A decrease in the ground surface height of coastal wetlands is of worldwide concern because of its relationship to peat loss, coastal carbon, and biodiversity in freshwater wetlands. We asked if it is possible to determine indicators of impending transitions of freshwater swamps to other coastal types by examining long-term changes in the environment and vegetation. In a tidal Taxodium distichum swamp in Hickory Point State Forest, Maryland, the topographic surface height (ground surface height) decreased by as much as 25.6 ± 2.2 to 50.8 ± 3.8 cm at two Surface Elevation Tables from 2015 to 2021 following salinity intrusion events related to hurricanes and offshore storms (e.g., Hurricane Melissa). In 2019, rooting zone salinity exceeded 5 ppt for >24.9 % of the time, with a maximum salinity level of 12.5 ppt. Tree growth of T. distichum trees declined and 60 % of these trees died along a 4 m wide × 125 m transect in 2014–2016. Root biomass and ground surface height decreased roughly in conjunction with a salinity pulse in the rooting zone during Hurricane Melissa in 2019. Saplings survived but T. distichum seedlings were uncommon and did not survive in the study area. Typha × glauca increased in cover (0.2 to 5.6 % cover plot−1) from 2014 to 2016 so a vegetation shift toward T. × glauca was apparent by 2021. This work captures a multi-year trend of decreasing ground surface height, tree growth and health, and freshwater status in the rooting zone that may be an indicator of impending vegetation transition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109637","usgsCitation":"Middleton, B., and David, J.L., 2022, Trends in vegetation and height of the topographic surface in a tidal freshwater swamp experiencing rooting zone saltwater intrusion: Ecological Applications, v. 145, 109637, 11 p., https://doi.org/10.1016/j.ecolind.2022.109637.","productDescription":"109637, 11 p.","ipdsId":"IP-126845","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":489206,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109637","text":"Publisher Index Page"},{"id":435623,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99LLMXQ","text":"USGS data release","linkHelpText":"Peat collapse and vegetation shift at Hickory Point"},{"id":435622,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UITS3D","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, Taxodium distichum growth"},{"id":435621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V1N524","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, tree height and density 2021"},{"id":435620,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JDOY24","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, CTD Diver data"},{"id":435619,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P997WSVS","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, vegetation"},{"id":435618,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O3U8A9","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, roots"},{"id":435617,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P928FLVR","text":"USGS data release","linkHelpText":"Data Release: Peat collapse and vegetation shift after storm-driven saltwater surge in a tidal freshwater swamp, SET"},{"id":409994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Hickory Point State Forest, Pocomoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.59867363122336,\n 38.06239155638218\n ],\n [\n -75.66797775370112,\n 38.06239155638218\n ],\n [\n -75.66797775370112,\n 38.00946004126109\n ],\n [\n -75.59867363122336,\n 38.00946004126109\n ],\n [\n -75.59867363122336,\n 38.06239155638218\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"145","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206922,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":843840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David, John L. 0000-0002-9254-5299","orcid":"https://orcid.org/0000-0002-9254-5299","contributorId":299294,"corporation":false,"usgs":false,"family":"David","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":37174,"text":"Volunteer","active":true,"usgs":false}],"preferred":false,"id":858229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238049,"text":"sir20225102 - 2022 - Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","interactions":[],"lastModifiedDate":"2022-11-11T17:47:08.905958","indexId":"sir20225102","displayToPublicDate":"2022-11-10T07:15:06","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":"2022-5102","displayTitle":"Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana","title":"Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","docAbstract":"Simulation models of watershed hydrology (also referred to as “rainfall-runoff models”) are calibrated to the best available streamflow data, which are typically published discharge time series at the outlet of the watershed. Even after calibration, the model generally cannot replicate the published discharges because of simplifications of the physical system embedded in the model structure and uncertainties of the input data and of the estimated model parameters, which, although optimized for the given calibration data, remain uncertain. The input data errors are caused by uncertainties in the forcing data, such as precipitation and other climatological data, and in the published discharges used for calibration. In the numerical algorithms used for calibration, the published discharges are often assumed to be without error, but they are themselves uncertain, typically having been computed using ratings, which are models fitted to uncertain discharge measurements.
In this study, uncertainty of published daily discharge data and how the discharge uncertainty is transmitted to the parameter values of the Hydrological Simulation Program–FORTRAN (HSPF) rainfall-runoff model and to the simulated discharge at both calibration and prediction locations were investigated for the Lake Michigan diversion in northeastern Illinois and northwestern Indiana. The HSPF model used in this study is used by the U.S. Army Corps of Engineers as part of quantifying the diversion of water from Lake Michigan by the State of Illinois. In this study, the model is calibrated jointly at two watersheds in the study area; the resulting model is considered the base model in this study. Seven other gaged watersheds in the study area are used for testing predictive simulations. A Bayesian rating curve estimation (BaRatin) approach, the BaRatin stage-period-discharge (SPD) method, was used to estimate the uncertainty of the published discharge from the calibration watersheds. To characterize the effect of the discharge uncertainty on parameter values, the HSPF model parameters were recalibrated to 17 nonrandomly selected pairs of discharge series from the BaRatin SPD analysis. To provide an indicator of the effect of parameter uncertainty to compare to the effect of discharge uncertainty, 1,000 parameter sets also were randomly generated from the estimated parameter covariance matrix of the base model. The recalibrated and random parameter sets were then used in HSPF simulations of discharge at the two calibration watersheds and at the seven prediction watersheds. Selected discharge summary statistics—the period-of-study (POS, water years 1997 to 2015) mean discharge, selected flow-duration curve (FDC) quantiles, and water year mean discharges—are used to characterize the variability between simulated and published discharge.
A normalized variability index (VN) is used as a measure of the uncertainty of flow statistics arising from the uncertainty of the sources considered in this study. When this index is at least 1, the variability of the simulations is large enough to explain the median error between simulated and published values, although offsetting errors from other sources are also likely. When the index is appreciably less than 1, the variability of the simulations is clearly insufficient to explain the median error between simulated and published values. At the two calibration watersheds and for results of the two simulation sets considered together, the VN values ranged from 0.2 to 0.8 for POS mean discharge, from 0.3 to 0.6 in the median for a set of FDC quantiles, and from 0.1 to 0.2 in the median for water year mean discharges. These values indicate that substantial uncertainty remains unexplained. Even though two watersheds were used in calibration, that calibration was highly constrained because it was applied to the watersheds simultaneously and was subject to parameter regularization that constrained the adjustment of the parameters from their initial values. These constraints were applied to avoid overfitting to the calibration watersheds and thus to increase the likelihood that the resulting parameters would give accurate results at watersheds not used in the calibration, but they created a parameter transfer error in the calibration watershed results shown by the balancing of errors between the two watersheds. Additional remaining error sources include model structural error and meteorological forcing error to the degree that the calibration was unable to adjust the parameters to account for these errors. At the prediction watersheds, the corresponding VN values were almost always substantially lower than those values at the calibration watersheds. This result is expected because the prediction watersheds have additional uncertainty, including parameter transfer error.
The work described in this report provides preliminary estimates of a limited range of sources of error in predicted discharge uncertainty. Future work would be beneficial to obtain a better statistical characterization of the effect of the uncertainty of calibration discharge series and to address additional sources of uncertainty, such as from precipitation input data used in calibration and prediction and from structural (model) errors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225102","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Soong, D.T., and Over, T.M., 2022, Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2022–5102, 54 p., https://doi.org/10.3133/sir20225102.","productDescription":"Report: ix, 54 p.; 2 Data releases; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-120412","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409202,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97S2IID","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2011 Land Cover Conterminous United States"},{"id":409201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UC21B0","text":"USGS data release","linkHelpText":"Models, inputs, and outputs for estimating the uncertainty of discharge simulations for the Lake Michigan Diversion using the Hydrological Simulation Program – FORTRAN model"},{"id":409196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5102/coverthb.jpg"},{"id":409197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.pdf","text":"Report","size":"8.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5102"},{"id":409198,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.XML"},{"id":409199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5102/images"},{"id":409200,"rank":5,"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"}],"country":"United States","state":"Illinois, Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.34881814497747,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 42.492126793048925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow Mw 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.
Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone.
We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries.
We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities.
The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals.
Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.
Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter, Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality particularly in Upper Klamath Lake. The U.S. Geological Survey (USGS) monitoring program, begun in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Upper Klamath Lake indices of year-class strength suggest that the 2020 age-0 cohort is one of the lowest since standardized monitoring began. Despite apparently low over-winter survival, the relatively large 2019 cohort persisted in our 2020 samples and continues to contribute to the populations. Although the 2019 cohort age-0 suckers were composed mainly of Lost River suckers, the age-1 suckers from the 2019 cohort were mainly shortnose suckers. Lost River suckers comprised the largest proportion of the 2020 year-class and were only captured in July and August. Shortnose suckers were mainly captured in August and September and comprised a smaller proportion of the 2020 year-class.
Age distribution of suckers captured in Clear Lake indicates greater juvenile survival than in Upper Klamath Lake. Most juvenile suckers captured were age-3 and age-4 suckers classified as the combination of Klamath largescale suckers (Catostomus snyderi) and shortnose suckers from the Lost River Basin, from the 2016 and 2017 cohorts. A lack of age-0 suckers captured in Clear Lake during years with the low inflow or lake levels initially lead us to believe that low water prevented spawning and year class formation. However, recent data indicate that some cohorts that were not captured as age-0 suckers were detected in later years at age-1 or age-2. This finding indicates that juvenile suckers in Clear Lake may spend one or more years in the tributaries or that sampling efficacy for age-0 suckers varies among years because of water depth.
The first 5 years of this monitoring program indicated different patterns in recruitment and survival of juvenile suckers between Upper Klamath and Clear Lakes. Since the monitoring program began in 2015, age-0 sucker catch rates, interpreted as indices of year-class strength, were greatest in Upper Klamath Lake in 2016 and 2019. In those years Lost River suckers made up the majority of age-0 sucker catches; however, in 2017 and 2020 the age-1 sucker catches from these cohorts were mainly composed of shortnose suckers or suckers with genetic markers of both Klamath largescale and shortnose suckers, indicating a low overwinter survival for Lost River suckers even when the age-0 catches were high. Age-0 suckers do not fully recruit to our sampling gear in Upper Klamath Lake until August, experience high mortality by September, and are almost undetectable by the following July or August in most years. In Clear Lake, suckers frequently are not captured until age-1 or age-2 and annual survival appears much greater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221099","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martin, B.A., Kelsey, C.M., Burdick, S.M., and Bart, R.J., 2022, Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report: U.S. Geological Survey Open-File Report 2022–1099, 27 p., https://doi.org/10.3133/ofr20221099.","productDescription":"vi, 27 p.","onlineOnly":"Y","ipdsId":"IP-141866","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409276,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1099"},{"id":409274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1099/coverthb.jpg"},{"id":409278,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.XML"},{"id":409277,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1099/images"},{"id":409275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1099"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath Lake, Clear Lake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23841270893135,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 42.66770378348696\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Director, North Central Climate Adaptation Science Center
U.S. Geological Survey
University of Colorado - Boulder
Sustainability, Energy and Environment Community
4001 Discovery Dr., Suite 348
Boulder, CO 80303
No abstract available.
","language":"English","publisher":"Columbia Basin Research, School of Aquatic and Fishery Sciences, University of Washington","usgsCitation":"Kelley, J.R., Whitlock, S., Buchanan, R., and Perry, R., 2022, Resource guide and literature review for addressing the problem of tag predation in salmonid studies in the Central Valley of California, 40 p.","productDescription":"40 p.","ipdsId":"IP-142677","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":427217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411416,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbr.washington.edu/analysis/apps/tagpredation"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, Sacramento River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.07407209452549,\n 37.03003597568832\n ],\n [\n -120.20599440615521,\n 37.73368625903554\n ],\n [\n -121.60886401142395,\n 39.703614189808775\n ],\n [\n -122.56466653379951,\n 39.242668117453576\n ],\n [\n -121.07407209452549,\n 37.03003597568832\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Jacob Ryan 0000-0002-0316-679X","orcid":"https://orcid.org/0000-0002-0316-679X","contributorId":300600,"corporation":false,"usgs":true,"family":"Kelley","given":"Jacob","email":"","middleInitial":"Ryan","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":860906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitlock, Steven L.","contributorId":267708,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":860907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Rebecca A.","contributorId":300601,"corporation":false,"usgs":false,"family":"Buchanan","given":"Rebecca A.","affiliations":[{"id":65208,"text":"Columbia Basin Research, School of Aquatic and Fishery Sciences, University of Washington 1325 Fourth Avenue, Suite 1515, Seattle, Washington 98101-2540","active":true,"usgs":false}],"preferred":false,"id":860908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":860909,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236074,"text":"70236074 - 2022 - Assessing global geologic carbon dioxide storage resources","interactions":[],"lastModifiedDate":"2023-04-26T14:49:25.005136","indexId":"70236074","displayToPublicDate":"2022-11-09T09:43:50","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessing global geologic carbon dioxide storage resources","docAbstract":"The U.S. Geological Survey (USGS), in conjunction with the U.S. Department of Energy (U.S. DOE) Office of Fossil Energy and Carbon Management (FECM), the IEA Greenhouse Gas R&D Programme (IEAGHG), and the Clean Energy Ministerial Carbon Capture, Utilization and Storage Initiative (CEM-CCUS Initiative), plans to work with partner nations to assess geologic carbon dioxide (CO2) storage resources globally. The goal of this work is to help countries, particularly those with emerging economies, understand the mass of CO2 they could potentially store in geologic units within their borders. Knowledge of the CO2 storage resources in their geologic units can provide countries pathways for reducing emissions to meet their future climate mitigation goals.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"16th Greenhouse Gas Control Technologies Conference","conferenceDate":"Oct 23-27, 2022","conferenceLocation":"Lyon, France","language":"English","publisher":"GHGT","doi":"10.2139/ssrn.4271675","usgsCitation":"Brennan, S., Warwick, P., Karimjee, A., Wong, A.Y., Dixon, T., Craig, J., and Lipponen, J., 2022, Assessing global geologic carbon dioxide storage resources, in Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16), Lyon, France, Oct 23-27, 2022, 6 p., https://doi.org/10.2139/ssrn.4271675.","productDescription":"6 p.","ipdsId":"IP-144166","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2139/ssrn.4271675","text":"Publisher Index Page"},{"id":416380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brennan, Sean T. 0000-0002-7102-9359","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":204982,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karimjee, Anhar","contributorId":295752,"corporation":false,"usgs":false,"family":"Karimjee","given":"Anhar","email":"","affiliations":[],"preferred":false,"id":849938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wong, Adam Y.","contributorId":295753,"corporation":false,"usgs":false,"family":"Wong","given":"Adam","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":849939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, Timothy","contributorId":191178,"corporation":false,"usgs":false,"family":"Dixon","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":849940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craig, James","contributorId":295756,"corporation":false,"usgs":false,"family":"Craig","given":"James","affiliations":[],"preferred":false,"id":849941,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lipponen, Juho","contributorId":295758,"corporation":false,"usgs":false,"family":"Lipponen","given":"Juho","email":"","affiliations":[],"preferred":false,"id":849942,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70241491,"text":"70241491 - 2022 - High dispersal rates in hybrids drive expansion of maladaptive hybridization","interactions":[],"lastModifiedDate":"2023-03-22T13:52:04.753564","indexId":"70241491","displayToPublicDate":"2022-11-09T08:40:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"High dispersal rates in hybrids drive expansion of maladaptive hybridization","docAbstract":"Hybridization between native and invasive species, a major cause of biodiversity loss, can spread rapidly even when hybrids have reduced fitness. This paradox suggests that hybrids have greater dispersal rates than non-hybridized individuals, yet this mechanism has not been empirically tested in animal populations. Here, we test if non-native genetic introgression increases reproductive dispersal using a human-mediated hybrid zone between native cutthroat trout (Oncorhynchus clarkii) and invasive rainbow trout (Oncorhynchus mykiss) in a large and connected river system. We quantified the propensity for individuals to migrate from natal rearing habitats (migrate), reproduce in non-natal habitats (stray), and the joint probability of dispersal as a function of genetic ancestry. Hybrid trout with predominantly non-native rainbow trout ancestry were more likely to migrate as juveniles and to stray as adults. Overall, hybrids with greater than 50% rainbow trout ancestry were 5.7 times more likely to disperse than native or hybrid trout with small amounts of rainbow trout ancestry. Our results show a genetic basis for increased dispersal in hybrids that is likely contributing to the rapid expansion of invasive hybridization between these species. Management actions that decrease the probability of hybrid dispersal may mitigate the harmful effects of invasive hybridization on native biodiversity.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2022.1813","usgsCitation":"Bourret, S., Kovach, R., Cline, T.J., Strait, J., and Muhlfeld, C.C., 2022, High dispersal rates in hybrids drive expansion of maladaptive hybridization: Proceedings of the Royal Society B, v. 289, 20221813, 7 p., https://doi.org/10.1098/rspb.2022.1813.","productDescription":"20221813, 7 p.","ipdsId":"IP-142129","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":445927,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9653238","text":"External Repository"},{"id":414548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Abbot Creek, Upper Flathead River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06071873441293,\n 48.42865807789937\n ],\n [\n -114.06071873441293,\n 48.38447026195061\n ],\n [\n -113.89518022172545,\n 48.38447026195061\n ],\n [\n -113.89518022172545,\n 48.42865807789937\n ],\n [\n -114.06071873441293,\n 48.42865807789937\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"289","noUsgsAuthors":false,"publicationDate":"2022-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bourret, Samuel 0000-0002-8521-1020","orcid":"https://orcid.org/0000-0002-8521-1020","contributorId":290597,"corporation":false,"usgs":false,"family":"Bourret","given":"Samuel","email":"","affiliations":[{"id":52338,"text":"Montana Fish, Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":867011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kovach, Ryan P.","contributorId":126724,"corporation":false,"usgs":false,"family":"Kovach","given":"Ryan P.","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":867012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cline, Timothy Joseph 0000-0002-4955-654X","orcid":"https://orcid.org/0000-0002-4955-654X","contributorId":228871,"corporation":false,"usgs":true,"family":"Cline","given":"Timothy","email":"","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":867013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strait, Jeffrey 0000-0002-0901-3911","orcid":"https://orcid.org/0000-0002-0901-3911","contributorId":260879,"corporation":false,"usgs":false,"family":"Strait","given":"Jeffrey","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":867014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":867015,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238108,"text":"70238108 - 2022 - Tough places and safe spaces: Can refuges save salmon from a warming climate?","interactions":[],"lastModifiedDate":"2022-11-10T13:30:41.807133","indexId":"70238108","displayToPublicDate":"2022-11-09T07:28:41","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":"Tough places and safe spaces: Can refuges save salmon from a warming climate?","docAbstract":"The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual-based simulation model to evaluate the buffering potential of cold-water thermal refuges for anadromous salmon and trout (Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold-water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold-water thermal refuges and mainstem temperatures. Use of cold-water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree-days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy-conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy-conserving phenotypic space contracted by 7%–23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool- and cold-water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change.
The Big Lost River Basin, located in parts of Butte and Custer Counties in south-central Idaho, supports the communities surrounding the cities of Arco, Leslie, Mackay, and Moore and provides for agricultural resources that depend on a sustainable supply of surface water from the Big Lost River and its tributaries and groundwater from an unconfined aquifer. The aquifer, situated in a structurally controlled intermontane valley, is composed of unconsolidated alluvium, consolidated sedimentary and volcanic rocks, and younger interbedded volcanic rocks.
This report presents two separate groundwater budgets for the aquifer, one above and one below Mackay Dam, as well as a combined groundwater budget for the aquifer within the entire Big Lost River Basin. The budgets span a 20-year period (2000–19), characterizing average conditions, a dry year (2014), and a wet year (2017). The groundwater budgets will help address questions regarding the availability of groundwater supply in the Big Lost River Basin and inform future groundwater modeling. The Idaho Geological Survey has prepared the groundwater budgets as part of a larger hydrogeologic investigation completed by the U.S. Geological Survey and the Idaho Geological Survey in cooperation with the Idaho Department of Water Resources during 2018–21. Other reports describe the hydrogeologic framework and several streamflow-measurement events to evaluate gains and losses on the Big Lost River. Collectively, these reports provide an updated characterization of groundwater resources in the Big Lost River Basin which will help address water resources challenges.
A groundwater budget is a conceptual and numerical accounting of inflow (recharge) to groundwater and outflow (discharge) from groundwater. The predominant sources of recharge to the aquifer include losing river reaches (33 percent), areal recharge (as precipitation less evapotranspiration and surface runoff, comprising about 23 percent of the total inflow), tributary canyon underflow from higher altitudes (20 percent), canal seepage (13 percent), recharge through applied irrigation on fields below the root zone and other minor sources (11 percent), and Mackay Reservoir seepage (less than 1 percent). The primary sources of discharge from the aquifer are groundwater pumpage to meet irrigation demand, domestic supply, and municipal supply (76 percent) and gaining river reaches (24 percent).
The positive or negative difference between the sum of all inflows and outflows is regarded as the residual, representing the change in groundwater storage, groundwater outflow from the basin or subbasins, and uncertainty and errors in the budget. In the Big Lost River Basin, groundwater outflow is at the mouth of the basin below Arco into the eastern Snake River Plain aquifer.
The total mean annual estimated recharge to the Big Lost River Basin was 439,100 acre-feet per year (acre-ft/yr; 607 cubic feet per second [ft3/s]) for 2000–19, 373,900 acre-ft/yr (516 ft3/s) in 2014, and 762,100 acre-ft/yr (1,053 ft3/s) in 2017. The mean annual estimated groundwater discharge from the aquifer was about 112,300 acre-ft/yr (155 ft3/s) for 2000–19, 153,500 acre-ft/yr (212 ft3/s) in 2014, and 53,400 acre-ft/yr (74 ft3/s) in 2017. The estimated mean annual groundwater residual was 326,800 acre-ft/yr (451 ft3/s) for 2000–19, 220,400 acre-ft/yr (304 ft3/s) in 2014, and 708,700 acre-ft/yr (979 ft3/s) in 2017. The mean annual residual above Mackay Dam was 100,400 acre-ft/yr (2000-19), 96,700 acre-ft (2014), and 248,300 acre-ft (2017). The mean annual residual contribution below Mackay Dam, minus any groundwater-flow above Mackay Dam, was 226,400 acre-ft/yr (2000-19), 123,700 acre-ft (2014), and 460,400 acre-ft (2017).
These results are highly sensitive to assumptions about certain budget inflow parameters. In particular, the magnitude of the budget residuals during especially dry and wet periods is amplified by the groundwater-budget terms tributary streamflow and tributary underflow that contribute appreciable recharge but also have high uncertainty.
The results of the groundwater-budget evaluation describe an interconnected and complex hydrologic response throughout the basin to various climatic and water-use trends. The part of the basin above Mackay Dam typically has a positive groundwater residual derived from snowmelt recharge to tributary canyons and areal recharge in excess of groundwater pumpage for irrigation demand. This supply is used to meet irrigation demand above Mackay Dam and to provide for water supply below Mackay Dam. On average, groundwater inflow from above Mackay Dam to below Mackay Dam, assuming negligible reservoir storage effects, accounts for about 25 percent of the total groundwater recharge below Mackay Dam. Considerable recharge to groundwater below Mackay Dam occurs through seepage from the Big Lost River and canals and ditches. Most groundwater discharge from the aquifer is through irrigation pumping. The water supply below Mackay Dam is highly dependent on available upstream surface-water flows, the magnitude of the groundwater residual from above Mackay Dam, and annual variability in local groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078C","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Clark, A., 2022, Groundwater budgets for the Big Lost River Basin, south-central Idaho, 2000–19, chap. C of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–C, 111 p., https://doi.org/10.3133/sir20215078C.","productDescription":"xi, 111 p.","ipdsId":"IP-125226","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":409232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/coverthb.jpg"},{"id":409233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.pdf","text":"Reports","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078-C"},{"id":409235,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/images"},{"id":409236,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.XML"},{"id":502105,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113824.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.1863738631967,\n 43.10571945845362\n ],\n [\n -113.42308735779262,\n 43.54649028685452\n ],\n [\n -112.13258233834704,\n 44.22138739870667\n ],\n [\n -112.23487846793722,\n 44.737914300373745\n ],\n [\n -114.26506595862107,\n 46.10751185031063\n ],\n [\n -115.75229430420214,\n 46.493497990156555\n ],\n [\n -117.884775159506,\n 45.476547804668826\n ],\n [\n -117.57788677073549,\n 45.01671717637413\n ],\n [\n -116.38967788087962,\n 44.5307302025393\n ],\n [\n -115.2014689910242,\n 43.60919623765622\n ],\n [\n -114.1863738631967,\n 43.10571945845362\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director , Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
The Powder River Basin (PRB) is a world-class oil province, in large part thanks to contributions from premier source rocks, Cretaceous Mowry and Niobrara shales. Both formations are also unconventional reservoirs. A critical aspect of evaluating production potential and finding sweet spots is the nature of the pore systems in these fine-grained source-rock reservoirs. Variation by stratigraphic interval is important for selecting optimum target zones for horizontal wells. Understanding variation in pore type, size, and connectivity and relationships with mineralogy and fabric help in determining prospectivity in different parts of the basin. Deciphering controls on pore-system development helps predict intervals and locations of optimum reservoir quality.
Imaging of Niobrara and Mowry samples from a range of thermal maturities provided observations and data on pore systems, organic matter (OM) types and associations with mineralogy and fabric, wettability, and microporosity associated with both diagenetic and detrital clays. Imaging techniques included scanning electron microscopy, organic petrography and correlative scanning electron microscopy, and mapping of mineralogy through energy dispersive spectroscopy.
Mean solid bitumen (BRo) and vitrinite reflectance (VRo) values indicate all samples are in the oil window with values ranging from 0.52 to 1.15%. Organic fluorescence is prominent in amorphous OM, solid bitumen and some vitrinite in the early oil window. The fluorescence is extinguished at higher thermal maturity. Carbonate pellets (in Niobrara) mainly contain migrated solid bitumen and residual live oil and little or no terrigenous OM (vitrinite and inertinite). However, terrigenous OM is common in siliceous/argillaceous laminae in both formations, where it occurs with amorphous OM, some of which has converted in situ to a solid bitumen petroleum residue.
One key finding is the widespread presence of migrated OM at very early oil window maturity. Distribution of such OM and associated wettability alteration is fabric-controlled, at all levels of thermal maturity studied. Clay morphology and abundance and supporting rigid mineral grain framework strongly influence pore development, preservation, and connectivity in both formations. Carbonate content is a good proxy for reservoir quality in Niobrara intervals due to association of porous solid bitumen with calcareous fecal pellets. High recrystallized microquartz content is associated with the best reservoir intervals in the Mowry.
","language":"English","publisher":"Elsesvier","doi":"10.1016/j.coal.2022.104134","usgsCitation":"Olson, T., Michalchuk, B., Hackley, P.C., Valentine, B.J., Parker, J., and San Martin, R., 2022, Pore systems and organic petrology of cretaceous Mowry and Niobrara source-rock reservoirs, Powder River Basin, Wyoming, USA: International Journal of Coal Geology, v. 264, 104134, 13 p., https://doi.org/10.1016/j.coal.2022.104134.","productDescription":"104134, 13 p.","ipdsId":"IP-142426","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":418454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.22939078183438,\n 45.01127679602621\n ],\n [\n -106.22939078183438,\n 42.73172365239171\n ],\n [\n -104.01110426262045,\n 42.73172365239171\n ],\n [\n -104.01110426262045,\n 45.01127679602621\n ],\n [\n -106.22939078183438,\n 45.01127679602621\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, Terri","contributorId":312451,"corporation":false,"usgs":false,"family":"Olson","given":"Terri","email":"","affiliations":[{"id":67672,"text":"Digital Rock Petrophysics LLC","active":true,"usgs":false}],"preferred":false,"id":876154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michalchuk, Brad","contributorId":312452,"corporation":false,"usgs":false,"family":"Michalchuk","given":"Brad","email":"","affiliations":[{"id":67673,"text":"Anschutz Exploration and Production","active":true,"usgs":false}],"preferred":false,"id":876155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":876157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Jason","contributorId":312453,"corporation":false,"usgs":false,"family":"Parker","given":"Jason","email":"","affiliations":[{"id":67675,"text":"FIB-X","active":true,"usgs":false}],"preferred":false,"id":876158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"San Martin, Ricardo","contributorId":312454,"corporation":false,"usgs":false,"family":"San Martin","given":"Ricardo","email":"","affiliations":[{"id":67675,"text":"FIB-X","active":true,"usgs":false}],"preferred":false,"id":876159,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238130,"text":"70238130 - 2022 - Flyway-scale GPS tracking reveals migratory routes and key stopover and non-breeding locations of lesser yellowlegs","interactions":[],"lastModifiedDate":"2022-11-14T12:22:44.856742","indexId":"70238130","displayToPublicDate":"2022-11-09T06:12:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12820,"text":"Ecology and Evolution: Nature Notes","active":true,"publicationSubtype":{"id":10}},"title":"Flyway-scale GPS tracking reveals migratory routes and key stopover and non-breeding locations of lesser yellowlegs","docAbstract":"Many populations of long-distance migrant shorebirds are declining rapidly. Since the 1970s, the lesser yellowlegs (Tringa flavipes) has experienced a pronounced reduction in abundance of ~63%. The potential causes of the species' decline are complex and interrelated. Understanding the timing of migration, seasonal routes, and important stopover and non-breeding locations used by this species will aid in directing conservation planning to address potential threats. During 2018–2022, we tracked 118 adult lesser yellowlegs using GPS satellite tags deployed on birds from five breeding and two migratory stopover locations spanning the boreal forest of North America from Alaska to Eastern Canada. Our objectives were to identify migratory routes, quantify migratory connectivity, and describe key stopover and non-breeding locations. We also evaluated predictors of southbound migratory departure date and migration distance. Individuals tagged in Alaska and Central Canada followed similar southbound migratory routes, stopping to refuel in the Prairie Pothole Region of North America, whereas birds tagged in Eastern Canada completed multi-day transoceanic flights covering distances of >4000 km across the Atlantic between North and South America. Upon reaching their non-breeding locations, lesser yellowlegs populations overlapped, resulting in weak migratory connectivity. Sex and population origin were significantly associated with the timing of migratory departure from breeding locations, and body mass at the time of GPS-tag deployment was the best predictor of southbound migratory distance. Our findings suggest that lesser yellowlegs travel long distances and traverse numerous political boundaries each year, and breeding location likely has the greatest influence on migratory routes and therefore the threats birds experience during migration. Further, the species' dependence on wetlands in agricultural landscapes during migration and the non-breeding period may make them vulnerable to threats related to agricultural practices, such as pesticide exposure.
Construction and operation of dams provide sources of clean drinking water, support large-scale irrigation, generate hydroelectricity, control floods, and improve river navigation. Yet these benefits are not without cost. Dams affect the natural flow regime, downstream sediment fluxes, and riverine and riparian ecosystems. The Jemez Canyon Dam in New Mexico was constructed in 1953 by the U.S. Army Corps of Engineers with authorizations for flood control and sediment retention. Water managers of the dam use various operational techniques to restore peak streamflow, improve sediment management, and restore altered ecosystem processes, while maintaining the authorized purposes of the dam. This study focuses on four distinct reservoir management operation periods implemented at the Jemez Canyon Dam: (1) predam (pre-1953), (2) a seasonal 24-hour hold pool (1953–79), (3) a permanent pool (1979–2001), and (4) dry reservoir (2001–18).
Results of this study indicate successful flood control and reduction in peak instantaneous streamflow events following construction of the dam, specifically documented in 1958 and 2013. During the second water management operation period, moderate sediment retention (also defined as trap efficiency, which is the percentage of incoming sediments trapped within a reservoir during a given time) occurred (between 41.0 and 67.0 percent of sediments were retained). During the third period (1979–2001), between 61.2 and 99.8 percent of sediments were retained. During the fourth period (2001–18), at least 1,909 acre-feet of accumulated sediment were remobilized. The estimated dam trap efficiency during the fourth water management operation period was −37.2 percent, indicating that more sediments were being removed from the Jemez Canyon Reservoir than were being deposited. These remobilized sediments supplemented the natural sediment delivery in the Jemez River to the middle Rio Grande. The current (2022) dry reservoir operation allows sediment delivery during periods when flooding is not a concern while still providing flood control when needed.
Suspended-sediment particle size data indicate potential coarsening of suspended sediments during the fourth water management operation period, likely resulting from erosion of coarse bed sediments deposited in the reservoir. Suspended-sediment particle size data during the first and fourth water management operation periods indicate that finer sediment mobilized during monsoon season than during snowmelt. Also, suspended-sediment concentrations during the predam and post-hold pool periods indicate concentrations were higher during monsoon season than during snowmelt. Seasonal variations in suspended-sediment concentration and particle size may help dam managers make operational decisions by increasing the understanding of particle size, concentration, and variation of suspended sediment during a given year. The seasonality of suspended-sediment transport can also vary, depending not only on concentration and particle size, but on precipitation. The maximum annual suspended-sediment loads occurred during all three seasonal categories analyzed in this study: snowmelt, monsoon, and the remainder of the year. This indicates that, in addition to sediment particle size and concentration, understanding the variability of transport mechanisms of suspended-sediment load can also guide optimal water management operations at a dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225081","isbn":"978-1-4113-4481-5","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Brown, J.E., Matherne, A.M., Reale, J.K., and Miltenberger, K.E., 2022, Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018: U.S. Geological Survey Scientific Investigations Report 2022–5081, 30 p., https://doi.org/10.3133/sir20225081.","productDescription":"Report: vii, 30 p.; 2 Datasets","numberOfPages":"42","onlineOnly":"N","ipdsId":"IP-107586","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":408900,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5081/coverthb.jpg"},{"id":408901,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5081"},{"id":408902,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.XML"},{"id":409231,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225081/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":408905,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":408904,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS Earth Resources Observation and Science Center database","linkHelpText":"—EarthExplorer"},{"id":408903,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5081/images"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.61655311950582,\n 35.438783063650746\n ],\n [\n -106.61655311950582,\n 35.32720598341298\n ],\n [\n -106.46641220000733,\n 35.32720598341298\n ],\n [\n -106.46641220000733,\n 35.438783063650746\n ],\n [\n -106.61655311950582,\n 35.438783063650746\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The Katahdin Woods and Waters National Monument, located in the forests of central Maine, is a newly (2016) established unit for the National Park Service. To better understand the condition of lands within the monument and inform management planning, Katahdin Woods and Waters National Monument resource managers wanted better information of the vegetation present within the monument. To meet this need, scientists at the U.S. Geological Survey Upper Midwest Environmental Sciences Center worked with ecologists at the Maine Natural Areas Program to catalog and map the vegetation of the Seboeis Unit of the monument. This report details this process, provides results of the survey and mapping efforts, presents results in the form of a vegetation map for the Seboeis Unit, and provides vegetation descriptions and a dichotomous key for the entire Katahdin Woods and Waters National Monument.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225078","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Strassman, A.C., Hop, K.D., Sattler, S.R., Schlawin, J., and Cameron, D., 2022, Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument: U.S. Geological Survey Scientific Investigations Report 2022–5078, 73 p., https://doi.org/10.3133/sir20225078.","productDescription":"Report: x, 73 p.; Data Releases","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-130383","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":407273,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93HGWGB","text":"USGS data release","linkHelpText":"Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument (vector and tabular data)"},{"id":407272,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5078/images"},{"id":407267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5078/coverthb.jpg"},{"id":407269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.pdf","text":"Report","size":"19.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5078"},{"id":407270,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.XML"},{"id":409229,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BW6YWP","text":"USGS data release","linkHelpText":"2019 Katahdin Woods and Waters National Monument 4-band imagery products"}],"country":"United States","state":"Maine","otherGeospatial":"Seboeis Unit of Katahdin Woods and Waters National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.82465497885659,\n 46.12747294389601\n ],\n [\n -68.82465497885659,\n 45.82583589711629\n ],\n [\n -68.51101993751016,\n 45.82583589711629\n ],\n [\n -68.51101993751016,\n 46.12747294389601\n ],\n [\n -68.82465497885659,\n 46.12747294389601\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
Hiking and backpacking on American National Scenic Trails has increased in popularity in recent years. To encourage responsible and sustainable outdoor recreation on these much-loved trails, direct and indirect management strategies must be employed by managerial agencies. The Leave No Trace (LNT) education program aims to protect natural resources by promoting minimum-impact behaviours that lessen environmental impacts. The accidental introduction and dispersal of non-native invasive flora by hikers is little studied but can have a detrimental environmental impact on protected areas. The purpose of our study was to understand whether Appalachian Trail thru-hikers are: 1) aware of this problem, 2) adhering to LNT principles to reduce this problem, and 3) willing to learn and adopt minimum-impact behaviours to address this problem. We found that thru-hiker knowledge of invasive plants was limited and that very few thru-hikers adopted low-impact practices to minimise plant introduction and spread. Promisingly, we found that most thru-hikers, once aware of the problems, were willing to learn and apply low-impact practices to minimise plant introduction and spread. We discuss the barriers to their adoption of these behaviours and present a comprehensive list of suggested LNT practices to limit invasive plant introduction and spread. We conclude that, whilst challenging, protected area managers can help deter the spread of invasive plants along trails by improving educational messaging, signage, personal communication, and providing supporting infrastructure that encourages visitors to adopt specific practices to minimise invasive plant introduction and spread within protected areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2022.100581","usgsCitation":"Dolman, M., and Marion, J.L., 2022, Invasive plant hitchhikers: Appalachian Trail thru-hiker knowledge and attitudes of invasive plants and Leave No Trace practices: Journal of Outdoor Recreation and Tourism, v. 40, 100581, 12 p., https://doi.org/10.1016/j.jort.2022.100581.","productDescription":"100581, 12 p.","ipdsId":"IP-132845","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":410278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","otherGeospatial":"Appalachian Trail","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.663426481162,\n 39.327334819713826\n ],\n [\n -77.84650013772489,\n 39.352244826545075\n ],\n [\n -80.24694411951128,\n 37.65331631118197\n ],\n [\n -80.62871457673847,\n 37.33610604928302\n ],\n [\n -81.72490463550588,\n 36.63467327613432\n ],\n [\n -80.86786667184651,\n 36.60267551794206\n ],\n [\n -79.06482033698572,\n 37.834500309643815\n ],\n [\n -77.64378265768026,\n 39.08720414992473\n ],\n [\n -77.663426481162,\n 39.327334819713826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dolman, Megan","contributorId":298242,"corporation":false,"usgs":false,"family":"Dolman","given":"Megan","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":858566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238960,"text":"70238960 - 2022 - Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","interactions":[],"lastModifiedDate":"2022-12-19T13:43:37.234094","indexId":"70238960","displayToPublicDate":"2022-11-08T07:36:03","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":"Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","docAbstract":"Drylands represent more than 41% of the global land surface and are at degradation risk due to land use and climate change. Developing strategies to mitigate degradation and restore drylands in the face of these threats requires an understanding of how drylands are shaped by not only soils and climate, but also geology and geomorphology. However, few studies have completed such a comprehensive analysis that relates spatial variation in plant communities to all aspects of the geologic–geomorphic–edaphic–plant–climate system. The focus of this study is the Colorado Plateau, a high-elevation dryland in the southwestern United States, which is particularly sensitive to future change due to climate vulnerability and increasing land-use pressure. Here, we examined 135 long-term vegetation-monitoring sites in three national parks and characterized connections between geology, geomorphology, soils, climate, and dryland plant communities. To first understand the geologic and geomorphic influences on soil formation and characteristics, we explore associations between soil pedons, bedrock geology, and geomorphology. Then, we characterize principal axes of variation in plant communities and ascertain controls and linkages between components of the edaphic–geomorphic system and plant community ordinations. Geologic and geomorphic substrate exerted controls on important properties of the soil profile, particularly depth, water-holding capacity, rockiness, salinity, and fine sands. Ordination identified five distinct plant communities and three primary axes of variation, representing gradients of woody- to herbaceous-dominated communities (Axis 1), saline scrublands to C3 grasslands (Axis 2), and annual to perennial communities (Axis 3). Geology, geomorphology, and soil explained a large proportion of variation in Axis 1 (74%), while climate variables largely explained Axis 2 (68%), and Axis 3 was not well explained by the random forest models. The variables identified as most influential to each axis were, respectively: (1) soil depth; (2) aridity, lithology, and soil salinity; and (3) temperature and precipitation. We posit that Axis 3 represents a land degradation gradient due to historic grazing, likely exacerbated by dry conditions. Results provide a novel framework that links the geologic and geomorphic evolution of landscapes, with the distribution of soils and plant communities that can guide ecosystem management, exemplifying an approach applicable to drylands globally.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4273","usgsCitation":"Duniway, M.C., Benson, C., Nauman, T.W., Knight, A.C., Bradford, J., Munson, S.M., Witwicki, D.L., Livensperger, C., Van Scoyoc, M.W., Fisk, T.T., Thoma, D., and Miller, M.E., 2022, Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world: Ecosphere, v. 13, no. 11, e4273, 27 p., https://doi.org/10.1002/ecs2.4273.","productDescription":"e4273, 27 p.","ipdsId":"IP-135505","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4273","text":"Publisher Index Page"},{"id":435625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Z8NDP","text":"USGS data release","linkHelpText":"Soil, geologic, geomorphic, climate, and vegetation data from long-term monitoring plots (2009 - 2018) in Arches, Canyonlands, and Capitol Reef National Parks, Utah, USA"},{"id":410697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.63689444724997,\n 36.734805586098716\n ],\n [\n -108.00129122959586,\n 36.72595486884292\n ],\n [\n -107.41606847690218,\n 37.63008491281205\n ],\n [\n -107.57066880734789,\n 38.70708139014661\n ],\n [\n -107.76120496171856,\n 39.973850096503895\n ],\n [\n -108.78556565774403,\n 40.46292505503848\n ],\n [\n -110.23348660705287,\n 40.36792094423029\n ],\n [\n -111.02839675350845,\n 39.403592925523014\n ],\n [\n -111.43291910676305,\n 38.05141646696123\n ],\n [\n -112.77571792678364,\n 37.21069090791468\n ],\n [\n -112.28678230930984,\n 36.79511547655869\n ],\n [\n -111.63689444724997,\n 36.734805586098716\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benson, Christopher","contributorId":296064,"corporation":false,"usgs":false,"family":"Benson","given":"Christopher","email":"","affiliations":[{"id":63978,"text":"formerly) US Geological Survey, Southwest Biological Science Center, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859392,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":859393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witwicki, Dana L.","contributorId":207763,"corporation":false,"usgs":false,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[{"id":37628,"text":"National Park Service Inventory and Monitoring Program, P.O. Box 848, Moab, UT 84532, USA","active":true,"usgs":false}],"preferred":false,"id":859394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livensperger, Carolyn","contributorId":260927,"corporation":false,"usgs":false,"family":"Livensperger","given":"Carolyn","email":"","affiliations":[{"id":52723,"text":"National Park Service, Capitol Reef National Park, 52 Headquarters Dr., Torrey UT 84775","active":true,"usgs":false}],"preferred":false,"id":859395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Scoyoc, Matthew W. 0000-0001-6821-4476","orcid":"https://orcid.org/0000-0001-6821-4476","contributorId":290213,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":62383,"text":"Southeast Utah Group, National Park Service, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisk, Terry T","contributorId":289096,"corporation":false,"usgs":false,"family":"Fisk","given":"Terry","email":"","middleInitial":"T","affiliations":[{"id":62042,"text":"Water Resources Division, National Park Service","active":true,"usgs":false}],"preferred":false,"id":859397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thoma, David","contributorId":265911,"corporation":false,"usgs":false,"family":"Thoma","given":"David","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859398,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":859399,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238582,"text":"70238582 - 2022 - Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","interactions":[],"lastModifiedDate":"2022-11-30T12:53:57.31331","indexId":"70238582","displayToPublicDate":"2022-11-08T06:50:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","docAbstract":"This paper introduces a method for determining spatially-distributed, 2-D bedload rates using repeat, high-resolution surveys of the bed topography. As opposed to existing methods, bedform parameters and bedload rates are computed from bed elevation profiles interpolated along the local bedform velocities. The bedform velocity fields are computed applying Large-Scale Particle Image Velocimetry, initially developed for surface velocity measurements, to pairs of successive Digital Elevation Models (DEMs). The bathymetry data are interpolated along the direction of each bedform velocity and the mean height of the closest bedform is computed. The dune shape factor is also evaluated along each bedform direction of travel. The local bedload fluxes can be computed by multiplying the bedform velocity by its mean height averaged over the successive two DEMs, and they can be time-averaged over a series of DEM pairs. This method is applied to a high-resolution acoustical survey of an approximately 300 m long by 40 m wide reach of the Colorado River in Grand Canyon upstream from Diamond Creek, USA. The repeat period was about 6–10 min and bed elevation was interpolated every 0.25 m. The obtained results provide insight to the spatial and temporal variability of bedload rates, bedform parameters and bedload fluxes through cross-sections. The method can be applied to other repeated acoustical surveys of river reaches provided that the space and time resolutions are high enough to capture the local movement of bedforms.
Using multi-species time series data has long been of interest for estimating inter-specific interactions with vector autoregressive models (VAR) and state space VAR models (VARSS); these methods are also described in the ecological literature as multivariate autoregressive models (MAR, MARSS). To date, most studies have used these approaches on relatively small food webs where the total number of interactions to be estimated is relatively small. However, as the number of species or functional groups increases, the length of the time series must also increase to provide enough degrees of freedom with which to estimate the pairwise interactions. To address this issue, we use Bayesian methods to explore the potential benefits of using regularized priors, such as Laplace and regularized horseshoe, on estimating interspecific interactions with VAR and VARSS models. We first perform a large-scale simulation study, examining the performance of alternative priors across various levels of observation error. Results from these simulations show that for sparse matrices, the regularized horseshoe prior minimizes the bias and variance across all inter-specific interactions. We then apply the Bayesian VAR model with regularized priors to a output from a large marine food web model (37 species) from the west coast of the USA. Results from this analysis indicate that regularization improves predictive performance of the VAR model, while still identifying important inter-specific interactions.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.14332","usgsCitation":"Ward, E.J., Marshall, K.N., Scheuerell, M.D., 2022, Regularizing priors for Bayesian VAR applications to large ecological datasets: PeerJ, v. 10, e14332, 18 p., https://doi.org/10.7717/peerj.14332.","productDescription":"e14332, 18 p.","ipdsId":"IP-144838","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500605,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.14332","text":"Publisher Index Page"},{"id":500429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Eric J.","contributorId":366786,"corporation":false,"usgs":false,"family":"Ward","given":"Eric","middleInitial":"J.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Kristin N.","contributorId":366787,"corporation":false,"usgs":false,"family":"Marshall","given":"Kristin","middleInitial":"N.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237990,"text":"tm17A1 - 2022 - Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","interactions":[],"lastModifiedDate":"2022-11-07T17:14:33.667614","indexId":"tm17A1","displayToPublicDate":"2022-11-07T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"17-A1","displayTitle":"Rapidly Assessing Social Characteristics of Drought Preparedness and Decision Making: A Guide for Practitioners","title":"Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","docAbstract":"This guide is intended to provide managers, decision makers, and other practitioners with advice on conducting a rapid assessment of the social dimensions of drought. Findings from a rapid assessment can provide key social context that may aid in decision making, such as when preparing a drought plan, allocating local drought resilience funding, or gathering the support of local agencies and organizations for collective action related to drought mitigation.
Part I—In the introduction to Part I, we describe the unique problems associated with drought—particularly its slow onset and long duration, which make it difficult to define drought—and highlight five major types of drought (see Box 1). We introduce a few social dimensions of drought (such as economic and institutional perspectives), demonstrate how these dimensions can be interrelated, and describe a few of the modern challenges (such as transformational change and cascading risks) that practitioners face.
We also provide background on the rapid assessment method, first describing it as a “snapshot” of the social landscape, then providing some key advantages of the method (it can be quicker and cheaper than more in-depth methods), and lastly describing how secondary data and other methods can help overcome some of the disadvantages of rapid assessments.
Then, after summarizing the process of developing this guide, we outline the process of using the guide. Importantly, we compare the guide to a travel guide, which provides many different types of information and is best approached with specific interests in mind. Ultimately, we hope for this guide to be malleable enough that it can be helpful to researchers and practitioners in many different contexts, using many different research methods. Related to how to use the guide, we characterize the type of person who might be motivated to use this guide. We also specify key qualifications for a researcher conducting a rapid assessment, drawing particular attention to training on ethical considerations.
We sketch out key considerations when choosing social dimensions of drought to focus on, and the type of data used for analysis. First, it is important to note that in this guide we provide nine important social dimensions of drought, but this is by no means a comprehensive list, and a researcher may find that other dimensions better fit their local context. Second, we provide some pros and cons to a narrow (focusing on just a few dimensions or at a smaller scale) versus broad research focus. Lastly, we describe the pros and cons of using primary versus secondary data (one strategy is to use both, sequentially) and qualitative versus quantitative data.
Ultimately, Part I of this guide functions as an exploration of the various decisions a researcher will make when designing a rapid assessment. These decisions will inform the type of findings and other outcomes that result from the rapid assessment.
Part II—Part II of this guide introduces nine key social dimensions of drought: defining the problem of drought, individual perceptions, social relationships, technology, economics and livelihoods, water governance, decision making, information, and social vulnerability. Each section provides background and key considerations related to a particular dimension, as well as ideas for how to explore the dimension via a rapid assessment.
Part III—Part III of this guide provides two hypothetical examples of how one might use this guide to aid the practitioner in implementing the lessons learned here. In the first example, a watershed group uses two dimensions, defining the problem of drought and social relationships, to inform a community meeting about protecting fisheries from drought. In the second example, a resource manager uses the economics and livelihoods and social vulnerability dimensions to inform the development of a livestock grazing drought management plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm17A1","usgsCitation":"Clifford, K.R., Goolsby, J.B., Cravens, A.E., and Cooper, A.E., 2022, Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners: U.S. Geological Survey Techniques and Methods 17-A1, 41 p., https://doi.org/10.3133/tm17A1.","productDescription":"vii, 41 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":409066,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.xml"},{"id":409065,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/17/a1/images"},{"id":409061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/17/a1/coverthb.jpg"},{"id":409062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 17-A1"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Habitat selection involves a series of decisions that are arguably the most important decisions that animals make and these decisions occur at multiple hierarchical spatial scales. Colonial-nesting birds face a unique challenge when selecting a nest site because each bird’s choices are severely constrained by other birds within their breeding colony. Individuals must seek out optimum nesting locations within the constraint of the colony’s geographic location. We investigated how water depth and proximity to open water affected 4th-order nest-site selection of Western and Clark’s Grebes (Aechmophorus occidentalis, Aechmophorus clarkii), colonial nesting waterbirds that have declined in abundance across their range. We used an orthomosiac that we created from ~ 500 aerial drone images of a large breeding colony to construct a Resource Selection Function to describe microhabitat features that influence nest-site placement within the colony footprint. Grebes preferred to nest in portions of the colony with intermediate water depths (40-80 cm during nest construction) and they preferred to nest in portions of the colony furthest from open water. Understanding how individual birds make use of available microhabitat features within the footprint of their breeding colony can help inform conservation efforts of colonial-nesting birds, particularly for species that nest in wetland habitats whose water levels are managed for human use.
","language":"English","publisher":"Springer Link","doi":"10.1007/s13157-022-01602-1","usgsCitation":"Lachman, D.A., Conway, C.J., Vierling, K.T., Matthews, T., and Mack, D., 2022, Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes: Wetlands, v. 42, 110, 10 p., https://doi.org/10.1007/s13157-022-01602-1.","productDescription":"110, 10 p.","ipdsId":"IP-132937","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Valley County","otherGeospatial":"Cascade Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.20273923505505,\n 44.769058037542806\n ],\n [\n -116.20273923505505,\n 44.47495390440537\n ],\n [\n -116.01258023679465,\n 44.47495390440537\n ],\n [\n -116.01258023679465,\n 44.769058037542806\n ],\n [\n -116.20273923505505,\n 44.769058037542806\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lachman, Deo A.","contributorId":338149,"corporation":false,"usgs":false,"family":"Lachman","given":"Deo","email":"","middleInitial":"A.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Kerri T.","contributorId":338150,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, Ty","contributorId":338151,"corporation":false,"usgs":false,"family":"Matthews","given":"Ty","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mack, Diane Evans","contributorId":338152,"corporation":false,"usgs":false,"family":"Mack","given":"Diane Evans","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":902979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242697,"text":"70242697 - 2022 - Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","interactions":[],"lastModifiedDate":"2023-04-13T12:18:36.893973","indexId":"70242697","displayToPublicDate":"2022-11-06T07:13:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","docAbstract":"Like many impaired Great Lakes tributaries, Apple Creek, Wisconsin (119 km2) has Total Maximum Daily Load (TMDL) targets for reducing suspended sediment and total phosphorus by 51.2 % and 64.2 %, respectively. From August 2017 - October 2018, a stream sediment budget and fingerprinting integrated study was conducted to quantify upland and stream corridor sources of suspended sediment and sediment-bound phosphorus. Phosphorus concentrations varied among source groups and fluvial sediments, with higher concentrations among suspended sediment and cropland soils. Eroding streambanks identified in the stream corridor sediment budget accounted for 100 % of the TMDL Soil and Water Assessment Tool (SWAT) suspended sediment load but only 20 % of the total phosphorus load. Fine-grained streambed sediment equated to approximately-three years of modeled suspended sediment load but only one third of total phosphorus load. The two primary sources of fine-grained streambed sediment were streambanks and cropland, with relative streambank contributions increasing with downstream direction and watershed area. The relative proportion of suspended sediment varied by season and streamflow; however, cropland and streambank erosion accounted for 54 % and 23 % of the suspended sediment when weighted by of the proportion for representative streamflow. Urban land was a source in the upper watershed, but the signature was sequestered by a mid-watershed detention basin. Contributions from construction sites were higher in the fall 2018, likely corresponding to increased activity following a wet spring. These integrated techniques helped describe sources, transport, and sinks of fluvial sediment and phosphorus throughout the watershed at a range of spatial and temporal scales.
Arthropods are important prey for many avian taxa, particularly during the breeding season. Many studies have used sticky traps to estimate relative abundance of arthropods as avian prey, but we know little about the potential biases associated with sticky traps. We evaluated the effect of small-scale variation in trap placement on the biomass of arthropods caught on sticky traps in six riparian woodlands in southeastern Arizona. We detected differences in arthropod biomass between two height categories (1 and 4 m off the ground) for three insect orders and between two sampling locations (0 and 10 m from the center of the stream bed) for two insect orders. These differences indicate that placement of sticky traps affects arthropod capture rates and, hence, small variation in trap placement can bias investigators' ability to document spatial and temporal differences in arthropod abundance. Investigators who use sticky traps to make comparisons of arthropod abundance need to ensure that placement is consistent over time or across treatments to ensure that comparisons are not biased.
","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-66.4.275","usgsCitation":"LaRoche, D.D., Kirkpatrick, C., and Conway, C.J., 2022, Small-scale variation in trap placement affects arthropod capture rates on sticky traps in riparian woodlands: The Southwestern Naturalist, v. 66, no. 4, p. 275-279, https://doi.org/10.1894/0038-4909-66.4.275.","productDescription":"5 p.","startPage":"275","endPage":"279","ipdsId":"IP-123873","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LaRoche, Dominic D.","contributorId":338468,"corporation":false,"usgs":false,"family":"LaRoche","given":"Dominic","email":"","middleInitial":"D.","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":903288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirkpatrick, Chris","contributorId":338469,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"Chris","email":"","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":903289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903287,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238042,"text":"ofr20221083 - 2022 - Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","interactions":[],"lastModifiedDate":"2022-12-08T18:11:30.705283","indexId":"ofr20221083","displayToPublicDate":"2022-11-04T11:13:16","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1083","displayTitle":"Passage of Adult Coho Salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","title":"Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","docAbstract":"Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (Oncorhynchus kisutch), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.61844237310005,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.17170307975459\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
We describe and interpret deposits associated with the final Ubehebe Crater-forming, phreatomagmatic explosive phase of the multivent, monogenetic Ubehebe volcanic center. Ubehebe volcano is located in Death Valley, California, USA. Pyroclastic deposits occur in four main facies: (1) lapilli- and blockdominated beds, (2) thinly bedded lapilli tuff, (3) laminated and cross-laminated ash, and (4) massive lapilli ash/tuff. Lapilli- and block-dominated beds are found mostly within several hundred meters of the crater and transition outward into discontinuous lenses of lapilli and blocks; they are interpreted to have been deposited by ballistic processes associated with crater-forming explosions. Thinly bedded lapilli tuff is found mainly within several hundred meters, and laminated and cross-laminated ash extends at least 9 km from the crater center. Dune forms are common within ~2 km of the crater center, while finer-grained, distal deposits tend to exhibit planar lamination. These two facies (thinly bedded lapilli tuff and laminated and cross-laminated ash) are interpreted to record multiple pyroclastic surges (dilute pyroclastic currents). Repeated couplets of coarse layers overlain by finer-grained, laminated horizons suggest that many or most of the surges were transient, likely recording individual explosions, and they traveled over complex topography in some areas. These two factors complicate the application of classical sediment-transport theory to quantify surge properties. However, dune-form data provide possible constraints on the relationships between suspended load sedimentation and bed-load transport that are consistent using two independent approaches. Massive lapilli ash/tuff beds occur in drainages below steep slopes and can extend up to ~1 km onto adjacent valley floors beneath large catchments. Although they are massive in texture, their grain-size characteristics are shared with laminated and cross-laminated ash facies, with which they are locally interbedded. These are interpreted to record concentrated granular flows sourced by remobilized pyroclastic surge deposits, either during surge transport or shortly after, while the surge deposits retained their elevated initial pore-gas pressures. Although similar surge-derived concentrated flows have been described elsewhere (e.g., Mount St. Helens, Washington, USA, and Soufriére Hills, Montserrat, West Indies), to our knowledge Ubehebe is the first case where such processes have been identified at a maar volcano. These concentrated flows followed paths that were independent of the pyroclastic surges and represent a potential hazard at similar maar volcanoes in areas with complex terrain.