Expansion of exotic annual grass (EAG), such as cheatgrass (Bromus tectorum L.) and medusahead (Taeniatherum caput-medusae [L.] Nevski), could cause irreversible changes to arid and semiarid rangeland ecosystems in the western United States. The distribution and abundance of EAG species are highly affected by weather variables such as temperature and precipitation. The study's goal is to understand how different precipitation scenarios affect EAG abundance estimates and dynamics, and we develop a machine learning modeling approach to predict how changes in annual and immediate past precipitation patterns could affect the abundance of EAG. The machine learning predictive model used seed source from previous years, weather variables, and soil profiles to drive its predictions. We achieved excellent training accuracy (r = 0.95 and median absolute error [MdAE] = 2.36% cover) and strong test accuracy (r = 0.79 and MdAE = 4.54% cover). We developed five versions of EAG abundance maps for 2022 with different precipitation scenarios: 9 yr of average precipitation, half of the average, three-fourths of the average, one and one-half times the average, and two times the average. The approach presented can be replicated to new study domains and easily modified for use with other precipitation scenarios. Developing multiple versions of a year's EAG spatially explicit abundance dataset predictions from multiple weather-based scenarios can provide important information to land managers as they prepare for variable EAG dynamics each year. Informed annual predictions based on weather scenario−driven models have the potential to improve fire preparation decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2023.04.011","usgsCitation":"Dahal, D., Boyte, S., and Oimoen, M., 2023, Predicting exotic annual grass abundance in rangelands of the western United States using various precipitation scenarios: Rangeland Ecology and Management, v. 90, p. 221-230, https://doi.org/10.1016/j.rama.2023.04.011.","productDescription":"10 p.","startPage":"221","endPage":"230","ipdsId":"IP-147979","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":442239,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2023.04.011","text":"Publisher Index Page"},{"id":435197,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X84TAN","text":"USGS data release","linkHelpText":"Predicted exotic annual grass abundance in rangelands of the western United States using various precipitation scenarios for 2022"},{"id":420908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western Untied States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.45242355750227,\n 31.772396987581942\n ],\n [\n -105.1856936491761,\n 30.61399546239568\n ],\n [\n -103.99021246136934,\n 29.26283280175393\n ],\n [\n -103.16733033715471,\n 29.0039474055486\n ],\n [\n -102.42076887243283,\n 29.768041549861138\n ],\n [\n -101.95576605455685,\n 29.91825265532337\n ],\n [\n -102.93797212338004,\n 32.12981720017679\n ],\n [\n -103.29104623071706,\n 33.65426042984974\n ],\n [\n -99.71789757762204,\n 36.53137424080809\n ],\n [\n -99.79387490882343,\n 38.32597830940938\n ],\n [\n -104.7122126346035,\n 39.695295228078066\n ],\n [\n -104.9226858781989,\n 42.06948221578742\n ],\n [\n -101.68340311320938,\n 43.22455913455809\n ],\n [\n -101.91662344068945,\n 43.972451825245315\n ],\n [\n -102.87963556603896,\n 43.61356143611883\n ],\n [\n -102.18437570164278,\n 45.23113085310041\n ],\n [\n -102.63345526939472,\n 47.81616204600766\n ],\n [\n -103.44717923975836,\n 48.88719726526338\n ],\n [\n -120.6910476023584,\n 48.97188633840639\n ],\n [\n -122.70208295005929,\n 37.79126641008084\n ],\n [\n -121.84809706782082,\n 36.52429215449969\n ],\n [\n -121.04163391277447,\n 34.926756477563686\n ],\n [\n -120.43670816364622,\n 34.38681644210135\n ],\n [\n -118.39009707275434,\n 33.78569314825347\n ],\n [\n -117.21108571885287,\n 32.40614115660614\n ],\n [\n -114.51291465224432,\n 32.69460597026193\n ],\n [\n -114.73627119941546,\n 32.42891363567611\n ],\n [\n -111.10415956640946,\n 31.340607654617102\n ],\n [\n -108.17206424833958,\n 31.203549116979488\n ],\n [\n -107.9994867044243,\n 31.734373523939368\n ],\n [\n -106.45242355750227,\n 31.772396987581942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dahal, Devendra 0000-0001-9594-1249","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":192023,"corporation":false,"usgs":false,"family":"Dahal","given":"Devendra","affiliations":[],"preferred":false,"id":883228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":883229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oimoen, Michael","contributorId":329763,"corporation":false,"usgs":false,"family":"Oimoen","given":"Michael","affiliations":[{"id":65508,"text":"KBR, Contractor to the USGS EROS Center","active":true,"usgs":false}],"preferred":false,"id":883230,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248872,"text":"70248872 - 2023 - Ground motion and seismic hazard in the central and eastern United States","interactions":[],"lastModifiedDate":"2026-03-19T15:08:47.759038","indexId":"70248872","displayToPublicDate":"2023-09-01T10:02:25","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":21641,"text":"Technical Letter Report","active":true,"publicationSubtype":{"id":1}},"title":"Ground motion and seismic hazard in the central and eastern United States","docAbstract":"This report describes work carried out under the U.S. Nuclear Regulatory Commission (NRC) Interagency Agreement to the U.S. Geological Survey (USGS) “Research to Support NRC’s Seismic Hazard Analyses” for Task 3, “Seismic Hazard and Ground Motion Models.” The focus of this work has been on evaluation of the Next Generation Attenuation (NGA)-East groundmotion models (GMMs) with available ground-motion data and evaluation of alternative methods for characterizing epistemic uncertainty for probabilistic seismic hazard analysis (PSHA).
When the Interagency Agreement commenced, the USGS’s National Seismic Hazard Model (NSHM) was being updated, and a significant part of the update for the 2018 NSHM included the introduction of new GMMs for the central and eastern United States (CEUS) (Petersen et al., 2020). In addition to the implementation of the then-recently developed NGA-East GMMs (Goulet et al., 2018), the ground-motion characterization for the CEUS in the 2018 NSHM also included a logic-tree branch with weights applied to the updated “adjusted seed” models that were developed as part of the NGA-East process and in updates by the GMM developers.
The Statement of Work for Task 3 of the NRC Interagency Agreement to the USGS included the following parts: (1) Describe technically acceptable approaches in combining GMMs for use in PSHA calculations; (2) Evaluate the effect of using different sets of GMMs (NGA-East SSHAC versus NGA-East USGS) on PSHA calculations; (3) Describe the results of the GMM testing against recorded data, and provide a recommendation on the GMMs application for use in the PSHA; (4) Evaluate the impacts of recently updated individual GMMs on the published NGAEast models; and (5) Submit a final Technical Letter Report documenting results of this task.
We present results from this work in two sections: (Chapter 1) Updated Central and Eastern United States Ground Motions and Ground-Motion Analyses; and (Chapter 2) Approaches to Combining Ground-Motion Models for Probabilistic Seismic Hazard Analysis in the Central and Eastern United States.
","language":"English","publisher":"U.S. Nuclear Regulatory Commission","usgsCitation":"Moschetti, M.P., Thompson, E.M., Boyd, O.S., Engler, D.T., Worden, B., Ferragut, G., Rezaeian, S., and Powers, P.M., 2023, Ground motion and seismic hazard in the central and eastern United States: Technical Letter Report, 73 p.","productDescription":"73 p.","ipdsId":"IP-154468","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"central and eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.90807059528223,\n 48.94073422059739\n ],\n [\n -106.90807059528223,\n 20.331161730583176\n ],\n [\n -61.27021618898843,\n 20.331161730583176\n ],\n [\n -61.27021618898843,\n 48.94073422059739\n ],\n [\n -106.90807059528223,\n 48.94073422059739\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":883994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883995,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Worden, Bruce","contributorId":64648,"corporation":false,"usgs":true,"family":"Worden","given":"Bruce","affiliations":[],"preferred":false,"id":957156,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ferragut, Gabriel Christian 0000-0002-0776-9176","orcid":"https://orcid.org/0000-0002-0776-9176","contributorId":330101,"corporation":false,"usgs":true,"family":"Ferragut","given":"Gabriel Christian","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":883996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883998,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70237615,"text":"70237615 - 2023 - Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits","interactions":[],"lastModifiedDate":"2023-09-19T14:52:37.538067","indexId":"70237615","displayToPublicDate":"2023-09-01T09:46:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits","docAbstract":"Fluorine-rich granites and rhyolites occur throughout the southern Rocky Mountains, but the origin of F-enrichment has remained unclear. We test if F-enrichment could be inherited from ancient mafic lower crust by: (1) measuring amphibole compositions, including F and Cl contents, of lower crustal mafic granulite xenoliths from northern Colorado to determine if they are unusually enriched in halogens; (2) analyzing whole-rock elemental and Sr, Nd, and Pb isotopic compositions for upper crustal Cretaceous to Oligocene igneous rocks in Colorado to evaluate their sources; and (3) comparing batch melting models of mafic lower crustal source rocks to melt F and Cl abundances derived from biotite data from the F-rich silicic Never Summer batholith. This approach allows us to better determine if the mafic lower crust was pre-enriched in F, if it is concentrated enough to generate F-rich anatectic melts, and if geochemical data support an ancient lower crustal origin for the F-rich rocks in the southern Rocky Mountains.
Electron microprobe analyses of amphibole in lower crustal mafic granulite xenoliths show they contain 0.56–1.38 wt% F and 0.45–0.73 wt% Cl. Titanium in calcium amphibole thermometry indicates that the amphiboles equilibrated at high to ultrahigh temperature conditions (805 to 940 °C), and semiquantitative amphibole thermobarometry indicates the amphiboles equilibrated at 0.5 to 1.0 GPa prior to entrainment in magmas during the Devonian. Mass balance calculations, based on these new measurements, indicate parts of the mafic lower crust in Colorado are at least 3.5 times more enriched in F than average mafic lower crust. Intrusions coeval with the Laramide Orogeny (75 to 38 Ma) pre-date F-rich magmatism in Colorado and have Sr and Nd isotopic compositions consistent with mafic lower crust ± mantle sources, but many of these intrusions contain elevated Sr/Y ratios (>40) that suggest amphibole was a stable phase during magma generation. The F-rich igneous rocks from the Never Summer igneous complex and Colorado Mineral Belt also have Sr and Nd isotopic compositions that overlap with the lower crustal mafic granulite xenoliths, but they have lower Sr/Y, higher Nb and Y abundances, and distinctly less radiogenic 206Pb/204Pbi compositions than preceding Laramide magmatism. Batch melt modeling indicates low-degree partial melts derived from rocks similar to the mafic lower crustal xenoliths we analyzed can yield silicic melts with >2000 ppm F, similar to estimated F melt concentrations for silicic melts that are interpreted to be parental to evolved leucogranites.
We suggest that F-rich silicic melts in the southern Rocky Mountains were sourced from garnet-free mafic lower crust, and that fluid-absent breakdown of amphibole in ultrahigh temperature metamorphic rocks was a key process in their generation. Based on the composition of high-F amphibole measured from lower crustal xenoliths, the temperature of amphibole breakdown and melt generation for these F-enriched source rocks is likely >100 °C higher than similar lower crust with low or average F abundances. As such, these source rocks only melted during periods of unusually high heat flow into the lower crust, such as during an influx of mantle-derived magmas related to rifting or the post-Laramide ignimbrite flare-up in the region. These data have direct implications for the genesis of porphyry Mo mineralization, because they indicate that pre-enrichment of F in the deep crust could be a necessary condition for later anatexis and generation of F-rich magmas.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2022-8503","usgsCitation":"Rosera, J.M., Frazer, R.E., Mills, R.D., Jacob, K., Gaynor, S., Coleman, D., and Farmer, G.L., 2023, Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits: American Mineralogist, v. 108, no. 9, p. 1573-1596, https://doi.org/10.2138/am-2022-8503.","productDescription":"24 p.","startPage":"1573","endPage":"1596","ipdsId":"IP-136845","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":442244,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.2138/am-2022-8503","text":"External Repository"},{"id":420952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Colorado Mineral Belt","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.67084182013525,\n 40.707591104691545\n ],\n [\n -108.59155062790768,\n 40.707591104691545\n ],\n [\n -108.59155062790768,\n 36.46218720422068\n ],\n [\n -104.67084182013525,\n 36.46218720422068\n ],\n [\n -104.67084182013525,\n 40.707591104691545\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":854657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frazer, Ryan Edward 0000-0002-7319-1894","orcid":"https://orcid.org/0000-0002-7319-1894","contributorId":297924,"corporation":false,"usgs":true,"family":"Frazer","given":"Ryan","email":"","middleInitial":"Edward","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":854658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mills, Ryan D.","contributorId":297925,"corporation":false,"usgs":false,"family":"Mills","given":"Ryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":854659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacob, Kristin","contributorId":297926,"corporation":false,"usgs":false,"family":"Jacob","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":854660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaynor, Sean P.","contributorId":297927,"corporation":false,"usgs":false,"family":"Gaynor","given":"Sean P.","affiliations":[],"preferred":false,"id":854661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coleman, Drew S.","contributorId":297928,"corporation":false,"usgs":false,"family":"Coleman","given":"Drew S.","affiliations":[],"preferred":false,"id":854662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Farmer, G. Lang","contributorId":15075,"corporation":false,"usgs":false,"family":"Farmer","given":"G.","email":"","middleInitial":"Lang","affiliations":[],"preferred":false,"id":854663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248459,"text":"70248459 - 2023 - Constraints on the genesis of Au veins in interior Alaska: Evidence from geochronology and vein textures","interactions":[],"lastModifiedDate":"2023-09-14T14:09:36.134544","indexId":"70248459","displayToPublicDate":"2023-09-01T09:08:45","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Constraints on the genesis of Au veins in interior Alaska: Evidence from geochronology and vein textures","docAbstract":"The origin of Au-bearing, low sulfide quartz veins in the Pogo and Tibbs Creek regions of interior Alaska remain enigmatic. Intrusion-related Au and mesozonal orogenic vein models have both been proposed (Thompson and Newberry, 2000; Rhys et al., 2003; Goldfarb et al., 2022; Dilworth et al., 2007). To date, studies of igneous geochronology and metamorphic timing have shown that gold veins formed between intervals of magmatism and post-date regional metamorphic fabrics. Relatively little description of detailed mineralogy, vein textures, and absolute timing of mineralization exist – resulting in new questions about the deposit origin. This study attempts to relate these parameters through investigation of new U-Pb crystallization and Re-Os mineralization ages combined with detailed descriptions of vein textures to constrain the origin of the veins.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SGA 2023: Mineral resources in a changing world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SGA 2023: Mineral Resources in a Changing World","conferenceDate":"August 29-September 1, 2023","conferenceLocation":"Zürich, Switzerland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Kreiner, D.C., Thompson, W., Caine, J., Ball, A., Holm-Denoma, C., O’Sullivan, P., and Stein, H.J., 2023, Constraints on the genesis of Au veins in interior Alaska: Evidence from geochronology and vein textures, in Proceedings of SGA 2023: Mineral resources in a changing world, v. 3, Zürich, Switzerland, August 29-September 1, 2023, p. 80-83.","productDescription":"4 p.","startPage":"80","endPage":"83","ipdsId":"IP-150573","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":420790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -139.65067350561475,\n 61.56694937120494\n ],\n [\n -139.05576620713518,\n 63.59626040438653\n ],\n [\n -149.50481315806874,\n 65.5506094851404\n ],\n [\n -149.72901973722165,\n 63.35621506893642\n ],\n [\n -139.65067350561475,\n 61.56694937120494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kreiner, Douglas C. 0000-0002-4405-1403","orcid":"https://orcid.org/0000-0002-4405-1403","contributorId":220474,"corporation":false,"usgs":true,"family":"Kreiner","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":882986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, William","contributorId":329692,"corporation":false,"usgs":false,"family":"Thompson","given":"William","affiliations":[{"id":78688,"text":"Northern Star Resources","active":true,"usgs":false}],"preferred":false,"id":882987,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":882988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ball, Ashleigh","contributorId":329693,"corporation":false,"usgs":false,"family":"Ball","given":"Ashleigh","email":"","affiliations":[{"id":78688,"text":"Northern Star Resources","active":true,"usgs":false}],"preferred":false,"id":882989,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":882990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":882991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stein, Holly J. 0000-0002-9709-7165","orcid":"https://orcid.org/0000-0002-9709-7165","contributorId":210107,"corporation":false,"usgs":false,"family":"Stein","given":"Holly","email":"","middleInitial":"J.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":true,"id":882992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267362,"text":"70267362 - 2023 - Induced seismicity and its impact on existing seismic hazard analysis","interactions":[],"lastModifiedDate":"2025-05-21T13:52:21.335242","indexId":"70267362","displayToPublicDate":"2023-09-01T08:48:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":21641,"text":"Technical Letter Report","active":true,"publicationSubtype":{"id":1}},"title":"Induced seismicity and its impact on existing seismic hazard analysis","docAbstract":"We develop a scheme for mapping changes in earthquake rates within a region in near-real-time. A specific goal of the work is to track recent changes in the rates of induced earthquakes in the central and eastern United States. We map rates in a time window of interest, map rates in a preceding time window, and then ratio the two maps to show changes. A proof-of-concept map is first prepared, comparing rates during the first six months of 2010 with rates from the preceding five years; this demonstration map shows, among other things, the growth of induced seismicity in Oklahoma during 2010. We then present a series of ten ratio maps: the first six months of 2018 compared with the preceding five years, and so on in six-month increments through the end of 2022. These maps show changes in the rates and locations of induced earthquakes, as well as other seismicity trends. Map regions, time windows, and other model parameters are easily adaptable for other applications.","language":"English","publisher":"U.S. Nuclear Regulatory Comission","usgsCitation":"Mueller, C., and Shumway, A., 2023, Induced seismicity and its impact on existing seismic hazard analysis: Technical Letter Report, xv, 17 p.","productDescription":"xv, 17 p.","ipdsId":"IP-152895","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":486279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":486278,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nrc.gov/docs/ML2325/ML23257A188.pdf"}],"noUsgsAuthors":false,"publicationDate":"2023-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":937973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937974,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252959,"text":"70252959 - 2023 - Interstate 15 wildlife crossing design considerations for focal wildlife species - Santa Ana-Palomar Mountains Linkage southern California","interactions":[],"lastModifiedDate":"2024-04-12T13:52:55.734858","indexId":"70252959","displayToPublicDate":"2023-09-01T08:38:51","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Interstate 15 wildlife crossing design considerations for focal wildlife species - Santa Ana-Palomar Mountains Linkage southern California","docAbstract":"The Nature Conservancy (TNC) and the California Department of Transportation (Caltrans), along with landowners including San Diego State University, California Department of Fish and Wildlife, Western Riverside Regional Conservation Authority and Riverside County Flood Control District are developing wildlife crossing infrastructure projects along a 3-mile stretch of Interstate 15 (I-15) in the Santa Ana-Palomar Mountains Linkage (hereafter ‘Linkage’) in southern California. These crossings will provide a critical missing link that will help reconnect wildlife in the coastal Santa Ana Mountains west of I-15 with those in the interior Palomar and Eastern Peninsular ranges to the east of I-15. The Linkage supports intact and diverse habitats including coastal sage scrub, grasslands, chaparral, and oak and riparian woodlands, and has been a focus of regional conservation efforts for the last 30 years.
The three wildlife crossing infrastructure projects include enhancement of the existing Temecula Creek I-15 Bridge, construction of a new vegetated wildlife overcrossing, and construction of a new stand-alone wildlife culvert.
Given the challenges and level of financial investment required to secure wildlife crossings for I-15 in the Linkage, TNC and Caltrans proposed that planning efforts would benefit from input by taxonomic experts on design concepts that meet the needs of the broadest range of wildlife. While wildlife crossings are becoming more common, optimal designs that meet the needs of a variety of wildlife species are largely unknown and can be site specific. To address this challenge, we held a workshop in February 2022 that brought together over 50 wildlife experts to brainstorm and identify specific design considerations for various focal wildlife species groups (medium/large mammals, small animals, birds, bats, plants, and invertebrates) that might use the identified I-15 wildlife crossings (The Nature Conservancy 2022).
Lead experts for each focal species group worked together to identify specific wildlife crossing features or attributes for each of the three proposed wildlife crossings.
Specific attributes evaluated by experts for each crossing type and species group included, at a minimum:
• Crossing Structure Attributes;
o Habitat features? (cover, habitat structure, substrate, moisture, light and noise mitigation)
• Crossing Approach Area Features;
o Habitat features (cover type/density, substrate, water, light and noise mitigation)
• Barrier design to reduce roadkill and/or to funnel wildlife to the crossing;
• Additional research to resolve uncertainties related to crossing design
Based on the design considerations for each potential crossing type, the experts then weighed in on the suitability of the existing location and probability of use by their focal species or groups of species. With proposed design features, Temecula Creek Bridge has moderate or high probability of use by 27 of the 36 focal wildlife species assessed, while the vegetated overcrossing could meet the needs of 26 of the 36 species. When combined, Temecula Creek Bridge and the vegetated overcrossing have a moderate or high probability of use for 34 of the 36 species. The wildlife culvert has a moderate or high level of expected use by 10 of the 36 focal species and could serve connectivity needs for representative species from all but the bird and plant species groups.
","language":"English","publisher":"The Nature Conservancy","usgsCitation":"Smith, T., Brehme, C.S., Carpenter, J., Frost, N.A., Jennings, M., Kus, B., Quinnell, S., Straham, S., and Vickers, T.W., 2023, Interstate 15 wildlife crossing design considerations for focal wildlife species - Santa Ana-Palomar Mountains Linkage southern California, iv, 46 p.","productDescription":"iv, 46 p.","ipdsId":"IP-156534","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":427729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427723,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.scienceforconservation.org/products/interstate-15-wildlife-crossing-design"}],"country":"United States","state":"California","otherGeospatial":"Santa Ana-Palomar Mountains Linkage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.96277940038678,\n 33.17061852067067\n ],\n [\n -116.96277940038678,\n 33.583670223835924\n ],\n [\n -117.44162796500501,\n 33.583670223835924\n ],\n [\n -117.44162796500501,\n 33.17061852067067\n ],\n [\n -116.96277940038678,\n 33.17061852067067\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Trish","contributorId":335587,"corporation":false,"usgs":false,"family":"Smith","given":"Trish","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":898763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":898764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpenter, Jill","contributorId":335588,"corporation":false,"usgs":false,"family":"Carpenter","given":"Jill","email":"","affiliations":[{"id":80443,"text":"LSA Associates","active":true,"usgs":false}],"preferred":false,"id":898765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Nancy A.","contributorId":200382,"corporation":false,"usgs":false,"family":"Frost","given":"Nancy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":898766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jennings, Megan","contributorId":298254,"corporation":false,"usgs":false,"family":"Jennings","given":"Megan","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":898767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":898768,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quinnell, Scott","contributorId":335593,"corporation":false,"usgs":false,"family":"Quinnell","given":"Scott","email":"","affiliations":[],"preferred":false,"id":898780,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Straham, Spring","contributorId":335589,"corporation":false,"usgs":false,"family":"Straham","given":"Spring","email":"","affiliations":[{"id":80444,"text":"Wildspring Ecology","active":true,"usgs":false}],"preferred":false,"id":898769,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vickers, T. Winston","contributorId":198755,"corporation":false,"usgs":false,"family":"Vickers","given":"T.","email":"","middleInitial":"Winston","affiliations":[],"preferred":false,"id":898770,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70248041,"text":"70248041 - 2023 - The consequences of neglecting reservoir storage in national-scale hydrologic models: An appraisal of key streamflow statistics","interactions":[],"lastModifiedDate":"2024-02-26T15:39:42.549578","indexId":"70248041","displayToPublicDate":"2023-09-01T08:12:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"The consequences of neglecting reservoir storage in national-scale hydrologic models: An appraisal of key streamflow statistics","docAbstract":"A better understanding of modeled streamflow errors related to basin reservoir storage is needed for large regions, which normally have many ungaged basins with reservoirs. We quantified the difference between modeled and observed streamflows for one process-based and three statistical-transfer hydrologic models, none of which explicitly accounted for reservoir storage. Streamflow statistics representing low to high flows, seasonality, annual variability, and daily autocorrelation were examined at 1082 study basins across the conterminous USA. All models increasingly overpredict (or decreasingly underpredict) observed annual maximum flows with increasing storage. Correlations between absolute values of errors for low-flow statistics and storage are often larger in magnitude than those for signed errors—additional storage is associated with increases in model errors in both directions even when its overall effect in one direction is weak. The rate of increase in absolute values of model errors was nonlinear for most statistics. For low flows, model errors had a change point to larger errors at 48 days of reservoir storage (relative to long-term mean daily flow); mean and high flows had change points at 147 to 176 days. We present predicted-to-observed errors for nine streamflow statistics over a large range of reservoir storage to help modelers and users of modeled streamflow understand the amount of storage for which explicit reservoir modeling is needed.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13161","usgsCitation":"Hodgkins, G.A., Over, T.M., Dudley, R., Russell, A.M., and LaFontaine, J.H., 2023, The consequences of neglecting reservoir storage in national-scale hydrologic models: An appraisal of key streamflow statistics: Journal of the American Water Resources Association, v. 60, no. 1, p. 110-131, https://doi.org/10.1111/1752-1688.13161.","productDescription":"22 p.","startPage":"110","endPage":"131","ipdsId":"IP-122614","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":420408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"60","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Amy M. 0000-0003-0582-0094 arussell@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0094","contributorId":200011,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","email":"arussell@usgs.gov","middleInitial":"M.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881601,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881602,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259736,"text":"70259736 - 2023 - Pre-eruptive outgassing and pressurization, and post-fragmentation bubble nucleation, recorded by vesicles in breadcrust bombs from vulcanian activity at Guagua Pichincha Volcano, Ecuador","interactions":[],"lastModifiedDate":"2024-10-22T12:23:03.054841","indexId":"70259736","displayToPublicDate":"2023-09-01T07:21:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7514,"text":"Journal of Geophysical Research - Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Pre-eruptive outgassing and pressurization, and post-fragmentation bubble nucleation, recorded by vesicles in breadcrust bombs from vulcanian activity at Guagua Pichincha Volcano, Ecuador","docAbstract":"Breadcrust bombs formed during Vulcanian eruptions are assumed to originate from the shallow plug or dome. Their rim to core texture reflects the competition between cooling and degassing timescales, which results in a dense crust with isolated vesicles contrasting with a highly vesicular vesicle network in the interior. Due to relatively fast quenching, the crust can shed light on pre- and syn-eruptive conditions prior to or during fragmentation, whereas the interior allows us to explore post-fragmentation vesiculation. Investigation of pre- to post-fragmentation processes in breadcrust bombs from the 1999 Vulcanian activity at Guagua Pichincha, Ecuador, via 2D and 3D textural analysis reveals a complex vesiculation history, with multiple, spatially localized nucleation and growth events. Large vesicles (Type 1), present in low number density in the crust, are interpreted as pre-eruptive bubbles formed by outgassing and collapse of a permeable bubble network during ascent or stalling in the plug. Haloes of small, syn-fragmentation vesicles (Type 2), distributed about large vesicles, are formed by pressurization and enrichment of volatiles in these haloes. The nature of the pressurization process in the plug is discussed in light of seismicity and ground deformation signals, and previous textural and chemical studies. A third population (Type 3) of post-fragmentation small vesicles appears in the interior of the bomb, and growth and coalescence of Type 2 and 3 vesicles causes the transition from isolated to interconnected bubble network in the interior. We model the evolution of viscosity, bubble growth rate, diffusion timescales, bubble radius and porosity during fragmentation and cooling. These models reveal that thermal quenching dominates in the crust whereas the interior undergoes a viscosity quench caused by degassing, and that the transition from crust to interior corresponds to the onset of percolation and development of permeability in the bubble network.
Life history diversity is generated and maintained in part by density-dependent fitness tradeoffs that inhibit a single trait value from reaching fixation. While central to our understanding of evolution, demonstrating density dependence in the strength of fitness tradeoffs is difficult in natural systems. The timing of reproduction is a key life history trait that determines access to breeding habitat and exposure of offspring to competitive interactions and environmental conditions. Understanding the processes underlying diversity in reproductive timing will aid efforts to increase adaptive capacity under global environmental change. Here, we used detailed field studies, genetic parentage assignment, and simulation modeling to evaluate the fitness tradeoffs associated with the timing of reproduction for Yellowstone cutthroat trout Oncorhynchus clarkii bouvieri in groundwater-dominated tributaries to the upper Snake River, Wyoming, USA. We conducted our study across two years to understand how the strength of tradeoffs changes with population density. We found that early breeders experienced reduced reproductive success relative to later breeders due to the negative impact of nest superimposition (where later breeders construct nests overlapping those constructed previously) on embryo survival. However, as the risk of superimposition declined in the low-density year and early breeders experienced fewer losses, reproductive success became more similar among individuals breeding at different times. Further, in the spring following the critical period for growth and survival, offspring of early breeders had experienced longer growing seasons, attained larger body sizes, and were equally abundant relative to those of later breeders, suggesting that fitness losses due to superimposition may be offset by size-dependent competitive ability and overwinter survival. Our results illustrate a mechanism underlying diversity in the timing of reproduction for salmonids. This type of life history diversity will help to ensure the resilience and stability of salmonid populations attempting to adapt to changing local stressors associated with global climate change.
Nest survival has been identified as one of the most influential vital rates causing population change in game birds, and depredation, often influenced by habitat loss and fragmentation, is the primary cause of nest failure of upland game birds. We were interested in quantifying and comparing the perspectives of landowners and biologists in South Dakota regarding complex predator-prey interactions to improve communication and management efficacy. We developed a questionnaire regarding the following: 1) general attitude statements about game bird species; 2) perceived impacts of 9 factors (e.g., development, pollution, predators) and 13 potential predators on game bird abundances; and 3) attitude statements regarding use of lethal predator control and nesting habitat management practices. A cluster analysis using landowner attitude statements about predator management identified 3 landowner segments that had strong (most supportive; 37%), moderate (moderately supportive; 35%), or weak (least supportive; 28%) attitude statements about lethal predator control. Landowner segments most supportive and moderately supportive of predator control rated predators as the primary negative factor impacting game bird abundances and agreed that predators were the primary cause of game bird abundance declines, whereas the landowner segment least supportive of predator control rated habitat loss as the top factor and disagreed that predators were the primary cause of game bird declines. Biologists rated habitat loss as the top factor negatively impacting game bird abundances and disagreed that predators were the primary cause of game bird abundance declines. Thus, when considering the effectiveness of strategies to reduce nest depredation, most landowners focused on the direct cause of nest failures (predators), whereas biologists focused on an indirect cause (habitat loss). Perception differences among these groups emphasizes the need for better communication on proximate and ultimate factors affecting game bird populations and how these differences may impact management decisions.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1443","usgsCitation":"Fina, S., Gigliotti, L.M., Pearse, A., and Stafford, J.D., 2023, Landowner and biologist perceptions of game bird predators and management: Wildlife Society Bulletin, v. 47, no. 3, e1443, 15 p., https://doi.org/10.1002/wsb.1443.","productDescription":"e1443, 15 p.","ipdsId":"IP-129641","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1443","text":"Publisher Index Page"},{"id":480738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","county":"Faulk County, Hand County","otherGeospatial":"north-central South Dakota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.7249,45.2459],[-98.7184,45.2449],[-98.7209,45.1024],[-98.7186,44.8965],[-98.707,44.8959],[-98.7069,44.6348],[-98.7066,44.5481],[-98.7034,44.5481],[-98.6994,44.4354],[-98.7012,44.1979],[-98.8077,44.1979],[-98.8211,44.1986],[-98.9257,44.1976],[-98.9448,44.1982],[-99.0417,44.1971],[-99.0627,44.1982],[-99.1654,44.1974],[-99.1833,44.1967],[-99.2866,44.1959],[-99.2987,44.1964],[-99.2992,44.2397],[-99.302,44.5498],[-99.3123,44.5499],[-99.3132,44.8976],[-99.3287,44.8986],[-99.5728,44.8983],[-99.5743,45.0722],[-99.5719,45.1019],[-99.5751,45.2458],[-99.4735,45.2464],[-99.4515,45.2453],[-99.3414,45.2462],[-99.2177,45.2465],[-99.2054,45.2454],[-98.7249,45.2459]]]},\"properties\":{\"name\":\"Faulk\",\"state\":\"SD\"}}]}","volume":"47","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Fina, Samantha R.","contributorId":349107,"corporation":false,"usgs":false,"family":"Fina","given":"Samantha R.","affiliations":[{"id":5088,"text":"SDSU","active":true,"usgs":false}],"preferred":false,"id":924014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gigliotti, Larry M. 0000-0002-1693-5113 lgigliotti@usgs.gov","orcid":"https://orcid.org/0000-0002-1693-5113","contributorId":3906,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Larry","email":"lgigliotti@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T.","contributorId":349108,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":924016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stafford, Joshua D. 0000-0001-7590-8708 jstafford@usgs.gov","orcid":"https://orcid.org/0000-0001-7590-8708","contributorId":267260,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924013,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247995,"text":"sir20235047 - 2023 - Compound flood model for the lower Nooksack River and delta, western Washington—Assessment of vulnerability and nature-based adaptation opportunities to mitigate higher sea level and stream flooding","interactions":[],"lastModifiedDate":"2026-03-09T16:02:11.243737","indexId":"sir20235047","displayToPublicDate":"2023-08-31T12:53:36","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":"2023-5047","displayTitle":"Compound Flood Model for the Lower Nooksack River and Delta, Western Washington—Assessment of Vulnerability and Nature-Based Adaptation Opportunities to Mitigate Higher Sea Level and Stream Flooding","title":"Compound flood model for the lower Nooksack River and delta, western Washington—Assessment of vulnerability and nature-based adaptation opportunities to mitigate higher sea level and stream flooding","docAbstract":"Higher sea level and stream runoff associated with climate change is expected to lead to greater lowland flooding across the Pacific Northwest. Increases in stream runoff that range from 20 to 32 percent by the 2040s and from 52 to 72 percent by the 2080s is expected to steadily increase flood risk. Flood risk is also expected to increase in response to the landward shift in high tides and storm surge, which will retard downstream conveyance. The combination of higher stream runoff, which is expected to drive greater fluvial sediment delivery to the coast, and more frequent, higher coastal waters relative to present-day (2023) levels, which will retard streamflow, is projected to cause more sedimentation across coastal and estuarine systems, exacerbating the flood risk. In the Nooksack River delta of western Washington, as in many Puget Sound deltas, resilient adaptation planning to mitigate impacts to community assets and infrastructure, nationally essential agricultural areas, and valued habitats and restoration investments that support endangered and threatened salmon recovery are underway but are in need of more informed projections of compound flood hazards.
A Delft3D Flexible Mesh hydrodynamic model was constructed and used to assess changes in the extent, frequency, and timing of flood exposure associated with higher sea level and stream runoff projected to occur in the 2040s and 2080s. The model was also used to evaluate the change in and potential mitigating effects to flood exposure associated with individual and cumulative salmon-habitat-restoration strategies. Model simulations also evaluated the sensitivity of sedimentation to the individual and cumulative effects of higher fluvial delivery, trapping by sea-level rise, and changes in hydrodynamics associated with the rerouting of flows by proposed restoration strategies. The model performed well, having mean absolute errors for water levels below 1 foot (0.3 meters) when tested during a 2-year period for two recent flood events of record, the February 2, 2020, “Super Bowl flood” and the January 8, 2009, stream flood, both of which caused substantial flooding and damage across the study area. Fluvial discharge was found to dominate flood hazard at higher elevations in the study area, whereas near the coast, sea-level rise is computed to turn a less extreme 2-year (50 percent annual exceedance probability [AEP]) bankfull streamflow, which, at present (2023), causes nuisance flooding, into a more extreme 5-year (20 percent AEP) and 10 percent AEP stream-flood event by the 2050s and 2100, respectively.
The February 2020 Super Bowl flood was calculated to be a 10-year or 10 percent AEP peak-flow event, and the January 2009 flood was calculated to be a 25-year (4 percent AEP) peak-flow event. Extreme events such as the February 2020 Super Bowl flood and the January 2009 flood caused extensive damage across the Nooksack River floodplain, and model computations predict these magnitudes of events would have notably greater effect in the 2040s and 2080s in response to higher projected sea level and stream runoff. The modeled January 2009 flood is predicted to transform into a flood event, causing flood exposure that is comparable to the 100-year or 1 percent AEP flood by the 2040s. The modeled January 2009 flood is also predicted to exceed the flood exposure of the recent November 16, 2021, flood, which caused substantial damage in the lower Nooksack River floodplain and restricted access for emergency-management efforts on important arterial roadways in the area; the measured peak discharge during the November 16, 2021, flood exceeded that of the January 2009 flood.
Two of several identified alternative strategies that reroute floodwaters to restore salmon habitat were projected to reduce exposure to the increasingly impactful 10 and 4 percent AEP stream-flood events through the 2080s. The effects of the suggested alternatives, however, were found to reduce flow velocities, promote additional sedimentation, and reduce flow conveyance in the main-stem Nooksack River, a concern to flood-management efforts, navigation, and fishing. The model also suggests that main-stem channel sedimentation is likely, given projected climate change. Higher stream runoff that increases fluvial-sediment delivery and higher sea levels that retard downstream flow are expected to lead to greater sedimentation. Lastly, the model was used to assess the sensitivity of flood exposure to the individual and cumulative effects of climate changes, alternative strategies, and sedimentation, including recently observed decadal-scale aggradation patterns. These results indicate that sediment is likely to continue to be a challenge to flood-management efforts and that nature-based alternatives that benefit ecosystem restoration may also mitigate flood exposure for several decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235047","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency through Washington State Department of Fish and WildlifePacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Populations of endangered Banbury Springs limpet (Idaholanx fresti) and threatened Bliss Rapids snail (Taylorconcha serpenticola) are declining in springs north of the Snake River along the southern Gooding County boundary, in south-central Idaho. One hypothesis for the decline is that increased macrophyte growth, associated with elevated nitrate concentrations in the springs, is decreasing aquatic habitat for the limpet and snail populations. In support of U.S. Fish and Wildlife Service efforts to understand the population declines, the U.S. Geological Survey developed surrogate regression models to estimate nitrate concentrations at six springs influenced by upgradient agriculture, which results in an increase and decrease each year of streamflow, specific conductance, and nitrate concentrations. The surrogate regression models use continuous specific conductance data and streamflow data (available at two springs from existing U.S. Geological Survey streamgages).
The spring surrogate regression models showed that specific conductance can be an effective surrogate for nitrate in springs affected by agriculture and that the model results improved when streamflow data were included. Four of the six springs had surrogate regression models (using specific conductance and day of the year as explanatory variables) that performed well based on model summary statistics, and these models improved further with the inclusion of streamflow as an explanatory variable. The surrogate regression models at four springs had coefficient of determination (R2) values ranging from 0.79 to 0.94. The root mean squared error of the four models ranged from 0.07 to 0.11 milligrams per liter. Two of the six springs were not well modeled, with adjusted R2 values of 0.15 and 0.80. The surrogate regression models for these two springs also did not meet the required assumption of linearity between explanatory and response variables for linear regression. The surrogate regression models show that specific conductance can be an effective surrogate for nitrate in springs affected by agriculture and that models are improved where streamflow data are included. These surrogates improve understanding of nitrate concentration variability in the springs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235095","usgsCitation":"Skinner, K.D., 2023, Surrogate regression models estimating nitrate concentrations at six springs in Gooding County, south-central Idaho, 2018–22: U.S. Geological Survey Scientific Investigations Report 2023–5095, 22 p., https://doi.org/10.3133/sir20235095.","productDescription":"Report: vii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-147907","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":420343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5095/coverthb.jpg"},{"id":420347,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5095/sir20235095.XML"},{"id":420346,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5095/images"},{"id":420345,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235095/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5095"},{"id":420344,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5095/sir20235095.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5095"},{"id":420348,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BXIBF9","text":"USGS data release","description":"USGS data release","linkHelpText":"Surrogate regression model data for estimating nitrate concentrations at six springs in Gooding County, south-central Idaho"},{"id":501061,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115234.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","county":"Gooding County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115,\n 42.9167\n ],\n [\n -115,\n 42.6\n ],\n [\n -114.6,\n 42.6\n ],\n [\n -114.6,\n 42.9167\n ],\n [\n -115,\n 42.9167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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We investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge-n Seismic Survey in Oklahoma (LASSO). While it is well known that near-surface unconsolidated sediments can cause an apparent breakdown of earthquake self-similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825-station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P-wave ground motions below 8 Hz, the surface geology correlates with P-wave ground motions above 8 Hz and S-wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes (ML = 0.01–3) estimated using a standard single-spectra approach show negative correlations with the site-effect proxy, while the seismic moments show positive correlations. In contrast, the spectral-ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site-related biases requires at least 30 stations. Correcting for site-related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.
Shelters are critical for many species as protection from predators and extreme temperatures. Successful conservation of reptiles requires understanding both shelter site requirements and availability. The Eastern Indigo Snake (EIS; Drymarchon couperi) is endemic to the southeastern U.S. and is federally listed. Recovery has focused on maximizing unfragmented landscapes, with less attention on fine-scale features such as shelter sites. In the northern EIS range, Gopher Tortoise (Gopherus polyphemus) burrows are used extensively for shelter. Although EIS in peninsular Florida often shelter in tortoise burrows, they also use other shelters where tortoise burrows are scarce or absent. Solely focusing EIS survey and management efforts where Gopher Tortoises are present may overlook occupied habitats and misallocate resources. We investigated the importance of different shelter sites in central Florida using data from radio-tracked EIS. We modeled the use of shelter categories as a function of sex, season, and habitat using Bayesian multinomial Generalized Linear Models. Results showed that EIS in peninsular Florida used Gopher Tortoise burrows across all seasons and habitats. Tortoise burrow use was highest in xeric habitats and lowest in mesic habitats where burrows are most and least abundant, respectively. There was less variability in shelter site use in disturbed habitats and flatwoods. Tortoise burrow use by EIS in the cool season across sexes and habitats in our study was much lower than in southern Georgia. Our results indicate that EIS are less dependent on Gopher Tortoise burrows in peninsular Florida and that suitable habitats with few or no tortoise burrows could still provide conservation value for EIS.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Bolt, M., Bauder, J.M., Legare, M., Jenkins, C., Rothermel, B., and Breininger, D., 2023, Eastern Indigo snake (Drymarchon couperi) shelter site use In peninsular Florida, USA, and implicatIons for habItat conservatIon: Herpetological Conservation and Biology, v. 18, no. 2, p. 362-373.","productDescription":"12 p.","startPage":"362","endPage":"373","ipdsId":"IP-139825","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482919,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol18_issue2.html","linkFileType":{"id":8,"text":"xml"}},{"id":482920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, 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In recent decades, barred owls (Strix varia) have become a species of conservation concern as they invaded older forests of the US Pacific Northwest, and caused population declines of the closely related and federally threatened northern spotted owl (Strix occidentalis caurina). A simple and effective measure of barred owl body condition could help to understand how habitat quality varies within their new range, which in turn can inform their management and other aspects of their ecology. Using 77 barred owl carcasses collected during experimental removals in Washington and Oregon, USA, we measured the amount of lipid in each specimen with proximate body composition analysis. We then fit and compared (with adjusted R2 values) alternative linear regression models to estimate the percent lipids in dry mass of the owls based on morphometric body condition indices, a qualitative fat score of subcutaneous breast fat, sex and the time of year females were collected (relative to egg production). Adjusted R2 values for all models ranged from 0.49 to 0.87, with the best model including mass divided by foot-pad length, fat score, sex and the time of year a female was collected. Most models generated comparable estimates of percent lipids at a population level and we provided correction factors to apply these models when used with live barred owls, allowing for site-specific comparisons of body condition among individuals inhabiting a diversity of environmental conditions.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coad069","usgsCitation":"Baumbusch, R.C., Dugger, K., and Wiens, D., 2023, Estimating fat content in barred owls (Strix varia) with predictive models developed from direct measures of proximate body composition: Conservation Physiology, v. 11, no. 1, coad069, 9 p., https://doi.org/10.1093/conphys/coad069.","productDescription":"coad069, 9 p.","ipdsId":"IP-139469","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":442265,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad069","text":"Publisher Index Page"},{"id":435202,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BY17SZ","text":"USGS data release","linkHelpText":"Fat content and morphometric data in barred owls (Strix varia) in the Pacific Northwest"},{"id":422066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Baumbusch, Ryan C.","contributorId":331066,"corporation":false,"usgs":false,"family":"Baumbusch","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":79110,"text":"Oregon Cooperative Fish and Wildlife Research Unit, Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":886640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":886641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiens, David 0000-0002-2020-038X","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":267230,"corporation":false,"usgs":true,"family":"Wiens","given":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":886642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247959,"text":"70247959 - 2023 - Improvements and evaluation of the agro-hydrologic VegET model for large-area water budget analysis and drought monitoring","interactions":[],"lastModifiedDate":"2023-08-29T14:48:08.706864","indexId":"70247959","displayToPublicDate":"2023-08-29T09:26:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10778,"text":"Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Improvements and evaluation of the agro-hydrologic VegET model for large-area water budget analysis and drought monitoring","docAbstract":"We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.
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Inc., Contractor to the USGS EROS Center","active":true,"usgs":false}],"preferred":false,"id":881252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":259185,"corporation":false,"usgs":false,"family":"Khand","given":"Kul Bikram","affiliations":[{"id":52326,"text":"AFDS, Contractor to USGS ERSOS Center","active":true,"usgs":false}],"preferred":false,"id":881253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boiko, Olena 0000-0002-2007-7852","orcid":"https://orcid.org/0000-0002-2007-7852","contributorId":272079,"corporation":false,"usgs":false,"family":"Boiko","given":"Olena","email":"","affiliations":[{"id":56343,"text":"KBR, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":881254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":222983,"corporation":false,"usgs":false,"family":"Velpuri","given":"Naga Manohar","affiliations":[{"id":40633,"text":"CIGAR","active":true,"usgs":false}],"preferred":false,"id":881255,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249905,"text":"70249905 - 2023 - Macroscale analyses suggest invasive plant impacts depend more on the composition of invading plants than on environmental context","interactions":[],"lastModifiedDate":"2023-11-04T13:09:05.804684","indexId":"70249905","displayToPublicDate":"2023-08-29T08:02:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Macroscale analyses suggest invasive plant impacts depend more on the composition of invading plants than on environmental context","docAbstract":"Native biodiversity is threatened by the spread of non-native invasive species. Many studies demonstrate that invasions reduce local biodiversity but we lack an understanding of how impacts vary across environments at the macroscale. Using ~11,500 vegetation surveys from ecosystems across the United States, we quantified how the relationship between non-native plant cover and native plant diversity varied across different compositions of invading plants (measured by non-native plant richness and evenness) and environmental contexts (measured by productivity and human activity).
Continental United States.
Surveys from 1990s-present.
Terrestrial plant communities.
We fit mixed effects models to understand how native plant richness, diversity and evenness varied with non-native cover. We tested how this relationship varied when non-native cover interacted with non-native plant richness and evenness, and with productivity and human activity.
Across the United States, communities with greater cover of non-native plants had lower native plant richness and diversity but higher evenness, suggesting rare native plants can be lost while dominant plants decline in abundance. The relationship between non-native cover and native community diversity varied with non-native plant richness and evenness but was not associated with productivity and human activity. Negative associations were strongest in areas with low non-native richness and evenness, characterizing plant communities that were invaded by a dominant non-native plant.
Non-native plant cover provides a first approximation of invasion impacts on native community diversity, but the magnitude of impact depended on non-native plant richness and evenness. Relationships between non-native cover and native diversity were consistent in strength across continental scale gradients of productivity and human activity. Therefore, at the macroscale, invasive plant impacts on native plant communities likely depend more on the characteristics of the invading plants, that is the presence of a dominant invader, than on the environmental context.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13749","usgsCitation":"Beaury, E.M., Sofaer, H., Early, R., Pearse, I., Blumenthal, D.M., Corbin, J., Diez, J.M., Dukes, J., Barnett, D., Ibanez, I., Petri, L., Vilà, M., and Bradley, B., 2023, Macroscale analyses suggest invasive plant impacts depend more on the composition of invading plants than on environmental context: Global Ecology and Biogeography, v. 23, no. 11, p. 1964-1976, https://doi.org/10.1111/geb.13749.","productDescription":"13 p.","startPage":"1964","endPage":"1976","ipdsId":"IP-139929","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":442282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.13749","text":"Publisher Index 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[\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"23","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaury, Evelyn M.","contributorId":236820,"corporation":false,"usgs":false,"family":"Beaury","given":"Evelyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Early, Regan","contributorId":236832,"corporation":false,"usgs":false,"family":"Early","given":"Regan","email":"","affiliations":[],"preferred":false,"id":887632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blumenthal, Dana M.","contributorId":203896,"corporation":false,"usgs":false,"family":"Blumenthal","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":36745,"text":"USDA-ARS Rangeland Resources Research Unit","active":true,"usgs":false}],"preferred":false,"id":887634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corbin, Jeffrey","contributorId":331412,"corporation":false,"usgs":false,"family":"Corbin","given":"Jeffrey","email":"","affiliations":[{"id":65470,"text":"Union College","active":true,"usgs":false}],"preferred":false,"id":887635,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diez, Jeffrey M.","contributorId":169803,"corporation":false,"usgs":false,"family":"Diez","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":887636,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dukes, Jeffrey","contributorId":299987,"corporation":false,"usgs":false,"family":"Dukes","given":"Jeffrey","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":887637,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barnett, David","contributorId":174944,"corporation":false,"usgs":false,"family":"Barnett","given":"David","affiliations":[],"preferred":false,"id":887638,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ibanez, Ines","contributorId":236833,"corporation":false,"usgs":false,"family":"Ibanez","given":"Ines","affiliations":[],"preferred":false,"id":887639,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petri, Laís","contributorId":331416,"corporation":false,"usgs":false,"family":"Petri","given":"Laís","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":887640,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vilà, Montserrat","contributorId":331419,"corporation":false,"usgs":false,"family":"Vilà","given":"Montserrat","affiliations":[{"id":64996,"text":"University of Sevilla","active":true,"usgs":false}],"preferred":false,"id":887641,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bradley, Bethany A. 0000-0003-4912-4971","orcid":"https://orcid.org/0000-0003-4912-4971","contributorId":299998,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany A.","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":887642,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70248868,"text":"70248868 - 2023 - Potential economic consequences along migratory flyways from reductions in breeding habitat of migratory waterbirds","interactions":[],"lastModifiedDate":"2023-11-03T16:34:21.911286","indexId":"70248868","displayToPublicDate":"2023-08-29T07:17:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Potential economic consequences along migratory flyways from reductions in breeding habitat of migratory waterbirds","docAbstract":"The migration of species, often across continents, makes it difficult to quantify the cumulative effects of local- and regional-scale conservation actions. Further, variation in stakeholder interests, differing jurisdictional governance processes, priorities, and monitoring abilities across the migratory range shapes place-specific differences in management actions. These differences may lead management of migratory species to benefit both species and stakeholders in some places more than others. In the case of North American waterfowl, possible reduction of wetland protection in breeding areas may lead to substantive shifts in benefits among stakeholders across their range by adversely affecting recreational viewing and hunting opportunities for these species. To understand possible consequences of wetland loss in the U.S. Prairie Pothole Region, the breeding region for 12 focal species of waterfowl, on the recreation economics for these species, we modeled a causal pathway linking wetland loss in the breeding grounds to changes in duck abundance and then assessed the consequences of that change in abundance on recreational hunting and viewing within migratory flyways. Under a scenario where wetland protections cease, we find annual economic activity associated with recreation may decrease as much as \\$489 million at the highest levels of predicted wetland loss, the majority of it coming from impacts to viewing behavior in the Mississippi Flyway. The number of hunters may decline by as much as 18,000, leading to \\$32 million less in annual economic activity. At highest levels of wetland loss, viewing value is expected to decline by more than one-quarter. Lost economic value associated with reductions in recreation in the Mississippi and Central Flyway states is not likely to be overcome by increases in agricultural economic output in drained wetlands of the Prairie Pothole Region. Our analyses indicate local effects of national water policies likely have far-reaching consequences because of the multi-dimensional connections arising from place-specific differences in management action, global and national agricultural economic drivers of crop expansion, and the biotic phenomena of transcontinental avian migration. Reductions in habitat in one location could ramify to economic consequences throughout the continent through connections fostered by migrating waterfowl.
Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management. Environ Toxicol Chem 2023;42:2506–2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Mantle plumes originate at depths near the core−mantle boundary (~2,800 km). As such, they provide invaluable information about the composition of the deep mantle and insight into convection, crustal formation, and crustal recycling, as well as global heat and volatile budgets. In this Review, we discuss the effectiveness and challenges of using isotopic analyses of plume-generated rocks to infer mantle composition and to constrain geodynamic models. Isotopic analyses of plume-derived ocean island basalts, including radiogenic (Sr, Nd, Pb, Hf, W, noble gas) and stable isotopes (Li, C, O, S, Fe, Tl), permit determination of mantle plume composition, which in turn generate insight into mantle plume origins, dynamics, mantle heterogeneities, early-formed mantle reservoirs, crustal recycling processes, core−mantle interactions and mantle evolution. Nevertheless, the magmatic flux, temperature, tectonic environment and compositions of mantle plumes can vary. Consequently, plumes and their melts are best evaluated along a spectrum that acknowledges their different properties, particularly mantle flux, before making interpretations about the interior of the Earth. To provide insight into specific mantle and plume processes, future work should document correlations across elemental and isotopic data sets on the same sample powder, coordinate targeting sampling strategies, and refine stable isotopic fractionation factors through experiments. Such work will benefit from collaboration across geochemical laboratories, as well as among geochemists, mineral physicists, seismologists and geodynamicists.
3D geologic modeling and mapping often relies on gravity modeling to identify key geologic structures, such as basin depth, fault offset, or fault dip. Such gravity models generally assume either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments, with average densities typically derived from surface and drill-hole sampling. The noise contributed to the gravity anomaly by these density assumptions is zero in the homogeneous case and typically <200 μGal in the uncorrelated case. Rock bodies and sediments, however, show both a range of densities and spatial correlation of these densities, in both surface and drill-hole samples, and this correlation causes an increase in power in the low frequency content of the resulting gravity anomaly. Spatial correlation of densities can be modeled as a Gaussian random field (GRF), with the random field parameters derived from drill-hole and geologic map data. Data from alluvial fan sediments in southern Nevada indicate correlation lengths of up to 300 m in the vertical dimension and kilometers in the horizontal dimension. The resulting GRF density models show that the noise contributed to the measured gravity anomaly is of low frequency and can be several mGal in amplitude, contradicting the common attribution of lower frequencies to deeper sources. This low-frequency noise increases in power with an increase in sediment thickness. Its presence increases the ambiguity of interpretations of subsurface geologic body shape, such as basin analyses that attempt to quantify concealed basement fault depths, offsets, and dip angles. In the southwestern United States, where basin analyses are important for natural resource applications, such ambiguity increases the uncertainty of subsequent process modeling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.acags.2023.100131","usgsCitation":"Phelps, G., and Cronkite-Ratcliff, C., 2023, Near surface sediments introduce low frequency noise into gravity models: Applied Computing and Geosciences, v. 19, 100131, 18 p., https://doi.org/10.1016/j.acags.2023.100131.","productDescription":"100131, 18 p.","ipdsId":"IP-146760","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":442296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.acags.2023.100131","text":"Publisher Index Page"},{"id":432029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":908038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":908039,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248806,"text":"70248806 - 2023 - CGS: Coupled growth and survival model with cohort fairness","interactions":[],"lastModifiedDate":"2023-09-21T11:52:01.073506","indexId":"70248806","displayToPublicDate":"2023-08-27T06:46:51","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"CGS: Coupled growth and survival model with cohort fairness","docAbstract":"The potential recirculation of Klamath Strait Drain (hereafter called by its local name, “Klamath Straits Drain”) water into Ady Canal to reduce the drain discharge of high nutrient loads into the Klamath River was assessed by the U.S. Geological Survey for the Bureau of Reclamation. To study the feasibility of recirculation, this investigation evaluated three recirculation scenarios over a 10-year period from 2006 to 2015, as a series of 1-year model simulations. A combination of two existing hydrodynamic, water-temperature, and water-quality models (CE-QUAL-W2) were used, including (1) the Link-Keno reach of the Klamath River, using Klamath Straits Drain as a tributary and for calendar years 2006–11, and (2) the same Link-Keno model used for calendar years 2012–15 in combination with an independent Klamath Straits Drain model from 2012 to 2015. Model simulations using the water-quality models were configured for the base case conditions and three different sets of recirculation scenarios: the maximum year-round recirculation without limits (scenario 1), limited year-round recirculation fixed by the current pipe flow configuration (scenario 2), and limited seasonal recirculation (May–September) also fixed by the current pipe flow configuration (scenario 3).
In the base case, estimates of annual average daily total nitrogen loads and daily total phosphorus loads exported to the Klamath River from the Klamath Straits Drain were as much as 3,060 and 457 pounds per day (lbs/day), respectively. Currently (2023), the Total Maximum Daily Loads allocations for the Klamath Straits Drain are 21 and 268 lbs/day for total phosphorus and total nitrogen, respectively, so these maximum estimates exceed the current Total Maximum Daily Loads by greater than an order of magnitude. With scenario 1, load reductions occurred year-round for all constituents evaluated (total nitrogen, total phosphorus, 5-day biochemical oxygen demand [BOD5], 5-day carbonaceous biochemical oxygen demand) for the Klamath Straits Drain discharging to the Klamath River. Scenario 2 also had large reductions in total nitrogen, total phosphorus, and BOD5 loads. Substantial reductions did occur for scenario 3 but were constrained to only the active recirculation period from May through September. Despite the restricted period, the average reductions in the annual average daily load for total phosphorus and total nitrogen were 32.1 percent and 26.5 percent, respectively.
The Ady Canal diverts high nutrient loads from the Klamath River, so the loading tradeoffs to the Klamath River between no recirculation and the recirculation scenarios were calculated. On an annual basis, the overall net balance between the Klamath Straits Drain and Ady Canal resulted in more total nitrogen and total phosphorus load reductions to the Klamath River for the three recirculation scenarios than the base case, for most years. In contrast, the net balance for BOD5 loads was higher to the Klamath River for the three recirculation scenarios than the base case, for most years.
With the recirculation scenarios, the optimal recirculation periods to benefit Ady Canal, Klamath River, and Klamath Straits Drain did not always coincide. Recirculation would be most effective at reducing loads toward the Klamath Straits Drain Total Maximum Daily Load allocations in the spring (March–May) of each year. However, recirculation during these months would also increase salinity in the Ady Canal. In summer, recirculation would reduce Klamath Straits Drain loads toward the Total Maximum Daily Load allocations, though recirculation could decrease Klamath River water quality mostly because of decreased withdrawals of Klamath River water by the Ady Canal. Scenario 3 avoided recirculation into Ady Canal in the early spring months when salinity concerns would be the highest, while still decreasing nutrient loads exported from the Klamath Straits Drain to the Klamath River in the summer months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235059","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Smith, E.A., and Sullivan, A.B., 2023, Modeling the water-quality effects to the Klamath River from recirculation in drains and canals, Oregon and California, 2006–15: U.S. Geological Survey Scientific Investigations Report 2023–5059, 87 p., https://doi.org/10.3133/sir20235059.","productDescription":"Report: vii, 87 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-131325","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":420409,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235059/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5059"},{"id":420166,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5059/sir20235059.XML"},{"id":420165,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5059/images"},{"id":420163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5059/sir20235059.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5059"},{"id":420162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5059/coverthb.jpg"},{"id":500940,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115220.htm","linkFileType":{"id":5,"text":"html"}},{"id":420167,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RWP4F9","text":"USGS data release","description":"USGS data release","linkHelpText":"CE–QUAL–W2 water-quality models for Klamath Straits Drain recirculation scenarios, Klamath River, Oregon, 2006–15"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.21689162756053,\n 42.44595704887348\n ],\n [\n -122.21689162756053,\n 41.58110381721761\n ],\n [\n -121.27247261442969,\n 41.58110381721761\n ],\n [\n -121.27247261442969,\n 42.44595704887348\n ],\n [\n -122.21689162756053,\n 42.44595704887348\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s aquifers to determine the maximum annual yield for each groundwater basin. Because more than 20 years have elapsed since the final order was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an updated hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in reaches 3 and 4 of the Washita River aquifer in southern Oklahoma for a study period spanning 1980–2017. A hydrogeologic framework and conceptual model were developed to guide the construction and calibration of a numerical model of the Washita River aquifer. The numerical model was calibrated to water-table-altitude observations at selected wells, base-flow observations at selected U.S. Geological Survey streamgages, and the conceptual-model recharge.
Three types of groundwater-availability scenarios were run using the calibrated numerical model. These scenarios were used to (1) estimate equal-proportionate-share pumping rates, (2) quantify the potential effects of projected well withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought. With Washita River main-stem inflows, the 20-, 40-, and 50-year equal-proportionate-share pumping rates under normal recharge conditions were about 3.08 acre-feet per acre per year for reach 3 and about 3.80 acre-feet per acre per year for reach 4. Projected 50-year pumping scenarios were used to simulate the effects of modified well withdrawal rates. Because well withdrawals were less than 1 percent of the calibrated numerical-model water budget, changes to the well pumping rates had little effect on Washita River base flows and groundwater storage in the Washita River aquifer. A hypothetical 10-year drought scenario was used to simulate the potential effects of a prolonged period of reduced recharge on groundwater storage. Groundwater storage at the end of the drought period was 4.6 percent less than the groundwater storage of the calibrated numerical model at the end of the drought period.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501