The connection of rivers with their floodplains has been greatly reduced in agricultural drainage basins, especially in the Upper Mississippi River Basin. The restriction of the Mississippi River from its floodplain has reduced the sediment trapping and nutrient deposition capabilities of the floodplain, exacerbating water quality problems in the river and in downstream waterbodies. A small part of the Maquoketa River, a tributary to the Upper Mississippi River, was permanently reconnected to its floodplain in 2010 when a levee failure resulted in breaches in two locations. This study quantified the water quality benefits of that reconnection from October 2013 through September 2018. As part of the study, data from groundwater monitoring wells were used to determined hydraulic connectivity and surface-water/groundwater mixing; soil samples were collected in the floodplain to quantify floodplain sediment and nutrient retention potential during postflood and dry, interflood periods; and sensors were placed in the Maquoketa River to quantify total suspended solids, nitrogen, and phosphorus concentrations and loads.
The floodplain aquifer in the study area had low hydraulic gradients toward the Maquoketa (mean of 0.017) and Mississippi Rivers (mean of 0.0029) and reducing water-quality conditions (dissolved oxygen less than 1.0 milligram per liter [mg/L] and nitrate less than 0.04 mg/L as nitrogen) capable of denitrification. A specific conductance-based mixing indicated precipitation was the predominate source of groundwater; however, specific conductance-based mixing analysis was unable to distinguish between the river or direct precipitation as the source.
The floodplain was fully inundated five times during the study: in June–July 2014, March 2015, January 2017, February 2018, and September 2018. During the March 2015 flood (the only inundation event with sufficient duration to leave quantifiable sediment deposition in the study area), the equivalent of 0.91 percent of the nitrate load and 3.8 percent of the phosphorus load was deposited as sediment on the floodplain. Potential nitrogen losses on the floodplain because of denitrification ranged from 250 kilograms per day (kg/d) as nitrogen in March 2015 to 668 kg/d as nitrogen in October 2014. Potential denitrification rates indicate that when the soil is inundated, inorganic nitrogen present in the soil and in the water column is rapidly denitrified. Soil phosphorus measurements indicated that floodplain soils contain a mean of 365 milligrams per kilogram as phosphorus but still have the capacity to remove phosphorus from flood waters of the Maquoketa River depending on the surface water phosphorus concentration. Results from this study indicate that restoration of even small river-floodplain connections can improve water quality in the Upper Mississippi River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225030","collaboration":"Prepared in cooperation with the Eastern Tallgrass Prairie & Big Rivers Landscape Conservation Cooperative","usgsCitation":"Bartsch, L.A., Kreiling, R.M., Gruhn, L.R., Garrett, J.D., Richardson, W.B., and Nalley, G.M., 2022, Sediment and nutrient retention on a reconnected floodplain of an Upper Mississippi River Tributary, 2013–2018: U.S. Geological Survey Scientific Investigations Report 2022–5030, 27 p., https://doi.org/10.3133/sir20225030.","productDescription":"Report: viii, 27 p.; Data Releases; Datasets","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-121775","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":608,"text":"Upper Mississippi Science Center","active":false,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":404760,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A12PVX","text":"USGS data release","linkHelpText":"Maquoketa River floodplain-river connectivity 2014-2016 data"},{"id":404761,"rank":4,"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":404762,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://www.umesc.usgs.gov/data_library/water_quality/water_quality_data_page.html","text":"USGS Long Term Resource Monitoring Program database","linkHelpText":"—Long Term Resource Monitoring Program—Water Quality"},{"id":404757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5030/coverthb.jpg"},{"id":502387,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113356.htm","linkFileType":{"id":5,"text":"html"}},{"id":404758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5030/sir20225030.pdf","text":"Report","size":"7.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5030"}],"country":"United States","state":"Iowa","otherGeospatial":"Maquoketa River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.35,\n 42.1333\n ],\n [\n -90.2667,\n 42.1333\n ],\n [\n -90.2667,\n 42.1833\n ],\n [\n -90.35,\n 42.1833\n ],\n [\n -90.35,\n 42.1333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Less than 30% of all species reintroductions have been successful and it is important that factors associated with success or failure be identified. Officials experimentally translocated 14 adult female American black bears (Ursus americanus) from Great Smoky Mountains National Park, North Carolina and Tennessee, USA, to Big South Fork National River and Recreation Area in the Cumberland Plateau of Kentucky and Tennessee, USA, in 1996–1997. Since that time, the reintroduced bear population has continued to expand in size and range so our study objective was to use spatially explicit capture-recapture methods across a wide spatial extent to estimate bear population abundance and growth. We constructed 440 (223 in KY, 217 in TN) hair traps in our primary sampling area in 2019 arranged in clusters of 4–9 traps/cluster, which we augmented with data from 138 hair traps in a secondary sampling area in Tennessee collected in 2018. We extracted and genotyped DNA from hair samples to construct spatially explicit capture histories, using spatial covariates to model inhomogeneous densities. Population abundance estimates across our 36,035-km2 study area were 411 males and 406 females excluding cubs. Based on an initial standing population of 18 adult and subadult bears, the mean annual growth rate (λ) from 1998 to 2019 was 1.199. The mean annual harvest rate in Kentucky from 2013 to 2019 was 5.1% and in Tennessee from 2014 to 2019 was 13.2%. Based on simulations, the hunting seasons reduced mean λ from 1.217 to 1.199, but growth was rapid despite harvest. Genetic diversity was retained, with similar expected heterozygosity as in the source population. The lack of conspecifics, highly productive habitat, and an initial age and sex distribution that was skewed toward the most fecund members of the population likely contributed to the rapid growth and high levels of gene retention in this bear population.
Several mechanisms have been proposed to allow highly viscous silicic magma to outgas efficiently enough to erupt effusively. There is increasing evidence that challenges the classic foam-collapse model in which gas escapes through permeable bubble networks, and instead suggests that magmatic fracturing and/or accompanying localized fragmentation and welding within the conduit play an important role in outgassing. The 2011–2012 eruption at Cordón Caulle volcano, Chile, provides direct observations of the role of magmatic fractures. This eruption exhibited a months-long hybrid phase, in which rhyolitic lava extrusion was accompanied by vigorous gas-and-tephra venting through fractures in the lava dome surface. Some of these fractures were preserved as tuffisites (tephra-filled veins) in erupted lava and bombs. We integrate constraints from petrologic analyses of erupted products and video analyses of gas-and-tephra venting to construct a model for magma ascent in a conduit. The one-dimensional, two-phase, steady-state model considers outgassing through deforming permeable bubble networks, magmatic fractures, and adjacent wall rock. Simulations for a range of plausible magma ascent conditions indicate that the eruption of low-porosity lava observed at Cordón Caulle volcano occurs because of significant gas flux through fracture networks in the upper conduit. This modeling emphasizes the important role that outgassing through magmatic fractures plays in sustaining effusive or hybrid eruptions of silicic magma and in facilitating explosive-effusive transitions.
The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) routinely produces finite‐fault models following significant earthquakes. These models are spatiotemporal estimates of coseismic slip critical to constraining downstream response products such as ShakeMap ground motion estimates, Prompt Assessment of Global Earthquake for Response loss estimates, and ground failure assessments. Because large earthquakes can involve slip over tens to hundreds of kilometers, point‐source approximations are insufficient, and it is vital to rapidly assess the amount, timing, and location of slip along the fault. Initially, the USGS finite‐fault products were computed in the first several hours after a significant earthquake, using teleseismic body wave and surface wave observations. With only teleseismic waveforms, it is generally possible to obtain a reliable model for earthquakes of magnitude 7 and larger. Here, we detail newly implemented updates to NEIC’s modeling capabilities, specifically to allow joint modeling of local‐to‐regional strong‐motion accelerometer, Global Navigation Satellite System (GNSS), and Interferometric Synthetic Aperture Radar (InSAR) observations in addition to teleseismic waveforms. We present joint inversion results for the 2015
Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/pnasnexus/pgac115","usgsCitation":"Shuman, J.K., Balch, J.K., Barnes, R.T., Higuera, P., Roos, C.I., Schwilk, D.W., Stavros, E.N., Banerjee, T., Bela, M., Bendix, J., Bertolino, S., Bililign, S., Bladon, K.D., Brando, P., Breidenthal, R.E., Buma, B., Calhoun, D., Carvalho, L.M., Cattau, M., Cawley, K.M., Chandra, S., Chipman, M.L., Cobian, J., Conlisk, E., Coop, J., Cullen, A., Davis, K., Dayalu, A., Dolman, M., Ellsworth, L.M., Franklin, S., Guiterman, C., Hamilton, M., Hanan, E.J., Hansen, W.D., Hantson, S., Harvey, B., Holz, A., Hurteau, M., Ilangakoon, N.T., Jennings, M., Jones, C., Klimaszewski-Patterson, A., Kobziar, L., Kominoski, J., Kosovic, B., Krawchuk, M., Laris, P., Leonard, J., Loria- Salazar, S.M., Lucash, M., Mahmoud, H., Margolis, E.Q., Maxwell, T., McCarty, J., McWethy, D.B., Meyer, R., Miesel, J.R., Moser, W., Nagy, R.C., Niyogi, D., Palmer, H.M., Pellegrini, A., Poulter, B., Robertson, K., Rocha, A., Sadegh, M., De Sales, F., Santos, F., Scordo, F., Sexton, J., Sharma, A., Smith, A., Soja, A., Still, C., Swetnam, T., Syphard, A., Tingey, M.W., Tohidi, A., Trugman, A., Turetsky, M., Varner, J., Wang, Y., Whitman, T., Yelenik, S., and Zhang, X., 2022, Reimagine fire science for the anthropocene: PNAS Nexus, v. 1, no. 3, pgac115, 14 p., https://doi.org/10.1093/pnasnexus/pgac115.","productDescription":"pgac115, 14 p.","ipdsId":"IP-139388","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446940,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/pnasnexus/pgac115","text":"External Repository"},{"id":408571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Shuman, Jacquelyn K.","contributorId":298194,"corporation":false,"usgs":false,"family":"Shuman","given":"Jacquelyn","email":"","middleInitial":"K.","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":855248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Balch, Jennifer K.","contributorId":298195,"corporation":false,"usgs":false,"family":"Balch","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":855249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Rebecca T.","contributorId":298197,"corporation":false,"usgs":false,"family":"Barnes","given":"Rebecca","email":"","middleInitial":"T.","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":855250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higuera, Philip E.","contributorId":298199,"corporation":false,"usgs":false,"family":"Higuera","given":"Philip E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":855251,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roos, Christopher I.","contributorId":298201,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","email":"","middleInitial":"I.","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":855252,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwilk, Dylan W.","contributorId":298203,"corporation":false,"usgs":false,"family":"Schwilk","given":"Dylan","email":"","middleInitial":"W.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":855253,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stavros, E. 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In the last decades, the ACP landscape experienced extreme climate events and increased lake water withdrawal (LWW) for construction of infrastructure related to resource extraction (primarily ice roads and industrial operations). However, their potential (combined) effects on streamflow are relatively underexplored. Here, we applied the process-based, spatially distributed hydrological and thermal Water Balance Simulation Model (WaSiM) (10 m spatial resolution) to the 30 km² Crea Creek watershed located on the ACP. The impacts of documented seasonal climate extremes and LWW were evaluated on seasonal runoff (May-August), including minimum 7-day mean flow (MQ7), the recovery time of MQ7 to pre-perturbation conditions and the duration of streamflow conditions that prevents fish passage. Low-rainfall scenarios (21% of normal, 1 to 3 summers in a row) caused a larger reduction in MQ7 (56 - 69%) than LWW alone (44 - 58%). Decadal-long consecutive LWW resulted in a new equilibrium in low-flow and seasonal runoff after the third year of LWW that included a disconnected stream network, a reduced contributing area (54% of the watershed area) and limited fish passage throughout summer. Our results highlight that LWW is not offset by same-year snowmelt for lake water levels and streamflow as currently assumed in land management regulations. Effective land management would therefore benefit from considering the combined impact of climate change and industrial lake water withdrawals. \n\n ","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022wr032119","usgsCitation":"Gädeke, A., Arp, C., Liljedahl, A., Daanen, R., Cai, L., Alexeev, V., Jones, B., Wipfli, M.S., and Schulla, J., 2022, Modeled streamflow response to scenarios of Tundra Lake water withdrawal and seasonal climate extremes, Arctic Coastal Plain, Alaska: Water Resources Research, v. 58, no. 8, e2022WR032119, 19 p., https://doi.org/10.1029/2022wr032119.","productDescription":"e2022WR032119, 19 p.","ipdsId":"IP-126871","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr032119","text":"Publisher Index Page"},{"id":486512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.42580071682042,\n 70.81109388282138\n ],\n [\n -155.42580071682042,\n 69.72800714139643\n ],\n [\n -150.42311039636033,\n 69.72800714139643\n ],\n [\n -150.42311039636033,\n 70.81109388282138\n ],\n [\n -155.42580071682042,\n 70.81109388282138\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gädeke, Anne","contributorId":355846,"corporation":false,"usgs":false,"family":"Gädeke","given":"Anne","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher","contributorId":355847,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liljedahl, Anna K.","contributorId":355848,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna K.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daanen, Ronald P.","contributorId":355849,"corporation":false,"usgs":false,"family":"Daanen","given":"Ronald P.","affiliations":[{"id":84845,"text":"Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":938267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cai, Lei","contributorId":355850,"corporation":false,"usgs":false,"family":"Cai","given":"Lei","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexeev, Vladimir","contributorId":355851,"corporation":false,"usgs":false,"family":"Alexeev","given":"Vladimir","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Benjamin","contributorId":355852,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schulla, Jörg","contributorId":355853,"corporation":false,"usgs":false,"family":"Schulla","given":"Jörg","affiliations":[{"id":84846,"text":"Hydrology Software Consulting","active":true,"usgs":false}],"preferred":false,"id":938271,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70234224,"text":"fs20223052 - 2022 - Groundwater resources of the Harney Basin, southeastern Oregon","interactions":[],"lastModifiedDate":"2025-08-14T19:34:27.315056","indexId":"fs20223052","displayToPublicDate":"2022-08-03T15:24:49","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3052","displayTitle":"Groundwater Resources of the Harney Basin, Southeastern Oregon","title":"Groundwater resources of the Harney Basin, southeastern Oregon","docAbstract":"In response to increasing groundwater demand and declining groundwater levels in the Harney Basin of southeastern Oregon, the U.S. Geological Survey and the Oregon Water Resources Department conducted a cooperative groundwater-availability study during 2016–22. This Fact Sheet summarizes the results of this study. Full details of the study are provided in Gingerich and others (2022a, 2022b), Garcia and others (2022), and the other supporting documents listed on the last page of this Fact Sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223052","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gingerich, S.B., Garcia, C.A., and Johnson, H.M., 2022, Groundwater resources of the Harney Basin, southeastern Oregon (ver. 1.1, June 2025): U.S. Geological Survey Fact Sheet 2022–3052, 6 p., https://doi.org/10.3133/fs20223052.","productDescription":"Report: 6 p.; Data Release","ipdsId":"IP-140289","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":494145,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113361.htm","linkFileType":{"id":5,"text":"html"}},{"id":404793,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215103","text":"Scientific Investigations Report 2021–5103","description":"SIR 2021–5103","linkHelpText":"- Groundwater resources of the Harney Basin, Oregon"},{"id":404792,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215128","text":"Scientific Investigations Report 2021–5128","description":"SIR 2021–5128","linkHelpText":"- Hydrologic budget of the Harney Basin groundwater system, Oregon"},{"id":404791,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J0FE5M","text":"USGS data release","description":"USGS data release","linkHelpText":"Location information, discharge, and water-quality data for selected wells, springs, and streams in the Harney Basin, Oregon"},{"id":490440,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3052/versionHistory.txt","description":"FS 2022-3052 version history"},{"id":404790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3052/fs20223052.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3052"},{"id":404789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3052/coverthb2.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.2783203125,\n 42.39912215986002\n ],\n [\n -117.94921874999999,\n 42.39912215986002\n ],\n [\n -117.94921874999999,\n 44.276671273775186\n ],\n [\n -120.2783203125,\n 44.276671273775186\n ],\n [\n -120.2783203125,\n 42.39912215986002\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 3, 2022; Version 1.1: June 11, 2025","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
911 NE 11th Avenue
Portland, Oregon 97232
We present a method for classification of the two distinct types of electrical activity that occur during an explosive volcanic eruption: vent discharges and lightning. Vent discharges occur at the onset of an explosion and create a distinctive radio frequency signature called continual radio frequency. Seconds to minutes after the onset of the eruption, lightning begins to occur throughout the eruption column. We use logistic regression to classify a radio frequency impulse as being part of either a lightning flash or a period of continual radio frequency. The classifier uses the number of peaks in the amplitude envelope from 1 ms windows before and after the impulsive very high frequency waveform, with an average accuracy of 97.9%. We propose that this method could be used in an algorithm to determine when explosive eruptions occurred by identification of the distinctive signatures of vent discharges and lightning.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL099370","usgsCitation":"Behnke, S.A., Edens, H., Theiler, J., Swanson, D., Senay, S., Van Eaton, A.R., Iguchi, M., and Miki, D., 2022, Discriminating types of volcanic electrical activity: Toward an eruption detection algorithm: Geophysical Research Letters, v. 49, e2022GL099370, 9 p., https://doi.org/10.1029/2022GL099370.","productDescription":"e2022GL099370, 9 p.","ipdsId":"IP-143042","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl099370","text":"Publisher Index Page"},{"id":466639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationDate":"2022-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Behnke, Sonja A.","contributorId":311230,"corporation":false,"usgs":false,"family":"Behnke","given":"Sonja","email":"","middleInitial":"A.","affiliations":[{"id":67364,"text":"Los Alamos National Laboratory, Los Alamos, New Mexico, USA","active":true,"usgs":false}],"preferred":false,"id":924023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edens, Harald E.","contributorId":349118,"corporation":false,"usgs":false,"family":"Edens","given":"Harald E.","affiliations":[{"id":83434,"text":"Los Alamos National Laboratory, USA","active":true,"usgs":false}],"preferred":false,"id":924024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Theiler, James","contributorId":349119,"corporation":false,"usgs":false,"family":"Theiler","given":"James","affiliations":[{"id":83434,"text":"Los Alamos National Laboratory, USA","active":true,"usgs":false}],"preferred":false,"id":924025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, D.J.","contributorId":349120,"corporation":false,"usgs":false,"family":"Swanson","given":"D.J.","affiliations":[{"id":83434,"text":"Los Alamos National Laboratory, USA","active":true,"usgs":false}],"preferred":false,"id":924026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senay, S.","contributorId":349121,"corporation":false,"usgs":false,"family":"Senay","given":"S.","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":924027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Iguchi, Masato","contributorId":219556,"corporation":false,"usgs":false,"family":"Iguchi","given":"Masato","email":"","affiliations":[{"id":37321,"text":"University of Kyoto","active":true,"usgs":false}],"preferred":false,"id":924029,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miki, D.","contributorId":349122,"corporation":false,"usgs":false,"family":"Miki","given":"D.","affiliations":[{"id":83437,"text":"Sakurajima Volcano Research Center, Disaster Prevention Research Institute, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":924030,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70256656,"text":"70256656 - 2022 - Are we falling short on restoring oysters at a regional scale?","interactions":[],"lastModifiedDate":"2024-08-29T15:26:43.155388","indexId":"70256656","displayToPublicDate":"2022-08-03T10:22:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Are we falling short on restoring oysters at a regional scale?","docAbstract":"Across coastal areas of the northern Gulf of Mexico, the Deepwater Horizon oil spill resulted in significant ecological injury, and over 8 billion USD directed to restoration activities. Oyster restoration projects were implemented with regional goals of restoring oyster abundance, spawning stock, and population resilience. Measuring regional or large-scale ecosystem restoration outcomes challenges traditional project-specific monitoring and outcome reporting. We examine the outcomes of oyster restoration at the project-level and discuss potential pathways to measure progress toward region-level goals. An estimated 15 km2 of oyster habitat was restored across 11 different estuaries with 62 individual reef footprints created, ranging in size from ~0.2 to 1.45 km2. Individual sites were distributed across the salinity gradient, and all reefs were subtidal. One-year post-restoration, mean total oyster density across all sites was 53.0 ± 60.7 ind m−2 of which 38.4 ± 42.2 ind m−2 were adult (>25 mm shell height) oysters. Recent data (2018/2019) available for all sites indicates reduced densities of total oysters (44.6 ± 70.9 ind m−2) and adult oysters (14.6 ± 21.6 ind m−2). These data provide insight into project specific outcomes, suggesting an overall enhancement in oyster abundance compared to pre-restoration, but fall short of informing outcomes at the regional-level that incorporate cumulative effects on adjacent and connected reef populations, or inform overall resiliency of the regional oyster resource. Developing regional outcome benchmarks that enable assessment of cumulative and synergistic impacts of individual projects may benefit from broader spatial and temporal monitoring requirements that can better inform development of regional tools or models. Such tools would enable cumulative effects analyses examining net resource change, resilience and assess impacts of restoration activities on regional resource status.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-022-01691-y","usgsCitation":"La Peyre, M., Marshall, D.A., Buie, S.C., Hijuelos, A., and Steyer, G., 2022, Are we falling short on restoring oysters at a regional scale?: Environmental Management, v. 70, p. 581-592, https://doi.org/10.1007/s00267-022-01691-y.","productDescription":"12 p.","startPage":"581","endPage":"592","ipdsId":"IP-138828","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.36958808470514,\n 24.1126519217827\n ],\n [\n -80.85940900302997,\n 24.714635678707992\n ],\n [\n -81.10116830711196,\n 25.46706673170469\n ],\n [\n -82.39537707405206,\n 27.091011945078975\n ],\n [\n -82.65786309241751,\n 28.308364041898628\n ],\n [\n -82.5772062119935,\n 28.999162563752748\n ],\n [\n -83.9904926193391,\n 30.19347675768212\n ],\n [\n -85.07008045187222,\n 29.677396598341033\n ],\n [\n -86.43938452544526,\n 30.518697342417497\n ],\n [\n -87.63633030899686,\n 30.340763113128546\n ],\n [\n -88.02876199353206,\n 30.727492702231586\n ],\n [\n -88.68357561069969,\n 30.436884709045927\n ],\n [\n -89.8845804986809,\n 30.130244087006545\n ],\n [\n -89.88022780179678,\n 29.65775338151731\n ],\n [\n -94.0525922925487,\n 29.622956144774975\n ],\n [\n -96.92033720263936,\n 28.066156015973654\n ],\n [\n -97.46297846111713,\n 26.978138281620108\n ],\n [\n -97.21131853158765,\n 25.94538903066173\n ],\n [\n -83.36958808470514,\n 24.1126519217827\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buie, Sarah Catherine Leblanc","contributorId":341510,"corporation":false,"usgs":false,"family":"Buie","given":"Sarah","email":"","middleInitial":"Catherine Leblanc","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hijuelos, Ann","contributorId":341511,"corporation":false,"usgs":false,"family":"Hijuelos","given":"Ann","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":908526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steyer, Gregory 0000-0001-7231-0110","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":218813,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":908527,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70235782,"text":"70235782 - 2022 - Morbidity and mortality of Hawaiin geese (Branta sandvicensis) and Laysan albatross (Phoebastria immutabilis) associated with reticuloendotheliosis virus","interactions":[],"lastModifiedDate":"2022-12-01T16:04:35.947395","indexId":"70235782","displayToPublicDate":"2022-08-03T07:22:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Morbidity and mortality of Hawaiin geese (Branta sandvicensis) and Laysan albatross (Phoebastria immutabilis) associated with reticuloendotheliosis virus","title":"Morbidity and mortality of Hawaiin geese (Branta sandvicensis) and Laysan albatross (Phoebastria immutabilis) associated with reticuloendotheliosis virus","docAbstract":"Only one virus, Avipox, has been documented previously in wild birds in Hawaii. Using immunohistochemistry and PCR, we found that two native threatened Hawaiian Geese (Branta sandvicensis), one with multicentric histiocytoma and the other with toxoplasmosis, and one Laysan Albatross (Phoebastria immutabilis) with avian pox were infected with reticuloendotheliosis virus (REV). The virus was isolated from one of the geese by cell culture. Surveys of other Hawaiian geese with various pathologies, avian pox cases, and pox viral isolates using PCR failed to reveal REV, suggesting that the virus is uncommon, at least in samples examined. The full genome of the Gag, Pol, and Env genes were sequenced for all three infected birds and revealed geographic divergence of the Pol gene, suggesting it to be under strong selective pressure. Our finding of REV in Hawaii makes this only the second virus documented in native Hawaiian birds associated with pathology. Moreover, the presence of REV in a pelagic seabird is unusual. Future surveys should seek the reservoir of the virus in efforts to trace its origins.
Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS-based hydrologic regions discern process differences across a data-sparse and hydrologically diverse landscape. Process importance rankings from random forest-derived BCs provided model-independent information for making modeling decisions.
As sustainable development practitioners have worked to “ensure healthy lives and promote well-being for all” and “conserve life on land and below water”, what progress has been made with win–win interventions that reduce human infectious disease burdens while advancing conservation goals? Using a systematic literature review, we identified 46 proposed solutions, which we then investigated individually using targeted literature reviews. The proposed solutions addressed diverse conservation threats and human infectious diseases, and thus, the proposed interventions varied in scale, costs, and impacts. Some potential solutions had medium-quality to high-quality evidence for previous success in achieving proposed impacts in one or both sectors. However, there were notable evidence gaps within and among solutions, highlighting opportunities for further research and adaptive implementation. Stakeholders seeking win–win interventions can explore this Review and an online database to find and tailor a relevant solution or brainstorm new solutions.
We investigate the shallow plumbing system of the Deccan Traps Large Igneous Province using rock and mineral data from Giant Plagioclase Basalt (GPB) lava flows from around the entire province, but with a focus on the Saurashtra Peninsula, the Malwa Plateau, and the base and top of the Western Ghats (WG) lava pile. GPB lavas in the WG typically occur at the transition between chemically distinct basalt formations. Most GPB samples are evolved basalts, with high Fe and Ti contents, and show major and trace elements and Sr-Nd-Pb isotopic compositions generally similar to those of previously studied Deccan basalts. Major element modeling suggests that high-Fe, evolved melts typical of GPB basalts may derive from less evolved Deccan basalts by low-pressure fractional crystallization in a generally dry magmatic plumbing system. The basalts are strongly porphyritic, with 6–25% of mm- to cm-sized plagioclase megacrysts, frequently occurring as crystal clots, plus relatively rare olivine and clinopyroxene. The plagioclase crystals are mostly labradoritic, but some show bytownitic cores (general range of anorthite mol%: 78–55). A common feature is a strong Fe enrichment at the plagioclase rims, indicating interaction with an Fe-rich melt similar to that represented by the matrix compositions (FeOt up to 16–17 wt%). Plagioclase minor and trace elements and Sr isotopic compositions analyzed by laser ablation inductively coupled plasma mass spectrometry show evidence of a hybrid and magma mixing origin. In particular, several plagioclase crystals show variable 87Sr/86Sri, which only partially overlaps with the 87Sr/86Sri of the surrounding matrix. Diffusion modeling suggests residence times of decades to centuries for most plagioclase megacrysts. Notably, some plagioclase crystal clots show textural evidence of deformation as recorded by electron back-scatter diffraction analyses and chemical maps, which suggest that the plagioclase megacrysts were deformed in a crystal-rich environment in the presence of melt. We interpret the plagioclase megacrysts as remnants of a crystal mush originally formed in the shallow plumbing system of the Deccan basalts. In this environment, plagioclase acquired a zoned composition due to the arrival of chemically distinct basaltic magmas. Prior to eruption, a rapidly rising but dense Fe-rich magma was capable of disrupting the shallow level crystal mush, remobilizing part of it and carrying a cargo of buoyant plagioclase megacrysts. Our findings suggest that basaltic magmas from the Deccan Traps, and possibly from LIPs in general, are produced within complex transcrustal magmatic plumbing systems with widespread crystal mushes developed in the shallow crust.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egac075","usgsCitation":"Marzoli, A., Renne, P.R., Andreasen, R., Spiess, R., Chiaradia, M., Ruth, D.C., Tholt, A., Pande, K., and Costa, F.J., 2022, The Shallow Magmatic Plumbing System of the Deccan Traps, Evidence from Plagioclase Megacrysts and Their Host Lavas: Journal of Petrology, v. 63, no. 9, egac075, https://doi.org/10.1093/petrology/egac075.","productDescription":"egac075","ipdsId":"IP-137938","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":489006,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/28790e6d-08a1-4f02-b893-195df971663e","text":"External Repository"},{"id":463238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Marzoli, A.","contributorId":167328,"corporation":false,"usgs":false,"family":"Marzoli","given":"A.","email":"","affiliations":[{"id":24687,"text":"Universitá Degli Studi di Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":916902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Renne, Paul R. 0000-0003-1769-5235","orcid":"https://orcid.org/0000-0003-1769-5235","contributorId":229577,"corporation":false,"usgs":false,"family":"Renne","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":37390,"text":"Department of Earth and Planetary Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":916903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andreasen, R","contributorId":345557,"corporation":false,"usgs":false,"family":"Andreasen","given":"R","email":"","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":916904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spiess, R","contributorId":345558,"corporation":false,"usgs":false,"family":"Spiess","given":"R","email":"","affiliations":[{"id":82629,"text":"Universita di Padova","active":true,"usgs":false}],"preferred":false,"id":916905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiaradia, M","contributorId":345561,"corporation":false,"usgs":false,"family":"Chiaradia","given":"M","email":"","affiliations":[{"id":82630,"text":"Universite de Geneve","active":true,"usgs":false}],"preferred":false,"id":916906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruth, Dawn Catherine Sweeney 0000-0001-9369-9364","orcid":"https://orcid.org/0000-0001-9369-9364","contributorId":334908,"corporation":false,"usgs":true,"family":"Ruth","given":"Dawn","email":"","middleInitial":"Catherine Sweeney","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916907,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tholt, A.J.","contributorId":345562,"corporation":false,"usgs":false,"family":"Tholt","given":"A.J.","email":"","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":916908,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pande, K","contributorId":345563,"corporation":false,"usgs":false,"family":"Pande","given":"K","email":"","affiliations":[{"id":7210,"text":"Indian Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916909,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Costa, Fabio J. V.","contributorId":289278,"corporation":false,"usgs":false,"family":"Costa","given":"Fabio","email":"","middleInitial":"J. V.","affiliations":[{"id":62093,"text":"Policia Federal","active":true,"usgs":false}],"preferred":false,"id":916910,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70263067,"text":"70263067 - 2022 - Juvenile salmon habitat use drives variation in growth and highlights vulnerability to river fragmentation","interactions":[],"lastModifiedDate":"2025-01-29T15:37:00.8291","indexId":"70263067","displayToPublicDate":"2022-08-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile salmon habitat use drives variation in growth and highlights vulnerability to river fragmentation","docAbstract":"Widespread stream network fragmentation from dams and culverts has altered habitat connectivity in river ecosystems and presents an acute threat to migratory fish. To support watershed management for an iconic migratory fish group, we assessed juvenile salmon growth outcomes across habitat use strategies and characterized how these life histories may be impacted by stream connectivity loss. Juvenile coho salmon (Oncorhynchus kisutch) in the Big Lake drainage, Alaska, USA, were individually tracked over 2012–2013 and categorized into habitat use behaviors, with fish either remaining in streams throughout freshwater residency or migrating seasonally to overwinter in lake habitats. Size, growth rate, and body condition of smolts (n = 1113) were compared across habitat use strategies. Juvenile coho salmon that moved seasonally to lake overwintering habitats, the most frequently observed strategy, grew faster and were significantly larger as smolts compared to their counterparts who remained in streams exclusively (spring Age 1 fish: 18% larger by weight, 9% faster growth rate; spring Age 2+ fish: 26% heavier, 11% faster growth). Environmental data from a subset of overwinter lakes indicate that greater foraging opportunity and lower energy costs may be implicated in growth advantages conferred by lentic overwintering strategies. Habitat use strategies requiring seasonal migrations, however, increased exposure to stream connectivity loss, and fish blocked from accessing a potential overwinter headwater lake by a culvert and dam had lowest body condition among study groups. Stream network fragmentation restricts access to preferred overwinter habitats, and our findings suggest this may constrain freshwater rearing strategies associated with strong juvenile coho salmon growth. As size at smolt has been implicated as a driver of salmon survival through ocean residency, reduced freshwater habitat connectivity during juvenile stages may have deleterious impacts on later marine life stages. Consequently, conservation of stream connectivity across lentic and lotic habitats represents an important watershed management priority for juvenile salmon.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4192","usgsCitation":"Sethi, S., Carey, M.P., Gerken, J., Harris, B., Wolf, N., Cunningham, C., Restrepo, F., and Ashline, J., 2022, Juvenile salmon habitat use drives variation in growth and highlights vulnerability to river fragmentation: Ecosphere, v. 13, no. 8, e4192, 14 p., https://doi.org/10.1002/ecs2.4192.","productDescription":"e4192, 14 p.","ipdsId":"IP-132334","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4192","text":"Publisher Index Page"},{"id":481452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Big Lake watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.98177488959556,\n 61.59244437152677\n ],\n [\n -149.98177488959556,\n 61.46764452271171\n ],\n [\n -149.59522554516565,\n 61.46764452271171\n ],\n [\n -149.59522554516565,\n 61.59244437152677\n ],\n [\n -149.98177488959556,\n 61.59244437152677\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":925436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerken, Jonathon","contributorId":350130,"corporation":false,"usgs":false,"family":"Gerken","given":"Jonathon","affiliations":[{"id":12428,"text":"U. 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Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":925437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Bradley P.","contributorId":350131,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley P.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Nathan","contributorId":350132,"corporation":false,"usgs":false,"family":"Wolf","given":"Nathan","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunningham, Curry","contributorId":350133,"corporation":false,"usgs":false,"family":"Cunningham","given":"Curry","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Restrepo, Felipe","contributorId":350134,"corporation":false,"usgs":false,"family":"Restrepo","given":"Felipe","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925441,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ashline, Josh","contributorId":350135,"corporation":false,"usgs":false,"family":"Ashline","given":"Josh","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925442,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70234174,"text":"sir20225063 - 2022 - Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington","interactions":[],"lastModifiedDate":"2022-08-03T11:00:43.649803","indexId":"sir20225063","displayToPublicDate":"2022-08-02T13:27:36","publicationYear":"2022","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":"2022-5063","displayTitle":"Longitudinal Water-Temperature Profiles in Mill Creek, Mason County, Washington","title":"Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington","docAbstract":"In streams supporting Pacific salmon (Oncorhynchus spp.) within the southern Puget Lowland, high water temperatures during late summer are a primary water-quality concern. The metabolic rates of fish and other ectothermic (in other words, cold-blooded) species are regulated by water temperature; salmon and other cold-water fish have specific thermal tolerances outside of which they are susceptible to infection, disease, increased predation, and decreased reproductive success. Mill and Gosnell Creeks, which collectively drain a 30-square mile area of the Puget Lowland in Mason County, Washington, support several species of anadromous salmonids. Whereas previous studies documented relatively cool water temperatures in Gosnell Creek, which drains the watershed upstream from Lake Isabella, water temperatures in Mill Creek, which heads at the outlet of Lake Isabella, regularly exceed thermal tolerances for cold-water fish. The occurrence and distribution of cold-water anomalies in less-than-ambient water temperatures in Mill Creek, however, have not been assessed. In this report, we present spatially and temporally continuous measurements of near-streambed water temperature measured using fiber-optic distributed temperature sensing for three reaches of Mill Creek during August–September 2020 when the water temperatures of streams in western Washington were near their annual maximum. Water temperature was collected every hour and averaged spatially over 1.015-meter sections of the fiber-optic cable deployed at the streambed of Mill Creek. The lengths of the fiber-optic cables deployed in Reaches A, B, and C were 883, 270, and 1,014 meters, respectively. Daily maximum water temperature and daily temperature variability, as measured by standard deviation of water temperature during the deployment, progressively decreased downstream as distance from Lake Isabella increased. However, no abrupt decreases in daily maximum or standard deviation of water temperature were detected in longitudinal temperature profiles of any of the three reaches. Collectively, these results suggest that warm water discharged from Lake Isabella was progressively buffered downstream as it equilibrated with downstream heat fluxes mediated by physical processes including riparian shading and diffuse groundwater input. Although parts of the surveyed reaches associated with deep pools were cooler than other locations, no large (less than 2 °C) water-temperature anomalies characteristic of discrete sources of cold groundwater or surface-water inputs were measured in any of the three surveyed reaches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225063","collaboration":"Prepared in cooperation with Squaxin Island Tribe","usgsCitation":"Gendaszek, A.S., Sheibley, R.W., Marbet, E., Puhn, J., and Seguin, C., 2022, Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington: U.S. Geological Survey Scientific Investigations Report 2022–5063, 11 p., https://doi.org/10.3133/sir20225063.","productDescription":"Report: v, 11 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132795","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404673,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RP12RQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Longitudinal profiles of water temperature in Mill Creek, Mason County, Washington, measured using fiber-optic distributed temperature sensing (FO-DTS)"},{"id":404671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5063"},{"id":404675,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.XML"},{"id":404674,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5063/images"},{"id":404670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5063/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mill Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.29750061035155,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.09490289688982\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
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Tacoma, Washington 98402
In 2019, the U.S. Geological Survey conducted a reconnaissance survey of concentrations of 41 trace elements present in bed sediment in the reservoir on the Similkameen River upstream from Enloe Dam, near Oroville, Washington. The Similkameen River drains a watershed containing highly mineralized geologic deposits with current (2019) and historical mining activity. Results of this survey indicated that surface and subsurface sediment are substantially enriched in element concentrations of silver (Ag), arsenic (As), gold (Au), bismuth (Bi), cadmium (Cd), copper (Cu), manganese (Mn), antimony (Sb), selenium (Se), tin (Sn), and tellurium (Te) relative to average concentrations found in upper continental-crustal material. Conversely, concentrations of mercury (Hg) and lead (Pb) in sediment above Enloe Dam (Enloe Reservoir) were generally less than average concentrations in upper continental-crustal material (Hg = 0.05 milligrams per kilogram [mg/kg]; Pb =17 mg/kg). Concentrations of most trace elements were higher in the less than 63-micrometer fraction (silt) and tended to be higher in subsurface than in surface sediment. The concentrations of trace elements were compared to consensus-based aquatic toxicity reference concentrations, Washington State Department of Ecology sediment management standards, and average concentrations of upper continental-crustal material. Arsenic concentrations were consistently elevated above these criteria among samples and often exceeded sediment management standards and aquatic toxicity reference values (both threshold effects and probable effects concentrations). High concentrations of As were measured in sediment with proportionally more material in the less than 63-micrometer size fraction; this result may be related to the presence of ore-processing waste material that has entered the aquatic system from approximately 125 years of mining operations in the basin. Elevated concentrations of chromium and copper that exceed the same criteria as arsenic (As) were measured less consistently and predominantly in the fine-grain size fraction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225073","collaboration":"Prepared in cooperation with Grant County Public Utility District","usgsCitation":"Cox, S.E., Curran, C.A., Spanjer, A.R., Opatz, C.C., Takesue, R.K., and Bell, J.L., 2022, Element concentrations and grain size of sediment from the Similkameen River above Enloe Dam (Enloe Reservoir) near Oroville, Washington, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5073, 47 p., https://doi.org/10.3133/sir20225073.","productDescription":"Report: x, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-120573","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404705,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225073/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5073"},{"id":404708,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.XML"},{"id":404707,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5073/images"},{"id":404704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5073"},{"id":404703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5073/coverthb.jpg"},{"id":404706,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9593V04","text":"USGS data release","description":"USGS data release","linkHelpText":"Sediment chemistry and characteristics of samples collected in 2019 from the Similkameen River above Enloe Dam, Okanogan County, Washington (ver. 3.0, March 2022):"}],"country":"United States","state":"Washington","otherGeospatial":"Enloe Dam, Enloe Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.520263671875,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.96218736991556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Land subsidence is a settling, sinking, or collapse of the land surface. In the southeastern United States, subsidence is frequently observed as sinkhole collapse in karst environments, wetland degradation and loss in coastal and other low-lying areas, and inundation of coastal urban communities. Human activities such as fluid extraction, mining, and overburden alteration can cause or exacerbate subsidence, which can result in damage to infrastructure and resources. Subsidence is a hazard that takes place throughout the United States; however, a systematic approach to recognize and develop informed responses to the drivers of subsidence has not yet been fully established. To address this problem, the U.S. Geological Survey (USGS) Southeast Region (SER) funded the gathering of a team of interdisciplinary USGS scientists to promote scientific collaboration. Southeast Region scientists welcomed scientists from other regions (see table 1.1 in Appendix 1) in September 2018 at the St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida for the first workshop of the Subsidence Flex Team (SFT) (see Appendix 2 for agenda). The SFT set out to review subsidence-related research and technology and develop a unifying framework for describing the processes and hazards associated with land subsidence. A more comprehensive understanding of subsidence hazards could help to inform regional vulnerability assessments that would prove invaluable to the public, community developers, policy makers, and resource managers in both inland and coastal states. The SFT analyzed USGS strengths and weaknesses to identify existing infrastructure and capabilities that could be leveraged to create a comprehensive and far-reaching subsidence-monitoring and mitigation program. Over the course of the 2-day workshop, interdisciplinary understandings of the processes and hazards related to subsidence were explored through individual presentations and group discussion. With all perspectives considered, the SFT recommended that subsidence-related research develop scientific approaches and metrics by which the subsidence component can be isolated and quantified in order to protect both the environment and human infrastructure from harm.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221064","usgsCitation":"Flocks, J., McGraw, E., Barras, J., Bernier, J., Bradley, M., Galloway, D., Landmeyer, J., McBride, W.S., Smith, C., Smith, K., Swarzenski, C., and Toth, L., 2022, Documenting the multiple facets of a subsiding landscape from coastal cities and wetlands to the continental shelf: U.S. Geological Survey Open-File Report 2022–1064, 22 p., https://doi.org/10.3133/ofr20221064.","productDescription":"viii, 22 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-106940","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":501871,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113357.htm","linkFileType":{"id":5,"text":"html"}},{"id":404582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1064/covrthb.jpg"},{"id":404583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1064/ofr20221064.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1064"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.603515625,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 24.5271348225978\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
In September 2019 The Economist wrote an obituary to Okjökull, a glacier in western Iceland that was declared “dead” in 2014, a victim of climate change. Although a few wildlife species have already incurred such a fate (e.g., the Bramble Cay melomys [Melomys rubicola]) (Fulton 2017), many more are on the path to climate-driven extinction (Andermann et al. 2020; Ceballos et al. 2015; He et al. 2019; Roman-Palacios and Wiens 2020; Sanchez-Bayo and Wyckhuys 2019; WWF 2020).
","language":"English","publisher":"Springer","doi":"10.1007/s10393-022-01604-9","usgsCitation":"Hofmeister, E.K., Ruhs, E.C., Fortini, L., Hopkins, M.C., Jones, L.C., Lafferty, K.D., Sleeman, J.M., and LeDee, O.E., 2022, Future directions to manage wildlife health in a changing climate: EcoHealth, v. 19, p. 329-334, https://doi.org/10.1007/s10393-022-01604-9.","productDescription":"6 p.","startPage":"329","endPage":"334","ipdsId":"IP-126986","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":404652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","noUsgsAuthors":false,"publicationDate":"2022-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":847991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruhs, Emily Cornelius","contributorId":294392,"corporation":false,"usgs":false,"family":"Ruhs","given":"Emily","email":"","middleInitial":"Cornelius","affiliations":[{"id":63565,"text":"University of South Florida, 4202 E. Fowler Ave. Tampa, FL 33620","active":true,"usgs":false}],"preferred":false,"id":847992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":847993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopkins, M. Camille 0000-0003-1465-6038","orcid":"https://orcid.org/0000-0003-1465-6038","contributorId":206863,"corporation":false,"usgs":true,"family":"Hopkins","given":"M.","email":"","middleInitial":"Camille","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":847994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Lee C.","contributorId":149998,"corporation":false,"usgs":false,"family":"Jones","given":"Lee","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":847995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":847996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":847997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LeDee, Olivia E. 0000-0002-7791-5829 oledee@usgs.gov","orcid":"https://orcid.org/0000-0002-7791-5829","contributorId":242820,"corporation":false,"usgs":true,"family":"LeDee","given":"Olivia","email":"oledee@usgs.gov","middleInitial":"E.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":847998,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70239760,"text":"70239760 - 2022 - Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam","interactions":[],"lastModifiedDate":"2023-01-18T14:30:11.981529","indexId":"70239760","displayToPublicDate":"2022-08-02T08:26:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam","docAbstract":"The brown treesnake (BTS) (Boiga irregularis) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird's perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan's birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan's forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek (Todiramphus cinnamominus) and Såli (Aplonis opaca), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (>0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/eap.2716","usgsCitation":"McElderry, R., Paxton, E.H., Nguyen, A.V., and Siers, S.R., 2022, Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam: Ecological Applications, v. 32, no. 8, e2716, 19 p., https://doi.org/10.1002/eap.2716.","productDescription":"e2716, 19 p.","ipdsId":"IP-130719","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":446952,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2716","text":"Publisher Index Page"},{"id":412025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.97077826134404,\n 13.59091065759955\n ],\n [\n 144.85095546721982,\n 13.663691679762252\n ],\n [\n 144.77392652814024,\n 13.509785599826927\n ],\n [\n 144.6134495717218,\n 13.445281650900142\n ],\n [\n 144.6284274209881,\n 13.332878728890421\n ],\n [\n 144.6797800470419,\n 13.235003984055268\n ],\n [\n 144.726853287589,\n 13.224589457355279\n ],\n [\n 144.78890437740444,\n 13.272492591536036\n ],\n [\n 144.7931837629091,\n 13.401575642368869\n ],\n [\n 144.93226379180425,\n 13.509785472844925\n ],\n [\n 144.97077826134404,\n 13.59091065759955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McElderry, Robert","contributorId":265185,"corporation":false,"usgs":false,"family":"McElderry","given":"Robert","email":"","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":861792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":861793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Andre Van 0000-0001-5917-0360","orcid":"https://orcid.org/0000-0001-5917-0360","contributorId":301028,"corporation":false,"usgs":true,"family":"Nguyen","given":"Andre","email":"","middleInitial":"Van","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":861794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":861795,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234147,"text":"70234147 - 2022 - Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary","interactions":[],"lastModifiedDate":"2022-10-31T14:29:19.249559","indexId":"70234147","displayToPublicDate":"2022-08-02T08:26:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2437,"text":"Journal of Quaternary Science","active":true,"publicationSubtype":{"id":10}},"title":"Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary","docAbstract":"We examine fossil foraminiferal assemblages from 20 sediment cores to assess sudden relative sea-level (RSL) changes across three mud-over-peat contacts at three salt marshes in northern Humboldt Bay, California (~44.8°N, -124.2°W). We use a validated foraminiferal-based Bayesian transfer function to evaluate the variability of subsidence stratigraphy at a range of 30-6000 m across an estuary. We use the consistency in RSL reconstructions to support estimates of coseismic subsidence from megathrust earthquakes. To assess the variability of subsidence estimates, we analyzed: nine examples of the 1700 CE earthquake (average of 0.64 ±0.14 m subsidence; range of 0.24 ±0.27 to 1.00 ±0.44 m), five examples of the ca. 875 cal a BP earthquake (average of 0.43 ±0.16 m; range of 0.41 ±0.36 to 0.48 ±0.39 m), and six examples of the ca. 1120 cal a BP earthquake (average of 0.70±0.18 m; range of 0.47 ±0.36 to 0.80 ±0.49 m). Our subsidence estimate results suggest ~±0.3 m of within-site (intra-site) variability, which is consistent with previous research. We also identify inconsistencies between sites (inter-site) at northern Humboldt Bay greater than one-sigma uncertainties, driven by variable foraminiferal assemblages in the mud overlying the 1700 CE subsidence contact. Therefore, we recommend at least two quantitative microfossil reconstructions across the same stratigraphic sequence from different marsh sites within an estuary to account for estimate variability and provide increased confidence in vertical coseismic deformation estimates. Our results have broad implications for quantitative, microfossil-based reconstructions of coseismic subsidence at temperate coastlines globally.","language":"English","publisher":"Wiley","doi":"10.1002/jqs.3446","usgsCitation":"Padgett, J.S., Engelhart, S.E., Kelsey, H., Witter, R., and Cahill, N., 2022, Reproducibility and variability of earthquake subsidence estimates from saltmarshes of a Cascadia estuary: Journal of Quaternary Science, v. 37, no. 7, p. 1294-1312, https://doi.org/10.1002/jqs.3446.","productDescription":"19 p.","startPage":"1294","endPage":"1312","ipdsId":"IP-137254","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jqs.3446","text":"External Repository"},{"id":404650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Humboldt Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.22721862792969,\n 40.764421348741976\n ],\n [\n -124.19013977050781,\n 40.75271883902363\n ],\n [\n -124.1891098022461,\n 40.77898159474759\n ],\n [\n -124.18224334716797,\n 40.78574062435701\n ],\n [\n -124.17469024658203,\n 40.80133575979201\n ],\n [\n -124.13692474365234,\n 40.804454347291006\n ],\n [\n -124.12559509277342,\n 40.804454347291006\n ],\n [\n -124.08473968505858,\n 40.824201998489904\n ],\n [\n -124.08267974853514,\n 40.82991732677595\n ],\n [\n -124.08130645751953,\n 40.84809918505204\n ],\n [\n -124.08473968505858,\n 40.85770758108904\n ],\n [\n -124.09194946289061,\n 40.87043006899356\n ],\n [\n -124.11632537841795,\n 40.86835309505014\n ],\n [\n -124.11872863769531,\n 40.85822691415107\n ],\n [\n -124.12799835205078,\n 40.86212178233553\n ],\n [\n -124.13383483886719,\n 40.867833841384936\n ],\n [\n -124.15752410888672,\n 40.86705495325258\n ],\n [\n -124.17915344238281,\n 40.82705972420505\n ],\n [\n -124.19528961181639,\n 40.81121078417314\n ],\n [\n -124.20318603515624,\n 40.78834006798032\n ],\n [\n -124.22721862792969,\n 40.764421348741976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Padgett, Jason Scott 0000-0003-1157-8716","orcid":"https://orcid.org/0000-0003-1157-8716","contributorId":294391,"corporation":false,"usgs":true,"family":"Padgett","given":"Jason","email":"","middleInitial":"Scott","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":847976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Harvey M.","contributorId":206893,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey M.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":847977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":847978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":847979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237685,"text":"70237685 - 2022 - Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18)","interactions":[],"lastModifiedDate":"2022-10-19T13:19:44.062612","indexId":"70237685","displayToPublicDate":"2022-08-02T08:11:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18)","docAbstract":"Movement and dispersal of migratory fish species is an important life-history characteristics that can be impeded by navigation dams. Although habitat fragmentation may be detrimental to native fish species, it might act as an effective and economical barrier for controlling the spread of invasive species in riverine systems. Various technologies have been proposed as potential fish deterrents at locks and dams to reduce bigheaded carp (i.e., silver carp and bighead carp (Hypophthalmichthys spp.)) range expansion in the Upper Mississippi River (UMR). Lock and Dam (LD) 15 is infrequently at open-river condition (spillway gates completely open; hydraulic head across the dam <0.4 m) and has been identified as a potential location for fish deterrent implementation. We used acoustic telemetry to evaluate paddlefish passage at UMR dams and to evaluate seasonal and diel movement of paddlefish and bigheaded carp relative to environmental conditions and lock operations at LD 15. We observed successful paddlefish passage at all dams, with the highest number of passages occurring at LDs 17 and 16. Paddlefish residency events in the downstream lock approach of LD 15 occurred more frequently and for longer durations than residency events of bigheaded carp. We documented upstream passages completed by two individual paddlefish through the lock chamber at LD 15, and a single bighead carp completed upstream passage through the lock chamber during two separate years of this study. We identified four bigheaded carp and 19 paddlefish that made upstream passages through the spillway gates at LD 15 during this study. The majority of the upstream passages through the spillway gates for both species occurred during open river conditions. When hydraulic head was approximately 1-m or greater, we observed these taxa opt for upstream passage through the lock chamber more often than the dam gates. In years with infrequent open-river condition, a deterrent placed in the downstream lock approach may assist in meeting the management goal of reducing upstream passage of bigheaded carps but could also potentially affect paddlefish residency and passage. Continued study to understand the effects of deterrents on native fish could be beneficial for implementing an integrated bigheaded carp control strategy. Understanding fish behavior at UMR dams is a critical information need for river managers as they evaluate potential tools or technologies to control upstream expansion of bigheaded carp in the UMR.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.13822","usgsCitation":"Turney, D.D., Fritts, A.K., Knights, B.C., Vallazza, J.M., Appel, D., and Lamar, J.T., 2022, Hydrological and lock operation conditions associated with paddlefish and bigheaded carp dam passage on a large and small scale in the Upper Mississippi River (Pools 14–18): PeerJ, v. 10, e13822, 31 p., https://doi.org/10.7717/peerj.13822.","productDescription":"e13822, 31 p.","ipdsId":"IP-135535","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":446958,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.13822","text":"Publisher Index Page"},{"id":435747,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CHJ8OG","text":"USGS data release","linkHelpText":"2017-2019 Telemetry data for invasive carp and paddlefish surrounding Lock and Dam 15 in the Upper Mississippi River Basin"},{"id":408536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.7138671875,\n 40.41767833585549\n ],\n [\n -89.8736572265625,\n 40.41767833585549\n ],\n [\n -89.8736572265625,\n 41.9921602333763\n ],\n [\n -91.7138671875,\n 41.9921602333763\n ],\n [\n -91.7138671875,\n 40.41767833585549\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Turney, Dominique D.","contributorId":298069,"corporation":false,"usgs":false,"family":"Turney","given":"Dominique","email":"","middleInitial":"D.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":855012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appel, Douglas 0000-0001-8775-1058","orcid":"https://orcid.org/0000-0001-8775-1058","contributorId":268159,"corporation":false,"usgs":true,"family":"Appel","given":"Douglas","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamar, James T.","contributorId":298070,"corporation":false,"usgs":false,"family":"Lamar","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":855017,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234212,"text":"70234212 - 2022 - Sclerochronological records of environmental variability and bivalve growth in the Pacific Arctic","interactions":[],"lastModifiedDate":"2022-08-15T14:03:40.905011","indexId":"70234212","displayToPublicDate":"2022-08-02T06:54:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Sclerochronological records of environmental variability and bivalve growth in the Pacific Arctic","docAbstract":"The Pacific Arctic region has experienced, and is projected to continue experiencing, rapid climate change. Large uncertainties exist in our understanding of the impact these physical changes have on the region’s ecology. This is, in part, due to the lack of long-term data. Here we investigate bivalve mollusc growth increment width chronologies (sclerochronologies) to develop a long-term biological data series in an Arctic species and address the hypothesis that benthic production in the Pacific Arctic region is in decline with implications for predators (e.g., walrus, whales, seals, and sea ducks). Growth increments formed in the shells of two bivalve mollusc species, Astarte borealis and Liocyma fluctuosa, were examined using conventional sclerochronological techniques. The A. borealis and L. fluctuosa samples exhibited measured longevities of >148 and >18 years, respectively, in the coastal waters of Alaska’s Chukchi Sea. Dendrochronology crossdating techniques facilitated the development of two robust (expressed population signal >0.85) independent growth increment width chronologies. These chronologies provide evidence of the growth conditions through time for each species (1985-2015 for A. borealis and 1997-2014 for L. fluctuosa). Linear regression analyses identified that both species grew more rapidly in years with warmer sea surface temperature and lower sea ice concentration. The results provide evidence that benthic ecosystems are benefiting from the warmer conditions and reduced sea ice that have accompanied recent Arctic climate trends. This result is encouraging for benthic predators in the eastern Chukchi Sea as it alleviates the concern that their benthic prey has already become food limited by weakened pelagic-benthic coupling. More broadly, this initial A. borealis chronology is among the longest biological data series for any Arctic species and highlights the feasibility of multicentennial biological data for the Arctic.
The 2018 eruption of Mount Veniaminof occurred from September 3–4 to December 27, lasting about 114 days. This report summarizes the types of volcanic unrest that accompanied the eruption and provides a chronology of events and observations. Information about the 2018 eruption was derived from geophysical instrumentation on or near the volcano that included an eight-station seismic network and regional infrasound sensors. Other observations came from frequent satellite images of the eruption, occasional aerial photographs and videos contributed by passing pilots, and web-camera views of the volcano from Perryville, Alaska, about 35 kilometers (km) south of the volcano. Eruptive activity involved small vents on the upper south flank of a cinder cone (cone A) within the ice-filled caldera that characterizes Mount Veniaminof. The 2018 eruption consisted of occasional explosive emissions of ash and gas (reaching up to 6,000 meters above sea level), episodes of low-level lava fountaining, Strombolian explosive activity, and effusion of lava flows. By the end of the eruption, lava covered an area of about 600,000 square meters (m2) on the lower south flank of cone A. The lava flows melted into ice and snow, slowly creating melt depressions around the flow margins. No unusual outflows of water were observed exiting the caldera through the main drainage northwest of the cone. Minor ash emissions were generated throughout the eruptive period, and trace amounts of ash fell on Perryville on October 25 and November 21–22. There were no reports of aircraft encounters with ash clouds. The amount of lava and ash erupted from early September to late December 2018 resulted in the generation of about 1,200,000 cubic meters (m3) of lava and 20,000–30,000 m3 of ash, which would characterize the 2018 activity as having an eruption magnitude of 1–2 on the Volcanic Explosivity Index (VEI) scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225075","usgsCitation":"Waythomas, C.F., Dietterich, H.R., Tepp, G.M., Lopez, T.M., and Loewen, M.W., 2022, The 2018 eruption of Mount Veniaminof, Alaska: U.S. Geological Survey Scientific Investigations Report 2022-5075, 32 p., https://doi.org/10.3133/sir20225075.","productDescription":"vii, 32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-120282","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":404574,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5075/covrthb.jpg"},{"id":404575,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5075/sir20225075.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Veniaminof","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.3399658203125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 55.83522882231773\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
This paper proposes a graph-based meta learning approach to separately predict water quantity and quality variables for river segments in stream networks. Given the heterogeneous water dynamic patterns in large-scale basins, we introduce an additional meta-learning condition based on physical characteristics of stream segments, which allows learning different sets of initial parameters for different stream segments. Specifically, we develop a representation learning method that leverages physical simulations to embed the physical characteristics of each segment. The obtained embeddings are then used to cluster river segments and add the condition for the meta-learning process. We have tested the performance of the proposed method for predicting daily water temperature and streamflow for the Delaware River Basin (DRB) over a 14 year period. The results confirm the effectiveness of our method in predicting target variables even using sparse training samples. We also show that our method can achieve robust performance with different numbers of clusterings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","conferenceDate":"August 14-18, 2022","conferenceLocation":"Washington DC","language":"English","publisher":"ACM Digital Library","doi":"10.1145/3534678.3539115","usgsCitation":"Chen, S., Zwart, J.A., and Jia, X., 2022, Physics-guided graph meta learning for predicting water temperature and streamflow in stream networks, in Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining, Washington DC, August 14-18, 2022, p. 2752-2761, https://doi.org/10.1145/3534678.3539115.","productDescription":"10 p.","startPage":"2752","endPage":"2761","ipdsId":"IP-138051","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":420911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":883313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":883315,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}