Theory of the evolution of pathogen specialization suggests that a specialist pathogen gains high fitness in one host, but this comes with fitness loss in other hosts. By contrast, a generalist pathogen does not achieve high fitness in any host, but gains ecological fitness by exploiting different hosts, and has higher fitness than specialists in nonspecialized hosts. As a result, specialist pathogens are predicted to have greater variation in fitness across hosts, and generalists would have lower fitness variation across hosts. We test these hypotheses by measuring pathogen replicative fitness as within-host viral loads from the onset of infection to the beginning of virus clearance, using the rhabdovirus infectious hematopoietic necrosis virus (IHNV) in salmonid fish. Based on field prevalence and virulence studies, the IHNV subgroups UP, MD, and L are specialists, causing infection and mortality in sockeye salmon, steelhead, and Chinook salmon juveniles, respectively. The UC subgroup evolved naturally from a UP ancestor and is a generalist infecting all three host species but without causing severe disease. We show that the specialist subgroups had the highest peak and mean viral loads in the hosts in which they are specialized, and they had low viral loads in nonspecialized hosts, resulting in large variation in viral load across hosts. Viral kinetics show that the mechanisms of specialization involve the ability to both maximize early virus replication and avoid clearance at later times, with different mechanisms of specialization evident in different host–virus combinations. Additional nuances in the data included different fitness levels for nonspecialist interactions, reflecting different trade-offs for specialist viruses in other hosts. The generalist UC subgroup reached intermediate viral loads in all hosts and showed the smallest variation in fitness across hosts. The evolution of the UC generalist from an ancestral UP sockeye specialist was associated with fitness increases in steelhead and Chinook salmon, but only slight decreases in fitness in sockeye salmon, consistent with low- or no-cost generalism. Our results support major elements of the specialist–generalist theory, providing evidence of a specialist–generalist continuum in a vertebrate pathogen. These results also quantify within-host replicative fitness trade-offs resulting from the natural evolution of specialist and generalist virus lineages in multi-host ecosystems
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ve/veac079","usgsCitation":"Paez, D.J., McKenney, D.G., Purcell, M.K., Naish, K.A., and Kurath, G., 2022, Variation in within-host replication kinetics among virus genotypes provides evidence of specialist and generalist infection strategies across three salmonid host species: Virus Evolution, v. 8, no. 2, veac079, 12 p., https://doi.org/10.1093/ve/veac079.","productDescription":"veac079, 12 p.","ipdsId":"IP-142038","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":446678,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ve/veac079","text":"Publisher Index Page"},{"id":435719,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98UQLLW","text":"USGS data release","linkHelpText":"Survival and viral load of chinook salmon, sockeye salmon, and steelhead trout exposed to 4 genogroups of infectious hematopoietic necrosis virus (IHNV)"},{"id":407051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Páez, David James 0000-0001-9035-394X","orcid":"https://orcid.org/0000-0001-9035-394X","contributorId":296751,"corporation":false,"usgs":true,"family":"Páez","given":"David","middleInitial":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenney, Douglas G.","contributorId":296750,"corporation":false,"usgs":false,"family":"McKenney","given":"Douglas","email":"","middleInitial":"G.","affiliations":[{"id":64163,"text":"Previously USGS, Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":852374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naish, Kerry A. 0000-0002-3275-8778","orcid":"https://orcid.org/0000-0002-3275-8778","contributorId":201136,"corporation":false,"usgs":false,"family":"Naish","given":"Kerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":852376,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852377,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245400,"text":"70245400 - 2022 - Forecasting and communicating the dispersion and fallout of ash during volcanic eruptions: lessons from the September 20, 2020 eruptive pulse at Sangay volcano, Ecuador","interactions":[],"lastModifiedDate":"2023-06-22T12:22:42.013017","indexId":"70245400","displayToPublicDate":"2022-08-24T07:14:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting and communicating the dispersion and fallout of ash during volcanic eruptions: lessons from the September 20, 2020 eruptive pulse at Sangay volcano, Ecuador","docAbstract":"Volcanic ash is a hazard to human health and activities. Accurate and timely forecasts coupled with effective communication about the dispersion and fallout of volcanic ash during explosive events are essential to reduce impacts on local communities and limit economic losses. In this study, we present the first detailed description of an eruptive pulse at Sangay volcano and its eruption source parameters. The eruptive pulse on September 20, 2020, started at about 9:20 UTC and lasted between 90 and 100 min, producing an eruptive column that rapidly separated into (1) a higher (15.2 km above sea level, asl), gas-rich cloud moving east-southeast and (2) a lower (12.2 km asl), ash-rich cloud moving west and causing ash fallout up to 280 km from the volcano. Field data collected immediately after the event allow estimating the volume of bulk tephra to be between 1.5 and 5.0 × 106 m3, corresponding to a volcanic explosivity index of 2. The eruptive pulse, identified as violent Strombolian, emitted andesitic ash that was more mafic than products ejected by Sangay volcano in recent decades. Component analysis and glass chemistry of juvenile particles support the hypothesis that this event excavated deeper into the upper conduit compared to typical Strombolian activity at Sangay volcano, while grain-size analysis allows reconstruction of the total grain-size distribution of the fallout deposit. The discrepancies between the ash fallout simulations performed with the Ash3D online tool and the actual deposit are mainly the result of inaccurate pre- and syn-eruptive configurations and highlight the importance of additional processes such as aggregation. Communication products issued during the event included (1) several standard short reports, (2) volcano observatory notices for aviation, (3) social media posts, and (4) a special report providing the results of the ash fallout simulation. Although communication was effective with the authorities and the connected population, an effort must be made to reach the most vulnerable isolated communities for future events. This study shows that forecasting ash dispersion and fallout during volcanic eruptions can guide early warnings and trigger humanitarian actions, and should become a standard in volcano observatories worldwide.
High-latitude peatlands are changing rapidly in response to climate change, including permafrost thaw. Here, we reconstruct hydrological conditions since the seventeenth century using testate amoeba data from 103 high-latitude peat archives. We show that 54% of the peatlands have been drying and 32% have been wetting over this period, illustrating the complex ecohydrological dynamics of high latitude peatlands and their highly uncertain responses to a warming climate.
Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further democratize macroecological research, as their strengths and weaknesses are complementary. However, using these tools for macroecology can be challenging because mental models are lacking, thus requiring large up-front investments in time, energy, and creativity to become proficient. This challenge inspired a working group of UAS-using academic ecologists, NEON professionals, imaging scientists, remote sensing specialists, and aeronautical engineers at the 2019 NEON Science Summit in Boulder, Colorado, to synthesize current knowledge on how to use UAS with NEON in a mental model for an intended audience of ecologists new to these tools. Specifically, we provide (1) a collection of core principles for collecting high-quality UAS data for NEON integration and (2) a case study illustrating a sample workflow for processing UAS data into meaningful ecological information and integrating it with NEON data collected on the ground—with the Terrestrial Observation System—and remotely—from the Airborne Observation Platform. With this mental model, we advance the democratization of macroecology by making a key observational domain—the broad-extent, fine-grain domain—more accessible via NEON/UAS integration.
The Great Lakes basin was historically populated by multiple, coevolved coregonine species, but much of that diversity has been lost. In Lakes Erie and Ontario, both lake whitefish (Coregonus clupeaformis) and cisco (Coregonus artedi) occurred in high numbers before habitat degradation, overfishing, invasive species, and other factors caused significant declines. There is growing interest in restoring these populations, and suggested actions include restoration of critical habitats such as spawning habitat. Unfortunately, our current understanding of lake whitefish and cisco spawning habitat characteristics and locations in these lakes is limited. To highlight areas of potential importance for conservation and restoration, we used random forest models and data on historical spawning locations to predict lake whitefish and cisco spawning habitats based on hypothesized key factors including wind fetch, ice cover duration, distance from 1st and 6th order tributaries, and lake bottom substrate. Our model accurately predicted spawning habitat locations for 71% and 54% of cases for lake whitefish and cisco, respectively. Fetch was the most important variable in the lake whitefish model, with spawning habitats being most likely to occur in regions of low to moderate fetch. Cisco spawning habitats were most likely to occur in areas of relatively low fetch near a 1st order stream. We used these models to predict spawning habitat locations for both species across Lakes Erie, Ontario, and St. Clair. Our results improve our understanding of lake whitefish and cisco spawning habitat characteristics and will aid in the spatial prioritization of actions to restore these native fishes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.08.014","usgsCitation":"Schaefer, H.M., Honsey, A.E., Bunnell, D., Weidel, B., DeBruyne, R., Diana, J.S., Gorsky, D., and Roseman, E., 2022, Predicting physical and geomorphic habitat associated with historical lake whitefish and cisco spawning locations in Lakes Erie and Ontario: Journal of Great Lakes Research, v. 48, no. 6, p. 1636-1646, https://doi.org/10.1016/j.jglr.2022.08.014.","productDescription":"11 p.","startPage":"1636","endPage":"1646","ipdsId":"IP-136743","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":405591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie, Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.509033203125,\n 44.731125592643274\n ],\n [\n -80.343017578125,\n 44.22158376545796\n ],\n [\n -82.298583984375,\n 42.84375132629021\n ],\n [\n -83.265380859375,\n 42.80346172417078\n ],\n [\n -84.287109375,\n 41.705728515237524\n ],\n [\n -82.452392578125,\n 40.772221877329024\n ],\n [\n -79.376220703125,\n 41.30257109430557\n ],\n [\n -76.35498046875,\n 43.18915769654922\n ],\n [\n -75.498046875,\n 43.76315996157264\n ],\n [\n -75.509033203125,\n 44.731125592643274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schaefer, Hannah M","contributorId":216810,"corporation":false,"usgs":false,"family":"Schaefer","given":"Hannah","email":"","middleInitial":"M","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":849641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Honsey, Andrew Edgar 0000-0001-7535-1321","orcid":"https://orcid.org/0000-0001-7535-1321","contributorId":295468,"corporation":false,"usgs":true,"family":"Honsey","given":"Andrew","email":"","middleInitial":"Edgar","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":849642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":217344,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":849643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":849644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeBruyne, Robin 0000-0002-9232-7937","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":240598,"corporation":false,"usgs":false,"family":"DeBruyne","given":"Robin","affiliations":[{"id":48111,"text":"Univ. Toledo","active":true,"usgs":false}],"preferred":false,"id":849645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diana, James S.","contributorId":216547,"corporation":false,"usgs":false,"family":"Diana","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":849646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gorsky, Dimitry 0000-0003-1708-539X","orcid":"https://orcid.org/0000-0003-1708-539X","contributorId":295528,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":849647,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":849648,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266889,"text":"70266889 - 2022 - Sedimentary geochemistry of deepwater slope deposits in southern Lake Tanganyika (East Africa): Effects of upwelling and minor lake level oscillations","interactions":[],"lastModifiedDate":"2025-05-14T14:38:39.481043","indexId":"70266889","displayToPublicDate":"2022-08-23T09:33:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2451,"text":"Journal of Sedimentary Research","onlineIssn":"1938-3681","printIssn":"1527-1404","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary geochemistry of deepwater slope deposits in southern Lake Tanganyika (East Africa): Effects of upwelling and minor lake level oscillations","docAbstract":"Lake Tanganyika ranks among the most valuable modern analogs for understanding depositional processes of carbonaceous sediments in ancient tropical rifts. Prior research on Lake Tanganyika has emphasized the importance of bottom-water anoxia, depositional processes (hemipelagic settling versus gravity flows), and large-scale (100s of meters) lake level change on the quality of sedimentary organic matter content. Here, facies analysis and numerous organic geochemical tools (elemental, carbon isotope, and programmed pyrolysis) were applied to a radiocarbon-dated core from southern Lake Tanganyika to investigate the accumulation of carbonaceous sediments in a deepwater slope environment influenced by high-frequency climatic fluctuations accompanied by only minor (10s of meters) lake level changes. Considerable variability in lithofacies and geochemistry characterizes the ∼ 1030-year-long core record, chiefly driven by climate-mediated changes to the lake's upwelling system. Laminated diatom oozes and sapropels with mean total organic carbon (TOC) concentrations and hydrogen indices of 6.9 wt.% and 385 mg hydrocarbon/g TOC, respectively, characterize sediments deposited during periods of strong upwelling and variable water levels. Silty sediments deposited via gravity-flow processes were likewise rich in organic matter, likely due to preservation-enhancing bottom-water anoxia. Dilution by reworked tephra was the chief constraint on organic enrichment at the study site. Data from this study reveal that oscillations in atmospheric and limnological processes in the absence of major shoreline movements can result in geochemically diverse deepwater slope sediments, which have implications for improving depositional models of petroliferous continental rift basins.
","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/jsr.2021.104","usgsCitation":"McGlue, M., Ellis, G.S., Brannon, M., Latimer, J., Stone, J., Ivory, S., Mganza, N., Soreghan, M.J., and Scholz, C., 2022, Sedimentary geochemistry of deepwater slope deposits in southern Lake Tanganyika (East Africa): Effects of upwelling and minor lake level oscillations: Journal of Sedimentary Research, v. 92, no. 8, p. 721-738, https://doi.org/10.2110/jsr.2021.104.","productDescription":"18 p.","startPage":"721","endPage":"738","ipdsId":"IP-128441","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":485933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Tanganyika","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 27.668481366027635,\n -3.1820760248469355\n ],\n [\n 27.668481366027635,\n -9.112434947743992\n ],\n [\n 31.779025954731935,\n -9.112434947743992\n ],\n [\n 31.779025954731935,\n -3.1820760248469355\n ],\n [\n 27.668481366027635,\n -3.1820760248469355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"McGlue, Michael M.","contributorId":225229,"corporation":false,"usgs":false,"family":"McGlue","given":"Michael M.","affiliations":[{"id":41081,"text":"Department of Geosciences, The University of Arizona, Tucson AZ","active":true,"usgs":false}],"preferred":false,"id":937045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":937046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brannon, McKenzie A","contributorId":355181,"corporation":false,"usgs":false,"family":"Brannon","given":"McKenzie A","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":937047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latimer, Jennifer C","contributorId":355182,"corporation":false,"usgs":false,"family":"Latimer","given":"Jennifer C","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":937048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Jeffery S","contributorId":355183,"corporation":false,"usgs":false,"family":"Stone","given":"Jeffery S","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":937049,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ivory, Sarah J.","contributorId":138493,"corporation":false,"usgs":false,"family":"Ivory","given":"Sarah J.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":937050,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mganza, Neema E","contributorId":355184,"corporation":false,"usgs":false,"family":"Mganza","given":"Neema E","affiliations":[{"id":84721,"text":"Tanzania Petroleum Development Corporation","active":true,"usgs":false}],"preferred":false,"id":937051,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Soreghan, Michael J.","contributorId":347062,"corporation":false,"usgs":false,"family":"Soreghan","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":83052,"text":"School of Geosciences, University of Oklahoma, Norman, OK, 73019, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":937052,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scholz, Christopher A.","contributorId":149267,"corporation":false,"usgs":false,"family":"Scholz","given":"Christopher A.","affiliations":[{"id":17692,"text":"Syracuse University, Syracuse NY","active":true,"usgs":false}],"preferred":false,"id":937053,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70236135,"text":"70236135 - 2022 - Interseismic lithospheric response of the southern end of the Cascadia Subduction Zone since the 1992 Cape Mendocino M 7.1 earthquake","interactions":[],"lastModifiedDate":"2022-08-30T14:20:40.201996","indexId":"70236135","displayToPublicDate":"2022-08-23T09:15:46","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Interseismic lithospheric response of the southern end of the Cascadia Subduction Zone since the 1992 Cape Mendocino M 7.1 earthquake","docAbstract":"No abstract available.
","conferenceTitle":"Friends of the Pleistocene Pacific Cell 2022 Field Conference","conferenceDate":"Aug 26-28, 2022","conferenceLocation":"Humboldt County, CA","language":"English","publisher":"Friends of the Pleistocene","usgsCitation":"Vermeer, J., and Hemphill-Haley, M., 2022, Interseismic lithospheric response of the southern end of the Cascadia Subduction Zone since the 1992 Cape Mendocino M 7.1 earthquake, Friends of the Pleistocene Pacific Cell 2022 Field Conference, Humboldt County, CA, Aug 26-28, 2022, 7 p.","productDescription":"7 p.","ipdsId":"IP-143548","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":405908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":405906,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fop.cascadiageo.org/field-trips/pacific-cell-field-trips/2022-triangle-of-doom-take-two/"}],"country":"United States","state":"California","otherGeospatial":"Cape Mendocino, Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8,\n 40.2\n ],\n [\n -124,\n 40.2\n ],\n [\n -124,\n 40.7\n ],\n [\n -124.8,\n 40.7\n ],\n [\n -124.8,\n 40.2\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vermeer, Jessica 0000-0001-8349-0137","orcid":"https://orcid.org/0000-0001-8349-0137","contributorId":295930,"corporation":false,"usgs":true,"family":"Vermeer","given":"Jessica","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemphill-Haley, Mark","contributorId":295931,"corporation":false,"usgs":false,"family":"Hemphill-Haley","given":"Mark","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":850204,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236700,"text":"70236700 - 2022 - Evaluation of Francisella orientalis ΔpdpA as a live attenuated vaccine against piscine Francisellosis in Nile tilapia","interactions":[],"lastModifiedDate":"2022-09-28T16:50:02.940647","indexId":"70236700","displayToPublicDate":"2022-08-23T08:57:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of Francisella orientalis ΔpdpA as a live attenuated vaccine against piscine Francisellosis in Nile tilapia","title":"Evaluation of Francisella orientalis ΔpdpA as a live attenuated vaccine against piscine Francisellosis in Nile tilapia","docAbstract":"Francisella orientalis is an important bacterial pathogen of marine and freshwater fish with worldwide distribution. Fish francisellosis is a severe subacute to chronic granulomatous disease, with high mortalities and high infectivity rates in cultured and wild fish. To date, there is no approved vaccine for this disease. In this study, we evaluated the efficacy of a defined F. orientalis pathogenicity determinant protein A (pdpA) mutant (ΔpdpA) as a live attenuated immersion vaccine against subsequent immersion challenge with the wild-type organism. Immunized Nile tilapia Oreochromis niloticus were protected (45% relative percent survival) from the lethal challenges and presented significantly lower mortality than nonvaccinated and challenged treatments. Although serum IgM was significantly higher in immunized fish, similar bacterial loads were detected in vaccinated and nonvaccinated survivors. In conclusion, although the F. orientalis ΔpdpA is attenuated and effectively stimulated an adaptive immune response, the low relative percent survival and high bacterial persistence in survivors of immunized and challenged treatments indicates low suitability of ΔpdpA as a mucosal vaccine for tilapia under conditions used in this study.
","language":"English","publisher":"Wiley","doi":"10.1002/aah.10166","usgsCitation":"de Alexandre Sebastiao, F., Hansen, J.D., and Soto, E., 2022, Evaluation of Francisella orientalis ΔpdpA as a live attenuated vaccine against piscine Francisellosis in Nile tilapia: Journal of Aquatic Animal Health, v. 34, no. 3, p. 134-139, https://doi.org/10.1002/aah.10166.","productDescription":"6 p.","startPage":"134","endPage":"139","ipdsId":"IP-137939","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":406835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"de Alexandre Sebastiao, Fernanda","contributorId":296594,"corporation":false,"usgs":false,"family":"de Alexandre Sebastiao","given":"Fernanda","email":"","affiliations":[{"id":64104,"text":"University of California-Davis, Department of Medicine and Epidemiology, School of Veterinary Medicine, Davis, CA 95616","active":true,"usgs":false}],"preferred":false,"id":851931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, John D. 0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":851932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soto, Esteban","contributorId":265184,"corporation":false,"usgs":false,"family":"Soto","given":"Esteban","affiliations":[{"id":54631,"text":"Department of Medicine and Epidemiology, University of California-Davis, School of Veterinary Medicine, Davis, CA","active":true,"usgs":false}],"preferred":false,"id":851933,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70244293,"text":"70244293 - 2022 - Eimeria albigulae (Apicomplexa: Eimeriidae): New host and distributional record from the Bryant's woodrat, Neotoma bryanti (Rodentia: Cricetidae), from California, U.S.A.","interactions":[],"lastModifiedDate":"2023-06-13T13:29:56.544935","indexId":"70244293","displayToPublicDate":"2022-08-23T08:05:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1298,"text":"Comparative Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Eimeria albigulae (Apicomplexa: Eimeriidae): New host and distributional record from the Bryant's woodrat, Neotoma bryanti (Rodentia: Cricetidae), from California, U.S.A.","title":"Eimeria albigulae (Apicomplexa: Eimeriidae): New host and distributional record from the Bryant's woodrat, Neotoma bryanti (Rodentia: Cricetidae), from California, U.S.A.","docAbstract":"Fecal samples, collected in July 2020 and April–May 2021 from 17 Bryant's woodrats, Neotoma bryanti Merriam, from 3 sites in San Diego, Orange, and San Bernardino counties, California, were examined for coccidial parasites. Three of 8 (38%) woodrats from a single site in San Diego County were found to be passing oocysts of Eimeria albigulae Levine, Ivens, and Kruidenier, 1957. Subspheroidal oocysts measured (average length [L] × width [W]) 23.5 × 21.4 µm with an average L/W ratio of 1.1. A micropyle was absent, but an oocyst residuum as well as a single polar granule was present. Ovoidal sporocysts measured (average L × W) 10.1 × 7.5 µm with an L/W ratio average of 1.4. A nipple-like Stieda body was present, but sub-Stieda and para-Stieda bodies were absent. The sporocyst residuum was composed of loosely packed granules between and around the sporozoites. This woodrat represents the sixth host to harbor this coccidian. We document a new host as well as a geographic distribution record for E. albigulae.
","language":"English","publisher":"The Helminthological Society of Washington","doi":"10.1654/COPA-D-21-00010","usgsCitation":"McAllister, C., Hnida, J.A., and Fisher, R., 2022, Eimeria albigulae (Apicomplexa: Eimeriidae): New host and distributional record from the Bryant's woodrat, Neotoma bryanti (Rodentia: Cricetidae), from California, U.S.A.: Comparative Parasitology, v. 89, no. 2, p. 59-62, https://doi.org/10.1654/COPA-D-21-00010.","productDescription":"4 p.","startPage":"59","endPage":"62","ipdsId":"IP-135980","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":418052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"89","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McAllister, Chris T.","contributorId":303299,"corporation":false,"usgs":false,"family":"McAllister","given":"Chris T.","affiliations":[{"id":65753,"text":"Eastern Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":875225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hnida, John A.","contributorId":306246,"corporation":false,"usgs":false,"family":"Hnida","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":66389,"text":"Midwestern University","active":true,"usgs":false}],"preferred":false,"id":875226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":875227,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238032,"text":"70238032 - 2022 - NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations","interactions":[],"lastModifiedDate":"2022-11-04T12:26:51.26005","indexId":"70238032","displayToPublicDate":"2022-08-23T07:22:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations","docAbstract":"This report addresses system characterization of the Instituto Nacional de Pesquisas Espaciais Amazônia-1 satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Amazônia-1 is a four-band imager with a 64-meter (m) pixel ground sample distance. Amazônia-1 was launched in February 2021 into a Sun-synchronous orbit of 752 kilometers with an inclination of 98.4 degrees and a swath width of 850 kilometers. The satellite has an expected lifetime of about 4 years. More information on Amazônia-1 is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium).
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that the Amazônia-1 satellite has an interior geometric performance in the range of −3.584 m (−0.056 pixel) to 0.320 m (0.005 pixel) in easting and −1.984 m (−0.031 pixel) to 2.048 m (0.032 pixel) in northing in band-to-band registration, an exterior geometric performance of −37.256 m (−0.621 pixel) to 54.758 m (0.913 pixel) in easting and −12.684 m (−0.211 pixel) to 54.898 m (0.915 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 0.030 to 0.143 in offset and 0.662 to 0.825 in slope, and a spatial performance in the range of 1.62 to 2.06 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.062 to 0.115.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030N","usgsCitation":"Vrabel, J.C., Stensaas, G.L., Anderson, C., Christopherson, J., Kim, M., and Park, S., 2022, System characterization report on the Amazônia-1 multispectral sensor, chap. N of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 33 p., https://doi.org/10.3133/ofr20211030N.","productDescription":"v, 33 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-142103","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":405398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/n/ofr20211030n.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–N"},{"id":405397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/n/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Surface-water-quality data in the Rapid Creek Basin in South Dakota were compiled to assess basic trends in the water quality of Rapid Creek. Spatial and temporal patterns in water quality were described for major ions, sediment, total suspended solids, nutrients, field measurements, bacteria, and select metals for the period of 1970–2020, and a water-quality trend analysis was completed for sites with enough data for selected constituents.
Major ions and total suspended solids had higher median concentrations in the lower basin (downstream from the city of Rapid City) relative to the upper and middle basins. Nutrient concentrations were generally low, and increased concentrations were only detected at the sites downstream from the City of Rapid City Water Reclamation Facility. Fecal indicator bacteria (Escherichia coli and fecal coliform) concentrations were highest downstream from the main urbanized area of Rapid City.
Water-quality trends were analyzed for total dissolved solids, specific conductance, calcium, magnesium, total suspended solids, total phosphorus, dissolved phosphorus, and total Kjeldahl nitrogen for the period of 1979–2019. Concentrations for major ions and total dissolved solids typically changed by less than 15 percent. Total dissolved solids concentrations upstream from Rapid City were generally decreasing, whereas concentrations downstream were generally increasing. The flow-averaged geometric mean concentration of total dissolved solids at three sites upstream from Rapid City decreased overall by 3–5 percent, and concentrations at two sites downstream from Rapid City increased by at least 7 percent between 1979 and 2019. Trends in specific conductance in the Rapid Creek Basin were mixed with alternating increasing and decreasing trends at many of the sites between 1979 and 2014. Total suspended solids concentrations were observed to be decreasing at two sites analyzed for trends. Concentrations in total phosphorus were observed to be decreasing at every site analyzed for trends between 1989 and 2014. Significant downward trends in total Kjeldahl nitrogen were observed at two sites in the lower Rapid Creek Basin for the trend period of 1999–2019. The decreases in total suspended solids and nutrient concentrations in the Rapid Creek Basin could be related to several processes such as the implementation of a stormwater management plan in Rapid City, improvements to the water reclamation facility downstream from Rapid City, and residual climatic effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225086","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Tatge, W.S., Hoogestraat, G.K., and Nustad, R.A., 2022, Water-quality data and trends in the Rapid Creek Basin, South Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5086, 67 p., https://doi.org/10.3133/sir20225086.","productDescription":"Report: viii, 67 p.; Data Release; Dataset","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-133856","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":405392,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225086/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":405347,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.XML"},{"id":405350,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":405346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5086"},{"id":405345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5086/coverthb.jpg"},{"id":405349,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D8BSXR","text":"USGS data release","linkHelpText":"Model scripts and water-quality data for trends in the Rapid Creek Basin, South Dakota, 1970–2020"},{"id":405348,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5086/images"}],"country":"United States","state":"South Dakota","otherGeospatial":"Rapid Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0185546875,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 43.84443209873525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Decades of research on the effects of urbanization on stream ecology have shown that urban stream problems are inherently wicked. These problems are wicked in the sense that they are difficult to solve because information is incomplete, changing, or conflicting and because finding potential solutions often requires input from stakeholders who can have conflicting and competing values. The 5th Symposium on Urbanization and Stream Ecology (SUSE5) in February 2020 brought together diverse perspectives from scientists, managers, practitioners, and local communities. Participants at SUSE5 discussed the state of the science in urban stream ecology and worked through in-depth case studies in teams to tackle complex real-world problems in urban stream management. The papers in this special series on urbanization and stream ecology include empirical research studies and synthesis papers sparked by discussions at SUSE5 and advance multidisciplinary solutions to wicked urban stream problems.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/721470","usgsCitation":"Fork, M.L., Hopkins, K.G., Chappell, J., Hawley, R.J., Kaushal, S., Murphy, B.M., Rios-Touma, B., and Roy, A.H., 2022, Urbanization and stream ecology: Moving the bar on multidisciplinary solutions to wicked urban stream problems: Freshwater Science, v. 41, no. 3, 6 p., https://doi.org/10.1086/721470.","productDescription":"6 p.","ipdsId":"IP-142003","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":405387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fork, Megan L.","contributorId":139659,"corporation":false,"usgs":false,"family":"Fork","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":12868,"text":"Nicholas School of the Environment, Duke University, Durham, NC, USA","active":true,"usgs":false}],"preferred":false,"id":849355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":849356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chappell, Jessica","contributorId":219589,"corporation":false,"usgs":false,"family":"Chappell","given":"Jessica","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":849357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawley, Robert J.","contributorId":167574,"corporation":false,"usgs":false,"family":"Hawley","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":24758,"text":"Sustainable Streams, LLC, Louisville, KY","active":true,"usgs":false}],"preferred":false,"id":849358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaushal, Sujay S.","contributorId":210125,"corporation":false,"usgs":false,"family":"Kaushal","given":"Sujay S.","affiliations":[{"id":38074,"text":"Univ. of Maryland","active":true,"usgs":false}],"preferred":false,"id":849359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Brian M. 0000-0002-7670-2469","orcid":"https://orcid.org/0000-0002-7670-2469","contributorId":292734,"corporation":false,"usgs":false,"family":"Murphy","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":849360,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rios-Touma, Blanca","contributorId":295395,"corporation":false,"usgs":false,"family":"Rios-Touma","given":"Blanca","email":"","affiliations":[{"id":63858,"text":"Universidad de Las Américas","active":true,"usgs":false}],"preferred":false,"id":849361,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":849362,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70235807,"text":"70235807 - 2022 - Magnetotelluric investigations of the Kīlauea Volcano, Hawaii","interactions":[],"lastModifiedDate":"2022-08-22T14:35:53.522926","indexId":"70235807","displayToPublicDate":"2022-08-22T09:35:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric investigations of the Kīlauea Volcano, Hawaii","docAbstract":"In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the U.S. Geological Survey (USGS) Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kīlauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kīlauea and the East and Southwest Rift zones, which has implications for understanding Kīlauea's plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone, where electrical contact resistances are on the order of 100 kΩ. A three-dimensional (3D) MT model study was done to guide interpretation of the observed MT measurements. Synthetic modeling demonstrates that conductive bodies in the upper 3 km can be spatially resolved where MT station sampling is good. Resistivity anomalies in the 3D inversions have a high degree of spatial correlation with previously published seismic velocity anomalies beneath Kīlauea. Melt fractions between 0.096 and 0.117 are calculated for the Kīlauea and Puʻuʻōʻō low resistivity anomalies, respectively.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024418","usgsCitation":"Hoversten, G., Gasperikova, E., Mackie, R., Myer, D., Kauahikaua, J.P., Newman, G.A., and Cuevas, N., 2022, Magnetotelluric investigations of the Kīlauea Volcano, Hawaii: Journal of Geophysical Research: Solid Earth, v. 127, no. 8, e2022JB024418, 24 p., https://doi.org/10.1029/2022JB024418.","productDescription":"e2022JB024418, 24 p.","ipdsId":"IP-135899","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":446701,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jb024418","text":"External Repository"},{"id":405386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.29131889343262,\n 19.396901484778134\n ],\n [\n -155.28496742248535,\n 19.39892544698541\n ],\n [\n -155.2786159515381,\n 19.399087362874425\n ],\n [\n -155.2730369567871,\n 19.39827778181811\n ],\n [\n -155.2676296234131,\n 19.400949384016776\n ],\n [\n -155.26385307312012,\n 19.403944764615613\n ],\n [\n -155.25887489318848,\n 19.40629245679785\n ],\n [\n -155.2511501312256,\n 19.4109877394962\n ],\n [\n -155.24694442749023,\n 19.408882974361152\n ],\n [\n -155.24042129516602,\n 19.408478208711944\n ],\n [\n -155.23784637451172,\n 19.410906787494763\n ],\n [\n -155.23836135864258,\n 19.414306736852605\n ],\n [\n -155.24102210998535,\n 19.414306736852605\n ],\n [\n -155.2434253692627,\n 19.418758943963656\n ],\n [\n -155.24943351745605,\n 19.42353481237166\n ],\n [\n -155.25372505187985,\n 19.427662992293143\n ],\n [\n -155.25853157043457,\n 19.4298484568423\n ],\n [\n -155.26239395141602,\n 19.43081976498137\n ],\n [\n -155.2672004699707,\n 19.430576938491143\n ],\n [\n -155.2708911895752,\n 19.4313863587134\n ],\n [\n -155.27406692504883,\n 19.432033891986865\n ],\n [\n -155.2799892425537,\n 19.429605628899985\n ],\n [\n -155.28857231140134,\n 19.42013505603468\n ],\n [\n -155.29492378234863,\n 19.416492381036047\n ],\n [\n -155.2946662902832,\n 19.413416280797698\n ],\n [\n -155.29646873474118,\n 19.410663931248664\n ],\n [\n -155.29698371887207,\n 19.407021044033193\n ],\n [\n -155.29131889343262,\n 19.396901484778134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoversten, G.M.","contributorId":295409,"corporation":false,"usgs":false,"family":"Hoversten","given":"G.M.","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":849391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gasperikova, Erika","contributorId":193561,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","affiliations":[],"preferred":false,"id":849392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackie, Randall","contributorId":295410,"corporation":false,"usgs":false,"family":"Mackie","given":"Randall","email":"","affiliations":[{"id":63861,"text":"CGG Multiphysics","active":true,"usgs":false}],"preferred":false,"id":849393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myer, David","contributorId":206497,"corporation":false,"usgs":false,"family":"Myer","given":"David","email":"","affiliations":[],"preferred":false,"id":849394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauahikaua, James P. 0000-0003-3777-503X jimk@usgs.gov","orcid":"https://orcid.org/0000-0003-3777-503X","contributorId":2146,"corporation":false,"usgs":true,"family":"Kauahikaua","given":"James","email":"jimk@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":849395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Greg A.","contributorId":295412,"corporation":false,"usgs":false,"family":"Newman","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":63862,"text":"Lawrence Berkeley National Laboratory, Sandia National Laboratory","active":true,"usgs":false}],"preferred":false,"id":849396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cuevas, Nestor","contributorId":295414,"corporation":false,"usgs":false,"family":"Cuevas","given":"Nestor","email":"","affiliations":[{"id":63864,"text":"Electromagnetic Instruments","active":true,"usgs":false}],"preferred":false,"id":849397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256645,"text":"70256645 - 2022 - Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment","interactions":[],"lastModifiedDate":"2024-08-29T14:15:54.163395","indexId":"70256645","displayToPublicDate":"2022-08-22T09:10:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment","docAbstract":"Greater Prairie-chickens (Tympanuchus cupido) historically occupied 20 states within the contiguous United States; however, due to habitat degradation and loss, they are currently found in 11 states, only four of which have a stable population. Kansas supports a relatively large abundance of Greater Prairie-chickens, where the Flint Hills ecoregion historically supported the largest population density of all ecoregions. In the past decade, the Flint Hills population has declined by 75 % to an estimated 8,334 individuals in 2021 from 34,180 individuals in 2015 due to landscape changes and intensification of grassland management practices. The Fort Riley Military Reservation in the northwest portion of the Flint Hills ecoregion is one of a few areas within the ecoregion that does not implement grazing or vast annual burning. The Greater Prairie-chicken population within Fort Riley has remained relatively stable over the past 25 years despite being constrained by surrounding landscape features and development. We analyzed multiple scales of resource selection by 46 female Greater Prairie-chickens during March-April 2019–2021 on Fort Riley to investigate why this population is doing relatively well compared to populations in surrounding areas. We tested landscape feature, vegetation, and burn mosaic variables to evaluate which variables had the greatest influence on resource selection. Landscape features had the greatest influence on resource selection. Females avoided trees within Fort Riley for both breeding season use and nest-site selection at a greater margin than any other study in Kansas. Additionally, fourth-order selection was not evident within this study system, contrary to studies within surrounding areas. Our findings join a growing body of literature that suggests containment of woody encroachment as a high priority for managers to maintain or expand prairie grouse habitat in many different environments. This containment is especially critical on Fort Riley because of its constrained environment, and further woody encroachment could lead to loss of habitat that is inescapable by the Greater Prairie-chicken population on Fort Riley. Spatially-explicit evaluations of habitat availability are increasingly important as more areas within the Greater Prairie-chicken range become constrained by urbanization, agricultural expansion, and intensive management practices.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02267","usgsCitation":"Gehrt, J., Moon, D.A., Stratton, S.C., and Haukos, D.A., 2022, Role of landscape features in resource selection by female Greater Prairie-chickens within a constrained environment: Global Ecology and Conservation, v. 38, e02267, 13 p., https://doi.org/10.1016/j.gecco.2022.e02267.","productDescription":"e02267, 13 p.","ipdsId":"IP-139155","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446703,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02267","text":"Publisher Index Page"},{"id":433302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Fort Riley Military Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.82607950738709,\n 39.04415304738848\n ],\n [\n -96.82067969589669,\n 39.04542338932923\n ],\n [\n -96.81264803264634,\n 39.066451102696\n ],\n [\n -96.7923343945162,\n 39.058185802106635\n ],\n [\n -96.76938890462613,\n 39.05945727775277\n ],\n [\n -96.75305336218368,\n 39.08838501409363\n ],\n [\n -96.73759510366125,\n 39.078835126800456\n ],\n [\n -96.70508270366084,\n 39.09431408766408\n ],\n [\n -96.7173117835789,\n 39.13021716548451\n ],\n [\n -96.68243974776027,\n 39.13008052495802\n ],\n [\n -96.68090450090028,\n 39.20341992876942\n ],\n [\n -96.84367647787,\n 39.301076682296724\n ],\n [\n -96.95952320021819,\n 39.3101541162184\n ],\n [\n -96.96098961442516,\n 39.209101370407836\n ],\n [\n -96.90984125155101,\n 39.18116605625954\n ],\n [\n -96.88033683304346,\n 39.18182625944928\n ],\n [\n -96.88913531828524,\n 39.15454056170077\n ],\n [\n -96.87740400462953,\n 39.13975638913726\n ],\n [\n -96.83047875000798,\n 39.137481625428194\n ],\n [\n -96.86753927807851,\n 39.07132797338471\n ],\n [\n -96.82607950738709,\n 39.04415304738848\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gehrt, Jacquelyn M.","contributorId":341459,"corporation":false,"usgs":false,"family":"Gehrt","given":"Jacquelyn M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moon, Derek A.","contributorId":341460,"corporation":false,"usgs":false,"family":"Moon","given":"Derek","email":"","middleInitial":"A.","affiliations":[{"id":81742,"text":"Fort Riley Environmental Division","active":true,"usgs":false}],"preferred":false,"id":908460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Shawn C.","contributorId":341461,"corporation":false,"usgs":false,"family":"Stratton","given":"Shawn","email":"","middleInitial":"C.","affiliations":[{"id":81743,"text":"Fort Riley Training Division","active":true,"usgs":false}],"preferred":false,"id":908461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908462,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255669,"text":"70255669 - 2022 - GSPy: A new toolbox and data standard for Geophysical Datasets","interactions":[],"lastModifiedDate":"2026-03-10T13:23:35.700958","indexId":"70255669","displayToPublicDate":"2022-08-22T06:45:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17985,"text":"Frontiers in Earth Science - Environmental Informatics and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"GSPy: A new toolbox and data standard for Geophysical Datasets","docAbstract":"The diversity of geophysical methods and datatypes, as well as the isolated nature of various specialties (e.g., electromagnetic, seismic, potential fields) leads to a profusion of separate data file formats and documentation conventions. This can hinder cooperation and reduce the impact of datasets researchers have invested in heavily to collect and prepare. An open, portable, and well-supported community data standard could greatly improve the interoperability, transferability, and long-term archival of geophysical data. Airborne geophysical methods particularly need an open and accessible data standard, and they exemplify the complexity that is common in geophysical datasets where critical auxiliary information on the survey and system parameters are required to fully utilize and understand the data. Here, we propose a new Geophysical Standard, termed the GS convention, that leverages the well-established and widely used NetCDF file format and builds on the Climate and Forecasts (CF) metadata convention. We also present an accompanying open-source Python package, GSPy, to provide methods and workflows for building the GS-standardized NetCDF files, importing and exporting between common data formats, preparing input files for geophysical inversion software, and visualizing data and inverted models. By using the NetCDF format, handled through the Xarray Python package, and following the CF conventions, we standardize how metadata is recorded and directly stored with the data, from general survey and system information down to specific variable attributes. Utilizing the hierarchical nature of NetCDF, GS-formatted files are organized with a root Survey group that contains global metadata about the geophysical survey. Data are then organized into subgroups beneath Survey and are categorized as Tabular or Raster depending on the geometry and point of origin for the data. Lastly, the standard ensures consistency in constructing and tracking coordinate reference systems, which is vital for accurate portability and analysis. Development and adoption of a NetCDF-based data standard for geophysical surveys can greatly improve how these complex datasets are shared and utilized, making the data more accessible to a broader science community. The architecture of GSPy can be easily transferred to additional geophysical datatypes and methods in future releases.
A paucity of detailed relative sea-level (RSL) reconstructions from low latitudes hinders efforts to understand the global, regional, and local processes that cause RSL change. We reconstruct RSL change during the past ~5 ka using cores of mangrove peat at two sites (Snipe Key and Swan Key) in the Florida Keys. Remote sensing and field surveys established the relationship between peat-forming mangroves and tidal elevation in South Florida. Core chronologies are developed from age-depth models applied to 72 radiocarbon dates (39 mangrove wood macrofossils and 33 fine-fraction bulk peat). RSL rose 3.7 m at Snipe Key and 5.0 m at Swan Key in the past 5 ka, with both sites recording the fastest century-scale rate of RSL rise since ~1900 CE (~2.1 mm/a). We demonstrate that it is feasible to produce near-continuous reconstructions of RSL from mangrove peat in regions with a microtidal regime and accommodation space created by millennial-scale RSL rise. Decomposition of RSL trends from a network of reconstructions across South Florida using a spatio-temporal model suggests that Snipe Key was representative of regional RSL trends, but Swan Key was influenced by an additional local-scale process acting over at least the past five millennia. Geotechnical analysis of modern and buried mangrove peat indicates that sediment compaction is not the local-scale process responsible for the exaggerated RSL rise at Swan Key. The substantial difference in RSL between two nearby sites highlights the critical need for within-region replication of RSL reconstructions to avoid misattribution of sea-level trends, which could also have implications for geophysical modeling studies using RSL data for model tuning and validation.
Large-area, high-resolution digital elevation models (DEMs) created from light detection and ranging (LIDAR) and/or multibeam echosounder data sets are commonly used in many scientific disciplines. These DEMs can span thousands of square kilometers, typically with a spatial resolution of 1 m or finer, and can be difficult to process and analyze without specialized computers and software. Such DEMs often can be subsampled to expedite analysis with negligible impact on results for large-scale geospatial analyses. Subsampling can be achieved by creating a grid of points that specify the locations from which to extract elevation values from the DEM. This paper presents a method that can be used to accurately perform subsampling of large-scale, high-resolution DEMs using GIS software. This subsampling method was applied to two LIDAR-derived DEMs encompassing 242 km2 of the northern Florida Reef Tract as an example application and to test subsampling accuracy. Results indicate that subsampling 1-m-resolution DEMs using a 2-m-spaced grid results in no significant difference in mean elevation or other basic statistics for analyses performed over multiple spatial scales ranging from 1 km2 to 242 km2.
An uncrewed aerial vehicle (UAV) multirotor aeromagnetic system using a 5-m sling load for a magnetic sensor system is described and characterized. Four magnetic surveys with identical flight lines were completed, at two nominal altitudes of 25 and 40 m. The surveys were used to assess the repeatability of data collected with the described UAV aeromagnetic system, and comparison with a ground survey was used to assess the precision. The 5-m sling is designed to reduce magnetic interference from the UAV. A magnetic compensation model was developed for this particular UAV aeromagnetic system. This custom compensation model reduces the noise in the collected data by a factor of five over the uncompensated data, and the 5-m sling further reduces the noise by an estimated factor of four over a similar system with a 3-m sling. The precision of the UAV aeromagnetic system was then estimated to be sub-nT, with 50% of the noise component <0.3 nT, and 90% <0.6 nT.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2022.104779","usgsCitation":"Phelps, G., Bracken, R.E., Spritzer, J., and White, D.S., 2022, Achieving sub-nanoTesla precision in multirotor UAV aeromagnetic surveys: Journal of Applied Geophysics, v. 206, 104779, 16 p., https://doi.org/10.1016/j.jappgeo.2022.104779.","productDescription":"104779, 16 p.","ipdsId":"IP-130875","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446713,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jappgeo.2022.104779","text":"Publisher Index Page"},{"id":435723,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HCY1NQ","text":"USGS data release","linkHelpText":"UASmagpy: Python code for compensating rotary-wing sling-load UAS aeromagnetic data"},{"id":435722,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92MXMM5","text":"USGS data release","linkHelpText":"Uncrewed aerial system aeromagnetic test survey at the Boulder Magnetic Observatory"},{"id":411343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":860859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bracken, Robert E. 0000-0001-7759-2743 rbracken@usgs.gov","orcid":"https://orcid.org/0000-0001-7759-2743","contributorId":2640,"corporation":false,"usgs":true,"family":"Bracken","given":"Robert","email":"rbracken@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spritzer, John 0000-0002-2147-530X jspritzer@usgs.gov","orcid":"https://orcid.org/0000-0002-2147-530X","contributorId":244361,"corporation":false,"usgs":true,"family":"Spritzer","given":"John","email":"jspritzer@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, David S.","contributorId":173069,"corporation":false,"usgs":false,"family":"White","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":860862,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237919,"text":"70237919 - 2022 - Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough","interactions":[],"lastModifiedDate":"2022-11-01T13:50:50.001339","indexId":"70237919","displayToPublicDate":"2022-08-21T08:28:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough","docAbstract":"Estuaries are among the most productive of aquatic ecosystems. Yet the collective understanding of patterns and drivers of primary production in estuaries is incomplete, in part due to complex hydrodynamics and multiple controlling factors that vary at a range of temporal and spatial scales. A whole-ecosystem experiment was conducted in a deep, pelagically dominated terminal channel of the Sacramento-San Joaquin Delta (California, USA) that seasonally appears to become nitrogen limited, to test whether adding calcium nitrate would stimulate primary productivity or increase phytoplankton density. Production did not respond consistently to fertilization, in part because nitrate and phytoplankton were dispersed away from the manipulated area within 1–3 days. Temporal and spatial patterns of gross primary production were more strongly related to stratification and light availability (i.e., turbidity) than nitrogen, highlighting the role of hydrodynamics in regulating system production. Similarly, chlorophyll was positively related not only to stratification but also to nitrogen—with a positive interaction—suggesting stratification may trigger nutrient limitation. The average rate of primary production (4.3 g O2 m−2 d−1), metabolic N demand (0.023 mg N L−1 d−1), and ambient dissolved inorganic nitrogen concentration (0.03 mg N L−1) indicate that nitrogen can become limiting in time and space, especially during episodic stratification events when phytoplankton are isolated within the photic zone, or farther upstream where water clarity increases, dispersive flux decreases, and stratification is stronger and more frequent. The role of hydrodynamics in organizing habitat connectivity and regulating physical and chemical processes at multiple temporal and spatial scales is critical for determining resource availability and evaluating biogeochemical processes in estuaries.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-022-01111-8","usgsCitation":"Loken, L.C., Sadro, S., Lenoch, L., Stumpner, P., Dahlgren, R.A., Burau, J.R., and Van Nieuwenhuyse, E.E., 2022, Whole-ecosystem experiment illustrates short timescale hydrodynamic, light, and nutrient control of primary production in a terminal slough: Estuaries and Coasts, v. 45, p. 2428-2449, https://doi.org/10.1007/s12237-022-01111-8.","productDescription":"22 p.","startPage":"2428","endPage":"2449","ipdsId":"IP-136358","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":446716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-022-01111-8","text":"Publisher Index Page"},{"id":408986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Deep Water Ship Channel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5493802954393,\n 38.55374191573719\n ],\n [\n -121.70672314658754,\n 38.55374191573719\n ],\n [\n -121.70672314658754,\n 38.26810056353631\n ],\n [\n -121.5493802954393,\n 38.26810056353631\n ],\n [\n -121.5493802954393,\n 38.55374191573719\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2022-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":856204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lenoch, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":270181,"corporation":false,"usgs":true,"family":"Lenoch","given":"Leah","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahlgren, Randy A 0000-0002-8961-875X","orcid":"https://orcid.org/0000-0002-8961-875X","contributorId":269424,"corporation":false,"usgs":false,"family":"Dahlgren","given":"Randy","email":"","middleInitial":"A","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":856207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Nieuwenhuyse, Erwin E 0000-0002-9032-2681","orcid":"https://orcid.org/0000-0002-9032-2681","contributorId":269423,"corporation":false,"usgs":false,"family":"Van Nieuwenhuyse","given":"Erwin","email":"","middleInitial":"E","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":856209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242886,"text":"70242886 - 2022 - Revised earthquake recurrence intervals in California, USA: New paleoseismic sites and application of event likelihoods","interactions":[],"lastModifiedDate":"2023-04-21T12:02:06.957613","indexId":"70242886","displayToPublicDate":"2022-08-21T07:00:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Revised earthquake recurrence intervals in California, USA: New paleoseismic sites and application of event likelihoods","docAbstract":"Recurrence intervals for ground rupturing earthquakes are critical data for assessing seismic hazard. Recurrence intervals are presented here for 38 paleoseismic sites in California. Eleven of these include new or updated data; the remainder use data previously included in the Unified California Earthquake Rupture Forecast Version 3 (UCERF3). The methods and results are consistent with UCERF3. In addition, revised recurrence intervals are presented at every site. The revised recurrence intervals incorporate uncertainty in the interpretation of paleoseismic evidence, which is expressed as event likelihood. Event likelihood is the probability that the evidence has been correctly interpreted as a unique earthquake. Event likelihoods are estimated here for 85 inferred past earthquakes at eight paleoseismic sites in California, using a single, consistent methodology. The average event likelihood is 0.85. The revised recurrence intervals are 16% longer, on average, than conventional estimates, and their confidence intervals are disproportionately wider. These recurrence intervals are suitable for inclusion in a “grand inversion” rupture forecast, and they may be important for addressing a systematic misfit in the UCERF3 grand inversion. The revised recurrence intervals may also be important for assessing the unusually long earthquake hiatus in California. Other applications may not need to consider event likelihoods because the effects are small relative to typical uncertainties.
Synthesizing large, complex data sets to inform resource managers towards effective environmental stewardship is a universal challenge. In Chesapeake Bay, a well-studied and intensively monitored estuary in North America, the challenge of synthesizing data on water quality and land use as factors related to a key habitat, submerged aquatic vegetation, was tackled by a team of scientists and resource managers operating at multiple levels of governance (state, federal). The synthesis effort took place over a two-year period (2016–2018), and the results were communicated widely to a) scientists via peer review publications and conference presentations; b) resource managers via web materials and workshop presentations; and c) the public through newspaper articles, radio interviews, and podcasts. The synthesis effort was initiated by resource managers at the United States Environmental Protection Agencys’ Chesapeake Bay Program and 16 scientist participants were recruited from a diversity of organizations. Multiple short, immersive workshops were conducted regularly to conceptualize the problem, followed by data analysis and interpretation that supported the preparation of the synthetic products that were communicated widely. Reflections on the process indicate that there are a variety of structural and functional requirements, as well as enabling conditions, that need to be considered to achieve successful outcomes from synthesis efforts.
The U.S. Geological Survey maintains a network of hydrologic monitoring stations across Kansas in cooperation with Federal, State, Tribal, and local agencies. During water year 2021, this network included 230 real-time surface water data collection sites, referred to as “streamgages.” A water year is the 12-month period from October 1 through September 30 and is designated by the calendar year in which it ends. These real-time data are routinely collected and calibrated by U.S. Geological Survey personnel via regular measurements of streamflow and water levels. Analyses of these data provide an understanding of hydrologic conditions in the State critical to the management of water resources, industrial and agricultural uses, protection of life and property during flooding, operation of reservoirs, recreation, and other activities.
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U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The maps and graphs in this summary describe national streamflow conditions for water year 2021 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2021 was from October 1, 2020, to September 30, 2021) in the context of streamflow ranks relative to the 92-year period of water years 1930–2021. Annual runoff in the Nation’s rivers and streams during water year 2021 (9.43 inches) was higher than the long-term (1930–2021) mean annual runoff of 9.42 inches for the contiguous United States. Nationwide, the 2021 streamflow ranked the 46th highest out of the 92 years.
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