{"pageNumber":"75","pageRowStart":"1850","pageSize":"25","recordCount":41028,"records":[{"id":70257062,"text":"70257062 - 2024 - Dopaminergic and anti-estrogenic responses in juvenile steelhead (Oncorhynchus mykiss) exposed to bifenthrin","interactions":[],"lastModifiedDate":"2024-08-09T11:05:58.442724","indexId":"70257062","displayToPublicDate":"2024-08-08T06:00:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18327,"text":"Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology","active":true,"publicationSubtype":{"id":10}},"title":"Dopaminergic and anti-estrogenic responses in juvenile steelhead (Oncorhynchus mykiss) exposed to bifenthrin","docAbstract":"

The frequency of detection and concentrations of bifenthrin, a pyrethroid insecticide, in the waterways inhabited by the endangered species, steelhead trout (Oncorhynchus mykiss), has become a significant concern for regulatory agencies. Endocrine disruption has been observed with estrogenic and anti-estrogenic responses in fish species at different life stages. Since several studies have indicated alterations in dopaminergic signaling associated with endocrine responses, juvenile steelhead were exposed to environmentally relevant concentrations of 60 or 120 ng/L bifenthrin for two weeks. Fish brains were assessed for dopamine levels and the expression of genes involved in dopaminergic and estrogenic processes, such as catechol-o-methyltransferase (comt) and monoamine oxidase (mao). Vitellogenin (vtg) and estrogenic receptors (ERα1, ERβ1, and ERβ2) were also evaluated in livers of the animals. Dopamine concentrations were significantly higher in fish brains following bifenthrin exposure. Consistent with a reduction in dopamine clearance, there was a significant decrease in the mRNA expression of comt with increased bifenthrin concentration. Hepatic expression of ERα1 and ERβ2 mRNA was significantly decreased with increased bifenthrin concentration. These data support the possible mechanism of bifenthrin altering the dopaminergic pathway at low ng/L concentrations, in juvenile steelhead, which could interfere with endocrine feedback loops. These findings support the need for and importance of identifying species and life stage differences in pesticide modes of action to reduce uncertainties in risk assessments.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.cbpc.2024.109995","usgsCitation":"Magnuson, J.T., Sy, N.D., Tanabe, P., Ji, C., Gan, J., and Schlenk, D., 2024, Dopaminergic and anti-estrogenic responses in juvenile steelhead (Oncorhynchus mykiss) exposed to bifenthrin: Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, v. 285, 109995, 6 p., https://doi.org/10.1016/j.cbpc.2024.109995.","productDescription":"109995, 6 p.","ipdsId":"IP-162473","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":439225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cbpc.2024.109995","text":"Publisher Index Page"},{"id":432415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":909306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sy, Nathan D.","contributorId":341968,"corporation":false,"usgs":false,"family":"Sy","given":"Nathan","email":"","middleInitial":"D.","affiliations":[{"id":64621,"text":"University of California-Riverside","active":true,"usgs":false}],"preferred":false,"id":909307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanabe, Philip","contributorId":333579,"corporation":false,"usgs":false,"family":"Tanabe","given":"Philip","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":909308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ji, Chenyang","contributorId":341969,"corporation":false,"usgs":false,"family":"Ji","given":"Chenyang","email":"","affiliations":[{"id":64621,"text":"University of California-Riverside","active":true,"usgs":false}],"preferred":false,"id":909309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gan, Jay","contributorId":341971,"corporation":false,"usgs":false,"family":"Gan","given":"Jay","email":"","affiliations":[{"id":64621,"text":"University of California-Riverside","active":true,"usgs":false}],"preferred":false,"id":909310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlenk, Daniel","contributorId":221106,"corporation":false,"usgs":false,"family":"Schlenk","given":"Daniel","email":"","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":909311,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256920,"text":"ofr20241033 - 2024 - A literature review and hypsometric analysis to support decisions on trout management flows on the Colorado River downstream from Glen Canyon Dam","interactions":[],"lastModifiedDate":"2024-08-07T23:06:30.701527","indexId":"ofr20241033","displayToPublicDate":"2024-08-07T10:46:04","publicationYear":"2024","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":"2024-1033","displayTitle":"A Literature Review and Hypsometric Analysis to Support Decisions on Trout Management Flows on the Colorado River Downstream from Glen Canyon Dam","title":"A literature review and hypsometric analysis to support decisions on trout management flows on the Colorado River downstream from Glen Canyon Dam","docAbstract":"

Executive Summary

Fish stranding has been studied in select rivers worldwide, often with the purpose of determining how to mitigate adverse effects of dam operations on highly valued salmon and trout populations. However, where a reduction in trout population size is desired by resource managers, as is the case downstream of the Glen Canyon Dam on the Colorado River, flow manipulations termed trout management flows (TMFs) may be used to optimize fish stranding and mortality. To inform the design and implementation of potential future TMFs, we reviewed relevant literature to identify key factors that influence fish stranding. We found that key factors were highly interdependent and site-specific, but general trends suggest that down-ramping (decreasing flow) at rapid rates in daytime during the late spring to summer emergence period would lead to stranding of age-0 rainbow trout in shallow shoreline habitat. A hypsometric analysis was then used to predict stranding risk for age-0 rainbow trout in Glen Canyon for a range of TMFs, which incorporated existing bathymetric data and flow and habitat suitability models. Our results indicate that a TMF with a steady high flow ranging from 12,000 to 16,000 cubic feet per second (ft3/s) combined with a minimum flow ranging from 3,000 to 5,000 ft3/s may effectively strand age-0 fish while also minimizing risk to water storage in Lake Powell and other resources. This strategy implemented under normal hydropeaking operations was predicted to lead to a substantive stranding risk when paired with low flows of 5,000 ft3/s, and especially 3,000 ft3/s. However, there remains uncertainty associated with elements of implementing an effective TMF downstream from Glen Canyon Dam. The main uncertainties include (1) the down-ramp rate that maximizes stranding of age-0 trout, (2) the duration of drawdown to maximize stranding mortality while minimizing impact to downstream resources, (3) duration of high flows required for age-0 fish to colonize newly created shoreline habitat (this is only for certain TMF hydrographs), (4) number of repetitions of TMF cycles to minimize compensatory survival response, and (5) recruitment threshold of both rainbow and brown trout populations to trigger TMF implementation.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241033","collaboration":"Prepared in cooperation with Ecometric Research Inc.","usgsCitation":"Giardina, M., Korman, J., Yard, M.D., Wright, S., Kaplinski, M., and Bennett, G., 2024, A literature review and hypsometric analysis to support decisions on trout management flows on the Colorado River downstream from Glen Canyon Dam: U.S. Geological Survey Open-File Report 2024–1033, 50 p., https://doi.org/10.3133/ofr20241033.","productDescription":"Report: viii, 50 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-133316","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":432181,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241033/full"},{"id":432178,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L1XEZO","text":"USGS Data Release","description":"Korman, J., Giardina, M.A., Yard, M.D., Wright, S.A., Kaplinski, M., and Bennett, G., 2024, Colorado River milage system and ancillary attribute data for connecting to hydrodynamic model output in Glen Canyon, AZ: U.S. Geological Survey data release, https://doi.org/10.5066/P9L1XEZO.","linkHelpText":"Colorado River milage system and ancillary attribute data for connecting to hydrodynamic model output in Glen Canyon, AZ"},{"id":432177,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1033/ofr20241033.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432179,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1033/ofr20241033.xml"},{"id":432180,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1033/images"},{"id":432176,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1033/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Glen Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.636412112225,\n 36.82347668968964\n ],\n [\n -111.44233548505323,\n 36.82347668968964\n ],\n [\n -111.44233548505323,\n 36.96315377672772\n ],\n [\n -111.636412112225,\n 36.96315377672772\n ],\n [\n -111.636412112225,\n 36.82347668968964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2024-08-07","noUsgsAuthors":false,"publicationDate":"2024-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Giardina, Mariah","contributorId":341843,"corporation":false,"usgs":true,"family":"Giardina","given":"Mariah","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":909002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":909003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":169281,"corporation":false,"usgs":true,"family":"Yard","given":"Michael","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":909004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":909005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, Matthew A. 0000-0001-6232-8325","orcid":"https://orcid.org/0000-0001-6232-8325","contributorId":333646,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":909006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennett, Glenn gbennett@usgs.gov","contributorId":292564,"corporation":false,"usgs":false,"family":"Bennett","given":"Glenn","email":"gbennett@usgs.gov","affiliations":[],"preferred":true,"id":909007,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70270165,"text":"70270165 - 2024 - The 2023 Alaska National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2025-08-12T14:54:28.804879","indexId":"70270165","displayToPublicDate":"2024-08-07T07:48:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2023 Alaska National Seismic Hazard Model","docAbstract":"

US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) are used extensively for seismic design regulations in the United States and earthquake scenario development, as well as risk assessment and mitigation for both buildings and infrastructure. This 2023 update of the long-term, time-independent Alaska NSHM includes substantial changes to both the earthquake rupture forecast (ERF) and ground motion models (GMMs). The ERF includes numerous additions to the finite-fault model, considers two deformation models, and introduces updated declustering and smoothing algorithms in the gridded background seismicity model. For the Alaska–Aleutian subduction zone, megathrust earthquakes occur on an updated structural and segmentation model, and the moment magnitude (M) 8+ rupture and rate model include a logic tree branch that considers slip rates derived from geodetic models of interface coupling. The megathrust model considers multiple models of down-dip width, and magnitudes are computed using newly developed scaling relations. For subduction intraslab events and subduction interface events with M < 7, the 2023 update uses a smoothed seismicity model with rupture depths derived from Slab2. The 2023 model updates GMMs in all tectonic settings using the recently published Next Generation Attenuation Subduction (NGA-Sub) GMMs for subduction interface and intraslab events, and the NGA-West2 GMMs for active crustal settings. Collectively, additions and updates to the Alaska NSHM result in hazard increases across most of south-central Alaska relative to the previous model, published in 2007. These changes are primarily due to the adoption of updated rate models for the large-magnitude interface events and the NGA-Sub GMMs that have much higher aleatory variability (sigma), consistent with global observations, and that include models of epistemic uncertainty.

","language":"English","publisher":"SAGE Publications","doi":"10.1177/87552930241266741","usgsCitation":"Powers, P.M., Altekruse, J.M., Llenos, A.L., Michael, A.J., Haynie, K.L., Haeussler, P., Bender, A., Rezaeian, S., Moschetti, M.P., Smith, J.A., Briggs, R.W., Witter, R.C., Mueller, C., Zeng, Y., Girot, D.L., Herrick, J.A., Shumway, A., and Petersen, M.D., 2024, The 2023 Alaska National Seismic Hazard Model: Earthquake Spectra, v. 40, no. 4, p. 2545-2597, https://doi.org/10.1177/87552930241266741.","productDescription":"53 p.","startPage":"2545","endPage":"2597","ipdsId":"IP-155656","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494194,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241266741","text":"Publisher Index 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Invasive annual grasses are often facilitated by fire, yet they can become ecologically dominant in susceptible locations even in the absence of fire. We used an extensive vegetation plot database to model susceptibility to the invasive annual grass cheatgrass (Bromus tectorum L.) in the sagebrush biome as a function of climate and soil water availability variables. We built random forest models predicting cheatgrass presence or dominance (greater than 15 % relative cover) under unburned (37,219 plots) and burned conditions (6340 plots). We mapped predicted probability of cheatgrass presence and dominance, conditional on burning. We combined predicted susceptibility with burn probability to quantify the 10-year total risk of cheatgrass dominance. Finally, we identified portions of the landscape (1) at risk of fire-induced conversion to cheatgrass dominance, (2) consistently susceptible to cheatgrass dominance, or (3) consistently resistant to cheatgrass dominance. At the scale of the sagebrush biome, we found that abiotic susceptibility to cheatgrass dominance drives total risk, regardless of fire. At local scales (i.e., individual 30 m pixels), burning increased the probability of cheatgrass dominance by a median of 14 %. Threshold-based analyses indicate that 10–31 % of the sagebrush biome was at risk of fire-induced dominance, with 55 % exhibiting abiotic resistance and 5 % exhibiting abiotic susceptibility to dominance regardless of fire. Burn probability was higher in areas predicted to be susceptible to dominance, illustrating how cheatgrass invasion can cause ecosystem conversions that are then sustained by grass-fire cycles. Disentangling the influence of abiotic conditions and fire contributes to our understanding of the mechanisms driving invasion dynamics, and modeling the probability of dominance can help anticipate where ecological transformations are at risk of occurring. Our approach can facilitate the prioritization of management actions in the sagebrush biome and be used as a framework for modeling invasion risk in other disturbance-prone ecosystems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110737","usgsCitation":"Urza, A.K., Board, D.I., Bradford, J., Brown, J.L., Chambers, D.R., Schlaepfer, D.R., and Short, K.C., 2024, Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome: Biological Conservation, v. 297, 110737, 14 p., https://doi.org/10.1016/j.biocon.2024.110737.","productDescription":"110737, 14 p.","ipdsId":"IP-163547","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":466970,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2024.110737","text":"Publisher Index Page"},{"id":462431,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.38170765935128,\n 49.047724062278405\n ],\n [\n -120.32300963112243,\n 34.387472184773415\n ],\n [\n -103.22828306862252,\n 34.387472184773415\n ],\n [\n -103.0521889839356,\n 49.04575364957779\n ],\n [\n -120.38170765935128,\n 49.047724062278405\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"297","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Urza, Alexandra K. 0000-0001-9795-6735","orcid":"https://orcid.org/0000-0001-9795-6735","contributorId":261259,"corporation":false,"usgs":false,"family":"Urza","given":"Alexandra","email":"","middleInitial":"K.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":914454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Board, David I.","contributorId":261260,"corporation":false,"usgs":false,"family":"Board","given":"David","email":"","middleInitial":"I.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":914455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":914456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":914457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chambers, Daniel R. 0000-0003-3111-269X","orcid":"https://orcid.org/0000-0003-3111-269X","contributorId":344664,"corporation":false,"usgs":false,"family":"Chambers","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":82408,"text":"USDA Forest Service, Rocky Mountain Research Station, Reno, Nevada U.S.A.","active":true,"usgs":false}],"preferred":false,"id":914458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Short, Karen C.","contributorId":335894,"corporation":false,"usgs":false,"family":"Short","given":"Karen","email":"","middleInitial":"C.","affiliations":[{"id":80571,"text":"U.S. Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory, 5775 W Broadway Street, Missoula, Montana 59808, USA","active":true,"usgs":false}],"preferred":false,"id":914460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70257043,"text":"70257043 - 2024 - Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance","interactions":[],"lastModifiedDate":"2024-08-09T16:14:16.630524","indexId":"70257043","displayToPublicDate":"2024-08-06T10:54:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance","docAbstract":"

Understanding the movement patterns of an invasive species can be a powerful tool in designing effective management and control strategies. Here, we used a Bayesian multistate model to investigate the movement of two invasive carp species, silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis), using acoustic telemetry. The invaded portions of the Illinois and Des Plaines Rivers, USA, are a high priority management zone in the broader efforts to combat the spread of invasive carps from reaching the Laurentian Great Lakes. Our main objective was to characterize the rates of upstream and downstream movements by carps between river pools that are maintained by navigation lock and dam structures. However, we also aimed to evaluate the efficacy of the available telemetry infrastructure to monitor carp movements through this system. We found that, on a monthly basis, most individuals of both species remained within their current river pools: averaging 76.2% of silver carp and 75.5% of bighead carp. Conversely, a smaller proportion of silver carp, averaging 14.2%, and bighead carp, averaging 13.9%, moved to downstream river pools. Movements towards upstream pools were the least likely for both species, with silver carp at an average of 6.7% and bighead carp at 7.9%. The highest probabilities for upstream movements were for fish originating from the three most downstream river pools, where most of the population recruitment occurs. However, our evaluation of the telemetry array’s effectiveness indicated low probability to detect fish in this portion of the river. We provide insights to enhance the placement and use of these monitoring tools, aiming to deepen our comprehension of these species’ movement patterns in the system.

","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.17834","usgsCitation":"Stanton, J.C., Brey, M.K., Coulter, A.A., Stewart, D.R., and Knights, B., 2024, Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance: PeerJ, v. 12, e17834, 24 p., https://doi.org/10.7717/peerj.17834.","productDescription":"e17834, 24 p.","ipdsId":"IP-151880","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":439228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.17834","text":"Publisher Index Page"},{"id":432445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.49554914748546,\n 41.90688869415442\n ],\n [\n -89.45630498792075,\n 41.4339499690158\n ],\n [\n -90.8325528903585,\n 39.87365631252747\n ],\n [\n -90.76518343836855,\n 38.31770023259065\n ],\n [\n -89.99975174472505,\n 40.02128386582143\n ],\n [\n -88.86084431751425,\n 41.19214478105948\n ],\n [\n -87.61745601726525,\n 41.47177424129181\n ],\n [\n -87.49554914748546,\n 41.90688869415442\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":909278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":909279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, Alison A.","contributorId":90992,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[{"id":26877,"text":"Southern Illinois University, Carbondale, IL","active":true,"usgs":false},{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":909281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, David R.","contributorId":337778,"corporation":false,"usgs":false,"family":"Stewart","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":40296,"text":"United States Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":909282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knights, Brent C. 0000-0001-8526-8468","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":304124,"corporation":false,"usgs":false,"family":"Knights","given":"Brent","middleInitial":"C.","affiliations":[{"id":65975,"text":"UMESC Retired","active":true,"usgs":false}],"preferred":false,"id":909280,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70276625,"text":"70276625 - 2024 - Using models of local environmental conditions for biological assessment","interactions":[],"lastModifiedDate":"2026-06-12T14:53:10.691042","indexId":"70276625","displayToPublicDate":"2024-08-06T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Using models of local environmental conditions for biological assessment","docAbstract":"

A common approach for biological assessment is to compare current observations of biota at a site to predictions of the biota that would occur if the site were in reference condition. To estimate these reference expectations, predictive bioassessment models use only data collected at reference sites and estimate relationships between biota and environmental variables that are unaffected by human activities (i.e., immutable variables). However, in some areas where human activities are pervasive, few reference sites are available. Here, we introduce a new approach for bioassessment, in which we first estimate relationships between widely available measurements of both immutable and human-influenced landscape variables and local environmental conditions (conductivity, dissolved total P, total suspended solids, percentage of sand and fines in the substrate, and dissolved organic C), and then we estimate the relationship between these local environmental variables and total macroinvertebrate richness. We then calculate the values of the local environmental variables under reference conditions by adjusting predictors that are strongly influenced by human activities to levels that are consistent with those observed at reference sites. Reference values of local environmental variables are then combined with the model for taxon richness to calculate taxon richness expected under reference conditions. Predictions of total taxon richness in validation data using the new approach are similar in accuracy and precision as predictions calculated using a traditional approach that focuses only on reference site data. The new approach complements existing bioassessment methods by highlighting types of sites in which estimates of reference expectations are uncertain and by improving our understanding of how instream stressors affect expected total taxon richness.

","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/731770","usgsCitation":"Yuan, L.L., Carlisle, D.M., Mitchell, R., and Pollard, A.I., 2024, Using models of local environmental conditions for biological assessment: Freshwater Science, v. 43, no. 3, p. 325-339, https://doi.org/10.1086/731770.","productDescription":"15 p.","startPage":"325","endPage":"339","ipdsId":"IP-157907","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":505550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 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Division","active":true,"usgs":true}],"preferred":true,"id":962888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Richard M.","contributorId":215406,"corporation":false,"usgs":false,"family":"Mitchell","given":"Richard M.","affiliations":[{"id":39239,"text":"USEPA, Washington D.C.","active":true,"usgs":false}],"preferred":false,"id":962889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollard, Amina I.","contributorId":372181,"corporation":false,"usgs":false,"family":"Pollard","given":"Amina","middleInitial":"I.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":962890,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267863,"text":"70267863 - 2024 - Risk of capture is modified by hypoxia and interjurisdictional migration of Lake Whitefish (Coregonus clupeaformis)","interactions":[],"lastModifiedDate":"2025-06-05T14:53:00.097594","indexId":"70267863","displayToPublicDate":"2024-08-05T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Risk of capture is modified by hypoxia and interjurisdictional migration of Lake Whitefish (Coregonus clupeaformis)","docAbstract":"Interjurisdictional migrations lead to seasonally changing patterns of exploitation risk, emphasizing the importance of spatially explicit approaches to fishery management. Understanding how risk changes along a migration route supports time-area based fishery management, but quantifying risk can be complicated when multiple fishing methods are geographically segregated and when bycatch species are considered. Further, habitat selection in dynamic environments can influence migration behavior, interacting with other management objectives such as water quality and habitat restoration. As a case study, we examined a novel acoustic telemetry data set for Lake Whitefish in Lake Erie, where they migrate through multiple spatial management units that are variably affected by seasonal hypoxia and host a variety of fisheries. Combining telemetry results with fishery catch and water quality monitoring, we demonstrate three exploitation risk scenarios: i) high risk due to high residency and high catch, ii) high risk due to high residency in time-areas with moderate catch, and iii) low risk due to residency in time-areas with low catch. Interestingly, occupation of low risk refugia was increased by the development of hypoxia in adjacent areas. Consequently, fishery management goals to sustainably manage other target species may be directly and indirectly linked to water quality management goals through Lake Whitefish.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-024-65147-5","usgsCitation":"Kraus, R., Cook, H., Sakis, A., MacDougall, T., Faust, M., Schmitt, J., and Vandergoot, C., 2024, Risk of capture is modified by hypoxia and interjurisdictional migration of Lake Whitefish (Coregonus clupeaformis): Scientific Reports, v. 14, no. 1, 180061, 13 p., https://doi.org/10.1038/s41598-024-65147-5.","productDescription":"180061, 13 p.","ipdsId":"IP-161549","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-65147-5","text":"Publisher Index Page"},{"id":489682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United Sates","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.3340237734879,\n 42.2003107892165\n ],\n [\n -83.76123811265276,\n 41.36759241460828\n ],\n [\n -81.80316880718208,\n 41.3146825621337\n ],\n [\n -78.64522615109004,\n 42.56891605267103\n ],\n [\n -78.69689358833503,\n 42.91401349265345\n ],\n [\n -79.6373646641363,\n 43.07393720267635\n ],\n [\n -81.57717526647028,\n 42.625802175312444\n ],\n [\n -83.3340237734879,\n 42.2003107892165\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":939160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, H. Andrew","contributorId":181530,"corporation":false,"usgs":false,"family":"Cook","given":"H. Andrew","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":939161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sakis, Alexis","contributorId":356356,"corporation":false,"usgs":false,"family":"Sakis","given":"Alexis","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":939162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDougall, Thomas","contributorId":354792,"corporation":false,"usgs":false,"family":"MacDougall","given":"Thomas","affiliations":[{"id":84663,"text":"Ontario Ministry of Nat. Res. and Forestry","active":true,"usgs":false}],"preferred":false,"id":939163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Faust, Matthew","contributorId":268770,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":939164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":939165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vandergoot, Christopher","contributorId":340837,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":939166,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70258147,"text":"70258147 - 2024 - A robust quantitative method to distinguish runoff-generated debris flows from floods","interactions":[],"lastModifiedDate":"2024-09-05T14:28:51.565094","indexId":"70258147","displayToPublicDate":"2024-08-04T09:26:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"A robust quantitative method to distinguish runoff-generated debris flows from floods","docAbstract":"

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric (Q*) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL109768","usgsCitation":"Cavagnaro, D.B., McCoy, S., Kean, J.W., Thomas, M.A., Lindsay, D.N., McArdell, B.W., and Hirschberg, J., 2024, A robust quantitative method to distinguish runoff-generated debris flows from floods: Geophysical Research Letters, v. 51, no. 15, e2024GL109768, 11 p., https://doi.org/10.1029/2024GL109768.","productDescription":"e2024GL109768, 11 p.","ipdsId":"IP-159087","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":439232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl109768","text":"Publisher Index Page"},{"id":433497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"15","noUsgsAuthors":false,"publicationDate":"2024-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":912366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":912367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":912370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McArdell, Brian W.","contributorId":269977,"corporation":false,"usgs":false,"family":"McArdell","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":40850,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research","active":true,"usgs":false}],"preferred":false,"id":912371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hirschberg, Jacob","contributorId":301934,"corporation":false,"usgs":false,"family":"Hirschberg","given":"Jacob","affiliations":[{"id":65368,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research, Birmensdorf, Switzerland; Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":912372,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264829,"text":"70264829 - 2024 - Observations of flocs in an estuary and implications for computation of settling velocity","interactions":[],"lastModifiedDate":"2025-03-26T15:29:46.647918","indexId":"70264829","displayToPublicDate":"2024-08-04T08:01:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Observations of flocs in an estuary and implications for computation of settling velocity","docAbstract":"

The settling velocity (ws) in estuarine environments can impact whether a region is eroding or accreting sediment on the bed, yet determining this rate can be an indirect process requiring a number of assumptions. Accurate determination of ws is especially needed for numerical models to reproduce observed sediment concentrations at the appropriate timescale. We collected information on suspended sediment flocculation at a channel site (13 m deep) and a shallows site (4 m deep) within South San Francisco Estuary, alongside timeseries of flow, wave statistics, turbulent shear, and bottle samples analyzed for both ws and particle size. Using the measurements of floc size and settling velocity, we performed a sensitivity analysis on the unknown parameters in the general explicit formula for settling velocity. The collected particle size distribution data show that multiple classes of flocs are present; these are characterized as flocculi, microflocs, and macroflocs. We show that ws of flocculi is closest to ws for the full distribution. The determined parameter values lead to near-bed mass-weighted settling velocities (standard deviation) of 1.18 (0.55) and 0.22 (0.15) mm/s at the channel and shallows sites, respectively. Modeling efforts can use this work to help select an appropriate sediment model and parameter values.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JC019402","usgsCitation":"Allen, R., Livsey, D., and McGill, S., 2024, Observations of flocs in an estuary and implications for computation of settling velocity: Journal of Geophysical Research: Oceans, v. 129, no. 8, e2022JC019402, 21 p., https://doi.org/10.1029/2022JC019402.","productDescription":"e2022JC019402, 21 p.","ipdsId":"IP-143577","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488664,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jc019402","text":"Publisher Index Page"},{"id":483876,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.73260724811783,\n 38.375373912625804\n ],\n [\n -123.73260724811783,\n 37.14063832700886\n ],\n [\n -121.47531521074498,\n 37.14063832700886\n ],\n [\n -121.47531521074498,\n 38.375373912625804\n ],\n [\n -123.73260724811783,\n 38.375373912625804\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Rachel 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":216002,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Livsey, Daniel","contributorId":352687,"corporation":false,"usgs":false,"family":"Livsey","given":"Daniel","affiliations":[{"id":37600,"text":"Queensland University of Technology","active":true,"usgs":false}],"preferred":false,"id":932005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGill, Samantha C. 0000-0001-9320-8764","orcid":"https://orcid.org/0000-0001-9320-8764","contributorId":304095,"corporation":false,"usgs":true,"family":"McGill","given":"Samantha C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932006,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70262363,"text":"70262363 - 2024 - Clustering and unconstrained ordination with Dirichlet process mixture models","interactions":[],"lastModifiedDate":"2025-01-16T17:42:37.701078","indexId":"70262363","displayToPublicDate":"2024-08-02T11:33:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Clustering and unconstrained ordination with Dirichlet process mixture models","docAbstract":"
  1. Assessment of similarity in species composition or abundance across sampled locations is a common goal in multi-species monitoring programs. Existing ordination techniques provide a framework for clustering sample locations based on species composition by projecting high-dimensional community data into a low-dimensional, latent ecological gradient representing species composition. However, these techniques require specification of the number of distinct ecological communities present in the latent space, which can be difficult to determine in advance.
  2. We develop an ordination model capable of simultaneous clustering and ordination that allows for estimation of the number of clusters present in the latent ecological gradient. This model draws latent coordinates for each sample location from a Dirichlet process mixture model, affording researchers with probabilistic statements about the number of clusters present in the latent ecological gradient.
  3. The model is compared to existing methods for simultaneous clustering and ordination via simulation and applied to two empirical datasets; JAGS code to fit the proposed model is provided in an appendix. The first dataset concerns presence-absence records of fish in the Doubs river in eastern France and the second dataset describes presence-absence records of plant species in Craters of the Moon National Monument and Preserve (CRMO) in Idaho, USA. Results from both analyses align with existing ecological gradients at each location.
  4. Development of the Dirichlet process ordination model provides wildlife managers with data-driven inferences about the number of distinct communities present across monitored locations, allowing for more cost-effective monitoring and reliable decision-making for conservation management.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14389","usgsCitation":"Stratton, C., Hoegh, A., Rodhouse, T., Green, J., Banner, K., and Irvine, K., 2024, Clustering and unconstrained ordination with Dirichlet process mixture models: Methods in Ecology and Evolution, v. 15, no. 9, p. 1720-1732, https://doi.org/10.1111/2041-210X.14389.","productDescription":"13 p.","startPage":"1720","endPage":"1732","ipdsId":"IP-149492","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14389","text":"Publisher Index Page"},{"id":466648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":923932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoegh, Andrew","contributorId":265906,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":923933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodhouse, Thomas","contributorId":244880,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":923934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, Jennifer L.","contributorId":349024,"corporation":false,"usgs":false,"family":"Green","given":"Jennifer L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":923935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banner, Katharine M.","contributorId":244876,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":923936,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":221555,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":923937,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262796,"text":"70262796 - 2024 - Wide-ranging migration of post-nesting hawksbill sea turtles (Eretmochelys imbricata) from the Caribbean island of Nevis","interactions":[],"lastModifiedDate":"2025-01-23T15:23:20.197825","indexId":"70262796","displayToPublicDate":"2024-08-02T09:18:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Wide-ranging migration of post-nesting hawksbill sea turtles (Eretmochelys imbricata) from the Caribbean island of Nevis","title":"Wide-ranging migration of post-nesting hawksbill sea turtles (Eretmochelys imbricata) from the Caribbean island of Nevis","docAbstract":"

Little is known about the post-nesting migration and foraging areas of hawksbill turtles (Eretmochelys imbricata) nesting on St. Kitts and Nevis, an important nesting site for hawksbills in the eastern Caribbean. To elucidate internesting, migration and foraging patterns of hawksbills from Nevis, we satellite tagged 28 post-nesting turtles between 2006 and 2022. Internesting, migrating and foraging activity periods were determined using a switching state–space model to estimate the behavioral state of the turtle’s locations. Twenty-five turtles (83–2,171 tracking days) established a foraging area, migrating between 5.3 and 2,799.5 km from the nesting beach. Twenty-one turtles were tracked during internesting movements with internesting areas ranging between 1.9 and 28.2 km2. Nearly half of the internesting centroids were located closer to a different beach than the beach where the turtle was originally encountered nesting. Hawksbills crossed through 29 different Exclusive Economic Zones (EEZs), including zones with legal sea turtle fisheries or traditional subsistence use. Core foraging areas (KDE 50%) ranged between 3.8 and 69.0 km2. Nearly a third of foraging centroids were within a Marine Protected Area (MPA), while nearly a quarter were within a legal sea turtle fishery EEZ. Hawksbills nesting on Nevis disperse to local, regional, and Caribbean wide foraging grounds, emphasizing the necessity of cooperative efforts to protect turtles and their habitats to ensure support of the recovery of hawksbill turtles throughout the wider Caribbean.

","language":"English","publisher":"Springer","doi":"10.1007/s00227-024-04491-6","usgsCitation":"Evans, D.R., Pemberton, L., and Carthy, R., 2024, Wide-ranging migration of post-nesting hawksbill sea turtles (Eretmochelys imbricata) from the Caribbean island of Nevis: Marine Biology, v. 171, 171, 16 p., https://doi.org/10.1007/s00227-024-04491-6.","productDescription":"171, 16 p.","ipdsId":"IP-161346","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00227-024-04491-6","text":"Publisher Index Page"},{"id":480988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saint Kitts and Nevis","otherGeospatial":"Caribbean, Nevis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.72100737406826,\n 25.303247272191882\n ],\n [\n -89.72100737406826,\n 10.779361764328613\n ],\n [\n -57.461761139581384,\n 10.779361764328613\n ],\n [\n -57.461761139581384,\n 25.303247272191882\n ],\n [\n -89.72100737406826,\n 25.303247272191882\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"171","noUsgsAuthors":false,"publicationDate":"2024-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Daniel R.","contributorId":331390,"corporation":false,"usgs":false,"family":"Evans","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":79193,"text":"Sea Turtle Conservancy, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":924801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pemberton, Lemuel","contributorId":349785,"corporation":false,"usgs":false,"family":"Pemberton","given":"Lemuel","affiliations":[{"id":83514,"text":"Nevis Turtle Group","active":true,"usgs":false}],"preferred":false,"id":924802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924803,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264138,"text":"70264138 - 2024 - Evaluation of techniques for estimating the age and growth of known‐age White Sturgeon","interactions":[],"lastModifiedDate":"2025-03-07T15:24:54.336028","indexId":"70264138","displayToPublicDate":"2024-08-02T08:16:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of techniques for estimating the age and growth of known‐age White Sturgeon","docAbstract":"

Objective

Successful conservation and management of fishes require an understanding of their age and growth. However, methods for estimating the age and growth of long-lived fish species are difficult to validate. The Kootenai River basin has a decades-long mark–recapture program for endangered White Sturgeon Acipenser transmontanus. The mark–recapture history information for White Sturgeon allowed for the evaluation of fin rays for age and growth analysis.

Methods

Age was estimated from pectoral fin rays of known‐age White Sturgeon (n = 162) to evaluate ageing accuracy and precision. Lengths were back‐calculated using four models and measurements obtained from two fin ray transects (i.e., lateral and posterior).

Result

Between-reader agreement for White Sturgeon ages was 58.7%. Consensus age agreement with known ages was poor (30.7%) and decreased with age. Among the four back-calculation models, the Fraser–Lee model provided the lowest root mean square error and percent error. Estimates of mean back-calculated lengths at age derived from the Fraser–Lee model were similar between the two measurement transects. Back-calculated lengths at age were similar to known lengths at age.

Conclusion

Ageing of White Sturgeon using fin rays was unreliable, and accuracy decreased with fish age. Back-calculated lengths at age were accurate using measurements from fin rays of known-age fish. Length estimates from the two measurement transects were similar when using the Fraser–Lee method, suggesting that they may be used interchangeably.

","language":"English","publisher":"Wiley","doi":"10.1002/nafm.11021","usgsCitation":"Ghere, C., Hardy, R.S., Wilson, S., and Quist, M.C., 2024, Evaluation of techniques for estimating the age and growth of known‐age White Sturgeon: North American Journal of Fisheries Management, v. 44, no. 4, p. 880-889, https://doi.org/10.1002/nafm.11021.","productDescription":"10 p.","startPage":"880","endPage":"889","ipdsId":"IP-159650","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11021","text":"Publisher Index Page"},{"id":483052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Idaho, Montana","otherGeospatial":"British Columbia, Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.01115919803547,\n 49.581745610583226\n ],\n [\n -118.01115919803547,\n 48.153450574705346\n ],\n [\n -115.33492252918343,\n 48.153450574705346\n ],\n [\n -115.33492252918343,\n 49.581745610583226\n ],\n [\n -118.01115919803547,\n 49.581745610583226\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ghere, Courtnie L.","contributorId":352032,"corporation":false,"usgs":false,"family":"Ghere","given":"Courtnie","middleInitial":"L.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":929930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":929931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Sean","contributorId":352033,"corporation":false,"usgs":false,"family":"Wilson","given":"Sean","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":929932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":929933,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257321,"text":"70257321 - 2024 - Environmental drivers and spatial patterns of antibiotic-resistant, enteric coliforms across a forest–urban riverscape","interactions":[],"lastModifiedDate":"2024-09-11T16:25:03.119913","indexId":"70257321","displayToPublicDate":"2024-08-02T07:19:11","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Environmental drivers and spatial patterns of antibiotic-resistant, enteric coliforms across a forest–urban riverscape","docAbstract":"

Antibiotic resistant bacteria are prevalent environmental contaminants in freshwaters, and antibiotic resistance genes circulate throughout the urban water cycle. The increase of antibiotic resistant pathogens threatens public health through direct and indirect exposure, and natural resource managers need information on the spatial patterns of antibiotic resistant bacteria and environmental factors associated with their distribution to improve water quality monitoring and to better assess human, animal, and environmental health risks. We collected water and epilithic biofilm samples and measured physicochemical environmental variables at 29 sites distributed longitudinally in the Green-Duwamish River basin, Washington, USA. We characterized catchment-wide patterns of gram-negative fecal indicator bacteria and hypothesized that the presence of antibiotic resistance would be associated with environmental heterogeneity, bacterial primary ecology, stream compartment, and stream type. Antibiotic resistance was determined by microbial growth on selective media supplemented with 3 different antibiotics (ampicillin, chloramphenicol, or tetracycline). Phenotypic antibiotic resistance was positively associated with disturbance, but resistance to at least 1 antibiotic was also detected in undeveloped river segments, with an 83% overall detection rate (i.e., 24 out of 29 sites, 17 in the mainstem and 7 in tributaries). The most probable number of Escherichia coli was associated with higher levels of antibiotic resistance of non-E. coli coliforms across the basin (ρ = 0.38, p < 0.01) but was not associated with antibiotic resistance of E. coli. Phenotypic resistance was highest among non-E. coli coliforms in the water column of tributaries draining moderately to extensively developed subcatchments. Generalized linear mixed-effects model results showed that 18% of the variance in presence of antibiotic resistance was explained by the fixed effects (summed CV across environmental variables, stream type, primary ecology, and stream compartment), and when a spatial random effect was included, the model explained 27% of the variance. Our study provides new evidence that environmental factors and bacterial primary ecology are important underlying factors associated with spatial patterns of antibiotic resistant enteric coliforms. We used macroecological concepts and a riverscape approach to characterize the distribution of antibiotic resistance with methods applicable to municipalities.

","language":"English","publisher":"University of Chicago Press","doi":"10.1086/731976","usgsCitation":"Klock, A.M., Torgersen, C.E., Roberts, M.C., Vogt, D.J., and Vogt, K.A., 2024, Environmental drivers and spatial patterns of antibiotic-resistant, enteric coliforms across a forest–urban riverscape: Freshwater Science, v. 43, no. 3, p. 231-249, https://doi.org/10.1086/731976.","productDescription":"19 p.","startPage":"231","endPage":"249","ipdsId":"IP-100689","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":432756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Klock, Angela M","contributorId":342283,"corporation":false,"usgs":false,"family":"Klock","given":"Angela","email":"","middleInitial":"M","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":909967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":909969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Marilyn C","contributorId":342285,"corporation":false,"usgs":false,"family":"Roberts","given":"Marilyn","email":"","middleInitial":"C","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":909968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogt, Daniel J","contributorId":342289,"corporation":false,"usgs":false,"family":"Vogt","given":"Daniel","email":"","middleInitial":"J","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":909970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogt, Kristiina A","contributorId":342291,"corporation":false,"usgs":false,"family":"Vogt","given":"Kristiina","email":"","middleInitial":"A","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":909971,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257086,"text":"70257086 - 2024 - Peri-Gondwanan sediment in the Arkoma Basin derived from the north: The detrital zircon record of a uniquely concentrated non-Laurentian source signal in the late Paleozoic","interactions":[],"lastModifiedDate":"2024-10-07T16:14:46.422867","indexId":"70257086","displayToPublicDate":"2024-08-02T06:46:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Peri-Gondwanan sediment in the Arkoma Basin derived from the north: The detrital zircon record of a uniquely concentrated non-Laurentian source signal in the late Paleozoic","docAbstract":"

During the assembly of Pangea, peri-Gondwanan terranes collided with the eastern and southern margins of Laurentia and brought with them unique detrital zircon U-Pb signatures. Discriminating between individual peri-Gondwanan terranes in the detrital record is difficult due to their similar geologic histories. However, characterization of this provenance is critical for understanding late Paleozoic sediment routing during development of Pangea. Along southeastern Laurentia, in the Arkoma Basin (present-day Arkansas and eastern Oklahoma, southeastern United States), we identified Middle Pennsylvanian (Desmoinesian) strata that exhibit a concentrated peri-Gondwanan detrital zircon signature (e.g., ca. 800–550 Ma). Although several southern peri-Gondwanan terranes (e.g., Maya, Suwannee) are closer to the Arkoma Basin, geologic data, such as predominantly north-to-south paleocurrents and proximal-to-distal facies relationships in these Desmoinesian strata, support a northern source (e.g., Ganderia, Avalonia, Meguma). Further evidence of a northern source comes from detrital zircon source mapping, which reveals the persistence of this peri-Gondwanan signal in depocenters to the north of the basin after the signal had diminished in the Arkoma Basin. To this end, bottom-up detrital zircon source modeling, source mapping, regional stratigraphy, paleocurrent data, and sandstone petrography allow us to reconstruct the evolution of this Middle Pennsylvanian (Desmoinesian) sediment pathway in the context of intraplate and plate-margin tectonic activity. This reconstruction documents processes affecting Earth’s surface (e.g., tectonics, climate) during the assembly of Pangea and describes in detail part of a dynamic continental-scale drainage system.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02740.1","usgsCitation":"Smith, T.M., Dechesne, M., Hirtz, J.A., Sharman, G.R., Hudson, M.R., Lutz, B.M., and Griffis, N.P., 2024, Peri-Gondwanan sediment in the Arkoma Basin derived from the north: The detrital zircon record of a uniquely concentrated non-Laurentian source signal in the late Paleozoic: Geosphere, v. 20, no. 5, p. 1286-1314, https://doi.org/10.1130/GES02740.1.","productDescription":"29 p.","startPage":"1286","endPage":"1314","ipdsId":"IP-159412","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":486904,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02740.1","text":"Publisher Index Page"},{"id":432430,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Tyson Michael 0000-0003-2834-3526","orcid":"https://orcid.org/0000-0003-2834-3526","contributorId":330276,"corporation":false,"usgs":true,"family":"Smith","given":"Tyson","email":"","middleInitial":"Michael","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":909355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":909356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirtz, Jaime Ann Megumi 0000-0002-6701-0137","orcid":"https://orcid.org/0000-0002-6701-0137","contributorId":292911,"corporation":false,"usgs":true,"family":"Hirtz","given":"Jaime","email":"","middleInitial":"Ann Megumi","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":909357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharman, Glenn R.","contributorId":341980,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":909358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Mark R. 0000-0003-4447-7989 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-4447-7989","contributorId":341982,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark","email":"mhudson@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":909359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lutz, Brandon Michael 0000-0002-6580-9025","orcid":"https://orcid.org/0000-0002-6580-9025","contributorId":299272,"corporation":false,"usgs":true,"family":"Lutz","given":"Brandon","email":"","middleInitial":"Michael","affiliations":[{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"preferred":true,"id":909360,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffis, Neil Patrick 0000-0002-2506-7549","orcid":"https://orcid.org/0000-0002-2506-7549","contributorId":330218,"corporation":false,"usgs":true,"family":"Griffis","given":"Neil","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":909361,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70257114,"text":"70257114 - 2024 - Wave propagation in layered soil deposits","interactions":[],"lastModifiedDate":"2026-04-10T13:18:46.134058","indexId":"70257114","displayToPublicDate":"2024-08-01T11:02:01","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wave propagation in layered soil deposits","docAbstract":"

Recent advances in the general theory of viscoelastic waves and rays in layered media provide a rigorous mathematical framework for site-specific, soil-response models used for earthquake resistant design. The advances provide general closed-form anelastic solutions for the classic problems of the response of a stack of soil layers to S and P waves, ray theory for reflected and refracted waves, Rayleigh- and Love-Type surface waves, and head waves. These general solutions valid for anelastic media regardless of the amount of material damping yield new insights regarding the characteristics of seismic waves and their ray paths that are not provided by conventional models. They provide corresponding numerical ground-response models and ray-tracing computation algorithms that account for changes in velocity and attenuation of anelastic waves associated with changes in inhomogeneity of the waves induced by anelastic soil and soil-rock boundaries. These anelastic effects manifest themselves as variations in amplitude response, amplitude attenuation, raypath location, and travel time as observed at the Earth’s surface. Implications of these anelastic effects for soil-response models used for earthquake resistant design are provided herein. 

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 18th WCEE 2024","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Borcherdt, R.D., 2024, Wave propagation in layered soil deposits, in Proceedings of the 18th WCEE 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-158288","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":502364,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=22759&conference=18WCEE"},{"id":502365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Borcherdt, Roger D. 0000-0002-8668-0849 borcherdt@usgs.gov","orcid":"https://orcid.org/0000-0002-8668-0849","contributorId":2373,"corporation":false,"usgs":true,"family":"Borcherdt","given":"Roger","email":"borcherdt@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":909459,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256972,"text":"70256972 - 2024 - Asynchronous movement patterns between breeding and stopover locations in a long-distance migratory songbird","interactions":[],"lastModifiedDate":"2024-08-05T15:55:44.670373","indexId":"70256972","displayToPublicDate":"2024-08-01T10:52:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Asynchronous movement patterns between breeding and stopover locations in a long-distance migratory songbird","docAbstract":"

The species-specific migratory patterns and strategies of many songbirds remain unknown or understudied, as research in animal ecology is biased toward the breeding period, with the fewest studies on the migratory period across taxa. Identifying large-scale spatiotemporal migratory patterns is challenging, as individuals within a species may vary in their migratory behavior and strategies. The Yellow Warbler (Setophaga petechia) is a Nearctic-Neotropical migrant that is relatively well studied during the breeding season, but its species-wide migratory patterns remain understudied. Our aim in studying Yellow Warbler movement ecology was to characterize temporal migration patterns during fall migration. We sought to determine the temporal migration pattern among breeding locations, as determined by the hydrogen stable isotope values in feather samples collected at disjunct (~2000 km) stopover sites in the Gulf of Maine (n = 50) and the Gulf of Mexico (n = 150). We used a similarity matrix to group individuals into a geographic cluster by breeding location, which was then used as the response variable in a modeling analysis. Our results provide evidence that Yellow Warblers exhibit an asynchronous, type 1 temporal migration pattern with southern breeding populations initiating migration prior to northern populations. Using hydrogen isotopes, we identified the temporal migration patterns between geographic clusters, representing an individual’s breeding location, and stopover sites along the Gulf of Maine and Gulf of Mexico, which fills a gap in understanding Yellow Warbler migration ecology.

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-02688-190203","usgsCitation":"Zenzal, T.J., Contina, A., Vander Zanden, H.B., Kuwahara, L.K., Allen, D.C., and Covino, K.M., 2024, Asynchronous movement patterns between breeding and stopover locations in a long-distance migratory songbird: Avian Conservation and Ecology, v. 19, no. 2, 3, 13 p., https://doi.org/10.5751/ACE-02688-190203.","productDescription":"3, 13 p.","ipdsId":"IP-148926","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439233,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02688-190203","text":"Publisher Index Page"},{"id":432197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":909033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Contina, Andrea","contributorId":341849,"corporation":false,"usgs":false,"family":"Contina","given":"Andrea","email":"","affiliations":[{"id":78410,"text":"University of Texas Rio Grande Valley","active":true,"usgs":false}],"preferred":false,"id":909034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vander Zanden, Hannah B.","contributorId":138885,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"Hannah","email":"","middleInitial":"B.","affiliations":[{"id":12562,"text":"Department of Geology and Geophysics, University of Utah; Archie Carr Center for Sea Turtle Research, University of Florida","active":true,"usgs":false}],"preferred":false,"id":909035,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuwahara, Leanne K.","contributorId":341850,"corporation":false,"usgs":false,"family":"Kuwahara","given":"Leanne","email":"","middleInitial":"K.","affiliations":[{"id":81800,"text":"Layola Marymount University","active":true,"usgs":false}],"preferred":false,"id":909036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Daniel C.","contributorId":335231,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":909037,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Covino, Kristen M.","contributorId":341851,"corporation":false,"usgs":false,"family":"Covino","given":"Kristen","email":"","middleInitial":"M.","affiliations":[{"id":81801,"text":"Loyola Marymount University","active":true,"usgs":false}],"preferred":false,"id":909038,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257480,"text":"70257480 - 2024 - Capelin on the rebound: Using seabird diets to track trends in forage fish populations","interactions":[],"lastModifiedDate":"2024-08-16T15:28:57.932189","indexId":"70257480","displayToPublicDate":"2024-08-01T10:25:33","publicationYear":"2024","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":18341,"text":"Delta Sound Connections","active":true,"publicationSubtype":{"id":30}},"title":"Capelin on the rebound: Using seabird diets to track trends in forage fish populations","docAbstract":"Capelin are cold-water forage fish that respond rapidly to fluctuating ocean temperatures. They are prized food for seabirds and other marine predators in Alaska. Researchers have monitored seabird diets at Middleton Island for decades to make connections between changes in abundance of predators and their prey. During a prolonged marine heatwave in the Gulf of Alaska, seabird diets and limited trawl surveys showed that capelin populations collapsed from record high abundance during the 2007–2013 cool period (Hatch 2013) to record lows in 2016 (Arimitsu et al. 2021). Capelin occurrence in diets had previously oscillated out of phase with Pacific sand lance numbers during cold and warm years (Sydeman et al. 2017), however, the occurrence of both prey species in seabird diets fell below average during 2014–2022 (Fig. 1). Following a period of cooler ocean temperatures in the Gulf of Alaska, during 2023 we began to see signs of capelin stock recovery, with a moderate increase in occurrence in spring and summer seabird diets (Fig. 1, Hatch et al. 2023). Continued monitoring of seabird diets can help track capelin populations and other key forage fish to inform ecosystem-based management in 2024 and beyond.","language":"English","publisher":"Prince William Sound Science Center","usgsCitation":"Arimitsu, M.L., Marsteller, C.E., Piatt, J., Hatch, S., and Wheland, S., 2024, Capelin on the rebound: Using seabird diets to track trends in forage fish populations: Delta Sound Connections, v. 2024-'25.","productDescription":"1 p.","startPage":"6","ipdsId":"IP-163358","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":432862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":432861,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pwssc.org/education/delta-sound-connections/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.77199585957212,\n 59.26881099856607\n ],\n [\n -153.94611405017184,\n 56.51729622949853\n ],\n [\n -134.98579563208682,\n 56.545558198375346\n ],\n [\n -137.67284996186456,\n 58.70580202741482\n ],\n [\n -141.66575217225886,\n 59.854419527837756\n ],\n [\n -146.2252427959988,\n 60.429156939699894\n ],\n [\n -150.77199585957212,\n 59.26881099856607\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2024-'25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":910510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marsteller, Caitlin Elizabeth 0000-0002-2430-0708","orcid":"https://orcid.org/0000-0002-2430-0708","contributorId":251784,"corporation":false,"usgs":true,"family":"Marsteller","given":"Caitlin","email":"","middleInitial":"Elizabeth","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":910822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":244053,"corporation":false,"usgs":true,"family":"Piatt","given":"John F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":910513,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatch, Scott","contributorId":258853,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott","affiliations":[{"id":52319,"text":"ISRC","active":true,"usgs":false}],"preferred":false,"id":910511,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wheland, Shannon","contributorId":342935,"corporation":false,"usgs":false,"family":"Wheland","given":"Shannon","email":"","affiliations":[{"id":35874,"text":"Institute for Seabird Research and Conservation","active":true,"usgs":false}],"preferred":false,"id":910512,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261861,"text":"70261861 - 2024 - Observing systems, modeling, and forecasting","interactions":[],"lastModifiedDate":"2025-01-02T14:29:47.543312","indexId":"70261861","displayToPublicDate":"2024-08-01T10:16:25","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"chapter":"1","title":"Observing systems, modeling, and forecasting","docAbstract":"

Predicting harmful algal blooms (HABs) requires integrating physical, chemical, and biological data collected from observing networks and then assimilating these data into models, which are used to generate forecasts. In 2005, the Harmful Algal Research and Response: A National Environmental Science Strategy 2005-2015 (HARRNESS, 2005) made recommendations on how to improve HAB modeling and forecasting over the next decade. Key HARRNESS recommendations related to sensing, networking, and modeling HABs included:

● Support the development and validation of new and improved technologies for remote cell and toxin detection, and for modeling and forecasting,

● Improve coordination of monitoring/ and modeling efforts, both at national and regional levels,

● Improve the use of networking technologies for monitoring and modeling efforts,

● Conduct sustained time series measurements of the biotic, chemical, and physical environments impacted by HABs,

● Develop food web models on the ecosystem fate and effects of toxins,

● Develop and improve species-specific models that link to physical-biological models.

Here we review HAB observing, modeling, and forecasting advances and technologies and recommend research and management priorities for the next decade and beyond. Our report encompasses sensing technologies, sensor networking and data management, models and forecasts, and the paths to operationalize forecasts.

Continued improvements of deployable sensors are foundational to improving early warning indicators, models, and forecasts, which are only as good as the underlying data. Sensing technology has advanced considerably in the last decade; for example, more capable fluorometric pigment sensors can track changes in bloom biomass in real-time. Additionally, automated imaging/classifying systems to identify and quantify key harmful algal (HA) taxa are being routinely deployed. However, deployable toxin sensors are available for only some HAB toxins and continue to be identified as a critical need by researchers and managers. As more and improved sensors and technologies become available, the data quality associated with each sensor needs to be assessed. Data quality encompasses the reliability, accuracy, and uncertainty associated with sensor-generated data. These data need to be of known quality so that researchers, managers, and end-users can reliably determine if the information is appropriate for their intended applications. Many of the data quality recommendations from HARRNESS (2005) are still relevant and have been reiterated within the management community. Understanding and documenting data quality, and when applicable, standardizing best practices for sensor use, continue to be recommended.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Harmful algal research & response: A national environmental science strategy (HARRNESS), 2024-2034","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Woods Hole Oceanographic Institution","doi":"10.1575/1912/69773","usgsCitation":"Bouma-Gregson, K., Doucette, G., Graham, J.L., Kudela, R., Stauffer, B., Anderson, C., Bratton, J.F., Holcomb, B.M., Hubbard, K., Norris, T., Stiles, T., Tango, P.J., Raymond, H., and Zubkousky, V., 2024, Observing systems, modeling, and forecasting, 25 p., https://doi.org/10.1575/1912/69773.","productDescription":"25 p.","startPage":"31","endPage":"55","ipdsId":"IP-146565","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":465571,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doucette, Gregory","contributorId":347606,"corporation":false,"usgs":false,"family":"Doucette","given":"Gregory","affiliations":[],"preferred":false,"id":922057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kudela, Raphael","contributorId":196461,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","affiliations":[],"preferred":false,"id":922061,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stauffer, Beth","contributorId":347626,"corporation":false,"usgs":false,"family":"Stauffer","given":"Beth","affiliations":[],"preferred":false,"id":922072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Clarissa 0000-0001-5970-0253","orcid":"https://orcid.org/0000-0001-5970-0253","contributorId":213451,"corporation":false,"usgs":false,"family":"Anderson","given":"Clarissa","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":922056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bratton, John F. 0000-0003-0376-4981 jbratton@usgs.gov","orcid":"https://orcid.org/0000-0003-0376-4981","contributorId":92757,"corporation":false,"usgs":true,"family":"Bratton","given":"John","email":"jbratton@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":922059,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holcomb, Benjamin M.","contributorId":53700,"corporation":false,"usgs":true,"family":"Holcomb","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":922060,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hubbard, Kate","contributorId":347683,"corporation":false,"usgs":false,"family":"Hubbard","given":"Kate","affiliations":[],"preferred":false,"id":922062,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Norris, Tenaya","contributorId":347684,"corporation":false,"usgs":false,"family":"Norris","given":"Tenaya","affiliations":[],"preferred":false,"id":922063,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stiles, Tom","contributorId":347685,"corporation":false,"usgs":false,"family":"Stiles","given":"Tom","affiliations":[],"preferred":false,"id":922064,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tango, Peter J. pjtango@usgs.gov","contributorId":4088,"corporation":false,"usgs":true,"family":"Tango","given":"Peter","email":"pjtango@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922065,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Raymond, Heather","contributorId":291257,"corporation":false,"usgs":false,"family":"Raymond","given":"Heather","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":922067,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Zubkousky, Vanessa","contributorId":347686,"corporation":false,"usgs":false,"family":"Zubkousky","given":"Vanessa","affiliations":[],"preferred":false,"id":922066,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70258271,"text":"70258271 - 2024 - Abundance and distribution of white-tailed deer on First State National Historical Park and surrounding lands","interactions":[],"lastModifiedDate":"2024-09-11T15:14:35.971177","indexId":"70258271","displayToPublicDate":"2024-08-01T10:13:51","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":18517,"text":"Science Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SR—2024/176","title":"Abundance and distribution of white-tailed deer on First State National Historical Park and surrounding lands","docAbstract":"

We estimated both abundance and distribution of white-tailed deer (Odocoileus virginianus) on the Brandywine Valley unit of First State National Historical Park (FRST) and the Brandywine Creek State Park (BCSP) during 2020 and 2021 with two widely used field methods — a road-based count and a network of camera traps. We conducted 24 road-based counts, covering 260 km of roadway, and deployed up to 16 camera traps, processing over 82,000 images representing over 5,000 independent observations.

In both years, we identified bucks based on their body and antler characteristics, tracking their movements between baited camera trap locations. We tested seven estimators commonly reported in the literature, comparing the relative merits for managers of small, protected natural areas like FRST.

Deer densities estimated from conventional road-based distance sampling were approximately 10 deer/km2 lower than densities estimated from camera-trapping surveys. We attribute the bias in roadbased distance sampling to the difficulty of recording the precise effort expended to obtain the counts. Modifying the distance sampling method addressed many of the issues associated with the conventional approach. Despite little substantive differences in land cover types between the two methods, a clear spatial segregation of male and female deer at camera trap locations could bias roadbased counts if the sexes are not encountered in proportion to their abundances. There was a distinct gradient in deer distribution across the study area, with higher proportions of deer recorded in camera traps at FRST than BCSP, which harvests 20–60 deer annually during a regulated, hunting season.

The most reliable (i.e., low bias, acceptable precision) methods, Spatial Capture Recapture (SCR) and Density Surface Modeling (DSM), produced deer densities of approximately 50 deer/km2 in each year — a number which is consistent with previous estimates for New Castle County, Delaware, and our experience in similar, unhunted natural areas. Across both FRST and BCSP, these densities translated into area-wide (~1000 ha) population sizes between 650–1000 deer, with about one-half to two-thirds comprising the FRST population.

Density surface modeling of mapped locations of deer detected during surveys, combined with camera-trapping and a time-to-event data analysis might be the only practical means of reliably assessing white-tailed deer abundance in small (<2000 ha), protected natural areas like FRST. Most other approaches are either too time-consuming, require identification and tracking of individual deer, the use of bait, or require intervention by a subject-area expert.

","language":"English","publisher":"National Park Service","doi":"10.36967/2305428","usgsCitation":"Underwood, H.B., Hand, M.R., and Leopold, D.J., 2024, Abundance and distribution of white-tailed deer on First State National Historical Park and surrounding lands: Science Report NPS/SR—2024/176, x, 76 p., https://doi.org/10.36967/2305428.","productDescription":"x, 76 p.","ipdsId":"IP-154880","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":433697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Pennsylvania","otherGeospatial":"Brandywine Creek State Park, Brandywine Valley unit of First State National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.57893855864407,\n 39.84864721075371\n ],\n [\n -75.57893855864407,\n 39.79988968093724\n ],\n [\n -75.54431018453508,\n 39.79988968093724\n ],\n [\n -75.54431018453508,\n 39.84864721075371\n ],\n [\n -75.57893855864407,\n 39.84864721075371\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Underwood, H. Brian 0000-0002-2064-9128 hbunderw@usgs.gov","orcid":"https://orcid.org/0000-0002-2064-9128","contributorId":140185,"corporation":false,"usgs":true,"family":"Underwood","given":"H.","email":"hbunderw@usgs.gov","middleInitial":"Brian","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":912809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hand, Madison R.","contributorId":344097,"corporation":false,"usgs":false,"family":"Hand","given":"Madison","email":"","middleInitial":"R.","affiliations":[{"id":13404,"text":"SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":912810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leopold, Donald J.","contributorId":220142,"corporation":false,"usgs":false,"family":"Leopold","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":13404,"text":"SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":912811,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257637,"text":"70257637 - 2024 - Incorporating climate data into emergency planning and exercises: A primer for emergency management practioners and data developers","interactions":[],"lastModifiedDate":"2024-08-21T14:39:36.800563","indexId":"70257637","displayToPublicDate":"2024-08-01T09:33:38","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Incorporating climate data into emergency planning and exercises: A primer for emergency management practioners and data developers","docAbstract":"

Climate change has and will continue to sharpen climate-related risks to communities and natural resources in California and elsewhere, as the probabilities of more extreme weather, floods, and fires continue to increase. This poses a problem of novel situations for emergency management. Progress has been made in terms of formally incorporating climate projections, data, and research on expected changes in climate-driven hazards into long-term hazard mitigation and climate adaptation strategies at both state and national levels. However, there are fewer examples of how climate change considerations have, or could be, incorporated into shorter-term emergency preparedness and response strategies. This is an important gap to fill, as climate resilience depends not only on mitigation and prevention measures, but also on the ability of agencies to coordinate and effectively minimize impacts when prevention measures fall short.

The goal of this primer is to provide guidance on how to incorporate the best available information on climate variability and change into emergency management planning, with a focus on the development and use of extreme weather event scenarios for use in exercises. The first section is aimed toward a broad audience, including emergency management practitioners who use extreme weather event scenarios. It provides an overview of available data and tools that can inform scenario design as well as techniques for scenario design based on the hazard of interest, the audience and application, and the technical skills and resources required to develop, summarize, and/or visualize the data. This section concludes with an overview of approaches and lessons learned related to extreme event response planning and exercise design. Overall, this section highlights the advantages of developing quantitative scenarios based on spatial data, which allows visualizations and interactive data explorations that can provide greater specificity in discussions related to preparedness and response strategies. It further highlights the advantages of developing a core expert working group to guide planning, holding pre-exercise workshops to engage diverse communities outside of the emergency management sector, and engaging decisionmakers post-exercise to communicate key issues and outcomes as well as potential approaches for mitigating consequences that were identified by participants.

The second section is aimed toward the scientific community and data developers involved in the creation of extreme weather event scenarios. This section provides technical guidance and detailed descriptions of four types of data resources and five analytical approaches that can be used to create extreme weather event scenarios based on the design considerations highlighted in section one. The computational resources and expertise required varies substantially across the options presented and is a primary consideration. These requirements, in addition to considerations related to audience and application, may determine the novelty and detail of the event, the detail of weather forecast information that can be provided, and the spatial extent across which the event can reasonably be modeled. The importance of, and approaches for, delivering information in a form that is accessible to emergency management practitioners is also discussed.

","language":"English","publisher":"Desert Research Institute","usgsCitation":"Albano, C.M., McCarthy, M.I., Mcafee, S.A., Wein, A., and Dettinger, M., 2024, Incorporating climate data into emergency planning and exercises: A primer for emergency management practioners and data developers, x, 32 p.","productDescription":"x, 32 p.","ipdsId":"IP-164123","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":433003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":433002,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.dri.edu/project/arkstormsierrafront-2-0/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Albano, Christine M.","contributorId":169455,"corporation":false,"usgs":false,"family":"Albano","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":911158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Maureen I.","contributorId":343457,"corporation":false,"usgs":false,"family":"McCarthy","given":"Maureen","email":"","middleInitial":"I.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":911159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAfee, Stephanie Anne 0000-0002-9313-5857","orcid":"https://orcid.org/0000-0002-9313-5857","contributorId":343458,"corporation":false,"usgs":true,"family":"McAfee","given":"Stephanie","middleInitial":"Anne","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":911160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":911161,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dettinger, Michael D.","contributorId":343459,"corporation":false,"usgs":false,"family":"Dettinger","given":"Michael D.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":911162,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257588,"text":"70257588 - 2024 - Diminishing productivity and hyperstable harvest in northern Wisconsin walleye fisheries","interactions":[],"lastModifiedDate":"2024-12-11T15:56:41.280711","indexId":"70257588","displayToPublicDate":"2024-08-01T09:22:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Diminishing productivity and hyperstable harvest in northern Wisconsin walleye fisheries","docAbstract":"

Managing fisheries in a changing socio-ecological environment may require holistic approaches for identifying and adapting to novel ecosystem dynamics. Using 32 years of Ceded Territory of Wisconsin (CTWI) walleye (Sander vitreus) data, we estimated production (P), biomass (B), biomass turnover (P/B), yield (Y), and yield over production (Y/P) and tested for hyperstability in walleye yield. Most CTWI walleye populations showed low P, and B, and Y/P < 1. Yet, production overharvest (Y/P > 1) was prevalent among Wisconsin walleye recruitment-based management approaches (natural recruitment [NR], sustained only by stocking, combination). Production, B, and P/B have declined in NR populations, while Y and Y/P have remained constant. Walleye Y was hyperstable along a production gradient among all management approaches and fishery types (i.e., angling only, angling/tribal harvest combined). Diminishing productivity and hyperstable yield may be jointly contributing to observed walleye declines. We classified lakes into management groups of low, moderate, or high vulnerability to harvest based on Y/P and P/B dynamics and recommend that exploitation may need to decline to maintain or increase the adaptive capacity of CTWI walleye.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0372","usgsCitation":"Mrnak, J.T., Embke, H.S., Wilkinson, M.V., Shaw, S.L., Vander Zanden, M.J., and Sass, G., 2024, Diminishing productivity and hyperstable harvest in northern Wisconsin walleye fisheries: Canadian Journal of Fisheries and Aquatic Sciences, v. 81, no. 12, p. 1650-1665, https://doi.org/10.1139/cjfas-2023-0372.","productDescription":"16 p.","startPage":"1650","endPage":"1665","ipdsId":"IP-160358","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":489877,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2023-0372","text":"Publisher Index Page"},{"id":432934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.18049419077052,\n 45.948938075630764\n ],\n [\n -88.62936625659313,\n 45.99443402697818\n ],\n [\n -90.13495797737319,\n 46.33769085403185\n ],\n [\n -90.45290902399807,\n 46.58248141670697\n ],\n [\n -90.71475106239458,\n 46.659555080264994\n ],\n [\n -90.27523049794291,\n 47.05602167993885\n ],\n [\n -90.41550301851264,\n 47.11969380652522\n ],\n [\n -91.04205361039043,\n 46.96037076403644\n ],\n [\n -91.63119819678276,\n 46.73651903458966\n ],\n [\n -91.94914924340715,\n 46.68522192077327\n ],\n [\n -92.0800702626054,\n 46.755742883136094\n ],\n [\n -92.20163978043216,\n 46.69805077000643\n ],\n [\n -92.27645179140251,\n 46.68522192077327\n ],\n [\n -92.29515479414547,\n 46.0917995100892\n ],\n [\n -92.71597235585415,\n 45.89038836410472\n ],\n [\n -92.86559637779489,\n 45.668642940969534\n ],\n [\n -92.87494787916634,\n 45.58362485690526\n ],\n [\n -92.70662085448265,\n 45.524690647636874\n ],\n [\n -92.65051184625477,\n 45.43945434374024\n ],\n [\n -92.77208136408203,\n 45.17637992800505\n ],\n [\n -90.04144296366039,\n 44.48667212247656\n ],\n [\n -88.06827617431473,\n 45.3869371369814\n ],\n [\n -88.18049419077052,\n 45.948938075630764\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"81","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mrnak, Joseph T.","contributorId":275764,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joseph","email":"","middleInitial":"T.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":910969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":910970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkinson, Max V.","contributorId":343401,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Max","email":"","middleInitial":"V.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaw, Steph L.","contributorId":343404,"corporation":false,"usgs":false,"family":"Shaw","given":"Steph","email":"","middleInitial":"L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vander Zanden, M. Jake","contributorId":265448,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"M.","email":"","middleInitial":"Jake","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":910973,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sass, Greg G.","contributorId":244466,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":910974,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257411,"text":"70257411 - 2024 - Disentangling genetic diversity of Myotis septentrionalis: population structure, demographic history, and effective population size","interactions":[],"lastModifiedDate":"2024-08-30T16:27:16.23961","indexId":"70257411","displayToPublicDate":"2024-08-01T09:19:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling genetic diversity of Myotis septentrionalis: population structure, demographic history, and effective population size","docAbstract":"

Myotis septentrionalis (Northern Long-eared Bat) has recently suffered a >90% decline in population size in North America due to white-nose syndrome (WNS). We assessed genetic diversity, population structure, current effective population size, and demographic history of M. septentrionalis distributed across the United States to determine baseline levels pre-WNS. We analyzed RADseq data from 81 individuals from Kentucky, Louisiana, Michigan, Minnesota, North Carolina, Oklahoma, and Wisconsin. Additionally, we examined population genetic structure using discriminant analysis of principal components, fastStructure, and STRUCTURE. We then estimated effective population size and demographic history using fastsimcoal2. Similar levels of genetic diversity were found across all samples. We found no population genetic structure in the varied analyses from these contemporary samples. The best model for demographic history estimated a rapid population expansion followed by a slower expansion approximately 340,000 years ago. The vagility of M. septentrionalis, along with male dispersal and random mating, may provide a buffer against serious bottleneck effects stemming from rapid population declines due to WNS. This research provides a baseline for tracking and monitoring the influence of WNS on genetic diversity such as potential reduced diversity or increased population structuring in the future.

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 Community wildfire readiness includes actions taken by residents, including wildfire risk mitigation at the parcel level and evacuation preparedness. This report presents results from two data collection efforts in the Lake Wenatchee Fire & Rescue service district in Chelan County, Washington: parcel level rapid wildfire risk assessments and household surveys sent to the owners of assessed parcels. Respondents reported that they were moderately aware of the risk of wildfire to their home, were discussing wildfire with their neighbors, and were taking action to reduce risk. There are gaps in respondents’ understanding of wildfire risk that might be addressed through educational outreach. Respondents were supportive of wildfire risk reduction strategies at the community level, including fuel treatments and policy options.

","language":"English","publisher":"USDA Forest Service Rocky Mountain Research Station","doi":"10.2737/RMRS-RN-103","usgsCitation":"Goolsby, J., Champ, P.A., Wittenbrink, S., Donovan, C., King, K., Brenkert-Smith, H., Meldrum, J., Barth, C.M., Wagner, C., and Forrester, C., 2024, Living with wildfire in Lake Wenatchee, Chelan County, Washington: 2022 Data report: Research Note RMRS-RN-103, vi, 130 p., https://doi.org/10.2737/RMRS-RN-103.","productDescription":"vi, 130 p.","ipdsId":"IP-162048","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":432651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","county":"Chelan County","otherGeospatial":"Lake Wenatchee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.99524534788046,\n 47.91597533876984\n ],\n [\n -120.99524534788046,\n 47.73844761896257\n ],\n [\n -120.60585715934415,\n 47.73844761896257\n ],\n [\n -120.60585715934415,\n 47.91597533876984\n ],\n [\n -120.99524534788046,\n 47.91597533876984\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goolsby, Julia 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":295471,"corporation":false,"usgs":false,"family":"Goolsby","given":"Julia","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":909825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champ, Patricia A.","contributorId":195486,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":909826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wittenbrink, Suzanne","contributorId":333353,"corporation":false,"usgs":false,"family":"Wittenbrink","given":"Suzanne","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":909827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":909828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Kris","contributorId":342230,"corporation":false,"usgs":false,"family":"King","given":"Kris","email":"","affiliations":[{"id":81845,"text":"Lake Wenatchee Fire & Rescue","active":true,"usgs":false}],"preferred":false,"id":909829,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":909830,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":909831,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barth, Christopher M.","contributorId":195487,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":909832,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":909833,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Forrester, Chiara","contributorId":328660,"corporation":false,"usgs":false,"family":"Forrester","given":"Chiara","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":909834,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70256402,"text":"ofr20241049 - 2024 - Methods for computing water-quality concentrations and loads at sites operated by the U.S. Geological Survey Kansas Water Science Center","interactions":[],"lastModifiedDate":"2024-08-01T13:51:09.369775","indexId":"ofr20241049","displayToPublicDate":"2024-08-01T07:14:10","publicationYear":"2024","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":"2024-1049","displayTitle":"Methods for Computing Water-Quality Concentrations and Loads at Sites Operated by the U.S. Geological Survey Kansas Water Science Center","title":"Methods for computing water-quality concentrations and loads at sites operated by the U.S. Geological Survey Kansas Water Science Center","docAbstract":"

The U.S. Geological Survey (USGS) Kansas Water Science Center (KSWSC) has published time-series computations of water-quality concentrations and loads based on in situ sensor data since 1995. Water-quality constituent concentrations or densities are computed using regression models that relate in situ sensor values to laboratory analyses of periodically collected samples. These regression models currently (2024) follow no uniform published guidance and are individually documented through USGS reports. This report describes updated (2024) procedures designed to improve the consistency, quality, and timeliness of computed continuous water-quality data produced by the USGS KSWSC. Beginning in 2024, models developed by the USGS KSWSC that follow specific procedures and requirements related to sample collection, model fit, and model documentation outlined in this report are planned to be published and stored in the USGS National Real-Time Water Quality Data for the Nation Data Service. This report also describes USGS KSWSC procedures for evaluating and publishing time-series water-quality computations after initial model development and documentation. This guidance can be used to improve USGS KSWSC model development and data computation consistency and streamline the time-series water-quality computation process from model development to publication.

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Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-08-01","noUsgsAuthors":false,"publicationDate":"2024-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":214749,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":907261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Casey J. 0000-0002-5753-2038 cjlee@usgs.gov","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":2627,"corporation":false,"usgs":true,"family":"Lee","given":"Casey","email":"cjlee@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":907262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rasmussen, Teresa J. 0000-0002-7023-3868 rasmuss@usgs.gov","orcid":"https://orcid.org/0000-0002-7023-3868","contributorId":3336,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Teresa","email":"rasmuss@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":907263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Thomas J. 0000-0003-3124-3243 tjwilliams@usgs.gov","orcid":"https://orcid.org/0000-0003-3124-3243","contributorId":185244,"corporation":false,"usgs":true,"family":"Williams","given":"Thomas","email":"tjwilliams@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":907264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kramer, Ariele R. 0000-0002-7075-3310 akramer@usgs.gov","orcid":"https://orcid.org/0000-0002-7075-3310","contributorId":185245,"corporation":false,"usgs":true,"family":"Kramer","given":"Ariele","email":"akramer@usgs.gov","middleInitial":"R.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":907265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klager, Brian J. 0000-0001-8361-6043","orcid":"https://orcid.org/0000-0001-8361-6043","contributorId":214750,"corporation":false,"usgs":true,"family":"Klager","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":907266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267204,"text":"70267204 - 2024 - Boom and bust: The effects of masting on seed predator range dynamics and trophic cascades","interactions":[],"lastModifiedDate":"2025-05-16T15:59:30.509122","indexId":"70267204","displayToPublicDate":"2024-08-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Boom and bust: The effects of masting on seed predator range dynamics and trophic cascades","docAbstract":"

AimSpatiotemporal variation in resource availability is a strong driver of animal distributions. In the northern hardwood and boreal forests of the northeastern United States, tree mast events provide resource pulses that drive the population dynamics of small mammals, including the American red squirrel (Tamiasciurus hudsonicus), a primary songbird nest predator. This study sought to determine whether mast availability ameliorates their abiotic limits, enabling red squirrel elevational distributions to temporarily expand and negatively impact high-elevation songbirds.

Location

Northeastern United States.

Methods

We used two independent datasets to evaluate our hypotheses. First, we fit a dynamic occupancy model using data from camera trap surveys to evaluate red squirrel distributional responses to pulses in the tree mast. We also assessed population responses using systematic auditory surveys analysed with an open-population binomial mixture model. Further, we used modelled red squirrel abundance in nest-survival models to evaluate whether their abundance is correlated with the daily nest survival of three songbird species.

Results

The tree mast provided a critical resource pulse that resulted in a two-fold increase in the annual elevational distribution of red squirrels. The elevational distribution of red squirrels ranged from a minimum of ~450 m (range: 663–1145 m asl) following two consecutive years without a masting event to a maximum of over 1000 m (range: 443–1545 m asl) after a large mast event. The daily nest survival of three songbird species tended to decline with an increase in the abundance of red squirrels.

Main Conclusions

Tree mast is a central biological phenomenon in many temperate and boreal forests. This study reveals how this resource pulse results in range changes in a small mammal that is both a seed and bird predator, as well as prey for many carnivores. Thus, understanding this phenomenon can inform the conservation and management of northern forests, including breeding songbirds.

","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13861","usgsCitation":"Hallworth, M.T., Sirén, A., DeLuca, W., Duclos, T., McFarland, K.P., Hill, J.M., Rimmer, C.C., and Morelli, T.L., 2024, Boom and bust: The effects of masting on seed predator range dynamics and trophic cascades: Diversity and Distributions, v. 30, no. 8, e13861, 13 p., https://doi.org/10.1111/ddi.13861.","productDescription":"e13861, 13 p.","ipdsId":"IP-129255","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":489019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13861","text":"Publisher Index Page"},{"id":486083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont","otherGeospatial":"northeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.10575084649285,\n 43.37093588190811\n ],\n [\n -79.75309493274816,\n 41.99258454725708\n ],\n [\n -75.45135133469833,\n 42.005404340434055\n ],\n [\n -74.94884725348038,\n 41.60054495898998\n ],\n [\n -74.90966943261284,\n 40.41115406110167\n ],\n [\n -69.50442652451818,\n 41.140541678401235\n ],\n [\n -70.21215396984903,\n 43.20792379414405\n ],\n [\n -66.98409511373686,\n 44.634391727144134\n ],\n [\n -67.64757065599491,\n 47.18695334041415\n ],\n [\n -68.97147672811981,\n 47.48919160963973\n ],\n [\n -71.61820175777069,\n 45.07428624184727\n ],\n [\n -74.6889940707864,\n 45.17423846474814\n ],\n [\n -79.10575084649285,\n 43.37093588190811\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hallworth, Michael T.","contributorId":213805,"corporation":false,"usgs":false,"family":"Hallworth","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":38879,"text":"National Zoological Park, Migratory Bird Center","active":true,"usgs":false}],"preferred":false,"id":937261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sirén, Alexej","contributorId":300102,"corporation":false,"usgs":false,"family":"Sirén","given":"Alexej","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":937262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLuca, William","contributorId":192836,"corporation":false,"usgs":false,"family":"DeLuca","given":"William","affiliations":[],"preferred":false,"id":937263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duclos, Timothy","contributorId":236781,"corporation":false,"usgs":false,"family":"Duclos","given":"Timothy","email":"","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McFarland, Kent P.","contributorId":213789,"corporation":false,"usgs":false,"family":"McFarland","given":"Kent","email":"","middleInitial":"P.","affiliations":[{"id":38867,"text":"Vermont Center for Ecostudies","active":true,"usgs":false}],"preferred":false,"id":937265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hill, Jason M.","contributorId":191616,"corporation":false,"usgs":false,"family":"Hill","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":937266,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rimmer, Christopher C.","contributorId":213817,"corporation":false,"usgs":false,"family":"Rimmer","given":"Christopher","email":"","middleInitial":"C.","affiliations":[{"id":38867,"text":"Vermont Center for Ecostudies","active":true,"usgs":false}],"preferred":false,"id":937267,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":937268,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}