The foundation of earthquake monitoring is the ability to rapidly detect, locate, and estimate the size of seismic sources. Earthquake magnitudes are particularly difficult to rapidly characterize because magnitude types are only applicable to specific magnitude ranges, and location errors propagate to substantial magnitude errors. We developed a method for rapid estimation of single‐station earthquake magnitudes using raw three‐component P waveforms observed at local to teleseismic distances, independent of prior size or location information. We used the MagNet regression model architecture (Mousavi and Beroza, 2020b), which combines convolutional and recurrent neural networks. We trained our model using ∼2.4 million P‐phase arrivals labeled by the authoritative magnitude assigned by the U.S. Geological Survey. We tested input data parameters (e.g., window length) that could affect the performance of our model in near‐real‐time monitoring applications. At the longest waveform window length of 114 s, our model (Artificial Intelligence Magnitude [AIMag]) is accurate (median estimated magnitude within ±0.5 magnitude units from catalog magnitude) between M 2.3 and 7.6. However, magnitudes above M ∼7 are more underestimated as true magnitude increases. As the windows are shortened down to 1 s, the point at which higher magnitudes begin to be underestimated moves toward lower magnitudes, and the degree of underestimation increases. The over and underestimation of magnitudes for the smallest and largest earthquakes, respectively, are potentially related to the limited number of events in these ranges within the training data, as well as magnitude saturation effects related to not capturing the full source time function of large earthquakes. Importantly, AIMag can determine earthquake magnitudes with individual stations’ waveforms without instrument response correction or knowledge of an earthquake’s source‐station distance. This work may enable monitoring agencies to more rapidly recognize large, potentially tsunamigenic global earthquakes from few stations, allowing for faster event processing and reporting. This is critical for timely warnings for seismic‐related hazards.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230171","usgsCitation":"Dybing, S., Yeck, W.L., Cole, H.M., and Melgar, D., 2024, Rapid estimation of single-station earthquake magnitudes with machine learning on a global scale: Bulletin of the Seismological Society of America, v. 114, no. 3, p. 1523-1538, https://doi.org/10.1785/0120230171.","productDescription":"16 p.","startPage":"1523","endPage":"1538","ipdsId":"IP-158857","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":432030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dybing, Sydney","contributorId":341314,"corporation":false,"usgs":false,"family":"Dybing","given":"Sydney","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":908222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":908223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Hank M. 0000-0003-1684-9116","orcid":"https://orcid.org/0000-0003-1684-9116","contributorId":335228,"corporation":false,"usgs":true,"family":"Cole","given":"Hank","email":"","middleInitial":"M.","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":908224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melgar, Diego","contributorId":341315,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":908225,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250758,"text":"70250758 - 2024 - Note to All Banders - January 2024","interactions":[],"lastModifiedDate":"2024-02-16T15:11:52.550919","indexId":"70250758","displayToPublicDate":"2024-01-02T09:05:09","publicationYear":"2024","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"title":"Note to All Banders - January 2024","docAbstract":"Note to All Banders was a special extra communication with more urgent information relevant to banders. . This note includes holiday greetings and a review of the 2023 successes at the Bird Banding Laboratory. Throughout 2022, the BBL increased communication, engagement, and collaboration, within the Eastern Ecological Science Center, U.S. Geological Survey, and with organization partners and local communities. This Note to All Banders highlights these efforts in more detail.","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Celis-Murillo, A., 2024, Note to All Banders - January 2024, 5 p.","productDescription":"5 p.","ipdsId":"IP-160851","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424056,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/note-banders-january-2024","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Celis-Murillo, Antonio 0000-0002-3371-6529","orcid":"https://orcid.org/0000-0002-3371-6529","contributorId":237851,"corporation":false,"usgs":true,"family":"Celis-Murillo","given":"Antonio","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891288,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256115,"text":"70256115 - 2024 - Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources","interactions":[],"lastModifiedDate":"2024-07-23T13:40:07.15414","indexId":"70256115","displayToPublicDate":"2024-01-02T08:33:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources","docAbstract":"Global resource extraction raises concerns about environmental pressures and the security of mineral supply. Strategies to address these concerns depend on robust information on natural resource endowments, and on suitable methods to monitor and model their changes over time. However, current mineral resources and reserves reporting and accounting workflows are poorly suited for addressing mineral depletion or answering questions about the long-term sustainable supply. Our integrative review finds that the lack of a robust theoretical concept and framework for mass-balance (MB)-consistent geological stock accounting hinders systematic industry-government data integration, resource governance, and strategy development. We evaluate the existing literature on geological stock accounting, identify shortcomings of current monitoring of mine production, and outline a conceptual framework for MB-consistent system integration based on material flow analysis (MFA). Our synthesis shows that recent developments in Earth observation, geoinformation management, and sustainability reporting act as catalysts that make MB-consistent geological stock accounting increasingly feasible. We propose first steps for its implementation and anticipate that our perspective as “resource realists” will facilitate the integration of geological and anthropogenic material systems, help secure future mineral supply, and support the global sustainability transition.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.3c03088","usgsCitation":"Simoni, M.U., Drielsma, J.A., Ericsson, M., Gunn, A.G., Heiberg, S., Heldal, T.A., Nassar, N.T., Petavratz, E., and Muller, D.B., 2024, Mass-balance-consistent geological stock accounting: A new approach toward sustainable management of mineral resources: Environmental Science and Technology, v. 58, p. 971-990, https://doi.org/10.1021/acs.est.3c03088.","productDescription":"20 p.","startPage":"971","endPage":"990","ipdsId":"IP-145992","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":440814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c03088","text":"Publisher Index Page"},{"id":431350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Simoni, Mark U.","contributorId":340251,"corporation":false,"usgs":false,"family":"Simoni","given":"Mark","email":"","middleInitial":"U.","affiliations":[{"id":81520,"text":"Norwegian University of Science and Technology, Norway","active":true,"usgs":false}],"preferred":false,"id":906749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drielsma, Johannes A.","contributorId":340252,"corporation":false,"usgs":false,"family":"Drielsma","given":"Johannes","email":"","middleInitial":"A.","affiliations":[{"id":81521,"text":"Drielsma Resources Europe, Germany","active":true,"usgs":false}],"preferred":false,"id":906750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ericsson, Magnus","contributorId":340253,"corporation":false,"usgs":false,"family":"Ericsson","given":"Magnus","email":"","affiliations":[{"id":81522,"text":"Luleå University of Technology, Sweden","active":true,"usgs":false}],"preferred":false,"id":906751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunn, Andrew G.","contributorId":340254,"corporation":false,"usgs":false,"family":"Gunn","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heiberg, Sigurd","contributorId":340255,"corporation":false,"usgs":false,"family":"Heiberg","given":"Sigurd","email":"","affiliations":[{"id":81523,"text":"Petronavit AS, Norway","active":true,"usgs":false}],"preferred":false,"id":906753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Heldal, Tom A.","contributorId":340256,"corporation":false,"usgs":false,"family":"Heldal","given":"Tom","email":"","middleInitial":"A.","affiliations":[{"id":35509,"text":"Geological Survey of Norway","active":true,"usgs":false}],"preferred":false,"id":906754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":906755,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Petavratz, Evi","contributorId":340257,"corporation":false,"usgs":false,"family":"Petavratz","given":"Evi","email":"","affiliations":[{"id":25567,"text":"British Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906756,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Muller, Daniel B.","contributorId":340258,"corporation":false,"usgs":false,"family":"Muller","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":39348,"text":"Norwegian University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":906757,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70251342,"text":"70251342 - 2024 - Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","interactions":[],"lastModifiedDate":"2024-02-06T13:19:35.568516","indexId":"70251342","displayToPublicDate":"2024-01-02T07:15:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","docAbstract":"Most of the world’s river-floodplain ecosystems are simultaneously undergoing modifications to their hydrological regimes and experiencing species invasions, making it unclear whether invasive species are the main drivers of ecosystem change or simply responding to changes in the hydrological regime.
We simulated patterns of forest recruitment and succession in a 2500-ha portion of the Upper Mississippi River floodplain with and without removal of invasive Phalaris arundinacea and under two different future 100-year hydrological scenarios: a future maintaining the average flooding conditions of the past 40 years (random) and a future that projects an observed upward 40-year trend in flooding conditions forward (trending). By comparing scenarios that included Phalaris removal and ones that did not, we were able to identify the conditions where Phalaris was the main driver of forest loss vs. the conditions where hydrology was the main driver of forest loss. Areas where Phalaris was the main driver of forest loss had mean annual flood inundation durations that were similar to areas that did not lose forest cover (60–90 growing season days), while areas where flooding was the main driver of forest loss had longer mean inundation durations (102–124 growing season days). In comparison to the random hydrology scenario, the trending scenario produced a decrease in the area over which Phalaris was identified as the main driver of forest loss and an increase in the area over which flood inundation was identified as the main driver of forest loss. Thus, if the observed trends in flooding continue, our model projects an increase in the area over which eradicating Phalaris is unlikely to result in the maintenance of forest cover. We used the Resist-Accept-Direct (RAD) framework to discuss potential management options to resist changes and maintain forest cover where Phalaris is likely to be the main driver of forest loss and to accept or direct changes in areas where forest loss is likely driven by hydrological change.
Coastal communities are vulnerable to multihazards, which are exacerbated by land subsidence. On the US east coast, the high density of population and assets amplifies the region's exposure to coastal hazards. We utilized measurements of vertical land motion rates obtained from analysis of radar datasets to evaluate the subsidence-hazard exposure to population, assets, and infrastructure systems/facilities along the US east coast. Here, we show that 2,000 to 74,000 km2 land area, 1.2 to 14 million people, 476,000 to 6.3 million properties, and >50% of infrastructures in major cities such as New York, Baltimore, and Norfolk are exposed to subsidence rates between 1 and 2 mm per year. Additionally, our analysis indicates a notable trend: as subsidence rates increase, the extent of area exposed to these hazards correspondingly decreases. Our analysis has far-reaching implications for community and infrastructure resilience planning, emphasizing the need for a targeted approach in transitioning from reactive to proactive hazard mitigation strategies in the era of climate change.
","language":"English","publisher":"Proceedings of the National Academy of Sciences","doi":"10.1093/pnasnexus/pgad426","usgsCitation":"Ohenhen, L.O., Shirzaei, M., and Barnard, P.L., 2024, Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast: PNAS Nexus, v. 3, no. 1, pgad426, 14 p., https://doi.org/10.1093/pnasnexus/pgad426.","productDescription":"pgad426, 14 p.","ipdsId":"IP-144579","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440818,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/pnasnexus/pgad426","text":"Publisher Index Page"},{"id":424065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.68468831217973,\n 40.41367726741822\n ],\n [\n -69.60900471842967,\n 40.41367726741822\n ],\n [\n -69.60900471842967,\n 42.22869359582157\n ],\n [\n -74.68468831217973,\n 42.22869359582157\n ],\n [\n -74.68468831217973,\n 40.41367726741822\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Ohenhen, Leonard O.","contributorId":290168,"corporation":false,"usgs":false,"family":"Ohenhen","given":"Leonard","email":"","middleInitial":"O.","affiliations":[{"id":62367,"text":"Department of Earth Sciences, University of Delaware, Newark, DE, USA","active":true,"usgs":false}],"preferred":false,"id":891289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shirzaei, Manoochehr 0000-0003-0086-3722","orcid":"https://orcid.org/0000-0003-0086-3722","contributorId":245637,"corporation":false,"usgs":false,"family":"Shirzaei","given":"Manoochehr","email":"","affiliations":[{"id":49242,"text":"Dept. of Geosciences, Virginia Tech Univ.","active":true,"usgs":false}],"preferred":false,"id":891290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891291,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263337,"text":"70263337 - 2024 - K-12 trade books’ representation of earthquake safety and protective actions: A content analysis","interactions":[],"lastModifiedDate":"2025-02-06T15:37:21.697759","indexId":"70263337","displayToPublicDate":"2024-01-02T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2324,"text":"Journal of Geoscience Education","active":true,"publicationSubtype":{"id":10}},"title":"K-12 trade books’ representation of earthquake safety and protective actions: A content analysis","docAbstract":"Meaningful learning resources for earthquake safety and survival have become an increasingly important topic among geoscientists, especially educators and researchers. Various members of the public, especially K-12 (ages 5–18) learners, continue to depend on scientific trade books available at their local public and school libraries for information about earthquake concepts. To our knowledge, no research has empirically examined how trade books represent earthquake safety and survival actions. In this research, we combine an iterative qualitative inductive and deductive analysis to explore the representation of earthquake safety and protective actions in 50 trade books. We categorize these actions into time-based practices related to preparedness before an earthquake, protective actions during an earthquake, and recovery after an earthquake. These trade books emphasize preparedness by means of building earthquake-resistant structures and urban planning, and efforts toward community resilience and keeping home supplies. The recommended personal protective action during an earthquake in the United States (“Drop, Cover, and Hold On”) is emphasized in the majority of the trade books, as well as other protective actions related to emotional actions and current technological automated actions such as earthquake early warning systems. Finally, the books highlight actions such as damage evaluation and support as ways to recover after an earthquake. Our findings highlight the issues between accepted earthquake safety and survival actions and the limited and/or inaccurate knowledge represented in some trade books. We provide interpretations of how presentation of limited or inaccurate information may increase confusion about appropriate protective actions. The inclusion of accepted and recommended protective actions in future trade books and the use of earthquake drills in public libraries as a supplement for trade book users may improve understanding and implementation of appropriate actions. We further demonstrate the potential of trade book contents in fostering earthquake education through library-community partnerships.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10899995.2023.2294672","usgsCitation":"Nyarko, S., Sumy, D.F., and McBride, S., 2024, K-12 trade books’ representation of earthquake safety and protective actions: A content analysis: Journal of Geoscience Education, v. 73, no. 1, p. 28-45, https://doi.org/10.1080/10899995.2023.2294672.","productDescription":"18 p.","startPage":"28","endPage":"45","ipdsId":"IP-150274","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":490089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1805/42990","text":"Publisher Index Page"},{"id":481743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"73","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Nyarko, Samuel","contributorId":350630,"corporation":false,"usgs":false,"family":"Nyarko","given":"Samuel","affiliations":[{"id":32889,"text":"Indiana University-Purdue University Indianapolis","active":true,"usgs":false}],"preferred":false,"id":926503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sumy, Danielle F.","contributorId":197628,"corporation":false,"usgs":false,"family":"Sumy","given":"Danielle","middleInitial":"F.","affiliations":[],"preferred":false,"id":926504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":926505,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249904,"text":"70249904 - 2024 - Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series","interactions":[],"lastModifiedDate":"2024-04-01T17:30:03.617149","indexId":"70249904","displayToPublicDate":"2024-01-01T12:27:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series","docAbstract":"The U.S. Geological Survey (USGS) and NOAA’s National Integrated Drought Information System (NIDIS) conducted a series of four Listening Sessions in 2022 – each with a different application or topical focus – to seek input on priorities and needs related to predicting water availability changes under drought conditions at national and regional scales. This input was gathered to help inform the USGS Drought Program, regional and national drought efforts at NIDIS, and other national drought efforts. The series started with a February 2022 kick-off that introduced the series of Listening Sessions being held from March through September 2022. This kickoff also provided an overview of the USGS Drought Program’s work to characterize hydrological (e.g., streamflow and groundwater) drought, drought variability, drivers, and trends over the past century. Participants in these Listening Sessions included diverse stakeholder representation and perspectives.\n\nThe first of the four Listening Sessions focused on streamflow (March 3, 2022), and included a short introduction to the USGS national streamflow drought research, the properties of a national drought prediction system, as well as presentations by other agencies on different drought prediction and forecasting efforts. The second session focused on groundwater (May 5, 2022), and included presentations on groundwater drought, sustainable groundwater management, and improving our understanding of soil moisture, groundwater, and surface water drought. The third session focused on water use (July 14, 2022), and included a discussion of the different drought types, as well as an introduction to several key projects, including the USGS Upper Colorado River Basin Study, the Ogallala Data Directory project, and a multi-agency drought prediction partnership in Oklahoma. The fourth and final Listening Session focused on water availability prediction for ecosystems (September 8, 2022), and included presentations on the development of a national capacity for eco-hydrological and drought science, building climate resilience, and actionable ecodrought resources.","language":"English","publisher":"National Integrated Drought Information System","usgsCitation":"Skumanich, M., Smith, E., Lisonbee, J., and Hammond, J., 2024, Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series, 24 p.","productDescription":"24 p.","ipdsId":"IP-153596","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":427276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422385,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.drought.gov/documents/drought-prediction-and-water-availability-report-2022-usgs-nidis-national-listening","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skumanich, Marina","contributorId":260137,"corporation":false,"usgs":false,"family":"Skumanich","given":"Marina","email":"","affiliations":[{"id":52519,"text":"NOAA National Integrated Drought Information System","active":true,"usgs":false}],"preferred":false,"id":897766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Erik 0000-0001-8434-0798","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":221804,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisonbee, Joel","contributorId":298624,"corporation":false,"usgs":false,"family":"Lisonbee","given":"Joel","email":"","affiliations":[{"id":64629,"text":"NOAA-NIDIS","active":true,"usgs":false}],"preferred":false,"id":897768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259501,"text":"70259501 - 2024 - Snake River Fall Chinook Salmon research and monitoring","interactions":[],"lastModifiedDate":"2024-10-10T16:16:16.36293","indexId":"70259501","displayToPublicDate":"2024-01-01T10:59:34","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Snake River Fall Chinook Salmon research and monitoring","docAbstract":"In Chapter 1, we report on development and application of an integrated population model (IPM) for the natural-origin fall Chinook salmon population upstream of Lower Granite Dam. This year’s efforts represent the third update to the model. Initial efforts focused on generating juvenile and adult abundance estimates, with estimates of uncertainty, for informing the life-cycle model and estimating the effects of covariates on key demographic parameters. The goals of this year’s report are to 1) describe the modifications and advances made since the previous report, 2) to annually update and report the abundance estimates and other quantities used in the model, 3) to provide annual estimates of population parameters estimated by the IPM, and 4) to outline the next year’s tasks for advancing and/or applying the model.\n Since our last report on the life-cycle model, we have made a number of changes including: 1) incorporating jack abundance and age-structure data into the observation model, 2) changing smolt-to-adult survival (SAR) for subyearling and yearling to partial SARs that represent the joint probability surviving and entering the ocean at a given juvenile age, 3) combining age categories for rarely observed ages, 4) using scale data from unmarked fish to estimate age structure, and 5) generating composite life-cycle demographic parameters (cumulative capacity and productivity) from stage-specific parameters. We also generated juvenile abundance estimates, extended the model to include three additional brood years (1992– 2021), and ran the model to forecast returns to Lower Granite in 2022. \n For posterior medians of life stage-specific parameters, we estimated a mean productivity of 438 natural-origin juvenile recruits per female spawner, a capacity of 1.36 million juveniles, and a mean smolt-to-adult survival (SAR) of 1.2%. We detected strong density-dependent regulation, with juvenile recruits per spawner declining to about 50 juvenile recruits per female spawner at high spawner abundance. Across the entire life cycle, these stage-specific parameters resulted in a median cumulative intrinsic productivity of 1.93 adult female recruits per female spawner and a median equilibrium abundance of 2,851 female spawners (7,842 total spawners). Annual juvenile productivity varied from about 250–1,000 juveniles per spawner but displayed no temporal trends or patterns. For the three most recent brood years added to the model, recruits per spawner were higher than average but well within the range of uncertainty observed over the entire time series. In contrast to juvenile recruitment variability, SAR varied considerably among years and exhibited two periods of high survival (1996–2001 and 2007–2012) when SAR ranged from 2% to 6% and cumulative productivity ranged from 2 to 8 recruits per spawner. Partial SARs revealed that yearling outmigrants contributed substantially to the high SARs in the first high-survival period, but the second period was dominated by subyearlings. Yearlings contributed >30% to SAR in most years prior to 2007, and <30% since 2007.\n\nOur two-stage IPM provides a wealth of information about population dynamics affecting two key life-stage transitions (spawner to juvenile, and juvenile to spawner) centered on passage at Lower Granite Dam. By summarizing these stage-specific demographic parameters across the entire life cycle, this information will be useful for informing the recovery status of this threatened population. Whereas previous versions introduced hydrosystem and ocean covariates into the model, this phase of model development focused on solidifying the underlying model structure by introducing the concept of partial SARs and developing composite productivity and capacity as a function of underlying stage-specific parameters. Given this advancement, our next steps are to re-incorporate covariates into the model, specifically to understand how different factors affect partial SARs of subyearling and yearlings. Longer term model developments include:1) incorporating hatchery fish to explicitly estimate their survival as an alternative method for estimating natural-origin age composition, 2) expanding the model’s structure to include the three major spawning aggregates, 3) more explicitly modeling hydrosystem effects including transportation, and 4) using the model to assess retrospective and prospective management actions.\n\nIn 2022, the U.S. Geological Survey (USGS) focused adult salmon survey efforts in the Snake River on deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses. We use used a boat-mounted underwater video camera to count 99 deepwater redds at 16 of the 29 sites surveyed. Redd depths averaged 4.4 m. In conjunction with the Idaho Power Company, we collected genetic samples from 318 live fall Chinook salmon (Oncorhynchus tshawytscha) and 19 carcasses at 40 unique geographic locations that spanned 91 river kilometers. Eighty fish were collected at three sites (High Range [rkm 332.3], Dug Bar [rkm 315.4], and Three Creek [rkm 384.0]), which accounted for 23% of all collected fish in 2022. Most (333 fish) post-spawned salmon were collected from early to mid-November just after the peak of spawning. A summary of 2021 PBT results produced by the Idaho Power Company can be found in Appendix A.2.\n\nBeach seining and PIT tagging of subyearling fall Chinook salmon was conducted in Snake and Salmon rivers to obtain information on population metrics and growth as well as to provide data for ongoing life-cycle modeling. In the Snake River, we collected 7,496 subyearlings, tagged 4,139, and recaptured 502 (12.1%). Using 8-mm tags in 45–49-mm fish allowed us to represent an additional 25% of the juvenile population through PIT tagging beyond just using standard 9- and 12-mm tags. In the Salmon River, we captured 206 natural subyearlings with the majority (52%) of fish being captured at two sites: rkm 20 and 26. We tagged 145 subyearlings and recaptured 9 fish. \n\nMany of the subyearlings we tagged in the Snake River were detected passing Lower Granite Dam, but only 4 fish tagged in the Salmon River were detected. In total we detected 484 (11.3%) tagged fish at Lower Granite Dam, and detection rates varied by tag size and passage route. More subyearlings were detected passing via the removable spill weir (RSW) earlier in the season while more fish were detected passing through the juvenile fish bypass system (JBS) earlier in the season while more fish were detected passing via the removable spill weir (RSW) later in the season. In general, fish tagged with 12-mm PIT tags had higher detection rates than fish tagged with smaller tags. Survival to Lower Granite Dam was low and ranged from 0.22 to 0.36. Season-wide, growth of subyearlings was higher in the lower reach than in the upper reach of the Snake River.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Perry, R., Hance, D., Plumb, J., Tiffan, K.F., Bickford, B., Benson, S.L., Rhodes, T., Brink, S., and Alcorn, B., 2024, Snake River Fall Chinook Salmon research and monitoring, v, 110 p.","productDescription":"v, 110 p.","ipdsId":"IP-159991","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":462763,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org"},{"id":462792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": 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0000-0003-0397-1200","orcid":"https://orcid.org/0000-0003-0397-1200","contributorId":303796,"corporation":false,"usgs":true,"family":"Benson","given":"Scott","email":"","middleInitial":"Louis","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":915514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodes, Tobyn 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":220181,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":915513,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brink, Steve","contributorId":222508,"corporation":false,"usgs":false,"family":"Brink","given":"Steve","email":"","affiliations":[],"preferred":false,"id":915516,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alcorn, 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Desert, California","docAbstract":"The Pinto Mountain Fault Zone (PMFZ) marks a major structural boundary between east-oriented sinistral faults of the eastern Transverse Ranges (to the south) and northwest-oriented dextral faults of the south-central Mojave Desert (to the north). These structural fault systems comprise sinistral and dextral deformational domains of the Eastern California Shear Zone (ECSZ) that intersect one another in the Copper Mountain and Twentynine Palms areas. The U.S. Geological Survey (USGS) is conducting detailed geologic mapping and geochronologic investigations designed to clarify geometric, kinematic, and temporal relations among the two domains, that are focused on the central portion of the left-lateral PMFZ near its intersection with the right-lateral Copper Mountain Fault (CMF) and Mesquite Lake Fault Zone (MLFZ).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 23/24 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Minnesota","usgsCitation":"Menges, C., Dudash, S.L., and Mahan, S.A., 2024, Using geologic mapping to understand temporal and spatial relations of closely clustered to concurrent latest Holocene surface ruptures on two intersecting faults, south-central Mojave Desert, California, in Geologic Mapping Forum 23/24 abstracts, p. 16-17.","productDescription":"2 p.","startPage":"16","endPage":"17","ipdsId":"IP-160493","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":464812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464783,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://conservancy.umn.edu/items/f2deba60-7ac2-49ac-b63f-b7422a85065d","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"south-central Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.1167,\n 34.2333\n ],\n [\n -116.1167,\n 34.125\n ],\n [\n -116,\n 34.125\n ],\n [\n -116,\n 34.2333\n ],\n [\n -116.1167,\n 34.2333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Menges, Christopher M. 0000-0002-8045-2933","orcid":"https://orcid.org/0000-0002-8045-2933","contributorId":204511,"corporation":false,"usgs":true,"family":"Menges","given":"Christopher M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudash, Stephanie L. 0000-0001-8728-5915 sdudash@usgs.gov","orcid":"https://orcid.org/0000-0001-8728-5915","contributorId":5911,"corporation":false,"usgs":true,"family":"Dudash","given":"Stephanie","email":"sdudash@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":920290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274318,"text":"70274318 - 2024 - Climate-resource scenarios to inform climate change adaptation in Wrangell-St. Elias National Park and Preserve: Summary of 2021 climate change scenario planning","interactions":[],"lastModifiedDate":"2026-03-26T15:45:20.211683","indexId":"70274318","displayToPublicDate":"2024-01-01T10:29:04","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/WRST/NRR-2024/2613","title":"Climate-resource scenarios to inform climate change adaptation in Wrangell-St. Elias National Park and Preserve: Summary of 2021 climate change scenario planning","docAbstract":"This report illustrates use of scenario planning as a climate change adaptation tool supporting Wrangell-St. Elias National Park and Preserve’s Resource Stewardship Strategy. The primary objective of scenario planning is to help resource managers and scientists make management and planning decisions informed by assessments of critical future uncertainties. This report outlines a process that synthesized future climate projections into three distinct but plausible and relevant climate summaries for the focal area and used them to develop climate-resource scenarios through participatory scenario planning.
Initial steps identified the priority resource management topics and the corresponding related climate uncertainties. Next, local climate summaries were used to develop divergent climate futures: those that describe the broadest possible range of plausible conditions while capturing relevant uncertainty. The final phase further developed the climate futures and their resource implications. These participatory scenario planning exercises occurred virtually in fall (August–November) 2021. The climate-resource scenarios informed adaptation strategies in conjunction with the park’s Resource Stewardship Strategy development. The scope and complexity of this effort is unique but elements from the scenarios and resource implications have broad applicability to other large, protected areas in Alaska and Northwest Canada.
The early-life history stages of fish are sensitive to environmental change and therefore can indicate habitat quality as well as help predict recruitment of resident and transient fishes. In 2019, as part of the Lake Erie Cooperative Science and Monitoring Initiative, we conducted a lake-wide assessment of the ichthyoplankton community in U.S. nearshore waters and international offshore waters. The goal of this work was to characterize the larval fish community across the lake and assess species composition, phenology, and distribution of larvae. Ichthyoplankton were sampled weekly using bongo nets at ports beginning at the Detroit River and along the southern shore of Lake Erie to Dunkirk, NY, and less frequently in the Niagara River and offshore areas. Larval fish were present from March 26 through August 29, 2019. The first taxon to emerge was Lake Whitefish in all basins, followed by Walleye, Yellow Perch, and catostomids, depending on port. Mean total density peaked in mid-June due to high catches of Gizzard Shad, Morone spp., and Freshwater Drum in the western basin. Few fish were collected in the offshore sites. Taxa richness, diversity, and larval density were higher in the western basin and lower in the central and eastern basins, generally following the productivity gradient. This was the first study to provide a comprehensive community assessment of the ichthyoplankton community of Lake Erie and can provide a baseline to assess future change, especially in community composition or phenology, of larvae which are likely to respond to climate and habitat change.
","language":"English","publisher":"Michigan State University Press","doi":"10.14321/aehm.027.01.98","usgsCitation":"DeBruyne, R.L., Amidon, Z., Angelosanto, M.J., Eberly, E.A., Gorsky, D., Ireland, S., Mayer, C., Provo, S., VanScoyoc, H., Watkins, J.M., and Roseman, E., 2024, Broad scale community-level larval fish survey of southern Lake Erie: Aquatic Ecosystem Health and Management, v. 27, p. 97-114, https://doi.org/10.14321/aehm.027.01.98.","productDescription":"18 p.","startPage":"97","endPage":"114","ipdsId":"IP-151982","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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Crustal Model for Seismic Hazard Studies","interactions":[],"lastModifiedDate":"2024-08-15T15:19:06.555598","indexId":"70257354","displayToPublicDate":"2024-01-01T10:06:04","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Recent applications of the USGS National Crustal Model for Seismic Hazard Studies","docAbstract":"The U.S. Geological Survey is developing the National Crustal Model (NCM) for seismic hazard studies to facilitate modeling site, path, and source components of seismic hazard across the conterminous United States. The NCM is composed of a 1km grid of geophysical profiles, extending from the Earth’s surface into the upper mantle. It is constructed from a threedimensional (3D) geologic framework and geophysical rules that use (1) a petrologic and mineral physics database; (2) a 3D temperature model; and (3) a calibrated rock type- and age-dependent porosity model. Parameters needed to estimate site response for existing ground motion models (GMMs), including the time-averaged velocity in the upper 30 meters (VS30), the depths to 1.0 and 2.5 km/s shear-wave velocity (Z1.0 and Z2.5), and sediment thickness, can be computed from the NCM. As GMMs continue to improve in the future, other metrics could also be extracted or derived from the NCM, such as fundamental period, site attenuation (ko), a fully frequency-dependent site response function, or 3D geophysical volumes for wavefield simulations. 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","language":"English","publisher":"College of Agriculture, Life & Environmental Sciences, University of Arizona","usgsCitation":"Gornish, E.S., Shriver, L.C., Corwin, R., Havrilla, C., Gehring, C.A., and Costanzo, S.A., 2024, Germination information for common Arizona restoration species: Cooperative Extension Publication AZ2076, 3 p.","productDescription":"3 p.","ipdsId":"IP-158177","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":463763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":463744,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://hdl.handle.net/10150/671178","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gornish, Elise S 0000-0002-2055-4874","orcid":"https://orcid.org/0000-0002-2055-4874","contributorId":240596,"corporation":false,"usgs":false,"family":"Gornish","given":"Elise","email":"","middleInitial":"S","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":917941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shriver, Laura Cecilia 0009-0008-5567-0868","orcid":"https://orcid.org/0009-0008-5567-0868","contributorId":334175,"corporation":false,"usgs":true,"family":"Shriver","given":"Laura","email":"","middleInitial":"Cecilia","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":917942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corwin, Ri","contributorId":346084,"corporation":false,"usgs":false,"family":"Corwin","given":"Ri","email":"","affiliations":[{"id":25557,"text":"Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":917943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Havrilla, Caroline 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":245368,"corporation":false,"usgs":false,"family":"Havrilla","given":"Caroline","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":917944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gehring, Catherine A.","contributorId":189076,"corporation":false,"usgs":false,"family":"Gehring","given":"Catherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":917945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costanzo, Sarah A. 0000-0003-4137-1548","orcid":"https://orcid.org/0000-0003-4137-1548","contributorId":346108,"corporation":false,"usgs":true,"family":"Costanzo","given":"Sarah","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":917946,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261588,"text":"70261588 - 2024 - Investigating the atmospheric conditions associated with impactful shallow landslides in California (USA)","interactions":[],"lastModifiedDate":"2024-12-16T15:32:25.983624","indexId":"70261588","displayToPublicDate":"2024-01-01T09:26:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the atmospheric conditions associated with impactful shallow landslides in California (USA)","docAbstract":"Shallow landslides are often triggered during rainfall events, which can increase subsurface soil water pressure and destabilize hillslopes. The likelihood of regional shallow landslide initiation is often assessed through a comparison of rainfall intensity and duration to pre-established thresholds. While informative for landslide warning, this exclusive focus on rainfall exceeding thresholds does not consider the meteorological conditions producing the rainfall. Here, we ask the question, are there common meteorological characteristics that lead to landslide-triggering precipitation? We develop a catalog of 18 post-1995 widespread, impactful shallow landslide events occurring within 13 storms across California, USA, where initiation time could be constrained to a ≤6-h window. We examine storm characteristics during the landslide initiation window using atmospheric reanalysis products, radar observations, and quantitative precipitation estimates. We find that, while there are some common atmospheric characteristics across landslide events, they can occur under a range of atmospheric conditions. For example, all Northern California landslide events assessed are associated with moderate to strong atmospheric rivers (ARs), while Southern California landslides feature non-AR to strong AR conditions. The storm events evaluated herein share many characteristics of hydrologically important storms in California that did not necessarily result in landslides; thus, atmospheric characteristics alone may not be sufficient to determine whether landslides will occur. However, documenting the characteristics of landslide-triggering storms defines the conditions under which landslides tend to occur, provides analog events that can be useful in forecast applications, helps define future research directions relating to atmospheric conditions and landslides, and supports interdisciplinary research efforts.
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scorbett@usgs.gov","orcid":"https://orcid.org/0000-0003-3277-1021","contributorId":200617,"corporation":false,"usgs":true,"family":"Corbett","given":"Skye","email":"scorbett@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":921123,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70270799,"text":"70270799 - 2024 - Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries","interactions":[],"lastModifiedDate":"2025-08-28T14:31:44.183974","indexId":"70270799","displayToPublicDate":"2024-01-01T09:09:48","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":6053,"text":"Hawaii Cooperative Studies Unit Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"HCFRU-002","title":"Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries","docAbstract":"Noncommercial, shore-based fisheries provide economic, social, and cultural services to communities throughout the Hawaiian Islands. The State of Hawai‘i Department of Land and Natural Resources (DLNR), Division of Aquatic Resources (DAR) routinely conducts surveys to monitor noncommercial fisheries such that estimates of fishing effort and catch by gear type can be generated and used to implement more sustainable management practices. DAR executes both the Hawai‘i Marine Recreational Fishery Survey (HMRFS), a nationally standardized survey that focuses on intercepting fishers at access points (i.e., boat ramps) across the main Hawaiian Islands, and a set of roving creel surveys on O‘ahu, Maui Nui, and Kaua‘i that observe and intercept fishers at locations along the shoreline outside of those targeted by HMRFS. The latter set of creel surveys were designed to complement HMRFS by expanding its geographic coverage and thus providing a more representative picture of noncommercial fishing in Hawai‘i.
Sustainable management priorities set by DAR rely on the availability of statewide, fishery- dependent data. Thus, we collate information from island-based roving creel surveys into a cohesive Statewide Creel Survey Database. Further, we provide preliminary analyses and describe ways that surveys could be streamlined to improve future data collection, analysis, and utility. In so doing, we synthesize the most detailed information to-date about noncommercial shore-based fisheries of Hawai‘i. The unprecedented spatial and temporal coverage of DAR’s dataset reveals the value of their survey efforts over the last decade to address fishery management needs. Our primary objectives, results, and conclusions are summarized below:
1) Integrate DAR roving creel survey data from different islands into a single Statewide Creel Survey Dataset (Chapter II). We describe the collation of creel survey data from O‘ahu, Maui Nui, and Kaua‘i into a statewide dataset. We also offer ways in which these surveys could be streamlined to meet the needs of managers and decision makers. Briefly, these are to create a statewide strategic plan, standardize the execution of standard operating procedures, centralize the creel survey database and associated metadata, and consider using technology that improves the data pipeline, including transitioning from paper-based to electronic systems for data entry and processing.
2) Assess whether the new Statewide Creel Survey Dataset can provide inputs for length-based stock assessments (Chapter III). Only on Maui were interviews conducted with associated catch data. There was reasonably high taxonomic coverage (42 species from 186 interviews with 310 fishers), but low sample sizes for nearly all species precluded the development of length-based stock assessments. We provide summary statistics from the existing data and briefly discuss how technologies could be used to automate analysis of images of noncommercial catch.
3) Analyze the Statewide Creel Survey Dataset for spatial and temporal patterns in fishing effort (Chapter IV):
a. Visualizing noncommercial fishing pressure. We found that fishing effort (mean number of fishers observed per survey event at a site) on O'ahu was over three times greater than that recorded during similar surveys conducted on Maui or Kaua'i. We create maps that display the distribution of angling and spearfishing effort around each of the three islands.
b. Factors that predict fishing “hotspots” around Maui. Fishing effort on Maui was associated with areas with more wave power and less parking availability. There were half as many fishers in areas with parking lots than in areas with parking on the road shoulder only.
c. Changes in fishing effort during the COVID-19 pandemic. There was no change in fishing effort on O‘ahu during the first year of the pandemic, but there was a 20% decline in year 2 and a 33% decline in year 3, both in comparison to pre-pandemic levels. Pre-pandemic creel survey data were unavailable for Maui and Kaua‘i, but fishing effort on these islands also declined as the pandemic progressed at similar or greater rates than those observed on O‘ahu.
4) Quantify potential bias in survey methods by experimentally deriving fisher detection probabilities of shore-based and drone-based surveys (Chapter V):
a. Shore-based surveys. We conducted roving creel surveys for four months at three locations around Hilo Bay, designed to emulate and estimate the efficacy of DAR standard operating procedures. There was high agreement between paired observers in counting fishers, leading to near-perfect detection probabilities of both anglers (94%) and spearfishers (97%), but relatively low agreement and detection probabilities of other fishers (throw net, ‘opihi picking, etc.) (52%).
b. Drone-based surveys. We used an unmanned aerial vehicle (UAV; operated by DAR staff) to collect imagery of fishers along the Hilo Bay shoreline. We used still images and video clips (with known fishing activity) to build an online survey that was distributed to DAR and HCFRU personnel, asking them to count and categorize resource users as a snorkeler, spearfisher, angler, or other fisher. Only 40.0% of the responses correctly counted and categorized resource users in the image. Anglers were correctly identified and enumerated in 90.0% of the responses, but the correct response rates of the other three user categories ranged from 67.8% – 79.4%. Snorkelers and anglers tended to be undercounted while spearfishers and other fishers were overcounted.
5) Review the potential for incorporating emerging technologies that will improve, augment, and evolve creel survey data collection, especially for spearfishing (Chapter VI). Within the context of monitoring shore-based noncommercial fishing, we review the use of electronic data entry/processing systems with geospatial and image capabilities, field cameras, drones, smart buoys, citizen science apps, data mining social media, artificial intelligence and machine learning. We highlight several of the challenges and considerations when implementing these technologies into creel surveys and provide a synthesis of options that could be used to better estimate spearfishing.
The general conclusion of this assessment is that the DAR roving creel survey program is collecting valuable data that supplement the existing HMRFS efforts. However, there are a number of areas that could be improved to make these efforts a more effective tool for decision-making processes in resource management and conservation:
1) Establishment of clear statewide and island objectives for the Statewide Creel Survey Dataset. Currently, data collection efforts are focused towards addressing a very broad purpose – supplementing the HMRFS data collection efforts. However, the results of the preliminary analyses conducted as part of this project suggest that the data could be used to address other areas of need if these objectives were clearly defined. Further, the design of the creel survey would benefit from greater standardization of survey protocols between islands and an effort to define a) the acceptable margins of error associated with the estimates generated by these data and b) the minimum level of change that the surveys would need to detect to be useful to managers.
2) Centralization of data entry, data quality assessment, and data accessibility. Currently, each DAR office manages data entry, checks the data for errors, and is responsible for managing and storing the data. Instituting a centralized data entry system, particularly an online database that can receive survey data from tablets or smartphones running a standardized data collection application would improve efficiency, reduce data entry errors, and accelerate the availability of data to managers. A substantial amount of time and effort from the project described in this report was devoted to checking the dataset for errors. The development and application of data quality assurance protocols would ensure that the data are reliable and available in a timely fashion to support management decisions.
3) Address lingering questions regarding the efficacy of current survey protocols to capture and characterize the spearfishing component of the noncommercial fishery. The results presented in the report suggest that the current creel survey protocols do a good job detecting spearfishers when present but are not capturing sufficient data about their catch or total effort. There are also questions remaining as to whether the survey times and sites are sufficiently capturing the behavior of spearfishers in Hawai‘i. A more thorough assessment – whether through additional research, alteration of survey design, or review of data by representatives of the spearfishing community – would provide insight on how to use the Statewide Creel Survey Database to inform management of spearfishing.
4) Investigate the integration of technological advancements into the creel survey methods. As priorities and needs are developed and formalized, it would be valuable to consider how various technological advancements might enhance and streamline data collection or open new avenues of inquiry.
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We used a popular culturomics tool based on search engine usage to investigate how the U.S. Endangered Species Act listing actions may influence public interest in imperiled freshwater taxa. Yet questions remain regarding the acceptable applications of these data leading us to also evaluate aspects of data quality such as repeatability of timeseries and spatial relative search volume (RSV) data for our search terms. We discovered that low search volume for many freshwater species restricted the number of species that could be analyzed and may signal low public awareness for these species. Low repeatability of timeseries relative search volume data suggests that greater scrutiny and quality control methods may be needed when analyzing these data. For species that had the highest data repeatability, there were positive associations of listing actions and relative search volume for threatened and endangered species. Anomalous peaks of search volume were sometimes but not always related to listing actions or online news stories. Spatial analysis indicated that search volumes were highest in states within species’ native ranges suggesting that people are most interested in species that occur near where they live.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.110397","usgsCitation":"Moore, M.J., and Hyman, A.A., 2024, What can conservation culturomics tell us about factors driving public interest in aquatic endangered species: Biological Conservation, v. 289, 110397, 8 p., https://doi.org/10.1016/j.biocon.2023.110397.","productDescription":"110397, 8 p.","ipdsId":"IP-154898","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"289","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hyman, A. A","contributorId":342659,"corporation":false,"usgs":false,"family":"Hyman","given":"A.","email":"","middleInitial":"A","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":910264,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259272,"text":"70259272 - 2024 - Larval Lake Whitefish (Coregonus clupeaformis) zooplankton consumption remains constant despite variation in prey densities in western Lake Erie","interactions":[],"lastModifiedDate":"2024-10-03T13:59:57.68966","indexId":"70259272","displayToPublicDate":"2024-01-01T08:55:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18728,"text":"Aquatic Ecosystem Health and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Larval Lake Whitefish (Coregonus clupeaformis) zooplankton consumption remains constant despite variation in prey densities in western Lake Erie","title":"Larval Lake Whitefish (Coregonus clupeaformis) zooplankton consumption remains constant despite variation in prey densities in western Lake Erie","docAbstract":"Larval fish growth and survival could be limited or reduced due to patchiness of zooplankton densities, even in productive aquatic systems. Recent declines in Lake Whitefish (Coregonus clupeaformis) populations prompted research to identify underlying mechanisms controlling survival at early life stages. In Lake Erie, the bottleneck window controlling year-class strength of Lake Whitefish likely occurs during the first growing season, suggesting that availability of important prey could influence year-class strength. Therefore, spatial and temporal larval Lake Whitefish distribution, diet, and prey utilization were evaluated in western Lake Erie. The pelagic Lake Whitefish larval period in the western basin extends from April 1 to May 15 with most larvae concentrated nearshore at the surface both day and night. Cyclopoid copepods were the most important prey item; however, calanoid copepods and Cladocera were consistently consumed, indicating that copepods and Cladocera were important larval Lake Whitefish prey items. Copepod and Cladocera biomass were the highest nearshore, overlapping with the highest larval Lake Whitefish densities. However, the amount of food consumed by larvae was consistent in all areas, suggesting that offshore areas in western Lake Erie with relatively low zooplankton biomass harbor enough food to satiate larval Lake Whitefish. Therefore, it is unlikely that prey availability limits survival through means of starvation during the larval phase.
","language":"English","publisher":"Michigan State University Press","doi":"10.14321/aehm.027.01.85","usgsCitation":"Amidon, Z.J., DeBruyne, R.L., Roseman, E., Mayer, C., and Sakas, A., 2024, Larval Lake Whitefish (Coregonus clupeaformis) zooplankton consumption remains constant despite variation in prey densities in western Lake Erie: Aquatic Ecosystem Health and Management, v. 27, no. 1, p. 85-97, https://doi.org/10.14321/aehm.027.01.85.","productDescription":"13 p.","startPage":"85","endPage":"97","ipdsId":"IP-151984","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"western Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.84247076900705,\n 42.305276207315416\n ],\n [\n -82.2017867383284,\n 42.18036652529425\n ],\n [\n -82.47190741565669,\n 41.988026074700485\n ],\n [\n -83.3006979100112,\n 42.03890482252197\n ],\n [\n -83.5046343851954,\n 41.78590293990335\n ],\n [\n -83.24036024165017,\n 41.58468492061536\n ],\n [\n -82.95312928144114,\n 41.426580086404556\n ],\n [\n -81.908009660297,\n 41.402547807875536\n ],\n [\n -80.98977052909981,\n 41.79736635963681\n ],\n [\n -81.84247076900705,\n 42.305276207315416\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Amidon, Zachary J","contributorId":214490,"corporation":false,"usgs":false,"family":"Amidon","given":"Zachary","email":"","middleInitial":"J","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":914735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":914736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":914737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Christine","contributorId":237769,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","affiliations":[{"id":47604,"text":"University of Toledo, Lake Erie Center","active":true,"usgs":false}],"preferred":false,"id":914738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sakas, Alexis","contributorId":343802,"corporation":false,"usgs":false,"family":"Sakas","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":914739,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70255255,"text":"70255255 - 2024 - Hit snooze: An imperiled hibernator assesses spring snow conditions to decide whether to terminate hibernation or reenter torpor","interactions":[],"lastModifiedDate":"2024-06-13T13:55:23.43611","indexId":"70255255","displayToPublicDate":"2024-01-01T08:55:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17824,"text":"Ecological and Evolutionary Physiology","active":true,"publicationSubtype":{"id":10}},"title":"Hit snooze: An imperiled hibernator assesses spring snow conditions to decide whether to terminate hibernation or reenter torpor","docAbstract":"Many animals follow annual cycles wherein physiology and behavior change seasonally. Hibernating mammals undergo one of the most drastic seasonal alterations of physiology and behavior, the timing of which can have significant fitness consequences. The environmental cues regulating these profound phenotypic changes will heavily influence whether hibernators acclimate and ultimately adapt to climate change. Hence, identifying the cues and proximate mechanisms responsible for hibernation termination timing is critical. Northern Idaho ground squirrels (Urocitellus brunneus)—a rare, endemic species threatened with extinction—exhibit substantial variation in hibernation termination phenology, but it is unclear what causes this variation. We attached geolocators to free-ranging squirrels to test the hypothesis that squirrels assess surface conditions in spring before deciding whether to terminate seasonal heterothermy or reenter torpor. Northern Idaho ground squirrels frequently reentered torpor following a brief initial emergence from hibernacula and were more likely to do so earlier in spring or when challenged by residual snowpack. Female squirrels reentered torpor when confronted with relatively shallow snowpack upon emergence, whereas male squirrels reentered torpor in response to deeper spring snowpack. This novel behavior was previously assumed to be physiologically constrained in male ground squirrels by testosterone production required for spermatogenesis and activated by the circannual clock. Assessing surface conditions to decide when to terminate hibernation may help buffer these threatened squirrels against climate change. Documenting the extent to which other hibernators can facultatively alter emergence timing by reentering torpor after emergence will help identify which species are most likely to persist under climate change.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/729775","usgsCitation":"Allison, A.Z., Conway, C.J., Morris, A.E., Goldberg, A., Lohr, K., Richards, R., and Almack, J., 2024, Hit snooze: An imperiled hibernator assesses spring snow conditions to decide whether to terminate hibernation or reenter torpor: Ecological and Evolutionary Physiology, v. 97, no. 1, p. 53-63, https://doi.org/10.1086/729775.","productDescription":"11 p.","startPage":"53","endPage":"63","ipdsId":"IP-155349","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allison, Austin Z.T.","contributorId":339231,"corporation":false,"usgs":false,"family":"Allison","given":"Austin","email":"","middleInitial":"Z.T.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Alice E","contributorId":339157,"corporation":false,"usgs":false,"family":"Morris","given":"Alice","email":"","middleInitial":"E","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Amanda R.","contributorId":265814,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":54806,"text":"iu","active":true,"usgs":false}],"preferred":false,"id":903881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lohr, Kristin","contributorId":127012,"corporation":false,"usgs":false,"family":"Lohr","given":"Kristin","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":903883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richards, Russell","contributorId":339244,"corporation":false,"usgs":false,"family":"Richards","given":"Russell","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":903884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Almack, Jon","contributorId":339247,"corporation":false,"usgs":false,"family":"Almack","given":"Jon","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":903885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250999,"text":"70250999 - 2024 - Watershed hydrology assessment for the Lower Colorado River Basin. Appendix D: RiverWare analyses","interactions":[],"lastModifiedDate":"2024-02-02T14:59:59.031674","indexId":"70250999","displayToPublicDate":"2024-01-01T08:50:09","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17147,"text":"Interagency Flood Risk Management Report","active":true,"publicationSubtype":{"id":1}},"title":"Watershed hydrology assessment for the Lower Colorado River Basin. Appendix D: RiverWare analyses","docAbstract":"RiverWare is a river system modeling tool developed by CADSWES (Center of Advanced Decision Support for Water and Environmental Systems) that allows the user to simulate complex reservoir operations and perform period-of-record analyses for different scenarios. For the InFRM hydrology studies, RiverWare is used to generate a homogeneous regulated POR by simulating the basin as if the reservoirs and their current rule sets had been present in the basin for the entire time period. Statistical analyses can then be performed on the extended records at the gages. This report summarizes the RiverWare portion of the hydrologic analysis being completed for the InFRM Hydrology study of the Colorado River Basin.
The RiverWare model described in this chapter presents development of the Colorado River Basin hydrology, which mimics current operational conditions. The use of the RiverWare program allows for data extension to periods prior to dam construction. The utilization of longer gage record improves discharge frequency results and increases the confidence of the analysis being performed. The modeling evaluation criteria are: (1) evaluate output based on validating policies and functions, and (2) prioritize operation based on surcharge and flood control. A detailed explanation of the Colorado River Basin POR hydrology will be in a later section.
Calibration results will also be shown that illustrate the overall model performance for the POR. The time window simulation run is for January 01, 1930 – September 30, 2019. This time window captures all big events occurred over the Colorado River basin. Each simulated water year was inspected individually to better validate the results.
Historical pool elevations along with observed inflows and outflows were compared against the model simulated results.
","language":"English","publisher":"Interagency Flood Risk Management","collaboration":"USACE Fort Worth District, FEMA Region 6, NWS WGRFC","usgsCitation":"Wallace, D., and Watson, K.M., 2024, Watershed hydrology assessment for the Lower Colorado River Basin. Appendix D: RiverWare analyses: Interagency Flood Risk Management Report, 166 p.","productDescription":"166 p.","ipdsId":"IP-127610","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":424561,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://webapps.usgs.gov/infrm/"},{"id":425286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.8,\n 28.65\n ],\n [\n -95.8,\n 32\n ],\n [\n -101,\n 32\n ],\n [\n -101,\n 28.65\n ],\n [\n -95.8,\n 28.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, David 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":220786,"corporation":false,"usgs":true,"family":"Wallace","given":"David","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892730,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259275,"text":"70259275 - 2024 - Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis","interactions":[],"lastModifiedDate":"2024-10-03T13:31:43.005985","indexId":"70259275","displayToPublicDate":"2024-01-01T08:28:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18728,"text":"Aquatic Ecosystem Health and Management","active":true,"publicationSubtype":{"id":10}},"title":"Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis","docAbstract":"As with other large lake ecosystems worldwide, Lake Erie can be considered a moving target for management, owing to physicochemical and biological changes brought on by anthropogenic change, both planned (e.g. nutrient and fisheries management) and unplanned (e.g. climate change, invasive species, modified land-use activities). These changes have challenged efforts to conserve biodiversity, sustain exploitable resources, and maintain the integrity of services valued by society both within the Lake Erie basin and (Fraker et al., 2022; Fussell et al., 2016; Sinclair et al., 2021; Sinclair et al., 2023) and outside of it (Allan et al., 2013; Jenny et al., 2020; Sterner et al., 2017). Some of these changes and their ramifications for management were documented in the first of four AEHM special issues devoted to the Lake Erie ecosystem (the fourth issue of 2023, volume 26, issue 4; see overview by Ludsin et al., 2023). That special issue focused explicitly on nutrient inputs and availability in Lake Erie and the lower food web, including planktonic and benthic microbial (including cyanobacteria), algal, and invasive dreissenid mussel communities. Similar to the previous Lake Erie special issue, this second one has focused on documenting the state of the lake, providing ecological understanding that could potentially benefit management. While some overlap in topics exists between issues, the studies conducted herein were completely independent of those previous investigations and offer unique insights. Specifically, the contributions to this current issue center on: 1) dynamics of water chemistry in Lake Erie’s central basin (i.e. bottom hypoxia; Ackerman et al., 2024) and western basin (i.e. mercury; Starr et al., 2024); 2) changes in primary producer biomass (Lesht et al., 2024), cyanotoxins (i.e. microcystin; Zastepa et al., 2024), and water quality (e.g. water clarity and dissolved nutrients; Howell et al., 2024); and 3) larval fish foraging (i.e. Lake Whitefish; Coregonus clupeaformis; Amidon et al., 2024) and community structure and phenology (DeBruyne et al., 2024). Below we summarize the major findings of these papers and offer a synthetic perspective on the value of this research for understanding the state of Lake Erie and enhancing management.
","language":"English","publisher":"Michigan State University Press","doi":"10.14321/aehm.027.01.116","usgsCitation":"Ludsin, S., Munawar, M., DeBruyne, R.L., Howell, E.T., Tyson, J., and Watkins, J.M., 2024, Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis: Aquatic Ecosystem Health and Management, v. 27, no. 1, p. 116-124, https://doi.org/10.14321/aehm.027.01.116.","productDescription":"9 p.","startPage":"116","endPage":"124","ipdsId":"IP-163615","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.90437674926393,\n 42.88573072124271\n ],\n [\n -79.52141499356523,\n 42.87769210959476\n ],\n [\n -80.22678399206747,\n 42.79281581499302\n ],\n [\n -80.51880625151767,\n 42.57814946253396\n ],\n [\n -81.02026663661093,\n 42.67543230196293\n ],\n [\n -81.30128454543694,\n 42.67543535756306\n ],\n [\n -81.53822853578485,\n 42.56596464399709\n ],\n [\n -81.9019334399238,\n 42.33014170165541\n ],\n [\n -81.95153424579222,\n 42.26492779780335\n ],\n [\n -82.12236039987853,\n 42.236375180224144\n ],\n [\n -82.45298532777961,\n 42.08524033767702\n ],\n [\n -82.5191058069868,\n 41.92964634487325\n ],\n [\n -82.61828632462084,\n 42.04024072452731\n ],\n [\n -82.91034362126736,\n 41.987015817617134\n ],\n [\n -83.11972864041921,\n 42.077062926530004\n ],\n [\n -83.10317152070901,\n 42.24453450962994\n ],\n [\n -83.29610139408294,\n 41.9419412108324\n ],\n [\n -83.3622121286252,\n 41.92964573816295\n ],\n [\n -83.51644448225035,\n 41.69555451568095\n ],\n [\n -82.9488535420495,\n 41.41103910261083\n ],\n [\n -82.71193183972241,\n 41.41929329585025\n ],\n [\n -82.47491670465367,\n 41.35733064230888\n ],\n [\n -81.99008606791249,\n 41.477110666960954\n ],\n [\n -81.70899983775189,\n 41.46067864477564\n ],\n [\n -81.25720217469238,\n 41.736707291689584\n ],\n [\n -80.6842102922714,\n 41.88460348122109\n ],\n [\n -79.96258495960994,\n 42.16700280222196\n ],\n [\n -79.42295622097835,\n 42.38302164176207\n ],\n [\n -79.37861904307078,\n 42.4440510296389\n ],\n [\n -79.15795348814065,\n 42.52534601120243\n ],\n [\n -79.00930804606551,\n 42.69563463834368\n ],\n [\n -78.83853732874603,\n 42.76038448982763\n ],\n [\n -78.84931646792415,\n 42.86956831700121\n ],\n [\n -78.90437674926393,\n 42.88573072124271\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ludsin, Stuart A.","contributorId":270532,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":914751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munawar, Mohiuddin","contributorId":344801,"corporation":false,"usgs":false,"family":"Munawar","given":"Mohiuddin","email":"","affiliations":[{"id":13015,"text":"Department of Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":914752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":914753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howell, E. Todd","contributorId":344802,"corporation":false,"usgs":false,"family":"Howell","given":"E.","email":"","middleInitial":"Todd","affiliations":[{"id":82411,"text":"Ontario Ministry of the Environment, Conservation, and Parks","active":true,"usgs":false}],"preferred":false,"id":914754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyson, Jeffrey","contributorId":344803,"corporation":false,"usgs":false,"family":"Tyson","given":"Jeffrey","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":914755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":914756,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250996,"text":"70250996 - 2024 - Watershed hydrology assessment for the Lower Colorado River Basin. Appendix A: Statistical hydrology","interactions":[],"lastModifiedDate":"2024-02-02T14:47:45.280372","indexId":"70250996","displayToPublicDate":"2024-01-01T08:26:24","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17147,"text":"Interagency Flood Risk Management Report","active":true,"publicationSubtype":{"id":1}},"title":"Watershed hydrology assessment for the Lower Colorado River Basin. Appendix A: Statistical hydrology","docAbstract":"Statistical analysis of the observational record from U.S. Geological Survey (USGS) streamgages and period of historical flow observations prior to the gage installation provides an informative means of estimating flood flow frequency. The U.S. Geological Survey contributed to the InFRM team’s efforts by performing the statistical analysis of the gaged record and authored this Appendix to the Lower Watershed Hydrology Assessment. Flood flow frequency is defined by values or quantiles of streamflow for selected annual exceedance probabilities (AEPs) (England and others, 2019). The annual peak streamflow data collected as part of the systematic operation of a streamgage provides the foundation for a detailed analysis of peak streamflow, but additional historical information pertaining to peak streamflows that predates the installation of a streamgage also can be used. An annual peak streamflow is defined as the maximum instantaneous streamflow for a streamgage for a given water year, and annual peak streamflow data for USGS streamgages can be acquired through the USGS National Water Information System (NWIS) database (USGS, 2022). The statistical analyses are based on water-year increments. A water year is the 12-month period from October 1 of a given year through September 30 of the following year designated by the calendar year in which it ends.
For the statistical hydrology portion of a multifaceted analysis, InFRM team members from the USGS analyzed annual peak streamflow records for the 45 USGS streamgages (gages) and 21 Lower Colorado River Authority (LCRA) streamgages (gages) in the lower Colorado River Basin listed in Table A.1 and Table A.8. The locations of USGS gages are also shown on Figure A.1, Figure A.2, and Figure A.3, and the locations of LCRA gages are shown in Section 1.4. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
","language":"English","publisher":"Interagency Flood Risk Management","collaboration":"USACE-Fort Worth District, FEMA Region 6, NWS West Gulf River Forecast Center","usgsCitation":"Wallace, D., and Watson, K.M., 2024, Watershed hydrology assessment for the Lower Colorado River Basin. Appendix A: Statistical hydrology: Interagency Flood Risk Management Report, 246 p.","productDescription":"246 p.","ipdsId":"IP-133413","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":424560,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://webapps.usgs.gov/infrm/"},{"id":425285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.8,\n 28.65\n ],\n [\n -95.8,\n 32\n ],\n [\n -101,\n 32\n ],\n [\n -101,\n 28.65\n ],\n [\n -95.8,\n 28.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, David 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":220786,"corporation":false,"usgs":true,"family":"Wallace","given":"David","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892728,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255310,"text":"70255310 - 2024 - Managed wetlands for climate action: Potential greenhouse gas and subsidence mitigation in the Sacramento-San Joaquin Delta","interactions":[],"lastModifiedDate":"2024-06-17T13:32:35.178591","indexId":"70255310","displayToPublicDate":"2024-01-01T08:22:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Managed wetlands for climate action: Potential greenhouse gas and subsidence mitigation in the Sacramento-San Joaquin Delta","docAbstract":"