestock and grazing management to specific ecosystem vegetation and climate variability is needed to manage for the myriad global changes affecting rangeland production and diversity.

","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12719","usgsCitation":"Copeland, S., Hoover, D.L., Augustine, D.J., Bates, J.D., Boyd, C.S., Davies, K.W., Derner, J., Duniway, M.C., Porensky, L., and Vermeire, L.T., 2023, Variable effects of long-term livestock grazing across the western United States suggest diverse approaches are needed to meet global change challenges: Applied Vegetation Science, v. 26, no. 1, e12719, 16 p., https://doi.org/10.1111/avsc.12719.","productDescription":"e12719, 16 p.","ipdsId":"IP-133319","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/avsc.12719","text":"Publisher Index Page"},{"id":414881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.46681746772508,\n 47.39667163190734\n ],\n [\n -125.58511650460318,\n 47.39667163190734\n ],\n [\n -125.58511650460318,\n 34.02051503113559\n ],\n [\n -105.46681746772508,\n 34.02051503113559\n ],\n [\n -105.46681746772508,\n 47.39667163190734\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":867982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":245331,"corporation":false,"usgs":false,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":49151,"text":"USDA-ARS Rangeland Resources Research Unit, Crops Research Laboratory, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":867983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Augustine, David J.","contributorId":189957,"corporation":false,"usgs":false,"family":"Augustine","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":867984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bates, Jonathan D","contributorId":303747,"corporation":false,"usgs":false,"family":"Bates","given":"Jonathan","email":"","middleInitial":"D","affiliations":[{"id":65895,"text":"USDA-Agricultural Research Service, Eastern Oregon Agricultural Research Center, Burns, OR","active":true,"usgs":false}],"preferred":false,"id":867985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Chad S.","contributorId":255106,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","email":"","middleInitial":"S.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":867986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":867987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Derner, Justin D.","contributorId":270261,"corporation":false,"usgs":false,"family":"Derner","given":"Justin D.","affiliations":[{"id":56124,"text":"USDA, Agricultural Research Service, Rangeland Resources and Systems Research Unit","active":true,"usgs":false}],"preferred":false,"id":867988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":867989,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Porensky, Lauren M.","contributorId":264925,"corporation":false,"usgs":false,"family":"Porensky","given":"Lauren M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":867990,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vermeire, Lance T","contributorId":303748,"corporation":false,"usgs":false,"family":"Vermeire","given":"Lance","email":"","middleInitial":"T","affiliations":[{"id":65897,"text":"USDA-Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT","active":true,"usgs":false}],"preferred":false,"id":867991,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70243046,"text":"70243046 - 2023 - Plant water-use strategies predict restoration success across degraded drylands","interactions":[],"lastModifiedDate":"2023-06-09T15:23:00.168208","indexId":"70243046","displayToPublicDate":"2023-03-13T07:17:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Plant water-use strategies predict restoration success across degraded drylands","docAbstract":"
  1. Plant strategies for coping with water limitation are likely to mediate restoration outcomes in degraded dryland ecosystems. Trade-offs in traits related to water acquisition and use can intensify in more arid environments, making their effects on dryland restoration success even more salient. However, isolating the effects of drought responses from those of other environmental factors, as well as identifying the specific drought resistance traits that influence restoration success, can be difficult.
  2. In the present study, we couple a controlled dry-down experiment with a cross-site restoration field trial of out-planted seedlings (RestoreNet) using a suite of dryland herbaceous plant species from the same seed sources. We quantified interspecific variation in physiological responses to drought, specifically reductions in stomatal conductance (gs) and stem water potential (SWP), by comparing well-watered control plants to those experiencing decreasing soil moisture.
  3. Drought responses of SWP and gs varied independently among species, but both were related to survival in the cross-site restoration field trial when effect sizes were aggregated across all sites. Responses were consistent with acquisitive water-use strategies resulting in greater success, where species with greater declines in SWP or weaker declines in gs under drought had greater survival. The correlation between SWP drought response and survival also intensified in sites with lower accumulated precipitation following restoration.
  4. Differences among functional groups revealed two different paths to restoration success: forbs that maintain high gs and narrow safety margins to maximize exploitation of moisture pulses before going into drought dormancy, or C4 grasses that maintain efficient water uptake in drying soils while risking cavitation. C3 grass species varied between these two strategies.
  5. Synthesis and applications. Taken together, the results of this study and others conducted at RestoreNet sites indicate that while a diversity of physiological responses to drought may exist in dryland plant communities, successfully restoring herbaceous species through out-planting in degraded conditions is likely to be achieved with species that maximize water uptake via one of two strategies, with tolerance of low SWP being particularly important in the most arid settings.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14393","usgsCitation":"Butterfield, B.J., Munson, S.M., and Farrell, H., 2023, Plant water-use strategies predict restoration success across degraded drylands: Journal of Applied Ecology, v. 60, no. 6, p. 1170-1180, https://doi.org/10.1111/1365-2664.14393.","productDescription":"11 p.","startPage":"1170","endPage":"1180","ipdsId":"IP-146904","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444219,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index Page"},{"id":416435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":870795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":870796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrell, Hannah L.","contributorId":304525,"corporation":false,"usgs":false,"family":"Farrell","given":"Hannah L.","affiliations":[{"id":66095,"text":"formerly: US Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":870797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}