Effective habitat management for rare and endangered species requires a thorough understanding of their specific habitat requirements. Although machine learning models have been increasingly used in the analyses of habitat use by wildlife, the primary focus of these models has been on generating spatial predictions. In this study, we used machine learning models in combination with simulated management actions to guide planning and inform managers. We used data from 61 whooping cranes (Grus americana) tagged with GPS telemetry collars between 2009 and 2018 near Aransas National Wildlife Refuge in coastal Texas. We included variables based on topography, land use classification, vegetation height, plant phenology, drought, storm surge events, and both wild and prescribed fires. We then built models at multiple scales: population level, home range level, and roosting and daytime within home range level. We simulated responses to the two primary management actions used to enhance whooping crane habitat on Aransas National Wildlife Refuge: prescribed fire and removal of woody vegetation. At the population and home range scales, land use classification variables had the highest importance values, whereas the combined elevation and bathymetry layer was the most important predictor at both roosting and daytime within home range scales. Our findings revealed that the effects of fire, although generally modest, varied spatially. Areas dominated by estuarine wetlands exhibited higher predicted use within the first months after a fire, whereas those dominated by palustrine wetlands were more likely to be avoided in the immediate postfire years. Our simulation of vegetation removal identified the areas on Aransas National Wildlife Refuge where whooping cranes were predicted to benefit the most if vegetation were removed. These techniques can be used by other researchers wanting to examine and predict the effects of potential management actions on target species habitat.
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Fungal infections were severe and one individual likely died from infection. Surveillance efforts are needed to better understand the threat of this pathogen to snake conservation.","language":"English","publisher":"CDC","doi":"10.3201/eid3005.231317","usgsCitation":"Blanvillain, G., Martínez-Freiría, F., Hoyt, J.R., Lorch, J., and Martinez Silvestre, A., 2024, Paranannizziopsis spp. Infection in Wild Vipers, Europe: Emerging Infectious Diseases, v. 30, no. 5, p. 1000-1003, https://doi.org/10.3201/eid3005.231317.","productDescription":"4 p.","startPage":"1000","endPage":"1003","ipdsId":"IP-159670","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":439865,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid3005.231317","text":"Publisher Index Page"},{"id":428071,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Portugal, Spain","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":144,\"properties\":{\"name\":\"Portugal\"},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-9.03482,41.88057],[-8.67195,42.13469],[-8.26386,42.28047],[-8.01317,41.79089],[-7.42251,41.79207],[-7.25131,41.91835],[-6.66861,41.88339],[-6.38909,41.38182],[-6.85113,41.11108],[-6.86402,40.33087],[-7.02641,40.18452],[-7.06659,39.71189],[-7.49863,39.62957],[-7.09804,39.03007],[-7.37409,38.37306],[-7.02928,38.07576],[-7.16651,37.80389],[-7.53711,37.4289],[-7.45373,37.09779],[-7.85561,36.83827],[-8.38282,36.97888],[-8.89886,36.86881],[-8.7461,37.65135],[-8.84,38.26624],[-9.28746,38.35849],[-9.52657,38.73743],[-9.44699,39.39207],[-9.04831,39.75509],[-8.97735,40.15931],[-8.76868,40.76064],[-8.79085,41.18433],[-8.99079,41.54346],[-9.03482,41.88057],[-9.03482,41.88057]]]}},{\"type\":\"Feature\",\"id\":158,\"properties\":{\"name\":\"Spain\"},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-9.03482,41.88057],[-8.98443,42.59278],[-9.39288,43.02662],[-7.97819,43.74834],[-6.75449,43.56791],[-5.41189,43.57424],[-4.34784,43.40345],[-3.51753,43.4559],[-1.90135,43.4228],[-1.50277,43.03401],[0.33805,42.57955],[0.70159,42.79573],[1.82679,42.34338],[2.986,42.47302],[3.03948,41.89212],[2.09184,41.22609],[0.81052,41.01473],[0.72133,40.67832],[0.10669,40.12393],[-0.27871,39.30998],[0.11129,38.73851],[-0.46712,38.29237],[-0.68339,37.64235],[-1.43838,37.44306],[-2.14645,36.67414],[-3.41578,36.6589],[-4.3689,36.67784],[-4.99522,36.32471],[-5.37716,35.94685],[-5.86643,36.02982],[-6.23669,36.36768],[-6.52019,36.94291],[-7.45373,37.09779],[-7.53711,37.4289],[-7.16651,37.80389],[-7.02928,38.07576],[-7.37409,38.37306],[-7.09804,39.03007],[-7.49863,39.62957],[-7.06659,39.71189],[-7.02641,40.18452],[-6.86402,40.33087],[-6.85113,41.11108],[-6.38909,41.38182],[-6.66861,41.88339],[-7.25131,41.91835],[-7.42251,41.79207],[-8.01317,41.79089],[-8.26386,42.28047],[-8.67195,42.13469],[-9.03482,41.88057],[-9.03482,41.88057]]]}}]}","volume":"30","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blanvillain, Gaelle","contributorId":335744,"corporation":false,"usgs":false,"family":"Blanvillain","given":"Gaelle","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":899402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martínez-Freiría, Fernando","contributorId":335745,"corporation":false,"usgs":false,"family":"Martínez-Freiría","given":"Fernando","affiliations":[{"id":28077,"text":"Universidade do Porto","active":true,"usgs":false}],"preferred":false,"id":899403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoyt, Joseph R.","contributorId":201314,"corporation":false,"usgs":false,"family":"Hoyt","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":899404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":335548,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":899405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martinez Silvestre, Albert","contributorId":335746,"corporation":false,"usgs":false,"family":"Martinez Silvestre","given":"Albert","email":"","affiliations":[{"id":80496,"text":"Catalonian Reptiles and Amphibians Rescue Center","active":true,"usgs":false}],"preferred":false,"id":899406,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70253188,"text":"70253188 - 2024 - Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity","interactions":[],"lastModifiedDate":"2024-07-30T14:25:07.421636","indexId":"70253188","displayToPublicDate":"2024-04-12T09:35:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity","docAbstract":"Probabilistic seismic hazard analyses such as the U.S. National Seismic Hazard Model (NSHM) typically rely on declustering and spatially smoothing an earthquake catalog to estimate a long‐term time‐independent (background) seismicity rate to forecast future seismicity. In support of the U.S. Geological Survey’s (USGS) 2023 update to the NSHM, we update the methods used to develop this background or gridded seismicity model component of the NSHM. As in 2018, we use a combination of fixed and adaptive kernel Gaussian smoothing. However, we implement two additional declustering methods to account for the fact that declustering is a nonunique process. These new declustering methods result in different forecasts for the locations of future seismicity, as represented by spatial probability density functions that are later combined with a rate model to produce a full gridded earthquake rate forecast. The method updates, particularly in the separation of the spatial and rate models as well as revised regional boundaries, in some places cause substantive changes to the seismic hazard forecast compared to the previous 2018 NSHM. Additional updates to catalog processing and induced seismicity zones also contribute to changes in the gridded seismicity hazard since 2018. However, these changes are well understood and reflect improvements in our modeling of gridded seismicity hazard.
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These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.
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The effect of less water released, as well as lower lake levels and associated water quality concerns, on downstream resources was not analyzed in the 2007 Interim Guidelines EIS. Reclamation requested GCMRC support to provide models predicting the effects to resources of water releases lower than 7M acre feet/year, including models predicting effects to threatened and endangered species for use in a Biological Assessment.","language":"English","publisher":"Bureau of Reclamation","collaboration":"Bureau of Reclamation, Glen Canyon Dam Adaptive Management Program","usgsCitation":"Yackulic, C., Bair, L., Eppehimer, D.E., Salter, G.L., Deemer, B., Butterfield, B.J., Kasprak, A., Caster, J., Fairley, H.C., Grams, P.E., Mihalevich, B.A., Palmquist, E.C., and Sankey, J., 2024, Modeling the impacts of Glen Canyon Dam operations on Colorado River resources, ii, 133 p.","productDescription":"ii, 133 p.","ipdsId":"IP-163024","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":427772,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/uc/progact/amp/pdfs/LTEMP/20240408-ModelingImpactsGlenCanyonDamOperationsColoradoRiverResources-508-UCRO.pdf"},{"id":427780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Hartwell, Meredith A. 0000-0001-6350-5450 mhartwell@usgs.gov","orcid":"https://orcid.org/0000-0001-6350-5450","contributorId":4842,"corporation":false,"usgs":true,"family":"Hartwell","given":"Meredith","email":"mhartwell@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898821,"contributorType":{"id":2,"text":"Editors"},"rank":14}],"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bair, Lucas 0000-0002-9911-3624","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":248714,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eppehimer, Drew Elliot 0000-0003-0076-1494","orcid":"https://orcid.org/0000-0003-0076-1494","contributorId":333633,"corporation":false,"usgs":true,"family":"Eppehimer","given":"Drew","email":"","middleInitial":"Elliot","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salter, Gerard Lewis 0000-0001-6426-0133","orcid":"https://orcid.org/0000-0001-6426-0133","contributorId":333645,"corporation":false,"usgs":true,"family":"Salter","given":"Gerard","email":"","middleInitial":"Lewis","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":898813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":898814,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898815,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fairley, Helen C. 0000-0001-6151-4804 hfairley@usgs.gov","orcid":"https://orcid.org/0000-0001-6151-4804","contributorId":3040,"corporation":false,"usgs":true,"family":"Fairley","given":"Helen","email":"hfairley@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":898816,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898817,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mihalevich, Bryce Anthony 0000-0001-5492-221X","orcid":"https://orcid.org/0000-0001-5492-221X","contributorId":335493,"corporation":false,"usgs":false,"family":"Mihalevich","given":"Bryce","email":"","middleInitial":"Anthony","affiliations":[{"id":80423,"text":"U.S. Bureau of Reclamation, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":898818,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898819,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898820,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70254514,"text":"70254514 - 2024 - Seasonal mortality of Wild Atlantic Menhaden (Brevoortia tyrannus) is caused by a virulent clone of Vibrio (Listonella) anguillarum; Implications for biosecurity along the Atlantic Coastal United States","interactions":[],"lastModifiedDate":"2024-05-30T11:43:36.09668","indexId":"70254514","displayToPublicDate":"2024-04-12T06:42:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal mortality of Wild Atlantic Menhaden (Brevoortia tyrannus) is caused by a virulent clone of Vibrio (Listonella) anguillarum; Implications for biosecurity along the Atlantic Coastal United States","docAbstract":"Atlantic menhaden are a highly migratory marine species in the Eastern United States that suffer from seasonal chronic mortality. Affected fish show neurologic signs referred to as spinning disease, including circling at the surface and erratic corkscrew swimming before death. We investigated three similar menhaden mortality events consistent with spinning disease in coastal New Jersey and New York between 2020 and 2021 to understand the cause. A unique strain of Vibrio (Listonella) anguillarum (serogroup O3) was detected regularly in high loads, particularly in the brains of moribund fish, by both metagenomics and bacterial isolation. The most common histopathological changes in moribund fish were hemorrhagic meningitis, encephalitis, pyknosis, and karyorrhexis of hematopoietic tissues in the kidney and spleen. Whole genome sequencing of isolates from moribund fish representing a wide spatial and temporal range showed that they were nearly identical clones, suggesting it to be a pathogenic strain circulating in the population. Though V. anguillarum is believed to be the main pathogen associated with spinning disease and mortality, Yersinia ruckeri (serotype O1) was isolated from smaller numbers of fish. Considering the highly migratory nature of Atlantic menhaden throughout the eastern United States and their use as bait for other fisheries, these findings identify potential biosecurity challenges that should be considered in Atlantic salmon aquaculture, fisheries, and emerging marine aquaculture in the region.
","language":"English","publisher":"Hindawi","doi":"10.1155/2024/8816604","usgsCitation":"Lovy, J., Iwanowicz, L., Welch, T.J., Allem, B., Getchell, R.G., Geraci-Yee, S., Goodale, C., Snyder, J., Raines, C.D., and Das, N., 2024, Seasonal mortality of Wild Atlantic Menhaden (Brevoortia tyrannus) is caused by a virulent clone of Vibrio (Listonella) anguillarum; Implications for biosecurity along the Atlantic Coastal United States: Transboundary and Emerging Diseases, v. 2024, 8816604 , 18 p., https://doi.org/10.1155/2024/8816604.","productDescription":"8816604 , 18 p.","ipdsId":"IP-153348","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":487999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2024/8816604","text":"Publisher Index Page"},{"id":429380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2024","noUsgsAuthors":false,"publicationDate":"2024-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Lovy, Jan 0000-0003-2704-0822","orcid":"https://orcid.org/0000-0003-2704-0822","contributorId":331539,"corporation":false,"usgs":true,"family":"Lovy","given":"Jan","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":901692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":901693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Timothy J.","contributorId":336999,"corporation":false,"usgs":false,"family":"Welch","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":80941,"text":"National Center for Cool and Cold Water Aquaculture, US Department of Agriculture/Agricultural Research Service, WV 25430, USA","active":true,"usgs":false}],"preferred":false,"id":901694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allem, Bassem","contributorId":337000,"corporation":false,"usgs":false,"family":"Allem","given":"Bassem","email":"","affiliations":[{"id":80942,"text":"School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000, USA","active":true,"usgs":false}],"preferred":false,"id":901695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Getchell, Rodman G.","contributorId":201129,"corporation":false,"usgs":false,"family":"Getchell","given":"Rodman","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":901696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geraci-Yee, Sabrina","contributorId":337001,"corporation":false,"usgs":false,"family":"Geraci-Yee","given":"Sabrina","email":"","affiliations":[{"id":80942,"text":"School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000, USA","active":true,"usgs":false}],"preferred":false,"id":901697,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goodale, Christine L","contributorId":243972,"corporation":false,"usgs":false,"family":"Goodale","given":"Christine L","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":901698,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Snyder, Jeremy","contributorId":337002,"corporation":false,"usgs":false,"family":"Snyder","given":"Jeremy","email":"","affiliations":[{"id":80943,"text":"Animal Health Diagnostic Laboratory, New Jersey Department of Agriculture, Ewing, NJ 08628, USA","active":true,"usgs":false}],"preferred":false,"id":901699,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Raines, Clayton D. 0000-0002-0403-190X","orcid":"https://orcid.org/0000-0002-0403-190X","contributorId":296362,"corporation":false,"usgs":true,"family":"Raines","given":"Clayton","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":901700,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Das, Nilanjana","contributorId":337003,"corporation":false,"usgs":false,"family":"Das","given":"Nilanjana","email":"","affiliations":[{"id":80944,"text":"Office of Fish and Wildlife Health and Forensics, New Jersey Fish and Wildlife, Oxford, NJ 07863, USA","active":true,"usgs":false}],"preferred":false,"id":901701,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70254074,"text":"70254074 - 2024 - Methane seeps on the U.S. Atlantic margin: An updated inventory and interpretative framework","interactions":[],"lastModifiedDate":"2024-05-06T11:10:25.339469","indexId":"70254074","displayToPublicDate":"2024-04-12T06:08:11","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Methane seeps on the U.S. Atlantic margin: An updated inventory and interpretative framework","docAbstract":"Since the discovery of >570 methane flares on the northern U.S. Atlantic margin between Cape Hatteras and Georges Bank in the last decade, the acquisition of thousands of kilometers of additional water column imaging data has provided greater coverage at water depths between the outer continental shelf and the lower continental slope. The additional high-resolution data reveal >1400 gas flares, but the removal of probable duplicates from the combined database of new flares and those recognized in 2014 yields ∼1139 unique sites. Most of these sites occur in clusters of 5 or more seeps, leaving about 275 unique locations (including 47 clusters) for seepage along the margin. As a function of depth, seep distribution is heavily skewed toward the upper continental slope at water depths shallower than 400 m on the southern New England margin and ∼ 550 m in the Mid-Atlantic Bight, with additional seeps clustered at ∼1100 m and just deeper than ∼1400 m in both sectors. Despite little ongoing tectonic deformation or active faulting on this passive margin, a variety of processes driven from below the seafloor (e.g., migration of fluids along faults or through permeable strata, seepage above diapirs or other pre-existing structures) and from above (e.g., erosion, sapping, unroofing) contribute to the development of seeps in different settings along the margin. In addition, the prevalence of seeps on promontories overlooking shelf-breaking canyons may be directly related to the three-dimensional nature of the hydrate stability zone in these locations. As a function of depth, the parts of the slope at the contemporary landward limit of gas hydrate stability are devoid of seeps, and the upper slope zones with the most concentrated seepage were not within the gas hydrate stability zone even during the Last Glacial Maximum. Thus, if the large number of upper slope seeps is at least partially sourced in gas hydrate degradation, the gas emitted at these seeps must have migrated there from greater depths on the continental slope.
Age and growth data are frequently used to monitor and manage important North American sport fishes such as Largemouth Bass Micropterus salmoides. Continental and regional growth standards have been developed for this species to assess fish growth over time and across space. However, Largemouth Bass age and growth data are infrequently collected in Arizona and the reliability of age estimates derived from typical structures (e.g., scales, otoliths) in the Southwest is uncertain. Our objectives were to 1) compare precision and bias of age estimates from scales with those from otoliths and 2) estimate Largemouth Bass growth in several southwestern warmwater reservoirs by using otoliths. We collected Largemouth Bass from three Arizona reservoirs—Alamo, Peña Blanca, and Roosevelt—by boat electrofishing in spring 2021. We removed scales and sagittal otoliths from fish and then prepared and independently aged them three times. We compared differences in precision and bias between scales and otoliths using reader agreement percentages, confidence ratings, average coefficients of variation, and age-bias plots. We used age estimates from Largemouth Bass otoliths to calculate mean lengths-at-age at capture and relative growth indices based on published growth standards in each reservoir. Largemouth Bass scale age estimates were less precise, overestimated ages of younger fish, and underestimated age of older fish compared with those of otoliths. Growth was lower in Peña Blanca Lake than in the other two reservoirs according to mean length-at-age estimates, and relative growth indices suggested that Largemouth Bass growth in all three reservoirs was above average at younger ages, but less so at older ages. The results from this study add to a growing body of literature supporting the use of otoliths for estimating age and growth of Largemouth Bass.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-23-006","usgsCitation":"Ingram, S., Grant, J., Beard, Z.S., Berg, N., Ringelman, A.M., and Bonar, S.A., 2024, Estimating age and growth of Largemouth Bass in southwestern reservoirs using otoliths and scales: Journal of Fish and Wildlife Management, v. 14, no. 2, p. 315-323, https://doi.org/10.3996/JFWM-23-006.","productDescription":"9 p.","startPage":"315","endPage":"323","ipdsId":"IP-152855","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":439874,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-23-006","text":"Publisher Index Page"},{"id":429650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Alamo Lake, Rena Blanca Lake, Roosevelt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.08210462737988,\n 31.40979882180362\n ],\n [\n -111.0921670470852,\n 31.40979882180362\n ],\n [\n -111.0921670470852,\n 31.397486172336002\n ],\n [\n -111.08210462737988,\n 31.397486172336002\n ],\n [\n -111.08210462737988,\n 31.40979882180362\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.55375068272383,\n 34.281204643167825\n ],\n [\n -113.61396524331289,\n 34.281204643167825\n ],\n [\n -113.61396524331289,\n 34.22354373694439\n ],\n [\n -113.55375068272383,\n 34.22354373694439\n ],\n [\n -113.55375068272383,\n 34.281204643167825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.2613555367119,\n 33.79316218206927\n ],\n [\n -111.2613555367119,\n 33.6099720664448\n ],\n [\n -110.9547021734547,\n 33.6099720664448\n ],\n [\n -110.9547021734547,\n 33.79316218206927\n ],\n [\n -111.2613555367119,\n 33.79316218206927\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ingram, Steven J.","contributorId":288205,"corporation":false,"usgs":false,"family":"Ingram","given":"Steven J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Joshua D.","contributorId":288304,"corporation":false,"usgs":false,"family":"Grant","given":"Joshua D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, Zachary S.","contributorId":198840,"corporation":false,"usgs":false,"family":"Beard","given":"Zachary","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":902427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berg, Nathan","contributorId":337443,"corporation":false,"usgs":false,"family":"Berg","given":"Nathan","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":902428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ringelman, Anna M.","contributorId":337445,"corporation":false,"usgs":false,"family":"Ringelman","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":902429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254780,"text":"70254780 - 2024 - Evaluating streamflow and temperature effects on Bull Trout migration and survival with linear spatial capture-recapture models","interactions":[],"lastModifiedDate":"2024-06-07T14:54:04.427532","indexId":"70254780","displayToPublicDate":"2024-04-11T09:50:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating streamflow and temperature effects on Bull Trout migration and survival with linear spatial capture-recapture models","docAbstract":"In the U.S. Pacific Northwest, climate change is increasing air temperatures, decreasing warm season (April–September) streamflow, and increasing cool season (October–March) streamflow. Warmer water temperatures may alter conditions for migratory coldwater fishes like the Bull Trout Salvelinus confluentus. Consequently, an understanding of Bull Trout migration and survival is critical for species conservation and restoration. In the Salmon River basin, Idaho, 1992 and 1993 transpired to be two of the most opposing extreme years among the past three decades for warm season water temperature and streamflow. These extremes provided a unique opportunity to retrospectively compare Bull Trout survival and migration under potential climate change scenarios.
We evaluated prespawning and postspawning migrations and survival of fluvial Bull Trout that were radio-tagged and tracked from 1992 to 1994. We used a Cormack–Jolly–Seber linear spatial capture–recapture model to simultaneously model the migration and survival of radio-tagged prespawn (n = 58) and postspawn (n = 23) Bull Trout among weeks and river reaches with streamflow, water temperature, and habitat covariates.
Most individual prespawning migrations were similar among tagged fish, whereas postspawn fish adopted multiple migration and overwintering strategies. Movements of prespawn Bull Trout were larger when (1) weekly average daily maximum streamflow increased and (2) weekly average daily maximum water temperature increased. The model estimated that at least 52% of spawners survived to spawning, and mean weekly prespawning apparent survival was higher in the low-streamflow year (1992) than in the year with higher and more variable streamflow (1993). Survival of 1992–1994 fish during the 38-week postspawning period was intermediate to that in the prespawning period. Detections of prespawn Bull Trout were generally higher at sites with more complex habitats, less large woody debris, and fewer undercut banks.
We found that the prespawn life stage can represent a shorter time frame (14–18 weeks) with increased mortality compared to the longer postspawning period (38 weeks). Bull Trout apparent survival increased with lower streamflow variability, indicating that expected future changes in climate may adversely affect Bull Trout.
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U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Broadly distributed across the Western United States, ungulates (hooved mammals) play an important role in ecosystem function by affecting vegetation communities and forming the prey base for large carnivores. Additionally, ungulates provide economic benefits to regional communities through tourism and hunting and hold cultural significance for many Tribal communities. Many ungulates migrate seasonally between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. Increasingly, these migrations are threatened by the growing human footprint and associated subdivisions, energy development, and increased traffic volume. Efforts to study ungulate populations and conserve their migrations received support in recent years from the U.S. Department of the Interior Secretarial Order No. 3362, which provided Federal support for enhancing habitat quality for ungulates across the Western States. In response to Secretarial Order No. 3362, the U.S. Geological Survey (USGS) established the Corridor Mapping Team, a collaboration among USGS and participating State and Federal wildlife management agencies and numerous Tribal Nations. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States in the USGS “Ungulate Migrations of the Western United States” report series. This report (volume 4) details migrations and seasonal ranges from 31 new herds throughout nine Western States. Additionally, this report includes updates to two herds published in previous reports. Including this report, the report series has provided the mapped migrations and seasonal ranges of 182 unique herds and has provided a map-based inventory of the documented ungulate migrations across the Western United States for biologists, managers, policy makers, and conservation practitioners. This report also discusses how the mapping efforts associated with the Corridor Mapping Team can be used to guide management and policy regarding renewable energy development and ungulate disease, specifically chronic wasting disease, in the Western United States.
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\"}}]}","contact":"Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 300
Reston, VA 20192
Ecosystems that are coupled by reciprocal flows of energy and nutrient subsidies can be viewed as a single “meta-ecosystem.” Despite these connections, the reciprocal flow of subsidies is greatly asymmetrical and seasonally pulsed. Here, we synthesize existing literature on stream–riparian meta-ecosystems to quantify global patterns of the amount of subsidy consumption by organisms, known as “allochthony.” These resource flows are important since they can comprise a large portion of consumer diets, but can be disrupted by human modification of streams and riparian zones. Despite asymmetrical subsidy flows, we found stream and riparian consumer allochthony to be equivalent. Although both fish and stream invertebrates rely on seasonally pulsed allochthonous resources, we find allochthony varies seasonally only for fish, being nearly three times greater during the summer and fall than during the winter and spring. We also find that consumer allochthony varies with feeding traits for aquatic invertebrates, fish, and terrestrial arthropods, but not for terrestrial vertebrates. Finally, we find that allochthony varies by climate for aquatic invertebrates, being nearly twice as great in arid climates than in tropical climates, but not for fish. These findings are critical to understanding the consequences of global change, as ecosystem connections are being increasingly disrupted.
Incorporating societal considerations into decisions related to invasive species management is desirable, but can be challenging because it requires a solid understanding of the ecological functions and socio-cultural and economic benefits and values of the invaded environment before and after invasion. The ecosystem service (ES) concept was designed to facilitate such decision-making by establishing direct connections between ecosystem properties and human well-being, but its application in invasive species management has not been systematic. In this Discussion paper, we propose the adoption of the ES cascade model as a framework for understanding the environmental effects, costs and benefits associated with controlling an invasive shrub (Tamarix spp.) in riparian systems of the western United States. The cascade model has the advantage of explicitly dissecting social-ecological systems into five components: ecosystem structure and processes, ecological functions, ecosystem services, benefits and the economic and socio-cultural valuation of these services and benefits. The first two have received significant attention in the evaluation of Tamarix control effectiveness. The last three have long been implicitly acknowledged over decades of Tamarix management in the region, but have not been formally accounted for, which we believe would increase the effectiveness, accountability and transparency of management efforts.
Knowledge of the spatial and temporal distribution of surface water is important for water resource management, flood risk assessment, monitoring ecosystem health, constraining estimates of biogeochemical cycles and understanding our climate. While global-scale spatiotemporal change detection of surface water has significantly improved in recent years due to planetary-scale remote sensing and computing, it has remained challenging to distinguish the changing characteristics of rivers and lakes. Here we analyze the spatial extent of permanent and seasonal rivers and lakes globally over the past 38 years based on new data of river system extents and surface water trends. Results show that while the total permanent surface area of both rivers and lakes has remained relatively constant, the areas with intermittent seasonal coverage have increased by 12 % and 27 % for rivers and lakes, respectively. The increase is statistically significant in over 84 % of global water catchments based on Spearman's rank correlations (rho) above 0.05 and p values less than 0.05. The seasonal river extent is nearly 32 % larger than the previously observed annual mean river extent, suggesting large seasonal variations that impact not only ecosystem health but also estimations of terrestrial biogeochemical cycles of carbon. The outcomes of our analysis are shared as the Surface Area of Rivers and Lakes (SARL) database, serving as a valuable resource for monitoring and research of hydrological cycles, ecosystem accounting, and water management.
Volcanic islands are often subject to flank instability, resulting from a combination of magmatic intrusions along rift zones and gravitational spreading causing extensional faulting at the surface. Here, we study the Koaʻe fault system (KFS), located south of the summit caldera of Kīlauea volcano in Hawaiʻi, one of the most active volcanoes on Earth, prone to active faulting, episodic dike intrusions, and flank instability. Two rift zones and the KFS are major structures controlling volcanic flank instability and magma propagation. Although several magmatic intrusions occurred over the KFS, the link between these faults, two nearby rift zones and the flank instability, is still poorly studied. To better characterize the KFS and its structural linkage with the surrounding fault and rift zones, we performed a detailed structural analysis of the extensional fault system, coupled with a helicopter photogrammetric survey, covering part of the south flank of Kīlauea. We generated a high-resolution DEM (~ 8 cm) and orthomosaic (~ 4 cm) to map the fracture field in detail. We also collected ~ 1000 ground structural measurements of extensional fractures during our three field missions (2019, 2022, and 2023). We observed many small, interconnected grabens, monoclines, rollover structures, and en-echelon fractures that were in part previously undocumented. We estimate the cumulative displacement rate across the KFS during the last 600 ~ 700 years and found a decrease toward the west of the horizontal component from 2 to 6 cm per year, consistent with GNSS data. Integrating morphology observations, fault mapping, and kinematic measurements, we propose a new kinematic model of the upper part of the Kīlauea’s south flank, suggesting a clockwise rotation and a translation of a triangular wedge. This wedge is bordered by the extensional structures (ERZ, SWRZ, and the KFS), largely influenced by gravitational spreading. These findings illustrate a structural linkage between the two rift zones and the KFS, the latter being episodically affected by dike intrusions.
Infectious diseases are influenced by interactions between host and pathogen, and the number of infected hosts is rarely homogenous across the landscape. Areas with elevated pathogen prevalence can maintain a high force of infection and may indicate areas with disease impacts on host populations. However, isolating the ecological processes that result in increases in infection prevalence and intensity remains a challenge. Here we elucidate the contribution of pathogen clade and host species in disease hotspots caused by Ophidiomyces ophidiicola, the pathogen responsible for snake fungal disease, in 21 species of snakes infected with multiple pathogen strains across 10 countries in Europe. We found isolated areas of disease hotspots in a landscape where infections were otherwise low. O. ophidiicola clade had important effects on transmission, and areas with multiple pathogen clades had higher host infection prevalence. Snake species further influenced infection, with most positive detections coming from species within the Natrix genus. Our results suggest that both host and pathogen identity are essential components contributing to increased pathogen prevalence.
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Hungary","active":true,"usgs":false}],"preferred":false,"id":899415,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kolanek, Aleksandra","contributorId":335754,"corporation":false,"usgs":false,"family":"Kolanek","given":"Aleksandra","email":"","affiliations":[{"id":64462,"text":"University of Wroclaw","active":true,"usgs":false}],"preferred":false,"id":899416,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kurek, Katarzyna","contributorId":335755,"corporation":false,"usgs":false,"family":"Kurek","given":"Katarzyna","email":"","affiliations":[{"id":80500,"text":"Institute of Nature Conservation Polish Academy of Science","active":true,"usgs":false}],"preferred":false,"id":899417,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lourdais, Olivier","contributorId":335756,"corporation":false,"usgs":false,"family":"Lourdais","given":"Olivier","email":"","affiliations":[{"id":80501,"text":"Centre d’Etudes Biologiques de 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Vienna","active":true,"usgs":false}],"preferred":false,"id":899421,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Szulc, Barbara","contributorId":335760,"corporation":false,"usgs":false,"family":"Szulc","given":"Barbara","email":"","affiliations":[{"id":80505,"text":"Kazimierz Wielki University","active":true,"usgs":false}],"preferred":false,"id":899422,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ursenbacher, Sylvain","contributorId":335761,"corporation":false,"usgs":false,"family":"Ursenbacher","given":"Sylvain","email":"","affiliations":[{"id":37150,"text":"University of Neuchâtel","active":true,"usgs":false}],"preferred":false,"id":899423,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zinenko, Oleksandr","contributorId":335762,"corporation":false,"usgs":false,"family":"Zinenko","given":"Oleksandr","email":"","affiliations":[{"id":80506,"text":"Museum of Nature at V.N. Karazin Kharkiv National University","active":true,"usgs":false}],"preferred":false,"id":899424,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hoyt, Joseph R.","contributorId":201314,"corporation":false,"usgs":false,"family":"Hoyt","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":899425,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70254548,"text":"70254548 - 2024 - Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites","interactions":[],"lastModifiedDate":"2024-05-31T14:14:31.067436","indexId":"70254548","displayToPublicDate":"2024-04-10T08:48:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites","docAbstract":"The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)’s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16081333","usgsCitation":"Thankappan, M., Christopherson, J., Cantrell, S.J., Ryan, R., Pagnutti, M., Bright, C., Naughton, D., Ruslander, K.L., Wang, L., Hudson, D., Shaw, J., Ramaseri Chandra, S.N., and Anderson, C., 2024, Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites: Remote Sensing, v. 16, no. 8, 1333, 20 p., https://doi.org/10.3390/rs16081333.","productDescription":"1333, 20 p.","ipdsId":"IP-161574","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":439890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16081333","text":"Publisher Index Page"},{"id":429400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Thankappan, Medhavy","contributorId":337054,"corporation":false,"usgs":false,"family":"Thankappan","given":"Medhavy","email":"","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopherson, Jon 0000-0002-2472-0059 jonchris@usgs.gov","orcid":"https://orcid.org/0000-0002-2472-0059","contributorId":2552,"corporation":false,"usgs":true,"family":"Christopherson","given":"Jon","email":"jonchris@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cantrell, Simon John 0000-0001-6909-1973","orcid":"https://orcid.org/0000-0001-6909-1973","contributorId":337055,"corporation":false,"usgs":true,"family":"Cantrell","given":"Simon","email":"","middleInitial":"John","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Robert","contributorId":337056,"corporation":false,"usgs":false,"family":"Ryan","given":"Robert","affiliations":[{"id":80960,"text":"Innovative Imaging and Research Inc. (I2R)","active":true,"usgs":false}],"preferred":false,"id":901857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pagnutti, Mary","contributorId":337057,"corporation":false,"usgs":false,"family":"Pagnutti","given":"Mary","email":"","affiliations":[{"id":80960,"text":"Innovative Imaging and Research Inc. (I2R)","active":true,"usgs":false}],"preferred":false,"id":901858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bright, Courtney","contributorId":337058,"corporation":false,"usgs":false,"family":"Bright","given":"Courtney","email":"","affiliations":[{"id":80961,"text":"Commonwealth Scientific and Industrial Research Organisation (CSIRO)","active":true,"usgs":false}],"preferred":false,"id":901860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Naughton, Denis","contributorId":337059,"corporation":false,"usgs":false,"family":"Naughton","given":"Denis","email":"","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruslander, Kathryn Lynn 0000-0003-3036-1731","orcid":"https://orcid.org/0000-0003-3036-1731","contributorId":337060,"corporation":false,"usgs":true,"family":"Ruslander","given":"Kathryn","email":"","middleInitial":"Lynn","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wang, Lan-Wei","contributorId":337061,"corporation":false,"usgs":false,"family":"Wang","given":"Lan-Wei","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901863,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, David","contributorId":337062,"corporation":false,"usgs":false,"family":"Hudson","given":"David","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901864,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shaw, Jerad 0000-0002-8319-2778 jshaw@usgs.gov","orcid":"https://orcid.org/0000-0002-8319-2778","contributorId":3564,"corporation":false,"usgs":true,"family":"Shaw","given":"Jerad","email":"jshaw@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":901865,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ramaseri Chandra, Shankar N. 0000-0002-4434-4468","orcid":"https://orcid.org/0000-0002-4434-4468","contributorId":216043,"corporation":false,"usgs":true,"family":"Ramaseri Chandra","given":"Shankar","email":"","middleInitial":"N.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901859,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901866,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70256587,"text":"70256587 - 2024 - Artificial structure selection by economically important reef fishes at North Carolina artificial reefs","interactions":[],"lastModifiedDate":"2024-08-06T12:30:55.981873","indexId":"70256587","displayToPublicDate":"2024-04-10T07:23:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Artificial structure selection by economically important reef fishes at North Carolina artificial reefs","docAbstract":"Artificial reefs can play an important role in marine fisheries management by supplementing or enhancing natural habitats. Despite their increased use in recent years, the choice of structures used at artificial reefs remains largely haphazard due to the lack of information on reef structure performance. Few studies have examined the use of different artificial reef structures by individual fish. From 2021-2022, we acoustically tagged 72 black sea bass (Centropristis striata), 34 gag (Mycteroperca mircrolepis), 27 greater amberjack (Seriola dumerili), nine almaco jack (S. rivoliana), and eight red snapper (Lutjanus campechanus) on four artificial reef complexes near Cape Lookout, North Carolina, U.S. Available artificial reef structures consisted of materials of various sizes and heights made of concrete and metal. We tracked tagged fish using a fine-scale positioning system for ~100 days. Black sea bass exhibited high site fidelity to the artificial structure where we caught them, rarely moving away from that structure. The limited movement resulted in low transition probabilities; we conclude that black sea bass do not select for particular artificial structures. Gag and red snapper moved greater distances away from artificial structures and routinely moved between them. Greater amberjack and almaco jack moved the most within the complexes displaying circling behavior around individual structures and were the only species that regularly moved off the artificial reef complexes. Greater amberjack movements away from artificial sites were most commonly directed to surrounding shipwrecks. Whereas gag, red snapper, almaco jack, and greater amberjack used all available structures, they consistently selected for high relief structures, such as vessels, more than other structures. These results will be useful to managers charged with decisions on what types of structures to place at artificial reef complexes to supplement or enhance habitat for economically important fishes.
Magnetotelluric (MT) and audiomagnetotelluric (AMT) data are used to better understand the subsurface geology and mineral resources in the San Juan–Silverton caldera complex located near Silverton, Colorado, western United States, as part of the extensive southern Rocky Mountains volcanic field that covers much of southwestern Colorado and northern New Mexico. Seven MT and AMT profiles of varying lengths image resistivity structure to depths of ~5 km. The AMT inversion models characterize geophysical responses of near-surface lithologies, structures, and mineralized systems and also help corroborate airborne electromagnetic data at shallow levels. The MT inversion models extend our depth of investigation from near the surface to great depths (~5 km) and help to form hypotheses about roots of the hydrothermal plumbing that fed shallower mineralized systems. Subsurface high resistivities occur beneath intermediate-composition lava flows and Proterozoic units. Subsurface moderate- to low-resistivity values may reflect hydrothermal plumbing that served as flow paths for mineralizing fluids and metallic ore formation. The model interpretations presented in this study could be utilized in remediation planning or mineral resource applications. The methods used could be applied to other watersheds with similar volcanic environments containing acid-generating historical mines or hydrothermally altered and mineralized source rocks.
This paper aims to expand fisheries managers' understanding of how the science of communication can facilitate effective fisheries management. We offer context-specific definitions of four communication approaches that are commonly performed by fisheries managers but poorly defined and can easily be confused or conflated. These are as follows:
Genetic variation in Arctic species is often influenced by vicariance during the Pleistocene, as ice sheets fragmented the landscape and displaced populations to low- and high-latitude refugia. The formation of secondary contact or suture zones during periods of ice sheet retraction has important consequences on genetic diversity by facilitating genetic connectivity between formerly isolated populations. Brant geese (Branta bernicla) are a maritime migratory waterfowl (Anseriformes) species that almost exclusively uses coastal habitats. Within North America, brant geese are characterized by two phenotypically distinct subspecies that utilize disjunct breeding and wintering areas in the northern Pacific and Atlantic. In the Western High Arctic of Canada, brant geese consist of individuals with an intermediate phenotype that are rarely observed nesting outside this region. We examined the genetic structure of brant geese populations from each subspecies and areas consisting of intermediate phenotypes using mitochondrial DNA (mtDNA) control region sequence data and microsatellite loci. We found a strong east–west partition in both marker types consistent with refugial populations. Within subspecies, structure was also observed at mtDNA while microsatellite data suggested the presence of only two distinct genetic clusters. The Western High Arctic (WHA) appears to be a secondary contact zone for both Atlantic and Pacific lineages as mtDNA and nuclear genotypes were assigned to both subspecies, and admixed individuals were observed in this region. The mtDNA sequence data outside WHA suggests no or very restricted intermixing between Atlantic and Pacific wintering populations which is consistent with published banding and telemetry data. Our study indicates that, although brant geese in the WHA are not a genetically distinct lineage, this region may act as a reservoir of genetic diversity and may be an area of high conservation value given the potential of low reproductive output in this species.
We introduce a Python package for computing focal mechanism solutions. This algorithm, which we refer to as SKHASH, is largely based on the HASH algorithm originally written in Fortran over 20 yr ago. HASH innovated the use of suites of solutions, spanning the expected errors in polarities and takeoff angles, to estimate focal mechanism uncertainty. SKHASH benefits from new features with flexible input formats and allows users to take advantage of recent advances in constraining focal mechanisms for small magnitude or poorly recorded earthquakes. The 3D locations of earthquakes and the velocity models used are varied when finding acceptable solutions. As a result, source–receiver azimuths are reflective of errors from the earthquake locations and velocity models, in addition to the takeoff angles. Users can consider weighted P‐wave first‐motion polarities derived from traditional or machine‐learning picks, cross‐correlation consensus, and/or imputation techniques using SKHASH. Focal mechanism solutions can also be further constrained using traditional, machine learning, and/or cross‐correlation consensus S/P amplitude ratios. With improved reporting of individual and collective P polarity and S/P amplitude misfits, users can better evaluate the success of the solutions and the quality of the measurements. The reporting also makes it easier to identify potential issues with metadata, including incorrectly reported station polarity reversals. In addition, by leveraging vectorized operations, taking advantage of an efficient backend Python C Application Programming Interface, and the use of a parallel environment, the Python SKHASH routine may compute mechanisms quicker than the HASH routine.
High subsidence rates are inherent to coastal deltas worldwide, contributing to rapid rates of relative sea-level rise and compromising the sustainability of coastal wetlands. Different parts of river deltas, however, experience accretion or erosion, depending on the coupling between ecological and morphological processes. Wetland expansion occurs in active deltaic coastal basins that are connected to riverine sedimentation. In contrast, wetland degradation occurs in inactive deltaic coastal basins where river engineering strategies associated with flood control restrict river connectivity. Here, we investigated the relative role of inorganic and organic loading to marsh accretion rates spanning fresh to brackish to saline zones between active and inactive coastal deltaic floodplains of the Mississippi River Delta. Marsh surface accretion rates monitored over 36 months using the feldspar marker horizon technique ranged from 1.24 ± 0.35 cm yr−1 in the freshwater marsh to 2.94 ± 0.51 cm yr−1 in the saline marsh in the inactive coastal basin compared to an opposite trend in the active coastal basin with a low vertical accretion rate in the saline site at 1.12 ± 0.17 cm yr−1 and higher accretion values at the freshwater site (2.14 ± 0.49 cm yr−1). Our results suggest that saline marshes have high resilience identified by high vertical accretion rates exceeding those of river-dominated freshwater marshes in active deltaic floodplains. Overall, the marsh surface accretionary patterns detected in this study underscores the relative contribution of organic and inorganic sediments to elevation capital across salinity gradients between active and inactive basins in coastal Louisiana with particular interest to river management and restoration strategies. These findings, however, are applicable to coastal deltaic floodplains elsewhere given the repetition geomorphic forcings (e.g., relative contribution of riverine, tidal and wave power) and coastal typologies worldwide.
In 2021, the Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, increased seismicity, and other significant activity at 15 volcanic centers in Alaska and the Commonwealth of the Northern Mariana Islands. Eruptive activity in Alaska consisted of repeated small, ash-producing, phreatomagmatic explosions from Mount Young on Semisopochnoi Island; an explosion at Great Sitkin Volcano followed by the eruption of a thick lava flow that filled and overflowed the summit crater; weak explosive activity and the eruption of small, channelized flows at Pavlof Volcano; and a short-lived eruption at Mount Veniaminof that produced ash emissions from an intracaldera cone, as well as lava flows confined to a melt pit in the ice mantling the cone’s flank. Mount Cleveland had a period of unrest, but no eruptive activity took place there. Anomalous seismicity was also detected at Atka volcanic complex, Mount Gareloi, and Davidof volcano. New warm springs opened and deposited mud at the summit and north base of Shrub mud volcano. Other activity of note in Alaska consisted of large ice and rock avalanches at Iliamna Volcano and Mount Spurr, ash resuspension events at Mount Katmai and Aniakchak Crater, and anomalous deformation at Mount Okmok that was consistent with a shallow intrusion of magma. In the Commonwealth of the Northern Marianas Islands, a brief, ash-producing eruption occurred at Mount Pagan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245014","collaboration":"The Alaska Volcano Observatory is a consortium between the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Orr, T.R., Dietterich, H.R., Fee D., Girona, T., Grapenthin, R., Haney, M.M., Loewen, M.W., Lyons, J.J., Power, J.A., Schwaiger, H.F., Schneider, D.J., Tan, D., Toney, L., Wasser, V.K., Waythomas, C.F., 2024, 2021 Volcanic activity in Alaska and the Commonwealth of the Northern Mariana Islands—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2024–5014, 64 p., https://doi.org/10.3133/sir20245014.","productDescription":"ix, 64 p.","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-139235","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":427361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5014/sir20245014.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5014"},{"id":427360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5014/covrthb.jpg"}],"country":"Northern Mariana Islands, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -180.91039541038674,\n 52.397333461784\n ],\n [\n -179.15258291038657,\n 50.647658713281515\n ],\n [\n -154.36742666038634,\n 54.59269911796724\n ],\n [\n -144.8752391603861,\n 61.7067556778085\n ],\n [\n -148.56664541038634,\n 63.09098661447797\n ],\n [\n -154.01586416038626,\n 61.95569747993264\n ],\n [\n -158.93773916038643,\n 59.28407472678845\n ],\n [\n -165.7932079103864,\n 55.399337204164055\n ],\n [\n -173.17602041038666,\n 53.76976304468752\n ],\n [\n -178.62523916038657,\n 52.71793714020785\n ],\n [\n -180.91039541038674,\n 52.397333461784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 146,\n 20\n ],\n [\n 146,\n 14\n ],\n [\n 144,\n 14\n ],\n [\n 144,\n 20\n ],\n [\n 146,\n 20\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508