The Hayward fault in California's San Francisco Bay area produces large earthquakes, with the last occurring in 1868. We examine how physics‐based dynamic rupture modeling can be used to numerically simulate large earthquakes on not only the Hayward fault, but also its connected companions to the north and south, the Rodgers Creek and Calaveras faults. Equipped with a wealth of images of this fault system, including those of its 3D geology and 3D geometry, in addition to inferences about its interseismic creep‐rate pattern and rock‐friction behavior, we use a finite‐element computer code to perform 3D dynamic earthquake rupture simulations. We find that the rock properties affect the locations and amount of slip produced in our simulated large earthquakes. Crucial factors that control rupture behavior in our modeling are the earthquake nucleation locations, the fault geometry, and the data that reveal where the fault system is creeping or locked. Our findings suggest that large Rodgers Creek‐Hayward‐Calaveras‐Northern Calaveras (RC‐H‐C‐NC) fault‐system earthquakes may result from dynamic rupture that starts in a locked part of the fault system, but is then stopped by the creeping parts, leading to high‐magnitude‐6 earthquakes; or, from dynamic rupture that starts in a locked part of the fault system, then cascades through some of the creeping parts, leading to magnitude‐7 earthquakes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020577","usgsCitation":"Harris, R.A., Barall, M., Lockner, D.A., Moore, D.E., Ponce, D.A., Graymer, R., Funning, G.J., Morrow, C.A., Kyriakopoulos, C., and Eberhart-Phillips, D., 2021, A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek‐Hayward‐Calaveras Fault System, California: JGR Solid Earth, v. 126, e2020JB020577, 28 p., https://doi.org/10.1029/2020JB020577.","productDescription":"e2020JB020577, 28 p.","ipdsId":"IP-120122","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb020577","text":"Publisher Index Page"},{"id":384448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Andres Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.98095703125,\n 37.18657859524883\n ],\n [\n -121.77246093750001,\n 37.18657859524883\n ],\n [\n -121.77246093750001,\n 38.38472766885085\n ],\n [\n -122.98095703125,\n 38.38472766885085\n ],\n [\n -122.98095703125,\n 37.18657859524883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":812382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":198670,"corporation":false,"usgs":false,"family":"Barall","given":"Michael","affiliations":[],"preferred":false,"id":812383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":812384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Diane E. 0000-0002-8641-1075 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0000-0003-4910-5682","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":207816,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":812387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Funning, Gareth J. 0000-0002-8247-0545","orcid":"https://orcid.org/0000-0002-8247-0545","contributorId":172418,"corporation":false,"usgs":false,"family":"Funning","given":"Gareth","email":"","middleInitial":"J.","affiliations":[{"id":6984,"text":"UC Riverside","active":true,"usgs":false}],"preferred":false,"id":812388,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrow, Carolyn A. 0000-0003-3500-6181 cmorrow@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-6181","contributorId":3206,"corporation":false,"usgs":true,"family":"Morrow","given":"Carolyn","email":"cmorrow@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":812389,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kyriakopoulos, Christodoulos 0000-0001-9283-2282","orcid":"https://orcid.org/0000-0001-9283-2282","contributorId":255461,"corporation":false,"usgs":false,"family":"Kyriakopoulos","given":"Christodoulos","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":812390,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Eberhart-Phillips, Donna 0000-0003-0392-8659","orcid":"https://orcid.org/0000-0003-0392-8659","contributorId":190650,"corporation":false,"usgs":false,"family":"Eberhart-Phillips","given":"Donna","email":"","affiliations":[],"preferred":false,"id":812391,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237711,"text":"70237711 - 2021 - Assessing the feasibility of managed aquifer recharge in California","interactions":[],"lastModifiedDate":"2022-10-21T13:20:08.072357","indexId":"70237711","displayToPublicDate":"2021-01-16T06:40:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the feasibility of managed aquifer recharge in California","docAbstract":"With aquifers around the world stressed by over-extraction, water managers are increasingly turning to managed aquifer recharge (MAR), directly replenishing groundwater resources through injection wells, recharge basins, or other approaches. While there has been progress in understanding the geological and infrastructure-related considerations to make MAR more effective, critical evaluations of its institutional design and implementation are limited. This study assesses MAR projects, using a case study of projects proposed by groundwater sustainability agencies (GSAs) in California to comply with the state's Sustainable Groundwater Management Act of 2014; these projects will almost double the number of MAR projects in the United States. We draw on content analysis of groundwater sustainability plans that propose these projects. We first assess the types of recharge projects proposed and the stated aims of the projects, to assess when and why agencies are turning to MAR as a solution. We find that recharge basins are by far the most common approach, and that GSAs hope these basins will improve water table levels, reduce subsidence, and improve water quality. We then analyze potential barriers to project implementation and assess the projects' ability to achieve the stated goals. Primary concerns identified include a potential lack of available water, a potentially challenging legal framework, and minimal consideration of funding and cumulative land needs. To conclude, we discuss broader considerations for ensuring that MAR is an effective water management tool.
Coral reefs worldwide are experiencing rapid degradation in response to climate and land-use change, namely effects of warming sea-surface temperatures, contaminant runoff, and overfishing. Extensive coral bleaching caused by the steady rise of sea-surface temperatures is projected to increase, but our understanding and ability to predict where corals may be most resilient to this effect is limited owing to a lack of knowledge of nearshore habitat conditions and the role of compromised coral health in preconditioning bleaching vulnerability. On high islands and most atolls, fresh to brackish groundwater discharges to the coast through the beach face and seafloor, where it mixes with marine waters and commonly creates cool estuarine nearshore waters that are important to wildlife and ecosystem services that benefit people. Here, we summarize results of a study to evaluate the ecosystem services and effects of groundwater on coral reef health and the potential role of groundwater to maintain cold-water refugia that can buffer corals from thermal stress during temperature maxima. Across 75 kilometers of the west coastline of the Island of Hawaiʻi, paired time-series and discrete measurements of water quality, coral-community and colony size structures, and coral health indicators, including bleaching, at 33 stations grouped into 12 study areas were made from July 2010 to December 2013. The results show that nearshore water temperatures are depressed by groundwater across extensive areas of the nearshore. Persistent cold-water refugia ranging from 1 to 5 degrees Celsius below surrounding marine water temperatures are shown to be associated with identified groundwater inputs. Significant correlations were found between metrics of coral health and water temperature. Because areas of temperature refugia were notable along the west coast of the Island of Hawaiʻi and are identified by ecologists as increasingly important to valued wildlife, improved understanding of groundwater flux to the long-term resilience of coral reefs is likely important. In particular, evaluating the extent that the magnitude and timing of groundwater discharge across the nearshore mitigate thermal bleaching stress may help inform the fate of coral reefs projected to experience rising sea-surface temperatures worldwide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201128","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Grossman, E.E., Marrack, L., and vanArendonk, N.R., 2021, Nearshore water quality and coral health indicators along the west coast of the Island of Hawaiʻi, 2010–2014: U.S. Geological Survey Open-File Report 2020–1128, 45 p., https://doi.org/10.3133/ofr20201128.","productDescription":"Report: vii, 45 p.; Data Releases","numberOfPages":"45","onlineOnly":"Y","ipdsId":"IP-112588","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":382234,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X569K","linkHelpText":"Coral cover and health determined from seafloor photographs and diver observations, West Hawai'i, 2010-2011"},{"id":382235,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154FJQ","linkHelpText":"Nearshore water properties and estuary conditions along the coral reef coastline of west Hawaii Island (2010-2014)"},{"id":382232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1128/covrthb.jpg"},{"id":382233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1128/ofr20201128.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawaii, Kaloko-Honokōhau National Historical Park, Puʻuhonua O Hōnaunau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.05006217956543,\n 19.666513211037795\n ],\n [\n -156.01581573486328,\n 19.666513211037795\n ],\n [\n -156.01581573486328,\n 19.6935061404277\n ],\n [\n -156.05006217956543,\n 19.6935061404277\n ],\n [\n -156.05006217956543,\n 19.666513211037795\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.91865539550778,\n 19.406980567050198\n ],\n [\n -155.90157508850095,\n 19.406980567050198\n ],\n [\n -155.90157508850095,\n 19.42357528523296\n ],\n [\n -155.91865539550778,\n 19.42357528523296\n ],\n [\n -155.91865539550778,\n 19.406980567050198\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
The recovery of large carnivore species from over‐exploitation can have socioecological effects; thus, reliable estimates of potential abundance and distribution represent a valuable tool for developing management objectives and recovery criteria. For sea otters (Enhydra lutris), as with many apex predators, equilibrium abundance is not constant across space but rather varies as a function of local habitat quality and resource dynamics, thereby complicating the extrapolation of carrying capacity (K) from one location to another. To overcome this challenge, we developed a state‐space model of density‐dependent population dynamics in southern sea otters (E. l. nereis), in which K is estimated as a continuously varying function of a suite of physical, biotic, and oceanographic variables, all described at fine spatial scales. We used a theta‐logistic process model that included environmental stochasticity and allowed for density‐independent mortality associated with shark bites. We used Bayesian methods to fit the model to time series of survey data, augmented by auxiliary data on cause of death in stranded otters. Our model results showed that the expected density at K for a given area can be predicted based on local bathymetry (depth and distance from shore), benthic substrate composition (rocky vs. soft sediments), presence of kelp canopy, net primary productivity, and whether or not the area is inside an estuary. In addition to density‐dependent reductions in growth, increased levels of shark‐bite mortality over the last decade have also acted to limit population expansion. We used the functional relationships between habitat variables and equilibrium density to project estimated values of K for the entire historical range of southern sea otters in California, USA, accounting for spatial variation in habitat quality. Our results suggest that California could eventually support 17,226 otters (95% CrI = 9,739–30,087). We also used the fitted model to compute candidate values of optimal sustainable population abundance (OSP) for all of California and for regions within California. We employed a simulation‐based approach to determine the abundance associated with the maximum net productivity level (MNPL) and propose that the upper quartile of the distribution of MNPL estimates (accounting for parameter uncertainty) represents an appropriate threshold value for OSP. Based on this analysis, we suggest a candidate value for OSP (for all of California) of 10,236, which represents 59.4% of projected K.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21985","usgsCitation":"Tinker, M., Yee, J.L., Laidre, K.L., Hatfield, B.B., Harris, M.D., Tomoleoni, J.A., Bell, T.W., Saarman, E., Carswell, L., and Miles, A.K., 2021, Habitat features predict carrying capacity of a recovering marine carnivore: Journal of Wildlife Management, v. 85, no. 2, p. 303-323, https://doi.org/10.1002/jwmg.21985.","productDescription":"21 p.","startPage":"303","endPage":"323","ipdsId":"IP-122195","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21985","text":"Publisher Index Page"},{"id":382279,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.27880859375001,\n 33.815666308702774\n ],\n [\n -118.740234375,\n 34.125447565116126\n ],\n [\n -119.091796875,\n 34.23451236236987\n ],\n [\n -119.61914062499999,\n 34.50655662164561\n ],\n [\n -120.36621093749999,\n 34.56085936708384\n ],\n [\n -120.69580078125001,\n 35.31736632923788\n ],\n [\n -121.728515625,\n 36.474306755095235\n ],\n [\n -121.70654296874999,\n 36.94989178681327\n ],\n [\n -122.34374999999999,\n 37.43997405227057\n ],\n [\n -121.75048828124999,\n 37.54457732085582\n ],\n [\n -121.97021484374999,\n 37.96152331396614\n ],\n [\n -120.7177734375,\n 38.03078569382294\n ],\n [\n -121.28906250000001,\n 38.39333888832238\n ],\n [\n -122.58544921875,\n 38.238180119798635\n ],\n [\n -123.06884765625,\n 38.08268954483802\n ],\n [\n -122.82714843749999,\n 37.666429212090605\n ],\n [\n -122.54150390625,\n 37.125286284966805\n ],\n [\n -122.01416015625,\n 36.77409249464195\n ],\n [\n -122.1240234375,\n 36.43896124085945\n ],\n [\n -121.33300781249999,\n 35.51434313431818\n ],\n [\n -120.87158203125,\n 34.88593094075317\n ],\n [\n -120.78369140624999,\n 34.470335121217474\n ],\n [\n -120.12451171875,\n 33.687781758439364\n ],\n [\n -118.27880859375001,\n 33.815666308702774\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":207839,"corporation":false,"usgs":true,"family":"Tinker","given":"M. Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":808385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laidre, Kristin L.","contributorId":191798,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Brian B. 0000-0003-1432-2660 brian_hatfield@usgs.gov","orcid":"https://orcid.org/0000-0003-1432-2660","contributorId":147917,"corporation":false,"usgs":true,"family":"Hatfield","given":"Brian","email":"brian_hatfield@usgs.gov","middleInitial":"B.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Michael D.","contributorId":127460,"corporation":false,"usgs":false,"family":"Harris","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":808389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, Tom W.","contributorId":149016,"corporation":false,"usgs":false,"family":"Bell","given":"Tom","email":"","middleInitial":"W.","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":808391,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saarman, Emily","contributorId":247807,"corporation":false,"usgs":false,"family":"Saarman","given":"Emily","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":808392,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carswell, Lilian P.","contributorId":221789,"corporation":false,"usgs":false,"family":"Carswell","given":"Lilian P.","affiliations":[{"id":40429,"text":"USFWS - Ventura FWO","active":true,"usgs":false}],"preferred":false,"id":808393,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808394,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70227447,"text":"70227447 - 2021 - Movements of marine and estuarine turtles during Hurricane Michael","interactions":[],"lastModifiedDate":"2022-01-17T16:16:36.898138","indexId":"70227447","displayToPublicDate":"2021-01-15T10:08:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Movements of marine and estuarine turtles during Hurricane Michael","docAbstract":"Natural disturbances are an important driver of population dynamics. Because it is difficult to observe wildlife during these events, our understanding of the strategies that species use to survive these disturbances is limited. On October 10, 2018, Hurricane Michael made landfall on Florida’s northwest coast. Using satellite and acoustic telemetry, we documented movements of 6 individual turtles: one loggerhead sea turtle, one Kemp’s ridley sea turtle, three green sea turtles and one diamondback terrapin, in a coastal bay located less than 30 km from hurricane landfall. Post-storm survival was confirmed for all but the Kemp’s ridley; the final condition of that individual remains unknown. No obvious movements were observed for the remaining turtles however the loggerhead used a larger home range in the week after the storm. This study highlights the resiliency of turtles in response to extreme weather conditions. However, long-term impacts to these species from habitat changes post-hurricane are unknown.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-021-81234-3","usgsCitation":"Lamont, M.M., Johnson, D., and Catizone, D.J., 2021, Movements of marine and estuarine turtles during Hurricane Michael: Scientific Reports, v. 11, p. 1-11, https://doi.org/10.1038/s41598-021-81234-3.","productDescription":"1577, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-118507","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-81234-3","text":"Publisher Index Page"},{"id":394437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.42822265625,\n 18.083200903334312\n ],\n [\n -80.88134765625,\n 18.083200903334312\n ],\n [\n -80.88134765625,\n 30.751277776257812\n ],\n [\n -91.42822265625,\n 30.751277776257812\n ],\n [\n -91.42822265625,\n 18.083200903334312\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227769,"text":"70227769 - 2021 - Using grazing to manage herbaceous structure for a heterogeneity-dependent bird","interactions":[],"lastModifiedDate":"2022-01-31T15:19:36.502867","indexId":"70227769","displayToPublicDate":"2021-01-15T09:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Using grazing to manage herbaceous structure for a heterogeneity-dependent bird","docAbstract":"Grazing management recommendations often sacrifice the intrinsic heterogeneity of grasslands by prescribing uniform grazing distributions through smaller pastures, increased stocking densities, and reduced grazing periods. The lack of patch-burn grazing in semi-arid landscapes of the western Great Plains in North America requires alternative grazing management strategies to create and maintain heterogeneity of habitat structure (e.g., animal unit distribution, pasture configuration), but knowledge of their effects on grassland fauna is limited. The lesser prairie-chicken (Tympanuchus pallidicinctus), an imperiled, grassland-obligate, native to the southern Great Plains, is an excellent candidate for investigating effects of heterogeneity-based grazing management strategies because it requires diverse microhabitats among life-history stages in a semi-arid landscape. We evaluated influences of heterogeneity-based grazing management strategies on vegetation structure, habitat selection, and nest and adult survival of lesser prairie-chickens in western Kansas, USA. We captured and monitored 116 female lesser prairie-chickens marked with very high frequency (VHF) or global positioning system (GPS) transmitters and collected landscape-scale vegetation and grazing data during 2013–2015. Vegetation structure heterogeneity increased at stocking densities ≤0.26 animal units/ha, where use by nonbreeding female lesser prairie-chickens also increased. Probability of use for nonbreeding lesser prairie-chickens peaked at values of cattle forage use values near 37% and steadily decreased with use ≥40%. Probability of use was positively affected by increasing pasture area. A quadratic relationship existed between growing season deferment and probability of use. We found that 70% of nests were located in grazing units in which grazing pressure was <0.8 animal unit months/ha. Daily nest survival was negatively correlated with grazing pressure. We found no relationship between adult survival and grazing management strategies. Conservation in grasslands expressing flora community composition appropriate for lesser prairie-chickens can maintain appropriate habitat structure heterogeneity through the use of low to moderate stocking densities (<0.26 animal units/ha), greater pasture areas, and site-appropriate deferment periods. Alternative grazing management strategies (e.g., rest-rotation, season-long rest) may be appropriate in grasslands requiring greater heterogeneity or during intensive drought. Grazing management favoring habitat heterogeneity instead of uniform grazing distributions will likely be more conducive for preserving lesser prairie-chicken populations and grassland biodiversity.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.21984","usgsCitation":"Kraft, J.D., Haukos, D.A., Bain, M.R., Rice, M.B., Robinson, S., Sullins, D.S., Hagen, C., Pitman, J., Lautenbach, J., Plumb, R., and Lautenbach, J., 2021, Using grazing to manage herbaceous structure for a heterogeneity-dependent bird: Journal of Wildlife Management, v. 85, no. 2, p. 354-368, https://doi.org/10.1002/jwmg.21984.","productDescription":"15 p.","startPage":"354","endPage":"368","ipdsId":"IP-092108","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jwmg.21984","text":"External Repository"},{"id":395138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.953125,\n 37.01132594307015\n ],\n [\n -98.382568359375,\n 37.01132594307015\n ],\n [\n -98.382568359375,\n 39.29179704377487\n ],\n [\n -101.953125,\n 39.29179704377487\n ],\n [\n -101.953125,\n 37.01132594307015\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraft, John D.","contributorId":172789,"corporation":false,"usgs":false,"family":"Kraft","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bain, Matthew R.","contributorId":272571,"corporation":false,"usgs":false,"family":"Bain","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":832157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Samantha","contributorId":272573,"corporation":false,"usgs":false,"family":"Robinson","given":"Samantha","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullins, Dan S.","contributorId":272574,"corporation":false,"usgs":false,"family":"Sullins","given":"Dan","email":"","middleInitial":"S.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hagen, Christian A.","contributorId":272575,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":832161,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pitman, James","contributorId":176512,"corporation":false,"usgs":false,"family":"Pitman","given":"James","affiliations":[],"preferred":false,"id":832162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lautenbach, Joseph","contributorId":272577,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Joseph","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832163,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Plumb, Reid","contributorId":272578,"corporation":false,"usgs":false,"family":"Plumb","given":"Reid","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832164,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lautenbach, Jonathan","contributorId":272579,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Jonathan","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832165,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70217305,"text":"70217305 - 2021 - Seed production patterns of surviving Sierra Nevada conifers show minimal change following drought","interactions":[],"lastModifiedDate":"2021-01-18T13:39:10.353799","indexId":"70217305","displayToPublicDate":"2021-01-15T07:37:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Seed production patterns of surviving Sierra Nevada conifers show minimal change following drought","docAbstract":"Reproduction is a key component of ecological resilience in forest ecosystems, so understanding how seed production is influenced by extreme drought is key to understanding forest recovery trajectories. If trees respond to mortality-inducing drought by preferentially allocating resources for reproduction, the recovery of the stand to pre-drought conditions may be enhanced accordingly. We used a 20-year annual seed capture data set to investigate whether seed production by three tree genera commonly found in the Sierra Nevada (Abies, Pinus, and Calocedrus) was correlated with variation in local weather, which included an extreme drought spanning multiple years. We tested whether average seed production differed during the drought years, and whether annual seed counts could be explained by three weather variables: spring temperature, annual precipitation, and summer climatic water deficit (CWD). We fit models testing for four separate effects: (1) a priming year model (weather 1 year prior to reproductive bud initiation), (2) a bud initiation model (weather in the year of reproductive bud initiation), (3) a pollination year model (weather in the year of pollination), and (4) maturation year model (weather in the year of seed maturation). For genera with two-year reproductive cycles, the pollination and maturation models were combined. We found support for the summer CWD Abies maturation year model, which suggested higher seed outputs immediately following dry summer conditions. The spring temperature pollination year model was selected for Pinus, which suggested that seed output is higher following warm spring weather during pollination. The annual precipitation priming year model was selected for Calocedrus, which showed a negative association between seed production and wetter conditions two years prior to seed production. More parent tree basal area resulted in higher seed output for all genera, though the confidence intervals overlapped 0 for Calocedrus. Permutation tests sugested there was no systematic difference in mean seed production during the drought after accounting for live tree basal area, regardless of genus. These results highlight the variability in response across genera, and suggest that the influence of seed production on forest recovery following drought-related mortality may depend on affected species and the timing of the mortality event within the masting cycle. A greater understanding of species-level masting to drought stress is needed to more precisely predict community-level recovery following drought.
Understanding the carbon transport within aquatic environments is crucial to quantifying global and local carbon budgets, yet limited empirical data currently (2021) exist. This report documents methodology and provides data for quantifying the aquatic export of carbon from a cypress swamp within Big Cypress National Preserve and is part of a larger carbon budget study. The U.S. Geological Survey operated two continuous monitoring stations, 022889001 and 022909471, that measured flow volume and water quality within the Big Cypress National Preserve in South Florida from September 2015 to October 2017. Station 022889001 represented the flow into the study area and station 022909471 represented the flow out of the study area. Site-specific regression models were developed by using continuously measured specific conductance and concomitant, discretely collected dissolved organic carbon, dissolved inorganic carbon, and particulate carbon samples to calculate total carbon (TC) concentrations at 15-minute intervals.
Calculated TC concentrations typically increased as flow was decreasing and decreased as flow was increasing. TC loads were calculated by multiplying concentrations and flow volume, and the difference between the load calculations for input/output locations of the swamp flow system was used to determine the aquatic carbon export from the study area.
Calculated monthly TC loads ranged from 0 metric tons in spring 2017 at both stations to 3,145 and 7,821 metric tons in September 2017 at 022889001 and 022909471, respectively. During 2016, the annual loads were 10,479 and 15,243 metric tons at 022889001 and 022909471, respectively. Calculated monthly aquatic TC exports from the study area ranged from −0.7 gram of carbon per square meter in May 2016 to 44.1 grams of carbon per square meter during September 2017. The carbon export from the study area varied monthly, increased as flow increased, and was greatly influenced by Hurricane Irma in September 2017. The aquatic TC export from the Sweetwater Strand study area was 42.0 grams of carbon per square meter per year in 2016, which is substantially (about 15 times) larger than the estimated overall mean riverine carbon export per square meter for the eastern United States; however, it was also less than the monthly export of carbon in September 2017. The monthly aquatic carbon export from the study area in September 2017 alone was greater than the aquatic carbon export from all of 2016, which is largely the result of the substantial increase in flow attributed to Hurricane Irma.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201136","collaboration":"Greater Everglades Priority Ecosystem Science Program","usgsCitation":"Booth, A.C., 2021, Development and application of surrogate models, calculated loads, and aquatic export of carbon based on specific conductance, Big Cypress National Preserve, South Florida, 2015–17: U.S. Geological Survey Open-File Report 2020–1136, 14 p., https://doi.org/10.3133/ofr20201136.","productDescription":"Report: v, 14 p.; Data Release; 2 Appendixes","onlineOnly":"Y","ipdsId":"IP-112929","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":382104,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.rtf","text":"Appendix 2","size":"960 kB","description":"OFR 2020-1136 Appendix 2 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida (rtf file)"},{"id":382062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1136/coverthb.jpg"},{"id":382063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1136/ofr20201136.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136"},{"id":382064,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EXZLJT","text":"USGS data release","linkHelpText":"Calculated carbon concentrations, loads, and export in Big Cypress National Preserve, South Florida, 2015-2017"},{"id":382101,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.pdf","text":"Appendix 1","size":"424 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 1 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida"},{"id":382102,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.pdf","text":"Appendix 2","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 2 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida"},{"id":382103,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.rtf","text":"Appendix 1","size":"2.91 MB","description":"OFR 2020-1136 Appendix 1 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida (rtf file)"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.22604370117186,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 25.812254545273433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Although Arctic ringed seals Phoca hispida hispida are currently abundant and broadly distributed, their numbers are projected to decline substantially by the year 2100 due to climate warming. While understanding population structure could provide insight into the impact of environmental changes on this subspecies, detecting demographically important levels of exchange can be difficult in taxa with high abundance. We used a next-generation sequencing approach (DArTseq) to genotype ~5700 single nucleotide polymorphisms in 79 seals from 4 Pacific Arctic regions. Comparison of the 2 most geographically separated strata (eastern Bering vs. northeastern Chukchi-Beaufort Seas) revealed a statistically significant level of genetic differentiation (FST = 0.001, p = 0.005) that, while small, was 1 to 2 orders of magnitude greater than expected based on divergence estimated for similarly sized populations connected by low (1% yr-1) dispersal. A relatively high proportion (72 to 88%) of individuals within these strata could be genetically assigned to their stratum of origin. These results indicate that demographically important structure may be present among Arctic ringed seals breeding in different areas, increasing the risk that declines in the number of seals breeding in areas most negatively affected by environmental warming could occur.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01087","usgsCitation":"Lang, A.R., Boveng, P.L., Quakenbush, L., Robertson, K., Lauf, M., Rode, K.D., Ziel, H., and Taylor, B., 2021, Re-examination of population structure in Arctic ringed seals using DArTseq genotyping: Endangered Species Research, v. 44, p. 11-31, https://doi.org/10.3354/esr01087.","productDescription":"21 p.","startPage":"11","endPage":"31","ipdsId":"IP-104727","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453844,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01087","text":"Publisher Index Page"},{"id":382277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": 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]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, Aimee R.","contributorId":247810,"corporation":false,"usgs":false,"family":"Lang","given":"Aimee","email":"","middleInitial":"R.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boveng, Peter L.","contributorId":171523,"corporation":false,"usgs":false,"family":"Boveng","given":"Peter","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quakenbush, L.","contributorId":243091,"corporation":false,"usgs":false,"family":"Quakenbush","given":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":808402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, K.","contributorId":247811,"corporation":false,"usgs":false,"family":"Robertson","given":"K.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lauf, M.","contributorId":247812,"corporation":false,"usgs":false,"family":"Lauf","given":"M.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":808405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ziel, H.","contributorId":247813,"corporation":false,"usgs":false,"family":"Ziel","given":"H.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Taylor, B .L.","contributorId":181914,"corporation":false,"usgs":false,"family":"Taylor","given":"B .L.","affiliations":[],"preferred":false,"id":808407,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218755,"text":"70218755 - 2021 - The weight of cities: Urbanization effects on Earth’s subsurface","interactions":[],"lastModifiedDate":"2021-03-12T14:56:28.755208","indexId":"70218755","displayToPublicDate":"2021-01-14T08:55:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"The weight of cities: Urbanization effects on Earth’s subsurface","docAbstract":"Across the world, people increasingly choose to live in cities. By 2050, 70% of Earth's population will live in large urban areas. Upon considering a large city, questions arise such as, how much does that weigh? What are its effects on the landscape? Does it cause measurable subsidence? Here I calculate the weight of San Francisco Bay region urbanization, where 7.75 million people live at, or near the coast. It is difficult to account for everything that is in a city. I assume that most of the weight is buildings and their contents, which allows the use of base outline and height data to approximate their mass, which is cumulatively 1.6·1012 kg. I build a series of finite element models to study effects of pressure exerted by the weight distribution. Within the elastic realm, I look at compression, flexure, isostatic compensation, stress change, dilatation, and fluid flow changes. Within the nonlinear realm I show example calculations of primary and secondary settlement of soils under load. The combined modeled subsidence from building loads is at least 5–80 mm, with the largest contributions coming from nonlinear settlement and creep in soils. A general result is closing of pore space and redirection of pore fluids. While the calculated subsidence of the Bay Area is relatively small compared with other sources of elevation change such as pumping and recharge of aquifers, all sources of subsidence are concerning given an expected 200–300 mm sea level rise at San Francisco by the year 2050.
Water-quality effects after remediating abandoned draining mine tunnels using structural bulkheads were examined in two study areas in Colorado, USA. A bulkhead was installed in the Dinero mine tunnel in 2009 to improve water quality in Lake Fork Creek, a tributary to the upper Arkansas River. Although bulkhead installation improved pH, and manganese and zinc concentrations and loads at the Dinero mine tunnel, water-quality degradation was observed at the nearby Nelson tunnel. Only manganese concentrations improved in Lake Fork Creek downstream from the tunnel. To improve water quality in Cement Creek, a tributary of the Animas River, multiple bulkheads were installed in mine tunnels during 1996–2003 and a water treatment plant operated from 1989 to 2003 to treat drainage from several draining tunnels. After bulkhead installation and cessation of active water treatment (about 2003), water quality (pH and dissolved copper, manganese, and zinc concentrations) degraded at the mouth of Cement Creek. The patterns and timing were similar to post-bulkhead increased discharge and trace-metal loads at non-bulkheaded tunnels indicating the bulkheads might have been the cause. Pre-1989 water-quality data for Cement Creek are scarce, although limited historical data indicate possible, slight improvement in only manganese concentrations after bulkhead installation. Increased zinc loads in Lake Fork Creek and decreased pH through time in Cement Creek may indicate increased groundwater discharge to the streams after bulkhead installation. In these two study areas, bulkheads did not substantially improve downstream water quality.
The Bureau of Land Management (BLM) requested assistance from the U.S. Geological Survey (USGS) to conduct an assessment study to identify areas that may have economic potential for the future extraction of lignite and leonardite resources in the Williston Basin in North Dakota. The study will be used by the BLM to assist with the preparation of a revised resource management plan for the Williston Basin, in accordance with BLM planning policies.
The assessment of the economic potential of lignite resources required the establishment of criteria defining an economic lignite deposit. In consultation with the BLM, criteria were established to delineate drill holes that contained economic lignite beds. The criteria established are a minimum lignite bed thickness, a minimum cumulative lignite thickness, a maximum cumulative stripping ratio, and a maximum overburden. Likewise, an assessment of the economic potential of leonardite deposits required the establishment of criteria delineating drill holes that contained economic leonardite deposits. The criteria established are a minimum leonardite bed thickness, a minimum cumulative leonardite thickness, and a maximum overburden.
The drill hole data utilized in this study were obtained from the National Coal Resources Data System database and from several coal companies. Data from more than 20,000 drill holes, both proprietary and nonproprietary, were used to compile areas of economic potential for lignite or leonardite.
Areas delineated as having lignite or leonardite resources with economic potential, based on the established criteria, were present in 24 counties in the western portion of North Dakota. Areas of economic potential were delineated using a visual best-fit method without croplines. Areas defined as having economic potential for certain lignite beds or leonardite deposits may extend beyond known croplines in this study.
Stratigraphically, the lignite and leonardite deposits in the Williston Basin in North Dakota are mostly found in the Paleocene Fort Union Formation. Thick (greater than 20 feet) and laterally extensive (greater than 5 square miles) lignite beds are present in the Fort Union Formation throughout the Sentinel Butte and Tongue River Members. Lignite beds are also present in the Ludlow Member of the Fort Union Formation, although they are not as numerous or thick as they are in the overlying Sentinel Butte and Tongue River Members. As a result of lateral facies changes and migrating fluvial channel complexes in the Fort Union Formation, lignite beds of varying thickness occupy different stratigraphic horizons vertically throughout the Williston Basin.
The calculation of volumes for lignite and leonardite resources was not part of the scope of this study requested by the BLM, but a future study by the USGS may involve a comprehensive assessment of lignite resources and reserves in the Williston Basin. This future study could combine geologic data compiled in this study with geologic data from a previously unpublished 2019 assessment study by the USGS in the Williston Basin in eastern Montana. This future USGS study could also include the calculation of volumes for lignite resources and reserves, based on economic models derived using analogs from active mining operations in the Williston Basin and available spot market or contract coal prices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201135","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shaffer, B.N., 2021, An assessment of the economic potential of lignite and leonardite resources in the Williston Basin, North Dakota: U.S. Geological Survey Open-File Report 2020–1135, 14 p., https://doi.org/10.3133/ofr20201135.","productDescription":"vi, 14 p.","onlineOnly":"Y","ipdsId":"IP-120360","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":436582,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436581,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436580,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436579,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436578,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436577,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436576,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436575,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FHHH4T","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Dunn County, North Dakota"},{"id":382138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1135/coverthb.jpg"},{"id":382139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1135/ofr20201135.pdf","text":"Report","size":"6.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1135"}],"country":"United States","state":"North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 45.89000815866184\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Quantitative reconstructions of vegetation abundance from sediment-derived pollen systems provide unique insights into past ecological conditions. Recently, the use of pollen accumulation rates (PAR, grains cm−2 year−1) has shown promise as a bioproxy for plant abundance. However, successfully reconstructing region-specific vegetation dynamics using PAR requires that accurate assessments of pollen deposition processes be quantitatively linked to spatially-explicit measures of plant abundance. Our study addressed these methodological challenges. Modern PAR and vegetation data were obtained from seven lakes in the western Klamath Mountains, California. To determine how to best calibrate our PAR-biomass model, we first calculated the spatial area of vegetation where vegetation composition and patterning is recorded by changes in the pollen signal using two metrics. These metrics were an assemblage-level relevant source area of pollen (aRSAP) derived from extended R-value analysis (sensu Sugita, 1993) and a taxon-specific relevant source area of pollen (tRSAP) derived from PAR regression (sensu Jackson, 1990). To the best of our knowledge, aRSAP and tRSAP have not been directly compared. We found that the tRSAP estimated a smaller area for some taxa (e.g. a circular area with a 225 m radius for Pinus) than the aRSAP (a circular area with a 625 m radius). We fit linear models to relate PAR values from modern lake sediments with empirical, distance-weighted estimates of aboveground live biomass (AGLdw) for both the aRSAP and tRSAP distances. In both cases, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and TCT (Taxodiaceae, Cupressaceae, and Taxaceae families) – were statistically significant and reasonably precise estimators of contemporary AGLdw. However, predictions weighted by the distance defined by aRSAP tended to be more precise. The relative root-mean squared error for the aRSAP biomass estimates was 9% compared to 12% for tRSAP. Our results demonstrate that calibrated PAR-biomass relationships provide a robust method to infer changes in past plant biomass.
","language":"English","publisher":"SAGE Publishing","doi":"10.1177/0959683620988038","usgsCitation":"Knight, C.A., Baskaran, M., Bunting, M.J., Champagne, M.R., Potts, M.D., Wahl, D., Wanket, J., and Battles, J.J., 2021, Linking modern pollen accumulation rates to biomass: Quantitative vegetation reconstruction in the western Klamath Mountains, NW California, USA: The Holocene, v. 31, no. 5, p. 814-829, https://doi.org/10.1177/0959683620988038.","productDescription":"16 p.","startPage":"814","endPage":"829","ipdsId":"IP-122720","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":453850,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hull-repository.worktribe.com/output/3679635","text":"External Repository"},{"id":382454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Western Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.365234375,\n 40.052847601823984\n ],\n [\n -121.4208984375,\n 40.052847601823984\n ],\n [\n -121.4208984375,\n 42.220381783720605\n ],\n [\n -124.365234375,\n 42.220381783720605\n ],\n [\n -124.365234375,\n 40.052847601823984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Clarke A. 0000-0003-0002-6959","orcid":"https://orcid.org/0000-0003-0002-6959","contributorId":248212,"corporation":false,"usgs":false,"family":"Knight","given":"Clarke","email":"","middleInitial":"A.","affiliations":[{"id":49825,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California 94720 USA","active":true,"usgs":false}],"preferred":false,"id":808617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baskaran, Mark","contributorId":87867,"corporation":false,"usgs":false,"family":"Baskaran","given":"Mark","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":808618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunting, M. Jane 0000-0002-3152-5745","orcid":"https://orcid.org/0000-0002-3152-5745","contributorId":248213,"corporation":false,"usgs":false,"family":"Bunting","given":"M.","email":"","middleInitial":"Jane","affiliations":[{"id":49826,"text":"Department of Geography, Geology and Environment, University of Hull, Cottingham Road, Hull, HU6 7RX UK","active":true,"usgs":false}],"preferred":false,"id":808619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champagne, Marie Rhondelle 0000-0001-8236-3910","orcid":"https://orcid.org/0000-0001-8236-3910","contributorId":248214,"corporation":false,"usgs":true,"family":"Champagne","given":"Marie","email":"","middleInitial":"Rhondelle","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potts, Matthew D. 0000-0001-7442-3944","orcid":"https://orcid.org/0000-0001-7442-3944","contributorId":248215,"corporation":false,"usgs":false,"family":"Potts","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":49825,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California 94720 USA","active":true,"usgs":false}],"preferred":false,"id":808621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wanket, James","contributorId":248216,"corporation":false,"usgs":false,"family":"Wanket","given":"James","email":"","affiliations":[{"id":49829,"text":"Department of Geography, California State University, Sacramento, Sacramento, California 95819 USA","active":true,"usgs":false}],"preferred":false,"id":808623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":808624,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217337,"text":"70217337 - 2021 - Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","interactions":[],"lastModifiedDate":"2021-02-04T14:31:23.035113","indexId":"70217337","displayToPublicDate":"2021-01-13T11:02:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","docAbstract":"This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b05835","usgsCitation":"Lombard, M.A., Daniel, J., Jeddy, Z., Hay, L., and Ayotte, J.D., 2021, Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States: Environmental Science & Technology, v. 55, no. 3, p. 1822-1831, https://doi.org/10.1021/acs.est.9b05835.","productDescription":"10 p.","startPage":"1822","endPage":"1831","ipdsId":"IP-109293","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":453853,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.9b05835","text":"Publisher Index Page"},{"id":436586,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TU0R2T","text":"USGS data release","linkHelpText":"Datasets for assessing the impact of drought on arsenic exposure from private domestic wells in the 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\"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":808395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Johnni","contributorId":247808,"corporation":false,"usgs":false,"family":"Daniel","given":"Johnni","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeddy, Zuha","contributorId":247809,"corporation":false,"usgs":false,"family":"Jeddy","given":"Zuha","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":808398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808399,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222946,"text":"70222946 - 2021 - B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","interactions":[],"lastModifiedDate":"2021-08-10T13:59:41.764808","indexId":"70222946","displayToPublicDate":"2021-01-13T08:57:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"displayTitle":"B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","title":"B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","docAbstract":"The earthquake magnitude-frequency distribution is characterized by the b-value, which describes the relative frequency of large versus small earthquakes. It has been suggested that changes in b-value after an earthquake can be used to discriminate whether that earthquake is part of a foreshock sequence or a more typical mainshock-aftershock sequence, with a decrease in b-value heralding a larger earthquake to come. However, the measurement of b-value during an active aftershock sequence is strongly biased by short-term incompleteness of the earthquake catalog and by data-windowing, and these biases have the same direction as the proposed signal. Here I develop a new estimator of the b-value that is insensitive to transient changes in catalog completeness and that does not require data windowing. The new estimator “b-positive” is based on the positive-only subset of the differences in magnitude between successive earthquakes, which are described by a double-exponential (Laplace) distribution with the same b-value as the magnitude distribution itself. The b-positive estimator greatly improves the robustness of continuous b-value measurements during active earthquake sequences, as well as in historical catalogs with unknown or variable completeness. The new estimator confirms some of the observations of Gulia and Wiemer (2019), although at a reduced level, showing a decrease and recovery of the b-value during several recent foreshock sequences that cannot be attributed simply to measurement bias. However, the unbiased b-value changes may be too subtle to use in a real-time earthquake alarm system.
Dense, vitric, dacitic pyroclasts (dacite lithics) from the 1991 preclimactic explosions of Mt. Pinatubo were analyzed for their vesicular and crystal textures and dissolved H2O and CO2 contents. Micron-scale heterogeneities in groundmass glass volatile contents (0.9 wt% differences in H2O within 500 μm) are observed and argue that parts of the dacite lithics equilibrated at different depths before finally being constructed. Greater vesicularities and larger and greater number densities of vesicles are observed in groundmass glass around phenocrysts compared to groundmass glass away from phenocrysts, similar to textures produced in experiments that sintered bimodal distributions of particles. Furthermore, increasingly greater proportions of stretched and distorted vesicles are observed in lithics from the later explosions, which parallels the increasingly shorter reposes between explosions. Finally, micron-sized crystal fragments are ubiquitous in groundmass glass of all dacite lithics. The textures, together with the variable volatile contents, lead us to propose a model that the dacite lithics formed by rapid and repetitive sintering of ash particles derived from a variety of depths on the conduit walls above the fragmentation level. We speculate that sintering of conduit material produced impermeable layers that retarded gas flow through the conduit, causing pressure to build until the cap failed and the next explosion occurred.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01427-y","usgsCitation":"Wang, Y., Gardner, J., and Hoblitt, R., 2021, Formation of dense pyroclasts by sintering of ash particles during the preclimactic eruptions of Mt. Pinatubo in 1991: Bulletin of Volcanology, v. 83, 6, 13 p., https://doi.org/10.1007/s00445-020-01427-y.","productDescription":"6, 13 p.","ipdsId":"IP-123722","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":401291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Philippines","otherGeospatial":"Mount Pinatubo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120.28038024902344,\n 15.101957550324563\n ],\n [\n 120.41015624999999,\n 15.101957550324563\n ],\n [\n 120.41015624999999,\n 15.208662610868245\n ],\n [\n 120.28038024902344,\n 15.208662610868245\n ],\n [\n 120.28038024902344,\n 15.101957550324563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yining","contributorId":292117,"corporation":false,"usgs":false,"family":"Wang","given":"Yining","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":843815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, James E.","contributorId":292118,"corporation":false,"usgs":false,"family":"Gardner","given":"James E.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":843816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoblitt, Richard P. 0000-0001-5850-4760","orcid":"https://orcid.org/0000-0001-5850-4760","contributorId":292119,"corporation":false,"usgs":false,"family":"Hoblitt","given":"Richard P.","affiliations":[{"id":62834,"text":"USGS Volcano Science Center","active":true,"usgs":false}],"preferred":false,"id":843817,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217248,"text":"70217248 - 2021 - Monitoring wetland water quality related to livestock grazing in amphibian habitats","interactions":[],"lastModifiedDate":"2021-01-14T13:15:40.588803","indexId":"70217248","displayToPublicDate":"2021-01-13T07:09:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring wetland water quality related to livestock grazing in amphibian habitats","docAbstract":"Land use alteration such as livestock grazing can affect water quality in habitats of at-risk wildlife species. Data from managed wetlands are needed to understand levels of exposure for aquatic life stages and monitor grazing-related changes afield. We quantified spatial and temporal variation in water quality in wetlands occupied by threatened Oregon spotted frog (Rana pretiosa) at Klamath Marsh National Wildlife Refuge in Oregon, United States (US). We used analyses for censored data to evaluate the importance of habitat type and grazing history in predicting concentrations of nutrients, turbidity, fecal indicator bacteria (FIB; total coliforms, Escherichia coli (E. coli), and enterococci), and estrogenicity, an indicator of estrogenic activity. Nutrients (orthophosphate and ammonia) and enterococci varied over time and space, while E. coli, total coliforms, turbidity, and estrogenicity were more strongly associated with local livestock grazing metrics. Turbidity was correlated with several grazing-related constituents and may be particularly useful for monitoring water quality in landscapes with livestock use. Concentrations of orthophosphate and estrogenicity were elevated at several sites relative to published health benchmarks, and their potential effects on Rana pretiosa warrant further investigation. Our data provided an initial assessment of potential exposure of amphibians to grazing-related constituents in western US wetlands. Increased monitoring of surface water quality and amphibian population status in combination with controlled laboratory toxicity studies could help inform future research and targeted management strategies for wetlands with both grazing and amphibians of conservation concern.
The 2020 Magna, Utah, earthquake produced observable crustal deformation over a ∼ 100 km2 area around the southeast margin of Great Salt Lake, but it did not produce any surface rupture. To obtain a detailed picture of the fault slip, we combine strong motion seismic waveforms with GPS static offsets and Interferometric Synthetic Aperture Radar (InSAR) observations to obtain kinematic and static slip models of the event. We sample the regional seismic wavefield with 3-component records from 68 stations of the University of Utah Seismograph Stations network. We find that coseismic slip and afterslip, with predominantly normal slip, distributed on a shallowly west-dipping plane, possibly augmented by afterslip on a steeply northeast-dipping plane, best fits the joint dataset. The west-dipping plane locates near previously inferred sources of interseismic creep at depth. Hence the earthquake may have occurred on the downdip ex-tension of the Wasatch fault and activated further slip (afterslip) at shallow depth east of the hypocenter. This inferred afterslip may have driven the vigorous aftershock activity that was concentrated east of the hypocenter.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0220200312","usgsCitation":"Pollitz, F., Wicks, C., and Svarc, J.L., 2021, Coseismic fault slip and afterslip associated with the M5.7 March 18, 2020 Magna, Utah, earthquake: Seismological Research Letters, v. 92, no. 2A, p. 741-754, https://doi.org/10.1785/0220200312.","productDescription":"14 p.","startPage":"741","endPage":"754","ipdsId":"IP-122052","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Magna","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.10921941420736,\n 40.723327593996174\n ],\n [\n -112.10921941420736,\n 40.684935353345196\n ],\n [\n -112.05066964819599,\n 40.684935353345196\n ],\n [\n -112.05066964819599,\n 40.723327593996174\n ],\n [\n -112.10921941420736,\n 40.723327593996174\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","issue":"2A","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wicks, Charles 0000-0002-0809-1328","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":9023,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Svarc, Jerry L. 0000-0002-2802-4528","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":212736,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926886,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217226,"text":"70217226 - 2021 - Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health","interactions":[],"lastModifiedDate":"2021-05-03T19:21:42.325383","indexId":"70217226","displayToPublicDate":"2021-01-12T16:43:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health","docAbstract":"Agricultural production and associated applications of nitrogen (N) fertilizers have increased dramatically in the last century, and current projections to 2050 show that demands will continue to increase as the human population grows. Applied in both organic and inorganic fertilizer forms, N is an essential nutrient in crop productivity. Increased fertilizer applications, however, create the potential for more N loss before plant uptake. One strategy for minimizing N loss is the use of enhanced efficiency fertilizers, fortified with a nitrification inhibitor, such as nitrapyrin. In soils and water, nitrapyrin inhibits the activity of ammonia monooxygenase, a microbial enzyme that catalyzes the first step of nitrification from ammonium to nitrite. Potential benefits of using nitrification inhibitors range from reduced nitrate leaching and nitrous oxide emissions to increased crop yield. The extent of these benefits, however, depends on environmental conditions and management practices. Thus, such benefits are not always realized. Additionally, nitrapyrin has been shown to transport off-field, and it is unknown what effects environmental nitrapyrin could have on nontarget organisms and the ecological nitrogen cycle. Here, we review the agronomic and environmental benefits and costs of nitrapyrin use and present a series of research questions and considerations to be addressed with future nitrification inhibitor research.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.0c05732","usgsCitation":"Woodward, E., Edwards, T.M., Givens, C.E., Kolpin, D., and Hladik, M.L., 2021, Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health: Environmental Science and Technology, v. 55, no. 3, p. 1345-1353, https://doi.org/10.1021/acs.est.0c05732.","productDescription":"9 p.","startPage":"1345","endPage":"1353","ipdsId":"IP-122016","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":382528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70217226/coverthb.jpg"}],"volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Emily E. 0000-0001-9196-1349 ewoodward@usgs.gov","orcid":"https://orcid.org/0000-0001-9196-1349","contributorId":177364,"corporation":false,"usgs":true,"family":"Woodward","given":"Emily","email":"ewoodward@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Thea M. 0000-0002-6176-2872","orcid":"https://orcid.org/0000-0002-6176-2872","contributorId":241635,"corporation":false,"usgs":true,"family":"Edwards","given":"Thea","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":808113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":808115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808116,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217229,"text":"70217229 - 2021 - Comparison of specimen- and image-based morphometrics in Cisco","interactions":[],"lastModifiedDate":"2023-01-19T16:23:57.072018","indexId":"70217229","displayToPublicDate":"2021-01-12T08:14:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of specimen- and image-based morphometrics in Cisco","docAbstract":"Morphometric data from fish are typically generated using one of two methods: direct measurements made on a specimen or extraction of distances from a digital picture. We compared data on 12 morphometrics collected with these two methods on the same collection of Cisco Coregonus artedi from Lake Ontario, North America, to assess the degree of bias in measurements made directly on a specimen- vs. an image-based method. We also assessed the degree of reproducibility within the image-based method by evaluating the amount of variation between different analysts for each morphometric method. Our results indicate specific morphometrics may be more prone to bias across the two methods and between analysts. Four of 12 morphometrics evaluated showed significant deviation from a 1:1 relationship that would be expected if the imaged-based method produced accurate specimen-based measurements. Pelvic fin length and pelvic–anal fin distance had the highest between-analyst variation for image-based landmarks, indicating low reproducibility for these metrics, compared with pectoral fin or total length, which had lower between-analyst variation. Although some morphometric measurements can be accurately obtained with either method, and therefore potentially used interchangeably in studies on Cisco morphology, our findings highlight the importance of considering method bias in morphometric studies that use data collected by different methods.
Residence time distribution (RTD) is a critically important characteristic of groundwater flow systems; however, it cannot be measured directly. RTD can be inferred from tracer data with analytical models (few parameters) or with numerical models (many parameters). The second approach permits more variation in system properties but is used less frequently than the first because large‐scale numerical models can be resource intensive. Using a novel automated approach, a set of 115 inexpensive general simulation models (GSMs) was used to create RTD metrics (fraction of young groundwater, defined as < 65 years old; mean travel time of young fraction; median travel time of old fraction; and mean path length). GSMs captured the general trends in measured tritium concentrations in 431 wells. Boosted Regression Tree metamodels were trained to predict these RTD metrics using available wall‐to‐wall hydrogeographic digital sets as explanatory features. The metamodels produced a three‐dimensional distribution of predictions throughout the glacial system that generally matched with the numerical model RTD metrics. In addition to the expected importance of aquifer thickness and recharge rate in predicting RTD metrics, two new data sets, Multi‐Order Hydrologic Position (MOHP) and hydrogeologic terrane were important predictors. These variables by themselves produced metamodels with Nash‐Sutcliffe efficiency close to the full metamodel. Metamodel predictions showed that the volume of young groundwater stored in the glaciated U.S. is about 6,000 km3, or about 0.5% of globally stored young groundwater.
This study reports historic capture-mark-recapture survival and abundance estimates of common bottlenose dolphins (Tursiops truncatus) based on photo-identification surveys of coastal Venezuela (along the Aragua coast between Turiamo Bay and Puerto Colombia). We used the most recent data available: dolphins identified by unique dorsal fin marks during wet and dry season surveys conducted from 2004 to 2008. Dolphin encounter histories were analyzed in the Closed Capture Robust Design framework, with the top model including random movement, constant survival, and capture-recapture probabilities that varied by secondary periods. Survival of marked adults was estimated at 0.99 (95% CI = 0.97 to 1.00). Population estimates for all adults (marked and unmarked) averaged 31 animals (SD = 13.8), and for all dolphins (all adults and calves), 41 animals (SD = 17.2). Coastal bottlenose dolphins face numerous threats, including ship strikes, oil spills, conflict with recreational and industrial fisheries, other negative human interactions, biotoxins, chemicals, noise, freshwater discharge, and coastal development. Further, small populations are, in general, at increased risk due to reduced resiliency and recovery potential when exposed to such threats and to expected environmental and demographic stochasticity. These historic estimates of abundance and survival are critical for establishing a reference state and indicate a need for ongoing monitoring of the small dolphin population while the Aragua coast is still, as of yet, relatively little impacted by humans. Should coastal development increase (as is the global trend) and/or environmental catastrophes (e.g., harmful algal blooms, hurricanes, and oil spills) occur, these historic estimates will be essential for assessing impacts and guiding management and conservation interventions. Our results show year-round dolphin presence and highlight the Venezuelan coastal–oceanic landscape as an area of both future research and conservation importance.
Harmful algal blooms produce toxins that bioaccumulate in the food web and adversely affect humans, animals, and entire marine ecosystems. Blooms of the diatom Pseudo-nitzschia can produce domoic acid (DA), a toxin that most commonly causes neurological disease in endothermic animals, with cardiovascular effects that were first recognized in southern sea otters. Over the last 20 years, DA toxicosis has caused significant morbidity and mortality in marine mammals and seabirds along the west coast of the USA. Identifying DA exposure has been limited to toxin detection in biological fluids using biochemical assays, yet measurement of systemic toxin levels is an unreliable indicator of exposure dose or timing. Furthermore, there is little information regarding repeated DA exposure in marine wildlife. Here, the association between long-term environmental DA exposure and fatal cardiac disease was investigated in a longitudinal study of 186 free-ranging sea otters in California from 2001 – 2017, highlighting the chronic health effects of a marine toxin. A novel Bayesian spatiotemporal approach was used to characterize environmental DA exposure by combining several DA surveillance datasets and integrating this with life history data from radio-tagged otters in a time-dependent survival model. In this study, a sea otter with high DA exposure had a 1.7-fold increased hazard of fatal cardiomyopathy compared to an otter with low exposure. Otters that consumed a high proportion of crab and clam had a 2.5- and 1.2-times greater hazard of death due to cardiomyopathy than otters that consumed low proportions. Increasing age is a well-established predictor of cardiac disease, but this study is the first to identify that DA exposure affects the risk of cardiomyopathy more substantially in prime-age adults than aged adults. A 4-year-old otter with high DA exposure had 2.3 times greater risk of fatal cardiomyopathy than an otter with low exposure, while a 10-year old otter with high DA exposure had just 1.2 times greater risk. High Toxoplasma gondii titers also increased the hazard of death due to heart disease 2.4-fold. Domoic acid exposure was most detrimental for prime-age adults, whose survival and reproduction are vital for population growth, suggesting that persistent DA exposure will likely impact long-term viability of this threatened species. These results offer insight into the pervasiveness of DA in the food web and raise awareness of under-recognized chronic health effects of DA for wildlife at a time when toxic blooms are on the rise.
Tectonics inheritance controls the evolution of many orogens. To unravel the role of the Gondwanan heritage (late Paleozoic to Triassic) over the building of the Central Andes in northern Chile (Domeyko Range), we performed detrital U‐Pb zircon and 40Ar/39Ar muscovite geochronology along with structural analyses (kinematics and structural balancing). 40Ar/39Ar dating of detrital muscovite reveals contrasting cooling histories for the Paleozoic basement of Triassic rift sub‐basins, indicating that NW‐striking crustal structures segmented the Andean forearc since at least the middle Permian, likely related to an accretional fabric developed along SW Gondwana. These structures can be inferred based on scattered faults, gravimetric data, and basement age disruptions. During the Late Triassic, NS‐striking master faults and secondary NW‐ to NNW‐striking faults configured an oblique rift, primarily driven by subduction dynamics. We suggest that along SW Gondwana, the slab‐pull would have controlled the development of subduction‐related rift basins close to the trench whereas Triassic inland rifts were mainly driven by Pangea‐breakup stresses. Compressional tectonics began in the Late Cretaceous, yet the inversion of the Triassic rift would have started during the Eocene with the inception of the metallogenic‐fertile transpressional Domeyko fault system. Thus, the structural style of this range was determined by the architecture of the Triassic rift, where the inversion of deep‐seated faults accounted for west‐vergent thick‐ and thin‐skinned structures. Pre‐Andean NW‐striking structures also accommodated tectonic rotations during the Incaic orogeny (Eocene‐Oligocene) and may delimit the rupture zone of large earthquakes, suggesting an underestimated role of such ancient discontinuities in Andean neotectonics.
","language":"English","publisher":"Wiley","doi":"10.1029/2020TC006475","usgsCitation":"Espinoza, M., Oliveros, V., Vasquez, P., Giambiagi, L., Morgan, L.E., Gonzalez, R., Solari, L., and Bechis, F., 2021, Gondwanic inheritance on the building of the western Central Andes (Domeyko Range, Chile): Structural and thermochronological approach (U-Pb and 40Ar-39Ar): Tectonics, v. 40, no. 3, e2020TC006475, https://doi.org/10.1029/2020TC006475.","productDescription":"e2020TC006475","ipdsId":"IP-106092","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":382288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Espinoza, Mauricio 0000-0003-2557-1603","orcid":"https://orcid.org/0000-0003-2557-1603","contributorId":247823,"corporation":false,"usgs":false,"family":"Espinoza","given":"Mauricio","email":"","affiliations":[{"id":49667,"text":"Universidad de Concepción","active":true,"usgs":false}],"preferred":false,"id":808446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliveros, Veronica","contributorId":247824,"corporation":false,"usgs":false,"family":"Oliveros","given":"Veronica","email":"","affiliations":[{"id":49667,"text":"Universidad de Concepción","active":true,"usgs":false}],"preferred":false,"id":808447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vasquez, Paulina","contributorId":247826,"corporation":false,"usgs":false,"family":"Vasquez","given":"Paulina","email":"","affiliations":[{"id":49668,"text":"Servicio Nacional de Geología y Minería","active":true,"usgs":false}],"preferred":false,"id":808448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giambiagi, Laura 0000-0001-6286-7206","orcid":"https://orcid.org/0000-0001-6286-7206","contributorId":247829,"corporation":false,"usgs":false,"family":"Giambiagi","given":"Laura","email":"","affiliations":[{"id":49669,"text":"Centro Regional de Investigaciones Científicas y Tecnológicas","active":true,"usgs":false}],"preferred":false,"id":808449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":808450,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonzalez, Rodrigo","contributorId":247830,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Rodrigo","email":"","affiliations":[{"id":27795,"text":"Universidad Católica del Norte","active":true,"usgs":false}],"preferred":false,"id":808451,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Solari, Luigi 0000-0002-9769-6846","orcid":"https://orcid.org/0000-0002-9769-6846","contributorId":247831,"corporation":false,"usgs":false,"family":"Solari","given":"Luigi","email":"","affiliations":[{"id":25354,"text":"Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":808452,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bechis, Florencia","contributorId":247833,"corporation":false,"usgs":false,"family":"Bechis","given":"Florencia","email":"","affiliations":[{"id":49670,"text":"Universidad Nacional de Río Negro","active":true,"usgs":false}],"preferred":false,"id":808453,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217220,"text":"70217220 - 2021 - Eroding Cascadia— Sediment and solute transport and landscape denudation in western Oregon and northwestern California","interactions":[],"lastModifiedDate":"2021-10-08T11:27:36.141752","indexId":"70217220","displayToPublicDate":"2021-01-11T07:43:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Eroding Cascadia— Sediment and solute transport and landscape denudation in western Oregon and northwestern California","docAbstract":"Riverine measurements of sediment and solute transport give empirical basin-scale estimates of bed-load, suspended-sediment, and silicate-solute fluxes for 100,000 km2 of northwestern California and western Oregon. This spatially explicit sediment budget shows the multifaceted control of geology and physiography on the rates and processes of fluvial denudation. Bed-load transport is greatest for steep basins, particularly in areas underlain by the accreted Klamath terrane. Bed-load flux commonly decreases downstream as clasts convert to suspended load by breakage and attrition, particularly for softer rock types. Suspended load correlates strongly with lithology, basin slope, precipitation, and wildfire disturbance. It is highest in steep regions of soft rocks, and our estimates suggest that much of the suspended load is derived from bed-load comminution. Dissolution, measured by basin-scale silicate-solute yield, constitutes a third of regional landscape denudation. Solute yield correlates with precipitation and is proportionally greatest in low-gradient and wet basins and for high parts of the Cascade Range, where undissected Quaternary volcanic rocks soak in 2−3 m of annual precipitation. Combined, these estimates provide basin-scale erosion rates ranging from ∼50 t ∙ km−2 ∙ yr−1 (approximately equivalent to 0.02 mm ∙ yr−1) for low-gradient basins such as the Willamette River to ∼500 t ∙ km−2 ∙ yr−1 (∼0.2 mm ∙ yr−1) for steep coastal drainages. The denudation rates determined here from modern measurements are less than those estimated by longer-term geologic assessments, suggesting episodic disturbances such as fire, flood, seismic shaking, and climate change significantly add to long-term landscape denudation.