Each mineral commodity chapter of the 2024 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2023 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D.
The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2024 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mcs2024","isbn":"978-1-4113-4544-7","usgsCitation":"U.S. Geological Survey, 2024, Mineral commodity summaries 2024: U.S. Geological Survey, 212 p., https://doi.org/10.3133/mcs2024.","productDescription":"Report: 212 p.; Data Release","numberOfPages":"212","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-160630","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":425029,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://tableau.usgs.gov/views/MCSDashboardWorkbook_2024-01-30/MCSDashboard?%3Aembed=y&%3AisGuestRedirectFromVizportal=y#7","text":"Data visualization"},{"id":424958,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/commodity-statistics-and-information","text":"Commodity Statistics and Information"},{"id":424956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/periodicals/mcs2024/mcs2024.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"MCS 2024"},{"id":424955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/periodicals/mcs2024/coverthb.jpg"},{"id":424959,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144BA54","text":"USGS data release","linkHelpText":"U.S. Geological Survey Mineral Commodity Summaries 2024 Data Release"},{"id":424957,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/mineral-commodity-summaries","text":"Mineral Commodity Summaries Prior to 2024"},{"id":499130,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115979.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Species with extensive geographical ranges pose special challenges to assessing drivers of wildlife disease, necessitating collaborative and large-scale analyses. The imperilled foothill yellow-legged frog (Rana boylii) inhabits a wide geographical range and variable conditions in rivers of California and Oregon (USA), and is considered threatened by the pathogen Batrachochytrium dendrobatidis (Bd). To assess drivers of Bd infections over time and space, we compiled over 2000 datapoints from R. boylii museum specimens (collected 1897–2005) and field samples (2005–2021) spanning 9° of latitude. We observed a south-to-north spread of Bd detections beginning in the 1940s and increase in prevalence from the 1940s to 1970s, coinciding with extirpation from southern latitudes. We detected eight high-prevalence geographical clusters through time that span the species' geographical range. Field-sampled male R. boylii exhibited the highest prevalence, and juveniles sampled in autumn exhibited the highest loads. Bd infection risk was highest in lower elevation rain-dominated watersheds, and with cool temperatures and low stream-flow conditions at the end of the dry season. Through a holistic assessment of relationships between infection risk, geographical context and time, we identify the locations and time periods where Bd mitigation and monitoring will be critical for conservation of this imperilled species.
Avian eggshell thickness is an important life history metric in birds and has broad applications across disciplines ranging from animal behavior to toxicology. Empirical eggshell thickness values for songbirds (Order Passeriformes) are under-represented in the literature due to the difficulty of measuring smaller eggs using traditional methods. We used a Hall-effect thickness gauge to measure eggs of five focal songbird species from California’s Central Valley: House Wren (Troglodytes aedon; n = 567), Tree Swallow (Tachycineta bicolor; n = 297), Ash-throated Flycatcher (Myiarchus cinerascens; n = 21), Western Bluebird (Sialia mexicana; n = 13), and Bewick’s Wren (Thryomanes bewickii; n = 5). We compared minimum eggshell thickness measurements at the equator and sharp pole, and we related eggshell thickness to other egg morphometrics and adult body mass. Eggshell thickness at the equator was 5.6% thicker in Ash-throated Flycatchers and 3.5% thinner in Tree Swallows compared with eggshell thickness at the sharp pole. Among species, eggshell thickness at the sharp pole was greater in species with larger eggs, whereas, within species, larger eggs were thinner at the sharp pole. Eggshells were 8% and 11% thinner in late incubation eggs (≥75% of total incubation duration) than early incubation (≤10% of total incubation duration) for House Wren and Tree Swallow eggs, respectively. Whenever possible, it is preferable to use empirical eggshell thickness data that are specific to the species and geographic region being studied, and a relatively new method used in this study allows accurate measurement of small eggs without having to compromise the integrity of preserved eggshell specimens.
","language":"English","publisher":"Journal of Field Ornithology","doi":"10.5751/JFO-00410-950103","usgsCitation":"Schacter, C., Peterson, S.H., Hartman, C.A., Herzog, M.P., and Ackerman, J.T., 2024, Eggshell thickness and egg morphometrics in five songbird species from the Central Valley, California: Journal of Field Ornithology, v. 95, no. 1, 3, 10 p., https://doi.org/10.5751/JFO-00410-950103.","productDescription":"3, 10 p.","ipdsId":"IP-154263","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":440588,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.5751/jfo-00410-950103","text":"Publisher Index Page"},{"id":435054,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GL21VQ","text":"USGS data release","linkHelpText":"Eggshell Thickness in 5 Songbird Species"},{"id":425282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schacter, Carley R. 0000-0001-5493-2768","orcid":"https://orcid.org/0000-0001-5493-2768","contributorId":333758,"corporation":false,"usgs":false,"family":"Schacter","given":"Carley R.","affiliations":[{"id":79969,"text":"USFWS; Former USGS employee","active":true,"usgs":false}],"preferred":false,"id":893844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254428,"text":"70254428 - 2024 - Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","interactions":[],"lastModifiedDate":"2024-05-24T11:59:35.15136","indexId":"70254428","displayToPublicDate":"2024-01-31T06:56:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","docAbstract":"As part of the U.S. Geological Survey’s 2023 50‐State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault‐based seismic source model that result in locally substantial hazard changes. The CEUS fault‐based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn) Project. Since then, new geologic investigations have led to revised fault and fault‐zone inputs, and the release of databases of fault‐based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault‐based sources in the NSHM, as well as added five new fault‐based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault‐based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS‐SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.
Arundo donax, commonly called Arundo cane, giant reed, or Carrizo cane, is an invasive bamboo-like perennial grass common in riparian areas throughout the southwestern United States. In Texas, not only does it negatively affect riparian ecosystems, but it has also become a problem for border security because it reduces visibility along the Rio Grande. To address these problems, in 2015 the Texas State Soil and Water Conservation Board was authorized by the Texas State Legislature to develop a program to eradicate Arundo cane along the Rio Grande. In 2020, the Texas State Soil and Water Conservation Board applied imazapyr and glyphosate herbicides along a 19.3-kilometer reach of the Rio Grande, northwest of Laredo, Texas. The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District, used WorldView-3 Standard high-resolution satellite imagery to map Arundo cane extent along the reach before, during, and after the herbicide-treatment period on June 30, 2020, September 26, 2020, and May 7, 2021, respectively. A maximum likelihood supervised classification analysis was computed on the images to map the spatial extent and estimate the area covered by Arundo cane. The estimated area covered by Arundo cane in the before classification was 1,282,000 square meters, in the during classification was 1,064,000 square meters, and in the after classification was 1,108,000 square meters. The qualitative comparison of the three images shows that there was an overall decrease in vegetation classified as Arundo cane throughout the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3512","issn":"2329-132X","collaboration":"Prepared in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District","programNote":"Water Resources Research Act Program","usgsCitation":"Villa, J., 2024, Mapping Arundo donax (Arundo cane) with multispectral imagery before, during, and after herbicide treatment along the Rio Grande in Webb County, Texas, 2020–21: U.S. Geological Survey Scientific Investigations Map 3512, 1 sheet, includes 7-p. pamphlet, https://doi.org/10.3133/sim3512.","productDescription":"Report: viii, 7 p.; 1 Sheet: 32.00 × 34.00 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-144135","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":424979,"rank":7,"type":{"id":30,"text":"Data 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more information about this publication, contact
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
Changes in the quantity of sand stored within river segments can affect aquatic and riparian habitat, archeological resources, and recreation. Since summer to fall of 2002, gaging stations on the Colorado River in Grand Canyon National Park and on its major tributaries and selected lesser tributaries have measured the mass of sand transported past each station, which allows for changes in the mass of sand stored between gaging stations to be calculated. Sand mass balances on six Colorado River segments are currently measured; the upstream two segments measure sand mass balance in Marble Canyon, the middle three segments measure sand mass balance within the majority of Grand Canyon, and the downstream-most segment—western Grand Canyon and the Lake Mead delta—measures the quantity of sand transported past Diamond Creek and ultimately deposited in Lake Mead.
Between July 1, 2017, and June 30, 2020, the amount of sand stored in the Colorado River in Marble Canyon decreased, whereas the sand mass balance in Grand Canyon was indeterminate. Of the 3 years of study presented herein, sand was eroded from Marble Canyon during sediment year 2018 (July 1, 2017–June 30, 2018), a year with less than 40 percent of the 2003–2020 mean Paria River sand input, and sediment year 2020 (July 1, 2019–June 30, 2020), a year with negligible Paria River sand input. During sediment year 2018, when the Little Colorado River supplied negligible sand, sand was also eroded from Grand Canyon. The sand mass balance was indeterminate for Grand Canyon during sediment year 2020. During sediment year 2019 (July 1, 2018–June 30, 2019) sand accumulated in both Marble Canyon and Grand Canyon. This sediment year had sand inputs from both the Paria River and the Little Colorado River of more than 170 percent the 2003–2020 mean, coupled with below post-1964 mean discharge from Glen Canyon Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231093","usgsCitation":"Griffiths, R.E., Topping, D.J., and Unema, J.A., 2024, Changes in sand storage in the Colorado River in Grand Canyon National Park from July 2017 through June 2020: U.S. Geological Survey Open-File Report 2023–1093, 9 p., https://doi.org/10.3133/ofr20231093.","productDescription":"v, 9 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-147171","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":425105,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1093/images"},{"id":425103,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1093/ofr20231093.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":425102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1093/covrthb.jpg"},{"id":425104,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1093/ofr20231093.xml","linkFileType":{"id":8,"text":"xml"}},{"id":499200,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116003.htm","linkFileType":{"id":5,"text":"html"}},{"id":425106,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231093/full"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.67941991219553,\n 37.29250555492341\n ],\n [\n -114.67941991219553,\n 35.64936002497116\n ],\n [\n -111.03195897469551,\n 35.64936002497116\n ],\n [\n -111.03195897469551,\n 37.29250555492341\n ],\n [\n -114.67941991219553,\n 37.29250555492341\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
In 2012, the Secretary of the U.S. Department of the Interior placed a 20-year limit on mineral extraction on Federal lands in the Grand Canyon watershed to permit further study of the environmental effects of uranium mining. Tribal concerns were also noted by the U.S. Department of the Interior and included in the rationale for the decision stating Tribal resource impacts could not be mitigated and cultural degradation may result should mining occur within sacred and traditional places of Tribal peoples. The U.S. Geological Survey previously developed a conceptual framework for a uranium mine in the region that defined contaminant sources and physical, chemical, and biological processes that affect contaminant transport to ecological receptors. However, published risk models have largely ignored exposure pathways relevant to Tribal communities in terms of traditional uses and existential values of the resources included. This report presents an updated conceptual risk framework for uranium mining that includes indigenous knowledge components informed by the Havasupai Tribe perspective.
The expansion of the framework relied on connecting to the foundations of the Havasupai ceremonial wheel—food, environment, belief system, and ceremony. The framework is applied to uranium development near Red Butte, an important gathering place for multiple federally recognized Tribes including the Havasupai, Hopi, Navajo, and Zuni. Plants and animals important to the Havasupai for subsistence, ceremonial, and medicinal practices and how mining affects these practices are described. The final framework is presented in English and Havasupai to aid Tribal members in understanding how the framework relates to their community and to help preserve the language and historical cultural practices for future generations. New or expanded exposure pathways include inhalation, ingestion, and absorption from traditional food and medicines as well as ceremonial practices. The updated framework has allowed the U.S. Geological Survey to take first steps in understanding resources important to the Havasupai and to build relationships to improve co-production in our research. Ideally, the framework and other research can be used, along with indigenous knowledge, in Federal research and decision making for mining in the Grand Canyon region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231092","usgsCitation":"Tilousi, C., and Hinck, J.E., 2024, Expanded conceptual risk framework for uranium mining in Grand Canyon watershed—Inclusion of the Havasupai Tribe perspective (ver. 1.1, February 2024): U.S. Geological Survey Open-File Report 2023–1092, 25 p., https://doi.org/10.3133/ofr20231092.","productDescription":"vi, 25 p.","numberOfPages":"36","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-157227","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":499197,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116005.htm","linkFileType":{"id":5,"text":"html"}},{"id":425864,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip241","text":"General Information Product 241"},{"id":425233,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1092/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":424862,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231092/full"},{"id":424859,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1092/images/"},{"id":424858,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1092/ofr20231092.XML"},{"id":424857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1092/ofr20231092.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1092"},{"id":424856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1092/coverthb2.jpg"},{"id":425791,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip240","text":"General Information Product 240"},{"id":425790,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip239","text":"General Information Product 239"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.19147841939832,\n 38.32491175913418\n ],\n [\n -117.19147841939832,\n 32.88011313999995\n ],\n [\n -110.33600966939846,\n 32.88011313999995\n ],\n [\n -110.33600966939846,\n 38.32491175913418\n ],\n [\n -117.19147841939832,\n 38.32491175913418\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: January 30, 2024; Version 1.1: February 1, 2024","contact":"Associate Director, Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Many studies use landscape form to determine spatial patterns of tectonic deformation, and these are particularly effective when paired with independent measures of rock uplift and erosion. Here, we use morphometric analyses and 10Be catchment-averaged erosion rates, together with reverse slip rates from the Sierra Madre−Cucamonga fault zone, to reveal patterns in uplift, erosion, and fault activity in the range front of the San Gabriel Mountains in southern California, USA. Our analysis tests two prevailing hypotheses: (1) the range front of the San Gabriel Mountains is at steady state, in which rock uplift balances erosion and topographic elevations are stable throughout time, and (2) that west-to-east increases in elevation, relief, erosion rate, and stream-channel steepness across the interior of the massif reflect a parallel reverse-slip rate gradient on the range-bounding Sierra Madre−Cucamonga fault zone. We show that although deviations from steady state occur, the range-front hillslopes and stream channels are typically both well-connected and adjusted to patterns in Quaternary uplift driven by motion on the range-front fault network. Accordingly, landscape morphometrics, 10Be erosion rates, and model erosion rates effectively image spatial and temporal patterns in uplift. Interpreted jointly, these data reveal comparable peak slip rates on the Sierra Madre−Cucamonga fault zone and show that they do not monotonically increase from west to east. Thus, the eastward-increasing gradients developed within the interior of the massif are not solely related to reverse slip on the range-front faults. Evaluated on shorter length scales (<10 km), morphometric data corroborate earlier descriptions of the Sierra Madre−Cucamonga fault zone as multiple individual faults or fault sections, with slip rates tapering toward fault tips. We infer that these patterns imply the predominance of independent fault or fault section ruptures throughout the Quaternary, though data cannot rule out the possibility of large, connected Sierra Madre−Cucamonga fault zone ruptures. Deeper in the hanging wall of the Sierra Madre−Cucamonga fault zone, secondary faults accommodate range-front uplift. Motion on these faults may contribute to active uplift of the highest topography within the massif, in addition to partly reconciling differences between geologic and geodetic Sierra Madre−Cucamonga fault zone reverse-slip rates. This study provides a new, unified perspective on tectonics and landscape evolution in the San Gabriel Mountains.
The fracture of Earth materials occurs over a wide range of time and length scales. Physical conditions, particularly the stress field and Earth material properties, may condition rupture in a specific fracture regime. In nature, fast and slow fractures occur concurrently: tectonic tremor events are fast enough to emit seismic waves and frequently accompany slow earthquakes, which are too slow to emit seismic waves and are referred to as aseismic slip events. In this study, we generate simultaneous seismic and aseismic processes in a laboratory setting by driving a penny-shaped crack in a transparent sample with pressurized fluid. We leverage synchronized high-speed imaging and high-frequency acoustic emission (AE) sensing to visualize and listen to the various sequences of propagation (breaks) and arrest (sticks) of a fracture undergoing stick-break instabilities. Slow radial crack propagation is facilitated by fast tangential fractures. Fluid viscosity and pressure regulate the fracture dynamics of slow and fast events, and control the inter-event time and the energy released during individual fast events. These AE signals share behaviors with observations of episodic tremors in Cascadia, United States; these include: (a) bursty or intermittent slow propagation, and (b) nearly linear scaling of radiated energy with area. Our laboratory experiments provide a plausible model of tectonic tremor as an indicative of hydraulic fracturing facilitating shear slip during slow earthquakes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023AV001002","usgsCitation":"Yuan, C., Cochard, T., Denolle, M.A., Gomberg, J.S., Wech, A., Lizhi, X., and Weitz, D., 2024, Laboratory hydrofractures as analogs to tectonic tremors: AGU Advances, v. 5, no. 1, e2023AV001002, 15 p., https://doi.org/10.1029/2023AV001002.","productDescription":"e2023AV001002, 15 p.","ipdsId":"IP-155902","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023av001002","text":"Publisher Index Page"},{"id":480848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Yuan, Congcong","contributorId":349711,"corporation":false,"usgs":false,"family":"Yuan","given":"Congcong","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":924628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochard, Thomas","contributorId":349712,"corporation":false,"usgs":false,"family":"Cochard","given":"Thomas","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":924629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denolle, Marine A.","contributorId":345689,"corporation":false,"usgs":false,"family":"Denolle","given":"Marine","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":924630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924632,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lizhi, Xiao","contributorId":349713,"corporation":false,"usgs":false,"family":"Lizhi","given":"Xiao","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":924633,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weitz, David","contributorId":349714,"corporation":false,"usgs":false,"family":"Weitz","given":"David","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":924634,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70251180,"text":"fs20233028 - 2024 - Assessment of undiscovered conventional oil and gas resources in presalt reservoirs of the West-Central Coastal Province of Africa, 2022","interactions":[],"lastModifiedDate":"2024-01-30T18:36:25.793382","indexId":"fs20233028","displayToPublicDate":"2024-01-29T11:45:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3028","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in Presalt Reservoirs of the West-Central Coastal Province of Africa, 2022","title":"Assessment of undiscovered conventional oil and gas resources in presalt reservoirs of the West-Central Coastal Province of Africa, 2022","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 12.1 billion barrels of oil and 50 trillion cubic feet of gas in presalt reservoirs within the West-Central Coastal Province of Africa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20233028","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Le, P.A., Cicero, A.D., Drake, R.M., II, Ellis, G.S., Finn, T.M., Gardner, M.H., Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., Marra, K.R., Timm, K.K., and Young, S.S., 2024, Assessment of undiscovered conventional oil and gas resources in presalt reservoirs of the West-Central Coastal Province of Africa, 2022: U.S. Geological Survey Fact Sheet 2023–3028, 4 p., https://doi.org/10.3133/fs20233028.","onlineOnly":"Y","ipdsId":"IP-144479","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":425085,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3028"},{"id":425084,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3028/fs20233028.xml"},{"id":425083,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3028/images"},{"id":424969,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E3JNPI","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—West-Central Coastal Province (Africa) Presalt: Assessment Unit Boundaries, Assessment Input data, and Fact Sheet Data Tables"},{"id":424967,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3028/coverthb.jpg"},{"id":424968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3028/fs20233028.pdf","text":"Report","size":"1.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3028"}],"contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Leaf litter decomposition is a key ecosystem process in headwater streams, influenced by physical fragmentation, microbial degradation and feeding activity by stream biota. In some tropical streams, feeding by freshwater shrimps can exert strong top-down control on leaf litter decomposition, however, variation in shrimp macroconsumer effects across small spatial scales or among years is not well-known. We ran 50-day macroconsumer exclusion experiments to measure shrimp effects on leaf decomposition in two adjacent headwater streams in Puerto Rico, in 2017 (immediately prior to two Category 4 and 5 hurricanes) and again in 2018 and 2019, to assess shrimp effects in the context of post-hurricane conditions that included reduced canopy cover and higher shrimp (Atya and Xiphocaris) counts. Leaf decomposition was faster when shrimp had access to leaf packs, but only in the study stream with larger pools, which also had higher overall shrimp counts. However, increased shrimp abundances following the hurricanes did not result in faster decomposition, potentially because shrimp diets shifted toward algae post-hurricanes when canopies were more open. We conclude that shrimp effects on leaf litter breakdown may vary between adjacent streams that differ in habitat conditions and that increasing local shrimp abundances may fail to accelerate decomposition.
Despite the importance of sex-specific information for sturgeon conservation and management, sex identification has been a major challenge outside of mature adults on spawning grounds. Recent work identified a sex-specific locus (AllWSex2) that appears to be broadly conserved across many Acipenserids, but the assay was not validated for all species within the family. We tested the AllWSex2 marker in three sturgeon taxa (shortnose sturgeon Acipenser brevirostrum, Gulf sturgeon A. oxyrhinchus desotoi, and Atlantic sturgeon A. oxyrhinchus oxyrhinchus) from the Atlantic and Gulf of Mexico Coasts of North America to validate its use for sex identification. Our results indicate AllWSex2 is conserved in all three taxa, presenting a new opportunity to derive sex-specific information from tissue samples, which are routinely collected from these taxa. We found high concordance (range: 97–100%) between genotypic and phenotypic/histological methods, suggesting the assay is broadly effective. However, the small amount of discordance between the methods (< 3%) suggests further refinement may be possible.
This study characterizes hydroclimatic variability and change in peak streamflow and daily streamflow in Wisconsin from water years 1921 through 2020. Nonstationarity in peak streamflow in Wisconsin can include monotonic trends, change points, and autocorrelation. Spatial patterns of nonstationarity in peak streamflow, daily streamflow, and monthly precipitation, temperature, and snowfall were examined using four temporal periods. Upward trends in peak streamflow and daily streamflow were detected across the State, from around 1990 to 2020 and were likely predominantly driven by concurrent increases in precipitation and temperatures during this time. Earlier decreases in peak streamflow between the 1920s to the 1980s in the southern parts of the State were likely affected by nonclimate-related factors such as urbanization, water use, and land-use changes associated with agriculture.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064J","collaboration":"Prepared in cooperation with the Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Levin, S.B., 2024, Peak streamflow trends in Wisconsin and their relation to changes in climate, water years 1921–2020, chap. 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. This work is part of that reexamination.
The stationarity assumption is a concern because flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done to assess potential nonstationarity in peak flows in the north-central United States.
This report summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., comp., 2024, Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, [variously paged], https://doi.org/10.3133/sir20235064.","productDescription":"1 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":424953,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/sir20235064.pdf","text":"Abstract","size":"522 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5064"},{"id":424911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/coverthb.jpg"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States.
This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States.
Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Peak Streamflow Trends and Their Relation to Changes in Climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064A","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., Over, T.M., Levin, S.B., Heimann, D.C., Barth, N.A., Marti, M.K., O’Shea, P.S., Sanocki, C.A., Williams-Sether, T.J., Wavra, H.N., Sando, T.R., Sando, S.K., and Liu, M.S., 2024, Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin, chap. A of Ryberg, K.R., comp., Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, 27 p., https://doi.org/10.3133/sir20235064A.","productDescription":"Report: vi, 27 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145865","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Ocean acidification (OA) driven by eutrophication, riverine discharge, and other threats from local population growth that affect the inorganic carbonate system is already affecting the eastern Gulf of Mexico. Long-term declines in pH of ~ -0.001 pH units yr-1 have been observed in many southwest Florida estuaries over the past few decades. Coastal and estuarine waters of southwest Florida experience high biomass harmful algal blooms (HABs) of the dinoflagellate Karenia brevis nearly every year; and these blooms have the potential to impact and be impacted by seasonal to interannual patterns of carbonate chemistry. Sampling was conducted seasonally along three estuarine transects (Tampa Bay, Charlotte Harbor, Caloosahatchee River) between May 2020 and May 2023 to obtain baseline measurements of carbonate chemistry prior to, during, and following K. brevis blooms. Conductivity, temperature and depth data and discrete water samples for K. brevis cell abundance, nutrients, and carbonate chemistry (total alkalinity, dissolved inorganic carbonate (DIC), pCO2, and pHT were evaluated to identify seasonal patterns and linkages among carbonate system variables, nutrients, and K. brevis blooms. Karenia brevis blooms were observed during six samplings, and highest pCO2 and lowest pHT was observed either during or after blooms in all three estuaries. Highest average pH and lowest pCO2 were observed in Tampa Bay. In all three estuaries, average DIC and pHT were higher and pCO2 was lower during dry seasons than wet seasons. There was strong influence of net community calcification (NCC) and net community production (NCP) on the carbonate system; and NCC : NCP ratios in Tampa Bay, Charlotte Harbor, and the Caloosahatchee River were 0.83, 0.93, and 1.02, respectively. Linear relationships between salinity and dissolved ammonium, phosphate, and nitrate indicate strong influence of freshwater inflow from river input and discharge events on nutrient concentrations. This study is a first step towards connecting observations of high biomass blooms like those caused by K. brevis and alterations of carbonate chemistry in Southwest Florida. Our study demonstrates the need for integrated monitoring to improve understanding of interactions among the carbonate system, HABs, water quality, and acidification over local to regional spatial scales and event to decadal time scales.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2024.1331285","usgsCitation":"Hall, E.R., Yates, K., Hubbard, K.A., Garrett, M., and Frankle, J., 2024, Nutrient and carbonate chemistry patterns associated with Karenia brevis blooms in three West Florida Shelf estuaries 2020-2023: Frontiers in Marine Science, v. 11, 1331285, 16 p., https://doi.org/10.3389/fmars.2024.1331285.","productDescription":"1331285, 16 p.","ipdsId":"IP-159102","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2024.1331285","text":"Publisher Index Page"},{"id":426239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River, Charlotte Harbor, Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.34832763337916,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 28.08844843847784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.0334613261019,\n 26.994691244568983\n ],\n [\n -82.29301422823401,\n 26.99594814875003\n ],\n [\n -82.2944248418327,\n 26.644724858711314\n ],\n [\n -82.0334613261019,\n 26.643464039045767\n ],\n [\n -82.0334613261019,\n 26.994691244568983\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.835022542123,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.624097850120123\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Emily R.","contributorId":229381,"corporation":false,"usgs":false,"family":"Hall","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":41628,"text":"Mote Marine","active":true,"usgs":false}],"preferred":false,"id":895784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":202055,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":895785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, Katherine A.","contributorId":334472,"corporation":false,"usgs":false,"family":"Hubbard","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrett, Matt","contributorId":334473,"corporation":false,"usgs":false,"family":"Garrett","given":"Matt","email":"","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frankle, Jessica","contributorId":334474,"corporation":false,"usgs":false,"family":"Frankle","given":"Jessica","email":"","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":895788,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256443,"text":"70256443 - 2024 - Sources of bias in applying close-kin mark–recapture to terrestrial game species with different life histories","interactions":[],"lastModifiedDate":"2024-08-02T15:39:56.392104","indexId":"70256443","displayToPublicDate":"2024-01-25T10:32:49","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Sources of bias in applying close-kin mark–recapture to terrestrial game species with different life histories","docAbstract":"Close-kin mark–recapture (CKMR) is a method analogous to traditional mark–recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species’ and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent–offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.
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