{"pageNumber":"533","pageRowStart":"13300","pageSize":"25","recordCount":184828,"records":[{"id":70219219,"text":"70219219 - 2021 - Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression model","interactions":[],"lastModifiedDate":"2021-04-22T17:49:24.950695","indexId":"70219219","displayToPublicDate":"2021-02-24T06:44:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression model","docAbstract":"

Ensemble-tree machine learning (ML) regression models can be prone to systematic bias: small values are overestimated and large values are underestimated. Additional bias can be introduced if the dependent variable is a transform of the original data. Six methods were evaluated for their ability to correct systematic and introduced bias. Method performance was evaluated using four case studies of groundwater quality: the units of the dependent variable were pH in two and log-concentration in the others. When performance metrics (bias and RMSE for both points and the CDF) were computed using the same units as those in the ML model, empirical distribution matching (EDM) provided the best results. When the metrics were computed using retransformed concentration, EDM and a method incorporating Duan's smearing estimate were both effective. A method based on the Z-score transform approximates EDM if the correlation coefficient between rank-ordered ML estimates and rank-ordered observations approaches one.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105006","usgsCitation":"Belitz, K., and Stackelberg, P.E., 2021, Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression model: Environmental Modeling and Software, v. 139, 105006, 12 p., https://doi.org/10.1016/j.envsoft.2021.105006.","productDescription":"105006, 12 p.","ipdsId":"IP-122742","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":453331,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105006","text":"Publisher Index Page"},{"id":436490,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LCTYI2","text":"USGS data release","linkHelpText":"Data Release for Evaluation of Six Methods for Correcting Bias in Estimates from Ensemble Tree Machine Learning Regression Models"},{"id":384773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":813265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":813266,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225728,"text":"70225728 - 2021 - Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado","interactions":[],"lastModifiedDate":"2021-11-05T11:44:16.72004","indexId":"70225728","displayToPublicDate":"2021-02-24T06:36:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado","docAbstract":"

Loch Vale watershed was instrumented in 1983 with initial support from the National Acid Precipitation Assessment Program to ask whether ecosystems of Rocky Mountain National Park (RMNP) were affected by acidic atmospheric deposition. Research and monitoring activities were expanded in 1991 by the U.S. Geological Survey Water, Energy, and Biogeochemical Budgets program to understand the processes, and their interactions, controlling water, energy, and biogeochemical fluxes. With help from many collaborators we have characterized trends and patterns in atmospheric deposition, climate, and hydrology, including glaciers and other ice features. Instead of acidic deposition, we documented high atmospheric inputs of reactive nitrogen (Nr), and have studied the ecological consequences in soils, surface water, and vegetation. Using paleolimnology, we documented the onset of human-caused change to lake primary producers ca. 1950 in response to increased Nr deposition and warming. Our results provided the basis for the Colorado Nitrogen Deposition Reduction Plan, a state policy that aims to reduce Nr emissions to protect resources in RMNP by 2032. Carbon cycle research revealed mountain wetlands now release more carbon than they store, and respiration and methane flux occurs even during winter through deep snow packs. Trend analyses found export of Nr to be closely tied to atmospheric inputs, but can lag in response to drought. Current research explores consequences of the combination of warming, changes in precipitation dynamics, and atmospheric deposition of Nr and dust on stream and lake CO2 dynamics, lake biology and trophic state, and soil carbon composition. Dramatic increases in park visitors have prompted studies on the effects of recreational use on water quality. New tools such as remote sensing and high frequency instream water quality sensors are being applied to lake and stream studies. Monitoring, combined with experiments, models, and spatial comparisons is an essential foundation for science-based resource management.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14107","usgsCitation":"Baron, J., Clow, D.W., Oleksy, I., Weinmann, T., Charlton, C., and Jayo, A., 2021, Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado: Hydrological Processes, v. 35, no. 3, e14107, 5 p., https://doi.org/10.1002/hyp.14107.","productDescription":"e14107, 5 p.","ipdsId":"IP-123087","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":391419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park, Loch Vale","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.35314941406249,\n 39.47860556892209\n ],\n [\n -105.14465332031249,\n 39.47860556892209\n ],\n [\n -105.14465332031249,\n 40.40931350359072\n ],\n [\n -106.35314941406249,\n 40.40931350359072\n ],\n [\n -106.35314941406249,\n 39.47860556892209\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oleksy, Isabella A.","contributorId":268330,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella A.","affiliations":[{"id":33412,"text":"Cary Institute for Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":826425,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weinmann, Timothy 0000-0003-1502-5254","orcid":"https://orcid.org/0000-0003-1502-5254","contributorId":268331,"corporation":false,"usgs":true,"family":"Weinmann","given":"Timothy","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826426,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charlton, Caitlin","contributorId":268332,"corporation":false,"usgs":false,"family":"Charlton","given":"Caitlin","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":826427,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jayo, Amanda","contributorId":268333,"corporation":false,"usgs":false,"family":"Jayo","given":"Amanda","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":826428,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222588,"text":"70222588 - 2021 - No ring fracture in Mono Basin, California","interactions":[],"lastModifiedDate":"2021-09-14T16:47:00.411507","indexId":"70222588","displayToPublicDate":"2021-02-24T06:36:26","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":"No ring fracture in Mono Basin, California","docAbstract":"

In Mono Basin, California, USA, a near-circular ring fracture 12 km in diameter was proposed by R.W. Kistler in 1966 to have originated as the protoclastic margin of the Cretaceous Aeolian Buttes pluton, to have been reactivated in the middle Pleistocene, and to have influenced the arcuate trend of the chain of 30 young (62−0.7 ka) rhyolite domes called the Mono Craters. In view of the frequency and recency of explosive eruptions along the Mono chain, and because many geophysicists accepted the ring fracture model, we assembled evidence to test its plausibility. The shear zone interpreted as the margin of the Aeolian Buttes pluton by Kistler is 50−400 m wide but is exposed only along a 7-km-long set of four southwesterly outcrops that subtend only a 70° sector of the proposed ring. The southeast end of the exposed shear zone is largely within the older June Lake pluton, and at its northwest end, the contact of the Aeolian Buttes pluton with a much older one crosses the shear zone obliquely. Conflicting attitudes of shear structures are hard to reconcile with intrusive protoclasis. Also inconsistent with the margin of the ovoid intrusion proposed by Kistler, unsheared salients of the pluton extend ∼1 km north of its postulated circular outline at Williams Butte, where there is no fault or other structure to define the northern half of the hypothetical ring. The shear zone may represent regional Cretaceous transpression rather than the margin of a single intrusion. There is no evidence for the Aeolian Buttes pluton along the aqueduct tunnel beneath the Mono chain, nor is there evidence for a fault that could have influenced its vent pattern. The apparently arcuate chain actually consists of three linear segments that reflect Quaternary tectonic influence and not Cretaceous inheritance. A rhyolitic magma reservoir under the central segment of the Mono chain has erupted many times in the late Holocene and as recently as 700 years ago. The ring fracture idea, however, prompted several geophysical investigations that sought a much broader magma body, but none identified a low-density or low-velocity anomaly beneath the purported 12-km-wide ring, which we conclude does not exist.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35747.1","usgsCitation":"Hildreth, E., Fierstein, J., and Ryan-Davis, J., 2021, No ring fracture in Mono Basin, California: Geological Society of America Bulletin, v. 133, no. 9-10, p. 2210-2225, https://doi.org/10.1130/B35747.1.","productDescription":"16 p.","startPage":"2210","endPage":"2225","ipdsId":"IP-118844","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b35747.1","text":"Publisher Index Page"},{"id":387731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mono Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.9215087890625,\n 37.86618078529668\n ],\n [\n -118.751220703125,\n 37.86618078529668\n ],\n [\n -118.751220703125,\n 38.039438891821746\n ],\n [\n -118.9215087890625,\n 38.039438891821746\n ],\n [\n -118.9215087890625,\n 37.86618078529668\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"133","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2021-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Edward 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":146999,"corporation":false,"usgs":true,"family":"Hildreth","given":"Edward","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan-Davis, Juliet","contributorId":261795,"corporation":false,"usgs":false,"family":"Ryan-Davis","given":"Juliet","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":820666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218199,"text":"ofr20201149 - 2021 - Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing","interactions":[],"lastModifiedDate":"2021-02-24T12:54:58.879829","indexId":"ofr20201149","displayToPublicDate":"2021-02-23T14:19:37","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1149","displayTitle":"Hydrographic and Benthic Mapping—St. Croix National Scenic Riverway—Osceola Landing","title":"Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing","docAbstract":"

High-resolution topographic and bathymetric mapping can assist in the analysis of river habitat. The National Park Service has been planning to relocate a boat ramp along the St. Croix River in Minnesota, across the river from the town of Osceola, Wisconsin, to improve visitor safety, improve operations for commercial use, enhance the overall visitor experience, and eliminate deferred maintenance at the landing. This landing grants access to the St. Croix River, which is a part of the National Park Service St. Croix National Scenic Riverway. Hydrographic and topographic surveys were needed to determine where the new location should be. The objective for these surveys was to provide baseline information in order to assess the direct effects of the landing relocation on physical habitat in areas adjacent to Osceola, Wisconsin. The study area for these surveys was about 18.5 hectares and located directly off the existing landing. Although the existing boat launch is referred to as the Osceola landing, it is located on the Minnesota side of the river and is the busiest National Park Service landing on the St. Croix River (National Park Service St. Croix National Scenic Riverway, 2020). This report documents methods and results of aquatic benthic mapping in a small area of the St. Croix River.

The hydroacoustic and topographic surveys were collected from October 16–17, 2019. The hydrographic surveys consisted of multibeam and sidescan sound navigation and ranging (sonars). The topographic shoreline survey consisted of light detection and ranging (lidar) captured by boat adjacent to riverbanks. Additionally, an acoustic Doppler current profiler was used to measure flow velocities. The water level was higher than normal, and therefore had faster flow during the hydroacoustic surveys. Multibeam, lidar, and sidescan surveys occurred the first day, and the velocity mapping and ground truthing was conducted the second day. Multibeam and lidar provided derivative datasets that included bathymetry and a topobathy with a spatial resolution of 1 foot. From these data, additional data could be measured including slope and terrain ruggedness. Sidescan (acoustic reflectance measures) provided imagery that was used to help with interpretation of the river bottom.

Outcomes from these combined datasets were substrate and bedform maps. Much of the area was covered in sand ripples or small dunes. A small area running adjacent to the deeper valley or cut down the river consisted of harder substrates, such as cobble and gravel. Large woody debris piles were found throughout the study area. Multiple stationary moving-bed tests were completed, and no corrections were recommended for the conditions occurring during survey. Mussel presence was noted in some of the underwater videos. The physical parameters of depth, flow, bedforms, and substrate derived from the datasets provided baseline measures for a benthic habitat map. Further analysis of benthic habitat might be possible with additional biological and chemical data.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201149","collaboration":"Prepared in cooperation with the National Park Service, the St. Croix National Scenic Riverway, and the Denver Service Center","usgsCitation":"Hanson, J.L., and Strange, J.M., 2021, Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing: U.S. Geological Survey Open-File Report 2020–1149, 26 p., https://doi.org/10.3133/ofr20201149.","productDescription":"Report: vi, 26 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118301","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":383330,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1149/coverthb3.jpg"},{"id":383331,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1149/ofr20201149.pdf","text":"Report","size":"37.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1149"},{"id":383332,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O0QH8B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Saint Croix National Scenic Riverway (SACN)—Osceola boat landing 2019 benthic and bathymetry data"}],"country":"United States","state":"Wisconsin","county":"Osceola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.72460937499999,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.3111146177239\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2021-02-23","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hanson, Jenny L. 0000-0001-8353-6908 jhanson@usgs.gov","orcid":"https://orcid.org/0000-0001-8353-6908","contributorId":461,"corporation":false,"usgs":true,"family":"Hanson","given":"Jenny","email":"jhanson@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Jayme 0000-0002-0512-3072","orcid":"https://orcid.org/0000-0002-0512-3072","contributorId":251712,"corporation":false,"usgs":false,"family":"Stone","given":"Jayme","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":810405,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218477,"text":"70218477 - 2021 - Rangeland fractional components across the western United States from 1985 to 2018","interactions":[],"lastModifiedDate":"2022-02-03T17:59:45.727597","indexId":"70218477","displayToPublicDate":"2021-02-23T10:18:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Rangeland fractional components across the western United States from 1985 to 2018","docAbstract":"

Monitoring temporal dynamics of rangelands to detect and understand change in vegetation cover and composition provides a wealth of information to improve management and sustainability. Remote sensing allows the evaluation of both abrupt and gradual rangeland change at unprecedented spatial and temporal extents. Here, we describe the production of the National Land Cover Database (NLCD) Back in Time (BIT) dataset which quantified the percent cover of rangeland components (bare ground, herbaceous, annual herbaceous, litter, shrub, and sagebrush (Artemisia spp. Nutt.) across the western United States using Landsat imagery from 1985 to 2018. We evaluate the relationships of component trends with climate drivers at an ecoregion scale, describe the nature of landscape change, and demonstrate several case studies related to changes in grazing management, prescribed burns, and vegetation treatments. Our results showed the net cover of shrub, sagebrush, and litter significantly (p < 0.01) decreased, bare ground and herbaceous cover had no significant change, and annual herbaceous cover significantly (p < 0.05) increased. Change was ubiquitous, with a mean of 92% of pixels with some change and 38% of pixels with significant change (p < 0.10). However, most change was gradual, well over half of pixels have a range of less than 10%, and most change occurred outside of known disturbances. The BIT data facilitate a comprehensive assessment of rangeland condition, evaluation of past management actions, understanding of system variability, and opportunities for future planning.

","language":"English","publisher":"MDPI","doi":"10.3390/rs13040813","usgsCitation":"Rigge, M.B., Homer, C., Shi, H., Meyer, D., Bunde, B., Granneman, B.J., Postma, K., Danielson, P., Case, A., and Xian, G.Z., 2021, Rangeland fractional components across the western United States from 1985 to 2018: Remote Sensing, v. 13, no. 4, 813, 24 p., https://doi.org/10.3390/rs13040813.","productDescription":"813, 24 p.","ipdsId":"IP-119778","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":453335,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13040813","text":"Publisher Index Page"},{"id":436491,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ODAZHC","text":"USGS data release","linkHelpText":"Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2021"},{"id":384677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395378,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IQ4BT","text":"USGS data release","description":"USGS data release","linkHelpText":"Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oklahoma, Oregon, South Dakota, Texas, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.4697265625,\n 29.53522956294847\n ],\n [\n -102.6123046875,\n 32.58384932565662\n ],\n [\n -104.1064453125,\n 34.488447837809304\n ],\n [\n -100.0634765625,\n 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0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":238919,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811161,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70223108,"text":"70223108 - 2021 - Decadal-scale hotspot methane ebullition within lakes following abrupt permafrost thaw","interactions":[],"lastModifiedDate":"2021-08-11T13:18:06.415988","indexId":"70223108","displayToPublicDate":"2021-02-23T08:11:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale hotspot methane ebullition within lakes following abrupt permafrost 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Thermokarst lakes accelerate deep permafrost thaw and the mobilization of previously frozen soil organic carbon. This leads to microbial decomposition and large releases of carbon dioxide (CO2) and methane (CH4) that enhance climate warming. However, the time scale of permafrost-carbon emissions following thaw is not well known but is important for understanding how abrupt permafrost thaw impacts climate feedback. We combined field measurements and radiocarbon dating of CH4 ebullition with (a) an assessment of lake area changes delineated from high-resolution (1–2.5 m) optical imagery and (b) geophysical measurements of thaw bulbs (taliks) to determine the spatiotemporal dynamics of hotspot-seep CH4 ebullition in interior Alaska thermokarst lakes. Hotspot seeps are characterized as point-sources of high ebullition that release 14C-depleted CH4 from deep (up to tens of meters) within lake thaw bulbs year-round. Thermokarst lakes, initiated by a variety of factors, doubled in number and increased 37.5% in area from 1949 to 2009 as climate warmed. Approximately 80% of contemporary CH4 hotspot seeps were associated with this recent thermokarst activity, occurring where 60 years of abrupt thaw took place as a result of new and expanded lake areas. Hotspot occurrence diminished with distance from thermokarst lake margins. We attribute older 14C ages of CH4 released from hotspot seeps in older, expanding thermokarst lakes (14CCH4 20 079 ± 1227 years BP, mean ± standard error (s.e.m.) years) to deeper taliks (thaw bulbs) compared to younger 14CCH4 in new lakes (14CCH4 8526 ± 741 years BP) with shallower taliks. We find that smaller, non-hotspot ebullition seeps have younger 14C ages (expanding lakes 7473 ± 1762 years; new lakes 4742 ± 803 years) and that their emissions span a larger historic range. These observations provide a first-order constraint on the magnitude and decadal-scale duration of CH4-hotspot seep emissions following formation of thermokarst lakes as climate warms.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abc848","usgsCitation":"Anthony, K., Lindgren, P., Hanke, P., Engram, M., Anthony, P., Daanen, R., Bondurant, A., Liljedahl, A., Lenz, J., Grosse, G., Jones, B., Brosius, L.S., James, S.R., Minsley, B.J., Pastick, N., Munk, J., Chanton, J., Miller, C., and Meyer, F., 2021, Decadal-scale hotspot methane ebullition within lakes following abrupt permafrost thaw: Environmental Research Letters, v. 16, no. 3, 035010, 22 p., https://doi.org/10.1088/1748-9326/abc848.","productDescription":"035010, 22 p.","ipdsId":"IP-121976","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":453337,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abc848","text":"Publisher Index Page"},{"id":387848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.18359375,\n 64.67091929440798\n ],\n [\n -147.15087890625,\n 64.67091929440798\n ],\n [\n -147.15087890625,\n 64.9793592199603\n ],\n [\n -148.18359375,\n 64.9793592199603\n ],\n [\n -148.18359375,\n 64.67091929440798\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, K.W.","contributorId":264152,"corporation":false,"usgs":false,"family":"Anthony","given":"K.W.","affiliations":[{"id":54390,"text":"Water and Environmental Research Center, University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":820984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindgren, P.","contributorId":264153,"corporation":false,"usgs":false,"family":"Lindgren","given":"P.","email":"","affiliations":[{"id":13662,"text":"Geophysical Institute, University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":820985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanke, P.","contributorId":264154,"corporation":false,"usgs":false,"family":"Hanke","given":"P.","affiliations":[{"id":54391,"text":"Water and Environmental Research Center, University of Alaska, Fairbanks,","active":true,"usgs":false}],"preferred":false,"id":820986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engram, M.","contributorId":264171,"corporation":false,"usgs":false,"family":"Engram","given":"M.","affiliations":[],"preferred":false,"id":821046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anthony, P.","contributorId":147464,"corporation":false,"usgs":false,"family":"Anthony","given":"P.","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":820987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daanen, R.","contributorId":264155,"corporation":false,"usgs":false,"family":"Daanen","given":"R.","email":"","affiliations":[{"id":54392,"text":"Alaska Division of Geological & Geophysical Surveys, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":820988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bondurant, A.","contributorId":192804,"corporation":false,"usgs":false,"family":"Bondurant","given":"A.","affiliations":[],"preferred":false,"id":820989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liljedahl, A.K.","contributorId":264156,"corporation":false,"usgs":false,"family":"Liljedahl","given":"A.K.","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":820990,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lenz, J.","contributorId":257238,"corporation":false,"usgs":false,"family":"Lenz","given":"J.","email":"","affiliations":[{"id":51985,"text":"Alfred Wegener Institut Potsdam","active":true,"usgs":false}],"preferred":false,"id":820991,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grosse, G.","contributorId":192805,"corporation":false,"usgs":false,"family":"Grosse","given":"G.","email":"","affiliations":[],"preferred":false,"id":820992,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, B.M.","contributorId":264172,"corporation":false,"usgs":false,"family":"Jones","given":"B.M.","email":"","affiliations":[],"preferred":false,"id":820993,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brosius, L. 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Groundwater supplies 50% of drinking water worldwide and 30% in the United States. Geogenic and anthropogenic contaminants can, however, compromise water quality, thus limiting groundwater availability. Reduction/oxidation (redox) processes and redox conditions affect groundwater quality by influencing the mobility and transport of common geogenic and anthropogenic contaminants. In the glacial aquifer system, northern United States (GLAC, 1.87 million km2), groundwater with high arsenic or manganese concentration is associated with reducing conditions and high nitrate with oxidizing conditions. This study uses machine learning to identify the relative influence of drivers of redox conditions (e.g., residence time vs. reactivity) across the glacial landscape. We developed three‐dimensional boosted regression tree models to predict redox conditions using the likelihood of low dissolved oxygen or high iron as indicators of anoxic conditions. Results indicate that variation in redox condition is controlled primarily by residence time (e.g., groundwater age and relative depth) and to a lesser extent by geochemical reactivity (e.g., subsurface contact time, soil carbon). Older water and deeper wells, along with more water storage or slower water movement was associated with higher probability of anoxic conditions. Mapped model results illustrate regions where anoxic redox conditions may mobilize geogenic contaminants or oxic conditions may limit denitrification potential. Results may also provide simplified redox input for process or predictive models of, for example, arsenic, manganese, or nitrate. Machine learning modeling methods can lead to improved understanding of contaminant occurrence and what drives redox conditions, and the methods may be transferable to other settings.

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0000-0001-6195-7699","orcid":"https://orcid.org/0000-0001-6195-7699","contributorId":239552,"corporation":false,"usgs":true,"family":"Ransom","given":"Katherine","email":"","middleInitial":"Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reddy, James E. 0000-0002-6998-7267","orcid":"https://orcid.org/0000-0002-6998-7267","contributorId":202976,"corporation":false,"usgs":true,"family":"Reddy","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814864,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219245,"text":"70219245 - 2021 - Interrupted incubation: How dabbling ducks respond when flushed from the nest","interactions":[],"lastModifiedDate":"2021-04-01T12:22:55.712253","indexId":"70219245","displayToPublicDate":"2021-02-23T07:20:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Interrupted incubation: How dabbling ducks respond when flushed from the nest","docAbstract":"

Nesting birds must provide a thermal environment sufficient for egg development while also meeting self‐maintenance needs. Many birds, particularly those with uniparental incubation, achieve this balance through periodic incubation recesses, during which foraging and other self‐maintenance activities can occur. However, incubating birds may experience disturbances such as predator or human activity which interrupt natural incubation patterns by compelling them to leave the nest. We characterized incubating mallard Anas platyrhynchos and gadwall Mareca strepera hens’ responses when flushed by predators and investigators in Suisun Marsh, California, USA. Diurnal incubation recesses initiated by investigators approaching nests were 63% longer than natural diurnal incubation recesses initiated by the hen (geometric mean: 226.77 min versus 142.04 min). Nocturnal incubation recesses, many of which were likely the result of predators flushing hens, were of similar duration regardless of whether the nest was partially depredated during the event (115.33 [101.01;131.68] minutes) or not (119.62 [111.96;127.82] minutes), yet were 16% shorter than natural diurnal incubation recesses. Hens moved further from the nest during natural diurnal recesses or investigator‐initiated recesses than during nocturnal recesses, and the proportion of hen locations recorded in wetland versus upland habitat during recesses varied with recess type (model‐predicted means: natural diurnal recess 0.77; investigator‐initiated recess 0.82; nocturnal recess 0.31). Hens were more likely to take a natural recess following an investigator‐initiated recess earlier that same day than following a natural recess earlier that same day, and natural recesses that followed an investigator‐initiated recess were longer than natural recesses that followed an earlier natural recess, suggesting that hens may not fulfill all of their physiological needs during investigator‐initiated recesses. We found no evidence that the duration of investigator‐initiated recesses was influenced by repeated visits to the nest, whether by predators or by investigators, and trapping and handling the hen did not affect investigator‐initiated recess duration unless the hen was also fitted with a backpack‐harness style GPS–GSM transmitter at the time of capture. Hens that were captured and fitted with GPS–GSM transmitters took recesses that were 26% longer than recesses during which a hen was captured but a GPS–GSM transmitter was not attached. Incubation interruptions had measurable but limited and specific effects on hen behavior.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7245","usgsCitation":"Croston, R., Hartman, C.A., Herzog, M.P., Peterson, S.H., Kohl, J., Overton, C.T., Feldheim, C.L., Casazza, M.L., and Ackerman, J.T., 2021, Interrupted incubation: How dabbling ducks respond when flushed from the nest: Ecology and Evolution, v. 11, no. 6, p. 2862-2872, https://doi.org/10.1002/ece3.7245.","productDescription":"11 p.","startPage":"2862","endPage":"2872","ipdsId":"IP-122110","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453339,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7245","text":"External Repository"},{"id":436493,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JXF6J3","text":"USGS data release","linkHelpText":"How Mallard and Gadwall Hens Nesting in Grizzly Island Wildlife Area Respond when Flushed (2015 - 2018)"},{"id":384799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Croston, Rebecca 0000-0003-4696-0878","orcid":"https://orcid.org/0000-0003-4696-0878","contributorId":256911,"corporation":false,"usgs":false,"family":"Croston","given":"Rebecca","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":813395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kohl, Jeffrey","contributorId":256914,"corporation":false,"usgs":false,"family":"Kohl","given":"Jeffrey","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":813399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813400,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":813401,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813402,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813403,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70218500,"text":"70218500 - 2021 - Atmospheric nitrogen deposition in the Chesapeake Bay watershed: A history of change","interactions":[],"lastModifiedDate":"2021-07-02T13:34:45.078734","indexId":"70218500","displayToPublicDate":"2021-02-23T06:47:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric nitrogen deposition in the Chesapeake Bay watershed: A history of change","docAbstract":"

The Chesapeake Bay watershed has been the focus of pioneering studies of the role of atmospheric nitrogen (N) deposition as a nutrient source and driver of estuarine trophic status. Here, we review the history and evolution of scientific investigations of the role of atmospheric N deposition, examine trends from wet and dry deposition networks, and present century-long (1950–2050) atmospheric N deposition estimates. Early investigations demonstrated the importance of atmospheric deposition as an N source to the Bay, providing 25%–40% among all major N sources. These early studies led to the unprecedented inclusion of targeted decreases in atmospheric N deposition as part of the multi-stakeholder effort to reduce N loads to the Bay. Emissions of nitrogen oxides (NOx) and deposition of wet nitrate, oxidized dry N, and dry ammonium (NH4+) sharply and synchronously declined by 60%–73% during 1995–2019. These decreases largely resulted from implementation of Title IV of the 1990 Clean Air Act Amendments, which began in 1995. Wet NH4+ deposition shows no significant trend during this period. The century-long atmospheric N deposition estimates indicate an increase in total atmospheric N deposition in the Chesapeake watershed from 1950 to a peak of ~15 kg N/ha/yr in 1979, trailed by a slight decline of <10% through the mid-1990s, and followed by a sharp decline of about 40% thereafter through 2019. An additional 21% decline in atmospheric N deposition is projected from 2015 to 2050. A comparison of the Potomac River and James River watersheds indicates higher atmospheric N deposition in the Potomac, likely resulting from greater emissions from higher proportions of agricultural and urban land in this basin. Atmospheric N deposition rose from 30% among all N sources to the Chesapeake Bay watershed in 1950 to a peak of 40% in 1973, and a decline to 28% by 2015. These data highlight the important role of atmospheric N deposition in the Chesapeake Bay watershed and present a potential opportunity for decreases in deposition to contribute to further reducing N loads and improving the trophic status of tidal waters.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2021.118277","usgsCitation":"Burns, D., Bhatt, G., Linker, L.C., Bash, J., Capel, P., and Shenk, G.W., 2021, Atmospheric nitrogen deposition in the Chesapeake Bay watershed: A history of change: Atmospheric Environment, v. 251, 118277, 12 p., https://doi.org/10.1016/j.atmosenv.2021.118277.","productDescription":"118277, 12 p.","ipdsId":"IP-116699","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453341,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2021.118277","text":"Publisher Index Page"},{"id":436494,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P953SO6P","text":"USGS data release","linkHelpText":"Nitrogen sources to and export from the Chesapeake Bay watershed, 1950 to 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A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":811211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhatt, Gopal 0000-0002-6627-793X","orcid":"https://orcid.org/0000-0002-6627-793X","contributorId":252963,"corporation":false,"usgs":false,"family":"Bhatt","given":"Gopal","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":811212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":811213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bash, Jesse 0000-0001-8736-0102","orcid":"https://orcid.org/0000-0001-8736-0102","contributorId":252965,"corporation":false,"usgs":false,"family":"Bash","given":"Jesse","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":811214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Capel, Paul 0000-0003-1620-5185","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":252966,"corporation":false,"usgs":false,"family":"Capel","given":"Paul","affiliations":[{"id":27811,"text":"Univ. of Minnesota","active":true,"usgs":false}],"preferred":false,"id":811215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shenk, Gary W. 0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811216,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223867,"text":"70223867 - 2021 - Temporal influences on selenium partitioning, trophic transfer, and exposure in a major U.S. river","interactions":[],"lastModifiedDate":"2021-09-10T16:56:34.608508","indexId":"70223867","displayToPublicDate":"2021-02-22T11:48:13","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":"Temporal influences on selenium partitioning, trophic transfer, and exposure in a major U.S. river","docAbstract":"

Hydrologic and irrigation regimes mediate the timing of selenium (Se) mobilization to rivers, but the extent to which patterns in Se uptake and trophic transfer through recipient food webs reflect the temporal variation in Se delivery is unknown. We investigated Se mobilization, partitioning, and trophic transfer along approximately 60 river miles of the selenium-impaired segment of the Lower Gunnison River (Colorado, USA) during six sampling trips between June 2015 and October 2016. We found temporal patterns in Se partitioning and trophic transfer to be independent of those in dissolved Se concentrations and that the recipient food web sustained elevated Se concentrations from earlier periods of high Se mobilization. Using an ecosystem-scale Se accumulation model tailored to the Lower Gunnison River, we predicted that the endangered Razorback Sucker (Xyrauchen texanus) and Colorado Pikeminnow (Ptychocheilus lucius) achieve whole-body Se concentrations exceeding aquatic life protection criteria during periods of high runoff and irrigation activity (April–August) that coincide with susceptible phases of reproduction and early-life development. The results of this study challenge assumptions about Se trophodynamics in fast-flowing waters and introduce important considerations for the management of Se risks for biota in river ecosystems.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06582","usgsCitation":"Brandt, J., Roberts, J., Stricker, C.A., Rogers, H., Nease, P., and Schmidt, T., 2021, Temporal influences on selenium partitioning, trophic transfer, and exposure in a major U.S. river: Environmental Science and Technology, v. 55, no. 6, p. 3645-3656, https://doi.org/10.1021/acs.est.0c06582.","productDescription":"12 p.","startPage":"3645","endPage":"3656","ipdsId":"IP-122278","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":453343,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.0c06582","text":"Publisher Index Page"},{"id":436495,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TD4THX","text":"USGS data release","linkHelpText":"Dataset for temporal influences on selenium partitioning, trophic transfer, and exposure in a major U.S. river"},{"id":389070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.666,\n 38.0\n ],\n [\n -107.25,\n 38.0\n ],\n [\n -107.25,\n 39.16666667\n ],\n [\n -108.666,\n 39.16666667\n ],\n [\n -108.666,\n 38.0\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Brandt, Jessica E","contributorId":257351,"corporation":false,"usgs":false,"family":"Brandt","given":"Jessica E","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":823037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, James J. 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":823039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Holly hrogers@usgs.gov","contributorId":174358,"corporation":false,"usgs":true,"family":"Rogers","given":"Holly","email":"hrogers@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":823040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nease, Patricia","contributorId":265586,"corporation":false,"usgs":false,"family":"Nease","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":823041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":823042,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223864,"text":"70223864 - 2021 - Redefining the age of the lower Colorado River, southwestern United States","interactions":[],"lastModifiedDate":"2021-09-10T16:43:01.309017","indexId":"70223864","displayToPublicDate":"2021-02-22T11:26:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Redefining the age of the lower Colorado River, southwestern United States","docAbstract":"

Sanidine dating and magnetostratigraphy constrain the timing of integration of the lower Colorado River (southwestern United States and northern Mexico) with the evolving Gulf of California. The Colorado River arrived at Cottonwood Valley (Nevada and Arizona) after 5.24 Ma (during or after the Thvera subchron). The river reached the proto–Gulf of California once between 4.80 and 4.63 Ma (during the C3n.2r subchron), not at 5.3 Ma and 5.0 Ma as previously proposed. Duplication of section across newly identified strands of the Earthquake Valley fault zone (California) probably explains the discrepancy. The data also imply the start of focused plate motion and basin development in the Salton Trough (California) at 6–6.5 Ma and relative tectonic stability of the southernmost part of the lower Colorado River corridor after its integration. After integration, the Colorado River quickly incised through sediment-filled basins and divides between them as it also likely excavated Grand Canyon (Arizona). The liberated sediment from throughout the system led to deposition of hundreds of meters of Bullhead Alluvium downstream of Grand Canyon after 4.6 Ma as the river adjusted to its lower base level.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G48080.1","usgsCitation":"Crow, R.S., Schwing, J., Karlstrom, K.E., Heizler, M., Pearthree, P., House, P., Dulin, S., Janecke, S.U., Stelten, M.E., and Crossey, L.J., 2021, Redefining the age of the lower Colorado River, southwestern United States: Geology, v. 49, no. 6, p. 635-640, https://doi.org/10.1130/G48080.1.","productDescription":"6 p.","startPage":"635","endPage":"640","ipdsId":"IP-111384","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":389069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Nevada","otherGeospatial":"lower Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.01562499999999,\n 31.55981453201843\n ],\n [\n -114.136962890625,\n 31.55981453201843\n ],\n [\n -114.136962890625,\n 36.589068371399115\n ],\n [\n -116.01562499999999,\n 36.589068371399115\n ],\n [\n -116.01562499999999,\n 31.55981453201843\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Crow, Ryan S. 0000-0002-2403-6361 rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":823024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwing, J.","contributorId":265583,"corporation":false,"usgs":false,"family":"Schwing","given":"J.","email":"","affiliations":[],"preferred":false,"id":823025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karlstrom, K. E.","contributorId":45713,"corporation":false,"usgs":true,"family":"Karlstrom","given":"K.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":823026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heizler, M.","contributorId":265584,"corporation":false,"usgs":false,"family":"Heizler","given":"M.","email":"","affiliations":[],"preferred":false,"id":823027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearthree, P. A.","contributorId":77236,"corporation":false,"usgs":false,"family":"Pearthree","given":"P. A.","affiliations":[],"preferred":false,"id":823028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"House, P. K.","contributorId":127342,"corporation":false,"usgs":false,"family":"House","given":"P. K.","affiliations":[{"id":6783,"text":"Geology, Minerals, Energy, and Geophysics Program, U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":823029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dulin, S.","contributorId":265585,"corporation":false,"usgs":false,"family":"Dulin","given":"S.","email":"","affiliations":[],"preferred":false,"id":823030,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Janecke, S. U.","contributorId":42296,"corporation":false,"usgs":true,"family":"Janecke","given":"S.","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":823031,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823032,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crossey, L. J.","contributorId":192301,"corporation":false,"usgs":false,"family":"Crossey","given":"L.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":823033,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70218256,"text":"70218256 - 2021 - Evaluating fish rescue as a drought adaptation strategy using a life cycle modeling approach for imperiled coho salmon","interactions":[],"lastModifiedDate":"2021-02-22T14:36:57.130166","indexId":"70218256","displayToPublicDate":"2021-02-22T08:30:32","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":"Evaluating fish rescue as a drought adaptation strategy using a life cycle modeling approach for imperiled coho salmon","docAbstract":"

Projected intensification of drought as a result of climate change may reduce the capacity of streams to rear fish, exacerbating the challenge of recovering salmonid populations listed under the Endangered Species Act. Without management intervention, some stocks will likely go extinct as stream drying and fragmentation reduce juvenile survival to unsustainable levels. To offset drought‐related mortality, fish rescue programs have proliferated, whereby juvenile salmonids are captured and transferred to off‐site rearing facilities. However, the efficacy of this potential conservation tool remains poorly understood. We developed a life cycle model to examine the implications of fish rescue on the abundance of Coho Salmon Oncorhynchus kisutch across serial life stages. The simulation model examines scenarios with varying quantities of rescued fish, time in captivity, drought severity, and reduced smolt‐to‐adult return rates. Our results indicate that fish rescue can increase the abundance of adults and lower extinction risk, particularly for fish held in captivity for a full year. However, fish rescue can also decrease the abundance of adults and increase extinction risk if fish are held only for summer and there is limited winter habitat. We found that when fish rescue did increase returns, it functioned more like a stock enhancement program than a drought mitigation tool and it would likely lead to consecutive generations of captive rearing, which has been shown to have negative effects on fitness. We translated our model into an R Shiny application (https://shiny.wdfw‐fish.us/CohoPopulationDynamics/) that allows users to explore how fish rescue affects Coho Salmon population dynamics through customized parameterization of the model to represent different systems or different assumptions about the effects of fish rescue.

","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10532","usgsCitation":"Beebe, B.A., Bentley, K.T., Buehrens, T.W., Perry, R., and Armstrong, J.B., 2021, Evaluating fish rescue as a drought adaptation strategy using a life cycle modeling approach for imperiled coho salmon: North American Journal of Fisheries Management, v. 41, no. 1, p. 3-18, https://doi.org/10.1002/nafm.10532.","productDescription":"16 p.","startPage":"3","endPage":"18","ipdsId":"IP-119203","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":383418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Beebe, Brittany A","contributorId":251872,"corporation":false,"usgs":false,"family":"Beebe","given":"Brittany","email":"","middleInitial":"A","affiliations":[{"id":50408,"text":"Department of Fisheries and Wildlife Department, Oregon State University, Corvallis, OR, USA","active":true,"usgs":false}],"preferred":false,"id":810740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bentley, Kale T","contributorId":251873,"corporation":false,"usgs":false,"family":"Bentley","given":"Kale","email":"","middleInitial":"T","affiliations":[{"id":50409,"text":"Fish Science Division, Washington Department of Fish & Wildlife, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":810741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehrens, Thomas W.","contributorId":210018,"corporation":false,"usgs":false,"family":"Buehrens","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":38048,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195","active":true,"usgs":false}],"preferred":false,"id":810750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":223235,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":810742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Jonathan B.","contributorId":251874,"corporation":false,"usgs":false,"family":"Armstrong","given":"Jonathan","email":"","middleInitial":"B.","affiliations":[{"id":50408,"text":"Department of Fisheries and Wildlife Department, Oregon State University, Corvallis, OR, USA","active":true,"usgs":false}],"preferred":false,"id":810743,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220237,"text":"70220237 - 2021 - Discovery of a large subsoil nitrate reservoir in an arroyo floodplain and associated aquifer contamination","interactions":[],"lastModifiedDate":"2021-06-30T18:46:44.051993","indexId":"70220237","displayToPublicDate":"2021-02-22T07:57:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Discovery of a large subsoil nitrate reservoir in an arroyo floodplain and associated aquifer contamination","docAbstract":"

In an area of elevated nitrate (NO3) groundwater concentrations in the northern Chihuahuan Desert in central New Mexico (United States), a large reservoir of nitrate was found in the subsoil of an arroyo floodplain. Nitrate inventories in the floodplain subsoils ranged from 10,000 to 38,000 kg NO3-N/ha—over twice as high as any previously measured arid region. The floodplain subsoil NO3 reservoir was over 100 times higher than the adjacent desert (59–95 kg NO3-N/ha). Chloride mass balance calculations of subsoils indicate arroyo floodplain subsoils have undergone negative recharge since 2600–8600 yr ago, while the surrounding desert has had negative recharge since 13,000–17,000 yr ago. Compared to the adjacent desert, plant communities are larger and more abundant in the floodplain, though subsoil NO3 is apparently not utilized. We demonstrate that NO3 accumulates in the subsoil of the floodplain through evaporation of monsoon season precipitation funneled into the arroyo. Through a one-dimensional vadose zone model, we show that the NO3 inventories in the arroyo floodplain could be acquired 8 to 75 times faster than through atmospheric deposition through the lateral movement

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G47916.1","usgsCitation":"Linhoff, B., and Lunzer, J.J., 2021, Discovery of a large subsoil nitrate reservoir in an arroyo floodplain and associated aquifer contamination: Geology, v. 49, no. 6, p. 667-671, https://doi.org/10.1130/G47916.1.","productDescription":"5 p.","startPage":"667","endPage":"671","ipdsId":"IP-119573","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":453348,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g47916.1","text":"Publisher Index Page"},{"id":385347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Chihuahuan Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.70996093749999,\n 34.30714385628804\n ],\n [\n -105.6005859375,\n 34.30714385628804\n ],\n [\n -105.6005859375,\n 35.871246850027966\n ],\n [\n -107.70996093749999,\n 35.871246850027966\n ],\n [\n -107.70996093749999,\n 34.30714385628804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Linhoff, Benjamin Shawn 0000-0002-9478-7558","orcid":"https://orcid.org/0000-0002-9478-7558","contributorId":257665,"corporation":false,"usgs":true,"family":"Linhoff","given":"Benjamin Shawn","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lunzer, John Joseph 0000-0002-5159-7826","orcid":"https://orcid.org/0000-0002-5159-7826","contributorId":257666,"corporation":false,"usgs":true,"family":"Lunzer","given":"John","email":"","middleInitial":"Joseph","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218714,"text":"70218714 - 2021 - Estimating blue carbon sequestration under coastal management scenarios","interactions":[],"lastModifiedDate":"2021-03-08T14:08:19.821502","indexId":"70218714","displayToPublicDate":"2021-02-22T07:54:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimating blue carbon sequestration under coastal management scenarios","docAbstract":"

Restoring and protecting “blue carbon” ecosystems - mangrove forests, tidal marshes, and seagrass meadows - are actions considered for increasing global carbon sequestration. To improve understanding of which management actions produce the greatest gains in sequestration, we used a spatially explicit model to compare carbon sequestration and its economic value over a broad spatial scale (2500 km of coastline in southeastern Australia) for four management scenarios: (1) Managed Retreat, (2) Managed Retreat Plus Levee Removal, (3) Erosion of High Risk Areas, (4) Erosion of Moderate to High Risk Areas. We found that carbon sequestration from avoiding erosion-related emissions (abatement) would far exceed sequestration from coastal restoration. If erosion were limited only to the areas with highest erosion risk, sequestration in the non-eroded area exceeded emissions by 4.2 million Mg CO2 by 2100. However, losing blue carbon ecosystems in both moderate and high erosion risk areas would result in net emissions of 23.0 million Mg CO2 by 2100. The removal of levees combined with managed retreat was the strategy that sequestered the most carbon. Across all time points, removal of levees increased sequestration by only an additional 1 to 3% compared to managed retreat alone. Compared to the baseline erosion scenario, the managed retreat scenario increased sequestration by 7.40 million Mg CO2 by 2030, 8.69 million Mg CO2 by 2050, and 16.6 million Mg CO2 by 2100. Associated economic value followed the same patterns, with large potential value loss from erosion greater than potential gains from conserving or restoring ecosystems. This study quantifies the potential benefits of managed retreat and preventing erosion in existing blue carbon ecosystems to help meet climate change mitigation goals by reducing carbon emissions.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.145962","usgsCitation":"Moritsch, M.M., Young, M.A., Carnell, P., Macreadie, P., Lovelock, C.E., Nicholson, E., Raimondi, P.T., Wedding, L.M., and Ierodiaconou, D., 2021, Estimating blue carbon sequestration under coastal management scenarios: Science of the Total Environment, v. 777, 145962, 12 p., https://doi.org/10.1016/j.scitotenv.2021.145962.","productDescription":"145962, 12 p.","ipdsId":"IP-116919","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502652,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Estimating_blue_carbon_sequestration_under_coastal_management_scenarios/20674215","text":"External 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T.","contributorId":139302,"corporation":false,"usgs":false,"family":"Raimondi","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":811489,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wedding, Lisa M.","contributorId":241019,"corporation":false,"usgs":false,"family":"Wedding","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":811490,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ierodiaconou, Daniel","contributorId":254946,"corporation":false,"usgs":false,"family":"Ierodiaconou","given":"Daniel","email":"","affiliations":[{"id":51364,"text":"Deakin University, School of Life and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":811491,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70218796,"text":"70218796 - 2021 - Using decision science for monitoring threatened western snowy plovers to inform recovery","interactions":[],"lastModifiedDate":"2021-03-12T13:11:44.324103","indexId":"70218796","displayToPublicDate":"2021-02-22T07:08:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Using decision science for monitoring threatened western snowy plovers to inform recovery","docAbstract":"
Western Snowy Plovers (Charadrius nivosus nivosus) are federally listed under the US Endangered Species Act as Threatened. They occur along the US Pacific coastline and are threatened by habitat loss and destruction and excessive levels of predation and human disturbance. Populations have been monitored since the 1970s for distribution, reproduction, and survival. Since the species was federally listed in 1993 and a recovery plan was approved under the US Fish and Wildlife Service in 2007, recovery actions have resulted in growing populations with increased presence at breeding and wintering sites throughout their Pacific Coast range. This success has created logistical challenges related to monitoring a recovering species and a need for identifying and instituting the best monitoring approach given recovery goals, budgets, and the likelihood of monitoring success. We devised and implemented a structured decision analysis to evaluate nine alternative monitoring strategies. The analysis included inviting plover biologists involved in monitoring to score each strategy according to a suite of performance measures. Using multi-attribute utility theory, we combined scores across the performance measures for each monitoring strategy, and applied weighted utility values to show the implications of tradeoffs and find optimal decisions. We evaluated four scenarios for weighting the monitoring objectives and how risk attitude affects optimal decisions. This resulted in identifying six strategies that best meet recovery needs and were Pareto optimal for cost-effective monitoring. Results were presented to the US Fish and Wildlife Service, responsible for monitoring as well as for consideration to ensure consistent monitoring methods across the species’ range. Our use of structured decision-making can be applied to cases of other species once imperiled but now on the road to recovery. 
","language":"English","publisher":"MDPI","doi":"10.3390/ani11020569","usgsCitation":"Marcot, B.G., Lyons, J., Elbert, D.C., and Todd, L., 2021, Using decision science for monitoring threatened western snowy plovers to inform recovery: Animals, v. 11, no. 2, 569, 19 p., https://doi.org/10.3390/ani11020569.","productDescription":"569, 19 p.","ipdsId":"IP-123929","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani11020569","text":"Publisher Index Page"},{"id":384337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 47.754097979680026\n ],\n [\n -125.068359375,\n 48.80686346108517\n ],\n [\n -125.15625000000001,\n 48.22467264956519\n ],\n [\n -124.62890625,\n 46.619261036171515\n ],\n [\n -125.595703125,\n 43.51668853502906\n ],\n [\n -125.595703125,\n 41.57436130598913\n ],\n [\n -124.892578125,\n 38.54816542304656\n ],\n [\n -122.431640625,\n 35.38904996691167\n ],\n [\n -120.05859375,\n 33.797408767572485\n ],\n [\n -117.68554687499999,\n 32.32427558887655\n ],\n [\n -115.48828125000001,\n 32.69486597787505\n ],\n [\n -116.19140625,\n 33.797408767572485\n ],\n [\n -120.41015624999999,\n 36.527294814546245\n ],\n [\n -122.78320312499999,\n 41.178653972331674\n ],\n [\n -122.431640625,\n 44.402391829093915\n ],\n [\n -123.134765625,\n 47.754097979680026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":140456,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":811913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":210574,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":811914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elbert, Daniel C","contributorId":255179,"corporation":false,"usgs":false,"family":"Elbert","given":"Daniel","email":"","middleInitial":"C","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":811915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Laura","contributorId":255180,"corporation":false,"usgs":false,"family":"Todd","given":"Laura","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":811916,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218700,"text":"70218700 - 2021 - Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA","interactions":[],"lastModifiedDate":"2023-11-03T21:40:15.552191","indexId":"70218700","displayToPublicDate":"2021-02-22T07:02:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA","docAbstract":"

The Fairweather fault (southeastern Alaska, USA) is Earth’s fastest-slipping intracontinental strike-slip fault, but its long-term role in localizing Yakutat–(Pacific–)North America plate motion is poorly constrained. This plate boundary fault transitions northward from pure strike slip to transpression where it comes onshore and undergoes a <25°, 30-km-long restraining double bend. To the east, apatite (U-Th)/He (AHe) ages indicate that North America exhumation rates increase stepwise from ~0.7 to 1.7 km/m.y. across the bend. In contrast, to the west, AHe age-depth data indicate that extremely rapid 5–10 km/m.y. Yakutat exhumation rates are localized within the bend. Further northwest, Yakutat AHe and zircon (U-Th)/He (ZHe) ages gradually increase from 0.3 to 2.6 Ma over 150 km and depict an interval of extremely rapid >6–8 km/m.y. exhumation rates that increases in age away from the bend. We interpret this migration of rapid, transient exhumation to reflect prolonged advection of the Cenozoic–Cretaceous sedimentary cover of the eastern Yakutat microplate through a stationary restraining bend along the edge of the North America plate. Yakutat cooling ages imply a long-term strike-slip rate (54 ± 6 km/m.y.) that mimics the millennial (53 ± 5 m/k.y.) and decadal (46 mm/yr) rates. Fairweather fault slip can account for all Pacific–North America relative plate motion throughout Quaternary time and indicates stability of highly localized plate boundary strike slip on a single fault where extreme rock uplift rates are persistently localized within a restraining bend.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G48464.1","usgsCitation":"Lease, R.O., Haeussler, P., Witter, R., Stockli, D.F., Bender, A., Kelsey, H., and O’Sullivan, P., 2021, Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA: Geology, v. 49, no. 5, p. 602-606, https://doi.org/10.1130/G48464.1.","productDescription":"5 p.","startPage":"602","endPage":"606","ipdsId":"IP-124679","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":453351,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g48464.1","text":"Publisher Index Page"},{"id":436496,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FUIJG8","text":"USGS data release","linkHelpText":"Low-Temperature Thermochronometric Data along the Fairweather Fault, Southeast Alaska, 2015-2020"},{"id":384056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"southern Fairweather fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.64734789789867,\n 60.62832977945311\n ],\n [\n -142.84447658755874,\n 56.344276134374155\n ],\n [\n -130.03801608165645,\n 54.104139652147495\n ],\n [\n -130.03801608165645,\n 60.62832977945311\n ],\n [\n -146.64734789789867,\n 60.62832977945311\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":811420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":811422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockli, Daniel F. 0000-0001-7652-2129","orcid":"https://orcid.org/0000-0001-7652-2129","contributorId":254375,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":811423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelsey, Harvey","contributorId":254376,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":811425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":811426,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220204,"text":"70220204 - 2021 - A combined microbial and ecosystem metric of carbon retention efficiency explains land cover-dependent soil microbial biodiversity–ecosystem function relationships","interactions":[],"lastModifiedDate":"2021-04-27T11:47:41.692482","indexId":"70220204","displayToPublicDate":"2021-02-22T06:46:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8573,"text":"Biogeochemistry Letters","active":true,"publicationSubtype":{"id":10}},"title":"A combined microbial and ecosystem metric of carbon retention efficiency explains land cover-dependent soil microbial biodiversity–ecosystem function relationships","docAbstract":"

While soil organic carbon (C) is the foundation of productive and healthy ecosystems, the impact of the ecology of microorganisms on C-cycling remains unknown. We manipulated the diversity, applied here as species richness, of the microbial community present in similar soils on two contrasting land-covers—an adjacent pasture and forest—and observed the transformations of plant detritus and soil organic matter (SOM) using stable isotope (13C) tracing coupled with a novel nuclear magnetic resonance (NMR) experiment. The amount of detritus-C degraded was not affected by the microbial diversity (p > 0.05), however the fate of detritus- and SOM-C across the diversity gradient was complex and land cover-dependent. For example, in the pasture soil, higher diversity led to lower CO2 production (p = 0.001), a trend driven solely by SOM-C mineralization. There was no relationship between diversity and detritus-C mineralization or production of new mineral-associations after one year (p > 0.05). In contrast, in the forest soil higher diversity resulted in increased detritus-C (p = 0.01) and SOM-C (p = 0.0008) mineralization and decreased mineral-associated organic matter formation (p = 0.02). In both land cover types, retention efficiency—a measure that integrates both microbial physiology and the ability of the ecosystem to retain C—explained C loss and transformation trends. Overall, this demonstrates that the trajectory of C gained and lost is altered by land management-induced changes to microbial communities, soil structure, and chemical characteristics underlying SOM persistence.

","language":"English","publisher":"Springer","doi":"10.1007/s10533-020-00736-w","usgsCitation":"Ernakovich, J.G., Baldock, J., Creamer, C., Sanderman, J., Kalbitz, K., and Farrell, M., 2021, A combined microbial and ecosystem metric of carbon retention efficiency explains land cover-dependent soil microbial biodiversity–ecosystem function relationships: Biogeochemistry Letters, v. 153, p. 1-15, https://doi.org/10.1007/s10533-020-00736-w.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-115637","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":385314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"153","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ernakovich, Jessica G. 0000-0002-4493-2489","orcid":"https://orcid.org/0000-0002-4493-2489","contributorId":257626,"corporation":false,"usgs":false,"family":"Ernakovich","given":"Jessica","email":"","middleInitial":"G.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":814743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldock, Jeffrey R","contributorId":243644,"corporation":false,"usgs":false,"family":"Baldock","given":"Jeffrey R","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":814744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":814745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanderman, Jonathan","contributorId":187477,"corporation":false,"usgs":false,"family":"Sanderman","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":814746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kalbitz, Karsten 0000-0002-3920-4794","orcid":"https://orcid.org/0000-0002-3920-4794","contributorId":257629,"corporation":false,"usgs":false,"family":"Kalbitz","given":"Karsten","email":"","affiliations":[{"id":52069,"text":"Dresden University of Technology","active":true,"usgs":false}],"preferred":false,"id":814747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farrell, Mark 0000-0003-4562-2738","orcid":"https://orcid.org/0000-0003-4562-2738","contributorId":257630,"corporation":false,"usgs":false,"family":"Farrell","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":814748,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70218289,"text":"70218289 - 2021 - Amateur radio operators help fill earthquake donut holes","interactions":[],"lastModifiedDate":"2021-02-23T12:40:50.022035","indexId":"70218289","displayToPublicDate":"2021-02-22T06:32:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7602,"text":"Eos, American Geophysical Union","active":true,"publicationSubtype":{"id":10}},"title":"Amateur radio operators help fill earthquake donut holes","docAbstract":"

If you’ve ever seen tall antennas rising from everyday residences in your community and wondered what they are for, it could be that those homes belong to ham radio enthusiasts who enjoy communicating with each other over the airwaves. In addition to having fun with their radios and finding camaraderie, many ham radio operators are also prepared to help neighbors and authorities communicate during disasters. One such group of radio enthusiasts is poised now to serve yet another important role: They will be contributing to a more robust delivery mechanism for critical seismic intensity reports after major earthquakes through the U.S. Geological Survey’s (USGS) Did You Feel It? (DYFI) system.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EO155013","usgsCitation":"Wald, D.J., Quitoriano, V., and Dully, O., 2021, Amateur radio operators help fill earthquake donut holes: Eos, American Geophysical Union, v. 102, https://doi.org/10.1029/2021EO155013.","onlineOnly":"Y","ipdsId":"IP-122612","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":453355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021eo155013","text":"Publisher Index Page"},{"id":383583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Salt Lake City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1099853515625,\n 40.60144147645398\n ],\n [\n -111.6925048828125,\n 40.60144147645398\n ],\n [\n -111.6925048828125,\n 40.90936126702326\n ],\n [\n -112.1099853515625,\n 40.90936126702326\n ],\n [\n -112.1099853515625,\n 40.60144147645398\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dully, Oliver","contributorId":251929,"corporation":false,"usgs":false,"family":"Dully","given":"Oliver","email":"","affiliations":[{"id":50424,"text":"Amateur Radio Emergency Service","active":true,"usgs":false}],"preferred":false,"id":810831,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229171,"text":"70229171 - 2021 - Riverscape nesting dynamics of Neosho Smallmouth Bass: To cluster or not to cluster?","interactions":[],"lastModifiedDate":"2022-03-02T20:34:51.598697","indexId":"70229171","displayToPublicDate":"2021-02-21T14:26:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Riverscape nesting dynamics of Neosho Smallmouth Bass: To cluster or not to cluster?","docAbstract":"

Aim

Hierarchical stream habitat conditions influence patterns of fish abundance and population dynamics. The spawning period is important for stream fishes but coincides with unpredictable environmental conditions and stressors. Thus, identifying habitats that confer suitable spawning is crucial to managing vulnerable fish populations, including narrow-range endemics. Here, we evaluate reach- and catchment-scale habitat features related to Neosho Smallmouth Bass (Micropterus dolomieu velox) nest presence, abundance and aggregations (clusters) and quantify nest microhabitat.

Location

Ozark Highlands ecoregion, USA.

Methods

We conducted snorkel and habitat surveys from 2016 to 2018 to quantify nest abundance, describe nest cluster characteristics and quantify nest microhabitat. We used field-collected and geospatial variables and developed generalized mixed models to evaluate the influence of multi-scale habitat features on nest cluster presence and nest abundance.

Results

Nest clusters, scarcely known for other Smallmouth Bass populations, contained 25% of all documented nests. Presence of nests was more likely in warmer stream reaches with wide, shallow channels and more pool habitat. Nest cluster presence was more likely with greater nest densities and earlier in the spawning season. The abundance of Smallmouth Bass nests was related to several reach-scale habitat conditions, with greater nest counts in warmer reaches and reaches with deeper pool habitat. Regardless of cluster behaviour, nesting Smallmouth Bass used similar microhabitats, including a range of depths (0.26–1.85 m), low velocities (<0.1 m/s) and typically gravel substrates.

Main conclusions

Our results indicate plasticity in nesting ecology within Neosho Smallmouth Bass populations and highlight the need to consider multiple aspects of stream habitat when developing conservation and management plans. The importance of reach-scale habitat features suggests it may be important to limit landscape and channel alterations. Nest clustering behaviour suggests these populations may be vulnerable to human influence during the nesting season, but also provides management opportunities for protection during critical time periods.

","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13250","usgsCitation":"Miller, A., and Brewer, S.K., 2021, Riverscape nesting dynamics of Neosho Smallmouth Bass: To cluster or not to cluster?: Diversity and Distributions, v. 27, no. 6, p. 1005-1018, https://doi.org/10.1111/ddi.13250.","productDescription":"14 p.","startPage":"1005","endPage":"1018","ipdsId":"IP-122996","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":453357,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13250","text":"Publisher Index Page"},{"id":396671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, 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 -95.80078125,\n 35.88905007936091\n ],\n [\n -92.98828125,\n 35.88905007936091\n ],\n [\n -92.98828125,\n 37.3002752813443\n ],\n [\n -95.80078125,\n 37.3002752813443\n ],\n [\n -95.80078125,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Andrew D.","contributorId":287529,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":836856,"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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":836857,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218456,"text":"70218456 - 2021 - Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation","interactions":[],"lastModifiedDate":"2021-02-26T13:42:46.530587","indexId":"70218456","displayToPublicDate":"2021-02-21T07:32:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation","docAbstract":"

Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (<15 km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ∼20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.

","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2021.620813","usgsCitation":"Fee, D., Toney, L., Kim, K., Sanderson, R., Iezzi, A., Matoza, R.S., DeAngelis, S., Jolly, A., Lyons, J.J., and Haney, M.M., 2021, Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation: Frontiers in Earth Science, v. 9, 620813, 14 p., https://doi.org/10.3389/feart.2021.620813.","productDescription":"620813, 14 p.","ipdsId":"IP-125855","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.620813","text":"Publisher Index Page"},{"id":383634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Japan, Vanuatu","state":"Alaska","otherGeospatial":"Sakurajima Volcano, Shishaldin Volcano, Yasur Volcano, Vanuatu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 166.66259765625,\n -17.26672782352052\n ],\n [\n 168.71704101562503,\n -17.26672782352052\n ],\n [\n 168.71704101562503,\n -14.519780046326085\n ],\n [\n 166.66259765625,\n -14.519780046326085\n ],\n [\n 166.66259765625,\n -17.26672782352052\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 130.51345825195312,\n 31.505971031689416\n ],\n [\n 130.78262329101562,\n 31.505971031689416\n ],\n [\n 130.78262329101562,\n 31.659226205934562\n ],\n [\n 130.51345825195312,\n 31.659226205934562\n ],\n [\n 130.51345825195312,\n 31.505971031689416\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n 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Keehoon","contributorId":252842,"corporation":false,"usgs":false,"family":"Kim","given":"Keehoon","email":"","affiliations":[{"id":27196,"text":"LANL","active":true,"usgs":false}],"preferred":false,"id":810993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanderson, Richard","contributorId":252843,"corporation":false,"usgs":false,"family":"Sanderson","given":"Richard","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":810994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":810995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matoza, Robin S","contributorId":215528,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":810996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeAngelis, Silvio","contributorId":252846,"corporation":false,"usgs":false,"family":"DeAngelis","given":"Silvio","email":"","affiliations":[{"id":50448,"text":"Liverpool","active":true,"usgs":false}],"preferred":false,"id":810997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jolly, Art","contributorId":252847,"corporation":false,"usgs":false,"family":"Jolly","given":"Art","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810998,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":810999,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811000,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70218643,"text":"70218643 - 2021 - Gulf of Mexico blue hole harbors high levels of novel microbial lineages","interactions":[],"lastModifiedDate":"2025-05-13T16:08:29.968527","indexId":"70218643","displayToPublicDate":"2021-02-21T06:58:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7746,"text":"Interational Society of Microbial Ecology (ISME) Journal","active":true,"publicationSubtype":{"id":10}},"title":"Gulf of Mexico blue hole harbors high levels of novel microbial lineages","docAbstract":"

Exploration of oxygen-depleted marine environments has consistently revealed novel microbial taxa and metabolic capabilities that expand our understanding of microbial evolution and ecology. Marine blue holes are shallow karst formations characterized by low oxygen and high organic matter content. They are logistically challenging to sample, and thus our understanding of their biogeochemistry and microbial ecology is limited. We present a metagenomic and geochemical characterization of Amberjack Hole on the Florida continental shelf (Gulf of Mexico). Dissolved oxygen became depleted at the hole’s rim (32 m water depth), remained low but detectable in an intermediate hypoxic zone (40–75 m), and then increased to a secondary peak before falling below detection in the bottom layer (80–110 m), concomitant with increases in nutrients, dissolved iron, and a series of sequentially more reduced sulfur species. Microbial communities in the bottom layer contained heretofore undocumented levels of the recently discovered phylum Woesearchaeota (up to 58% of the community), along with lineages in the bacterial Candidate Phyla Radiation (CPR). Thirty-one high-quality metagenome-assembled genomes (MAGs) showed extensive biochemical capabilities for sulfur and nitrogen cycling, as well as for resisting and respiring arsenic. One uncharacterized gene associated with a CPR lineage differentiated hypoxic from anoxic zone communities. Overall, microbial communities and geochemical profiles were stable across two sampling dates in the spring and fall of 2019. The blue hole habitat is a natural marine laboratory that provides opportunities for sampling taxa with under-characterized but potentially important roles in redox-stratified microbial processes.

","language":"English","publisher":"Nature","doi":"10.1038/s41396-021-00917-x","usgsCitation":"Patin, N., Dietrich, Z., Stancil, A., Quinan, M., Beckler, J., Hall, E.R., Culter, J., Smith, C., Taillefert, M., and Stewart, F., 2021, Gulf of Mexico blue hole harbors high levels of novel microbial lineages: Interational Society of Microbial Ecology (ISME) Journal, v. 15, p. 2206-2232, https://doi.org/10.1038/s41396-021-00917-x.","productDescription":"17 p.","startPage":"2206","endPage":"2232","ipdsId":"IP-121475","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":383739,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":453364,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-021-00917-x","text":"Publisher Index Page"}],"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 -80.68359375,\n 25.20494115356912\n ],\n [\n -83.3203125,\n 29.458731185355344\n ],\n [\n -84.24316406249999,\n 30.031055426540206\n ],\n [\n -85.20996093749999,\n 29.649868677972304\n ],\n [\n -86.7919921875,\n 30.486550842588485\n ],\n [\n -89.384765625,\n 30.06909396443887\n ],\n [\n -90.2197265625,\n 29.22889003019423\n ],\n [\n -93.9990234375,\n 29.649868677972304\n ],\n [\n -97.119140625,\n 27.994401411046148\n ],\n [\n -97.6025390625,\n 25.284437746983055\n ],\n [\n -97.7783203125,\n 21.983801417384697\n ],\n [\n -80.68359375,\n 25.20494115356912\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2021-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Patin, N.V. 0000-0001-8522-7682","orcid":"https://orcid.org/0000-0001-8522-7682","contributorId":253112,"corporation":false,"usgs":false,"family":"Patin","given":"N.V.","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":811229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietrich, Z.A.","contributorId":253113,"corporation":false,"usgs":false,"family":"Dietrich","given":"Z.A.","email":"","affiliations":[{"id":33315,"text":"Bowdoin College","active":true,"usgs":false}],"preferred":false,"id":811230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stancil, A.","contributorId":253114,"corporation":false,"usgs":false,"family":"Stancil","given":"A.","email":"","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":811231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinan, M.","contributorId":253115,"corporation":false,"usgs":false,"family":"Quinan","given":"M.","email":"","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":811232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beckler, J.S.","contributorId":253116,"corporation":false,"usgs":false,"family":"Beckler","given":"J.S.","email":"","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":811233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, E. R. 0000-0002-9218-6097","orcid":"https://orcid.org/0000-0002-9218-6097","contributorId":253129,"corporation":false,"usgs":false,"family":"Hall","given":"E.","email":"","middleInitial":"R.","affiliations":[{"id":37075,"text":"Mote Marine Laboratory, Tropical Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":811268,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Culter, J","contributorId":253117,"corporation":false,"usgs":false,"family":"Culter","given":"J","email":"","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":811235,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":811236,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taillefert, Martial","contributorId":214794,"corporation":false,"usgs":false,"family":"Taillefert","given":"Martial","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":811237,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stewart, F.J.","contributorId":253118,"corporation":false,"usgs":false,"family":"Stewart","given":"F.J.","email":"","affiliations":[{"id":50483,"text":"Georgia Institute of Technology; Montana State University","active":true,"usgs":false}],"preferred":false,"id":811238,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70218297,"text":"70218297 - 2021 - Azorella compacta's long-term growth rate, longevity, and potential for dating geomorphological and archaeological features in the arid southern Peruvian Andes","interactions":[],"lastModifiedDate":"2021-02-24T12:51:03.305518","indexId":"70218297","displayToPublicDate":"2021-02-21T06:46:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Azorella compacta's long-term growth rate, longevity, and potential for dating geomorphological and archaeological features in the arid southern Peruvian Andes","docAbstract":"

We determine the long-term growth rate and longevity of an Azorella compacta growing on Misti volcano, near Arequipa, Peru to investigate the species' capacity as a geochronological resource. Using 14C dating on stem pieces sequestered within the plant's cushion, which grows larger through time, we obtain ages of 15 ± 15 14C yrs BP and 165 ± 15 14C yrs BP at depths of 15 cm and 29 cm below the cushion's living surface, respectively. Applying a mixed calibration curve with a Bayesian growth model yields calendar age ranges of 1948–1958 CE and 1802–1935 CE for our 14C dates, respectively. Such ages provide sufficiently precise constraints for investigations requiring dating during the last few hundred years when individual 14C dates yield imprecise calendar age ranges. We infer a long-term growth rate of 1.3–3.5 mm yr−1, corroborating published maximum short-term growth rates. Extrapolating our growth model to the A. compacta's core suggests that it began growing as early as 1462–1830 CE. At such age it lived through myriad important geological and historical events, including regional earthquakes, volcanic unrest at Misti, decades to centuries of the Little Ice Age, and a broad transect of Peruvian history possibly beginning during the Inca Empire. A. compacta may provide another important geochronological resource in the arid Central Andes that can be applied to date volcanological, glacial, mass-movement, and archaeological features, especially where dendrochronology and lichenometry are not possible.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2021.104470","usgsCitation":"Harpel, C., Kleier, C., and Aguilar, R., 2021, Azorella compacta's long-term growth rate, longevity, and potential for dating geomorphological and archaeological features in the arid southern Peruvian Andes: Journal of Arid Environments, v. 188, 104470, 5 p., https://doi.org/10.1016/j.jaridenv.2021.104470.","productDescription":"104470, 5 p.","ipdsId":"IP-120064","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/20.500.12390/2340","text":"Publisher Index Page"},{"id":383610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Peruvian Andes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5859375,\n 0.08789059053082422\n ],\n [\n -78.134765625,\n -2.8991526985043006\n ],\n [\n -80.244140625,\n -3.337953961416472\n ],\n [\n -81.38671875,\n -4.477856485570586\n ],\n [\n -81.03515625,\n -6.053161295714067\n ],\n [\n -75.6298828125,\n -15.114552871944102\n ],\n [\n -70.1806640625,\n -18.687878686034182\n ],\n [\n -69.4775390625,\n -17.26672782352052\n ],\n [\n -68.994140625,\n -16.299051014581817\n ],\n [\n -68.466796875,\n -12.382928338487396\n ],\n [\n -69.8291015625,\n -10.833305983642491\n ],\n [\n -70.6201171875,\n -9.44906182688142\n ],\n [\n -70.9716796875,\n -4.127285323245357\n ],\n [\n -70.09277343749999,\n -2.67968661580376\n ],\n [\n -75.5859375,\n 0.08789059053082422\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"188","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harpel, Christopher 0000-0001-8587-7845","orcid":"https://orcid.org/0000-0001-8587-7845","contributorId":204746,"corporation":false,"usgs":true,"family":"Harpel","given":"Christopher","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleier, Catherine","contributorId":252546,"corporation":false,"usgs":false,"family":"Kleier","given":"Catherine","email":"","affiliations":[{"id":50430,"text":"College of Agriculture, Forestry, and Environmental Science, California State Polytechnic University, San Luis Obispo","active":true,"usgs":false}],"preferred":false,"id":810901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aguilar, Rigoberto","contributorId":252547,"corporation":false,"usgs":false,"family":"Aguilar","given":"Rigoberto","affiliations":[{"id":50431,"text":"Observatorio Vulcanologico del Instituto Geologico, Minero y Metalurgico del Peru","active":true,"usgs":false}],"preferred":false,"id":810902,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218257,"text":"70218257 - 2021 - Long-term trends in regional wet mercury deposition and lacustrine mercury concentrations in four lakes in Voyageurs National Park","interactions":[],"lastModifiedDate":"2021-02-22T14:43:03.094759","indexId":"70218257","displayToPublicDate":"2021-02-20T08:38:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5841,"text":"Applied Sciences","onlineIssn":"2076-3417","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in regional wet mercury deposition and lacustrine mercury concentrations in four lakes in Voyageurs National Park","docAbstract":"

Although anthropogenic mercury (Hg) releases to the environment have been substantially lowered in the United States and Canada since 1990, concerns remain for contamination in fish from remote lakes and rivers where atmospheric deposition is the predominant source of mercury. How have aquatic ecosystems responded? We report on one of the longest known multimedia data sets for mercury in atmospheric deposition: aqueous total mercury (THgaq), methylmercury (MeHgaq), and sulfate from epilimnetic lake-water samples from four lakes in Voyageurs National Park (VNP) in northern Minnesota; and total mercury (THg) in aquatic biota from the same lakes from 2001–2018. Wet Hg deposition at two regional Mercury Deposition Network sites (Fernberg and Marcell, Minnesota) decreased by an average of 22 percent from 1998–2018; much of the decreases occurred prior to 2009, with relatively flat trends since 2009. In the four VNP lakes, epilimnetic MeHgaq concentrations declined by an average of 44 percent and THgaq by an average of 27 percent. For the three lakes with long-term biomonitoring, temporal patterns in biotic THg concentrations were similar to patterns in MeHgaq concentrations; however, biotic THg concentrations declined significantly in only one lake. Epilimnetic MeHgaq may be responding both to a decline in atmospheric Hg deposition as well as a decline in sulfate deposition, which is an important driver of mercury methylation in the environment. Results from this case study suggest that regional- to continental-scale decreases in both mercury and sulfate emissions have benefitted aquatic resources, even in the face of global increases in mercury emissions.

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The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

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Salinity can interact with organic compounds and modulate their toxicity. Studies have shown that the fraction of pyrethroid insecticides in the aqueous phase increases with increasing salinity, potentially increasing the risk of exposure for aquatic organisms at higher salinities. In the San Francisco Bay Delta (SFBD) estuary, pyrethroid concentrations increase during the rainy season, coinciding with the spawning season of Delta Smelt (Hypomesus transpacificus), an endangered, endemic fish. Furthermore, salinity intrusion in the SFBD is exacerbated by global climate change, which may change the dynamics of pyrethroid toxicity on aquatic animals. Therefore, examining the effect of salinity on the sublethal toxicity of pyrethroids is essential for risk assessments, especially during the early life stages of estuarine fishes. To address this, we investigated behavioral effects of permethrin and bifenthrin at three environmentally relevant concentrations across a salinity gradient (0.5, 2 and 6 PSU) on Delta Smelt yolk-sac larvae. Our results suggest that environmentally relevant concentrations of pyrethroids can perturb Delta Smelt larvae behavior even at the lowest concentrations (<1 ng/L) and that salinity can change the dynamic of pyrethroid toxicity in terms of behavioral effects, especially for bifenthrin, where salinity was positively correlated with anti-thigmotaxis at each concentration.
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