{"pageNumber":"556","pageRowStart":"13875","pageSize":"25","recordCount":165309,"records":[{"id":70217569,"text":"70217569 - 2020 - Phylogenetic escape from pests reduces pesticides on some crop plants","interactions":[],"lastModifiedDate":"2021-01-22T13:27:13.231465","indexId":"70217569","displayToPublicDate":"2020-10-12T07:25:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Phylogenetic escape from pests reduces pesticides on some crop plants","docAbstract":"<p><span>Pesticides are a ubiquitous component of conventional crop production but come with considerable economic and ecological costs. We tested the hypothesis that variation in pesticide use among crop species is a function of crop economics and the phylogenetic relationship of a crop to native plants because unrelated crops accrue fewer herbivores and pathogens. Comparative analyses of a dataset of 93 Californian crops showed that more valuable crops and crops with close relatives in the native plant flora received greater pesticide use, explaining roughly half of the variance in pesticide use among crops against pathogens and herbivores. Phylogenetic escape from arthropod and pathogen pests results in lower pesticides, suggesting that the introduced status of some crops can be leveraged to reduce pesticides.</span></p>","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2013751117","usgsCitation":"Pearse, I., and Rosenheim, J., 2020, Phylogenetic escape from pests reduces pesticides on some crop plants: Proceedings of the National Academy of Sciences, v. 117, no. 43, p. 26849-26853, https://doi.org/10.1073/pnas.2013751117.","productDescription":"5 p.","startPage":"26849","endPage":"26853","ipdsId":"IP-120433","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":455079,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7604411","text":"External Repository"},{"id":436756,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TIK3JP","text":"USGS data release","linkHelpText":"Californian crop pests, pesticide applications, and phylogenetic information of crops"},{"id":382488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"43","noUsgsAuthors":false,"publicationDate":"2020-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenheim, Jay 0000-0002-9228-4754","orcid":"https://orcid.org/0000-0002-9228-4754","contributorId":248267,"corporation":false,"usgs":false,"family":"Rosenheim","given":"Jay","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":808708,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215396,"text":"70215396 - 2020 - Four-dimensional thermal evolution of the East African Orogen: Accessory phase petrochronology of crustal profiles through the Tanzanian Craton and Mozambique Belt, northeastern Tanzania","interactions":[],"lastModifiedDate":"2020-10-17T15:47:10.208804","indexId":"70215396","displayToPublicDate":"2020-10-09T10:39:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Four-dimensional thermal evolution of the East African Orogen: Accessory phase petrochronology of crustal profiles through the Tanzanian Craton and Mozambique Belt, northeastern Tanzania","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>U–Pb petrochronology of deep crustal xenoliths and outcrops across northeastern Tanzania track the thermal evolution of the Mozambique Belt and Tanzanian Craton following the Neoproterozoic East African Orogeny (EAO) and subsequent Neogene rifting. At the craton margin, the upper–middle crust record thermal quiescence since the Archean (2.8–2.5&nbsp;Ga zircon, rutile, and apatite in granite and amphibolite xenoliths). The lower crust of the craton documents thermal pulses associated with Neoarchean ultra-high temperature metamorphism (ca. 2.64&nbsp;Ga, &gt; 900&nbsp;°C zircon), the EAO (600–500&nbsp;Ma rutile), and fluid influx during rifting (&lt; 5&nbsp;Ma apatite). Rutile in garnet granulite xenoliths exhibits partial Pb loss related to slow cooling of the lower crust after the EAO and suggests residence at 500–600&nbsp;°C prior to entrainment. In contrast to the craton, the entire crust of the Mozambique Belt underwent differential cooling following the EAO. Both the upper and middle crust record metamorphism from 640 to 560&nbsp;Ma (zircon, monazite, and titanite) and rapid exhumation at 510–440&nbsp;Ma (rutile and apatite). Lower crustal xenoliths contain Archean zircon, but near-zero age rutile and apatite, indicating residence &gt; 650&nbsp;°C (above Pb closure of rutile and apatite) at the time of eruption. Zoned titanite records growth during cooling of the lower crust at 550&nbsp;Ma, followed by fluid influx during slow cooling and exhumation (0.1–1&nbsp;°C/Myr after 450&nbsp;Ma). Permissible lower-crustal temperatures for the craton and orogen suggest variable mantle heat flow through the crust and reflect differences in mantle lithosphere thickness rather than advective heating from rifting.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s00410-020-01737-6","usgsCitation":"Apen, F.E., Rudnick, R.L., Cottle, J., Kylander-Clark, A., Blondes, M., Piccoli, P., and Seward, G., 2020, Four-dimensional thermal evolution of the East African Orogen: Accessory phase petrochronology of crustal profiles through the Tanzanian Craton and Mozambique Belt, northeastern Tanzania: Contributions to Mineralogy and Petrology, v. 175, no. 11, 97, 30 p., https://doi.org/10.1007/s00410-020-01737-6.","productDescription":"97, 30 p.","ipdsId":"IP-117363","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":379487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"East African Rift System","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              26.015625000000007,\n              -16.97274101999901\n            ],\n            [\n              40.25390625000001,\n              -16.97274101999901\n            ],\n            [\n              40.25390625000001,\n              1.0546279422758997\n            ],\n            [\n              26.015625000000007,\n              1.0546279422758997\n            ],\n            [\n              26.015625000000007,\n              -16.97274101999901\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"175","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Apen, Francisco E.","contributorId":243307,"corporation":false,"usgs":false,"family":"Apen","given":"Francisco","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":802004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rudnick, Roberta L.","contributorId":243308,"corporation":false,"usgs":false,"family":"Rudnick","given":"Roberta","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":802005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cottle, John M.","contributorId":243309,"corporation":false,"usgs":false,"family":"Cottle","given":"John M.","affiliations":[],"preferred":false,"id":802006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kylander-Clark, Andrew R.C.","contributorId":243310,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew R.C.","affiliations":[],"preferred":false,"id":802007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":802008,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piccoli, Phil","contributorId":243311,"corporation":false,"usgs":false,"family":"Piccoli","given":"Phil","email":"","affiliations":[],"preferred":false,"id":802009,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seward, Gareth","contributorId":243312,"corporation":false,"usgs":false,"family":"Seward","given":"Gareth","email":"","affiliations":[],"preferred":false,"id":802010,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70260189,"text":"70260189 - 2020 - Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust","interactions":[],"lastModifiedDate":"2024-10-30T13:48:22.975458","indexId":"70260189","displayToPublicDate":"2020-10-09T08:38:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust","docAbstract":"<p><span>In continental arcs, the exposure of primitive eruptive products at the surface is typically a result of rapid magmatic transfer through the crust. As a result, the initially primitive magma experiences minimal crustal residence and thus insignificant differentiation towards more evolved products. This rapid transfer of primitive magma through thickened crust is commonly recorded from smaller, monogenetic cinder cones. Manantial Pelado (35.5° S) is a long-lived stratocone in the Southern Andean Volcanic Zone (SVZ) overlying thick continental crust (45–50&nbsp;km) that produces almost exclusively mafic material. As Manantial Pelado is surrounded by extensive silicic volcanism, the study of its mafic exposure as a stratocone can be used to further understand magmatic origins of long-lived volcanic systems. Our study uses textural, geochemical, and geochronological data from lavas collected from Manantial Pelado to characterize its magmatic petrogenesis, assess the primitive nature, and explain processes in the crust within the SVZ. A geologic description of the volcano reveals a mostly monotonous eruptive history of basaltic andesites that are now accessible through glacially carved valleys. New&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar dating constrains most of the volcano’s cone constructing phase to last from ~ 220 to 190&nbsp;ka. At ~ 30&nbsp;ka, small-volume activity and different petrography of more intermediate magmas were present reflecting a change in the volcano’s character. A combination of the whole-rock and mineral-scale data reveals that basaltic andesites at Manantial Pelado are among the most primitive magmas in the thickened crust of the SVZ. Evidence for this primitive signature consists of textural and zonation patterns in olivine, the presence of Cr-spinel in olivine cores, and elevated Fo and Ni content within olivine cores. This data combined with elemental diffusion modeling provides evidence for a primitive signature for these lavas. Intermediate Fo olivines with uniform core compositions (Fo</span><sub>80–84</sub><span>) suggest that basaltic andesites reside in the crust in quasi-closed system environments for extended storage prior to eruption (~ 25–6000&nbsp;years). Diffusive equilibration in those intermediate Fo olivines masks the primitive nature of the magmas. These results suggest that mafic magmas can have a protracted storage history in the crust that does not significantly alter their primitive bulk composition before reaching the surface. We argue that these are important processes in understanding the magmatic origin of long-lived systems and the presence of compositionally homogenous olivines at intermediate Fo content may represent cryptic evidence for recharge with primitive magmas that experienced prolonged crustal storage.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01406-3","usgsCitation":"Winslow, H., Ruprecht, P., Stelten, M.E., and Amigo, A., 2020, Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust: Bulletin of Volcanology, v. 82, 69, 24 p., https://doi.org/10.1007/s00445-020-01406-3.","productDescription":"69, 24 p.","ipdsId":"IP-120597","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Manantial Pelado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -71.12460848108275,\n              -35.48782312280931\n            ],\n            [\n              -71.12460848108275,\n              -35.86478726958381\n            ],\n            [\n              -70.51553281855436,\n              -35.86478726958381\n            ],\n            [\n              -70.51553281855436,\n              -35.48782312280931\n            ],\n            [\n              -71.12460848108275,\n              -35.48782312280931\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Winslow, Heather 0000-0001-6664-6339","orcid":"https://orcid.org/0000-0001-6664-6339","contributorId":345733,"corporation":false,"usgs":false,"family":"Winslow","given":"Heather","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":917374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruprecht, Philipp","contributorId":199796,"corporation":false,"usgs":false,"family":"Ruprecht","given":"Philipp","email":"","affiliations":[{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false},{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":917375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amigo, Alvaro","contributorId":173513,"corporation":false,"usgs":false,"family":"Amigo","given":"Alvaro","affiliations":[{"id":27236,"text":"SERNAGEOMIN","active":true,"usgs":false}],"preferred":false,"id":917377,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215356,"text":"70215356 - 2020 - Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier","interactions":[],"lastModifiedDate":"2020-11-30T16:39:00.408384","indexId":"70215356","displayToPublicDate":"2020-10-09T08:22:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier","docAbstract":"<p><span>Tributaries provide spawning habitat for three of four major sub-stocks of Lake Erie walleye (</span><i>Sander vitreus</i><span>). Despite anthropogenic degradation and the extirpation of other potamodromous species, the Maumee River, Ohio, USA continues to support one of the largest fish migrations in the Laurentian Great Lakes. To determine if spawning habitat availability and quality could limit production of Maumee River walleye, two habitat suitability models were created for the lower 51&nbsp;km of the Maumee River and the distribution and numbers of walleye eggs deposited in a 25 km stretch of river were assessed. Walleye eggs were collected using a diaphragm pump at 7 and 10 sites from March/April to May 2014 and 2015. The habitat suitability models showed that &lt;3% of the river yielded ‘good’ walleye spawning habitat and 11–38% yielded ‘moderate’ walleye spawning habitat, depending on the model. However, a large set of rapids at river kilometer 28 and more than five river kilometers of less suitable habitat separated areas of ‘good’ habitat. The rapids may present a migratory barrier for many spawning walleye, as modeled water velocities exceed maximum estimated walleye swim speeds 71–100% of days during pre-spawn migration and spawning during the study period. In both study years, there was a sharp decline in mean egg numbers from spawning sites downstream of the rapids (439.7 eggs/2 min tow&nbsp;±&nbsp;990.6 SD) to upstream sites (5.9&nbsp;eggs/2 min tow&nbsp;±&nbsp;19.4 SD). Physical barriers like rapids may reduce spawning habitat connectivity and could limit walleye production in the Maumee River.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.08.022","usgsCitation":"Schmidt, B., Tucker, T., Collier, J., Mayer, C., Roseman, E., Stott, W., and Pritt, J., 2020, Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier: Journal of Great Lakes Research, v. 46, no. 6, p. 1661-1673, https://doi.org/10.1016/j.jglr.2020.08.022.","productDescription":"13 p.","startPage":"1661","endPage":"1673","ipdsId":"IP-115670","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436758,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9214IQU","text":"USGS data release","linkHelpText":"Walleye (Sander vitreus) egg deposition and spawning habitat suitability in the Maumee River, OH (2014-2015)"},{"id":379460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.36975097656249,\n              41.68111756290652\n            ],\n            [\n              -83.47412109375,\n              41.75492216766298\n            ],\n            [\n              -84.232177734375,\n              41.47977575214487\n            ],\n            [\n              -84.638671875,\n              41.31082388091818\n            ],\n            [\n              -84.5947265625,\n              41.08763212467916\n            ],\n            [\n              -83.81469726562499,\n              41.33970040774419\n            ],\n            [\n              -83.5015869140625,\n              41.51269075845857\n            ],\n            [\n              -83.36975097656249,\n              41.68111756290652\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Brian 0000-0001-7067-6194","orcid":"https://orcid.org/0000-0001-7067-6194","contributorId":242674,"corporation":false,"usgs":false,"family":"Schmidt","given":"Brian","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":801850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Taaja 0000-0003-1534-4677","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":217908,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collier, Jessica","contributorId":242677,"corporation":false,"usgs":false,"family":"Collier","given":"Jessica","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Christine","contributorId":237769,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","affiliations":[{"id":47604,"text":"University of Toledo, Lake Erie Center","active":true,"usgs":false}],"preferred":false,"id":801853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801854,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stott, Wendylee 0000-0002-5252-4901 wstott@usgs.gov","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":191249,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801855,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pritt, Jeremy J.","contributorId":138591,"corporation":false,"usgs":false,"family":"Pritt","given":"Jeremy J.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":801856,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70215178,"text":"70215178 - 2020 - Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation","interactions":[],"lastModifiedDate":"2020-10-09T12:45:17.757956","indexId":"70215178","displayToPublicDate":"2020-10-09T07:39:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\"><div id=\"abst0010\"><p id=\"spar0060\">If carbon capture and storage (CCS) needs to be deployed at basin- or larger-scale, it is likely that multiple sites will be injecting carbon dioxide (CO<sub>2</sub>) into the same geologic formation. This could lead to excessive pressure buildup, overlapping induced pressure fronts, and pressure interference with neighboring uses of the subsurface. Extracting the in situ brine from the storage formation could be necessary to relieve pressure constraints; control migration of the CO<sub>2</sub><span>&nbsp;</span>plume, displaced brine, and the induced pressure front; and sequester more CO<sub>2</sub><span>&nbsp;</span>while reducing potential risks. Such active pressure management could be very costly, and it could present a formidable economic constraint on the feasible scale of deployment of CCS. Alternatively, there may be high-injectivity zones (“storage sweet spots”) where a significant volume of CO<sub>2</sub><span>&nbsp;</span>could be stored without producing brine. For simulated deployment of CO<sub>2</sub><span>&nbsp;</span>storage sites across the Illinois Basin, the results of this study suggest that brine production could be required to sequester 20 % or more of the regional CO<sub>2</sub><span>&nbsp;</span>emissions of major stationary sources in the Mount Simon Sandstone saline formation. In some cases, brine production could expand pressure-limited CO<sub>2</sub><span>&nbsp;</span>storage capacity enough to more than compensate for the additional costs of pressure management, but only if produced brine could be cheaply reinjected onsite for disposal in an overlying geologic formation. With or without brine production, this study found that the lowest-cost deployment option was to inject CO<sub>2</sub><span>&nbsp;</span>only into a potential storage sweet spot of the Mount Simon Sandstone.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2020.103161","usgsCitation":"Anderson, S.T., and Jahediesfanjani, H., 2020, Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation: International Journal of Greenhouse Gas Control, v. 102, 103161, 13 p., https://doi.org/10.1016/j.ijggc.2020.103161.","productDescription":"103161, 13 p.","ipdsId":"IP-112472","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":455085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijggc.2020.103161","text":"Publisher Index Page"},{"id":379267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.62695312499999,\n              41.11246878918088\n            ],\n            [\n              -88.24218749999999,\n              40.94671366508002\n            ],\n            [\n              -88.87939453125,\n              40.97989806962013\n            ],\n            [\n              -89.6484375,\n              40.713955826286046\n            ],\n            [\n              -90.087890625,\n              39.70718665682654\n            ],\n            [\n              -89.71435546875,\n              38.51378825951165\n            ],\n            [\n              -89.07714843749999,\n              37.80544394934271\n            ],\n            [\n              -88.330078125,\n              37.56199695314352\n            ],\n            [\n              -87.07763671875,\n              37.90953361677018\n            ],\n            [\n              -85.95703125,\n              38.013476231041935\n            ],\n            [\n              -85.3857421875,\n              38.37611542403604\n            ],\n            [\n              -84.83642578125,\n              39.18117526158749\n            ],\n            [\n              -84.4189453125,\n              40.413496049701955\n            ],\n            [\n              -84.70458984375,\n              41.44272637767212\n            ],\n            [\n              -85.869140625,\n              41.49212083968776\n            ],\n            [\n              -87.03369140625,\n              41.29431726315258\n            ],\n            [\n              -87.62695312499999,\n              41.11246878918088\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":801067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166 hjahediesfanjani@usgs.gov","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":193397,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","email":"hjahediesfanjani@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":801073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216162,"text":"70216162 - 2020 - Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions","interactions":[],"lastModifiedDate":"2020-11-09T21:26:07.128755","indexId":"70216162","displayToPublicDate":"2020-10-09T07:36:34","publicationYear":"2020","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":"Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>Azimuthal variations in receiver function conversions can image lithospheric structural contrasts and anisotropic fabrics that together compose tectonic grain. We apply this method to data from EarthScope Transportable Array in Alaska and additional stations across the northern Cordillera. The best‐resolved quantities are the strike and depth of dipping fabric contrasts or interfaces. We find a strong geographic gradient in such anomalies, with large amplitudes extending inboard from the present‐day subduction margin, the Aleutian arc, and an influence of flat‐slab subduction of the Yakutat microplate north of the Denali fault. An east–west band across interior Alaska shows low‐amplitude crustal anomalies. Anomaly amplitudes correlate with structural intensity (density of aligned geological elements), but are the highest in areas of strong Cenozoic deformation, raising the question of an influence of current stress state. Imaged subsurface strikes show alignment with surface structures. We see concentric strikes around arc volcanoes implying dipping magmatic structures and fabric into the middle crust. Regions with present‐day weaker deformation show lower anomaly amplitudes but structurally aligned strikes, suggesting pre‐Cenozoic fabrics may have been overprinted or otherwise modified. We observe general coherence of the signal across the brittle‐plastic transition. Imaged crustal fabrics are aligned with major faults and shear zones, whereas intrafault blocks show imaged strikes both parallel to and at high angles to major block‐bounding faults. High‐angle strikes are subparallel to neotectonic deformation, seismicity, fault lineaments, and prominent metallogenic belts, possibly due to overprinting and/or co‐evolution with fault‐parallel fabrics. We suggest that the underlying tectonic grain in the northern Cordillera is broadly distributed rather than strongly localized. Receiver functions thus reveal key information about the nature and continuity of tectonic fabrics at depth and can provide unique insights into the deformation history and distribution of regional strain in complex orogenic belts.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200182","usgsCitation":"Schulte-Pelkum, V., Caine, J., Jones, J.V., and Becker, T.W., 2020, Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions: Seismological Research Letters, v. 91, no. 6, p. 3086-3105, https://doi.org/10.1785/0220200182.","productDescription":"20 p.","startPage":"3086","endPage":"3105","ipdsId":"IP-119039","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science 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Vera 0000-0002-6057-5637","orcid":"https://orcid.org/0000-0002-6057-5637","contributorId":244614,"corporation":false,"usgs":false,"family":"Schulte-Pelkum","given":"Vera","email":"","affiliations":[{"id":48947,"text":"Cooperative Institute for Research in Environmental Sciences and Department of Geological Sciences, University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":804261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":804262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":804263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becker, Thorsten W 0000-0002-5656-4564","orcid":"https://orcid.org/0000-0002-5656-4564","contributorId":244615,"corporation":false,"usgs":false,"family":"Becker","given":"Thorsten","email":"","middleInitial":"W","affiliations":[{"id":48948,"text":"Department of Geological Sciences and Institute for Geophysics, Jackson School of Geosciences, The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":804264,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215180,"text":"70215180 - 2020 - Micro-geographic variation in burrow use of Agassiz’s desert tortoises in the Sonoran Desert of California","interactions":[],"lastModifiedDate":"2020-10-09T12:35:41.521628","indexId":"70215180","displayToPublicDate":"2020-10-09T07:22:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7150,"text":"The Herpetological Journal","active":true,"publicationSubtype":{"id":10}},"title":"Micro-geographic variation in burrow use of Agassiz’s desert tortoises in the Sonoran Desert of California","docAbstract":"<p><span>Little has been published regarding the burrowing habits of Agassiz’s desert tortoises (</span><i>Gopherus agassizii</i><span>) in the Sonoran Desert of California. We monitored the interactions of tortoises with their burrows, and other tortoises, via radio-telemetry at two nearby sites between the Cottonwood and Orocopia Mountains, from 2015-2018. We examined how annual cycles of drought and non-drought years, behaviourally affected how tortoises use their burrows (i.e., burrow fidelity, cohabitation,</span><br><span>and location), including the timing of the tortoise brumation period. Burrow locations were strongly dependent on local geology and topography, with a tendency to orientate in conformance with the general aspect of the landscape. The timing of brumation was similar to records for&nbsp;</span><i>G. agassizii</i><span>&nbsp;throughout their range (with a few exceptions). There was no difference in the estimated number of burrows used per 30 days between the active seasons (2017 and 2018) at the Orocopia site, despite the occurrence of drought in 2018.</span></p>","language":"English","publisher":"British Herpetological Society","doi":"10.33256/hj30.4.177188","usgsCitation":"Cummings, K.L., Lovich, J.E., Puffer, S., Arundel, T.R., and Brundige, K., 2020, Micro-geographic variation in burrow use of Agassiz’s desert tortoises in the Sonoran Desert of California: The Herpetological Journal, v. 30, no. 4, p. 177-188, https://doi.org/10.33256/hj30.4.177188.","productDescription":"12 p.","startPage":"177","endPage":"188","ipdsId":"IP-114020","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.33256/hj30.4.177188","text":"Publisher Index Page"},{"id":379266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sonoran Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.70227050781249,\n              32.676372772089834\n            ],\n            [\n              -114.345703125,\n              32.676372772089834\n            ],\n            [\n              -114.345703125,\n              34.379712580462204\n            ],\n            [\n              -116.70227050781249,\n              34.379712580462204\n            ],\n            [\n              -116.70227050781249,\n              32.676372772089834\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Cummings, Kristy L. 0000-0002-8316-5059","orcid":"https://orcid.org/0000-0002-8316-5059","contributorId":202061,"corporation":false,"usgs":true,"family":"Cummings","given":"Kristy","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":801068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":801069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":801070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arundel, Terence R. 0000-0003-0324-4249 tarundel@usgs.gov","orcid":"https://orcid.org/0000-0003-0324-4249","contributorId":139242,"corporation":false,"usgs":true,"family":"Arundel","given":"Terence","email":"tarundel@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":801071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brundige, Kathleen D.","contributorId":225577,"corporation":false,"usgs":false,"family":"Brundige","given":"Kathleen D.","affiliations":[],"preferred":false,"id":801072,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215379,"text":"70215379 - 2020 - Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data","interactions":[],"lastModifiedDate":"2020-10-16T11:48:29.969933","indexId":"70215379","displayToPublicDate":"2020-10-09T06:45:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/land9100382","usgsCitation":"Baughman, C., Loehman, R.A., Magness, D.R., Saperstein, L., and Sherriff, R., 2020, Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data: Land, v. 9, no. 10, 382, 22 p., https://doi.org/10.3390/land9100382.","productDescription":"382, 22 p.","ipdsId":"IP-116240","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":455092,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land9100382","text":"Publisher Index Page"},{"id":436759,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92BGHW1","text":"USGS data release","linkHelpText":"Land Cover Estimates for the Kenai Peninsula Lowlands; 1973, 2002, and 2017"},{"id":379452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.10546875,\n              59.0405546167585\n            ],\n            [\n              -147.48046875,\n              59.0405546167585\n            ],\n            [\n              -147.48046875,\n              61.52269494598361\n            ],\n            [\n              -153.10546875,\n              61.52269494598361\n            ],\n            [\n              -153.10546875,\n              59.0405546167585\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":801904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":801905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magness, Dawn R.","contributorId":243262,"corporation":false,"usgs":false,"family":"Magness","given":"Dawn","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saperstein, Lisa","contributorId":218974,"corporation":false,"usgs":false,"family":"Saperstein","given":"Lisa","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherriff, Rosemary L.","contributorId":243263,"corporation":false,"usgs":false,"family":"Sherriff","given":"Rosemary L.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":801908,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228541,"text":"70228541 - 2020 - Methods for estimating vital rates of greater sage-grouse broods: A review","interactions":[],"lastModifiedDate":"2022-02-14T20:52:41.251421","indexId":"70228541","displayToPublicDate":"2020-10-08T15:52:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Methods for estimating vital rates of greater sage-grouse broods: A review","docAbstract":"<p>Biologists use a variety of methods to estimate productivity and resource selection of birds. The effectiveness and suitability of each method depends on the study's objectives, but is also influenced by many important traits, including detection probability, disturbance of focal birds and sampling frequency. We reviewed 504 greater sage-grouse Centrocercus urophasianus papers published from 1990 to 2019 to document the most common brood survey methods used by investigators and summarized if and how they used brood survey data to estimate brood survival and detection probability. Of the 504 papers, 16.1% (n = 81) had useful information relevant to the review. The most common methods included daytime visual surveys (46.9%; n = 38), daytime flush surveys (33.3%; n = 27), nocturnal spotlight surveys (19.8%; n = 16), radio-tagged chicks (16.0%; n = 13), wing surveys (9.9%; n = 8), brood routes (4.9%; n = 4) and pointing dogs (4.9%; n = 4). Fifty-nine of the 81 papers used &gt;1 method, only 2 of the 81 papers measured or reported detection probability, and none reported the level of disturbance caused by the method. Studies varied widely regarding the age of the brood when brood fate was confirmed (x̄ = 44.4 days post-hatch, range 14–84 days). The frequency of brood sampling visits also varied greatly among studies (range = 1.19–3.85 surveys/brood/week) and this variation complicates comparison in fecundity and survival estimates across studies. Furthermore, 35 papers used &gt;1 maternal behavior as purported indicators of brood fate, but none of them documented how accurate their indicators were. Future studies could reduce variance in estimates of sage-grouse fecundity and brood survival by employing empirical methods to estimate detection probability, standardizing brood sampling methods and conducting trials to document the effects of hen or brood capture, handling and flushing on brood survival estimates. Moreover, the accuracy of commonly used indicators of brood fate, including maternal behaviors, flocking behavior and distance moved after flush needs verification.</p>","language":"English","publisher":"BioOne","doi":"10.2981/wlb.00700","usgsCitation":"Riley, I.P., and Conway, C.J., 2020, Methods for estimating vital rates of greater sage-grouse broods: A review: Wildlife Biology, v. 4, wlb.00700, 12 p., https://doi.org/10.2981/wlb.00700.","productDescription":"wlb.00700, 12 p.","ipdsId":"IP-117997","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00700","text":"Publisher Index Page"},{"id":395937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Riley, Ian P.","contributorId":272044,"corporation":false,"usgs":false,"family":"Riley","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834534,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215393,"text":"70215393 - 2020 - Patterns and isotopic composition of greenhouse gases under ice in lakes of interior Alaska","interactions":[],"lastModifiedDate":"2020-10-17T15:25:20.524564","indexId":"70215393","displayToPublicDate":"2020-10-08T10:20:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and isotopic composition of greenhouse gases under ice in lakes of interior Alaska","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Arctic and boreal lake greenhouse gas emissions (GHG) are an important component of regional carbon (C) budgets. Yet the magnitude and seasonal patterns of lake GHG emissions are poorly constrained, because sampling is limited in these remote landscapes, particularly during winter and shoulder seasons. To better define patterns of under ice GHG content (and emissions potential at spring thaw), we surveyed carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) concentrations and stable isotopic composition during winter of 2017 in 13 lakes in the arid Yukon Flats Basin of interior Alaska, USA. Partial pressures of CO<sub>2</sub><span>&nbsp;</span>and CH<sub>4</sub><span>&nbsp;</span>ranged over three orders of magnitude, were positively correlated, and CO<sub>2</sub><span>&nbsp;</span>exceeded CH<sub>4</sub><span>&nbsp;</span>at all but one site. Shallow, organic matter-rich lakes located at lower elevations tended to have the highest concentrations of both gases, though CH<sub>4</sub><span>&nbsp;</span>content was more heterogeneous and only abundant in oxygen-depleted lakes, while CO<sub>2</sub><span>&nbsp;</span>was negatively correlated to oxygen content. Isotopic values of CO<sub>2</sub><span>&nbsp;</span>spanned a narrow range (−10‰ to −23‰) compared to CH<sub>4</sub>, which ranged over 50‰ (−19‰ to −71‰), indicating CH<sub>4</sub><span>&nbsp;</span>source pathways and sink strength varied widely between lakes. Miller-Tans and Keeling plots qualitatively suggested two groups of lakes were present; one with isotopically enriched source CH<sub>4</sub><span>&nbsp;</span>possibly more dominated by acetoclastic methanogenesis, and one with depleted signatures suggesting a dominance of the hydrogenotrophic production. Overall, regional lake differences in winter under ice GHG content appear to track landscape position, oxygen, and organic matter content and composition, causing patterns to vary widely even within a relatively small geographic area of interior Alaska.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abb493","usgsCitation":"O’Dwyer, M., Butman, D., Striegl, R.G., Dornblaser, M.M., Wickland, K.P., Kuhn, C.D., and Bogard, M.J., 2020, Patterns and isotopic composition of greenhouse gases under ice in lakes of interior Alaska: Environmental Research Letters, v. 15, no. 10, 105016, 12 p., https://doi.org/10.1088/1748-9326/abb493.","productDescription":"105016, 12 p.","ipdsId":"IP-116217","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":455096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abb493","text":"Publisher Index Page"},{"id":379483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.677734375,\n              66.05371622067922\n            ],\n            [\n              -141.0205078125,\n              66.05371622067922\n            ],\n            [\n              -141.0205078125,\n              68.47992564291266\n            ],\n            [\n              -149.677734375,\n              68.47992564291266\n            ],\n            [\n              -149.677734375,\n              66.05371622067922\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Dwyer, Madeline","contributorId":243303,"corporation":false,"usgs":false,"family":"O’Dwyer","given":"Madeline","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":801985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, David","contributorId":224754,"corporation":false,"usgs":false,"family":"Butman","given":"David","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":801986,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":801987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dornblaser, Mark M. 0000-0002-6298-3757 mmdornbl@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":1636,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","email":"mmdornbl@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":801988,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":801989,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuhn, Catherine D. 0000-0002-9220-630X","orcid":"https://orcid.org/0000-0002-9220-630X","contributorId":213255,"corporation":false,"usgs":false,"family":"Kuhn","given":"Catherine","email":"","middleInitial":"D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":801990,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bogard, Matthew J. 0000-0001-9491-0328","orcid":"https://orcid.org/0000-0001-9491-0328","contributorId":213254,"corporation":false,"usgs":false,"family":"Bogard","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":801991,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70205608,"text":"sim3443 - 2020 - Geologic map of the greater Portland metropolitan area and surrounding region, Oregon and Washington","interactions":[],"lastModifiedDate":"2022-03-10T17:43:21.40102","indexId":"sim3443","displayToPublicDate":"2020-10-08T09:21:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3443","displayTitle":"Geologic Map of the Greater Portland Metropolitan Area and Surrounding Region, Oregon and Washington","title":"Geologic map of the greater Portland metropolitan area and surrounding region, Oregon and Washington","docAbstract":"<p>The Portland-Vancouver-Hillsboro Metropolitan Area (metro area) has great scenic, natural, and cultural resources and is the major economic hub of Oregon. The metro area is subject to a variety of geologic hazards. Underthrusting of the oceanic plate along the Cascadia plate boundary fault, or megathrust, deforms the leading edge of North America and produces earthquakes on the megathrust and in the overlying plate. Rising magma from the deeper parts of the subduction zone produces active volcanoes that form the Cascades Arc, including Mount Hood and Mount St. Helens visible from Portland. Both volcanism and strong ground-shaking from earthquakes have impacted the metro area, most recently in the 1980 eruptions of Mount St. Helens and the 1993 magnitude (M) 5.7 Scotts Mills earthquake. Great offshore earthquakes as large as M 9 on the Cascadia megathrust have shaken the metro area every 500 years or so, most recently in 1700. Giant floods have inundated the metro area, from the ice age Missoula floods about 20,000 to 15,000 years ago to the flood generated by collapse of the Bridge of the Gods landslide dam on the Columbia River around 1421–1447 A.D.</p><p>Geologic resources of the metro area include the southern part of the Mist Natural Gas Storage Field in the northwest corner of the map area, the Columbia South Shore Well Field aquifer in the Portland Basin, the Columbia River Basalt aquifer of the Tualatin Basin, and the Tualatin Basin Aquifer Storage and Recovery projects. The metro area includes several well-known American Viticultural Areas in the western part of the map area and numerous transportation, electrical transmission, and pipeline corridors.</p><p>We created this map to provide a uniform, modern geologic database for the greater Portland metro area to better understand its tectonic setting, active faults, volcanoes, landslide hazards, and distribution of geologic materials and resources. Information in this database will be used to improve seismic hazard and resource assessments in this economically important region.</p><p>NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3443","collaboration":"Prepared in Cooperation with Oregon Department of Geology and Mineral Industries and Washington Geological Survey","usgsCitation":"Wells, R.E., Haugerud, R.A., Niem, A.R., Niem, W.A., Ma, L., Evarts, R.C., O’Connor, J.E., Madin, I.P., Sherrod, D.R., Beeson, M.H., Tolan, T.L., Wheeler, K.L., Hanson, W.B., and Sawlan, M.G., 2020, Geologic map of the greater Portland metropolitan area and surrounding region, Oregon and Washington: U.S. Geological Survey Scientific Investigations Map 3443, pamphlet 55 p., 2 sheets, scale 1:63,360, https://doi.org/10.3133/sim3443.","productDescription":"Pamphlet: iv, 55 p.; 2 Sheets: 58.43 x 60.16 inches and 38.76 x 30.86 inches; Table 3; Database; Metadata; Read Me","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081424","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":396997,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1_south.pdf","text":"Sheet 1 South","size":"55 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map."},{"id":396996,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1_north.pdf","text":"Sheet 1 North","size":"55 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map."},{"id":376987,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3443/database","text":"Database directory"},{"id":376984,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3443/metadata","text":"Metadata directory"},{"id":376983,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_table3.xlsx","text":"Table 3","size":"110 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":376982,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet2.pdf","text":"Sheet 2","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376981,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1.pdf","text":"Sheet 1","size":"80 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376980,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_readme.txt","size":"5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":376979,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_pamphlet.pdf","text":"Pamphlet","size":"28 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376953,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3443/covrthb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Greater Portland metropolitan area and surrounding region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.20617675781251,\n              44.95702412512118\n            ],\n            [\n              -122.0855712890625,\n              44.95702412512118\n            ],\n            [\n              -122.0855712890625,\n              46.145588688591964\n            ],\n            [\n              -123.20617675781251,\n              46.145588688591964\n            ],\n            [\n              -123.20617675781251,\n              44.95702412512118\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Menlo Park, California</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591</p>","tableOfContents":"<ul><li>Introduction</li><li>Previous Work</li><li>Geologic History</li><li>Earth Resources</li><li>Map Compilation</li><li>Acknowledgments</li><li>Description of Map Units</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-10-08","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":149772,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","email":"rwells@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":771833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":771838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niem, Alan R.","contributorId":219264,"corporation":false,"usgs":false,"family":"Niem","given":"Alan","email":"","middleInitial":"R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":771839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niem, Wendy A.","contributorId":219265,"corporation":false,"usgs":false,"family":"Niem","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":771840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ma, Lina","contributorId":204020,"corporation":false,"usgs":false,"family":"Ma","given":"Lina","email":"","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":771834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evarts, Russell C. 0000-0001-5103-9085","orcid":"https://orcid.org/0000-0001-5103-9085","contributorId":219266,"corporation":false,"usgs":false,"family":"Evarts","given":"Russell C.","affiliations":[],"preferred":false,"id":771841,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":771837,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Madin, Ian P.","contributorId":66404,"corporation":false,"usgs":true,"family":"Madin","given":"Ian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":771835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":771836,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beeson, Marvin H.","contributorId":219267,"corporation":false,"usgs":false,"family":"Beeson","given":"Marvin","email":"","middleInitial":"H.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":771842,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tolan, Terry L.","contributorId":219268,"corporation":false,"usgs":false,"family":"Tolan","given":"Terry","email":"","middleInitial":"L.","affiliations":[{"id":39980,"text":"Intera Geoscience and Engineering Solutions","active":true,"usgs":false}],"preferred":false,"id":771843,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wheeler, Karen L.","contributorId":219269,"corporation":false,"usgs":false,"family":"Wheeler","given":"Karen L.","affiliations":[],"preferred":false,"id":771844,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hanson, William B.","contributorId":219270,"corporation":false,"usgs":false,"family":"Hanson","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":39981,"text":"private consultant","active":true,"usgs":false}],"preferred":false,"id":771845,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sawlan, Michael G. 0000-0003-0637-2051 msawlan@usgs.gov","orcid":"https://orcid.org/0000-0003-0637-2051","contributorId":2291,"corporation":false,"usgs":true,"family":"Sawlan","given":"Michael","email":"msawlan@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":771846,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70215551,"text":"70215551 - 2020 - Getting to the root of restoration: Considering root traits for improved restoration outcomes under drought and competition","interactions":[],"lastModifiedDate":"2020-11-30T16:51:47.983035","indexId":"70215551","displayToPublicDate":"2020-10-08T08:29:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Getting to the root of restoration: Considering root traits for improved restoration outcomes under drought and competition","docAbstract":"A foundational goal of trait‐based ecology, including trait‐based restoration, is to link specific traits to community assembly, biodiversity, and ecosystem function. Despite a growing awareness of the importance of belowground traits for ecological processes, a synthesis of how to root traits can inform restoration of terrestrial plant communities is lacking. We reviewed and summarized existing literature focused on root traits in relation to plant performance measures (i.e. survival, establishment, productivity) in the contexts of drought and competition (including invasion). Root traits related to belowground resource acquisition (e.g. high specific root length, deep roots) are frequently related to drought avoidance (i.e. a plant strategy based on optimizing water uptake to maintain function), whereas studies relating root traits to drought tolerance (i.e. a plant strategy that allows plants to withstand low hydration) remain limited. More studies have linked root traits to plant competitive effects (i.e. the influence of a plant has on neighbors) than to competitive responses (i.e. a plant's ability to resist the effects of neighbors). Because plants with acquisitive traits decrease resources to the detriment of neighbors, root traits associated with rapid resource acquisition (e.g. high specific root length) may be important for understanding competitive effects. Albeit more limited, research suggests root traits associated with resource conservation or stress tolerance (e.g. high root tissue density, high root diameter) may elucidate mechanisms related to competitive responses. Re‐vegetation outcomes may be improved by considering root traits, but only if clear links are made between traits and plant performance in varied contexts.","language":"English","publisher":"Wiley","doi":"10.1111/rec.13291","usgsCitation":"Garbowski, M., Avera, B., Bertram, J.H., Courkamp, J., Gray, J., Hein, K., Lawrence, R., McIntosh, M., McClelland, S., Post, A., Slette, I.J., Winkler, D.E., and Brown, C.S., 2020, Getting to the root of restoration: Considering root traits for improved restoration outcomes under drought and competition: Restoration Ecology, v. 28, no. 6, p. 1384-1395, https://doi.org/10.1111/rec.13291.","productDescription":"12 p.","startPage":"1384","endPage":"1395","ipdsId":"IP-120212","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13291","text":"Publisher Index Page"},{"id":379646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Garbowski, M.","contributorId":243608,"corporation":false,"usgs":false,"family":"Garbowski","given":"M.","affiliations":[],"preferred":false,"id":802708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avera, B.","contributorId":243609,"corporation":false,"usgs":false,"family":"Avera","given":"B.","email":"","affiliations":[],"preferred":false,"id":802709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bertram, J. H.","contributorId":243610,"corporation":false,"usgs":false,"family":"Bertram","given":"J.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":802710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Courkamp, J.S.","contributorId":243611,"corporation":false,"usgs":false,"family":"Courkamp","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":802711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, J.","contributorId":100683,"corporation":false,"usgs":true,"family":"Gray","given":"J.","affiliations":[],"preferred":false,"id":802712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hein, K.M.","contributorId":243612,"corporation":false,"usgs":false,"family":"Hein","given":"K.M.","email":"","affiliations":[],"preferred":false,"id":802713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawrence, R.","contributorId":101430,"corporation":false,"usgs":false,"family":"Lawrence","given":"R.","email":"","affiliations":[],"preferred":false,"id":802714,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McIntosh, M.","contributorId":243613,"corporation":false,"usgs":false,"family":"McIntosh","given":"M.","email":"","affiliations":[],"preferred":false,"id":802715,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClelland, S.","contributorId":95633,"corporation":false,"usgs":false,"family":"McClelland","given":"S.","email":"","affiliations":[],"preferred":false,"id":802716,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Post, A.","contributorId":51033,"corporation":false,"usgs":false,"family":"Post","given":"A.","email":"","affiliations":[],"preferred":false,"id":802717,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Slette, Ingrid J.","contributorId":187583,"corporation":false,"usgs":false,"family":"Slette","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":802718,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":802719,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Brown, C. S.","contributorId":80675,"corporation":false,"usgs":false,"family":"Brown","given":"C.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":802720,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70215232,"text":"70215232 - 2020 - A latent process model approach to improve the utility of indicator species","interactions":[],"lastModifiedDate":"2020-12-14T16:42:07.776742","indexId":"70215232","displayToPublicDate":"2020-10-08T07:35:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"A latent process model approach to improve the utility of indicator species","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The state of an ecosystem is governed by dynamic biotic and abiotic processes, which can only be partially observed. Costs associated with measuring each component limit the feasibility of comprehensive assessments of target ecosystems. Instead, indicator species are recommended as a surrogate index. While this is an attractive concept, indicator species have rarely proven to be an effective tool for monitoring ecosystems and informing management decisions. One deficiency in the existing theoretical development of indicator species may be overcome with the incorporation of latent (i.e. unobservable) states. Advancements in quantitative ecological models allow for latent‐state models to be tested empirically, facilitating the robust evaluation and practical use of indicator species for ecosystem science and management. Here, we extend the existing conceptual models of indicator species to include a direct relationship between an indicator species, ecosystem change drivers and latent processes and variables. Our approach includes explicit consideration of important estimation uncertainty and narrows the range of values a latent variable may take by relating it to measurable attribute(s) of an indicator species. We demonstrate the utility of this approach by relating a commonly cited indicator species, the red‐backed salamander<span>&nbsp;</span><i>Plethodon cinereus</i>, to a typical latent process of interest – ecosystem health.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/oik.07334","usgsCitation":"Fleming, J.E., Sutherland, C., Sterrett, S., and Campbell Grant, E.H., 2020, A latent process model approach to improve the utility of indicator species: Oikos, v. 129, no. 12, p. 1753-1762, https://doi.org/10.1111/oik.07334.","productDescription":"10 p.","startPage":"1753","endPage":"1762","ipdsId":"IP-118473","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Jillian Elizabeth 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":238931,"corporation":false,"usgs":true,"family":"Fleming","given":"Jillian","email":"","middleInitial":"Elizabeth","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":801243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":801244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sterrett, Sean C 0000-0003-1356-2785","orcid":"https://orcid.org/0000-0003-1356-2785","contributorId":242972,"corporation":false,"usgs":false,"family":"Sterrett","given":"Sean C","affiliations":[{"id":38445,"text":"Monmouth University","active":true,"usgs":false}],"preferred":false,"id":801245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":801246,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70214611,"text":"sim3463 - 2020 - Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019","interactions":[],"lastModifiedDate":"2020-10-07T23:40:27.941947","indexId":"sim3463","displayToPublicDate":"2020-10-07T15:35:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3463","displayTitle":"Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019","title":"Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the U.S. Air Force Academy (USAFA), carried out bathymetric and topographic surveys to characterize the volume of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado. Bathymetric maps of each lake and reservoir are presented with figures of the elevation-volume curves. The bathymetric surveys were carried out from October 15, 2019, to December 12, 2019, using a manually operated, boat-mounted, single-beam echo sounder integrated with a Real-Time Kinematic Global Navigation Satellite Systems receiver. Topographic surveys were carried out during the same time period using Real-Time Kinematic Global Navigation Satellite System to collect elevation data at and above the water surface and up to the elevation of the dam or spillway at the time of the surveys. The topographic and bathymetric datasets were imported into Esri ArcMap 10.7.1. The combined survey points were then interpolated into digital elevation models, which were used to determine lake or reservoir volumes that correspond to water-surface elevations between the lakebed and the approximate top of the dam or spillway.</p><p>This report provides an updated characterization of storage capacity and improved understanding of present (2019) water capacity in the lakes and reservoirs at the USAFA. In addition, these surveys serve as a baseline that could be compared with future surveys of the lakes and reservoirs. The differences in these and future surveys could then be used to determine sedimentation infill rates and provide estimates of the lifespan of the lakes and reservoirs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3463","collaboration":"Prepared in cooperation with the U.S. Air Force Academy","usgsCitation":"Kohn, M.S., and Hempel, L.A., 2020, Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019: U.S. Geological Survey Scientific Investigations Map 3463, pamphlet 12 p., https://doi.org/10.3133/sim3463.","productDescription":"Pamphlet: vi, 12 p.; 1 Sheet: 36.00 x 32.00 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114390","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":378914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3463/coverthb.jpg"},{"id":378915,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3463/sim3463_map.pdf","text":"Map","size":"9.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3463"},{"id":378917,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LTH0RO","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Survey and Bathymetric Data of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1-3, and Non-Potable Reservoirs 1-4 at the U.S. Air Force Academy, Colorado, 2019 (ver. 1.1, June 2020)"},{"id":378916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3463/sim3463_pamphlet.pdf","text":"Pamphlet","size":"1.17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","city":"Colorado Springs","otherGeospatial":"U.S. Airforce Academy","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.91188049316406,\n              38.91561302513129\n            ],\n            [\n              -104.77867126464842,\n              38.93163900447185\n            ],\n            [\n              -104.8267364501953,\n              39.03731965210478\n            ],\n            [\n              -104.92767333984374,\n              39.03731965210478\n            ],\n            [\n              -104.91188049316406,\n              38.91561302513129\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/co-water\" data-mce-href=\"https://www.usgs.gov/centers/co-water\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS 415<br>Denver, CO 80225</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-10-07","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800223,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70214981,"text":"ofr20201077 - 2020 - Development of a suite of functional immune assays and initial assessment of their utility in wild smallmouth bass health assessments","interactions":[],"lastModifiedDate":"2024-03-04T19:49:56.75641","indexId":"ofr20201077","displayToPublicDate":"2020-10-07T10:05:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1077","displayTitle":"Development of a Suite of Functional Immune Assays and Initial Assessment of Their Utility in Wild Smallmouth Bass Health Assessments","title":"Development of a suite of functional immune assays and initial assessment of their utility in wild smallmouth bass health assessments","docAbstract":"<p>Methods were developed for measuring immune function in <i>Micropterus dolomieu</i> (smallmouth bass). The ultimate objective is to monitor and evaluate changes over time in immune status and disease resistance in conjunction with other characteristics of fish health and environmental stressors. To test these methods for utility in ecotoxicological studies, 192 smallmouth bass, age 2 years and older, were collected from three sites within the Susquehanna River Basin and one site in the Ohio River Basin during spring and fall 2016 and 2017. The anterior kidney was aseptically removed and homogenized for leukocyte isolation. Leukocytes were tested for bactericidal activity against two species of bacteria; respiratory burst activity when stimulated with phorbol 12-myristate 13-acetate; and mitogenesis activity when stimulated with concanavalin A, phytohemagglutinin, and lipopolysaccharide. Tissues were preserved for histopathological analyses.</p><p>Two of the sites were part of a monitoring program at which surface-water samples were collected monthly (bimonthly in spring) for chemical contaminants. Significant seasonal and (or) site differences in all three immune function tests were observed. Interpretations of seasonal trends in immune function of wild fish or correlations with environmental variables and other factors are difficult to make owing to the complex nature of the immune response and the environment. Differences in immune function could potentially be related to a variety of confounding factors; therefore, additional endpoints and repeated sampling over an extended period are essential to draw conclusions on the immune status of wild fish.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201077","collaboration":"Prepared in cooperation with Pennsylvania Department of Environmental Protection","usgsCitation":"Smith, C.R., Ottinger, C.A., Walsh, H.L., and Blazer, V.S., 2020, Development of a suite of functional immune assays and initial assessment of their utility in wild smallmouth bass health assessments: U.S. Geological Survey Open-File Report 2020–1077, 23 p., https://doi.org/10.3133/ofr20201077.","productDescription":"vii, 23 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118051","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":379041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1077/ofr20201077.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1077"},{"id":379040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1077/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Tionesta Lake, Pine Creek, Upper Juniata River, West Branch Mahantango Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.79919433593749,\n              41.30257109430557\n            ],\n            [\n              -77.38220214843749,\n              41.30257109430557\n            ],\n            [\n              -77.38220214843749,\n              42.00032514831621\n            ],\n            [\n              -79.79919433593749,\n              42.00032514831621\n            ],\n            [\n              -79.79919433593749,\n              41.30257109430557\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eesc\" data-mce-href=\"https://www.usgs.gov/centers/eesc\">Eastern Ecological Science Center</a><br>U.S. Geological Survey<br>11649 Leetown Road<br>Kearneysville, WV 25430</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Materials and Methods</li><li>Biometric Data and Immune Function Results</li><li>Summary of Findings</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2020-10-07","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":true,"id":800493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ottinger, Christopher A. 0000-0003-2551-1985 cottinger@usgs.gov","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":2559,"corporation":false,"usgs":true,"family":"Ottinger","given":"Christopher","email":"cottinger@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":800494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":800495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":800496,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215540,"text":"70215540 - 2020 - Yellowstone's Old Faithful Geyser shut down by a severe 13th century drought","interactions":[],"lastModifiedDate":"2020-10-22T14:47:58.754297","indexId":"70215540","displayToPublicDate":"2020-10-07T09:43:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Yellowstone's Old Faithful Geyser shut down by a severe 13th century drought","docAbstract":"<div class=\"article-section__content en main\"><p>To characterize eruption activity of the iconic Old Faithful Geyser in Yellowstone National Park over past centuries, we obtained 41 new radiocarbon dates of mineralized wood preserved in the mound of silica that precipitated from erupted waters. Trees do not grow on active geyser mounds, implying that trees grew on the Old Faithful Geyser mound during a protracted period of eruption quiescence. Rooted stumps and root crowns located on higher parts of the mound are evidence that at the time of tree growth, the geyser mound closely resembled its current appearance. The range of calibrated radiocarbon dates (1233–1362&nbsp;CE) is coincident with a series of severe multidecadal regional droughts toward the end of the Medieval Climate Anomaly, prior to the onset of the Little Ice Age. Climate models project increasingly severe droughts by mid‐21st century, suggesting that geyser eruptions could become less frequent or completely cease.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL089871","usgsCitation":"Hurwitz, S., King, J., Pederson, G.T., Martin, J.T., Damby, D., Manga, M., Hungerford, J., and Peek, S., 2020, Yellowstone's Old Faithful Geyser shut down by a severe 13th century drought: Geophysical Research Letters, v. 47, no. 20, e2020GL089871, 8 p., https://doi.org/10.1029/2020GL089871.","productDescription":"e2020GL089871, 8 p.","ipdsId":"IP-121756","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":436760,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LEQ5HC","text":"USGS data release","linkHelpText":"Silicified wood from around Old Faithful Geyser, Yellowstone National Park"},{"id":379654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.060791015625,\n              43.810747313446996\n            ],\n            [\n              -109.44030761718749,\n              43.810747313446996\n            ],\n            [\n              -109.44030761718749,\n              45.00947686967287\n            ],\n            [\n              -111.060791015625,\n              45.00947686967287\n            ],\n            [\n              -111.060791015625,\n              43.810747313446996\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"20","noUsgsAuthors":false,"publicationDate":"2020-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, John","contributorId":243582,"corporation":false,"usgs":false,"family":"King","given":"John","affiliations":[{"id":48739,"text":"Lon Pine Research","active":true,"usgs":false}],"preferred":false,"id":802624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":802625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Justin T. 0000-0002-3523-6596","orcid":"https://orcid.org/0000-0002-3523-6596","contributorId":215418,"corporation":false,"usgs":true,"family":"Martin","given":"Justin","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":802626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802627,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Manga, Michael","contributorId":243583,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":802628,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hungerford, Jefferson","contributorId":243584,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":802629,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802630,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70215372,"text":"70215372 - 2020 - Localized fault-zone dilatancy and surface inelasticity of the 2019 Ridgecrest earthquakes","interactions":[],"lastModifiedDate":"2020-10-16T13:01:02.459958","indexId":"70215372","displayToPublicDate":"2020-10-07T07:58:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Localized fault-zone dilatancy and surface inelasticity of the 2019 Ridgecrest earthquakes","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Earthquakes produce a spectrum of elastic and inelastic deformation processes that are reflected across various length and time scales. While elasticity has long dominated research assumptions in active tectonics, increasing interest has focused on the inelastic characteristics of earthquakes, particularly those of the surface fault rupture zone itself, and how they relate to ground rupture hazard and the mechanics of damage zones. Here we present detailed co-seismic surface-strain analysis of the 2019 Ridgecrest, California, earthquakes. We derive three-dimensional high-resolution surface displacements from satellite optical imagery, which we then invert for the co-seismic surface-strain tensors. We show that fault-zone dilation is pervasive throughout these earthquakes and that inelastic failure is present but relatively localized (median width of 31 m). The width of the inelastic failure zone is not correlated to off-fault deformation, surface geology or displacement magnitude. Instead, the extent and kinematics of inelastic failure reflect active, mylonitic deformation of the fault damage zone that is influenced by rupture velocity and fault maturity. These results highlight how a single earthquake contributes to the long-term, permanent geologic record of faulting.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Nature","doi":"10.1038/s41561-020-0628-8","usgsCitation":"Barnhart, W., Gold, R.D., and Hollingsworth, J., 2020, Localized fault-zone dilatancy and surface inelasticity of the 2019 Ridgecrest earthquakes: Nature Geoscience, v. 13, p. 699-704, https://doi.org/10.1038/s41561-020-0628-8.","productDescription":"6 p.","startPage":"699","endPage":"704","ipdsId":"IP-119584","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":496346,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-03062390","text":"External Repository"},{"id":436761,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QRZ6NR","text":"USGS data release","linkHelpText":"Displacement and strain field from the 2019 Ridgecrest earthquakes derived from analysis of WorldView optical satellite imagery (ver. 2.0, May 2021)"},{"id":379457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Ridgecrest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.960205078125,\n              35.37113502280101\n            ],\n            [\n              -117.366943359375,\n              35.37113502280101\n            ],\n            [\n              -117.366943359375,\n              35.84008157153468\n            ],\n            [\n              -117.960205078125,\n              35.84008157153468\n            ],\n            [\n              -117.960205078125,\n              35.37113502280101\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, William D. 0000-0003-0498-1697","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":192730,"corporation":false,"usgs":false,"family":"Barnhart","given":"William D.","affiliations":[],"preferred":false,"id":801888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":801889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollingsworth, James","contributorId":238812,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"James","email":"","affiliations":[],"preferred":false,"id":801890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70218453,"text":"70218453 - 2020 - Habitat characterization and species distribution model of the only large-lake population of the endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844)","interactions":[],"lastModifiedDate":"2021-02-26T13:59:53.610438","indexId":"70218453","displayToPublicDate":"2020-10-07T07:55:31","publicationYear":"2020","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":"Habitat characterization and species distribution model of the only large-lake population of the endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844)","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The endangered Silver Chub (<i>Macrhybopsis storeriana,</i><span>&nbsp;</span>Kirtland 1844) is native to North America and primarily riverine, with the only known large‐lake population in Lake Erie. Once a major component of the Lake Erie fish community, it declined and became nearly extirpated in the mid‐1900s. Recent collections in western Lake Erie suggest that Silver Chub may be able to recover, but their habitat and distribution are poorly known. A recent work showed an extensive area of western Lake Erie with the potential to support large numbers of Silver Chub, but was based on a geographically limited dataset. We developed a neural network‐based species distribution model for the Silver Chub in western Lake Erie, improved by new synoptic data and using habitat variables resistant to anthropogenic activities. The Potential model predictions were compared with a model that included anthropogenic‐sensitive variables. The Potential model used 10 habitat variables and performed well, explaining&nbsp;&gt;&nbsp;99% of data variation and had generally low error rates. Predictions indicated that a large area of the waters approximately 2–9&nbsp;m deep contained Appropriate habitat and the highest abundances should be supported by habitat in a wide arc through the western end of the basin. The model indicated that Appropriate Silver Chub habitat was associated with relatively deep water, near coastal wetlands, where effective fetch is less than average. Disturbance model predictions were similar, but predicted poorer Silver Chub habitat in more areas than that predicted by the Potential model. Our Potential model reveals Appropriate habitat conditions for Silver Chub and its spatial distribution, indicating that extensive areas of western Lake Erie could support Silver Chub. Comparisons with Disturbance model predictions demonstrate that Potential model predictions may be used in conjunction with analyses of degrading conditions in the system to better conserve and manage for this endangered species.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6830","usgsCitation":"McKenna, J.E., and Kocovsky, P., 2020, Habitat characterization and species distribution model of the only large-lake population of the endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844): Ecology and Evolution, v. 10, no. 21, p. 12076-12090, https://doi.org/10.1002/ece3.6830.","productDescription":"15 p.","startPage":"12076","endPage":"12090","ipdsId":"IP-062648","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":455100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6830","text":"Publisher Index Page"},{"id":383637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ohio","otherGeospatial":"Ontario","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.8916015625,\n              41.062786068733026\n            ],\n            [\n              -81.05712890625,\n              41.062786068733026\n            ],\n            [\n              -81.05712890625,\n              42.601619944327965\n            ],\n            [\n              -83.8916015625,\n              42.601619944327965\n            ],\n            [\n              -83.8916015625,\n              41.062786068733026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"21","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":195894,"corporation":false,"usgs":true,"family":"McKenna","given":"James","suffix":"Jr.","email":"jemckenna@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":810978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":810979,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215189,"text":"70215189 - 2020 - A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","interactions":[],"lastModifiedDate":"2020-10-29T15:15:46.334579","indexId":"70215189","displayToPublicDate":"2020-10-07T07:27:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16&nbsp;days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2020.1817461","usgsCitation":"Singh, R., Khand, K.B., Kagone, S., Schauer, M., Senay, G., and Wu, Z., 2020, A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data: Hydrological Sciences Journal, v. 65, no. 14, p. 2508-2519, https://doi.org/10.1080/02626667.2020.1817461.","productDescription":"12 p.","startPage":"2508","endPage":"2519","ipdsId":"IP-113350","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2020.1817461","text":"Publisher Index Page"},{"id":379288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California","otherGeospatial":"Palo Verde Irrigation District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.9444580078125,\n              32.9764120829052\n            ],\n            [\n              -114.3402099609375,\n              32.9764120829052\n            ],\n            [\n              -114.3402099609375,\n              33.911454454267606\n            ],\n            [\n              -114.9444580078125,\n              33.911454454267606\n            ],\n            [\n              -114.9444580078125,\n              32.9764120829052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"65","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Ramesh 0000-0002-8164-3483","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":210983,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":242921,"corporation":false,"usgs":true,"family":"Khand","given":"Kul","email":"","middleInitial":"Bikram","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kagone, Stefanie 0000-0002-2979-4655","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":216913,"corporation":false,"usgs":true,"family":"Kagone","given":"Stefanie","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":216909,"corporation":false,"usgs":true,"family":"Schauer","given":"Matthew","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":801111,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217169,"text":"70217169 - 2020 - Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California","interactions":[],"lastModifiedDate":"2021-01-08T13:33:13.082193","indexId":"70217169","displayToPublicDate":"2020-10-07T07:25:36","publicationYear":"2020","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":"Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California","docAbstract":"<p><span>Shallowly dipping (&lt;30°) low‐angle normal faults (LANFs) have been documented globally; however, examples of active LANFs in continental settings are limited. The western margin of the Panamint Range in eastern California is defined by a LANF that dips west beneath Panamint Valley and has evidence of Quaternary motion. In addition, high‐angle dextral‐oblique normal faults displace middle to late Quaternary alluvial fans near the range front. To image shallow (&lt;1&nbsp;km depth), crosscutting relationships between the low‐ and high‐angle faults along the range front, we acquired two high‐resolution&nbsp;</span><i>P</i><span>&nbsp;wave seismic reflection profiles. The northern, 4.6‐km‐long profile crosses the 2‐km‐wide Wildrose graben and the southern, 0.8‐km‐long profile extends onto the Panamint Valley playa, ~7.5&nbsp;km&nbsp;S of Ballarat, CA. The profile across the Wildrose graben reveals a robust, low‐angle reflector interpreted to represent the LANF separating Plio‐Pleistocene alluvial fanglomerate and Proterozoic metasedimentary deposits. High‐angle faults interpreted in the seismic profile correspond to fault scarps on Quaternary alluvial fan surfaces. Interpretation of the reflection data suggests that the high‐angle faults vertically displace the LANF up to 80&nbsp;m within the Wildrose graben. Similarly, the profile south of Ballarat reveals a low‐angle reflector, which appears both rotated and displaced up to 260&nbsp;m by high‐angle faults. These results suggest that near the Panamint range front, the high‐angle faults are the dominant active structures. We conclude that at least at shallow (&lt;1&nbsp;km) depths, the LANF we imaged is not active today.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020243","usgsCitation":"Gold, R.D., Stephenson, W.J., Briggs, R.W., DuRoss, C., Kirby, E., Woolery, E.W., Delano, J., and Odum, J., 2020, Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California: JGR Solid Earth, v. 125, no. 11, e2020JB020243, 18 p., https://doi.org/10.1029/2020JB020243.","productDescription":"e2020JB020243, 18 p.","ipdsId":"IP-122325","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455104,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://cdr.lib.unc.edu/downloads/gb19fg41w","text":"External Repository"},{"id":436762,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YY18PF","text":"USGS data release","linkHelpText":"Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California, 2018"},{"id":382016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Panamint Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.90527343750001,\n              34.95799531086792\n            ],\n            [\n              -116.3671875,\n              34.95799531086792\n            ],\n            [\n              -116.3671875,\n              37.125286284966805\n            ],\n            [\n              -117.90527343750001,\n              37.125286284966805\n            ],\n            [\n              -117.90527343750001,\n              34.95799531086792\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirby, Eric 0000-0002-5701-8688","orcid":"https://orcid.org/0000-0002-5701-8688","contributorId":197171,"corporation":false,"usgs":false,"family":"Kirby","given":"Eric","email":"","affiliations":[],"preferred":false,"id":807819,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woolery, Edward W 0000-0003-3398-5830","orcid":"https://orcid.org/0000-0003-3398-5830","contributorId":192994,"corporation":false,"usgs":false,"family":"Woolery","given":"Edward","email":"","middleInitial":"W","affiliations":[],"preferred":false,"id":807820,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delano, Jaime 0000-0003-2601-2600","orcid":"https://orcid.org/0000-0003-2601-2600","contributorId":225594,"corporation":false,"usgs":false,"family":"Delano","given":"Jaime","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":807821,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Odum, Jackson K. 0000-0003-4697-2430 odum@usgs.gov","orcid":"https://orcid.org/0000-0003-4697-2430","contributorId":1365,"corporation":false,"usgs":true,"family":"Odum","given":"Jackson K.","email":"odum@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807822,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70215231,"text":"70215231 - 2020 - Spatiotemporal pattern of interactions between an apex predator and sympatric species","interactions":[],"lastModifiedDate":"2020-12-14T16:39:26.143997","indexId":"70215231","displayToPublicDate":"2020-10-07T07:04:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7153,"text":"Journal of Mammology","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal pattern of interactions between an apex predator and sympatric species","docAbstract":"<p><span>Increases in apex predator abundance can influence the behavior of sympatric species, particularly when the available habitat and/or resources are limited. We assessed the temporal and spatiotemporal interactions between Florida panthers (</span><i>Puma concolor coryi</i><span>) and six focal sympatric species in South Florida, where Florida panther abundance has increased by more than 6-fold since the 1990’s. Using camera trap data, we quantified species’ diel activity patterns, temporal overlap, and time-to-encounter (i.e., time between consecutive visits of a Florida panther and a focal species and vice versa). The Florida panther and bobcat (</span><i>Lynx rufus</i><span>) displayed a nocturnal activity pattern; the black bear (</span><i>Ursus americanus</i><span>), white-tailed deer (</span><i>Odocoileus virginianus</i><span>), wild boar (</span><i>Sus scrofa</i><span>), and wild turkey (</span><i>Meleagris gallopavo</i><span>) were mostly diurnal; and the raccoon (</span><i>Procyon lotor</i><span>) was cathemeral. Prey species and black bears minimized encounters with Florida panthers by being active during the day and displaying longer time-to-encounter, whereas Florida panthers visited a site after a prey species at higher probabilities than after competitor species, and were more likely to visit an elevated site or upland habitat. Our results suggest that interactions between Florida panthers and sympatric species in our study system are driven by species-specific behavioral responses. Gaining a better understanding of the crucial interactions driving species coexistence is important for a better understanding of the structure and function of ecological communities and help manage the potential expansion of the Florida panther into Central Florida.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyaa071","usgsCitation":"Guitart, M.P., Onorato, D.P., Hines, J.E., and Oli, M.K., 2020, Spatiotemporal pattern of interactions between an apex predator and sympatric species: Journal of Mammology, v. 101, no. 5, p. 1279-1288, https://doi.org/10.1093/jmammal/gyaa071.","productDescription":"10 p.","startPage":"1279","endPage":"1288","ipdsId":"IP-102728","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Central Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.8369140625,\n              26.31311263768267\n            ],\n            [\n              -79.8046875,\n              26.31311263768267\n            ],\n            [\n              -79.8046875,\n              29.611670115197377\n            ],\n            [\n              -82.8369140625,\n              29.611670115197377\n            ],\n            [\n              -82.8369140625,\n              26.31311263768267\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"101","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Guitart, Marta P 0000-0002-2368-1422","orcid":"https://orcid.org/0000-0002-2368-1422","contributorId":242968,"corporation":false,"usgs":false,"family":"Guitart","given":"Marta","email":"","middleInitial":"P","affiliations":[{"id":38084,"text":"Univ. of Florida","active":true,"usgs":false}],"preferred":false,"id":801239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Onorato, David P","contributorId":242969,"corporation":false,"usgs":false,"family":"Onorato","given":"David","email":"","middleInitial":"P","affiliations":[{"id":48592,"text":"Florida Fish & Wildlife Conservation Comm.","active":true,"usgs":false}],"preferred":false,"id":801240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":801241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":801242,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274784,"text":"70274784 - 2020 - Vegetation vs. anoxic controls on degradation of plant litter in a restored wetland","interactions":[],"lastModifiedDate":"2026-04-10T13:38:43.045806","indexId":"70274784","displayToPublicDate":"2020-10-07T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation vs. anoxic controls on degradation of plant litter in a restored wetland","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The ability of wetlands to accrete organic matter in response to rising sea level is a key to landscape resilience, especially in light of reduced sediment availability consequent to dam construction and channelization. This study examined the degradation of cattail (</span><i>Typha</i><span>&nbsp;spp.) and tule (</span><i>Schoenoplectus acutus</i><span>) litters in restored wetlands through the lens of lignin, a major structural biopolymer in vascular plants with degradation characteristics very sensitive to oxic versus anoxic conditions. A series of litterbags were deployed during the first 10 years after flooding of Deep (55 cm) and Shallow (25 cm) restored wetlands. As emergent marsh vegetation spread through the maturing wetlands, anoxic conditions were more prevalent and overall degradation rates of litter in litterbags were lower. In later experiments in the maturing wetlands, lignin was progressively enriched in litter as evidenced by carbon-normalized yields (Λ</span><sub>8</sub><span>) that increased in tule starting materials from 6.3 to 7.1 mg 100 mgOC</span><sup>–1</sup><span>&nbsp;to as high as 9.9 mg 100 mgOC</span><sup>–1</sup><span>, and in cattail starting materials from 5.9 to 7.0 mg 100 mgOC</span><sup>–1</sup><span>&nbsp;to as high as 10.9 mg 100 mgOC</span><sup>–1</sup><span>. However, in an experiment initiated soon after the restored wetlands were constructed, Λ</span><sub>8</sub><span>&nbsp;in tule litter decreased from 6.8 to 3.6 mg 100 mgOC</span><sup>–1</sup><span>, highlighting the prevalence of initial oxic conditions. With the exception of the early oxic conditions for tule, there was an overall trend of decreasing lignin acid-to-aldehyde ratios with litter degradation, which runs counter to most studies in the literature. We hypothesize that this reflects the utilization of more oxygen-rich lignin components as electron acceptors in redox reactions. No consistent differences were observed in degradation patterns between the Shallow and Deep wetlands. There were distinct differences in lignin degradation in cattail (more resistant) versus tule (less resistant), which indicates that although anoxia may be the dominant control on organic matter accretion in wetlands, specific types of vegetation in restored or constructed wetlands affects organic matter preservation, and hence accretion. Thus, selective management of predominant species in wetlands may prove important for the ability of wetlands to maintain emergent vegetation during sea level rise and to preserve the overall stability of wetland soils.</span></span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2020.564603","usgsCitation":"Hernes, P.J., Miller, R.L., Dyda, R.Y., and Bergamaschi, B.A., 2020, Vegetation vs. anoxic controls on degradation of plant litter in a restored wetland: Frontiers in Environmental Science, v. 8, 564603, 11 p., https://doi.org/10.3389/fenvs.2020.564603.","productDescription":"564603, 11 p.","ipdsId":"IP-119215","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":502354,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502494,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2020.564603","text":"Publisher Index Page"}],"country":"United States","state":"California","otherGeospatial":"Twitchell Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.68381283679834,\n              38.12416147877542\n            ],\n            [\n              -121.68755028169036,\n              38.08707073917063\n            ],\n            [\n              -121.67928640312594,\n              38.08780599701319\n            ],\n            [\n              -121.66757273973434,\n              38.09442402508458\n            ],\n            [\n              -121.65265808360306,\n              38.09467806713366\n            ],\n            [\n              -121.63544357092064,\n              38.08904952104504\n            ],\n            [\n              -121.6280522656029,\n              38.09589585522204\n            ],\n            [\n              -121.62668326258334,\n              38.099398949521174\n            ],\n            [\n              -121.61151764873418,\n              38.10516475690591\n            ],\n            [\n              -121.61684341930066,\n              38.11624520495312\n            ],\n            [\n              -121.65443009534332,\n              38.11969426991299\n            ],\n            [\n              -121.66258531326154,\n              38.12254968333488\n            ],\n            [\n              -121.66666292222067,\n              38.12397739004583\n            ],\n            [\n              -121.67074053117977,\n              38.12540509675678\n            ],\n            [\n              -121.68381283679834,\n              38.12416147877542\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Hernes, Peter J. 0000-0001-7908-0936","orcid":"https://orcid.org/0000-0001-7908-0936","contributorId":329589,"corporation":false,"usgs":false,"family":"Hernes","given":"Peter","middleInitial":"J.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":959139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Robin L. 0000-0001-6931-3898","orcid":"https://orcid.org/0000-0001-6931-3898","contributorId":369566,"corporation":false,"usgs":true,"family":"Miller","given":"Robin","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dyda, Rachael Y. 0000-0002-4616-7231","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":369567,"corporation":false,"usgs":false,"family":"Dyda","given":"Rachael","middleInitial":"Y.","affiliations":[{"id":28024,"text":"UCDavis","active":true,"usgs":false}],"preferred":false,"id":959141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959142,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70213240,"text":"sir20205054 - 2020 - Estimating flood magnitude and frequency on streams and rivers in Connecticut, based on data through water year 2015","interactions":[],"lastModifiedDate":"2020-10-06T21:49:41.168644","indexId":"sir20205054","displayToPublicDate":"2020-10-06T16:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5054","displayTitle":"Estimating Flood Magnitude and Frequency on Streams and Rivers in Connecticut, Based on Data Through Water Year 2015","title":"Estimating flood magnitude and frequency on streams and rivers in Connecticut, based on data through water year 2015","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Connecticut Department of Transportation, updated flood-frequency estimates with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively) for 141 streamgages in Connecticut and 11 streamgages in adjacent States using annual peak-flow data through water year 2015. Peak-flow regression equations were derived for estimating flows at ungaged stream sites with annual exceedance probabilities from 50 to 0.2 percent. Methods for estimating prediction intervals for the peak-flow regression equations are presented. The regression equations are applicable for basins in Connecticut with drainage areas ranging from 0.69 to 325 square miles that are not affected by flood-control regulation or flow diversions.</p><p>The flood discharges for select annual exceedance probabilities were estimated following new (2018) national guidelines for flood-frequency analyses. New guidelines have improved statistical methods for flood-frequency analysis including (1) the expected moments algorithm to help describe uncertainty in annual peak flows and to better represent missing and historical record and (2) the generalized multiple Grubbs-Beck test to screen out potentially influential low outliers and to better fit the upper end of the peak-flow distribution. Additionally, a new regional skew (0.37) derived for New England was used in the flood-frequency analysis for the streamgages.</p><p>Annual peak flows were analyzed for trends for four time periods (30, 50, 70, and 90 years) through 2015. Trend results show some statistical evidence of increasing peak flows in each of the time periods analyzed; however, multidecadal climate cycles may be influencing the number and magnitude of the trends. Historical peak-flow trends in and near Connecticut do not offer clear and convincing evidence for incorporating trends into flood-frequency analyses. For this study, the traditional assumption of stationarity is used with no adjustment for trends.</p><p>Generalized least squares regression techniques were used to develop the final set of multivariable regression equations for estimating flood discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities. The standard error of prediction for the regional regression equations ranged from 26.3 to 45.0 percent. The standard error of prediction was slightly smaller in the current study compared to the 2004 study, indicating an improvement in the predictive ability of the equations (6 percent smaller at the 50-percent annual exceedance probability to about 1 percent smaller at the 1-percent annual exceedance probability). Generalized least squares regression techniques also were used to develop a one-variable (drainage-area-only) equation. Drainage-area-only equations can be used as an alternative to the multiexplanatory variable statewide regression equations if decreased accuracy is acceptable.</p><p>The revised statistical procedures and additional streamgage data applied in the current study result in a more accurate representation of peak-flow conditions in Connecticut than was previously available. The regional regression equations will be integrated in the U.S. Geological Survey StreamStats program, which estimates basin and climatic characteristics and streamflow statistics at user-selected ungaged stream sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205054","collaboration":"Prepared in cooperation with the Connecticut Department of Transportation","usgsCitation":"Ahearn, E.A., and Hodgkins, G.A., 2020, Estimating flood magnitude and frequency on streams and rivers in Connecticut, based on data through water year 2015: U.S. Geological Survey Scientific Investigations Report 2020–5054, 42 p., https://doi.org/10.3133/sir20205054.","productDescription":"Report: v, 42 p.; 2 Tables; 2 Data Releases","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108818","costCenters":[{"id":466,"text":"New England Water Science 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2020-5054"},{"id":378383,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5054/sir20205054_table01.xlsx","text":"Table 1","size":"35.3 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Descriptions of U.S. Geological Survey streamgages in Connecticut and adjacent States used in the flood-frequency analysis and regionalization of peaks flows in Connecticut"},{"id":378384,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5054/sir20205054_table01.csv","text":"Table 1","size":"33.5 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Descriptions of U.S. Geological Survey streamgages in Connecticut and adjacent States used in the flood-frequency analysis and regionalization of peaks flows in Connecticut"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of Study Area</li><li>Data Compilation</li><li>Magnitude and Frequency of Flood Discharges at Gaged Sites</li><li>Development of Regional Regression Equations for Estimating Flood Discharges</li><li>Accuracy and Limitations of the Regression Equations</li><li>Prediction Intervals of Regression Equations Estimates</li><li>Drainage-Area Only Regression Equations</li><li>Weighting of Streamgage Statistics and Regression Estimates</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Historical Hurricane Tracks</li><li>Appendix 2. Worksheet for Computing Annual Exceedance Probability Flood Discharges and Percent Prediction Intervals at Ungaged Sites</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-10-06","noUsgsAuthors":false,"publicationDate":"2020-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahearn, Elizabeth A. 0000-0002-5633-2640 eaahearn@usgs.gov","orcid":"https://orcid.org/0000-0002-5633-2640","contributorId":194658,"corporation":false,"usgs":true,"family":"Ahearn","given":"Elizabeth","email":"eaahearn@usgs.gov","middleInitial":"A.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true},{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"preferred":false,"id":798678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":798679,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70214665,"text":"sir20205087 - 2020 - Transmissivity estimated from brief aquifer tests of domestic wells and compared with bedrock lithofacies and position on hillsides in the Appalachian Plateau of New York","interactions":[],"lastModifiedDate":"2020-10-06T21:42:12.920668","indexId":"sir20205087","displayToPublicDate":"2020-10-06T15:30:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5087","displayTitle":"Transmissivity Estimated From Brief Aquifer Tests of Domestic Wells and Compared With Bedrock Lithofacies and Position on Hillsides in the Appalachian Plateau of New York","title":"Transmissivity estimated from brief aquifer tests of domestic wells and compared with bedrock lithofacies and position on hillsides in the Appalachian Plateau of New York","docAbstract":"<p>Procedures for undertaking and analyzing recovery from aquifer tests of 13 to 132 seconds (described in reports cited herein) were applied to 51 domestic drilled wells that penetrated bedrock outside major valleys in the part of the Appalachian Plateau of New York drained by the Susquehanna River. Transmissivities calculated from these tests ranged over three orders of magnitude in both the Catskill-Cattaraugus lithofacies (shales, mudstones, siltstones, medium to coarse sandstones, pebbly sandstones) and the Chemung-Hamilton lithofacies (shales, mudstones, siltstones, fine to medium sandstones). Median transmissivity values were 0.000425 foot squared per second (36.7 feet squared per day) in the Catskill-Cattaraugus lithofacies and 0.00055 foot squared per second (47.5 feet squared per day) in the Chemung-Hamilton lithofacies. The distributions of transmissivity values within the two lithofacies were likewise similar. The range and median values of transmissivity were also nearly the same on lower and midlevel hillsides and were only slightly greater on a few upper hillsides. Transmissivities estimated from such easily arranged and analyzed tests may be appropriate for estimating groundwater flux under the small gradients that prevail under natural conditions, but not under larger drawdowns and steeper gradients near clusters of domestic wells. Four of the 51 wells tested were also pumped for 10 to 32 minutes; analysis by the Theis recovery method yielded transmissivities consistent with the brief tests for 2 wells, but 7 to 9 times smaller for 2 wells.</p><p>Transmissivity values estimated by the PICKINGmodel were not significantly different from values estimated by an automated application of the Picking method (PPC-Recovery) at a probability of 95 percent. Transmissivities calculated by either method from data for time intervals of 120 seconds or less may be of limited practical value because they apply only to a small volume of bedrock close to the pumped well.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205087","usgsCitation":"Randall, A.D., and Mills, A.C., 2020, Transmissivity estimated from brief aquifer tests of domestic wells and compared with bedrock lithofacies and position on hillsides in the Appalachian Plateau of New York: U.S. Geological Survey Scientific Investigations Report 2020–5087, 21 p., https://doi.org/10.3133/sir20205087.","productDescription":"Report: iv, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091051","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":378953,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KLZD9M","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Field Data From Brief Aquifer Tests of Domestic Wells Penetrating Bedrock in the Appalachian Plateau of New York and Best Fits to Theoretical Curves of Aquifer Properties"},{"id":378951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5087/coverthb.jpg"},{"id":378952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5087/sir20205087.pdf","text":"Report","size":"1.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5087"}],"country":"United States","state":"New York","otherGeospatial":"Appalachian Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.2391357421875,\n              42.0125705565935\n            ],\n            [\n              -74.37744140625,\n              42.0125705565935\n            ],\n            [\n              -74.37744140625,\n              43.03677585761058\n            ],\n            [\n              -78.2391357421875,\n              43.03677585761058\n            ],\n            [\n              -78.2391357421875,\n              42.0125705565935\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Lithofacies Distribution in the Devonian Bedrock of the Appalachian Plateau of New York</li><li>Selection of Wells for Testing</li><li>Selection of a Procedure for Analyzing Brief Aquifer Tests of Domestic Wells</li><li>Analysis of 51 Brief Aquifer Tests</li><li>Longer Aquifer Tests of Five Wells</li><li>Comparison of PICKINGmodel to PPC-Recovery</li><li>Test Results Compared With Bedrock Lithofacies</li><li>Test Results Compared With Position on Hillsides</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-10-06","noUsgsAuthors":false,"publicationDate":"2020-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Randall, Allan D. arandall@usgs.gov","contributorId":1168,"corporation":false,"usgs":true,"family":"Randall","given":"Allan","email":"arandall@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":800356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Andrew C.","contributorId":242016,"corporation":false,"usgs":false,"family":"Mills","given":"Andrew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":800357,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215030,"text":"ofr20201110 - 2020 - A clarification on the effects of urbanization on Golden Eagle (Aquila chrysaetos) habitat selection","interactions":[],"lastModifiedDate":"2020-10-06T21:34:36.833735","indexId":"ofr20201110","displayToPublicDate":"2020-10-06T11:38:02","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1110","displayTitle":"A Clarification on the Effects of Urbanization on Golden Eagle (<i>Aquila chrysaetos</i>) Habitat Selection","title":"A clarification on the effects of urbanization on Golden Eagle (Aquila chrysaetos) habitat selection","docAbstract":"<h1>Introduction</h1><p>In 2018, the U.S. Geological Survey (USGS) published an Open-File Report (<a data-mce-href=\"https://doi.org/10.3133/ofr20181067\" href=\"https://doi.org/10.3133/ofr20181067\" target=\"_blank\" rel=\"noopener\">Tracey and others, 2018</a>) presenting a Bayesian habitat selection model for golden eagles (<i>Aquila chrysaetos</i>) in San Diego County, California. The model used telemetry data to examine the effects of urban development, exurban development, and topography (characterized by a topographic position index and a vector ruggedness measure, TPI and VRM respectively) on golden eagle habitat selection probability. Based on figures 3 and 6 of <a data-mce-href=\"https://doi.org/10.3133/ofr20181067\" href=\"https://doi.org/10.3133/ofr20181067\" target=\"_blank\" rel=\"noopener\">Tracey and others (2018)</a>, we received inquiries from cooperators (U.S. Fish and Wildlife Service and California Department of Fish and Wildlife) about how the probability of eagle use declines with decreasing distance to the urban edge. Here, we clarify our results by addressing that question.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201110","collaboration":"Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife Service, Bureau of Land Management, and California Department of Fish and Wildlife","usgsCitation":"Tracey, J.A., Madden, M.C., Bloom, P.H., and Fisher, R.N., 2020, A clarification on the effects of urbanization on Golden Eagle (<i>Aquila chrysaetos</i>) habitat selection: U.S. Geological Survey Open-File Report 2020–1110, 7 p., https://doi.org/10.3133/ofr20201110.","productDescription":"iv, 7 p.","numberOfPages":"7","onlineOnly":"Y","ipdsId":"IP-121710","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":379081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1110/covrthb.jpg"},{"id":379082,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1110/ofr20201110.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":379083,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181067","text":"Open-File Report 2018-1067","linkHelpText":"- Golden eagle (<i>Aquila chrysaetos</i>) habitat selection as a function of land use and terrain, San Diego County, California"}],"contact":"<p><a href=\"https://www.usgs.gov/centers/werc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc/connect\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-10-06","noUsgsAuthors":false,"publicationDate":"2020-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Tracey, Jeff A. 0000-0002-1619-1054 jatracey@usgs.gov","orcid":"https://orcid.org/0000-0002-1619-1054","contributorId":5780,"corporation":false,"usgs":true,"family":"Tracey","given":"Jeff","email":"jatracey@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madden, Melanie C. 0000-0003-4147-7254 mmadden@usgs.gov","orcid":"https://orcid.org/0000-0003-4147-7254","contributorId":229684,"corporation":false,"usgs":true,"family":"Madden","given":"Melanie","email":"mmadden@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bloom, Peter H.","contributorId":242659,"corporation":false,"usgs":true,"family":"Bloom","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800596,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}