The devastating Kahramanmaraş earthquake sequence occurred on February 6, 2023. Two main events, Mw 7.8 and Mw 7.5 occurred 9 hours apart, affected 11 cities in Turkey, and subjected an area of ∼90,000 km2 to shaking levels known to trigger landslides (peak ground acceleration > 0.08 g). Extensive landsliding was expected given the hilly terrain affected by this significant ground shaking—about 15% of the topography is steeper than 20°—but was not initially apparent in early satellite imagery, mostly because of obscuring snow that fell just after the earthquakes. However, after a more detailed investigation using high-resolution satellite images, aerial photos, and a field survey, we confirmed that this earthquake sequence did, indeed, trigger numerous landslides. In this study, we present those findings and provide a preliminary characterization of the spatial distribution, general characteristics, and dominant types of landslides and hillslope deformation triggered by the earthquake sequence. We mapped 3673 coseismic landslides, mostly concentrated in the northern half of the impacted area. Rock falls are the most abundant landslide type, but bedrock rotational landslides, translational slides and lateral spreads are also numerous. Surface rupture through mountainous terrain caused several large, and in some cases fatal, landslides. Incipient landslides and ground cracks are also widespread, especially in the north. Lithology, spatial variability of ground shaking, and topographic relief appear to be the main variables controlling the spatial distribution of coseismic landslides. There are few detailed studies of earthquake-triggered landslides in arid and semi-arid regions such as this one, nor for such complex earthquake sequences. Therefore, this contribution provides valuable information for future hazard and modeling efforts in arid and semi-arid regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2023.107315","usgsCitation":"Gorum, T., Tanyas, H., Karabacak, F., Yilmaz, A., Girgin, S., Allstadt, K.E., Suzen, M.L., and Burgi, P.M., 2023, Preliminary documentation of coseismic ground failure triggered by the February 6, 2023 Türkiye earthquake sequence: Engineering Geology, v. 327, 107315, 21 p., https://doi.org/10.1016/j.enggeo.2023.107315.","productDescription":"107315, 21 p.","ipdsId":"IP-154196","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":441713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2023.107315","text":"Publisher Index Page"},{"id":432031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Türkiye","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 35.932228360842544,\n 35.973045074631955\n ],\n [\n 36.32983932448548,\n 36.035276602908866\n ],\n [\n 37.86857056743534,\n 36.93821829196732\n ],\n [\n 39.69683217133675,\n 38.08156302992195\n ],\n [\n 38.989854338718345,\n 38.71377557689037\n ],\n [\n 38.469848249680496,\n 38.706777354491024\n ],\n [\n 36.898499605659964,\n 37.862404413864304\n ],\n [\n 35.469730632443316,\n 36.25972563387165\n ],\n [\n 35.932228360842544,\n 35.973045074631955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"327","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorum, Tolga 0000-0001-9407-7946","orcid":"https://orcid.org/0000-0001-9407-7946","contributorId":341389,"corporation":false,"usgs":false,"family":"Gorum","given":"Tolga","email":"","affiliations":[{"id":81732,"text":"Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":908338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":908339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karabacak, Furkan 0000-0001-5838-3196","orcid":"https://orcid.org/0000-0001-5838-3196","contributorId":341390,"corporation":false,"usgs":false,"family":"Karabacak","given":"Furkan","email":"","affiliations":[{"id":81732,"text":"Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":908340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yilmaz, Abdussamet 0000-0002-8707-8649","orcid":"https://orcid.org/0000-0002-8707-8649","contributorId":341391,"corporation":false,"usgs":false,"family":"Yilmaz","given":"Abdussamet","email":"","affiliations":[{"id":81732,"text":"Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":908341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Girgin, Serkan 0000-0002-0156-185X","orcid":"https://orcid.org/0000-0002-0156-185X","contributorId":341392,"corporation":false,"usgs":false,"family":"Girgin","given":"Serkan","email":"","affiliations":[{"id":81733,"text":"University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), Enschede, Netherlands","active":true,"usgs":false}],"preferred":false,"id":908342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":908343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suzen, M. Lutfi 0000-0003-0865-2022","orcid":"https://orcid.org/0000-0003-0865-2022","contributorId":341393,"corporation":false,"usgs":false,"family":"Suzen","given":"M.","email":"","middleInitial":"Lutfi","affiliations":[{"id":81734,"text":"Middle East Technical University, Geological Engineering Department, Ankara, Turkey","active":true,"usgs":false}],"preferred":false,"id":908344,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burgi, Paula Madeline 0000-0003-3001-5759","orcid":"https://orcid.org/0000-0003-3001-5759","contributorId":317875,"corporation":false,"usgs":true,"family":"Burgi","given":"Paula","email":"","middleInitial":"Madeline","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":908345,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257380,"text":"70257380 - 2023 - Developing a stochastic hydrological model for informing lake water level drawdown management","interactions":[],"lastModifiedDate":"2024-09-04T16:42:02.446596","indexId":"70257380","displayToPublicDate":"2023-11-01T09:17:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Developing a stochastic hydrological model for informing lake water level drawdown management","docAbstract":"Winter drawdown (WD) is a common lake management tool for multiple purposes such as flood control, aquatic vegetation reduction, and lake infrastructure maintenance. To minimize adverse impacts to a lake’s ecosystem, regulatory agencies may provide managers with general guidelines for drawdown and refill timing, drawdown magnitude, and outflow limitations. However, there is significant uncertainty associated with the potential to meet management targets due to variability in lake characteristics and hydrometeorology of each lake’s basin, making the use of modeling tools a necessity. In this context, we developed a hydrological modeling framework for lake water level drawdown management (HMF-Lake) and evaluated it at 15 Massachusetts lakes where WDs have been applied over multiple years for vegetation control. HMF-Lake is based on the daily lake water balance, with inflows simulated by a lumped rainfall-runoff model (Cemaneige-GR4J) and outflow rate calculated by a modified Target Storage and Release Based Method (TSRB). The model showed a satisfactory performance of simulating historical water levels (0.53 ≤ NSE ≤ 0.86), however, uncertainties from meteorological inputs and TSRB determined lake outflow rate affected the result accuracy. To account for these uncertainties, the model was executed stochastically to assess the ability of study lakes to follow the Massachusetts’ general WD guidelines: drawdown by Dec 1 and fully refilled by Apr 1. By using the stochastic HMF-Lake, the probabilities of each lake to reach the drawdown level by Dec 1 were calculated for different drawdown magnitudes (1–6 ft). The probability results suggest it was generally less possible for most of study lakes to achieve a drawdown of 3 ft or more by Dec 1. Moreover, we employed the stochastic model to derive the annual latest refill starting dates that ensure a 95 % probability of reaching the normal water level by Apr 1. We found starting a refill in March for drawdowns up to 6 ft was feasible for most of study lakes. These results provide lake managers with a quantitative understanding of the lake’s ability to follow the state guidelines. The model may be used to systematically evaluate current WD management strategies at state or regional scales and support adaptive WD management under changing climates.
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\"}}]}","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"He, Xinchen","contributorId":316775,"corporation":false,"usgs":false,"family":"He","given":"Xinchen","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andreadisa, Konstantinos","contributorId":342567,"corporation":false,"usgs":false,"family":"Andreadisa","given":"Konstantinos","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Abhiskek","contributorId":342569,"corporation":false,"usgs":false,"family":"Kumar","given":"Abhiskek","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butler, Caitlyn","contributorId":316779,"corporation":false,"usgs":false,"family":"Butler","given":"Caitlyn","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910197,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249866,"text":"70249866 - 2023 - Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk","interactions":[],"lastModifiedDate":"2023-11-02T14:02:20.152878","indexId":"70249866","displayToPublicDate":"2023-11-01T08:51:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk","docAbstract":"Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-46195-9","usgsCitation":"Sanchez, G.M., Petrasova, A., Skrip, M.M., Collins, E., Lawrimore, M.A., Vogler, J.B., Terando, A., Vukomanovic, J., Mitasova, H., and Meentemeyer, R.K., 2023, Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk: Scientific Reports, v. 13, 18869, 15 p., https://doi.org/10.1038/s41598-023-46195-9.","productDescription":"18869, 15 p.","ipdsId":"IP-144281","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":441720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-46195-9","text":"Publisher Index Page"},{"id":422331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","county":"Berkeley County, Charleston County, Dorchester County","city":"Charleston, Moncks Corner, 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0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":887448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vukomanovic, Jelena","contributorId":316275,"corporation":false,"usgs":false,"family":"Vukomanovic","given":"Jelena","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":887459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mitasova, Helena 0000-0002-6906-3398","orcid":"https://orcid.org/0000-0002-6906-3398","contributorId":296416,"corporation":false,"usgs":false,"family":"Mitasova","given":"Helena","email":"","affiliations":[{"id":7091,"text":"North Carolina State 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designed to identify favorable areas for geothermal resources have traditionally been focused on near-surface information, namely data that can be compiled into a 2D map. However, these methods fail to account for the third dimension: depth. As a result, they do not incorporate deep crustal and mantle features like heat sources. Geophysical methods with multi-scale capabilities, such as magnetotellurics (MT), provide tools to image deeper structures and bottom-up control on location of near surface hydrothermal systems in 3D. This study briefly demonstrates the advantage of understanding bottom-up control on hydrothermal systems to aid assessment and characterization. A regional 3D electrical resistivity model of the Great Basin is developed from MT data that images the near surface down to the mantle. From the 3D model, electrical conductance (depth integrated electrical conductivity) maps are created at logical depth intervals to identify anomalies. The conductance maps image discrete zones of high-conductance between 15-20 km depth indicative of fluid collection at the brittle-ductile transition; high-conductance zones around Moho depths (30-50 km) suggestive of partial melt; high-conductance zones in the upper mantle indicative of higher temperature and larger melt fraction, and low-conductance zones indicative of lithospheric material descending in the mantle. One anomalous zone of low-conductance in the mantle is under the north central Nevada, suggesting vertical mantle flow transport of heat to the crust related to sinking lithospheric material.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Using the Earth to save the Earth (GRC transactions)","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Peacock, J., and Bedrosian, P.A., 2023, Importance of understanding bottom-up control when characterizing geothermal systems, in Using the Earth to save the Earth (GRC transactions), v. 47, p. 1797-1807.","productDescription":"11 p.","startPage":"1797","endPage":"1807","ipdsId":"IP-154701","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":424332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424331,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034877","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":892011,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250023,"text":"70250023 - 2023 - Exploring centennial barrier-inlet evolution: Insights from undeveloped and developed phases at Barnegat Inlet, New Jersey","interactions":[],"lastModifiedDate":"2023-11-14T13:02:59.992292","indexId":"70250023","displayToPublicDate":"2023-11-01T07:02:07","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring centennial barrier-inlet evolution: Insights from undeveloped and developed phases at Barnegat Inlet, New Jersey","docAbstract":"This study aims to identify the natural processes and the subsequent responses to coastal engineering and development on the alongshore evolution of the IB-BI-LBI inlet-barrier system. The primary focus will be the quantification of barrier island and inlet sediment partitioning at decadal to centennial timescales, from 1839-1941. We analyze historical alongshore evolution and track coastal engineering efforts at the Island Beach–Barnegat Inlet–Long Beach Island, NJ barrier-inlet system, which has transitioned from natural to highly developed over the past 180 years. We build a quantitative mass-balance framework that tracks sediment reservoir volumes and transport fluxes within the barrier-inlet system to describe both the natural and developed alongshore evolution of this system. We find that minor coastal engineering efforts, including the construction of small-scale wood and stone jetties, not only shift sediment transport locally, but also shift system-wide sediment transport based on inlet-barrier island interactions and sediment partitioning. Better understanding these different modes of past evolution can help to guide coastal management strategies as beach nourishment increases in cost, sea level-rise accelerates, and extreme storm patterns change.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Proceedings of the Coastal Sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0130","usgsCitation":"Nichols-O’Neill, S., Lorenzo-Trueba, J., Ciarletta, D.J., and Miselis, J.L., 2023, Exploring centennial barrier-inlet evolution: Insights from undeveloped and developed phases at Barnegat Inlet, New Jersey, in The Proceedings of the Coastal Sediments 2023, p. 1403-1414, https://doi.org/10.1142/9789811275135_0130.","productDescription":"12 p.","startPage":"1403","endPage":"1414","ipdsId":"IP-148130","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":422572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.15617443689175,\n 39.81674675488196\n ],\n [\n -74.15617443689175,\n 39.71752217758285\n ],\n [\n -74.06965710290756,\n 39.71752217758285\n ],\n [\n -74.06965710290756,\n 39.81674675488196\n ],\n [\n -74.15617443689175,\n 39.81674675488196\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols-O’Neill, Shane","contributorId":297142,"corporation":false,"usgs":false,"family":"Nichols-O’Neill","given":"Shane","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":888021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorenzo-Trueba, Jorge","contributorId":297143,"corporation":false,"usgs":false,"family":"Lorenzo-Trueba","given":"Jorge","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":888022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250481,"text":"70250481 - 2023 - The Arctic Rivers Project: Using an equitable co-production framework for integrating meaningful community engagement and science to understand climate impacts","interactions":[],"lastModifiedDate":"2023-12-13T12:43:35.882553","indexId":"70250481","displayToPublicDate":"2023-11-01T06:38:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17107,"text":"Community Science","active":true,"publicationSubtype":{"id":10}},"title":"The Arctic Rivers Project: Using an equitable co-production framework for integrating meaningful community engagement and science to understand climate impacts","docAbstract":"As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community-engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project-specific knowledge co-production protocols. This paper provides a novel model of design and implementation to co-produce knowledge with communities across a large study domain.
Seismic images of Earth’s interior have revealed two continent-sized anomalies with low seismic velocities, known as the large low-velocity provinces (LLVPs), in the lowermost mantle. The LLVPs are often interpreted as intrinsically dense heterogeneities that are compositionally distinct from the surrounding mantle. Here we show that LLVPs may represent buried relics of Theia mantle material (TMM) that was preserved in proto-Earth’s mantle after the Moon-forming giant impact. Our canonical giant-impact simulations show that a fraction of Theia’s mantle could have been delivered to proto-Earth’s solid lower mantle. We find that TMM is intrinsically 2.0–3.5% denser than proto-Earth’s mantle based on models of Theia’s mantle and the observed higher FeO content of the Moon. Our mantle convection models show that dense TMM blobs with a size of tens of kilometres after the impact can later sink and accumulate into LLVP-like thermochemical piles atop Earth’s core and survive to the present day. The LLVPs may, thus, be a natural consequence of the Moon-forming giant impact. Because giant impacts are common at the end stages of planet accretion, similar mantle heterogeneities caused by impacts may also exist in the interiors of other planetary bodies.
Remote cameras (“trail cameras”) are a popular tool for non-invasive, continuous wildlife monitoring, and as they become more prevalent in wildlife research, machine learning (ML) is increasingly used to automate or accelerate the labor-intensive process of labelling (i.e., tagging) photos. Human-machine hybrid tagging approaches have been shown to greatly increase tagging efficiency (i.e., time to tag a single image). However, those potential increases hinge on the extent to which an ML model makes correct vs. incorrect predictions. We performed an experiment using a ML model that produces bounding boxes around animals, people, and vehicles in remote camera imagery (MegaDetector) to consider the impact of a ML model’s performance on its ability to accelerate human labeling. Six participants tagged trail camera images collected from 12 sites in Vermont and Maine, USA (January–September 2022) using three tagging methods (one with ML bounding box assistance and two without assistance). We used a generalized linear mixed model to examine the influence of ML model performance and tagging method on tagging efficiency. We found that ML bounding boxes offer significant improvement in tagging efficiency when labelling data compared to unassisted tagging. Additionally, the time taken to label with bounding boxes was not statistically different from an unassisted tagging approach. However, we found that gains in efficiency are contingent on the ML algorithm’s performance and that incorrect ML predictions, particularly the 4.2% false positive and 3.6% false negative predictions, can slow the tagging process compared to a non-hybrid approach. These findings indicate that although practitioners usually forgo the production of bounding boxes when selecting a data labelling process due to the increased effort, ML bounding box-assisted tagging can offer an efficient method for labeling. More broadly, ML-assisted data labelling offers an opportunity to accelerate the analysis of trail camera imagery, but an assessment of the ML model’s performance can illuminate whether the hybrid-tagging approach is ultimately a help or hinderance.
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In addition to point and non-point source nutrient inputs, factors such as hydrology, geomorphology, temperature, light, and biogeochemical transformations influence nutrient dynamics in surface waters, allowing for the formation of steep spatial gradients and patchiness. Documenting nutrient variability is also necessary to identify sources, quantify transformation rates, and understand drivers. Due to logistical and cost constraints, it is often unfeasible to measure concentrations of nutrients in surface waters using discrete sampling followed by laboratory analysis at a resolution high enough to identify steep spatial gradients and patchiness. Because of these constraints, data generated from discrete sampling are limited in space and time, often missing key variabilities. Recent advancements of in situ nitrate plus nitrite (NO3- and NO2-) sensor technology has enabled highly temporally and spatially resolved NO3- concentration measurements in aquatic ecosystems. However, comparable information about ammonium (NH4+) concentrations remains unavailable. To address this need, U.S. Geological Survey collaborated with Timberline Instruments to modify their commercially available benchtop TL-2800 ammonia analyzer to collect high-frequency continuous (1 unique sample measurement per second) NH4+ concentration measurements at a micromolar (0.5 µM) resolution in flow-through mode while receiving water pumped from a moving boat. Although the utility of this method is described for spatial surveys, we anticipate that it would be adaptable to installation at a fixed station for continuous monitoring of NH4+ concentration.","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lom3.10579","usgsCitation":"Richardson, E.T., Hansen, A., Kraus, T.E., Downing, B.D., Forsberg, D., Stillian, J., O’Donnell, K., Sturgeon, C.L., and Bergamaschi, B.A., 2023, A novel boat-based field application of a high-frequency conductometric ammonium analyzer to characterize spatial variation in aquatic ecosystems: Limnology and Oceanography Methods, v. 21, no. 12, p. 761-774, https://doi.org/10.1002/lom3.10579.","productDescription":"14 p.","startPage":"761","endPage":"774","ipdsId":"IP-117787","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":441730,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10579","text":"Publisher Index Page"},{"id":422311,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.20848323920738,\n 37.8750433280058\n ],\n [\n -121.07377092901734,\n 37.8750433280058\n ],\n [\n -121.07377092901734,\n 38.640000890410164\n ],\n [\n -122.20848323920738,\n 38.640000890410164\n ],\n [\n -122.20848323920738,\n 37.8750433280058\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Angela 0000-0003-0938-7611 anhansen@usgs.gov","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":171551,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela","email":"anhansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Tamara E. 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Advances in sensor design and sUAS capabilities have led to rapid advances in the amount and type of geophysical data that can be acquired using sUAS-based survey designs (Gavazzi et al., 2019). Here we showcase the utility of a single sUAS (the Matrice 600 Pro and accompanying sensor package) that collects magnetic, thermal infra-red (TIR) and gas (CO2, SO2, H2S, water vapor) data for use in geothermal resource exploration and monitoring, with case studies in eastern California and Iceland. The work highlights the flexibility of modern sUAS systems for single-team acquisition of multiple independent but coupled geophysical data which allow for a multidisciplinary approach to geothermal systems research. We summarize the workflows involved in collecting each dataset as well as several common issues encountered both during data collection and data processing.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2023 Summit on Drone Geophysics program book","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2023 Summit on Drone Geophysics","conferenceDate":"October 23-26, 2023","language":"English","publisher":"Society of Exploration Geophysicists","usgsCitation":"Rea-Downing, G.H., Bouligand, C., Glen, J.M., Earney, T.E., Zielinski, L., Anderson, J.E., and Kelly, P.J., 2023, Development of small uncrewed aerial systems for multi-instrument geophysical data acquisition in active geothermal systems, in 2023 Summit on Drone Geophysics program book, October 23-26, 2023, p. 50-51.","productDescription":"2 p.","startPage":"50","endPage":"51","ipdsId":"IP-156555","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":424271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424261,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://seg.org/calendar_events/2023-summit-on-drone-geophysics/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rea-Downing, Grant Harold 0000-0002-8567-683X","orcid":"https://orcid.org/0000-0002-8567-683X","contributorId":333087,"corporation":false,"usgs":true,"family":"Rea-Downing","given":"Grant","email":"","middleInitial":"Harold","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouligand, Claire","contributorId":240831,"corporation":false,"usgs":false,"family":"Bouligand","given":"Claire","affiliations":[{"id":34188,"text":"University of Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":891883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zielinski, Laurie A. 0000-0002-9309-9243","orcid":"https://orcid.org/0000-0002-9309-9243","contributorId":333088,"corporation":false,"usgs":false,"family":"Zielinski","given":"Laurie A.","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":891886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Jacob Elliott 0000-0002-0709-2548","orcid":"https://orcid.org/0000-0002-0709-2548","contributorId":329989,"corporation":false,"usgs":true,"family":"Anderson","given":"Jacob","email":"","middleInitial":"Elliott","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891887,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":891888,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70249991,"text":"70249991 - 2023 - Decadal shifts in the population growth, regeneration, and health of Taxodium distichum in swamps of the Cache River Watershed, Illinois","interactions":[],"lastModifiedDate":"2023-11-12T13:14:53.661538","indexId":"70249991","displayToPublicDate":"2023-10-31T07:11:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2142,"text":"Journal for Nature Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Decadal shifts in the population growth, regeneration, and health of Taxodium distichum in swamps of the Cache River Watershed, Illinois","docAbstract":"Population projection models based on long-term trends in regeneration and tree survival can be used to predict the future stability of swamp forest species using water management. Population growth and regeneration of a foundational tree species in North American cypress swamps (Taxodium distichum) were compared in the Cache River watershed of southern Illinois USA over several decades. This study examined T. distichum population growth in several regional swamps within the Cache River watershed along a moisture gradient to model growth, stability, or decline based on data of life history stage transitions, using data from the following time periods: the 1990s, 2002–2011, and 2012–2022. Using data from the 1990s, T. distichum populations in Crawford Tract in Buttonland Swamp were projected to increase over time because of the high frequency of juvenile stages at elevations with growing season drawdown and winter flooding. The situation in Crawford Tract had changed by 2019–2021 because T. distichum seedlings had not transitioned (i.e., saplings and young trees were absent) although no old-growth trees had died during or after the 1990s. In other regional swamps, projection models were constructed over two decades (2006–2021) along a dry-to-wet flood gradient including Section 8 Woods, Deer Pond, Wildcat Bluff, Snake Hole, and Heron Pond. Populations in swamps on the drier end of the gradient had more support from juvenile stages. In a tree health survey in 2022 within the impounded interior of Buttonland Swamp (not Crawford Tract), seventy percent of the old-growth T. distichum trees were stressed or declining. Coupled with the fact that no seedlings or saplings were observed, the populations in the interior of the swamp were not stable. Many factors could further stress these ancient T. distichum including interactions of impoundment with chemicals, disease, and changes in air temperature and precipitation. Overall, the seedling abundance in these swamps increased in these environments from 2012 to 2021, except in the most flooded swamps. From a management perspective, drier conditions were more conducive to the success of the earlier life history stages of T. distichum in these old-growth forests.
Updating predictions of the response of high-profile, at-risk species to climate change and anthropogenic stressors is vital for informing effective conservation action. Here, we review two prior generations of Bayesian network probability models predicting changes in global polar bear (Ursus maritimus) population status, and provide a contemporary update based on recent research findings and sea-ice projections by newer climate models. We compare predictions of polar bear population response from all 3 models among four circumpolar Arctic ecoregions, using sea ice projections based on three IPCC greenhouse gas emissions scenarios (SSP2.6, 4.5, 8.5). Consistent with the previous two model generations, polar bears will continue to experience increasing probability of declining or greatly declining populations throughout the 21st century, varying by emission scenario. Populations within the Polar Basin Divergent Ice Ecoregion have the highest predicted probability of declines, but predictions were slightly less dire relative to the previous model generation. Most of the influence, denoted by model sensitivity analysis, is from expected degradation and loss of sea ice and reduced access to marine prey. The lack of terrestrial prey adequate to substitute for loss of access to marine prey, as well as human-caused bear morality associated with hunting and defense of life and property encountered when polar bears are increasingly forced ashore also contributed to predicted declines. Although some tidewater glacial fjords and other localized onshore resources may provide local refugia, their benefit is transient. Our findings continue to inform priorities for inventory, monitoring, and research needs, and suggest that similar updates to models of other at-risk species can capitalize on the comparison framework we present here.
Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) to perform these checks and estimate probabilities that an analyst would publish or reject a site-specific trend model from a multi-site study. We trained these “model-checking models” (MCMs) using a national study of over 6000 trend models and tested the MCMs using a smaller set of novel trend models. Although the MCMs did not perform well enough to bypass analyst review entirely, we found incorporating an MCM into a larger evaluation workflow can reduce the number of trend models needing an analyst review by more than half.
The lower Mississippi River Valley spans over 200,000 square kilometres in parts of seven states, encompassing areas of critical groundwater supplies, natural hazards, infrastructure, and low-lying coastal regions. From 2018 - 2022, the U.S. Geological Survey acquired over 82,000 line-kilometres of airborne electromagnetic, radiometric, and magnetic data over this region to provide comprehensive and systematic information about subsurface geologic and hydrologic properties that support multiple scientific and societal interests. Most of the data were acquired on a regional grid of west-east flight lines separated by 3 - 6 kilometres; however, several high-resolution inset grids with line spacing as close as 200 m were acquired in targeted areas of interest. Approximately 8,000 line-kilometres were acquired along streams and rivers to characterise the potential for surface water-groundwater connection, and another 6,000 line-kilometres were acquired along the Mississippi and Arkansas River levees to characterise this critical infrastructure. Here, we present a summary of the data along with several examples of how they are being used to inform regional groundwater model development, inferences of groundwater salinity, identification of faults in the New Madrid seismic zone, and levee infrastructure.
","conferenceTitle":"AEM2023 8th International Airborne Electromagnetics Workshop","conferenceDate":"September 3-7, 2023","conferenceLocation":"Fitzroy Island, Queensland, Australia","language":"English","publisher":"Australian Society of Exploration Geophysicists","doi":"10.5281/zenodo.10052667","usgsCitation":"Minsley, B.J., Adams, R.F., Asquith, W.H., Burton, B.L., Hoogenboom, B.E., James, S.R., Killian, C.D., Knierim, K.J., Kress, W.H., Lindaman, M., Leaf, A.T., Rigby, J.R., and Traylor, J.P., 2023, System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications, AEM2023 8th International Airborne Electromagnetics Workshop, Fitzroy Island, Queensland, Australia, September 3-7, 2023, 5 p., https://doi.org/10.5281/zenodo.10052667.","productDescription":"5 p.","ipdsId":"IP-150848","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":501311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"lower Mississippi River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.74456800918571,\n 37.63192332238003\n ],\n [\n -92.98685410111881,\n 37.63192332238003\n ],\n [\n -92.98685410111881,\n 27.15668126283292\n ],\n [\n -87.74456800918571,\n 27.15668126283292\n ],\n [\n -87.74456800918571,\n 37.63192332238003\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 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Courtney D. 0000-0002-2137-2722","orcid":"https://orcid.org/0000-0002-2137-2722","contributorId":213990,"corporation":false,"usgs":true,"family":"Killian","given":"Courtney","email":"","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886133,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886134,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kress, Wade H. 0000-0002-6833-028X wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886135,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lindaman, Maxwell A. 0000-0003-1786-1272","orcid":"https://orcid.org/0000-0003-1786-1272","contributorId":219064,"corporation":false,"usgs":true,"family":"Lindaman","given":"Maxwell A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886136,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886137,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":260894,"corporation":false,"usgs":true,"family":"Rigby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886138,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Traylor, Jonathan P. 0000-0002-2008-1923 jtraylor@usgs.gov","orcid":"https://orcid.org/0000-0002-2008-1923","contributorId":5322,"corporation":false,"usgs":true,"family":"Traylor","given":"Jonathan","email":"jtraylor@usgs.gov","middleInitial":"P.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886139,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70273450,"text":"70273450 - 2023 - Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching","interactions":[],"lastModifiedDate":"2026-01-14T15:59:24.616609","indexId":"70273450","displayToPublicDate":"2023-10-30T08:53:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7169,"text":"Quaternary Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching","docAbstract":"A forest bed of tree stumps currently in the intertidal zone at Girdwood, south-central Alaska, records coseismic submergence during the penultimate great earthquake. Tree-ring samples from ten spruce stumps were crossdated to develop a 149-year-long ring-width chronology. Radiocarbon wiggle-matching found that single-ring ages from the chronology were offset 28 ± 7 years older than the IntCal20 calibration curve and that the last ring of the chronology dated as 1169 to 1189 CE (781–761 cal. yr. BP) at the 95% confidence level. Bark was observed on some stumps, six samples had the same year for the last growth ring, and so this wiggle-match date is also the best estimate of the date of the penultimate great earthquake. This date is in good agreement with a date for this event in a seismo-turbidite record from Skilak Lake but not with previous dates from Bayesian models of maximum- and minimum-limiting ages from coastal salt marshes. Reanalysis of the coastal salt marsh ages with the data grouped by area, context and material found that outer wood samples from stumps at coseismic submergence sites and a Bayesian limiting age model based on just herbaceous plant ages from Turnagain Arm and the Copper River area are both consistent with our wiggle-match date. Furthermore, coseismic emergence ages from Cape Suckling and Yakataga are older than the penultimate earthquake and so likely relate to an earlier uplift event in this eastern area. The rupture extent during the penultimate great earthquake appears to have been less than in the 1964 great earthquake and the interseismic interval between these two events was 785 ± 10 years.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.qsa.2023.100142","usgsCitation":"Barclay, D.J., Haeussler, P., and Witter, R.C., 2023, Dating the penultimate great earthquake in south-central Alaska using tree-ring crossdating and radiocarbon wiggle-matching: Quaternary Science Advances, v. 13, 100142, 13 p., https://doi.org/10.1016/j.qsa.2023.100142.","productDescription":"100142, 13 p.","ipdsId":"IP-158222","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.qsa.2023.100142","text":"Publisher Index Page"},{"id":498618,"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 -156.97392172569602,\n 60.587785877878815\n ],\n [\n -156.97392172569602,\n 56.48596044935496\n ],\n [\n -140.95577716118677,\n 56.48596044935496\n ],\n [\n -140.95577716118677,\n 60.587785877878815\n ],\n [\n -156.97392172569602,\n 60.587785877878815\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, David J 0009-0007-9629-3731","orcid":"https://orcid.org/0009-0007-9629-3731","contributorId":365136,"corporation":false,"usgs":false,"family":"Barclay","given":"David","middleInitial":"J","affiliations":[{"id":87054,"text":"SUNY Cortland, Cortland, NY","active":true,"usgs":false}],"preferred":false,"id":953743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":219962,"corporation":false,"usgs":true,"family":"Witter","given":"Robert","email":"rwitter@usgs.gov","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953745,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249787,"text":"ofr20231082 - 2023 - Annotated bibliography of scientific research on greater sage-grouse published from October 2019 to July 2022","interactions":[],"lastModifiedDate":"2023-12-14T20:58:32.054422","indexId":"ofr20231082","displayToPublicDate":"2023-10-27T16:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1082","displayTitle":"Annotated Bibliography of Scientific Research on Greater Sage-Grouse Published from October 2019 to July 2022","title":"Annotated bibliography of scientific research on greater sage-grouse published from October 2019 to July 2022","docAbstract":"Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey (USGS) created a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here and built on to incorporate new information. The greater sage-grouse (Centrocercus urophasianus; hereafter “GRSG”) has been a focus of scientific investigation and management action for the past two decades. The 2015 U.S. Fish and Wildlife Service listing determination of “not warranted” under the Endangered Species Act was in part a result of a large-scale collaborative effort to develop strategies to conserve GRSG populations and their habitat and to reduce threats to both. New scientific information augments existing knowledge and can help inform updates or modifications to existing plans for managing GRSG and sagebrush ecosystems. However, the sheer number of scientific publications can be a challenge for managers tasked with evaluating and determining the need for potential updates to existing planning documents. To assist in this process, the USGS has reviewed and summarized the scientific literature published since January 1, 2015. Our most recent GRSG literature summary was published in 2020 (Carter and others, 2020) and included products published through October 2, 2019. Here, we consider products published between October 2, 2019, and July 21, 2022. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and USGS Open-File Reports) on greater sage-grouse. We first systematically searched three reference databases and three government databases using the search phrase “greater sage-grouse.” We refined the initial list of products by removing (1) duplicates, (2) publications not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products for which greater sage-grouse was not a research focus or the study did not present new data or findings about greater sage-grouse. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified management topics addressed by each product; for example, species and population characteristics. We also identified projects that provided new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and formal peer review. Our initial searches resulted in 221 total products, of which 147 met our criteria for inclusion. Across products summarized in the annotated bibliography, broad-scale habitat characteristics, behavior or demographics, site-scale habitat characteristics, habitat selection, and population estimates or targets were the most commonly addressed management topics. The online version of this bibliography, which will be available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers), will be searchable by topic, location, and year, and will include links to each original publication. The studies compiled and summarized here may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GRSG populations across the GRSG range.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231082","usgsCitation":"Teige, E.C., Maxwell, L.M., Jordan, S.E., Rutherford, T.K., Dietrich, E.I., Samuel, E.M., Stoneburner, A.L., Kleist, N.J., Meineke, J.K., Selby, L.B., Foster, A.C., and Carter, S.K., 2023, Annotated bibliography of scientific research on greater sage-grouse published from October 2019 to July 2022 (ver. 1.1, November 2023): U.S. Geological Survey Open-File Report 2023–1082, 122 p., https://doi.org/10.3133/ofr20231082.","productDescription":"ix, 122 p.","onlineOnly":"Y","ipdsId":"IP-152382","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":422491,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1082/versionHist.txt","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1082 version history"},{"id":422190,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1082/ofr20231082.pdf","text":"Report","size":"5.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1082"},{"id":422189,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1082/coverthb2.jpg"},{"id":422620,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231082/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1082"},{"id":422537,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1082/images"},{"id":422538,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1082/ofr20231082.xml"}],"edition":"Version 1.0: October 27, 2023; Version 1.1: November 13, 2023","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Metabolic rate is a key parameter in fish energy budgets that strongly influences the output of bioenergetics models. In this study, we tested the hypothesis that metabolic rate varies with growth history of age-1 largemouth bass Micropterus nigricans Cuvier, 1828. Two groups of fish were fed alternating maintenance or ad libitum rations of fathead minnow Pimephales promelas Rafinesque, 1820, so that over a 9-week period, initial and ending size of fish was similar. After 9 weeks, oxygen consumption was measured using static, closed respirometry. Although final body weight was similar between the two groups (means, 104–108 g), specific oxygen consumption for fish fed maintenance rations (0.094 mg O2 g−2 h−1) was 38% less than that measured for fish fed ad libitum (0.152 mg O2 g−2 h−1). Bioenergetics estimates of food consumption were similar to observed values for fish fed ad libitum (∼7% error), but for fish fed maintenance rations, the model overestimated food consumption by 65%. By accounting for changes in metabolic rate owing to reduced feeding, error in model estimates of food consumption was reduced. These findings shed new insight into factors associated with consumption-dependent error in bioenergetics models and highlight the importance of feeding history on metabolic rate of fish. Incorporating growth-dependent metabolism into bioenergetics models can improve model accuracy and allow fisheries biologists to make more informed decisions regarding fish growth and energetics.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2023-0047","usgsCitation":"Ranney, S., Chipps, S.R., and Wahl, D., 2023, Effect of feeding history on metabolic rate of largemouth bass (Micropterus nigricans): implications for bioenergetics models: Canadian Journal of Zoology, v. 102, no. 3, p. 207-216, https://doi.org/10.1139/cjz-2023-0047.","productDescription":"10 p.","startPage":"207","endPage":"216","ipdsId":"IP-064668","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ranney, Steven H.","contributorId":342588,"corporation":false,"usgs":false,"family":"Ranney","given":"Steven H.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":910204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wahl, David H.","contributorId":342591,"corporation":false,"usgs":false,"family":"Wahl","given":"David H.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":910206,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251059,"text":"70251059 - 2023 - Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals","interactions":[],"lastModifiedDate":"2024-01-19T13:23:35.008001","indexId":"70251059","displayToPublicDate":"2023-10-26T07:21:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals","docAbstract":"Excess sediment is a common reason water bodies in the USA become listed as impaired resulting in total maximum daily loads (TMDL) that require municipalities to invest millions of dollars annually on management practices aimed at reducing suspended-sediment loads (SSLs), yet monitoring data are rarely used to quantify SSLs and track TMDL progress. A monitoring network was created to quantify the SSL from the City of Roanoke, Virginia, USA (CoR), to the Roanoke River and Tinker Creek and help guide TMDL assessment and implementation. Suspended-sediment concentrations were estimated between 2020 and 2022 from high-frequency turbidity data using surrogate linear-regression models. Sixty-one percent of the total three-year SSL resulted from five large storm events. The average suspended-sediment yield from the CoR (58.1 metric tons/km2/year) was similar to other urban watersheds in the Eastern United States; however, the yield was nearly five times larger than the TMDL allocation (12.2 metric tons/km2/year). The TMDL allocated load was modeled based on a predominantly forested reference watershed and may not be a practical target for highly impervious watersheds within the CoR. The TMDL model used daily input data which likely does not capture the full range of SSLs during storm events, particularly from flashy urban streams. The average SSL following the five large storm events doubled that of the CoR’s annual allocated load from the TMDL. The results of this study highlight the importance of using high-frequency monitoring data to accurately estimate SSLs and evaluate TMDLs in urban areas.
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American ungulates and small mammals, including rodents and leporids. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on ungulates and small mammals, and measures to reduce noise emissions. We organized the sections of this synthesis to align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. A substantial body of research shows that human-caused noise can affect wildlife health and behavior, with variation in sensitivity to noise among species. Studies have shown consistent, detectable effects of noise on ungulates, but the amount of literature on ungulates is very small, and additional research could improve our understanding of differences in effects among species, seasons, and individual indicators of fitness. Several species of small mammals are dependent on audible signals for predator detection and communication, and noise has been shown to affect their vigilance and foraging behavior. However, other studies have documented no effects to rodents in noisy areas, and the effects of noise on small mammals may differ by species and study system. Techniques suggested in the literature for reducing noise emissions include sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference for literature about the effects of noise from oil and gas development on ungulates and small mammals.
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The recreational fishery for salmonine species in Lake Michigan (lake trout, Chinook salmon, coho salmon, steelhead, and brown trout) is largely maintained through stocking. Decisions about how many of each species to stock require an understanding of how to maintain a sustainable balance of predators (salmonine species) to prey (alewife) in the lake. The current models used to make these decisions can estimate the ratio of Chinook salmon to alewife in the lake. However, the Lake Michigan Committee’s new stocking strategy aims to incorporate the other salmonine species into this predator-prey ratio. We used structured decision making to evaluate potential stocking strategies. We worked with fishery stakeholders and members of the Lake Michigan Committee, conducted participatory modeling to forecast outcomes of stocking scenarios using updated information on fish movement and feeding, and evaluated the risk of these stocking strategies. Most of the stocking practices we evaluated resulted in a high risk of large declines in alewife abundance, negatively affecting future salmon fisheries. The forecasts were substantially more pessimistic than those resulting from a similar analysis conducted a decade earlier, apparently due to more recent alewife assessments indicating lower alewife productivity (recruits per spawner). Alewife recruitment dynamics is an area of substantial uncertainty, with apparently large consequences for management; decision makers on Lake Michigan would benefit from greater understanding of alewife recruitment dynamics to reduce this uncertainty when accounting for risks.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Robinson, K.F., Jones, M.L., Clark, R., Roth, B., Jonas, J., Tsehaye, I., Kornis, M.S., Turschak, B., O’Keefe, D., and Brenton, B., 2023, Updated decision analysis to inform multi-species salmonine management in Lake Michigan: Cooperator Science Series FWS/CSS-154-2023, 23 p.","productDescription":"23 p.","ipdsId":"IP-158445","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431814,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/updated-decision-analysis-inform-multi-species-salmonine-management-lake-michigan"},{"id":433625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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L.","contributorId":139526,"corporation":false,"usgs":false,"family":"Jones","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Richard","contributorId":340763,"corporation":false,"usgs":false,"family":"Clark","given":"Richard","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roth, Brian","contributorId":299805,"corporation":false,"usgs":false,"family":"Roth","given":"Brian","email":"","affiliations":[],"preferred":false,"id":907530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jonas, Jory","contributorId":195544,"corporation":false,"usgs":false,"family":"Jonas","given":"Jory","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":907531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsehaye, Iyob","contributorId":106801,"corporation":false,"usgs":true,"family":"Tsehaye","given":"Iyob","email":"","affiliations":[],"preferred":false,"id":907532,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kornis, Matthew S.","contributorId":201252,"corporation":false,"usgs":false,"family":"Kornis","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":907533,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Turschak, Benjamin A.","contributorId":340768,"corporation":false,"usgs":false,"family":"Turschak","given":"Benjamin A.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907534,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Keefe, Daniel","contributorId":340769,"corporation":false,"usgs":false,"family":"O’Keefe","given":"Daniel","email":"","affiliations":[{"id":37753,"text":"Michigan Sea Grant","active":true,"usgs":false}],"preferred":false,"id":907535,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brenton, Brian","contributorId":340770,"corporation":false,"usgs":false,"family":"Brenton","given":"Brian","email":"","affiliations":[{"id":81664,"text":"Brenton Consulting, LLC","active":true,"usgs":false}],"preferred":false,"id":907536,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70249996,"text":"70249996 - 2023 - Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado","interactions":[],"lastModifiedDate":"2023-11-12T14:15:31.35482","indexId":"70249996","displayToPublicDate":"2023-10-25T08:03:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5198,"text":"Geological Society of America Special Papers ","active":true,"publicationSubtype":{"id":10}},"title":"Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado","docAbstract":"Debris-flow alluvial fans are iconic features of dynamic landscapes and are hypothesized to record tectonic and climatic change. Here, we highlight their complex formation and evolution through an exemplary suite of Quaternary debris-flow alluvial fans emanating from the western range front of the Sangre de Cristo Mountains in south-central Colorado, USA. To evaluate the constructive and modifying processes that produce fan form and the associated sedimentary signatures, we applied a combined geomorphologic and sedimentologic approach using sedimentary facies analysis, soils mapping, high-resolution topographic data, and luminescence geochronology to document timing of fan construction and modification. We explored two subsets of fans in the study area: a southern set sourced from the extensively glaciated drainages of the Blanca Peak massif, and a northern set from the unglaciated drainages south of Great Sand Dunes National Park. Both sets of fans have: (1) active and successively abandoned surfaces that show evolving degradation of primary features through modification by secondary processes, (2) associated facies that display distinct characteristics representative of primary depositional and secondary modifying sedimentary processes, and (3) evidence of primary debris flow with subsequent modification by secondary processes. We found that surface geomorphology and facies assemblages in exposed alluvial-fan deposits represent sediment transport processes on both active and abandoned lobes. The link between fan surface morphologies and the sedimentary facies of their deposits provides a basis for an evolutionary process–based interpretation of debris-flow alluvial-fan geomorphology and provides a better understanding of complexities in buried paleosurfaces (intraformational progressive unconformities), surficial deformation, and landform development as recorded in debris-flow fan deposits in the sedimentary record.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2023.2561(01)","usgsCitation":"Nicovich, S., Schmitt, J., Gray, H., Klinger, R.E., and Mahan, S.A., 2023, Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado: Geological Society of America Special Papers , v. 561, 48 p., https://doi.org/10.1130/2023.2561(01).","productDescription":"48 p.","ipdsId":"IP-144536","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":441768,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2023.2561(01)","text":"Publisher Index Page"},{"id":435138,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96162BF","text":"USGS data release","linkHelpText":"Data Release for Luminescence: Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: examples from the western Sangre de Cristo Mountains, south-central Colorado"},{"id":422521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Sangre de Cristo Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.01583616224015,\n 38.75219123538736\n ],\n [\n -107.01583616224015,\n 37.01816107244015\n ],\n [\n -104.81857053724035,\n 37.01816107244015\n ],\n [\n -104.81857053724035,\n 38.75219123538736\n ],\n [\n -107.01583616224015,\n 38.75219123538736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"561","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nicovich, Sylvia","contributorId":210054,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":887922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmitt, James","contributorId":256655,"corporation":false,"usgs":false,"family":"Schmitt","given":"James","email":"","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":887923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Harrison J. 0000-0002-4555-7473","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":207019,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klinger, Ralph E.","contributorId":172929,"corporation":false,"usgs":false,"family":"Klinger","given":"Ralph","email":"","middleInitial":"E.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":887925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887926,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251200,"text":"70251200 - 2023 - Model-based surveillance system design under practical constraints with application to white-nose syndrome","interactions":[],"lastModifiedDate":"2024-01-29T12:21:40.355884","indexId":"70251200","displayToPublicDate":"2023-10-25T06:18:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1573,"text":"Environmental and Ecological Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Model-based surveillance system design under practical constraints with application to white-nose syndrome","docAbstract":"Infectious diseases are powerful ecological forces structuring ecosystems, causing devastating economic impacts and disrupting society. Successful prevention and control of pathogens requires knowledge of the current scope and severity of disease, as well as the ability to forecast future disease dynamics. Assessment of the current situation as well as prediction of the future conditions, rely on spatially referenced information regarding the presence or absence of a pathogen, and the prevalence of the pathogen in the population. In particular, knowledge about the location of the disease front is foundational for deploying disease countermeasures to prevent further disease spread and focusing control efforts to reduce disease intensity in affected areas. In this paper, we develop a model-based approach to designing sampling strategies for wildlife disease surveillance at the disease front. Specifically, we use a mechanistic spatio-temporal model based on an underlying partial differential equation to track the disease dynamics and predict the disease prevalence in the future. We also devise an optimal surveillance system design at the disease front that takes into account the practical constraints of sampling. We evaluate the effectiveness of our proposed design via a simulation study and demonstrate the application of the proposed approach by designing a surveillance strategy for the pathogen that causes white-nose syndrome.
Water clarity, defined in this study using measurements of the downwelling diffuse light attenuation coefficient (Kd) and turbidity, is an important indicator of lake trophic status and ecosystem health. We used in-situ measurements to evaluate existing semi-analytical models for Kd and turbidity, developed a regional turbidity model based on spectral shape, and evaluated the spatial and temporal trends in Lake Washington from 2013 to 2022 using Landsat-8/9 Operational Land Imager (OLI). We found no significant trends from 2013 to 2022 in Kd or turbidity when both the annual and full datasets were considered. In addition to the spring peak lasting from April through June, autumn Kd peaks were present at all sites, a pattern consistent with seasonal chlorophyll a and zooplankton concentrations. There existed no autumn peak in the monthly turbidity dataset, and the spring peak occurred two months before the Kd peak, nearly mirroring seasonal variability in the Cedar River discharge rates over the same period. The Kd and turbidity algorithms were thus each more sensitive to different sources of water clarity variability in Lake Washington.
","language":"English","publisher":"MPDI","doi":"10.3390/rs15205055","usgsCitation":"Schulien, J.A., Code, T.J., DeGasperi, C.L., Beauchamp, D., Tonus Ellis, A., and Litt, A.H., 2023, Annual and inter-annual variability in the diffuse attenuation coefficient and turbidity in an urbanized Washington lake from 2013 to 2022 assessed using Landsat-8/9: Remote Sensing, v. 15, no. 20, 5055, 19 p., https://doi.org/10.3390/rs15205055.","productDescription":"5055, 19 p.","ipdsId":"IP-158607","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":441806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15205055","text":"Publisher Index Page"},{"id":422837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.29668187426911,\n 47.76219367672758\n ],\n [\n -122.2936983290256,\n 47.49342533323215\n ],\n [\n -122.1703784589545,\n 47.49342533323215\n ],\n [\n -122.19822488122844,\n 47.75617656843582\n ],\n [\n -122.29668187426911,\n 47.76219367672758\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"20","noUsgsAuthors":false,"publicationDate":"2023-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulien, Jennifer A.","contributorId":331715,"corporation":false,"usgs":false,"family":"Schulien","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":79272,"text":"Schulien Consulting","active":true,"usgs":false}],"preferred":false,"id":888561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Code, Tessa Julianne 0000-0003-1481-020X","orcid":"https://orcid.org/0000-0003-1481-020X","contributorId":331687,"corporation":false,"usgs":true,"family":"Code","given":"Tessa","email":"","middleInitial":"Julianne","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeGasperi, Curtis L.","contributorId":257393,"corporation":false,"usgs":false,"family":"DeGasperi","given":"Curtis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":888563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tonus Ellis, Arielle","contributorId":331716,"corporation":false,"usgs":false,"family":"Tonus Ellis","given":"Arielle","email":"","affiliations":[{"id":36795,"text":"University of Washington, School of Aquatic and Fishery Sciences","active":true,"usgs":false}],"preferred":false,"id":888565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Litt, Arni H.","contributorId":331717,"corporation":false,"usgs":false,"family":"Litt","given":"Arni","email":"","middleInitial":"H.","affiliations":[{"id":36795,"text":"University of Washington, School of Aquatic and Fishery Sciences","active":true,"usgs":false}],"preferred":false,"id":888566,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249725,"text":"70249725 - 2023 - Climate-induced shifts in grassland bird nesting phenology have implications for grassland management","interactions":[],"lastModifiedDate":"2023-10-26T11:52:39.435755","indexId":"70249725","displayToPublicDate":"2023-10-21T06:47:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Climate-induced shifts in grassland bird nesting phenology have implications for grassland management","docAbstract":"Grasslands are among the most impacted ecosystems globally. In the midcontinent of North America, a > 80% loss of grasslands has made their conservation a major priority for resource managers. Grassland ecosystems evolved under periodic disturbances; consequently, grassland management often involves regular actions such as grazing, haying, or burning to maintain ecosystem integrity. The timing of such practices has direct implications on grassland ecology, agricultural economics, and survival and fecundity of grassland nesting birds (hereafter grassland birds). We conducted a meta-analysis on the nesting phenology of grassland birds throughout North America, focusing on nest-survival literature. We constructed a well-fitting model to predict median date of expected nest departure (hereafter fledge date) for grassland birds across the midcontinent. Predictions from our model demonstrate considerable spatial variation in median nesting phenology that is predictable using a spatially explicit spring phenology index. Median fledge dates were 8 or 13 days earlier in years of extreme weather conditions (dry or wet, respectively) than in years of average conditions. Species that generally nest in taller vegetation tended to have later median nest phenologies than those using shorter vegetation. Our results incorporate the most rigorous information available in the literature on nesting phenology of 36 grassland bird species and improve information available to managers about nesting phenology of grassland birds in the midcontinent of North America. Our predictions approximate the day when one-half of the nesting efforts would be complete for a given area within the midcontinent grasslands and can inform management and conservation decisions about the timing of management actions in grassland ecosystems.