Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.
The great 1957 Aleutian Islands earthquake ruptured ∼1200 km of the plate boundary along the Aleutian subduction zone and produced a destructive tsunami across Hawaiʻi. Early seismic and tsunami analyses indicated that large megathrust fault slip was concentrated in the western Aleutian Islands, but tsunami waves generated by slip in the west cannot explain the large observed runup in Hawaiʻi far to the southeast. Recently mapped 1957 geologic deposits on eastern Aleutian Islands suggest occurrence of very large nearby slip. Jointly modeling tsunami runup along the eastern Aleutian and Hawaiian Islands together with tide gauge recordings across the Pacific resolves 12-26 m shallow slip along 600 km of the eastern Aleutian Islands in addition to modest, deeper western slip inferred from seismic records. The eastern near-trench slip results in an MW 8.3-8.6 tsunami earthquake component of the MW 8.6-8.8 rupture, comparable in size to the adjacent 1946 Aleutian tsunami earthquake to the east. The reexamination of the 1957 rupture confirms the tsunami hazards posed by the eastern Aleutian subduction zone to Hawaiʻi and lays the groundwork for investigation of large prehistoric earthquakes through modeling tsunami runup inferred from stratigraphic observations to constrain their rupture processes.
Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230229","usgsCitation":"Fichtner, A., Kennett, B., Tsai, V.C., Thurber, C., Rodgers, A., Tape, C., Rawlinson, N., Borcherdt, R.D., Lebedev, S., Priestley, K., Morency, C., Bozdag, E., Tromp, J., Ritsema, J., Romanowicz, B., Liu, Q., Golos, E., and Lin, F., 2024, Seismic tomography 2023: Bulletin of the Seismological Society of America, v. 114, no. 3, p. 1185-1213, https://doi.org/10.1785/0120230229.","productDescription":"29 p.","startPage":"1185","endPage":"1213","ipdsId":"IP-157788","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499626,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/2426716","text":"External 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Jeroen","contributorId":365874,"corporation":false,"usgs":false,"family":"Ritsema","given":"Jeroen","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":954939,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Romanowicz, Barbara","contributorId":365875,"corporation":false,"usgs":false,"family":"Romanowicz","given":"Barbara","affiliations":[{"id":87237,"text":"University of California- Berkeley","active":true,"usgs":false}],"preferred":false,"id":954940,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Liu, Qinya","contributorId":365876,"corporation":false,"usgs":false,"family":"Liu","given":"Qinya","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":954941,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Golos, Eva","contributorId":365877,"corporation":false,"usgs":false,"family":"Golos","given":"Eva","affiliations":[{"id":82473,"text":"University of Wisconsin- Madison","active":true,"usgs":false}],"preferred":false,"id":954942,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lin, Fan-Chi","contributorId":175478,"corporation":false,"usgs":false,"family":"Lin","given":"Fan-Chi","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":955031,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70255660,"text":"70255660 - 2024 - Combining terrestrial lidar with single line transects to investigate geomorphic change: A case study on the Upper Verde River, Arizona","interactions":[],"lastModifiedDate":"2024-06-27T12:27:55.213471","indexId":"70255660","displayToPublicDate":"2024-05-03T07:24:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Combining terrestrial lidar with single line transects to investigate geomorphic change: A case study on the Upper Verde River, Arizona","docAbstract":"The Upper Verde River in northern Arizona, USA is a vital resource for the wildlife and humans that rely on its waters. We characterize the riparian corridor topography using terrestrial laser scanner (TLS) data from 2021 to 2022. We also quantify geomorphic changes associated with human and climate-driven alterations in river flow and vegetation changes by combining the contemporary lidar surveys with legacy measurements from single line geomorphology transects measured by the United States Forest Service (USFS) in 2009. Seventeen plots along the Upper Verde River were surveyed with the TLS and the data were coregistered within individual plots with a Root Mean Square Error of <0.03 m among scan positions. Digital Elevation Models (DEM) were derived for each plot from the TLS data at 10 cm resolution and compared to the 2009 USFS cross-section data to quantify elevation changes. In areas with statistically significant change, we detected maximum changes in elevation due to erosion and deposition of −0.37 m and + 0.97 m, respectively. Topographic changes over the 13-year period were predominately aggradation and associated with sediment deposition, which we hypothesize might have resulted from altered river flow and vegetation encroachment. This study also demonstrates a quantitative and statistical methodology to fuse traditional single line cross-section data with contemporary lidar data to quantify geomorphic change. The novel approach demonstrated here is broadly applicable to natural resource managers for integrating and contextualizing legacy topographic data for understanding past, present, and future landscape and habitat changes.
Wetlands are integral to the global carbon cycle, serving as both a source and a sink for organic carbon. Their potential for carbon storage will likely change in the coming decades in response to higher temperatures and variable precipitation patterns. We characterized the dissolved organic carbon (DOC) and dissolved organic matter (DOM) composition from 12 different wetland sites across the USA spanning gradients in climate, landcover, sampling depth, and hydroperiod for comparison to DOM in other inland waters. Using absorption spectroscopy, parallel factor analysis modeling, and ultra-high resolution mass spectroscopy, we identified differences in DOM sourcing and processing by geographic site. Wetland DOM composition was driven primarily by differences in landcover where forested sites contained greater aromatic and oxygenated DOM content compared to grassland/herbaceous sites which were more aliphatic and enriched in N and S molecular formulae. Furthermore, surface and porewater DOM was also influenced by properties such as soil type, organic matter content, and precipitation. Surface water DOM was relatively enriched in oxygenated higher molecular weight formulae representing HUPHigh O/C compounds than porewaters, whose DOM composition suggests abiotic sulfurization from dissolved inorganic sulfide. Finally, we identified a group of persistent molecular formulae (3,489) present across all sites and sampling depths (i.e., the signature of wetland DOM) that are likely important for riverine-to-coastal DOM transport. As anthropogenic disturbances continue to impact temperate wetlands, this study highlights drivers of DOM composition fundamental for understanding how wetland organic carbon will change, and thus its role in biogeochemical cycling.
The US Geological Survey National Seismic Hazard Models (NSHMs) are used to calculate earthquake ground-shaking intensities for design and rehabilitation of structures in the United States. The most recent 2014 and 2018 versions of the NSHM for the conterminous United States included major updates to ground-motion models (GMMs) for active and stable crustal tectonic settings; however, the subduction zone GMMs were largely unchanged. With the recent development of the next generation attenuation-subduction (NGA-Sub) GMMs, and recent progress in the utilization of “M9” Cascadia earthquake simulations, we now have access to improved models of ground shaking in the US subduction zones and the Seattle basin. The new NGA-Sub GMMs support multi-period response spectra calculations. They provide global models and regional terms specific to Cascadia and terms that account for deep-basin effects. This article focuses on the updates to subduction GMMs for implementation in the 2023 NSHM and compares them to the GMMs of previous NSHMs. Individual subduction GMMs, their weighted averages, and their impact on the estimated mean hazard relative to the 2018 NSHM are discussed. The updated logic trees include three of the new NGA-Sub GMMs and retain two older models to represent epistemic uncertainty in both the median and standard deviation of ground-shaking intensities at all periods of interest. Epistemic uncertainty is further represented by a three-point logic tree for the NGA-Sub median models. Finally, in the Seattle region, basin amplification factors are adjusted at long periods based on the state-of-the-art M9 Cascadia earthquake simulations. The new models increase the estimated mean hazard values at short periods and short source-to-site distances for interface earthquakes, but decrease them otherwise, relative to the 2018 NSHM. On softer soils, the new models cause decreases to the estimated mean hazard for long periods in the Puget Lowlands basin but increases within the deep Seattle portion of this basin for short periods relative to the 2018 NSHM.
","language":"English","publisher":"SAGE Publications","doi":"10.1177/87552930241243069","usgsCitation":"Rezaeian, S., Powers, P.M., Altekruse, J.M., Ahdi, S.K., Petersen, M.D., Shumway, A., Frankel, A.D., Wirth, E.A., Smith, J.A., Moschetti, M.P., Withers, K., and Herrick, J.A., 2024, The 2023 U.S. National Seismic Hazard Model: Subduction ground motion models: Earthquake Spectra, v. 41, no. 3, p. 1739-1786, https://doi.org/10.1177/87552930241243069.","productDescription":"48 p.","startPage":"1739","endPage":"1786","ipdsId":"IP-155768","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":498237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241243069","text":"Publisher Index Page"},{"id":493844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Altekruse, Jason M. 0000-0002-8798-9514","orcid":"https://orcid.org/0000-0002-8798-9514","contributorId":291308,"corporation":false,"usgs":true,"family":"Altekruse","given":"Jason","email":"","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahdi, Sean Kamran 0000-0003-0274-5180","orcid":"https://orcid.org/0000-0003-0274-5180","contributorId":265143,"corporation":false,"usgs":true,"family":"Ahdi","given":"Sean","email":"","middleInitial":"Kamran","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shumway, Allison M. 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945374,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":945375,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":945376,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, James Andrew 0000-0002-5565-9254 jimsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-9254","contributorId":332933,"corporation":false,"usgs":true,"family":"Smith","given":"James","email":"jimsmith@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":945377,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945378,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Withers, Kyle B. 0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945379,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Herrick, Julie A. 0000-0003-0682-760X","orcid":"https://orcid.org/0000-0003-0682-760X","contributorId":243649,"corporation":false,"usgs":true,"family":"Herrick","given":"Julie","middleInitial":"A.","affiliations":[],"preferred":true,"id":945380,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70254788,"text":"70254788 - 2024 - Prototyping structured decision making for water resource management in the San Francisco Bay-Delta","interactions":[],"lastModifiedDate":"2024-06-07T12:10:31.334355","indexId":"70254788","displayToPublicDate":"2024-05-02T07:06:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1563,"text":"Environmental Science and Policy","active":true,"publicationSubtype":{"id":10}},"title":"Prototyping structured decision making for water resource management in the San Francisco Bay-Delta","docAbstract":"A structured decision making (SDM) approach can help evaluate tradeoffs between conservation and human-benefit objectives by fostering communication and knowledge transfer among stakeholders, decision makers, and the public. However, the process is iterative and completing the full process may take years. It can be difficult to initiate an SDM effort when problems seem insurmountable. Occasionally, SDM may not even be the best or correct approach for addressing the conservation problem at hand. We describe the implementation of an SDM process to help inform difficult decisions related to competing objectives. We convened a diverse stakeholder group from the largest estuary in the western United States; the San Francisco Bay and Sacramento-San Joaquin Delta (Bay-Delta). The stakeholder group consisted of representatives from local, state, and federal agencies, non-profit organizations, and recreational fishers. The stakeholder group agreed on a problem statement and identified four priority objectives related to Chinook salmon, delta smelt, water availability and reliability, and agricultural water use. Furthermore, they proposed 14 candidate management actions to achieve their objectives. The group then used existing quantitative models and data to evaluate trade-offs in proposed management actions to identify areas of agreement of proposed candidate actions. The clear communication of the problem statement and objectives among the stakeholder group, along with evaluation of tradeoffs and uncertainty via decision-support models suggest that a full SDM approach may work in the Bay-Delta. We further communicate lessons learned during our implementation of SDM to help guide future SDM efforts in the region and elsewhere.
We develop basin-depth-scaling models (i.e. “basin terms”) from the long-period (T≥2s) simulated ground motions of the Southern California Earthquake Center (SCEC) CyberShake project for use in seismic hazard analyses at sites within the sedimentary basins of southern California. Basin terms use the Next Generation Attenuation (NGA)-West-2 ground-motion models (GMMs) as reference models and use their functional forms with slight modifications. We investigate the use of two approaches to incorporate the time-averaged shear-wave velocity in the upper 30 m (VS30) in these calculations and find that the use of site-specific and uniform VS30 has minor effects on the resulting basin terms for this data set. By centering the simulated ground motions on the basin terms, we separate the information from the simulations about absolute ground-motion level from information relating to the relative amplifications, such as the differences between shallow- and deep-basin sites. Recent observations from sedimentary basins of southern California indicate that additional amplification effect may persist at relatively shallow basin depths (i.e. the GMM basin terms should have positive values when differential depths, δZ1, are near zero), and we present models for “centered” and “adjusted” basin-depth scaling models that reflect this potential. The simulation-modified GMMs are appropriate for crustal sources and for deep-basin sites (δZ1>0) within basins of the Greater Los Angeles region, for the magnitudes and distances defined by each of the reference NGA-West-2 GMMs.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930241232372","usgsCitation":"Moschetti, M.P., Thompson, E.M., and Withers, K., 2024, Basin effects from 3D simulated ground motions in the Greater Los Angeles region for use in seismic-hazard analyses: Earthquake Spectra, v. 40, no. 2, p. 1042-1065, https://doi.org/10.1177/87552930241232372.","productDescription":"24 p.","startPage":"1042","endPage":"1065","ipdsId":"IP-158956","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":488992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241232372","text":"Publisher Index Page"},{"id":432198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Greater Los Angeles Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.94149918428957,\n 34.32364441847551\n ],\n [\n -117.43918255359767,\n 33.188428269892825\n ],\n [\n -116.44515493576301,\n 34.234161392994224\n ],\n [\n -119.42762588538866,\n 35.4271042958259\n ],\n [\n -119.94149918428957,\n 34.32364441847551\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":909052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":909053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Withers, Kyle B. 0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":909054,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257455,"text":"70257455 - 2024 - A video monitoring and computational system for estimating migratory juvenile fish abundance in river systems","interactions":[],"lastModifiedDate":"2024-09-06T17:36:38.170712","indexId":"70257455","displayToPublicDate":"2024-05-01T10:26:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7183,"text":"Limnology and Oceanography Methods","active":true,"publicationSubtype":{"id":10}},"title":"A video monitoring and computational system for estimating migratory juvenile fish abundance in river systems","docAbstract":"Diadromous fishes migrate between marine and fresh waters for reproduction. For anadromous species, which spawn in freshwater, improved access to freshwater spawning and nursery habitats and ability of juveniles to emigrate to the ocean may support population recovery. Despite the potentially enormous influence of early life stage survival on adult population size, managers and scientists have limited capacity to assess numbers of juvenile anadromous fishes leaving freshwater ecosystems. Such data are critical for evaluating reproductive success and habitat suitability and have been identified as a top priority in anadromous fish research and management. We developed a state-of-the-art underwater video and computational system to collect videos to estimate abundances and migration timing for juvenile river herring (Alosa pseudoharengus; Alosa aestivalis). We collected continuous video in the Monument River (Bourne, Massachusetts, USA) from June to November 2017. We trained three types of neural network models to detect and count fish in video frames and evaluated model performance by comparing human counts to model outputs. Our top model assessed presence and absence (F1 = 87%) and counted fish (counting error 9.4%) with an accuracy comparable to human counters (F1 = 88%). Our system's capability to collect accurate counts of emigrating juveniles will provide critical information that could be related to the numbers of spawning adults, system-specific productivity, and spawning and nursery habitat suitability. Both the video collection system and computational model may be transferrable to other sites and for other species where tracking juvenile emigration may inform management efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10607","usgsCitation":"Marjadi, M., Batchelder, S., Govostes, R., Roy, A.H., Sheppard, J.J., Slocombe, M., and Llopiz, J.K., 2024, A video monitoring and computational system for estimating migratory juvenile fish abundance in river systems: Limnology and Oceanography Methods, v. 22, no. 5, p. 295-310, https://doi.org/10.1002/lom3.10607.","productDescription":"16 p.","startPage":"295","endPage":"310","ipdsId":"IP-153977","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":499869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10607","text":"Publisher Index Page"},{"id":433576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Bourne","otherGeospatial":"Monument River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.64760395310527,\n 41.776303905697034\n ],\n [\n -70.64760395310527,\n 41.73753363601219\n ],\n [\n -70.46626157712495,\n 41.73753363601219\n ],\n [\n -70.46626157712495,\n 41.776303905697034\n ],\n [\n -70.64760395310527,\n 41.776303905697034\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Marjadi, Meghna N.","contributorId":342885,"corporation":false,"usgs":false,"family":"Marjadi","given":"Meghna N.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batchelder, Sidney","contributorId":342893,"corporation":false,"usgs":false,"family":"Batchelder","given":"Sidney","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":910469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Govostes, Ryan","contributorId":343989,"corporation":false,"usgs":false,"family":"Govostes","given":"Ryan","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":912569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sheppard, John J.","contributorId":342890,"corporation":false,"usgs":false,"family":"Sheppard","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":39892,"text":"Massachusetts Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":910468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slocombe, Meghan-Grace","contributorId":342888,"corporation":false,"usgs":false,"family":"Slocombe","given":"Meghan-Grace","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910467,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Llopiz, Joel K.","contributorId":317780,"corporation":false,"usgs":false,"family":"Llopiz","given":"Joel","email":"","middleInitial":"K.","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":912570,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70253577,"text":"70253577 - 2024 - Abundance of Long-billed Curlews on military lands in the Columbia Basin","interactions":[],"lastModifiedDate":"2024-05-02T13:49:39.165904","indexId":"70253577","displayToPublicDate":"2024-05-01T08:44:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Abundance of Long-billed Curlews on military lands in the Columbia Basin","docAbstract":"Long-billed Curlews (Numenius americanus) are declining throughout North America, and the loss of grassland breeding habitat is one of the primary threats to the species. Intermountain West, in particular, has been identified as the most important region in North America for breeding curlews. Nevertheless, the density and abundance of Long-billed Curlews in this region is not well understood. Lands managed for military training can provide habitat for wildlife species of conservation concern, and increasingly these lands are becoming relevant to sustaining biodiversity. We conducted point count surveys of Long-billed Curlews on Department of Defense lands in the Columbia Basin near Boardman, Oregon, USA during two consecutive breeding seasons. We used multinomial-Poisson mixture models to estimate detection probability and density of curlews and to investigate environmental correlates of those metrics. Mean detection probability at a distance of 400 m was 0.45 and 0.61 in 2015 and 2016, respectively. In 2015, the clarity of skies increased detection probability, but in 2016, none of the variables we measured influenced detection probability. Mean predicted density was 3.3 (95% confidence interval: 2.4–4.7) and 1.8 (1.2–2.7) curlews/km² in 2015 and 2016, respectively. In both years, curlew density was higher in lower-elevation or topographically smoother areas. Estimated abundance of curlews in the study area was 639 (456–912) and 350 (237–520) birds in 2015 and 2016, respectively. The number of curlews appeared to fluctuate across the two years of our study, a demographic trend that may have been influenced by a wildfire in our study area in June 2015. The results of our study indicate that federal grasslands, including areas where military operations are conducted, can provide conservation benefit to breeding Long-billed Curlews.
","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ACE-02616-190114","usgsCitation":"Poessel, S.A., Elliott-Smith, E., Murphy, S.M., Haig, S.M., Duerr, A.E., and Katzner, T., 2024, Abundance of Long-billed Curlews on military lands in the Columbia Basin: Avian Conservation and Ecology, v. 19, no. 1, 14, 10 p., https://doi.org/10.5751/ACE-02616-190114.","productDescription":"14, 10 p.","ipdsId":"IP-154373","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":439686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.5751/ace-02616-190114","text":"Publisher Index Page"},{"id":428322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Naval Weapons Systems Training Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.79030685893883,\n 45.806959816149686\n ],\n [\n -119.79030685893883,\n 45.799712936914204\n ],\n [\n -119.74959152473441,\n 45.798807010728154\n ],\n [\n -119.74872524102787,\n 45.63338027358941\n ],\n [\n -119.62224781988232,\n 45.63156300534766\n ],\n [\n -119.6226809617356,\n 45.80635594555136\n ],\n [\n -119.79030685893883,\n 45.806959816149686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poessel, Sharon A. 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":168465,"corporation":false,"usgs":true,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":899966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott-Smith, Elise 0000-0003-1399-0093 eelliott-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1399-0093","contributorId":222848,"corporation":false,"usgs":true,"family":"Elliott-Smith","given":"Elise","email":"eelliott-smith@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":899967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sean M.","contributorId":140195,"corporation":false,"usgs":false,"family":"Murphy","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":899968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M 0000-0002-6616-7589","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":299819,"corporation":false,"usgs":false,"family":"Haig","given":"Susan","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":899969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":899970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":899971,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257186,"text":"70257186 - 2024 - Revisiting geophysical interpretations of the Midcontinent Rift below Lake Superior— Insights from GLIMPCE seismic-reflection line C","interactions":[],"lastModifiedDate":"2024-08-13T13:40:42.756398","indexId":"70257186","displayToPublicDate":"2024-05-01T08:30:10","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Revisiting geophysical interpretations of the Midcontinent Rift below Lake Superior— Insights from GLIMPCE seismic-reflection line C","docAbstract":"The 1.1 Ga Midcontinent Rift System (MRS) has been investigated in the Lake Superior region for more than a century. The most influential geophysical data for modern paradigms has come from seismic-reflection profiles collected by the Great Lakes International Multidisciplinary Program on Crustal Evolution (GLIMPCE) in the late 1980s. We are revisiting seismic-reflection GLIMPCE line C by constructing a detailed velocity model for conversion of the seismic data measured in two-way travel time to a section plotted versus depth. Preliminary results from the velocity modeling, depth conversion, and ties to onshore geology have led to a significantly different view of Line C as primarily a sag basin rather than a half-graben. Narrow intervals of high-velocity material that emanate upwards along both sides of the sag basin are interpreted as mafic intrusions connected to the mantle. This new interpretation suggests that basin subsidence was the dominant process in the development of rift stage troughs rather than major half-graben structures.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology: proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"70th Annual Meeting, Institute on Lake Superior Geology","conferenceDate":"May 15-18, 2024","conferenceLocation":"Houghton, MI","language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Grauch, V.J., Heller, S.J., Woodruff, L.G., and Stewart, E.K., 2024, Revisiting geophysical interpretations of the Midcontinent Rift below Lake Superior— Insights from GLIMPCE seismic-reflection line C, in Institute on Lake Superior Geology: proceedings, Houghton, MI, May 15-18, 2024, p. 33-34.","productDescription":"2 p.","startPage":"33","endPage":"34","ipdsId":"IP-164264","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":432595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":432585,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/items/show/10352","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.47304855185763,\n 47.73518373503143\n ],\n [\n -90.04285901104943,\n 46.65693682540714\n ],\n [\n -89.11556155641922,\n 46.97753491798878\n ],\n [\n -89.81820447307238,\n 47.879649078872575\n ],\n [\n -90.47304855185763,\n 47.73518373503143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":909677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heller, Samuel J. 0000-0002-6579-5620 sheller@usgs.gov","orcid":"https://orcid.org/0000-0002-6579-5620","contributorId":201350,"corporation":false,"usgs":true,"family":"Heller","given":"Samuel","email":"sheller@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":909678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":909679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, Esther K.","contributorId":247878,"corporation":false,"usgs":false,"family":"Stewart","given":"Esther","email":"","middleInitial":"K.","affiliations":[{"id":39043,"text":"Wisconsin Geological and Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":909680,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263625,"text":"70263625 - 2024 - Why do seismic hazard models worldwide appear to overpredict historical intensity observations?","interactions":[],"lastModifiedDate":"2025-02-18T15:27:18.152919","indexId":"70263625","displayToPublicDate":"2024-05-01T08:19:49","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Why do seismic hazard models worldwide appear to overpredict historical intensity observations?","docAbstract":"Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models—which forecast shaking as peak ground acceleration or velocity—and observations—parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes.
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Leah Marschall 0000-0002-4478-1836","orcid":"https://orcid.org/0000-0002-4478-1836","contributorId":297144,"corporation":false,"usgs":true,"family":"Salditch","given":"Leah","email":"","middleInitial":"Marschall","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":927603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927604,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257438,"text":"70257438 - 2024 - Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology","interactions":[],"lastModifiedDate":"2024-08-16T12:24:55.911749","indexId":"70257438","displayToPublicDate":"2024-05-01T07:23:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology","docAbstract":"The Atlantic and Gulf Coastal Plains (CPs) are characterized by widespread accumulations of low-velocity sediments and sedimentary rock that overlay high-velocity bedrock. Geology and sediment thickness greatly influence seismic wave propagation, but current regional ground motion amplification and seismic hazard models include limited characterization of these site conditions. In this study, a new regional seismic velocity model for the CPs is created by integrating shear wave velocity (VS) measurements, surface geology, and a sediment thickness model recently developed for the CPs. A reference rock VS of 3000 m/s has been assumed at the bottom of the sedimentary columns, which corresponds to the base of Cretaceous and Mesozoic sediments underlying the Atlantic CP and the Gulf CP, respectively. Measured VS profiles located throughout the CPs are sorted into five geologic groups of varying age, and median VS profiles are developed for each group by combining measured VS values within layer thicknesses defined by an assumed layering ratio. Statistical analyses are also conducted to test the appropriateness of the selected groups. A power law model with geology-informed coefficients is used to extend the median velocity models beyond the depths where measured data were available. The median VS profiles provide reasonable agreement with other generic models applicable for the region, but they also incorporate new information that enables more advanced characterizations of site response at regional scales and their effective incorporation into seismic hazard models and building codes. The proposed median velocity profiles can be assigned within a grid-based model of the CPs according to the spatial distribution of geologic units at the surface.
The Statewide (formerly Southern) California Earthquake Center (SCEC) conducts multidisciplinary earthquake system science research that aims to develop predictive models of earthquake processes, and to produce accurate seismic hazard information that can improve societal preparedness and resiliency to earthquake hazards. As part of this program, SCEC has developed the CyberShake platform, which calculates physics-based probabilistic seismic hazard analysis (PSHA) models for regions with high-quality seismic velocity and fault models. The CyberShake platform implements a sophisticated computational workflow that includes over 15 individual codes written by 6 developers. These codes are heterogeneous, ranging from short-running high-throughput serial CPU codes to large, long-running, parallel GPU codes. Additionally, CyberShake simulation campaigns are computationally extensive, typically producing tens of terabytes of meaningful scientific data and metadata over several months of around-the-clock execution on leadership-class supercomputers. To meet the needs of the CyberShake platform, we have developed an extreme-scale workflow stack, including the Pegasus Workflow Management System, HTCondor, Globus, and custom tools. We present this workflow software stack and identify how the CyberShake platform and supporting tools enable us to meet a variety of challenges that come with large-scale simulations, such as automated remote job submission, data management, and verification and validation. This platform enabled us to perform our most recent simulation campaign, CyberShake Study 22.12, from December 2022 to April 2023. During this time, our workflow tools executed approximately 32,000 jobs, and used up to 73% of the Summit system at Oak Ridge Leadership Computing Facility. Our workflow tools managed about 2.5 PB of total temporary and output data, and automatically staged 19 million output files totaling 74 TB back to archival storage on the University of Southern California's Center for Advanced Research Computing systems, including file-based relational data and large binary files to efficiently store millions of simulated seismograms. CyberShake extreme-scale workflows have generated simulation-based probabilistic seismic hazard models that are being used by seismological, engineering, and governmental communities.
Several rupture directivity models (DMs) have been developed in recent years to describe the near-source spatial variations in ground motion amplitudes related to propagation of rupture along the fault. We recently organized an effort towards incorporating these directivity effects into the USGS National Seismic Hazard Model (NSHM), by first evaluating the community's work and potential methods to implement directivity adjustments into probabilistic seismic hazard analysis (PSHA). Guided by this evaluation and comparison among the considered DMs, we selected an approach that can be readily implemented into the USGS hazard software, that provides an azimuthally varying adjustment to the median ground motion and its aleatory variability. This method allows assessment of the impact on hazard levels and provides a platform to test the DM amplification predictions using a generalized coordinate system, necessary for consistent calculation of source-to-site distance terms for complex ruptures. We give examples of the directivity-related impact on hazard, progressing from a simple, hypothetical rupture, to more complex fault systems, composed of multiple rupture segments and sources. The directivity adjustments were constrained to strike-slip faulting, where DMs have good agreement. We find that rupture directivity adjustments using a simple median and aleatory adjustment approach can impact hazard both from a site perspective and on a regional scale, increasing shaking off the end of the fault trace up to 30--40\\% and potentially reducing it for sites along strike. Statewide hazard maps of California show that the change in shaking along major faults can be a factor to consider for assessing long-period (>ls) near-source effects within the USGS NSHM going forward, reaching up to 10--20\\%. Finally, we suggest consideration of minimum parameter ranges and baseline requirements as future DMs are developed to minimize single approach adaptations, to enable more consistent application within both ground motion and hazard studies.
","language":"English","publisher":"Sage","doi":"10.1177/87552930241232708","usgsCitation":"Withers, K., Moschetti, M.P., Powers, P.M., Petersen, M.D., Graves, R., Aagaard, B.T., Baltay Sundstrom, A.S., Luco, N., Wirth, E.A., Rezaeian, S., and Thompson, E.M., 2024, Integration of rupture directivity models for the US National Seismic Hazard Model: Earthquake Spectra, v. 40, no. 2, p. 1066-1098, https://doi.org/10.1177/87552930241232708.","productDescription":"33 p.","startPage":"1066","endPage":"1098","ipdsId":"IP-153605","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":490134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241232708","text":"Publisher Index Page"},{"id":486170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":937576,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937577,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":937578,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70253244,"text":"tm7A3 - 2024 - Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities","interactions":[],"lastModifiedDate":"2024-12-03T19:57:00.75842","indexId":"tm7A3","displayToPublicDate":"2024-04-30T16:58:47","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-A3","displayTitle":"Accounting for the Fraction of Carcasses Outside the Searched Area in the Estimation of Bird and Bat Fatalities at Wind Energy Facilities","title":"Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities","docAbstract":"Accurate estimation of bird and bat mortality at wind energy facilities requires accounting for carcasses that lie outside the search plots because they lie beyond the search radius or in areas within the search radius that remain unsearched due to sub-optimal search conditions such as thick vegetation, rough or dangerous ground, water, or restricted access to the land. However, carcass density is not constant around a turbine and the fraction of carcasses within the unsearched area can vary greatly depending on where the area lies relative to the turbine. The density-weighted proportion approach takes into account the changing density of carcasses around turbines to estimate the fraction of carcasses lying in unsearched areas (dwp). It involves tallying the carcasses found in concentric rings centered at the turbine, fitting a curve to the carcass densities in the rings, and dividing the integral of the curve over the area searched by the integral over the total area. Accounting for unsearched area presents special difficulties such as extrapolation beyond the search radius, spatial prediction, and model selection, which are frequently ignored or under-appreciated, potentially resulting in substantial estimation errors.
A powerful new R software package (dwp) is available to perform the calculations, given the distances at which carcasses were found from turbines and a map of the searched area used to discern the fraction of the ground searched at each distance. If all ground within a given search radius has been searched, the map is simply the search radius. For more complicated search plots, other kinds of maps may be used: R polygons for plots that can be readily delineated into searched and not-searched areas (for example, searches restricted to access roads and turbine pads), GIS shape files for complicated search patterns (for example, non-uniform vegetation or ground texture resulting in spatially varying search conditions), or raster files for complicated search patterns coupled with carcass spatial distribution that depends on both distance and direction from turbines.
This study discusses estimation and interpretation of dwp in the context of several realistic examples; provides guidance for use of the dwp software for doing the analyses; and addresses questions of extrapolation, spatial prediction, and model selection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7A3","usgsCitation":"Dalthorp, D., Huso, M., Dalthorp, M., and Mintz, J., 2024, Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities: U.S. Geological Survey Techniques and Methods, book 7, chap. A3, 104 p., https://doi.org/10.3133/tm7A3.","productDescription":"vii, 104 p.","onlineOnly":"Y","ipdsId":"IP-135475","costCenters":[],"links":[{"id":428248,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.XML"},{"id":428246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.jpg"},{"id":428247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7A3"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th Street, Suite 400
Corvallis, Oregon 97330
Lotic fish species distributions are frequently predicted using remotely sensed habitat variables that characterize the adjacent landscape and serve as proxies for instream habitat. Recent advancements in statistical methodology, however, allow for leveraging fish assemblage data when predicting distributions. This is important because assemblage composition likely provides better information about instream habitat compared to landscape-derived metrics and therefore may improve predictions. To better understand the value of using multi-species fish data in species distribution modeling, we fit two conditional random fields (CRF) models to quantify the relative importance of fish assemblage co-occurrence, landscape-derived habitat variables, and interactions between these two predictor groups (i.e., effects of co-occurrence could be context-dependent) at over 1200 stream catchments in Pennsylvania, USA. We first compared predictive performance of CRF models against traditionally used single-species logistic regressions (generalized linear models; GLMs) and found that inclusion of fish assemblage data often improved predictive performance. The multi-species CRF models performed significantly better at predicting occurrence for 63% of species with an average percent increase in AUC of 25% compared to GLMs. Furthermore, the CRF identified species co-occurrences as more informative, and thus relatively more important, at predicting occurrence than the other effect types. The CRF also suggested that allowing these biotic effects to be context-dependent was important for predicting occurrence of many species. These findings illustrate the value of fish assemblage data for landscape-scale species distribution modeling and leveraging this information can improve predictions and inferences to help inform the management and conservation of freshwater fishes.
","language":"English","publisher":"Springer","doi":"10.1007/s42974-024-00183-9","usgsCitation":"Custer, C., Fischer, D., Smith, G., Henning, A., Kepler Schall, M., Shank, M.K., Wertz, T.A., and Isermann, D.A., 2024, Quantifying the relative importance of biotic and abiotic factors in landscape-based models of stream fish distributions: Community Ecology, v. 25, p. 145-196, https://doi.org/10.1007/s42974-024-00183-9.","productDescription":"52 p.","startPage":"145","endPage":"196","ipdsId":"IP-147148","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s42974-024-00183-9","text":"Publisher Index Page"},{"id":433512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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A.","contributorId":342455,"corporation":false,"usgs":false,"family":"Wertz","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":910114,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910115,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257781,"text":"70257781 - 2024 - Ancient permafrost and past permafrost in the Northern Hemisphere","interactions":[],"lastModifiedDate":"2024-08-27T14:13:01.25462","indexId":"70257781","displayToPublicDate":"2024-04-30T09:10:16","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Ancient permafrost and past permafrost in the Northern Hemisphere","docAbstract":"The existence and dynamics of permafrost depend on the prevailing climate conditions. Therefore, the study of ancient permafrost (existing since the Pleistocene or earlier) and past permafrost (Late Pleistocene or older permafrost that no longer exists) and their dynamics may inform about climate and environmental changes in the past. In this chapter, we provide a brief overview of characteristics, detection and dating methods of ancient and past permafrost, before presenting a spatial and temporal history of permafrost in the middle and high northern latitudes. While the first permafrost may have formed about 3 million years ago, the late Pliocene and Early Pleistocene were characterized by frequent thawing and new formation of permafrost. It was not until the Middle and Late Pleistocene that permafrost became more persistent and widespread due to prolonged cooling. The most ancient dated permafrost formed between 800 and 600 ka in Yukon/Canada and East Siberia. Interglacial warming after the last ice age has led to massive thawing of permafrost and large areas in Europe, Asia and America are now characterized by traces of past permafrost.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in Earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-99931-1.00258-0","usgsCitation":"Opel, T., Bertran, P., Grosse, G., Jones, M.C., Luetscher, M., Schirrmeister, L., Stadelmeier, K., and Veremeeva, A., 2024, Ancient permafrost and past permafrost in the Northern Hemisphere, chap. of Reference module in Earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-323-99931-1.00258-0.","productDescription":"HTML Document","ipdsId":"IP-164376","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":439707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-04581090","text":"External Repository"},{"id":433194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Hemisphere","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 89\n ],\n [\n -179.9,\n 1\n ],\n [\n 179.9,\n 1\n ],\n [\n 179.9,\n 89\n ],\n [\n -179.9,\n 89\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Opel, Thomas","contributorId":195054,"corporation":false,"usgs":false,"family":"Opel","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":911664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bertran, Pascal","contributorId":343679,"corporation":false,"usgs":false,"family":"Bertran","given":"Pascal","email":"","affiliations":[{"id":82154,"text":"Institut National de Recherches Archéologiques Préventives","active":true,"usgs":false}],"preferred":false,"id":911665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":911666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":911667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luetscher, Marc","contributorId":343680,"corporation":false,"usgs":false,"family":"Luetscher","given":"Marc","email":"","affiliations":[{"id":82157,"text":"Swiss Institute for Speleology and Karst Studies","active":true,"usgs":false}],"preferred":false,"id":911668,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schirrmeister, Lutz","contributorId":200976,"corporation":false,"usgs":false,"family":"Schirrmeister","given":"Lutz","email":"","affiliations":[],"preferred":false,"id":911669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stadelmeier, Kim","contributorId":343681,"corporation":false,"usgs":false,"family":"Stadelmeier","given":"Kim","email":"","affiliations":[{"id":82158,"text":"Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research Troposphere Research (IMKTRO","active":true,"usgs":false}],"preferred":false,"id":911670,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veremeeva, Alexandra","contributorId":194028,"corporation":false,"usgs":false,"family":"Veremeeva","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":911671,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70253582,"text":"70253582 - 2024 - NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","interactions":[],"lastModifiedDate":"2024-05-02T13:42:54.186655","indexId":"70253582","displayToPublicDate":"2024-04-30T08:41:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","docAbstract":"Models of rocky-coast erosion help us understand the physical phenomena that control coastal morphology and evolution, infer the processes shaping coasts in remote environments, and evaluate risk from natural hazards and future climate change. Existing models, however, are highly complex, are computationally expensive, and depend on many input parameters; this limits our ability to explore planform erosion of rocky coasts over long timescales (thousands to millions of years) and over a range of conditions. In this paper, we present a simplified cellular model of coastline evolution in closed basins through uniform erosion and wave-driven erosion. Uniform erosion is modeled as a constant rate of retreat. Wave erosion is modeled as a function of fetch, the distance over which the wind blows to generate waves, and the angle between the incident wave and the shoreline. This reduced-complexity model can be used to evaluate how a detachment-limited coastal landscape reflects climate, sea-level history, material properties, and the relative influence of different erosional processes.
","language":"English","publisher":"Copernicus","doi":"10.5194/gmd-17-3433-2024","usgsCitation":"Palermo, R.E., Perron, J.T., Soderblom, J.M., Birch, S.P., Hayes, A.G., and Ashton, A.D., 2024, NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps: Geoscientific Model Development, v. 17, no. 8, p. 3433-3445, https://doi.org/10.5194/gmd-17-3433-2024.","productDescription":"13 p.","startPage":"3433","endPage":"3445","ipdsId":"IP-157241","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-17-3433-2024","text":"Publisher Index Page"},{"id":428321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Palermo, Rose Elizabeth 0000-0002-7438-361X","orcid":"https://orcid.org/0000-0002-7438-361X","contributorId":300046,"corporation":false,"usgs":true,"family":"Palermo","given":"Rose","email":"","middleInitial":"Elizabeth","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":899974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":899975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soderblom, Jason M.","contributorId":193866,"corporation":false,"usgs":false,"family":"Soderblom","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":899976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birch, Samuel P. D.","contributorId":202322,"corporation":false,"usgs":false,"family":"Birch","given":"Samuel","email":"","middleInitial":"P. D.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":899977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Alexander G.","contributorId":211180,"corporation":false,"usgs":false,"family":"Hayes","given":"Alexander","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":899978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ashton, Andrew D.","contributorId":300047,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":899979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253227,"text":"sir20245025 - 2024 - Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","interactions":[],"lastModifiedDate":"2026-02-03T18:10:33.629761","indexId":"sir20245025","displayToPublicDate":"2024-04-30T07:15:01","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5025","displayTitle":"Simulation of Hydrodynamics and Water Temperature in a 21-Mile Reach of the Upper Illinois River, Illinois, 2020–22","title":"Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","docAbstract":"This report describes the development of a CE-QUAL-W2 river hydrodynamics and temperature model of a 21-mile reach of the Illinois River including a 3-mile reach of a major tributary, the Fox River. Model outputs consist of streamflow, water velocity, water-surface elevation, and water-temperature time series that can be used to simulate summer conditions in years with and without extensive development of harmful algal blooms (HABs). These analyses may provide a better understanding of some complex factors contributing to HAB development along the Illinois River. Such an understanding may provide more accurate HAB timing and location predictions and may help determine potential mitigating activities to prevent or limit the size and duration of HABs.
Using the observed and simulated hydrodynamic conditions in the Illinois River study reach, it was possible to compare and contrast streamflow, velocity, and temperature conditions in years with varying HAB distributions. Occurrences of extensive HABs were documented in the study reach in June 2020 and June 2021, but only a small HAB restricted to the Marseilles Lock and Dam pool occurred in the summer of 2022. The objective then was to find similarities in site conditions between 2020 and 2021 that may contrast with the conditions in 2022. Among the 3 years included in the study, the variability in simulated water temperature exceeded variability in observed streamflow and simulated velocities. The longest period of water temperatures greater than 27 degrees Celsius (°C) in the selected locations in June of the three analysis years was in the second half of June 2022, yet no study-area wide HAB was documented in 2022. Simulations indicated that after warm water temperatures were established in the reach in June 2022, a cooling period broke up the warming period. This period of cooling was greater in magnitude and duration downstream from the location of a localized HAB perhaps limiting the spread of the bloom.
Residence times differed substantially in segments representing different channel features; values ranged from 0.28 to 17.3 (days per 500 meters of channel) between the main stem and backwater areas, respectively. Variation in average June residence times was also greater among different channel features than among different years in the study period. The HABs in 2020 and 2021 at Starved Rock Dam were documented when water temperatures were about 26 °C. River backwater areas at some locations did attain these temperatures 2 to 3 days before the conditions in the main stem. Residence times in the backwater areas, however, generally exceeded 9 days, thus limiting the exchange of water carrying algal biomass into the main channel.
Hydrodynamic model calibration involved adjusting model parameters until observed and simulated daily water-surface elevations, daily streamflows, discrete velocities, and channel areas were similar. Temperature calibration was done with near-surface continuous time-series data and discrete vertical profile temperatures. Observed and simulated water temperatures generally were within 1 °C at all monitoring locations.
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Returning monarch butterflies (Danaus plexippus) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.
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Laura","contributorId":336723,"corporation":false,"usgs":false,"family":"Lukens","given":"Laura","affiliations":[{"id":80852,"text":"Monarch Joint Venture","active":true,"usgs":false}],"preferred":false,"id":900890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":900891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Christian","contributorId":336724,"corporation":false,"usgs":false,"family":"Newman","given":"Christian","email":"","affiliations":[{"id":80850,"text":"Electric Power Research Institute","active":true,"usgs":false}],"preferred":false,"id":900892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253576,"text":"70253576 - 2024 - Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","interactions":[],"lastModifiedDate":"2024-07-01T14:41:54.77567","indexId":"70253576","displayToPublicDate":"2024-04-29T08:28:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","docAbstract":"An important provision of the Minamata Convention on Mercury is to monitor and evaluate the effectiveness of the adopted measures and its implementation. Here, we describe for the first time currently available biotic mercury (Hg) data on a global scale to improve the understanding of global efforts to reduce the impact of Hg pollution on people and the environment. Data from the peer-reviewed literature were compiled in the Global Biotic Mercury Synthesis (GBMS) database (>550,000 data points). These data provide a foundation for establishing a biomonitoring framework needed to track Hg concentrations in biota globally. We describe Hg exposure in the taxa identified by the Minamata Convention: fish, sea turtles, birds, and marine mammals. Based on the GBMS database, Hg concentrations are presented at relevant geographic scales for continents and oceanic basins. We identify some effective regional templates for monitoring methylmercury (MeHg) availability in the environment, but overall illustrate that there is a general lack of regional biomonitoring initiatives around the world, especially in Africa, Australia, Indo-Pacific, Middle East, and South Atlantic and Pacific Oceans. Temporal trend data for Hg in biota are generally limited. Ecologically sensitive sites (where biota have above average MeHg tissue concentrations) have been identified throughout the world. Efforts to model and quantify ecosystem sensitivity locally, regionally, and globally could help establish effective and efficient biomonitoring programs. We present a framework for a global Hg biomonitoring network that includes a three-step continental and oceanic approach to integrate existing biomonitoring efforts and prioritize filling regional data gaps linked with key Hg sources. We describe a standardized approach that builds on an evidence-based evaluation to assess the Minamata Convention’s progress to reduce the impact of global Hg pollution on people and the environment.
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debris-flow building damage forecasts","docAbstract":"Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.
Birds are used as bioindicators of environmental mercury (Hg) contamination, and toxicity reference values are needed for injury assessments. We conducted a comprehensive review, summarized data from 168 studies, performed a series of Bayesian hierarchical meta-analyses, and developed new toxicity reference values for the effects of methylmercury (MeHg) on birds using a benchmark dose analysis framework. Lethal and sublethal effects of MeHg on birds were categorized into nine biologically relevant endpoint categories and three age classes. Effective Hg concentrations where there was a 10% reduction (EC10) in the production of juvenile offspring (0.55 µg/g wet wt adult blood-equivalent Hg concentrations, 80% credible interval: [0.33, 0.85]), histology endpoints (0.49 [0.15, 0.96] and 0.61 [0.09, 2.48]), and biochemical markers (0.77 [<0.25, 2.12] and 0.57 [0.35, 0.92]) were substantially lower than those for survival (2.97 [2.10, 4.73] and 5.24 [3.30, 9.55]) and behavior (6.23 [1.84, >13.42] and 3.11 [2.10, 4.64]) of juveniles and adults, respectively. Within the egg age class, survival was the most sensitive endpoint (EC10 = 2.02 µg/g wet wt adult blood-equivalent Hg concentrations [1.39, 2.94] or 1.17 µg/g fresh wet wt egg-equivalent Hg concentrations [0.80, 1.70]). Body morphology was not particularly sensitive to Hg. We developed toxicity reference values using a combined survival and reproduction endpoints category for juveniles, because juveniles were more sensitive to Hg toxicity than eggs or adults. Adult blood-equivalent Hg concentrations (µg/g wet wt) and egg-equivalent Hg concentrations (µg/g fresh wet wt) caused low injury to birds (EC1) at 0.09 [0.04, 0.17] and 0.04 [0.01, 0.08], moderate injury (EC5) at 0.6 [0.37, 0.84] and 0.3 [0.17, 0.44], high injury (EC10) at 1.3 [0.94, 1.89] and 0.7 [0.49, 1.02], and severe injury (EC20) at 3.2 [2.24, 4.78] and 1.8 [1.28, 2.79], respectively. Maternal dietary Hg (µg/g dry wt) caused low injury to juveniles at 0.16 [0.05, 0.38], moderate injury at 0.6 [0.29, 1.03], high injury at 1.1 [0.63, 1.87], and severe injury at 2.4 [1.42, 4.13]. We found few substantial differences in Hg toxicity among avian taxonomic orders, including for controlled laboratory studies that injected Hg into eggs. Our results can be used to quantify injury to birds caused by Hg pollution.