Thousands of abandoned mines throughout the western region of North America contain elevated total-mercury (THg) concentrations. Mercury is mobilized from these sites primarily due to erosion of particulate-bound Hg (THg-P). Organic matter-based soil amendments can promote vegetation growth on mine tailings, reducing erosion and subsequent loading of THg-P into downstream waterbodies. However, the introduction of a labile carbon source may stimulate microbial activity that can produce methylmercury (MeHg)—the more toxic and bioaccumulative form of Hg. Our objectives were to investigate how additions of different organic matter substrates impact Hg mobilization and methylation using a combination of field observations and controlled experiments. Field measurements of water, sediment, and porewater were collected downstream of the site and multi-year monitoring (and load calculations) were conducted at a downstream gaging station. MeHg production was assessed using stable isotope methylation assays and mesocosm experiments that were conducted using different types of organic carbon soil amendments mixed with materials from the mine site. The results showed that >80% of the THg mobilized from the mine was bound to particles and that >90% of the annual Hg loading occurred during the period of elevated discharge during spring snowmelt. Methylation rates varied between different types of soil amendments and were correlated with the components of excitation emission matrices (EEMs) associated with humic acid fractions of organic matter. The mesocosm experiments showed that under anoxic conditions carbon amendments to tailings could significantly increase porewater MeHg concentrations (up to 13 ± 3 ng/L). In addition, the carbon amendments significantly increased THg partitioning into porewater. Overall, these results indicate that soil amendment applications to reduce surface erosion at abandoned mine sites could be effective at reducing particulate Hg mobilization to downstream waterbodies; however, some types of carbon amendments can significantly increase Hg methylation as well as increase the mobilization of dissolved THg from the site.
Climate change has contributed to recent declines in mountain snowpack and earlier runoff, which in turn has intensified hydrological droughts in western North America. Climate model projections suggest that continued and severe snowpack reductions are expected over the 21st century, with profound consequences for ecosystems and human welfare. Yet the current understanding of trends and variability in mountain snowpack is limited by the relatively short and strongly temperature forced observational record. Motivated by the urgent need to better understand snowpack dynamics in a long-term, spatially coherent framework, here we examine snow-growth relationships in western North American tree-ring chronologies. We present an extensive network of snow-sensitive proxy data to support high space/time resolution paleosnow reconstruction, quantify and interpret the type and spatial density of snow related signals in tree-ring records, and examine the potential for regional bias in the tree-ring based reconstruction of different snow drought types (dry versus warm). Our results indicate three distinct snow-growth relationships in tree-ring chronologies: moisture-limited snow proxies that include a spring temperature signal, moisture-limited snow proxies lacking a spring temperature signal, and energy-limited snow proxies. Each proxy type is based on distinct physiological tree-growth mechanisms related to topographic and climatic site conditions, and provides unique information on mountain snowpack dynamics that can be capitalized upon within a statistical reconstruction framework. This work provides a platform and foundational background required for the accelerated production of high-quality annually-resolved snowpack reconstructions from regional to high (<12 km) spatial scales in western North America, and by extension, will support an improved understanding of the vulnerability of snowmelt-derived water resources to natural variability and future climate warming.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abd5de","usgsCitation":"Coulthard, B.L., Anchukaitis, K.J., Pederson, G.T., Cook, E.R., Littell, J., and Smith, D.J., 2021, Snowpack signals in North American tree rings: Environmental Research Letters, v. 16, no. 3, 034037, 13 p., https://doi.org/10.1088/1748-9326/abd5de.","productDescription":"034037, 13 p.","ipdsId":"IP-122302","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abd5de","text":"Publisher Index Page"},{"id":383252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Coulthard, Bethany L.","contributorId":250711,"corporation":false,"usgs":false,"family":"Coulthard","given":"Bethany","email":"","middleInitial":"L.","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":810246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anchukaitis, Kevin J.","contributorId":195005,"corporation":false,"usgs":false,"family":"Anchukaitis","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":810247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Edward R","contributorId":218752,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","email":"","middleInitial":"R","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":810249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":810250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Dan J.","contributorId":250712,"corporation":false,"usgs":false,"family":"Smith","given":"Dan","email":"","middleInitial":"J.","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":810251,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70218733,"text":"70218733 - 2021 - Spatial clustering of aftershocks impacts the performance of physics‐based earthquake forecasting models","interactions":[],"lastModifiedDate":"2021-03-10T13:13:17.025736","indexId":"70218733","displayToPublicDate":"2020-12-22T07:10:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Spatial clustering of aftershocks impacts the performance of physics‐based earthquake forecasting models","docAbstract":"I explore why physics‐based models of earthquake triggering rarely outperform statistical models in prospective testing, outside of limited spatial‐temporal windows. Pseudo‐prospective tests on suites of synthetic aftershock sequences show that a major factor is the level of unmodeled spatial clustering of the direct aftershocks triggered by the mainshock. The synthetic sequences are generated from generalized “physical” triggering models, optionally superimposed on background heterogeneity that controls the level of clustering. The statistical Epidemic Type Aftershock Sequence (ETAS) model performs relatively better the more clustered the direct aftershocks, while the true generalized “physical” model performs relatively worse. Real aftershocks appear to be sufficiently clustered to allow ETAS to perform as well as or better than physical models such as Coulomb stress triggering. A likely cause of the spatial clustering of direct aftershocks is heterogeneity of the background physical conditions, which typically is not modeled in physics‐based forecasts. This implies that the forecast performance of physical models could be substantially improved through a better understanding of the interaction between earthquake stress changes and variable background physical conditions such as stress state, fault strength, and fluid pressure.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020824","usgsCitation":"Hardebeck, J.L., 2021, Spatial clustering of aftershocks impacts the performance of physics‐based earthquake forecasting models: JGR Solid Earth, v. 126, no. 2, e2020JB020824, 16 p., https://doi.org/10.1029/2020JB020824.","productDescription":"e2020JB020824, 16 p.","ipdsId":"IP-117739","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":811557,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70218214,"text":"70218214 - 2021 - Sentinel coyote pathogen survey to assess declining black-footed ferret (Mustela nigripes) population in South Dakota, USA","interactions":[],"lastModifiedDate":"2022-01-24T16:00:47.907583","indexId":"70218214","displayToPublicDate":"2020-12-21T14:21:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sentinel coyote pathogen survey to assess declining black-footed ferret (Mustela nigripes) population in South Dakota, USA","title":"Sentinel coyote pathogen survey to assess declining black-footed ferret (Mustela nigripes) population in South Dakota, USA","docAbstract":"As part of the national recovery effort, endangered black-footed ferrets (Mustela nigripes) were reintroduced to the Cheyenne River Sioux Reservation in South Dakota, US in 2000. Despite an encouraging start, numbers of ferrets at the site have declined. In an effort to determine possible causes of the population decline, we undertook a pathogen survey in 2012 to detect exposure to West Nile virus (WNV), canine distemper virus (CDV), plague (Yersinia pestis), tularemia (Francisella tularensis), and heartworm (Dirofilaria immitis) using coyotes (Canis latrans) as a sentinel animal. The highest seroprevalence was for WNV with 71% (20/28) of coyotes testing antibody-positive. Seroprevalence of CDV and plague were lower, 27% and 13%, respectively. No evidence of active infection with tularemia or heartworm was seen in the coyotes sampled. As this study did not sample black-footed ferrets themselves, the definitive cause for the decline of this population cannot be determined. However, the presence of coyotes seropositive for two diseases, plague and CDV, lethal to black-footed ferrets, indicated the potential for exposure and infection. The high seroprevalence of WNV in the coyotes indicated a wide exposure to the virus; therefore, exposure of black-footed ferrets to the virus is also likely. Due to the ability of WNV to cause fatal disease in other species, studies may be useful to elucidate the impact that WNV could have on the success of reintroduced black-footed ferrets as well as factors influencing the spread and incidence of the disease in a prairie ecosystem.
","language":"English","publisher":"Allen Press","doi":"10.7589/JWD-D-20-00015","usgsCitation":"Schuler, K.L., Claymore, M., Schnitzler, H., Dubovi, E., Rocke, T.E., Perry, M.J., Bowman, D., and Abbott, R., 2021, Sentinel coyote pathogen survey to assess declining black-footed ferret (Mustela nigripes) population in South Dakota, USA: Journal of Wildlife Diseases, v. 57, no. 2, p. 264-272, https://doi.org/10.7589/JWD-D-20-00015.","productDescription":"9 p.","startPage":"264","endPage":"272","ipdsId":"IP-117390","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":383396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Cheyenne River Sioux Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.0684814453125,\n 44.46123053905879\n ],\n [\n -100.2227783203125,\n 44.46123053905879\n ],\n [\n -100.2227783203125,\n 45.4947963896697\n ],\n [\n -102.0684814453125,\n 45.4947963896697\n ],\n [\n -102.0684814453125,\n 44.46123053905879\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schuler, Krysten L.","contributorId":176255,"corporation":false,"usgs":false,"family":"Schuler","given":"Krysten","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":810438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claymore, Michael","contributorId":251727,"corporation":false,"usgs":false,"family":"Claymore","given":"Michael","email":"","affiliations":[{"id":50381,"text":"Cheyenne River Sioux Tribe, Prairie Management Program, P.O. Box 590, Eagle Butte, SD USA","active":true,"usgs":false}],"preferred":false,"id":810439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schnitzler, Hannah","contributorId":251728,"corporation":false,"usgs":false,"family":"Schnitzler","given":"Hannah","email":"","affiliations":[{"id":50384,"text":"Cornell Wildlife Health Lab, Cornell University College of Veterinary Medicine, 240","active":true,"usgs":false}],"preferred":false,"id":810440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dubovi, Edward","contributorId":251729,"corporation":false,"usgs":false,"family":"Dubovi","given":"Edward","email":"","affiliations":[{"id":50385,"text":"Animal Health Diagnostic Center, Cornell University, 240 Farrier Rd., Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":810441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":810442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perry, Michael J.","contributorId":251730,"corporation":false,"usgs":false,"family":"Perry","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":50386,"text":"New York State Department of Health, Wadsworth Center Biodefense Laboratory, Albany NY","active":true,"usgs":false}],"preferred":false,"id":810443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowman, Dwight","contributorId":251731,"corporation":false,"usgs":false,"family":"Bowman","given":"Dwight","email":"","affiliations":[{"id":50387,"text":"Department of Microbiology and Immunology, Cornell University College ofVeterinary Medicine, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":810444,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Abbott, Rachel","contributorId":240909,"corporation":false,"usgs":false,"family":"Abbott","given":"Rachel","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":810445,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222340,"text":"70222340 - 2021 - A long-term geothermal observatory across subseafloor gas hydrates, IODP Hole U1364A, Cascadia accretionary prism","interactions":[],"lastModifiedDate":"2021-07-22T14:58:08.11708","indexId":"70222340","displayToPublicDate":"2020-12-21T09:52:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9110,"text":"Frontiers in Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A long-term geothermal observatory across subseafloor gas hydrates, IODP Hole U1364A, Cascadia accretionary prism","docAbstract":"We report 4 years of temperature profiles collected from May 2014 to May 2018 in Integrated Ocean Drilling Program Hole U1364A in the frontal accretionary prism of the Cascadia subduction zone. The temperature data extend to depths of nearly 300 m below seafloor (mbsf), spanning the gas hydrate stability zone at the location and a clear bottom-simulating reflector (BSR) at ∼230 mbsf. When the hole was drilled in 2010, a pressure-monitoring Advanced CORK (ACORK) observatory was installed, sealed at the bottom by a bridge plug and cement below 302 mbsf. In May 2014, a temperature profile was collected by lowering a probe down the hole from the ROV ROPOS. From July 2016 through May 2018, temperature data were collected during a nearly two-year deployment of a 24-thermistor cable installed to 268 m below seafloor (mbsf). The cable and a seismic-tilt instrument package also deployed in 2016 were connected to the Ocean Networks Canada (ONC) NEPTUNE cabled observatory in June of 2017, after which the thermistor temperatures were logged by Ocean Networks Canada at one-minute intervals until failure of the main ethernet switch in the integrated seafloor control unit in May 2018. The thermistor array had been designed with concentrated vertical spacing around the bottom-simulating reflector and two pressure-monitoring screens at 203 and 244 mbsf, with wider thermistor spacing elsewhere to document the geothermal state up to seafloor. The 4 years of data show a generally linear temperature gradient of 0.055°C/m consistent with a heat flux of 61–64 mW/m2. The data show no indications of thermal transients. A slight departure from a linear gradient provides an approximate limit of ∼10−10 m/s for any possible slow upward advection of pore fluids. In-situ temperatures are ∼15.8°C at the BSR position, consistent with methane hydrate stability at that depth and pressure.
","language":"English","publisher":"Frontiers Media SA","doi":"10.3389/feart.2020.568566","usgsCitation":"Becker, K.E., Davis, E.E., Hessemann, M., Collins, J.A., and McGuire, J., 2021, A long-term geothermal observatory across subseafloor gas hydrates, IODP Hole U1364A, Cascadia accretionary prism: Frontiers in Earth Sciences, v. 8, 568566, 10 p., https://doi.org/10.3389/feart.2020.568566.","productDescription":"568566, 10 p.","ipdsId":"IP-119212","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":454042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.568566","text":"Publisher Index Page"},{"id":387385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.3759765625,\n 49.10983779052439\n ],\n [\n -133.22021484375,\n 48.472921272487824\n ],\n [\n -135.46142578124997,\n 47.32393057095941\n ],\n [\n -136.6259765625,\n 46.14939437647686\n ],\n [\n -135.46142578124997,\n 45.413876460821086\n ],\n [\n -132.802734375,\n 45.49094569262732\n ],\n [\n -130.36376953125,\n 45.38301927899065\n ],\n [\n -126.38671874999999,\n 47.57652571374621\n ],\n [\n -125.3759765625,\n 49.10983779052439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Becker, K. Elizabeth","contributorId":196545,"corporation":false,"usgs":false,"family":"Becker","given":"K.","email":"","middleInitial":"Elizabeth","affiliations":[],"preferred":false,"id":819674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, E. E.","contributorId":261294,"corporation":false,"usgs":false,"family":"Davis","given":"E.","email":"","middleInitial":"E.","affiliations":[{"id":52792,"text":"Geol. Surv. of Canada","active":true,"usgs":false}],"preferred":false,"id":819675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hessemann, M.","contributorId":261295,"corporation":false,"usgs":false,"family":"Hessemann","given":"M.","email":"","affiliations":[{"id":52794,"text":"Ocean Networks Canada","active":true,"usgs":false}],"preferred":false,"id":819676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, J. A.","contributorId":213074,"corporation":false,"usgs":false,"family":"Collins","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":819677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819678,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229076,"text":"70229076 - 2021 - Variation in black bass angler characteristics by stream size and accessibility in Oklahoma’s Ozark Highland streams","interactions":[],"lastModifiedDate":"2022-02-28T15:31:45.800061","indexId":"70229076","displayToPublicDate":"2020-12-21T09:27:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Variation in black bass angler characteristics by stream size and accessibility in Oklahoma’s Ozark Highland streams","docAbstract":"Fishing in streams and rivers is a popular outdoor recreation activity in eastern Oklahoma, where most anglers target black bass (Micropterus) species. Since the early 1990s, when the last assessment of black bass fishing in the region was conducted, broadscale factors such as harvesting behavior, state fishery regulations, and bass population dynamics have changed. In 2018, we conducted creel and fish tagging surveys in three tributaries of Lake Tenkiller (Caney Creek, Baron Fork, and Illinois River) that differed in size and accessibility to provide current estimates of catch, harvest, and effort directed toward black bass. We then related these estimates to angler socioeconomic characteristics. The amount of angler effort was concomitant with stream size and accessibility, being greatest in the largest stream with the most access (Illinois River). However, catch rates were highest in the medium-sized stream (Baron Fork). Harvest rates and exploitation were near zero in all systems. Anglers fishing Caney Creek, the smallest and least accessible stream, were nearly all local, coming from zip codes ~42 km away, with low median household incomes compared to anglers at the other streams who came from a broader array of more distant zip codes and had higher median household incomes. Anglers fishing the smallest stream were also more interested in harvesting fish and having higher creel limits than anglers at the other two systems. In the Oklahoma Ozark Highlands, stream size and accessibility appear to be a significant factor in angler demographics, potentially necessitating different management strategies.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10565","usgsCitation":"Chapagain, B., Long, J.M., Taylor, A.T., and Joshi, O., 2021, Variation in black bass angler characteristics by stream size and accessibility in Oklahoma’s Ozark Highland streams: North American Journal of Fisheries Management, v. 41, no. 3, p. 585-599, https://doi.org/10.1002/nafm.10565.","productDescription":"15 p.","startPage":"585","endPage":"599","ipdsId":"IP-121658","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454045,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/11244/334600","text":"External Repository"},{"id":396553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.22125244140625,\n 35.572448615622804\n ],\n [\n -93.94958496093749,\n 35.572448615622804\n ],\n [\n -93.94958496093749,\n 36.910372213522535\n ],\n [\n -95.22125244140625,\n 36.910372213522535\n ],\n [\n -95.22125244140625,\n 35.572448615622804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapagain, B.","contributorId":280237,"corporation":false,"usgs":false,"family":"Chapagain","given":"B.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":836417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Andrew T.","contributorId":177197,"corporation":false,"usgs":false,"family":"Taylor","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":836419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joshi, O.","contributorId":280236,"corporation":false,"usgs":false,"family":"Joshi","given":"O.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":836420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218478,"text":"70218478 - 2021 - In‐situ mass balance estimates offshore Costa Rica","interactions":[],"lastModifiedDate":"2021-03-01T14:49:47.347398","indexId":"70218478","displayToPublicDate":"2020-12-21T08:42:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"In‐situ mass balance estimates offshore Costa Rica","docAbstract":"The Costa Rican convergent margin has been considered a type erosive margin, with erosional models suggesting average losses up to −153 km3/km/m.y. However, three‐dimensional (3D) seismic reflection and Integrated Ocean Drilling Program data collected offshore the Osa Peninsula images accretionary structures and vertical motions that conflict with the forearc basal erosion model. Here we integrate such data to do an in‐situ accounting of material transfer at the plate boundary across the outermost 10 km of the forearc, characterized by active and inactive megathrusts. Our in‐situ budget finds an approximate balance between sediment recycling via accretion and underplating, 0.7–2.3 km3/km/m.y., and basal erosion, 0.7 km3/km/m.y., while subducting sediment volumes, 7.8 km3/km/m.y., greatly outpace either material transfer volumes. These budget results differ significantly from published estimates based on simple proxies of trench axis deflection and slope subsidence. These budget results are the summation of thin incoming hemipelagic sediments that variably accrete along the deformation front, underplating of hemipelagic sediments on the upthrown‐side and basal erosion on the downthrown‐side of active plate bending faulting landward of the trench axis, and sediment subduction primarily composed of pelagic sediments.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GC009190","usgsCitation":"Edwards, J., Kluesner, J.W., Silver, E., Lauer, R., Bangs, N., and Boston, B., 2021, In‐situ mass balance estimates offshore Costa Rica: Geochemistry, Geophysics, Geosystems, v. 22, e2020GC009190, 13 p., https://doi.org/10.1029/2020GC009190.","productDescription":"e2020GC009190, 13 p.","ipdsId":"IP-106898","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/6804fd0b6f724ecb9c8aad62cdccfc0b","text":"Publisher Index Page"},{"id":383681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.9852294921875,\n 8.597315884206026\n ],\n [\n -85.15502929687499,\n 10.487811882056695\n ],\n [\n -86.23168945312499,\n 9.56283423106296\n ],\n [\n -83.6883544921875,\n 7.656553242193619\n ],\n [\n -82.9852294921875,\n 8.597315884206026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2021-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Edwards, Joel","contributorId":252933,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":811162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":811163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silver, Eli","contributorId":252934,"corporation":false,"usgs":false,"family":"Silver","given":"Eli","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":811164,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauer, Rachel","contributorId":252935,"corporation":false,"usgs":false,"family":"Lauer","given":"Rachel","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":811165,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bangs, Nathan","contributorId":252936,"corporation":false,"usgs":false,"family":"Bangs","given":"Nathan","affiliations":[{"id":50475,"text":"UTIG","active":true,"usgs":false}],"preferred":false,"id":811166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boston, Brian","contributorId":252937,"corporation":false,"usgs":false,"family":"Boston","given":"Brian","email":"","affiliations":[{"id":40272,"text":"Japan Agency for Marine-Earth Science and Technology","active":true,"usgs":false}],"preferred":false,"id":811167,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229429,"text":"70229429 - 2021 - Canada goose survival and recovery rates in urban and rural areas of Iowa, USA","interactions":[],"lastModifiedDate":"2022-03-08T12:50:04.301788","indexId":"70229429","displayToPublicDate":"2020-12-21T06:46:00","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":"Canada goose survival and recovery rates in urban and rural areas of Iowa, USA","docAbstract":"Once extirpated from much of their North American range, temperate-breeding Canada geese (Branta canadensis maxima) have reached high abundance. As a result, focus has shifted from restoration to managing harvest and addressing human-goose conflict. Conflict persists or is increasing in urban areas throughout the Mississippi Flyway. Managers need more information regarding demographic rates to determine how hunting affects geese breeding in urban areas and what management actions may be required to achieve management goals. We estimated survival, dead recovery, live recapture, and fidelity probabilities using data from 77,872 Canada geese banded in Iowa, USA, during 1999–2019 using Burnham joint live-dead band recovery models. Factors predicted to affect parameters in candidate models included age (juvenile, subadult, adult), banding site (urban, rural), time, trend, harvest regulation index, and winter severity index. We predicted Canada geese banded in urban areas would have higher survival and lower dead recovery rates than geese banded at rural sites. The top model indicated support for age and banding site effects, and trends in survival and recovery rate (Brownie parameterization). Adult survival was similar for urban (0.75; range = 0.60–0.92) and rural (0.75; range = 0.66–0.82) geese and relatively constant across years. Mean juvenile survival was lower in urban (0.74; range = 0.48–0.93) than rural (0.85; range = 0.68–0.92) areas. Survival increased for urban-banded juveniles and recovery rates increased during liberalization of harvest regulations and decreased after regulations stabilized. Recovery rates of subadults increased for the urban and rural groups. Our results suggest Canada geese breeding in urban areas contribute to harvest and specialized regulations can affect these populations. Harvest regulations in place during our analysis may not have reached a threshold required to observe substantial changes in survival. Current human-goose conflict in urban areas suggests survival has not decreased to a level required to completely address conflict via reduction in goose abundance. Managers may consider additional liberalization of harvest regulations and monitoring via banding to determine to what degree hunter harvest contributes to reducing human-goose conflict and what additional management actions will be required to achieve goals. © 2020 The Wildlife Society.
Stocking Rainbow Trout Oncorhynchus mykiss to create additional angling opportunities is common; however, the spatial and temporal dynamics of such stocking practices are unclear in groundwater-influenced, warmwater streams. Our objectives were to determine Rainbow Trout dispersal from a stocking location on Spavinaw Creek, Oklahoma and to quantify apparent survival of two cohorts of Rainbow Trout stocked in November 2018 and February 2019. Rainbow Trout were PIT-tagged prior to autumn (N = 495) and winter (N = 605) stocking and located poststocking using both an active floating array and two passive fixed arrays. We actively tracked a 6-km extent every 2–3 weeks poststocking and found that PIT-tagged Rainbow Trout dispersal ranged from 0 to 4 km with ~90% of detected tagged fish remaining within 1 km of the stocking location. Directional movement by stocked Rainbow Trout was evident with upstream movements related to increases in daily water discharge and downstream movements related to decreases in daily discharge. Estimated apparent weekly survival of Rainbow Trout was lowest during the first 2 weeks poststocking (91% and 75% for autumn and spring cohorts, respectively). Apparent weekly survival rates for both autumn and spring stocked fish increased through winter and spring when maximum water temperatures were below 25℃, reaching survival rates of 99% by the end of spring. Rainbow Trout persisted in Spavinaw Creek throughout the summer; however, the weekly apparent survival rate declined for both cohorts (93%) when maximum daily water temperatures exceeded 25°C. Our results can be used to guide stocking decisions in similar warmwater streams and suggest that Rainbow Trout persist through spring and summer poststocking under the conditions encountered during our study.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10566","usgsCitation":"Wolf, S.L., and Brewer, S.K., 2021, Survival and movement patterns of Rainbow Trout stocked in a groundwater-influenced warmwater stream: North American Journal of Fisheries Management, v. 41, no. 3, p. 600-615, https://doi.org/10.1002/nafm.10566.","productDescription":"16 p.","startPage":"600","endPage":"615","ipdsId":"IP-119658","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Spavinaw Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.73939895629883,\n 36.2986633386112\n ],\n [\n -94.59692001342773,\n 36.2986633386112\n ],\n [\n -94.59692001342773,\n 36.35439810755854\n ],\n [\n -94.73939895629883,\n 36.35439810755854\n ],\n [\n -94.73939895629883,\n 36.2986633386112\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolf, S. L.","contributorId":242898,"corporation":false,"usgs":false,"family":"Wolf","given":"S.","email":"","middleInitial":"L.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":836064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836065,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223318,"text":"70223318 - 2021 - Exploring relationships among stream health, human well-being, and demographics in Virginia, USA","interactions":[],"lastModifiedDate":"2021-08-23T14:33:51.591281","indexId":"70223318","displayToPublicDate":"2020-12-20T09:24:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Exploring relationships among stream health, human well-being, and demographics in Virginia, USA","docAbstract":"Quantification of empirical relationships between ecosystem health and human well-being is uncommon at broad spatial scales. We used public data for Virginia (USA) counties to examine pairwise correlations among two indicators of stream health, thirteen indicators of human well-being, and four demographic metrics. Our indicators of stream health included the Virginia Stream Condition Index (VSCI) and the percentage of stream kilometers with a fish consumption advisory (%FCA); these measures are inversely related. VSCI and %FCA were correlated with some indicators of human health, safety and security, and living standards, as well as with some demographic metrics. VSCI was most strongly correlated (positively) with the percentage of a county’s population self-identifying as White; %FCA was most strongly correlated (positively) with overall mortality rate (number of deaths per 100,000 people). This exploratory study highlights the need for future multidisciplinary, multiscale studies to characterize toxicological, epidemiological, socioeconomic, and political linkages – including causal mechanisms – between ecosystem health and human well-being.
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\"}}]}","volume":"121","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stern, Marc J.","contributorId":264592,"corporation":false,"usgs":false,"family":"Stern","given":"Marc","email":"","middleInitial":"J.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":821711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krometis, Leigh Anne","contributorId":264591,"corporation":false,"usgs":false,"family":"Krometis","given":"Leigh Anne","affiliations":[{"id":54511,"text":"Virginai Tech","active":true,"usgs":false}],"preferred":false,"id":821710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemby, Tyler L.","contributorId":264593,"corporation":false,"usgs":false,"family":"Hemby","given":"Tyler","email":"","middleInitial":"L.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":821712,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220277,"text":"70220277 - 2021 - Recruitment dynamics of non-native largemouth bass within the Sacramento-San Joaquin delta","interactions":[],"lastModifiedDate":"2021-05-13T15:24:51.258767","indexId":"70220277","displayToPublicDate":"2020-12-20T07:29:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Recruitment dynamics of non-native largemouth bass within the Sacramento-San Joaquin delta","docAbstract":"The Cichlidae are among the most diversified families of fish in the Neotropics and represent an important component of aquatic biodiversity. Understanding cichlid nest‐site selection is important for assemblages facing uncertain futures due to species invasions and environmental change. This information could be used to predict how inter‐ and intraspecific competition for reproductive space may affect populations with changing community dynamics or to identify areas as targets for conservation. We investigated which hydrogeomorphological factors correlated to preferred nest sites of four native cichlid species in the Bladen River, Belize. We recorded the locations of nest sites and collected habitat data through the study reach, including flow velocity, depth, sediment type, fish cover type richness and distance to the bank. Nest locations and physical habitat data were used to construct spatially explicit habitat models using boosted regression trees (BRTs). The models provided statistically significant evidence that physical habitat variables influence the distribution of the nest sites. We found that all species except Archocentrus spilurus were associated with substrate, specifically sand. Thorichthys meeki was also associated with lower water velocities, whereas Cichlasoma salvini was influenced by all five variables. Vieja maculicauda and Archocentrus spilurus were both influenced by flow velocity, distance to bank and depth, although A. spilurus preferred deeper, slightly faster locations about the same distance to the bank. This study suggests that the spatial distribution of nest sites within this cichlid community is significantly different than random and is at least partially governed by physical controls.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12580","usgsCitation":"Buege, E.A., Esselman, P., and Praskievicz, S.J., 2021, Hydrogeomorphological controls on reach‐scale distributions of cichlid nest sites in a small neotropical river: Ecology of Freshwater Fish, v. 30, no. 2, p. 244-255, https://doi.org/10.1111/eff.12580.","productDescription":"12 p.","startPage":"244","endPage":"255","ipdsId":"IP-121602","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","otherGeospatial":"Monkey River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.132080078125,\n 16.251593732779515\n ],\n [\n -88.35205078124999,\n 16.251593732779515\n ],\n [\n -88.35205078124999,\n 17.13554114256562\n ],\n [\n -89.132080078125,\n 17.13554114256562\n ],\n [\n -89.132080078125,\n 16.251593732779515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Buege, Emily A. 0000-0002-9141-529X","orcid":"https://orcid.org/0000-0002-9141-529X","contributorId":245987,"corporation":false,"usgs":false,"family":"Buege","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":807454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Praskievicz, Sarah J. 0000-0002-9380-7625","orcid":"https://orcid.org/0000-0002-9380-7625","contributorId":245989,"corporation":false,"usgs":false,"family":"Praskievicz","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":49396,"text":"University of North Carolina-Greensboro","active":true,"usgs":false}],"preferred":false,"id":807456,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217066,"text":"70217066 - 2021 - Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina","interactions":[],"lastModifiedDate":"2021-06-30T17:41:53.333707","indexId":"70217066","displayToPublicDate":"2020-12-20T06:35:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina","docAbstract":"Following centuries of declines, there is growing interest in conserving extant wild populations and reintroducing Brook Trout (Salvelinus fontinalis) populations of native ancestry. A population genetic baseline can enhance conservation outcomes and promote restoration success. Consequently, it is important to document existing patterns of genetic variation across the landscape and translate these data into an approachable format for fisheries managers. We genotyped 9,507 Brook Trout representing 467 wild collections at 12 microsatellite loci to establish a genetic baseline for North Carolina, USA. Rarefied allelic richness and observed heterozygosity, which reflect within‐population diversity, were low to moderate relative to levels typically observed at higher latitudes (means = 3.12 and 0.42, respectively). Effective population sizes varied widely, but were often very low (151 collections with an estimated Ne < 10). Despite decades of intensive stocking across the state, we found little to no evidence of hatchery introgression in most populations. Although genetic variation was significant at a variety of spatial scales (mean pairwise F’ST = 0.73), substantial genetic variation occurred between patches within individual watersheds. Analysis of molecular variance (AMOVA) found that a substantial portion (28.5%) of the observed genetic variation was attributed to differences among populations, with additional genetic variation among hydrological units (HUCs; 16.0%, 16.6%, 12.1%, and 9.4% of the overall variation among twelve‐, ten‐, eight‐, and six‐digit HUCs, respectively). We discuss a suite of potential applications for this type of genetic data to enhance management outcomes, such as conservation prioritization and selection of source stocks for reintroductions or genetic rescue.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10569","usgsCitation":"Kazyak, D., Lubinski, B.A., Rash, J.M., Johnson, T.C., and King, T.L., 2021, Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina: North American Journal of Fisheries Management, v. 41, no. 3, p. 626-638, https://doi.org/10.1002/nafm.10569.","productDescription":"13 p.","startPage":"626","endPage":"638","ipdsId":"IP-101589","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":381793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.860595703125,\n 36.53612263184686\n ],\n [\n -81.7822265625,\n 36.63316209558658\n ],\n [\n -83.84765625,\n 35.460669951495305\n ],\n [\n -84.375,\n 35.02999636902566\n ],\n [\n -81.03515625,\n 35.28150065789119\n ],\n [\n -80.7275390625,\n 34.813803317113155\n ],\n [\n -79.4970703125,\n 34.813803317113155\n ],\n [\n -78.44238281249999,\n 33.797408767572485\n ],\n [\n -76.2451171875,\n 34.994003757575776\n ],\n [\n -75.7177734375,\n 35.817813158696616\n ],\n [\n -75.860595703125,\n 36.53612263184686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":807465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":807466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rash, Jacob M","contributorId":218128,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","email":"","middleInitial":"M","affiliations":[{"id":39760,"text":"Division of Inland Fisheries, North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":807467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Thomas C","contributorId":245999,"corporation":false,"usgs":false,"family":"Johnson","given":"Thomas","email":"","middleInitial":"C","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":807468,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Timothy L.","contributorId":199023,"corporation":false,"usgs":false,"family":"King","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":807469,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218000,"text":"70218000 - 2021 - A global perspective on the influence of the COVID-19 pandemic on freshwater fish biodiversity","interactions":[],"lastModifiedDate":"2021-02-11T19:35:21.921623","indexId":"70218000","displayToPublicDate":"2020-12-19T13:31:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A global perspective on the influence of the COVID-19 pandemic on freshwater fish biodiversity","docAbstract":"The COVID-19 global pandemic and resulting effects on the economy and society (e.g., sheltering-in-place, alterations in transportation, changes in consumer behaviour, loss of employment) have yielded some benefits and risks to biodiversity. Here, we considered the ways the COVID-19 pandemic has influenced (or may influence) freshwater fish biodiversity (e.g., richness, abundance). In many cases, we could only consider potential impacts using documented examples (often from the media) of likely changes, because anecdotal observations are still emerging and data-driven studies are yet to be completed or even undertaken. We evaluated the potential for the pandemic to either mitigate or amplify widely acknowledged, pre-existing threats to freshwater fish biodiversity (i.e., invasive species, pollution, fragmentation, flow alteration, habitat loss and alteration, climate change, exploitation). Indeed, we identified examples spanning the extremes of positive and negative outcomes for almost all known threats. We also considered the pandemic's impact on freshwater fisheries demand, assessment, research, compliance monitoring, and management interventions (e.g., restoration), with disruptions being experienced in all domains. Importantly, we provide a forward-looking synthesis that considers the potential mechanisms and pathways by which the consequences of the pandemic may positively and negatively impact freshwater fishes over the longer term. We conclude with a candid assessment of the current management and policy responses and the extent to which they ensure freshwater fish populations and biodiversity are conserved for human and aquatic ecosystem benefits in perpetuity.
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Conservation opportunities for these subspecies are limited and costly. Consequently, well‐targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30‐m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post‐storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. 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Evaluating changes to streamflow, including flood characteristics, across this large and diverse environment can be improved by identifying the distribution and influence of flow drivers. Using metrics of mean monthly streamflow data from 253 streamgages, seasonal flow regimes were clustered to guide identification of seasonal‐flow drivers and form hydrologic groups for identification of peak‐flow populations. Nine seasonally distinct subclasses described variability within three classes dominated by (mostly fall) rainfall, (spring) snowmelt, and (summer) high‐elevation melt. The most glacierized basins exclusively grouped into high‐elevation melt subclasses, and less glacierized basins sometimes exhibited seasonal patterns aligned with rainfall‐ and snowmelt‐dominated regimes. Peak‐flow populations varied by subclass from dominant rainfall or dominant snowmelt to mixed rainfall‐snowmelt or mixed rainfall, snowmelt, and high‐elevation melt. Within subclasses, rainfall generated higher mean peak flows (relative to mean annual flow) than snowmelt or high‐elevation melt. Seasonal flow regimes showed clear but complex associations with basin characteristics, primarily elevation and winter temperature, and with geographic location. These dependencies provided elevation‐based analogies for changes associated with warming and insights for seasonal flow regime prediction and hydrologic region delineation. These results provide a spatially comprehensive perspective on seasonal streamflow drivers across Alaska from historical data and serve as an important historical basis for analysis.
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Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":807827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biles, Frances E. 0000-0002-7298-2811","orcid":"https://orcid.org/0000-0002-7298-2811","contributorId":247517,"corporation":false,"usgs":false,"family":"Biles","given":"Frances","email":"","middleInitial":"E.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":807828,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217163,"text":"70217163 - 2021 - Characterizing physical properties of streambed interface sediments using in situ complex electrical conductivity measurements","interactions":[],"lastModifiedDate":"2021-02-17T21:51:47.504261","indexId":"70217163","displayToPublicDate":"2020-12-17T08:11:24","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":"Characterizing physical properties of streambed interface sediments using in situ complex electrical conductivity measurements","docAbstract":"Streambed sediment physical properties such as surface area, are difficult to quantify in situ but exert a high‐level control on a wide range of biogeochemical processes and sorption of contaminants. We introduce the use of complex electrical conductivity (CC) methods (also known as spectral induced polarization (SIP)) that measure both real and imaginary conductivity to non‐invasively and efficiently characterize shallow streambed sediments. We explore the method through synthetic modeling, laboratory, and field measurements to demonstrate the sensitivity of imaginary conductivity to sediment surface area, controlled in part by fine‐grained iron oxides produced by anoxic groundwater discharge. Laboratory measurements verify expected relationships between CC parameters and sediment properties. Synthetic modeling using a 1D analytical model illustrates the influence of water layer depth and conductivity on the field CC measurements made at the streambed‐stream water interface. Specifically, the inverted sediment imaginary conductivity is less impacted by uncertainty in the water layer depth and conductivity relative to the real conductivity and phase shift. Field CC measurements along a landfill‐impacted river reveal discrete streambed zones with enhanced bulk surface area generally corresponding to anoxic groundwater discharges zones with high concentrations of fine‐grained iron oxide precipitates.
A new quantitative mineral resource assessment for tungsten, a critical mineral commodity with highly concentrated production and a moderate risk of global supply disruption, was conducted for the Great Basin region of western Nevada and eastern California. This assessment was part of a larger effort focusing on three regions in the United States and represents the first study of domestic tungsten resources and mineral potential in over twenty years. By integrating geology, bedrock and stream sediment geochemistry, geophysics, and remote sensing data with recently developed software tools and analyses, estimates of undiscovered tungsten skarn deposits in permissive tracts are combined with grade and tonnage distributions of known deposits to generate probabilistic estimates of undiscovered resources. Identified resources in the Great Basin region total 168 thousand metric tons (kt) of tungsten trioxide (WO3), including 116 kt of past production and 52 kt remaining in place. Consistent with the historic significance of the Great Basin region as a past producer containing a large portion of U.S. identified resources, undiscovered resources are likely to occur adjacent to known deposits and prospects and at unexplored depths. Undiscovered deposits are estimated to contain median resources of 940 kt of WO3 with a 90% probability of at least 420 kt and a 10% probability of at least 1.7 million metric tons (Mt), of which 240 kt to 1.1 Mt may be economic to extract. Based on a 20-year average price, median recoverable undiscovered resources are estimated at 570 kt WO3 equivalent with a net present value of $3 billion U.S. dollars. The methods, data, results, and economic significance of the assessment contribute to a scientific understanding of a critical mineral resource with direct implications for policy and land management decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2020.106712","usgsCitation":"Lederer, G.W., Solano, F., Coyan, J.A., Denton, K., Watts, K., Mercer, C.N., Bickerstaff, D., and Granitto, M., 2021, Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California: Journal of Geochemical Exploration, v. 223, 106712, 24 p., https://doi.org/10.1016/j.gexplo.2020.106712.","productDescription":"106712, 24 p.","ipdsId":"IP-119992","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488120,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gexplo.2020.106712","text":"Publisher Index Page"},{"id":436615,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D1KQGR","text":"USGS data release","linkHelpText":"Tungsten skarn mineral resource assessment of the Great Basin region 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Water managers are concerned with the impacts of warming on water year streamflow, but uncertainties in projections of climate make the application of these projections to planning a challenge. Instead, water managers considered a plausible scenario for future drought to be historical droughts to which warming is added. We used a simple statistical model of water year streamflow with temperatures increased by 1 °C to 4 °C, and then examined reductions in flow and runoff efficiency (RE) with each degree of warming for the six droughts defined in the observed streamflow record. In order to place these results into a management context, we employed an existing framework for system reliability, and in particular, a vulnerability assessment for water delivery metrics. Using modeled streamflow resulting from 1 °C to 4 °C warming, we found vulnerable condition thresholds for the two water delivery metrics assessed, Upper Basin Shortage and Lees Ferry Deficit, were crossed relatively infrequently at +1 °C, but with a substantially increased frequency under additional warming. Results are more relevant to resource management because the impacts of warming on Upper Colorado River streamflow were assessed in the context of management metrics and vulnerability thresholds, in collaboration with members of the water management community of practice.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cliser.2020.100206","usgsCitation":"Woodhouse, C.A., Smith, R.M., McAfee, S., Pederson, G.T., McCabe, G.J., Miller, W.P., and Csank, A., 2021, Upper Colorado River Basin 20th century droughts under 21st century warming: Plausible scenarios for the future: Climate Services, v. 21, 100206, 11 p., https://doi.org/10.1016/j.cliser.2020.100206.","productDescription":"100206, 11 p.","ipdsId":"IP-118594","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cliser.2020.100206","text":"Publisher Index Page"},{"id":383249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming, Utah, Colorado, New Mexico, Arizona","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 44.731125592643274\n ],\n [\n -111.1376953125,\n 42.114523952464246\n ],\n [\n -112.78564453124999,\n 41.902277040963696\n ],\n [\n -112.6318359375,\n 38.03078569382294\n ],\n [\n -111.9287109375,\n 36.756490329505176\n ],\n [\n -110.1708984375,\n 35.8356283888737\n ],\n [\n -106.63330078125,\n 35.55010533588552\n ],\n [\n -106.787109375,\n 35.88905007936091\n ],\n [\n -104.83154296875,\n 38.77121637244273\n ],\n [\n -104.96337890625,\n 40.93011520598305\n ],\n [\n -111.0498046875,\n 44.731125592643274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":810260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Rebecca M.","contributorId":250719,"corporation":false,"usgs":false,"family":"Smith","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":810261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":810262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":810264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, W. 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Dams provide water security, however, the allocation of dwindling water supply among reservoirs could exacerbate or ameliorate the effects of climate change on aquatic communities. Here, we show that the relative sensitivity of river thermal regimes to direct impacts of climate change and societal decisions concerning water storage vary substantially throughout a river basin. In the absence of interspecific interactions, future Colorado River temperatures would appear to benefit both endemic and nonnative fish species. However, endemic species are already declining or extirpated in locations where their ranges overlap with warmwater nonnatives and changes in water storage may lead to warming in some of the coolest portions of the river basin, facilitating further nonnative expansion. Integrating environmental considerations into ongoing water storage negotiations may lead to better resource outcomes than mitigating nonnative species impacts after the fact.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2279","usgsCitation":"Dibble, K.L., Yackulic, C., Kennedy, T., Bestgen, K.R., and Schmidt, J.C., 2021, Water storage decisions will determine the distribution and persistence of imperiled river fishes: Ecological Applications, v. 31, no. 2, e02279, 9 p., https://doi.org/10.1002/eap.2279.","productDescription":"e02279, 9 p.","ipdsId":"IP-098535","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454067,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2279","text":"Publisher Index Page"},{"id":436617,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HFKV7Q","text":"USGS data release","linkHelpText":"Water temperature models, data and code for the Colorado, Green, San Juan, Yampa, and White rivers in the Colorado River basin"},{"id":436616,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HFKV7Q","text":"USGS data release","linkHelpText":"Water temperature models, data and code for the Colorado, Green, San Juan, Yampa, and White rivers in the Colorado River basin"},{"id":381641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bestgen, Kevin R. 0000-0001-8691-2227","orcid":"https://orcid.org/0000-0001-8691-2227","contributorId":171573,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":807280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807281,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222932,"text":"70222932 - 2021 - The normal faulting 2020 Mw5.8 Lone Pine, Eastern California earthquake sequence","interactions":[],"lastModifiedDate":"2021-08-10T14:45:36.085592","indexId":"70222932","displayToPublicDate":"2020-12-16T09:35:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The normal faulting 2020 Mw5.8 Lone Pine, Eastern California earthquake sequence","title":"The normal faulting 2020 Mw5.8 Lone Pine, Eastern California earthquake sequence","docAbstract":"The 2020