Invertebrates are well-known predators of amphibians with many documented cases of spiders preying upon anurans (reviewed in Toledo 2005. Herpetol. Rev. 36:395–400). Wolf spiders are known to feed on a variety of frogs, including those in the genus Acris (Blackburn et al. 2002. Herpetol. Rev. 33:299). Although typically terrestrial, wolf spiders have been found feeding on arboreal frogs ca. 1 m above the ground (Aucone and Card 2002. Herpetol. Rev. 33:48). To our knowledge, no records exist of a wolf spider feeding on a terrestrial frog at an elevated height. At 0113 h on 30 April 2019, we observed an adult female wolf spider (Tigrosa georgicola: Lycosidae) feeding on an adult Acris blanchardi ca. 1.5 m high on the trunk of a small tree at the edge of a pond in Sherburne Wildlife Management Area, St. Martin Parish, Louisiana, USA (30.424°N, 91.663°W; WGS 84; Fig. 1). The spider was positioned facing the ground and the partially digested frog was hanging from its mouthparts. The spider likely captured the frog on the ground near the edge of the water and retreated up the tree with its meal (Fig. 1B). Movement of spiders with prey from an initial point of capture is documented in wolf spiders (Aucone and Card 2002, op. cit.) and other large terrestrial spiders (Maffei et al. 2010. Herpetol. Notes 3:167–170). This behavior may minimize the vulnerability of the spider to predators. We thank Zack Lemann, Curator of Animal Collections at the Audubon Butterfly Garden and Insectarium, for spider identification.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Maldonado, B.R., Glorioso, B., and Kidder, R.P., 2020, Acris blanchardi (Blanchard's Cricket Frog), Predation: Herpetological Review, v. 51, no. 2.","productDescription":"1 p.","startPage":"296","ipdsId":"IP-112194","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":375469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375441,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/"}],"country":"United States","state":"Louisiana","county":"St Martin Parish","otherGeospatial":"Sherburne Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.73468112945557,\n 30.445306929719315\n ],\n [\n -91.70335292816162,\n 30.445306929719315\n ],\n [\n -91.70335292816162,\n 30.469685487622733\n ],\n [\n -91.73468112945557,\n 30.469685487622733\n ],\n [\n -91.73468112945557,\n 30.445306929719315\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maldonado, Brittany R. 0000-0002-9737-6922","orcid":"https://orcid.org/0000-0002-9737-6922","contributorId":225150,"corporation":false,"usgs":true,"family":"Maldonado","given":"Brittany","email":"","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":204397,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kidder, Raymond P. II 0000-0002-7102-788X","orcid":"https://orcid.org/0000-0002-7102-788X","contributorId":225151,"corporation":false,"usgs":true,"family":"Kidder","given":"Raymond","suffix":"II","email":"","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790561,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210530,"text":"70210530 - 2020 - Low-level detection of SFD-causing Ophidiomyces on Burmese Pythons in southwest Florida, with confirmation of the pathogen on co-occurring native snakes","interactions":[],"lastModifiedDate":"2020-12-15T20:27:43.701359","indexId":"70210530","displayToPublicDate":"2020-06-09T11:09:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Low-level detection of SFD-causing Ophidiomyces on Burmese Pythons in southwest Florida, with confirmation of the pathogen on co-occurring native snakes","title":"Low-level detection of SFD-causing Ophidiomyces on Burmese Pythons in southwest Florida, with confirmation of the pathogen on co-occurring native snakes","docAbstract":"Snake fungal disease (SFD), or ophidiomycosis, is caused by the fungus Ophidiomyces ophiodiicola (Allender et al. 2015; Lorch et al. 2015). SFD is widespread across wild populations in the eastern United States (Lorch et al. 2016) and is known to infect more than 30 species of snake in North America and Europe (Lorch et al. 2016; Franklinos et al. 2017). No known phylogenetic or ecological patterns have been observed in susceptibility among snake taxa, and it is presumed that all species are likely susceptible (Burbrink et al. 2017).
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Glorioso, B., Bartoszek, I.A., and Lorch, J.M., 2020, Low-level detection of SFD-causing Ophidiomyces on Burmese Pythons in southwest Florida, with confirmation of the pathogen on co-occurring native snakes: Herpetological Review, v. 51, no. 2, p. 245-247.","productDescription":"3 p.","startPage":"245","endPage":"247","ipdsId":"IP-113676","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":375468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375438,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.6171875,\n 24.986058021167594\n ],\n [\n -80.4638671875,\n 24.986058021167594\n ],\n [\n -80.4638671875,\n 27.352252938063845\n ],\n [\n -82.6171875,\n 27.352252938063845\n ],\n [\n -82.6171875,\n 24.986058021167594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":204397,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartoszek, Ian A.","contributorId":138954,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian","email":"","middleInitial":"A.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":790541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":790542,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263557,"text":"70263557 - 2020 - Optimizing earthquake early warning alert distance strategies using the July 2019 Mw6.4 and Mw7.1 Ridgecrest, California, earthquakes","interactions":[],"lastModifiedDate":"2025-02-13T16:51:37.501189","indexId":"70263557","displayToPublicDate":"2020-06-09T10:48:49","publicationYear":"2020","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":"Optimizing earthquake early warning alert distance strategies using the July 2019 Mw6.4 and Mw7.1 Ridgecrest, California, earthquakes","docAbstract":"The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median‐expected peak ground motions with distance, then using these ground motions to determine median‐expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground‐motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground‐motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground‐motion uncertainties, we find MMI IV alert regions using median‐expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground‐motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade‐off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200022","usgsCitation":"Saunders, J.K., Aagaard, B.T., Baltay Sundstrom, A.S., and Minson, S.E., 2020, Optimizing earthquake early warning alert distance strategies using the July 2019 Mw6.4 and Mw7.1 Ridgecrest, California, earthquakes: Bulletin of the Seismological Society of America, v. 110, no. 4, p. 1872-1886, https://doi.org/10.1785/0120200022.","productDescription":"15 p.","startPage":"1872","endPage":"1886","ipdsId":"IP-115105","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.78214580574435,\n 37.13529952586548\n ],\n [\n -118.8143775521145,\n 37.13529952586548\n ],\n [\n -118.8143775521145,\n 34.29388629344095\n ],\n [\n -115.78214580574435,\n 34.29388629344095\n ],\n [\n -115.78214580574435,\n 37.13529952586548\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"110","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders, Jessie Kate 0000-0001-5340-6715","orcid":"https://orcid.org/0000-0001-5340-6715","contributorId":290634,"corporation":false,"usgs":true,"family":"Saunders","given":"Jessie","email":"","middleInitial":"Kate","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":927336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927338,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211027,"text":"70211027 - 2020 - Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters","interactions":[],"lastModifiedDate":"2023-03-27T17:19:48.95791","indexId":"70211027","displayToPublicDate":"2020-06-09T09:51:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters","docAbstract":"Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12863","usgsCitation":"Penn, C.A., Clow, D.W., Sexstone, G.A., and Murphy, S.F., 2020, Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters: Journal of the American Water Resources Association, v. 56, no. 5, p. 882-902, https://doi.org/10.1111/1752-1688.12863.","productDescription":"21 p.","startPage":"882","endPage":"902","ipdsId":"IP-109042","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":436937,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B08S5N","text":"USGS data release","linkHelpText":"Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS)"},{"id":376258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 37.25\n ],\n [\n -106,\n 37.25\n ],\n [\n -106,\n 38.25\n ],\n [\n -108,\n 38.25\n ],\n [\n -108,\n 37.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Penn, Colin A. 0000-0002-5195-2744 cpenn@usgs.gov","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":5336,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"cpenn@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexstone, Graham A. 0000-0001-8913-0546 sexstone@usgs.gov","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":5159,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham","email":"sexstone@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":792478,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212498,"text":"70212498 - 2020 - The impact of sediment supply on the initiation and magnitude of runoff-generated debris flows","interactions":[],"lastModifiedDate":"2020-08-18T14:37:14.303197","indexId":"70212498","displayToPublicDate":"2020-06-09T09:37:07","publicationYear":"2020","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":"The impact of sediment supply on the initiation and magnitude of runoff-generated debris flows","docAbstract":"Rainfall intensity‐duration (ID) thresholds are commonly used to assess the potential for runoff‐generated debris flows, but the sensitivity of these thresholds to sediment supply, which can change rapidly with time, is relatively unexplored. Furthermore, debris flows often self‐organize into distinct surges, but the factors controlling the magnitude and frequency of these surges, including sediment supply and grain size, are poorly constrained. We use a combination of numerical modeling and debris flow monitoring data from Chalk Cliffs, Colorado, USA, to explore how sediment supply influences rainfall ID thresholds for debris flows and surge properties. Results suggest that rainfall ID thresholds only become sensitive to sediment supply below a sediment thickness threshold. Surge magnitude is a nonmonotonic function of sediment supply (i.e., channel bed sediment thickness and grain size) with the largest surges tending to form at intermediate values of sediment availability with intermediate grain sizes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL087643","usgsCitation":"Tang, H., McGuire, L.A., Kean, J.W., and Smith, J.B., 2020, The impact of sediment supply on the initiation and magnitude of runoff-generated debris flows: Geophysical Research Letters, v. 47, no. 14, e2020GL087643, 13 p., https://doi.org/10.1029/2020GL087643.","productDescription":"e2020GL087643, 13 p.","ipdsId":"IP-118444","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":456464,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl087643","text":"Publisher Index Page"},{"id":377602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.31280899047852,\n 38.7080176975273\n ],\n [\n -106.17565155029297,\n 38.7080176975273\n ],\n [\n -106.17565155029297,\n 38.76613041372937\n ],\n [\n -106.31280899047852,\n 38.76613041372937\n ],\n [\n -106.31280899047852,\n 38.7080176975273\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Tang, Hui","contributorId":215352,"corporation":false,"usgs":false,"family":"Tang","given":"Hui","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":796587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":796588,"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":796589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796590,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256216,"text":"70256216 - 2020 - Felsic melt and gas mobilisation during magma solidification: An experimental study at 1.1 kbar","interactions":[],"lastModifiedDate":"2024-07-29T14:47:14.850019","indexId":"70256216","displayToPublicDate":"2020-06-09T09:35:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Felsic melt and gas mobilisation during magma solidification: An experimental study at 1.1 kbar","docAbstract":"Melt and gas transfer processes are essential to the formation and growth of the Earth’s crust and for sustaining volcanic activity. These processes also play a major role in magma fractionation at shallow depths (<10 km) where magmas stall rheologically and solidify. In this scenario, the conditions of melt and gas mobilization during progressive cooling of crystal mushes down to their solidus remain poorly understood. We present experimental data (at 1.1 kbar) showing how a combination of temperature and crystal content control the ability of melt and gas to escape from cooling and solidifying hydrous silicic magmas with initial crystal volume fractions (Φ) of 0.6, 0.7, and 0.8, and for temperature snapshots of 850, 800, and 750°. Microstructural observations and chemical data show that the amount of extracted melt increases by 70% from 850 to 750° and by 40% from Φ = 0.6 to 0.8 at 750°, due to the formation of interconnected crystal frameworks, gas expansion in constricted pore space, and filter pressing during cooling. As a result, our experiments suggest that melt and gas extraction from cooling mushes increases in proximity to their solidus and can operate efficiently at 0.6 < Φ <0.93. These observations shed light on maximum estimates of the segregation of gas-rich, crystal-poor magmas (0.02 m/year at 850° to 9 m/year at 750°) to form felsic dykes or eruptible systems feeding volcanoes.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2020.00175","usgsCitation":"Pistone, M., Baumgartner, L., Begue, F., Jarvis, P., Bloch, E., Robyr, M., Muntener, O., Sisson, T.W., and Blundy, J.D., 2020, Felsic melt and gas mobilisation during magma solidification: An experimental study at 1.1 kbar: Frontiers in Earth Science, v. 8, 175, 18 p., https://doi.org/10.3389/feart.2020.00175.","productDescription":"175, 18 p.","ipdsId":"IP-118636","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.00175","text":"Publisher Index Page"},{"id":431562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2020-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Pistone, Mattia","contributorId":340416,"corporation":false,"usgs":false,"family":"Pistone","given":"Mattia","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baumgartner, Lukas","contributorId":340419,"corporation":false,"usgs":false,"family":"Baumgartner","given":"Lukas","email":"","affiliations":[{"id":35541,"text":"University of Lausanne","active":true,"usgs":false}],"preferred":false,"id":907127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Begue, Florence","contributorId":340422,"corporation":false,"usgs":false,"family":"Begue","given":"Florence","email":"","affiliations":[{"id":35541,"text":"University of Lausanne","active":true,"usgs":false}],"preferred":false,"id":907128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarvis, Paul A.","contributorId":340425,"corporation":false,"usgs":false,"family":"Jarvis","given":"Paul A.","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":907129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bloch, Elias","contributorId":340427,"corporation":false,"usgs":false,"family":"Bloch","given":"Elias","email":"","affiliations":[{"id":35541,"text":"University of Lausanne","active":true,"usgs":false}],"preferred":false,"id":907130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robyr, Martin","contributorId":340457,"corporation":false,"usgs":false,"family":"Robyr","given":"Martin","email":"","affiliations":[],"preferred":false,"id":907178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muntener, Othmar","contributorId":340431,"corporation":false,"usgs":false,"family":"Muntener","given":"Othmar","email":"","affiliations":[{"id":35541,"text":"University of Lausanne","active":true,"usgs":false}],"preferred":false,"id":907131,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sisson, Thomas W. 0000-0003-3380-6425 tsisson@usgs.gov","orcid":"https://orcid.org/0000-0003-3380-6425","contributorId":2341,"corporation":false,"usgs":true,"family":"Sisson","given":"Thomas","email":"tsisson@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":907132,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blundy, Jon D.","contributorId":340433,"corporation":false,"usgs":false,"family":"Blundy","given":"Jon","email":"","middleInitial":"D.","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":907133,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211707,"text":"70211707 - 2020 - Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence","interactions":[],"lastModifiedDate":"2020-08-07T13:28:29.468565","indexId":"70211707","displayToPublicDate":"2020-06-09T08:24:46","publicationYear":"2020","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":"Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence","docAbstract":"We use a large instrumental dataset from the 2019 Ridgecrest earthquake sequence (Rekoske et al., 2019, 2020) to examine repeatable source‐, path‐, and site‐specific ground motions. A mixed‐effects analysis is used to partition total residuals relative to the Boore et al. (2014; hereafter, BSSA14) ground‐motion model. We calculate the Arias intensity stress drop for the earthquakes and find strong correlation with our event terms, indicating that they are consistent with source processes. We look for physically meaningful trends in the partitioned residuals and test the ability of BSSA14 to capture the behavior we observe in the data.
We find that BSSA14 is a good match to the median observations for
Native steelhead (anadromous form of rainbow trout [Oncorhynchus mykiss]) and bridgelip sucker (Catostomus columbianus) were historically used by the Kah-miltpah (Rock Creek) Band for sustenance, trade, and traditional practices in Rock Creek, a tributary to the Columbia River in southeastern Washington State. Rock Creek flows south to the Columbia River at river kilometer (rkm) 368 and is an intermittent stream of great significance to the Yakama Nation and to the Kah-miltpah Band in particular. Concern over declines in the abundance of these fish in Rock Creek prompted a research and monitoring program to better understand habitat conditions, population status, and limiting factors. In addition to steelhead and bridgelip sucker, coho salmon (Oncorhynchus kisutch) and resident rainbow trout are also present and monitored. Rainbow trout and steelhead will be collectively referred to as O. mykiss. Streamflow is a limiting habitat factor in this system, but steelhead and coho salmon still successfully return to spawn, rear, outmigrate, and survive over summer in many of the isolated pools that provide important refuge for juvenile rearing.
We completed a habitat survey during autumn 2018 to assess the perennial pools during low-flow conditions. In Rock Creek, the overall percentage of habitat recorded as dry was 41, non-pool wet was 42, and pool was 17. The number of pools (n=93) recorded was less than during previous years’ survey efforts (2015–17). The percentage of non-pool wet habitat was generally higher in 2018 than in previous years. This is a likely result of habitat reaches, which in the past, were considered pools but have become shallower and smaller and are now categorized as non-pool wet habitat. However, the fewer habitat reaches categorized as pools in 2018 now have an average length, area, and depth that are generally greater than in past years. In Walaluuks Creek, the percentage of habitat recorded as dry was 53, non-pool wet was 40, and pool was 7. The percentage of pool habitat was the lowest of all years surveyed since 2015.
Fish sampling occurred during autumn after habitat surveys were completed from October 1 to November 9. Fish species distribution, relative abundance, length-frequency distribution, and pool fish density were determined using backpack electrofishing in stratified, systematically selected pools. During fish sampling, 855 O. mykiss were handled and 662 were tagged with a passive integrated transponder (PIT) tag, and 718 coho salmon were handled and 567 were PIT tagged. A total of 536 bridgelip suckers and largescale suckers (Catostomus macrocheilus [n=6]) were handled and 294 were PIT tagged. In Rock Creek, pool abundance estimates were calculated for six pools for both O. mykiss age classes (age 0 and age 1 or older [age 1+]) and one additional pool for age 1+. For pools where age-0 O. mykiss were present, the average pool population abundance was 0.144 (n=6; range: 0.052–0.208) fish per square meter. For age-1+ O. mykiss, the average pool population abundance was 0.045 (n=7; range: 0.002–0.179) fish per square meter. For age-0 O. mykiss in Walaluuks Creek, the average pool abundance was 0.207 fish per square meter (n=7; range: 0.038–0.416), and for age-1+ fish, the average pool abundance was 0.382 fish per square meter (n=6; range: 0.009–0.761). In Rock Creek, coho salmon were more abundant than O. mykiss in pools except for three pools upstream from rkm 20. The average pool abundance for coho salmon was 0.256 fish per square meter (n=8; range: 0.019–0.756) in Rock Creek pools. In Walaluuks Creek, coho salmon were captured in four pools and were not captured in the upstream pools sampled. The average pool abundance for coho salmon in the four lower pools was 0.488 fish per square meter (n=4; range: 0.417–0.548). Bridgelip suckers were captured in all pools in Rock Creek except the pool sampled at rkm 21.8. The average pool abundance for bridgelip suckers was 0.552 fish per square meter (n=7; range: 0.015–1.554) in Rock Creek. Bridgelip suckers were captured in three downstream pools in Walaluuks Creek, and the average abundance was 0.044 fish per square meter (n=3; range: 0.024–0.085).
Overwinter and reach survival probabilities were estimated for O. mykiss and coho salmon using a Cormack-Jolly-Seber modeling approach. The best fit survival model for the O. mykiss and coho salmon was a reach only model. The upstream reach includes overwinter survival probability because fish are tagged and released in autumn and primarily migrate the following spring. During 2018, coho salmon (0.568, standard error [SE]=0.027) had a significantly higher probability of overwinter survival than O. mykiss (0.276, SE=0.019). The reach survival probability was higher for O. mykiss than coho salmon in the downstream migratory reaches. Survival was not modeled for bridgelip suckers. For bridgelip suckers, 147 were detected of 294, that were PIT tagged and released in the Rock Creek subbasin (50.0 percent).
Information provided in this report increases our understanding of the status and trends of these populations. It further documents how intermittent streams can support salmonid populations. It also provides insight into potential management and restoration actions that could be beneficial and timing and allocation of resources. Ongoing monitoring work of this population will inform progress towards Rock Creek species recovery goals and contribution to recovery goals for the steelhead Middle Columbia River Distinct Population Segment.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The role of subduction zone geometry in the nucleation and propagation of great-sized earthquake ruptures is an important topic for earthquake hazard, since knowing how big an earthquake can be on a given fault is fundamentally important. Past studies have shown subducting bathymetric features (e.g. ridges, fracture zones, seamount chains) may arrest a propagating rupture. Other studies have correlated the occurrence of great-sized earthquakes with flat megathrusts and homogenous stresses over large distances. It remains unclear, however, how subduction zone geometry and the potential for great-sized earthquakes (M 8+) are quantifiably linked—or indeed whether they can be. Here, we examine the potential role of subduction zone geometry in limiting earthquake rupture by mapping the planarity of seismogenic zones in the Slab2 subduction zone geometry database. We build from the observation that historical great-sized earthquakes have preferentially occurred where the surrounding megathrust is broadly planar, and we use this relationship to search for geometrically similar features elsewhere in subduction zones worldwide. Assuming geometry exerts a primary control on earthquake propagation and termination, we estimate the potential size distribution of large (M 7+) earthquakes and the maximum earthquake magnitude along global subduction faults based on geometrical features alone. Our results suggest that most subduction zones are capable of hosting great-sized earthquakes over much of their area. Many bathymetric features previously identified as barriers are indistinguishable from the surrounding megathrust from the perspective of slab curvature, meaning that they either do not play an important role in arresting earthquake rupture or that their influence on slab geometry at depth is not resolvable at the spatial scale of our subduction zone geometry models.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggaa254","usgsCitation":"Plescia, S.M., and Hayes, G., 2020, Geometric controls on megathrust earthquakes: Geophysical Journal International, v. 222, no. 2, p. 1270-1282, https://doi.org/10.1093/gji/ggaa254.","productDescription":"13 p.","startPage":"1270","endPage":"1282","ipdsId":"IP-118723","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":387672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"222","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Plescia, Steven M.","contributorId":261740,"corporation":false,"usgs":false,"family":"Plescia","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":52978,"text":"Department of Geological Sciences, University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":820518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820519,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218221,"text":"70218221 - 2020 - Survival estimates for the invasive American bullfrog","interactions":[],"lastModifiedDate":"2021-02-19T19:59:33.384981","indexId":"70218221","displayToPublicDate":"2020-06-05T13:54:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":751,"text":"Amphibia-Reptilia","active":true,"publicationSubtype":{"id":10}},"title":"Survival estimates for the invasive American bullfrog","docAbstract":"American bullfrogs (Lithobates catesbeianus) are significant invaders in many places and can negatively impact native species. Despite their impact and wide distribution, little is known about their demography. We used five years of capture mark-recapture data to estimate annual apparent survival of post-metamorphic bullfrogs in a population on the Buenos Aires National Wildlife Refuge in their invaded range in Arizona, U.S.A. This population is a potential source of colonists into breeding ponds used by the federally threatened Chiricahua leopard frog (L. chiricahuensis). Results from robust-design Cormack-Jolly-Seber models suggested that survival of bullfrogs was influenced by sex and precipitation but not body condition. Survival was higher for females (mean = 0.37; 95% CI=0.15, 0.72) than males (mean = 0.17; 95% CI=0.02, 0.49), and declined with reduced annual precipitation (mean = −0.36, 95% CI = −2.09, 0.84). These survival estimates can be incorporated into models of population dynamics and to help predict spread of bullfrogs.
","language":"English","publisher":"Brill","doi":"10.1163/15685381-bja10016","usgsCitation":"Howell, P., Muths, E., Sigafus, B.H., and Hossack, B., 2020, Survival estimates for the invasive American bullfrog: Amphibia-Reptilia, v. 41, no. 4, p. 559-564, https://doi.org/10.1163/15685381-bja10016.","productDescription":"6 p.","startPage":"559","endPage":"564","ipdsId":"IP-112892","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":456482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://figshare.com/articles/journal_contribution/Survival_estimates_for_the_invasive_American_bullfrog/12301367","text":"Publisher Index Page"},{"id":383391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Buenos Aires National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.61148071289062,\n 31.439208864183147\n ],\n [\n -111.3079833984375,\n 31.439208864183147\n ],\n [\n -111.3079833984375,\n 31.85773063158148\n ],\n [\n -111.61148071289062,\n 31.85773063158148\n ],\n [\n -111.61148071289062,\n 31.439208864183147\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":810470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":243368,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":810472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810473,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70214644,"text":"70214644 - 2020 - The Moon as a climate-quality radiometric calibration reference","interactions":[],"lastModifiedDate":"2020-10-01T17:45:54.634478","indexId":"70214644","displayToPublicDate":"2020-06-05T12:42:02","publicationYear":"2020","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":"The Moon as a climate-quality radiometric calibration reference","docAbstract":"On-orbit calibration requirements for a space-based climate observing system include long-term sensor response stability and reliable inter-calibration of multiple sensors, both contemporaneous and in succession. The difficulties with achieving these for reflected solar wavelength instruments are well known. The Moon can be considered a diffuse reflector of sunlight, and its exceptional photometric stability has enabled development of a lunar radiometric reference, manifest as a model that is queried for the specific conditions of Moon observations. The lunar irradiance model developed by the Robotic Lunar Observatory (ROLO) project has adequate precision for sensor response temporal trending, but a climate-quality lunar reference will require at least an order of magnitude improvement in absolute accuracy. To redevelop the lunar calibration reference with sub-percent uncertainty and SI traceability requires collecting new, high-accuracy Moon characterization measurements. This paper describes specifications for such measurements, along with a conceptual framework for reconstructing the lunar reference using them. Three currently active NASA-sponsored projects have objectives to acquire measurements that can support a climate-quality lunar reference: air-LUSI, dedicated lunar spectral irradiance measurements from the NASA ER-2 high altitude aircraft; ARCSTONE, dedicated lunar spectral reflectance measurements from a small satellite; and Moon viewing opportunities by CLARREO Pathfinder from the International Space Station.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12111837","usgsCitation":"Stone, T.C., Kieffer, H.H., Lukashin, C., and Turpie, K., 2020, The Moon as a climate-quality radiometric calibration reference: Remote Sensing, v. 12, no. 11, p. 1837-1853, https://doi.org/10.3390/rs12111837.","productDescription":"17 p.","startPage":"1837","endPage":"1853","ipdsId":"IP-118345","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":456486,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12111837","text":"Publisher Index Page"},{"id":378965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moon","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Thomas C. 0000-0001-5088-3495 tstone@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3495","contributorId":242004,"corporation":false,"usgs":true,"family":"Stone","given":"Thomas","email":"tstone@usgs.gov","middleInitial":"C.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":800322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kieffer, Hugh H.","contributorId":41137,"corporation":false,"usgs":false,"family":"Kieffer","given":"Hugh","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":800323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lukashin, Constantine","contributorId":242007,"corporation":false,"usgs":false,"family":"Lukashin","given":"Constantine","email":"","affiliations":[{"id":48472,"text":"NASA Langley Reseach Center","active":true,"usgs":false}],"preferred":false,"id":800324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turpie, Kevin","contributorId":242008,"corporation":false,"usgs":false,"family":"Turpie","given":"Kevin","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":800325,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210506,"text":"ds1126 - 2020 - Rock strength properties of granitic rocks in Yosemite Valley, Yosemite National Park, California","interactions":[],"lastModifiedDate":"2020-06-08T11:26:04.891116","indexId":"ds1126","displayToPublicDate":"2020-06-05T10:02:01","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1126","displayTitle":"Rock Strength Properties of Granitic Rocks in Yosemite Valley, Yosemite National Park, California","title":"Rock strength properties of granitic rocks in Yosemite Valley, Yosemite National Park, California","docAbstract":"Yosemite National Park, located in the central part of California’s Sierra Nevada mountains, is a glacially carved landscape filled with iconic rock formations such as Cathedral Peak, El Capitan, and Half Dome. Igneous rocks, consisting primarily of variations of granite, granodiorite, and tonalite, make up the majority of the bedrock geology and their overall strength supports the spectacular cliffs and domes of Yosemite Valley that draw many visitors to the park. These same sheer cliffs also are the source areas for frequent rock falls, which, in addition to being the primary mechanism for cliff formation, can also pose a hazard to visitors and infrastructure located below. To obtain rock strength parameters for use in assessing rock-fall potential in Yosemite National Park, we conducted a comprehensive rock mechanics laboratory testing program on a set of granitic rocks that form many of the cliffs in Yosemite Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1126","collaboration":"Prepared in cooperation with the École Polytechnique Fédérale de Lausanne, National Park Service, and Université de Lausanne","usgsCitation":"Collins, B.D., Sandstrone, F., Gastaldo, L., Stock, G.M., and Jaboyedoff, M., 2020, Rock strength properties of granitic rocks in Yosemite Valley, Yosemite National Park, California: U.S. Geological Survey Data Series 1126, 158 p., https://doi.org/10.3133/ds1126.","productDescription":"vii, 158 p.","numberOfPages":"158","onlineOnly":"Y","ipdsId":"IP-113982","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":375394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1126/ds1126.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":375393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1126/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.90478515625,\n 37.74682893940135\n ],\n [\n -119.23873901367188,\n 37.74682893940135\n ],\n [\n -119.23873901367188,\n 38.01888587738773\n ],\n [\n -119.90478515625,\n 38.01888587738773\n ],\n [\n -119.90478515625,\n 37.74682893940135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
On the basis of lifetime cancer risks, lead-210 (210Pb) and polonium-210 (210Po) ≥ 1.0 and 0.7 pCi/L (picocuries per liter), respectively, in drinking-water supplies may pose human-health concerns. 210Pb and 210Po were detected at concentrations greater than these thresholds at 3.7 and 1.5%, respectively, of filtered untreated groundwater samples from 1263 public-supply wells in 19 principal aquifers across the United States. Nationally, 72% of samples with radon-222 (222Rn) concentrations > 4000 pCi/L had 210Pb ≥ 1.0 pCi/L. 210Pb is mobilized by alpha recoil associated with the decay of 222Rn and short-lived progeny. 210Pb concentrations ≥ 1.0 pCi/L occurred most frequently where acidic groundwaters inhibited 210Pb readsorption (felsic-crystalline rocks) and where reducing alkaline conditions favored dissolution of iron–manganese- (Fe–Mn-) oxyhydroxides (which adsorb 210Pb) and formation of lead–carbonate complexes (enhancing lead (Pb) mobility). 210Po concentrations ≥ 0.7 pCi/L occurred almost exclusively in confined Coastal Plain aquifers where old (low percent-modern carbon-14) groundwaters were reducing, with high pH (>7.5) and high sodium/chloride (Na/Cl) ratios resulting from cation exchange. In high-pH environments, aqueous polonium (Po) is poorly sorbed, occurring as dihydrogen polonate (H2PoO3(aq)) or, under strongly reducing conditions, as a hydrogen-polonide anion (HPo–). Fe–Mn- and sulfate-reduction and cation-exchange processes may mobilize polonium from mineral surfaces. Po2+ occurrence in low-to-neutral-pH waters is attenuated by adsorption.
Recreational fisheries have high economic worth, valued at US$190 billion globally. An important, but underappreciated, secondary value of recreational catch is its role as a source of food. This contribution is poorly understood due to difficulty in estimating recreational harvest at spatial scales beyond a single system, as traditionally estimated from individual creel surveys. Here, we address this gap using 28‐year creel surveys of ~300 Wisconsin inland lakes. We develop a statistical model of recreational harvest for individual lakes and then scale‐up to unsurveyed lakes (3,769 lakes; 73% of statewide lake surface area). We generate a statewide estimate of recreational lake harvest of ~4,200 metric tons and an estimated annual angler consumption rate of ~1.1 kg, nearly equal to the total estimated United States per capita freshwater fish consumption. An important ecosystem service, recreational harvest makes significant contributions to human diets and plays an often‐unheralded role in food security.
Prior to emergence as fry, salmonid embryos incubating within gravel nests called “redds” are vulnerable to substrate mobilization and lowering of the streambed, a process termed “streambed scour,” during floods. Water managers regulating discharge in salmonid-bearing rivers need information about the magnitude of discharge during which the scour of substrate surrounding salmonid redds occurs. The time when scour occurs, however, is difficult to measure and usually poorly constrained. The South Fork Tolt River in western Washington supplies the City of Seattle with hydroelectric power and about 40 percent of its municipal water needs, while providing spawning habitat for two salmonid species listed under the Endangered Species Act: Chinook salmon (Oncorhynchus tshawytscha) and steelhead trout (O. mykiss). The U.S. Geological Survey, in cooperation with Seattle City Light and Seattle Public Utilities, began a study in 2015 using accelerometer scour monitors (ASM) to characterize the timing of and hydrologic conditions associated with streambed scour at the depth of incubating salmonid embryos in the South Fork Tolt River. Prior to this study, operational thresholds for peak discharge on the South Fork Tolt River were 350 cubic feet per second (cfs) in the upper part of the river and 550 cfs in the lower part of the river as measured at USGS streamgages 12148000 and 12148300, respectively. These thresholds were developed from the peak discharge associated with observations of the flattening of redd structure and not from direct measurement of scour at the depth of egg pockets within redds. Accelerometer scour monitors were deployed at the level of salmonid egg pockets in spawning habitat of the South Fork Tolt River to record the temporal pattern of streambed scour at the depth of incubating salmon eggs during fall and winter flood seasons of water years (WY) 2016 and 2017. Thirteen of 48 ASMs deployed during the WY 2016 flood season recorded scour attributed to high streamflow when discharge measured at USGS streamgage 12148300 (the lower river streamgage used as an index gage) was between 969 and 1,360 cfs. Local discharge at individual scour sites varied depending on the timing of tributary inputs and downstream transport of water. During the subsequent flood season in WY 2017, peak discharge at the index gage reached 809 cfs. None of the 38 ASMs deployed recorded scour attributed to streamflow alone, although 10 ASMs recorded localized bed movement attributed to spawning activity of fish. Most scour at the depth of redds measured during WY 2016 occurred at or before peak flood discharge consistent with previous redd scour studies. The lack of scour measured in WY 2017 when peak discharge (809 cfs) was less than the minimum discharge when scour occurred in WY 2016 (969 cfs) suggests minimal to no scour of egg pockets in salmonid redds when discharge is less than 809 cfs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205044","collaboration":"Prepared in cooperation with Seattle City Light and Seattle Public Utilities","usgsCitation":"Gendaszek, A.S., Ablow, E., and Marks, D., 2020, Streambed scour of salmon (Oncorhynchus spp.) and steelhead (Oncorhynchus mykiss) redds in the South Fork Tolt River, King County, Washington: U.S. Geological Survey Scientific Investigations Report 2020–5044, 20 p., https://doi.org/10.3133/sir20205044.","productDescription":"iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-110809","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":375381,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5044/coverthb.jpg"},{"id":375382,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5044/sir20205044.pdf","text":"Report","size":"3 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Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Delimiting biodiversity units is difficult in organisms in which differentiation is obscured by hybridization, plasticity, and other factors that blur phenotypic boundaries. Such work is more complicated when the focal units are subspecies, the definition of which has not been broadly explored in the era of modern genetic methods. Eastwood manzanita (Arctostaphylos glandulosa Eastw.) is a widely distributed and morphologically complex chaparral shrub species with much subspecific variation, which has proven challenging to categorize. Currently 10 subspecies are recognized, however, many of them are not geographically segregated, and morphological intermediates are common. Subspecies delimitation is of particular importance in this species because two of the subspecies are rare. The goal of this study was to apply an evolutionary definition of “subspecies” to characterize structure within Eastwood manzanita.
We used publicly available geospatial environmental data and reduced‐representation genome sequencing to characterize environmental and genetic differentiation among subspecies. In addition, we tested whether subspecies could be differentiated by environmentally associated genetic variation.
Our analyses do not show genetic differentiation among subspecies of Eastwood manzanita, with the exception of one of the two rare subspecies. In addition, our environmental analyses did not show ecological differentiation, though limitations of the analysis prevent strong conclusions.
Genetic structure within Eastwood manzanita does not correspond to current subspecies circumscriptions, but rather reflects geographic distribution. Our study suggests that subspecies concepts need to be reconsidered in long‐lived plant species, especially in the age of next‐generation sequencing.
","language":"English","publisher":"Botanical Society of America","doi":"10.1002/ajb2.1496","usgsCitation":"Huang, Y., Morrison, G.R., Brelsford, A., Franklin, J., Jolles, D.D., Keeley, J., Parker, V., Saavedra, N., Sanders, A.C., Stoughton, T., Wahlert, G.A., and Litt, A., 2020, Subspecies differentiation in an enigmatic chaparral shrub species: American Journal of Botany, v. 107, no. 6, p. 923-940, https://doi.org/10.1002/ajb2.1496.","productDescription":"18 p.","startPage":"923","endPage":"940","ipdsId":"IP-115824","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":456496,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ajb2.1496","text":"Publisher Index Page"},{"id":375519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Yi","contributorId":225188,"corporation":false,"usgs":false,"family":"Huang","given":"Yi","email":"","affiliations":[{"id":41068,"text":"University of California, Riverside, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":790719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Glen R.","contributorId":225189,"corporation":false,"usgs":false,"family":"Morrison","given":"Glen","email":"","middleInitial":"R.","affiliations":[{"id":41068,"text":"University of California, Riverside, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":790720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brelsford, Alan","contributorId":225190,"corporation":false,"usgs":false,"family":"Brelsford","given":"Alan","email":"","affiliations":[{"id":41068,"text":"University of California, Riverside, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":790721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Franklin, Janet","contributorId":192373,"corporation":false,"usgs":false,"family":"Franklin","given":"Janet","affiliations":[],"preferred":false,"id":790722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jolles, Diana D","contributorId":225191,"corporation":false,"usgs":false,"family":"Jolles","given":"Diana","email":"","middleInitial":"D","affiliations":[{"id":41069,"text":"Plymouth State University, Plymouth, NH 03264","active":true,"usgs":false}],"preferred":false,"id":790723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keeley, Jon 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92521","active":true,"usgs":false}],"preferred":false,"id":790726,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanders, Andrew C","contributorId":225194,"corporation":false,"usgs":false,"family":"Sanders","given":"Andrew","email":"","middleInitial":"C","affiliations":[{"id":41068,"text":"University of California, Riverside, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":790727,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stoughton, Thomas","contributorId":225195,"corporation":false,"usgs":false,"family":"Stoughton","given":"Thomas","email":"","affiliations":[{"id":41069,"text":"Plymouth State University, Plymouth, NH 03264","active":true,"usgs":false}],"preferred":false,"id":790728,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wahlert, Gregory A.","contributorId":225196,"corporation":false,"usgs":false,"family":"Wahlert","given":"Gregory","email":"","middleInitial":"A.","affiliations":[{"id":41071,"text":"University of California, Santa Barbara, Santa Barbara, CA 93106","active":true,"usgs":false}],"preferred":false,"id":790729,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Litt, Amy","contributorId":225197,"corporation":false,"usgs":false,"family":"Litt","given":"Amy","email":"","affiliations":[{"id":41068,"text":"University of California, Riverside, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":790730,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70211578,"text":"70211578 - 2020 - Hyperpigmented melanistic skin lesions of smallmouth bass Micropterus dolomieu from the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2021-07-02T13:39:55.015334","indexId":"70211578","displayToPublicDate":"2020-06-04T09:14:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hyperpigmented melanistic skin lesions of smallmouth bass Micropterus dolomieu from the Chesapeake Bay watershed","title":"Hyperpigmented melanistic skin lesions of smallmouth bass Micropterus dolomieu from the Chesapeake Bay watershed","docAbstract":"Hyperpigmented melanistic skin lesions (HPMLs) of smallmouth bass Micropterus dolomieu are observed in the Potomac and Susquehanna rivers, Chesapeake Bay watershed, USA. Routine, nonlethal population surveys were conducted at 8 sites on the mainstem Susquehanna River and 9 on the Juniata River, a tributary of the Susquehanna River, between 2012 and 2018, and the prevalence of HPMLs was documented. A total of 4078 smallmouth bass were collected from the mainstem Susquehanna River and 6478 from the Juniata River. Lesions were primarily seen in bass greater than 200 mm, and prevalence in the Susquehanna River (8%) was higher (p < 0.001) than in the Juniata River (2%). As part of ongoing fish health monitoring projects, smallmouth bass were collected at additional sites, primarily tributaries of the Susquehanna (n = 758) and Potomac (n = 545) rivers between 2013 and 2018. Prevalence in the Susquehanna River (13%) was higher (p < 0.001) than the Potomac (3%). Microscopically, HPMLs were characterized by an increased number of melanocytes in the epidermis or within the dermis and epidermis. RNAseq analyses of normal and melanistic skin identified 3 unique sequences in HPMLs. Two were unidentified and the third was a viral helicase (E1). Transcript abundance in 16 normal skin samples and 16 HPMLs showed upregulation of genes associated with melanogenesis and cell proliferation in HPMLs. The E1 transcript was detected in 12 of the 16 melanistic areas but in no samples from normal skin. Further research will be necessary to identify the putative new virus and determine its role in melanocyte proliferation.
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Georgia","active":true,"usgs":false}],"preferred":false,"id":794679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Geoffrey D.","contributorId":224595,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey D.","affiliations":[{"id":40898,"text":"Pennsylvania Fish & Boat Commission","active":true,"usgs":false}],"preferred":false,"id":794680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sperry, Adam 0000-0002-4815-3730","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":203243,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 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(CECs) in tree swallows along an agricultural to industrial gradient: Maumee River, OH","docAbstract":"Exposure to multiple classes of contaminants, both legacy and contaminants of emerging concern (CECs), were assessed in tree swallow (Tachycineta bicolor) tissue and diet samples from 6 sites along the Maumee River, Ohio, USA, to understand both exposure and possible effects of exposure to those CECs for which there are little avian data. The 6 sites represented a gradient from intensive agriculture upstream to highly urbanized and industrial landscapes downstream; 1 or 2 remote Wisconsin lakes were assessed for comparative purposes. Cytochrome P450 induction, DNA damage, and thyroid function were also assessed relative to contaminant exposure. Bioaccumulative CECs, such as polybrominated diphenyl ethers (PBDEs) and perfluorinated substances, did not follow any upstream to downstream gradient; but both had significantly greater concentrations along the Maumee River than at the remote lake sites. Greater exposure to PBDEs was apparent in swallows at or near wastewater‐treatment facilities than at other sites. Total polychlorinated biphenyl and total polycyclic aromatic hydrocarbon concentrations were greater in swallows at downstream locations compared to upstream sites and were associated with higher ethoxyresorufin‐O‐dealkylase activity. Few herbicides or nonorganochlorine insecticides were detected in swallow tissues or their food, except for atrazine and its metabolite desethylatrazine. Few pharmaceuticals and personal care products were detected except for DEET and iopamidol. Both were detected in most liver samples but not in eggs, as well as detected at the remote lake sites. This is one of the most comprehensive assessments to date of exposure and effects of a wide variety of CECs in birds.
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