The recently emerged novel coronavirus, SARS‐CoV‐2, is phylogenetically related to bat coronaviruses (CoVs), specifically SARS‐related CoVs from the Eurasian bat family Rhinolophidae. As this human pandemic virus has spread across the world, the potential impacts of SARS‐CoV‐2 on native North American bat populations are unknown, as is the ability of North American bats to serve as reservoirs or intermediate hosts able to transmit the virus to humans or to other animal species. To help determine the impacts of the pandemic virus on North American bat populations, we experimentally challenged big brown bats (Eptesicus fuscus) with SARS‐CoV‐2 under BSL‐3 conditions. We inoculated the bats both oropharyngeally and nasally, and over the ensuing three weeks, we measured infectivity, pathology, virus concentrations in tissues, oral and rectal virus excretion, virus transmission, and clinical signs of disease. We found no evidence of SARS‐CoV‐2 infection in any examined bat, including no viral excretion, no transmission, no detectable virus in tissues, and no signs of disease or pathology. Based on our findings, it appears that big brown bats are resistant to infection with the SARS‐CoV‐2. The potential susceptibility of other North American bat species to SARS‐CoV‐2 remains to be investigated.
","language":"English","publisher":"Wiley","doi":"10.1111/tbed.13949","usgsCitation":"Hall, J.S., Knowles, S., Nashold, S., Ip, H., Leon, A.E., Rocke, T.E., Keller, S.A., Carossino, M., Balasuriya, U.B., and Hofmeister, E.K., 2021, Experimental challenge of a North American bat species, big brown bat (Eptesicus fuscus), with SARS-CoV-2: Transboundary and Emerging Diseases, v. 68, no. 6, p. 3443-3452, https://doi.org/10.1111/tbed.13949.","productDescription":"10 p.","startPage":"3443","endPage":"3452","ipdsId":"IP-122290","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454133,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.lsu.edu/vetmed_pubs/875","text":"Publisher Index Page"},{"id":382088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nashold, Sean 0000-0002-8869-6633","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":214978,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leon, Ariel Elizabeth 0000-0001-9246-4619","orcid":"https://orcid.org/0000-0001-9246-4619","contributorId":247573,"corporation":false,"usgs":true,"family":"Leon","given":"Ariel","email":"","middleInitial":"Elizabeth","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keller, Saskia Annatina 0000-0002-9653-516X","orcid":"https://orcid.org/0000-0002-9653-516X","contributorId":247574,"corporation":false,"usgs":true,"family":"Keller","given":"Saskia","email":"","middleInitial":"Annatina","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carossino, Mariano","contributorId":245857,"corporation":false,"usgs":false,"family":"Carossino","given":"Mariano","email":"","affiliations":[],"preferred":false,"id":807944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Balasuriya, Udeni B.R.","contributorId":245862,"corporation":false,"usgs":false,"family":"Balasuriya","given":"Udeni","email":"","middleInitial":"B.R.","affiliations":[],"preferred":false,"id":807945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":807946,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70218694,"text":"70218694 - 2021 - Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models","interactions":[],"lastModifiedDate":"2021-03-05T13:14:47.975659","indexId":"70218694","displayToPublicDate":"2020-12-09T07:10:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models","docAbstract":"Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.
Specific conductivity (SC) is commonly used to estimate the proportion of baseflow (i.e., waters from within catchments such as groundwater, interflow, or bank return flows) contributing to rivers. Reach-scale SC comparisons are also useful for identifying where multiple water stores contribute to baseflow. Daily SC values of adjacent gauges in Australian (the Barwon, Glenelg, and Campaspe Rivers) and North American (the Upper Colorado River) catchments are commonly not well correlated (R2 = 0.32 to 0.82). Smoothed inter-gauge SC values averaged over 7 to 45 days are better correlated and define a series of hysteresis loops. The variable SC patterns between adjacent gauges probably reflect varying proportions of groundwater, bank return waters, interflow, and soil water contributing to baseflow. In some rivers using SC values to compare baseflow along river reaches on sub-annual timescales may be not be feasible.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125895","usgsCitation":"Cartwright, I., and Miller, M., 2021, Temporal and spatial variations in river specific conductivity: Implications for understanding sources of river water and hydrograph separations: Journal of Hydrology, v. 593, 125895, 8 p., https://doi.org/10.1016/j.jhydrol.2020.125895.","productDescription":"125895, 8 p.","ipdsId":"IP-120526","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":381795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"593","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cartwright, Ian 0000-0001-5300-4716","orcid":"https://orcid.org/0000-0001-5300-4716","contributorId":245985,"corporation":false,"usgs":false,"family":"Cartwright","given":"Ian","email":"","affiliations":[{"id":27278,"text":"Monash University","active":true,"usgs":false}],"preferred":false,"id":807452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228565,"text":"70228565 - 2021 - Temporal invariance of social-ecological catchments","interactions":[],"lastModifiedDate":"2022-02-14T19:55:29.246571","indexId":"70228565","displayToPublicDate":"2020-12-08T14:55:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Temporal invariance of social-ecological catchments","docAbstract":"Natural resources such as waterbodies, public parks, and wildlife refuges attract people from varying distances on the landscape, creating \"social-ecological catchments.\" Catchments have provided great utility for understanding physical and social relationships within specific disciplines. Yet, catchments are rarely used across disciplines, such as its application to understand complex spatiotemporal dynamics between mobile human users and patchily distributed natural resources. We collected residence ZIP codes from 19,983 angler parties during 2014–2017 to construct seven angler–waterbody catchments in Nebraska, USA. We predicted that sizes of dense (10% utilization distribution) and dispersed (95% utilization distribution) angler–waterbody catchments would change across seasons and years as a function of diverse resource selection among mobile anglers. Contrary to expectations, we revealed that catchment size was invariant. We discuss how social (conservation actions) and ecological (low water quality, reduction in species diversity) conditions are expected to impact landscape patterns in resource use. We highlight how this simple concept and user-friendly technique can inform timely landscape-level conservation decisions within coupled social-ecological systems that are currently difficult to study and understand.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2272","usgsCitation":"Kaemingk, M., Bender, C.N., Chizinski, C., Bunch, A., and Pope, K.L., 2021, Temporal invariance of social-ecological catchments: Ecological Applications, v. 31, no. 2, e02272, 7 p., https://doi.org/10.1002/eap.2272.","productDescription":"e02272, 7 p.","ipdsId":"IP-118117","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kaemingk, Mark A.","contributorId":276159,"corporation":false,"usgs":false,"family":"Kaemingk","given":"Mark A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bender, Christine N.","contributorId":276158,"corporation":false,"usgs":false,"family":"Bender","given":"Christine","email":"","middleInitial":"N.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":834614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chizinski, Christopher J.","contributorId":274559,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunch, Aaron J.","contributorId":276161,"corporation":false,"usgs":false,"family":"Bunch","given":"Aaron J.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834618,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70224749,"text":"70224749 - 2021 - Holocene paleoseismology of the Steamboat Mountain Site: Evidence for full‐Llngth rupture of the Teton Fault, Wyoming","interactions":[],"lastModifiedDate":"2021-10-04T12:25:15.08622","indexId":"70224749","displayToPublicDate":"2020-12-08T07:22:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Holocene paleoseismology of the Steamboat Mountain Site: Evidence for full‐Llngth rupture of the Teton Fault, Wyoming","docAbstract":"The 72‐km‐long Teton fault in northwestern Wyoming is an ideal candidate for reconstructing the lateral extent of surface‐rupturing earthquakes and testing models of normal‐fault segmentation. To explore the history of earthquakes on the northern Teton fault, we hand‐excavated two trenches at the Steamboat Mountain site, where the east‐dipping Teton fault has vertically displaced west‐sloping alluvial‐fan surfaces. The trenches exposed glaciofluvial, alluvial‐fan, and scarp‐derived colluvial sediments and stratigraphic and structural evidence of two surface‐rupturing earthquakes (SM1 and SM2). A Bayesian geochronologic model for the site includes three optically stimulated luminescence ages (∼12–17 ka) for the glaciofluvial units and 16 radiocarbon ages (∼1.2–8.6 ka) for the alluvial‐fan and colluvial units and constrains SM1 and SM2 to 5.5±0.2 ka, 1σ (5.2–5.9 ka, 95%) and 9.7±0.9 ka, 1σ (8.5–11.5 ka, 95%), respectively. Structural, stratigraphic, and geomorphic relations yield vertical displacements for SM1 (2.0±0.6 m, 1σ) and SM2 (2.0±1.0 m, 1σ). The Steamboat Mountain paleoseismic chronology overlaps temporally with earthquakes interpreted from previous terrestrial and lacustrine paleoseismic data along the fault. Integrating these data, we infer that the youngest Teton fault rupture occurred at ∼5.3 ka, generated 1.7±1.0 m, 1σ of vertical displacement along 51–70 km of the fault, and had a moment magnitude (Mw) of ∼7.0–7.2. This rupture was apparently unimpeded by structural complexities along the Teton fault. The integrated chronology permits a previous full‐length rupture at ∼10 ka and possible partial ruptures of the fault at ∼8–9 ka. To reconcile conflicting terrestrial and lacustrine paleoseismic data, we propose a hypothesis of alternating full‐ and partial‐length ruptures of the Teton fault, including Mw∼6.5–7.2 earthquakes every ∼1.2 ky. Additional paleoseismic data for the northern and central sections of the fault would serve to test this bimodal rupture hypothesis.
Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.112223","usgsCitation":"Sankey, J.B., Sankey, T.T., Li, J., Ravi, S., Wang, G., Caster, J., and Kasprak, A., 2021, Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland: Remote Sensing of Environment, v. 253, 112223, 18 p., https://doi.org/10.1016/j.rse.2020.112223.","productDescription":"112223, 18 p.","ipdsId":"IP-110017","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454141,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.112223","text":"Publisher Index Page"},{"id":381413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Sevilleta National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.80770874023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.301471780404476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"253","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":806946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Junran","contributorId":202740,"corporation":false,"usgs":false,"family":"Li","given":"Junran","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravi, Sujith","contributorId":202738,"corporation":false,"usgs":false,"family":"Ravi","given":"Sujith","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":806948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Guan","contributorId":202741,"corporation":false,"usgs":false,"family":"Wang","given":"Guan","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":806951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219508,"text":"70219508 - 2021 - Expert assessment of future vulnerability of the global peatland carbon sink","interactions":[],"lastModifiedDate":"2021-04-12T19:54:42.096571","indexId":"70219508","displayToPublicDate":"2020-12-07T10:48:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Expert assessment of future vulnerability of the global peatland carbon sink","docAbstract":"The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus.
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Recent changes in global temperatures have resulted in distributional shifts of wildlife species, as well as amelioration of winter climates in northern landscapes. The emperor goose (Anser canagicus), an endemic migratory bird of the Bering Sea region, winters across a large area of the subarctic, with potential differences in migration strategies and costs among individuals. As a long-standing species of conservation concern due to decreased population size, understanding the response of emperor geese to changing conditions has become critical to on-going management. We sought to evaluate changes in wintering distribution and arrival/departure dates over time, by comparing spatial and temporal patterns of wintering emperor geese from 2015 to 2017 (using geolocator data) to satellite telemetry data collected from 1999 to 2004. Further, we quantified changes in spatial patterns of winter abundance by comparing historical and contemporary aerial and ground surveys at three island complexes encompassing most of their winter distribution. Our results indicate that emperor geese are arriving at wintering areas earlier and spending more time at these areas than in the past. Our comparisons among historical aerial and ground surveys suggests that increasing numbers of emperor geese are wintering closer to breeding areas in western Alaska; a change likely related to increasing habitat availability due to shifting environmental conditions. Our results also showed that fewer emperor geese are using an area in the core of their wintering range, suggesting either decreased habitat quality or a reduction in migration distance via alternative wintering locations. 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An intermediate-depth (1751 m) ice core was drilled at the South Pole between 2014 and 2016 using the newly designed US Intermediate Depth Drill. The South Pole ice core is the highest-resolution interior East Antarctic ice core record that extends into the glacial period. The methods used at the South Pole to handle and log the drilled ice, the procedures used to safely retrograde the ice back to the National Science Foundation Ice Core Facility (NSF-ICF), and the methods used to process and sample the ice at the NSF-ICF are described. The South Pole ice core exhibited minimal brittle ice, which was likely due to site characteristics and, to a lesser extent, to drill technology and core handling procedures.
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Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":809567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Street, Leah V.","contributorId":248648,"corporation":false,"usgs":false,"family":"Street","given":"Leah","email":"","middleInitial":"V.","affiliations":[{"id":49971,"text":"Antarctic Support Contract, U.S. Antarctic Program, Denver, CO, USA","active":true,"usgs":false}],"preferred":false,"id":809568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicewonger, Melinda R.","contributorId":248649,"corporation":false,"usgs":false,"family":"Nicewonger","given":"Melinda","email":"","middleInitial":"R.","affiliations":[{"id":49968,"text":"Department of Earth System Science, University of California Irvine, Irvine, CA, USA","active":true,"usgs":false}],"preferred":false,"id":809569,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kahle, Emma C.","contributorId":248650,"corporation":false,"usgs":false,"family":"Kahle","given":"Emma","email":"","middleInitial":"C.","affiliations":[{"id":49969,"text":"Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":809570,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Jay A.","contributorId":248651,"corporation":false,"usgs":false,"family":"Johnson","given":"Jay","email":"","middleInitial":"A.","affiliations":[{"id":49972,"text":"U.S. Ice Drilling Program, University of Wisconsin-Madison, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":809571,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kuhl, Tanner W.","contributorId":248652,"corporation":false,"usgs":false,"family":"Kuhl","given":"Tanner W.","affiliations":[{"id":49972,"text":"U.S. Ice Drilling Program, University of Wisconsin-Madison, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":809572,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Casey, Kimberly Ann 0000-0002-6115-7525","orcid":"https://orcid.org/0000-0002-6115-7525","contributorId":245548,"corporation":false,"usgs":true,"family":"Casey","given":"Kimberly","email":"","middleInitial":"Ann","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":809573,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fegyveresi, John M. 0000-0002-1029-6277","orcid":"https://orcid.org/0000-0002-1029-6277","contributorId":248653,"corporation":false,"usgs":false,"family":"Fegyveresi","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":49973,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":809574,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nunn, Richard 0000-0002-6476-0768","orcid":"https://orcid.org/0000-0002-6476-0768","contributorId":248654,"corporation":false,"usgs":true,"family":"Nunn","given":"Richard","email":"","affiliations":[{"id":207,"text":"Core Research Center","active":true,"usgs":true}],"preferred":true,"id":809575,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hargreaves, Geoffrey Mill 0000-0001-9847-3065 ghargreaves@usgs.gov","orcid":"https://orcid.org/0000-0001-9847-3065","contributorId":248655,"corporation":false,"usgs":true,"family":"Hargreaves","given":"Geoffrey","email":"ghargreaves@usgs.gov","middleInitial":"Mill","affiliations":[{"id":207,"text":"Core Research Center","active":true,"usgs":true}],"preferred":true,"id":809576,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70217113,"text":"70217113 - 2021 - Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie","interactions":[],"lastModifiedDate":"2021-01-07T12:36:19.107351","indexId":"70217113","displayToPublicDate":"2020-12-07T07:00:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie","docAbstract":"The spatial distribution, concentration, particle size, and polymer compositions of microplastics in Lake Michigan and Lake Erie sediment were investigated. Fibers/lines were the most abundant of the five particle types characterized. Microplastic particles were observed in all samples with mean concentrations for particles greater than 0.355 mm of 65.2 p kg–1 in Lake Michigan samples (n = 20) and 431 p kg–1 in Lake Erie samples (n = 12). Additional analysis of particles with size 0.1250–0.3549 mm in Lake Erie resulted in a mean concentration of 631 p kg–1. The majority of polymers in Lake Michigan samples were poly(ethylene terephthalate) (PET), high-density polyethylene (HDPE), and semisynthetic cellulose (S.S. Cellulose), and in Lake Erie samples were S.S. Cellulose, polypropylene (PP), and poly(vinyl chloride) (PVC). Polymer density estimates indicated that 85 and 74% of observed microplastic particles have a density greater than 1.1 g cm–3 for Lake Michigan and Lake Erie, respectively. The current study provided a multidimensional dataset on the spatial distribution of microplastics in benthic sediment from Lake Michigan and Lake Erie and valuable information for assessment of the fate of microplastics in the Great Lakes.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06087","usgsCitation":"Lenaker, P.L., Corsi, S., and Mason, S.A., 2021, Spatial distribution of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie: Environmental Science & Technology, v. 55, no. 1, p. 373-384, https://doi.org/10.1021/acs.est.0c06087.","productDescription":"12 p.","startPage":"373","endPage":"384","ipdsId":"IP-119261","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":454148,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.0c06087","text":"Publisher Index Page"},{"id":436628,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WJUODZ","text":"USGS data release","linkHelpText":"Microplastics in the surficial benthic sediment from Lake Michigan and Lake Erie, 2013 and 2014"},{"id":381937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Ontario, Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.71484375,\n 41.50857729743935\n ],\n [\n -86.1328125,\n 41.50857729743935\n ],\n [\n -86.1328125,\n 46.255846818480315\n ],\n [\n -87.71484375,\n 46.255846818480315\n ],\n [\n -87.71484375,\n 41.50857729743935\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.3203125,\n 41.244772343082076\n ],\n [\n -79.013671875,\n 41.244772343082076\n ],\n [\n -79.013671875,\n 42.48830197960227\n ],\n [\n -83.3203125,\n 42.48830197960227\n ],\n [\n -83.3203125,\n 41.244772343082076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Sherri A.","contributorId":176172,"corporation":false,"usgs":false,"family":"Mason","given":"Sherri","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":807636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250892,"text":"70250892 - 2021 - Multi-geophysical parameter classification of the Montserrat geothermal system","interactions":[],"lastModifiedDate":"2024-01-11T14:11:47.485373","indexId":"70250892","displayToPublicDate":"2020-12-05T08:07:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Multi-geophysical parameter classification of the Montserrat geothermal system","docAbstract":"Multi-geophysical parameter classification can help to reduce the uncertainties of interpretations that often rely on one geophysical technique. Integrating these varying datasets requires a more robust classification approach rather than traditional qualitative methods. In this study, we applied the Fuzzy c-means (FCM) method to quantitatively classify similarities in a high resolution seismic tomography, a magnetotellurics and gravity datasets obtained in Montserrat. To group similar datapoints, this application uses a Euclidean distance measure and a membership function. Assigned membership values indicate the degree to which a datapoint belongs to a specific class. The spatial distribution of the derived classes, each classified with distinct geophysical parameters, helped to provide new structural and petrological information of the Montserrat geothermal system. In comparison to previous models, our new cluster model highlights two major improvements. These include the resolution and assessment of the spatial extension and 3D geometry of previously undetected features within the Montserrat geothermal system and the constrain and characterization of earlier identified anomalies. We additionally utilized geological and petrological data obtained from three geothermal wells in the Montserrat geothermal system to help validate our classifications. Based on a semi-quantitative approach we assessed the reliability of the FCM technique in relation to the likely uncertainties of the different geophysical models.
Niche breadth and position can influence diversification among closely related species or populations, yet limited empirical data exist concerning the predictability of the outcomes. We explored the effects of these factors on the evolution of the Emoia atrocostata species group, an insular radiation of lizards in the western Pacific Ocean and Indo-Australasia composed of both endemic and widespread species that differ in niche occupancy. We used molecular data and phylogeographical diffusion models to estimate the timing and patterns of range expansion, and ancestral reconstruction methods to infer shifts in ecology. We show evidence of multidirectional spread from a centre of origin in western Micronesia, and that the phyletic diversity of the group is derived from a putative habitat specialist that survives in the littoral zone. This species is composed of paraphyletic lineages that represent stages or possible endpoints in the continuum toward speciation. Several descendant species have transitioned to either strand or interior forest habitat, but only on remote islands with depauperate terrestrial faunas. Our results suggest that the atrocostata group might be in the early phases of a Wilsonian taxon cycle and that the capacity to tolerate salt stress has promoted dispersal and colonization of remote oceanic islands. Divergence itself, however, is largely driven by geographical isolation rather than shifts in ecology.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biolinnean/blaa172","usgsCitation":"Richmond, J.Q., Ota, H., Grismer, L., and Fisher, R., 2021, Influence of niche breadth and position on the historical biogeography of seafaring scincid lizards: Biological Journal of the Linnean Society, v. 132, no. 1, p. 74-92, https://doi.org/10.1093/biolinnean/blaa172.","productDescription":"19 p.","startPage":"74","endPage":"92","ipdsId":"IP-123408","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biolinnean/blaa172","text":"Publisher Index Page"},{"id":391914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 104.23828125,\n -47.04018214480665\n ],\n [\n 165.76171875,\n -47.04018214480665\n ],\n [\n 165.76171875,\n 5.61598581915534\n ],\n [\n 104.23828125,\n 5.61598581915534\n ],\n [\n 104.23828125,\n -47.04018214480665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ota, Hidetoshi","contributorId":147501,"corporation":false,"usgs":false,"family":"Ota","given":"Hidetoshi","email":"","affiliations":[],"preferred":false,"id":827040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grismer, L Lee","contributorId":269404,"corporation":false,"usgs":false,"family":"Grismer","given":"L Lee","affiliations":[{"id":41086,"text":"La Sierra University","active":true,"usgs":false}],"preferred":false,"id":827041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217537,"text":"70217537 - 2021 - Age and mantle sources of Quaternary basalts associated with “leaky” transform faults of the migrating Anatolia-Arabia-Africa triple junction","interactions":[],"lastModifiedDate":"2021-02-04T14:30:00.957595","indexId":"70217537","displayToPublicDate":"2020-12-04T15:21:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Age and mantle sources of Quaternary basalts associated with “leaky” transform faults of the migrating Anatolia-Arabia-Africa triple junction","docAbstract":"The Anatolia (Eurasia), Arabia, and Africa tectonic plates intersect in southeast Turkey, near the Gulf of İskenderun, forming a tectonically active and unstable triple junction (the A3 triple junction). The plate boundaries are marked by broad zones of major, dominantly left-lateral transform faults including the East Anatolian fault zone (the Anatolia-Arabia boundary) and the Dead Sea fault zone (the Arabia-Africa boundary). Quaternary basalts occur locally within these “leaky” transform fault zones (similar to those observed within oceanic transform faults), providing evidence that mantle melting, basalt genesis, and eruption are linked to crustal deformation and faulting that extends into the upper mantle. We investigated samples of alkaline basalt (including basanite) from the Toprakkale and Karasu volcanic fields within a broad zone of transtension associated with these plate-boundary faults near the İskenderun and Amik Basins, respectively.
Toprakkale basalts and basanites have 40Ar/39Ar plateau ages ranging from 810 ± 60 ka to 46 ± 13 ka, and Karasu volcanic field basalts have 40Ar/39Ar plateau ages ranging from 2.63 ± 0.17 Ma to 52 ± 16 ka. Two basanite samples within the Toprakkale volcanic field have isotopic characteristics of a depleted mantle source, with 87Sr/86Sr of 0.703070 and 0.703136, 143Nd/144Nd of 0.512931 and 0.512893, 176Hf/177Hf of 0.283019 and 0.282995, 206Pb/204Pb of 19.087 and 19.155, and 208Pb/204Pb of 38.861 and 38.915. The 176Hf/177Hf ratios of Toprakkale basalts (0.282966–0.283019) are more radiogenic than Karasu basalts (0.282837–0.282965), with some overlap in 143Nd/144Nd ratios (0.512781–0.512866 vs. 0.512648–0.512806). Toprakkale 206Pb/204Pb ratios (19.025 ± 0.001) exhibit less variation than that observed for Karasu basalts (18.800–19.324), and 208Pb/204Pb values for Toprakkale basalts (38.978– 39.103) are slightly lower than values for Karasu basalts (39.100–39.219). Melting depths estimated for the basalts from both volcanic fields generally cluster between 60 and 70 km, whereas the basanites record melting depths of ~90 km. Depth estimates for the basalts largely correspond to the base of a thin lithosphere (~60 km) observed by seismic imaging. We interpret the combined radiogenic isotope data (Sr, Nd, Hf, Pb) from all alkaline basalts to reflect partial melting at the base of the lithospheric mantle. In contrast, seismic imaging indicates a much thicker (>100 km) lithosphere beneath southern Anatolia, a substantial part of which is likely subducted African lithosphere. This thicker lithosphere is adjacent to the surface locations of the basanites. Thus, the greater melting depths inferred for the basanites may include partial melt contributions either from the lithospheric mantle of the attached and subducting African (Cyprean) slab, or from partial melting of detached blocks that foundered due to convective removal of the Anatolian lithosphere and that subsequently melted at ~90 km depth within the asthenosphere.
The Quaternary basalts studied here are restricted to a broad zone of transtension formed in response to the development of the A3 triple junction, with an earliest erupted age of 2.63 Ma. This indicates that the triple junction was well established by this time. While the current position of the A3 triple junction is near the Amik Basin, faults and topographic expressions indicate that inception of the triple junction began as early as 5 Ma in a position farther to the northeast of the erupted basalts. Therefore, the position of the A3 triple junction appears to have migrated to the southwest since the beginning of the Pliocene as the Anatolia-Africa plate boundary has adjusted to extrusion (tectonic escape) of the Anatolia plate. Establishment of the triple junction over the past 5 m.y. was synchronous with rollback of the African slab beneath Anatolia and associated trench retreat, consistent with Pliocene uplift in Cyprus and with the current positions of plate boundaries. The A3 triple junction is considered to be unstable and likely to continue migrating to the southwest for the foreseeable geologic future.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02266.1","usgsCitation":"Cosca, M., Reid, M., Delph, J., Gencalioglu Kuscu, G., Blichert-Toft, J., Premo, W.R., Whitney, D., Teyssier, C., and Rojay, B., 2021, Age and mantle sources of Quaternary basalts associated with “leaky” transform faults of the migrating Anatolia-Arabia-Africa triple junction: Geosphere, v. 17, no. 1, p. 69-94, https://doi.org/10.1130/GES02266.1.","productDescription":"26 p.","startPage":"69","endPage":"94","ipdsId":"IP-118084","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02266.1","text":"Publisher Index Page"},{"id":382444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 33.94775390625,\n 35.82672127366604\n ],\n [\n 36.705322265625,\n 35.82672127366604\n ],\n [\n 36.705322265625,\n 37.020098201368114\n ],\n [\n 33.94775390625,\n 37.020098201368114\n ],\n [\n 33.94775390625,\n 35.82672127366604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cosca, Michael 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":33043,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":808602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mary","contributorId":248200,"corporation":false,"usgs":false,"family":"Reid","given":"Mary","affiliations":[{"id":49820,"text":"Northern Arizona U","active":true,"usgs":false}],"preferred":false,"id":808603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delph, Jonathan","contributorId":248201,"corporation":false,"usgs":false,"family":"Delph","given":"Jonathan","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":808604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gencalioglu Kuscu, Gonca","contributorId":248202,"corporation":false,"usgs":false,"family":"Gencalioglu Kuscu","given":"Gonca","email":"","affiliations":[{"id":49821,"text":"Muğla Sıtkı Koçman University","active":true,"usgs":false}],"preferred":false,"id":808605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blichert-Toft, Janne","contributorId":248203,"corporation":false,"usgs":false,"family":"Blichert-Toft","given":"Janne","affiliations":[{"id":49822,"text":"Ecole Normale Supérieure de Lyon","active":true,"usgs":false}],"preferred":false,"id":808606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Premo, Wayne R. 0000-0001-9904-4801 wpremo@usgs.gov","orcid":"https://orcid.org/0000-0001-9904-4801","contributorId":1697,"corporation":false,"usgs":true,"family":"Premo","given":"Wayne","email":"wpremo@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":808607,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitney, Donna","contributorId":248204,"corporation":false,"usgs":false,"family":"Whitney","given":"Donna","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":808608,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Teyssier, Christian","contributorId":248205,"corporation":false,"usgs":false,"family":"Teyssier","given":"Christian","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":808609,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rojay, Bora","contributorId":248206,"corporation":false,"usgs":false,"family":"Rojay","given":"Bora","email":"","affiliations":[{"id":49823,"text":"Middle East Technical University","active":true,"usgs":false}],"preferred":false,"id":808610,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227144,"text":"70227144 - 2021 - Infection status as the basis for habitat choices in a wild amphibian","interactions":[],"lastModifiedDate":"2022-01-03T15:39:28.742022","indexId":"70227144","displayToPublicDate":"2020-12-04T08:52:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Infection status as the basis for habitat choices in a wild amphibian","docAbstract":"Animals challenged with disease may select specific habitat conditions that help prevent or reduce infection. Whereas preinfection avoidance of habitats with a high risk of disease exposure has been documented in both captive and free-ranging animals, evidence of switching habitats after infection to support the clearing of the infection is limited to laboratory experiments. The extent to which wild animals proximately modify habitat choices in response to infection status thus remains unclear. We investigated preinfection behavioral avoidance and postinfection habitat switching using wild, radio-tracked boreal toads (Anaxyrus boreas boreas) in a population challenged with Batrachochytrium dendrobatidis (Bd), a pathogenic fungus responsible for a catastrophic panzootic affecting hundreds of amphibian species worldwide. Boreal toads did not preemptively avoid microhabitats with conditions conducive to Bd growth. Infected individuals, however, selected warmer, more open habitats, which were associated with elevated body temperature and the subsequent clearing of infection. Our results suggest that disease can comprise an important selective pressure on animal habitat and space use. Habitat selection models, therefore, may be greatly improved by including variables that quantify infection risk and/or the infection status of individuals through time.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/711927","usgsCitation":"Barrile, G.M., Chalfoun, A.D., and Walters, A.W., 2021, Infection status as the basis for habitat choices in a wild amphibian: American Naturalist, v. 197, no. 1, p. 128-137, https://doi.org/10.1086/711927.","productDescription":"10 p.","startPage":"128","endPage":"137","ipdsId":"IP-107230","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":454157,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/711927","text":"Publisher Index Page"},{"id":393736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5,\n 42.5\n ],\n [\n -110.35,\n 42.5\n ],\n [\n -110.35,\n 43\n ],\n [\n -110.5,\n 43\n ],\n [\n -110.5,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"197","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barrile, Gabriel M.","contributorId":270694,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel","email":"","middleInitial":"M.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":829777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829776,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229336,"text":"70229336 - 2021 - Resilient and rapid recovery of native trout after removal of a non-native trout","interactions":[],"lastModifiedDate":"2022-03-04T13:23:31.358573","indexId":"70229336","displayToPublicDate":"2020-12-04T07:18:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Resilient and rapid recovery of native trout after removal of a non-native trout","docAbstract":"While the importance of reducing impacts of non-native species is increasingly recognized in conservation, the feasibility of such actions is highly dependent upon several key uncertainties including stage of invasion, size of the ecosystem being restored, and magnitude of the restoration activity. Here, we present results of a multi-year, non-native brown trout (Salmo trutta) removal and native Bonneville cutthroat trout (Oncorhynchus clarkii utah) response to this removal in a small tributary in the Intermountain West, United States. We monitored trout for 10 years prior to the onset of eradication efforts, which included 2 years of mechanical removal followed by 2 years of chemical treatment. Cutthroat trout were then seeded with low numbers of both eggs and juvenile trout. We monitored demographics and estimated population growth rates and carrying capacities for cutthroat trout from long-term depletion estimate data, assuming logistic population growth. Following brown trout eradication and initial seeding efforts, cutthroat trout in this tributary have responded rapidly and have approached their estimated carrying capacity within 6 years. Population projections suggest a 95% probability that cutthroat trout will be at or above 90% of their carrying capacity within 10 years of the eradication of brown trout. Additionally, at least four age-classes are present including adults large enough to satisfy angling demand. These results demonstrate native trout species have substantial capacity to rapidly recover following removal of invasive species in otherwise minimally altered habitats. While tributaries such as like this study location are likely limited in extent individually, collectively they may serve such as source populations for larger connected systems. In such cases, these source populations may provide additional conservation potential through biotic resistance.
Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow (n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c02495","usgsCitation":"Wherry, S., Tesoriero, A.J., and Terziotti, S., 2021, Factors affecting nitrate concentrations in stream base flow: Environmental Science and Technology, v. 55, no. 2, p. 902-911, https://doi.org/10.1021/acs.est.0c02495.","productDescription":"10 p.","startPage":"902","endPage":"911","ipdsId":"IP-109230","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":436629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RXR45G","text":"USGS data release","linkHelpText":"Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)"},{"id":381871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, 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Center","active":true,"usgs":true}],"preferred":true,"id":807557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217206,"text":"70217206 - 2021 - The birth of a Hawaiian fissure eruption","interactions":[],"lastModifiedDate":"2021-01-12T12:59:59.391343","indexId":"70217206","displayToPublicDate":"2020-12-04T06:52:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The birth of a Hawaiian fissure eruption","docAbstract":"Most basaltic explosive eruptions intensify abruptly, allowing little time to document processes at the start of eruption. One opportunity came with the initiation of activity from fissure 8 (F8) during the 2018 eruption on the lower East Rift Zone of Kīlauea, Hawaii. F8 erupted in four episodes. We recorded 28 min of high‐definition video during a 51‐min period, capturing the onset of the second episode on 5 May. From the videos, we were able to analyze the following in‐flight parameters: frequency and duration of explosions; ejecta heights; pyroclast exit velocities; in‐flight total mass and estimated mass eruption rates; and the in‐flight total grain size distributions. The videos record a transition from initial pulsating outgassing, via spaced, but increasingly rapid, discrete explosions, to quasisustained, unsteady fountaining. This transition accompanied waxing intensity (mass flux) of the F8 eruption. We infer that all activity was driven by a combination of the ascent of a coupled mixture of small bubbles and melt, and the buoyant rise of decoupled gas slugs and/or pockets. The balance between these two types of concurrent flow determined the exact form of the eruptive activity at any point in time, and changes to their relative contributions drove the transition we observed at early F8. Qualitative observations of other Hawaiian fountains at Kīlauea suggest that this physical model may apply more generally. This study demonstrates the value of in‐flight parameters derived from high‐resolution videos, which offer a rapid and highly time‐sensitive alternative to measurements based on sampling of deposits posteruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020903","usgsCitation":"Houghton, B.F., Tisdale, C.M., Llewellin, E.W., Taddeucci, J., Orr, T.R., Walker, B.H., and Patrick, M.R., 2021, The birth of a Hawaiian fissure eruption: Journal of Geophysical Research: Solid Earth, v. 126, no. 1, e2020JB020903, 17 p., https://doi.org/10.1029/2020JB020903.","productDescription":"e2020JB020903, 17 p.","ipdsId":"IP-120595","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1255250","text":"External Repository"},{"id":382080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hawaii","otherGeospatial":"Island of Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.11572265624997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 18.875102750356465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":807999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tisdale, Caroline M.","contributorId":247598,"corporation":false,"usgs":false,"family":"Tisdale","given":"Caroline","middleInitial":"M.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":808000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Llewellin, Edward W. 0000-0003-2165-7426","orcid":"https://orcid.org/0000-0003-2165-7426","contributorId":247599,"corporation":false,"usgs":false,"family":"Llewellin","given":"Edward","email":"","middleInitial":"W.","affiliations":[{"id":25252,"text":"Durham University","active":true,"usgs":false}],"preferred":true,"id":808001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taddeucci, Jacopo 0000-0002-0516-3699","orcid":"https://orcid.org/0000-0002-0516-3699","contributorId":184101,"corporation":false,"usgs":false,"family":"Taddeucci","given":"Jacopo","email":"","affiliations":[],"preferred":false,"id":808002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Brett H.","contributorId":225523,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"H.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":808004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808005,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217650,"text":"70217650 - 2021 - The induced Mw 5.0 March 2020 west Texas seismic sequence","interactions":[],"lastModifiedDate":"2021-01-27T13:03:11.497441","indexId":"70217650","displayToPublicDate":"2020-12-04T06:42:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The induced Mw 5.0 March 2020 west Texas seismic sequence","docAbstract":"On March 26, 2020, a M 5.0 earthquake occurred in the Delaware Basin, Texas, near the border between Reeves and Culberson Counties. This was the third largest earthquake recorded in Texas and the largest earthquake in the Central and Eastern United States since the three M 5.0–5.8 induced events in Oklahoma during 2016. Using multistation waveform template matching, we detect 3,940 earthquakes in the sequence with the first event in the area occurring in May 2018. The M 5.0 earthquake sequence occurred on a ENE (∼082°) normal fault dipping ∼37° toward the south. The earthquake caused 6 mm of oblique surface deformation, and geodetic slip inversion suggests slip was isolated above 6 km depth. We find that the sequence was most likely induced by nearby wastewater disposal operations, and seismicity rates in the region surrounding the M 5.0 will likely continue to increase in the future if disposal operations continue unaltered.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020693","usgsCitation":"Skoumal, R., Kaven, J., Barbour, A.J., Wicks, C., Brudzinski, M.R., Cochran, E.S., and Rubinstein, J., 2021, The induced Mw 5.0 March 2020 west Texas seismic sequence: Journal of Geophysical Research: Solid Earth, v. 126, no. 1, e2020JB020693, 17 p., https://doi.org/10.1029/2020JB020693.","productDescription":"e2020JB020693, 17 p.","ipdsId":"IP-120659","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":382575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.919189453125,\n 31.043521630684204\n ],\n [\n -103.29345703125,\n 31.043521630684204\n ],\n [\n -103.29345703125,\n 31.99875937194732\n ],\n [\n -105.919189453125,\n 31.99875937194732\n ],\n [\n -105.919189453125,\n 31.043521630684204\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Skoumal, Robert","contributorId":217693,"corporation":false,"usgs":true,"family":"Skoumal","given":"Robert","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaven, Joern 0000-0003-2625-2786","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":217694,"corporation":false,"usgs":true,"family":"Kaven","given":"Joern","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wicks, Charles 0000-0002-0809-1328","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":9023,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brudzinski, Michael R. 0000-0003-1869-0700","orcid":"https://orcid.org/0000-0003-1869-0700","contributorId":207880,"corporation":false,"usgs":false,"family":"Brudzinski","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":809115,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809116,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":809117,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217898,"text":"70217898 - 2021 - Evidence that watershed nutrient management practices effectively reduce estrogens in environmental waters","interactions":[],"lastModifiedDate":"2021-02-10T13:41:33.260981","indexId":"70217898","displayToPublicDate":"2020-12-03T07:37:03","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":"Evidence that watershed nutrient management practices effectively reduce estrogens in environmental waters","docAbstract":"We evaluate the impacts of different nutrient management strategies on the potential for co-managing estrogens and nutrients in environmental waters of the Potomac watershed of the Chesapeake Bay. These potential co-management approaches represent agricultural and urban runoff, wastewater treatment plant effluent, and combined sewer overflow replacements. Twelve estrogenic compounds and their metabolites were analysed by gas chromatography–mass spectrometry. Estrogenic activity (E2Eq) was measured by in vitro bioassay. We detected estrone E1 (0.05–6.97 ng L−1) and estriol E3 (below detection-8.13 ng L−1) and one conjugated estrogen (estrone-3-sulfate E1-3S; below detection-8.13 ng L−1). E1 was widely distributed and positively correlated with E2Eq, water temperature, and dissolved organic carbon (DOC). Among nonpoint sources, E2Eq, and concentrations of E1, soluble reactive phosphorus (SRP) and total dissolved nitrogen (TDN) decreased by 51–61%, 77–82%, 62–64%, 4–16% in restored urban and agricultural streams with best management practices (BMPs) relative to unrestored streams without BMPs. In a wastewater treatment plant (Blue Plains WWTP), >94% of E1, E1-3S, E3, E2Eq and TDN were removed while SRP increased by 305% during nitrification/denitrification as a part of advanced wastewater treatment. Consequently, E1 and TDN concentrations in WWTP effluents were comparable or even lower than those observed in the receiving stream or river waters, and the effects of wastewater discharges on downstream E1 and TDN concentrations were minor. Highest E2Eq value and concentrations of E1, E3, and TDN were detected in combined sewer overflow (CSO). This study suggests that WWTP upgrades with biological nutrient removal, CSO management, and certain agricultural and urban BMPs for nutrient controls have the potential to remove estrogens from point and nonpoint sources along with other contaminants in streams and rivers.
Long known as the island chain farthest from any continental landmass, the Hawaiian Islands are the subaerial expression of volcanism above the relatively fixed Hawaiian hot spot as the Pacific plate drifts northwest above it. Each island is built by one or several overlapping shield volcanoes, some of the most voluminous on Earth. Plate translation creates the well-known age-progressive sequence of shield volcanoes from northwest to southeast. Total volume of magma produced along the Hawaiian chain has been irregular but generally increasing for the past 50 million years, a trend that has peaked in the last 3 million years.
Hawaiian volcanoes grow through stages that have geologic expression and geochemical differences that reflect position relative to the underlying hot spot. Of these stages, the shield stage is the most productive when an estimated 80–95% of a volcano's ultimate volume is emplaced. The shield stage endures for about 1 million years.
The burden of shield volcanoes depresses the ocean crust near the hot spot, creating the Hawaiian Moat. Greatest rate of subsidence today occurs at the Island of Hawai‘i, 2–3 mm per year along its coast. Flexural rebound occurs as volcanoes move away from the hot spot; the Island of O‘ahu shows the greatest uplift. Slow subsidence resumes downstream from the flexure, leading ultimately to submergence of each island in the chain.
Large landslides, albeit infrequent, can occur at any stage of island evolution. Ground water is the principal source of potable and agricultural water on all islands; its distribution both reflects and influences island geology.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sinton, John M","contributorId":261682,"corporation":false,"usgs":false,"family":"Sinton","given":"John M","affiliations":[{"id":52956,"text":"University of Hawai‘i at Mānoa, Honolulu, Hawai‘i,","active":true,"usgs":false}],"preferred":false,"id":820408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820409,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251779,"text":"70251779 - 2021 - Porphyry and epithermal mineral deposits","interactions":[],"lastModifiedDate":"2024-02-28T15:46:44.606969","indexId":"70251779","displayToPublicDate":"2020-12-02T09:45:21","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Porphyry and epithermal mineral deposits","docAbstract":"Porphyry and epithermal mineral deposits form large economic ore bodies that provide the global economy with copper, molybdenum, gold, silver and other byproducts (Re, Te, Se). They form in the upper crust and are related to sulfur- and water-rich intermediate to silicic magmatic sources of hydrothermal fluids that move upward and produce extensive hydrolytic and alkali wall-rock alteration, quartz veins, and sulfides. Porphyry-type deposits are formed above magma chambers where fluids hydrofracture rock at 700–350 °C and at pressures ranging from supra-lithostatic to supra-hydrostatic. The depth of formation ranges from 2 to 10 km and influences orebody geometries and the types and mineralogy of veins, sulfides and wall-rock alteration. The temporal evolution of hydrothermal events is documented by cross-cutting veins and is commonly characterized by a decline in fluid temperature and concordant evolution from potassic alteration to sericitic alteration, with attendant increase in sulfidation state of copper-iron sulfides.
In some localities porphyry copper deposits transition upwards to lower temperature base metal lodes (350–200 °C) and eventually the formation of near surface (<1.5 km depth) intermediate- and high-sulfidation epithermal deposits (~300–120 °C). Extensional environments are often characterized by porphyry molybdenum and low-sulfidation epithermal deposits. In the base metal lode and epithermal environments, mixtures of magmatic and meteoric fluids produce ore fluids at hydrostatic pressures that advect freely both vertically and laterally along permeability provided by faults, joints, and porous lithologies. Wall-rock alteration ranges from hydrolytic to alkali-carbonate, and from high- to low-sulfidation state sulfide assemblages, respectively.
In porphyry, base metal lode, and epithermal environments, geology and the zonation of wall-rock alteration, veins, sulfide assemblages, and metals are useful for exploration.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology (secind editon)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-102908-4.00005-9","usgsCitation":"Dilles, J.H., and John, D.A., 2021, Porphyry and epithermal mineral deposits, chap. of Encyclopedia of geology (secind editon), p. 847-866, https://doi.org/10.1016/B978-0-08-102908-4.00005-9.","productDescription":"20 p.","startPage":"847","endPage":"866","ipdsId":"IP-116791","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":426066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dilles, John H","contributorId":214317,"corporation":false,"usgs":false,"family":"Dilles","given":"John","email":"","middleInitial":"H","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216879,"text":"70216879 - 2021 - Ocean floor manganese deposits","interactions":[],"lastModifiedDate":"2020-12-11T14:49:39.09465","indexId":"70216879","displayToPublicDate":"2020-12-02T08:46:13","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Ocean floor manganese deposits","docAbstract":"Much of the dissolved Mn delivered to the oceans is slowly oxidized and precipitated alongside varying amounts of Fe into Mn and ferromanganese (FeMn) mineral deposits that occur extensively in the deep ocean wherever sediment accumulation is low and substrate is available. FeMn crusts grow as pavements on rock outcrops throughout the global ocean whereas nodules form as individual FeMn-encrusted particles on the sediment-covered abyssal plains. Both crusts and nodules are composed predominantly of Fe and Mn oxide minerals that precipitate from seawater and for some nodules also from porewaters of deep-sea sediment. In contrast, hydrothermal oxide deposits consist predominantly of Mn or Fe oxide. FeMn crusts and nodules exhibit very high specific surface areas that allow them to scavenge abundant metals and other elements, recording the history of the source waters. Crusts especially serve as an important record of paleoceanographic conditions over the past 70 + million years. Critical metals essential to many computer, military, and green technologies are enriched in crust and nodule deposits to concentrations high enough to compare with, or exceed, typical terrestrial deposits, and they can be considered as potential resources for mining in the near future. Twenty-three contracts pertaining to exploration for nodules and crusts have been signed with the International Seabed Authority, and resource/reserve, baseline, and environmental impact assessments are underway. Many challenges remain to be addressed before full-scale mining of marine FeMn deposits will occur. However, their unique genesis and the growing worldwide need for rare and critical metals keep these deep-ocean deposits relevant to industry, scientists, and governments.
Soils are naturally occurring bodies that form in the interface between the geosphere, biosphere, hydrosphere, and atmosphere. They are the medium for much of the Earth's plant and animal growth. Soil morphology and how it evolves are functions of the soil-forming factors of climate, organisms, relief, parent material, and time. The expression of soil morphology takes the form of layers, called horizons, that differ in their color, particle size distribution, structure, chemistry, and organic matter content from the parent material. A fundamental soil mapping unit in the USA is the soil order and 12 soil orders have been defined on the basis of soil morphology, physical and chemical properties, and climate. Soil geography in the USA is explained by an examination of how these 12 soil orders are found in particular climates, under specific vegetation communities, how they develop from compositionally distinct parent materials, or how they are a result of the age of soil parent material. Paleosols are ancient soils, those that formed in the past. Three types of paleosols are recognized, buried soils (those covered by a younger sediment or rock), exhumed paleosols (formerly buried soils that are now exposed at the surface due to erosion of overlying materials), and relict paleosols (soils that occur at the land surface, but which formed in an environment, such as a climate or biome, very different from that at the present time). Paleosols can help define geologic contacts and can aid in elucidating past climates or vegetation regimes. Although there are rich geologic records of paleosols in the Quaternary, there is an increasing recognition of the importance of all these features in the longer, pre-Quaternary geologic record.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12002-0","usgsCitation":"Muhs, D.R., 2021, Soils and paleosols, chap. of Encyclopedia of geology, p. 370-384, https://doi.org/10.1016/B978-0-12-409548-9.12002-0.","productDescription":"15 p.","startPage":"370","endPage":"384","ipdsId":"IP-109564","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":396903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":837628,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70229501,"text":"70229501 - 2021 - Eolian sediments","interactions":[],"lastModifiedDate":"2022-03-09T14:20:27.61191","indexId":"70229501","displayToPublicDate":"2020-12-02T08:17:11","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Eolian sediments","docAbstract":"The origin and nature of eolian (wind-blown) sediments are reviewed, with an emphasis on the occurrence of these features in the Quaternary. Eolian sediments consist of windblown sand, loess, and long-range-transported (LRT) dust, in order of decreasing particle size. Eolian sand forms some of the most dramatic landscapes in the world, particularly when these sediments are deposited as dunes in sand seas. The largest eolian sand seas are found in subtropical deserts and in mid-latitude basins that are arid because of rainshadow effects. Dunes can be helpful in interpreting past climates, both for understanding past moisture balance and paleowinds (past wind directions). Loess is windblown silt that can be recognized in the field and mapped as a geologic body. It can be many tens of meters thick, but usually decreases systematically with distance from its source or sources. Much loess is glaciogenic, the result of glacial grinding of bedrock into “rock flour” that is easily entrained by the wind, but some loess owes its origins to nonglacial processes or is simply inherited from silt-rich rocks. The geologic record shows that both glacial loess and non-glacial loess accumulated mostly during glacial periods, suggesting that particular environmental conditions are favorable for loess accumulation. These conditions include increased source sediments, a dry, windy environment with minimal vegetation cover, and a decreased intensity of the hydrological cycle. The same conditions apparently enhance the production of LRT dust, which consists of particles generally less than 10 μm. At present, most dust sources are in the same regions where the largest eolian sand seas occur, although sandy sediments are not the only sources of finer-grained dust. LRT dust can be transported across oceans, from continent to continent, and may play important roles in the overall planetary radiation balance, as fertilizer to the world's primary producers in the oceans, and as a soil parent material. Geologic records of LRT dust transport can be found in deep-sea sediments, ice caps, lakes, distal loess deposits, and soils. These records indicate that, like loess, the flux of dust was greater during glacial periods. Although eolian sand, loess, and LRT dust all have rich geologic records in the Quaternary, there is an increasing recognition of the importance of all these features in the longer, pre-Quaternary geologic record.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12491-1","usgsCitation":"Muhs, D.R., 2021, Eolian sediments, chap. of Encyclopedia of Geology, p. 348-369, https://doi.org/10.1016/B978-0-12-409548-9.12491-1.","productDescription":"22 p.","startPage":"348","endPage":"369","ipdsId":"IP-108752","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":396901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd editionE","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":837629,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}