{"pageNumber":"244","pageRowStart":"6075","pageSize":"25","recordCount":40783,"records":[{"id":70220277,"text":"70220277 - 2021 - Recruitment dynamics of non-native largemouth bass within the Sacramento-San Joaquin delta","interactions":[],"lastModifiedDate":"2021-05-13T15:24:51.258767","indexId":"70220277","displayToPublicDate":"2020-12-20T07:29:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Recruitment dynamics of non-native largemouth bass within the Sacramento-San Joaquin delta","docAbstract":"
Largemouth bass (LMB; Micropterus salmoides) recruitment is limited by a critical developmental period during early life stages, but this mechanism may be less important within non-native habitats. We conducted boat electrofishing surveys in four tidal lakes of California’s Sacramento–San Joaquin Delta (SSJD) from 2010 to 2011 to describe introduced LMB recruitment dynamics. We evaluated growth, proximate composition, and health indices of young-of-the-year (YOY) LMB among tidal lakes and developed an integrated count model to determine how factors known to affect LMB recruitment shape SSJD population structure. Our results show a mismatch among growth, nutrition, and YOY abundance, where the tidal lake with the most abundant and fastest-growing LMB had the poorest nutritional status. The warm winter water temperatures and lack of a hatching-cohort growth advantage suggests overwinter starvation plays a less important role in SSJD LMB recruitment than in many native LMB habitats. Collectively, our results suggest that habitat characteristics (submerged aquatic vegetation) and not overwinter mortality shapes SSJD LMB population structure, a mechanism consistent with contemporary hypotheses about the altered fish community structure of the SSJD.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0241","usgsCitation":"Huntsman, B., Feyrer, F.V., Young, M.J., Hobbs, J.A., Acuna, S., Kirsch, J.E., Mahardja, B., and Teh, S., 2021, Recruitment dynamics of non-native largemouth bass within the Sacramento-San Joaquin delta: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 5, p. 505-521, https://doi.org/10.1139/cjfas-2020-0241.","productDescription":"17 p.","startPage":"505","endPage":"521","ipdsId":"IP-120365","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":454053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2020-0241","text":"Publisher Index Page"},{"id":385411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.32177734375,\n 37.82280243352756\n ],\n [\n -120.38818359375,\n 37.82280243352756\n ],\n [\n -120.38818359375,\n 39.11301365149975\n ],\n [\n -122.32177734375,\n 39.11301365149975\n ],\n [\n -122.32177734375,\n 37.82280243352756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobbs, James A.","contributorId":171638,"corporation":false,"usgs":false,"family":"Hobbs","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":814981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Acuna, Shawn","contributorId":257756,"corporation":false,"usgs":false,"family":"Acuna","given":"Shawn","email":"","affiliations":[{"id":52106,"text":"Metropolitan Water District of Southern California","active":true,"usgs":false}],"preferred":false,"id":814982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirsch, Joseph E.","contributorId":196891,"corporation":false,"usgs":false,"family":"Kirsch","given":"Joseph","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":814983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mahardja, Brian","contributorId":174645,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":814984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Teh, Swee","contributorId":257757,"corporation":false,"usgs":false,"family":"Teh","given":"Swee","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":814985,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217063,"text":"70217063 - 2021 - Hydrogeomorphological controls on reach‐scale distributions of cichlid nest sites in a small neotropical river","interactions":[],"lastModifiedDate":"2021-03-19T20:21:37.986406","indexId":"70217063","displayToPublicDate":"2020-12-20T06:41:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeomorphological controls on reach‐scale distributions of cichlid nest sites in a small neotropical river","docAbstract":"

The Cichlidae are among the most diversified families of fish in the Neotropics and represent an important component of aquatic biodiversity. Understanding cichlid nest‐site selection is important for assemblages facing uncertain futures due to species invasions and environmental change. This information could be used to predict how inter‐ and intraspecific competition for reproductive space may affect populations with changing community dynamics or to identify areas as targets for conservation. We investigated which hydrogeomorphological factors correlated to preferred nest sites of four native cichlid species in the Bladen River, Belize. We recorded the locations of nest sites and collected habitat data through the study reach, including flow velocity, depth, sediment type, fish cover type richness and distance to the bank. Nest locations and physical habitat data were used to construct spatially explicit habitat models using boosted regression trees (BRTs). The models provided statistically significant evidence that physical habitat variables influence the distribution of the nest sites. We found that all species except Archocentrus spilurus were associated with substrate, specifically sand. Thorichthys meeki was also associated with lower water velocities, whereas Cichlasoma salvini was influenced by all five variables. Vieja maculicauda and Archocentrus spilurus were both influenced by flow velocity, distance to bank and depth, although A. spilurus preferred deeper, slightly faster locations about the same distance to the bank. This study suggests that the spatial distribution of nest sites within this cichlid community is significantly different than random and is at least partially governed by physical controls.

","language":"English","publisher":"Wiley","doi":"10.1111/eff.12580","usgsCitation":"Buege, E.A., Esselman, P., and Praskievicz, S.J., 2021, Hydrogeomorphological controls on reach‐scale distributions of cichlid nest sites in a small neotropical river: Ecology of Freshwater Fish, v. 30, no. 2, p. 244-255, https://doi.org/10.1111/eff.12580.","productDescription":"12 p.","startPage":"244","endPage":"255","ipdsId":"IP-121602","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","otherGeospatial":"Monkey River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.132080078125,\n 16.251593732779515\n ],\n [\n -88.35205078124999,\n 16.251593732779515\n ],\n [\n -88.35205078124999,\n 17.13554114256562\n ],\n [\n -89.132080078125,\n 17.13554114256562\n ],\n [\n -89.132080078125,\n 16.251593732779515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Buege, Emily A. 0000-0002-9141-529X","orcid":"https://orcid.org/0000-0002-9141-529X","contributorId":245987,"corporation":false,"usgs":false,"family":"Buege","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":807454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Praskievicz, Sarah J. 0000-0002-9380-7625","orcid":"https://orcid.org/0000-0002-9380-7625","contributorId":245989,"corporation":false,"usgs":false,"family":"Praskievicz","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":49396,"text":"University of North Carolina-Greensboro","active":true,"usgs":false}],"preferred":false,"id":807456,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217066,"text":"70217066 - 2021 - Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina","interactions":[],"lastModifiedDate":"2021-06-30T17:41:53.333707","indexId":"70217066","displayToPublicDate":"2020-12-20T06:35:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina","docAbstract":"

Following centuries of declines, there is growing interest in conserving extant wild populations and reintroducing Brook Trout (Salvelinus fontinalis) populations of native ancestry. A population genetic baseline can enhance conservation outcomes and promote restoration success. Consequently, it is important to document existing patterns of genetic variation across the landscape and translate these data into an approachable format for fisheries managers. We genotyped 9,507 Brook Trout representing 467 wild collections at 12 microsatellite loci to establish a genetic baseline for North Carolina, USA. Rarefied allelic richness and observed heterozygosity, which reflect within‐population diversity, were low to moderate relative to levels typically observed at higher latitudes (means = 3.12 and 0.42, respectively). Effective population sizes varied widely, but were often very low (151 collections with an estimated Ne < 10). Despite decades of intensive stocking across the state, we found little to no evidence of hatchery introgression in most populations. Although genetic variation was significant at a variety of spatial scales (mean pairwise F’ST = 0.73), substantial genetic variation occurred between patches within individual watersheds. Analysis of molecular variance (AMOVA) found that a substantial portion (28.5%) of the observed genetic variation was attributed to differences among populations, with additional genetic variation among hydrological units (HUCs; 16.0%, 16.6%, 12.1%, and 9.4% of the overall variation among twelve‐, ten‐, eight‐, and six‐digit HUCs, respectively). We discuss a suite of potential applications for this type of genetic data to enhance management outcomes, such as conservation prioritization and selection of source stocks for reintroductions or genetic rescue.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10569","usgsCitation":"Kazyak, D., Lubinski, B.A., Rash, J.M., Johnson, T.C., and King, T.L., 2021, Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina: North American Journal of Fisheries Management, v. 41, no. 3, p. 626-638, https://doi.org/10.1002/nafm.10569.","productDescription":"13 p.","startPage":"626","endPage":"638","ipdsId":"IP-101589","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":381793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.860595703125,\n 36.53612263184686\n ],\n [\n -81.7822265625,\n 36.63316209558658\n ],\n [\n -83.84765625,\n 35.460669951495305\n ],\n [\n -84.375,\n 35.02999636902566\n ],\n [\n -81.03515625,\n 35.28150065789119\n ],\n [\n -80.7275390625,\n 34.813803317113155\n ],\n [\n -79.4970703125,\n 34.813803317113155\n ],\n [\n -78.44238281249999,\n 33.797408767572485\n ],\n [\n -76.2451171875,\n 34.994003757575776\n ],\n [\n -75.7177734375,\n 35.817813158696616\n ],\n [\n -75.860595703125,\n 36.53612263184686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":807465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":807466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rash, Jacob M","contributorId":218128,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","email":"","middleInitial":"M","affiliations":[{"id":39760,"text":"Division of Inland Fisheries, North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":807467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Thomas C","contributorId":245999,"corporation":false,"usgs":false,"family":"Johnson","given":"Thomas","email":"","middleInitial":"C","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":807468,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Timothy L.","contributorId":199023,"corporation":false,"usgs":false,"family":"King","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":807469,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229090,"text":"70229090 - 2021 - Effects of increased temperature on arctic slimy sculpin Cottus cognatus is mediated by food availability: Implications for climate change","interactions":[],"lastModifiedDate":"2022-02-28T14:36:00.422518","indexId":"70229090","displayToPublicDate":"2020-12-19T08:27:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of increased temperature on arctic slimy sculpin Cottus cognatus is mediated by food availability: Implications for climate change","title":"Effects of increased temperature on arctic slimy sculpin Cottus cognatus is mediated by food availability: Implications for climate change","docAbstract":"
  1. Lakes are vulnerable to climate change, and warming rates in the Arctic are faster than anywhere on Earth. Fishes are sensitive to changing temperatures, which directly control physiological processes. Food availability should partly dictate responses to climate change because energetic demands change with temperature, but few studies have simultaneously examined temperature and food availability.
  2. We used a fully factorial experiment to test effects of food availability and temperature (7.6, 12.7, and 17.4°C; 50 days) on growth, consumption, respiration, and excretion, and effects of temperature (12 and 19.3°C; 27 days) on habitat use and growth of a common, but understudied, mid-level consumer, slimy sculpin Cottus cognatus, in arctic lakes. We also used bioenergetics modelling to predict consumptive demand under future warming scenarios.
  3. Growth rates were 3.4× higher at 12.7°C in high food compared to low food treatments, but the magnitude of differences depended on temperature. Within low food treatments, there was no statistical difference in growth rates among temperatures, suggesting food limitation. Consumption, respiration, and nitrogen excretion increased with temperature independent of food availability. Lower growth rates coincided with lower phosphorus excretion at the highest temperature, suggesting that fish selectively retained phosphorus at high temperatures and low food. In habitat choice experiments, fish were more likely to use the 12°C side of the tank, closely matching their optimal temperature. We predicted a 9% increase in consumption is required to maintain observed growth under a 4°C warming scenario.
  4. These results highlight considering changes in food resources and other associated indirect effects (e.g. excretion) that accompany changing temperatures with climate change. Depending on how food webs respond to warming, fish may cope with predicted warming if density-dependent feedback maintains population sizes.
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13659","usgsCitation":"Pennock, C., Budy, P., Atkinson, C., and Barrett, N., 2021, Effects of increased temperature on arctic slimy sculpin Cottus cognatus is mediated by food availability: Implications for climate change: Freshwater Biology, v. 66, no. 3, p. 549-561, https://doi.org/10.1111/fwb.13659.","productDescription":"13 p.","startPage":"549","endPage":"561","ipdsId":"IP-121940","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Toolik Field Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.05401611328125,\n 68.32220458597388\n ],\n [\n -149.14764404296875,\n 68.32220458597388\n ],\n [\n -149.14764404296875,\n 68.67354240601256\n ],\n [\n -150.05401611328125,\n 68.67354240601256\n ],\n [\n -150.05401611328125,\n 68.32220458597388\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":836452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Carla","contributorId":287046,"corporation":false,"usgs":false,"family":"Atkinson","given":"Carla","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":836453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrett, Nick","contributorId":287048,"corporation":false,"usgs":false,"family":"Barrett","given":"Nick","email":"","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":836454,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215497,"text":"70215497 - 2021 - Strategic habitat conservation for beach mice: Estimating management scenario efficiencies","interactions":[],"lastModifiedDate":"2023-07-07T14:12:25.874819","indexId":"70215497","displayToPublicDate":"2020-12-18T13:23:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Strategic habitat conservation for beach mice: Estimating management scenario efficiencies","docAbstract":"

The Perdido Key beach mouse (Peromyscus polionotus trissyllepsis), Choctawhatchee beach mouse (P. p. allophrys), and St. Andrew beach mouse (P. p. peninsularis) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well‐targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30‐m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post‐storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km2 of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21983","usgsCitation":"Cronin, J.P., Tirpak, B., Dale, L.L., Robenski, V.L., Tirpak, J.M., and Marcot, B.G., 2021, Strategic habitat conservation for beach mice: Estimating management scenario efficiencies: Journal of Wildlife Management, v. 85, no. 2, p. 324-339, https://doi.org/10.1002/jwmg.21983.","productDescription":"16 p.; Data Release","startPage":"324","endPage":"339","ipdsId":"IP-113555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":382514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418750,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OWRTW8","text":"Data for Beach Mice Bayesian Network Model","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.2861328125,\n 29.76437737516313\n ],\n [\n -83.408203125,\n 29.76437737516313\n ],\n [\n -83.408203125,\n 30.939924331023445\n ],\n [\n -88.2861328125,\n 30.939924331023445\n ],\n [\n -88.2861328125,\n 29.76437737516313\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":802499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tirpak, Blair 0000-0002-2679-8378","orcid":"https://orcid.org/0000-0002-2679-8378","contributorId":206275,"corporation":false,"usgs":true,"family":"Tirpak","given":"Blair","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":802500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dale, Leah L. 0000-0002-3480-9954","orcid":"https://orcid.org/0000-0002-3480-9954","contributorId":243547,"corporation":false,"usgs":false,"family":"Dale","given":"Leah","middleInitial":"L.","affiliations":[{"id":48726,"text":"Cherokee Nations Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":802501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robenski, Virginia L.","contributorId":243548,"corporation":false,"usgs":false,"family":"Robenski","given":"Virginia","middleInitial":"L.","affiliations":[{"id":48726,"text":"Cherokee Nations Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":802502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tirpak, John M.","contributorId":191024,"corporation":false,"usgs":false,"family":"Tirpak","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":34307,"text":"U.S. Fish and Wildlife Service, Lafayette, LA, USA","active":true,"usgs":false}],"preferred":false,"id":802503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marcot, Bruce G.","contributorId":152612,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":802504,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217059,"text":"70217059 - 2021 - Evidence for continental-scale dispersal of antimicrobial resistant bacteria by landfill-foraging gulls","interactions":[],"lastModifiedDate":"2020-12-31T12:57:39.015312","indexId":"70217059","displayToPublicDate":"2020-12-18T06:56:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Evidence for continental-scale dispersal of antimicrobial resistant bacteria by landfill-foraging gulls","docAbstract":"

Anthropogenic inputs into the environment may serve as sources of antimicrobial resistant bacteria and alter the ecology and population dynamics of synanthropic wild animals by providing supplemental forage. In this study, we used a combination of phenotypic and genomic approaches to characterize antimicrobial resistant indicator bacteria, animal telemetry to describe host movement patterns, and a novel modeling approach to combine information from these diverse data streams to investigate the acquisition and long-distance dispersal of antimicrobial resistant bacteria by landfill-foraging gulls. Our results provide evidence that gulls acquire antimicrobial resistant bacteria from anthropogenic sources, which they may subsequently disperse across and between continents via migratory movements. Furthermore, we introduce a flexible modeling framework to estimate the relative dispersal risk of antimicrobial resistant bacteria in western North America and adjacent areas within East Asia, which may be adapted to provide information on the risk of dissemination of other organisms and pathogens maintained by wildlife through space and time.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.144551","usgsCitation":"Ahlstrom, C., van Toor, M.L., Woksepp, H., Chandler, J.C., Reed, J., Reeves, A.B., Waldenström, J., Franklin, A.B., Douglas, D.C., Bonnedahl, J., and Ramey, A.M., 2021, Evidence for continental-scale dispersal of antimicrobial resistant bacteria by landfill-foraging gulls, v. 764, 144551, 10 p., https://doi.org/10.1016/j.scitotenv.2020.144551.","productDescription":"144551, 10 p.","ipdsId":"IP-118432","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":454059,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.unl.edu/icwdm_usdanwrc/2401","text":"Publisher Index Page"},{"id":436609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U0XGI3","text":"USGS data release","linkHelpText":"Data for Continental-Scale Dispersal of Antimicrobial Resistant Bacteria by Alaska Landfill-Foraging Gulls"},{"id":381796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"764","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":807441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Toor, Marielle L.","contributorId":205670,"corporation":false,"usgs":false,"family":"van Toor","given":"Marielle","email":"","middleInitial":"L.","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for 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B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":807448,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":807449,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":807450,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":807451,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70217163,"text":"70217163 - 2021 - Characterizing physical properties of streambed interface sediments using in situ complex electrical conductivity measurements","interactions":[],"lastModifiedDate":"2021-02-17T21:51:47.504261","indexId":"70217163","displayToPublicDate":"2020-12-17T08:11:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing physical properties of streambed interface sediments using in situ complex electrical conductivity measurements","docAbstract":"

Streambed sediment physical properties such as surface area, are difficult to quantify in situ but exert a high‐level control on a wide range of biogeochemical processes and sorption of contaminants. We introduce the use of complex electrical conductivity (CC) methods (also known as spectral induced polarization (SIP)) that measure both real and imaginary conductivity to non‐invasively and efficiently characterize shallow streambed sediments. We explore the method through synthetic modeling, laboratory, and field measurements to demonstrate the sensitivity of imaginary conductivity to sediment surface area, controlled in part by fine‐grained iron oxides produced by anoxic groundwater discharge. Laboratory measurements verify expected relationships between CC parameters and sediment properties. Synthetic modeling using a 1D analytical model illustrates the influence of water layer depth and conductivity on the field CC measurements made at the streambed‐stream water interface. Specifically, the inverted sediment imaginary conductivity is less impacted by uncertainty in the water layer depth and conductivity relative to the real conductivity and phase shift. Field CC measurements along a landfill‐impacted river reveal discrete streambed zones with enhanced bulk surface area generally corresponding to anoxic groundwater discharges zones with high concentrations of fine‐grained iron oxide precipitates.

","language":"English","publisher":"Wiley","doi":"10.1029/2020WR027995","usgsCitation":"Wang, C., Briggs, M.A., Day-Lewis, F., and Slater, L., 2021, Characterizing physical properties of streambed interface sediments using in situ complex electrical conductivity measurements: Water Resources Research, v. 57, no. 21, ee2020WR027995, https://doi.org/10.1029/2020WR027995.","productDescription":"ee2020WR027995","ipdsId":"IP-123328","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1786827","text":"Publisher Index Page"},{"id":382018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Cheng-Hui 0000-0001-9508-7425","orcid":"https://orcid.org/0000-0001-9508-7425","contributorId":194062,"corporation":false,"usgs":false,"family":"Wang","given":"Cheng-Hui","email":"","affiliations":[],"preferred":false,"id":807796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":807798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slater, L. 0000-0003-0292-746X","orcid":"https://orcid.org/0000-0003-0292-746X","contributorId":247506,"corporation":false,"usgs":false,"family":"Slater","given":"L.","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":807799,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217104,"text":"70217104 - 2021 - Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California","interactions":[],"lastModifiedDate":"2021-02-17T22:15:32.622555","indexId":"70217104","displayToPublicDate":"2020-12-17T07:12:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California","docAbstract":"

A new quantitative mineral resource assessment for tungsten, a critical mineral commodity with highly concentrated production and a moderate risk of global supply disruption, was conducted for the Great Basin region of western Nevada and eastern California. This assessment was part of a larger effort focusing on three regions in the United States and represents the first study of domestic tungsten resources and mineral potential in over twenty years. By integrating geology, bedrock and stream sediment geochemistry, geophysics, and remote sensing data with recently developed software tools and analyses, estimates of undiscovered tungsten skarn deposits in permissive tracts are combined with grade and tonnage distributions of known deposits to generate probabilistic estimates of undiscovered resources. Identified resources in the Great Basin region total 168 thousand metric tons (kt) of tungsten trioxide (WO3), including 116 kt of past production and 52 kt remaining in place. Consistent with the historic significance of the Great Basin region as a past producer containing a large portion of U.S. identified resources, undiscovered resources are likely to occur adjacent to known deposits and prospects and at unexplored depths. Undiscovered deposits are estimated to contain median resources of 940 kt of WO3 with a 90% probability of at least 420 kt and a 10% probability of at least 1.7 million metric tons (Mt), of which 240 kt to 1.1 Mt may be economic to extract. Based on a 20-year average price, median recoverable undiscovered resources are estimated at 570 kt WO3 equivalent with a net present value of $3 billion U.S. dollars. The methods, data, results, and economic significance of the assessment contribute to a scientific understanding of a critical mineral resource with direct implications for policy and land management decisions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2020.106712","usgsCitation":"Lederer, G.W., Solano, F., Coyan, J.A., Denton, K., Watts, K., Mercer, C.N., Bickerstaff, D., and Granitto, M., 2021, Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California: Journal of Geochemical Exploration, v. 223, 106712, 24 p., https://doi.org/10.1016/j.gexplo.2020.106712.","productDescription":"106712, 24 p.","ipdsId":"IP-119992","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488120,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gexplo.2020.106712","text":"Publisher Index Page"},{"id":436615,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D1KQGR","text":"USGS data release","linkHelpText":"Tungsten skarn mineral resource assessment of the Great Basin region 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E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":807623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":807624,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bickerstaff, Damon 0000-0003-0887-9761","orcid":"https://orcid.org/0000-0003-0887-9761","contributorId":201974,"corporation":false,"usgs":true,"family":"Bickerstaff","given":"Damon","email":"","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science 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future","interactions":[],"lastModifiedDate":"2021-02-12T13:08:41.150759","indexId":"70218028","displayToPublicDate":"2020-12-17T07:04:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5567,"text":"Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"Upper Colorado River Basin 20th century droughts under 21st century warming: Plausible scenarios for the future","docAbstract":"

This study builds on a collaboration with a water resource management community of practice in the Upper Colorado River Basin to develop scenarios of future drought and assess impacts on water supply reliability. Water managers are concerned with the impacts of warming on water year streamflow, but uncertainties in projections of climate make the application of these projections to planning a challenge. Instead, water managers considered a plausible scenario for future drought to be historical droughts to which warming is added. We used a simple statistical model of water year streamflow with temperatures increased by 1 °C to 4 °C, and then examined reductions in flow and runoff efficiency (RE) with each degree of warming for the six droughts defined in the observed streamflow record. In order to place these results into a management context, we employed an existing framework for system reliability, and in particular, a vulnerability assessment for water delivery metrics. Using modeled streamflow resulting from 1 °C to 4 °C warming, we found vulnerable condition thresholds for the two water delivery metrics assessed, Upper Basin Shortage and Lees Ferry Deficit, were crossed relatively infrequently at +1 °C, but with a substantially increased frequency under additional warming. Results are more relevant to resource management because the impacts of warming on Upper Colorado River streamflow were assessed in the context of management metrics and vulnerability thresholds, in collaboration with members of the water management community of practice.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.cliser.2020.100206","usgsCitation":"Woodhouse, C.A., Smith, R.M., McAfee, S., Pederson, G.T., McCabe, G.J., Miller, W.P., and Csank, A., 2021, Upper Colorado River Basin 20th century droughts under 21st century warming: Plausible scenarios for the future: Climate Services, v. 21, 100206, 11 p., https://doi.org/10.1016/j.cliser.2020.100206.","productDescription":"100206, 11 p.","ipdsId":"IP-118594","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cliser.2020.100206","text":"Publisher Index Page"},{"id":383249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming, Utah, Colorado, New Mexico, Arizona","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 44.731125592643274\n ],\n [\n -111.1376953125,\n 42.114523952464246\n ],\n [\n -112.78564453124999,\n 41.902277040963696\n ],\n [\n -112.6318359375,\n 38.03078569382294\n ],\n [\n -111.9287109375,\n 36.756490329505176\n ],\n [\n -110.1708984375,\n 35.8356283888737\n ],\n [\n -106.63330078125,\n 35.55010533588552\n ],\n [\n -106.787109375,\n 35.88905007936091\n ],\n [\n -104.83154296875,\n 38.77121637244273\n ],\n [\n -104.96337890625,\n 40.93011520598305\n ],\n [\n -111.0498046875,\n 44.731125592643274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":810260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Rebecca M.","contributorId":250719,"corporation":false,"usgs":false,"family":"Smith","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":810261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":810262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":810264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, W. Paul","contributorId":250720,"corporation":false,"usgs":false,"family":"Miller","given":"W.","email":"","middleInitial":"Paul","affiliations":[{"id":50235,"text":"NOAA Colorado River Forecast Center","active":true,"usgs":false}],"preferred":false,"id":810265,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Csank, Adam","contributorId":191067,"corporation":false,"usgs":false,"family":"Csank","given":"Adam","email":"","affiliations":[],"preferred":false,"id":810266,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230052,"text":"70230052 - 2021 - Evidence of post-breeding prospecting in a long-distance migrant.","interactions":[],"lastModifiedDate":"2022-03-28T13:59:59.515137","indexId":"70230052","displayToPublicDate":"2020-12-16T08:52:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of post-breeding prospecting in a long-distance migrant.","docAbstract":"
  1. Organisms assess biotic and abiotic cues at multiple sites when deciding where to settle. However, due to temporal constraints on this prospecting, the suitability of available habitat may be difficult for an individual to assess when cues are most reliable, or at the time they are making settlement decisions. For migratory birds, the postbreeding season may be the optimal time to prospect and inform settlement decisions for future breeding seasons.
  2. We investigated the fall movements of flammulated owls (Psiloscops flammeolus) within breeding habitat after fledglings had gained independence and before adults left for migration. From 2013 to 2016, we trapped owls within a breeding population wherein all nesting owls and their young have been banded since 1981. We used stable isotopes in combination with mark–recapture data to identify local individuals and differentiate potential prospecting behavior from other seasonal movements such as migration or staging.
  3. We commonly captured owls in the fall—predominantly hatch-year owls—that were not known residents of the study area. Several of these nonresident owls were later found breeding within the study area. Stable isotope data suggested a local origin for virtually all owls captured during the fall.
  4. Our results suggest that hatch-year flammulated owls, but also some after-hatch-year owls, use the period between the breeding season and fall migration to prospect for future breeding sites. The timing of this behavior is likely driven by seasonally variable costs associated with prospecting.
  5. Determining the timing of prospecting and the specific cues that are being assessed will be important in helping predict the extent to which climate change and/or altered disturbance regimes will modify the ecology, behavior, and demographics associated with prospecting.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7085","usgsCitation":"Ciaglo, M., Calhoun, R., Yanco, S.W., Wunder, M., Stricker, C.A., and Linkhart, B.D., 2021, Evidence of post-breeding prospecting in a long-distance migrant.: Ecology and Evolution, v. 11, p. 599-611, https://doi.org/10.1002/ece3.7085.","productDescription":"13 p.","startPage":"599","endPage":"611","ipdsId":"IP-119113","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7085","text":"Publisher Index Page"},{"id":397699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Pike National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.3,\n 39.150\n ],\n [\n -105,\n 39.150\n ],\n [\n -105,\n 39\n ],\n [\n -105.3,\n 39\n ],\n [\n -105.3,\n 39.150\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ciaglo, Max","contributorId":289314,"corporation":false,"usgs":false,"family":"Ciaglo","given":"Max","email":"","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":838903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Ross","contributorId":289315,"corporation":false,"usgs":false,"family":"Calhoun","given":"Ross","email":"","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":838904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yanco, Scott W","contributorId":289316,"corporation":false,"usgs":false,"family":"Yanco","given":"Scott","email":"","middleInitial":"W","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":838905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":838906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":838907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linkhart, Brian D","contributorId":289318,"corporation":false,"usgs":false,"family":"Linkhart","given":"Brian","email":"","middleInitial":"D","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":838908,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217283,"text":"70217283 - 2021 - Effects of postfire climate and seed availability on postfire conifer regeneration","interactions":[],"lastModifiedDate":"2021-04-08T14:32:59.021108","indexId":"70217283","displayToPublicDate":"2020-12-16T08:08:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of postfire climate and seed availability on postfire conifer regeneration","docAbstract":"

Large, severe fires are becoming more frequent in many forest types across the western United States and have resulted in tree mortality across tens of thousands of hectares. Conifer regeneration in these areas is limited because seeds must travel long distances to reach the interior of large burned patches and establishment is jeopardized by increasingly hot and dry conditions. To better inform postfire management in low elevation forests of California, USA, we collected 5‐year postfire recovery data from 1,234 study plots in 19 wildfires that burned from 2004–2012 and 18 years of seed production data from 216 seed fall traps (1999–2017). We used this data in conjunction with spatially extensive estimates of climate, topography, forest composition, and burn severity to construct taxon‐specific, spatially explicit models of conifer regeneration that incorporate estimated climate conditions and seed availability during postfire recovery windows. We found that after accounting for other predictors both postfire and historical precipitation were strong predictors of regeneration, suggesting that both direct effects of postfire moisture conditions and biological inertia from historical climate may play a role in regeneration. Alternatively, postfire regeneration may simply be driven by postfire climate and apparent relationships with historical climate could be spurious. The estimated sensitivity of regeneration to postfire seed availability was strongest in firs and all conifers combined and weaker in pines. Seed production exhibited high temporal variability with seed production varying by over two orders of magnitude among years. Our models indicate that during droughts postfire conifer regeneration declines most substantially in low‐to‐moderate elevation forests. These findings enhance our mechanistic understanding of forecasted and historically documented shifts in the distribution of trees.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2280","usgsCitation":"Stewart, J.A., van Mantgem, P., Young, D., Shive, K.L., Preisler, H.K., Das, A., Stephenson, N.L., Keeley, J., Safford, H.D., Wright, M., Welch, K.R., and Thorne, J.H., 2021, Effects of postfire climate and seed availability on postfire conifer regeneration: Ecological Applications, v. 31, no. 3, e02280, 14 p., https://doi.org/10.1002/eap.2280.","productDescription":"e02280, 14 p.","ipdsId":"IP-121920","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CCBJ6M","text":"USGS data release","linkHelpText":"poscrptR"},{"id":436620,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CCBJ6M","text":"USGS data release","linkHelpText":"poscrptR"},{"id":436619,"rank":0,"type":{"id":30,"text":"Data 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N","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":808269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shive, Kristen L.","contributorId":194877,"corporation":false,"usgs":false,"family":"Shive","given":"Kristen","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preisler, Haiganoush K.","contributorId":149862,"corporation":false,"usgs":false,"family":"Preisler","given":"Haiganoush","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":808271,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808272,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808273,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808274,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Safford, Hugh D.","contributorId":229058,"corporation":false,"usgs":false,"family":"Safford","given":"Hugh","email":"","middleInitial":"D.","affiliations":[{"id":41570,"text":"Department of Environmental Science and Policy, University of California, Davis, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":808275,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wright, Micah C. 0000-0002-5324-1110","orcid":"https://orcid.org/0000-0002-5324-1110","contributorId":229071,"corporation":false,"usgs":true,"family":"Wright","given":"Micah","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808276,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Welch, Kevin R","contributorId":247753,"corporation":false,"usgs":false,"family":"Welch","given":"Kevin","email":"","middleInitial":"R","affiliations":[{"id":49640,"text":"Calfire","active":true,"usgs":false}],"preferred":false,"id":808277,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Thorne, James H.","contributorId":139144,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":12659,"text":"U C Davis","active":true,"usgs":false}],"preferred":false,"id":808278,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70222574,"text":"70222574 - 2021 - Numerical simulations of the geospace response to the arrival of an idealized perfect interplanetary coronal mass ejection","interactions":[],"lastModifiedDate":"2021-08-05T12:44:43.270977","indexId":"70222574","displayToPublicDate":"2020-12-16T07:38:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulations of the geospace response to the arrival of an idealized perfect interplanetary coronal mass ejection","docAbstract":"

Previously, Tsurutani and Lakhina (2014, https://doi.org/10.1002/2013GL058825) created estimates for a “perfect” interplanetary coronal mass ejection and performed simple calculations for the response of geospace, including \"urn:x-wiley:15427390:media:swe21087:swe21087-math-0001\". In this study, these estimates are used to drive a coupled magnetohydrodynamic-ring current-ionosphere model of geospace to obtain more physically accurate estimates of the geospace response to such an event. The sudden impulse phase is examined and compared to the estimations of Tsurutani and Lakhina (2014, https://doi.org/10.1002/2013GL058825). The physics-based simulation yields similar estimates for Dst rise, magnetopause compression, and equatorial \"urn:x-wiley:15427390:media:swe21087:swe21087-math-0002\" values as the previous study. However, results diverge away from the equator. \"urn:x-wiley:15427390:media:swe21087:swe21087-math-0003\" values in excess of 30 nT/s are found as low as \"urn:x-wiley:15427390:media:swe21087:swe21087-math-0004\" magnetic latitude. Under southward interplanetary magnetic field conditions, magnetopause erosion combines with strong region one Birkeland currents to intensify the \"urn:x-wiley:15427390:media:swe21087:swe21087-math-0005\" response. Values obtained here surpass those found in historically recorded events and set the upper threshold of extreme geomagnetically induced current activity at Earth.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020SW002489","usgsCitation":"Welling, D.T., Love, J.J., Rigler, E.J., Oliveira, D.M., Komar, C.M., and Morley, S., 2021, Numerical simulations of the geospace response to the arrival of an idealized perfect interplanetary coronal mass ejection: Space Weather, v. 19, no. 2, e2020SW002489, 15 p., https://doi.org/10.1029/2020SW002489.","productDescription":"e2020SW002489, 15 p.","ipdsId":"IP-120102","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":454073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020sw002489","text":"Publisher Index Page"},{"id":387708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Welling, Daniel T. 0000-0002-0590-1022","orcid":"https://orcid.org/0000-0002-0590-1022","contributorId":261765,"corporation":false,"usgs":false,"family":"Welling","given":"Daniel","email":"","middleInitial":"T.","affiliations":[{"id":53003,"text":"University of Texas at Arlington Department of Physics, Arlington, Texas, United States","active":true,"usgs":false}],"preferred":false,"id":820609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliveira, Denny M.","contributorId":261766,"corporation":false,"usgs":false,"family":"Oliveira","given":"Denny","email":"","middleInitial":"M.","affiliations":[{"id":53004,"text":"Goddard Planetary Heliophysics Institute, University of Maryland, Baltimore County, Baltimore, MD, USA; NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":820612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Komar, Colin M. 0000-0001-5850-7507","orcid":"https://orcid.org/0000-0001-5850-7507","contributorId":261767,"corporation":false,"usgs":false,"family":"Komar","given":"Colin","email":"","middleInitial":"M.","affiliations":[{"id":53007,"text":"NASA Goddard Space Flight Center, Greenbelt, MD, USA; The Catholic University of America, Washington DC, USA","active":true,"usgs":false}],"preferred":false,"id":820613,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morley, Steven 0000-0001-8520-0199","orcid":"https://orcid.org/0000-0001-8520-0199","contributorId":220242,"corporation":false,"usgs":false,"family":"Morley","given":"Steven","email":"","affiliations":[],"preferred":false,"id":820631,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222950,"text":"70222950 - 2021 - Revisiting California’s past great earthquakes and long-term earthquake rate","interactions":[],"lastModifiedDate":"2021-08-10T13:55:41.089339","indexId":"70222950","displayToPublicDate":"2020-12-15T08:47:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Revisiting California’s past great earthquakes and long-term earthquake rate","docAbstract":"

In this study, we revisit the three largest historical earthquakes in California—the 1857 Fort Tejon, 1872 Owens Valley, and 1906 San Francisco earthquakes—to review their published moment magnitudes, and compare their estimated shaking distributions with predictions using modern ground‐motion models (GMMs) and ground‐motion intensity conversion equations. Currently accepted moment magnitude estimates for the three earthquakes are 7.9, 7.6, and 7.8, respectively. We first consider the extent to which the intensity distributions of all three earthquakes are consistent with a moment magnitude toward the upper end of the estimated range. We then apply a GMM‐based method to estimate the magnitudes of large historical earthquakes. The intensity distribution of the 1857 earthquake is too sparse to provide a strong constraint on magnitude. For the 1872 earthquake, consideration of all available constraints suggests that it was a high stress‐drop event, with a magnitude on the higher end of the range implied by scaling relationships, that is, higher than moment magnitude 7.6. For the 1906 earthquake, based on our analysis of regional intensities and the detailed intensity distribution in San Francisco, along with other available constraints, we estimate a preferred moment magnitude of 7.9, consistent with the published estimate based on geodetic and instrumental seismic data. These results suggest that, although there can be a tendency for historical earthquake magnitudes to be overestimated, the accepted catalog magnitudes of California’s largest historical earthquakes could be too low. Given the uncertainties of the magnitude estimates, the seismic moment release rate between 1850 and 2019 could have been either higher or lower than the average over millennial time scales. It is further not possible to reject the hypothesis that California seismicity is described by an untruncated Gutenberg–Richter distribution with a b\">b‐value of 1.0 for moment magnitudes up to 8.0.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200253","usgsCitation":"Hough, S.E., Page, M.T., Salditch, L., Gallahue, M.M., Lucas, M.C., Neely, J.S., and Stein, S., 2021, Revisiting California’s past great earthquakes and long-term earthquake rate: Bulletin of the Seismological Society of America, v. 111, no. 1, p. 356-370, https://doi.org/10.1785/0120200253.","productDescription":"15 p.","startPage":"356","endPage":"370","ipdsId":"IP-119089","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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University","active":true,"usgs":false}],"preferred":false,"id":820883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":820884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":820885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216935,"text":"70216935 - 2021 - Modeling areal measures of campsite impacts on the Appalachian National Scenic Trail to enhance ecological sustainability","interactions":[],"lastModifiedDate":"2020-12-17T14:27:20.177567","indexId":"70216935","displayToPublicDate":"2020-12-15T08:24:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling areal measures of campsite impacts on the Appalachian National Scenic Trail to enhance ecological sustainability","docAbstract":"

Campsite impacts in protected natural areas are most effectively minimized by a containment strategy that focuses use on a limited number of sustainable campsites that spatially concentrate camping activities. This research employs spatial autoregressive (SAR) modeling to evaluate the relative influence of use-related, environmental, and managerial factors on two salient measures of campsite impact. Relational analyses examined numerous field-collected and GIS-derived indicators, including several new indicators calculated using high-resolution Light Detection and Ranging (LiDAR) topographic data to evaluate the influence of terrain characteristics on the dependent variables.

Chosen variables in the best SAR models explained 35% and 30% of the variation in campsite size and area of vegetation loss on campsites. Results identified three key indicators that managers can manipulate to enhance the sustainability of campsites: campsite type, and terrain characteristics relating to landform slope and topographic roughness. Results support indirect management methods that rely on the location, design, construction, and maintenance of campsites, instead of direct regulations that restrict visitation or visitor freedoms. As visitation pressures continue to increase, this knowledge can be applied to select and promote the use of more ecologically sustainable campsites.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2020.111693","usgsCitation":"Arredondo, J.R., Marion, J.L., Meadema, F.P., and Wimpey, J.F., 2021, Modeling areal measures of campsite impacts on the Appalachian National Scenic Trail to enhance ecological sustainability: Journal of Environmental Management, v. 279, 111693, 14 p., https://doi.org/10.1016/j.jenvman.2020.111693.","productDescription":"111693, 14 p.","ipdsId":"IP-105824","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454082,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/104153","text":"External Repository"},{"id":381441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Georgia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, North Carolina, Pennsylvania, South Carolina, Vermont, Virginia","otherGeospatial":"Appalachian National Scenic Trail","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.09277343749999,\n 45.521743896993634\n ],\n [\n -73.037109375,\n 44.15068115978094\n ],\n [\n -77.255859375,\n 40.17887331434696\n ],\n [\n -80.37597656249999,\n 38.47939467327645\n ],\n [\n -83.935546875,\n 35.85343961959182\n ],\n [\n -84.55078125,\n 34.63320791137959\n ],\n [\n -83.27636718749999,\n 33.247875947924385\n ],\n [\n -79.7607421875,\n 35.567980458012094\n ],\n [\n -76.0693359375,\n 39.605688178320804\n ],\n [\n -72.2021484375,\n 43.100982876188546\n ],\n [\n -69.521484375,\n 44.99588261816546\n ],\n [\n -68.7744140625,\n 45.55252525134013\n ],\n [\n -69.0380859375,\n 46.07323062540835\n ],\n [\n -69.521484375,\n 46.255846818480315\n ],\n [\n -70.09277343749999,\n 45.521743896993634\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"279","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arredondo, Johanna R.","contributorId":245781,"corporation":false,"usgs":false,"family":"Arredondo","given":"Johanna","email":"","middleInitial":"R.","affiliations":[{"id":49322,"text":"Virginia Tech, Forest Resources & Environmental Conservation, 310 W. Campus Dr., Blacksburg, VA 24061, USA","active":true,"usgs":false}],"preferred":false,"id":807024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meadema, Fletcher P.","contributorId":245782,"corporation":false,"usgs":false,"family":"Meadema","given":"Fletcher","email":"","middleInitial":"P.","affiliations":[{"id":49322,"text":"Virginia Tech, Forest Resources & Environmental Conservation, 310 W. Campus Dr., Blacksburg, VA 24061, USA","active":true,"usgs":false}],"preferred":false,"id":807025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wimpey, Jeremy F.","contributorId":245783,"corporation":false,"usgs":false,"family":"Wimpey","given":"Jeremy","email":"","middleInitial":"F.","affiliations":[{"id":49323,"text":"Applied Trails Research, State College, PA 16803, USA","active":true,"usgs":false}],"preferred":false,"id":807026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217658,"text":"70217658 - 2021 - Limited mantle hydration by bending faults at the Middle America Trench","interactions":[],"lastModifiedDate":"2021-01-27T13:45:54.761976","indexId":"70217658","displayToPublicDate":"2020-12-15T07:42:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Limited mantle hydration by bending faults at the Middle America Trench","docAbstract":"

Seismic anisotropy measurements show that upper mantle hydration at the Middle America Trench (MAT) is limited to serpentinization and/or water in fault zones, rather than distributed uniformly. Subduction of hydrated oceanic lithosphere recycles water back into the deep mantle, drives arc volcanism, and affects seismicity at subduction zones. Constraining the extent of upper mantle hydration is an important part of understanding many fundamental processes on Earth. Substantially reduced seismic velocities in tomography suggest that outer rise plate‐bending faults provide a pathway for seawater to rehydrate the slab mantle just prior to subduction. Estimates of outer‐rise hydration based on tomograms vary significantly, with some large enough to imply that, globally, subduction has consumed more than two oceans worth of water during the Phanerozoic. We found that, while the mean upper mantle wavespeed is reduced at the MAT outer rise, the amplitude and orientation of inherited anisotropy are preserved at depths >1 km below the Moho. At shallower depths, relict anisotropy is replaced by slowing in the fault‐normal direction. These observations are incompatible with pervasive hydration but consistent with models of wave propagation through serpentinized fault zones that thin to <100‐m in width at depths >1 km below Moho. Confining hydration to fault zones reduces water storage estimates for the MAT upper mantle from ∼3.5 wt% to <0.9 wt% H20. Since the intermediate thermal structure in the ∼24 Myr‐old MAT slab favors serpentinization, limited hydration suggests that fault mechanics are the limiting factor, not temperatures. Subducting mantle may be similarly dry globally.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020982","usgsCitation":"Miller, N.C., Lizarralde, D., Collins, J., Holbrook, S., and van Avendonk, H., 2021, Limited mantle hydration by bending faults at the Middle America Trench: Journal of Geophysical Research, v. 25, no. 12, e2020JB020982, 28 p., https://doi.org/10.1029/2020JB020982.","productDescription":"e2020JB020982, 28 p.","ipdsId":"IP-096423","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb020982","text":"Publisher Index Page"},{"id":382656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8671875,\n 17.308687886770034\n ],\n [\n -99.31640625,\n 15.114552871944115\n ],\n [\n -96.15234375,\n 10.833305983642491\n ],\n [\n -87.890625,\n 3.5134210456400448\n ],\n [\n -77.6953125,\n 3.6888551431470478\n ],\n [\n -77.6953125,\n 8.059229627200192\n ],\n [\n -93.8671875,\n 17.308687886770034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":809167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lizarralde, Danile","contributorId":248449,"corporation":false,"usgs":false,"family":"Lizarralde","given":"Danile","email":"","affiliations":[{"id":49912,"text":"Department of Geology and Geophysics, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts","active":true,"usgs":false}],"preferred":false,"id":809168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, John A. jcollins@whoi.edu","contributorId":177449,"corporation":false,"usgs":false,"family":"Collins","given":"John A.","email":"jcollins@whoi.edu","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":809169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holbrook, Steven","contributorId":248450,"corporation":false,"usgs":false,"family":"Holbrook","given":"Steven","email":"","affiliations":[{"id":49891,"text":"Department of Geosciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia","active":true,"usgs":false}],"preferred":false,"id":809170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Avendonk, Harm","contributorId":248451,"corporation":false,"usgs":false,"family":"van Avendonk","given":"Harm","email":"","affiliations":[{"id":49913,"text":"Jackson School of Geosciences, University of Texas Institute for Geophysics, Austin, Texas","active":true,"usgs":false}],"preferred":false,"id":809171,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219562,"text":"70219562 - 2021 - Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area","interactions":[],"lastModifiedDate":"2021-04-13T12:30:22.334486","indexId":"70219562","displayToPublicDate":"2020-12-15T07:27:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area","docAbstract":"

Dryland ecosystems play an important role in the global carbon cycle, including regulating the inter-annual global carbon sink. Dynamic global vegetation models (DGVMs) are essential tools that can help us better understand carbon cycling in different ecosystems. Currently, there is limited knowledge of the performance of these models in drylands partly due to characterizing the heterogeneity of the vegetation and hydrometeorological conditions. The aim of this study is to evaluate the performance of a DGVM for drylands to facilitate improved understanding of gross primary production (GPP) as one of the important components of the carbon cycle. We performed a sensitivity analysis and calibrated the Ecosystem Demography (EDv2.2) DGVM to simulate GPP in a dryland watershed (Reynolds Creek Experimental Watershed, Idaho) in the western US for the years 2000-2017. GPP capacity and activity were investigated by comparing model simulations with GPP estimated from eddy covariance data (available from 2015-2017) and remote sensing products (2000-2017). Our results show good performance of EDv2.2 at daily timesteps (RMSE&#x2248;0.38[kgC/m2/year])\">RMSE≈0.38[kgC/m2/year])

","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2020.108270","usgsCitation":"Dashti, H., Pandit, K., Glenn, N.F., Shinneman, D.J., Flerchinger, G.N., Hudak, A., de Graaf, M.A., Flores, A.N., Ustin, S.L., Ilangakoon, N., and Fellows, A.W., 2021, Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area: Agricultural and Forest Meteorology, v. 297, 108270, 10 p., https://doi.org/10.1016/j.agrformet.2020.108270.","productDescription":"108270, 10 p.","ipdsId":"IP-113788","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454086,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2020.108270","text":"Publisher Index Page"},{"id":385048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Reynolds Creek Experimental Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.98242187499999,\n 42.48830197960227\n ],\n [\n -115.224609375,\n 42.48830197960227\n ],\n [\n -115.224609375,\n 43.77109381775651\n ],\n [\n -116.98242187499999,\n 43.77109381775651\n ],\n [\n -116.98242187499999,\n 42.48830197960227\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"297","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dashti, Hamid","contributorId":257078,"corporation":false,"usgs":false,"family":"Dashti","given":"Hamid","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pandit, Karun","contributorId":221464,"corporation":false,"usgs":false,"family":"Pandit","given":"Karun","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Nancy F.","contributorId":195241,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":814146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":814147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flerchinger, Gerald N.","contributorId":257377,"corporation":false,"usgs":false,"family":"Flerchinger","given":"Gerald","email":"","middleInitial":"N.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":814148,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hudak, Andrew A.","contributorId":257079,"corporation":false,"usgs":false,"family":"Hudak","given":"Andrew A.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":814149,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de Graaf, Marie Anne","contributorId":257378,"corporation":false,"usgs":false,"family":"de Graaf","given":"Marie","email":"","middleInitial":"Anne","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814150,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flores, Alejandro N","contributorId":256965,"corporation":false,"usgs":false,"family":"Flores","given":"Alejandro","email":"","middleInitial":"N","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814151,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ustin, Susan L.","contributorId":52878,"corporation":false,"usgs":false,"family":"Ustin","given":"Susan","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":814152,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ilangakoon, Nayani","contributorId":257382,"corporation":false,"usgs":false,"family":"Ilangakoon","given":"Nayani","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814153,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fellows, Aaron W.","contributorId":257383,"corporation":false,"usgs":false,"family":"Fellows","given":"Aaron","email":"","middleInitial":"W.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":814154,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70218027,"text":"70218027 - 2021 - High elevation ice patch documents Holocene climate variability in the northern Rocky Mountains","interactions":[],"lastModifiedDate":"2021-02-12T13:19:54.335361","indexId":"70218027","displayToPublicDate":"2020-12-15T07:09:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7169,"text":"Quaternary Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"High elevation ice patch documents Holocene climate variability in the northern Rocky Mountains","docAbstract":"

Paleoclimate records from ice cores generally are considered to be the most direct indicators of environmental change, but are rare from mid-latitude, continental regions such as the western United States. High-elevation ice patches are known to be important archaeological archives in alpine regions and potentially could provide records important for Earth System Model evaluation and to understand linkages between climate and early human activities, but this potential largely is unexplored. Here we use a well-dated ice-core record from a shallow ice patch to investigate Rocky Mountain winter-season climate during the Holocene. Our records indicate that this ice patch consistently accumulated ice over the past 10 kyr, preserving a regionally representative climate record of stable water isotopes and ice accretion rates that documented generally cooler and wetter conditions during the early Holocene and 500 years of anomalous winter season warmth centered at 4100 cal yr BP followed by a rapid cooling and 1500 years of cooler and wetter winters.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.qsa.2020.100021","usgsCitation":"Chellman, N.J., Pederson, G.T., Lee, C., McWethy, D., Pusman, K., Stone, J.R., Brown, S., and McConnell, J.R., 2021, High elevation ice patch documents Holocene climate variability in the northern Rocky Mountains: Quaternary Science Advances, v. 3, 100021, 8 p., https://doi.org/10.1016/j.qsa.2020.100021.","productDescription":"100021, 8 p.","ipdsId":"IP-102980","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454090,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.qsa.2020.100021","text":"Publisher Index Page"},{"id":383250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Colorado, Utah, Wyoming","otherGeospatial":"Upper Kintla Lake, Beartooth ice patch, Emerald Lake, Beauty Lake, Island Lake, Bighorn Basin, Minnetonka Cave, Bison Lake","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chellman, Nathan J.","contributorId":140597,"corporation":false,"usgs":false,"family":"Chellman","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":810252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":810253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Craig","contributorId":250716,"corporation":false,"usgs":false,"family":"Lee","given":"Craig","email":"","affiliations":[{"id":50230,"text":"University of Colorado, Institute of Arctic and Alpine Research (INSTAAR), Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":810254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McWethy, Dave","contributorId":250717,"corporation":false,"usgs":false,"family":"McWethy","given":"Dave","affiliations":[{"id":50231,"text":"Montana State University, Department of Earth Sciences, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":810255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pusman, Kathryn","contributorId":250718,"corporation":false,"usgs":false,"family":"Pusman","given":"Kathryn","email":"","affiliations":[{"id":50232,"text":"Paleoscapes Archaeobotanical Services Team, Baily, CO","active":true,"usgs":false}],"preferred":false,"id":810256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stone, Jeffery R.","contributorId":222205,"corporation":false,"usgs":false,"family":"Stone","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":810257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Sabrina R.","contributorId":222194,"corporation":false,"usgs":false,"family":"Brown","given":"Sabrina R.","affiliations":[],"preferred":false,"id":810258,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McConnell, Joseph R.","contributorId":191064,"corporation":false,"usgs":false,"family":"McConnell","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":810259,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223853,"text":"70223853 - 2021 - Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States","interactions":[],"lastModifiedDate":"2021-09-10T13:45:18.247157","indexId":"70223853","displayToPublicDate":"2020-12-14T08:35:22","publicationYear":"2021","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":"Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States","docAbstract":"

Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no-flow fraction, date of first no flow, and duration of the dry-down period, with further divergence between natural and human-altered watersheds. Aridity was a primary driver of no-flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry-down duration showed stronger associations with nonclimate drivers compared to no-flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL090794","usgsCitation":"Hammond, J., Zimmer, M., Shanafield, M., Kaiser, K.E., Godsey, S., Mims, M.C., Zipper, S., Burrow, R., Kampf, S.K., Dodds, W., Jones, C., Krabbenhoft, C., Boersma, K., Datry, T., Olden, J., Allen, G., Price, A.N., Costigan, K., Hale, R., Ward, A.S., and Allen, D., 2021, Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States: Geophysical Research Letters, v. 48, no. 2, e2020GL090794, 11 p., https://doi.org/10.1029/2020GL090794.","productDescription":"e2020GL090794, 11 p.","ipdsId":"IP-119781","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":454097,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020gl090794","text":"External Repository"},{"id":436624,"rank":0,"type":{"id":30,"text":"Data 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As part of the update of the 2018 National Seismic Hazard Model (NSHM) for the conterminous United States (CONUS), new ground motion and site effect models for the central and eastern United States were incorporated, as well as basin depths from local seismic velocity models in four western US (WUS) urban areas. These additions allow us, for the first time, to calculate probabilistic seismic hazard curves for an expanded set of spectral periods (0.01 to 10 s) and site classes (VS30 = 150 to 1500 m/s) for the CONUS, as well as account for amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco Bay, Seattle, and Salt Lake City areas. Two sets of 2018 NSHM hazard data (hazard curves and uniform-hazard ground motions) are available: (1) 0.05°-latitude-by-0.05°-longitude gridded data for the CONUS and (2) higher resolution 0.01°-latitude-by-0.01°-longitude gridded data for the four WUS basins. Both sets of data contain basin effects in the WUS deep sedimentary basins. Uniform-hazard ground motion data are interpolated for 2, 5, and 10% probability of exceedance in 50 years from the hazard curves. The gridded data for the hazard curves and uniform-hazard ground motions, for all periods and site classes, are available for download at the U.S. Geological Survey ScienceBase Catalog (https://doi.org/10.5066/P9RQMREV). The design ground motions derived from the hazard curves have been accepted by the Building Seismic Safety Council for adoption in the 2020 National Earthquake Hazard Reduction Program Recommended Seismic Provisions.

","language":"English","publisher":"Sage Journals","doi":"10.1177/8755293020970979","usgsCitation":"Shumway, A., Petersen, M.D., Powers, P.M., Rezaeian, S., Rukstales, K.S., and Clayton, B., 2021, The 2018 update of the US National Seismic Hazard Model: Additional period and site class data: Earthquake Spectra, v. 37, no. 2, p. 1145-1161, https://doi.org/10.1177/8755293020970979.","productDescription":"17 p.","startPage":"1145","endPage":"1161","ipdsId":"IP-121790","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":385635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Utah, Washington","city":"San Francisco, Los Angeles, Seattle, Salt Lake City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": 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This is the first assessment of groundwater from public-supply wells across the United States to analyze for >100 pesticide degradates and to provide human-health context for degradates without benchmarks. Samples from 1204 wells in aquifers representing 70% of the volume pumped for drinking supply were analyzed for 109 pesticides (active ingredients) and 116 degradates. Among the 41% of wells where pesticide compounds were detected, nearly two-thirds contained compound mixtures and three-quarters contained degradates. Atrazine, hexazinone, prometon, tebuthiuron, four atrazine degradates, and one metolachlor degradate were each detected in >5% of wells. Detection frequencies were largest for aquifers with more shallow, unconfined wells producing modern-age groundwater. To screen for potential human-health concerns, benchmark quotients (BQs) were calculated by dividing concentrations by the human-health benchmark, when available. For degradates without benchmarks, estimated values (estimated benchmark quotients (BQE)) were first calculated by assuming equimolar toxicity to the most toxic parent; final analysis excluded degradates with likely overestimated toxicity. Six pesticide compounds and 1.6% of wells had concentrations approaching levels of potential concern (individual or summed BQ or BQE values >0.1), and none exceeded these levels (values >1). Therefore, although pesticide compounds occurred frequently, concentrations were low, even accounting for mixtures and degradates without benchmarks.

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48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"55","issue":"16","noUsgsAuthors":false,"publicationDate":"2020-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":806896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213727,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","email":"","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":806898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806899,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217007,"text":"70217007 - 2021 - Determination of four arsenic species in environmental water samples by liquid chromatography- inductively coupled plasma - tandem mass spectrometry","interactions":[],"lastModifiedDate":"2020-12-29T12:41:06.267628","indexId":"70217007","displayToPublicDate":"2020-12-14T06:48:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7479,"text":"MethodsX","active":true,"publicationSubtype":{"id":10}},"title":"Determination of four arsenic species in environmental water samples by liquid chromatography- inductively coupled plasma - tandem mass spectrometry","docAbstract":"

Robust and sensitive methods for monitoring inorganic and organic As species As(III), As(V), dimethylarsinate (DMA), and monomethylarsonate (MMA) in environmental water are necessary to understand the toxicity and redox processes of As in a specific environment. The method is sufficiently sensitive and selective to ensure accurate and precise quantitation of As(III), As(V), DMA, and MMA in surface water and groundwater samples with As species concentrations from tens of nanograms per liter to 50 µg/L without dilution of the sample. Mean recoveries of the four species spiked into reagent water, surface water and groundwater and measured periodically over three months ranged from 87.2 % to 108.7 % and relative standard deviation of replicates of all analytes ranged from 1.1 % to 9.0 %.

•A PRP-X100 column and nitrate/phosphate mobile phase was used to separate As(III), As(V), DMA, and MMA in 0.45 µm filtered surface water and groundwater matrices.
•Oxygen was used in the collision cell of the inductively coupled plasma-mass spectrometer with MS/MS mode to shift the measured As mass from 75 to 91.
• The analytical performance of the method and figures of merit including detection limits, precision, accuracy, and interferences when applied to surface water and groundwater matrices were investigated.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mex.2020.101183","usgsCitation":"Stetson, S., Lawrence, C.M., Whitcomb, S.M., and Kanagy, C.J., 2021, Determination of four arsenic species in environmental water samples by liquid chromatography- inductively coupled plasma - tandem mass spectrometry: MethodsX, v. 8, 101183, 12 p., https://doi.org/10.1016/j.mex.2020.101183.","productDescription":"101183, 12 p.","ipdsId":"IP-113219","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":454104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mex.2020.101183","text":"Publisher Index Page"},{"id":381642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stetson, Sarah 0000-0002-4930-4748 sstetson@usgs.gov","orcid":"https://orcid.org/0000-0002-4930-4748","contributorId":216528,"corporation":false,"usgs":true,"family":"Stetson","given":"Sarah","email":"sstetson@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":807249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Caitlyn Margaret 0000-0002-3073-1715","orcid":"https://orcid.org/0000-0002-3073-1715","contributorId":245873,"corporation":false,"usgs":true,"family":"Lawrence","given":"Caitlyn","email":"","middleInitial":"Margaret","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":807250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitcomb, Susan Melissa 0000-0001-6941-9465","orcid":"https://orcid.org/0000-0001-6941-9465","contributorId":245874,"corporation":false,"usgs":true,"family":"Whitcomb","given":"Susan","email":"","middleInitial":"Melissa","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":807251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanagy, Christopher J. 0000-0001-7674-0521 ckanagy@usgs.gov","orcid":"https://orcid.org/0000-0001-7674-0521","contributorId":245875,"corporation":false,"usgs":true,"family":"Kanagy","given":"Christopher","email":"ckanagy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":807252,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219122,"text":"70219122 - 2021 - Direct observation of the depth of active groundwater circulation in an alpine watershed","interactions":[],"lastModifiedDate":"2021-03-25T11:55:26.683201","indexId":"70219122","displayToPublicDate":"2020-12-14T06:42:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Direct observation of the depth of active groundwater circulation in an alpine watershed","docAbstract":"

The depth of active groundwater circulation is a fundamental control on stream flows and chemistry in mountain watersheds, yet it remains challenging to characterize and is rarely well constrained. We collected hydraulic conductivity, hydraulic head, temperature, chemical, noble gas, and 3H/3He groundwater age data from discrete levels in two boreholes 46 and 81 m deep in an alpine watershed, in combination with chemical and age data from shallow groundwater discharge, to discern groundwater flow rates at different depths and directly observe active and inactive groundwater. Vertical head gradients are steep (average of 0.4) and thermal profiles are consistent with typical linear conductive continental geotherms. Groundwater deeper than ∼20 m is distinct from shallow groundwater and creek water in its chemistry, noble gas signature, and age (dominantly >65 years compared to <9 years). Together these results suggest low vertical groundwater flow velocities and a relatively shallow active circulation depth of ∼20 m. This hypothesis is tested with a simple 2‐D numerical fluid flow and heat transport model representing a hillslope transect through the two boreholes. The modeling indicates that the subhorizontally bedded sedimentary rocks underlying the basin are highly anisotropic with low vertical hydraulic conductivity, and at most ∼10% of bedrock recharge (equivalent to <2% of stream baseflow) flows below a depth of 20 m. The study demonstrates the considerable value of discrete‐depth hydrogeologic, chemical, and age data for determining active circulation depth, and illustrates an approach for maximizing the utility of individual boreholes drilled for mountain bedrock aquifer characterization.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028548","usgsCitation":"Manning, A.H., Ball, L.B., Wanty, R., and Williams, K.H., 2021, Direct observation of the depth of active groundwater circulation in an alpine watershed: Water Resources Research, v. 57, no. 2, e2020WR028548, 21 p., https://doi.org/10.1029/2020WR028548.","productDescription":"e2020WR028548, 21 p.","ipdsId":"IP-121573","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028548","text":"Publisher Index Page"},{"id":384621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Redwell Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.13043212890625,\n 38.792626957868904\n ],\n [\n -106.80084228515625,\n 38.792626957868904\n ],\n [\n -106.80084228515625,\n 38.99997583555929\n ],\n [\n -107.13043212890625,\n 38.99997583555929\n ],\n [\n -107.13043212890625,\n 38.792626957868904\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":812858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wanty, Richard B. 0000-0002-2063-6423","orcid":"https://orcid.org/0000-0002-2063-6423","contributorId":209899,"corporation":false,"usgs":true,"family":"Wanty","given":"Richard","middleInitial":"B.","affiliations":[],"preferred":true,"id":812859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Kenneth H. 0000-0002-3568-1155","orcid":"https://orcid.org/0000-0002-3568-1155","contributorId":176791,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":812860,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263957,"text":"70263957 - 2021 - Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics","interactions":[],"lastModifiedDate":"2025-03-03T15:36:19.470968","indexId":"70263957","displayToPublicDate":"2020-12-11T09:30:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics","docAbstract":"

Regional triplication waveforms of five intermediate-depth events are modeled to simultaneously obtain the compressional (P) and shear (SH) wave velocity structure beneath northwestern Pacific subduction zone. Both the P- and SH-wave velocity models for three different sub-regions show a low-velocity layer (LVL) with a thickness of ∼55-80 km lying above the 410-km discontinuity with a ∼900 km lateral extent from the Japan Sea to the northeastern Asian continental margin. With the dihedral angle approaching to zero around 400 km, a minute amount of melt atop the 410-km discontinuity caused by the hydrous slab might completely wet olivine grain boundaries and result in a low seismic velocity layer in this specific subduction zone. This mechanism suggests that the 410-LVL is a low viscosity zone that would partially decouple the upper mantle from the transition zone. We infer that the widespread 410-LVL provides evidence for a water-bearing mantle transition zone beneath the western Pacific subduction zone.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2020.116642","usgsCitation":"Han, G., Li, J., Guo, G., Mooney, W.D., Karato, S., and Yuen, D., 2021, Pervasive low-velocity layer atop the 410-km discontinuity beneath the northwest Pacific subduction zone: Implications for rheology and geodynamics: Earth and Planetary Science Letters, v. 554, 116642, 13 p., https://doi.org/10.1016/j.epsl.2020.116642.","productDescription":"116642, 13 p.","ipdsId":"IP-122067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2020.116642","text":"Publisher Index Page"},{"id":482740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"554","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Han, Guangjie","contributorId":351730,"corporation":false,"usgs":false,"family":"Han","given":"Guangjie","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Juan","contributorId":351731,"corporation":false,"usgs":false,"family":"Li","given":"Juan","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guo, Guangrui","contributorId":351732,"corporation":false,"usgs":false,"family":"Guo","given":"Guangrui","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":929344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mooney, Walter D. 0000-0002-5310-3631 mooney@usgs.gov","orcid":"https://orcid.org/0000-0002-5310-3631","contributorId":3194,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","email":"mooney@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karato, Shun-Ichiro","contributorId":351733,"corporation":false,"usgs":false,"family":"Karato","given":"Shun-Ichiro","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":929346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuen, David A.","contributorId":351734,"corporation":false,"usgs":false,"family":"Yuen","given":"David A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":929347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217056,"text":"70217056 - 2021 - Permafrost promotes shallow groundwater flow and warmer headwater streams","interactions":[],"lastModifiedDate":"2021-03-05T21:14:01.609787","indexId":"70217056","displayToPublicDate":"2020-12-11T07:09:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost promotes shallow groundwater flow and warmer headwater streams","docAbstract":"

The presence of permafrost influences the flow paths of water through Arctic landscapes and thereby has the potential to impact stream discharge and thermal regimes. Observations from eleven headwater streams in Alaska showed that July water temperatures were higher in catchments with more near‐surface permafrost. We apply a fully coupled cryohydrology model to investigate if the impact of permafrost on flow path depth could cause the same pattern in temperatures of groundwater discharging from hillslopes to streams. The model simulates surface energy and water balances, snow, and subsurface water and energy balances for two‐dimensional hillslope model cases with varying permafrost extent. We find that hillslopes with continuous permafrost have more shallow flow paths and twice as high rates of evapotranspiration, compared to hillslopes with no permafrost. For our simulated cases, 6.7 % of the horizontal water flux moves through the top organic soil layers when there is continuous permafrost, while only 0.5 % moves through organic layers without permafrost. The deeper flow paths in permafrost‐free simulations buffer seasonal temperature extremes, so that summer groundwater discharge temperatures are highest with continuous permafrost. Our results suggest that permafrost thawing alters groundwater flow paths and can lead to decreases in summer stream temperatures and reductions in evapotranspiration in headwater catchments. These changes are of potential importance for stream biotic components of ecosystems, however, the full impact remains unknown.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027463","usgsCitation":"Sjoberg, Y., Janke, A.K., Painter, S., Coonradt, E., Carey, M.P., O’Donnell, J.A., and Koch, J.C., 2021, Permafrost promotes shallow groundwater flow and warmer headwater streams: Water Resources Research, v. 57, no. 2, e2020WR027463, 20 p., https://doi.org/10.1029/2020WR027463.","productDescription":"e2020WR027463, 20 p.","ipdsId":"IP-117601","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":491329,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91HI62H","text":"USGS data release","linkHelpText":"Stream Temperature, Dissolved Oxygen, Conductivity, and Photosynthetically Active Radiation (PAR) in River Basins of Northwest Alaska, 2017-2024"},{"id":454110,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr027463","text":"Publisher Index Page"},{"id":436625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C3JYUH","text":"USGS data release","linkHelpText":"Physical, Hydraulic, and Thermal Properties of Soils in the Noatak River Basin, Alaska, 2016"},{"id":381798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Noatak National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -163.685302734375,\n 66.93866882358137\n ],\n [\n -154.8193359375,\n 66.93866882358137\n ],\n [\n -154.8193359375,\n 68.62854757995426\n ],\n [\n -163.685302734375,\n 68.62854757995426\n ],\n [\n -163.685302734375,\n 66.93866882358137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Sjoberg, Ylva 0000-0002-4292-5808","orcid":"https://orcid.org/0000-0002-4292-5808","contributorId":194635,"corporation":false,"usgs":false,"family":"Sjoberg","given":"Ylva","email":"","affiliations":[],"preferred":false,"id":807421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":807422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, S 0000-0002-0901-6987","orcid":"https://orcid.org/0000-0002-0901-6987","contributorId":245978,"corporation":false,"usgs":false,"family":"Painter","given":"S","email":"","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":807423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coonradt, E. 0000-0001-8124-9622","orcid":"https://orcid.org/0000-0001-8124-9622","contributorId":140134,"corporation":false,"usgs":false,"family":"Coonradt","given":"E.","affiliations":[{"id":13388,"text":"ADF&G - Commercial Fisheries, 304 Lake Street, Sitka, Alaska 99835","active":true,"usgs":false}],"preferred":false,"id":807424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":807425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":807426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":807427,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217587,"text":"70217587 - 2021 - Machine learning predictions of pH in the Glacial Aquifer System, Northern USA","interactions":[],"lastModifiedDate":"2021-05-13T15:55:05.573687","indexId":"70217587","displayToPublicDate":"2020-12-11T06:59:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning predictions of pH in the Glacial Aquifer System, Northern USA","docAbstract":"

A boosted regression tree model was developed to predict pH conditions in three dimensions throughout the glacial aquifer system of the contiguous United States using pH measurements in samples from 18,386 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and, when coupled with long flowpaths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate‐poor, pH conditions remain acidic. At depths typical of drinking‐water supplies, predicted pH >7.5—which is associated with arsenic mobilization—occurs more frequently than predicted pH <6—which is associated with water corrosivity and the mobilization of other trace elements. A novel aspect of this model was the inclusion of numerically based estimates of groundwater flow characteristics (age and flowpath length) as predictor variables. The sensitivity of pH predictions to these variables was consistent with hydrologic understanding of groundwater flow systems and the geochemical evolution of groundwater quality. The model was not developed to provide precise estimates of pH at any given location. Rather, it can be used to more generally identify areas where contaminants may be mobilized into groundwater and where corrosivity issues may be of concern to prioritize areas for future groundwater monitoring.

","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13063","usgsCitation":"Stackelberg, P.E., Belitz, K., Brown, C., Erickson, M., Elliott, S.M., Kauffman, L.J., Ransom, K.M., and Reddy, J., 2021, Machine learning predictions of pH in the Glacial Aquifer System, Northern USA: Groundwater, v. 37, no. 4, p. 531-543, https://doi.org/10.1111/gwat.13063.","productDescription":"13 p.","startPage":"531","endPage":"543","ipdsId":"IP-122702","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454116,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gwat.13063","text":"External Repository"},{"id":436626,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RF0R6E","text":"USGS data release","linkHelpText":"Data for machine learning predictions of pH in the glacial aquifer system, northern USA"},{"id":382483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":808740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":808741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kauffman, Leon J. 0000-0003-4564-0362","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":206428,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ransom, Katherine Marie 0000-0001-6195-7699","orcid":"https://orcid.org/0000-0001-6195-7699","contributorId":239552,"corporation":false,"usgs":true,"family":"Ransom","given":"Katherine","email":"","middleInitial":"Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808746,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reddy, James E. 0000-0002-6998-7267","orcid":"https://orcid.org/0000-0002-6998-7267","contributorId":206426,"corporation":false,"usgs":true,"family":"Reddy","given":"James E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808747,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}