{"pageNumber":"543","pageRowStart":"13550","pageSize":"25","recordCount":184617,"records":[{"id":70220309,"text":"70220309 - 2021 - Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought","interactions":[],"lastModifiedDate":"2021-05-06T11:43:32.142205","indexId":"70220309","displayToPublicDate":"2020-12-29T07:19:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought","docAbstract":"<p><span>Recent snow droughts associated with unusually warm winters are predicted to increase in frequency and affect species dependent upon snowpack for winter survival. Changes in populations of some cold‐adapted species have been attributed to heat stress or indirect effects on habitat from unusually warm summers, but little is known about the importance of winter weather to population dynamics and how responses to snow drought vary among sympatric species. We evaluated changes in abundance of hoary marmots (</span><i>Marmota caligata</i><span>) over a period that included a year of record‐low snowpack to identify mechanisms associated with weather and snowpack. To consider interspecies comparisons, our analysis used the same a priori model set as a concurrent study that evaluated responses of American pikas (</span><i>Ochotona princeps</i><span>) to weather and snowpack in the same study area of North Cascades National Park, Washington, USA. We hypothesized that marmot abundance reflected mechanisms related to heat stress, cold stress, cold exposure without an insulating snowpack, snowpack duration, atmospheric moisture, growing‐season precipitation, or select combinations of these mechanisms. Changes in marmot abundances included a 74% decline from 2007 to 2016 and were best explained by an interaction of chronic dryness with exposure to acute cold without snowpack in winter. Physiological stress during hibernation from exposure to cold, dry air appeared to be the most likely mechanism of change in marmot abundance. Alternative mechanisms associated with changes to winter weather, including early emergence from hibernation or altered vegetation dynamics, had less support. A post hoc assessment of vegetative phenology and productivity did not support vegetation dynamics as a primary driver of marmot abundance across years. Although marmot and pika abundances were explained by strikingly similar models over periods of many years, details of the mechanisms involved likely differ between species because pika abundances increased in areas where marmots declined. Such differences may lead to diverging geographic distributions of these species as global change continues.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7126","usgsCitation":"Johnston, A.N., Christophersen, R.G., Beever, E.A., and Ransom, J.I., 2021, Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought: Ecology and Evolution, v. 11, no. 3, p. 1264-1279, https://doi.org/10.1002/ece3.7126.","productDescription":"16 p.","startPage":"1264","endPage":"1279","ipdsId":"IP-108644","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453991,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7126","text":"External Repository"},{"id":436605,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0QEDT","text":"USGS data release","linkHelpText":"Hoary Marmot Abundance in North Cascades National Park 2007-2008 and 2016-2017"},{"id":385448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.86035156249999,\n              47.60616304386874\n            ],\n            [\n              -118.5205078125,\n              47.60616304386874\n            ],\n            [\n              -118.5205078125,\n              48.980216985374994\n            ],\n            [\n              -121.86035156249999,\n              48.980216985374994\n            ],\n            [\n              -121.86035156249999,\n              47.60616304386874\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christophersen, Roger G","contributorId":257828,"corporation":false,"usgs":false,"family":"Christophersen","given":"Roger","email":"","middleInitial":"G","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":815107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ransom, Jason I.","contributorId":139841,"corporation":false,"usgs":false,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":815109,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217250,"text":"70217250 - 2021 - Apparent earthquake rupture predictability","interactions":[],"lastModifiedDate":"2021-02-17T22:01:37.15345","indexId":"70217250","displayToPublicDate":"2020-12-29T07:17:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Apparent earthquake rupture predictability","docAbstract":"<p class=\"chapter-para\">To what extent can the future evolution of an ongoing earthquake rupture be predicted? This question of fundamental scientific and practical importance has recently been addressed by studies of teleseismic source time functions (STFs) but reaching contrasting conclusions. One study concludes that the initial portion of STFs is the same regardless of magnitude. Another study concludes that the rate at which earthquakes grow increases systematically and strongly with final event magnitudes. Here we show that the latter reported trend is caused by a selection bias towards events with unusually long durations, and by estimates of STF growth made when the STF is already decaying. If these invalid estimates are left out, the trend is no longer present, except during the first few seconds of the smallest events in the dataset, Mw5–6.5, for which the reliability of the STF amplitudes is questionable. Simple synthetic tests show that the observations are consistent with statistically indistinguishable growth of smaller and larger earthquakes. A much weaker trend is apparent among events of comparable duration, but we argue that its significance is not resolvable by the current data. Finally, we propose a nomenclature to facilitate further discussions of earthquake rupture predictability and determinism.</p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggaa610","usgsCitation":"Meier, M., Ampuero, P., Cochran, E.S., and Page, M.T., 2021, Apparent earthquake rupture predictability: Geophysical Journal International, v. 225, p. 657-663, https://doi.org/10.1093/gji/ggaa610.","productDescription":"7 p.","startPage":"657","endPage":"663","ipdsId":"IP-124434","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453997,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/gji/ggaa610","text":"External Repository"},{"id":382147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"225","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Meier, M.-A.","contributorId":222138,"corporation":false,"usgs":false,"family":"Meier","given":"M.-A.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":808149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ampuero, P.","contributorId":247704,"corporation":false,"usgs":false,"family":"Ampuero","given":"P.","email":"","affiliations":[{"id":49622,"text":"Université Côte d’Azur","active":true,"usgs":false}],"preferred":false,"id":808150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":808151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":808152,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236888,"text":"70236888 - 2021 - A ground‐motion prediction model for shallow crustal earthquakes in Greece","interactions":[],"lastModifiedDate":"2022-09-21T12:17:14.197561","indexId":"70236888","displayToPublicDate":"2020-12-29T07:14:39","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":"A ground‐motion prediction model for shallow crustal earthquakes in Greece","docAbstract":"<p><span>Using a recently completed database of uniformly processed strong‐motion data recorded in Greece, we derive a ground‐motion prediction model (GMPM) for horizontal‐component peak ground velocity, peak ground acceleration, and 5% damped pseudoacceleration response spectra, at 105 periods ranging from 0.01 to 10&nbsp;s. The equations were developed by modifying a global GMPM, to account for more rapid attenuation and weaker magnitude scaling in the Greek ground motions than in the global GMPM. Our GMPM is calibrated using the Greek data for distances up to 300&nbsp;km, magnitudes from 4.0 to 7.0, and time‐averaged 30&nbsp;m shear‐wave velocities from 150 to&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mn xmlns=&quot;&quot;>1200</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>m</mi><mo xmlns=&quot;&quot;>/</mo><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>s</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mn\">1200</span><span id=\"MathJax-Span-4\" class=\"mtext\">  </span><span id=\"MathJax-Span-5\" class=\"mi\">m</span><span id=\"MathJax-Span-6\" class=\"mo\">/</span><span id=\"MathJax-Span-7\" class=\"mi\">s</span></span></span></span><span class=\"MJX_Assistive_MathML\">1200  m/s</span></span>⁠</span><span>. The GMPM has important attributes for hazard applications including magnitude scaling that extends the range of applicability to&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-8\" class=\"math\"><span><span id=\"MathJax-Span-9\" class=\"mrow\"><span id=\"MathJax-Span-10\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span><span>&nbsp;8.0 and nonlinear site response. These features are possible because they are well constrained by data in the global GMPM from which our model is derived. An interesting feature of the Greek data, also observed previously in studies of mid‐magnitude events (6.1–6.5) in Italy, is that they are substantially overpredicted by the global GMPM, which may be a repeatable regional feature, but may also be influenced by soil–structure interaction. This bias is an important source of epistemic uncertainty that should be considered in hazard analysis.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200270","usgsCitation":"Boore, D., Stewart, J.P., Skarlatoudis, A., Seyhan, E., Margaris, B., Theodoulidis, N., Scordilis, E., Kalogeras, I., Klimis, N., and Melis, N., 2021, A ground‐motion prediction model for shallow crustal earthquakes in Greece: Bulletin of the Seismological Society of America, v. 111, no. 2, p. 857-874, https://doi.org/10.1785/0120200270.","productDescription":"18 p.","startPage":"857","endPage":"874","ipdsId":"IP-121145","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greece","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[23.69998,35.705],[24.24667,35.36802],[25.02502,35.425],[25.76921,35.35402],[25.74502,35.18],[26.29,35.29999],[26.165,35.005],[24.72498,34.91999],[24.73501,35.08499],[23.51498,35.27999],[23.69998,35.705]]],[[[26.6042,41.56211],[26.2946,40.93626],[26.05694,40.82412],[25.44768,40.85255],[24.92585,40.94706],[23.71481,40.68713],[24.408,40.12499],[23.89997,39.96201],[23.343,39.961],[22.81399,40.47601],[22.6263,40.25656],[22.84975,39.65931],[23.35003,39.19001],[22.9731,38.9709],[23.53002,38.51],[24.02502,38.21999],[24.04001,37.65501],[23.115,37.92001],[23.40997,37.40999],[22.77497,37.30501],[23.15423,36.42251],[22.49003,36.41],[21.67003,36.84499],[21.29501,37.64499],[21.12003,38.31032],[20.73003,38.76999],[20.21771,39.34023],[20.15002,39.625],[20.615,40.11001],[20.675,40.435],[20.99999,40.58],[21.02004,40.84273],[21.67416,40.93127],[22.05538,41.14987],[22.59731,41.13049],[22.76177,41.3048],[22.95238,41.33799],[23.69207,41.30908],[24.49264,41.5839],[25.1972,41.23449],[26.10614,41.3289],[26.11704,41.8269],[26.6042,41.56211]]]]},\"properties\":{\"name\":\"Greece\"}}]}","volume":"111","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":852466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":852467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skarlatoudis, Andreas","contributorId":296779,"corporation":false,"usgs":false,"family":"Skarlatoudis","given":"Andreas","email":"","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":852468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seyhan, Emel","contributorId":51193,"corporation":false,"usgs":false,"family":"Seyhan","given":"Emel","email":"","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":852469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Margaris, Basil","contributorId":296782,"corporation":false,"usgs":false,"family":"Margaris","given":"Basil","email":"","affiliations":[{"id":64170,"text":"ITSAK","active":true,"usgs":false}],"preferred":false,"id":852470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Theodoulidis, Nikos","contributorId":296783,"corporation":false,"usgs":false,"family":"Theodoulidis","given":"Nikos","email":"","affiliations":[{"id":64170,"text":"ITSAK","active":true,"usgs":false}],"preferred":false,"id":852471,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scordilis, Emmanual","contributorId":296784,"corporation":false,"usgs":false,"family":"Scordilis","given":"Emmanual","email":"","affiliations":[{"id":64173,"text":"Dept. of Geophysics, Faculty of Sciences, Aristotle University","active":true,"usgs":false}],"preferred":false,"id":852472,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kalogeras, Ionnis","contributorId":296785,"corporation":false,"usgs":false,"family":"Kalogeras","given":"Ionnis","email":"","affiliations":[{"id":47503,"text":"Institute of Geodynamics, National Observatory of Athens","active":true,"usgs":false}],"preferred":false,"id":852473,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Klimis, Nikos","contributorId":296786,"corporation":false,"usgs":false,"family":"Klimis","given":"Nikos","email":"","affiliations":[{"id":64174,"text":"Democritus University of Thrace","active":true,"usgs":false}],"preferred":false,"id":852474,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Melis, Nikos","contributorId":296787,"corporation":false,"usgs":false,"family":"Melis","given":"Nikos","email":"","affiliations":[{"id":64175,"text":"INSTITUTE OF GEODYNAMICS NATIONAL, OBSERVATORY OF ATHENS","active":true,"usgs":false}],"preferred":false,"id":852475,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70217081,"text":"70217081 - 2021 - Red imported fire ants reduce invertebrate abundance, richness, and diversity in Gopher Tortoise burrows","interactions":[],"lastModifiedDate":"2021-01-05T13:20:51.185686","indexId":"70217081","displayToPublicDate":"2020-12-29T07:14:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Red imported fire ants reduce invertebrate abundance, richness, and diversity in Gopher Tortoise burrows","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Gopher Tortoise (<span class=\"html-italic\">Gopherus polyphemus</span>) burrows support diverse commensal invertebrate communities that may be of special conservation interest. We investigated the impact of red imported fire ants (<span class=\"html-italic\">Solenopsis invicta</span>) on the invertebrate burrow community at 10 study sites in southern Mississippi, sampling burrows (1998–2000) before and after bait treatments to reduce fire ant populations. We sampled invertebrates using an ant bait attractant for ants and burrow vacuums for the broader invertebrate community and calculated fire ant abundance, invertebrate abundance, species richness, and species diversity. Fire ant abundance in gopher tortoise burrows was reduced by &gt;98% in treated sites. There was a positive treatment effect on invertebrate abundance, diversity, and species richness from burrow vacuum sampling which was not observed in ant sampling from burrow baits. Management of fire ants around burrows may benefit both threatened gopher tortoises by reducing potential fire ant predation on hatchlings, as well as the diverse burrow invertebrate community. Fire-ant management may also benefit other species utilizing tortoise burrows, such as the endangered Dusky Gopher Frog and Schaus swallowtail butterfly. This has implications for more effective biodiversity conservation via targeted control of the invasive fire ant at gopher tortoise burrows.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/d13010007","usgsCitation":"Epperson, D.M., Allen, C., and Hogan, K.F., 2021, Red imported fire ants reduce invertebrate abundance, richness, and diversity in Gopher Tortoise burrows: Diversity, no. 1, 7, 14 p., https://doi.org/10.3390/d13010007.","productDescription":"7, 14 p.","ipdsId":"IP-122445","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d13010007","text":"Publisher Index Page"},{"id":381872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Camp Shelby Joint Forces Training Center","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.23782348632811,\n              31.17050982470345\n            ],\n            [\n              -89.18426513671875,\n              31.15405797549081\n            ],\n            [\n              -89.1815185546875,\n              31.0741083805733\n            ],\n            [\n              -88.92608642578124,\n              31.06940336686409\n            ],\n            [\n              -88.91784667968749,\n              31.12819929911196\n            ],\n            [\n              -88.94805908203124,\n              31.221022636447476\n            ],\n            [\n              -89.24331665039061,\n              31.21280145833882\n            ],\n            [\n              -89.23782348632811,\n              31.17050982470345\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","issue":"1","edition":"13","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Epperson, Deborah Mardeane 0000-0002-0567-4915","orcid":"https://orcid.org/0000-0002-0567-4915","contributorId":246028,"corporation":false,"usgs":true,"family":"Epperson","given":"Deborah","email":"","middleInitial":"Mardeane","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":807536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R.","contributorId":246029,"corporation":false,"usgs":false,"family":"Allen","given":"Craig R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":807537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, Katharine F.E.","contributorId":246030,"corporation":false,"usgs":false,"family":"Hogan","given":"Katharine","email":"","middleInitial":"F.E.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":807538,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217057,"text":"70217057 - 2021 - Effects-based monitoring of bioactive chemicals discharged to the Colorado River before and after a municipal wastewater treatment plant replacement","interactions":[],"lastModifiedDate":"2021-01-19T16:00:58.398085","indexId":"70217057","displayToPublicDate":"2020-12-29T07:00:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Effects-based monitoring of bioactive chemicals discharged to the Colorado River before and after a municipal wastewater treatment plant replacement","docAbstract":"<p><span>Monitoring of the Colorado River near the Moab, Utah, wastewater treatment plant (WWTP) outflow has detected pharmaceuticals, hormones, and estrogen-receptor (ER)-, glucocorticoid receptor (GR)-, and peroxisome proliferator-activated receptor-gamma (PPARγ)-mediated biological activities. The aim of the present multi-year study was to assess effects of a WWTP replacement on bioactive chemical (BC) concentrations. Water samples were collected bimonthly, pre- and post-replacement, at 11 sites along the Colorado River upstream and downstream of the WWTP and analyzed for&nbsp;</span><i>in vitro</i><span>&nbsp;bioactivities (e.g., agonism of ER, GR, and PPARγ) and BC concentrations; fathead minnows were cage deployed pre- and post-replacement at sites with varying proximities to the WWTP. Before the WWTP replacement,&nbsp;</span><i>in vitro</i><span>&nbsp;ER (24 ng 17β-estradiol equivalents/L)-, GR (60 ng dexamethasone equivalents/L)-, and PPARγ-mediated activities were detected at the WWTP outflow but diminished downstream. In March 2018, the WWTP effluent was acutely toxic to the fish, likely due to elevated ammonia concentrations. Following the WWTP replacement, ER, GR, and PPARγ bioactivities were reduced by approximately 60–79%, no toxicity was observed in caged fish, and there were marked decreases in concentrations of many BCs. Results suggest that replacement of the Moab WWTP achieved a significant reduction in BC concentrations to the Colorado River.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c05269","usgsCitation":"Cavallin, J., Battaglin, W., Beihoffer, J., Blackwell, B.D., Bradley, P., Cole, A., Ekman, D.R., Hofer, R., Kinsey, J., Keteles, K., Weissinger, R., Winkelman, D.L., and Villeneuve, D.L., 2021, Effects-based monitoring of bioactive chemicals discharged to the Colorado River before and after a municipal wastewater treatment plant replacement: Environmental Science and Technology, v. 55, no. 2, p. 974-984, https://doi.org/10.1021/acs.est.0c05269.","productDescription":"11 p.","startPage":"974","endPage":"984","ipdsId":"IP-119670","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":454003,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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,{"id":70218019,"text":"70218019 - 2021 - Lithium in groundwater used for drinking-water supply in the United States","interactions":[],"lastModifiedDate":"2021-02-12T13:36:33.223193","indexId":"70218019","displayToPublicDate":"2020-12-26T07:31:46","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":"Lithium in groundwater used for drinking-water supply in the United States","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0050\">Lithium concentrations in untreated groundwater from 1464 public-supply wells and 1676 domestic-supply wells distributed across 33 principal aquifers in the United States were evaluated for spatial variations and possible explanatory factors. Concentrations nationwide ranged from &lt;1 to 396&nbsp;μg/L (median of 8.1) for public supply wells and &lt;1 to 1700&nbsp;μg/L (median of 6&nbsp;μg/L) for domestic supply wells. For context, lithium concentrations were compared to a Health Based Screening Level (HBSL, 10&nbsp;μg/L) and a drinking-water only threshold (60&nbsp;μg/L). These thresholds were exceeded in 45% and 9% of samples from public-supply wells and in 37% and 6% from domestic-supply wells, respectively. However, exceedances and median concentrations ranged broadly across geographic regions and principal aquifers. Concentrations were highest in arid regions and older groundwater, particularly in unconsolidated clastic aquifers and sandstones, and lowest in carbonate-rock aquifers, consistent with differences in lithium abundance among major lithologies and rock weathering extent. The median concentration for public-supply wells in the unconsolidated clastic High Plains aquifer (central United States) was 24.6&nbsp;μg/L; 24% of the wells exceeded the drinking-water only threshold and 86% exceeded the HBSL. Other unconsolidated clastic aquifers in the arid West had exceedance rates comparable to the High Plains aquifer, whereas no public supply wells in the Biscayne aquifer (southern Florida) exceeded either threshold, and the highest concentration in that aquifer was 2.6&nbsp;μg/L. Multiple lines of evidence indicate natural sources for the lithium concentrations; however, anthropogenic sources may be important in the future because of the rapid increase of lithium battery use and subsequent disposal. Geochemical models demonstrate that extensive evaporation, mineral dissolution, cation exchange, and mixing with geothermal waters or brines may account for the observed lithium and associated constituent concentrations, with the latter two processes as major contributing factors.</p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.144691","usgsCitation":"Lindsey, B.D., Belitz, K., Cravotta, C., Toccalino, P., and Dubrovsky, N.M., 2021, Lithium in groundwater used for drinking-water supply in the United States: Science of the Total Environment, v. 767, 144691, 15 p., https://doi.org/10.1016/j.scitotenv.2020.144691.","productDescription":"144691, 15 p.","ipdsId":"IP-113406","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436606,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GCGY5K","text":"USGS data release","linkHelpText":"Inorganic Constituent and Ancillary Data for Evaluation of Lithium in Groundwater in the United States, 1991-2018"},{"id":383255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n  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0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":810233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213727,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","email":"","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":810235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubrovsky, Neil M. 0000-0001-7786-1149 nmdubrov@usgs.gov","orcid":"https://orcid.org/0000-0001-7786-1149","contributorId":1799,"corporation":false,"usgs":true,"family":"Dubrovsky","given":"Neil","email":"nmdubrov@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810236,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70218736,"text":"70218736 - 2021 - A unified model of crustal stress heterogeneity from borehole breakouts and earthquake focal mechanisms","interactions":[],"lastModifiedDate":"2021-03-10T13:19:08.525501","indexId":"70218736","displayToPublicDate":"2020-12-26T07:16:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"A unified model of crustal stress heterogeneity from borehole breakouts and earthquake focal mechanisms","docAbstract":"<p><span>Observations of crustal stress orientation from the regional inversion of earthquake focal mechanisms often conflict with those from borehole breakouts, possibly indicating local stress heterogeneity, either laterally or with depth. To investigate this heterogeneity, we compiled SHmax estimates from previous studies for 57 near‐vertical boreholes with measured breakout azimuths across the Los Angeles region. We identified subsets of earthquake focal mechanisms from established earthquake catalogs centered around each borehole with various criteria for maximum depth and maximum lateral distance from the borehole. Each subset was independently inverted for 3‐D stress orientation and corresponding SHmax probability distributions, then compared with the corresponding borehole breakout‐derived estimate. We find good agreement when both methods sample the basement stress (breakouts are close to the sediment‐basement interface), or when both methods sample the mid‐basin stress (sufficient earthquakes are present within a sedimentary basin). Along sedimentary basin margins, in contrast, we find acceptable agreement only when focal mechanisms are limited to shallow and close earthquakes, implying short‐length‐scale heterogeneity of &lt;20&nbsp;km. While the region as a whole shows evidence of both lateral and vertical stress orientation heterogeneity, we find a more homogeneous stress state within basement rock, over length scales of 1–35&nbsp;km. These results reconcile the apparently conflicting observations of short‐length‐scale heterogeneity observed in boreholes, which sample primarily the basins, with the relative homogeneity of stress inferred from focal mechanisms, which sample primarily the basement, and imply distinct regimes for the appropriate use of each type of stress indicator.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020817","usgsCitation":"Luttrell, K., and Hardebeck, J.L., 2021, A unified model of crustal stress heterogeneity from borehole breakouts and earthquake focal mechanisms: JGR Solid Earth, v. 126, no. 2, e2020JB020817, 13 p., https://doi.org/10.1029/2020JB020817.","productDescription":"e2020JB020817, 13 p.","ipdsId":"IP-121662","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":454007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb020817","text":"Publisher Index Page"},{"id":384262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Luttrell, Karen 0000-0003-1405-1207","orcid":"https://orcid.org/0000-0003-1405-1207","contributorId":254967,"corporation":false,"usgs":false,"family":"Luttrell","given":"Karen","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":811558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":811559,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219488,"text":"70219488 - 2021 - Shared functional traits explain synchronous changes in long‐term count trends of migratory raptors","interactions":[],"lastModifiedDate":"2021-10-26T16:09:06.790716","indexId":"70219488","displayToPublicDate":"2020-12-26T06:49:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Shared functional traits explain synchronous changes in long‐term count trends of migratory raptors","docAbstract":"<h3 id=\"geb13242-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Assessing long‐term shifts in faunal assemblages is important to understand the consequences of ongoing global environmental change. One approach to assess drivers of assemblage changes is to identify the traits associated with synchronous shifts in count trends among species. Our research identified traits influencing trends in 73&nbsp;years of count data on migrating raptors recorded in the north‐eastern USA.</p><h3 id=\"geb13242-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Pennsylvania, USA.</p><h3 id=\"geb13242-sec-0003-title\" class=\"article-section__sub-title section1\">Time period</h3><p>1946–2018.</p><h3 id=\"geb13242-sec-0004-title\" class=\"article-section__sub-title section1\">Major taxa studied</h3><p>Birds of prey/raptors.</p><h3 id=\"geb13242-sec-0005-title\" class=\"article-section__sub-title section1\">Methods</h3><p>Migrating raptors were counted during autumn, following a standardized protocol. We used a hierarchical breakpoint model to identify when count trends shifted and to assess the role of traits in driving these trends before and after the breakpoint. Specifically, we quantified the probability of the direction (PD) of an effect of body mass, habitat or dietary specialization, migratory behaviour and susceptibility to dichlorodiphenyltrichloroethane (DDT) on count trends.</p><h3 id=\"geb13242-sec-0006-title\" class=\"article-section__sub-title section1\">Results</h3><p>We documented an assemblage‐wide mean shift in count trends of migrating raptors in 1974. In general, species that exhibited negative count trends before the breakpoint exhibited positive count trends afterwards. We found that traits associated with resource use (diet and habitat specialization) had high probabilities of affecting count trends, pre‐ and post‐breakpoint (&gt;&nbsp;90%). Moreover, the direction of their effects differed during both periods. Unexpectedly, other traits we evaluated, including DDT susceptibility, had relatively weaker associations with count trends.</p><h3 id=\"geb13242-sec-0007-title\" class=\"article-section__sub-title section1\">Main conclusions</h3><p>Trait‐based frameworks have promise for testing generalized assumptions about drivers of population trajectories. Historically, DDT was considered a key driver of changes in raptor population trends. However, our analysis suggests that other factors were also relevant. Moreover, the positive association between count trends and generalist behaviour depended on the temporal context. This result has implications for other settings where demographic trends can be linked to traits and help to identify drivers of biodiversity change.</p>","language":"English","publisher":"Wiley","doi":"10.1111/geb.13242","usgsCitation":"Dumandan, P.K., Bildstein, K.L., Goodrich, L.J., Zaiats, A., Caughlin, T., and Katzner, T., 2021, Shared functional traits explain synchronous changes in long‐term count trends of migratory raptors: Global Ecology and Biogeography, v. 30, no. 3, p. 640-650, https://doi.org/10.1111/geb.13242.","productDescription":"11 p.","startPage":"640","endPage":"650","ipdsId":"IP-118350","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":384958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Dumandan, Patricia Kaye T. 0000-0003-3360-1534","orcid":"https://orcid.org/0000-0003-3360-1534","contributorId":257070,"corporation":false,"usgs":false,"family":"Dumandan","given":"Patricia","email":"","middleInitial":"Kaye T.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":813784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodrich, Laurie J. 0000-0001-8558-6538","orcid":"https://orcid.org/0000-0001-8558-6538","contributorId":257071,"corporation":false,"usgs":false,"family":"Goodrich","given":"Laurie","email":"","middleInitial":"J.","affiliations":[{"id":51980,"text":"Hawk Mountain Sanctuary","active":true,"usgs":false}],"preferred":false,"id":813785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zaiats, Andrii 0000-0001-8978-4152","orcid":"https://orcid.org/0000-0001-8978-4152","contributorId":257072,"corporation":false,"usgs":false,"family":"Zaiats","given":"Andrii","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":813787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813788,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217095,"text":"70217095 - 2021 - Fire controls annual bromes in northern great plains grasslands—Up to a point","interactions":[],"lastModifiedDate":"2021-01-06T13:33:28.974582","indexId":"70217095","displayToPublicDate":"2020-12-25T07:31:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Fire controls annual bromes in northern great plains grasslands—Up to a point","docAbstract":"<p><span>Concern about the impacts of two invasive annual brome grasses (cheatgrass and Japanese brome,&nbsp;</span><i>Bromus tectorum</i><span>&nbsp;L. and&nbsp;</span><i>B. japonicus</i><span>&nbsp;Thunb. ex Murray) on the mixed-grass prairie of North America's northern Great Plains (NGP) is growing. Cheatgrass is well known west of the NGP, where replacement of fire-intolerant, native sagebrush steppe by fire-prone, exotic annual grasslands is widespread. Consequently, fire is often not considered as a tool for controlling annual bromes. This should not be the case in the NGP, where mixed-grass prairie is adapted to frequent fires. Fire's efficacy may vary with the degree of invasion, though; suppressing postfire annual brome populations or enhancing the native plant community may improve postfire annual brome control in highly invaded areas. To test this, we performed an experiment at two sites to evaluate the relative effectiveness of prescribed fire alone, fire followed by imazapic application and fire followed by native seeding across a pretreatment invasion gradient of annual brome-to-native species cover ranging from 0.05 to 2.35. Fall-prescribed fire alone greatly reduced annual bromes, but by the second yr after treatment the effect was significant only at invasion ratios &lt; 1.2. Postfire imazapic application reduced annual bromes even further than fire alone, but only for 1 yr at the less invaded site and only at invasion ratios &gt; 1.2 in yr 2 at the other site. Native species cover and total species richness responded positively to all treatments, but the degree of their response varied along the invasion gradient, between sites, with time since treatment and among treatments. Also, at one site, fire yielded a lagged stimulation of short-lived, exotic forbs. Seeding had little effect. Fire is an effective tool for reducing annual bromes in the NGP at lower invasion levels, but more tools are needed for long-term, effective control at highly invaded sites.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2020.11.003","usgsCitation":"Symstad, A., Buhl, D.A., and Swanson, D., 2021, Fire controls annual bromes in northern great plains grasslands—Up to a point: Rangeland Ecology & Management, v. 75, p. 17-28, https://doi.org/10.1016/j.rama.2020.11.003.","productDescription":"12 p.","startPage":"17","endPage":"28","ipdsId":"IP-119284","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454011,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2020.11.003","text":"Publisher Index Page"},{"id":436607,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99MUP9L","text":"USGS data release","linkHelpText":"Plant community data for annual brome management experimental plots in grasslands of Badlands National Park, South Dakota, and Scotts Bluff National Monument, Nebraska, 2015-2018"},{"id":381944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Daniel J","contributorId":240932,"corporation":false,"usgs":false,"family":"Swanson","given":"Daniel J","affiliations":[{"id":48165,"text":"National Park Service, Hot Springs, SD","active":true,"usgs":false}],"preferred":false,"id":807602,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217054,"text":"70217054 - 2021 - A watershed moment: Analysis of sub-basins refocuses the geography of turtle conservation across the globe","interactions":[],"lastModifiedDate":"2020-12-30T12:56:39.90011","indexId":"70217054","displayToPublicDate":"2020-12-25T06:53:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A watershed moment: Analysis of sub-basins refocuses the geography of turtle conservation across the globe","docAbstract":"<p><span>Conservation planners use a variety of decision-making tools, many of which require identifying and prioritizing spatial units based on their biodiversity and levels of imperilment. Turtles are highly imperiled, but present schemes for determining global priority areas are focused mostly on broad regional scales. We conduct the first global evaluation of turtle biodiversity and imperilment at a sub-basin level to identify geographically smaller areas of high conservation value, and compare with these existing prioritizations. We employed two spatial analyses—bivariate maps and local indicator of spatial association (LISA)—to identify and prioritize sub-basin clusters based on multiple biodiversity and conservation metrics in addition to species richness. Most high-priority sub-basin clusters were located along tropical and subtropical coastlines. A new area of global significance for turtle conservation was identified in southwest India. Many sub-basins of the Indomalayan Realm were clustered as high or intermediate priority, with large clusters of high-priority sub-basins also in tropical Australasia. Other high and intermediate priority sub-basin clusters were found in the Afrotropical, Neotropical, and Nearctic realms, often in previously recognized turtle biodiversity hotspots. Many conservation-priority sub-basins with high turtle-species richness and endemism are in lowland and coastal areas where endemics (some from ancient lineages) are imperiled in association with a high human footprint. Our findings reiterate the global significance of Asia as a key area of chelonian conservation need, while identifying focal areas across the globe where the need for targeted turtle conservation is especially great.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108925","usgsCitation":"Ennen, J., Agha, M., Sweat, S.C., Matamoros, W.A., Lovich, J.E., Iverson, J.B., Rhodin, A.G., Thomson, R., Shaffer, H.B., and Hoagstrom, C.W., 2021, A watershed moment: Analysis of sub-basins refocuses the geography of turtle conservation across the globe: Biological Conservation, v. 253, 108925, 9 p.,, https://doi.org/10.1016/j.biocon.2020.108925.","productDescription":"108925, 9 p.,","ipdsId":"IP-122122","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":381752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"253","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":807405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false},{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":807406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweat, Sarah C.","contributorId":195519,"corporation":false,"usgs":false,"family":"Sweat","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":807407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matamoros, Wildredo A.","contributorId":245972,"corporation":false,"usgs":false,"family":"Matamoros","given":"Wildredo","email":"","middleInitial":"A.","affiliations":[{"id":49391,"text":"Facultad de Ciencias Biológicas, Universidad de Ciencias y Artes de Chiapas, Museo de Zoología, Tuxtla Gutiérrez, Chiapas, México Apartado Postal 29000, México","active":true,"usgs":false}],"preferred":false,"id":807408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iverson, John B.","contributorId":147488,"corporation":false,"usgs":false,"family":"Iverson","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":807410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodin, Anders G.J.","contributorId":212691,"corporation":false,"usgs":false,"family":"Rhodin","given":"Anders","email":"","middleInitial":"G.J.","affiliations":[{"id":38677,"text":"(1) Chelonian Research Foundation, Lunenburg, Massachusetts, USA (rhodincrf@aol.com); (2) University of Southern California, Los Angeles, California, USA (stanford@usc.edu)","active":true,"usgs":false}],"preferred":false,"id":807411,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thomson, Robert C.","contributorId":245973,"corporation":false,"usgs":false,"family":"Thomson","given":"Robert C.","affiliations":[{"id":49393,"text":"School of Life Sciences, University of Hawaiʻi, 2500 Campus Road, Honolulu, HI 96822, USA","active":true,"usgs":false}],"preferred":false,"id":807412,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shaffer, H. Bradley","contributorId":202769,"corporation":false,"usgs":false,"family":"Shaffer","given":"H.","email":"","middleInitial":"Bradley","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":807413,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hoagstrom, Christopher W.","contributorId":195520,"corporation":false,"usgs":false,"family":"Hoagstrom","given":"Christopher","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":807414,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70217071,"text":"70217071 - 2021 - The occurrence and distribution of strontium in U.S. groundwater","interactions":[],"lastModifiedDate":"2021-01-19T16:01:50.785334","indexId":"70217071","displayToPublicDate":"2020-12-24T07:19:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"The occurrence and distribution of strontium in U.S. groundwater","docAbstract":"<p><span>Groundwater samples from 32 principal aquifers across the United States (U.S.) provide a broad spatial scope of the occurrence and distribution of strontium (Sr) and are used to assess environments and factors that influence Sr concentration. Strontium is a common trace element in soils, rocks, and water and is ubiquitous in groundwater with detectable concentrations in 99.8% of samples (n=4,824; median = 225 μg/L). Concentrations in 2.3% of samples exceeded the 4,000 μg/L health-based screening level. The relative importance of controlling factors on Sr concentration are spatially variable and partly dependent on the type of groundwater well. Three case settings illustrate controls on Sr concentration. For drinking-water supply wells, most high concentrations (&gt;4,000 μg/L) were measured in samples from carbonate aquifers that resulted from water-rock interaction with Sr-bearing rocks and minerals. High Sr concentrations from monitoring wells were more common in unconsolidated sand and gravel aquifers in arid or semi-arid setting where shallow groundwater is affected by irrigation and evaporative concentration of dissolved constituents in combination with lithologic or applied Sr sources. Upwelling saline groundwater is also a source of Sr source in some locations. Total dissolved solids concentration is an indicator of high Sr in all settings. An estimated 2.2 million people in the conterminous U.S. are potentially supplied water from public-supply wells with high Sr concentration, ∼86% of whom use carbonate aquifers (with &gt; half supplied by the Floridan aquifer system). An additional 120,000 people are potentially supplied high-Sr-concentration water from domestic wells, &gt;half of whom (∼58%) are in Texas. This study markedly expands the coverage of previous surveys of Sr in groundwater and is of interest given potential adverse human-health effects related to elevated concentrations of Sr and consideration of Sr for drinking-water regulation. Case settings with elevated Sr described for U.S. groundwater are likely indicative of settings and processes affecting Sr concentration in groundwater globally.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2020.104867","usgsCitation":"Musgrove, M., 2021, The occurrence and distribution of strontium in U.S. groundwater: Applied Geochemistry, v. 126, 104867, 47 p., https://doi.org/10.1016/j.apgeochem.2020.104867.","productDescription":"104867, 47 p.","ipdsId":"IP-120115","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":454012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2020.104867","text":"Publisher Index Page"},{"id":381837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Continemtal United States","geographicExtents":"{\n  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mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":807481,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219269,"text":"70219269 - 2021 - Using turbulence to identify preferential areas for grass carp (Ctenopharyngodon idella) larvae in streams: A laboratory study","interactions":[],"lastModifiedDate":"2021-04-02T12:10:34.552968","indexId":"70219269","displayToPublicDate":"2020-12-24T07:07:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Using turbulence to identify preferential areas for grass carp (Ctenopharyngodon idella) larvae in streams: A laboratory study","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>In this experimental series, we studied the swimming capabilities and response of grass carp (<i>Ctenopharyngodon idella</i>) larvae to flow turbulence in a laboratory flume. We compared three different experimental configurations, representing in‐stream obstructions commonly found in natural streams (e.g., a gravel bump, a single vertical cylinder, and patches of submerged rigid vegetation). Grass carp larvae (postgas bladder emergence) were introduced to each experimental configuration and subjected to a variety of hydrodynamic forces of different magnitudes and scales. We varied the flow velocities and water depths and found ranges of turbulent kinetic energy and Reynolds stresses that triggered a response in larval trajectories, identified by measured horizontal and vertical swimming speeds for each flow condition. Larvae apparently actively avoided areas with increased levels of turbulence by swimming away, moving faster in short bursts, and expending more energy. In addition to the magnitude of turbulent kinetic energy, the length scale and time scale of turbulent eddies also influenced the larvae response. These findings support the development of new strategies for controlling the spread of grass carp larvae in rivers, as well as the development of numerical tools incorporating active swimming capabilities to predict larval transport in streams.</p></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028102","usgsCitation":"Prada, A.F., George, A.E., Stahlschmidt, B.H., Jackson, P.R., Chapman, D., and Tinoco, R.O., 2021, Using turbulence to identify preferential areas for grass carp (Ctenopharyngodon idella) larvae in streams: A laboratory study: Water Resources Research, v. 57, no. 2, e2020WR028102, 22 p., https://doi.org/10.1029/2020WR028102.","productDescription":"e2020WR028102, 22 p.","ipdsId":"IP-119688","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":454015,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028102","text":"Publisher Index Page"},{"id":384834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Prada, Andres F.","contributorId":211778,"corporation":false,"usgs":false,"family":"Prada","given":"Andres","email":"","middleInitial":"F.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":813448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":813449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":813450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813451,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":813452,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tinoco, Rafael O.","contributorId":211779,"corporation":false,"usgs":false,"family":"Tinoco","given":"Rafael","email":"","middleInitial":"O.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":813453,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217052,"text":"70217052 - 2021 - Crossroads of highly pathogenic H5N1: overlap between wild and domestic birds in the Black Sea-Mediterranean impacts global transmission","interactions":[],"lastModifiedDate":"2021-03-31T18:38:29.966004","indexId":"70217052","displayToPublicDate":"2020-12-24T06:57:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5051,"text":"Virus Evolution","onlineIssn":"2057-1577","active":true,"publicationSubtype":{"id":10}},"title":"Crossroads of highly pathogenic H5N1: overlap between wild and domestic birds in the Black Sea-Mediterranean impacts global transmission","docAbstract":"<p><span>Understanding transmission dynamics that link wild and domestic animals is a key element of predicting the emergence of infectious disease, an event that has highest likelihood of occurring wherever human livelihoods depend on agriculture and animal trade. Contact between poultry and wild birds is a key driver of the emergence of highly pathogenic avian influenza (HPAI), a process that allows for host-switching and accelerated reassortment, diversification and spread of virus between otherwise unconnected regions. This study addresses questions relevant to the spillover of HPAI at a transmission hotspot: what is the nature of the wild bird-poultry interface in Egypt and adjacent Black Sea-Mediterranean countries and how has this contributed to outbreaks occurring worldwide? Using a spatio-temporal model of infection risk informed by satellite tracking of waterfowl and viral phylogenetics, this study identified ecological conditions that contribute to spillover in this understudied region. Results indicated that multiple ducks (Northern Shoveler and Northern Pintail) hosted segments that shared ancestry with HPAI H5 from both clade 2.2.1 and clade 2.3.4 supporting the role of Anseriformes in linking viral populations in East Asia and Africa over large-distances. Quantifying the interface between wild ducks and H5N1-infected poultry revealed an increasing interface in late winter peaking in early spring when ducks expanded their range before migration, with key differences in the timing of poultry contact risk between local and long-distance migrants.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/ve/veaa093","usgsCitation":"Hill, N.J., Smith, L.M., Muzaffar, S.B., Nagel, J.L., Prosser, D., Sullivan, J., Spragens, K.A., DeMattos, C.A., Demattos, C.C., El Sayed, L., Erciyas-Yavuz, K., Davis, C.T., Jones, J., Kis, Z., Donis, R.O., Newman, S., and Takekawa, J.Y., 2021, Crossroads of highly pathogenic H5N1: overlap between wild and domestic birds in the Black Sea-Mediterranean impacts global transmission: Virus Evolution, v. 7, no. 1, veaa093, 12 p., https://doi.org/10.1093/ve/veaa093.","productDescription":"veaa093, 12 p.","ipdsId":"IP-099380","costCenters":[{"id":531,"text":"Patuxent Wildlife Research 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Studies of long-term trends in Lake Michigan have shown 2005–2016 densities to be 50–80% lower than 1990s densities, but these observations have been based on annual monitoring that is either spatially or seasonally limited. We combined Lake Michigan&nbsp;</span><i>Mysis</i><span>&nbsp;data from three annual programs and the 2015 Cooperative Science and Monitoring Initiative to achieve broad spatial coverage during spring, summer, and fall of 2015 and broad depth coverage during spring 2016. Lake-wide, annual density and biomass were 82 (SE: 10)&nbsp;</span><i>Mysis</i><span>/m</span><sup>2</sup><span>&nbsp;and 200 (SE: 36) mg dry mass/m</span><sup>2</sup><span>. Density and biomass estimates were highest offshore, generally higher in the north basin, and seasonally highest in summer. Annual lake-wide averages for depths &gt;30&nbsp;m were better captured by seasonally-extensive annual programs than spatially-extensive annual programs, although spring sampling may bias annual values low.&nbsp;</span><i>Mysis</i><span>&nbsp;cohorts grew 0.026&nbsp;mm/d (age-0) and 0.007 to 0.027&nbsp;mm/d (age-1). Annual mortality was 81–98%. Reproduction was fall-spring and seasonal lake-wide estimates ranged from 0.6 to 19.1% females brooding, 13–20 embryos/brood, and 3–46 embryos/m</span><sup>2</sup><span>. Annual production (423&nbsp;mg dry mass/m</span><sup>2</sup><span>/yr, SE: 31) was lower than all but one previous estimate from lakes Michigan, Huron, and Ontario. While&nbsp;</span><i>Mysis</i><span>&nbsp;tend to persist, low&nbsp;</span><i>Mysis</i><span>&nbsp;production may be a concern for prey fishes that feed on&nbsp;</span><i>Mysis</i><span>.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.11.012","usgsCitation":"Holda, T., Rudstam, L.G., Pothoven, S.A., Warner, D., Krystenko, D.S., and Watkins, J.M., 2021, Lake-wide annual status of Mysis diluviana population in Lake Michigan in 2015: Journal of Great Lakes Research, v. 47, no. 1, p. 190-203, https://doi.org/10.1016/j.jglr.2020.11.012.","productDescription":"14 p.","startPage":"190","endPage":"203","ipdsId":"IP-118982","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2020.11.012","text":"Publisher Index 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  ],\n            [\n              -85.84716796875,\n              45.98932892799953\n            ],\n            [\n              -85.9405517578125,\n              45.97406038956237\n            ],\n            [\n              -85.9954833984375,\n              46.0007775685566\n            ],\n            [\n              -86.165771484375,\n              45.97406038956237\n            ],\n            [\n              -86.28662109375,\n              45.96260622242165\n            ],\n            [\n              -86.3525390625,\n              45.90147732739488\n            ],\n            [\n              -86.36352539062499,\n              45.82114340079471\n            ],\n            [\n              -86.495361328125,\n              45.79050946752472\n            ],\n            [\n              -86.6436767578125,\n              45.69083283645816\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Holda, Toby J.","contributorId":189287,"corporation":false,"usgs":false,"family":"Holda","given":"Toby J.","affiliations":[],"preferred":false,"id":808682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":808683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, David 0000-0003-4939-5368","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":216543,"corporation":false,"usgs":true,"family":"Warner","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krystenko, Dmytro S.","contributorId":248259,"corporation":false,"usgs":false,"family":"Krystenko","given":"Dmytro","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":808685,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":808686,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263411,"text":"70263411 - 2021 - Rupture process of the M6.5 Stanley, Idaho, earthquake inferred from seismic waveform and geodetic data","interactions":[],"lastModifiedDate":"2025-02-10T16:40:39.947665","indexId":"70263411","displayToPublicDate":"2020-12-23T10:36:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Rupture process of the M6.5 Stanley, Idaho, earthquake inferred from seismic waveform and geodetic data","docAbstract":"<p><span>The 2020&nbsp;</span><strong>M</strong><span>&nbsp;6.5 Stanley, Idaho, earthquake produced rupture in the north of the active Sawtooth fault in the northern basin and range at depth, without any observable surface rupture. Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) data yield several millimeters of static offsets out to&nbsp;</span><span class=\"inline-formula no-formula-id\">∼100  km</span><span>&nbsp;from the rupture and up to&nbsp;</span><span class=\"inline-formula no-formula-id\">∼0.1  m</span><span>&nbsp;of near‐field crustal deformation. We combine the GPS and InSAR data with long‐period regional seismic waveforms to derive models of kinematic slip and afterslip. We find that the coseismic rupture is complex, likely involving up to 2&nbsp;m combined left‐lateral strike slip and normal slip on a previously unidentified ∼south‐southeast‐striking fault. This slip is predominantly left‐lateral strike slip, different from the dominant east‐northeast–west‐northwest normal faulting of the region. At least one ∼northeast‐trending fault, likely associated with the Trans‐Challis fault system, is inferred to have accommodated a few decimeters of right‐lateral afterslip, consistent with vigorous aftershock activity at depth along northeast‐trending lineations.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200315","usgsCitation":"Pollitz, F., Hammond, W.C., and Wicks, C., 2021, Rupture process of the M6.5 Stanley, Idaho, earthquake inferred from seismic waveform and geodetic data: Seismological Research Letters, v. 92, no. 2A, p. 699-709, https://doi.org/10.1785/0220200315.","productDescription":"11 p.","startPage":"699","endPage":"709","ipdsId":"IP-124061","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","city":"Stanley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.45,\n              44.5\n            ],\n            [\n              -115.45,\n              43.99\n            ],\n            [\n              -114.5,\n              43.99\n            ],\n            [\n              -114.5,\n              44.5\n            ],\n            [\n              -115.45,\n              44.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"92","issue":"2A","noUsgsAuthors":false,"publicationDate":"2020-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammond, William C.","contributorId":73735,"corporation":false,"usgs":true,"family":"Hammond","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":926888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":926889,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217371,"text":"70217371 - 2021 - The impacts of the 2015/2016 El Niño on California's sandy beaches","interactions":[],"lastModifiedDate":"2021-01-20T14:17:42.716823","indexId":"70217371","displayToPublicDate":"2020-12-23T08:15:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The impacts of the 2015/2016 El Niño on California's sandy beaches","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0095\">The El Niño Southern Oscillation is the most dominant mode of interannual climate variability in the Pacific. The 2015/2016 El Niño event was one of the strongest of the last 145 years, resulting in anomalously high wave energy across the U.S. West Coast, and record coastal erosion for many California beaches. To better manage coastal resources, it is critical to understand the impacts of both short-term climate variability and long-term climate impacts across the varied coastal settings of California. This study is the first to quantify the coastal response for one of the strongest El Niño events in the historical record across the coast of California through the analysis of nearshore wave conditions and seasonal beach changes for 8000 shore-normal transects. Through the analysis of pre- and post- El Niño LiDAR, we find that that central and northern California experienced the most sandy beach shoreline retreat/erosion during the El Niño winter, with a mean of 45.7 m of erosion (96% of beaches) in central California, a mean of 25.5 m of erosion (89% of beaches) in northern California, and a mean of 9.7 m of erosion (79% of beaches) in southern California. These patterns are compared to LiDAR and satellite-derived long-term shoreline change rates, in which southern California and central California beaches are moderately accreting, while northern California is eroding at an average of 79 cm per year. A significant correlation is found between cumulative wave energy flux and shoreline change during the El Niño winter across the state of California. Although local beach response during the El Niño winter was highly variable, heightened erosion was observed at river mouths and on the southern side of structures impeding littoral drift, with accretion observed on the northern side of these structures. These erosional patterns, driven by a northerly wave direction anomaly, contrast those of classic El Niño events such as the 1982–.83 and 1997–98 events, where more southerly storm tracks and southerly wave directions were key factors controlling shoreline behavior, and may indicate a shift in El Niño storm patterns driven by climate change.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2020.107583","usgsCitation":"Smith, S.A., and Barnard, P.L., 2021, The impacts of the 2015/2016 El Niño on California's sandy beaches: Geomorphology, v. 377, 107583, 18 p., https://doi.org/10.1016/j.geomorph.2020.107583.","productDescription":"107583, 18 p.","ipdsId":"IP-117937","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454023,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2020.107583","text":"Publisher Index Page"},{"id":436608,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91QSGXF","text":"USGS data release","linkHelpText":"California shorelines and shoreline change data, 1998-2016"},{"id":382317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.55224609375,\n              41.918628865183045\n            ],\n            [\n              -125.00244140625,\n              42.049292638686836\n            ],\n            [\n              -125.20019531249999,\n              41.5579215778042\n            ],\n            [\n              -125.46386718749999,\n              40.3130432088809\n            ],\n            [\n              -124.49707031249999,\n              39.14710270770074\n            ],\n            [\n              -123.33251953125,\n              36.87962060502676\n            ],\n            [\n              -122.36572265625,\n              35.0120020431607\n            ],\n            [\n              -121.04736328125,\n              33.687781758439364\n            ],\n            [\n              -119.17968749999999,\n              32.82421110161336\n            ],\n            [\n              -117.48779296875,\n              32.39851580247402\n            ],\n            [\n              -116.21337890625,\n              32.676372772089834\n            ],\n            [\n              -116.47705078125,\n              33.687781758439364\n            ],\n            [\n              -119.15771484375,\n              35.15584570226544\n            ],\n            [\n              -121.17919921875001,\n              37.28279464911045\n            ],\n            [\n              -123.02490234375,\n              39.04478604850143\n            ],\n            [\n              -123.55224609375,\n              41.918628865183045\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"377","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Schuyler A","contributorId":247875,"corporation":false,"usgs":false,"family":"Smith","given":"Schuyler","email":"","middleInitial":"A","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":808543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":808544,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70217834,"text":"70217834 - 2021 - Geometry of obstacle marks at instream boulders-Integration of laboratory investigations and field observations","interactions":[],"lastModifiedDate":"2021-04-08T14:51:04.593867","indexId":"70217834","displayToPublicDate":"2020-12-23T08:07:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Geometry of obstacle marks at instream boulders-Integration of laboratory investigations and field observations","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Obstacle marks are instream bedforms, typically composed of an upstream frontal scour hole and a downstream sediment accumulation in the vicinity of an obstacle. Local scouring at infrastructure (e.g. bridge piers) is a well‐studied phenomenon in hydraulic engineering, while less attention is given to the time‐dependent evolution of frontal scour holes at instream boulders and their geometric relations (depth to width, and length ratio). Furthermore, a comparison between laboratory studies and field observations is rare. Therefore, the morphodynamic importance of such scour features to fluvial sediment transport and morphological change is largely unknown. In this study, obstacle marks at boulder‐like obstructions were physically modelled in 30 unscaled process‐focused flume experiments (runtime per experiment ≥ 5760 min) at a range of flows (subcritical, clear‐water conditions, emergent and submerged water levels) and boundary conditions designed to represent the field setting (i.e. obstacle tilting, and limited thickness of the alluvial layer). Additionally, geometries of scour holes at 90<span>&nbsp;</span><i>in‐situ</i><span>&nbsp;</span>boulders (diameter ≥ 1 m) located in a 50‐km segment of the Colorado River in Marble Canyon (AZ) were measured from a 1 m‐resolution digital elevation model. Flume experiments reveal similar evolution of local scouring, irrespective of hydraulic conditions, controlled by the scour incision, whereas the thickness of the alluvial layer and obstacle tilting into the evolving frontal scour hole limit incision. Three temporal evolution phases—(1) rapid incision, (2) decreasing incision, and (3) scour widening—are identified based on statistical analysis of spatiotemporal bed elevation time series. A quantitative model is presented that mechanistically predicts enlargement in local scour length and width based on (1) scour depth, (2) the inclination of scour slopes, and (3) the planform area of the frontal scour hole bottom. The comparison of field observations and laboratory results demonstrates scale invariance of geometry, which implies similitude of processes and form rather than equifinality.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5055","usgsCitation":"Schlomer, O., Grams, P.E., Buscombe, D.D., and Herget, J., 2021, Geometry of obstacle marks at instream boulders-Integration of laboratory investigations and field observations: Earth Surface Processes and Landforms, v. 46, no. 3, p. 659-679, https://doi.org/10.1002/esp.5055.","productDescription":"21 p.","startPage":"659","endPage":"679","ipdsId":"IP-119535","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5055","text":"Publisher Index Page"},{"id":383050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Schlomer, Oliver","contributorId":248789,"corporation":false,"usgs":false,"family":"Schlomer","given":"Oliver","email":"","affiliations":[],"preferred":false,"id":809864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":809861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":809862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herget, Jurgen","contributorId":248788,"corporation":false,"usgs":false,"family":"Herget","given":"Jurgen","email":"","affiliations":[],"preferred":false,"id":809865,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217087,"text":"70217087 - 2021 - Rapid sensitivity analysis for reducing uncertainty in landslide hazard assessments","interactions":[],"lastModifiedDate":"2021-01-05T13:47:14.328525","indexId":"70217087","displayToPublicDate":"2020-12-23T07:45:34","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Rapid sensitivity analysis for reducing uncertainty in landslide hazard assessments","docAbstract":"<p id=\"Par1\" class=\"Para\">One of the challenges in assessing temporal and spatial aspects of landslide hazard using process-based models is estimating model input parameters, especially in areas where limited measurements of soil and rock properties are available. In an effort to simplify and streamline parameter estimation, development of a simple, rapid approach to sensitivity analysis relies on field measurements of landslide characteristics, especially slope and depth. This method is demonstrated for a case study in Puerto Rico where widespread destruction resulted from tens of thousands of debris flows induced by Hurricanes Irma and María in Puerto Rico in 2017. The approach can be applied to estimation of shear strength as well as hydrologic parameters that control infiltration and flow of water in the subsurface and ultimately the timing of landslides resulting from heavy rainfall. Results narrow the possible range of cohesion and friction parameters as well as hydraulic conductivity and other soil water parameters by counting the fraction of field observations that can be explained by each combination of parameters. For cases studied in Puerto Rico, the method identified combinations of cohesion and friction values that explain more than 80–90% of observed landslide source areas.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"WLF 2020: Understanding and reducing landslide disaster risk","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-60227-7_37","usgsCitation":"Baum, R.L., 2021, Rapid sensitivity analysis for reducing uncertainty in landslide hazard assessments, <i>in</i> WLF 2020: Understanding and reducing landslide disaster risk, p. 329-335, https://doi.org/10.1007/978-3-030-60227-7_37.","productDescription":"7 p.","startPage":"329","endPage":"335","ipdsId":"IP-117901","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":381876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70226971,"text":"70226971 - 2021 - Intrinsic and extrinsic drivers of life-history variability for a south-western cutthroat trout","interactions":[],"lastModifiedDate":"2021-12-23T13:49:00.421423","indexId":"70226971","displayToPublicDate":"2020-12-23T07:44:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Intrinsic and extrinsic drivers of life-history variability for a south-western cutthroat trout","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The impacts of climate change on cold-water fishes will likely negatively manifest in populations at the trailing edge of their distributions. Rio Grande cutthroat trout (<i>Oncorhynchus clarkii virginalis</i>, RGCT) occupy arid south-western U.S. streams at the southern-most edge of all cutthroat trout distributions, making RGCT particularly vulnerable to the anticipated warming and drying in this region. We hypothesised that RGCT possess a portfolio of life-history traits that aid in their persistence within streams of varying temperature and stream drying conditions. We used otolith and multistate capture–mark–recapture data to determine how these environmental constraints influence life-history trait expression (length- and age-at-maturity) and demography in RGCT populations from northern New Mexico, United States. We found evidence that RGCT reached maturity fastest at sites with warm stream temperatures and low densities. We did not find a strong relationship between discharge and any demographic rate, although apparent survival of mature RGCT decreased as stream temperature increased. Our study suggests plasticity in trait expression may be a life-history characteristic which can assist trailing edge populations like RGCT persist in a changing climate.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12567","usgsCitation":"Huntsman, B., Caldwell, C.A., Lynch, A.J., and Abadi, F., 2021, Intrinsic and extrinsic drivers of life-history variability for a south-western cutthroat trout: Ecology of Freshwater Fish, v. 30, no. 1, p. 100-114, https://doi.org/10.1111/eff.12567.","productDescription":"15 p.","startPage":"100","endPage":"114","ipdsId":"IP-106359","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"links":[{"id":393353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.09472656249999,\n              35.17380831799959\n            ],\n            [\n              -104.5458984375,\n              35.17380831799959\n            ],\n            [\n              -104.5458984375,\n              36.94989178681327\n            ],\n            [\n              -107.09472656249999,\n              36.94989178681327\n            ],\n            [\n              -107.09472656249999,\n              35.17380831799959\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock M.","contributorId":270315,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock M.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":829016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":829015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abadi, Fitsum","contributorId":270316,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","email":"","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":829017,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217032,"text":"70217032 - 2021 - Estimating the impact of seep methane oxidation on ocean pH and dissolved inorganic radiocarbon along the U.S. mid‐Atlantic Bight","interactions":[],"lastModifiedDate":"2021-01-19T16:02:39.317427","indexId":"70217032","displayToPublicDate":"2020-12-23T07:22:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7481,"text":"Journal of Geophysical Research- Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the impact of seep methane oxidation on ocean pH and dissolved inorganic radiocarbon along the U.S. mid‐Atlantic Bight","docAbstract":"<div class=\"article-section__content en main\"><p>Ongoing ocean warming can release methane (CH<sub>4</sub>) currently stored in ocean sediments as free gas and gas hydrates. Once dissolved in ocean waters, this CH<sub>4</sub><span>&nbsp;</span>can be oxidized to carbon dioxide (CO<sub>2</sub>). While it has been hypothesized that the CO<sub>2</sub><span>&nbsp;</span>produced from aerobic CH<sub>4</sub><span>&nbsp;</span>oxidation could enhance ocean acidification, a previous study conducted in Hudson Canyon shows that CH<sub>4</sub><span>&nbsp;</span>oxidation has a small short‐term influence on ocean pH and dissolved inorganic radiocarbon. Here we expand upon that investigation to assess the impact of widespread CH<sub>4</sub><span>&nbsp;</span>seepage on CO<sub>2</sub><span>&nbsp;</span>chemistry and possible accumulation of this carbon injection along 234 km of the U.S. Mid‐Atlantic Bight. Consistent with the estimates from Hudson Canyon, we demonstrate that a small fraction of ancient CH<sub>4</sub>‐derived carbon is being assimilated into the dissolved inorganic radiocarbon (mean fraction of 0.5 ± 0.4 %). The areas with the highest fractions of ancient carbon coincide with elevated CH<sub>4</sub><span>&nbsp;</span>concentration and active gas seepage. This suggests that aerobic CH<sub>4</sub><span>&nbsp;</span>oxidation has a greater influence on the dissolved inorganic pool in areas where CH<sub>4</sub><span>&nbsp;</span>concentrations are locally elevated, instead of displaying a cumulative effect downcurrent from widespread groupings of CH<sub>4</sub><span>&nbsp;</span>seeps. An upper limit approximation of the input rate of ancient‐derived DIC into the waters overlying the northern U. S Mid‐Atlantic Bight further suggests that oxidation of ancient CH<sub>4</sub>‐derived carbon is not negligible on the global scale and could contribute to deep‐water acidification over longer time scales.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JG005621","usgsCitation":"Garcia-Tigreros, F., Leonte, M., Ruppel, C.D., Ruiz-Angulo, A., Joung, D., Young, B., and Kessler, J.D., 2021, Estimating the impact of seep methane oxidation on ocean pH and dissolved inorganic radiocarbon along the U.S. mid‐Atlantic Bight: Journal of Geophysical Research- Biogeosciences, v. 126, e2019JG005621, 15 p., https://doi.org/10.1029/2019JG005621.","productDescription":"e2019JG005621, 15 p.","ipdsId":"IP-114837","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454028,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1849216","text":"External Repository"},{"id":381715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","noUsgsAuthors":false,"publicationDate":"2021-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Garcia-Tigreros, Fenix 0000-0001-8694-9046","orcid":"https://orcid.org/0000-0001-8694-9046","contributorId":194744,"corporation":false,"usgs":false,"family":"Garcia-Tigreros","given":"Fenix","email":"","affiliations":[],"preferred":false,"id":807310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonte, Mihai 0000-0003-1582-5606","orcid":"https://orcid.org/0000-0003-1582-5606","contributorId":224782,"corporation":false,"usgs":false,"family":"Leonte","given":"Mihai","email":"","affiliations":[{"id":40676,"text":"University of Rochester, NY","active":true,"usgs":false}],"preferred":false,"id":807312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruiz-Angulo, Angel","contributorId":245910,"corporation":false,"usgs":false,"family":"Ruiz-Angulo","given":"Angel","email":"","affiliations":[{"id":40940,"text":"Icelandic Meteorological Office","active":true,"usgs":false}],"preferred":false,"id":807314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joung, DoongJoo 0000-0002-2711-3780","orcid":"https://orcid.org/0000-0002-2711-3780","contributorId":245909,"corporation":false,"usgs":false,"family":"Joung","given":"DoongJoo","email":"","affiliations":[{"id":37381,"text":"University of Rochester","active":true,"usgs":false}],"preferred":false,"id":807313,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Benjamin","contributorId":245911,"corporation":false,"usgs":false,"family":"Young","given":"Benjamin","affiliations":[{"id":37381,"text":"University of Rochester","active":true,"usgs":false}],"preferred":false,"id":807315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":807316,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70222943,"text":"70222943 - 2021 - On the use of statistical analysis to understand submarine landslide processes and assess their hazard","interactions":[],"lastModifiedDate":"2021-08-10T15:37:59.128614","indexId":"70222943","displayToPublicDate":"2020-12-22T10:33:14","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"On the use of statistical analysis to understand submarine landslide processes and assess their hazard","docAbstract":"<p><span>Because of their inaccessibility, submarine landslides are typically studied individually and at great effort and expense to provide knowledge of the specific site conditions where these landslides occur. Statistical analysis of submarine landslide scars can offer generalized perspectives on the processes that initiate submarine landslides and can help toward hazard assessment in areas that have not been studied in detail. The following review discusses more than a decade of development of statistical approaches to studying submarine landslides. Landslides were previously viewed together with other natural hazards, such as earthquakes and fires, as a phenomenon whose size distribution obeys an inverse power law. Inverse power law distributions are the result of self-organized avalanche processes, in which the final hazard size cannot be predicted at the onset of the disturbance. We find that volume and area distributions of submarine landslides along the U.S. Atlantic continental slope and along nine other margins worldwide do not follow an inverse power law. Rigorous statistical tests of several different probability distribution models indicate that the lognormal model is most appropriate for these siliciclastic environments. Lognormal distributions can be simulated by assuming that the area of slope failure depends on earthquake magnitude, in other words, failure occurs simultaneously over the area affected by horizontal ground shaking and does not cascade from nucleating sources. Therefore, the maximum landslide size can be predicted from the earthquake magnitude and the distance from the rupturing fault. Moreover, earthquakes &lt;~M4.5 cannot generate significant submarine landslides. We further demonstrate that empirical, offshore landslide hazard curves can be developed from these lognormal landslide size distributions, if the duration of mapped landslide activity is known. In addition to hazard estimation, scaling relationships can yield insights on the physical processes associated with landslide failure. For example, the log-log relationship between volume and area of landslide scars in siliciclastic margins is observed to be almost linear implying that most landslides are translational. Carbonate margins, in contrast, show a power-law distribution of scar volumes and their volume to area relationship is ~1.3. These results suggest that landslides in carbonate margins are governed by the random distributions of existing fissures, and they act like rock falls on land. Although earthquakes are the principal trigger of submarine landslides, the effects of earthquake frequency on slope stability can be counterintuitive. The average size of landslide scars decreases non-linearly with increasing frequency of earthquakes and increases with increasing sedimentation rate. The effect is interpreted as evidence for densification and shear strength increase of margin sediment, induced by repeated seismic shaking.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Understanding and reducing landslide disaster risk","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer Link","doi":"10.1007/978-3-030-60196-6_23","usgsCitation":"ten Brink, U., and Geist, E.L., 2021, On the use of statistical analysis to understand submarine landslide processes and assess their hazard, chap. <i>of</i> Understanding and reducing landslide disaster risk, p. 329-341, https://doi.org/10.1007/978-3-030-60196-6_23.","productDescription":"13 p.","startPage":"329","endPage":"341","ipdsId":"IP-118112","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":387818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":820876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820877,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70218227,"text":"70218227 - 2021 - Progress and lessons learned from responses to landslide disasters","interactions":[],"lastModifiedDate":"2021-04-19T15:07:17.984422","indexId":"70218227","displayToPublicDate":"2020-12-22T09:43:44","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Progress and lessons learned from responses to landslide disasters","docAbstract":"<p><span>Landslides have the incredible power to transform landscapes and also, tragically, to cause disastrous societal impacts. Whereas the mechanics and effects of many landslide disasters have been analyzed in detail, the means by which landslide experts respond to these events has garnered much less attention. Herein, we evaluate nine landslide response case histories conducted by the&nbsp;U.S. Geological Survey over the past two decades and summarize the event history, the response conducted, and the lessons learned from each event. We group the responses into three categories—providing event context from past events, addressing ongoing hazards, and acquiring data for the future—and present the nine case studies accordingly. We also summarize the progress in landslide response that has been made over the past two decades, including insights and advancements on the preparation for such events, the use of new technologies, and the importance of clear communication between all parties during disasters. We believe that exchanging and sharing experiences such as these will promote more clear and successful approaches for responses to landslide disasters in the future.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Understanding and reducing landslide disaster risk","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-60196-6_4","collaboration":"National Park Service","usgsCitation":"Collins, B.D., Reid, M.E., Coe, J.A., Kean, J.W., Baum, R.L., Jibson, R.W., Godt, J.W., Slaughter, S., and Stock, G.M., 2021, Progress and lessons learned from responses to landslide disasters, chap. <i>of</i> Understanding and reducing landslide disaster risk, p. 85-111, https://doi.org/10.1007/978-3-030-60196-6_4.","productDescription":"17 p.","startPage":"85","endPage":"111","ipdsId":"IP-117641","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":385192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":810500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":810501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":810502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":810505,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":810506,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slaughter, Stephen","contributorId":216500,"corporation":false,"usgs":false,"family":"Slaughter","given":"Stephen","affiliations":[{"id":13477,"text":"Washington Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":810507,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stock, Greg M.","contributorId":202873,"corporation":false,"usgs":false,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":810508,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70216982,"text":"70216982 - 2021 - Marsh equilibrium theory: Implications for responses to rising sea level","interactions":[],"lastModifiedDate":"2021-10-01T16:33:15.34572","indexId":"70216982","displayToPublicDate":"2020-12-22T08:04:09","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Marsh equilibrium theory: Implications for responses to rising sea level","docAbstract":"<p>No abstract available.&nbsp;</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Salt marshes: Function, dynamics, and stresses","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge","doi":"10.1017/9781316888933.009","usgsCitation":"Morris, J.T., Cahoon, D., Callaway, J.C., Craft, C., Neubauer, S.C., and Weston, N.B., 2021, Marsh equilibrium theory: Implications for responses to rising sea level, chap. 7 <i>of</i> Salt marshes: Function, dynamics, and stresses, p. 157-177, https://doi.org/10.1017/9781316888933.009.","productDescription":"21 p.","startPage":"157","endPage":"177","ipdsId":"IP-096273","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":390117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Morris, James T","contributorId":245841,"corporation":false,"usgs":false,"family":"Morris","given":"James","email":"","middleInitial":"T","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":807164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cahoon, Donald R. 0000-0002-2591-5667","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":219657,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callaway, John C. 0000-0002-7364-286X","orcid":"https://orcid.org/0000-0002-7364-286X","contributorId":205456,"corporation":false,"usgs":false,"family":"Callaway","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37110,"text":"Dept. of Environmental Science, University of San Francisco, 2130 Fulton St., San Francisco, CA 94117","active":true,"usgs":false}],"preferred":false,"id":807166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craft, Christopher","contributorId":156398,"corporation":false,"usgs":false,"family":"Craft","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":807167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neubauer, Scott C","contributorId":169723,"corporation":false,"usgs":false,"family":"Neubauer","given":"Scott","email":"","middleInitial":"C","affiliations":[{"id":25575,"text":"Dept. of Biology, Virginia Commonwealth University, Richmond, VA","active":true,"usgs":false}],"preferred":false,"id":807168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weston, Nathaniel B","contributorId":245842,"corporation":false,"usgs":false,"family":"Weston","given":"Nathaniel","email":"","middleInitial":"B","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":807169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70224290,"text":"70224290 - 2021 - Identifying information gaps in predicting winter foraging habitat for juvenile Gulf Sturgeon","interactions":[],"lastModifiedDate":"2023-07-07T13:40:08.78752","indexId":"70224290","displayToPublicDate":"2020-12-22T07:38:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Identifying information gaps in predicting winter foraging habitat for juvenile Gulf Sturgeon","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The Gulf Sturgeon<span>&nbsp;</span><i>Acipenser oxyrinchus desotoi</i><span>&nbsp;</span>is an anadromous species that inhabits Gulf of Mexico coastal waters from Louisiana to Florida and is listed as threatened under the U.S. Endangered Species Act. Seasonal cues (e.g., freshwater discharge) determine the timing of spawning and migration and may influence the availability of critical habitat during winter months in six estuaries. Large information gaps, especially related to critical estuarine habitat for juveniles, hinder recovery efforts to protect these habitats and assess risks from emerging threats. Using Apalachicola Bay, Florida, as a model system, we developed and analyzed a preliminary Bayesian network model so that we could identify knowledge gaps (i.e., where expert knowledge was lacking) and data gaps (i.e., where data were unavailable) that limit the ability to assess the quantity of critical estuarine habitat for juvenile Gulf Sturgeon. The model hypothesized habitat availability per winter month in estuarine habitat under alternative scenarios of river discharge and length of the winter foraging season. A search for geospatial data sets revealed that the largest gap involved salinity, temperature, and oxygen (i.e., water condition) monitoring data, with data available only for Apalachicola Bay. For the Apalachicola Bay model, data gaps prevented the development of 53% of water condition geospatial data sets and a sensitivity analysis showed that water condition data most limited the ability to predict habitat availability. Expert knowledge was low, and conditional certainty scores showed that the relationships with the lowest certainty were abiotic suitability and habitat availability. Reducing information gaps could aid the development of a model that is appropriate for informing management. Future efforts could prioritize the expansion of water monitoring within critical habitat estuaries and predicting abiotic suitability and habitat availability. Bayesian network models can easily incorporate prior and new information for complex systems. Thus, our model could be updated as future research and monitoring efforts close these information gaps.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10288","usgsCitation":"Dale, L.L., Cronin, J.P., Brink, V., Tirpak, B., Tirpak, J., and Pine, W.E., 2021, Identifying information gaps in predicting winter foraging habitat for juvenile Gulf Sturgeon: Transactions of the American Fisheries Society, v. 150, no. 2, p. 222-241, https://doi.org/10.1002/tafs.10288.","productDescription":"20 p.; Data Release","startPage":"222","endPage":"241","ipdsId":"IP-107872","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":389469,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418745,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KNSKMT","text":"Data for Gulf Sturgeon Bayesian Network Model","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Apalachicola Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.6109619140625,\n              29.544787796199465\n            ],\n            [\n              -84.1607666015625,\n              29.544787796199465\n            ],\n            [\n              -84.1607666015625,\n              30.073847754270204\n            ],\n            [\n              -85.6109619140625,\n              30.073847754270204\n            ],\n            [\n              -85.6109619140625,\n              29.544787796199465\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"150","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Dale, Leah L. 0000-0002-3480-9954","orcid":"https://orcid.org/0000-0002-3480-9954","contributorId":243547,"corporation":false,"usgs":false,"family":"Dale","given":"Leah","middleInitial":"L.","affiliations":[{"id":48726,"text":"Cherokee Nations Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":823468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brink, Virginia 0000-0001-7575-6759 vbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-7575-6759","contributorId":191023,"corporation":false,"usgs":true,"family":"Brink","given":"Virginia","email":"vbrink@usgs.gov","affiliations":[],"preferred":true,"id":823470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tirpak, Blair 0000-0002-2679-8378","orcid":"https://orcid.org/0000-0002-2679-8378","contributorId":206275,"corporation":false,"usgs":true,"family":"Tirpak","given":"Blair","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tirpak, John M.","contributorId":197496,"corporation":false,"usgs":false,"family":"Tirpak","given":"John M.","affiliations":[],"preferred":false,"id":823472,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":823473,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217002,"text":"70217002 - 2021 - Assessing the hydrologic and physical conditions of a drainage basin","interactions":[],"lastModifiedDate":"2020-12-23T13:36:54.425907","indexId":"70217002","displayToPublicDate":"2020-12-22T07:35:53","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Assessing the hydrologic and physical conditions of a drainage basin","docAbstract":"<p>An assessment of a drainage basin and its stream corridor will provide the data and information needed to understand current biophysical conditions and trends. Developing an understanding of the drivers of change is the next essential step for restoration success (Osterkamp and Toy, 1997; Corenbilt et al., 2007; Briggs and Osterkamp, 2003), Shields et al. 2003; Osterkamp et al., 2011). Establishing such a robust scientific foundation will allow stream practitioners to develop realistic restoration objectives and the tactics that will be effective to achieve them. Accomplishing this requires collecting data at watershed and reach scales and by drawing on scientific data from areas where conditions may be similar to, or applicable to, your site. Although decisions should be backed by conclusive data, to make progress we need to rely on the best available information, even if scientific uncertainty remains. Additional information will become available, so it is necessary to plan a project in a manner that incorporates available knowledge and permits goals, objectives, and tactics to be adjusted accordingly.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Renewing our rivers—Stream corridor restoration in dryland regions","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of Arizona Press","usgsCitation":"Osterkamp, W., Briggs, M.K., Dean, D.J., and Rodriquez, A., 2021, Assessing the hydrologic and physical conditions of a drainage basin, chap. 3 <i>of</i> Renewing our rivers—Stream corridor restoration in dryland regions, p. 43-103.","productDescription":"61 p.","startPage":"43","endPage":"103","ipdsId":"IP-060923","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":381610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381603,"type":{"id":15,"text":"Index Page"},"url":"https://uapress.arizona.edu/book/renewing-our-rivers"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Osterkamp, Waite","contributorId":245868,"corporation":false,"usgs":false,"family":"Osterkamp","given":"Waite","affiliations":[{"id":49352,"text":"(Emeritus) National Research Program, Western Branch; University of Arizona Press, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":807215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Mark K.","contributorId":177076,"corporation":false,"usgs":false,"family":"Briggs","given":"Mark","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":807216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":807217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriquez, Alfredo","contributorId":245869,"corporation":false,"usgs":false,"family":"Rodriquez","given":"Alfredo","email":"","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":807218,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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